<%BANNER%>

Microbial Succession Associated with Soil Redevelopment along a Short-Term Restoration Chronosequence in the Florida Eve...

xml version 1.0 encoding UTF-8
REPORT xmlns http:www.fcla.edudlsmddaitss xmlns:xsi http:www.w3.org2001XMLSchema-instance xsi:schemaLocation http:www.fcla.edudlsmddaitssdaitssReport.xsd
INGEST IEID E20110217_AAAABO INGEST_TIME 2011-02-17T16:40:26Z PACKAGE UFE0015225_00001
AGREEMENT_INFO ACCOUNT UF PROJECT UFDC
FILES
FILE SIZE 8227 DFID F20110217_AABKUK ORIGIN DEPOSITOR PATH smith_j_Page_075thm.jpg GLOBAL false PRESERVATION BIT MESSAGE_DIGEST ALGORITHM MD5
c9b5b677da1680ecdca8192c34d30dec
SHA-1
529b819f53cb431aee9bf91f3ad5c94b3cefafea
4127 F20110217_AABKTW smith_j_Page_061thm.jpg
bb92b2fc38cb5197c3b658cc77adcf18
34ce60091bd19c2e6939f3c3838bc7f0b06d9519
8423998 F20110217_AABJRI smith_j_Page_122.tif
067e613e3f4c5d07eed2cbd975b8c113
9f3c4293436d61ebc784fb6b48d7686def2ba890
F20110217_AABJQU smith_j_Page_106.tif
e22d5ce29010425792ff4e98a5cdfd8b
59fde308194395e174648a8e533321f1eb7e192a
8233 F20110217_AABKUL smith_j_Page_076thm.jpg
30cbf57519e28e41100458c0d7598ba3
ae06acae57cb7f663a401f142fc72a8620d1940b
F20110217_AABJRJ smith_j_Page_123.tif
004c9170ff4107b54dcf0c6d3cf7600b
9725edc8f8e399eb24ac14f88dad07e5f54f8764
4788 F20110217_AABKVA smith_j_Page_092thm.jpg
a366d9874fa84b2c1eef06c748c27846
c9b374858b6c0f011b15058e5916af72c24c9020
8294 F20110217_AABKUM smith_j_Page_077thm.jpg
6e0f22cf0101096310c8fc487cd0b4cf
641775a941bc42d26a6f029ea29ce34394d1b487
3647 F20110217_AABKTX smith_j_Page_062thm.jpg
095b22a16744b72f04b1b5f7e0a8c9a3
95f5a69ddc0662698d6a42b8968c1cf2da7285ef
F20110217_AABJRK smith_j_Page_124.tif
5700454895104d2f08400cc58cc9ceb0
e717ff19571e23060b8b64ea164f0e5b86b5141a
F20110217_AABJQV smith_j_Page_107.tif
611d530ddfbe1de39a7e0fa89f80eb8f
0f869498e935880f0d64a80921f3e3aac805e2cd
7412 F20110217_AABKVB smith_j_Page_093thm.jpg
0933bd1d7eb6e43ea74cbe51287aa054
65d012d38d304ecfef8b61120ea970bd3742fa16
7854 F20110217_AABKUN smith_j_Page_078thm.jpg
870e22fa58293f78852a206d6db46355
0ad8e4eb99419f76df238e5b3e73b187aa987ffe
7605 F20110217_AABKTY smith_j_Page_063thm.jpg
2daa48b48b86e120d3ab8d3ef8389529
6e010a180668750f61e150acf1f5d57a5bf3990f
F20110217_AABJRL smith_j_Page_125.tif
721eb2bcdef6cf47638c75cc93899242
21e1fa91778be51ceacd1b28fea58694882ba4af
F20110217_AABJQW smith_j_Page_109.tif
622adc304e3d4fe7387ac6a14a2a7bd6
02ec617e314f20a80797212604c130a32e537113
8155 F20110217_AABKVC smith_j_Page_094thm.jpg
a852a85849ba2f0d963788350cc852cf
e5627ee93450ca524cf0209c49c440b29cdf5e84
7775 F20110217_AABKUO smith_j_Page_079thm.jpg
1f69977fedf8ffc89ff3dd45c47eed6b
ff2091a3461ee559bb108cc77e399e55d163dd06
7630 F20110217_AABKTZ smith_j_Page_064thm.jpg
6c2b036a63be1e54c2e61e5938ff4897
da4ec4035c01fd7ac22d1462a76acd522033b9d0
97 F20110217_AABJSA smith_j_Page_002.txt
f4ff257deb8e4ac7acec1db7ead5c1b0
5cb57b0a253503c341ad3b6413781967236f74c1
F20110217_AABJRM smith_j_Page_126.tif
bd1b8aa023f3a0cfc30a3d7a6d9b2aaf
4b67cfab3c50da4c303ad1867a4c7c04aef2caeb
F20110217_AABJQX smith_j_Page_110.tif
5b415662d616237d7373e2ab90207746
ed6614803c06dd4bd0b17a42a1d3a1186df49a17
7663 F20110217_AABKVD smith_j_Page_095thm.jpg
d332361cbd5593de1f3913d0b1c6f6ef
6ac78d6e2e5a2cb40b2e3686210720f65a21b1e3
8611 F20110217_AABKUP smith_j_Page_080thm.jpg
a51bf154223dc92ef0c7a7baa79bc91a
cd9cf98e220785656c5cdbd9b03852457e794170
83 F20110217_AABJSB smith_j_Page_003.txt
ba97695827fb4d25fcdc9ae766505733
0f108e4757ccd43ae823b9030eb7b9bf6eb8c2bc
F20110217_AABJRN smith_j_Page_128.tif
451fb014f03ac9a97d813d2dc2eba6d7
bbabc630c9faf2155188ea009c12f7b3d1751bb2
F20110217_AABJQY smith_j_Page_111.tif
dc93060dbd6b8bdbbf9339f2f5cb1015
023e62b417970b9b149bbd6cd6a2ad78e21a5908
8278 F20110217_AABKVE smith_j_Page_096thm.jpg
8f4e9fb2093ce772d5a65ac9a397be3a
c7e88de603b317ee3fefbd59ffbfb7c012c9d3d0
8266 F20110217_AABKUQ smith_j_Page_081thm.jpg
369a78173e11f52fe4507e085a546de4
2dd585b342705d7749bec7b4e2b77cd308028c94
1590 F20110217_AABJSC smith_j_Page_004.txt
fdb60ad704ca2382b7f029659925f0d2
65f3fc4136e93d80b2052c63eb00a9f7e8ec30a2
F20110217_AABJRO smith_j_Page_129.tif
2966815c4d3cf5171a38a432a81da378
12bb73f30352a1c329945a090971b6f23dd13b25
8425398 F20110217_AABJQZ smith_j_Page_112.tif
2f8af92d091f391199bae04e8eb55e4b
a0b78802c4e738f35d5717dfb5a0405ee90fbab7
7902 F20110217_AABKVF smith_j_Page_097thm.jpg
01b1bb56285acf95d2e2e576dbbac774
8728a4b0161dd7eb869bab7db84832e506ff3054
8251 F20110217_AABKUR smith_j_Page_082thm.jpg
b8889f949e83d34dcea1bc3cdceb0c42
c80e2aa819ead6cc76cf457092018394c4ef3a53
1553 F20110217_AABJSD smith_j_Page_005.txt
b8fcd56807928dc6cf93c95c284aca97
512b4ac95efbd4aae3f0f525a35adb31f741ed8f
F20110217_AABJRP smith_j_Page_130.tif
4a65b5b90f4257c17501ed552ec5138f
f20e6123e707abde3a853ad1a6cccf71ec4a6e16
8247 F20110217_AABKVG smith_j_Page_098thm.jpg
711ae81aa5ac6cc6912b284c2515c7de
c49689613dad8f2bff6f26b91dabbe264038d827
8431 F20110217_AABKUS smith_j_Page_084thm.jpg
268f010e0b438af4f5b794fd63fcec09
7fba1649af8cbb1fbccfa9063df93741cbb10b7d
3084 F20110217_AABJSE smith_j_Page_006.txt
192f26eda6117cd32c0d1ccf98d913be
7676d0e8c336edcd0b0e3964fcfb6a1837c17179
F20110217_AABJRQ smith_j_Page_131.tif
bdd6c1e522b7fda2abaf6bf8e0725903
596c7695e6043b8b866d78f0a4cd00e8b93ec6af
7894 F20110217_AABKVH smith_j_Page_099thm.jpg
8a7987efd05670f584a237914ba12198
599f2d6e6b24801f248a2adafb645ea64f70062c
6945 F20110217_AABKUT smith_j_Page_085thm.jpg
940ed6396b50e573278512fc104cf55b
b802a1181a4e6409d148622a5351dd23c725d381
3882 F20110217_AABJSF smith_j_Page_007.txt
e0d9fb0a81fd512c0efe6f1de1050655
22d3c5470ea319c137b817546cea9c94e991f06e
F20110217_AABJRR smith_j_Page_133.tif
36e4970ae348009e24dd0855df4c6cce
c0f0196b71b77dbcaa16a6df0f6346024dc7c51a
7853 F20110217_AABKVI smith_j_Page_100thm.jpg
e093eb0c26e0a3fb75452494d54682bf
b21ea6f5233a1ef24bb1421583c0c610d3aa7a4e
5816 F20110217_AABKUU smith_j_Page_086thm.jpg
173393b7bfa7eea4ef6ea975a5488aff
3402dd54745bcb744bfd3c91b17ea7a9bef2b385
731 F20110217_AABJSG smith_j_Page_008.txt
0cb5351bf69f416853e343cab99fbb4a
fc90b9b8d1c52c72a2be3999affcf4912d22cae3
F20110217_AABJRS smith_j_Page_134.tif
9fdbad421d922b0aaec81cd70491e384
0412cbc72662a761cef7a5c093b8e85f87e9158f
8259 F20110217_AABKVJ smith_j_Page_101thm.jpg
1a6819d4ab45ebfb53718c6315a078e6
c6e81fc2cad95953c2c05fd17a57d70af91faf01
4264 F20110217_AABKUV smith_j_Page_087thm.jpg
428d3ee55af515d3a06459e981d70ee6
48e60f5c5f74923c0c4fc7264e31d2d68076cb22
2314 F20110217_AABJSH smith_j_Page_009.txt
ab7579ae3a5a88c507525ddff95d6d3b
2d8b5494d986dda7d21c5d8e8a66b32902f6585c
F20110217_AABJRT smith_j_Page_135.tif
13efcc4191e2207aa3f1f7f6f6b2d960
075e9d64e1dd14ca9becf3fcaf0960f8579b077d
7972 F20110217_AABKVK smith_j_Page_102thm.jpg
5c67ca6f78355e58c39234f419b62399
1a4403e570276892e5aedb3d304b8cbb60b7ab5a
4455 F20110217_AABKUW smith_j_Page_088thm.jpg
ae3ca7698cad5bc2f99e63c8e73aa98e
9c2eb6bffc570093a8d900283c59ac2519f7b821
476 F20110217_AABJSI smith_j_Page_010.txt
752f1f9f8276e7da0c8b69f18de01eb8
6ec77be3e2eb6bdbf10f1c2ef9d470b663acf110
F20110217_AABJRU smith_j_Page_136.tif
0e282546929a683ee24cad21585eaaa6
3784b21edf52ae5e97b468f665392c5c0ac9dd17
8417 F20110217_AABKVL smith_j_Page_103thm.jpg
f439b658b17ce1a285e05fa47c12a5bd
be295e230a26f96982a0f22e7658353a5d711c6e
4814 F20110217_AABKUX smith_j_Page_089thm.jpg
ef1adf702b20b1e6f782d65be2dc090d
d9d47a5230690e4a84074076276df5b18b367741
2344 F20110217_AABJSJ smith_j_Page_011.txt
48c4a7f20cf5a7217c23f578dde90d40
ad44e933f4292fc46c7458892aed31b3d30e4700
F20110217_AABJRV smith_j_Page_138.tif
67b927d6b433308d930f61d5234512ed
22894eba76227895fe69d17fbbb73216ee7792fe
5133 F20110217_AABKWA smith_j_Page_123thm.jpg
decc1e2c7b647fc8b58dde8d86b3be0d
7f1edbc0e7dc4589cf07c703b473f30cffe2f1b6
8087 F20110217_AABKVM smith_j_Page_104thm.jpg
c25eba703ef70995bdd2952453c8dd69
2fff78f29afff634bcdbe9333e76c5b971a628b3
1770 F20110217_AABJSK smith_j_Page_013.txt
74a7ea9a56b4507d4187e9ec89c5d506
9c6f30102463bb58f8adb8879f45aa6647c57138
3409 F20110217_AABKWB smith_j_Page_124thm.jpg
dbea0742abc3a5b3a208098e30a1c0ab
c6df0611d699cf1450dbc16ec570e1a3c0842f32
8367 F20110217_AABKVN smith_j_Page_106thm.jpg
62eab5268bec5ff501633052f9fa2769
4aada2f4bc3e5eaceeb99077dbc576bcc183ae7b
4719 F20110217_AABKUY smith_j_Page_090thm.jpg
dc7fc3c850c951465f812a97ef9fc74c
806906c65554cbb16fb426a048cfe239039709dd
1790 F20110217_AABJSL smith_j_Page_014.txt
64c2bd667e527b8bef1b56f24db037cf
edc05ef9142160caff762f20dcbca23dcad1aba3
F20110217_AABJRW smith_j_Page_139.tif
fc6e05462fe987c2de479fe9e42d1de4
37fef710fd96e7f67956d653ace9a36aec19dc22
3476 F20110217_AABKWC smith_j_Page_125thm.jpg
f4461872f2fcd4623fa9a0605bd8ce9c
4ac40a39104ef7f7779404e8484349431d911b28
8429 F20110217_AABKVO smith_j_Page_107thm.jpg
78eaac613fbc8b4a3c34adc27f5dcfda
33279c0dffa2e85e0b8d2c6504bc59b81da5bcd3
4313 F20110217_AABKUZ smith_j_Page_091thm.jpg
0cec5818878a48cc08fc4456392f0e11
f2192684b7a0cf8b9be5bd20add828c289007e79
1960 F20110217_AABJSM smith_j_Page_016.txt
4902c267d756724a48b2a69c868dff5f
ade513ea2aaa39f3d00de9a81a0340610cad0adb
F20110217_AABJRX smith_j_Page_141.tif
113beb49a7a2228c191017bbe4a4fa6d
97004bbb77370fdc4b88d2f03d0382d9caf33b3e
1939 F20110217_AABJTA smith_j_Page_033.txt
bdb5e7e53a4e9b8935b12a0a14dd0bb8
6e83b0bb649c61b485cdb7d9df71cceffaa00159
4953 F20110217_AABKWD smith_j_Page_126thm.jpg
1565bc1df593949ff712f97f1c635a88
cfc4adc46baa9e1a5018255b684ee930dd7cb778
8545 F20110217_AABKVP smith_j_Page_108thm.jpg
e67687e5af33f2126c3611ecaab5d56c
372f73b6a9fee4047da5b56589a55d3cc786b458
2107 F20110217_AABJSN smith_j_Page_017.txt
cc1d9793953698d1c07eab43213e5d3c
57be7aa6b16ad607a2d375196476fc633d2cd611
F20110217_AABJRY smith_j_Page_144.tif
c068a36c831fce10eeaa420b6c807b1a
ad12f535d2dcf921164336a0404eedbbeecd22b0
1550 F20110217_AABJTB smith_j_Page_034.txt
3a6aad6b6db31062ff3e3548e9de73aa
e12057151ad9dea67e3a7985911345e281ad5968
5741 F20110217_AABKWE smith_j_Page_127thm.jpg
fe4dae1bb7dbf23f2b5564e138e12f2e
0617d59cef729f2e1867e4a19f673c93e965bf83
8458 F20110217_AABKVQ smith_j_Page_109thm.jpg
4ea8a424660d0e74a0f6d41509d19520
0024312295c33219206a0ad6e78ba8ccd5863a93
1869 F20110217_AABJSO smith_j_Page_018.txt
4df2bfc6bc42119cd24a8231c34424b5
c1d002fba116d0cadc3f7d60a292b455c9256b16
517 F20110217_AABJRZ smith_j_Page_001.txt
6086eff66314105b73e5a56984c9c682
0cdb4a2b246a4c94d3a56081111a2e834e98fd91
171 F20110217_AABJTC smith_j_Page_035.txt
578c4cfa43093cb5f2bc33282764af8d
8eca68932c1e360c3883d358591848db703defa1
7553 F20110217_AABKWF smith_j_Page_128thm.jpg
8d9b20ac0dc0af248276ccff8d14f338
e6032bec7ac2493cd57c52c0f4f543351c74bf02
3984 F20110217_AABKVR smith_j_Page_111thm.jpg
3555554534e209aa683e4d35ad664192
5958f440061da909d7d22b63f0d6a8447a90343a
2042 F20110217_AABJSP smith_j_Page_020.txt
40c0a1134cd69ff5c7ee959a36848c45
0ab9e923864c8f9301bfd0b2ddec13bb7360c269
620 F20110217_AABJTD smith_j_Page_036.txt
33515420a1cb636a407d15880ed15acb
86ea6ee768ef7b05a43572019fec66e7990b1548
8556 F20110217_AABKWG smith_j_Page_129thm.jpg
a8c1e4e983dfe11bc893a1f0d89f3a78
8c81396fa8cf6d460c95fc9d8f3f30930fb5bad7
3748 F20110217_AABKVS smith_j_Page_112thm.jpg
4eda75e549250baaa05cc2ed22c4ead1
77b3c9e8e6afa01b9977bbebc28f2bb40e52344f
1891 F20110217_AABJSQ smith_j_Page_022.txt
e59e5c76e9b5c010e21f6e6c8bbd558b
7b3e65c696082a97fcde1bbca1242f6289c9d31e
1035 F20110217_AABJTE smith_j_Page_037.txt
83ec5375d24c4b0a89144aa9c1d41e0b
8203957385cb0c8adf21dc6d72b76fff6121a80c
8555 F20110217_AABKWH smith_j_Page_130thm.jpg
07c52776eef6f907edc74d6918730646
92c26576cfe621351f4f560fe9a5232b599847d3
2975 F20110217_AABKVT smith_j_Page_113thm.jpg
939fc287b899a27d0bc3f3f74e3347f2
61b1035a33bae2ce712cc7cbb7ac6d602cb1b3f3
F20110217_AABJSR smith_j_Page_024.txt
c830650a2da09978f243cd77a65787d6
fc07e44c96c8f7c95ef123916535f4be938e14b1
891 F20110217_AABJTF smith_j_Page_038.txt
9475dda7b95e2d3a09d2d55b31ab88b9
99a8d8e25ceaf3e12af1e236e6eb31a8dbfcc233
8978 F20110217_AABKWI smith_j_Page_132thm.jpg
4553287c087abf9554d2012437caeb0c
94cda92771de76ba9d7fee73f8f0fa91e521d1c7
2537 F20110217_AABKVU smith_j_Page_114thm.jpg
3e090e22252d57ca3b79f25ac3eec90e
4cbad8a5da6396034592eb063738837409809a8e
2015 F20110217_AABJSS smith_j_Page_025.txt
5a47b38ea3eee33e863016891668e017
10e3a74736856301b0448f2c029103b8c665b27c
1117 F20110217_AABJTG smith_j_Page_039.txt
7b104a67504ca68daa5bce0478dff9f2
c96141c3784f64cbb47a8f03b2716651c763221c
8459 F20110217_AABKWJ smith_j_Page_133thm.jpg
53d69cbc122dc9db6f742b16eee82f58
e51526b043da38e4883baaecd9181773d6db1177
4350 F20110217_AABKVV smith_j_Page_115thm.jpg
aea8279023abe4e2fe75b127ff3cdf2d
1b62d7bdca169cd0530d0fb308315e1360705922
1835 F20110217_AABJST smith_j_Page_026.txt
e36f22004e3ecbe449b85b2a382fc18f
0218586ab022a351ff976fcbfdbac9866eae2fc1
272 F20110217_AABJTH smith_j_Page_040.txt
b1c885f445e02211ec49892bb9a0e9a3
6b16310662cdd19572e3d8d55fadeb13de70b738
8668 F20110217_AABKWK smith_j_Page_135thm.jpg
fc83fbda4f1e49107729f460be371b83
6ce64dacca271085a7af8527185508a6201fd414
5670 F20110217_AABKVW smith_j_Page_117thm.jpg
c4b43b7724a128f0d39fc7f6d061aee6
ff87cd4ca94e844bff02224758384dafe1be1b26
2005 F20110217_AABJSU smith_j_Page_027.txt
bff422cb328ad27e846b38e9856598ab
2738e93170c857a64626953414f1891f24670536
1739 F20110217_AABJTI smith_j_Page_041.txt
f46293556c328f471752e485edb15143
82843a0cd83c3926e925a9c068a6422dad17560d
8586 F20110217_AABKWL smith_j_Page_136thm.jpg
77604e729b8a36ce3f05ee3c1e49d01a
83e8062cfc9eaa75134fc95e4418c5339b1a128c
8067 F20110217_AABKVX smith_j_Page_119thm.jpg
cf1632d1c5c2722f59b00746781139c9
374c3f918940dc3624642e8560af7f1b751f75d4
1963 F20110217_AABJSV smith_j_Page_028.txt
14311a14924a70239588ea281b30fb62
343c0b487c7f930b70af9d90308d132eedc3bc4e
1988 F20110217_AABJTJ smith_j_Page_042.txt
e574887501fc74c8f628eff485ea0681
8306613e28ac1c53524ea73a2457ef9c1f0f85d1
8276 F20110217_AABKWM smith_j_Page_137thm.jpg
9e4aa11beeb2adfc2b085abcd90593f0
3bbfb5aa9613ca375e55a83a9bed388f0a4f7187
8303 F20110217_AABKVY smith_j_Page_121thm.jpg
d138b56fddea8ac40311498f9b996c03
abc528fd4ad97953f7d93093580437fd75a4400c
2024 F20110217_AABJTK smith_j_Page_043.txt
33f57512857d91be06654cccf88baad0
d6bfd0ce34bc36f7321a0335a83e5a4c2072fead
1781 F20110217_AABJSW smith_j_Page_029.txt
e966ce80465ba1d0d9271a8476f7caaf
e350c40e390f27aced75c0b8e4a676fc34a13c45
8457 F20110217_AABKWN smith_j_Page_138thm.jpg
59813c81af0d874211bc6c08113adf20
aedcc179bb4433504ecaff1ec9d3a86ca2d8d645
1782 F20110217_AABJTL smith_j_Page_045.txt
d90d25e01ba6ca17dee1df6d82adb2b9
59fa89fe44ed0d8aa9d824279b6ed3b27691ca2a
8571 F20110217_AABKWO smith_j_Page_139thm.jpg
2eda1ec43e48aeacc645168b23f1880d
52e0e6509389006de0e8742654c98d738fff1fec
4077 F20110217_AABKVZ smith_j_Page_122thm.jpg
2d3f9266140d4c1092b01931316d442f
679f00b1e0d8e973215fd9c5080f14574b113def
1740 F20110217_AABJUA smith_j_Page_061.txt
10347a77dbe20b4b1fec83310191c53e
8d85d3bc93810542c7b98abcbc0c4adddfde06ff
1833 F20110217_AABJTM smith_j_Page_046.txt
56191b49310ebdc103ec077f3034604c
42dd27c6bdc9530c738378e0b349354d0f022093
2084 F20110217_AABJSX smith_j_Page_030.txt
80b5e77565334c81bff8902e2f753949
095d0f363677387edcffd4504bce47396a1ce4a1
8652 F20110217_AABKWP smith_j_Page_140thm.jpg
9b3a2dc23cd9b6ec9d73338d6d8c2b06
b6e3b3e95c0fafec031c9bb9587bc26c992c0e0d
607 F20110217_AABJUB smith_j_Page_062.txt
e27542bf54be054166e8bc02103d57b3
350ea85839a3035b64ba40d56d52c62c4fe4d477
2075 F20110217_AABJTN smith_j_Page_048.txt
86476a67cde1ef0a0f33d75fe479791a
f661f3d9f2b7129a856c676df2e055e3a77f5e1d
1969 F20110217_AABJSY smith_j_Page_031.txt
646d7525d4eecd158587d99de5980f35
faa7fb659d9e896906003d244fc5a8bb9beb287f
8986 F20110217_AABKWQ smith_j_Page_141thm.jpg
8d0c852b7520839874ad9bc3f910ce00
da57139bae4525f7531b7aa205868e63b33dcbb6
1832 F20110217_AABJUC smith_j_Page_064.txt
3e4a92014c3499c4b9a3119bde891418
46bbfe8e298341666936149fd6826f92a70f91be
1996 F20110217_AABJTO smith_j_Page_049.txt
f4c464f68e077d73ca0bd9af6cd96021
e112e10bab05db71b3dd9c15784047cd8a094157
1800 F20110217_AABJSZ smith_j_Page_032.txt
17547ad2c185584793371cd18a58fe2a
bbdd1ef3abe59a4d7c0c838a1530079d5fdfa714
8270 F20110217_AABKWR smith_j_Page_143thm.jpg
9a03142719cfd3e6b7abf558f619702c
b5f643b5e54291d6f549e31e3e579ea99531ec1b
1995 F20110217_AABJUD smith_j_Page_065.txt
6e7e177eb753193f267c99af945f1b46
79ad34f8f9739e5d27e768d74174f3cf585376ac
1935 F20110217_AABJTP smith_j_Page_050.txt
99d522001490a865ba53249f81893bd0
d5f01ecfbc2bbb85c7993e01a65dae9e53a28fb3
7088 F20110217_AABKWS smith_j_Page_144thm.jpg
1f0c8ff2e6e8cc4def02d6f14f2029e1
ac9d3c71cdc9f30746660b4e43096a5301e50b46
1966 F20110217_AABJUE smith_j_Page_066.txt
5e6bc43fa24cca55f614b04f8d1df36f
db1d36fd583ba752825ce86a49a5654f35b74405
2055 F20110217_AABJTQ smith_j_Page_051.txt
c0b47d5aa5017eeae902776007a78a27
48a486d20d73151524eb7d1f2a66bc7684254a24
2328491 F20110217_AABKWT smith_j.pdf
0452f32c207d6bc9e6a2fa11d2257b08
353db9086a2ebcc519d017e74749617fab6eadea
1909 F20110217_AABJUF smith_j_Page_067.txt
1943187656232e15d0f98e1025f4ebe2
7b7d1fc2eedc3a8239630ca421946bde479dbba9
1957 F20110217_AABJTR smith_j_Page_052.txt
b860855e92d10542912abdcc5725814d
af7609eecb2f41e0c0b56483a46989242363ab0f
42935 F20110217_AABKAA smith_j_Page_085.pro
4ddd0cb6396b82fdfd41251ffb2290e9
c0516a846b84f9925b56b4c0c3f8cde8e366b083
169106 F20110217_AABKWU UFE0015225_00001.mets FULL
021c041753e74f2ee0be1f1ab55bfba2
5e5fb7220d8f423fe9e8e9789b7dbc618f827855
F20110217_AABJUG smith_j_Page_068.txt
c9c388dceea7d2e609f7adaef0afcb44
b6e6a70a05b90e463b5443f17133109a99be93a8
2001 F20110217_AABJTS smith_j_Page_053.txt
58af0d92f637042c98730297d33973ee
12e2b9ab865674ed56a421e9a0485425c1f1d327
40001 F20110217_AABKAB smith_j_Page_086.pro
80076d279543e06df347f3d551b64377
d6bef33e2eccfc5c7b735992d9540faf8fe4691a
1772 F20110217_AABJUH smith_j_Page_069.txt
4d9a29857724377dd71097d1317f6c9f
d4c4a66fb6e52aa24da152fb5ad833a6f57319b1
F20110217_AABJTT smith_j_Page_054.txt
d7745ff66b6d9930395938c89c047a45
ce0702aac411c722ad448b396ee60d1dddad98df
50298 F20110217_AABKAC smith_j_Page_087.pro
58f4d6657c3b4a9512b6346ad8240912
e52977d67316ba6aa5a728cfece426b6892547ac
1992 F20110217_AABJUI smith_j_Page_070.txt
d9e12ae9e44ed63fd787ce9a2ad1d343
9b129c76baff5b996d085570390600f548e518c8
1615 F20110217_AABJTU smith_j_Page_055.txt
8a16da39d0d8a15095189b743b26ac51
63f27da5bff66c8e75232fb7b72f7c5a28b1e92e
29259 F20110217_AABKAD smith_j_Page_088.pro
26e6b78f5aa99331096dd85f77323e47
ff419a2031b1d98b3fa9430dec892bf29916f2d2
1871 F20110217_AABJUJ smith_j_Page_071.txt
2694ded2641cda902a18077ad0412f30
f19f55dd81c66a01058ab2e8191c1f72acb7160d
F20110217_AABJTV smith_j_Page_056.txt
343f7aca6fec4656aeca772082d23db7
c8ef774c41fbf5b433fda114e92b3cbcc7a98d9a
1898 F20110217_AABJUK smith_j_Page_072.txt
38b9ea2ccf3fc648ec40b93fbb962666
d14786b89f7a8e3c8b5739f0124999de25628a02
1743 F20110217_AABJTW smith_j_Page_057.txt
d7fef05a8c17c36cf176aa41cfd0dfa7
31593d126b2b9250b041cb02bc72a648e70e9452
32512 F20110217_AABKAE smith_j_Page_089.pro
da4fce1ecface8e63fc64d412e4f8784
4ee657dd9ad9b218524917982257d0c784444c21
1928 F20110217_AABJUL smith_j_Page_073.txt
b2442e7143ca15d0aaf3979525df0c58
dce1751edf5689e8fad5c7855ee93fd9143efe63
1802 F20110217_AABJTX smith_j_Page_058.txt
7f29c474ae3451a05eb29fa967004745
13f410c0a2c5f7ecd4f274deec9bc6f499fe6f2a
62609 F20110217_AABKAF smith_j_Page_090.pro
bd520032b4bb11c35d7d4f4c59bb7a9a
abc4b8276839aedf7f44cb78e4bf812b5065b901
1916 F20110217_AABJUM smith_j_Page_074.txt
33de1d2ac8f3145d5685290c162386a7
3a19d2f6393c590f3ad57a483dd724aaba30876b
53361 F20110217_AABKAG smith_j_Page_091.pro
f6eafb3c4480597cc648593aaaa0778a
69a1836ffe391b2ac94467f4e1d671d8b23e3a98
1633 F20110217_AABJVA smith_j_Page_089.txt
a6f8d09243ccd7c272f78c2125309074
ffd0c2f1af87b338549ae994e1b9863485a0dc84
1965 F20110217_AABJUN smith_j_Page_075.txt
34c83939a030468bd26cfb0399809803
358f6161c5683165ebbcb96d0d38fdfbc1b227e9
5299 F20110217_AABJTY smith_j_Page_059.txt
a57c359b2f91a3da755cb052cd91484d
8729652b1a0d0b6ef3ae4b985fb4ee7355baeee9
20755 F20110217_AABKAH smith_j_Page_092.pro
7147d051bb70a10f47e566f7844c6048
259b1020457254bb455161fa6a452a5ad8be6385
6528 F20110217_AABJVB smith_j_Page_090.txt
17a38daf2c2a1d1e49ae8c95b217eced
71a48946e8ddca9b5f1691b6382085b0a257dca6
1970 F20110217_AABJUO smith_j_Page_076.txt
2d1ea37bebb24eabf9f6cf370a5ea19c
32da105e8cbb34b16e987c6034d13468b28eea2f
307 F20110217_AABJTZ smith_j_Page_060.txt
34dc8cea01b3a82a4771461daf81a527
b05c648bc10dd086aae90fadf9fc45bb763c569d
44070 F20110217_AABKAI smith_j_Page_093.pro
9135d880293ec82b5b7008a48ee2fa8b
fd4a9113e4afc2685c0c0378c985a47a9ad52a61
5232 F20110217_AABJVC smith_j_Page_091.txt
c04f3d0729c2b66894d9692ed98d9467
5004bb46e2675008be0e3ae80bb91f7056055a9a
F20110217_AABJUP smith_j_Page_077.txt
bbfcf1af0949b862c6911a494cac6763
30c8f0e5ed7cf70728052d33747a30a12e3e6643
49297 F20110217_AABKAJ smith_j_Page_094.pro
a97ed4e0168684101a05a5f12e73612a
497ead8f2155c698da1e7b417f7c09e2f590b6e1
986 F20110217_AABJVD smith_j_Page_092.txt
1a977ce27393280a09aa6c94786295c3
9bb66a4a36d70d2a1c9d9e6a936397f81a83ec8c
F20110217_AABJUQ smith_j_Page_078.txt
0e16c491e1c74e7df3f0023fa7728ee5
7135fd4ce27790d01d9d488d31978dbb8f766b92
47520 F20110217_AABKAK smith_j_Page_095.pro
6457c30e0f159749430b99cd5877c5ae
68c2f4e584197e1a95ca9a0e445742794241cdd9
1796 F20110217_AABJVE smith_j_Page_093.txt
3cbe7d1253b9483a6a8da5532db94eb1
2c92aecd5e8a99ad7c36d619ee0a25a2d5f62279
1906 F20110217_AABJUR smith_j_Page_079.txt
cd7b37bc8b8b5ec6d8b5fc872b1bc3f5
934b356a44a37d5f643b10dc1ab102644e5ff776
45548 F20110217_AABKBA smith_j_Page_112.pro
8fe8410136fe8fec8c303b07292b64ef
a519dd26d6fe9a31cb42aaa6d55145be6a409319
50650 F20110217_AABKAL smith_j_Page_096.pro
1f1cbb5e305ec6c7afbb2b2fa1309fe3
33a7d0d4c0ef5e6f6572b7a6ee37d992ff5b23e5
1947 F20110217_AABJVF smith_j_Page_094.txt
8493637e3a75af3156fcb1673ac81ead
62bb5f468538ef5cd0d2ac5ede5e34ef7427c11b
2096 F20110217_AABJUS smith_j_Page_080.txt
3f0052772f68a41025b791f8cf96c52b
0ce50603e495cd2ea1cf1b246da1b789d37b8edc
21807 F20110217_AABKBB smith_j_Page_113.pro
c07f5e25f88483d36230c74a9f89996a
88b949aac57088e1e0eadc66d7585caaf028014e
46467 F20110217_AABKAM smith_j_Page_097.pro
d293bfc87df56818e35baff45d5d1a03
256af70e22a02a61d11f99300522918d96d2db36
1873 F20110217_AABJVG smith_j_Page_095.txt
9aeb5c6bd384c41f546adf5cee34ce11
92e2794c6d9df0744cc49aa9dd8371d5f55c766e
2021 F20110217_AABJUT smith_j_Page_081.txt
6f5149e7ad172946203593aa2c75d618
0bb4a919b192ce0672457619d9e9ef8a19470968
23674 F20110217_AABKBC smith_j_Page_114.pro
894daef07bdcc0920b435d76974269f8
1c1524325ed04d3334e1388001cbc7ec177f1a2b
50143 F20110217_AABKAN smith_j_Page_098.pro
c1a3ef207ca86301c7873f5203c67ec4
3f6087d5715efb197b84cf11d825de1360e4e881
1840 F20110217_AABJVH smith_j_Page_097.txt
dd5aec1970c3d7c5e867822108ae827e
63356be06df8fc7b8169579f932e2ce95d146409
1958 F20110217_AABJUU smith_j_Page_082.txt
d108d60d1b1609eadea920964b89e30a
2970e19e3ffd823bc61275e8893e0a39190193f7
26845 F20110217_AABKBD smith_j_Page_115.pro
c7eb41a7f0c82449fd61ac6dbddc148a
c7785721356e3cc9f814e532db000278c43e1bb2
45869 F20110217_AABKAO smith_j_Page_100.pro
e66405fe9be3378683714cdc554c87cd
9c0ee8061460ff698af8443bac090b32023c02c6
1975 F20110217_AABJVI smith_j_Page_098.txt
d8fcab20dbc341f1c688701dd96a15cc
b2047855f316894f6093f9759b9cd2f87c5b4db8
1925 F20110217_AABJUV smith_j_Page_083.txt
3b0d2c14915a153143d9de7e8faf06a8
c94b6cbec7d0cd152106c00df5975188deecd895
40088 F20110217_AABKBE smith_j_Page_117.pro
04103b42c5af01a94abd3e2de63ba648
f96b92d1be868cc9311872952ee701ebe2dd531a
49755 F20110217_AABKAP smith_j_Page_101.pro
3b55b6e489e9e96bb206548ec7bcacfa
08676300a48eb6e481b104018cb3997b246fb429
F20110217_AABJVJ smith_j_Page_099.txt
744c6f29325abcee4d1d99956f8f44d0
65fda4a4c8695fa025484b1d8d7fea6472e254b8
2071 F20110217_AABJUW smith_j_Page_084.txt
290710d7d032956785ee908ad408893a
3f0db7eb948e80eb21022479c6f6dbdb6803d338
46063 F20110217_AABKAQ smith_j_Page_102.pro
27d09b9344fdd8ea23f940a1dda86ee6
ba3a11c1295f377d16dc9499faf03625fb451c5b
1819 F20110217_AABJVK smith_j_Page_100.txt
3ee680d7158e21ebb2cb834066b1f34a
66c8cf8578c86e2d5232b58a09d79c042a86fbcf
1741 F20110217_AABJUX smith_j_Page_085.txt
802cb1aaf52d9e0ac292b1437c53d6ed
2c7857c632011dd09aaaf5c9edd9911e9e7fbcc5
45228 F20110217_AABKBF smith_j_Page_118.pro
c9522d8b01ebd7eac92600729860d2ad
33d322175df0b88864f9cfde365fcbc52002e05e
50284 F20110217_AABKAR smith_j_Page_103.pro
ad14ff0d7707a036ec2c09d9703d4181
87a6c70e58e8564f45dd71278dd93a86bc964039
F20110217_AABJVL smith_j_Page_101.txt
42112e09432a49ef76d54647d43b0f51
c54f0f016b9bd47bddca5dc70e7ae7a5eb93a95f
1848 F20110217_AABJUY smith_j_Page_086.txt
fb09fcbf80e11a520ccc3e079c51cfe7
b57467d24ff8121ddfc021563af3841333ff4651
50075 F20110217_AABKBG smith_j_Page_119.pro
8e2e99c2176bf833fd67ff151fc656fc
7e85babc6d92ff393fd242163ca7b5b3f31b4e50
1854 F20110217_AABJWA smith_j_Page_118.txt
cc274248d445f177a6c244a13106c69c
f840ebdb89dc98147c820af30cae99276f4aea91
48923 F20110217_AABKAS smith_j_Page_104.pro
d8dd7634c6bd479033b50fe7762e6834
f5686bf1066478f2c3f8594f8df9645f38166f68
1855 F20110217_AABJVM smith_j_Page_102.txt
7a89c550c83ed64094150518c62b2c42
bc8e6cd250cb51c609917a5ebf26076247b0d7f0
51102 F20110217_AABKBH smith_j_Page_120.pro
7998a3369ab9750ae085d72d3b348d68
01fd6ebcc525fd17c8fa8ded9c5682d8fba0bda6
F20110217_AABJWB smith_j_Page_119.txt
c6b47b9a63a7121efab90a469e0f9bca
c72873d9cb43f7a213907d6e6951b668a901e22f
50846 F20110217_AABKAT smith_j_Page_105.pro
920cd77df694afafde854ab33b41c481
302e6844e4078d8ae1e8f63d3f0256d2de090f4e
1976 F20110217_AABJVN smith_j_Page_103.txt
e043e8b4da8eb839690752b423f24217
fec5874c3c4e2a84da3274775272d736030a3534
1548 F20110217_AABJUZ smith_j_Page_088.txt
51b8c395dfb44f84062d9fd92b991524
ebed341445ca35f1e62278ed41aaad9a0ce23669
49927 F20110217_AABKBI smith_j_Page_121.pro
d5fac99e8ed120cf04234725d8eed55c
941e0e4eb949e4e1da3a8b6afb2d399108804ffc
2019 F20110217_AABJWC smith_j_Page_120.txt
b9fa8336d620c8b8f2e18fe35238eed1
b3f1d772a51abcae3487ab4047e2a2bf594e179b
49889 F20110217_AABKAU smith_j_Page_106.pro
1441914f4795b721689181e61a1322f4
dbfa06c9b638ffe5dbf7e997e9fc8956ea1b8933
F20110217_AABJVO smith_j_Page_105.txt
cd319e6cd88aa3499ece8813acfdcaaf
87137ac41b108b239da8abdd6c9d92544a4663fa
23472 F20110217_AABKBJ smith_j_Page_122.pro
3eeb136a5214e6c17157e7395af75266
255bbf0f386e988dab6c42f58e4f44119a335bc7
F20110217_AABJWD smith_j_Page_121.txt
92c53a80858f29b44fad99c31c408108
82fd0053d9dc196f243d194a61cbeea0d11b1111
50201 F20110217_AABKAV smith_j_Page_107.pro
b23479c1fbd6f9fcca2728f550a67fad
2b9122a17d4efcc723cbe79665f2f3781939e74b
F20110217_AABJVP smith_j_Page_106.txt
a4da40b4244dc242a62130601d15fe50
60124089ea9491aba1525fe8d41f9807a8952149
30129 F20110217_AABKBK smith_j_Page_123.pro
fcd4814cf7e8d925ead20ae13877e1aa
aaf8bd497b4d9d8650992486bb804285889f4ad3
933 F20110217_AABJWE smith_j_Page_122.txt
638f899dab69802877c336114df8f10a
ee53649b2e69d861089ff3e35daae9b957be94a5
51555 F20110217_AABKAW smith_j_Page_108.pro
00fce45047164f6557c40a2cd10d6cd7
ae4589ce37bbdd27a35482a1496f804bfef01010
1977 F20110217_AABJVQ smith_j_Page_107.txt
3bdc4777ce10089b1eb8a4af6ef24d2d
398a30271c7e60f574c9856670cadb95ccdc7c1c
7029 F20110217_AABKBL smith_j_Page_124.pro
9d8673e750eb3c0cb5a829d334e5883e
a8d23477dc179d31dabf4174d23a7c5eb8159470
1634 F20110217_AABJWF smith_j_Page_123.txt
0057e7525b177244286f65aaedb15fc0
996d669427f3de1aac6dc9bed513b23e84e3e456
50695 F20110217_AABKAX smith_j_Page_109.pro
310763ba8ed4dcd7fbc46c84d7728402
02af7a992727da9837b65b4f09cb63a40d8e0f24
2023 F20110217_AABJVR smith_j_Page_108.txt
7a8a283c6cf7f8dd61c3398bb29d4e3f
4d7c92b538bfae2301186fc47192b80b9e0df0e6
63712 F20110217_AABKCA smith_j_Page_140.pro
2b5b55ce3920b5a7ef43b569b34e62a0
3d945c0b0ec5413ed11c3ad7d282a7c5b9689c8e
7742 F20110217_AABKBM smith_j_Page_125.pro
608427c16613c250aaca593010c760d0
b54a2929e20cb9eed15de4369683105b11e0e139
400 F20110217_AABJWG smith_j_Page_124.txt
4d3907d71649ee521a8f881e454f2b93
00133b1b800395a2a65b36b21eeb92a301feeb6b
54522 F20110217_AABKAY smith_j_Page_110.pro
365f68969ae8eaa84bee428c9e5fb141
dc6ea0e5322c0f22eadb6ce113eafbfcc42a3556
2133 F20110217_AABJVS smith_j_Page_110.txt
7dba6095da85101ad46c887db94d0cd9
5c04fc21c1aad11ab18eac3bd709092c62a54c60
66809 F20110217_AABKCB smith_j_Page_141.pro
2b0f3327d847bda22e2e6ca23c1a2e92
2801f3f98ead87c54f73c9c2b62247a2cdee6a60
19205 F20110217_AABKBN smith_j_Page_126.pro
bde1f6c4816b003367f2d3f130a78008
7f44b810cf7c5076b576e03035b03ad1e4e61b25
454 F20110217_AABJWH smith_j_Page_125.txt
20bcaf7370a782db6c0a3c16f61db3d1
ee1ce1957b3fc618eeb630652f49d4013a8bd00a
22442 F20110217_AABKAZ smith_j_Page_111.pro
8759c16b55a5b9cbe44e2c32ecf93783
12a93339a3dc0aace234bb21127745c36ad361d8
F20110217_AABJVT smith_j_Page_111.txt
0205cc153293cdd1ca233d7be0352b5d
a8c38d753e97296464c63b032ef5d5fa62f546c6
60571 F20110217_AABKCC smith_j_Page_142.pro
4e22d8573ddea4e46d36fd3744183386
0d7ab37f50780706ea2bd8d4a016e39d903b1ba2
13914 F20110217_AABKBO smith_j_Page_127.pro
e10a75a71dd09490f805f09f68eafa15
5beb78f8e838dfd2ce4e97973e4e0045bb4a2216
1308 F20110217_AABJWI smith_j_Page_126.txt
8a120a39628f710e5d0fd47440c9e1eb
ade7854720392986dacd90d50d55a9efe45a5245
2162 F20110217_AABJVU smith_j_Page_112.txt
be2316e24d9f86347e462318ba2035c8
64a3b7caab090761ebd9e7536ab5504dc55f8769
60155 F20110217_AABKCD smith_j_Page_143.pro
974c1b4704113fbe738d33dd76349c9b
409a4630d66660cdccd3c34dc757ed525a5294b7
64326 F20110217_AABKBP smith_j_Page_129.pro
8a2f79a4adbd9a4da31bc3445e991cbe
171a52312e5afa54411973ca6f89db5b3dc072b2
694 F20110217_AABJWJ smith_j_Page_127.txt
c6bbc2fcfcb4007c0441f0837bc595a7
6c8ebcc74ee82a2957214a9d55291e60f16f4034
1009 F20110217_AABJVV smith_j_Page_113.txt
7f49c927949355d21e82165f150da960
57fc738365520e45f285ee700c820482e7bdc8e8
40956 F20110217_AABKCE smith_j_Page_144.pro
eeb22c3720df4014e2bc9ee601fd0bdf
8b7074e63dfd8c9d553639a4adfdddcc78394243
62653 F20110217_AABKBQ smith_j_Page_130.pro
985896cd83a152c3ac4d36cff3555427
4186fb6bb63033bae9c84a134fe40e143ba81f2c
2073 F20110217_AABJWK smith_j_Page_128.txt
e4fe22c919011d343df0c3332a604a6c
4a9b65ba534020f3bda009d30f0ecd3a623f9437
1143 F20110217_AABJVW smith_j_Page_114.txt
61d5ae99de27866f2065e50dbee75890
f7160ba228aa6faa73e2b362022f48feec65d08d
28631 F20110217_AABKCF smith_j_Page_001.jpg
746deaaeffde46bd4052b90d36c6e334
ccdd2f2754344652de42bb539fb1995c65986aee
62101 F20110217_AABKBR smith_j_Page_131.pro
92e3b5973e45d2b8266ce2aa5f664f81
18e9a1bd107fe9ac5b7926ae1f15f5deded38922
2610 F20110217_AABJWL smith_j_Page_129.txt
6ea013530a510fe4178c3a84cf58abfd
d4c2494f24899e4aadd08c5fceba4f643b5c1ddc
1429 F20110217_AABJVX smith_j_Page_115.txt
2d252916e71be51341e2c3b7c5c964d7
1e4091cca5c817095f7ec044c585aff6f85d46c2
9291 F20110217_AABJXA smith_j_Page_001.pro
9493d85b246d9b3d3d9ff7c18431b955
288201cda6538ca29b4f1fe43e638e87fec5a40c
69835 F20110217_AABKBS smith_j_Page_132.pro
563471f4df2587befeff2784fb974d11
8b8ffb1fde620cd283d8667e9e04f54fcce14f92
2535 F20110217_AABJWM smith_j_Page_130.txt
7dcb395e29d72f0b18582257c9264b0a
814bf8e0c858b465ef17918837020c666a642825
1235 F20110217_AABJVY smith_j_Page_116.txt
4c171584cfec0adb353400d03eb8c623
81f9bc9516e91e1e5681f9cb36c9fd7312974a48
4582 F20110217_AABKCG smith_j_Page_002.jpg
13a4d4f966cbb40a4539b698ca7366a7
cbc6d08448201ff6e963fe45ceff7d81edf2bccc
1147 F20110217_AABJXB smith_j_Page_002.pro
325877aa509781908716867f8f066bb5
9c695225882109e5b8ee116ca1522cf3f505bdec
59883 F20110217_AABKBT smith_j_Page_133.pro
98b594d39c80532f0a1a97cfe4f64968
6f5eea82c0cf059e544de94b295bd2fe2011de57
2517 F20110217_AABJWN smith_j_Page_131.txt
198a4aa9a5fb0cdcdb0d022a52a5953b
7cf5846ab40a6abd36dbabb5d4602b35436e5405
3391 F20110217_AABJVZ smith_j_Page_117.txt
19718e3978aebe2b5a056199f9c199c0
f240bebed9062be8842337a3a5cf2f70cbd03b67
1572 F20110217_AABKCH smith_j_Page_002.QC.jpg
0260e74f80492fd06bd6ad3345bcebc3
2df6ab4d4c7058a65b210b167b912eaaf33f201b
649 F20110217_AABJXC smith_j_Page_003.pro
8db0f8e71848f5007cce0349f1066149
71df6cdc131a4fde84f6b602382c981ab11cf7a7
65992 F20110217_AABKBU smith_j_Page_134.pro
8ea16a58f0129073bb0d820d317dabb2
7990797c272ca6a2c92d4d5c7187797cfb019334
2818 F20110217_AABJWO smith_j_Page_132.txt
488ca772197c8848c489a2e7715c34f2
4b675e8876f0f376150d78750fbe182fd0d7ea1c
3262 F20110217_AABKCI smith_j_Page_003.jpg
e5987622484a78c16aa69ad3dc269428
549bff7b3a79d5d425e9a863a7d426d85b3189e1
38579 F20110217_AABJXD smith_j_Page_004.pro
d7a5fc47a0bbe3b2135d0d3891c49de5
0ec5205d45fb14171553611ebc06bdb2746621f5
64421 F20110217_AABKBV smith_j_Page_135.pro
c9561e198a3418fb90de326710095428
33ec8ef943eafcbadec198206e93880dbb53149b
2421 F20110217_AABJWP smith_j_Page_133.txt
9a1562f7d9f29107c84b45da83289fe6
ea0d6bfc2938cded857a35554ffe26f81659add8
943 F20110217_AABKCJ smith_j_Page_003.QC.jpg
eed852e01318d985e4db02b8f7c17fc9
d61740059e9653dc0f2ea04e3b538b4027ec5fdf
38178 F20110217_AABJXE smith_j_Page_005.pro
0a325c905623acce5ac13887ae6376bb
ee6103437956259806d573458c8e6ce898700aab
63673 F20110217_AABKBW smith_j_Page_136.pro
0710b91bb39811a7142b8652a4e1ea2f
82cbdf3b28444ec42697d650493b7f57f486b16d
2664 F20110217_AABJWQ smith_j_Page_134.txt
5bad0f475a2f3d4f90a7077c922c68d1
5cef257eb3c0b7c1e24f163cecd0715dc2e074a2
80630 F20110217_AABKCK smith_j_Page_004.jpg
b0d4d7a86ed61490fb6da8c59458411c
15cac7096712a52973e2af082d75f7188b13470b
75757 F20110217_AABJXF smith_j_Page_006.pro
36c8a54cd5c33ad2706f4dcba737ed7c
0a4811b9e6b48521a11983f74043114bff7e22f1
63411 F20110217_AABKBX smith_j_Page_137.pro
4a608204434e10788f3246969a786702
3ff6fa3dc4d71276ad03c6f88ee60c3c6890a32a
2611 F20110217_AABJWR smith_j_Page_135.txt
2fcc70077cd6b040554230258cdb0c56
f306f39ae698bf32ddce75e6546898591d833017
9016 F20110217_AABKDA smith_j_Page_012.jpg
aa436bd1710f6ae7ff746bb899e3d22c
da78a7085299e22cb51510485cebf3b129422b34
26304 F20110217_AABKCL smith_j_Page_004.QC.jpg
b4bc0808945cd2c58ad21946b860bedc
38159ae16b250ad553e755efbc4c5036c3d4877c
94399 F20110217_AABJXG smith_j_Page_007.pro
bf31b55f7868c266d13e836552905b49
b9ea4dfad10cf27d38105a0dcb8939eab703a0fd
60782 F20110217_AABKBY smith_j_Page_138.pro
57e97e749d3d7c0aeb9c29d1039faa02
e15a54f133285a70e1bf36b651ae0f186cf9af64
2569 F20110217_AABJWS smith_j_Page_136.txt
e7a35efc6a91a8c1d9878e69c2143fbd
d85decedb2154d25072564ff9d1fe0eb178ecabb
3044 F20110217_AABKDB smith_j_Page_012.QC.jpg
a1daacd3f926d2eccddd18c3cdbcfc70
d5dedfd08271e6a26229db3a2a2cdc049f8556a8
80966 F20110217_AABKCM smith_j_Page_005.jpg
5cf0067cc7881188b9c350883eb8d6c4
4f449f46c6707b4970f112d9924c5398ac8872e2
15526 F20110217_AABJXH smith_j_Page_008.pro
190df0a998d93d41e104baa73b043643
d288a585db0eba8ccb21318efb70b8e6065d917b
63017 F20110217_AABKBZ smith_j_Page_139.pro
b905a82b9a6898bfa2ef9a18ba190eea
c8fb659366036bc16a93b355bd22aee475a71219
2587 F20110217_AABJWT smith_j_Page_137.txt
6ba4cdc71bbb7028c88480fe297a1af6
d52e7f367bfafe379895619eb4e18792e0a387aa
87248 F20110217_AABKDC smith_j_Page_013.jpg
fd20b13408bbe5a4bca0cfa79d0742e6
a4b81bef201f56385de8ffdfff830e45b24339c7
26167 F20110217_AABKCN smith_j_Page_005.QC.jpg
831d1a6b78007905461be1a110c05a2b
ee421831f52e332dfe787151a48ebfe893911e52
57460 F20110217_AABJXI smith_j_Page_009.pro
a5a8af90c39fc3768dce2ee5e3834d36
eeeacc348948e3ddf10cdd8fed0f3cda1b87cd78
2464 F20110217_AABJWU smith_j_Page_138.txt
fa3a7c16786914d634d4ff4912777394
ce4bca3894ab2395606f50e8436753b6bb11d4d7
92286 F20110217_AABKDD smith_j_Page_014.jpg
69ff73e71e12f1f7c5edffa74e903026
df3bf4a636648d8da57efa82917b80a14131c834
85818 F20110217_AABKCO smith_j_Page_006.jpg
b07a05ba9e6254b9ea57e10a99f87407
7e5d93f8e284af62f73d98a705dbc7e9ac6ce401
11643 F20110217_AABJXJ smith_j_Page_010.pro
ee758edb4a98bf9c2fdeaee14fdb891f
795fb35a367ef7dea618078a765d95cc228273fe
2545 F20110217_AABJWV smith_j_Page_139.txt
7efda012b7ae1231adcfd11538f61297
7c100b631def205a884fa359db11e3ec9462fec6
30164 F20110217_AABKDE smith_j_Page_014.QC.jpg
65ae6ec65ba82b091c5243fd98627172
56b2cde021db3179b482fbf124a9bbecb64b950d
20020 F20110217_AABKCP smith_j_Page_006.QC.jpg
9fa70e173dfea283d44ee53f076f2f22
edb56e7e267b288a71b1e7a0692043722e59c36c
58323 F20110217_AABJXK smith_j_Page_011.pro
eb57dc943553eca0f87e855ad610c4c2
739e297bc9b86ba388a750755bd4dcd9f5cdb2f3
2582 F20110217_AABJWW smith_j_Page_140.txt
cc3602251d970852010517f92d8faf81
dd9212bce4d5488609bfdfc8379009dfd771a2c8
91012 F20110217_AABKDF smith_j_Page_015.jpg
9ed93e817cb43bc84fb6b7c5d79039d1
3c1b7a9a62aedc22a9d1f343d1b178daf030a01d
115387 F20110217_AABKCQ smith_j_Page_007.jpg
b264cc18c57a418ff20b14932b75f8fb
cb409e56fabac73d42473361f6750acc34a37648
5084 F20110217_AABJXL smith_j_Page_012.pro
2ac606eae85eea057661ab5c3596cc91
1f7780e9b17855b1987066380482533f3a4709e4
2687 F20110217_AABJWX smith_j_Page_141.txt
4e1957683f60bb78718686d461089577
20b4bd0292144f46fc18ff21bf126682fbbb1287
29297 F20110217_AABKDG smith_j_Page_015.QC.jpg
0d8bae8b10fea989378c05c809f08ace
34f5d40f90d9413459136e4b3bf3f0bb6e9a19cb
27747 F20110217_AABKCR smith_j_Page_007.QC.jpg
b651ba0594ff10f3aa25c49ea3ca321c
53a575b9d513ca51dff7c6c2d233c93a5c56967d
39978 F20110217_AABJXM smith_j_Page_013.pro
a67943b2ad76e9053b419d0bc08bcd7f
89e712c386d53d3d210762d7f24ed3a10e226884
2459 F20110217_AABJWY smith_j_Page_142.txt
20d34e701bf68d69e9b5469b2c6f2469
a1366e87a135ef81db33bbe9659eb0a8b0ac4f64
49989 F20110217_AABJYA smith_j_Page_028.pro
99500f65965e135ad357f717e8ce9963
49c34be2ffd78bb5e613c6faca1395945bd187bd
19152 F20110217_AABKCS smith_j_Page_008.jpg
c8372d659da50cea720cd1cad91f9cc0
da9fba78daa9ba2faa803e1f736227ca9abc183e
45371 F20110217_AABJXN smith_j_Page_014.pro
6ff8cb0781e71c4511e0dad6d804d814
a963d1ab57d87743f621418f5e467ac67e4c32fd
1668 F20110217_AABJWZ smith_j_Page_144.txt
1a16a33acebb431a69a308628c085bf1
861d496e6f2cd891a5b276f6a14a7b70200bb17c
101058 F20110217_AABKDH smith_j_Page_016.jpg
21e193c3217eaa7a8396abe3ab9c89d6
bb5a35bf2ebc741018f1c63f856be79d67db12a6
44659 F20110217_AABJYB smith_j_Page_029.pro
826cee0a0f39d6ae09a47010dc02147b
7bcfcbfbc5bae8339c61ce8ce24f3e9d313e050b
5200 F20110217_AABKCT smith_j_Page_008.QC.jpg
7fe6118ed3d4216d320e6eb9058cca49
425aff4d5f8db54de97ef92c76581a66bd684f82
44096 F20110217_AABJXO smith_j_Page_015.pro
64c80660a14fdacdcd838f2285044ba5
94304930e4c434a45cc222f6289fbfed6283b649
32330 F20110217_AABKDI smith_j_Page_016.QC.jpg
7058937f31b0a5429390a34a1598ea34
03af40f94bf98812f198c56ea136455167aa5362
52121 F20110217_AABJYC smith_j_Page_030.pro
9dcef4d01d58e9fc65fa0435ba9fd41a
7395fe7682cdd0668502ab48e00c6678984b0a22
81764 F20110217_AABKCU smith_j_Page_009.jpg
866aae03780c3053da64454957200c56
d4e7e01a62ea7da70aa2a60aed0ffd866bce21cd
49729 F20110217_AABJXP smith_j_Page_016.pro
63f5b474790b8675e269a06b5fa9b6a0
48d5c39e9687194cf02092880f14b29fc636da18
35402 F20110217_AABKDJ smith_j_Page_017.QC.jpg
40e88530569479ee41d387fd3873c06c
8d59f0709780e4d94920e9a4506b051b4192d9fe
49940 F20110217_AABJYD smith_j_Page_031.pro
f29dce8d7141ace1f155d97f268bf3e0
662f75e833bed77a83c4d90c854bc1d15d57ded7
23603 F20110217_AABKCV smith_j_Page_009.QC.jpg
f97d96d447b50edd18b34453d27f17c9
7673e7cb734ade02cbf54573c1eb079af3cf387c
52953 F20110217_AABJXQ smith_j_Page_017.pro
0e56c99be99c06fb0fd7e32256db4798
44e0431d1a42cef098e98ab3d9a76f71cdcccd0a
97023 F20110217_AABKDK smith_j_Page_018.jpg
9a14f1fc81f66855d53a1ddcecdc8b56
12fb89f86275b2a0a82f10043027c60da207e456
45446 F20110217_AABJYE smith_j_Page_032.pro
1dcd6cf98c42629c029e271318cc1729
f14d7614e0c46e3f4eb71d5136f363c62a7b5331
20767 F20110217_AABKCW smith_j_Page_010.jpg
ba9937890562a2d115906c6caf127ffd
1661f238df28834d434f0418d73e89ad3f63946b
47272 F20110217_AABJXR smith_j_Page_018.pro
01e7bce946015efa427ce1f725faf85b
6209f0a065414f48e526f5fe0fa6576fc49a7c53
94458 F20110217_AABKEA smith_j_Page_026.jpg
f10d93f5d7caa95c16a9ed7430fc06c2
4df3f4ec7a7d4edf08adcc639afe138dff9f0174
31567 F20110217_AABKDL smith_j_Page_018.QC.jpg
68229d7563863a8e3f864b47f7e3a658
53b12c65ea58fd2e4da46e113a93097c2eea3968
49211 F20110217_AABJYF smith_j_Page_033.pro
7a5521c0536609412ddf9a513e2a28f1
db17a37e8502308db75e192a2eede5b555f0c466
5499 F20110217_AABKCX smith_j_Page_010.QC.jpg
8da0f857c5208d2cdc34ab26fc7f6b5a
562c4bfee5dbb44659145d0070bcc86616d8c5a1
51026 F20110217_AABJXS smith_j_Page_019.pro
ef16adfe8b6c6f7155a2897caf9829d8
a2800202c0bef0af1023e90e83d111d457bd79d8
30531 F20110217_AABKEB smith_j_Page_026.QC.jpg
57391b76c7f15edb10bfc55a275be4ea
5031bc679035c300eb264d4e669dab01e1d8415a
103524 F20110217_AABKDM smith_j_Page_019.jpg
b300c58cb2afccccd93feca09d7f27b4
3f6e38efd6d0c1f4599cf24fa90edb8425dbb8b0
37799 F20110217_AABJYG smith_j_Page_034.pro
f811f003ce685cd531f0eed762b74bd2
30da21cb150d161745fa763570992474c1670c0c
85860 F20110217_AABKCY smith_j_Page_011.jpg
e23264453cba6fa6a6570905c98e455f
516233d114a1931e36be70ba55eedf2f23b67c80
103804 F20110217_AABKEC smith_j_Page_027.jpg
8a8c0722ed03d04c0eb98fcc7778b35c
ee7bf0546ecbee652774fa2f15421e77ce3e1daf
33135 F20110217_AABKDN smith_j_Page_019.QC.jpg
8dbfae1eacf87f88a5c59578893861f7
746afafeff697233ddd10ba838352ea5be3ff5f6
3360 F20110217_AABJYH smith_j_Page_035.pro
8529f0669b288d473a57b75b5c9a5bd5
5960abe76ae5683800dc0b4bdb796a9db0e5039a
24563 F20110217_AABKCZ smith_j_Page_011.QC.jpg
4d77bda072143c788a406cc0abf5c439
22c25d4b320a20a60b50e85f96e9ed4f1b4758f3
50929 F20110217_AABJXT smith_j_Page_020.pro
b0d55c80f49145d00ac346ce02eb2d57
a279555705aa18c2a75ff78125b5a782e6d4e371
33474 F20110217_AABKED smith_j_Page_027.QC.jpg
8551109dee3934b09ed52abea3721bf3
40bad4a4aa2e6531c7e9334ebd034a6b8d592e63
103831 F20110217_AABKDO smith_j_Page_020.jpg
4bff18bf13f39fce7406a82ee532ab8e
d48366c0b5bd8caf602d7c9801e76e73076faea1
12629 F20110217_AABJYI smith_j_Page_036.pro
d9b457923cfea05fe73ada44423ea2e1
07b200b5e7cdbb8251188dc052d13210a3634148
48021 F20110217_AABJXU smith_j_Page_021.pro
d37c7c542cd7fa3e7a424fc2d99341cc
27e068065b657a8e6354116d793d3317edfabb84
102112 F20110217_AABKEE smith_j_Page_028.jpg
621ec8ea39ad958baa48adb5e720a5a6
ad48aeeb8326b9494514493b84299693711c82ae
33404 F20110217_AABKDP smith_j_Page_020.QC.jpg
f2dc7fffbedb44053f9538a5dbe143bb
8533c0c08d5a9c5e8a9f39dac64ca232bb75d8d4
18775 F20110217_AABJYJ smith_j_Page_037.pro
215232020e0322281024452d5871b9c9
ce4b2a042573af78e36e85b31c7d3c5ac54bf47c
47738 F20110217_AABJXV smith_j_Page_022.pro
d0a0b5c81800e49e627a9ea863b978f4
055bc8a110f3e435ff6fde8596c896cf1e213333
33143 F20110217_AABKEF smith_j_Page_028.QC.jpg
b6e1cabf5b61f127aad483a07bbe1af1
9f0d97ce1fab80a5a5cfffdf39b7bba1d1c77ba4
98221 F20110217_AABKDQ smith_j_Page_021.jpg
39f7935146974d4177cca96e60bea501
d8818e2643368450e3221fdca2222a88b93458f0
15306 F20110217_AABJYK smith_j_Page_038.pro
10a53926dea5291f20ef7cc218d26bcd
85abece5e8a67609a5f882b2f60a99b72a281678
49042 F20110217_AABJXW smith_j_Page_023.pro
9d1d85b12c043b4cab04696711d3450e
bf2e848fe4e9cbc902c5b93997f3387c18a14086
93422 F20110217_AABKEG smith_j_Page_029.jpg
bbb6a9bb66ab3e9e8b9a0854d6404d6e
d8efcd87a02099e86fa8c67cdec20069600a585f
31208 F20110217_AABKDR smith_j_Page_021.QC.jpg
e295ba543638e76935cd5a1a72255b1f
37341550ca68b94215023c79e5d2709d33b82445
5481 F20110217_AABJYL smith_j_Page_040.pro
0651c8f4d1bfa9be5061adf0cf19d3da
85de2c10e5bb2f08a4564a1ca2c805f2b4073eab
50872 F20110217_AABJXX smith_j_Page_024.pro
1e4c7f12473016b00cf58591013cd3f4
b50538a63c565d899259d0ee94fd1a88c568ee17
30078 F20110217_AABKEH smith_j_Page_029.QC.jpg
6d2ab4d5940934616bb75efe4fe25491
54a3230228b3cd2d34bf19e43f87343fc300a9e1
39488 F20110217_AABJZA smith_j_Page_057.pro
c2013b71500df186655dd647ea09a449
90726548f7e10978eb16525e939432da5b6e02f3
99478 F20110217_AABKDS smith_j_Page_022.jpg
c5cc2ca8f4fbcb699747afea7da9cfa0
3aa7e53cc8b84cd02851e2e2272e529b589ed528
41685 F20110217_AABJYM smith_j_Page_041.pro
e7d1ad2b4264c21c0fb1d9f88fe0f145
fbbd91fc37681d1acd948f4473c71ba774dcf0cc
51338 F20110217_AABJXY smith_j_Page_025.pro
24d75130a376b111665c0fefde970ecd
313463c4177796dc5a0a6db9a5c69b0adf6faa6d
32050 F20110217_AABJZB smith_j_Page_058.pro
53ae733afa2fe08c583e80e22fb9720d
b3cf14a1a40bf245f9b84bc3f4f0c499e740836c
32232 F20110217_AABKDT smith_j_Page_022.QC.jpg
a9308035f6feff30e53db47c5d206f64
2e6b343a950d7cb8fde209d55f4b35090ea9e23f
50861 F20110217_AABJYN smith_j_Page_043.pro
9d9e534f5e01f36aa92a52c96e11331f
a368d44b430b71318f54a3cde7d097bcef58cb89
46326 F20110217_AABJXZ smith_j_Page_026.pro
65bc7581bb20fdabee3fcff3b7c7d18a
78063c50ab5d129eab2c8b96e52766d70a22b4f0
105709 F20110217_AABKEI smith_j_Page_030.jpg
0ff28c90e6147fb4a8ae29aeb5c86f3c
528c1ccb56d62d0c93dbd4ab2815027493eb9175
64289 F20110217_AABJZC smith_j_Page_059.pro
34773872188b31ed28b9dc70fae5cd67
0779b8f88c105aabf284f5a7ee21a898bdfe1ccf
100471 F20110217_AABKDU smith_j_Page_023.jpg
f967a40e9b137c4d91ffac05281b642d
7ffd2ca87f0aa0cfd8462ea3e430f4ea53863d11
47189 F20110217_AABJYO smith_j_Page_044.pro
b3a3cd08a33804f3ba1d22bd2b858404
d64c4c85ff51be67d14732ef454c762f09b4f32f
34866 F20110217_AABKEJ smith_j_Page_030.QC.jpg
1a917f9d57aa3fcfaa4bc4050ea3e57e
03b6d68d65ffa66240683c97b9ee0c07210845a5
6639 F20110217_AABJZD smith_j_Page_060.pro
fb4b1460959c8f2e84fec1cbdfa18827
c0bbddb986b4a77932a852f40a3d8ecacea48f44
32996 F20110217_AABKDV smith_j_Page_023.QC.jpg
75c5c97639a0a5b083c3a0704be34e57
49f5b37382dbe455dbeb4915b7a8471375119699
44997 F20110217_AABJYP smith_j_Page_045.pro
23564fc57e57af8ba67daf522a2a3784
d9560c7f8137b7d434da6b8f71b68bfc7e0117e0
101766 F20110217_AABKEK smith_j_Page_031.jpg
54699801f70ae814c954eb1aa6e8a353
7305926e72a1678b7c65a664d9e8f9cafdc93f80
16658 F20110217_AABJZE smith_j_Page_061.pro
18b0d4c11fc29b5699e3c48c91eff557
464d0550e0509e32c9d958100051851713a4836f
102558 F20110217_AABKDW smith_j_Page_024.jpg
6c6219cccfd1831dff9855077a314781
beb7553c4f6c3771183baf38f5b3ca5d625911ae
46381 F20110217_AABJYQ smith_j_Page_046.pro
4b7194b0d258a36cb0907667ed14af2c
e11caebebb44da83cc0b60abaaaae9b0b05747cf
32490 F20110217_AABKEL smith_j_Page_031.QC.jpg
bf5fa60b64456488c57b850951541cac
d4e6656df589ffe48f8257ca09e5eba5a35dc7ae
11109 F20110217_AABJZF smith_j_Page_062.pro
d9a3db235009659781f552117f1c991b
e2354a440955e298f708424af78d1133714715a2
34606 F20110217_AABKDX smith_j_Page_024.QC.jpg
d39ce90db539234f3b1c5f502e150a9e
6a8b8241364c0ebd5bcef8376974178827a89bc2
44427 F20110217_AABJYR smith_j_Page_047.pro
20b468d3dc17d9744bf8d717077e816a
d6458d51bf166a7d75507fa6399f5acc4ddd27ee
43856 F20110217_AABKFA smith_j_Page_039.jpg
2b9c7076e10c37a19617358afc446816
6e3482280772d4c6fb41f1dadac051eaebd01f6c
95538 F20110217_AABKEM smith_j_Page_032.jpg
e3e5cc62e1655e4a5286f04e1f90c7b1
2348853b3d6132372a9089f3060082213693cdb1
44774 F20110217_AABJZG smith_j_Page_063.pro
eb98b049288a08ee2b00a1f965221864
03a3d60d9d16657be600006253923983ecda54ae
102783 F20110217_AABKDY smith_j_Page_025.jpg
4ea6726464cdf93ae3b1166f33078936
d993e53c9f5153fafe8f6ada1a87826881055daa
52994 F20110217_AABJYS smith_j_Page_048.pro
d5a08dbdc0c6e0fd335b1d9da0ae86d3
686900cea7fc565a2c2edcef613781f2e9cf8a97
14200 F20110217_AABKFB smith_j_Page_039.QC.jpg
bc6a15ab169f7033b5a853e03eb1cbb5
f691ac4f50b1878f7acc726b9ca25c43cb5e5910
30898 F20110217_AABKEN smith_j_Page_032.QC.jpg
7b2cec12aaadb176874da297463a66bb
8bf973e276210c4842d88d962e52b294131397e7
46251 F20110217_AABJZH smith_j_Page_064.pro
9e933256ead142cb24f638ee55c58e58
77d76f0cfa7b802ecef876e7d7ee24c43faf66b1
33478 F20110217_AABKDZ smith_j_Page_025.QC.jpg
1db4965076552ac2d6feaf921fa344d7
4d1f87ce9af1cae7fa1c89c86097cd93ae6a3ec4
50755 F20110217_AABJYT smith_j_Page_049.pro
0776b9e1a09de26c3c33f54e5373ac4b
168c5f94584966526266934095589dc27ea0d6df
52098 F20110217_AABKFC smith_j_Page_040.jpg
f85a53baee158a0cab6e8a8fb05c5cce
3a444dbd2bb6db82e48622adbcfa5da7e3e0dd69
99250 F20110217_AABKEO smith_j_Page_033.jpg
b9caf1e27c58ad1c778aa3375fc53fdd
d8ee178004caa08e04656a916017d49c62b9bcfd
49908 F20110217_AABJZI smith_j_Page_065.pro
6f683217121b25a2261fcfe5126f0f17
8164e4024a02b5e5b53b32855206935aad2e3fda
49149 F20110217_AABJYU smith_j_Page_050.pro
c7320cf2199bd145580a44c49b632e65
4fd42afec3bf064e113b5f293091ce54be4d43e5
16519 F20110217_AABKFD smith_j_Page_040.QC.jpg
89857b7e8da1e5dd8e975c7179f556c5
93a09a4def6ddb1c1c5bb591e4d6da142ae7e965
31764 F20110217_AABKEP smith_j_Page_033.QC.jpg
42470eecb1cf1382cc78005f6e402f0e
b4fdebe5b55e125650e6ad690437617ea0ae6abb
50085 F20110217_AABJZJ smith_j_Page_066.pro
d29fb7fbef2f3c8d37f03248b710c725
8e7e32315e5589517d7462876b86949f75cbc51e
52240 F20110217_AABJYV smith_j_Page_051.pro
64e585a0ce27ddf0222a4542c42ac978
e48b8a1657238a47da7fda80418e408a3bddffc2
89610 F20110217_AABKFE smith_j_Page_041.jpg
a26680844d976e05346b3ce0a8fbdcda
2ddbe9aaf86c8f69a4b71b9fa0e832fe6779d16a
49864 F20110217_AABJZK smith_j_Page_068.pro
2d9f72a378ac67cb6a856485c7cdd6d3
21c5dc9907726bab8a8b18ef0ec5bcb57385353f
49832 F20110217_AABJYW smith_j_Page_052.pro
ae129af6acb380fa3be511d5aecab56f
fe1b9b694c0ce7c004799bde936d3819d98765a8
29391 F20110217_AABKFF smith_j_Page_041.QC.jpg
5535f4440474131754c724b7844658f0
bfbca29117428cf87dd35d5d4745b8bc80f554c6
78811 F20110217_AABKEQ smith_j_Page_034.jpg
4ba817a3eebbf30c276ec3a7c7e32b29
dddb8f4dee886686f31a116ec66f36eaf706d499
44760 F20110217_AABJZL smith_j_Page_069.pro
83ebb494e7090bff8901954af14bf83b
9a5bc7f7b8359c33b1b7698edaecddfe58f0016e
49824 F20110217_AABJYX smith_j_Page_054.pro
7f91089fdab921592b0f75d35b78f003
b7a9f5492d63b659522cc9e4b063e028e8e902d8
102985 F20110217_AABKFG smith_j_Page_042.jpg
e5124bb3024ee289885a0d74f3bcc8c9
17e640d9bc4a5c9ea991e262278acbde5ee1917d
25820 F20110217_AABKER smith_j_Page_034.QC.jpg
04dc99a9fe0442c7168c0cd2e5c616fe
b0383e936247b960a5846d75355cd7ef51f5f6ae
50559 F20110217_AABJZM smith_j_Page_070.pro
0c8c0318d1ba42c189bc68870da3db61
15eb02e61df5db4402e69af772b9df3d6baa4328
40520 F20110217_AABJYY smith_j_Page_055.pro
16870071a03be4701ba4e9ec022fb831
42dd5e2cc6e17561d800df69eedaefe7f6b3d18a
32831 F20110217_AABKFH smith_j_Page_042.QC.jpg
5d7bd64dd9575efc19577a7fc8398e10
c522a6c770e06da8741311f27e9a706148c68426
27108 F20110217_AABKES smith_j_Page_035.jpg
f521c319cc46b2d2e054b81700eb0517
6d5aab85d0042bc2e3e258ad6491b37b89044173
46667 F20110217_AABJZN smith_j_Page_071.pro
6c2bf08361e3a30deb57bc381be3df83
a1d7ca000aa4df0748fb76c818c3ec819f01dc85
40256 F20110217_AABJYZ smith_j_Page_056.pro
dc03745edee0bffe1552e7184122f3b6
38bc6e698aae34b27dc81dc4d44dc9b9dcc81ea0
104131 F20110217_AABKFI smith_j_Page_043.jpg
f45b8744fd45bdfe8920ec829018c23a
afc80c3e67f0e44a1960169589994afad7f079c8
8960 F20110217_AABKET smith_j_Page_035.QC.jpg
fa77626d535417773ed9c3272cf22705
1279a0986de6f00a9681410e502b5c1df7fe65e2
F20110217_AABJZO smith_j_Page_073.pro
c91cba378e05d2645fd95de7a0762989
5676c940ca3d9c1a093ced6e0cbcc5c2c5fbf2b5
40521 F20110217_AABKEU smith_j_Page_036.jpg
ad0416d20d327501d5bc7fbe7a47470d
3c991457683e66ee6ef7893c83898596bba0956b
48791 F20110217_AABJZP smith_j_Page_074.pro
02cc0a506b9c5b83deaa888dc8aba7ec
990edee9dc7219a723c39829f22cd27cec5867fd
34731 F20110217_AABKFJ smith_j_Page_043.QC.jpg
cbe21068298d50dc175fc278716388ad
e9f25b417a58c793a9df219ee32bcfe03a9143e3
13601 F20110217_AABKEV smith_j_Page_036.QC.jpg
4f167f001efa64c441ac560c3cc2c10f
92ecf490121fd8e1c7192856947ae919e9da92ec
49993 F20110217_AABJZQ smith_j_Page_075.pro
922eb169c7ef7a0930611bd296ea15ff
e57dcc924bb8f75c17d983a6e2af0f7af2959c7c
99845 F20110217_AABKFK smith_j_Page_044.jpg
25eca2b458e4bda887d72cddb46f3dcf
91071434ac40cb23910d2ca8453cdc10127029a9
39192 F20110217_AABKEW smith_j_Page_037.jpg
c82e0d6565db04ca449ef69fed2b2b13
304dfb728193a51d4b4556048aa2b785c3dc00a6
49769 F20110217_AABJZR smith_j_Page_076.pro
749b2cd25b8e45f4bef27674221d1233
4421fd73016d6608dffdb6e05fe01be5308a2ea1
104097 F20110217_AABKGA smith_j_Page_053.jpg
ebaed97534069495d2374b90ffc28f3b
bfa1a8c83e256050bb5fd24e00f3b13dcc96bcd6
33228 F20110217_AABKFL smith_j_Page_044.QC.jpg
3e661fb233a9684a640174ea221cfe48
98e145fbc355a54a08f3561be9cc7418ea1d0f13
12559 F20110217_AABKEX smith_j_Page_037.QC.jpg
d1d01bc57a1039eed4f32e597fda5bf8
f01412e4e15530cbe0fbd308feb51b3b5212a517
51650 F20110217_AABJZS smith_j_Page_077.pro
2e4a1d795c6ae6e310d82d104a1a2bdd
40f3ec899d46bd5e399b7e59f0c53b053b688bb8
33506 F20110217_AABKGB smith_j_Page_053.QC.jpg
827b97d94163154ebf09fd0e630323be
8457130a45962b0a1b765b095506e351524b53a7
96568 F20110217_AABKFM smith_j_Page_045.jpg
b551d8896bd1889280aa821d63ec23c5
c68df499d6afe644ab49d50302c42c62c18084b2
101725 F20110217_AABKEY smith_j_Page_038.jpg
c80e1264de37079f9d1d6b9148909cd4
8c8a4c93b8e5948f6c1b1974b47007e4ef2feacf
49006 F20110217_AABJZT smith_j_Page_078.pro
7f0f2775f02e53b51b3f1e97a68e97f1
0b12d00dda65f0e8a57a9cb3dafbcf74e57018f6
99357 F20110217_AABKGC smith_j_Page_054.jpg
16344f56f086c93d2f4fdaf12cf29faa
18ed7efe114950e9f205ffa9956cd5d662869802
96967 F20110217_AABKFN smith_j_Page_046.jpg
a8689a87e8b706ea09d0a8fdb9ac54eb
34492966f55d11d728b527fe0d0cfb2ac58633a9
25240 F20110217_AABKEZ smith_j_Page_038.QC.jpg
c390607ee3f83b234597402b7c10ecc4
278857a3d92493d51a9cadc4e21e4b6095d1c342
48164 F20110217_AABJZU smith_j_Page_079.pro
b2ce1c3f5c439503c25c6df1bb9b1b1a
55bbd6abff8969b8f1975081990f17deb3c67b2f
32302 F20110217_AABKGD smith_j_Page_054.QC.jpg
a6e3435e35c1cff153aa51cf942989ab
ba27e99cb895d6369e4a64148fc181034731b2f7
32997 F20110217_AABKFO smith_j_Page_046.QC.jpg
195692463ce6426a3533a4c4f95c017b
36dd359fb00c99c1034dd60bb24dbf3b5b09a2f2
53283 F20110217_AABJZV smith_j_Page_080.pro
6a28b358fc44e5034b7835ae56741bfc
ecf0074b038275e398002422cfa5b54a00aadd29
83979 F20110217_AABKGE smith_j_Page_055.jpg
97dfd7072a3ac3db6294178a43cb7b5b
5bc19a32f9bdd28162de0e82dd75e8d5c1268353
92575 F20110217_AABKFP smith_j_Page_047.jpg
9db540c7d9af9b0dc4f12a3ac9e545be
394495ab638df074e97be8a471125eb19ad080c3
51321 F20110217_AABJZW smith_j_Page_081.pro
1eb9eb4afb0d5ba85ba9ece6c05cff3d
36e938755cd9e2c65e11485d91ddbf2a4f2282a3
27358 F20110217_AABKGF smith_j_Page_055.QC.jpg
f995848b32ae35a407b93412e2ba5f7c
99520907f1cfbaa946b6ad7dc463c65094af082c
30306 F20110217_AABKFQ smith_j_Page_047.QC.jpg
10d875f706f7ca3f4d36a088e3536c17
d0551452fbaf39d454714e33608637d52f0769bb
49883 F20110217_AABJZX smith_j_Page_082.pro
ce6e0f768531429e59b94226deef84fa
d8af2cf97b118d658754f6c3a4e3fa12c73e945c
50709 F20110217_AABKGG smith_j_Page_056.jpg
772eaaecca671f22864afa6ab42ddffa
827a9d75483b0d84c212f797ce8aa7937e32f38b
109430 F20110217_AABKFR smith_j_Page_048.jpg
ae00a150d54f99fbe95497ce4272505d
85821a1937ad48fab03c6cd2e74ddcd016ab6372
48525 F20110217_AABJZY smith_j_Page_083.pro
aada48a10594d56806e40c9a963f0144
b75238f82d3e3bb3005e492ae8e4b8ff91c5f2ec
14854 F20110217_AABKGH smith_j_Page_056.QC.jpg
bc79646e37dc45b48d6f843ca2c57852
6bf8be0692085500cfbbd1d50f560adedee372b9
35816 F20110217_AABKFS smith_j_Page_048.QC.jpg
f70a6995dfbb13f0ab723a1dd251e30b
92d77d6e344f7b815c3100f455f70302ced8986c
52835 F20110217_AABJZZ smith_j_Page_084.pro
5cfb7fd7a5b4f1c6d23649f400038d85
373970b2bf1fc98ee3785e2af4f20f60d596f4a0
76079 F20110217_AABKGI smith_j_Page_057.jpg
c5666c244d822173df6e81f4fa1b3653
918a10a8d9e042c381b789e725994a30749a7bc9
104636 F20110217_AABKFT smith_j_Page_049.jpg
fb095c5979a2543025d511c15b15b1fc
ede1688686df14961d2c35fa293eb809e5430018
21029 F20110217_AABKGJ smith_j_Page_057.QC.jpg
70c3b2e7ec6df4c4cbc85493b1b87bc5
d71989b455ef0f8f328ae439f5bae9dcf69047e5
34339 F20110217_AABKFU smith_j_Page_049.QC.jpg
467089bffd5b163ccb2911bff3a4706a
611e2ca282d4a028845acf532c6ec0cad747a4d2
99537 F20110217_AABKFV smith_j_Page_050.jpg
cdd332441f1d13a28e1b8b0766d3bd91
d6fea463874023ee5e3ca2d3136f3a1ee236f758
63710 F20110217_AABKGK smith_j_Page_058.jpg
44c3cb684cde05559244d3619d35e802
fcd646e7ba0ab3d7e40d58e06ea52c8b96ba4689
32419 F20110217_AABKFW smith_j_Page_050.QC.jpg
24d94f3de459331d822b9b0d0b2f27e1
0103411b36a6334ac4316180956c63d02dc545b8
70569 F20110217_AABKGL smith_j_Page_059.jpg
a2d2c8f9de2f4cb6107ce515076df48b
32311ce374f4ba13a64e25e4ca994414129dcb8b
35767 F20110217_AABKFX smith_j_Page_051.QC.jpg
f0d63d515b6d03427b6f8de62be4bee8
f621a4eb92fea657fa0063375565e02319654aa8
33169 F20110217_AABKHA smith_j_Page_068.QC.jpg
5d93512a82d4fb948642afefd99c9c0b
a892d246251743dd63111a5c4fd01fbb77090c2e
11981 F20110217_AABKGM smith_j_Page_060.QC.jpg
d8e7f4143e09f51f81cdc00ad3fde41c
7966add7abba0694bb13c3c84252c8d3e7e506fa
101748 F20110217_AABKFY smith_j_Page_052.jpg
40eb475767489f984f76afd15fb1ec25
47fd75df3d0be6e4989f37f56cb8cb6b349947a4
92142 F20110217_AABKHB smith_j_Page_069.jpg
7fd42f220978c39db23201b09d2e0f4c
abbbc33230aa6c9181c411ab59bfd709280c0a4a
40585 F20110217_AABKGN smith_j_Page_061.jpg
3a2eee7c48a70bcf4a5d3125d60b2877
d6094620755bb28a57a2fbbe363bca8fbc0937ff
32657 F20110217_AABKFZ smith_j_Page_052.QC.jpg
8faf423003f4971660482d8580e503c7
9793351cd59ce81dd78f8b66ee3f853b2594e8b6
30024 F20110217_AABKHC smith_j_Page_069.QC.jpg
9b037ca5c3f00428d6ac714e45e4ba06
fab98bdb1d809dbbf9fd5f4805d4e8838f03fbce
35995 F20110217_AABKGO smith_j_Page_062.jpg
0277f505d062974a21f17e3678f67a68
909a4cae040e9d8eece7fd295a4717327c22c6f0
104288 F20110217_AABKHD smith_j_Page_070.jpg
673599f10629b8bb5e6115209401c161
851327c1892006354fe525b7a86848905ec7cb1f
11074 F20110217_AABKGP smith_j_Page_062.QC.jpg
bd2fff8b23285df4b21629487cc2f4c0
26376c3c1c425048ba9943fdcc4172e01920293a
34260 F20110217_AABKHE smith_j_Page_070.QC.jpg
487eff1bb09b5c6e520884b9ebbbb509
3d5a52cc6d360743ed853c98db13bcfc059fc577
95095 F20110217_AABKGQ smith_j_Page_063.jpg
d47372a6bb790c03c4cb7d385049f295
441a7b7deb92b95d8f1b7f11d8d2c7ab6309d32d
97934 F20110217_AABKHF smith_j_Page_071.jpg
5690bc2c3cc4653b6721b02de08fd3f6
0ba44783b46f8fdbd3651fd31c83331731a5f855
30348 F20110217_AABKGR smith_j_Page_063.QC.jpg
55771f1bb54257e998bbc49fb91b25ed
8bb2c17db3be84828a30b647a1e14b4d4f802b2a
32903 F20110217_AABKHG smith_j_Page_071.QC.jpg
52602ecad85d9af3ee4a0047cc50f16c
87b6aee5f0c6721fc11ba3350c5a144d17fcbed6
95950 F20110217_AABKGS smith_j_Page_064.jpg
305e24c216bfb50b99de1fa77b90c255
994d71f0f6cdcfbb1e1eaed8dc7ad58fba8f91c9
97094 F20110217_AABKHH smith_j_Page_072.jpg
ec136173e1c271de9e84879d0fc83e70
c5e7e752ea0f353dbffbb4aac0685995082dd0ad
31326 F20110217_AABKGT smith_j_Page_064.QC.jpg
bba89469d80cf52d951ba7f92d2489f9
10f120c4e3882a9f1468544ea1c8cf32a2f430d9
31074 F20110217_AABKHI smith_j_Page_072.QC.jpg
9e9e59858ba6a2978f166bc910f3d46c
dedc342a77234e170b37b85b5fd069012b798428
101479 F20110217_AABKGU smith_j_Page_065.jpg
6a46650f0baa2c584ecc432186311848
31bb49df6c2ae4176554a87342766a614a03a072
101119 F20110217_AABKHJ smith_j_Page_073.jpg
bc53a09a2781f58e5c829da0f88562fc
7faf1ecaf7a7da4fed193540a49bae5b9265b6db
33453 F20110217_AABKGV smith_j_Page_065.QC.jpg
3cbb29f4b6d028dc3e3ab8f7ec3986ed
8e94d94543ee41444c7a8b8afaba3304fb1b452b
31306 F20110217_AABKHK smith_j_Page_073.QC.jpg
e03d4af02c2bbbb5b0998757dc6573b8
c9a92694b5d576b85ffe0c859a70a30f9b4e6e21
104408 F20110217_AABKGW smith_j_Page_066.jpg
8621bd9f421a9fab11139360db92adf8
658e9145dd2603cf1e8899d28bd7bd9aa345eca5
34167 F20110217_AABKGX smith_j_Page_066.QC.jpg
8f38c076998053d86843ac0253ee5c1f
ece06569fec83f8cabbf1cf21f2b0a6c52979326
100783 F20110217_AABKIA smith_j_Page_082.jpg
3d86dc3798fa8a34eb9367ad50aab23f
e1633e63808b366a9ed2af952374ac1ce299d2a4
100776 F20110217_AABKHL smith_j_Page_074.jpg
4aa4f612d133613ea2f553db705e07b6
82a218a15c44836a2e470bf518ca70a03747a969
34186 F20110217_AABKGY smith_j_Page_067.QC.jpg
f1c72081c18c5469c6df86d7a3b20ba4
31f1b89392f5b6bf68d501ec5122aed9da1b736b
32585 F20110217_AABKIB smith_j_Page_082.QC.jpg
d32a062cd06457fb3a58080e750f3a62
a10349ce03adfa26e92ffc066233930eae302636
32057 F20110217_AABKHM smith_j_Page_074.QC.jpg
99dd28aa78b8d60382e55b4f7bcec2c2
cda204cd9a3307d7b879be35bb3cba1a27ce7b46
102989 F20110217_AABKGZ smith_j_Page_068.jpg
88dec122faf518787dddf533062ddbc5
6134cb8760d2eb3c9ff84f7ebd806d6458bd05b1
95821 F20110217_AABKIC smith_j_Page_083.jpg
fb305e93c8f5f5fb3390a8ba50e2287b
5126431e0a99f88386aee7f849fdb67b0aba2931
100533 F20110217_AABKHN smith_j_Page_075.jpg
b664dbdbca8170617aacfdb3eda142cf
73c58a7d0fbc18e37eceb02ab443a92e2be2feb2
31311 F20110217_AABKID smith_j_Page_083.QC.jpg
04113c6e855e4153b647fcaab74e989b
360af530aacfc580dd5cb127bff5447947947b79
32983 F20110217_AABKHO smith_j_Page_075.QC.jpg
211a1c65a1f19ef4085ce8ded48d3fd7
f0919e23efa5c0d7d5d35df51c5751581959b096
105189 F20110217_AABKIE smith_j_Page_084.jpg
5e57b67cfda4ec7d36623562e5a8b0b7
06aff7e8e8276e4ccbd221497a95aaede2349dce
100837 F20110217_AABKHP smith_j_Page_076.jpg
e8f8329613a9379f2e1c0b4731facfb7
b21e070aa2fd489097c9495ff1f31a0ab2d49d83
34676 F20110217_AABKIF smith_j_Page_084.QC.jpg
d56da87fcf6f51cb14306c5e3ef52e7c
c1520cfa31087460da5f29a23952fa6ef1d8577e
33763 F20110217_AABKHQ smith_j_Page_076.QC.jpg
de1de7a44caad954c2af6cb72241ae50
e69b797a724f117b78086c45f48a0e05f9616954
87690 F20110217_AABKIG smith_j_Page_085.jpg
7e642888f35394241171ff7760b858e3
ff39f0591c8e4f6faea892ae972bc878ac5778f3
103516 F20110217_AABKHR smith_j_Page_077.jpg
5b48d137922095fc55576d949fa18ca3
69e82845c6e9024b1505ddadea8a7f5099956884
28097 F20110217_AABKIH smith_j_Page_085.QC.jpg
525105de557f4eac885b22abae4376e4
3ea6763377b07aabd3d9d4093df4e74a5e4b7099
33532 F20110217_AABKHS smith_j_Page_077.QC.jpg
17c83c8bdbf76895166aaf1ab53fe9e0
028fe4c760b26ca65d09c164fbcae3d07111b153
75804 F20110217_AABKII smith_j_Page_086.jpg
4b407c25c8f99cf1330cba12d583c363
ac2bbc9757b3c5f8bf9830dcfb28aa1dc90f40be
100020 F20110217_AABKHT smith_j_Page_078.jpg
c78a27e54c273f612fa804cb46a3b4de
9a3a67759fb7781aa9df69cbb340448532cfe982
23116 F20110217_AABKIJ smith_j_Page_086.QC.jpg
cc1bbec3a8ee396196a2ed2707d9c594
0081986444111a006ed71b9363f09162cb45a6a3
97771 F20110217_AABKHU smith_j_Page_079.jpg
572cd8d45f09e3c1130599cf3eb93be1
ad4a291809b0984ea2aa635baa7e67b1567ba25f
51784 F20110217_AABKIK smith_j_Page_087.jpg
ff95b57993e98010219bdb6839d482b3
c3a6edf079a42954456c711e5245fa08d30cc46f
32509 F20110217_AABKHV smith_j_Page_079.QC.jpg
67a60ad7cc54dfb87b4b514760ab3966
49255c14c549c3152ec8283a9933b067d0468b6c
15528 F20110217_AABKIL smith_j_Page_087.QC.jpg
a8eaa4782774d9c3a9e518edef70969d
f8a1916b34f71632da7aff56935e964ba614e629
106621 F20110217_AABKHW smith_j_Page_080.jpg
877ff5c4d52aad5955184ed648b2f0b0
b4d07ce521d94b56cacb0fc88180dbbaa66bf741
96755 F20110217_AABKJA smith_j_Page_095.jpg
ef4245414b80485980cd51964e6e84e0
cc0411b73c59acbb03c184d1b4b66a077140ed24
34448 F20110217_AABKHX smith_j_Page_080.QC.jpg
06502837d9f9e3ebdb26145c0f5b8a97
3d5d78a3621fdbbbfb134c3e0177c55b0b9c9037
30895 F20110217_AABKJB smith_j_Page_095.QC.jpg
ea5eb28ebc09d33dac44702e82221111
c2693d645201cc22220fea46668aa29058cbd40f
54900 F20110217_AABKIM smith_j_Page_088.jpg
1e1fb9d9daa11b7bc328130a7a83e663
fb1e1cef0f2d789b7cf611479ed3d56cc0644c01
103285 F20110217_AABKHY smith_j_Page_081.jpg
7d9907de63750aa8d3b5dfd38e38cc11
19dc4d6236f5dfed4cc9dc28ba1ef6ff2c133510
103542 F20110217_AABKJC smith_j_Page_096.jpg
490b3b920fa49ca82e3232c63b52be2f
315df341015b236918ba61733097fad0750d5d29
16393 F20110217_AABKIN smith_j_Page_088.QC.jpg
2c9d9d2d4561f7e5733e0483cb3d207b
94b5e561212e4bdb62c6c52632d32afd374e98a5
34192 F20110217_AABKHZ smith_j_Page_081.QC.jpg
112ae206fa47db7cf7ca7db700fe3d21
b998298f0aa5916d6b2f362838a89c6e955a0244
33740 F20110217_AABKJD smith_j_Page_096.QC.jpg
90c73d22ad1ea2b565d275e640ff0d0c
e51ef67597c5903a9ab5a8069391e14117990a41
61348 F20110217_AABKIO smith_j_Page_089.jpg
860c09d53ad377d42042205420fa1af6
d93eb894572af7501799153b42012e8b29920830
97512 F20110217_AABKJE smith_j_Page_097.jpg
d40d7ce8d1b0f872f69f8015fbca54e9
e81041ec4266d09832b22a47a6421b086c32c91e
18936 F20110217_AABKIP smith_j_Page_089.QC.jpg
a1f125b69b944c82e9f1da9b9305ff35
d161f665bae59428db2be321b545095ca05e6174
31207 F20110217_AABKJF smith_j_Page_097.QC.jpg
30a5f409ca76d334017f9c860c883783
f86d91cdf35af08aca9b4382c7849337ba9147ee
53099 F20110217_AABKIQ smith_j_Page_090.jpg
da2fa4369e2989189fd153c919cf4fd5
14da3e81aa97e3ab90398622f359ef6573a46a74
103915 F20110217_AABKJG smith_j_Page_098.jpg
bd8afa1ecfff6bb4312491904f62acd0
d209df815582bf2e4acc199fe29ea8a73e2f52b2
16089 F20110217_AABKIR smith_j_Page_090.QC.jpg
3be023cda4ca69d46a102daceda376bc
676e95feecf0a5913ef8422e08aa583fe0d7e855
33185 F20110217_AABKJH smith_j_Page_098.QC.jpg
cd5ff36f88eba7ed283250425bb313e6
4e538780cd7ffb6a6ca83b0b6ff78a553d1e2c22
52583 F20110217_AABKIS smith_j_Page_091.jpg
16bafffe18c0ecdded4fa425d107f6ee
5fbc2b44fee28d1b205dabd8de662aadaabdc361
94685 F20110217_AABKJI smith_j_Page_099.jpg
867179d2d3bc3984be4fbdd893786e59
1fe1f6dff22dcd6d3640d81754598dede8b7c5f1
15082 F20110217_AABKIT smith_j_Page_091.QC.jpg
ff8842d41c7ffab36dd3eeb107e47d49
3427ba96cc8ee4e07f162edda34a0011728fdb02
31011 F20110217_AABKJJ smith_j_Page_099.QC.jpg
d245b316e6f0564e8a6d3b5288605160
7ea43949cc16d296934c5b59fe24d57c9ad4d995
59942 F20110217_AABKIU smith_j_Page_092.jpg
52bfc950dcafc0e5a188191847ec246b
1ffe827dc24bc069a4b5f09006fecc436c1a779c
96251 F20110217_AABKJK smith_j_Page_100.jpg
fc23db6a8531805ea7c1099afb1b6a8d
c60dca16786e818d7ffafc6305c659e54ae82061
18688 F20110217_AABKIV smith_j_Page_092.QC.jpg
2b8a60546ea8d0003f7da3993fd969da
5267f8e596e877d4e2b6eb989320517bd2914e43
31791 F20110217_AABKJL smith_j_Page_100.QC.jpg
dae61b088c47ffc34daddcdb85601b55
fa7afc175f2127a8d9134aae664b6d3d38b87b40
94169 F20110217_AABKIW smith_j_Page_093.jpg
c4ecad2bb1c3fd03cea7a767d95c5137
26c5aa89797bc0587e7663f69c9ba6a21f3623cd
103418 F20110217_AABKJM smith_j_Page_101.jpg
45fc6341b343eed3ffe915c9dcc4890a
35ad784852594799e7e135d7efbee3e70653310b
30608 F20110217_AABKIX smith_j_Page_093.QC.jpg
2d50cf5311208c5053660e6c1dda93a6
b868ce857c4db9e3bab0c0f012fb5e8ed7d6b6fc
34023 F20110217_AABKKA smith_j_Page_108.QC.jpg
4ddde355ec15913b1c93e36535caa362
2180a2eedbecfd14e6f57adc4b8a8a944fe929a3
102217 F20110217_AABKIY smith_j_Page_094.jpg
7a52a5e7c89c3c897b03a784f6263eb5
3447c10f933d55cd3a521a233465fc59a61efec9
102560 F20110217_AABKKB smith_j_Page_109.jpg
c82f7fdba455ce5eaac8f047c43e6f50
a1e3e6ce6630ce130cecbb604a9b1e6c59fa7fc6
32928 F20110217_AABKIZ smith_j_Page_094.QC.jpg
8d7822c1c1001424fc836a2f03dc9a47
b94a71dd029cf71b65d7bdeb4f9b7f2730d58037
33166 F20110217_AABKKC smith_j_Page_109.QC.jpg
a78b33ca2ed59ce919bfae889bd1a4bf
eeb5c6d7f5dd51a3b9140ae70553ac579d662435
33994 F20110217_AABKJN smith_j_Page_101.QC.jpg
8d02d440a979f9e1fb8c76e6662040a0
db6387e347c1e6615ee974bc519e66ed93d86de2
108635 F20110217_AABKKD smith_j_Page_110.jpg
4d74845135e6e2efcb57807d6de9c973
77bd22e2e969900da2786f5e6f4ff980309c6347
95332 F20110217_AABKJO smith_j_Page_102.jpg
dd0ac055e63a6c0daa7032281444b5ac
3f0c34e6172903df6192f8d91eb555e7b80ded24
35758 F20110217_AABKKE smith_j_Page_110.QC.jpg
448e0a7fc0a4a54307ecc02cbbf8438e
97594048cd647318e8a23f0dd21dc089c0e96fd2
31062 F20110217_AABKJP smith_j_Page_102.QC.jpg
5eb46f54de90daf469e4bed7494e9b73
5f6af97ced04abb393bc74a80d5504e05601d398
47581 F20110217_AABKKF smith_j_Page_111.jpg
16af70b239f7e12b28944a0a67e85fb2
e1c2816e6ffb71e52771f7fd463413bae8b49d49
102949 F20110217_AABKJQ smith_j_Page_103.jpg
42555548a8e14539e2cee0f560cc4023
79f54fff41791534108edb0b45a312ce80f8c104
15408 F20110217_AABKKG smith_j_Page_111.QC.jpg
ae0f477fc9a11ded3864085113acdf3d
bde03f15185120e9aa16c407cb818b1722a27814
32861 F20110217_AABKJR smith_j_Page_103.QC.jpg
009a178d87fa9a25aae6cdfa335814cc
7d8bc8228b2c1701ac99be724ed48d1b9415b781
52503 F20110217_AABKKH smith_j_Page_112.jpg
ecdced9a40d7cd0e5d24888a57277af7
5de037d501690d65ffa4ca924fe4fa6db32e909b
99281 F20110217_AABKJS smith_j_Page_104.jpg
b6f367f9d4630b3718904a6831a4ec26
b0775063a2685bd07eae86a0aa2f3275761f6c50
15147 F20110217_AABKKI smith_j_Page_112.QC.jpg
20e0dfeb2cdce443d9364dcd85a61723
e0d56e4746ade9ad1960fc2c51981aa23488cde3
104609 F20110217_AABKJT smith_j_Page_105.jpg
cc2b3a4567f402f4669dd0dec75cf358
68ca7369d9bc1393d586f90eb250e0942d826d51
33066 F20110217_AABKKJ smith_j_Page_113.jpg
6b5015e918ddc3fc47cfdc21662c165f
8961210396e0ddb6b0a5690997ff0db68384fd94
34328 F20110217_AABKJU smith_j_Page_105.QC.jpg
4df58de2b4b351022ce6d58a5fdbfd3a
330e6a7147f9906b050d2e58686ee86e8e173d84
10711 F20110217_AABKKK smith_j_Page_113.QC.jpg
7087ed8d249f6db880fbfbd2a24765ca
b380bab4de84fe0cdb790827771c62ebf9cb1036
102256 F20110217_AABKJV smith_j_Page_106.jpg
61ada72fdd7b7463357f34f856f828f9
8f5159159a88ec3ff08a4441a57ef33adfb66fe9
32127 F20110217_AABKKL smith_j_Page_114.jpg
add658de65e32753f2e9578c99738a67
888a21b7a65197765f0d245043c45bb6b1b9e266
33148 F20110217_AABKJW smith_j_Page_106.QC.jpg
014dd3bedd3711f413719d81968d00f3
6d9b41f5131ef6f0dc0821eefaee770792dd5cbe
50172 F20110217_AABKLA smith_j_Page_122.jpg
ebb8c127a646108f12849690c7480cc9
7251e3c2db222071a3581780702f24354859bc23
9559 F20110217_AABKKM smith_j_Page_114.QC.jpg
0e11120aa90e1013e5549c62e7e22b5a
7774e81a75c81d2da54099033451ba16fd5ba482
102005 F20110217_AABKJX smith_j_Page_107.jpg
7008a0f5b43aa19b7bdcecd23b3d90a3
7cfd1452474f226a93fb0587a9d105ea989bc63c
16409 F20110217_AABKLB smith_j_Page_122.QC.jpg
8249ddf91f5d9eac00ed4eef61f2b16a
b2cd2448839c3874e3b258f56928919e99443928
50106 F20110217_AABKKN smith_j_Page_115.jpg
48216904d6c9288a9415a144bad2f810
8b7ac46bfb0b3ef17140eb555e7b48c944c7c483
33433 F20110217_AABKJY smith_j_Page_107.QC.jpg
881185a9d0511a81a44e284b5195af49
951840568eb32b1fa825ed9d24d96740e8622bdb
59702 F20110217_AABKLC smith_j_Page_123.jpg
96a62bf1e3172609754db299c0bb6ee1
9ceddc55ef3afdfac014dd763e487f5e3c110e78
105056 F20110217_AABKJZ smith_j_Page_108.jpg
3c3cba706311971a1860c1f8f3b5a996
a02e143906c1fb91c2c4a00403f82075f04c65f6
18180 F20110217_AABKLD smith_j_Page_123.QC.jpg
d5001322cb5ff0b0d261f60a89821211
172a38b3dc1fa25ba399d5d90fd22df755a25bf2
16001 F20110217_AABKKO smith_j_Page_115.QC.jpg
934f6aea2e494dc136e28681b4eae670
1c2c3ceb0103471d02f3c392adc1d360d1661529
9190 F20110217_AABKLE smith_j_Page_124.QC.jpg
c8eca4e913e8b2cafbbe482bd370b6eb
8339a45be379b0c59cec2b6abc333b38289cb7e4
44125 F20110217_AABKKP smith_j_Page_116.jpg
fc93722b816d8c5dfeff5e869b5294ef
42d424405201d02b5e279adfe6f0896a0f695af8
11240 F20110217_AABKLF smith_j_Page_125.QC.jpg
af951cdba914f1d589ea0abd12731a51
38ac793cfd3e458a5d29fc080ba8eed2b6e980e7
14016 F20110217_AABKKQ smith_j_Page_116.QC.jpg
2887a98905bbfd87ba34b2c30503afd6
13e397665e3cb7bbaddc54b8448bbc00a4295382
43751 F20110217_AABKLG smith_j_Page_126.jpg
bcc9c386d9efc0dd8408e5169e73d879
33d5a944d74c9ee1f046ff554ab0562a249ab53c
57799 F20110217_AABKKR smith_j_Page_117.jpg
3a80eeea8ec097ae06271b7cdbd7dbd7
04678fbf347e0ca075614344d4c22270f2c02cf7
15391 F20110217_AABKLH smith_j_Page_126.QC.jpg
994f5b17a1ff4203e73c8464d6475ce9
1592152de591b7aba5b2aa8e61f6252a15fa0800
19465 F20110217_AABKKS smith_j_Page_117.QC.jpg
fd676410ce24c922992f494011740afc
0e6f161f705ab0f5b825ddb5afcec238d80c168c
55692 F20110217_AABKLI smith_j_Page_127.jpg
be1e51f5e1072816789afc2b2cc1d605
6fd370d60beb291426dc96d1f1b87dd0da42aa0f
92747 F20110217_AABKKT smith_j_Page_118.jpg
a36c54cb35c5fe53af2cd85478a684a9
88fbefd4879bfa4760e40104dc434ade3d0f725a
18702 F20110217_AABKLJ smith_j_Page_127.QC.jpg
60f5deaf3c7647b6ba8479d7a8207481
2314bf5bc58a9bb9c05cf0efa4cba7efc1fa88c5
29448 F20110217_AABKKU smith_j_Page_118.QC.jpg
66c27e8e9a8c005e9ea1f4ef511c109d
fbe936dd0f007f618d9c0aab4dd963fccf52e18d
28711 F20110217_AABKLK smith_j_Page_128.QC.jpg
0ca3ca8ebfc3d000c8f45c275353e2ee
06787f7b19e4651ed2729bd84d9f9707d1b91637
101864 F20110217_AABKKV smith_j_Page_119.jpg
44d86dbc46649597da005301a11fa8a1
9b07026a6cb13153d7f6dd5c89b2538b94d1e17c
128770 F20110217_AABKLL smith_j_Page_129.jpg
795be4e3aa2ab91b80b4c3d2166eed87
193aa243f71a6e0e061c1da389fe6cd1b0adf8e8
32420 F20110217_AABKKW smith_j_Page_119.QC.jpg
a1ceb2dad6b2f71f007b366feaae3d73
dd4610e50970c504da3615377f849971a9ccb45d
122099 F20110217_AABKLM smith_j_Page_130.jpg
d5bd3d4199f4be8fbefbc6b8e28652cc
8fd54686be9e8c57fab7cc0fa6f90cd6e0a8d985
101794 F20110217_AABKKX smith_j_Page_120.jpg
53953721294aef870905bb5548a6bdfa
caf7a689cdcf79b235b01d88e7a7f0e8644531e7
122400 F20110217_AABKMA smith_j_Page_138.jpg
ec8e7341e108c7e6b56feaa5120c3334
5d6ef6541e404878c9a19c2d4fab603ea9613cab
34133 F20110217_AABKLN smith_j_Page_130.QC.jpg
e7966f2de2de9e332e83d7496d50fa66
0f8c33b93699972335b9fc66850c0e08f377bdd1
32906 F20110217_AABKKY smith_j_Page_120.QC.jpg
f9462dcafb6261fe443f52319ce1afdc
04fca2057e0f1a81aae914488d05fa4b199bbdbb
34424 F20110217_AABKMB smith_j_Page_138.QC.jpg
e713c7bb0866818cf59cef13df461b0c
21ec8025f34de40c5fa0240f9ac352b35821d852
119895 F20110217_AABKLO smith_j_Page_131.jpg
1ff2bfe34675fb31d13d51e86721e1ae
8c986d67d2edd0907e3f2974dea9741c56a75a16
31989 F20110217_AABKKZ smith_j_Page_121.QC.jpg
0a55ed1aa18b220ea722afed0401fb92
1386e28c6518aa628dfb038ee03d17f9248c0db5
128671 F20110217_AABKMC smith_j_Page_139.jpg
6905474a7a239ddb3ee5f8826cb2d39a
68a702a626ba058a60c38fa1d0bcef0f80bb157e
35391 F20110217_AABKMD smith_j_Page_139.QC.jpg
d76a7835bf6153d26c1cc3d13a228123
0f47357c0d33dd267e0bf2294e4ea6466c851c2c
34239 F20110217_AABKLP smith_j_Page_131.QC.jpg
c78576c506a91f18e1d9d9f0a5553b45
e086f503b319358db9ae563f20fa40599a89f5ba
125397 F20110217_AABKME smith_j_Page_140.jpg
675401129310919a5bc098e9c5cc6ff6
a9829dce62eb75cee3b203e6358e853bdf9a3606
142069 F20110217_AABKLQ smith_j_Page_132.jpg
bc1799de92616b9ddfe4a54c7efb03a3
006791133cf95c14cff729d6ba7ef79e621a73b6
34978 F20110217_AABKMF smith_j_Page_140.QC.jpg
407e5605c1b54f77acad3b01e9647ca2
1b85655c95173912131962494f64877c90e9acb6
38501 F20110217_AABKLR smith_j_Page_132.QC.jpg
9668d4689749e617d62f29c2be55bc48
53f9f47224207f34e3dd71c75583549e55bd8835
133608 F20110217_AABKMG smith_j_Page_141.jpg
fe9aa4a2adc9526acd7c59ff0fcabd15
74f3eaac0123290460e9cb3e4578443d75664511
121416 F20110217_AABKLS smith_j_Page_133.jpg
d686a699692659f059fac89ef41b6794
e00f4cb29a27f1891b1f73f2833eb8c861aa3416
37337 F20110217_AABKMH smith_j_Page_141.QC.jpg
dd73932c2329b461802484753b6dfa6b
7959be02be54e9b098fdc83bd9725efeae173959
33832 F20110217_AABKLT smith_j_Page_133.QC.jpg
148cf311f1dbab358a5f25fad6963836
1918806a1128e215844c738d2e91227c5c939793
124843 F20110217_AABKMI smith_j_Page_142.jpg
cd3732378edede5e946ef9d7b0d6ffb8
6455c15b64f6a844fc2702781e102de75c2515f8
129766 F20110217_AABKLU smith_j_Page_134.jpg
a80b5414397b5304a959270229817ca5
4416bcb0d616772418af612e1e13b733f9ab4cf2
34561 F20110217_AABKMJ smith_j_Page_142.QC.jpg
8f27eee1fb2e277b7813db958826540c
72c746e753b12859be08e8e58a872f5ff0fba595
125796 F20110217_AABKLV smith_j_Page_135.jpg
58ced5c3f0827051210b9b50755480a9
6812931fd8cad7007724585dc15f56b4c5abd66b
125302 F20110217_AABKMK smith_j_Page_143.jpg
2a95bee65060d5f3340fab6a121ee6d7
c2307a36dfed67660534075500e914519e4db1e9
35578 F20110217_AABKLW smith_j_Page_135.QC.jpg
0a304f6c0c030098f7e845524f15ca8c
7749fe2df08494ecd849799eee369ee96667d2d1
34870 F20110217_AABKML smith_j_Page_143.QC.jpg
64c51e794ad5de842116f824bc803586
f72c9c5efb6ed3cd239686ef416299ade424d6ab
127336 F20110217_AABKLX smith_j_Page_136.jpg
515aea24ac272ec1f093304fadc2be1d
092e9709422b874941a05d2e42a908a7996a6431
1028550 F20110217_AABKNA smith_j_Page_014.jp2
122d68467a7d70201be655fb4c37586e
6a8acb2d81284c077b48f85735b8adae7c195cd8
86080 F20110217_AABKMM smith_j_Page_144.jpg
d27f7266ab12617144492acf8593bd40
d26bf6f5f5fbf1e45fd4b2b87d895b3db06a1016
35933 F20110217_AABKLY smith_j_Page_136.QC.jpg
d6e2855461b72aab43c9e3b616e397e7
0ff651d549d949108bbe8b1939f28fb3f428592f
985302 F20110217_AABKNB smith_j_Page_015.jp2
0cf10e31ecd43e7b1cabd0682354fb2c
4d3c9116fead351e23c98cb9382d579177031052
28763 F20110217_AABKMN smith_j_Page_144.QC.jpg
89c429d490468a2790885277c83107cc
034bfd454177dfe4bd703003401caab83fd339c5
129418 F20110217_AABKLZ smith_j_Page_137.jpg
b761167fab3aa4a85e80dfa832535e0b
d19ab801512a4b4238360ecc9f0ec36e25febd0d
F20110217_AABJKA smith_j_Page_013.tif
a050640341984f4af7e2e57d0406a4e3
aff2f37688900205596ddb06ce381413a93ec84b
1051978 F20110217_AABKNC smith_j_Page_016.jp2
a38a533d9b4b18fd5b6c653665847624
ca8eeab9ba322a6e67f958de85c79b02064394a5
276396 F20110217_AABKMO smith_j_Page_001.jp2
5680d48676a96a0b1c62726557ce24f1
245792de2f62ff1b938343543bbd4d7ee35ea94c
7616 F20110217_AABJKB smith_j_Page_032thm.jpg
ee766d4d8f3023154a75490f1ff24d6b
b5fd9c27ed1771d290c462b7994b7bce0f95b7d5
1051918 F20110217_AABKND smith_j_Page_017.jp2
09945120c0e3463bd14fec933c8a7ba4
e7a17d5f4d4677ceb38ce7b96181e4749bcaa3b9
26418 F20110217_AABKMP smith_j_Page_002.jp2
e38bcc6a01e37b80faafc42ef47d630b
3bc6dbc72d7186faee6d230def33d0f72ec1d6d6
44170 F20110217_AABJKC smith_j_Page_099.pro
217d28d2cbf9e33b9c1faea6bd15b9f8
6c391805ccff786aad606d1fed4a0fa6264d2c77
1051969 F20110217_AABKNE smith_j_Page_018.jp2
06ef161cd78040f385475ee1c04cb321
2fb48c21a3ac89535dd6aecba52541f3b40ff61a
50406 F20110217_AABJKD smith_j_Page_042.pro
0e5365305e655531cbffb7b78070b10b
d068b0968447c9d5fd9061032898b463e52d2bcd
1051921 F20110217_AABKNF smith_j_Page_019.jp2
9366a6eb84df5a3fe483a5bf52b7b4c9
3c5a7c50f084a199dd6bc0025302e4c567e11acf
12759 F20110217_AABKMQ smith_j_Page_003.jp2
07ec6128107d2503283f495fb5450f40
1535f864d0ae9df8646f1b272f07314c5cf241de
50873 F20110217_AABJKE smith_j_Page_053.pro
f920ccb0b9fed538c735b167514a575f
b217a7c2f4b785306f81da98af7a8311d2284cd2
1051982 F20110217_AABKNG smith_j_Page_020.jp2
aaf32b070942bcc7ee4ec5f0297cd2c8
66ca8e0ae9fa4fb99b7d859ddde4fb2b14626365
870811 F20110217_AABKMR smith_j_Page_005.jp2
66243d8f8548ba06121c1b878b0f5013
b8f3a8c9be31d6435a54423f98efb73baf1f8b16
1051935 F20110217_AABJKF smith_j_Page_022.jp2
d8e76f841ae93a59fb7674f4961b1263
cf94c4c0b2ed878da7a339e2c56c3d599fe4119c
1051986 F20110217_AABKNH smith_j_Page_021.jp2
bd342c574df217fb27b634892aaa9370
5b3678101cc2edccc17c6f3be17ddaaed4612df0
879291 F20110217_AABKMS smith_j_Page_006.jp2
2eb44304bab30495a1734d8d6e6530e1
11bfa339e0b5f5f339beffa136f311a529b40b62
F20110217_AABJKG smith_j_Page_132.tif
0b47ec66cc4009bac720d60e617ad202
b668bad00646651f3933625f204f40d4636a9906
1051930 F20110217_AABKNI smith_j_Page_023.jp2
85ff37e61afbaea759f50d2c55acff86
22925ad28b339e20e4b3129227ba05fda83bc88b
1051961 F20110217_AABKMT smith_j_Page_007.jp2
666bb7dd2643823f26a2300df52ebaeb
ca0f2eeab153d530626a3b331f339617ec1354af
F20110217_AABJKH smith_j_Page_137.tif
fd5dd68c72e810527abd45e199926032
25326e481905d27c4a51ce54d7abb4c8e9ea5e97
1051985 F20110217_AABKNJ smith_j_Page_024.jp2
30ac9c512aef5bc0be120b8a43e3de64
97bb8d54bfa5e1871ff82d2a636334a073cab64c
162224 F20110217_AABKMU smith_j_Page_008.jp2
b600aaa1a5c799179e435246c9648073
3c671d3f997856ce5f650c117fdb5b2270851f42
32373 F20110217_AABJKI smith_j_Page_078.QC.jpg
09df0deb952993b3cab4fe95392ca933
119829ad2b677c398ae0a888d80226a15388def1
F20110217_AABKNK smith_j_Page_025.jp2
7fd3944a18aba461d73e732b5bf99dbf
3c3b04f2f010d9a16f569e8b3c15cd207993ef3e
875747 F20110217_AABKMV smith_j_Page_009.jp2
5d899438454e0fa1d6bec7a19760a23f
0c8fee9a9421cc4bbc2e4db59cbec7057b36659f
1922 F20110217_AABJKJ smith_j_Page_104.txt
612082e5096bcd18cf6713bd6e6b595b
e160366c6e1c67ffe331ac06f2d23d5b33333baf
1030701 F20110217_AABKNL smith_j_Page_026.jp2
7227f3334654ee4e05474805cba628fa
88d2194743925c2830301b3f59761205d5dae412
186793 F20110217_AABKMW smith_j_Page_010.jp2
1a7392487c6cbf294974cc56f43c2f7a
af1a10129f019171e886cb9fee7e1554ca49323e
970505 F20110217_AABKOA smith_j_Page_041.jp2
5b4fa81a3c8e9c7fe2aad69eb03e501b
0b9c3e71fe59c4c5e7ca95896cec0528018ca530
19786 F20110217_AABJKK smith_j_Page_059.QC.jpg
1379bbb5f776bfeaf4e812c7e6ec05ef
a6af34d6290cc134b2670a723ea169bba5eff5b4
1051960 F20110217_AABKNM smith_j_Page_027.jp2
79ec992713ab2b8e3e088e4b2d2d6611
5009004a4b1ffe5c1911fe551de9a8c98747a275
902336 F20110217_AABKMX smith_j_Page_011.jp2
b3ec7c5f85d7012b5e1f32989aa84c64
25e7c9b8bb9740cceb7e5d5ede345013826f7b09
1051955 F20110217_AABKOB smith_j_Page_042.jp2
0d29ffc6b39cac314bcc0db778e2a961
9157bfdbd0d8e0470d1d904f833f8ef43c595b12
35400 F20110217_AABJKL smith_j_Page_129.QC.jpg
ec03cfac82eefcb1d686a1e0dd9e42a7
2dbc72544b22285d1bea5b368432c646ffd70dba
1051964 F20110217_AABKNN smith_j_Page_028.jp2
f532ebef7fda2363559d76b349a2be41
c00cc7dfbf4f0436abb9869efd9c622489d8d6cf
1997 F20110217_AABJJW smith_j_Page_109.txt
133fa462e3805c0eef0d6fc0dd5c7108
0256114bde0b5f193b49ab424aa62de7f03c1043
72139 F20110217_AABKMY smith_j_Page_012.jp2
511571743e967991e80759ddf4ae7afe
fdd685485ed8b273a28ef0da9ff0ec46bf2bcbff
1051971 F20110217_AABKOC smith_j_Page_043.jp2
d3a6a9a3dfd1a2ac9b5ec1ab14275983
e5de3012429eb2db10a50e97e896763128344cbd
F20110217_AABJKM smith_j_Page_032.tif
2c57f2902776269cf8597d8637c7e3f4
abd3494a0c1de9c1627cadf82377d7ea9b8fe031
1018336 F20110217_AABKNO smith_j_Page_029.jp2
692bc2ab2a4bfdebc78575cd085100b8
55ebf7c0b69d1f512e5cc7bc275c8604eb03d65c
F20110217_AABJJX smith_j_Page_014.tif
4045f151354c3910112720d6339a66bb
732fc02a182c0490aaf3cd3b27be6ae5a0867778
930121 F20110217_AABKMZ smith_j_Page_013.jp2
34e61944e1029ca6c224f51fa2dc22b9
ff60090ca45967b5d4ed0fc824e2b675c715f05f
8147 F20110217_AABJLA smith_j_Page_046thm.jpg
3e505463ea81d4615baa5307309efb2e
b6899e3a350a8f3f9d2e13916a53a6d6a321a02f
1051967 F20110217_AABKOD smith_j_Page_044.jp2
f59613c8fc900c50c19c9bf2bcd972b9
10ce8d950c3ebc14937c297093ca9a84aecabce7
8234 F20110217_AABJKN smith_j_Page_019thm.jpg
a115724308ecd3fa5f8c29aaa5c79afc
e8e1bf8b4e4e66d1ca991e8e9923331d06e13dea
1051983 F20110217_AABKNP smith_j_Page_030.jp2
0d3ad28bddd7856e0f0e18f357dbaafe
2e76e4e7a8909499aaeea47a25139d19e9864d6e
50957 F20110217_AABJJY smith_j_Page_128.pro
4b7ea1cc7563a43761957f78d145f8dd
9528694e246685510ba20f3d4d0597fde570c86a
208 F20110217_AABJLB smith_j_Page_012.txt
68b893ef3d5229cd1bbe934c723aee86
67125702f99017ce3e2ec6b400cd92c658896119
1029325 F20110217_AABKOE smith_j_Page_045.jp2
05e246aeefda7c9bb08c5a692d2381a6
670419364338f524139fbbe9b7e647cdea40acda
F20110217_AABJKO smith_j_Page_096.txt
6b68a124e13f7252178a18c02efafb20
d48678a9fe59bb5a98b86c00d8650a56ff9d1b86
1051945 F20110217_AABKNQ smith_j_Page_031.jp2
697bb3964e8fb2c8e5ecb594e3925096
6de6b3bb68ad4440f0d634dc3bb8693cdcf1a16f
8768 F20110217_AABJJZ smith_j_Page_134thm.jpg
0b7e331636ae2c7ebfd98495f2606f68
8964f451ecd2d92603307cfb92cbf5c344e11401
7971 F20110217_AABJLC smith_j_Page_045thm.jpg
b49ceb74bd2e811ead5307522d0983f7
652640b6f899c1fc4d55086d63a73f7411a1f01c
1051959 F20110217_AABKOF smith_j_Page_046.jp2
b0a914060eaf1dff007151688264d66e
0b3fd89799c2eef5dcab289820ac282ccb0e752c
1847 F20110217_AABJLD smith_j_Page_015.txt
d60355d2bcd2a6d77f09e53dd745c906
41cb86cdbac57db0743529e0064605d948f63a07
1014311 F20110217_AABKOG smith_j_Page_047.jp2
e6dd88d69f834d36100524f11802f51d
3c3fba1840e0516b94514d7994a22b7c6bf0da94
1051947 F20110217_AABJKP smith_j_Page_068.jp2
4e6ec9117e44140167efc0affe0b81ca
174bdf0d6981c0623d71583db3060a236559d415
1038274 F20110217_AABKNR smith_j_Page_032.jp2
450d32dcc72b173d61dc4cf747e12c96
4e7d4d2b720881fc1c2472d0b3eeb986efc4462a
F20110217_AABJLE smith_j_Page_077.tif
e57ad50d13953c2785a4fff36c0cb81e
b379f8ce77351d727c223dcd4feb91e5f96f750c
F20110217_AABKOH smith_j_Page_048.jp2
a63522f0e61e2a53f6f08b6ec2a13821
8e76ef2268dd097e8253a88864ce2d3cf70ca856
F20110217_AABJKQ smith_j_Page_108.tif
5469bde60cc98677497ef25c5b3a9fda
6965a0e6db28d8aecd22e78600ebd72149e899b1
F20110217_AABKNS smith_j_Page_033.jp2
d8ea8d31f0932f168b79365b74651233
3404b82c6a9cacb167608700d39db031fd7398bb
8301 F20110217_AABJLF smith_j_Page_083thm.jpg
b324d89f3ce357392afa649da1c31faf
7a67891e91a991432ddc2d7eff24d12620c8aff1
F20110217_AABKOI smith_j_Page_049.jp2
20d8ebdaff1bd9f80875941a82536f4c
52007451c4e83c7df7d31a3581e1c631bccd075e
23752 F20110217_AABJKR smith_j_Page_116.pro
32f9fc6bb94b6d73b1ec7193b5b6b6f0
0822ccd4ba1692291bee99fa50e5eafa117cc837
863518 F20110217_AABKNT smith_j_Page_034.jp2
43d129b9d283b616e59a7da7b56ef89a
48df3026e31b684d58e65f59f90874b73b1c7eda
1021925 F20110217_AABJLG smith_j_Page_063.jp2
dcb5e6c5e35dafc68e52986ca43d6f45
75972fe7c99cbd8a8eb0eb2664dee74d0e5066f6
F20110217_AABKOJ smith_j_Page_050.jp2
2a9fe7502e2f5a82d6e22c03c3dfba2c
ee13f74d8de44905bab241ec1ba55ef89d1dec7c
19091 F20110217_AABJKS smith_j_Page_058.QC.jpg
1c48ae45468966dd42578a5ca5b988cb
198b86631017ea850e6599dd8072c79a960adddd
221277 F20110217_AABKNU smith_j_Page_035.jp2
43275ecdb87942d1cac177ba153bce23
2efcd659c53c4a930fa29c71449cbd30d05148ac
4220 F20110217_AABJLH smith_j_Page_116thm.jpg
158d64c62249a4423b859049df10d20b
276eea8210ca61d30599242c826507af6995e6ae
F20110217_AABKOK smith_j_Page_051.jp2
3ee319a167ef6fbcc44a03d4fe273ee0
36f6b41adefce211161cd6defcad9f6fe1d010eb
48177 F20110217_AABJKT smith_j_Page_067.pro
b2e24f1c875f91a04d0ccd77641db8c3
5deda9f161abadf9be902936017b227e5a904cca
391897 F20110217_AABKNV smith_j_Page_036.jp2
c755da3eb48644fcf6e27665f8160618
236e4da8aba3a5fed982384b97846aaa4f981163
1851 F20110217_AABJLI smith_j_Page_063.txt
fbb1c772b2cef0888a64423325efee9c
0cf5877ab4313e53967185fdddd4ef88acc4a5cd
1051984 F20110217_AABKOL smith_j_Page_052.jp2
3ebd687011acd0a2bb45bbe2f8ac94da
f245ae1fce67e5f92e9cc3cb9766406527dea167
107779 F20110217_AABJKU smith_j_Page_017.jpg
4b34a47e07907b44b4c75df0ba1f3c85
23b74d931a4b450cc7b2d54eac95e0e87802f381
376085 F20110217_AABKNW smith_j_Page_037.jp2
2d23844ac93ccb426de738e63b63286d
9f2213f6a79daba557a5816447a759c92499d0b4
8249 F20110217_AABJLJ smith_j_Page_001.QC.jpg
16d063c1bf37c5b045065dace620bafd
26894fdf0517d2c97065fa66e6e808a209fed927
1051976 F20110217_AABKPA smith_j_Page_070.jp2
a8aa7ae5cce127f01c1da7854af249ce
727dbd1eb36c5ddb27bc344c07ef878a52b9bf16
1051972 F20110217_AABKOM smith_j_Page_053.jp2
da397e2c3084b516295a38962de7e008
de46a3af8b138d3208bfa11c4f522f664b0cd243
F20110217_AABJKV smith_j_Page_101.tif
5e11f8a98dc6980859bd1ed0c75e7faa
e7a176a314faef241f8b95e947f6bcc7b6553755
1051895 F20110217_AABKNX smith_j_Page_038.jp2
ac589e452180e7fcf1a84fbfe6827113
fa485cce24de6e4072d26933d0805f15dd6a5211
F20110217_AABJLK smith_j_Page_023.txt
a123d6479ad7ef2b7fe32d1445b685b2
4035e93fed2c6d84694f7980de284358047e1266
1051936 F20110217_AABKPB smith_j_Page_071.jp2
662f9b521a35144f0ba7593cc4159203
128729995b5dc849a9f664ba6d7227a937362de6
1051909 F20110217_AABKON smith_j_Page_054.jp2
7cf737d1d4ec9beb4c56c0484a32d53e
9891cda9ac74be7d2bc83de2c71f6c6bc58e89dc
8043 F20110217_AABJKW smith_j_Page_044thm.jpg
6ed1d141a7ec3ae953c9268e16f6ac4a
c6ad0aa6db0cd15bf5ca4a4b8d861c2861e4b54d
409812 F20110217_AABKNY smith_j_Page_039.jp2
2abd30b1f660b06e484bab14b731190f
7597fcaefce1fe94837ab2b4b4378d4d71276497
8094 F20110217_AABJLL smith_j_Page_024thm.jpg
8229ad43afbdb0e27905d9f8c8878042
93a6bf224cc432d4ddaa3b9ea3c03f68b6f8258b
F20110217_AABKPC smith_j_Page_072.jp2
947fbd41a4d23141cae46157b6bab0de
f5416cb96fb9022b43c134938a764830fb1e8cd2
925596 F20110217_AABKOO smith_j_Page_055.jp2
91956d0b1b552881b1fd0f89cf293d91
7f0c30deb29cc633ffa1204256de1ac6a2404ecf
F20110217_AABJKX smith_j_Page_089.tif
14df75c9b3d8a88456a33fc686fd1ca8
fe0fe60f9d01ea6b8a4ef04709646d3f6fa6e2dd
529319 F20110217_AABKNZ smith_j_Page_040.jp2
9248aba812e62146372bebe45e293c6d
fd6763a903f721016f24aef8477321c3ea7f8fc6
19330 F20110217_AABJMA smith_j_Page_039.pro
a63fd5e1a3cc76fa13858aa22ef212b9
797563ae0c1a80f1d419275a47199503a7bc9805
2454 F20110217_AABJLM smith_j_Page_143.txt
244791e580359d8e2483c1ba00ebd6a3
3ae446cf5a0df5d93a20589e519d969a098dce82
F20110217_AABKPD smith_j_Page_073.jp2
81b61c18703b8872cbea9df2e1ddceea
d9f2badf0206c83080fd285478a2b0a1183ddbb2
824668 F20110217_AABKOP smith_j_Page_056.jp2
4656d1d3c14441811e9a9b71f67499b4
23e40fe30251ef3dab548f7ff977d10d2a721892
95255 F20110217_AABJKY smith_j_Page_128.jpg
15bd64a3bc995f97676f1c1ec5e6f349
938c6ec6f63221190cfb45c92f5ab9feb45bf5ff
1900 F20110217_AABJMB smith_j_Page_021.txt
07bc331a067c37cd4a2be4b4351b58bb
c82d02ddeb45b7375519b2840d42e84aa2fcc443
101293 F20110217_AABJLN smith_j_Page_121.jpg
7c2a073e45851744ce212c9641700bc0
fd574c5c585b842d75c50fb6a6e1027cef9ad3f2
F20110217_AABKPE smith_j_Page_074.jp2
ab06be76c7706c362c60b718edbe9e29
ca38506896d096dc75ded2db259198ced77156b4
802708 F20110217_AABKOQ smith_j_Page_057.jp2
7ba12a5688d010f0da82f3ec1d3a490f
6cc56be6935b69e3e6b464b07664b32633fb7486
50734 F20110217_AABJKZ smith_j_Page_027.pro
903dff3db2ba5fb7ec650f67d79b77de
f920a58e5c8c348c725c78e8cb3aa2f5cecfad2b
11737 F20110217_AABJMC smith_j_Page_061.QC.jpg
6f5fea93f278a8adb6206ceb418c623e
f23652d8a7b5111388b28883389ee47ab1a9b0bf
26458 F20110217_AABJLO smith_j_Page_013.QC.jpg
24fb44cfde8536343c80b7f125f7433d
0bdbb8be0f2943aab40a434cd10cba033d738cac
F20110217_AABKPF smith_j_Page_075.jp2
7029b15bbb01e9b6ec8b279e2c5dea3d
058289c9183424a1535a1f1ce28e222502a7ff5f
638073 F20110217_AABKOR smith_j_Page_058.jp2
387147fd66d339d1a4b968125c0542a8
497838cf72712c3d05e33d54ddba4b66295ca7b5
7485 F20110217_AABJMD smith_j_Page_118thm.jpg
a02e3ef59beb3b5b57a566c518446bff
dab40386f2a30a86c2fbb6ece7ad16ba2dacd3e3
8664 F20110217_AABJLP smith_j_Page_105thm.jpg
4e900f09fff5f49066010823e141a6a6
cb118ab50b32ae6a34cead0c7d6e92d9050a4062
F20110217_AABKPG smith_j_Page_076.jp2
13209e35c0de0bd57518f283eb7b53fe
cabc28282a2446f18706d6bb409a1801bac6a02c
F20110217_AABJME smith_j_Page_025.tif
3acd10bc70087234b8cd49cff461f64b
94f3f8d78864e2e59ea9512f0d1ddab60217ba15
1051963 F20110217_AABKPH smith_j_Page_077.jp2
8bf30424c34856dddab0d4d7e565bf50
53c1c7b1d9e1d3c03917f4a230e39f1cf5139a9a
842510 F20110217_AABKOS smith_j_Page_059.jp2
b1fc95807fdc377e7992ef20317493b9
d9b92550198262bbd9672b9219acdb934512f4c3
8467 F20110217_AABJMF smith_j_Page_142thm.jpg
3967b83a602f803b988cf9cb2204144d
83405defccf64148b037dc4a315abb4acc2d354a
F20110217_AABJLQ smith_j_Page_142.tif
0ef06a551bd700d416c8c197b646f78c
f7762ee7db3f68da2f47d2f9f138616fbfa67434
1051966 F20110217_AABKPI smith_j_Page_078.jp2
c4979f48b8e392708c1298916f8af569
9103d5bd678cf32fffeeb983c394759fc6592d04
741023 F20110217_AABKOT smith_j_Page_061.jp2
ca89522905e8928213e18e9fcee3bf16
6e4ee9787f0e561bc240796ea1199949b685c1c9
862468 F20110217_AABJMG smith_j_Page_004.jp2
1155827e47bd9e54ba3e7eae65e25cef
3e5eba4d2739f8595f703d3a0e91ac3002cdf187
2433 F20110217_AABJLR smith_j_Page_087.txt
387f853f3adb00af55f14135a15e8761
af315482ac59f0ff122db0f790c6e67bd02d0706
1051977 F20110217_AABKPJ smith_j_Page_079.jp2
09c478e23d7129014261011e62db8e5e
09101072cb4c2817003e0fd645b58c9f8255b8ab
646169 F20110217_AABKOU smith_j_Page_062.jp2
064fc078337191a84b16dc5b3f9c1aa6
9c54412f873502b576ab20d87dd7ad755fec6542
26703 F20110217_AABJMH smith_j_Page_124.jpg
2af602a47f5fbe16296d88e6373964d1
ac3ff5b94a2a0beecd1374f97fab9ffd02e0274e
8198 F20110217_AABJLS smith_j_Page_120thm.jpg
1019bd3258f4e9eb2edfc1b20fa2d482
53bd59475f28b52fc71a4b46bff8531300c72bc0
1051938 F20110217_AABKPK smith_j_Page_080.jp2
5830cd53b9f6e687f1bf4bdedaa0640d
8f7ab1aa8f6df79936e07241b693d7ebb6aa7c99
1042900 F20110217_AABKOV smith_j_Page_064.jp2
17d3dcdf06ff0f74b5c7c19ba665714c
75d23c121600ff39d7520f5200e91fff24f809dc
103441 F20110217_AABJMI smith_j_Page_067.jpg
a8b9634a4dbfad444d4829c5d4b9c06d
31d406c071d867968b223e3d01c2b52f7d689def
31124 F20110217_AABJLT smith_j_Page_045.QC.jpg
cf2f75ef1c5ad911c3d111efd808af24
53591c4dcfafb47b549d67ddd76f39455eb264bb
F20110217_AABKPL smith_j_Page_081.jp2
5ac4549dd40c50c97975211c3b745658
6f9433a567e1df6d0c764e5f82a10a6e2aca85ff
1051951 F20110217_AABKOW smith_j_Page_065.jp2
f46b28411d8e80aabdcb1fcc378e5c4d
fac00d04671a5344974316f8718b4f51e4c2686f
F20110217_AABJMJ smith_j_Page_143.tif
ead1ea3f62a90d77b676d568d4258ce8
b7fc7f6d45a1bf004c28375546a49551934c93a9
F20110217_AABJLU smith_j_Page_140.tif
6349ee46596e497c8e398125f785d277
e6a1b6a434fbb7e89d083fe1bcb7833b946d8a83
1044785 F20110217_AABKQA smith_j_Page_097.jp2
7fd5a409278731a201e8fa81ab62faa8
250035e21246be884015cf7c17ce8b26cefd63e3
1051908 F20110217_AABKPM smith_j_Page_082.jp2
8d2cc1a8db1fb87dea3404199a450ed5
fe35dc8e9a14a053a0d9409ff5fb0be9442f632d
1051925 F20110217_AABKOX smith_j_Page_066.jp2
3122819b85afd195b31b642943abefdb
562f7dd676508033f4b43dc275f6663e1469233e
36345 F20110217_AABJMK smith_j_Page_134.QC.jpg
068837d6d079bf07d7e1d934cfc09cf1
2c3ba1d5d4daf12f5488c5458e1b555c416b7c97
857961 F20110217_AABJLV smith_j_Page_112.jp2
466cd1e0b370e42e874ae9641f9c479d
5b7f87d483593fa91788e136f12e6af7999d850b
1051956 F20110217_AABKQB smith_j_Page_098.jp2
70a464b97f905a89d6491e4515220e63
7c73501aff9e1cf49e4984e8444368308dce7b52
F20110217_AABKPN smith_j_Page_083.jp2
cceb8b79229d9c75539a879d90e3844d
cac2d4e423d2b634934d8ca6ef8071f43be83bc4
1051980 F20110217_AABKOY smith_j_Page_067.jp2
4626ff455b581e20b4e9b7a4aefe88a6
c57548553a91437ea744563b46651e154564251f
F20110217_AABJML smith_j_Page_102.tif
3088c0a7e2ac00eb61e1ea2fec40b15e
8c669cca7afbb3bd2b154a7665957307a042b1b9
527459 F20110217_AABJLW smith_j_Page_092.jp2
548ff7c16bff76bdf0b547330f271155
4f76c5f15ddcfb31d7634e76a15323e3826c1a03
1017267 F20110217_AABKQC smith_j_Page_099.jp2
947e2f35f102a0e040c49ed5e49404a7
81073fab1c40527dbceb6922d024b9b312dc021e
1051897 F20110217_AABKPO smith_j_Page_084.jp2
e21738f83925bf3b6690d46167afb634
c203a54f3463fbe4f4c01d0169dcf279870c9287
1031520 F20110217_AABKOZ smith_j_Page_069.jp2
137290cffc222973f55b5dafbe023d3a
40d658e31943ac2467c58015978f555e1322535e
231643 F20110217_AABJNA UFE0015225_00001.xml
6697a5a4b6a563c083e774ac0f24648f
fb167f205ae532ba8f3c902457e20f83e7c1ad1a
F20110217_AABJMM smith_j_Page_098.tif
e9e74b9406447535838c1f364ae9ade7
2f88c8cedbc1cd6db3e87697caed18a11f7b5947
395562 F20110217_AABJLX smith_j_Page_060.jp2
c8ae4ae0a94982a30f2647234bcf8a70
4a39bd1fb417681fb87381fc1a806f8ca9c083a5
1051974 F20110217_AABKQD smith_j_Page_100.jp2
1e0728c0610aa21d8122a242d06f1d5b
143c19059ca7d393f7ccfefefac6f42294e2b4f3
960217 F20110217_AABKPP smith_j_Page_085.jp2
daed354944f5d906402064310c071957
b7597f5c81019a65b24e06c6f93f69fa58c2afd8
F20110217_AABJMN smith_j_Page_127.tif
cdb87a7cac9dff4c5fae711a9bfc4052
3846f1c44d3ab145d869d17a8144086dea8ccfdd
1786 F20110217_AABJLY smith_j_Page_047.txt
65841dafa98297a958e9d98bf70cdb75
4171b0dfd475d43400d51193f21de1c2e0e30bd4
1051958 F20110217_AABKQE smith_j_Page_101.jp2
cb47e37a23b1e9e3c4a871614bb51925
abfff18a00f42bc573d8649ef445c52d9858206e
776445 F20110217_AABKPQ smith_j_Page_086.jp2
29fc8977f340e1a1ea6ec2a84d3e7f2d
6aaf2ae0a0d26fc6e753e8eebc8657d2fe248a1c
1865 F20110217_AABJMO smith_j_Page_044.txt
2adb085e50d9748a4094f00773016719
e7c0a2e48ce949d66bede7e1caa2726f8d44b25a
F20110217_AABJLZ smith_j_Page_117.tif
97a61dd657b05ab0b1a9cc759015c9fa
58f14db2f5ac28bcc4a8be07200e47776510c617
1051572 F20110217_AABKQF smith_j_Page_102.jp2
3173e1dff5e3d53b865e2c2f6a3b2d8a
4f4bf549f6e113c323b225138bc52cb32f3338be
814278 F20110217_AABKPR smith_j_Page_087.jp2
122a72e30d687e7d6f66bc55abedbb13
7c0c36787e0391a679f35d4d0c3d825c2b581172
F20110217_AABJND smith_j_Page_001.tif
ea8fe73c4e09951049a451e7e32ded6b
6a5f3da8aa60de0432b0f15c388733e91b586a39
1051950 F20110217_AABJMP smith_j_Page_119.jp2
ae3371be8416c4b77c9bfad73c8306f0
3568f3ef96095493377a6435b7158cbe9d15c26e
F20110217_AABKQG smith_j_Page_103.jp2
7aced636c33033ffaace41d55cd95f5c
329cc04554de5ee35ec35fdaa38c1885c94a2e9d
562034 F20110217_AABKPS smith_j_Page_088.jp2
a1b96b57ddd91b158ef564a022f2da0f
b178f8248b3282957bcf19957b906cff551eda17
F20110217_AABJNE smith_j_Page_002.tif
a8319905c2cd23c25ada835d3dc5ef42
f0ba88cb650725137be4231abf4da44122fc5331
31949 F20110217_AABJMQ smith_j_Page_104.QC.jpg
8890902260d0dd789044c66908c4099b
09e018be9621da97e3818335267d9fba81c68ae4
1051853 F20110217_AABKQH smith_j_Page_104.jp2
dd29a2621c1570538a6f51e623ccd879
b447b43ce3d48bda89f799ad586cd6b91f6070f2
F20110217_AABJNF smith_j_Page_003.tif
e6dcf505b71f9bcd35dd6ed6ee3bcd69
563a73504f89e2dbdc3384f2239ed860f1235ad9
1051965 F20110217_AABKQI smith_j_Page_105.jp2
70e0ec4e20a751603a7d12790c493b15
45b0fb7ab7a1d40c8970551f14ce1b28b0e7427a
620895 F20110217_AABKPT smith_j_Page_089.jp2
7bb9b4138b1159984bf0bd718f0ad31b
fa28bedebf997c30ee3597b1c7d1d7a36f604b5a
F20110217_AABJNG smith_j_Page_004.tif
39cbd9020de0a1397b3ce188437f3f6d
34f1cfb7901fe09ee803114eec15440f3919a152
F20110217_AABJMR smith_j_Page_012.tif
9c709eca5a18450aa630fb4039881521
057cf0768c5844a442907407f606fbfedb776bc2
1051979 F20110217_AABKQJ smith_j_Page_106.jp2
022ea2b3117bb7329f435d31eeff2bcb
b141414803b026b6c8e062786286f6c9d44473c6
628412 F20110217_AABKPU smith_j_Page_090.jp2
5be02f00e52ed3a5a680d7d62148a6d2
cdf54eb62328039fbce4a769fa9111cb0d5ed6e3
F20110217_AABJNH smith_j_Page_005.tif
c01804b676a9dacbf45735db92ce9a73
cf4dc0d4565962669d7e59786d3967d39b23f056
35398 F20110217_AABJMS smith_j_Page_137.QC.jpg
d646469c8f9a0ba99001c23d54372f3e
cc255c2f4dde69e4dc2e9384a6fa23b3998e6f11
1051937 F20110217_AABKQK smith_j_Page_107.jp2
0a2f50c27a2c0705964d72e5e4efa07b
c85628f36a62ed1f64310149aec964c96c48350a
660393 F20110217_AABKPV smith_j_Page_091.jp2
981f76e6237cf9e9e69ffd3f4c4f16a5
5026d4b04d74dc6190821f4c25bfdd7e2e8947e5
F20110217_AABJNI smith_j_Page_006.tif
32636c18b28df0f78fa43ee4237d8676
350729fbb778dbee118994b5df25e186bd7ede31
48026 F20110217_AABJMT smith_j_Page_072.pro
e3d1631aea79c8f175fc75a7ff41dfe5
54623132352c1660b3afaf8347942ad199c3235c
F20110217_AABKQL smith_j_Page_108.jp2
6ee6532c375ca2663ff4d864fcb3e921
05253f8ca9736bf209c4da0e431db4756dc131af
1021602 F20110217_AABKPW smith_j_Page_093.jp2
2773d314b81b827bb6992ce2194bcae3
64be585d35b43b72f95256b1f569f6d1ae289f3c
F20110217_AABJNJ smith_j_Page_007.tif
3e8bd0c5572342986548d0997a5c0808
42959858af9ca3fdbfb2cc401642b1a29a735b27
32163 F20110217_AABJMU smith_j_Page_125.jpg
193f93667e4a99cdb20935d96350c61e
b7b3cfcd3c04e6f8ec7920fb9fdc860cf678a4d2
295669 F20110217_AABKRA smith_j_Page_125.jp2
8a9d4b0e1fccb8f8ee1efe3845ecbd9d
eff0e635a56660a9c0972958f59c919e0228bf87
1051953 F20110217_AABKQM smith_j_Page_109.jp2
d5e53c19851ab76bea4b0fe81d8c5338
b216731d804265211b8b96eab1b066778f0a4cdc
F20110217_AABKPX smith_j_Page_094.jp2
33098908a391305b80506d4224c07887
0e2e4ae2173bcf5d9db2ef13ad8127c3ea1f58e5
F20110217_AABJNK smith_j_Page_008.tif
cf6292cea28ec76bc06344275eaac65d
beb89e3b17d66765f7d57e6d56904f4688349970
8600 F20110217_AABJMV smith_j_Page_110thm.jpg
0d82259459e2772c22b892a48dc73711
ea58aafb54395882c7b8ce40042b74b527bc7447
400251 F20110217_AABKRB smith_j_Page_126.jp2
fa9628310dfd1b958fccefe05f382ddd
6b436adc26dcefc8f447b90cc7264400b3882c0d
F20110217_AABKQN smith_j_Page_110.jp2
f3e837d10dd20dc0a475ed206f1a95cd
1c939b7a3254736a18ff76b4d78ab60c616dcf64
1051954 F20110217_AABKPY smith_j_Page_095.jp2
28b4515f79f9b675df8002222fdcbab1
1257f9992e2e040993165f8d4e9d7ec93b261a20
F20110217_AABJNL smith_j_Page_009.tif
58a79bac023a05bd93436c2afe777e8b
6501c9b1991cc7da85f3e2e259c25de0245a5726
2010 F20110217_AABJMW smith_j_Page_019.txt
aec8f3974814d5468293bb8989a4d72d
dd46251b6632d0ab017991935e655b16f0586ad2
489223 F20110217_AABKRC smith_j_Page_127.jp2
d5c443499c74bbaf7bcdeedd3b37551e
85ffa6109e6b079228a1ca84e533c94c3c0255df
506217 F20110217_AABKQO smith_j_Page_111.jp2
a65b30582312180f01cf43e52f5d203a
9dc7edf112ac03271ba0a4600aa9c1c5340732a4
F20110217_AABKPZ smith_j_Page_096.jp2
ca2795e7885573d2742fb284c6b4463e
4facc4f4555abaf114dac1e9dd1237338397598f
F20110217_AABJNM smith_j_Page_010.tif
da1f04d3954bc571f4f3a6605d4f4e21
6fd3fe08d567b41d9388a2888854b593e30531b6
107884 F20110217_AABJMX smith_j_Page_051.jpg
153dd9562a19552e2b33948d685a95ae
eb535a151edb916fe2d60fa7fc08e7b7dd950298
F20110217_AABJOA smith_j_Page_028.tif
00a4ae8cf68f7140b68ac1d430d3bcc8
bc0a215f9ced192dc4e6970d72e983b927028364
F20110217_AABKRD smith_j_Page_128.jp2
7cf08c42403812f6c117fad4182d4192
c4efc4f63e05090707efcc01043ad2577a44013a
482285 F20110217_AABKQP smith_j_Page_113.jp2
d81e79844bfce72d7f88cc97c2571848
ab7bca3941fdc8853b7a8f2f3658648c8e81514a
F20110217_AABJNN smith_j_Page_011.tif
ae5e3ec28140d580c0d406a9097e6fe0
7c1f08239bdf62cea70284850759a587ac83249c
42490 F20110217_AABJMY smith_j_Page_060.jpg
e1dc4af3482e3927b7ae54c27d1961f0
1c2e56f0bafcd7974268897e9efa85f261f0350b
F20110217_AABJOB smith_j_Page_029.tif
140fea3ab9240c71c8fa0f6a4d0e27fb
43ccd5e73d2b69897f3c19fb0721274e6d60b7bd
F20110217_AABKRE smith_j_Page_129.jp2
5a2984f89fa4a41704e749941cb51107
91ee648f01f4ae2f7d275112f4eb955ace859d4f
456025 F20110217_AABKQQ smith_j_Page_114.jp2
8acbad29335d610511e621d8e50aa9d1
c04711fb13b9b50786e37f96a5fb784495e240d4
F20110217_AABJNO smith_j_Page_015.tif
564f415676148dbe7c775d712089b72e
60738e5540df3bccb822c7dfba22e6b62d2ce814
8575 F20110217_AABJMZ smith_j_Page_131thm.jpg
7659f6521ed60ff7bc42db66df77ad04
0313e1963943867faa4ff4ac2c807c53de97d5de
F20110217_AABJOC smith_j_Page_030.tif
76b1efe6df3bc5c34f9b0536c175a7b1
968ae691f6b689e1eda545bc52107cc9a7439c81
F20110217_AABKRF smith_j_Page_130.jp2
57d6d451c3e816b86e60649d100e2b78
8861fb3b23e470a3542687c80ba37c7d9e11a82a
491092 F20110217_AABKQR smith_j_Page_115.jp2
12d087c8b31eee0ee3d6a762508a5b2d
dac8fee6a4663247c304db44b3af74e5480a6cec
F20110217_AABJNP smith_j_Page_016.tif
90ddda9791062a41a1eb50a4b5d463d6
afab045dbbb1667ca5eef042f7382d39cae40f04
F20110217_AABJOD smith_j_Page_031.tif
a6c9ebaf852043c6982d9676bae52f93
444f21a729088234ceff19c87bd983a8beea0c6f
1051949 F20110217_AABKRG smith_j_Page_131.jp2
cbc45a2f4c452786ffea0f2e99bb8a5b
464408f7934bd241f9fc158cff1f21910093e9fc
446174 F20110217_AABKQS smith_j_Page_116.jp2
3f18fb2de457d0f7439eaf81c0cf8f25
847332eaeba955c3393d269dab7e30f528e66789
F20110217_AABJNQ smith_j_Page_017.tif
3cc34cf6d7282113612230d7d38b6b52
f063940fa718a05ce63779e0d3de6b3f41f2f42c
F20110217_AABJOE smith_j_Page_033.tif
0f76df9a2fd643750565e3cce4ea013c
60e2e9ca84bbbbde36c00ac34990c22cd49e363f
F20110217_AABKRH smith_j_Page_132.jp2
7fc78f9f901842ff7d50412837e365c5
a5edfb29860c8b0baadd2dd81d26504bbe6c9302
544901 F20110217_AABKQT smith_j_Page_117.jp2
9b8b461b82f421e00bc6bda0a5c64daa
774b63261aab1f0639601dcf9c52707685025976
F20110217_AABJNR smith_j_Page_018.tif
50d3fbcd90415da6ecddbf3ed6624d1e
69fb52fc8275c18533ee5bcf293f1a50f4c1f124
F20110217_AABJOF smith_j_Page_034.tif
ebe7e51f39a3ae9eb62ded008f8ebbe1
fe58308bc129d32e779285abb7593e225cc92ac1
1051923 F20110217_AABKRI smith_j_Page_133.jp2
edd7884a8e70f43947a22dabbf641b7e
54659cf2bd3dbe75f5828f241ab770f7583cf8e6
F20110217_AABJOG smith_j_Page_035.tif
f63d30e06cf2136855a51ef59cc882d7
0a761792b793e807d6660cdcea39bfb6453c821b
F20110217_AABKRJ smith_j_Page_134.jp2
ee19cc24933e3a7c3be534870d8123b9
bec9f068e2f2f0c9a98728a5563f624bc1951f77
1012208 F20110217_AABKQU smith_j_Page_118.jp2
6449f5a01a2efbf290135ddd75f50128
757df9133532bed2910c1d210cc27de1abc58b00
F20110217_AABJNS smith_j_Page_019.tif
50aec3a29b2a444f958f531af19832e3
6a21a7c22fc6382e4b42d0750823f1abc0484a77
F20110217_AABJOH smith_j_Page_036.tif
7fc95aa24edad684c5f62526bd3b8cef
6e22d9878e69308ba739c89984c95655c60f3ce6
F20110217_AABKRK smith_j_Page_135.jp2
327953f3c1f97b7e759df2bfe0966910
3a93be40a0784ec36fe1b968690bdd8ba75fa470
1051973 F20110217_AABKQV smith_j_Page_120.jp2
9d42a6fb8a7a5972ab5762e86a752f6b
4b3ce2c2eb5edcc07b74118a194dc8e0209e2e40
F20110217_AABJNT smith_j_Page_020.tif
b5bd7ecd87711812711c7866b86f10f9
130d1963aea32294fcfadd4b4e57576aa0097e1d
F20110217_AABJOI smith_j_Page_037.tif
65d4bde95b36320a891c91b4dc000664
5a0b791ef6867a781f8d37a712e69e7c0b3a3475
F20110217_AABKRL smith_j_Page_136.jp2
d47ef17f3524d6952863d49fe3a7278f
f0ebc2c28ba227446b0024c87d4cbb58aa16ceef
F20110217_AABKQW smith_j_Page_121.jp2
4f2c977544b66279b4715c4c0550d988
6e7dd086bd8efc76c9456d5300d625daa128f980
F20110217_AABJNU smith_j_Page_021.tif
2d1ea34e888bf1319f3c16a1e22a75f5
7ea8a1a339f58883bdee18cab325216ea1aa5808
F20110217_AABJOJ smith_j_Page_038.tif
a0ad87b6df73521efad3278dee807b09
2be71c89425b5d18006e810d05ad0c58e1b9153c
6577 F20110217_AABKSA smith_j_Page_007thm.jpg
5aab15e4eed6677d39579c26976abe2e
f8ce302518eb197092941416a94d662100dbc5a7
F20110217_AABKRM smith_j_Page_137.jp2
a557f0b6402efd6c3646ce4c79039b83
be037d8e057bb7066a93908bd501aad052af8054
533534 F20110217_AABKQX smith_j_Page_122.jp2
f4559e0b10ef3f0e2dd0c9a4d87b6434
fcdc1aead597dabc4e10690af8482cba6fc740e4
F20110217_AABJNV smith_j_Page_022.tif
29be97a0bd2cc068adb9da7a6edfc0f7
da9fc424186c8b9f660675fbf8759db7bec52d5c
F20110217_AABJOK smith_j_Page_039.tif
3d966225672458ab7a53eb2b80b7a399
6e0213aa2d5912d56d49659d84d80162dd0829ef
1325 F20110217_AABKSB smith_j_Page_008thm.jpg
9443f4d7ffc1fa91b609948fac15d4b7
658ae5be114fc4860f809e29e8e91c225f8f3793
1051926 F20110217_AABKRN smith_j_Page_138.jp2
d881abf0291865d0887f71e9fe5708a0
ad0b7e3b559e365011fde3e742e5f2702c1c072d
604149 F20110217_AABKQY smith_j_Page_123.jp2
99f4516204110c6aecdec49434905275
efcb3e65918ef72819212854d0518ca2270dc3fc
F20110217_AABJNW smith_j_Page_023.tif
780d7380304380f730ec7ca335196826
1650d2f3db5c2bea14712b39a7dacf17c0a1ff82
F20110217_AABJOL smith_j_Page_040.tif
d3130b56f504e4f9d789f6dedcfca1f3
c35985126cadc912bb9f32a966fc609d37bc1e99
5901 F20110217_AABKSC smith_j_Page_009thm.jpg
06d92a5e3f9961bdd77ca4c6710abb5e
5db6c8150df82a090b4bc34078afda3506f0d9f5
1051948 F20110217_AABKRO smith_j_Page_139.jp2
982f1ae146db6692a179775a863b24fe
eb788d7fec64fdd6313a868f2747333cc53cff7c
221718 F20110217_AABKQZ smith_j_Page_124.jp2
900744a0891ef18d6ce6b296705c861c
03dc60cda8fcda6663fc98e9f274f07c64d1033b
F20110217_AABJNX smith_j_Page_024.tif
22d367d43dcecf7b6a7adb3cb7021488
fbe9fdb40f703df23beec154cb0f9b5335cd6157
F20110217_AABJPA smith_j_Page_055.tif
0bd3f95a5aa13f1877defb756868e083
2a06fa960619cf5a7a472b2962dd8a3768c92c9c
F20110217_AABJOM smith_j_Page_041.tif
1bf2c165d874d4143117e8607debbd53
efc0beadc54fde55285083175129512c28981b98
1491 F20110217_AABKSD smith_j_Page_010thm.jpg
a3b1c9c7136ecf66ea7c57936ee644de
082d530de9efdfafe17f3928edf327d2e14776d9
1051915 F20110217_AABKRP smith_j_Page_140.jp2
cc054ead29db0a5c1729c955b2ad6311
a78265b13e7ae029e427514148a152d3eaf39b53
F20110217_AABJPB smith_j_Page_056.tif
0469457064cd5553b73e0e9f1daa47ef
df36415b17d6e7999d9ae628ad075deb89275093
F20110217_AABJON smith_j_Page_042.tif
6c922463691152eec5f7537fd45ceebc
0658401e14824f4fe4520f165819f458d15d4061
F20110217_AABJNY smith_j_Page_026.tif
a5c82b2965ce05558540f55a1c17281d
a2f68fb9e6193831c4dd7d8d5f21007570790606
6116 F20110217_AABKSE smith_j_Page_011thm.jpg
52b5210dfdadc3af29e61b9d54add7b7
fdcdf258ffc5f9df72d1ff1c02e96f480f2ac2c1
F20110217_AABKRQ smith_j_Page_141.jp2
f8b7631172d3c65cc0e72e542549ce92
3d049bd237f8dbd1858c5a7708ac0ae75566149b
F20110217_AABJPC smith_j_Page_057.tif
4ca2313596b4fba0df43455ef4eccd67
f151e46b41742ab69d38ebc0faaab1ac77e0ed81
F20110217_AABJOO smith_j_Page_043.tif
0f347ba296ed958b46dc5e3b3b0e47d4
9992459aba1c189a7fb33f262d321ad6dab666c5
F20110217_AABJNZ smith_j_Page_027.tif
2298e955b67a89765212136766300dea
6132343bdebd832a76ca7f7cde1dad296a43cdb3
870 F20110217_AABKSF smith_j_Page_012thm.jpg
1c2022fcde5795dd38393366ef74c136
9083fba175667ad8160f85c27ca633d6f40758a9
F20110217_AABKRR smith_j_Page_142.jp2
3b8861b69c179d37afa955f9516c81e1
dd8cc5bb0d97d973d888fab8b14315ccea1cf3d4
F20110217_AABJPD smith_j_Page_058.tif
a878f27d73bb8daff6f2b57de0b5d6e4
6e8b0abe40eab80e7a2c8a772daabebf7851d170
F20110217_AABJOP smith_j_Page_044.tif
313fa8355aedb811f2e295b9d67d990b
760faadc46374104c4e9086b19a8e9101c2d5eda
6670 F20110217_AABKSG smith_j_Page_013thm.jpg
b34efffe5fcb33f4a16fb40432333c5e
23d44aff853a9ceaf695b2a15ba9a4b19ef6d58f
F20110217_AABKRS smith_j_Page_143.jp2
f1609b85ebbd6419848c16ca023cce5b
100d00a0891b50529359d13d86a10e35cc5790f6
F20110217_AABJPE smith_j_Page_059.tif
ef7560154160515521556fb22270b2af
5ed534ebf69bf03b483e8d2e7de706464a3ffc48
F20110217_AABJOQ smith_j_Page_045.tif
209a5516151fd07a06bfec2a9d04346b
f7212acf5b18329f95b3e3ec19f68fddaca9df71
7318 F20110217_AABKSH smith_j_Page_014thm.jpg
2102d526eeb3c4fefae2131c4265e21b
13b5c22fe6fde9c439e2d1154173ce78768e587f
925387 F20110217_AABKRT smith_j_Page_144.jp2
a53544312e55099696a7e8086358bd42
a0a9faad15cbae3126ecf787b9843fc154478321
F20110217_AABJPF smith_j_Page_060.tif
efca4e98085df236238f0d46597cbce6
9d65a38514c02058d5af079e586103a91288bb5e
F20110217_AABJOR smith_j_Page_046.tif
654fecaf08a9aa11cc4fae460b88aa3b
5295320d119c696b61567437d12bc9e0cdd7914c
7285 F20110217_AABKSI smith_j_Page_015thm.jpg
74ae06ebcae85926d600eb8e22c5246a
4b4f85fff37b7c1027d3be932ea9bb95b5c4272b
2436 F20110217_AABKRU smith_j_Page_001thm.jpg
57f1bac1035e819b304f9a2303370de1
11af145ec1addf48ef2cbb9693f9c55aad8cb11e
F20110217_AABJPG smith_j_Page_061.tif
a75161fca1a5f3578208bfe4db99b383
8925220ac6db707e9c8da8c0fd250f4b99c2d613
F20110217_AABJOS smith_j_Page_047.tif
299e34f58b298ec4beacd279cc941220
d6b72f83e2d84cf94a3dedcdad766b2bf8b0ba94
8129 F20110217_AABKSJ smith_j_Page_016thm.jpg
6c6849456fa84dbedb7207c11aaee644
1a42d451592ed3db366ee0ba985b1aecc3d46673
F20110217_AABJPH smith_j_Page_062.tif
224d7861729ceda1712908c1d315a355
b3be2f0a04a5e32315109976d13d006f8f6993f0
8162 F20110217_AABKSK smith_j_Page_017thm.jpg
b703830f71cd1a1f41d4d0c7da7d59f2
272593c537c3cf28b503de8fa8c72c1f42130137
629 F20110217_AABKRV smith_j_Page_002thm.jpg
6021835e1133df9b2ec1e7c915e15812
719e3bb9e18f62a25e703eea456b0124ef357cd2
F20110217_AABJPI smith_j_Page_063.tif
1416a938c006d18486fc7626ee17980d
30c213549289eba9918726102eceb40ebd7964e1
F20110217_AABJOT smith_j_Page_048.tif
201e9424da3f583555740ffae018d7e7
f3c7e3a60f56206d0561e905952a6fc9608190be
7725 F20110217_AABKSL smith_j_Page_018thm.jpg
b55034ed4d3c2ab273399844e3c34bb6
d7b0c14c6c505f489710217e2fb25296018d5043
406 F20110217_AABKRW smith_j_Page_003thm.jpg
fb82c458efb7b0f144d206440e3c35ae
b45ef11659c08eb411133d526347f7096466628f
F20110217_AABJPJ smith_j_Page_064.tif
50200ce56e275221447a15076f4f909c
d22c7af31e0c5de6c76da3394cd52343f7a30391
F20110217_AABJOU smith_j_Page_049.tif
9b9ce2c1f02f7a2a98c5d43a25dd668d
545bc408aecfb975a8c5684ec8149e8fe8a68e2c
4218 F20110217_AABKTA smith_j_Page_036thm.jpg
9e5e0d71eb75c293b743f68532337613
2cfa9bb58c4c1300d75fe896e00e52e95f980585
8136 F20110217_AABKSM smith_j_Page_020thm.jpg
fb9484c813233d10654e3453013bda1d
6afba1c755ed986467fcd242cab2e2ed18d890a6
6764 F20110217_AABKRX smith_j_Page_004thm.jpg
51099fa0c6e0659d15ee0c2b3b8db0bf
1593762efe1bed77d2d1906f74e8b0b7e0127bda
F20110217_AABJPK smith_j_Page_065.tif
8a22f7bd01a4de3925892c3b431f9bf2
fea78f0f5a7cd9efe7f2bc90c8a0ac0f019b386e
F20110217_AABJOV smith_j_Page_050.tif
1ebdc2bc8adf1900433b51fbff0d0609
21b494c5beec06a5a4687b67b6500678c8540b13
3802 F20110217_AABKTB smith_j_Page_037thm.jpg
d58091bbe3c11c12837428d6899a3a4e
36fc75e17af55b5e18f85006805bb47356635e35
7991 F20110217_AABKSN smith_j_Page_021thm.jpg
d1e9038d0215d3d5368d977403417dad
c2cbfe588098fce00efab6d5ff0bd474e95dee78
6746 F20110217_AABKRY smith_j_Page_005thm.jpg
1363eb3781e8ae4e6d13e91ea793e4c6
cf69059a77d871fd6128fcacea6cff3c53d13b70
F20110217_AABJPL smith_j_Page_066.tif
14a63f587933ca6c635ee0c18167441d
eb89dbf3e56211ac6899e15939e588af9f5ade95
F20110217_AABJOW smith_j_Page_051.tif
13486f01acb23cdcc050dd3952c97f7f
7ab62e13b4291c71128b41d5f16b36e8b7fb4ba2
7044 F20110217_AABKTC smith_j_Page_038thm.jpg
c3921b7af4d3e102bc2750c25d075b00
42a51baa6a57daf01f15aea68e4b2899eec68448
8244 F20110217_AABKSO smith_j_Page_022thm.jpg
7878cb131c391e549767c2becf272c27
3b9e5b01e998a882cb142382a874e95f56e930c2
4722 F20110217_AABKRZ smith_j_Page_006thm.jpg
bfed8e4cfdb61d709f90a0431b3ef486
5007e11798d1998d56e98550a025d32f5be601ca
F20110217_AABJPM smith_j_Page_067.tif
917b7b5db2ffdde9963f655848aa7dac
1de651cdb25c94e8a82483dda919b073093f5027
F20110217_AABJOX smith_j_Page_052.tif
286e7d643edba0b62cbb2f2cfb0fd4b7
d5fc7b960e94bbc50a5ecbe6ce1c9522887f2e89
F20110217_AABJQA smith_j_Page_082.tif
d30ad33e1a6f59aa5c47449860c2d11a
a5c7ecbd334b42b6d202849a0eb96c9fc62bf4d7
3968 F20110217_AABKTD smith_j_Page_039thm.jpg
14e906349b6a9c814665cbdd003bbf87
cd91419ba2d9336e77d806cd04243742a014e195
8329 F20110217_AABKSP smith_j_Page_023thm.jpg
0cdff2ffc4015c7f1ecd0e64a3b1072b
ddb87856076ba4d2a6554b1622f3f867c38281e2
F20110217_AABJPN smith_j_Page_068.tif
851af90e07f9c94386e2263a972275dc
c4befbca5a5940150fc90aff3b966666ca2fce94
F20110217_AABJOY smith_j_Page_053.tif
01119d272639b560cb4e7d400ac24323
8264b0d2e6f8b94caa1649b7fe0314641465c240
F20110217_AABJQB smith_j_Page_083.tif
420b8abff0b34856e2fac208a0212b8c
ec5651b74d7c3c5d779b8e2bb766297d38079ea2
5320 F20110217_AABKTE smith_j_Page_040thm.jpg
cbbac22901606a351bf46866ca4e174b
f8a6da0dff19f5197fe48d0a15d14cedced3e449
F20110217_AABKSQ smith_j_Page_025thm.jpg
d748ab862ddc799f5c4ade10116f24bd
dbbd34798b3714e8804340a29e308b95876593d8
F20110217_AABJPO smith_j_Page_069.tif
227be87d956f34745681f3958faad842
d4316aacf5505aabb15ad9a6a4e50c4e2ff42cc7
F20110217_AABJOZ smith_j_Page_054.tif
310dc5858a05cef75712646303b783ed
f3e281a2bbf8a4945cc1a71ac352193266d08944
F20110217_AABJQC smith_j_Page_084.tif
490c4602bfeb312ecfd98adf0404be03
388ae4ad1c1049e415250663242ecaadea6ea71d
7312 F20110217_AABKTF smith_j_Page_041thm.jpg
90fbe94bb241e130dc92e31e830d4f0a
49752b0da87de79e07118720b7c4a6f416494bc5
7710 F20110217_AABKSR smith_j_Page_026thm.jpg
6898c2b48699cc5b6fa82168e02cc23a
4f1749ce5c06149364da78fc19497331e5fa07e5
F20110217_AABJPP smith_j_Page_070.tif
396e9e53d92495ea8b603c7e815087fc
c5f679778af5be44e569860edf032b094f4f6d65
F20110217_AABJQD smith_j_Page_085.tif
454b68d1dd6afba002c4d7994be73932
883c0b2e70bea257904b42a2c2bd023de39ca4a7
8288 F20110217_AABKTG smith_j_Page_042thm.jpg
d4be28644d42889d557106923a53ddfc
16913562086b00bbd98735d3dc9feab8d1aaac79
8371 F20110217_AABKSS smith_j_Page_027thm.jpg
4a8716b05fe16502463d4121999585f6
e99a94162f15e5e195708c202cad207f7201e2ee
F20110217_AABJPQ smith_j_Page_071.tif
d808d0f34e3655968972ee141fb10f78
caa0dec7382155ba5a4d814da60a31cb47ba229b
F20110217_AABJQE smith_j_Page_086.tif
ef9f95470b54968cf8dc781046637134
787d0d9800aac56042611b9d821529ec932dfbb3
8488 F20110217_AABKTH smith_j_Page_043thm.jpg
1d6588329a6174511d4adb284aa58b0f
d4712d01b4240863cf4c125ed7f8d8aed587015e
8523 F20110217_AABKST smith_j_Page_028thm.jpg
70f9e21cd23b25cfdb49b6533d303be4
7bf3b89ad152f63120f62ad645aa6595c8884de1
F20110217_AABJPR smith_j_Page_072.tif
5339cffedbde697582cb35cb9e117fc0
c0f12468d77103da6ddb4f0c1cba575ea535f46f
F20110217_AABJQF smith_j_Page_087.tif
22bb05d49f0977a2807884c92a602068
593cd6e8f587cfbde742692a63f7c4d1e20df63e
7672 F20110217_AABKTI smith_j_Page_047thm.jpg
5891d82620ee622df2e4be3b25d284fa
c3b75afcf8346b5f3ed12652a59d6cd1c7bb858a
7840 F20110217_AABKSU smith_j_Page_029thm.jpg
7f86a14ea3e6bfdc2551f55da95e164a
dd266fb8b2ef51de04d4d58e5190d42d573cdb76
F20110217_AABJPS smith_j_Page_073.tif
5ce32a10861bbf50db14cafbde0fa203
3180cab6f15247f9bf5bb126188f9bfffe4a9932
F20110217_AABJQG smith_j_Page_088.tif
88bb5857e388811f70a02334460c0b7a
23c7c3f41e0c747d9424e702aa3cab6ac9439a72
8703 F20110217_AABKTJ smith_j_Page_048thm.jpg
1f6e151c1225bea0b9d4e0b11928af8c
15631596e3b9f9a39ea9ff43fad3c0a798160d4a
8171 F20110217_AABKSV smith_j_Page_030thm.jpg
613adf3adcc40c879f78b09f07ffd56c
02dccf10f4a3fc90f2af4f2a440dbb68ceaf4cc3
F20110217_AABJPT smith_j_Page_074.tif
7e3d9300d4f926d3d0ad44b99c6ee594
caf22474c69f0c51862e85b953d07773af889461
F20110217_AABJQH smith_j_Page_090.tif
151ef86f3e01395bee9116f259cdf5c1
026d12342738ce53326c894873dfbefb66e8aeb2
F20110217_AABKTK smith_j_Page_049thm.jpg
99ce5dcc8c854ea47b61bf9b0980e0bc
e5c6f63b78ee9a703db214dde3a5f93d54e03e79
F20110217_AABJQI smith_j_Page_091.tif
8a36012715fd58bd960023df4d9986aa
5ae8c1728abae54ac22576b14175e097bc43c522
8179 F20110217_AABKTL smith_j_Page_050thm.jpg
b86cf1a54294b05064a3f5fe84e36deb
c6497481823dc0b3c9c2fac0327f3d58438f1e1c
8332 F20110217_AABKSW smith_j_Page_031thm.jpg
1bba5f5fb143973aae494a7ef8d99fac
52ee855ca922903283e854ced5cd97a6bc7e4dd9
F20110217_AABJPU smith_j_Page_075.tif
a4efeebef744f1df57c38e82cc71da7c
ffb39ef76afccf9ee902c3848a5d50d2031dccdd
F20110217_AABJQJ smith_j_Page_092.tif
a6afb2b33e9ec550ce7f5bd315709e25
bb6eb46f3206b21be3af020e7b44e1090a2a35cc
8004 F20110217_AABKUA smith_j_Page_065thm.jpg
341c86f0825fe1e634fc5da35308c20b
9ec7a1afebb8daf9ddfbff89be8a489b4b191cf9
8547 F20110217_AABKTM smith_j_Page_051thm.jpg
0ea570855f2bd60d003adbdb247d9c85
5edbda65476b36fbc9755c87714c6b98497cf91d
7841 F20110217_AABKSX smith_j_Page_033thm.jpg
e4d73d67be052f3e3460f23d45f34944
ccdcd6d8dd3526e45594fb0292771d8c512765cf
F20110217_AABJPV smith_j_Page_076.tif
14dbb36b71d4e5f1a3cdc98f94da4aa5
a38c2cd00d9d92b5f4c86f546785def07b9f1128
F20110217_AABJQK smith_j_Page_093.tif
ee3392f36912160b561d5ea2bdc9a53e
1bca0ffdbb609d932c77d70fa9c5d9bef053b637
8445 F20110217_AABKUB smith_j_Page_066thm.jpg
88cdf07dfbb2b35c8c6fb54bcda84a2e
689cdfb50f4d137d68f275732768b116e57b5c2e
8432 F20110217_AABKTN smith_j_Page_052thm.jpg
b26dd75104000d0c3f5a8560665970da
f144a8bc707915ffce776512cb9de7582b7f357d
6359 F20110217_AABKSY smith_j_Page_034thm.jpg
7c884b933bcd1a5145d07aedc3a0ee2e
258e732a73ad6063fe40aaea3d944912e1b3b5e0
F20110217_AABJPW smith_j_Page_078.tif
c11e405cbcf7cec3fd25e42e3a84de38
0f945feaa8fac41b35c3c71b305acad3e984769a
F20110217_AABJQL smith_j_Page_094.tif
9923433dcf3a5c2ce83b006ab24fe370
eb61a370a8258ad7d90fc5ce47e4c5eae7edda99
8366 F20110217_AABKUC smith_j_Page_067thm.jpg
bff8118c5d56c650b09ba28ffb703faf
ba10bf87ac8f4621d7655cfe61fa66c7a3d9c9ed
8487 F20110217_AABKTO smith_j_Page_053thm.jpg
07a9a58c0a2fc4456acbc3a978e092a3
d998b7a471b451aeb35323ca5e71521416a8e55d
2832 F20110217_AABKSZ smith_j_Page_035thm.jpg
754bfae7f5206e3b176030694f670f48
30dc989612ee20806ba9d7fd27daa5da286a99b1
F20110217_AABJPX smith_j_Page_079.tif
e20a3fcb33b4ef7f098a1d23d7ab6f0f
3592317e169f6c33f2f8a07192800aac71fc8ff7
F20110217_AABJRA smith_j_Page_113.tif
782de98fc283d59e58fa4211064c07ae
963c43845b925661d06ab1ae8bd69b9bd8f5d2eb
F20110217_AABJQM smith_j_Page_095.tif
d0ce772a5201e79f1d4688f6d320343a
65df4f15401f3ae694353a24f6872d6c54824328
8595 F20110217_AABKUD smith_j_Page_068thm.jpg
553fb903b21bb63f4c52ed379644d903
5330f34dcfde4ce3a5d3803014a808584ad9159b
7940 F20110217_AABKTP smith_j_Page_054thm.jpg
d5ddfcd195caeadeebd418b38b78df04
540f84f37640afde36743ad6714a7e0d4952c133
F20110217_AABJPY smith_j_Page_080.tif
ea037eff0ab5d37e5da5ec3325eeb2b0
667f2999cc7820fba91bf389d192fa8125b00a51
F20110217_AABJRB smith_j_Page_114.tif
30b3cad370d5faca038b7a158f8dc4ea
96f426a38aaaa8f8bd0d288c1dd5bf77c162c462
F20110217_AABJQN smith_j_Page_096.tif
0a2ea924a9e6c6f84b68ffde37a37247
514e5280e79f1c2bda27ba150aa47f0cb6b18388
7700 F20110217_AABKUE smith_j_Page_069thm.jpg
75eacf9d4b7481820df5c5a7a6fe83a9
1f21d3b3b938430dac59e7ec327b97e680713810
6742 F20110217_AABKTQ smith_j_Page_055thm.jpg
b1b76762d8b9175782fdf711c0113b94
e499098101242598dea8cd6a871ca34c1496bcee
F20110217_AABJPZ smith_j_Page_081.tif
96b3dcc0e925eb737910c52fbb1353c5
f42005406838906577e290dc52212a0dc9e0e7ac
F20110217_AABJRC smith_j_Page_115.tif
15a9791b54d5775b6f5bfe28d258f4a9
8e5792fa670ddc0827a1b373a2bfb4b765e4bbbf
F20110217_AABJQO smith_j_Page_097.tif
a236a2e69626e689dcb62a60f2ea5dee
8373699ca1491f02e2b9ab09923b16668e3a1d57
8320 F20110217_AABKUF smith_j_Page_070thm.jpg
45ec632f3b51d0e98488859af3aa049b
e8b382727392346ff8a30415d49782960bb09878
3738 F20110217_AABKTR smith_j_Page_056thm.jpg
31f402bda7fae0e664482581c782dfe4
6750280b508b1a2f30cc25997cd0678d52ec68b8
F20110217_AABJRD smith_j_Page_116.tif
961414f7448b62b219cb45892826e162
423ecadd750a0200a2b87623ee77633baf3d9f3a
F20110217_AABJQP smith_j_Page_099.tif
8c389cf384f2e8be5bbd540e52e94dcc
30362a0132787e1c9491e3cc017ce126c4dd7826
8099 F20110217_AABKUG smith_j_Page_071thm.jpg
e7eeec74225bb5e6500ac57113fc41d8
e0d656b543062b119daca2715145d02020def482
5276 F20110217_AABKTS smith_j_Page_057thm.jpg
53c91bcbfa6f37edf848954064cdb0dc
6ef6f32067d80ab3dd242b735f054a1dc88283a4
F20110217_AABJRE smith_j_Page_118.tif
731a5e6ea47524c49d6a46137ae64df4
5fc6d68006d33d068beb4ec2935386d98cc434cf
F20110217_AABJQQ smith_j_Page_100.tif
215f859eea3894d8dfe44d45afde2ca0
a44998bf7e407c2b2baa333fa8115439a737e019
7827 F20110217_AABKUH smith_j_Page_072thm.jpg
a462f24a7b380aaade6f6e1ba8091ad3
d2a69f24749e21bf97f43278cd2464e15551dbe5
4511 F20110217_AABKTT smith_j_Page_058thm.jpg
fd782073f96c2e796afb744a7caac63f
eeb19a89d2604cea18b7d5afb6d803919e8ce378
F20110217_AABJRF smith_j_Page_119.tif
2fda39f3a377c917499b663f762052cc
2b92d8d5bf2047dcce0c9cf059c75757127f31f1
F20110217_AABJQR smith_j_Page_103.tif
ba2336a21bc94c6dce1bfb9d62570c3a
07301817a3a8741a67fc397a6fcb3def2377ddc5
8140 F20110217_AABKUI smith_j_Page_073thm.jpg
6dda1d5106e4eebb6193a334a6a5efa6
4cfeaebb0203e4d1a3014b1234afc03be13f690f
5220 F20110217_AABKTU smith_j_Page_059thm.jpg
8bb57a44d6fc156a29dbf144c9311228
0806e92a5bccbc3d568daf920cf982931775ee52
F20110217_AABJRG smith_j_Page_120.tif
f6e0aebb862c894e70489dbc64126dc9
5b2cf724be93b54cdc894a9ae64423a790a619e7
F20110217_AABJQS smith_j_Page_104.tif
f3dbffe7a7a7cb0f890f919df043ab8b
551c17114bb5c5b809c71df9dc42905364efaa9d
8223 F20110217_AABKUJ smith_j_Page_074thm.jpg
a3c440a57d619e5415ab152f6b66a7a6
86ca8aa12d57a3936f000a2bc9f7ba6c2fb85da7
3635 F20110217_AABKTV smith_j_Page_060thm.jpg
78ac0f04a09de06bd7e08faf7270e25f
2da6ce2314873a98c5a68ed1789093ca2465fc27
F20110217_AABJRH smith_j_Page_121.tif
4c789f76d08517627526ca240562a65e
4a5af1be9cb87ec80d6addfe245585c6912c3f38
F20110217_AABJQT smith_j_Page_105.tif
4405baf51adc0aedd89c35c0576c3dc0
ff4540dea88ffba4d4a3f47a4768368eaad600bf



PAGE 1

MICROBIAL SUCCESSION ASSOCIATED WITH SOIL REDEVELOPMENT ALONG A SHORT-TERM RESTORAT ION CHRONOSEQUENCE IN THE FLORIDA EVERGLADES By JASON M. SMITH A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2006

PAGE 2

Copyright 2006 by Jason M. Smith

PAGE 3

For my mother.

PAGE 4

iv ACKNOWLEDGMENTS I would like to especially recognize Dr. Andrew Ogram, chair of my graduate committee, for his unconditional support, introducing me to microbial ecology, which has yet to cease fascinating me, and allowing me to pursue questions independently. Further, I am thankful for the financial support pr ovided to me from his grant money, and foremost for his moral support, and for being the kind of advisor you never want to disappoint. I would like to extend my gratitude to Drs. Nicholas Comerford and K. Ramesh Reddy, members of my graduate committee, for their helpful comments and advice during my studies. I am thankful to the Department of the In terior, the National Park Service, and the late Dr. Michael Norland for providing funding and access to research sites. I would like to extend my sincere gratitude to Dr. Hector Castro for his endless encouragement, truthful criticisms, and ma ny paid lunches. Mostly, I would like to acknowledge his influence on my understand ing of what it means to become an independent thinker, and his continued insist ence that I learn to a pproach questions and problems with tenacity. I wish to thank my current and former lab-mates, Drs. Abid Al-Agely, Ashvini Chauhan, Ilker Uz, and Yannis Ipsilantis, Puja Jasrotia, and Lisa St anley, for making long days in the lab more interesting. Special thanks go to Yun Cheng for her continued friendship throughout my te nure in the department.

PAGE 5

v I am grateful to all the people who were in strumental in the success of this study; including Drs. Kanika Sharma and Pa trick Inglett, Ms. Yu Wang, the Wetland Biogeochemistry Laboratory, for sampling coordination and biogeochemical data. Adrienne Frisbee and Isabela Claret Torres we re both instrumental in the completion of my studies involving gas chromatography. I want to thank the faculty, staff, and a ll graduate students in the Soil and Water Science Department for their support. Speci al thanks to go Dr. George OConnor for being a source of encouragement at th e beginning of my graduate studies. I would like to acknowledge the support of my colleagues at NASA Ames Research Center for their words of encour agement and helpful discussions. Dr. Brad Bebout and Ms. Mary Hogan are thanked fo r providing a method of nitrate analysis. I am greatly indebted to my brother Chris and my grandparents Herbert and Shirley Smith, for their love and encouragemen t. My mother, Debi, has been a constant source of support and encouragement throughout my academic career, and it is she whom I strive to make proud. Finally, I would like to thank my long time friends and unconditional supporters, who have made my time in Gainesville bear able, even through the hardest of times. I would like to especially thank Jared Ausani o, Adrienne Frisbee, Yvan Levesque, and Melissa Lott, for always making time for a b eer on the porch at the end of a rough day.

PAGE 6

vi TABLE OF CONTENTS page ACKNOWLEDGMENTS.................................................................................................iv LIST OF TABLES.............................................................................................................ix LIST OF FIGURES...........................................................................................................xi ABSTRACT.....................................................................................................................xiii CHAPTER 1 INTRODUCTION........................................................................................................1 The Hole-in-the-Donut.................................................................................................1 Microbial Indicators......................................................................................................3 Methanogenesis............................................................................................................6 Nitrification.................................................................................................................10 Denitrification.............................................................................................................16 Hypotheses and Objectives.........................................................................................20 2 STRUCTURE AND FUNCTION OF METHANOGENIC ASSEMBLAGES ALONG A SHORT-TERM REST ORATION CHRONOSEQUENCE....................27 Introduction.................................................................................................................27 Materials and Methods...............................................................................................29 Site Characteristics, Sample Collection, and Biogeochemical Characterization...............................................................................................29 Methane Production Potentials............................................................................30 Nucleic Acid Extraction and PCR Amplification...............................................30 Cloning and RFLP Analysis................................................................................31 Sequencing and Phylogenetic Analysis...............................................................32 T-RFLP Analysis.................................................................................................32 Diversity Indices..................................................................................................33 Results and Discussion...............................................................................................33 Methane Production in HID Soils.......................................................................34 Phylogenetic Characterization of Meth anogenic Assemblages in HID Soils.....35 T-RFLP Analysis of Methanoge nic Assemblage Structure................................37 Seasonal Structure of Methanogenic Assemblages.............................................37 Shifts in Methanogenic Assemb lages with Restoration Age..............................39

PAGE 7

vii Conclusions.................................................................................................................40 3 GENETIC AND FUNCTIONAL VARIATION IN DENITRIFIER POPULATIONS ALONG A SHORT-TERM RESTORATION CHRONOSEQUENCE...............................................................................................49 Introduction.................................................................................................................49 Materials and Methods...............................................................................................51 Site Characteristics, Sampling, a nd Biogeochemical Characterization...............51 Denitrifying Enzyme Activity and Gas Analysis................................................52 Nucleic Acid Extraction, PCR Amplification, Cloning and Sequencing............53 Phylogenetic and Diversity Analysis...................................................................54 Statistical Analysis of Phylogenetic Data............................................................55 Statistical Analysis of Biogeochemical Data......................................................57 Results and Discussion...............................................................................................57 Soil Biogeochemical Parameters Along the Restoration Gradient......................57 nirS phylogeny.....................................................................................................59 nirK phylogeny....................................................................................................60 Richness and Diversity of nirS and nirK Populations.........................................62 Population-Based Library Compositions............................................................64 Variance within nirK Clone Libraries.................................................................68 Conclusions.................................................................................................................71 4 SEASONAL DIVERSITY AND FUNC TION OF AMMONIA OXIDIZING BACTERIA ALONG A SHORT-TERM RESTORATION CHRONOSEQUENCE...............................................................................................79 Materials and Methods...............................................................................................82 Site Description, Sampling, and Bi ogeochemical Characterization....................82 Determination of Potential Nitrification Rates....................................................83 Extraction of Nucleic Acids and PCR.................................................................85 Cloning and Sequencing......................................................................................85 Phylogenetic Analysis.........................................................................................86 Statistical Analysis of Phylogenetic Data............................................................86 Statistical Analysis of Biogeochemical Data......................................................88 Results and Discussion...............................................................................................88 Biogeochemical Parameters of Soils Along the Restoration Gradient................88 Phylogenetic Analysis of amoA ...........................................................................90 Statistical Analysis of Clone Libraries................................................................93 Correlation of Differences in amoA Diversity With Environmental Variables..96 5 SUMMARY AND CONCLUSIONS.......................................................................104 APPENDIX A SUPPLEMENTAL TABLES...................................................................................109 Chapter 4...................................................................................................................109

PAGE 8

viii B SUPPLEMENTAL FIGURES..................................................................................110 Chapter 2...................................................................................................................110 Chapter 3...................................................................................................................111 Chapter 4...................................................................................................................113 LIST OF REFERENCES.................................................................................................114 BIOGRAPHICAL SKETCH...........................................................................................130

PAGE 9

ix LIST OF TABLES Table page 2-1 Geochemical parameters of dry and wet season soils...............................................42 2-2 Potential methanogenesis rates and accumulated CH4 in wet season soils...............43 2-3 Expected and observed phylotypes and diversity indices for dry season mcrA clone libraries...........................................................................................................43 2-4 Phylogenetic affiliation of mcrA T-RFs....................................................................44 3-1 Biogeochemical parameters of HID soils..................................................................72 3-2 Distribution of nirS sequences from each study site within designated phylogenetic clusters................................................................................................72 3-3 Values of nirS and nirK diversity and richness in HID soils.....................................73 3-4 Population similarity P values for co mparison of nirK and nirS clone libraries.......74 3-5 Corrected average pairwise differe nces and pairwise fixation indices for nirK ........75 3-6 Fixation indices, average pairwise differences, nucleotide diversity, and shared haplotypes of nirK clone libraries............................................................................75 4-1 Biogeochemical parameters of dry and wet season HID soils..................................98 4-2 Results of sequence analysis of amoA sequences obtained from dry and wet season soils...............................................................................................................99 4-3 Fixation indices, average pairwise differences, nucleotid e diversity, and unique haplotypes for wet and dry season amoA clone libraries.......................................100 4-4 Corrected average pairwise differen ces and pairwise fixa tion indices for dry season amoA sequences..........................................................................................101 4-5 Corrected average pairwise differen ces and pairwise fixa tion indices for wet season amoA sequences..........................................................................................101

PAGE 10

x 4-6 Results of Mantel correlation tests between pairwise diffe rences of population specific FST values for wet and dry season amoA clone libraries with biogeochemical parameters....................................................................................102 A-1 Population similarity P values for comparison of amoA dry and wet season clone libraries...................................................................................................................109

PAGE 11

xi LIST OF FIGURES Figure page 1-1 The Hole-in-theDonut restoration area....................................................................21 1-2 Pathways of autotrophi c nitrification and of denitrif ication and the nitrogen trace gases emitted............................................................................................................22 1-3 The major factors contro lling nitrifica tion in soils....................................................23 1-4 Schematic representation of nitroge n cycling in flooded soils and sediments..........24 1-5 The major factors control ling denitrification in soils................................................25 1-6 The basic arrangement of the nitrog en oxide reductases required for complete denitrification by a single organism.........................................................................26 2-1 Neighbor-joining mcrA tree for representative clones from April 2004 soils...........45 2-2 Distribution of mcrA sequences obtained from dry s eason soils within designated phylogenetic clusters................................................................................................46 2-3 Community dynamics for the mcrA gene in dry season HID soils determined by T-RFLP analysis.......................................................................................................47 2-4 Community dynamics for the mcrA gene in wet season HID soils determined by T-RFLP analysis.......................................................................................................48 3-1 Neighbor-joining tree of nirS sequences obtained from wet season soils.................76 3-2 Neighbor-joining tree of nirK sequences obtained from wet season soils................77 3-3 Sequence analysis of nirK clones obtained from wet season soils............................78 4-1 Cladogram of representative amoA sequences obtained from HID soils................103 B-1 Rarefaction curves for mcrA clone libraries...........................................................110 B-2 Potential denitrifica tion rates as a function of N2O-N production with time.........111 B-3 Rarefaction curves for nirS and nirK clone libraries..............................................112

PAGE 12

xii B-4 Rarefaction curves for amoA clone libraries from dry season and wet season soils.........................................................................................................................113

PAGE 13

xiii Abstract of Thesis Presen ted to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science MICROBIAL SUCCESSION ASSOCIATED SOIL REDEVELOPMENT ALONG A SHORT-TERM RESTORATION CHRONOSEQUENCE IN THE FLORIDA EVERGLADES By Jason M. Smith August 2006 Chair: Andrew V. Ogram Major Department: Soil and Water Science The Hole-in-the-Donut (HID) restoration program involves removal of non-native Brazilian pepper ( Schinus terebinthefolius ) from land within Everglades National Park. The restoration approach i nvolves complete clearing of Schinus and removal of topsoil down to bedrock. Subsections within the HI D are cleared at diffe rent times, creating a series of sites at different stages of recove ry. As the direct linkage between nutrients retained in parent material and plant roots, soil development in newly cleared sites will be essential to successful reestablishment of plant communities and biogeochemical linkages. Establishment of microbial co mmunities will precede plan t colonization. As the primary mediators of biogeochemical cy cling of carbon and nitrogen, ecology of microorganisms responsible for key roles in nut rient cycling in developing HID soils may provide insights into the reestablishmen t of biogeochemical linkages with soil redevelopment, the recovery stage of each site and whether the direction of recovery is towards that of an undisturbed wetland ecosystem. Methane production potentials

PAGE 14

xiv suggest hydrogen as the dominant methanogeni c precursor. Further, highest methane production was observed from most recently re stored sites; data suggest decreased contribution of methanogenesis to anaerobic mineralization with restoration age. Molecular analyses indicate th e presence of all major meta bolic groups of methanogens in all sites. Methanogenic communities we re stable between seasons; however, both cloning and T-RFLP analyses indicated shifts within the Methanobacteriales with restoration age. Denitrifying bacterial communities were active in all study sites. Phylogenetic analyses of genes associated with nitrite reduction indicate the presence of unique lineages in soils from all sites. Iter ative statistical analyses of clone libraries suggest different disturbance response re gimes of groups harboring different genes encoding for the same enzyme. nirS genotypes suggest an appr oximately linear response of diversity to restoration age, while nirK analyses suggest a biomodal response with restoration age. Nitrifying bacterial populations were activ e in both seasons, although rates decreased significantly in wet season soils. Mol ecular analyses suggest two genotypes of nitrifiers to domi nate restored and undisturbed soils, and each site harbors unique distributions of the genotypes. Pairwi se differences in diversity between sites were strongly correlated with soil oxygen demand. Collect ively, these data indicate compositional shifts in microbial populations associated with carbon and nitrogen cycling in the context of soil redevelopment and restor ation age, and provide significant insights into the response of specific microbial popula tions to severe dist urbance and recovery.

PAGE 15

1 CHAPTER 1 INTRODUCTION Ecosystem disturbance involves an even t occurring over a relatively discrete space and time that alters the physical environm ent, leading to change s in the structure of populations and communities, de nsity of biomass, spatial distribution of biota, and resource availability (Walker and del Moral, 2003). The types of disturbance imposed upon an ecosystem are grouped into four majo r categories, as outlined by Walker and Willig (1999); they include earth, air, water, and fire. The four disturbance classes are related to natural processes, such as the move ment of tectonic plates and the interplay of climatic, topographic, and soil factors, for example: hurricanes, wild fires, volcanic eruptions, and land slides (Walker and Willi ng, 1999). An additional category involves those disturbances imposed upon the environmen t by the activities of humans, such as agricultural activity, deforesta tion, and urbanization. The im pacts of human activity are apparent in all of the Earths biomes; it is most often human activity that leads to ecosystem disturbance or restoration (McKi bben, 1989). Many of the modern instances of an ecosystem undergoing primary succession are either directly anthropogenic in origin or influenced to some de gree by human activities (Walker, 1999). The Hole-in-the-Donut The Hole-in-the-Donut (HID) is a 4000-ha region within Everglades National Park (ENP), Florida, USA (Figure 1-1). Once consisting of oligotrophic sawgrass ( Cladium jamaicense Crantz) prairies and short h ydroperiod pinelands, the HID was subjected to agricultural land use practices from 1916 to 1978 (Dalryample et al., 2003).

PAGE 16

2 When farming activity stopped, the HID was le ft as an abandoned, high nutrient, high oxygen environment (Aziz and Sylvia, 1995). The abandoned farmland within the HID was invaded by Schinus terebinthifolius Raddi (Brazilian pepper), an exotic shrub native to Brazil, Argentina and Paragua y (Mytinger and Williamson, 1987). Schnius terebinthifolius formed dense thickets of shrubs ove r the most intensely farmed portions of the HID, which were resi stant to common management pr actices (Dalrymple et al., 2003). Restoration efforts initiated by ENP bega n in 1996 and involve complete removal of all plants and much of the soil down to the consolidated oolithic limestone bedrock (Li and Norland, 2001). Following restoration, the most recently restor ed areas of the HID initiate primary succession, by colonization of bare substrate by plant and microbial communities. Cleared transect s are left undisturbed to al low the reestablishment of native wetland plants and mi crobial communities. HID restoration has been done systematically in specified areas, resulting in regions in different stages of recovery, creating a short-term chronos equence of sites at differe nt stages of recovery. The disturbance caused by complete soil removal is of the severest nature, resulting in surface denudati on and little to no biological legacy of the previous ecosystem (Walker and del Moral, 2003). T hus, each newly cleared site will immediately enter the primary stages of ecological re-d evelopment and primary succession. The rates of successional change and the number of states between surface recolonization and stability are not known, and can not be predicted for one part icular ecosystem. Changes of state will be controlled th rough interactions of the biota with the physical environment and thus may not occur in a manner previous ly observed (Odum, 1969; Walker, 1999).

PAGE 17

3 However, several characteristics of devel oping ecosystems, as outlined by Odum (1969) may provide insight into how the HID recovery will progress. Initially, newly restored sites will be characterized by open nutrien t cycles, low productivity, and communities structured as a result of the random coalesci ng of individuals. As succession progresses, communities will be predictably structured and stratified by ecological function, and nutrients will be recycled and retained in biomass. Changes in recovery states will be biologically controlled, o ccur in a predictable manner, and result in a progressively more stable ecosystem. The stable ecosystem will contain maximum biomass and harbor communities that interact symb iotically to sustain function. The relatively short timespan for recovery between restoration sites in the HID provides an excellent opportunity to investigate the application of classical theories of ecosystem development over time periods for which the direction and rate of recovery is not known. Microbial Indicators Microorganisms mediate nutrient cycli ng in terrestrial ecosystems and are an integral part of soil quality. Bacteria maintain the greates t population numbers per gram soil than any other organism. Separated from their environment by little more than their cell membranes, they are very sensitive to environmental conditions (Tate, 1995; Hill et al., 2000). Gross activities of soil microorganism s, such as respiration and biomass, have been commonly used as indicators of soil quality (termed proce ss-level indicators) (DAngelo and Reddy, 1999; Wander and Bolle ro, 1999; White and Reddy, 1999; Wright and reddy, 2001; Sjogersten and Wookey, 2002). For instance, observed reductions in soil microbial biomass and respiration have been correlated with soil subjected to nutrient enrichment, loss of organic matter, a nd heavy metal pollution (Jenkinson, 1988; Frostegard et al, 1993; Arunachalam a nd Melkania, 1999; Kandler et al., 2000).

PAGE 18

4 Extracellular enzyme activ ities, such as alkalin e and acid phosphatases and glucosidase, have been correlated with nut rient cycling and lim itation, productivity, and xenobiotic degradation (Tate, 1995; Prenger and Reddy, 2004). Process-level indicators do not reflec t dynamics within the soil microbial community. An understanding of the physio logy and population dynamics of certain functional groups of microbes can provide clue s about the efficiency of biogeochemical cycling within an ecosystem. Temporal changes in soil microbes and their functions occur in response to changes in biotic and abiotic properties at a site (Walker and del Moral, 2003). Changes in microbial co mmunity structure may precede changes in communities of higher organisms. For this r eason, studies of the dynamics of functional components of microbial communities unde r various conditions have attracted considerable attention by ecologist s (Kennedy, 1999; Hill et al., 2000). Schimel and Gulledge (1998) presente d cases in which ecosystem function appears to result from differences in microbi al community structure. The ability of environmental factors to c ontrol species and functiona l group structure has been demonstrated in the northern Everglades (Castro et al., 2002). One approach to investigating compositions of functional gr oups of microorganisms is to analyze the distribution of functional genes from genomic DNA extracted from soils. The functional genes maintained by an organism define its interaction with the environment; thus, functional gene ecology provides informa tion on the potential occurrence of the processes associated with these genes. Molecular biological tools applied to study natural assemblages of microorganisms have allowed phylogenetic or functional level

PAGE 19

5 identification of indigenous microbial comm unities in the context of spatio-temporal variation, land use types, and different environments (Palumbo et al., 2004). Molecular and biogeochemical approaches have been applied to understand the response and recovery of ecosystems subjecte d to disturbance. Microbial community structure has been shown to change in re sponse to secondary succession of grassland soils (Kowalchuk et al., 2000), al ong plant diversity gradient s occurring in response to nutrient enrichment (Carney et al., 2004) in wetland soils exposed to varying concentrations of dairy effluent (Ibek we et al., 2003), and along a phosphorous enrichment gradient in the Florida Everglad es (Castro et al., 2002; Castro et al., 2004; Chauhan et al., 2004; Castro et al., 2005; Chauhan and Ogram, 2006). Much work has been done on process-level indicators of ecosystem nitrogen loss during primary succession (Robertson and Vitousek, 1981; R obertson, 1982; Vitousek et al., 1989). However, little is known about the microbial communities mediating these processes, or how they are affected by the various fact ors imposed upon them during recovery. The occurrence of primary succession is a relatively uncommon event; few natural or anthropogenic disturbance events ar e severe enough to completely remove both soil and plant communities, leaving bare substrate. The HID provides a unique opportunity to investigate the dynamics of bi ogeochemical processes and their microbial mediators in concert with soil formation a nd accretion. As the direct linkage between nutrients retained in parent material and plant roots, the development of soil in newly cleared sites will be essential to successful reestablishment of plant communities and biogeochemical linkages. The establishment of microbial communities on newly cleared surfaces will likely precede the development of plant communities. Microbial activity

PAGE 20

6 will lead to the destruction of parent material and release of nutrients, as well as a source of new nutrients, through fixation of nitrog en and carbon. As the primary mediators of biogeochemical cycling of carbon and nitrog en, investigation in to the ecology of microorganisms responsible for key roles in nut rient cycling in developing HID soils may provide insight into the reestablishmen t of biogeochemical linkages with soil redevelopment, the recovery stage of each site and whether the direction of recovery is towards that of an undisturbed wetland ecosystem. Nutrient recycling and retention within HID restoration sites should grow more efficient with the development of soil and plant communities. Microorganisms are relatively short-term sinks for soil nutrients, and can also play an integral role in ecosystem nutrient loss. Trace gas loss of nutri ents due to respiratory activity of soil microbial communities may significantly alter the rate at which biogeochemical linkages and nutrient use efficiencies are reestablis hed. Carbon loss in gaseous form may occur through heterotrophic respirati on or methanogenesis. Nitr ogen loss may occur through leaching of nitrates produced during nitrification, or in ga seous forms due to the activity of both ammonia oxidizing bacteria and heterotr ophic denitrifying bact eria (Figure 1-2). An understanding of the activ ity and ecology of the microbial groups mediating ecosystem nutrient loss may provide significan t insights into the na ture and state of nutrient recycling and reten tion in developing sites. Methanogenesis The concentration of methane (CH4) in Earths atmosphere is approximately 1.8 parts per million (ppm) by volume, much less than that of carbon dioxide (CO2); however, a molecule of CH4 is approximately 20 times more potent as a green house gas than one of CO2 (Chapin III et al., 2004). Approximately 80% of atmospheric methane is

PAGE 21

7 derived from freshwater environments, the va st majority from biogenic sources such as plants and methanogenic bacteria. Methane is produced in greatest quantities under anaerobic conditions, such as those present in wetlands. Wetland ecosystems are among the most important natural sources of methane to the atmosphere; they emit approximately 22% of total methane (90 x 106 metric tons per year). Other natural sources, such as rice paddy fields, landf ills, and ruminants follow closely behind (Cicerone and Oremland, 1988). Methanogenic bacteria belong to the Ar chaeal domain, characterized by extreme phenotypes such as methanogens, halophile s, and thermophiles (De Long, 1992). Methanogens are a specialized group of obligate anaerobes th at use a narrow range of electron donors for the reduction of CO2 to methane, namely H2, acetate, formate, and a limited range of methyl compounds. The major ity of isolated meth anogens exhibit the ability to grow on H2 and CO2, several species utilize methyl compounds and formate, and a relative few utilize acetate as an electron donor (Garcia et al., 2000). In freshwater and terrestrial ecosystems, methanogenesi s occurs through reduc tion of acetate, CO2 and formate (Schutz et al., 1989). In these ecosyst ems, the majority of methane is thought to come from acetoclastic methanogens (Conr ad, 1999; Wolfe, 1996). In sulfate-rich marine ecosystems, where methanogens are ou t competed by sulfate reducing bacteria for resources, methyl compounds are non-competitive precursors of methanogenesis (Madigan et al., 1996). Methane production has been characteriz ed from a variety of natural sources, including geologic deposits, te rmites and ruminants, freshwater and oceanic sediments, and wetlands. Major anthropogenic sources are fossil fuel use, waste management

PAGE 22

8 (landfills), animal husbandry, and rice paddy soils. A great amount of work has been done to characterize methane sources a nd sinks in the natural environments. Strict nutritional and cultiv ation requirements and slow growth make the isolation and characterization of methanogens cumberso me. Therefore, most recent research on their ecology has been based on cultivati on independent molecular methods. The two most common molecular markers used to study the ecology of methanogens are 16S ribosomal RNA (rRNA) and methyl coenzyme M reductase (MCR) genes. However, primers previously developed to specifi cally target methanogen 16S rRNA genes by Marchesi et al. (2001) were later determined to be limited in range (Luton et al., 2002). Thus, the most effective way to study metha nogens using 16S rRNA genes is to sequence exhaustively or maintain enrichment cultures. Alternatively, the methanogen-specific mcr functional gene has been used as a molecular marker to study the distribution of methanogens in a variety of environments. MCR is an enzyme specific to methanogens that catalyzes the final step in methane production, the reduction of methyl-coenz yme M to methane (Thauer, 1998): CH3-S-CoM + HS-CoB CoM-S-S-CoB + CH4 HS-CoM represent coenzyme M and HS-CoB represents coenzyme B. The genes mcrA mcrB and mcrG are included in the mcrBDCGA transcriptional unit, which encodes the , and subunits of MCR. The functions of mcrD and mcrC gene products are not known. Two isozymes of MCR have been identified, and their expression correlated with growth stages. MCRI is synthesized during less active and stationary phase growth and MCRII duri ng exponential growth (Reeve, 1992). Additionally, some metha nogens of the orders Methanobacteriales and Methanococcales

PAGE 23

9 contain an additional isozyme of methyl coenzyme-M reductase, termed Mrt (MRT). The MRT operon is arranged as either mrtBDA or mrtBGA (Thauer, 1998). The expression of either MCR or MRT is depende nt on growth stage or oxidative stress (Ferry, 1999). There is strong evidence for the evolution of the mcrA gene from a single common ancestor (Springer et al., 1995; Garcia et al., 2000 ; Luton et al., 2002), making phylogenetic approaches to studying methanoge ns relatively simple. Additionally, the three broad groups of substrate user s, the acetotrophs, methylotrophs, and hydrogenotrophs, form distinct phylogenetic clusters associated with their metabolic potential. Thus, genetic data can often be used to infer metabolic capabilities of methanogens inhabiting an environment. However, potential biases of PCR primers targeting mcrA have been reported, and must be ta ken into account upon interpretation of mcrA sequence data in an ecological context (Luton et al., 2002; Lu eders and Friedrich, 2003). Those designed by Luton et al. (2002) are the most widely spanning, meaning they have shown the ability to amplify genes from all orders of methanogens. However, the affinity of these primers to wards hydrogenotrophs of the orders Methanobacteriales Methanomicrobiales and Methanococcales may prove problematic when they are employed to investigate the full metabolic potential of methanogens within an environment (Luton et al., 2002; Lueders a nd Friedrich, 2003; Castro et al., 2004). Information on the ecology and function of methanogenic assemblages in the developing soils along the HID chronosequence will provide significant insights into the efficiency and state of nutrient cycling within the system. For instance, the occurrence of methanogenesis in environments harboring hi gh concentrations of more energetically

PAGE 24

10 favorable terminal anaerobic electron accepto rs was attributed to non-steady state conditions, at which methanogens were able to compete for resources with other functional groups previously shown to preclud e their activity (Roy et al., 1997). Further, methanogenesis is the final step in anaerobi c carbon mineralization, a nd generally occurs through two major metabolic pathways; the de gree and nature of methanogenic activity through each of these respective pathways may provide insight into the function and efficiency of microbial guilds me diating degradation of higher carbon. Nitrification Nitrification is the oxidation of ammonia (NH3) to nitrite (NO2 -) and subsequently to nitrate (NO3 -), most of which is carried out by a restricted group of nitrifying bacteria. The resultant effects of nitrification on ecosystem function are well documented. The initial oxidation of ammonium (NH4 +) to nitrite produces two moles of H+ per mole of NH4 + consumed, leading to pH shifts in so ils and possible losses in quality. Loss of ecosystem nitrogen due to nitr ification occurs by three genera l mechanisms (Chapin III et al., 2004). First, the production of nitrate fuels denitrificat ion, the main loss mechanism of fixed N. Second, cationic nitrate is much mo re mobile in most soils, and thus presents a greater risk for loss due to leaching. Finally, some evidence exists for abiotic transformation of nitrite to gas, termed chemodenitrification (R eddy and Patrick, 1984; Kowalchuk and Stephen, 2001). Conversel y, ammonia oxidizing bacterial (AOB) activity is often harnessed for the benefit of wastewater treatment facilities (Laanbroek and Woldendorp, 1995). Two classes of bacteria able to produ ce oxidized N compounds exist in nature, and differ by their carbon source. Heterotrophic nitrifiers gain their energy from the decomposition of organic matter. Many he terotrophic fungi and bacteria, including

PAGE 25

11 actinomyctetes, are able to produce either NO2 or NO3 from NH4 + (Chapin III et al., 2004). While their contribution to nitrate pr oduction has been observed in nature, their role in nitrification is negligible in most ecosystems; however, significant rates have been observed in some acidic soils (Schimel et al., 1984; Killham, 1990). Autotrophic ammonia oxidizers (AOB) fix carbon for bi omass using energy gained from ammonia oxidation. Most AOB are oblig ate aerobes, but some stra ins have demonstrated the ability to proliferate under low oxygen concentrations (Laanbroek and Woldendorp, 1995). Within the AOB are two groups, one th at converts ammonia to nitrite and another that converts nitrite to nitrate. These tw o groups occur together in most ecosystems, NO2 does not generally accumulate in soils. Nitrite accumulation has been observed in soils from extremely dry savannahs and heavily fert ilized farmlands (Chapin III et al., 2004). Those autotrophic organisms responsible for th e conversion of ammonia to nitrite will be the subjects of this review. Availability of NH4 + is the most important determinant of nitrification rates (Robertson, 1989) (Figure 1-3). Concentrations must be high enough for nitrifiers to compete with other soil microbes; this is particularly important to autotrophic nitrifiers, which rely on NH4 + as their sole source of energy. Significant nitrification rates have been observed in soils with relatively low NH4 + concentrations in bulk soils, perhaps due to spatial heterogeneity. Nitrification is thought to be limited to circumneutral conditions. Bacterial cell membranes are only pe rmeable to ammonia, rather than anionic ammonium, and thus the process is favored in non-acidic cond itions (Laanbroek and Woldendorp, 1995). Significant nitr ification rates measured in acid soils are attributed to the presence of near-neutral microsites where AOB can thrive. Their existence in acid

PAGE 26

12 soils may be stimulated by urea, which can pr ovide substrate to AMO at low pH (Bothe et al, 2000). Other factors controlling AOB activit y in soils are oxygen concentrations (moisture) and plant communities (Figure 1-3). Soil moisture directly affects O2 concentrations of the soil atmosphere, as well as microbial metabolism. While some metabolic activity in pure cultures of Nitrosomonas europaea was evident under anaerobic conditions, AOB activity is genera lly thought to cease under highly anaerobic conditions (Stuven et al., 1992) In water-logged soils, AOB abundance is significantly higher in the rhizosphere of plants with aer enchymous root tissue (Reddy and Patrick, 1984; Reddy et al., 1989; Uhel et al., 1989) (Fig ure 1-4). It is still unknown whether the influence of vegetation on AOB activity is due to allelochemical inhibition (Rice and Pancholy, 1972), decreasing ammonium availabi lity due to immobilization, or factors yet to be determined (Stienstra et al., 1994). In most ecosystems, AOB constitute a small portion (<<1%) of the total bacterial population. However, AOB play a unique role in global N cycling. Their abundance and distribution in the environment is important to ecologists. The monophyletic nature of AOB in terrestrial and freshwater environments facilitates the use of molecular biological approaches in studying their ecology. Molecula r and process level-indicators have been paired in a variety of terrest rial and freshwater environmen ts, such as lakes, forest-tomeadow transects, estuaries, contaminated ground water wells, and waste treatment bioreactors (Rotthauwe et al., 1997; Kowalc huk and Stephen, 2001; Minitie et al., 2003; Araki et al., 2004; Carney et al., 2004; Bernhard et al., 2005).

PAGE 27

13 Taxonomically, we know of three distin ct groups of autotrophic AOBs, two monophyletic lineages of obligate aerobes with in the betaand gammaproteobacteria and anaerobes within the Planctomycetales (n ot addressed in this review) (Head et al., 1993; Teske et al., 1994; Purkhold et al ., 2000). Based on 16S rRNA gene sequence analysis, we know of two AOB lineages with in the proteobacteria. AOB of the genus Nitrosococcus are found within gamma-proteobacteria, and have been isolated exclusively from marine environments (Alz erreca et al., 1999), and a closely related grouping of the genera Nitrosomonas (including Nitrosococcus mobilis ) and Nitrosospira comprise a monophyletic cluster within the be ta-proteobacteria, all of which have been isolated from terrestrial or freshwater environments (Purkhold et al., 2000). Much of the initial knowledge ga ined about AOB ecology and phylogeny stemmed from isolation of pur e cultures. Inherent biases associated with all culture techniques may limit the characterization of in situ community diversity (Amann et al., 1995; Klotz and Norton, 1995). Further, the slow growth rates of AOB make them difficult to culture, as cultivation generally selects for faster growing organisms. As a result, early studies of AOB ecology in soils suggested a dominance of Nitrosospira populations over Nitrosomonas in most terrestrial envi ronments (Belser, 1979). Not until the development of 16S rRNA gene primers by McCaig et al. (1994) specifically targeting AOB did significant pa tterns of ecological distribution become apparent. Primers specifically targeti ng AOB 16S rRNA genes allowed phylogenetic inventories to be constructed in various environments. Further, the degeneracy of these primers permitted the amplification of their target, but also of closely related relatives, allowing for the recovery of novel members of the AOB clades (K owalchuk and Stephen,

PAGE 28

14 2001). However, such degeneracy has led to the recovery of sequences outside of the target clade, sometimes as great as 70 to 100% of total sequences obtained (Kowalchuk et al., 1999). Initial phylogenetic characterization of AOB 16S rRNA genes recovered from soils and marine environments divided beta-p rotebacterial AOB into seven clusters ( Nitrosospira clusters 1 to 4; Nitrosomonas clusters 5 to 7). (Stephen et al., 1996; Purkhold et al., 2000). Nitrosospira spp. of clusters 2, 3, and 4 are thought to dominate soils (Kowalchuk et al., 1998; St ephen et al., 1998; Kowalchuck et al., 1999). Patterns of ammonia oxidizer 16S rRNA clones obtained from various soils were strongly correlated with acidity, with cluster 2-type AOB most frequently recovered from acidic soils (Stephen et al., 1998; Kowalc huk et al., 2000). Cluster 3 Nitrosospira spp. have recovered from young and early successional so ils with high ammoni um concentrations (Kowalchuck et al., 2000) a nd untilled soils (Bruns et al., 1998), while cluster 4 organisms dominated older and late succes sional soils (Kowalchuck et al., 2000). Nitrosospira cluster 3 and Nitrosomonas cluster 7 AOB dominate d agricultural fields subjected to intense fertilizati on (Webster et al., 2002; Webster et al., 2005). In general, Nitrosomonas spp. are more frequently isolated fr om high nutrient environments, such as sewage sludge and wastewat er (Rotthauwe et al., 1997; Purkhold et al., 2000). Nitrosmonas strains have been described as r strategists, with low substrate affinities and high maximum activity compared to K strategists Nitrosospira (Andrews and Harris, 1986; Schramm et al., 1998; Schramm et al., 199 9). Phylogenetic surveys of AOB in the environment suggest strong correlations betw een community structure and environment; to date no study has direc tly correlated abundance of AOB 16S rRNA sequence types

PAGE 29

15 with nitrification rates (Kow alchuk and Stephen, 2001). Furt her, the physiological basis for observed difference in AOB sequence types is unknown. Alternatively, primers developed to targ et the gene encoding the alpha subunit of the ammonia monooxygenase enzyme (AMO) have been applied for study of AOB ecology. AMO catalyzes that first and rate limiting step, the conversion of ammonia to hydroxylamine (Hollocher et al., 1981): NH3 + O2 + 2e+ 2H+ NH2OH + H20 Hydroxylamine is then oxidized to nitr ite in an energy yi elding dehydrogenase reaction (McTavish and Hooper, 1993). The amoCAB operon is transcribed to form a 3.2 kb RNA (Hommes et al., 2001). amoA encodes the 32 kDa acetelyene binding protein of AMO; to date, the functions of the amoB and amoC genes are unknown (Stein et al., 2000). The amoA gene can serve as a useful target for environmental studies, since it reflects the 16S rRNA phylogeny of beta-subcl ass AOB very well (Purkhold et al., 2000; Kowalchuk and Stephen, 2001), provides a hi gher degree of sequence variation and greater phylogenetic resolution of closely re lated ecotypes (Rotthuw ae et al., 1997). In recent years, amoA diversity has been investigated in a wide variety of natural environments, including soils, sediments, pl ant roots, groundwater, marine and fresh waters, and estuaries (Stephen et al., 1996; Rotthuwae et al., 1997; Kowalchuk et al., 1998; Stephen et al., 1998; Kowalchuk et al., 1999; Kowalchuk and Stephen, 2001; Avrahami et al., 2002; Carney et al., 2004). The activity of AOB has been studied extensively in the context of primary succession (Rice and Pancholy, 1972; Robert son and Vitousek, 1981; Robertson, 1982;

PAGE 30

16 Robertson, 1989; Vitousek et al ., 1989). Nitrifica tion has been implicated as the major source of N loss in developing terrestrial ecosystems (Robertson and Vitousek, 1981; Vitousek et al., 1989). The seasonally i nundated nature of the HID may provide enhanced conditions for N loss potential. Ammonium accumulation in the wet season may provide enough substrate for significant n itrification activity during the dry season. High nitrification in the dry season will lead to loss of N due to leaching, and possibly fuel significant denitrifica tion in the wet season. Further, both physiological and molecular responses of AOB to differences in soil parameters have been documented, and the presence or absence of certain genotypes correlated w ith differences in resource availability. An understanding of the struct ure and function of AOB in HID soils may provide insight into the potential for N loss at each stage of recovery and the efficiency of N use within the developing soils. Denitrification Nitrate respiration can occu r through two dissimilatory pathways. The first, reduction of NO3 or NO2 to NH4 +, occurs widely but is not co nsidered denitrification in the strict sense. Denitrification is the di ssimilatory reduction of nitrate or nitrite to oxidized gaseous forms of nitrogen (either nitr ic or nitrous oxide), which may be further reduced to dinitrogen gas (N2). As the major loss mechanism for fixed nitrogen from the biosphere, denitrification plays a crucial role in the balance of the global nitrogen cycle. Significant rates of denitrification may be of consequence in nitrogen limited and agricultural ecosystems. However, it is also a significant source of atmospheric N2O, a greenhouse gas involved in stra tospheric ozone depletion (Chapin III et al., 2004). Several factors control denitrifying enzyme activity (DEA) in so ils (Figure 1-5). Oxygen and moisture levels, temperature, a nd organic carbon availa bility are the most

PAGE 31

17 influential factors on DEA (Knowles, 1982). Mo isture content indirectly controls the availability of both oxygen and orga nic carbon; slowed diffusion of O2 leads to decreased heterotrophic activity. DEA is often highest in facultative soils with renewable supplies of organic carbon, such as periodically i nundated wetlands, tidal ma rshes, and riparian zones. The ability to denitrify is widespread among bacteria of unrelated systematic affiliation, most likely due to lateral gene transfer events (Zumft, 1997). Although it is a facultative process, the capacity for denitrif ication is almost excl usively expressed in Eubacterial strains capable of aerobic growth. Prokaryotes constitute the vast majority of organisms capable of denitr ification, although a number of fungal isolates have demonstrated the ability, but with minima l cellular energy gained (Kobayashi et al., 1996; Shapleigh, 2000). Many prokar yotes identified as denitrifiers have the ability to couple both O2 and NO3 reduction to ATP synthesis; energy yields from nitrate respiration are similar to thos e gained by aerobic respiration. Complete reduction of nitrate to dinitr ogen gas requires a suite of four enzymes (Figure 1-6). The second step is the conve rsion of nitrite to n itric oxide by nitrite reductase (NIR). As the first gas-generating st ep, it is the defining st ep of denitrification, and will be the focus of this review (for more details on the molecular basis of denitrification see Zumft, 1997). The NIR reaction is complemented by the activity of two distinct metalloenzymes, one with a copper center (CuNIR) and the other with a heme-based cytochrome (Fe-NIR). Both forms of the enzyme occur in the periplasm and appear to be functionally re dundant (Coyne et al., 1989; Gl ockner et al., 1993). Cu-NIR is more widely distributed within proka ryotes, including both archaebacteria and

PAGE 32

18 Eubacteria, while Fe-NIR is more widely spread across environments, but found only in Eubacteria (thus far) (Bothe et al., 2000). Fe-NIR occurs in proteobacteria at a much greater frequency relative to ot her Eubacterial groups; type stra ins from four of the five major proteobacteria sub-classes (alpha, beta delta, epsilon) have been characterized. Currently, no Fe-NIR containing organisms have been identified in the gamma sub-class. To date, there is no apparent agreement in the phylogenetic dist ribution of the two enzymes types with 16S rRNA gene phylogenies of the harboring organisms (Shapleigh, 2000). Genes encoding both NIR enzymes are not fully understood. Fe-NIR genes from Pseudomonas aeruginosa were adjacent, while those in Pseudomonas stutzeri were rearranged into three differen t transcriptional units (Palme do et al., 1995). Comparison of four Cu-NIR containing bacteria reve aled a single conserved gene. However, quantities of DNA required to encode Fe-NIR and Cu-NIR is significantly different (Shapleigh, 2000). The phylogenetically diverse nature of de nitrifying bacteria makes the design of 16S rRNA group-specific probes impossible. Thus, molecular ecological studies of the distribution of denitrifying b acteria always target functi onal genes and their products. Highly conserved regions of genes involved in denitrification ha ve allowed for the development of group-specific primers. Fe-NIR and Cu-NIR are encoded by nirS and nirK genes, respectively. DNA sequences encoding the two enzymes share little sequence homology; thus, probes specific to eac h gene have been developed (Braker et al., 2000). Because of their role in the gas-producing step of denitrification, nirK and

PAGE 33

19 nirS are most often employed in ecological studies of denitrifier dist ribution (Michotey et al., 2000; Yan et al., 2003; Santoro et al., 2006). The exact environmental factor s affecting the distribution of nirS and nirK containing organisms in the environment are not fully understood. The ubiquity of the gene, along with its high late ral transfer rate, makes phyl ogenetic characterization of denitrifying bacterial communities difficult. However, the responses of one or both genotypes to environmental conditions have been reported. A previous characterization of nirS and nirK diversity in forested upland and wetland ecosystems was only able to recover nirS in upland soils, while both were pr esent in wetland soils (Priem et al., 2001); the actual environmental reasons for the observed pa tterns were not apparent. More often, both genes are detected within an environment, but the response of the organisms harboring them is different. Liu et al. (2003) re ported a greater response of nirK than nirS containing denitrifiers in marine sediments; nirK diversity correlated strongly with nitrate availability, while nirS diversity was correlated with oxygen concentrations. Instances of differing responses to the same environmental factor have also been observed. Santoro et al (2006) reported a gr eater response of nirK to nitrate concentrations in ground waters. nirS diversity was still indica tive of response, but less pronounced, a greater degree of overlap between genotypes along the ni trate gradient was observed. Thus, investigation into th e diversity and populat ion structure of nirS and nirK in association with shifts in biogeochemical processes in HID soils may provide insight into the state of N cycling, the potential fo r gaseous N loss, and factors controlling the response of organisms harboring functionally redundant enzymes.

PAGE 34

20 Hypotheses and Objectives The central hypothesis of this study is that an understanding of microbial assemblages associated with carbon and nitroge n cycling and the measurement of certain forms of carbon and nitrogen can be used to assi gn value to restoration efforts in the HID, and predict the rates of ecologically important processes regulating av ailability. Specific hypotheses to be tested include: (i) soil redeve lopment will lead to the establishment of methanogen, denitrifying, and ammonia oxi dizing microbial comm unities which will grow more predictably consiste nt in structure with restoration age; and (ii) seasonal variations in methanogenesis, denitrifica tion, and ammonia oxidation rates will reflect observed differences in community structure and restoration age. The main objectives of this investigation are to: (i) identify spatial and temporal changes in community structure of microor ganisms associated with methanogenesis, denitrification, and ammonia oxi dation; and (ii) monitor the relevant biogeochemical processes associated with methanogenesis, denitrification, and ammonia oxidation in restored and undisturbed wetlands. Investig ation of the dynamics of these microbial communities may provide insights into the reestablishment of biogeochemical linkages with soil redevelopment, the recovery stage of each site, and whet her the direction of recovery is towards that of an undisturbed wetland ecosystem.

PAGE 35

21 Figure 1-1. The Hole-in-th e-Donut restoration area.

PAGE 36

22 Dissolved Organic Nitrogen NH4 +NO2 -NO3 -NO N2O N2 Assimilatory Nitrate Reduction to Ammonium (ANRA)NO N2O NO N2O N2 NO2 -Ammonification (Mineralization) Nitrification Denitrification Process Optimal environmentsWarm, moist High oxygen ANRA: High carbon Low nitrogen Low oxygen High carbonDissolved Organic Nitrogen NH4 +NO2 -NO3 -NO N2O N2 Assimilatory Nitrate Reduction to Ammonium (ANRA)NO N2O NO N2O N2 NO2 -Ammonification (Mineralization) Nitrification Denitrification Process Optimal environmentsWarm, moist High oxygen ANRA: High carbon Low nitrogen Low oxygen High carbon Figure 1-2. Pathways of autotrophic nitrificat ion and of denitrification and the nitrogen trace gases emitted by these pathways. Adapted from Chapin et al. (2004).

PAGE 37

23 NH4 +availability O2availability Interactive controls Indirect controls Direct controls State factorsBIOTA TIME PARENT MATERIAL CLIMATE Plant functional types Soil Resources Plant NH4 +uptake Litter quality Carbon quality Respiration microbial/root Temperature H2O Soil texture NITRIFICATION LONG-TERM SHORT-TERMNH4 +availability O2availability Interactive controls Indirect controls Direct controls State factorsBIOTA TIME PARENT MATERIAL CLIMATE Plant functional types Soil Resources Plant NH4 +uptake Litter quality Carbon quality Respiration microbial/root Temperature H2O Soil texture NITRIFICATION LONG-TERM SHORT-TERM Figure 1-3. The major factors c ontrolling nitrification in soils. Thickness of the arrows represents the strength of effects. Bl ack arrows represent positive influences and white arrows represent negative influences. Adapted from Chapin III et al. (2004).

PAGE 38

24 Figure 1-4. Schematic representation of nitr ogen cycling in flooded soils and sediments. Inset depicts diffusion processes occurring at the root-soil interface. Adapted from Reddy and Patrick (1984). N2N2O Denitrification Leaching N2N2O NH3 NO Chemical DecompositionHNO2HNO3 NH4 + HNO2HNO3 NH4 + Ammonia Vocalization Nitrification NH4 + Upward Diffusion Diffusion Downward Diffusion N2 Fixation AIR WATER Oxidized Zone Reduced Zone O x i d i z e d Z o n eR e d u c e d Z o n eN H4 + N O3 Organic N NH4+ N2, N2O NO3 -D i f f u s i o nD if f u s io n Organic N N2N2O Denitrification Leaching N2N2O NH3 NO Chemical DecompositionHNO2HNO3 NH4 + HNO2HNO3 NH4 + HNO2HNO3 NH4 + HNO2HNO3 NH4 + Ammonia Vocalization Nitrification NH4 + Upward Diffusion Diffusion Downward Diffusion N2 Fixation AIR WATER Oxidized Zone Reduced Zone O x i d i z e d Z o n eR e d u c e d Z o n eN H4 + N O3 Organic N NH4+ N2, N2O NO3 -D i f f u s i o nD if f u s io n O x i d i z e d Z o n eR e d u c e d Z o n eN H4 + N O3 Organic N NH4+ N2, N2O NO3 -D i f f u s i o nD if f u s io n Organic N

PAGE 39

25 DENITRIFICATIONPARENT MATERIALNO3 -availability O2availability Interactive controls Indirect controls Direct controls State factorsBIOTA TIME CLIMATE Plant functional types Soil Resources Plant NO3 -uptake Litter quality Carbon quality Respiration microbial/root Temperature H2O Soil texture Labile carbon LONG-TERM CONTROLS SHORT-TERM CONTROLS DENITRIFICATIONPARENT MATERIALNO3 -availability O2availability Interactive controls Indirect controls Direct controls State factorsBIOTA TIME CLIMATE Plant functional types Soil Resources Plant NO3 -uptake Litter quality Carbon quality Respiration microbial/root Temperature H2O Soil texture Labile carbon LONG-TERM CONTROLS SHORT-TERM CONTROLS LONG-TERM CONTROLS SHORT-TERM CONTROLS Figure 1-5. The major factors controlling denitrification in soils. Thickness of the arrows represents the strength of effe cts. Black arrows represent positive influences and white arrows represent negative influences. Adapted from Chapin III et al. (2004).

PAGE 40

26 Nir Nos CYTOPLASM Nor Nar NDH bc1complex Cyt cd1or Cu proteinPERIPLASMNO2 -NO N2O N2NO N2O NO3 -N2O NADH +H+NAD+ QP QP Nir Nos CYTOPLASM Nor Nor Nar Nar NDH bc1complex Cyt cd1or Cu proteinPERIPLASMNO2 -NO N2O N2NO N2O NO3 -N2O NADH +H+NAD+ QP QP Figure 1-6. The basic arrangement of the nitrog en oxide reductases required for complete denitrification by a single organism. Adapted from Shapleigh (2000).

PAGE 41

27 CHAPTER 2 STRUCTURE AND FUNCTION OF M ETHANOGENIC ASSEMBLAGES ALONG A SHORT-TERM RESTORATION CHRONOSEQUENCE Introduction The Hole-in-the-Donut (HID) is a 4000 ha re gion within Everglades National Park (ENP), Florida, USA. Once consisting of oligotrophic sawgrass ( Cladium jamaicense Crantz) prairies and short hydroperiod pinela nds, the HID was subj ected to ag ricultural land use practices for 60 years (Loope and Dunevitz, 1981; Dalryample et al., 2003). Pre-agriculture, HID soils were characterized as shallow, poorly drained and low nutrient marls. Intensive rock plowing efforts de stroyed underlying limest one bedrock, creating coarsely textured, well drained soil more suitable for vegetable production (Li and Norland, 2001). When farming activity ended, the HID was left as an abandoned, high nutrient, high oxygen environment. Farmland within the HID was invaded by stands of Schinus terebinthifolius Raddi (Brazilian pepper), a sh rub native to South America, intentionally introduced to Fl orida as an ornamental in the 1898 (Austin, 1978), and is though to have entered ENP in the 1940s (B ancroft, 1973; Loope and Dunevitz, 1981). HID restoration plans initiated by ENP in 1996 include complete removal of all plants and much of the soil down to bedrock. Following removal, cleared plots are left undisturbed to allow natural reestabl ishment of microbial communities and recolonization by native wetlands plants. HID restoration is conducte d in specified areas of varying size, such that regions at different stages of recovery are present at one time.

PAGE 42

28 Soil development is a critical first step in plant colonization on bare substrate. Soil formation results from complex inter actions between phys ical, chemical and biological factors. Subsequently, soil will become the direct link between biotic and abiotic factors that drive primary su ccession (Walker and del Moral, 2003). Recolonization by microorganisms will precede the establishment of plant communities. Biogeochemical processes mediated by soil mi crobial communities wi ll contribute both to soil formation and release of nutrients fo r plants. Significant geochemical differences between undisturbed and clea red sites have been reported (Li and Norland, 2001). Microbe-mediated processes are most sensi tive to disturbance, therefore study of microbial communities may be an effective measure to assess the response of soil to perturbation (Nannipieri et al., 2003). Complete soil removal likely destroyed linkages between functional groups of microorganisms. Microorganisms play a central role in carbon and nitrogen cycling, such that development of microbi al communities is critical to soil quality and the reestablishment of biogeochemical linkages (Nannipieri et al., 2003). Functional shifts within bacterial groups could potentially a lter processes at the ecosystem scale (Schimel and Gulledge, 1998). Anaerobic microorganisms, such as those found in anoxic soils characteristic of many mature wetlands, mineralize organic carbo n through a variety of terminal electron accepting processes. In a developing system, such as the HID, establishment of anaerobic microbial communities may occur in con cert with soil profile development. Methanogenesis is a major process res ponsible for termin al anaerobic carbon mineralization in freshwater wetlands (Sch imel and Gulledge, 1998). Methyl coenzyme M reductase, partially encoded for by mcrA, is the enzyme responsible for the terminal

PAGE 43

29 step in methane production, the operon and mcrA are functionally linked and phylogenetically conserved in methanogens (L euders et al., 2001; Luton et al., 2002), making mcrA a candidate gene for monitoring potential shifts in methanogenic populations in developing HID soils. The objectives of investigating methane and methanogen dynamics in the HID were (i) to assess whether differences in structure and function of methanogenic assemblages may be used as an indicator of soil profile development along the restoration gradient; and (ii) to gain insight into the state of both carbon cycling and anaerobic electron accepting processes in developing soils along the restoration chronosequence. Materials and Methods Site Characteristics, Sample Collecti on, and Biogeochemical Characterization Samples were collected in April and November 2004. Plots 20 x 20 m2 were established in sites restored in 1989, 1997, 2000, and 2003 (R89, R97, R00, and R03, respectively), and in an undistur bed site (UND). The range of elevation for the five plots was 0.5 to 0.6 m. Within each sampling area, 2 x 2 m2 grids were used to establish 81 sampling nodes, which were monitored for so il depth, ground covera ge, and elevation. Nine nodes were chosen based on relative range of soil depth within each site, 3 from each depth range (shallow, intermediate, deep). Sampling nodes were color coded and marked for future sampling efforts. Soil samples were taken with a plastic coring device; however, due to non-uniform soil cover in recen tly restored sites, grab samples were collected where necessary. Individual sample s from each depth range were combined to make three representative soil samples, whic h were used for molecular and geochemical analyses. Soil samples were kept on ice and transported to the labor atory within 72 h of collection, where they were manually mixed and large roots removed. Subsamples for

PAGE 44

30 DNA analysis were stored at -70 C until analysis. Biogeochemical analyses were conducted at the Wetland Biogeochemistry Laboratory (DAngelo and Reddy, 1999; White and Reddy, 1999; Wright and Reddy, 2001). Values for select parameters are presented in Table 2-1. Methane Production Potentials Two g soil, sampled in November 2004, from UND, R89, R97, R00, and R03 sites were mixed with 25 ml of anoxic modified basal carbonate yeas t extract trypticase medium (Touzel and Albagnac, 1983) under an N2 stream in 50 ml anaerobic culture bottles that were later closed with butyl rubber stoppers and aluminum crimp seals. Tubes were pre-incubated for ten days prior to addition of electr on donors. Acetate and formate (20 mM each) were added from N2 sparged sterile stock solutions. The bottles were fitted with three-way Luer stopcock s (Cole-Parmer, Vernon Hills, IL) for gas sampling, and incubated in the dark at 25oC without shaking. Methane in the headspace was measured by gas chromatography with a Shimadzu 8A GC equipped with a Carboxen 1000 column (Supelco, Bellefonte, PA) and a flame ionization detector operating at 110 oC. The carrier gas was N2 and the oven temperature was 160 oC. All determinations were carried out in triplicate bot tles with soil samples from each site (3 bottles per site). Headspace pressure was measured using a digital pressure indicator (DPI 705, Druck, New Fairfield, CT). Nucleic Acid Extraction and PCR Amplification Nucleic acids were extracted from 0.25 g of soil with Power Soil DNA Isolation kit (MoBio, Carlsbad, CA, USA) according to the manufacturer's instructions. PCR amplification was conducted using the primer set designed by Lut on et al. (2002), and consists of primers mcrA-f (5 '-GGTGGTGTMGGATTCACACARTAYGCWACAGC-

PAGE 45

31 3') and mcrA-r (5'-TTCATTGCRTAGTTWGGRTA GTT-3') which amplify a fragment of between 465 and 490 bp of mcrA Each 20 l PCR reaction mixture contained 7 l of distilled water, 1 l of each primer (10 pmol l-1), 10 l of HotStarTaq Master Mix (Qiagen, Valencia, CA) and one l of diluted template DNA. PCR amplification was carried out in a GeneAmp PCR system 9700 (PerkinElmer Applied Biosystems, Norwalk, CT). The initial enzyme activation and DNA denaturation was performed for 15 min at 95C, followed by 5 cycles of 30 s at 95C, 30 s at 55C, and 30 s extension at 72C, a nd the temperature ramp rate between the annealing and extension segment was set to 0.1 oC s-1 because of the degeneracy of the primers (Luton et al., 2002). After this, the ramp rate was set to 1oC s-1 and 30 cycles were performed with the following conditi ons: 30 s at 95C, 30 s at 55C, and 30 s extension at 72C, and a final extension of 72C for 7 min. PCR conditions for T-RFLP analysis were identical, except the anneali ng temperature was decr eased to 53C. PCR products were analyzed by electrophoresis through 2% agarose gels to confirm amplification of expected size product. Cloning and RFLP Analysis Fresh PCR amplicons were ligated into pCRII-TOPO cloning vector and transformed into chemically competent Escherichia coli TOP10F cells according to the manufacturer's instructions (Invitrogen, Carlsbad, CA). Positive colonies were screened by PCR amplification with the primer set and PCR conditions described above. PCR production from positive clone s was digested with RsaI restriction enzyme. Each 10 l reaction consisted of 5U of enzyme 1x restriction enzyme buffer, 0.6 g of bovine serum

PAGE 46

32 albumin, 5 l of PCR amplicon, and water to vo lume. Digests were analyzed by electrophoresis through 4% agarose gels. Sequencing and Phylogenetic Analysis Representative clones from the most freque ntly occurring restriction patterns in each library were sequenced at the DNA Sequencing Core La boratory at the University of Florida using internal vect or primers. DNA sequences of mcrA genes generated from each treatment were translated into putati ve amino acid sequences and aligned manually in Se-Al version 2.0a11 (Rambaut, 1996). Alignments were then aligned with Clustal version 1.81 (Thompson et al., 1997). Phyl ogenetic trees were built with a neighborjoining analysis using a Jukes and Cantor correction method as implemented in the TREECON software package (van de Peer and de Wachter, 1994). Bootstrap analysis was performed with 100 resamplings of the amino acid sequences. T-RFLP Analysis Approximately 100 to 150 ng of PCR product was digested with RsaI The enzymatic digestion reaction consisted of 5 units of re striction enzyme (Promega, Madison, WI), 1x restriction enzyme buffer, 0.6 g bovine serum albumin, and deionized water to a final volume of 10 l. Enzymatic digestions were incubated at 37 oC overnight. One and one half l of digested product were us ed for terminal restriction fragment (T-RF) detection by the DNA Sequenci ng Core Laboratory at the University of Florida. Briefly, digested products were mixed with 2.5 l deionized formamide, 0.5 l ROX-labeled GeneScan 500-bp internal sized standard (Applied Biosystems, Perkin Elmer Corporation, Norwalk, CT) and 0.5 l of loading buffer (50 mM EDTA, 50 mg/ml blue dextran). Samples were denatured by heating at 95 oC for 3 min and subsequently

PAGE 47

33 transferred to ice until lo ading of the gel. One l was electrophores ed through a 36 cm, 5% polyacrylamide gel containing 7 M urea at 3 kV on an ABI 377 Genetic Analyzer (Applied Biosystems). T-RFLP profiles we re analyzed with GeneScan version 2.1 (Applied Biosystems). T-RF size (bp) was calcula ted using internal sta ndards. Peak sizes in base pairs and peak areas were exported to Excel 97 SR-1 (Microsoft Corporation, Redmond, WA) for data analysis. Diversity Indices Clone libraries were analyzed by anal ytic rarefaction employing RarefactWin (version 1.3; S. Holland, Stratigraphy La b, University of Georgia, Athens [http://www.uga.edu/~strata/software/]). Cumulative expected phylotypes were calculated for each clone library according to Castro et al. (2004). Rarefaction curves were fit to a hyperbolic mode l with the formula y = a x /(b + x ) using Datafit software version 8.0.32 (Oakdale engineering, Oakdale PA), where y represents number of phylotypes, and x is the number of individuals. Coverage values were determined by comparison of obtained versus cumulative e xpected phylotypes. Shannon-Weaver values were calculated using default parameters of the program by DOTUR (Schloss and Handlesmann, 2005). Results and Discussion To our knowledge, this is the first study to monitor the composition and activity of microbial assemblages during the restoration of a freshwat er wetland ecosystem. The short-term chronosequence created by comple te soil removal allowed us to characterize those communities initially co lonizing bare substrate, a nd monitor their dynamics in concert with soil accretion and changes in geochemical processes. Monitoring the

PAGE 48

34 development and subsequent changes in me thanogenic assemblages may provide insight into possible shifts in terminal anaerobic mine ralization processes with soil development. Methane Production in HID Soils Observed rates of methane production did not correlate with measured geochemical parameters (Table 2-1), or show clear tren ds associated with time since restoration. Intrinsic methane production rates were highest in R97 and R03 soils (Table 2-2). UND soil produced the least methane, with rates approximately 30 times lower than intrinsic rates reported from oligotrophic soils of the Everglades Water Conservation Area 2A (Castro et al., 2004). Additions of acetate to microcosms lead to slight increases in methane production after 10 d. R03 showed th e greatest rate of methane production, but the average rate was only 1.2 fold higher than in unamended soils. Methane production from acetate was two fold higher in R03 so ils compared to unamended microcosms. UND soils were unaffected by acetate addition, and rates suggest a general decline in acetoclastic methanogenesis with restoration age. Overall, less than 2% of acetate was converted to methane over the 10 d incubation period. Formate was added to soil microcosms to assess the activity and popul ation sizes of hydrogenotrophic methanogens. Formate is commonly used as an analogue to H2-CO2 in anaerobic mineralization studies (Dolfing and Bloemen, 1985). Hydrogen has be en shown to be an important electron donor to methanogenesis in other regions of th e Everglades (Castro et al, 2004; Chauhan et al., 2004). Methane production potentials in formate-amended soils were 4 to 17 times higher than in unamended soils, and 4 to 20 tim es higher than in acetate amended soils. Approximately 18 to 50% of added formate was converted to methane over the 10 d incubation period, production rate s and total substrate conversi on percentage values were strongly correlated. This may indi cate the dominance of hydrogenotrophic

PAGE 49

35 methanogenesis in HID soils. Further, this may be an underestimate of actual hydrogenotrophic production potentials, as on ly 60% of hydrogenotrophic methanogens are able to utilize form ate for methane production (Garcia et al., 2000). Hydrogenotrophic methanogens were 1000 to 100 times more abundant than acetoclastic methanogens in other regions of th e Everglades (Chauhan et al., 2004). Methane production potentials in UND so ils were lowest of all study sites, regardless of treatment, and data suggest a general decline in me thanogenic activity in older sites (Table 2-2). A pr evious comparison of Everglad es soils indicated greatest methane production from marl after additi on of acetate and other carbon sources (Bachoon and Jones, 1992). However, our data suggest that methanogenesis may not be an important part of terminal anaerobic carbon cy cling in the HID. Currently, factors possibly limiting methane production in HI D soils are unknown. However, short hydroperiods and shallow soils may provide co nditions conducive to the occurrence of more energetically favorable terminal anae robic electron accepting processes, such as denitrification. Phylogenetic Characterization of Met hanogenic Assemblages in HID Soils PCR amplification of mcrA from soils sampled in undisturbed and restored sites, in the dry season (April 2004), yielde d the expected ca. 465 to 490 bp mcrA fragments. Clone libraries constructed from dry season so ils indicated the presence of considerable diversity of methanogens in HID soils. Th e number of obtained and expected phylotypes was highest in UND soils and lowest in R00 so ils (Table 2-3) Coverage of expected mcrA diversity within each cl one library was ascertaine d by comparison of observed versus expected phylotypes for each librar y. Values ranged from 45 to 76%, highest in R97 and R00 libraries, and lowest in UND (T able 2-3). Both measures of sampling

PAGE 50

36 coverage indicate that our clone libraries do not fully represent mcrA diversity in HID soils. mcrA sequences obtained from dry season soils formed seven clades encompassing the orders Methanobacteriales, Methanococca les, Methanomicrobiales, Methanosarcinales and two clades sharing greatest si milarity with uncultured organisms (Figure 2-1). MCR-1 sequences shar e ca. 90% DNA sequence similarity to Methanosarcina ; these sequences were obtained fr om UND, R89 and R00 soils, but not in significant quantities. Related sequences we re reported from nutrient impacted regions of the Florida Everglades (C astro et al, 2004). MCR-2 sequen ces were most abundant in UND soils, but comprised a small percentage of R03 and R00 sequences; they shared highest similarity with uncultivated metha nogens in rice paddy (Lue ders et al., 2001) and Everglades soils (Castro et al., 2004), sharing 87 to 94% similarity with putative hydrogenotrophs in Rice Cluster I (Lueders et al., 2001). Clones in MCR-3, present in R89, R00, and R03 libraries, were most similar to uncultured Methanosaeta spp. obtained from permanently flooded riparian soils (Kemnitz et al., 2004). Methanosaeta spp. are specialists able to generate methane only from catabolism of acetate (Boone et al., 1993). Cluster MCR-4 branched deeply within cultured Methanomicrobiales and contained sequences obtained from UND, R89, and R 03 soils. MCR-4-like sequences have also been obtained from eutrophic Everglades so ils (Castro et al., 2004) and a peat bog (Juottonen et al., 2005); our clones share ca. 85% sim ilarity with Fen Cluster methanogens, a potentially novel group of uncertain function (Galand et al., 2002; Galand et al., 2005). Cluster MCR-5 se quences branch deeply within the Methanococcales. They were obtained from all st udy sites; an increase in MCR-5

PAGE 51

37 abundance was observed in more established sites (Figure 2-2). These sequences are closest to those from uncultiv ated organisms obtained from ri ce roots (Chin et al., 2004). Previous characterizatio n of methanogenic assemblages in the Florida Everglades did not recover sequences clustering with Methanococcales (Castro et al., 2004; Castro et al., 2005). Cluster MCR-6 sequences, present in UND and R97, clustered outside of cultured Methanococcales and shared greatest similarity with clones from other regions of the Everglades (Castro et al., 2004). Clones asso ciated with MCR-7 were found in all sites, and formed a distinct clade within Methanobacteriales Sequence distributions suggest a general decrease in MCR-7 relative abundance as restoration progr esses (Figure 2-2). Methanobacteriales mcrA comprised a significant portion of clone libraries constructed from other regions of the Ev erglades (Castro et al., 2004) T-RFLP Analysis of Methan ogenic Assemblage Structure Composition of methanogenic assemblages in HID soils was monitored with TRFLP. The possible phylogenetic affiliations of the T-RFs are presented in Table 2-4. In silico analyses of mcrA clones indicates that some T-RFs may be associated with distinct phylogenetic groups of methanogens. Averages of T-RF relative frequencies for dry and wet season samples for UND, R89, R97, R00, and R03 sites are presented in Figures 2-3 and 2-4, respectively. PCR amplification of mcrA in UND samples was generally weak and we did not obtain significant quantities of amplicons in wet soils for T-RFLP analysis. Thus, only dry season T-RF profile s are presented for the UND site. Dominant T-RFs for each site were obtained consis tently from replicate soil samples. Seasonal Structure of Methanogenic Assemblages Thirteen T-RFs were obtained from both wet and dry season samples. In silico digestion indicate T-RFs 85, 186, and 305 are excl usively associated with cluster MCR-7,

PAGE 52

38 associated with Methanobacteriales Seasonally, there were no significant changes in relative abundance of MCR-7 T-RFs within sites. Methanobacteriales T-RFs comprised between 35 to 55% of total fluorescence within each site for both we t and dry seasons. T-RFs 65 and 302 were associated exclus ively with cluster MCR-5. Sequences comprising MCR-5 branch deeply within Methanococcales, and sequences from all study sites are found within this cluster. Increases in T-RF 302 in R00 and R97 between seasons were evident, but comprised only 5 to 20% of total fluorescence in each site. TRF 65 comprised between 5 to 10% of total fl uorescence in all sites and between seasons. T-RFs 48, 80, 96, and 180 corresponded to multiple phylogenetic clusters. For the most part, these T-RFs remained relatively stable between seasons, and were detected in all soils. Because they share affiliation with two metabolically distinct clusters of methanogens, it is impossible to discern wh ich organisms are contributing greatest to shifts in abundance. T-RFs 198, 201, 315, and 317 had no phylogenetic affiliation and were obtained from all samples, but comprised only a small percentage of total fluorescence. These T-RFs may represent methanogens not obtained in our clone libraries. Our T-RFLP analysis did not identify shifts in composition of methanogenic assemblages between seasons. Significant shif ts in soil moisture between seasons may lead to the development of methanogenic ac tivity hot spots in dr y soils. Methanogenic activity has been detected in extremely dr y soils (Peters and Conrad, 1995). Rewetting events have been correlated to observed shif ts in dominant organisms (Nannipieri et al., 2003). However, organisms inhabiting seasonally water stressed soils are thought to be more resistant to moisture fluctuations (F ierer et al., 2002). Fu rther, slow growing

PAGE 53

39 organisms, such as methanogens, may be less affected by dry-wet cycles (VanGestel et al., 1993). Archaeal communities remained relati vely stable during rice field rewetting events (Lueders et al., 2000). Within s ite differences in methanogenic assemblages observed were less than between site differe nces across seasons in other regions of the Florida Everglades (Castro et al., 2005). Shifts in Methanogenic Assemblages with Restoration Age T-RFs associated with MCR-5 and MCR-7 dominated samples from all study sites, as well as clone libraries (F igures 2-2 and 2-3). The rela tive abundance of MCR-5 T-RFs (65 and 302) differ slightly within sites, w ith respect to each other, but significant variation between sites was not evident. Their combined abunda nce suggests that Methanococcales populations remain stable in soils fr om all sites. Relative abundance of MCR-7 T-RFs decreased with successional st age. Interestingly, T-RF 85 was most abundant in UND, R00, and R03 soils, showi ng an approximately lin ear decrease with restoration age. Decreased abundance of T-RF 85 in R89 and R97 soils corresponds with increased abundance of T-RF 305. Shifts in MCR-7 T-RFs are evident in both seasons, but more pronounced in dry season profiles. Assuming these T-RFs are exclusively associated with Methanobacteriales mcrA as in silico digestion indicate s, this suggests a shift within Methanobacteriales populations with restoration age. Methanobacteriales were also obtained in different proportions along a nutrient impact ed gradient of the Everglades (Castro et al., 2004). T-RFLP analysis of mcrA obtained from riparian soils also reported shifts in abundance of Methanobacteriales ; T-RFs differing by approximately 100 bp were obtained in significan tly different quantities in soils subjected to differing periods of inundation (Kemnitz et al., 2004). Thus, the apparent association

PAGE 54

40 of T-RF 85 may represent a shift within the Methanobacteriales associated with restoration age. At best, T-RFLP may be employed as a semi-quantitative me asure of community structure. Interpretation of shifts in T-RF abundance may not indicate significant changes in assemblage composition. Further, differe nt efficiencies of labeled and unlabelled primers required use of different anneali ng temperatures during PCR for cloning and TRFLP analysis, further allowing for discre pancies between T-RFLP profiles and clone libraries. Such discrepancies have been described previously for mcrA PCR-cloning and T-RFLP analyses (Leuders et al., 2003; Castro et al., 2005) Putative hydrogenotrophic mcrA genes were most freque ntly observed in clone libraries and T-RFLP profiles. This is c onsistent with the highest methane production resulting from formate addition in all s ites. However, the exact proportion of Methanobacteriales and Methanococcales in HID restorations sites is not reflected in TRFLP results, as the degenerate primer s employed in this study do not provide quantitative recovery of all phylogenetic lineages (Lueders et al., 2003). Further, it has been suggested that the primer set em ployed for this study is biased toward hydrogenotrophic orders of methanogens, and particularly under represent Methanosaeta spp. and Methanosarcina spp. (Luton et al., 2002; Castro et al., 2004) Conclusions Little work has been done to char acterize establishment and succession of microbial communities in the context of ecosy stem restoration. Clone libraries suggest initial establishment of all major metabolic guilds of methanogens in the most recently restored site. Methanogens have been show n to colonize bare surfaces as members of biofilms (Kussmaul et al., 1998). All T-RFs obt ained were present in all sites, and in

PAGE 55

41 approximately similar ratios between seasons. However, there is some evidence of shifts within Methanobacteriales (T-RFs 85 and 305) populations associated with restoration age, suggesting that individual groups of methanogens may respond differently to geochemical and environment differences be tween restoration sites. Interestingly, TRFLP profiles of methanogenic communities in early sites of a long-term successional bog chronosequence were nearly indistinguishab le; however, differences were evident in late succession sites (Meril et al., 2006). It must be noted that DNA-based assessments of bacterial community composition provide s information on the potential metabolic activity, rather than the actual activity. Thus, further studies of gene expression may, in fact, indicate differences in activity within each site. In summary, our results suggest that a diverse assemblage of methanogenic bacteria colonize recently restored sites. Seasonal T-RFLP profiles indicated methanogenic assemblage structures to remain consistent in composition despite seasonal changes in biogeochemical parameters. This is consistent with previ ous studies reporting temporal stability of prokaryotic communities (Lueders et al., 2001; Fierer et al., 2003; Castro et al., 2005). Shifts within certain methanogenic groups in association with restoration age were evident. Both molecular and functional assessments suggest hydrogenotrophic methanogens are responsible for most of the methane production observed along the chronosequence.

PAGE 56

42Table 2-1. Geochemical parameters of dry (A pril 2004) and wet (November 2004) season soils. Study Site Soil Depth (cm)a Moisture (%)b TC (g kg-1) TN (g kg-1) TP (g kg-1) LOI (%) MBC (mg kg-1) April 2004 UND 5.9 (1.5-10) 43.7 (10.4) 159.4 (10) 6.6 (0.8) 0.2 (0.0) 17.03 3881.2 (829) R89 4.5 (3-6.5) 28.3 (7.4) 164.5 (16) 7.7 (1.6) 0.7 (0.2) 23.96 5003.8 (1323) R97 5.2 (2-8) 39.1 (18.2) 169.4 (8) 8.2 (0.8) 1.0 (0.2) 24.84 4806.3 (1340) R00 2.7 (1-5.5) 36.8 (12.2) 161.1 (17) 6.7 (0.9) 0.6 (0.1) 20.88 4185.3 (1472) R03 1.6 (0.5-2.5) 13.5 (9.1) 139.9 (9.7) 4.0 (0.9) 1.0 (0.1) 15.90 2161.3 (579) November 2004 UND 10.1 (2-15) 49.6 (4.5) 192.5 (8.8) 7.2 (0.9) 0.1 (0.2) 16.71 1925.1 (516) R89 5.4 (1-17) 56.7 (8.9) 340.9 (17.2) 9.2 (1.5) 0.8 (0.2) 14.38 3109.9 (1009) R97 4.6 (3-11) 53.4 (5.8) 323.7 (15.5) 9.0 (1.4) 1.0 (0.2) 14.19 3237.5 (1303) R00 3.3 (1) 54.8 (0.8) 234.3 (11.3) 7.4 (0.8) 0.6 (0.1) 23.90 2343.7 (494) R03 1.2 (0-3) 52.2 (7.0) 194.1 (7.7) 5.2 (0.6) 0.9 (0.2) 18.86 1752.5 (680.8) aValues in parentheses represent the range of soil depths measured over 81 samp les nodes, as described in the Materials and Methods. bValues in parentheses are standard deviati ons of the mean values for determinations based on three soil samples; TC, total carb on; TN, total nitrogen; TP, total phosphorous, LOI, lo ss on ignition; MBC, microbial biomass carbon.

PAGE 57

43 Table 2-2. Potential methanogenesis rates and accumulated CH4 in wet season soils. No Addition Formate Acetate Site Ratea Totalb Rate Total Rate Total UND 0.1 (0.0) 41 (16) 0.4 (0.1) 198 (37) 0.1 (0.1) 52 (21) 1989 1.1 (0.3) 513 (112) 26.6 (1.6) 8843 (3951) 1.5 (0.1) 700 (34) 1997 11.4 (4.7) 4193 (283) 36.0 (11.1)17274 (3066) 7.3 (1.0) 3782 (141) 2000 3.4 (1.3) 1619 (425) 22.6 (13.9)10844 (3843) 6.6 (12.0) 3178 (701) 2003 7.4 (2.2) 1052 (744) 50.4 (14.7)24183 (4077) 8.8 (3.3) 2998 (926) aPotential methanogenic rates (in nanomoles per gram soil per hour); Standard errors of the means are shown in parentheses for determinations with three replicate soil samples. bAverage total methane accumulated in headspace of three replicate samples were site, expressed as nanomoles of methane accumulated. Table 2-3. Expected and observed phylot ypes and diversity i ndices for dry season mcrA clone libraries for HID soils. Site Expected Phylotypesa Observed Phylotypesb Coverage (%)c Shannons H UND 35.35 (1.60) 16 (31) 45 2.09 R89 21.41 (0.13) 14 (39) 67 2.01 R97 13.62 (0.53) 10 (39) 76 1.68 R00 13.29 (0.43) 10 (39) 76 2.10 R03 19.20 (1.32) 12 (37) 63 1.76 aValue of constant a from equation y = ax /( b + x ) (standard error) bValue in parentheses is tota l number of clones screened cExpressed as percent of expected phylotypes obtained within each library.

PAGE 58

44 Table 2-4. Phylogenetic affiliation of mcrA T-RFs for HID soil samples. Observed T-RF (bp) Theoreti cal T-RF (bp) Cluster Order 48 48 MCR-1 MCR-7 Methanosarcinales Methanobacteriales 65 65 MCR-5 Methanococcales 80 80 MCR-1 MCR-5 Methanosarcinales Methanococcales 85 84 MCR-7 Methanobacteriales 96 95 MCR-2 MCR-4 MCR-6 M ethanosarcinales Methanomicrobiales Uncultured Not Obtained 175 MCR-6 Uncultured Not Obtained 177 MCR-3 MCR-4 Methanosarcinales Methanomicrobiales 180 179 MCR-3 MCR-4 Methanosarcinales Methanomicrobiales 186 188 MCR-7 Methanobacteriales 198 Unknown phylogenetic affiliation 201 Unknown phylogenetic affiliation 302 302 MCR-5 Methanococcales 305 305 MCR-7 Methanobacteriales 315 Unknown phylogenetic affiliation 317 Unknown phylogenetic affiliation Not Obtained 438 MCR-5 Methanococcales 458-487 No Cut Not Obtained

PAGE 59

45 Figure 2-1. Neighbor-joining mcrA tree for representative clones from April 2004 soils. Clones are named according to the site of origin; UND, undisturbed site, R, restoration site (followed by year of restoration). Scale bar represents 10% sequence divergence. Numbers at node s represent percentage of bootstrap resamplings based on 100 replicates. Va lues greater than 85 are shown, while black dots ( ) on nodes represent values between 50 and 85.

PAGE 60

46 0% 20% 40% 60% 80% 100% UNDR89R97R00R03Clone frequency MCR-7 MCR-6 MCR-5 MCR-4 MCR-3 MCR-2 MCR-1 Figure 2-2. Distribution of mcrA sequences obtained from dry season soils within designated phylogenetic clusters.

PAGE 61

47 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%UNDR89R97R00R03 317 bp 315 bp 305 bp 302 bp 201 bp 198 bp 186 bp 180 bp 96 bp 85 bp 80 bp 65 bp 48 bp Figure 2-3. Community dynamics for the mcrA gene in dry season HID soils determined by T-RFLP analysis. Y-axis values represent percent of total fluorescence.

PAGE 62

48 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%R89R97R00R03 317 bp 315 bp 305 bp 302 bp 201 bp 198 bp 186 bp 180 bp 96 bp 85 bp 80 bp 65 bp 48 bp Figure 2-4. Community dynamics for the mcrA gene in wet season HID soils determined by T-RFLP analysis. Y-axis values represent percent of total fluorescence.

PAGE 63

49 CHAPTER 3 GENETIC AND FUNCTIONAL VARIATION IN DENITRIFIER POPULATIONS ALONG A SHORT-TERM REST ORATION CHRONOSEQUENCE Introduction Nitrogen is the nutrient most likely to limit primary productiv ity in temperate terrestrial ecosystems. Desp ite the extraordinary supply of N in the atmosphere, great demand for it by producers and costly energetics of N2 fixation present the opportunity for supply-side imbalance (Vitousek and Howarth, 1991). Retention of N within terrestrial ecosystems is dependent on the interaction of physical, chemical, and biotic variables. In soils, N can be retained in organic matter, biomass of plants or soil microbiota, or through surface associations w ith soil particles. The most common N loss mechanisms occur through leaching, denitrification, or disturbances (Payne, 1981). Denitrification is the microbially mediat ed dissimilatory reduction of nitrogen oxides to gaseous end products (NO, N2O, N2) for energy production (Zumft, 1997). It is the dominant loss mechanism of biologically preferred nitrogen from terrestrial ecosystems, as well as the most prevalent an aerobic respiratory pro cess based on nitrogen (Megonigal et al., 2004). The capab ility of respiring by denitrif ication is maintained by a taxonomically diverse group of facultative anaerobic Eubact eria; however, a few Archaea and fungi also exhibit denitr ification (Tiedje, 1988; Shoun and Tanimoto, 1991; Usuda et al., 1995). The multi-step process is carried out by a series of membrane bound enzymes. With few exceptions, most bacterial denitrifiers possess the capacity to carry out the entire process (Tiedje, 1988). The defini ng (first gas forming step) and often rate-

PAGE 64

50 limiting step of denitrification is conversion of nitrite to nitr ic oxide, and is catalyzed by two distinct but functionally equivalent me talloenzymes (Glockner et al., 1993; Zumft, 1997), i.e., the copper-containing NirK and the cytochrome cd1 NirS enzymes. The genes encoding the two enzymes, nirK and nirS have been used extensively to detect and characterize denitrifiers in activated sludge (You, 2005), marine sedi ments (Braker et al., 2000; Braker et al., 2001; Liu et al., 2003), forested upla nds (Priem et al., 2002), and freshwater riparian (Schipper et al., 1993; Rich and Myrold, 2004) and wetland ecosystems (Priem et al., 2002). High carbon inputs, water column-sedim ent surface exchange of reduced and oxidized forms of fixed nitrogen, and low oxygen partial pressures may be favorable conditions for the development of robust denitrifying communiti es in wetland soils (Reddy and Patrick, 1984). In seasonally inundated wetland ecosystems, denitrifying activity may be accelerated, as influx of fres h waters may introduce fresh labile carbon sources and sub-oxic conditions (Bow den, 1987). Activity and dynamics of denitrification in freshwater wetlands have been characterized extensively (Bowden, 1987; Reddy et al., 1989; Hanson et al., 1994; Seitzinger, 1994; White and Reddy, 1999). However, little information exists on the comm unity composition of denitrifiers in these systems (Priem et al., 2002). Nitrogen loss due to denitrification in the Florida Everglades has been characterized in permanently flooded, nut rient impacted and oligotrophic regions (DAngelo and Reddy, 2001; White and Reddy 1999; White and Reddy, 2001), and in both dominant soil types of the ecosystem (marl and peat) (Gordon et al, 1986).

PAGE 65

51 Denitrification has been suggest ed to be the most important nitrate loss mechanism in these regions (White and Reddy, 1999). Nitrogen is the most commonly limiting nutrient to primary productivity during primary succession (Vitousek and Howarth, 198 9). Thus, its retention within the ecosystem may be crucial to restoration su ccess. Shallow soil depths and periodic inundation of HID restoration sites suggest de nitrification as a potentially important mechanism for N loss. Elucidation of the differences in compos ition and function of denitrifying communities at varying stages of recovery will underpin further interpretation of responses at the physiological an d ecological scales. Specific questions to be addressed include the following: (i) what is the phylogenetic composition of denitrifiers in HID soils; (ii) how do communities differ in the context of measured activity and restoration stage; and (iii) ar e there significant patt erns in community composition associated with restoration stage? Materials and Methods Site Characteristics, Sampling, a nd Biogeochemical Characterization Samples were collected in November 2005. Plots 20 x 20 m2 were established in sites restored in 1989, 1997, 2000, 2001, and 2003 (R89, R97, R00, R01, and R03), and in an undisturbed site (UND). The range of el evation for the five plots was 0.5 to 0.6 m. Within each sampling area, 2 x 2 m2 grids were used to establish 81 sampling nodes, which were monitored for soil depth, ground coverage, and elevation. Nine nodes were chosen based on relative range of soil dept h within each site, 3 from each depth range (shallow, intermediate, deep). Sampling node s were color coded and marked for future sampling efforts. Soil samples were taken w ith a plastic coring device; however, due to non-uniform soil cover in recently restored site s, grab samples were collected at some

PAGE 66

52 nodes. Individual samples from each depth range were combined to make three representative soil samples that were used for molecular and geochemical analyses. Soil samples were kept on ice and transported to the laboratory within 72 h of collection, where they were manually mixed and la rge roots removed. Subsamples for DNA analysis were stored at 70 C. Biogeochemical analyses were conducted at the Wetland Biogeochemistry Laboratory (DAngelo and Reddy, 1999; White and Reddy, 1999). Values for select parameters are presented in Table 3-1. Denitrifying Enzyme Activity and Gas Analysis Laboratory denitrifying enzyme activity (DEA) incubations were performed on soils collected in November 2005 according to the method outlined by White and Reddy (1999) with slight modifications Approximately 15 g of fiel d-moist soil from each site were placed in quadruplet 220 ml serum bottle s, which were sealed with butyl rubber septa and aluminum crimp seals. To estab lish anaerobic conditions in each bottle, the headspace was evacuated to approximately -85 kPa and replaced with O2-free N2 gas. Five milliliters of N2-sparged deionized water were adde d to each serum bottle to create soil slurries. Approximately 15% of head space gas was replaced with acetylene (C2H2) (Balderston et al., 1976; Yoshin ari and Knowles, 1976). Bottles were shaken for 1 h on a longitudinal shaker in the dark to allow C2H2 to distribute evenly th rough the soil slurries. Following pre-incubation, 8 ml of DEA potential solution (56 mg NO3-N L-1, 288 mg C6H12O6 L-1, 100 mg L-1 chloramphenicol) were added to each bottle, creating a slight over pressure in the head space (Smith and Tiedje, 1979); the original protocol by White and Reddy (1999) employed 1g L-1 of chloramphenicol; however, at nearly the same time a report by Murry and Knowles ( 1999) indicated levels of chloramphenicol greater than

PAGE 67

53 100 to 200 mg L-1 may inhibit DEA activity by up to 60%. Samples were incubated in the dark at room temperature (24oC) and continually shaken, and headspace gas was sampled every 1 h for 4 h. A Bunsen absorpti on coefficient of 0.544 was used to adjust for nitrous oxide dissolved in the aqueous phase (Tiedje, 1982) Potential denitrification rates were determined by the calculated slop e of the linear curve produced for cumulative N2O evolution with time. Two milliliters of headspace gas from each sampling time was stored in N2-flushed 2 ml serum bottles sealed with butyl rubber stoppers and aluminum crimp seals for 24 to 48 h until determination of N2O concentrations by gas chromatography. Gas samples were analyzed for N2O on a Shimadzu gas chromatograph (GC-14A, Shimadzu Scientific, Kyoto, Ja pan) fitted with a 3.7 x 108 (10 mCi) 63Ni electron capture detector (300 oC). A 1.8 m by 2 mm i.d. st ainless steel column packed with Poropak Q (0.177 to 0.149 mm; 80 to 100 mesh) was used (Supelco, Bellefonte, PA). The carrier gas was 5% methane in argon (v/v) flowing at a rate of 30 ml min-1 at 30oC. Working standards consisted of N2O in He (Scott Specialty Gas, Plumsteadville, PA). Nucleic Acid Extraction, PCR Amp lification, Cloning and Sequencing Nucleic acids were extracted from 0.25 g of soil with Power Soil DNA Isolation kit (MoBio, Carlsbad, CA, USA) according to th e manufacturer's instructions. Purified DNA extracts were used as template in PCR; amplification was conducted using primer sets designed by Yan et al. (2004), consis ting of primers 583F (5-TCA TGG TGC TGC CGC CKG ACG-3) and 909R (5-GAA C TT GCC GGT KGC CCA GAC-3) which amplify a 326 bp region of nirK and 832 F (5-TCA CAC CCC GAG CCG CGC GT-3) and 1606R (5-AGK CGT TGA ACT TKC CGG TCG G-3) which amplify a 774 bp

PAGE 68

54 region of nirS Each 20 l PCR reaction mixture contained 7 l of distilled water, 1 l of each primer (10 pmol l-1), 10 l of HotStarTaq Master Mi x (Qiagen, Valencia, CA) and one l of template DNA. PCR amplification wa s carried out in a GeneAmp PCR system 9700 (Perkin-Elmer Applied Biosystems, Norwal k, CT). PCR conditions for both primer sets were identical and consisted of the following: an initial enzyme activation and DNA denaturation for 15 min at 95C, followed by 30 s at 94C, 30 s at 60C, and 60 s extension at 72C for 30 cycles and a final extension of 72C for 7 min. PCR products were analyzed by electrophoresis on 1.5% TAE agarose gels. To account for the spatial patchiness of soils and attempt to more fu lly characterize diversity, bulk nucleic acid extracts from all soil samples from within a site were combined. PCR amplicons were ligated into pCRII-TOPO cloning vector and transformed into chemically competent Escherichia coli TOP10F cells according to the manufacturer's instructions (I nvitrogen, Carlsbad, CA). White colonies were screened for correct inserts by PCR amplification using the protocol and conditions described above. Insert-bearing clones were transfe rred to 96-well pl ates containing 200 l of Luria Bertini broth plus 8% (v/v) glyc erol and kanamycin (50 g ml-1). Plates were incubated for approximately 24 h at 37oC, covered with gas permeable membranes (Breath-easy, Diversified Biotech, USA), and transported to the University of Florida Genome Sequencing Service Laboratory for sequencing w ith internal vector-s pecific primers. Phylogenetic and Diversity Analysis Nucleotide sequences were manually aligne d and translated into putative amino acids in Se-Al v. 2.0 a 11 (Rambaut, 1996) and aligned with Clustal v.1.81 (Thompson et al., 1997). Phylogenetic trees were produced for approximately 100 and 250 amino acid

PAGE 69

55 segments of nirK and nirS respectively, using Tejima and Nei corrected distance matrices in the TREECON software packag e (van de Peer an d de Wachter, 1994). Bootstrap analysis (500 resamplings) was used to estimate reproducib ility of phylogenies. Similarities of sequences obtained in this study were compared to those obtained from other studies using BLAST queries (http ://www.ncbi.nlm.nih.gov) of the nucleotide database. Community analyses were performed by generating operational taxonomic units (OTUs) in DOTUR, using the furthest neighbo r algorithm and a 3% difference in nucleic acid sequences. Non-parametric estimates of richness and di versity were calculated using DOTUR (Schloss and Handelsman, 2005), including Chao1, Shannon index, and Simpson index. Statistical Analysis of Phylogenetic Data To assess whether gross differences obs erved between denitrifier populations between sites represented statis tically different populations, well-aligned subsets of each gene fragment were chosen for analysis using -Libshuff (Schloss et al., 2004) with 1,000,000 randomizations and a distance interval ( D ) of 0.01 (Santoro et al., 2006) using Jukes-Cantor corrected pairwi se distance matrices generate d in PAUP (Swofford, 1998). The program employs Monte Carl o methods to calculate the in tegral form of the Cramrvon Mise statistic by constructing random sub-se t populations from the entire data set and comparing the coverage of the generated populat ions to coverage in the experimentally obtained data set. Populations were consider ed significantly different with P value below 0.0026 after a Bonferroni correction for multiple pairwise comparison ( =0.05, n = 20).

PAGE 70

56 Analysis of molecular variance (AM OVA), pairwise comparisons of population specific pairwise fixation indices (FST) (Martin, 2002), and aver age pairwise sequence similarities were conducted with the pr ogram Arlequin (version 3.001, Genetics and Biometry Laboratory, University of Gene va [http://lgb.unige.ch/arlequin]). AMOVA (Excoffier et al., 1992) employs a hierarchica lly partitioned matrix of Euclidean distances to assess by permutation the significance of variance components at each level of partitioning. All analyses were performed under default parameters, with the following exceptions: analyses were conducted at 90,000 iterations and distan ce matrices defined haplotype definitions. FST tests were employed as measures of genetic differentiation between all pairs of samples. The test determines whether samples contain close phylogenetic relatives or more deeply divergen t sequences. Mantel tests (Mantel, 1967; Mantel and Valand, 1970) were implemented in Arelquin and used to test correlations between population specific FST values and geochemical parameters. The method is based on a nonparametric general regressi on model which employs squared Euclidean distance matrices between variables to test significance of and degree of predictability one variable has on another (Dutilleul et al., 2000). Parsimony tests (P-test) were implemented in TreeClimber (Schloss and Handelsman, 2006). Clustal X (version 1.83) was used to generate sequence alignments, constructed under default parameters. Trees were constructed by Bayesian analysis as implemented in Mr. Bayes version 3.1 (H uelsenbeck and Ronqui st, 2001; Ronquist and Huelsenbeck, 2003) under default model parameters, with trees sampled every 1000 generations. All Bayesian analyses were run for 1,000,000 generations, of which 10% were discarded to account for initial divergen ce in log likelihood scor es between chains.

PAGE 71

57 The resultant 990 trees were used for analysis in TreeClimber (http://www.plantpath.wisc.edu/fac/joh /treeclimber.html) and compared to 1,000,000 randomly generated trees. Statistical Analysis of Biogeochemical Data Environmental parameters were tested for significance across treatment groups (study sites) using one-way ANOVA in JMP version 5.1 (SAS Institute) on both log transformed and raw data. Pairwise compar isons of means were conducted in the same software using Tukeys HSD, which account s for unequal variances among samples. Results and Discussion Soil Biogeochemical Parameters Al ong the Restoration Gradient Measured values of nitrate, ammoni um, and organic matter content (loss on ignition) in HID soils ra nged from 1.8 to 6.8 mg kg -1, 15.2 to 49.5 mg kg -1, and 14.19 to 23.9 %, respectively; values for these parame ters did not differ significantly across sites (ANOVA, p < 0.05). Potential Denitrifying En zyme Activity (DEA) ranged from 0.12 to 1.15 mg N2O-N kg-1 hr -1; DEA rates for UND, R89, and R00 sites were significantly different from R97, R01, and R03 sites ( ANOVA, p < 0.05). There was no evident trend in DEA associated with restoration age or other measured environmental parameters, although there may be disparity between actual a nd potential activities of denitrifiers in soils. Tiedje (1988) suggested that lab-base d determinations overestimate field activity 40 to 100 times. Values reported in this study are within the range of values reported in surface soils from oligotrophic regions of th e Everglades using similar methods (White and Reddy, 1999), as well as those reported from riparian (Schipper et al., 1993) and agricultural soils (Pell et al., 1996, Espinoza, 1997). Alt hough there was no clear trend

PAGE 72

58 associated with DEA and recovery stage in HID soils, statistical analysis (randomized complete block design, ANOVA) of site e ffects on biogeochemical data indicated significant ( = 0.05, P < 0.0001) within-site effects on DEA. This may indicate that, while there does not seem to be an obvious or homogenously controlling factor on DEA along the restoration gradient activity may be more str ongly controlled by different factors within each restoration site. Interestingly, relatively high DEA activ ities were observed in the two most recently restored sites, despite having less than 3 cm of soil and moisture contents similar to all other sites (Table 3-1). DEA activit y may be spatially patchy, and is thought to occur in response to hot-spots within soil mi cro-aggregates (Parkin, 1987). Further, senescing plant material and leaf litter may support anaerobic processes (Kusel and Drake, 1996); Parkin (1987) observed that carbon inputs from a single leaf were sufficient to support 85% of observed denitrification. A previous investigation of DEA in Ever glades soils reported 3 to 30 fold higher activity in marl than peat soils from the Everglades (Gordon et al ., 1986). Our results suggest less activity in marl so ils compared with values from peat soils reported by White and Reddy (1999) the disparity may be due to lo wer soil depth at our sites, or that marl sampling sites differed in hydrologic features. Interestingly, potenti al denitrification from the two marl soils showed identical patterns (Gordon et al ., 1986; this study); dentrifying populations in all but R00 soils showed no lag in response following nitrate addition. Nitrate accumulation was approxima tely linear over the course of the 4h incubation. This indicates denitrifying enzyme systems were fully induced in most sites.

PAGE 73

59 nirS phylogeny nirS -type denitrificat ion genes were obtained from all HID study sites, and grouped into six (I to VI) dis tinct phylogenetic clusters (F igure 3-1), the relative abundances of clones from each library are pres ented in Table 3-2. Seventy-five percent amino acid similarity in DOTUR grouped se quences into phylogene tically distinct clusters. Genes from all clusters shared 78 to 98% similarity of amino acids with previously obtained environmental clones in GenBank. Most notably, of the 117 clones obtained from all study sites, 58% shared gr eatest similarity with environmental clones obtained from a Michigan wetland; nucleoti de sequence similarities ranged from 80 to 98%. Clones of this sequence type may repr esent a group of uncultivated denitrifying bacteria that are physiological ly adapted to wetland ecosystems (Priem et al, 2002). Thirty percent of all clones were 80 to 87% similar to uncultivated denitrifying bacteria inhabiting high nitrate brackish ground waters in California (Santoro et al., 2006). The remaining 12% of obtained sequences vari ed in similarity from 76 to 86 % to environmental nirS obtained from wetland soil s incubated under elevated CO2 (Lee et al., 2005), activated sludge (Ohsaka et al., 2004), or Baltic Sea cya nobacterial aggregates (Tuomainen et al., 2003). Clusters I, II, and III shared relatively high average pairwise sequence similarities, ranging from 92 to 97%; these sequence type s may represent more abundant NirS-type denitrifiers common to all HID soils. Clusters IV, V, and VI comprised the lower portion of the tree, and consisted of loosely associat ed divergent lineages, with little apparent redundancy in the library (Figure 3-1, Table 3-2). Of the six designated phylogenetic clusters, only Cluster VI sequences were similar to nirS of previously characterized

PAGE 74

60 denitrifiers, and shared 71 to 75% of predic ted amino acids with organisms of the alphaproteobacterial genera Thauera and Azoarcus or the beta-proteobacterial Magnetospirillum spp. Cluster VI was comprised of sequences from all HID sites. However, sequence similarity is too low to confidently conclude that Cluster VI nirS genotypes obtained in this study belong to organisms within these genera. Sequences from all other clusters showed low similar ity to cultivated denitrifiers based on both nucleotide and putative amino acid BLAST search es. With the exception of Cluster III sequences, which showed ca. 95% similarity to uncultivated or ganisms from wetland soils, nirS genotypes obtained in this study shar ed less than 85% similarity with previously reported sequences, and may be indicative of a unique assemblage of denitrifying bacteria in HID soils. nirK phylogeny Phylogenetic diversity was apparent from analysis of the 158 obtained nirK sequences (Figure 3-2). Cl ones obtained from all study s ites grouped into 12 distinct phylogenetic clusters; within cluster sequence similarities ranged from 85 to 98% (Figure 3-3). Additionally, nirK clone libraries, more so than nirS contained a number of deeply branching divergent singletons from all sites: REF (7), R89 (3), R97 (6), R00 (5), R01 (4), and R03 (5). The relative percentages of sequence types within each cluster are presented in Figure 3-3. Of the 158 sequen ces included in the phyl ogenetic analysis, 66 (42%) shared 90 to 91% similarity with envi ronmental clones previously obtained from a wetland soil; these sequences co mprised clusters A through E, and were obtained from all restoration sites (Figure 3-3). The remaining clusters (F through L) each formed distinct, deeply branching clades. Cluster F se quences were 84 to 92% similar to nirK genes

PAGE 75

61 obtained from a potentially novel group of unc ultured denitrifiers in fertilized upland soils (Wolsing and Priem, 2004). Cluster G clones were 82% similar to environmental sequences obtained from peat (Throbck et al., 2004), and shared 79 to 80% similarity with nirK of Alcaligenes xylosoxidans Cluster H sequences shared greatest similarity with uncultivated denitrifiers obtained from forest soils (Priem, 2002). Sequences comprising Cluster I were 93% similar to those in Bradyrhizobium japonicum Cluster J clones were 92% similar to nirK of Ensifer sp. 2FB8. Clusters K and L clones were 73 to 84% similar to environmental clones from m unicipal wastewater (Throbck et al., 2004). Those comprising Cluster L were also 81 to 87% identical to sequences reported for Sinorhizobium meliloti Overall, the majority of both nirS and nirK sequences obtained in this study shared less than 90% sequence similarity with previously reported environmental sequences. While the exact cut-off of se quence similarity to previously reported environmental clones or cultiv ated isolates for either gene is not known, previous reports have employed a cut off of 75% nucleotide similarity as the threshold for claiming recovery of novel nir genes. This is based on the obs ervation of an approximately 75% shared nucleotide identity between the alpha-, beta-, and gamma-proteobacteria (Yan et al., 2003). In consideration of this, and the fact that the majority of sequences obtained in this study shared no significant similarity to cultivated organisms upon BLAST search, it may be likely that our sequences repres ent several lineages of novel denitrifying organisms. However, the existence of den itfying bacteria from previously characterized lineages within the alphaand beta-Proteoba cteria are evident in both clone libraries (Cluster IV in Figure 3-1; Cl usters I and J in Fig 3-2).

PAGE 76

62 While the occurrence of novel lineages of denitrifiers based on studies of both nirS and nirK have been reported (Yan et al., 2001; Priem et al., 2002; Liu et al., 2003), the uniqueness of such results may not be uncommon when certain factors are taken into consideration: i) functional gene diversity is generally gr eater than 16S rRNA diversity (Ward, 2002); and (ii) the abil ity to denitrify spans all three kingdoms of life (Ward, 2002). The pertinent point regard ing novel groups to this study is not their existence, but that soils from each of the HID study sites appear to harbor uniquely divergent populations of denitrifiers. Richness and Diversity of nirS and nirK Populations Rarefaction analysis was used to compare richness of nir clone libraries in the context of restoration stage. OTUs were defined by DOTUR using a 97% DNA sequence similarity cutoff. Rarefaction indicated nirK and nirS richness to be approximately similar between all restoration sites; how ever, there was a clear difference in OTU richness between populations in UND soils. With the exception of the UND nirS curve, which was nearing a plateau, curves for all lib raries were steeply sl oped at the respective cut off points for sequences obtained from each site, suggesting that our clone libraries do not represent the entire divers ity of the denitrifying populat ions. Coverage values for nirS and nirK clone libraries for each site are pr esented in Table 3-3. Coverage for nirS libraries ranged from 45 to 90%, R01 and R03 libraries had the highest and lowest coverage values, respectively. nirK coverage values ranged from 45 to 100%, and were highest for the UND library and lowest for the R01 library. Both Simpson and Shannon diversity indices indicate nirS libraries to be the most diverse in restoration study s ites; UND soils maintain greater nirK diversity (Table 3-3).

PAGE 77

63 Greater diversity of nirS relative to nirK has been previously observed in wetland soils (Prieme et al., 2002), groundwaters (Yan et al ., 2001; Santoro et al., 2006), and sediments from a marine oxygen minimum zone (Liu et al ., 2003). Differences in diversity are more clearly pronounced in Simpson values versus Shannon values (Table 3-3); this difference may be due to the stronger influence of library eveness on Shannon values (Magurran, 2004). Further, the log-transformed Simpson va lues presented in Table 3-3 are sample size independent estimates (Magurran, 2004). There is a clear i nverse relationship between nirS and nirK population diversities within sites. This relationship has also been observed in both marine (Braker et al., 2000) and terrestrial environments (Priem, 2002; Yan et al, 2003), and may suggest that di fferent environmental parameters alter abundances of organisms containing nirS or nirK and that community dynamics of each group may alter dynamics of the other (Yan et al., 2003). However, detailed discussion of HID site parameters controlling diversity of nir genotypes using the presented diversity and richness estimates must consider that fact that the estimates presented here are based on clone libraries that do no t represent the entire diversity of nir populations. Attempts to correlate measures of diversity or richness with geochemical parameters or restoration age yielded no significance. Prev ious studies have also failed to make significant correlations between diversity or richness measures and environmental variables (Yan et al., 2003; Sa ntoro et al., 2006). The inabil ity to correlate statistical measures of community composition with geoche mical parameters may be due in part to the relatively poor understanding we have of factors controll ing diversity of nir genotypes in the environment, or that co mmunity structure is controlled by less quantifiable factors (S antoro et al., 2006).

PAGE 78

64 Population-Based Library Compositions Iterative statistical analyses were employed to asse ss significant differences in population composition between restoration sites. UND sequences for either nir genes were excluded, as the focus of this study was to assess nir population dynamics in the context of disturbance recovery. Not only wa s the UND site never di sturbed, it is not at the same successional stage as th e restoration study sites. To assess gross differences in nir populations represented by our clone libraries, Libshuff (Singleton et al., 2001; Schloss et al., 2004) was employed. By comparing random permutations of sequences from tw o libraries, determination of whether two clone libraries are likely to re present samples drawn from sta tistically distinct populations can be made. The asymmetrical nature of th e test allows for the determination of clone libraries as distinctly different, drawn from the same population, or if one library is the subset of another. If libraries X and Y do not share common ancestry, comparisons of both will result in significant P values (bold in Table 3-4). However, if library X is statistically different from libra ry Y, but Y versus X is not, Y is a subset of X. In cases where homologous (within one library) and heterologous (between two libraries) coverages differ significantly, one can be reasonably certain that the samples are drawn from different populations (Sch loss et al., 2004). Advantages of the method are that it operates on an individual sequence level, rather than the arbitrary assignment of OTUs, and does not consider clone fr equency (Singleton et al., 2001 ; Schloss et al., 2004). This method of community differentiation was deve loped for 16S rRNA gene libraries, but has been used to differentiate functional gene libraries (Horn et al., 2006; Yannarell et al.,

PAGE 79

65 2006;), including nirS and nirK (Santoro et al., 2006), obtai ned from sites at different successional stages (Dunfield and King, 2004; Nanba et al., 2004). Further, to test whether observed phyl ogenetic structures ar e the result of random variation, parsimony tests were employed. Th e test assesses the probability that phylogenetic patterns observed in user-c onstructed trees varies from randomly constructed trees after multip le iterations (Schloss and Handelsman, 2006). If the observed patterns are due to random variati on, than user-generated trees would have similar parsimony scores as randomly generate d tress. The null hypothesis of the analysis is that the compared communities share an ancestral community structure and observed patterns are due to accumulation of random va riation; significance indicates observed phylogenetic differences between tw o communities to be the resu lt of selective pressures, such as perturbation, that force differentiati on within treatment populations (i.e gain or loss of groups) (Schloss and Handelsman, 2006). The approach of the two tests differs and must be noted. -Libshuff is based on a continuous statistic, measures community me mbership (the presence or absence of individuals within a pop ulation), and is relatively less sensitive to library size (Schloss et al., 2004). The parsimony (P) test is based on a discrete statistic, measures community structure (the distribution and abundances of individuals within a population), and is more sensitive to library size (Schloss and Handelsman, 2006). However, library sample sizes approximately equal to those employed by this study have been proven effectively large enough for both tests (Singleton et al ., 2001; Dunfield and King, 2004; Nanba et al., 2004; Schloss et al., 2004; Schloss and Handelsman, 2006).

PAGE 80

66 Results of the nirS analysis indicate that most sequences obtained from each site are site-specific (Table 3-4). Further, the shared similarity between sites most closely related in time since restoration do not diffe r significantly; this may indicate a succession of shared lineages between the most closely relate d or all restoration site s. As seen in the phylogenetic analysis, several clusters were comprised of sequences obtained from all sites. However, the deeply divergent taxa a ppear to be unique to each site, and are likely responsible for much of the di fference between restoration site s. Analysis of community covariance with phylogeny, as implemented in TreeClimber, confirms that community structures from each site are significantly di fferent (P < 0.02); removal of any site from the analysis did not lead to loss of signifi cance, and pairwise comp arisons of all sites were significantly different (P < 0.02). Prio r studies that removed distinct groups for P test analysis discerned groups responsible for differentiat ion (Martin, 2002; Schloss and Handelsman, 2006). However, the consistency of P values upon library removal in this study suggests that each site harbors di stinct and unique divergent lineages. Succession of shared sequence types was not as clear when nirK clone libraries were analyzed with -Libshuff (Table 3-4). R03 and R 01 clone libraries were drawn from the same population, which is a subset of the R00 library. The R00 library differed significantly from R97 and R89 libraries, how ever, R89 and R97 libraries had shared lineages. A P test including all populations indicated signif icant differences (P = 0.032), and pairwise comparisons for all sites were also significant (P < 0.02). Thus, while the more recovered sites (R89 and R97) sh are an underlying comm unity, both harbor unique lineages of denitrifiers, possibly sel ected for by disturbance recovery stage. A comparison of sites grouped into two data se ts consisting of more and less recovered

PAGE 81

67 clone libraries yield the lowe st significance value of any nirK library comparisons (P = 0.012). Removal of R97 or R00 libraries from analysis lead to loss of significance between groups (P = 0.08 for R97 and P=0.06 for R00), however when the two libraries were compared they were significantly different. Thus, consistent with -Libshuff analysis, this indicates a divi de in population composition betw een early (< 6 yr) and late (> 6 yr) restoration sites, and suggests that R97 and R00 sites harbor more divergent lineages or that populations differ si gnificantly from R89, R01, or R03. Statistical analyses of nirS suggest shared lineag es along the restoration chronosequence. Though it was not addressed in this study, it is likely that Cluster A sequences, which were obtained from all sites represent a group of deni trifiers native to HID soils, regardless of disturbance st age. Interestingly, analysis of nirK libraries indicates a bimodal response to recovery stage, with sites closer in disturbance recovery sharing similar, but distinct, communities of denitrifiers. Alte rnatively, R00 and R97 sites, for which these analyses sugges t harbor different populations, may be representative of intermediate states of disturbance. Ac cording to the Intermediate Disturbance Hypothesis, ecosystem s at intermediate stages of recovery from disturbance harbor the greatest species diversity (Connell, 1978). Consistent with nirK variation, geochemical da ta show a similar, but insignificant, trend. Soils in later successi on sites share similar related organic matter, nitrate, and ammonium contents (Table 3-1) th an sites at early stages of recovery. While it may seem contrived, the variability in the data should not hinder inferences based on geochemical trends. Geochemical analyses were conducted on trip licate composite soil samples; each representative sample was comprised of three soil samples taken at relative

PAGE 82

68 depth intervals (shallow, medium, deep) with in each site. Compositing of samples was done in this manner to account for varia tions in both bedrock surface topography and spatial differences in regions of soil accretion. At successional stages as early as those in the HID, spatial patchiness is inevitable, and likely to overwhelm statistical differentiability. Several previous studie s have observed different responses of nirS -and nirK -type denitrifying communities to environmental gradients; in several cases nirK showed greater habita t selectivity (Throbck et al., 2004; Wolsing and Priem, 2004; Santoro et al., 2006), however, the opposite ha s also been reported (Liu et al., 2003, Yan et al., 2003). Variance within nirK Clone Libraries To further test the observed trends in ge netic variation in denitrifier communities among restoration sites, analysis of mo lecular variance (AMOVA) was implemented (Excoffier et al., 1992); AMOVA has been prev iously applied for differentiation between community structures based on functional ge nes (Dunfield and King, 2004; Nanba et al., 2004; Yannarell et al., 2006). Only nirK libraries were chosen for this level of analysis, due both to the observed difference in res ponse to recovery and discrepancies in nirS phylogenetic analysis in previous st udies. Some studies correlating nirS response to environmental gradients have included (Bra ker et al., 2000; Prie m et al., 2002) or excluded (Santoro et al., 2006) regions of in sertion or deletion for sequence alignments and phylogenetic analysis. AMOVA estimates the significance of differences in population pairwise fixation indices (FST). FST values for a population, or group of populations, are an indication of genetic differentiation; in the case of molecular ecology, it is a representation of within population dive rsity relative to to tal population diversity

PAGE 83

69 (in this case, diversity of pool ed sequences to diversity of libraries from each site) (Martin, 2002). Pairwise comparisons of FST values for each site reveal whether genetic diversity between sites differs (Martin, 2002). In relation to total population diversity, low FST values indicate that diversity of the indi vidual community is similar to that of the two communities combined (Martin, 2002). Variation of nirK populations within sites account ed for approximately 98% of variance, only 2% was due to variation between libraries from each site. The large percentage of variation within popula tion further confirms the uniqueness of nirK communities from each site. Although small, variance in diversity between populations differed significantly from pooled populations (P = 0.013), consistent with results of the parsimony test, and further confirms the exis tence of unique lineages of denitrifiers within each restoration site. FST values for each site declined with tim e since restoration; these values are measures of genetic diversity within population compared to the total population. The general decline in values with time since restoration suggests that populations of denitrifiers become more reflective of total observed diversity in HID soils as recovery progresses. Further, FST values confirm the results of -Libshuff analysis: FST values between sites nearer in recovery stages are closely related. Values for R89 and R97 range from 0.030 to 0.033 and values for R00, R01, and R03 range from 0.045 to 0.042. This bimodal trend is also evident in average pairwise sequence similarity ( [ ]) and nucleotide diversity (Table 3-6). Pairwise comparison of population FST and [ ] values are presented in Table 3-6. Results for comparison of both values be tween sites are identical, as both are de facto

PAGE 84

70 measures of within-populati on diversity. Signif icance of both tests implies genetic diversity within sites is less than for site s combined, but that each harbors distinct phylogenetic lineages; this is the case for the R89 community. Insignificance of FST paired with significant P tests, which is th e case for pairwise comparison of R97, R00, R01, and R03, is indicative of high diversity within each of these populations and that each harbors different phylogenetic lineages; this can occur when each population is comprised of many ancient lineages that do no overlap (Martin, 2002). A Mantel (Mantel, 1967; Mantel and Va land, 1970; Dutilleul et al., 2000) test was used to examine the correlation between pairwise differences in nirK population-specific FST values between sites to matrices of pairwi se differences in geochemical parameters. Such analyses have been used previously to test whether observed differences in functional gene diversity correlated with ge ochemical variables be tween sampling sites (Francis et al., 2003). The Mant el test judges whether closene ss of one set of variables is related to closeness in another set of variables. In the cont ext of this study, the test was employed to determine correlations between observed differences in nirK diversity between sites and measured environmental pa rameters along the ch ronosequence, and to ultimately gain an understanding of environm ental factors most likely controlling the observed differences in nirK -type denitrifier populations in HID soils. Pairwise FST matrices were tested for correlation with environmental factors most likely controlling denitrifier activity: organic matter (loss on ignition), mois ture content, and soil oxygen demand. Differences in nirK FST values between sites were strongly correlated with differences in soil moisture content (r = 0.895, P=0.017), and marginally with differences in organic matter content (r = 0.61, P = 0.05). The results suggest that soil moisture plays

PAGE 85

71 a strong role on nirK population diversity within each si te, and may be used to explain differences in populations between sites. Conclusions Little work to has been done to charac terize denitrifying microbial communities in wetland ecosystems. Further, this is the fi rst study to characteri ze the development of wetland communities of denitrifying bacteria in response to severe disturbance. While geochemical data in sites of varying stages of recovery since complete soil removal suggest loose trends associated with time since restoration, seve ral lines of evidence indicate the existence of si gnificantly different populations of denitrifying bacterial communities at each of the study sites. nirS clone libraries suggest an approximately linear response with time since disturbance, while nirK sequences appear to respond bimodally. In either case, this suggests that diversity of functiona lly redundant enzymes results from adaptation to particular envi ronments. The factors governing community diversity are not entirely clear. However, th e most obvious variable is recovery stage, the gradual accumulation of nutrients, soil and asso ciated moisture, and the maturing of plant communities. Further, results of AMOVA i ndicate population diversity within sites to decline with time since restor ation, which may indicate a gr adual decrease in species recruitment as conditions within each site converge toward stability. These results highlight the sensitivity of denitrifying bacterial communities to environmental conditions, and provide insight into microbial community dynamics in response to ecosystem recovery.

PAGE 86

72 Table 3-1. Biogeochemical pa rameters of HID soils as measured in November 2005. Site Soil Depth (cm) Moisture (% ) LOI (%) NH4 +-N (mg kg-1) NO3 --N (mg kg-1) Denitrification Potential UND 10 (2-15) 43.8 (0.6) 16.71 9.9 (0.9) 6.8 (0.5) 0.51 (0.14) R89 6 (1-17) 59.6 (2.4) 14.38 46.9 (1.9) 3.1 (0.5) 0.48 (0.14) R97 5 (3-11) 58.8 (4.5) 14.19 49.5 (10.8) 1.8 (0.6) 1.01 (0.27) R00 3 (1) 48.3 (1.4) 23.90 25.1 (7.7) 7.8 (2.8) 0.12 (0.03) R01 3 (1-7) 41.6 (1.1) 23.58 15.2 (5.1) 6.5 (2.8) 1.15 (0.33) R03 1 (0-3) 43.5 (10.1) 18.86 26.9 (9.2) 5.1 (2.8) 0.77 (0.11) Values in parentheses are stan dard deviations of the mean of three replicate samples. Potential denitrifying enzyme activity expressed as milligrams of N2O-N per kilogram soil per hour. Table 3-2. Distribution of nirS sequences from each study site within designated phylogenetic clusters. Relative abundance of sequences from each clone library (%) Cluster UND R89 R97 R00 R01 R03 Average similarity (%)a No. of sequences I 32 11 7 27 9 14 97 (4) 44 II 36 0 18 18 0 27 92 (12) 11 III 0 0 16 32 32 21 97 (4) 19 IV 0 13 25 13 25 25 83 (20) 8 V 9 36 14 23 5 14 79 (18) 22 VI 8 23 15 8 15 31 72 (16) 13 aBased on pairwise comparison of deduced am ino acid sequences within each cluster, values in parenthesis are sta ndard deviations

PAGE 87

73Table 3-3. Values of nirS and nirK diversity and richness in HID soils, as estim ated by Shannon diversity index, Simpson index, and Chao1 richness calculated using DOTUR (Schloss and Handelsman, 2005). Site and gene No. of clones sequenced No. of OTUsa Shannon index Diversityb Richnessc No. of singletons Coveraged (%) nirK UND 28 13 2.3 (1.9, 2.6) 2.5 20 (13, 54) 6 100 R89 28 12 2.3 (1.8, 2.5) 2.2 22 (14, 66) 7 69 R97 25 11 2.0 (1.7, 2.4) 1.9 21 (13, 65) 7 86 R00 30 16 2.4 (1.9, 2.8) 2.1 38 (21, 102) 12 72 R01 24 12 2.3 (1.9, 2.6) 2.4 19 (13, 48) 7 45 R03 23 12 2.2 (1.9, 2.6) 2.3 26 (15, 79) 8 71 ALL 158 NirS UND 21 8 1.8 (1.4, 2.1) 1.8 11 (8, 31) 4 48 R89 17 10 2.2 (1.8, 2.5) 2.7 15 (11, 39) 6 56 R97 15 16 2.7 (2.4, 3.0) 3.7 32 (20, 80) 12 67 R00 27 16 2.6 (2.2, 2.9) 2.8 82 (38, 212) 12 76 R01 15 12 2.4 (2.1, 2.7) 3.1 16 (13, 34) 7 90 R03 22 18 2.8 (2.5, 3.1) 3.8 53 (27, 144) 15 45 ALL 117 aEstimates of OTUs, Shannon index, diversity an d richness are all based on 3% differences in nucleic acid sequence alignments; values in parantheses are upper and lower bounds of 95% confidence intervals as calculated by DOTUR. bSample size independent estimate of diversity based on negative natural log transformation of Si mpsons index values as calcula ted in DOTUR. cChao1 values, a non-parametric es timate of species richness. dCoverage values for at dist ance = 0.01, as calculated by -Libshuff (Schloss et al., 2004).

PAGE 88

74 Table 3-4. Population similarity P values for comparison of nirK and nirS clone libraries determined using Cramer-von Mises test statistic, implemented in -Libshuff (Schloss et al., 2004). Gene (n) P values for comparison of heterologous library ( Y ) with Xa Site for homologous library ( X ) R89 R87 R00 R01 R03 nirK (158) R89 0.036 0.000 0.000 0.000 R97 0.400 0.000 0.000 0.000 R00 0.000 0.000 0.000 0.000 R01 0.000 0.000 0.040 0.957 R03 0.000 0.000 0.000 0.304 nirS (117) R89 0.421 0.000 0.000 0.000 R97 0.125 0.040 0.000 0.000 R00 0.000 0.210 0.056 0.000 R01 0.000 0.000 0.269 0.000 R03 0.000 0.000 0.000 0.000 aValues in bold indicate significant P values (P < 0.0017)after Bonf erroni correction for multiple pairwise comparisons. Libraries are distinct from one another if both comparisons (X versus Y and Y versus X) are si gnificant. Values in italics indicate that library Y is a subset of library X.

PAGE 89

75 Table 3-5. Corrected average pairwise differences ( [ ]), above diagonal) and pairwise fixation indices (FST, below diagonal) for nirK Result for study sitea: Site R89 R97 R00 R01 R03 R89 4.312 1.344 3.201 4.564 R97 0.060 3.021 1.569 1.825 R00 0.029 0.049 0.905 0.922 R01 0.048 0.028 0.015 -1.031 R03 0.069 0.034 0.016 -0.023 aBold values are sign ificant at P < 0.05. Table 3-6. Fixation indices, av erage pairwise differences ( [ ]), nucleotide diversity, and shared haplotypes of nirK clone libraries as calcul ated by Arlequin (Excoffier et al., 1992). No. of shared haplotypes Site FST [ ] Nucleotide Diversity No. of unique haplotypes R89 R97 R00 R01 R03 R89 0.030 89 (44) 0.25 (0.12)a 23 1 1 2 1 R97 0.033 83 (37) 0.24 (0.11)a 21 2 4 3 3 R00 0.042 66 (29) 0.19 (0.01)b 28 1 4 3 4 R01 0.043 64 (27) 0.18 (0.01)b 17 2 3 3 3 R03 0.045 62 (28) 0.17 (0.09)b 18 1 3 4 3 Values sharing same letter notation are not statistically different, based on pairwise Students t-test (P 0.05).

PAGE 90

76 Figure 3-1. Neighbo r-joining tree of nirS sequences obtained from wet season soils. Values on nodes are bootstrap scores based on percent occurrence of 1000 resamplings.

PAGE 91

77 Figure 3-2. Neighbor-joining tree of nirK sequences obtained from wet season soils. Values on nodes are bootstrap scores after 1000 resamplings.

PAGE 92

78 Figure 3-3. Sequence analysis of nirK clones obtained from wet season soils. Sequences were grouped into clusters (A to L) based on inspection of alignments, distance data, and neighbor-joining tr ees. Percent similarity is based on comparison of putative amino acids and was determined between all members of each group(s). The percentage of each nirK sequence types recovered from each site is listed in the table next to the figure. Asterisk represents sequences that could not be readily assi gned to a cluster (singletons).

PAGE 93

79 CHAPTER 4 SEASONAL DIVERSITY AND FUNCTION OF AMMONIA OXIDIZING BACTERIA ALONG A SHORT-TERM REST ORATION CHRONOSEQUENCE As the linking process between organi c nitrogen mineralization and loss of biologically preferable forms of inorganic nitrogen, nitrificat ion is a determinate process in the availability of N within an ecosystem and an influential factor on productivity of plant and microbial communities. Nitrificat ion is a two-step process involving two distinct groups of bacteria. The first, the conversion of ammonium to nitrite is mediated by ammonia oxidizing bacteria ( AOB); the second step is th e conversion of nitrite to nitrate, and is mediated by nitrite oxidizi ng bacteria (NOB). The most common ratelimiting step is the conversion of ammonium to nitrate, carried out by AOB. The first step involves conversion of ammoni a to hydroxylamine by ammonia monooxygenase (AMO), while hydroxylamine oxidoreductase converts hydroxylamine to nitrite (Hooper et al., 1997). Nitrate produc tion due to heterotrophic bact erial activity has also been observed, though it is generally limited to condi tions of high carbon-to-nitrogen ratios or acidic soils (Pedersen et al., 1999; Bothe et al., 2000; Kowalchuck and Stephen, 2001). Chemolithotrophic AOB are thought to be the majo r contributors to ni trification in soil, sediment, marine, freshwater, and estuarine environments (Belser, 1979; Bothe et al., 2000). All AOB possess amoA which codes for the alpha-subunit of AMO. Early characterization of AOB divers ity within the environment i nvolved the use of 16S rRNA gene specific primers (Stephen et al., 1996; Kowalkchuk and Stephen, 2001); these

PAGE 94

80 studies revealed significant patterns in phylogenetic cl ustering of AOB sequences putatively in response to environmental pa rameters. However, ribosomal DNA does not provide significant evidence of function. F unctional genes maintained by an organism define its interaction with the environment. They evolve faster and may provide greater phylogenetic resolution. Recent work by Purkhol d et al. (2000) revealed a congruence of phylogenetic clustering between amoA and 16S rRNA genes of AOB, allowing for correlation of amoA clusters with established 16S rRNA clusters, and subsequently providing further insight into possible mechanisms controllin g the ecology of organisms within the established clusters. Si nce the initial identification of amoA as a molecular marker of AOB diversity in the environm ent (Rotthuwae et al., 1997), diversity and structure of AOB populations have been studied along environm ental gradients and correlated with shifts in environmental vari ables in successional grasslands (Kowalchuk et al., 2000), estuarine sedi ments (Francis et al., 2003) wastewater bioreactors (Rotthuwae et al., 1997), marine environments (Mullan and Ward, 2005), and in response to global change (H orz et al., 2004). Despite clear evidence of AOB activity in wetlands and other anoxic systems (Reddy and Patrick, 1984; Laanbroek and Wo ldendorp, 1995), relatively little work has been done to characterize dynamics of AOB populations or nitrific ation activity in wetland soils (Duncan and Groffmann, 1994; Wh ite and Reddy, 2003). To date, the only study to characterize wetland AOB using mol ecular approaches was conducted in a manure-impacted treatment wetl and (Ibekwe et al., 2003). Oxygen transport by aerenchymatous plant tissues to saturate d soils establishes oxygenated microsites within the rhizosphere conducive to AOB activity (Reddy and

PAGE 95

81 Patrick, 1984; Kowalchuk et al., 1998). Diffu sion gradients of re duced and oxidized compounds between aerobic microsites and anoxic bulk soil, or between sedimentsurface water column exchange, may provide sufficient supply of resources to maintain nitrifying activity under flooded conditions (Reddy et al., 1989). Further, seasonal inundation provides a unique opportunity to study the response of nitrification and AOB in concert with shifts in availability of regulatory substrates such as oxygen and ammonium. Primary succession is the development of plant and microbial communities on bare substrate. Parent substrate usually c ontains sufficient amounts of mineral nutrients, such as phosphorous, but generally harbors negligible amounts of bioavailable N (Vitousek et al., 1989). Thus, nitrogen inputs to developing ecosystems likely originate from exogenous sources, such as atmospheri c fixation and rainwater. Successional changes in the availability of N have received much attention, in particular because N most often limits primary production in te rrestrial ecosystems (Vitousek and Howarth, 1991). It has been hypothesized that successi onal changes in nitrate production have substantial effects on ecosystem level N losses. Nitrification has been implicated as the primary mechanism of N loss during succession in upland soils (Robertson and Vitousek, 1982). Further, Rice and Panchloy (1972) hypot hesized that nitrification generally decreases with successional stage due to inhi bition of nitrifying bacteria by plant allelochemicals in later successional stages. While several studies have proven this hypothesis to be true in the context of primary to secondary succession (Rice and Pancholy, 1972; Robertson, 1982; Robertson, 19 89), nitrification rates in ecosystems

PAGE 96

82 undergoing primary succession have indicate d the opposite (Robertson and Vitousek, 1981). Sequential development of microbial and plant communities in concert with soil accretion in HID sites at diffe ring stages of disturbance recovery provides an excellent opportunity to characterize the dynamics of nitrification and AOB during a critical stage of initial ecosystem recovery. Specifically, th is study sought to: (i) explore nitrification activity during early stages of primary succession, by assessing the activity of AOB concurrent with the development of soils; a nd (ii) characterize th e activity and population genetic structure of specific genotypes of AOB across seasons and time since restoration, in hopes of elucidating factors that contro l activity and guild composition within and between seasons both within each site and along the restoration gradient. Materials and Methods Site Description, Sampling, and Biogeochemical Characterization Samples were collected in Novemb er 2004 and May 2005. Plots 20 x 20 m2 were established in sites restored in 1989, 1997, 2000, 2001, and 2003 (R89, R97, R00, R01, and R03, respectively), and in an undisturbed site (UND). Th e range of elevation for the five plots was 0.5 to 0.6 m. Within each sampling area, 2 x 2 m2 grids were used to establish 81 sampling nodes, which were mon itored for soil depth, ground coverage, and elevation. Nine nodes were chosen based on re lative range of soil dept h within each site, 3 from each depth range (shallow, intermediate, deep). Sampling nodes were color coded and marked for future sampling efforts. So il samples were taken with a plastic coring device; however, due to non-unifo rm soil cover in recently restored sites, grab samples were collected where appropriate. Indivi dual samples from each depth range were combined to make three representative soil samples, which were used for molecular and

PAGE 97

83 geochemical analyses. Soil samples were kept on ice and transported to the laboratory within 72 h of the collection, where they we re manually mixed and large roots removed. Subsamples for DNA analysis were stored at -70 C until analysis. Biogeochemical analyses were conducted at the Wetland Bi ogeochemistry Laboratory (DAngelo and Reddy, 1999; White and Reddy, 1999). Values for select parameters are presented in Table 4-1. Determination of Potential Nitrification Rates Nitrification potential activities of HID soils were determined using the shaken soil slurry method of Hart et al. (1994). Nine random samples were taken from 20 x 20 m2 plots within each study site. Samples were sieved through 2 mm mesh, and nine 50 g sub-samples were combined to make a composite for each site. Composite samples were divided into five 15 g replicates. Each soil sample was suspended in 1mM phosphate buffer (pH 7.2) and amended with 1.5mM (NH4)2SO4. Samples were shaken in autoclaved, acid rinsed 250 mL Erlenmeyer fl asks in the dark for 24 h at 180 rpm and 24oC. Aliquots (10 mL) of soil slurry were taken for NO3 analysis at 5 time points (0, 2, 4, 8, 20, 24 h) and frozen at -80oC until analysis. Nitrate concentrations were determined by conversion to nitrite by shaking with cadmium (Jones, 1984). For determination of nitrate, 10 ml samples from each time point and replicates were centrifuged at 5000 rpm for 5 min to separate soil particles from buffer solution. Then, 2 to 2.5 mg of s pongy cadmium and 1 ml of 0.7 M ammonium chloride (pH 8.5) were added to 5 ml aliquo ts of buffer from each sample, in 10% HClrinsed 15 ml conical centrifuge tubes (BD Bi osciences, San Jose, CA, USA), and shaken on a rotary shaker at 100 rpm for 1.5 h.

PAGE 98

84 Spongy cadmium was generated by reaction of 20% (w/v) cadmium sulfate with one zinc bar (Sigma-Aldrich, St. Louis, MO, USA) for 8 h; spongy cadmium which precipitated on the surf ace of the zinc bar, was scrappe d off into a clean container, acidified with 3 drops of 6N HCl, and washed with 18 M distilled deionized water (DDW) six times. Until use, spongy cadmium was stored under DDW. Activated cadmium was prepared by washing with 6N HCl solution for five minutes, and then rinsed ten times with DDW (at which point th e pH of decanted waters was approximately pH 5 or greater). Colorimetric determination of nitrite c oncentrations were don e by reacting 5 ml of sample solution with 100 l of combined diazotizing and coloring agents (0.05 g sulfanilamide, 0.05 g N-(1-naphthyl) ethylened iamine, 5 ml of 85% phosphoric acid, and water to final volume of 50 ml) in acid washed 7ml plastic scintillation vials; color was allowed to develop for 15 min, with periodic swirling, prior to analysis. Following color development, 1 ml of sample was transferre d to 1.5 ml polystyrene disposable cuvettes (10 mm path length, Fisher Scie ntific) and nitrite concentrat ions were determined as a function of absorbance intens ity at 540 nm, with a Shim adzu UV 1201 spectrophotometer (Shimadzu, Kyoto, Japan). Nitrate standard s prepared by serial dilution of 1000 ppm nitrate solution (Fisher Scient ific, Pittsburg, PA, USA) were run during each series of cadmium-reduction reactions. To determine conve rsion efficiency, nitrite concentrations in standards after shaking we re compared to values of nitrite standards; conversion efficiencies for cadmium shaken samples co mpared to nitrite standards in this study ranged from 95 to 102%, consistent with thos e reported by Jones (1984). To standardize for differences in initial nitrate concentrations in replicate samples, time zero values were

PAGE 99

85 subtracted from values at each time point, prior to rate determin ation. Nitrification potentials were determined by the slope of a linear regression of cumulative nitrate concentrations with time (Hart et al., 1994). Extraction of Nucleic Acids and PCR Nucleic acids were extracted from appr oximately 0.25 g soil using the PowerSoil DNA Kit (MoBio, Solana Beach, CA) followi ng the manufacturers instructions. Extracts were examined by electrophoresis through 1% agarose gels made with trisacetate-EDTA buffer, staining w ith ethidium bromide, and visualization under UV light. In an effort to fully characterize communities within HID soils and account for spatial variability, equal volumes of bulk DNA extract s from three replicate soil samples per study site were pooled prior to PCR analysis. A 491 bp fragment of amo A was amplified using pr imer set amoA1f (5'GGGGTTTCTACTGGTGGT-3') and amoA2r (5'-CCCCTCKGSAAAGCCTTCTTC-3') developed by Rottauwe et al. (1997). Each 25 l reaction contained 12.5 l of HotStar Taq Master Mix (QIAGEN, Valencia, CA, USA), 8.75 l of distilled water, 1.25 l of each primer (20 pmol l-1), and 1 l of undiluted template DNA. PCR amplification was carried out in GeneAMP PCR system 9600 (Perkin-Elmer, Applied Biosystems, Norwalk, CN, USA). Initial enzyme activat ion and denaturation were performed at 95 oC for 15 min, followed by 35 cycles of 95oC for 30s, 55oC for 45s and 72oC for 45 s, with a final extension step at 72oC for 7 min. Cloning and Sequencing Fresh PCR products from all samples we re ligated into pCRII-TOPO cloning vector and transformed into chemically competent Escherichia coli TOP10F cells

PAGE 100

86 according to manufacturers recommendations (I nvitrogen, Carlsbad, Calif.). Randomly picked white or light blue clones were in oculated into 96 well plates containing 200 l of LB broth with kanamycin (50 g ml-1) and grown overnight at 37oC. Live clones were screened directly for inserts using live cell PCR and SP6 and T7 vector primers. Clones containing the correct insert size were transf erred to 96 well plates containing LB broth amended with kanamycin (50ug ml) and 8% (v/v) glycerol and incubated for 24 h at 37oC. Overnight cultures were submitted to the Genome Sequencing Core Laboratory at the University of Florida. Phylogenetic Analysis Nucleotide sequences were manually ali gned in Se-Al version 2.0a11 (Rambaut, 1996) and aligned with ClustalX versi on.1.81 (Thompson et al., 1997). Phylogenetic trees were produced from a 450 bp amoA fragment, using Jukes and Cantor corrected distance matrices in the TREECON software package (van de Peer and de Wachter, 1994). Bootstrap analysis (1000 resamplings) was used to estimate reproducibility of phylogenies. Bayesian analysis was conducted using ClustalX generated alignments in Mr. Bayes (Huelsenbeck and Ronquist, 2001; Ronquist and Huelsenbeck, 2003) software under default model parameters for 2.5 milli on generations. Due to high redundancy in sequence similarity, only sequences sharing less than 97% sequence similarity were included in the final cladogram. Statistical Analysis of Phylogenetic Data To assess whether observed AOB clone libraries between sites represented statistically different populat ions, well-aligned subsets of each gene fragment were chosen for analysis using -Libshuff (Schloss et al., 2004) with 1,000,000 randomizations

PAGE 101

87 and a distance interval ( D ) of 0.01 in PAUP* (Swofford, 1998) employing Jukes-Cantor corrected pairwise distance matrices. The program empl oys Monte Carlo methods to calculate the integral form of the Cramrvon Mise statistic by constructing random subset populations from the entire data set and comparing coverage of the generated populations to coverage of experimentally obtained data sets Populations were considered significantly differe nt with P value below 0.0017 af ter a Bonferroni correction for multiple pairwise comparisons ( =0.05, n = 20). Analysis of molecular variance (AM OVA), pairwise comparisons of population specific pairwise fixation indices (FST) (Martin, 2002), and aver age pairwise sequence similarities were conducted with the pr ogram Arlequin version 3.001 (Genetics and Biometry Laboratory, University of Gene va [http://lgb.unige.ch/arlequin]). AMOVA (Excoffier et al., 1992) employs a hierarchica lly partitioned matrix of Euclidean distances to assess by permutation the significance of variance components at each level of partitioning. All analyses were performed under default parameters, with the following exceptions: analyses were conducted at 90,000 iterations and haplot ypes were defined by Euclidean distances. FST tests were employed as measur es of genetic differentiation between all pairs of samples. The test determines whether samples contain close phylogenetic relatives or more deeply divergen t sequences. Mantel tests (Mantel, 1967; Mantel and Valand, 1970) were implemented in Arelquin and to test correlations between population specific FST values and geochemical parame ters. The method is based on a nonparametric general regression model wh ich employs squared Euclidean distance matrices between variables to test signifi cance of and degree of predictability one variable has on another (Dutilleul et al., 2000).

PAGE 102

88 Parsimony tests (P-test) were implemented in TreeClimber (Schloss and Handelsman, 2006). Clustal X version 1.83 was used to generate sequence alignments, constructed under default parameters. Trees were constructed by Bayesian analysis as implemented in Mr. Bayes version 3.1 (H uelsenbeck and Ronqui st, 2001; Ronquist and Huelsenbeck, 2003) under default model parameters, with trees sampled every 1000 generations. All Bayesian analyses were run for 1,000,000 generations, of which 10% were discarded to account for initial divergen ce in log likelihood scor es between chains. The resultant 990 trees were used for analysis in TreeClimber (http://www.plantpath.wisc.edu/fac/joh /treeclimber.html) and compared to 1,000,000 randomly generated trees. Statistical Analysis of Biogeochemical Data Environmental parameters were tested for significance across treatment groups (study sites) using one-way ANOVA in JMP version 5.1 (SAS Institute) on both log transformed and raw data. Pairwise compar isons of means were conducted in the same software using Tukeys HSD, which acc ounts for unequal variances among samples. Results and Discussion Biogeochemical Parameters of Soils Along the Restoration Gradient Values for select geochemical parameters are presented in Table 4-1. Mean soil depth increased linearly with time since disturbance for both wet (R2 = 0.82, P = 0.033 ) and dry (R2 = 0.78, P = 0.046) season measurements. Nitrate concentrations ranged from 4.00 to 36.21 mg N kg-1 in the dry season and from 1.79 to 7.83 mg N kg-1in the wet season, R00 soils contained the highest nitrate co ncentrations in both seasons (Table 4-1). Interestingly, previous studies of soils from other regions of the Everglades have been

PAGE 103

89 unable to extract nitrate, which was attribut ed to high denitrification rates (White and Reddy, 1999; White and Reddy, 2003). Ammonium concentrations ranged from 5.13 to 16.46 mg N kg-1 and 9.86 to 46.96 mg N kg-1 in dry and wet season soils, respectively. Ammonimum concentrations in HID soils were approximately 5 to 70 fold lower than in nutrient impacted surface soils of the Everglades (White and Reddy, 2003). There was a significant positive linear increase in a mmonium concentrations with time since restoration in both wet (R2 = 0.61, P = 0.04) and dry (R2 = 0.96, P = 0.003) seasons. Additionally, wet season soil de pth correlated well with am monium concentrations (R2 = 0.81, P = 0.03). Initially extractable ammoni um concentrations have been used previously as estimates of heterotrophic N mineralization potentials in wetland and upland soils (Williams and Sparling, 1988; Ross et al., 1995, White and Reddy, 2000; White and Reddy, 2003). Thus, the observed li near increase in extractable ammonium with time since restoration may indicate gr eater mineralization of organic nitrogen, possibly resulting from increased accumulation of labile organic nitrogen (due to greater plant density or carbon accumulation), or a su ccessional increase in carbon limitation of microbial communities. Dry season nitrification potenti als ranged from 0.08 to 0.20 mg NO3 --N kg-1 hr1, the highest values were observed in R89 a nd R00 sites and the lowest in UND and R03 soils. In the wet season, nitrification potenti als decreased signifi cantly in all sites (ANOVA, P < 0.05) and ranged from 0.05 to 0.12 mg NO3 --N kg-1hr-1, highest in R97 and lowest in R03 soils. Dry season values are within the lower range of initial nitrification rates measured in phosphorous impacted Everglades soils, and wet season values are 2 to 4 fold lower that those reported by White and Reddy (2003). There was no

PAGE 104

90 observed correlation between dry season nitrif ication potentials and other measured biogeochemical parameters, further measurem ents may elucidate factors controlling AOB activity in dry season soils. Soil oxygen demand (Table 4-1) correlated strongly with wet season nitrification potentials (R2=0.893, P=0.04), suggesting that in situ ammonia oxidation activities may be most limited by oxygen availability in the wet season. Although there was no clear trend associated with nitrificat ion potentials and recovery stage in HID soils, statistical analysis (randomized comple te block design, ANOVA) of site effects on biogeochemical data indicated significant ( = 0.05, P = 0.0032) withinsite effects on nitrification potentials. This may indicate that, while there does not seem to be an obvious or homogenously cont rolling factor on AOB activity along the restoration gradient, nitrification activity ma y be more strongly controlled by different factors within each restoration site, such competition with hetrotrophs for available ammonium, inhabitation by plan t allelochemicals, or di fferences in soil oxygen availability. Phylogenetic Analysis of amoA An expected 491 bp fragment of amoA was amplified from all study sites in both wet and dry season soils. Phylogeneti c analysis of the 313 obtained partial amoA revealed relatively low phylogenetic diversity of beta-proteobacterial AOB in HID soils. Clone libraries from both seasons were dominated by two sequence types, one corresponding to Nitrosospira -like and the other to Nitrosomonas -like amoA (Figure 4-1, Table 4-2); sequences comprising the two phylogenetic groups were approximately 75% similar on the nucleotide level. Analysis of all clones re vealed 181 (58%), 95 sequences from dry and 86 from wet season clone lib raries, to be associated with the Nitrosospira

PAGE 105

91 (NSP) clade. These sequences were obtained from all soils, and ranged in pairwise DNA sequence similarity from 97 to 100%. NSP cl ones shared high similarity (98 to 99%, DNA) to database sequences obtained from ag ricultural soils (Corredor et al., 2005), soils incubated under varying temperature and a mmonium regimes (Avrahami et al., 2003), and from rice roots (Rotthuwae et al., 1997). Sequences within the NSP clade were 96 to 97% similar to amoA of Nitrosospira sp. Nsp 17, isolated from Icelandic soils (Purkhold et al., 2003) and 93% with Nitrosospira sp. Nsp 2, isolated from German soils (Purkhold et al., 2003). Little is known about these NSP isolates; they do not cluster tightly within 16S rRNA Cluster 3 Nitrosospiras (Purkhold et al., 2000), and may represent a unique group of Nitrosospiras or be a divergent member of Cluster 3 (Purkhold et al., 2003). The remaining 132 (42%) sequences were associated with the Nitrosomonas (NSM) lineage, sharing ca. 99% sequence similarity with NSM-like clones obtained from activated sludge (Park and Noguera, 2004) and the roots an d rhizospheres of different rice cultivars (Briones et al., 2002). HID clones associated with the NSM cluster also shared 98 to 99% DNA sequence similarity with Nitrosomonas europaea ATCC 19718. NSP and NSM sequences were obtained from all site s, although abundance varied between sites and seasons (Table 4-2). The occurrence of both Nitrosmonas and Nitrosospira amoA have been previously reported from estuarine sediments (Franc is et al., 2003; Ber nhard et al., 2005), membrane-bound biofilms (Schramm et al., 2000), forest and meadow soils (Mintie et al., 2003), grassland soils (Webst er et al., 2002), and in bulk paddy soil and the oxidized rhizospheres of rice plants (Rotthauwe et al ., 1997). Several studies have demonstrated the affinity of Nitrsomonas spp. for high nutrient environments and Nitrosospira spp. to

PAGE 106

92 be generalists; however, current knowledge of Nitrosomonas spp. physiologies far outweighs that of Nitrsospira spp. (Kowalchuk and Stephen, 2001). Interestingly, both amoA and 16S rRNA genes corresponding to Nitrosospira Cluster 3 have been obtained from a young successional grassland (Kowalc huk et al., 2000) and wetland soils (Ibekwe et al., 2003). Nitrosospiria of Cluster 3 have been most commonly obtained from undisturbed soils of near neutral pH (S tephen et al., 1996; Kowalchuk and Stephen, 2001). Cluster 3 isolates have shown different responses to commonly regulating factors in pure culture (Webster et al., 2005). The apparent seasonal stability of AOB populations between wet and dry seasons is cons istent with previous observations of the presence of both groups in anoxic or sub-oxic environmen ts (Bodelier et al., 1996), and their ability to survive at low ammonium concentrations and prolonged periods of starvation (Bollmann et al., 2002). Relative abundance of se quence types obtained from dry and wet season soils suggest interesting dynamics between Nitrosomonas and Nitrosospira type AOB. Dry season clone libraries obtained from R 03, R01, R00, and R89 soils suggest an approximately linear decrease in Nitrosospira with restoration age. However, this trend is less clear in wet season clone librarie s. In both wet and dry seasons, R97 and R03 clone libraries were dominated by Nitrosmonas -like and Nitrosospira -like amoA sequences, respectively. The ecological factors possibly controlling these trends are not clear. Attempts to further investigate the dynamics of Nitrosomonas and Nitrosospira sequence types in HID soils were unsu ccessful. Low gene copy numbers in DNA extracted from individual samples yieled insufficient quantities of amoA PCR amplicons for downstream applications such as T-RFLP. Thus, without further data to confirm the

PAGE 107

93 observed trends suggested by the clone librari es, discussion of ecol ogical factors that control AOB diversity in HID so ils would be inappropriate. Statistical Analysis of Clone Libraries Observed amoA sequence diversity was low in HID samples, as evidenced by the rarefaction analysis; clone libra ry coverage, as calculated by -Libshuff (Schloss et al., 2004), ranged from 97 to 100% at evolutionary distances greater than 0.01. Distance matrices of amoA from each site and season were subjec ted to iterative statistical analysis with the software -Libshuff (Schloss et al., 2004) to determine the significance of patterns observed in clone libraries. For the dry season, R89, R97, and R03 clone libraries were significantly different from each other, and R00 and R01 were subsets of R03. For the wet season, R03 was significantl y different from R00 and R97, but was drawn from the sample population as R01. Overall, -Libshuff analysis suggests that population membership does not di ffer significantly in any of the HID sites. Patterns observed in significance between R03 and othe r clone libraries is likely to due the dominance of NSP sequences in bo th wet and dry season libraries. To test the significance of observed population struct ures between restoration sites based on amoA clone libraries parsimony (P) tests of phylogenetic variation were implemented in TreeClimber (Schloss and Handelsman, 2006). Underlying hypotheses and application of P tests to phylogenetic data se ts of this size are explained in detail in Chapter 3. Population structur es were significantly differe nt within both wet (P=0.026 ) and dry (P=0.023 ) season clone libraries. Re moval of specific groups of sequences or clone libraries from any site did not yield loss of significance suggesting that each site harbors unique sequence types. Table 4-3 pr esents the number of unique haplotypes, as

PAGE 108

94 determined by Arlequin (Excoffier et al., 1992); unique haplotypes were determined by pairwise comparison of squared Euclidean di stances of sequences from each site. Further, despite high sequence similarity wi thin the NSM and NSP clades, regions of difference may exist, such that subcluster s of unique sequence types form within the NSM and NSP clades. A comparison of pooled wet and dry season clone libraries failed to yield significance (P=0.65), suggesting as a whole that community structure did not vary between seasons. Interestingly, individu al pairwise comparisons of clone libraries from each restoration site between seasons we re significantly differe nt (P < 0.05). Thus, while the overall community structure did not shift significantly between seasons, there is clear evidence for within-site sh ifts in genetic composition of amoA between seasons. Further, there were observed sh ifts in average nucleotide di versity and pairwise sequence similarities between seasons (Table 4-3). Analysis of molecular variance (AMOVA) was used to assess differences in genetic variation within and between clone li braries from each restor ation site. For the dry season, variation among populations account ed for approximately 42% of total variance. For wet season libraries, among population variance accounted for 34% of total variance. Among population variance differe d significantly from total population variance (P < 0.000001) for both seasons. AMOVA results imply that genetic variation within sites is significantly different from variance when a ll libraries were pooled. This suggests that each site harbors a unique asse mblage of AOB, consistent with the results of P test analyses. The decrease in among population variation in wet season libraries is likely due to the small increas es in relative abundance of Nitrosomonas sequences in R89, R00, R01, and R03, and Nitrosospira in R97 (Table 4 -2). There was no significant

PAGE 109

95 variation (P=0.91) when dry and wet season cl one libraries were compared in AMOVA. This is consistent with the recovery of nearly similar distribution of NSM and NSP sequences within each library between seasons. Dissimilarity indices (FST) (Reynolds et al., 1983; Mart in, 2002) can be used to compare average genetic variation within a group to the variation between groups. By comparing the observed variation with that of randomly generated groups, the analysis evaluates the statistical likeli hood that observed variation between two sites is significant. Results of pairwise comparisons of FST values for dry and wet season clone libraries are presented in Table 4-4 and 4-5, resp ectively. Pairwise comparisons of FST and average pairwise sequence similarity values between re storation sites yielded similar patterns for both dry and wet seasons. For both dry and wet seasons, diversity in R89 was significantly higher than R 97 and R03 (Tables 4-4 and 4-5), which can likely be attributed to the dominance of Nitrosomonas and Nitrosospira clones within R97 and R03 libraries, respectively. For dry season libraries, both R97 and R03 FST values and average pairwise sequence similarities were si gnificantly different from all other sites. The same pattern was observed for R97 in the wet season, however R03 was not significantly different from R00, which may be attributed to the observed increase in Nitrosomonas sequences in the R03 wet season clone library. Population specific FST values for clone libraries from each restoration site and season are presented in Table 4-3; these values are measures of within population diversity to total population dive rsity, a low number indicates dive rsity within a site to be similar to diversity when any two sites are combined (Martin, 2002). Values in Table 4-3 are based on comparison of within-site divers ity to total diversity observed within all

PAGE 110

96 sites per season. In both seasons, population specific FST values were highest in R97 and R03 libraries, indicating that th ese libraries share least simila rity with the total population as represented by our clone libraries. Nitrosomonas or Nitrosospira -type AOB dominated clone libraries from R 97 and R03 sites, respectively. Correlation of Differences in amoA Diversity With Environmental Variables Mantel tests (Mantel, 1967; Mantel and Valand, 1970; Duti lleul et al., 2000) were implemented to examine correlations between pairwise differences in amoA populationspecific FST values between sites and seasons to matrices of pairwise differences in geochemical parameters. A previous study of amoA diversity in es tuarine sediments correlated differences in amoA FST values between sites to differences in nitrate concentrations and salinity (Francis et al ., 2003). The Mantel test examines whether closeness observed in one set of variables is related to closeness in another set of variables. For these data, it was employed to test for correlati ons between observed differences in amoA diversity between sites and seas ons, as represented by populationspecific FST values, and factors most likely to a ffect AOB activity in HID soils: time since restoration, extractable NH4 +, extractable NO3 -, potential nitrification rates, soil moisture, and soil oxygen demand. Results of Ma ntel tests of correlation for differences both within and between season FST values with biogeochemical parameters are presented in Table 4. Pairwise differences in FST values for dry season clone libraries correlated significantly with soil oxygen demand (SOD) and nitrifi cation potentials. For the wet season, SOD and extractable nitrate concentr ations correlated str ongly with wet season differences in pairwise FST values. Interestingly, in both dry and wet season results, one factor is inversely correlated with differe nces in diversity, and the other positively correlated. In both seasons, pairwise differences in SOD between sites were positively

PAGE 111

97 correlated with diversity, and may indicate oxyge n availability as a controlling factor on AOB diversity between sites. Pairwise FST values were inversely correlated with potential nitrification rates a nd extractable nitrate concentrat ions in dry and wet seasons, respectively. Both may be used as indicat ors of AOB activity in soils, and suggests a decoupling of genetic diversity and activity, as sites with greatest differences in diversity have similar nitrification activities. Pair wise differences between seasons correlated significantly with extractable ammonium, extract able nitrate, nitrifi cation potentials, and soil oxygen demand, and suggest several fact ors controlling observed difference in diversity between seasons; the magnitude of which each of these correlating factors control diversity between seas ons may vary between sties.

PAGE 112

98Table 4-1. Biogeochemical parameters of dry and wet season HID soils. Values in parentheses for soil depths repr esent that range in values from 81 nodes sa mpled per site; all other values in parent heses represent standard deviations of the mean of three amples per site; SOD, soil oxygen demand; MBN, microbial biomass nitrogen. Wet season determinations were conducted on a single soil sample Nitrification potential rates are expressed as mg NO3 --N kg-1soil h-1. Study Site Soil Depth (cm) Moisture (%) SOD (g kg-1) Nitrate (mg NO3 -N kg-1) Ammonium (mg NH4 +-N kg-1) Nitrification Potential Dry UND 8.1 (4-16) 10.9 (2.5) 36.21 12.81 (1.30) 0.08 (0.02) R89 3.1 (1-7) 17.1 (2.9) 7.32 (2.28) 16.46 (2.27) 0.20 (0.02) R97 2.6 (1-9) 27.6 (13.7) 8.69 (0.18) 9.26 (2.14) 0.14 (0.03) R00 1.1 (0-3) 17.7 (5.2) 14.28 7.94 (2.42) 0.18 (0.03) R01 1.6 (0-3) 14.2 (6.3) 9.76 (2.24) 5.13 (0.55) 0.17 (0.02) R03 0.2 (0 -1) 20.0(11.5) 4.00 (1.56) 5.54 (1.18) 0.13 (0.05) Wet UND 10 (4-19) 43.8 (0.6) 79.6 6.77 (0.92) 9.86 (1.51) 0.09 (0.02) R89 5.4 (2-9) 59.6 (2.4) 261.4 3.08 (0.93) 46.96 (3.32) 0.06 (0.01) R97 4.6 (0-5) 58.8 (4.5) 359.2 1.79 (1.05) 49.48 (18.67) 0.12 (0.02) R00 3.3 (1-5) 48.3 (1.4) 184.9 7.83 (4.93) 25.06 (13.33) 0.07 (0.02) R01 2.2 (0-4) 41.6 (1.1) 135.9 6.84 (4.84) 15.21 (8.84) 0.06 (0.02) R03 1.2 (0-3) 43.5 (10.1) 230.1 5.09 (4.88) 15.89 (5.09) 0.05 (0.01)

PAGE 113

99Table4-2. Results of sequence analysis of amoA sequences obtained from dry and wet season soils. Relative percentage (%) of sequence types within each cluster (dry/wet) Phylogenetic Cluster UND R89 R97 R00 R01 R03 Closest cultivated isolatea 16S rRNA clusterb Nitrosospira 28/12 56/69 0/10 70/77 80/77 100/95 Nsp. sp, 17 (96%) 3 Nitrosomonas 72/88 44/31 100/90 30/23 20/22 0/4 Nsm. europaea (99%) 6 No. of clones 25/25 27/26 26/20 30/26 31/27 27/23 aAs determined by BLAST search under default parameters; values in parenthesis are av erage nucleotide similarity bBased on analyses of 16S rRNA sequences, as outlined by Stephen et al. (1996), and reexamined by Purkhold et al. (2000); Nsm., Nitrosomona s; Nsp., Nitrosospira

PAGE 114

100 Table 4-3. Fixation indices (FST), average pairwise differences ( [ ]), nucleotide diversity, and uni que haplotypes for wet and dry season amoA clone libraries as calculated by Arlequin (Excoffier et al., 1992). Dry season clone library We t season clone libraries Study site FST Unique haplotypes [ ] Nucleotide diversity FST Unique haplotypes [ ] Nucleotide diversity R89 0.382 21 89.9 (39.9) 0.19 (0.09) 0.336 18 75.5 (33.6) 0.16 (0.08) R97 0.435 24 5.2 (2.6) 0.01 (0.01) 0.341 17 33.2 (15.1) 0.07 (0.04) R00 0.412 20 58.0 (25.8) 0.12 (0.06) 0.325 22 64.2 (28.6) 0.13 (0.07) R01 0.418 19 43.6 (19.4) 0.09 (0.05) 0.325 20 56.3 (25.1) 0.14 (0.07) R03 0.437 16 2.0 (1.17) 0.004 (0.01) 0.347 20 20.1 (9.2) 0.04 (0.02)

PAGE 115

101 101 Table 4-4. Corrected average pairwise diffe rences (above diagonal) and pairwise fixation indices (below diagonal) for dry season amoA sequences. Result for study sitea: Site R89 R97 R00 R01 R03 R89 52.91 0.11 6.11 26.34 R97 0.38 77.73 103.92 160.35 R00 0.00 0.62 -0.16 13.20 R01 0.05 0.76 -0.02 5.07 R03 0.24 0.97 0.25 0.14 aBold face values are significant at P<0.05. Table 4-5. Corrected average pairwise diffe rences (above diagonal) and pairwise fixation indices (below diagonal) for wet season amoA sequences. Result for study sitea: Site R89 R97 R00 R01 R03 R89 108.45 68.37 68.57 57.73 R97 0.48 118.43 118.43 144.07 R00 -0.02 0.57 62.41 46.57 R01 -0.01 0.57 -0.02 47.01 R03 0.16 0.81 0.08 0.09 aBold face values are significant at P<0.05.

PAGE 116

102 Table 4-6. Results of Mantel (Mantel, 1967 ; Mantel and Valand, 1970) correlation tests between pairwise differences of population specific FST values for wet and dry season amoA clone libraries with biogeochemical parameters. Dry Season Wet Season Across Seasons Environmental Parameter Correlation coefficient P-value Correlation coefficient P value Correlation coefficient P value Time Since Restoration -0.536 0.158 -0.419 0.300 NDa ND Extractable NH4 + -0.522 0.167 0.147 0.291 -0.756 0.002 Extractable NO3 -0.327 0.258 -0.704 0.017 0.331 0.038 Nitrification Potential -0.989 0.008 0.600 0.075 0.631 0.008 Soil Moisture -0.287 0.200 0.399 0.092 -0.279 0.448 Soil Oxygen Demand 0.885 0.017 0.832 0.008 -0.7515 0.008 aND, not determined.

PAGE 117

103 Figure 4-1. Cladogram of representative amoA sequences obtained from HID soils. Nodal support values represent percen t of 1000 bootstrap resamplings (top) and Bayesian posterior probability af ter 2.5 million generations (bottom). Nodes with only a single value ar e unsupported by Bayesian methods.

PAGE 118

104 CHAPTER 5 SUMMARY AND CONCLUSIONS The severe disturbance imposed upon HID restoration sites due to complete removal of plant communities and much of the remaining soil likely destroyed any vestiges of the previous biogeochemical li nkages and the microbial communities which mediate them. The recovery of the HID ecosystem is strongly dependent upon the development of soils. Soil provides a direct linkage between the nutrients retained in parent materials and plant root s, and a medium for the rees tablishment of biogeochemical linkages. Nutrient accretion and recycling ma y play a major role in the rates at which restored sites reach stability. Changes in recovery stage will be largely dependent upon biological activity within each restoration site. The retention of nutrients within restored sites will be strongly dependent upon the activ ity of plant and microbial communities. Further, imbalances in the cycling of carbon and nitrogen in restor ed sites may present the opportunity for signif icant loss of nutrient stores due to microbial processes. Trace gas loss of nutrients due to respiratory activity of soil microbial communities may significantly alter the rate at which biogeoche mical linkages and nutrient use efficiencies are restored. Thus, an understanding of the activity and ecology of microbial groups associated with trace gas production, such as methanogenic, ammonia oxidizing, and denitrifying bacteria, maybe pr ovide insights into the stat e of nutrient recycling and retention in re-developing sites. The activity and molecular ecology of methanogenic bact eria in HID soils was investigated in Chapter 2. Methanogenic ba cteria occupy an exclusive niche in terminal

PAGE 119

105 anaerobic carbon mineralization in most freshw ater wetlands; their activity and structure may provide insight into the nature of both carbon cycling and anaerobic electron accepting processes. Methanogenic activity was detected in HID soils from both restored and undisturbed wetlands. Microcosm expe riments to determine the most likely methanogenic precursors in soils from each study site strongly suggested hydrogenotrophic methanogenesis as the most fa vorable pathway of methane formation. Methane production potentials indicated a general decline in methanogenic activity with restoration age and were lowest in soils from undisturbed sites. Culture independent techniques targeti ng methyl coenzyme M reductase genes ( mcrA ) were used to assess the dynamics of methanogenic assemblages. mcrA clone libraries were dominated by sequences rela ted to hydrogenotrophic methanogens of the orders Methanobacteriales and Methanococcales and suggested a general decline in the relative abundance of Methanobacteriales mcrA with time since restoration. Terminal restriction fragment length polymorphism (T-RFLP) was employed to monitor the composition of methanogenic assemblages in HID soils between wet and dry seasons, and within restoration sites. Results of T-RFLP analysis indicated methanogeneic assemblages to remain relatively stable betw een seasons. Interesti ngly, T-RFLP analysis of soils across the restoration chrono sequence indicated a putative shift in Methanobacteriales populations with time since rest oration, suggesting that factors associated with each sites recovery stage may cause shifts in dominant genotypes. However, further studies into th e activity of specific members of Methanobacteriales in HID soils are required to determine if these results are due to diffe rences in regulating factors associated with restoration age.

PAGE 120

106 The relatively low activity of methanogenic bacteria in HID soils, as discussed in Chapter 2, suggested the occu rrence of more energetically favorable anaerobic electron accepting process in HID soils. Denitrificat ion is the most energetically favorable respiratory pathway in the absence of oxygen. Shallow soil depths and seasonal inundation may provide conditions conducive to the activity of denitrifying bacteria. Chapter 3 focused on the activity and gene tic diversity of denitrifying bacterial populations in restored and undi sturbed wet season soils. Denitrifying enzyme activity was detected in soils from both restored and undisturbed sites; however, no trend associated with time since restoration was ev ident. Factors contro lling denitrification activity in HID soils are not clear. A si gnificant difference in activity between sites closely related in time since restoration sugge sts factors controlling de nitrification in HID soils are site specific. The genetic diversity of denitrifying bacterial populations in HID soils was investigated by construction of clone librari es for genes associated with the enzyme nitrite reductase, which catalyzes the first gas-forming step of denitrification. Two functionally redundant nitrite reductases exis t in bacteria and are encoded for by two divergent genes ( nirS and nirK ); no bacterium possesses both. Both genes were obtained from soils in all study sites. Phylogenetic an alysis of clone libraries constructed from each study site indicated high diversity of both genotypes within HID soils, and suggested the existence of unique lineages of denitrifier populations in soils from each study site. Statistical analysis of nirS and nirK clone libraries confirmed the existence of unique divergent lineages in soils from each restoration site. Further, these analyses provided evidence of di fferent responses of nirS and nirK populations to restoration age.

PAGE 121

107 A greater overlap in shared nirS phylotypes between all rest oration sites suggested a linear response in diversity associ ated with succession. Interestingly, nirK populations from more recently restored sites shared lin eages that were statistically distinct from populations recovered for older sites, suggesting a bimodal re sponse with restoration age. Several lines of evidence suggest that ex istence of unique dive rgent populations of denitrifying bacteria in soils from each rest oration site. This may be in response to different selection factors associat ed with development of HID soils. The activity and genetic structure of ammonia oxidizing bacterial populations was the subject of Chapter 4. Nitrification may be a significant source of nitrogen loss in young soils by conversion of biologically prefer red ammonium to nitrate which may be subsequently lost from soils due to leaching or denitrification. Nitr ification potentials in HID soils were monitored in wet and dry s easons. Rates were highest during the dry season and decreased significantly in the we t season. Nitrification potentials were not correlated significantly with any geochemical pa rameters or with time since restoration. Statistical analysis suggests control of nitr ification activity in HID soils to be site specific. The genetic structure of ammonia oxi dizing bacteria was monitored by cloning and sequencing of amoA obtained from HID soils. amoA encodes the acetylene binding protein of the ammonia monoxygenase enzyme responsible for conversion of ammonia to hydroxylamine. amoA diversity was low relative to ot her functional genes obtained from HID soils. Of the two amoA genotypes obtained in clone libraries, sequences corresponding to Nitrosospira amoA were most abundant in samples from recently restored sites. Nitrosomonas -like amoA were obtained in greater abundance from soils in

PAGE 122

108 older restoration sites. Genetic diversity observed in amoA clones libraries was strongly correlated with environmental factors, and suggested amoA diversity in dry season soils to be associated with nitrif ication rates and wet season diversity to be most strongly associated with oxygen availability. While uncertain of in situ distributions of the two groups of ammonia oxidizers represented by clon e libraries from each site, differences in activities of Nitrosomonas and Nitrosospira populations in response to environmental factors are well documented. Variations in their abundance in soils of differing restoration age may indicate varying degrees of resource partitioning and niche differentiation. However, quantitative molecu lar and culture based studies are required for a full understanding of population dynami cs of ammonia oxidizing bacteria in developing soils of the HID

PAGE 123

109 APPENDIX A SUPPLEMENTAL TABLES Chapter 4 Table A-1. Population similarity P values for comparison of amoA dry and wet season clone libraries determined using Crame r-von Mises test statistic, implemented in -Libshuff (Schloss et al., 2004) Season (n) P values for comparison of heterologous library ( Y ) with Xa Site for homologous library ( X ) R89 R97 R00 R01 R03 Dry (166) R89 0.963 9.963 0.013 0.000 R97 1.000 0.885 0.846 0.000 R00 1.000 1.000 0.900 0.000 R01 0.163 0.129 0.129 1.000 R03 0.000 0.000 0.926 0.926 Wet (147) R89 0.923 0.923 0.962 0.923 R97 0.650 0.900 0.700 0.000 R00 0.423 0.210 0.577 0.000 R01 0.111 0.148 0.222 0.593 R03 0.000 0.000 0.000 0.913 aValues in bold indicate significant P values (P < 0.0017) after Bonf erroni correction for multiple pairwise comparisons. Libraries are distinct from one another if both comparisons ( X versus Y and Y versus X ) are significant. Values in italics indicate that library Y is a subset of library X .

PAGE 124

110 APPENDIX B SUPPLEMENTAL FIGURES Chapter 2 mcrA0 2 4 6 8 10 12 14 16 18 05101520253035Number of sequencesNumber of phylotypes UND R89 R97 R00 R03 Figure B-1. Rarefaction curves for mcrA clone libraries constr ucted from dry season soils.

PAGE 125

111 Chapter 3 0 1 2 3 4 5 6 01234 Time (h)mg N2O-N kg-1 hr-1 UND R89 R97 R00 R01 R03 Figure B-2. Potential denitrifi cation rates as a function of N2O-N production with time. Error bars represent standard error of five replicate determinations.

PAGE 126

112 nirK0 2 4 6 8 10 12 14 16 18051015202530 Number of SequencesNumber of OTUs nirS0 2 4 6 8 10 12 14 16 18 051015202530Number of OTUs UND R89 R97 R00 R01 R03A) B) Figure B-3. Rarefaction curves for A) nirS and B) nirK clone libraries determined in DOTUR (Schloss and Handelsman, 2005) employing a 97% nucleotide sequence similarity cut-off.

PAGE 127

113 0 1 2 3 4 5 05101520253035Number of OTUs UND R89 R97 R00 R01 R03 0 1 2 3 4 5 6 7 051015202530Number of SequencesNumber of OTUsChapter 4 A) B) Figure B-4. Rarefaction curves for amoA clone libraries from A) dry season (April 2004) and B) wet season (November 2004) so ils determined in DOTUR (Schloss and Handelsman, 2005) employing a 97% nuc leotide sequence similarity cutoff

PAGE 128

114 LIST OF REFERENCES Alzerreca, J. J., J.M. Norton, and M.G. Klotz. 1999. The amo operon in marine, ammonia-oxidizing -proteobacteria. FEMS Microbiol. Lett. 189:21-29. Amann, R. I., W. Ludwig, and K.H. Schlei fer. 1995. Phylogenetic identification and in situ detection of individual microbial cel ls without cultivation. Microbiol. Rev. 59:143-169. Andrews, J. H., and R.F. Harris. 1986. rand Kselection and microbial ecology. Adv. Microb. Ecol 9:99-147. Araki, N., T. Yamaguchi, S. Yamazaki, and H. Harada. 2004. Quantification of amoA gene abundance and their amoA mRNA levels in activat ed sludge by real-time PCR. Water Sci. Tech. 50:1-8. Arunachalam, K. A., and N.P. Melkania. 1999. Influence of soil properties on microbial populations, activity, and biomass in humi d subtropical mountainous ecosystems of India. Biol. Fert il. Soils 30:217-223. Austin, D. F. 1978. Exotic plants and their effects in southeastern Florida. Environ. Conserv. 5:25-34. Avrahami, S., Conrad, R., and G. Braker. 2002. Effect of soil ammonia concentration on N2O release and on the community structure of ammonia oxidizers and denitrifiers. Appl. Environ. Microbiol. 68:5685-5692. Avrahami, S., W. Liesack, and R. Conrad. 2003. Effects of te mperature and fertilizer on activity and community structure of so il ammonia oxidizers. Environ. Microbiol. 5:691-705. Aziz, T., and D.M. Sylvia. 1995. Activity and species composition of arbuscular mycorrhizal fungi following so il removal. Biol. App. 5:776-784. Bachoon, D., and R.D. Jones. 1992. Potentia l rates of methanogenesis in sawgrass marshes with peat and marl soils in th e Everglades. Soil Biol. Biochem. 24:21-27. Balderston, W. L., B. Sherr, and W.J. Payne. 1976. Blockage by acetylene of nitrous oxide reduction in Pseudomonas perfectomarinus Appl. Environ. Microbiol. 31:504-504. Bancroft, L. 1973. Exotic control plan. Ev erglades National Park, Homestead, FL

PAGE 129

115 Belser, L. W. 1979. Population ecology of n itrifying bacteria. A nn. Rev. Microbiol. 33:309-333. Bernhard, A. E., T. Donn, A.E. Giblin, a nd D.A. Stahl. 2005. Loss of diversity of ammonia-oxidizing bacteria correlates w ith increasing salinity in an estuary system. Environ. Microbiol. 7:1289-1297. Bodelier, P.L.E., J.A. Libochant, C.W.P. Bl om, and H.J. Laanbroek. 1996. Dynamics of nitrification and denitrifi cation in root-oxygenated se diments and adaptation of ammonia-oxidizing bacteria to low-oxyge n or anoxic habitats. Appl. Environ. Microbiol. 62:4100-4107. Bollman, A., M.J. Bar-Gilissen, and H.J. Laanbroek. 2002. Growth at low ammonium concentrations and starvation response as potential factor s involved in niche differentiation among ammonia-oxidizing bacteria. Appl. Environ. Microbiol. 68:4751-4757. Boone, D. R., W.B. Whitman, and P. R ouvire. 1993. Diversity and taxonomy of methanogens, p. 35-80. In J. G. Ferry (ed.), Methanogens: ecology, physiology, biochemistry and genetics, vol. 1. Chapman and Hall, New York, NY. Bothe, H., G. Jost, M. Schloter, B.B. War d, and K.P. Witzel. 2000. Molecular analysis of ammonia oxidation and denitrif ication in natural environments. FEMS Microbiol. Rev. 24:676-690. Bowden, W. B. 1987. The biogeochemistry of nitrogen in freshwater wetlands. Biogeochemistry 4:313-348. Braker, G., J. Zhou, L. Wu, A.H. Devol, and J.M. Tiedje. 2000. Nitr ite reductase genes ( nirK and nirS ) as functional makers to investig ate the diversity of denitrifying bacteria in Pacific Northwest marine sediment communities. Appl. Environ. Microbiol. 66:2096-2104. Braker, G., H.L. Ayala, A.H. Devol, A. Fesefeldt, and J.M. Tiedje. 2001. Community structure of denitrifiers, Bacteria and Archaea along redox gradients in Pacific Northwest marine sediments by terminal re striction fragment length polymorphism analysis of amplifie d nitrite reductase ( nirS ) and 16S rRNA genes. Appl. Environ. Microbiol. 67:1893-1901. Briones, A. M., S. Okabe, Y. Umemiya, N.B. Ramsing, W. Reichardt, and H. Okuyama. 2002. Influence of different cultivars on popul ations of ammonia-oxidizing bacteria in the root environment of rice. Appl. Environ. Microbiol. 68:3067-3075. Bruns, M. A., J.R. Stephen, G.A. Kowa lchuk, J.I. Prosser, and E.A. Paul. 1999. Comparative diversity of ammonia oxidiz er 16S rRNA gene sequences in native, tilled, and successional soils. A ppl. Environ. Microbiol. 65:2994-3000.

PAGE 130

116 Carney, K. M., P.A. Matson, B.J.M. Bohannan. 2004. Diversity and composition of tropical soils nitrifers acro ss a plant diversity gradient and among land-use types. Ecology Lett. 7:684-694. Castro, H. F., K.R. Reddy, and Ogram, A. V. 2002. Composition and function of sulfatereducing prokaryotes in eutrophic and pris tine areas of the Florida Everglades. Appl. Environ. Microbiol. 68:6129-6137. Castro, H. F., K.R. Reddy, and A.V. Ogra m. 2004. Phylogenetic characterization of methanogenic assemblages in eutrophic and oligotrophic areas of the Florida Everglades. Appl. Environ. Microbiol 70:6559-6568. Castro, H., S. Newman, K.R. Reddy, and A. Ogram. 2005. Distributi on and stability of sulfate-reducing proka ryotic and hydrogenotrophic methanogenic assemblages in nutrient-impacted regions of the Florida Everglades. Appl. Environ. Microbiol. 71:2695-2704. Chapin III, F. S., P.A. Matson, and H.A. Mooney. 2004. Principles of terrestrial ecosystem ecology, 1 ed. Springer, New York, NY. Chauhan, A., A. Ogram, and K.R. Reddy. 2004. Syntrophic-methanogenic associations along a nutrient gradient in the Florida Everglades. Appl. Environ. Microbiol. 70:3475-3484. Chauhan, A., and A.V. Ogram. 2006. Fatty acid-oxidizing consortia along a nutrient gradient in the Florida Everglades. Appl. Environ. Microbiol. 72:2400-2406. Chin, K.-J., T. Lueders, M.W. Friedric h, M. Klose, and R. Conrad. 2004. Archaeal community structure and pathway of me thane formation on rice roots. Microb. Ecol. 47:59-67. Cicerone, R. J., and R.S Oremland. 1988. Bi ogeochemical aspects of atmospheric methane. Global Biogeochem. Cycles 2:299-327. Connell, J. H. 1978. Diversity in tropical rain forests and coral reefs. Science 199:13021310. Conrad, R. 1999. Contribution of hydrogen to methane production and control of hydrogen concentrations in methanogenic soils and sediments. FEMS Microbiol. Ecol. 28:193-202. Corredor, P., M. Caru, and K.P. Wit zel. 2005. Composition of ammonia-oxidizing bacteria in soil planted with comm on bean.Genbank direct submission: http://www.ncbi.nlm.nih.gov. Unpublished data, Rutgers University. Coyne, M. S., A. Arunakumari, B.A. Aver ill, and J.M. Tiedje. 1989. Immunological identification and distributi on of dissimilatory heme cd1 and non-heme copper nitrite reductases in Alcaligenes eutrophus H16. J Bacteriol. 174:5332-5339.

PAGE 131

117 D'Angelo, E. M., and K.R. Reddy. 1999. Regulat ors of heterotrophic microbial potentials in wetland soils. Soil Bi ol. Biochem. 31:815-830. Dalryample, G. H., R.F. Doren, N.K. O'Ha re, M.R. Norland, and T.V. Armentano. 2003. Plant colonization after comp lete and partial removal of disturbed soils for wetland restoration of former agricultural fields in Everglades National Park. Wetlands 22:1015-1029. Delong, E. F. 1992. Archaea in coastal marine sediments. Proc. Natl. Acad. Sci. 89:56855689. Dolfing, J., and W.G.B.M. Bloemen. 1985. Ac tivity measurements as a tool to characterize the microbial composition of methanogenic environments. J. Microbiol. Methods 4:1-12. Dunfield, K. E., and G.M. King. 2004. Molecu lar analysis of carbon monoxide oxidizing bacteria associated with recent Hawa iian volcanic deposits. Appl. Environ. Microbiol. 70:4242-4248. Dutilleul, P., J.D. Stockwell, D. Frigon, and P. Legendre. 2000. The mantel test versus pearson's correlation analysis: assessment of the differences for biological and environmental studies. J. Agric. Biolog. Environ. Stat. 5:131-150. Enwall, K., L. Phillippot, and S. Hallin. 2005. Activity and composition of the denitrifying bacterial community respond differently to long-term fertilization. Appl. Environ. Microbiol. 71:8335-8343. Espinoza, L. 1997. Fate of nitrogen and meta ls following waste applications to some Florida soils. University of Florida, Gainesville, FL. Excoffier, L. P., P.E. Smouse, and J.M. Qu attro. 1992. Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial-DNA restricti on data. Genetics 131:479-491 Ferry, J. G. 1999. Enzymology of one-car bon metabolism in methanogenic pathways. FEMS Microbiol. Rev 23:13-38. Fierer, N., J.P. Schimel, and P.A. Holde n. 2003. Influence of drying-rewetting frequency on soil bacterial community stru cture. Microb. Ecol. 45:63-71. Francis, C. A., G. D. O'Mullan, and B.B. Ward. 2003. Diversity of ammonia monooxygenase ( amoA ) genes across environmental gradients in Chesapeke Bay sediments. Geobiology 1:129-140. Frostegard, A., Tunlid, A., and Baath, E. 1993. Phospholipid fatty acid composition and activity of microbial communities from two soil types experimentally exposed to different heavy metals. Appl. Environ. Microbiol. 59:3605-3617.

PAGE 132

118 Galand, P. E., H. Saarnio,H. Fritze, and K. Yrjl. 2002. Depth related diversity of methanogen Archaea in Finnish oligotr ophic fen. FEMS Microbiol. Ecol. 42:441449. Galand, P. E., H. Fritze, R. Conrad, and K. Yrjl. 2005. Pathways for methanogenesis and diversity of methanogeni c archaea in three boreal peatland ecosystems. Appl. Environ. Microbiol. 71:2195-2198. Garcia, J. L., Patel, B.K.C, and Ollivier, B. 2000. Taxonomic phylogenetic and ecological diversity of methanogenic Archaea. Anaerobe 6:205-226. Glockner, A. B., A. Juengst, and W.G. Zu mft. 1993. Copper containing nitrite reductase from Psuedomonas aureofaciens is functional in a mutationally cytochrome Cdfree background nirS negative Psuedomonas stutzeri Arch. Microbiol. 160:18-26. Gordon, A. S., W.J. Cooper, and D.J. Scheid t. 1986. Denitrificati on in marl and peat sediments in the Florida Everglades Appl. Environ. Microbiol. 52:987-991. Hallin, S., and P. Lindgren. 1999. PCR detection of genes encoding nitrite reductase in denitrifying bacteria. Appl. E nviron. Microbiol. 65:1652-1657. Hanson, G. C., P.M. Groffman, and A.J. Gol d. 1994. Denitrification in riparian wetlands receiving high and low groundwater nitrat e inputs. J. Environ. Qual. 23:917-922. Hart, S. C., J.M. Stark, E.A. Davids on, and M.K. Firestone. 1994. Nitrogen mineralization, immobilization, and nitrification, p. 985-1018. In D. Bezdiecek (ed.), Methods of soil analysis, part 2: mi crobiological and biochemical properties. Soil Science Society of America, Madison, WI. Head, I. M., W.D. Hiorns, T.M. Emble y, A.J. McCarthy, and J.R. Saunders. 1993. The phylogeny of autotrophic ammonia-oxidizing bact eria as determined by analysis of 16S ribosomal RNA gene sequences. J. General Microbiol. 139:1147-1153. Hill, G. T., N.A. Mitkowski, L. Aldrich-Wolfe, L.R. Emele, D.D. Jurkonie, A. Ficke, S. Maldonado-Ramirez, S.T. Lynch, and E.B. Nelson. 2000. Methods for assessing the composition and diversity of microbi al communities. Appl. Soil Ecol. 15:25-36. Hollocher, T. C., M.E. Tate, and D.J. D Nicholas. 1981. Oxidation of ammonia by Nitrosomonas europaea : definitive 18O-tracer evidence that hydroxylamine formation involves a monooxygenase J. Biol. Chem. 256:10834-10836. Hommes, N. G., L.A. Sayave dra-Soto, and D.J. Arp. 2001. Transcript analysis of multiple copies of amo (encoding ammonia monooxygenase) and hao (encoding hydroxylamine oxidoreductase) in Nitrosomonas europaea J. Bacteriol. 183:10961100. Hooper, A. B., T. Vannelli, D.J. Bergma nn, and D.M. Arciero. 1997. Enzymology of the oxidation of ammonia to nitrite by ba cteria. Antonie Leeuwenhoek 71:59-67.

PAGE 133

119 Horn, M. A., H.L. Drake, A. Schra mm. 2006. Nitrous oxide reductase genes ( nosZ ) of denitrifying microbial populations in soil and the earthworm guy are phylogenetically similar. Appl Environ. Microbiol. 2006:1019-1026. Horz, H. P., A. Barbrook, C.B. Field, and B.J.M Bohannan. 2004. Ammonia-oxidizing bacteria respond to multifactorial global change. Proc. Nat. Acad. Sci. 101:1513615141. Huelsenback, J. P., and F. Ronquist. 2001. MRBAYES: Bayesian inference of phylogenetic trees. Bioinformatics 17:754-755. Ibekwe, A. M., C.M. Grieve, and S.R. Lyon. 2003. Characteriza tion of microbial communities and composition in constructed dairy wetland wastewater effluent. Appl. Environ. Microbiol. 69:5060-5069. Jenkinson, D. S. 1988. Determination of microbi al biomass carbon and nitrogen in soil, p. 368-386. In J. R. Wilson (ed.), Advances in so il nitrogen cycling in agricultural ecosystems. CAB Int., Wallingford, England. Jones, M.N. 1984. Nitrate reduction by shaking with cadmium: alternative to cadmium columns. Water Res. 18: 643-646. Juottonen, H., P.E. Galand, E.-S. Tuittila, J. Laine, H. Fritze, and K. Yrjala. 2005. Methanogen communities and bacteria al ong an ecohydrological gradient in a northern raised bog complex. E nviron. Microbiol. 7:1547-1557. Kandler, E., D. Tshcerko, K.D. Bruce, J. Stemmer, P.J. Hobbs, R.D. Bardgett, and W. Amelung. 2000. Structure and function of the soil microbial community in microhabitats of a heavy metal pollute d soil. Biol. Fertil. Soils 32:390-400. Kemnitz, D., K.-J. Chin, P. Bodelier, and R. Conrad. 2004. Community analysis of methanogenic Archaea within a riparian flooding gradient. Environ. Microbiol. 6:449-462. Kennedy, A. C. 1999. Bacterial diversity in ag roecosystems. Agric. Ecosyst. Environ. 74:65-76 Killham, K. 1990. Nitrification in conifer ous forest soils. Plant Soil 128:31-44. Klotz, M. G., and J.M. Norton. 1995. Seque nce of an ammonia monooxygenase subunit A encoding gene from Nitrsosospria sp. NpAV. Gene 163:159-160. Knowles, R. 1982. Denitrifica tion. Microbiol. Rev. 46:43-71. Kobayashi, M., Y. Matsuo, A. Takimot o, S. Suzuki, F. Maruo, and H. Shoun. 1996. Denitrification, a novel type of respirator y metabolism in fungal mitochondrion. J. Biol. Chem. 271:16263-16267.

PAGE 134

120 Kowalchuck, G. A., A.W. Stienstra, G.H.J. Heilig, J.R. Stephen, and J.W. Woldendorp. 2000. Molecular analysis of ammonia-oxidizi ng bacteria in soil of successional grasslands of the Drentsche A (The Ne therlands). FEMS Microbiol. Ecol. 31:207215. Kowalchuk, G. A., and J.R. Stephen. 2001. Am monia-oxidizing bact eria: a model for molecular microbial ecology. A nnu. Rev. Microbiol. 55:485-529. Kowalchuk, G. A., P.L.E. Bodelier, G.H.J. Heilig, J.R. Stephen, and H.J. Laanbroek. 1998. Community analysis of ammonia-oxid izing bacteria, in relation to oxygen availability in soils and root-oxygena ted sediments, using PCR, DGGE and oligonucleotide probe hy bridisation. FEMS Micr obiol. Ecol. 27:339-350. Kowalchuk, G. A., Z.S. Naoumenko, P.J. Deri kx, A. Felske, J.R. Stephen, and I.A. Arkhipchenko. 1999. Molecular analysis of a mmonia oxidizing bacteria of the beta subdivision of the class Prot eobacteria in compost and composted materials. Appl. Environ. Microbiol. 65:396-403. Kowalchuk, G. A., A.W. Stienstra, G.H.J. Heilig, J.R. Stephen, and J.W. Woldendrop. 2000. Changes in the community structure of ammonia-oxidizing bacteria during secondary succession of calcareous gra sslands. Environ. Microbiol. 2:99-110. Kowalchuk, G. A., and Stephen, J.R. 2001. Am monia-oxidizing bact eria: a model for molecular microbial ecology. Ann. Rev. Microbiol. Kuenen, J. G., and L.A. Robertson. 1994. Combin ed nitrification-deni tification processes. FEMS Microbiol. Rev. 15:109-117. Kusel, K., and H.L. Drake. 1996. Anaerobic cap acities of leaf litter. Appl. Environ. Microbiol. 62:4216-4219. Kussmaul, M., M. Wilimzig, and E. Broc k. 1998. Methanotrophs and methanogens in masonry. Appl. Environ. Microbiol. 64:4530-4532. Laanbroek, H. J., and J.W. Woldendorp. 1995. Activity of chemolithotrophic nitrifying bacteria under stress in natural soils. Adv. Microb. Ecol. 14:275-304. Lashof, D. A., and D.R. Ahuja. 1990. Relativ e contributions of greenhouse gas emission to global warming. Nature 344:529-531. Lee, S. H., Kim, S.Y., and H. Kang. 2005. Impact of elevated CO2 on diversity of denitrifiers in wetland ecosyste m. Genbank direct submission: http://ncbi.nlm.nih.gov. Unpublished data, University of Kyoto. Leuders, T., Chin, K.-J., Conrad, R., and Friedrich, M. 2001. Molecular analyses of methyl-coenzyme M reductase subunit ( mcrA ) genes in rice field soil and enrichment cultures reveal the methanogeni c phylotype of a novel archaeal lineage. Environ. Microbiol. 3:194-204.

PAGE 135

121 Li, Y., and M. Norland. 2001. The role of soil fertility in invasion of Brazillian Pepper ( Schinus terebinthifolius ) in Everglades National Park, Florida. Soil Sci. 166:400405. Liu, X., S.M. Tiquia, G. Holguin, L. Wu, S. C. Nold, A.H. Devol, A.V. Palumbo, J.M Tiedje, and J. Zhou. 2003. Molecular diversity of denitrifying ge nes in continental margin sediments within the oxygen-deficien t zone off the Pacific coast of Mexico. Appl. Environ. Microbiol. 69:3549-3560. Loope, L. L., and V.L. Dunevitz. 1981. Imp act of fire exclusion and invasion of Schinus terebinthifolius on limestone rockland pine forests of southeastern Florida. National Park Service, Homestead, FL. Lueders, T., and M. Friedrich. 2000. Arch aeal population dynamics during sequential reduction processes in rice field soil. Appl. Environ. Microbiol. 66:2732-2742. Lueders, T., K.-J. Chin, R. Conrad, and M. Friedrich. 2001. Molecular analyses of methyl-coenzyme M reductase -subunit ( mcrA ) genes in rice field soil and enrichment cultures reveal the methanogenic phenotype of a novel Archaeal lineage. Environ. Mi crobiol. 3:194-204. Lueders, T., and M. Friedrich. 2003. Evaluati on of PCR amplification bias by terminal restriction fragment length polymorphism analysis of small-subunit rRNA and mcrA genes by using defined template mixtur es of methanogenic pure cultures and soil DNA extracts. Appl. Environ. Microbiol. 69:320-326. Luton, P. E., J.M. Wayne, R.J. Sharp, and P.W. Riley. 2002. The mcrA gene as an alternative to 16s rRNA in the phylogenetic analysis of methanogen populations in landfill. Microbiology 148:3521-3530 Madigan, M. T., Martinko, J.M., and Park er, J. 1996. Biology of microorganisms. Prentice-Hall, Inc., Upper Saddle River, NJ. Magurran, A. E. 2004. Measuring biological di versity. Blackwell Science, Malden, MA. Mantel, N. 1967. The detection of disease clustering and a generalized regression approach. Cancer Res. 27:209-220. Mantel, N., and R.S. Valand. 1970. A technique of nonparametric multivariate analysis. Biometrics 26:547-558. Marchesi, J., A. Weightman, B. Cragg, R. Parkes, and J. Fry. 2001. Methanogen and bacterial diversity and dist ribution in deep gas hydrat e sediments from Cascadia Margin as revealed by 16s rRNA. FEMS Microbiol. Ecol. 34:221-228. Martin, A. P. 2002. Phylogenetic approaches for describing and comparing diversity of microbial communities. Appl. Environ. Microbiol. 68:3673-3682.

PAGE 136

122 McCaig, A. E., Embley, T.M., Prosser, J. L. 1994. Molecular analysis of enrichment cultures of marine ammonium oxidizer s. FEMS Microbiol. Lett. 120:363-368. McKibben, B. 1989. The end of nature Random House, New York, NY. McTavish, H. J. A. F., and A. B. Ho oper. 1993. Sequence of the gene coding for ammonia monooxygenase in Nitrosomonas europaea J. Bact. 175:2436-2444. Megonigal, J. P., M.E. Hines, and P.T. Visscher. 2004. Anaerobic metabolism: linkages to trace gases and aerobic processes, p. 317-424. In W. H. Schlesinger (ed.), Biogeochemistry. Elsevier-Pergamon, Oxford, UK. Meril, P., P.E. Galand, H. Fritze, E.-S. Tuitt ila, K. Kukko-oja, J. Laine, and K. Yrl. 2006. Methanogen communities along a primary succession transect of mire ecosystems. FEMS Microbiol. Ecol. 55:221-229. Michotey, V., V. Mejean, and P. Bonin. 2000. Comparison of methods for quantification of cytochrome cd(1)-denitrif ying bacteria in environmen tal marine samples. Appl. Environ. Microbiol. 66:1564-1571. Mintie, A. T., Heichen, R.S., Cromack, Jr ., Myrold, D.D., and P.J. Bottomley. 2003. Ammonia-oxidizing bacteria along a meadow-to-forest transect in the Oregon Cascade Mountains. Appl. Envi ron. Microbiol. 69:3129-3136. Murray, R. E., and R. K. Knowles. 1999. Ch loramphenicol inhibition of denitrifying enzyme activity in two agricultural so ils. Appl. Environ. Microbiol. 65:3487-3492. Mytinger, L., and G.B.Williamson. 1987. The invasion of Schinus into saline communities of Everglades National Park. Fla. Sci. 50:7-12. Nanba, K., G.M. King, and K. Dunfield. 2004. Analysis of facultative lithotroph distribution and diversity on volcanic depos its by use of the large subunit of ribulose 1,5-bisphosphate carboxylase/ oxygenase. Appl. Environ. Microbiol. 70:2245-2253. Nannipieri, P., J. Ascher, M.T. Ceccherini, L. Landi, G. Pietramellara, and G. Renella. 2003. Microbial diversity and soil func tions. Eur. J. Soil Sci. 54:655-670. Norton, J. M., J.J. Alzerreca, Y. Suwa, a nd M.G. Klotz. 2002. Diversity of ammonia monooxygenase operon in autotrophic ammonia-oxidizing bacteria. Arch. Microbiol. 177:139-149. Odum, E.P. 1969. The strategy of ecosyste m development. Science. 164: 262-270. O'Mullan, G. D., and B. B. Ward. 2005. Relations hip of temporal and spatial vari abilities of ammonia-oxidizing bacteria to nitrific ation rates in Monterey Bay, California. Appl. Environ. Microbiol. 71:697-705.

PAGE 137

123 Ohsaka, T., S. Yoshie, S. Tsuneda, A. Hira ta, and Y. Inamori. 2004. Characterization of nitrite reductase gene ( nirS and nirK ) in active denitrifying population in activated sludge on the basis of stable isotope probing. Genbank direct submission: http://www.ncbi.nlm.nih.gov. Unpublished da ta, University of Osaka, Japan. Okano, Y., Hristove, K.R., Leutenegger, C.M ., Jackson, L.E., Denison, R.F., Gebreyesus, B., Lebauer, D. and K.M. Scow. 2004. A pplication of real-time PCR to study effects of ammonium on population size of ammonia-oxidizing bacteria in soil. Appl. Environ. Microbiol. 70:1008-1016. Palmedo, G., P. Seither, H. Korner, J.C. Ma tthews, R.S. Burkhalter, R. Timkovich, and W.G. Zumft. 1995. Resolution of the nirD locus for heme d1 synthesis of cytochrome cd1 (respiratory nitrit e reductase) from Pseudomonas stutzeri Eur. J. Biochem. 232:737-746. Palumbo, A. V., J.C. Schryver, M.W. Fields C.E. Bagwell, J.Z. Zhou, T. Yan, X. Liu, and C.C. Brandt. 2004. Coupling of functiona l gene diversity and geochemical data from environmental samples. A ppl. Environ. Microbiol. 70:6525-6534. Park, H. D., and D.R. Noguera. 2004. Eval uating the effect of dissolved oxygen on ammonia-oxidizing bacterial communities in activated sludge. Water. Res. 38:3275-3286. Parkin, T. B. 1987. Soil microsites as a source of denitrification variab ility. Soil Sci. Soc. Am. J. 51:1194-1199. Payne, W. J. 1981. Denitrification, 1 ed. John Wiley & Sons, Inc., New York, NY. Pedersen, H., K.A. Dunkin, and M.K. Fi restone. 1999. The relative importance of autotrophic and heterotrophic ni trification in a conifer fo rest soil as measured by 15N tracer and pool dilution tec hniques. Biogeochemistry 44:135-150. Pell, M., B. Stenberg, J. Stenstrom, and L. Torstensson. 1996. Potential denitrification activity assay in soil with or without chloramphenicol?. Soil Biol. Biochem. 28:393-398. Peters, V., and R. Conrad. 1995. Methanogenic a nd other strictly anaerobic bacteria in desert soil and other oxic soils Appl. Environ. Microbiol. 61:1673-1676. Prenger, J. P., and K.R. Reddy. 2004. Microbial enzyme activities in a freshwater marsh after cessation of nutrient loadi ng. Soil Sci. Soc. Am. J 68:1796-1804. Priem, A., G. Braker, and J.M. Tiedje 2002. Diversity of nitrite reductase ( nirK and nirS ) gene fragments in forested up land and wetland soils. Appl. Environ. Microbiol. 68:1893-1900.

PAGE 138

124 Purkhold, U., A. Pommerening-Roser, S. Jure tchko, M.C. Schmid, H.P. Koops, and M. Wagner. 2000. Phylogeny of all recognized sp ecies of ammonia oxidizers based on comparative 16S rRNA and amoA sequence analysis: implications for molecular diversity surveys. Appl. Environ. Microbiol. 66:5368-5382. Purkhold, U., M. Wagner, G. Timmermann, A. Pommerening-Roser, and H.P. Koops. 2003. 16S rRNA and amoA based phylogeny of 12 novel beta-proteobacterial ammonia-oxidizing isolates: ex tension of the dataset and proposal of a new lineage with the nitrosomonads. Int. J. Syst. Evol. Microbiol.:53. Rambaut, A. 1996. Se-Al: sequence alignment editor. Oxford University. [Online.] http://evolove.zoo.ox.ac.uk. May 2006. Reddy, K. R., and W.H. Patrick. 1984. Nitrogen transformations and loss in flooded soils and sediments. CRC Critical Re v. Environ. Controls 13:273-309. Reddy, K. R., W.H. Patrick, C.W. Lindau. 1989. N itrification-denitrific ation at the plant root-sediment interface in wetlands. Limnol. Oceanogr. 34:1004-1013. Reeve, J. N. 1992. Molecular biology of methanogens. Ann. Rev. Microbiol. 46:165191. Reynolds, J. B. S. W., and C.C. Cocker ham. 1983. Estimation for the coancestry coefficient: basis for a short-term genetic distance. Genetics 105:767-779. Rice, E. L., and S.K. Pancholy. 1972. Inhibitio n of nitrification by climax vegetation. Am. J. Botany 59:1033-1040. Rich, J. J., and D.D. Myrold. 2004. Community composition and activities of denitrifying bacteria from adjacent agricultural soil, ri parian soil, and creek sediment in Oregon, USA. Soil Biol. Biochem. 36:1434-1441. Risgaard-Peterson, N., Nicolaisen, M.H., Revsbeech, N.P., and B.A. Lomstein. 2004. Competition between ammonia-oxidizing bacteria and benthic microalgae. Appl. Environ. Microbiol. 70:5528-5537. Robertson, G. P., and P.M. Vitousek. 1981. N itrification potentials in primary and secondary succession. Ecology 62:376-386. Robertson, G. P. 1982. Factors regulating ni trification in primary and secondary succession. Ecology 63:1561-1573. Robertson, G. P. 1989. Nitrification and deni trification in humid tropical ecosystems: potential controls on nitrogen retention, p. 55-70. In J. Proctor (ed.), Mineral nutrients in tropical forest and savanna ecosystems. Blackwell Scientific, Oxford, UK.

PAGE 139

125 Ronquist, F., and J.P. Huelsenbeck. 2003. Mr Bayes 3: Bayesian phylogenetic inference under mixed models. Bioinformatics 19:1572-1574. Ross, D. J., T.W. Speir, H.A. Kettle, and A.D Mackay. 1995. Soil microbial biomass, C and N mineralization, and enzyme activities in a hill pasture: influence of season and slow-release P and S fertiliz er. Soil Biol. Biochem. 27:1431-1443. Rotthauwe, J. H., K.P. Witzel, and W. Liesack. 1997. The ammonia monooxygenase structural gene amoA as a functional marker: molecular fine-scale analysis of natural ammonia-oxidizi ng populations. Appl. Environ. Microbiol. 63:4704-4712. Roy, R., H.D. Kluber, and R. Conrad. 1997. Early initiation of methane production in anoxic rice soil despite the presence of oxidants. FE MS Microbiol. Ecol. 24:311320. Santoro, A. E., A.B. Boehm, and C.A. Francis. 2006. Denitrifier community composition along a nitrate and salinity gr adient in a coastal aquifer. Appl. Environ. Microbiol. 72:2102-2109. Schimel, J. P., M.K. Firestone, and K.S. Killham. 1984. Identification of heterotrophic nitrification in a Sierra n forest soil. Appl. Envi ron. Microbiol. 48:802-806. Schimel, J. P., and J. Gulledge. 1998. Micr obial community struct ure and global trace gases. Global Change Biol. 4:745-758. Schipper, L. A., A.B. Cooper, C.G. Harf oot, and W.J. Dyck. 1993. Regulators of soil denitrification in an organic ripari an soil. Soil. Biol. Biochem 25:925-933. Schloss, P. D., B.R. Larget, and J. Ha ndelsman. 2004. Integration of microbial ecology and statistics: a test to compare gene libraries. Appl. Envi ron. Microbiol. 70:54855492. Schloss, P. D., and J. Handelsman. 2005. In troducing DOTUR, a computer program for defining operational taxonomic units a nd estimating species richness. Appl. Environ. Microbiol. 71:1501-1506. Schloss, P.D., and J. Handelsman. 2006. In troducing TreeClimber, a test to compare microbial community structures. Ap pl. Environ. Microbiol. 72:2379-2384. Schneider, S., D. Roessli, and L. Excoffi er. 2000. Arlequin: a software for population genetics data analysis, 3.ed. Genetics and Biometry Laboratory, University of Geneva, Switzerland. Schramm, A., D. de Beer, M. Wagner, a nd R. Amann. 1998. Identification and activities in situ of Nitrosospira and Nitrosospira spp. as dominant populations in a nitrifying fluidized bed reactor. Appl. Environ. Microbiol. 64:3480-3485.

PAGE 140

126 Schramm, A., D. de Beer, J.C. van de n Heuvel, S. Ottengraf, and R. Amann. 1999. Microscale distribution of popul ations and activities of Nitrosospira and Nitrosospira spp. along a macroscale gradient in a nitrifying bioreactor: quantification by in situ hybridization and the use of microelectrodes. Appl. Environ. Microbiol. 65:3690-3696. Schramm, A., D. De Beer, A. Gieseke, and R. Amann. 2000. Microenvironments and distribution of nitrifying bacteria in a membrane-bound biofilm. Environ. Microbiol. 2:680-686. Schutz, H., W. Seiler, and R. Conrad. 1989. Processes involved in formation and emission of methane from rice pa ddies. Biogeochemistry 7:33-53. Seitzinger, S. P. L. 1994. Linkages betw een organic matter mineralization and denitrification in eight riparian wetlands. Biogeochemistry 25:19-39. Shapleigh, J. P. 2000. The denitrifying prokaryotes. In M. Dworkin (ed.), The prokaryotes: an evolving electronic re source for the microbiological community. Springer-Verlag, New York, NY. [Online]. http://141.150.157:8080/prok/PUB/index.htm May 2006. Shoun, H., and T. Tanimoto. 1991. Denitrification by the fungus Fusarium oxysporum and involvement of cytochrome P-450 in respiratory nitrite reduction. J. Biol. Chem. 266:11078-11082. Singleton, D. R., M.A. Furlong, S.L. Ra thbun, and W.B. Whitman. 2001. Quantitative comparisons of 16S rRNA sequence librari es from enviromental samples. Appl. Environ. Microbiol. 70:1608-1616. Sjogersten, S., and P.A. Wookey. 2002. Climatic and resource quality controls soil respiration across a forest-tundra ecotone in Swedish Lapland. Soil Biol. Biochem. 34:1633-1646. Smith, M. S., and J.M. Tiedje. 1979. Phases of denitrification fo llowing oxygen depletion in soil. Soil. Biol. Biochem 11:261-267. Springer, E., M.S. Sachs, C.R. Woese, a nd D.R. Boone. 1995. Partial gene sequences for the A subunit of methyl-coenzyme M reductase ( mcrI ) as a phylogenetic tool for the family Methanosarcinaceae. In t. J. Syst. Bacteriol. 45:554-559. Stein, L. Y., L.A. Sayavedra-Soto, N.G. Hommes, D.J. Arp. 2000. Differential regulation of amoA and amoB gene copies in Nitrosmonas europaea FEMS Microbiol. Lett. 192:163-168. Stephen, J. R., A.E. McCaig, Z. Smith, J.I. Prosser, and T.M. Embley. 1996. Molecular diversity of soil and marine 16S rRNA gene sequences related to -subgroup ammonia-oxidizing bacteria. Appl Environ. Microbiol. 62:4147-4154.

PAGE 141

127 Stephen, J. R., G.A. Kowalchuk, M.A.V. Bu rns, A.E. McCaig, C.J. Phillips, T.M. Embley, and J.I. Prosser. 1998. Analysis of subgroup proteobacterial ammonia oxidizer populations in sol by denaturing gr adient gel electrophoresis analysis and hierarchical phylogenetic probing. Appl Environ. Microbiol. 64:2958-2965. Stienstra, A. W., P.K. Gunnewick, and H.J. Laanbroek. 1994. Repression of nitrification in soils under climax grassland vege tation. FEMS Microbiol. Ecol. 14:45-52. Stuven, R., M. Vollmer, and E. Bock. 1992. The impact of organic matter on nitric oxide formation by Nitrosomonas europaea Arch. Microbiol. 158:439-443. Swofford, D. L. 1998. PAUP*. Phylogenetic analysis using parsimony (*and other methods), 4 ed. Sinauer A ssociates, Sunderland, MA. Tate, R. L. 1995. Soil microbiology. John Wiley & Sons, Inc., New York, NY. Teske, A., E. Alm, J.M. Regan, S. Toze, B.E. Rittmann, and D.A. Stahl. 1994. Evolutionary relationships among ammoni aand nitrite-oxidizing bacteria. J. Bacteriol. 176:6623-6630. Thauer, R. K. 1998. Biochemistry of metha nogenesis: a tribute to Marjory Stephenson. Microbiology. 144:2377-2406. Thompson, J. D., T.J. Gibson, F. Plewniak, F. Jeanmougin, and D.G. Higgins. 1997. The ClustalX windows interface: flexible stra tegies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Res. 24:4876-4882. Throbck, I. N., K. Enwall, A. Jarvis, and S. Hallin. 2004. Reassessing PCR primers targeting nirS nirK, and nosZ genes from community surveys of denitrying bacteria with DGGE. FEMS Microbiol. Ecol. 49:401-417. Tiedje, J. M. 1982. Deni trification, p. 1011-1026. In A. L. Page, et al. (ed.), Methods of soil analysis, 2 ed, vol. 2. Agron. M onogr. 9. Amer. Soc. Agron., Madison, WI. Tiedje, J. M. 1988. Ecology of denitrification and dissimila tory nitrate reduction to ammonium, p. 179-244. In A. J. B. Zehnder (ed.), Biology of anaerobic microorganisms. Wiley, New York, NY. Touzel, J. P., and G. Albagnac. 1983. Isolation and characterization of Methanococcus mazei strain MC3. FEMS Mi crobiol. Lett. 16:241-245. Tuomainen, J. M., S. Hietanen, J. Kuparine n, P.J. Maritkainen, and K. Servomaa. 2003. Baltic Sea cyanobacterial bloom contains den itrification and nitrif ication genes, but has negligible denitrif ication activity. FEMS Microbiol. Ecol. 45:83-96. Uhel, C., C. Roumet, and L. Salsac. 1989. Inducib le nitrate reductase of rice plants as a possible indicator of nitrification in water-logged paddy soils. Plant Soil 76:252264.

PAGE 142

128 Usuda, K., N. Toritsuka, T. Matsuo, D.H. Ki m, and H. Shoun. 1995. Denitification by the fungus Cylindrocarpon tonkinense : anaerobic cell growth and two isozyme forms of cyctochrome P-450nor. Appl. Environ. Microbiol. 61:883-889. Van de Peer, Y., and R. De Wachter. 1994. TREECON for Windows: a software package for the construction of evolutionary tr ees for Microsoft Windows environment. Comput. Appl. Bi osci. 10:569-570. VanGestel, M., R. Merckx, and K. Vlassak. 1993. Microbial biomass responses to soil drying and rewetting: the fate of fast and slow growing microorganisms in soils from different climates. Soil. Biol. Biochem. 25:109-123. Vitousek, P. M., P.A. Matson, and K. Van Cleve. 1989. Nitrogen availability and nitrification during succession: primary, s econdary, and old-field seres. Plant Soil 115:229-239. Vitousek, P. M., and R.W. Howarth. 1991. Nitr ogen limitation on land and in the sea: how can it occur? Biogeochemistry 13:212-218. Walker, L. R. 1999. Patterns and processes in primary succession, ecosystems of disturbed ground, ecosystems of the world 16. Elsevier, Amsterdam. Walker, L. R., and M.R. Willig. 1999. An introduction to terrestrial disturbances. In L. R. Walker (ed.), Ecosystems of distur bed ground, ecosystems of the world 16. Elsevier, Amsterdam. Walker, L. R., and R. del Moral. 2003. Pr imary succession and ecosystem rehabilitation. Cambridge University Press, Cambridge, UK. Wander, M. M., and G.A. Bollero. 1999. Soil quality assessment of tillage impacts in Illinois. Soil Sci. Soc. Am. J. 63:961-971. Ward, B. B. 2002. How many species of prokary otes are there? Proc. Nat. Acad. Sci. 99:10234-10236. Webster, G., T.M. Embley, and J.I Pro sser. 2002. Grassland management regimens reduce small-scale heterogeneity and species diversity of -proteobacterial ammonia oxidizer populations. Appl Environ. Microbiol. 68:20-30. Webster, G., T.M. Embley, T.E. Freitage, Z. Smith, and J.I Prosser. 2005. Links between ammonia oxidizer species composition, f unctional diversity and nitrification kinetics in grassland soils Environ. Microbiol. 7:676-684. White, J. R., and K.R. Reddy. 1999. Influence of nitrate and phosphorous loading on denitrifying enzyme activity in Everglades wetland soils. Soil Sci. Soc. Am. J. 63:1945-1954.

PAGE 143

129 White, J. R., and K.R. Reddy. 2000. Influence of phosphorous loading on organic N mineralization rates in Everglades so ils. Soil. Sci. Soc. Am. J. 63:1945-1954. White, J. R., and K.R. Reddy. 2003. Nitrification and denitrification ra tes of Everglades wetland soils along a phosphorous-impacted gradient. J. Environ. Qual. 32:24362443. Williams, B. L., and G.P. Sparling. 1 988. Microbial biomass carbon and readily mineralizable nitrogen in peat and fore st humus. Soil Biol. Biochem. 20:579-581. Wolfe, R. S. 1996. 1776-1996: Alessandro Volta 's combustible air. ASM News 62:529539. Wolsing, M., and A. Prieme. 2004. Observation of high seasonal variation in community structure of denitrifying bact eria in arable soil receiving artificial fertilizer and cattle manure by determining T-RFLP of nir gene fragments. FEMS Microbiol. Ecol. 48:261-271. Wood, P. M. 1986. Nitrification as a bacterial energy source, p. 39-62. In J. I. Prossor (ed.), Nitrification. Society for Gene ral Microbiology, IRL Press, Oxford. Wright, A. L., and K.R. Reddy. 2001. Hetero trophic microbial activity in northern Everglades wetland soils. Soil Sci. Soc. Am. J. 65:1856-1864. Yan, T., Fields, M.W., Wu, L., Zu, Y., Tiedje, J.M., and Zhou, J. 2003. Molecular diversity and characterization of n itrite reductase gene fragments ( nirK and nirS ) from nitrateand uranium-contaminated groundwater. Environ. Microbiol. 5:13-24. Yannarell, A. C., T.F. Steppe, and H.W. P aerl. 2006. Genetic variance in composition of two functional groups (diazotrophs an d cyanobacteria) from a hypersaline microbial mat. Appl. Environ. Microbiol. 72:1207-1217. Yoshinari, T., and R. Knowles. 1976. Acetyl ene inhibition and nitr ous oxide reduction by denitrifying bacteria. Biochem. Biophys. Res. Commun. 69:705-710. You, S. J. 2005. Identification of denitrifying bacteria diversity in an activated sludge system by using nitrite reductase genes. Biotechnol. Lett. 27:1477-1482 Zhou, J., Xia, B., Treves, D.S., Wu, L.Y., Ma rsh, T.L., O'Neill, R.V., Palumbo, A.V., and J.M. Tiedje. 2002. Spatial and resource fact ors influencing high microbial diversity in soil. Appl. Environ. Microbiol. 68:326-334. Zumft, W. G. 1997. Cell biology an d molecular basis of denitr ification. Microbiol. Mol. Biol. Rev. 61:533-616.

PAGE 144

130 BIOGRAPHICAL SKETCH Jason M. Smith was born in Rochester, New York, on the 7th of March, 1981. Having spent his entire life in the suburbs gr owing up with the same people, the abrupt move to Orlando, Florida, in 1997 came as a shock. Warned by his previous teachers about the dregs of southern educational idea ls, he entered Lake Mary High School with some skepticism. After finishing high sc hool in 1999, he entered the University of Florida believing he was cut out to be a lawyer. His initial exposure to science came as a result of University of Florida coursetracking requirements. After taking his first lab-based chemistry course, he realized the excitement of research. He graduated cum laude from the University of Florida, Gainesville, Florida, in 2003 with a B. S. in microbiology and cell science. He joined the Soil and Water Science De partment during the final year of his undergraduate career as a student volunteer, studying th e ecology of naphthalene biodegradation under Dr. Andrew Ogram. His involvement in the Soil Molecular Ecology Laboratory was integral in the initial developmen t of his fascination with environmental systems. He decided to st ay involved, and in 2004 he began pursuing a Master of Science degree under Dr. Andrew Ogram. Following graduation Jason plans to move to San Francisco, California, to continue working in molecular ecology in the Microb ial Ecology and Biogeochemistry Laboratory at NASA Ames Research Center. Eventually, he hopes to obtain a doctorate and join the professoriate.


Permanent Link: http://ufdc.ufl.edu/UFE0015225/00001

Material Information

Title: Microbial Succession Associated with Soil Redevelopment along a Short-Term Restoration Chronosequence in the Florida Everglades
Physical Description: Mixed Material
Copyright Date: 2008

Record Information

Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
System ID: UFE0015225:00001

Permanent Link: http://ufdc.ufl.edu/UFE0015225/00001

Material Information

Title: Microbial Succession Associated with Soil Redevelopment along a Short-Term Restoration Chronosequence in the Florida Everglades
Physical Description: Mixed Material
Copyright Date: 2008

Record Information

Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
System ID: UFE0015225:00001


This item has the following downloads:


Full Text


















MICROBIAL SUCCESSION ASSOCIATED WITH SOIL REDEVELOPMENT
ALONG A SHORT-TERM RESTORATION CHRONOSEQUENCE IN THE
FLORIDA EVERGLADES















By

JASON M. SMITH


A THESIS PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE

UNIVERSITY OF FLORIDA


2006



























Copyright 2006

by

Jason M. Smith



































For my mother.















ACKNOWLEDGMENTS

I would like to especially recognize Dr. Andrew Ogram, chair of my graduate

committee, for his unconditional support, introducing me to microbial ecology, which has

yet to cease fascinating me, and allowing me to pursue questions independently. Further,

I am thankful for the financial support provided to me from his grant money, and

foremost for his moral support, and for being the kind of advisor you never want to

disappoint.

I would like to extend my gratitude to Drs. Nicholas Comerford and K. Ramesh

Reddy, members of my graduate committee, for their helpful comments and advice

during my studies.

I am thankful to the Department of the Interior, the National Park Service, and the

late Dr. Michael Norland for providing funding and access to research sites.

I would like to extend my sincere gratitude to Dr. Hector Castro for his endless

encouragement, truthful criticisms, and many paid lunches. Mostly, I would like to

acknowledge his influence on my understanding of what it means to become an

independent thinker, and his continued insistence that I learn to approach questions and

problems with tenacity.

I wish to thank my current and former lab-mates, Drs. Abid Al-Agely, Ashvini

Chauhan, Ilker Uz, and Yannis Ipsilantis, Puja Jasrotia, and Lisa Stanley, for making long

days in the lab more interesting. Special thanks go to Yun Cheng for her continued

friendship throughout my tenure in the department.









I am grateful to all the people who were instrumental in the success of this study;

including Drs. Kanika Sharma and Patrick Inglett, Ms. Yu Wang, the Wetland

Biogeochemistry Laboratory, for sampling coordination and biogeochemical data.

Adrienne Frisbee and Isabela Claret Torres were both instrumental in the completion of

my studies involving gas chromatography.

I want to thank the faculty, staff, and all graduate students in the Soil and Water

Science Department for their support. Special thanks to go Dr. George O'Connor for

being a source of encouragement at the beginning of my graduate studies.

I would like to acknowledge the support of my colleagues at NASA Ames

Research Center for their words of encouragement and helpful discussions. Dr. Brad

Bebout and Ms. Mary Hogan are thanked for providing a method of nitrate analysis.

I am greatly indebted to my brother Chris and my grandparents Herbert and

Shirley Smith, for their love and encouragement. My mother, Debi, has been a constant

source of support and encouragement throughout my academic career, and it is she whom

I strive to make proud.

Finally, I would like to thank my long time friends and unconditional supporters,

who have made my time in Gainesville bearable, even through the hardest of times. I

would like to especially thank Jared Ausanio, Adrienne Frisbee, Yvan Levesque, and

Melissa Lott, for always making time for a beer on the porch at the end of a rough day.
















TABLE OF CONTENTS



A C K N O W L E D G M E N T S ................................................................................................. iv

LIST OF TA BLES .................................................................... ............ .. ix

LIST OF FIGURES ......... ......................... ...... ........ ............ xi

A B S T R A C T .......................................... .................................................. x iii

CHAPTER

1 IN TR OD U CTION ............................................... .. ......................... ..

The H ole-in-the-D onut ..................... .. .... .... ... ... .... .... .. ...... .......... .... ..
M icrobial Indicators.............................................. 3
M ethanogenesis ...................... ........ ...... ... ............... ....
N itrifi c a tio n ........................................................................................................... 1 0
Denitrification ............... ....... ........... ....... .........16
H ypotheses and O bjectives......... ................. ................... ................. ............... 20

2 STRUCTURE AND FUNCTION OF METHANOGENIC ASSEMBLAGES
ALONG A SHORT-TERM RESTORATION CHRONOSEQUENCE ....................27

Introduction .............. .. ..... ......... ............... .............................27
M materials and M methods ............................ ............... ........... ............ ............... 29
Site Characteristics, Sample Collection, and Biogeochemical
Characterization ............................................... .. ...... .. ............ 29
Methane Production Potentials...................... ......... ..................30
Nucleic Acid Extraction and PCR Amplification ............................................30
Cloning and R FLP A nalysis........................................... ......................... 31
Sequencing and Phylogenetic Analysis.................................... ............... 32
T -R F L P A n aly sis................................... .................................. ....................3 2
D iv ersity In dices................................................................................ .... 33
R results and D discussion ................................ .................. .................. ......... 33
M ethane Production in H ID Soils ......................... ... ...................... .... 34
Phylogenetic Characterization of Methanogenic Assemblages in HID Soils .....35
T-RFLP Analysis of Methanogenic Assemblage Structure ..............................37
Seasonal Structure of Methanogenic Assemblages .....................................37
Shifts in Methanogenic Assemblages with Restoration Age ...........................39









C o n clu sio n s..................................................... ................ 4 0

3 GENETIC AND FUNCTIONAL VARIATION IN DENITRIFIER
POPULATIONS ALONG A SHORT-TERM RESTORATION
C H R O N O SE Q U EN C E ......... .. ....... .............. ............................................49

Introduction .............. ..... ... .............. .................................. 49
M materials and M methods .................. ........... ......................................................51
Site Characteristics, Sampling, and Biogeochemical Characterization..............51
Denitrifying Enzyme Activity and Gas Analysis.........................................52
Nucleic Acid Extraction, PCR Amplification, Cloning and Sequencing............53
Phylogenetic and D diversity A nalysis........................................ ............... 54
Statistical Analysis of Phylogenetic Data......................................................55
Statistical Analysis of Biogeochemical Data ................................. ............... 57
R results and D discussion ........................... ........ ........ .... ............ ... ... .. ....... ....57
Soil Biogeochemical Parameters Along the Restoration Gradient....................57
nirS phylogeny.................................... ............................... .......59
nirK phylogeny ........... .. .. .... ............................................ ...... ....... 60
Richness and Diversity of nirS and nirK Populations ..................................62
Population-Based Library Compositions .................................... ............... 64
Variance within nirK Clone Libraries ...................................... ............... 68
C o n c lu sio n s..................................................... ................ 7 1

4 SEASONAL DIVERSITY AND FUNCTION OF AMMONIA OXIDIZING
BACTERIA ALONG A SHORT-TERM RESTORATION
C H R O N O SE Q U EN C E ......... .. ....... .............. ............................................79

M materials and M methods ................ ....... ............. .............. ............................82
Site Description, Sampling, and Biogeochemical Characterization..................82
Determination of Potential Nitrification Rates................ ...............83
Extraction of Nucleic Acids and PCR .................... ........ .. ... ............ 85
C loning and Sequ encing ........................................................... .....................85
Phylogenetic Analysis ........................ .............................. 86
Statistical Analysis of Phylogenetic Data......................................................86
Statistical Analysis of Biogeochemical Data ................................. ............... 88
R results and D discussion ................................. ........................ ......... ............... 88
Biogeochemical Parameters of Soils Along the Restoration Gradient ..............88
Phylogenetic Analysis of amoA.................... ........ ............... 90
Statistical Analysis of Clone Libraries ......... .............. ... .....................93
Correlation of Differences in amoA Diversity With Environmental Variables ..96

5 SUMMARY AND CONCLUSIONS ............. ................ ........... ...............104

APPENDIX

A SUPPLEMENTAL TABLES ............................................................................109

C chapter 4 ............ ..... ................................................................ 109










B SU PPLEM EN TAL FIG U RE S ............... ............. .................................................110

C h a p te r 2 .............. ..... ............ ................. ..... ................................... 1 1 0
Chapter 3 ..................................... ................... 111
Chapter 4 ............... ............................... ...............113

LIST OF REFERENCES ........................ ......... ......... 114

BIOGRAPHICAL SKETCH ................ ........ ........ ........130















































V111iii
















LIST OF TABLES


Table page

2-1 Geochemical parameters of dry and wet season soils. ............................................42

2-2 Potential methanogenesis rates and accumulated CH4 in wet season soils ..............43

2-3 Expected and observed phylotypes and diversity indices for dry season mcrA
clone libraries. ........................................................................43

2-4 Phylogenetic affiliation of mcrA T-RFs. ................................................................44

3-1 Biogeochem ical param eters of HID soils ............................................................. 72

3-2 Distribution of nirS sequences from each study site within designated
phylogenetic clusters. ............................ ........................... .......... ................72

3-3 Values of nirS and nirK diversity and richness in HID soils...................................73

3-4 Population similarity P values for comparison of nirK and nirS clone libraries.......74

3-5 Corrected average pairwise differences and pairwise fixation indices for nirK........75

3-6 Fixation indices, average pairwise differences, nucleotide diversity, and shared
haplotypes of nirK clone libraries ..................................... ........................ ......... 75

4-1 Biogeochemical parameters of dry and wet season HID soils. ................................98

4-2 Results of sequence analysis of amoA sequences obtained from dry and wet
season soils ............................................. ............................ 99

4-3 Fixation indices, average pairwise differences, nucleotide diversity, and unique
haplotypes for wet and dry season amoA clone libraries. ......................................100

4-4 Corrected average pairwise differences and pairwise fixation indices for dry
season am oA sequences.................................................. ............................ 101

4-5 Corrected average pairwise differences and pairwise fixation indices for wet
season am oA sequences.................................................. ............................ 101









4-6 Results of Mantel correlation tests between pairwise differences of population
specific FST values for wet and dry season amoA clone libraries with
biogeochem ical param eters. ........................................... ............................ 102

A-1 Population similarity P values for comparison of amoA dry and wet season clone
lib ra rie s ...................................................................... 1 0 9
















LIST OF FIGURES


Figure page

1-1 The Hole-in-the-Donut restoration area. ...................................... ............... 21

1-2 Pathways of autotrophic nitrification and of denitrification and the nitrogen trace
gases em itted .........................................................................22

1-3 The major factors controlling nitrification in soils...........................................23

1-4 Schematic representation of nitrogen cycling in flooded soils and sediments..........24

1-5 The major factors controlling denitrification in soils........................ .............25

1-6 The basic arrangement of the nitrogen oxide reductases required for complete
denitrification by a single organism ........................................ ...... ............... 26

2-1 Neighbor-joining mcrA tree for representative clones from April 2004 soils...........45

2-2 Distribution of mcrA sequences obtained from dry season soils within designated
phylogenetic clusters. ............................ ........................... .......... ................46

2-3 Community dynamics for the mcrA gene in dry season HID soils determined by
T -R F L P an aly sis........... .................................................................... ....... ............... 4 7

2-4 Community dynamics for the mcrA gene in wet season HID soils determined by
T -R F L P an aly sis................................................ ................. 4 8

3-1 Neighbor-joining tree of nirS sequences obtained from wet season soils ...............76

3-2 Neighbor-joining tree of nirK sequences obtained from wet season soils ...............77

3-3 Sequence analysis of nirK clones obtained from wet season soils............................78

4-1 Cladogram of representative amoA sequences obtained from HID soils ...............103

B-l Rarefaction curves for mcrA clone libraries ......................................................110

B-2 Potential denitrification rates as a function of N20-N production with time. ........111

B-3 Rarefaction curves for nirS and nirK clone libraries .............................................112









B-4 Rarefaction curves for amoA clone libraries from dry season and wet season
so ils .................................................................................. . 1 1 3















Abstract of Thesis Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Master of Science

MICROBIAL SUCCESSION ASSOCIATED SOIL REDEVELOPMENT ALONG A
SHORT-TERM RESTORATION CHRONOSEQUENCE IN THE FLORIDA
EVERGLADES

By

Jason M. Smith

August 2006

Chair: Andrew V. Ogram
Major Department: Soil and Water Science

The Hole-in-the-Donut (HID) restoration program involves removal of non-native

Brazilian pepper (Schinus terebinthefolius) from land within Everglades National Park.

The restoration approach involves complete clearing of Schinus and removal of topsoil

down to bedrock. Subsections within the HID are cleared at different times, creating a

series of sites at different stages of recovery. As the direct linkage between nutrients

retained in parent material and plant roots, soil development in newly cleared sites will be

essential to successful reestablishment of plant communities and biogeochemical

linkages. Establishment of microbial communities will precede plant colonization. As

the primary mediators of biogeochemical cycling of carbon and nitrogen, ecology of

microorganisms responsible for key roles in nutrient cycling in developing HID soils may

provide insights into the reestablishment of biogeochemical linkages with soil

redevelopment, the recovery stage of each site, and whether the direction of recovery is

towards that of an undisturbed wetland ecosystem. Methane production potentials









suggest hydrogen as the dominant methanogenic precursor. Further, highest methane

production was observed from most recently restored sites; data suggest decreased

contribution of methanogenesis to anaerobic mineralization with restoration age.

Molecular analyses indicate the presence of all major metabolic groups of methanogens

in all sites. Methanogenic communities were stable between seasons; however, both

cloning and T-RFLP analyses indicated shifts within the M thitI i tI ict il'%e with

restoration age. Denitrifying bacterial communities were active in all study sites.

Phylogenetic analyses of genes associated with nitrite reduction indicate the presence of

unique lineages in soils from all sites. Iterative statistical analyses of clone libraries

suggest different disturbance response regimes of groups harboring different genes

encoding for the same enzyme. nirS genotypes suggest an approximately linear response

of diversity to restoration age, while nirK analyses suggest a biomodal response with

restoration age. Nitrifying bacterial populations were active in both seasons, although

rates decreased significantly in wet season soils. Molecular analyses suggest two

genotypes of nitrifiers to dominate restored and undisturbed soils, and each site harbors

unique distributions of the genotypes. Pairwise differences in diversity between sites

were strongly correlated with soil oxygen demand. Collectively, these data indicate

compositional shifts in microbial populations associated with carbon and nitrogen cycling

in the context of soil redevelopment and restoration age, and provide significant insights

into the response of specific microbial populations to severe disturbance and recovery.














CHAPTER 1
INTRODUCTION

Ecosystem disturbance involves an event occurring over a relatively discrete

space and time that alters the physical environment, leading to changes in the structure of

populations and communities, density of biomass, spatial distribution of biota, and

resource availability (Walker and del Moral, 2003). The types of disturbance imposed

upon an ecosystem are grouped into four major categories, as outlined by Walker and

Willig (1999); they include earth, air, water, and fire. The four disturbance classes are

related to natural processes, such as the movement of tectonic plates, and the interplay of

climatic, topographic, and soil factors, for example: hurricanes, wild fires, volcanic

eruptions, and land slides (Walker and Willing, 1999). An additional category involves

those disturbances imposed upon the environment by the activities of humans, such as

agricultural activity, deforestation, and urbanization. The impacts of human activity are

apparent in all of the Earth's biomes; it is most often human activity that leads to

ecosystem disturbance or restoration (McKibben, 1989). Many of the modern instances

of an ecosystem undergoing primary succession are either directly anthropogenic in

origin or influenced to some degree by human activities (Walker, 1999).

The Hole-in-the-Donut

The Hole-in-the-Donut (HID) is a 4000-ha region within Everglades National

Park (ENP), Florida, USA (Figure 1-1). Once consisting of oligotrophic sawgrass

(Cladiumjamaicense Crantz) prairies and short hydroperiod pinelands, the HID was

subjected to agricultural land use practices from 1916 to 1978 (Dalryample et al., 2003).









When farming activity stopped, the HID was left as an abandoned, high nutrient, high

oxygen environment (Aziz and Sylvia, 1995). The abandoned farmland within the HID

was invaded by Schinus terebinthifolius Raddi (Brazilian pepper), an exotic shrub native

to Brazil, Argentina and Paraguay (Mytinger and Williamson, 1987). Schnius

terebinthifolius formed dense thickets of shrubs over the most intensely farmed portions

of the HID, which were resistant to common management practices (Dalrymple et al.,

2003).

Restoration efforts initiated by ENP began in 1996 and involve complete removal

of all plants and much of the soil down to the consolidated oolithic limestone bedrock (Li

and Norland, 2001). Following restoration, the most recently restored areas of the HID

initiate primary succession, by colonization of bare substrate by plant and microbial

communities. Cleared transects are left undisturbed to allow the reestablishment of

native wetland plants and microbial communities. HID restoration has been done

systematically in specified areas, resulting in regions in different stages of recovery,

creating a short-term chronosequence of sites at different stages of recovery.

The disturbance caused by complete soil removal is of the severest nature,

resulting in surface denudation and little to no biological legacy of the previous

ecosystem (Walker and del Moral, 2003). Thus, each newly cleared site will immediately

enter the primary stages of ecological re-development and primary succession. The rates

of successional change and the number of states between surface recolonization and

stability are not known, and can not be predicted for one particular ecosystem. Changes

of state will be controlled through interactions of the biota with the physical environment

and thus may not occur in a manner previously observed (Odum, 1969; Walker, 1999).









However, several characteristics of developing ecosystems, as outlined by Odum (1969)

may provide insight into how the HID recovery will progress. Initially, newly restored

sites will be characterized by open nutrient cycles, low productivity, and communities

structured as a result of the random coalescing of individuals. As succession progresses,

communities will be predictably structured and stratified by ecological function, and

nutrients will be recycled and retained in biomass. Changes in recovery states will be

biologically controlled, occur in a predictable manner, and result in a progressively more

stable ecosystem. The stable ecosystem will contain maximum biomass and harbor

communities that interact symbiotically to sustain function. The relatively short time-

span for recovery between restoration sites in the HID provides an excellent opportunity

to investigate the application of classical theories of ecosystem development over time

periods for which the direction and rate of recovery is not known.

Microbial Indicators

Microorganisms mediate nutrient cycling in terrestrial ecosystems and are an

integral part of soil quality. Bacteria maintain the greatest population numbers per gram

soil than any other organism. Separated from their environment by little more than their

cell membranes, they are very sensitive to environmental conditions (Tate, 1995; Hill et

al., 2000). Gross activities of soil microorganisms, such as respiration and biomass, have

been commonly used as indicators of soil quality (termed process-level indicators)

(D'Angelo and Reddy, 1999; Wander and Bollero, 1999; White and Reddy, 1999; Wright

and reddy, 2001; Sjogersten and Wookey, 2002). For instance, observed reductions in

soil microbial biomass and respiration have been correlated with soil subjected to nutrient

enrichment, loss of organic matter, and heavy metal pollution (Jenkinson, 1988;

Frostegard et al, 1993; Arunachalam and Melkania, 1999; Kandler et al., 2000).









Extracellular enzyme activities, such as alkaline and acid phosphatases and 3-

glucosidase, have been correlated with nutrient cycling and limitation, productivity, and

xenobiotic degradation (Tate, 1995; Prenger and Reddy, 2004).

Process-level indicators do not reflect dynamics within the soil microbial

community. An understanding of the physiology and population dynamics of certain

functional groups of microbes can provide clues about the efficiency of biogeochemical

cycling within an ecosystem. Temporal changes in soil microbes and their functions

occur in response to changes in biotic and abiotic properties at a site (Walker and del

Moral, 2003). Changes in microbial community structure may precede changes in

communities of higher organisms. For this reason, studies of the dynamics of functional

components of microbial communities under various conditions have attracted

considerable attention by ecologists (Kennedy, 1999; Hill et al., 2000).

Schimel and Gulledge (1998) presented cases in which ecosystem function

appears to result from differences in microbial community structure. The ability of

environmental factors to control species and functional group structure has been

demonstrated in the northern Everglades (Castro et al., 2002). One approach to

investigating compositions of functional groups of microorganisms is to analyze the

distribution of functional genes from genomic DNA extracted from soils. The functional

genes maintained by an organism define its interaction with the environment; thus,

functional gene ecology provides information on the potential occurrence of the

processes associated with these genes. Molecular biological tools applied to study

natural assemblages of microorganisms have allowed phylogenetic or functional level









identification of indigenous microbial communities in the context of spatio-temporal

variation, land use types, and different environments (Palumbo et al., 2004).

Molecular and biogeochemical approaches have been applied to understand the

response and recovery of ecosystems subjected to disturbance. Microbial community

structure has been shown to change in response to secondary succession of grassland

soils (Kowalchuk et al., 2000), along plant diversity gradients occurring in response to

nutrient enrichment (Carney et al., 2004), in wetland soils exposed to varying

concentrations of dairy effluent (Ibekwe et al., 2003), and along a phosphorous

enrichment gradient in the Florida Everglades (Castro et al., 2002; Castro et al., 2004;

Chauhan et al., 2004; Castro et al., 2005; Chauhan and Ogram, 2006). Much work has

been done on process-level indicators of ecosystem nitrogen loss during primary

succession (Robertson and Vitousek, 1981; Robertson, 1982; Vitousek et al., 1989).

However, little is known about the microbial communities mediating these processes, or

how they are affected by the various factors imposed upon them during recovery.

The occurrence of primary succession is a relatively uncommon event; few

natural or anthropogenic disturbance events are severe enough to completely remove both

soil and plant communities, leaving bare substrate. The HID provides a unique

opportunity to investigate the dynamics of biogeochemical processes and their microbial

mediators in concert with soil formation and accretion. As the direct linkage between

nutrients retained in parent material and plant roots, the development of soil in newly

cleared sites will be essential to successful reestablishment of plant communities and

biogeochemical linkages. The establishment of microbial communities on newly cleared

surfaces will likely precede the development of plant communities. Microbial activity









will lead to the destruction of parent material and release of nutrients, as well as a source

of new nutrients, through fixation of nitrogen and carbon. As the primary mediators of

biogeochemical cycling of carbon and nitrogen, investigation into the ecology of

microorganisms responsible for key roles in nutrient cycling in developing HID soils may

provide insight into the reestablishment of biogeochemical linkages with soil

redevelopment, the recovery stage of each site, and whether the direction of recovery is

towards that of an undisturbed wetland ecosystem.

Nutrient recycling and retention within HID restoration sites should grow more

efficient with the development of soil and plant communities. Microorganisms are

relatively short-term sinks for soil nutrients, and can also play an integral role in

ecosystem nutrient loss. Trace gas loss of nutrients due to respiratory activity of soil

microbial communities may significantly alter the rate at which biogeochemical linkages

and nutrient use efficiencies are reestablished. Carbon loss in gaseous form may occur

through heterotrophic respiration or methanogenesis. Nitrogen loss may occur through

leaching of nitrates produced during nitrification, or in gaseous forms due to the activity

of both ammonia oxidizing bacteria and heterotrophic denitrifying bacteria (Figure 1-2).

An understanding of the activity and ecology of the microbial groups mediating

ecosystem nutrient loss may provide significant insights into the nature and state of

nutrient recycling and retention in developing sites.

Methanogenesis

The concentration of methane (CH4) in Earth's atmosphere is approximately 1.8

parts per million (ppm) by volume, much less than that of carbon dioxide (CO2);

however, a molecule of CH4 is approximately 20 times more potent as a green house gas

than one of CO2 (Chapin III et al., 2004). Approximately 80% of atmospheric methane is









derived from freshwater environments, the vast majority from biogenic sources such as

plants and methanogenic bacteria. Methane is produced in greatest quantities under

anaerobic conditions, such as those present in wetlands. Wetland ecosystems are among

the most important natural sources of methane to the atmosphere; they emit

approximately 22% of total methane (90 x 106 metric tons per year). Other natural

sources, such as rice paddy fields, landfills, and ruminants follow closely behind

(Cicerone and Oremland, 1988).

Methanogenic bacteria belong to the Archaeal domain, characterized by extreme

phenotypes such as methanogens, halophiles, and thermophiles (De Long, 1992).

Methanogens are a specialized group of obligate anaerobes that use a narrow range of

electron donors for the reduction of CO2 to methane, namely H2, acetate, format, and a

limited range of methyl compounds. The majority of isolated methanogens exhibit the

ability to grow on H2 and CO2, several species utilize methyl compounds and format,

and a relative few utilize acetate as an electron donor (Garcia et al., 2000). In freshwater

and terrestrial ecosystems, methanogenesis occurs through reduction of acetate, CO2 and

format (Schutz et al., 1989). In these ecosystems, the majority of methane is thought to

come from acetoclastic methanogens (Conrad, 1999; Wolfe, 1996). In sulfate-rich

marine ecosystems, where methanogens are out competed by sulfate reducing bacteria for

resources, methyl compounds are non-competitive precursors of methanogenesis

(Madigan et al., 1996).

Methane production has been characterized from a variety of natural sources,

including geologic deposits, termites and ruminants, freshwater and oceanic sediments,

and wetlands. Major anthropogenic sources are fossil fuel use, waste management









(landfills), animal husbandry, and rice paddy soils. A great amount of work has been

done to characterize methane sources and sinks in the natural environments.

Strict nutritional and cultivation requirements and slow growth make the isolation

and characterization of methanogens cumbersome. Therefore, most recent research on

their ecology has been based on cultivation independent molecular methods. The two

most common molecular markers used to study the ecology of methanogens are 16S

ribosomal RNA (rRNA) and methyl coenzyme M reductase (MCR) genes. However,

primers previously developed to specifically target methanogen 16S rRNA genes by

Marchesi et al. (2001) were later determined to be limited in range (Luton et al., 2002).

Thus, the most effective way to study methanogens using 16S rRNA genes is to sequence

exhaustively or maintain enrichment cultures.

Alternatively, the methanogen-specific mcr functional gene has been used as a

molecular marker to study the distribution of methanogens in a variety of environments.

MCR is an enzyme specific to methanogens that catalyzes the final step in methane

production, the reduction of methyl-coenzyme M to methane (Thauer, 1998):

CH3-S-CoM + HS-CoB -> CoM-S-S-CoB + CH4

HS-CoM represent coenzyme M and HS-CoB represents coenzyme B.

The genes mcrA, mcrB, and mcrG are included in the mcrBDCGA transcriptional

unit, which encodes the ca, 3, and y subunits of MCR. The functions ofmcrD and mcrC

gene products are not known. Two isozymes of MCR have been identified, and their

expression correlated with growth stages. MCRI is synthesized during less active and

stationary phase growth and MCRII during exponential growth (Reeve, 1992).

Additionally, some methanogens of the orders ['/htllhtc iteli i ie', and //hrll,,t I,/ tl /'









contain an additional isozyme of methyl coenzyme-M reductase, termed Mrt (MRT).

The MRT operon is arranged as either mrtBDA or mrtBGA (Thauer, 1998). The

expression of either MCR or MRT is dependent on growth stage or oxidative stress

(Ferry, 1999).

There is strong evidence for the evolution of the mcrA gene from a single

common ancestor (Springer et al., 1995; Garcia et al., 2000; Luton et al., 2002), making

phylogenetic approaches to studying methanogens relatively simple. Additionally, the

three broad groups of substrate users, the acetotrophs, methylotrophs, and

hydrogenotrophs, form distinct phylogenetic clusters associated with their metabolic

potential. Thus, genetic data can often be used to infer metabolic capabilities of

methanogens inhabiting an environment. However, potential biases of PCR primers

targeting mcrA have been reported, and must be taken into account upon interpretation of

mcrA sequence data in an ecological context (Luton et al., 2002; Lueders and Friedrich,

2003). Those designed by Luton et al. (2002) are the most widely spanning, meaning

they have shown the ability to amplify genes from all orders of methanogens. However,

the affinity of these primers towards hydrogenotrophs of the orders Methanobacteriales,

Methanomicrobiales, and '/ethi//I'L InL L/ d may prove problematic when they are

employed to investigate the full metabolic potential of methanogens within an

environment (Luton et al., 2002; Lueders and Friedrich, 2003; Castro et al., 2004).

Information on the ecology and function of methanogenic assemblages in the

developing soils along the HID chronosequence will provide significant insights into the

efficiency and state of nutrient cycling within the system. For instance, the occurrence of

methanogenesis in environments harboring high concentrations of more energetically









favorable terminal anaerobic electron acceptors was attributed to non-steady state

conditions, at which methanogens were able to compete for resources with other

functional groups previously shown to preclude their activity (Roy et al., 1997). Further,

methanogenesis is the final step in anaerobic carbon mineralization, and generally occurs

through two major metabolic pathways; the degree and nature of methanogenic activity

through each of these respective pathways may provide insight into the function and

efficiency of microbial guilds mediating degradation of higher carbon.

Nitrification

Nitrification is the oxidation of ammonia (NH3) to nitrite (NO2-) and subsequently

to nitrate (N03-), most of which is carried out by a restricted group of nitrifying bacteria.

The resultant effects of nitrification on ecosystem function are well documented. The

initial oxidation of ammonium (NH4+) to nitrite produces two moles of H per mole of

NH4 consumed, leading to pH shifts in soils and possible losses in quality. Loss of

ecosystem nitrogen due to nitrification occurs by three general mechanisms (Chapin III et

al., 2004). First, the production of nitrate fuels denitrification, the main loss mechanism

of fixed N. Second, cationic nitrate is much more mobile in most soils, and thus presents

a greater risk for loss due to leaching. Finally, some evidence exists for abiotic

transformation of nitrite to gas, termed chemodenitrification (Reddy and Patrick, 1984;

Kowalchuk and Stephen, 2001). Conversely, ammonia oxidizing bacterial (AOB)

activity is often harnessed for the benefit of wastewater treatment facilities (Laanbroek

and Woldendorp, 1995).

Two classes of bacteria able to produce oxidized N compounds exist in nature,

and differ by their carbon source. Heterotrophic nitrifiers gain their energy from the

decomposition of organic matter. Many heterotrophic fungi and bacteria, including









actinomyctetes, are able to produce either NO2- or NO3s from NH4 (Chapin III et al.,

2004). While their contribution to nitrate production has been observed in nature, their

role in nitrification is negligible in most ecosystems; however, significant rates have been

observed in some acidic soils (Schimel et al., 1984; Killham, 1990). Autotrophic

ammonia oxidizers (AOB) fix carbon for biomass using energy gained from ammonia

oxidation. Most AOB are obligate aerobes, but some strains have demonstrated the

ability to proliferate under low oxygen concentrations (Laanbroek and Woldendorp,

1995). Within the AOB are two groups, one that converts ammonia to nitrite and another

that converts nitrite to nitrate. These two groups occur together in most ecosystems, NO2-

does not generally accumulate in soils. Nitrite accumulation has been observed in soils

from extremely dry savannahs and heavily fertilized farmlands (Chapin III et al., 2004).

Those autotrophic organisms responsible for the conversion of ammonia to nitrite will be

the subjects of this review.

Availability of NH4 is the most important determinant of nitrification rates

(Robertson, 1989) (Figure 1-3). Concentrations must be high enough for nitrifiers to

compete with other soil microbes; this is particularly important to autotrophic nitrifiers,

which rely on NH4+ as their sole source of energy. Significant nitrification rates have

been observed in soils with relatively low NH4+ concentrations in bulk soils, perhaps due

to spatial heterogeneity. Nitrification is thought to be limited to circumneutral

conditions. Bacterial cell membranes are only permeable to ammonia, rather than anionic

ammonium, and thus the process is favored in non-acidic conditions (Laanbroek and

Woldendorp, 1995). Significant nitrification rates measured in acid soils are attributed to

the presence of near-neutral microsites where AOB can thrive. Their existence in acid









soils may be stimulated by urea, which can provide substrate to AMO at low pH (Bothe

et al, 2000).

Other factors controlling AOB activity in soils are oxygen concentrations

(moisture) and plant communities (Figure 1-3). Soil moisture directly affects 02

concentrations of the soil atmosphere, as well as microbial metabolism. While some

metabolic activity in pure cultures of Nitrosomonas europaea was evident under

anaerobic conditions, AOB activity is generally thought to cease under highly anaerobic

conditions (Stuven et al., 1992). In water-logged soils, AOB abundance is significantly

higher in the rhizosphere of plants with aerenchymous root tissue (Reddy and Patrick,

1984; Reddy et al., 1989; Uhel et al., 1989) (Figure 1-4). It is still unknown whether the

influence of vegetation on AOB activity is due to allelochemical inhibition (Rice and

Pancholy, 1972), decreasing ammonium availability due to immobilization, or factors yet

to be determined (Stienstra et al., 1994).

In most ecosystems, AOB constitute a small portion (<<1%) of the total bacterial

population. However, AOB play a unique role in global N cycling. Their abundance and

distribution in the environment is important to ecologists. The monophyletic nature of

AOB in terrestrial and freshwater environments facilitates the use of molecular biological

approaches in studying their ecology. Molecular and process level-indicators have been

paired in a variety of terrestrial and freshwater environments, such as lakes, forest-to-

meadow transects, estuaries, contaminated ground water wells, and waste treatment

bioreactors (Rotthauwe et al., 1997; Kowalchuk and Stephen, 2001; Minitie et al., 2003;

Araki et al., 2004; Carney et al., 2004; Bernhard et al., 2005).









Taxonomically, we know of three distinct groups of autotrophic AOBs, two

monophyletic lineages of obligate aerobes within the beta- and gamma- proteobacteria

and anaerobes within the Planctomycetales (not addressed in this review) (Head et al.,

1993; Teske et al., 1994; Purkhold et al., 2000). Based on 16S rRNA gene sequence

analysis, we know of two AOB lineages within the proteobacteria. AOB of the genus

Nitrosococcus are found within gamma-proteobacteria, and have been isolated

exclusively from marine environments (Alzerreca et al., 1999), and a closely related

grouping of the genera Nitrosomonas (including Nitrosococcus mobilis) and Nitrosospira

comprise a monophyletic cluster within the beta-proteobacteria, all of which have been

isolated from terrestrial or freshwater environments (Purkhold et al., 2000).

Much of the initial knowledge gained about AOB ecology and phylogeny

stemmed from isolation of pure cultures. Inherent biases associated with all culture

techniques may limit the characterization of in situ community diversity (Amann et al.,

1995; Klotz and Norton, 1995). Further, the slow growth rates of AOB make them

difficult to culture, as cultivation generally selects for faster growing organisms. As a

result, early studies of AOB ecology in soils suggested a dominance of Nitrosospira

populations over Nitrosomonas in most terrestrial environments (Belser, 1979).

Not until the development of 16S rRNA gene primers by McCaig et al. (1994)

specifically targeting AOB did significant patterns of ecological distribution become

apparent. Primers specifically targeting AOB 16S rRNA genes allowed phylogenetic

inventories to be constructed in various environments. Further, the degeneracy of these

primers permitted the amplification of their target, but also of closely related relatives,

allowing for the recovery of novel members of the AOB clades (Kowalchuk and Stephen,









2001). However, such degeneracy has led to the recovery of sequences outside of the

target clade, sometimes as great as 70 to 100% of total sequences obtained (Kowalchuk et

al., 1999).

Initial phylogenetic characterization of AOB 16S rRNA genes recovered from soils

and marine environments divided beta-protebacterial AOB into seven clusters

(Nitrosospira clusters 1 to 4; Nitrosomonas clusters 5 to 7). (Stephen et al., 1996;

Purkhold et al., 2000). Nitrosospira spp. of clusters 2, 3, and 4 are thought to dominate

soils (Kowalchuk et al., 1998; Stephen et al., 1998; Kowalchuck et al., 1999). Patterns of

ammonia oxidizer 16S rRNA clones obtained from various soils were strongly correlated

with acidity, with cluster 2-type AOB most frequently recovered from acidic soils

(Stephen et al., 1998; Kowalchuk et al., 2000). Cluster 3 Nitrosospira spp. have

recovered from young and early successional soils with high ammonium concentrations

(Kowalchuck et al., 2000) and untilled soils (Bruns et al., 1998), while cluster 4

organisms dominated older and late successional soils (Kowalchuck et al., 2000).

Nitrosospira cluster 3 and Nitrosomonas cluster 7 AOB dominated agricultural fields

subjected to intense fertilization (Webster et al., 2002; Webster et al., 2005). In general,

Nitrosomonas spp. are more frequently isolated from high nutrient environments, such as

sewage sludge and wastewater (Rotthauwe et al., 1997; Purkhold et al., 2000).

Nitrosmonas strains have been described as r strategists, with low substrate affinities and

high maximum activity compared to K strategists Nitrosospira (Andrews and Harris,

1986; Schramm et al., 1998; Schramm et al., 1999). Phylogenetic surveys of AOB in the

environment suggest strong correlations between community structure and environment;

to date no study has directly correlated abundance of AOB 16S rRNA sequence types









with nitrification rates (Kowalchuk and Stephen, 2001). Further, the physiological basis

for observed difference in AOB sequence types is unknown.

Alternatively, primers developed to target the gene encoding the alpha subunit of

the ammonia monooxygenase enzyme (AMO) have been applied for study of AOB

ecology. AMO catalyzes that first and rate limiting step, the conversion of ammonia to

hydroxylamine (Hollocher et al., 1981):

NH3 + 02 + 2e- + 2H+ NH2H + H20

Hydroxylamine is then oxidized to nitrite in an energy yielding dehydrogenase

reaction (McTavish and Hooper, 1993). The amoCAB operon is transcribed to form a 3.2

kb RNA (Hommes et al., 2001). amoA encodes the 32 kDa acetelyene binding protein of

AMO; to date, the functions of the amoB and amoC genes are unknown (Stein et al.,

2000).

The amoA gene can serve as a useful target for environmental studies, since it

reflects the 16S rRNA phylogeny of beta-subclass AOB very well (Purkhold et al., 2000;

Kowalchuk and Stephen, 2001), provides a higher degree of sequence variation and

greater phylogenetic resolution of closely related ecotypes (Rotthuwae et al., 1997). In

recent years, amoA diversity has been investigated in a wide variety of natural

environments, including soils, sediments, plant roots, groundwater, marine and fresh

waters, and estuaries (Stephen et al., 1996; Rotthuwae et al., 1997; Kowalchuk et al.,

1998; Stephen et al., 1998; Kowalchuk et al., 1999; Kowalchuk and Stephen, 2001;

Avrahami et al., 2002; Carney et al., 2004).

The activity of AOB has been studied extensively in the context of primary

succession (Rice and Pancholy, 1972; Robertson and Vitousek, 1981; Robertson, 1982;









Robertson, 1989; Vitousek et al., 1989). Nitrification has been implicated as the major

source of N loss in developing terrestrial ecosystems (Robertson and Vitousek, 1981;

Vitousek et al., 1989). The seasonally inundated nature of the HID may provide

enhanced conditions for N loss potential. Ammonium accumulation in the wet season

may provide enough substrate for significant nitrification activity during the dry season.

High nitrification in the dry season will lead to loss ofN due to leaching, and possibly

fuel significant denitrification in the wet season. Further, both physiological and

molecular responses of AOB to differences in soil parameters have been documented,

and the presence or absence of certain genotypes correlated with differences in resource

availability. An understanding of the structure and function of AOB in HID soils may

provide insight into the potential for N loss at each stage of recovery and the efficiency of

N use within the developing soils.

Denitrification

Nitrate respiration can occur through two dissimilatory pathways. The first,

reduction ofNOs3 or NO2- to NH4+, occurs widely but is not considered denitrification in

the strict sense. Denitrification is the dissimilatory reduction of nitrate or nitrite to

oxidized gaseous forms of nitrogen (either nitric or nitrous oxide), which may be further

reduced to dinitrogen gas (N2). As the major loss mechanism for fixed nitrogen from the

biosphere, denitrification plays a crucial role in the balance of the global nitrogen cycle.

Significant rates of denitrification may be of consequence in nitrogen limited and

agricultural ecosystems. However, it is also a significant source of atmospheric N20, a

greenhouse gas involved in stratospheric ozone depletion (Chapin III et al., 2004).

Several factors control denitrifying enzyme activity (DEA) in soils (Figure 1-5).

Oxygen and moisture levels, temperature, and organic carbon availability are the most









influential factors on DEA (Knowles, 1982). Moisture content indirectly controls the

availability of both oxygen and organic carbon; slowed diffusion of 02 leads to decreased

heterotrophic activity. DEA is often highest in facultative soils with renewable supplies

of organic carbon, such as periodically inundated wetlands, tidal marshes, and riparian

zones.

The ability to denitrify is widespread among bacteria of unrelated systematic

affiliation, most likely due to lateral gene transfer events (Zumft, 1997). Although it is a

facultative process, the capacity for denitrification is almost exclusively expressed in

Eubacterial strains capable of aerobic growth. Prokaryotes constitute the vast majority of

organisms capable of denitrification, although a number of fungal isolates have

demonstrated the ability, but with minimal cellular energy gained (Kobayashi et al.,

1996; Shapleigh, 2000). Many prokaryotes identified as denitrifiers have the ability to

couple both 02 and NO3- reduction to ATP synthesis; energy yields from nitrate

respiration are similar to those gained by aerobic respiration.

Complete reduction of nitrate to dinitrogen gas requires a suite of four enzymes

(Figure 1-6). The second step is the conversion of nitrite to nitric oxide by nitrite

reductase (NIR). As the first gas-generating step, it is the defining step of denitrification,

and will be the focus of this review (for more details on the molecular basis of

denitrification see Zumft, 1997). The NIR reaction is complemented by the activity of

two distinct metalloenzymes, one with a copper center (Cu-NIR) and the other with a

heme-based cytochrome (Fe-NIR). Both forms of the enzyme occur in the periplasm and

appear to be functionally redundant (Coyne et al., 1989; Glockner et al., 1993). Cu-NIR

is more widely distributed within prokaryotes, including both archaebacteria and









Eubacteria, while Fe-NIR is more widely spread across environments, but found only in

Eubacteria (thus far) (Bothe et al., 2000). Fe-NIR occurs in proteobacteria at a much

greater frequency relative to other Eubacterial groups; type strains from four of the five

major proteobacteria sub-classes (alpha, beta, delta, epsilon) have been characterized.

Currently, no Fe-NIR containing organisms have been identified in the gamma sub-class.

To date, there is no apparent agreement in the phylogenetic distribution of the two

enzymes types with 16S rRNA gene phylogenies of the harboring organisms (Shapleigh,

2000).

Genes encoding both NIR enzymes are not fully understood. Fe-NIR genes from

Pseudomonas aeruginosa were adjacent, while those in Pseudomonas stutzeri were

rearranged into three different transcriptional units (Palmedo et al., 1995). Comparison

of four Cu-NIR containing bacteria revealed a single conserved gene. However,

quantities of DNA required to encode Fe-NIR and Cu-NIR is significantly different

(Shapleigh, 2000).

The phylogenetically diverse nature of denitrifying bacteria makes the design of

16S rRNA group-specific probes impossible. Thus, molecular ecological studies of the

distribution of denitrifying bacteria always target functional genes and their products.

Highly conserved regions of genes involved in denitrification have allowed for the

development of group-specific primers. Fe-NIR and Cu-NIR are encoded by nirS and

nirK genes, respectively. DNA sequences encoding the two enzymes share little

sequence homology; thus, probes specific to each gene have been developed (Braker et

al., 2000). Because of their role in the gas-producing step of denitrification, nirK and









nirS are most often employed in ecological studies of denitrifier distribution (Michotey et

al., 2000; Yan et al., 2003; Santoro et al., 2006).

The exact environmental factors affecting the distribution of nirS and nirK

containing organisms in the environment are not fully understood. The ubiquity of the

gene, along with its high lateral transfer rate, makes phylogenetic characterization of

denitrifying bacterial communities difficult. However, the responses of one or both

genotypes to environmental conditions have been reported. A previous characterization

of nirS and nirK diversity in forested upland and wetland ecosystems was only able to

recover nirS in upland soils, while both were present in wetland soils (Prieme et al.,

2001); the actual environmental reasons for the observed patterns were not apparent.

More often, both genes are detected within an environment, but the response of the

organisms harboring them is different. Liu et al. (2003) reported a greater response of

nirK than nirS containing denitrifiers in marine sediments; nirK diversity correlated

strongly with nitrate availability, while nirS diversity was correlated with oxygen

concentrations. Instances of differing responses to the same environmental factor have

also been observed. Santoro et al. (2006) reported a greater response of nirK to nitrate

concentrations in ground waters. nirS diversity was still indicative of response, but less

pronounced, a greater degree of overlap between genotypes along the nitrate gradient was

observed. Thus, investigation into the diversity and population structure of nirS and nirK

in association with shifts in biogeochemical processes in HID soils may provide insight

into the state of N cycling, the potential for gaseous N loss, and factors controlling the

response of organisms harboring functionally redundant enzymes.











Hypotheses and Objectives


The central hypothesis of this study is that an understanding of microbial

assemblages associated with carbon and nitrogen cycling and the measurement of certain

forms of carbon and nitrogen can be used to assign value to restoration efforts in the HID,

and predict the rates of ecologically important processes regulating availability. Specific

hypotheses to be tested include: (i) soil redevelopment will lead to the establishment of

methanogen, denitrifying, and ammonia oxidizing microbial communities which will

grow more predictably consistent in structure with restoration age; and (ii) seasonal

variations in methanogenesis, denitrification, and ammonia oxidation rates will reflect

observed differences in community structure and restoration age.

The main objectives of this investigation are to: (i) identify spatial and temporal

changes in community structure of microorganisms associated with methanogenesis,

denitrification, and ammonia oxidation; and (ii) monitor the relevant biogeochemical

processes associated with methanogenesis, denitrification, and ammonia oxidation in

restored and undisturbed wetlands. Investigation of the dynamics of these microbial

communities may provide insights into the reestablishment of biogeochemical linkages

with soil redevelopment, the recovery stage of each site, and whether the direction of

recovery is towards that of an undisturbed wetland ecosystem.





















The Hole-in-the Donut,
Everglades National Park, FL, USA


|UND|


Figure 1-1. The Hole-in-the-Donut restoration area.












Dissolved
Organic
Nitrogen





NT1LI +


Assimilatory
Nitrate Reduction
to Ammonium
(ANRA)


Process




Ammonification
(Mineralization)









>- Nitrification


Optimal
environments




Warm, moist










High oxygen

ANRA:
High carbon
Low nitrogen


Denitrification


Low oxygen
High carbon


Figure 1-2. Pathways of autotrophic nitrification and of denitrification and the nitrogen
trace gases emitted by these pathways. Adapted from Chapin et al. (2004).


0n-^
N2
0










LONGTERMSHOR TER


State Interactive Indirect Direct
factors controls controls controls

Plant 0 0 Plant NH/4
BIOTA functional uptake NH +
TIME ypes Litter quality availability
TIME R r Carbon quality

PARENT Soil Respiration NITRIF
MATERIAL sourcess n microbial/root

CLIMATE U0 [HO, availability "


Soil texture


Figure 1-3. The major factors controlling nitrification in soils. Thickness of the arrows
represents the strength of effects. Black arrows represent positive influences
and white arrows represent negative influences. Adapted from Chapin III et al.
(2004).


LONG-TERM


SHORT-TERM













(Z7


Chemical -,


WATER H4- HNO ,- HN03
SNitrification
Fixation N
NH4 HNO, HNO,

*.- I- - i DilTu>ion
|.DiTffuiion NH T
-----Ora-- nic N -- r ----- -i
S".O_ D.Denilrilirii ioin L.'icliin, I
N --- --

\ Oxidized Zone \

I Reduced Zone


Figure 1-4. Schematic representation of nitrogen cycling in flooded soils and sediments.
Inset depicts diffusion processes occurring at the root-soil interface. Adapted
from Reddy and Patrick (1984).











LONG-TERM
CONTROLS


SHORT-TERM
CONTROLS


State Interactive Indirect Direct
factors controls controls controls

Plant # W Plant NO,
BIOTA functional uptake NO -
T types 1 Litter quality availability
TIME C Carbon quality

PARENT S Reices Respiration Labile BS
MATERIAL R er microbial/root a carbon

CLIMATE Temperature 02
H,20 I availability

Soil texture


Figure 1-5. The major factors controlling denitrification in soils. Thickness of the
arrows represents the strength of effects. Black arrows represent positive
influences and white arrows represent negative influences. Adapted from
Chapin III et al. (2004).










N20 N2


NO3 N20 NADH NADU
+H+
Figure 1-6. The basic arrangement of the nitrogen oxide reductases required for complete
denitrification by a single organism. Adapted from Shapleigh (2000).














CHAPTER 2
STRUCTURE AND FUNCTION OF METHANOGENIC ASSEMBLAGES ALONG A
SHORT-TERM RESTORATION CHRONOSEQUENCE

Introduction

The Hole-in-the-Donut (HID) is a 4000 ha region within Everglades National Park

(ENP), Florida, USA. Once consisting of oligotrophic sawgrass (Cladiumjamaicense

Crantz) prairies and short hydroperiod pinelands, the HID was subjected to agricultural

land use practices for 60 years (Loope and Dunevitz, 1981; Dalryample et al., 2003).

Pre-agriculture, HID soils were characterized as shallow, poorly drained and low nutrient

marls. Intensive rock plowing efforts destroyed underlying limestone bedrock, creating

coarsely textured, well drained soil more suitable for vegetable production (Li and

Norland, 2001). When farming activity ended, the HID was left as an abandoned, high

nutrient, high oxygen environment. Farmland within the HID was invaded by stands of

Schinus terebinthifolius Raddi (Brazilian pepper), a shrub native to South America,

intentionally introduced to Florida as an ornamental in the 1898 (Austin, 1978), and is

though to have entered ENP in the 1940's (Bancroft, 1973; Loope and Dunevitz, 1981).

HID restoration plans initiated by ENP in 1996 include complete removal of all

plants and much of the soil down to bedrock. Following removal, cleared plots are left

undisturbed to allow natural reestablishment of microbial communities and

recolonization by native wetlands plants. HID restoration is conducted in specified areas

of varying size, such that regions at different stages of recovery are present at one time.









Soil development is a critical first step in plant colonization on bare substrate.

Soil formation results from complex interactions between physical, chemical and

biological factors. Subsequently, soil will become the direct link between biotic and

abiotic factors that drive primary succession (Walker and del Moral, 2003).

Recolonization by microorganisms will precede the establishment of plant communities.

Biogeochemical processes mediated by soil microbial communities will contribute both

to soil formation and release of nutrients for plants. Significant geochemical differences

between undisturbed and cleared sites have been reported (Li and Norland, 2001).

Microbe-mediated processes are most sensitive to disturbance, therefore study of

microbial communities may be an effective measure to assess the response of soil to

perturbation (Nannipieri et al., 2003). Complete soil removal likely destroyed linkages

between functional groups of microorganisms. Microorganisms play a central role in

carbon and nitrogen cycling, such that development of microbial communities is critical

to soil quality and the reestablishment of biogeochemical linkages (Nannipieri et al.,

2003). Functional shifts within bacterial groups could potentially alter processes at the

ecosystem scale (Schimel and Gulledge, 1998).

Anaerobic microorganisms, such as those found in anoxic soils characteristic of

many mature wetlands, mineralize organic carbon through a variety of terminal electron

accepting processes. In a developing system, such as the HID, establishment of anaerobic

microbial communities may occur in concert with soil profile development.

Methanogenesis is a major process responsible for terminal anaerobic carbon

mineralization in freshwater wetlands (Schimel and Gulledge, 1998). Methyl coenzyme

M reductase, partially encoded for by mcrA, is the enzyme responsible for the terminal









step in methane production, the operon and mcrA are functionally linked and

phylogenetically conserved in methanogens (Leuders et al., 2001; Luton et al., 2002),

making mcrA a candidate gene for monitoring potential shifts in methanogenic

populations in developing HID soils. The objectives of investigating methane and

methanogen dynamics in the HID were (i) to assess whether differences in structure and

function of methanogenic assemblages may be used as an indicator of soil profile

development along the restoration gradient; and (ii) to gain insight into the state of both

carbon cycling and anaerobic electron accepting processes in developing soils along the

restoration chronosequence.

Materials and Methods

Site Characteristics, Sample Collection, and Biogeochemical Characterization

Samples were collected in April and November 2004. Plots 20 x 20 m2 were

established in sites restored in 1989, 1997, 2000, and 2003 (R89, R97, R00, and R03,

respectively), and in an undisturbed site (UND). The range of elevation for the five plots

was 0.5 to 0.6 m. Within each sampling area, 2 x 2 m2 grids were used to establish 81

sampling nodes, which were monitored for soil depth, ground coverage, and elevation.

Nine nodes were chosen based on relative range of soil depth within each site, 3 from

each depth range (shallow, intermediate, deep). Sampling nodes were color coded and

marked for future sampling efforts. Soil samples were taken with a plastic coring device;

however, due to non-uniform soil cover in recently restored sites, grab samples were

collected where necessary. Individual samples from each depth range were combined to

make three representative soil samples, which were used for molecular and geochemical

analyses. Soil samples were kept on ice and transported to the laboratory within 72 h of

collection, where they were manually mixed and large roots removed. Subsamples for









DNA analysis were stored at -70 OC until analysis. Biogeochemical analyses were

conducted at the Wetland Biogeochemistry Laboratory (D'Angelo and Reddy, 1999;

White and Reddy, 1999; Wright and Reddy, 2001). Values for select parameters are

presented in Table 2-1.

Methane Production Potentials

Two g soil, sampled in November 2004, from UND, R89, R97, ROO, and R03 sites

were mixed with 25 ml of anoxic modified basal carbonate yeast extract trypticase

medium (Touzel and Albagnac, 1983) under an N2 stream in 50 ml anaerobic culture

bottles that were later closed with butyl rubber stoppers and aluminum crimp seals.

Tubes were pre-incubated for ten days prior to addition of electron donors. Acetate and

format (20 mM each) were added from N2 sparged sterile stock solutions. The bottles

were fitted with three-way Luer stopcocks (Cole-Parmer, Vernon Hills, IL) for gas

sampling, and incubated in the dark at 250C without shaking. Methane in the headspace

was measured by gas chromatography with a Shimadzu 8A GC equipped with a

Carboxen 1000 column (Supelco, Bellefonte, PA) and a flame ionization detector

operating at 110 C. The carrier gas was N2 and the oven temperature was 160 C. All

determinations were carried out in triplicate bottles with soil samples from each site (3

bottles per site). Headspace pressure was measured using a digital pressure indicator

(DPI 705, Druck, New Fairfield, CT).

Nucleic Acid Extraction and PCR Amplification

Nucleic acids were extracted from 0.25 g of soil with Power Soil DNA Isolation kit

(MoBio, Carlsbad, CA, USA) according to the manufacturer's instructions. PCR

amplification was conducted using the primer set designed by Luton et al. (2002), and

consists of primers mcrA-f (5'-GGTGGTGTMGGATTCACACARTAYGCWACAGC-









3') and mcrA-r (5'-TTCATTGCRTAGTTWGGRTAGTT-3') which amplify a fragment

of between 465 and 490 bp of mcrA. Each 20 [l PCR reaction mixture contained 7 [tl of

distilled water, 1 ul of each primer (10 pmol [l-1), 10 ul of HotStarTaq Master Mix

(Qiagen, Valencia, CA) and one [l of diluted template DNA.

PCR amplification was carried out in a GeneAmp PCR system 9700 (Perkin-

Elmer Applied Biosystems, Norwalk, CT). The initial enzyme activation and DNA

denaturation was performed for 15 min at 950C, followed by 5 cycles of 30 s at 950C, 30

s at 550C, and 30 s extension at 720C, and the temperature ramp rate between the

annealing and extension segment was set to 0.1 C s-1 because of the degeneracy of the

primers (Luton et al., 2002). After this, the ramp rate was set to 10C s- and 30 cycles

were performed with the following conditions: 30 s at 950C, 30 s at 550C, and 30 s

extension at 720C, and a final extension of 720C for 7 min. PCR conditions for T-RFLP

analysis were identical, except the annealing temperature was decreased to 530C. PCR

products were analyzed by electrophoresis through 2% agarose gels to confirm

amplification of expected size product.

Cloning and RFLP Analysis

Fresh PCR amplicons were ligated into pCRII-TOPO cloning vector and

transformed into chemically competent Escherichia coli TOP1OF cells according to the

manufacturer's instructions (Invitrogen, Carlsbad, CA). Positive colonies were screened

by PCR amplification with the primer set and PCR conditions described above. PCR

production from positive clones was digested with Rsal restriction enzyme. Each 10 [tl

reaction consisted of 5U of enzyme, lx restriction enzyme buffer, 0.6 utg of bovine serum









albumin, 5 [tl of PCR amplicon, and water to volume. Digests were analyzed by

electrophoresis through 4% agarose gels.

Sequencing and Phylogenetic Analysis

Representative clones from the most frequently occurring restriction patterns in

each library were sequenced at the DNA Sequencing Core Laboratory at the University

of Florida using internal vector primers. DNA sequences of mcrA genes generated from

each treatment were translated into putative amino acid sequences and aligned manually

in Se-Al version 2.0al 1 (Rambaut, 1996). Alignments were then aligned with Clustal

version 1.81 (Thompson et al., 1997). Phylogenetic trees were built with a neighbor-

joining analysis using a Jukes and Cantor correction method as implemented in the

TREECON software package (van de Peer and de Wachter, 1994). Bootstrap analysis

was performed with 100 resamplings of the amino acid sequences.

T-RFLP Analysis

Approximately 100 to 150 ng of PCR product was digested with Rsal. The

enzymatic digestion reaction consisted of 5 units of restriction enzyme (Promega,

Madison, WI), lx restriction enzyme buffer, 0.6 |tg bovine serum albumin, and

deionized water to a final volume of 10 [tl. Enzymatic digestions were incubated at 37 C

overnight. One and one half [tl of digested product were used for terminal restriction

fragment (T-RF) detection by the DNA Sequencing Core Laboratory at the University of

Florida. Briefly, digested products were mixed with 2.5 [tl deionized formamide, 0.5 dtl

ROX-labeled GeneScan 500-bp internal sized standard (Applied Biosystems, Perkin

Elmer Corporation, Norwalk, CT) and 0.5 [tl of loading buffer (50 mM EDTA, 50 mg/ml

blue dextran). Samples were denatured by heating at 95 C for 3 min and subsequently









transferred to ice until loading of the gel. One [l was electrophoresed through a 36 cm,

5% polyacrylamide gel containing 7 M urea at 3 kV on an ABI 377 Genetic Analyzer

(Applied Biosystems). T-RFLP profiles were analyzed with GeneScan version 2.1

(Applied Biosystems). T-RF size (bp) was calculated using internal standards. Peak sizes

in base pairs and peak areas were exported to Excel 97 SR-1 (Microsoft Corporation,

Redmond, WA) for data analysis.

Diversity Indices

Clone libraries were analyzed by analytic rarefaction employing RarefactWin

(version 1.3; S. Holland, Stratigraphy Lab, University of Georgia, Athens

[http://www.uga.edu/-strata/software/]). Cumulative expected phylotypes were

calculated for each clone library according to Castro et al. (2004). Rarefaction curves

were fit to a hyperbolic model with the formula y = ax/(b + x) using Datafit software

version 8.0.32 (Oakdale engineering, Oakdale, PA), where y represents number of

phylotypes, and x is the number of individuals. Coverage values were determined by

comparison of obtained versus cumulative expected phylotypes. Shannon-Weaver values

were calculated using default parameters of the program by DOTUR (Schloss and

Handlesmann, 2005).

Results and Discussion

To our knowledge, this is the first study to monitor the composition and activity

of microbial assemblages during the restoration of a freshwater wetland ecosystem. The

short-term chronosequence created by complete soil removal allowed us to characterize

those communities initially colonizing bare substrate, and monitor their dynamics in

concert with soil accretion and changes in geochemical processes. Monitoring the









development and subsequent changes in methanogenic assemblages may provide insight

into possible shifts in terminal anaerobic mineralization processes with soil development.

Methane Production in HID Soils

Observed rates of methane production did not correlate with measured geochemical

parameters (Table 2-1), or show clear trends associated with time since restoration.

Intrinsic methane production rates were highest in R97 and R03 soils (Table 2-2). UND

soil produced the least methane, with rates approximately 30 times lower than intrinsic

rates reported from oligotrophic soils of the Everglades Water Conservation Area 2A

(Castro et al., 2004). Additions of acetate to microcosms lead to slight increases in

methane production after 10 d. R03 showed the greatest rate of methane production, but

the average rate was only 1.2 fold higher than in unamended soils. Methane production

from acetate was two fold higher in R03 soils compared to unamended microcosms.

UND soils were unaffected by acetate addition, and rates suggest a general decline in

acetoclastic methanogenesis with restoration age. Overall, less than 2% of acetate was

converted to methane over the 10 d incubation period. Formate was added to soil

microcosms to assess the activity and population sizes of hydrogenotrophic methanogens.

Formate is commonly used as an analogue to H2-CO2 in anaerobic mineralization studies

(Dolfing and Bloemen, 1985). Hydrogen has been shown to be an important electron

donor to methanogenesis in other regions of the Everglades (Castro et al, 2004; Chauhan

et al., 2004). Methane production potentials in formate-amended soils were 4 to 17 times

higher than in unamended soils, and 4 to 20 times higher than in acetate amended soils.

Approximately 18 to 50% of added format was converted to methane over the 10 d

incubation period, production rates and total substrate conversion percentage values were

strongly correlated. This may indicate the dominance of hydrogenotrophic









methanogenesis in HID soils. Further, this may be an underestimate of actual

hydrogenotrophic production potentials, as only 60% of hydrogenotrophic methanogens

are able to utilize format for methane production (Garcia et al., 2000).

Hydrogenotrophic methanogens were 1000 to 100 times more abundant than acetoclastic

methanogens in other regions of the Everglades (Chauhan et al., 2004).

Methane production potentials in UND soils were lowest of all study sites,

regardless of treatment, and data suggest a general decline in methanogenic activity in

older sites (Table 2-2). A previous comparison of Everglades soils indicated greatest

methane production from marl after addition of acetate and other carbon sources

(Bachoon and Jones, 1992). However, our data suggest that methanogenesis may not be

an important part of terminal anaerobic carbon cycling in the HID. Currently, factors

possibly limiting methane production in HID soils are unknown. However, short

hydroperiods and shallow soils may provide conditions conducive to the occurrence of

more energetically favorable terminal anaerobic electron accepting processes, such as

denitrification.

Phylogenetic Characterization of Methanogenic Assemblages in HID Soils

PCR amplification of mcrA from soils sampled in undisturbed and restored sites, in

the dry season (April 2004), yielded the expected ca. 465 to 490 bp mcrA fragments.

Clone libraries constructed from dry season soils indicated the presence of considerable

diversity of methanogens in HID soils. The number of obtained and expected phylotypes

was highest in UND soils and lowest in ROO soils (Table 2-3) Coverage of expected

mcrA diversity within each clone library was ascertained by comparison of observed

versus expected phylotypes for each library. Values ranged from 45 to 76%, highest in

R97 and ROO libraries, and lowest in UND (Table 2-3). Both measures of sampling









coverage indicate that our clone libraries do not fully represent mcrA diversity in HID

soils.

mcrA sequences obtained from dry season soils formed seven clades

encompassing the orders Methanobacteriales, Methanococcales, Methanomicrobiales,

. //l/thA\t/. ilile' and two clades sharing greatest similarity with uncultured organisms

(Figure 2-1). MCR-1 sequences share ca. 90% DNA sequence similarity to

1 l'thkinUtA, iit, these sequences were obtained from UND, R89 and R00 soils, but not

in significant quantities. Related sequences were reported from nutrient impacted regions

of the Florida Everglades (Castro et al, 2004). MCR-2 sequences were most abundant in

UND soils, but comprised a small percentage of R03 and R00 sequences; they shared

highest similarity with uncultivated methanogens in rice paddy (Lueders et al., 2001) and

Everglades soils (Castro et al., 2004), sharing 87 to 94% similarity with putative

hydrogenotrophs in Rice Cluster I (Lueders et al., 2001). Clones in MCR-3, present in

R89, ROO, and R03 libraries, were most similar to uncultured \ K'thii,,e\ia spp. obtained

from permanently flooded riparian soils (Kemnitz et al., 2004). 1i/[ti/,,,eia spp. are

specialists able to generate methane only from catabolism of acetate (Boone et al., 1993).

Cluster MCR-4 branched deeply within cultured '/lth ti/l,/uiL / ,hi, i //'bl, and contained

sequences obtained from UND, R89, and R03 soils. MCR-4-like sequences have also

been obtained from eutrophic Everglades soils (Castro et al., 2004) and a peat bog

(Juottonen et al., 2005); our clones share ca. 85% similarity with Fen Cluster

methanogens, a potentially novel group of uncertain function (Galand et al., 2002;

Galand et al., 2005). Cluster MCR-5 sequences branch deeply within the

Methanococcales. They were obtained from all study sites; an increase in MCR-5









abundance was observed in more established sites (Figure 2-2). These sequences are

closest to those from uncultivated organisms obtained from rice roots (Chin et al., 2004).

Previous characterization of methanogenic assemblages in the Florida Everglades did not

recover sequences clustering with Methanococcales (Castro et al., 2004; Castro et al.,

2005). Cluster MCR-6 sequences, present in UND and R97, clustered outside of cultured

Methanococcales, and shared greatest similarity with clones from other regions of the

Everglades (Castro et al., 2004). Clones associated with MCR-7 were found in all sites,

and formed a distinct clade within 'lethtib,1,t I i ie'\ Sequence distributions suggest a

general decrease in MCR-7 relative abundance as restoration progresses (Figure 2-2).

3 LI/hitlhiihtiL i i//le' mcrA comprised a significant portion of clone libraries constructed

from other regions of the Everglades (Castro et al., 2004)

T-RFLP Analysis of Methanogenic Assemblage Structure

Composition of methanogenic assemblages in HID soils was monitored with T-

RFLP. The possible phylogenetic affiliations of the T-RFs are presented in Table 2-4. In

silico analyses of mcrA clones indicates that some T-RFs may be associated with distinct

phylogenetic groups of methanogens. Averages of T-RF relative frequencies for dry and

wet season samples for UND, R89, R97, ROO, and R03 sites are presented in Figures 2-3

and 2-4, respectively. PCR amplification ofmcrA in UND samples was generally weak

and we did not obtain significant quantities of amplicons in wet soils for T-RFLP

analysis. Thus, only dry season T-RF profiles are presented for the UND site. Dominant

T-RFs for each site were obtained consistently from replicate soil samples.

Seasonal Structure of Methanogenic Assemblages

Thirteen T-RFs were obtained from both wet and dry season samples. In silicon

digestion indicate T-RFs 85, 186, and 305 are exclusively associated with cluster MCR-7,









associated with 'lrhi,1 ,i i le'. Seasonally, there were no significant changes in

relative abundance of MCR-7 T-RFs within sites. A ['ibhiui 1 tii le\ T-RFs comprised

between 35 to 55% of total fluorescence within each site for both wet and dry seasons.

T-RFs 65 and 302 were associated exclusively with cluster MCR-5. Sequences

comprising MCR-5 branch deeply within Methanococcales, and sequences from all study

sites are found within this cluster. Increases in T-RF 302 in R00 and R97 between

seasons were evident, but comprised only 5 to 20% of total fluorescence in each site. T-

RF 65 comprised between 5 to 10% of total fluorescence in all sites and between seasons.

T-RFs 48, 80, 96, and 180 corresponded to multiple phylogenetic clusters. For the most

part, these T-RFs remained relatively stable between seasons, and were detected in all

soils. Because they share affiliation with two metabolically distinct clusters of

methanogens, it is impossible to discern which organisms are contributing greatest to

shifts in abundance. T-RFs 198, 201, 315, and 317 had no phylogenetic affiliation and

were obtained from all samples, but comprised only a small percentage of total

fluorescence. These T-RFs may represent methanogens not obtained in our clone

libraries.

Our T-RFLP analysis did not identify shifts in composition of methanogenic

assemblages between seasons. Significant shifts in soil moisture between seasons may

lead to the development of methanogenic activity hot spots in dry soils. Methanogenic

activity has been detected in extremely dry soils (Peters and Conrad, 1995). Rewetting

events have been correlated to observed shifts in dominant organisms (Nannipieri et al.,

2003). However, organisms inhabiting seasonally water stressed soils are thought to be

more resistant to moisture fluctuations (Fierer et al., 2002). Further, slow growing









organisms, such as methanogens, may be less affected by dry-wet cycles (VanGestel et

al., 1993). Archaeal communities remained relatively stable during rice field rewetting

events (Lueders et al., 2000). Within site differences in methanogenic assemblages

observed were less than between site differences across seasons in other regions of the

Florida Everglades (Castro et al., 2005).

Shifts in Methanogenic Assemblages with Restoration Age

T-RFs associated with MCR-5 and MCR-7 dominated samples from all study sites,

as well as clone libraries (Figures 2-2 and 2-3). The relative abundance of MCR-5 T-RFs

(65 and 302) differ slightly within sites, with respect to each other, but significant

variation between sites was not evident. Their combined abundance suggests that

.A'////l,,ull ,n ,/t' populations remain stable in soils from all sites. Relative abundance of

MCR-7 T-RFs decreased with successional stage. Interestingly, T-RF 85 was most

abundant in UND, ROO, and R03 soils, showing an approximately linear decrease with

restoration age. Decreased abundance of T-RF 85 in R89 and R97 soils corresponds with

increased abundance of T-RF 305. Shifts in MCR-7 T-RFs are evident in both seasons,

but more pronounced in dry season profiles. Assuming these T-RFs are exclusively

associated with .1 ['//hi///t /it i //le, mcrA, as in silico digestion indicates, this suggests a

shift within wlkibhli, tI i ide1' populations with restoration age. lulihi ic iide

were also obtained in different proportions along a nutrient impacted gradient of the

Everglades (Castro et al., 2004). T-RFLP analysis of mcrA obtained from riparian soils

also reported shifts in abundance of .1A '//ui//hi't/L W i ie', T-RFs differing by

approximately 100 bp were obtained in significantly different quantities in soils subjected

to differing periods of inundation (Kemnitz et al., 2004). Thus, the apparent association









of T-RF 85 may represent a shift within the A '//l///h/,h(/ tel it tle' associated with

restoration age.

At best, T-RFLP may be employed as a semi-quantitative measure of community

structure. Interpretation of shifts in T-RF abundance may not indicate significant changes

in assemblage composition. Further, different efficiencies of labeled and unlabelled

primers required use of different annealing temperatures during PCR for cloning and T-

RFLP analysis, further allowing for discrepancies between T-RFLP profiles and clone

libraries. Such discrepancies have been described previously for mcrA PCR-cloning and

T-RFLP analyses (Leuders et al., 2003; Castro et al., 2005)

Putative hydrogenotrophic mcrA genes were most frequently observed in clone

libraries and T-RFLP profiles. This is consistent with the highest methane production

resulting from format addition in all sites. However, the exact proportion of

1 l'/thie//,h IL /' i //ei' and A^ AlthnMv c (i//e'\s in HID restorations sites is not reflected in T-

RFLP results, as the degenerate primers employed in this study do not provide

quantitative recovery of all phylogenetic lineages (Lueders et al., 2003). Further, it has

been suggested that the primer set employed for this study is biased toward

hydrogenotrophic orders of methanogens, and particularly under represent -.1'thin,,,'eu

spp. and I' lth,/il,,I"Ai itia spp. (Luton et al., 2002; Castro et al., 2004)

Conclusions

Little work has been done to characterize establishment and succession of

microbial communities in the context of ecosystem restoration. Clone libraries suggest

initial establishment of all major metabolic guilds of methanogens in the most recently

restored site. Methanogens have been shown to colonize bare surfaces as members of

biofilms (Kussmaul et al., 1998). All T-RFs obtained were present in all sites, and in









approximately similar ratios between seasons. However, there is some evidence of shifts

within -//li ////,,//l'tIr i/1ei' (T-RFs 85 and 305) populations associated with restoration

age, suggesting that individual groups of methanogens may respond differently to

geochemical and environment differences between restoration sites. Interestingly, T-

RFLP profiles of methanogenic communities in early sites of a long-term successional

bog chronosequence were nearly indistinguishable; however, differences were evident in

late succession sites (Merila et al., 2006). It must be noted that DNA-based assessments

of bacterial community composition provides information on the potential metabolic

activity, rather than the actual activity. Thus, further studies of gene expression may, in

fact, indicate differences in activity within each site.

In summary, our results suggest that a diverse assemblage of methanogenic

bacteria colonize recently restored sites. Seasonal T-RFLP profiles indicated

methanogenic assemblage structures to remain consistent in composition despite seasonal

changes in biogeochemical parameters. This is consistent with previous studies reporting

temporal stability of prokaryotic communities (Lueders et al., 2001; Fierer et al., 2003;

Castro et al., 2005). Shifts within certain methanogenic groups in association with

restoration age were evident. Both molecular and functional assessments suggest

hydrogenotrophic methanogens are responsible for most of the methane production

observed along the chronosequence.












Table 2-1. Geochemical parameters of dry (April 2004) and wet (November 2004) season soils.
Soil Depth Moisture TC TN TP LOI MBC
Study Site (cm)a (%)b (g kg-1) (g kg-1) (g kg-1) (%) (mg kg-1)
April 2004
UND 5.9 (1.5-10) 43.7 (10.4) 159.4 (10) 6.6 (0.8) 0.2 (0.0) 17.03 3881.2 (829)
R89 4.5 (3-6.5) 28.3 (7.4) 164.5 (16) 7.7 (1.6) 0.7 (0.2) 23.96 5003.8 (1323)
R97 5.2 (2-8) 39.1(18.2) 169.4 (8) 8.2 (0.8) 1.0 (0.2) 24.84 4806.3 (1340)
ROO 2.7 (1-5.5) 36.8 (12.2) 161.1 (17) 6.7 (0.9) 0.6 (0.1) 20.88 4185.3 (1472)
R03 1.6 (0.5-2.5) 13.5(9.1) 139.9(9.7) 4.0(0.9) 1.0(0.1) 15.90 2161.3 (579)
November 2004
UND 10.1 (2-15) 49.6 (4.5) 192.5 (8.8) 7.2 (0.9) 0.1 (0.2) 16.71 1925.1(516)
R89 5.4 (1-17) 56.7(8.9) 340.9 (17.2) 9.2(1.5) 0.8(0.2) 14.38 3109.9 (1009)
R97 4.6(3-11) 53.4(5.8) 323.7 (15.5) 9.0(1.4) 1.0(0.2) 14.19 3237.5 (1303)
ROO 3.3 (1-4) 54.8(0.8) 234.3 (11.3) 7.4(0.8) 0.6(0.1) 23.90 2343.7 (494)
R03 1.2 (0-3) 52.2 (7.0) 194.1 (7.7) 5.2 (0.6) 0.9 (0.2) 18.86 1752.5 (680.8)


aValues in parentheses represent the range of soil
and Methods.


depths measured over 81 samples nodes, as described in the Materials


bValues in parentheses are standard deviations of the mean values for determinations based on three soil samples; TC, total carbon;
TN, total nitrogen; TP, total phosphorous, LOI, loss on ignition; MBC, microbial biomass carbon.









Table 2-2. Potential methanogenesis rates and accumulated CH4 in wet season soils.
No Addition Formate Acetate
Site Ratea Totalb Rate Total Rate Total
UND 0.1 (0.0) 41(16) 0.4 (0.1) 198 (37) 0.1 (0.1) 52 (21)
1989 1.1(0.3) 513 (112) 26.6 (1.6) 8843 (3951) 1.5(0.1) 700 (34)
1997 11.4(4.7) 4193(283) 36.0(11.1) 17274(3066) 7.3 (1.0) 3782(141)
2000 3.4 (1.3) 1619 (425) 22.6 (13.9) 10844 (3843) 6.6 (12.0) 3178 (701)
2003 7.4 (2.2) 1052 (744) 50.4 (14.7) 24183 (4077) 8.8 (3.3) 2998 (926)
aPotential methanogenic rates (in nanomoles per gram soil per hour); Standard errors
of the means are shown in parentheses for determinations with three replicate soil
samples.

bAverage total methane accumulated in headspace of three replicate
samples were site, expressed as nanomoles of methane accumulated.


Table 2-3. Expected and observed phylotypes and diversity indices for dry season mcrA
clone libraries for HID soils.
Expected Observed Coverage Shannon's
Site Phylotypesa Phylotypesb c(%) H'
UND 35.35 (1.60) 16 (31) 45 2.09
R89 21.41 (0.13) 14 (39) 67 2.01
R97 13.62 (0.53) 10(39) 76 1.68
R00 13.29 (0.43) 10(39) 76 2.10
R03 19.20 (1.32) 12(37) 63 1.76
aValue of constant a from equation y = ax/(b + x) (standard error)


bValue in parentheses is total number of clones screened

cExpressed as percent of expected phylotypes obtained within each
library.












Table 2-4. Phylogenetic affiliation ofmcrA T-RFs for HID soil samples.
Observed T-RF (bp) Theoretical T-RF (bp) Cluster Order
48 48 MCR-1 .I'/h// It/, I i /i, th
MCR-7 I Ai/,i1h ,h1 /LW it /e'
65 65 MCR-5 I 'l/h I ,t I I L t/eA
MCR-1 .I A'I/h/ I,,/ // ilit[l'e
80 80
MCR-5 I A'//h t I t ILI[ILL (c //I
85 84 MCR-7 A'ilh/1,h, / e icit te
96 95 MCR-2 N let/h/IIi(/ L ilit t//t
MCR-4 A'/Wit lttit I ,hiahi'
MCR-6 Uncultured
Not Obtained 175 MCR-6 Uncultured
Not Obtained 177 MCR-3 .I A'i/h/,/, //. il/ite'
MCR-4 A'i/bt 1,ltitti 11 hi, tbI'
179 MCR-3 I A'l/hn/ t In il, e,'.
MCR-4 I A'l iti ttiti 1 hi//'\
186 188 MCR-7 A'i/1th,1, /h e ici itle
198 Unknown phylogenetic affiliation
201 Unknown phylogenetic affiliation
302 302 MCR-5 .1 A'iinh tle.
305 305 MCR-7 A'i/i th,1\ Wc iit /te
315 Unknown phylogenetic affiliation
317 Unknown phylogenetic affiliation
Not Obtained 438 MCR-5 A'i//ia11 11L a te
458-487 No Cut Not Obtained























Melanwrvnskandleri fLT7340)
-Merowpyrus kaidl risl rain DSMN(6324 fAF414042)
Merha bwlobr usraylir (22243)
S Merhanotobus bornbarwensis (U22257)
S aanolIubus tndarius 22244)
Mehan m oreoreis (U22242)
MI ,he anococcoids bunoiio (Ui222it 3
Medlrnocco rles merln l nerv s (L22235)
I Merhanoplhnpis maihi W(122237)
M hfhaIphIus mtius (U22259)
i l------ -- -- 1 hinert IB.DU.
99 Mernnofia)
._r- H-6 i MCR-1
I I I -- it.-- O 14 I
91 Meanoarcina throaphila (i221
MItlbataaaori a v, calnt, (ul2225i


4 awneta nilii sr i strain DSM 2367 ( (AFAF4 1401437)
I Me nthaav sarcorim n t eii a ain C 16 (U2228)

100 MMCHD-S MCR-2
9 IO M cr-HIDL0-1



I iM IID-DU- 24 MCR-4

M- a,"-er-HIDWB-.

o"Merha rp un agggas slrin D 3027 (AF4 14414)


I Metharah p irium n a i strain JF- 1 (AF31380
r- Melrlm nocvulleum Iwmo asri strain DSM 2624 (AF313 4
Sa Mehus am folm s rriminta Main DSM 4140 (AFN14041)
Mehawcr les bourgemh sis strain DSM 1045 (AF414036)
2 Methmroaldon as jumamellwii &strain DSM 266 D(L77117)
94 Whaaat nlors imus strain DSM 1 666 (AF14039)
MnhMel'an aucM- Mmawnire strain 6DSM 3095 1(AF414047)
Malmiuinirm ignevr rain DSMA 5666M(AF14(9)
I Me l Meramnpsker meaa stlmaas sstin DSM3091AF,414047)
M*- h- A uiimtr ul iilil (M 16893)
Af phca vdims uain DSM 3a091 (AF414047)
h d o "ciftj astch strain DSM 2661(L6746.9)
7 Meia-o-Melnlslallatlermils nrans sX 7


Mcr-HIIDU-30
McarHID7-24
M Ir-HID89-19
lMer Ilm-19 MCR-5

McIlD89-14
Mcr- IMlDO-37
l "-HI-DU 18l

100 11M 8 MCR-6
r~esoaio'iefb tye ba.fR n f io rest iWo, ,,rn strain DSM 1093 (,w414046)
99 I dMeihoreIlwnnodrer trhernau lofrp irus (X07794)
l. K- Metlho rcterium lmermoanit M (U10036
SMelanobacterimn browii snun DSM 863 (AR I13806)
Sd (etmobrenibaterarboriphids~srflepin USMtWticain DSM 1312 (AF41405)
Mcr-HIID3-27
MerHIDO0-S
9S Mcr- D89-28
|Me--FD9F7-22
0 I stultniats.le ,k-HDS -3tl

MLr-HIDOA3-13 MCR-7
-Mr-HIDO-26

MAr-H]D03-S

Mcr--HIDB? -
-13




Figure 2-1. Neighbor-joining mcrA tree for representative clones from April 2004 soils.

Clones are named according to the site of origin; UND, undisturbed site, R,

restoration site (followed by year of restoration). Scale bar represents 10%

sequence divergence. Numbers at nodes represent percentage of bootstrap

resamplings based on 100 replicates. Values greater than 85 are shown, while

black dots (*) on nodes represent values between 50 and 85.








100%

80% -

g 60%-

E 40%-
2%
20% -


0% -


UND


R89


U MCR-7 U MCR-6 G MCR-5 8 MCR-4 0 MCR-3 0 MCR-2 0 MCR-1


Figure 2-2. Distribution of mcrA sequences obtained from dry season soils within
designated phylogenetic clusters.


i














100%


90% 1 317 bp
El 315 bp
80% -0 305 bp

0 1302 bp
70%
mu. E 201 bp

60% 198 bp

[ 186 bp
50%
1 180 bp

40% 096 bp

I 85 bp
30%
0 80 bp

20% / 65 bp

1 48 bp
10% -


0%
UND R89 R97 ROO R03

Figure 2-3. Community dynamics for the mcrA gene in dry season HID soils determined by T-RFLP analysis. Y-axis values
represent percent of total fluorescence.
















S317 bp

0315 bp

E 305 bp

* 302 bp
o 201 bp

* 198 bp
C 186 bp

8 180 bp

0 96 bp

E 85 bp

[ 80 bp

S65 bp

S48 bp


90%


80%


70%


60%


50%


40%


30%


20%


10%


0%


Figure 2-4


R89 R97 ROO R03

Community dynamics for the mcrA gene in wet season HID soils determined by T-RFLP analysis. Y-axis values
represent percent of total fluorescence.


100%


I I


k














CHAPTER 3
GENETIC AND FUNCTIONAL VARIATION IN DENITRIFIER POPULATIONS
ALONG A SHORT-TERM RESTORATION CHRONOSEQUENCE

Introduction

Nitrogen is the nutrient most likely to limit primary productivity in temperate

terrestrial ecosystems. Despite the extraordinary supply of N in the atmosphere, great

demand for it by producers and costly energetic of N2 fixation present the opportunity

for supply-side imbalance (Vitousek and Howarth, 1991). Retention of N within

terrestrial ecosystems is dependent on the interaction of physical, chemical, and biotic

variables. In soils, N can be retained in organic matter, biomass of plants or soil

microbiota, or through surface associations with soil particles. The most common N loss

mechanisms occur through leaching, denitrification, or disturbances (Payne, 1981).

Denitrification is the microbially mediated dissimilatory reduction of nitrogen

oxides to gaseous end products (NO, N20, N2) for energy production (Zumft, 1997). It is

the dominant loss mechanism of biologically preferred nitrogen from terrestrial

ecosystems, as well as the most prevalent anaerobic respiratory process based on nitrogen

(Megonigal et al., 2004). The capability of respiring by denitrification is maintained by a

taxonomically diverse group of facultative anaerobic Eubacteria; however, a few Archaea

and fungi also exhibit denitrification (Tiedje, 1988; Shoun and Tanimoto, 1991; Usuda et

al., 1995). The multi-step process is carried out by a series of membrane bound enzymes.

With few exceptions, most bacterial denitrifiers possess the capacity to carry out the

entire process (Tiedje, 1988). The defining (first gas forming step) and often rate-









limiting step of denitrification is conversion of nitrite to nitric oxide, and is catalyzed by

two distinct but functionally equivalent metalloenzymes (Glockner et al., 1993; Zumft,

1997), i.e., the copper-containing NirK and the cytochrome cd1 NirS enzymes. The genes

encoding the two enzymes, nirK and nirS, have been used extensively to detect and

characterize denitrifiers in activated sludge (You, 2005), marine sediments (Braker et al.,

2000; Braker et al., 2001; Liu et al., 2003), forested uplands (Prieme et al., 2002), and

freshwater riparian (Schipper et al., 1993; Rich and Myrold, 2004) and wetland

ecosystems (Prieme et al., 2002).

High carbon inputs, water column-sediment surface exchange of reduced and

oxidized forms of fixed nitrogen, and low oxygen partial pressures may be favorable

conditions for the development of robust denitrifying communities in wetland soils

(Reddy and Patrick, 1984). In seasonally inundated wetland ecosystems, denitrifying

activity may be accelerated, as influx of fresh waters may introduce fresh labile carbon

sources and sub-oxic conditions (Bowden, 1987). Activity and dynamics of

denitrification in freshwater wetlands have been characterized extensively (Bowden,

1987; Reddy et al., 1989; Hanson et al., 1994; Seitzinger, 1994; White and Reddy, 1999).

However, little information exists on the community composition of denitrifiers in these

systems (Prieme et al., 2002).

Nitrogen loss due to denitrification in the Florida Everglades has been

characterized in permanently flooded, nutrient impacted and oligotrophic regions

(D'Angelo and Reddy, 2001; White and Reddy 1999; White and Reddy, 2001), and in

both dominant soil types of the ecosystem (marl and peat) (Gordon et al, 1986).









Denitrification has been suggested to be the most important nitrate loss mechanism in

these regions (White and Reddy, 1999).

Nitrogen is the most commonly limiting nutrient to primary productivity during

primary succession (Vitousek and Howarth, 1989). Thus, its retention within the

ecosystem may be crucial to restoration success. Shallow soil depths and periodic

inundation of HID restoration sites suggest denitrification as a potentially important

mechanism for N loss. Elucidation of the differences in composition and function of

denitrifying communities at varying stages of recovery will underpin further

interpretation of responses at the physiological and ecological scales. Specific questions

to be addressed include the following: (i) what is the phylogenetic composition of

denitrifiers in HID soils; (ii) how do communities differ in the context of measured

activity and restoration stage; and (iii) are there significant patterns in community

composition associated with restoration stage?

Materials and Methods

Site Characteristics, Sampling, and Biogeochemical Characterization

Samples were collected in November 2005. Plots 20 x 20 m2 were established in

sites restored in 1989, 1997, 2000, 2001, and 2003 (R89, R97, R00, R01, and R03), and

in an undisturbed site (UND). The range of elevation for the five plots was 0.5 to 0.6 m.

Within each sampling area, 2 x 2 m2 grids were used to establish 81 sampling nodes,

which were monitored for soil depth, ground coverage, and elevation. Nine nodes were

chosen based on relative range of soil depth within each site, 3 from each depth range

(shallow, intermediate, deep). Sampling nodes were color coded and marked for future

sampling efforts. Soil samples were taken with a plastic coring device; however, due to

non-uniform soil cover in recently restored sites, grab samples were collected at some









nodes. Individual samples from each depth range were combined to make three

representative soil samples that were used for molecular and geochemical analyses. Soil

samples were kept on ice and transported to the laboratory within 72 h of collection,

where they were manually mixed and large roots removed. Subsamples for DNA

analysis were stored at -70 OC. Biogeochemical analyses were conducted at the Wetland

Biogeochemistry Laboratory (D'Angelo and Reddy, 1999; White and Reddy, 1999).

Values for select parameters are presented in Table 3-1.

Denitrifying Enzyme Activity and Gas Analysis

Laboratory denitrifying enzyme activity (DEA) incubations were performed on

soils collected in November 2005 according to the method outlined by White and Reddy

(1999) with slight modifications. Approximately 15 g of field-moist soil from each site

were placed in quadruplet 220 ml serum bottles, which were sealed with butyl rubber

septa and aluminum crimp seals. To establish anaerobic conditions in each bottle, the

headspace was evacuated to approximately -85 kPa and replaced with 02-free N2 gas.

Five milliliters ofN2-sparged deionized water were added to each serum bottle to create

soil slurries. Approximately 15% of headspace gas was replaced with acetylene (C2H2)

(Balderston et al., 1976; Yoshinari and Knowles, 1976). Bottles were shaken for 1 h on a

longitudinal shaker in the dark to allow C2H2 to distribute evenly through the soil slurries.

Following pre-incubation, 8 ml of DEA potential solution (56 mg N03-N L1, 288 mg

C6H1206 L1, 100 mg L-1 chloramphenicol) were added to each bottle, creating a slight

over pressure in the head space (Smith and Tiedje, 1979); the original protocol by White

and Reddy (1999) employed Ig L-1 of chloramphenicol; however, at nearly the same time

a report by Murry and Knowles (1999) indicated levels of chloramphenicol greater than









100 to 200 mg L-1 may inhibit DEA activity by up to 60%. Samples were incubated in

the dark at room temperature (24C) and continually shaken, and headspace gas was

sampled every 1 h for 4 h. A Bunsen absorption coefficient of 0.544 was used to adjust

for nitrous oxide dissolved in the aqueous phase (Tiedje, 1982). Potential denitrification

rates were determined by the calculated slope of the linear curve produced for cumulative

N20 evolution with time. Two milliliters of headspace gas from each sampling time was

stored in N2-flushed 2 ml serum bottles sealed with butyl rubber stoppers and aluminum

crimp seals for 24 to 48 h until determination of N20 concentrations by gas

chromatography.

Gas samples were analyzed for N20 on a Shimadzu gas chromatograph (GC-14A,

Shimadzu Scientific, Kyoto, Japan) fitted with a 3.7 x 108 (10 mCi) 63Ni electron capture

detector (300 C). A 1.8 m by 2 mm i.d. stainless steel column packed with Poropak Q

(0.177 to 0.149 mm; 80 to 100 mesh) was used (Supelco, Bellefonte, PA). The carrier

gas was 5% methane in argon (v/v) flowing at a rate of 30 ml min-1 at 30C. Working

standards consisted of N20 in He (Scott Specialty Gas, Plumsteadville, PA).

Nucleic Acid Extraction, PCR Amplification, Cloning and Sequencing

Nucleic acids were extracted from 0.25 g of soil with Power Soil DNA Isolation

kit (MoBio, Carlsbad, CA, USA) according to the manufacturer's instructions. Purified

DNA extracts were used as template in PCR; amplification was conducted using primer

sets designed by Yan et al. (2004), consisting of primers 583F (5'-TCA TGG TGC TGC

CGC CKG ACG-3') and 909R (5'-GAA CTT GCC GGT KGC CCA GAC-3') which

amplify a 326 bp region of nirK, and 832 F (5'-TCA CAC CCC GAG CCG CGC GT-3')

and 1606R (5'-AGK CGT TGA ACT TKC CGG TCG G-3') which amplify a 774 bp









region of nirS. Each 20 tl PCR reaction mixture contained 7 [tl of distilled water, 1 tl of

each primer (10 pmol tl-1), 10 tl of HotStarTaq Master Mix (Qiagen, Valencia, CA) and

one tl of template DNA. PCR amplification was carried out in a GeneAmp PCR system

9700 (Perkin-Elmer Applied Biosystems, Norwalk, CT). PCR conditions for both primer

sets were identical and consisted of the following: an initial enzyme activation and DNA

denaturation for 15 min at 950C, followed by 30 s at 940C, 30 s at 600C, and 60 s

extension at 720C for 30 cycles, and a final extension of 720C for 7 min. PCR products

were analyzed by electrophoresis on 1.5% TAE agarose gels. To account for the spatial

patchiness of soils and attempt to more fully characterize diversity, bulk nucleic acid

extracts from all soil samples from within a site were combined.

PCR amplicons were ligated into pCRII-TOPO cloning vector and transformed

into chemically competent Escherichia coli TOP OF' cells according to the

manufacturer's instructions (Invitrogen, Carlsbad, CA). White colonies were screened for

correct inserts by PCR amplification using the protocol and conditions described above.

Insert-bearing clones were transferred to 96-well plates containing 200 [tl of Luria Bertini

broth plus 8% (v/v) glycerol and kanamycin (50 [tg ml-1). Plates were incubated for

approximately 24 h at 370C, covered with gas permeable membranes (Breath-easy,

Diversified Biotech, USA), and transported to the University of Florida Genome

Sequencing Service Laboratory for sequencing with internal vector-specific primers.

Phylogenetic and Diversity Analysis

Nucleotide sequences were manually aligned and translated into putative amino

acids in Se-Al v. 2.0 a 11 (Rambaut, 1996) and aligned with Clustal v.1.81 (Thompson et

al., 1997). Phylogenetic trees were produced for approximately 100 and 250 amino acid









segments of nirK and nirS, respectively, using Tejima and Nei corrected distance

matrices in the TREECON software package (van de Peer and de Wachter, 1994).

Bootstrap analysis (500 resamplings) was used to estimate reproducibility of phylogenies.

Similarities of sequences obtained in this study were compared to those obtained from

other studies using BLAST queries (http://www.ncbi.nlm.nih.gov) of the nucleotide

database.

Community analyses were performed by generating operational taxonomic units

(OTUs) in DOTUR, using the furthest neighbor algorithm and a 3% difference in nucleic

acid sequences. Non-parametric estimates of richness and diversity were calculated using

DOTUR (Schloss and Handelsman, 2005), including Chaol, Shannon index, and

Simpson index.

Statistical Analysis of Phylogenetic Data

To assess whether gross differences observed between denitrifier populations

between sites represented statistically different populations, well-aligned subsets of each

gene fragment were chosen for analysis using J-Libshuff (Schloss et al., 2004) with

1,000,000 randomizations and a distance interval (D) of 0.01 (Santoro et al., 2006) using

Jukes-Cantor corrected pairwise distance matrices generated in PAUP (Swofford, 1998).

The program employs Monte Carlo methods to calculate the integral form of the Cramer-

von Mise statistic by constructing random sub-set populations from the entire data set and

comparing the coverage of the generated populations to coverage in the experimentally

obtained data set. Populations were considered significantly different with P value below

0.0026 after a Bonferroni correction for multiple pairwise comparison (ca=0.05, n = 20).









Analysis of molecular variance (AMOVA), pairwise comparisons of population

specific pairwise fixation indices (FST) (Martin, 2002), and average pairwise sequence

similarities were conducted with the program Arlequin (version 3.001, Genetics and

Biometry Laboratory, University of Geneva [http://lgb.unige.ch/arlequin]). AMOVA

(Excoffier et al., 1992) employs a hierarchically partitioned matrix of Euclidean distances

to assess by permutation the significance of variance components at each level of

partitioning. All analyses were performed under default parameters, with the following

exceptions: analyses were conducted at 90,000 iterations and distance matrices defined

haplotype definitions. FST tests were employed as measures of genetic differentiation

between all pairs of samples. The test determines whether samples contain close

phylogenetic relatives or more deeply divergent sequences. Mantel tests (Mantel, 1967;

Mantel and Valand, 1970) were implemented in Arelquin and used to test correlations

between population specific FST values and geochemical parameters. The method is

based on a nonparametric general regression model which employs squared Euclidean

distance matrices between variables to test significance of and degree of predictability

one variable has on another (Dutilleul et al., 2000).

Parsimony tests (P-test) were implemented in TreeClimber (Schloss and

Handelsman, 2006). Clustal X (version 1.83) was used to generate sequence alignments,

constructed under default parameters. Trees were constructed by Bayesian analysis as

implemented in Mr. Bayes version 3.1 (Huelsenbeck and Ronquist, 2001; Ronquist and

Huelsenbeck, 2003) under default model parameters, with trees sampled every 1000

generations. All Bayesian analyses were run for 1,000,000 generations, of which 10%

were discarded to account for initial divergence in log likelihood scores between chains.









The resultant 990 trees were used for analysis in TreeClimber

(http://www.plantpath.wisc.edu/fac/joh/treeclimber.html) and compared to 1,000,000

randomly generated trees.

Statistical Analysis of Biogeochemical Data

Environmental parameters were tested for significance across treatment groups

(study sites) using one-way ANOVA in JMP version 5.1 (SAS Institute) on both log

transformed and raw data. Pairwise comparisons of means were conducted in the same

software using Tukey's HSD, which accounts for unequal variances among samples.

Results and Discussion

Soil Biogeochemical Parameters Along the Restoration Gradient

Measured values of nitrate, ammonium, and organic matter content (loss on

ignition) in HID soils ranged from 1.8 to 6.8 mg kg-1, 15.2 to 49.5 mg kg-1, and 14.19 to

23.9 %, respectively; values for these parameters did not differ significantly across sites

(ANOVA, p < 0.05). Potential Denitrifying Enzyme Activity (DEA) ranged from 0.12 to

1.15 mg N20-N kg- hr -1; DEA rates for UND, R89, and ROO sites were significantly

different from R97, R01, and R03 sites (ANOVA, p < 0.05). There was no evident trend

in DEA associated with restoration age or other measured environmental parameters,

although there may be disparity between actual and potential activities of denitrifiers in

soils. Tiedje (1988) suggested that lab-based determinations overestimate field activity

40 to 100 times. Values reported in this study are within the range of values reported in

surface soils from oligotrophic regions of the Everglades using similar methods (White

and Reddy, 1999), as well as those reported from riparian (Schipper et al., 1993) and

agricultural soils (Pell et al., 1996, Espinoza, 1997). Although there was no clear trend









associated with DEA and recovery stage in HID soils, statistical analysis (randomized

complete block design, ANOVA) of site effects on biogeochemical data indicated

significant (c = 0.05, P < 0.0001) within-site effects on DEA. This may indicate that,

while there does not seem to be an obvious or homogenously controlling factor on DEA

along the restoration gradient, activity may be more strongly controlled by different

factors within each restoration site.

Interestingly, relatively high DEA activities were observed in the two most

recently restored sites, despite having less than 3 cm of soil and moisture contents similar

to all other sites (Table 3-1). DEA activity may be spatially patchy, and is thought to

occur in response to hot-spots within soil micro-aggregates (Parkin, 1987). Further,

senescing plant material and leaf litter may support anaerobic processes (Kusel and

Drake, 1996); Parkin (1987) observed that carbon inputs from a single leaf were

sufficient to support 85% of observed denitrification.

A previous investigation of DEA in Everglades soils reported 3 to 30 fold higher

activity in marl than peat soils from the Everglades (Gordon et al., 1986). Our results

suggest less activity in marl soils compared with values from peat soils reported by White

and Reddy (1999) the disparity may be due to lower soil depth at our sites, or that marl

sampling sites differed in hydrologic features. Interestingly, potential denitrification

from the two marl soils showed identical patterns (Gordon et al., 1986; this study);

dentrifying populations in all but ROO soils showed no lag in response following nitrate

addition. Nitrate accumulation was approximately linear over the course of the 4h

incubation. This indicates denitrifying enzyme systems were fully induced in most sites.









nirS phylogeny

nirS-type denitrification genes were obtained from all HID study sites, and

grouped into six (I to VI) distinct phylogenetic clusters (Figure 3-1), the relative

abundances of clones from each library are presented in Table 3-2. Seventy-five percent

amino acid similarity in DOTUR grouped sequences into phylogenetically distinct

clusters. Genes from all clusters shared 78 to 98% similarity of amino acids with

previously obtained environmental clones in GenBank. Most notably, of the 117 clones

obtained from all study sites, 58% shared greatest similarity with environmental clones

obtained from a Michigan wetland; nucleotide sequence similarities ranged from 80 to

98%. Clones of this sequence type may represent a group of uncultivated denitrifying

bacteria that are physiologically adapted to wetland ecosystems (Prieme et al, 2002).

Thirty percent of all clones were 80 to 87% similar to uncultivated denitrifying bacteria

inhabiting high nitrate brackish ground waters in California (Santoro et al., 2006). The

remaining 12% of obtained sequences varied in similarity from 76 to 86 % to

environmental nirS obtained from wetland soils incubated under elevated CO2 (Lee et

al., 2005), activated sludge (Ohsaka et al., 2004), or Baltic Sea cyanobacterial aggregates

(Tuomainen et al., 2003).

Clusters I, II, and III shared relatively high average pairwise sequence similarities,

ranging from 92 to 97%; these sequence types may represent more abundant NirS-type

denitrifiers common to all HID soils. Clusters IV, V, and VI comprised the lower portion

of the tree, and consisted of loosely associated divergent lineages, with little apparent

redundancy in the library (Figure 3-1, Table 3-2). Of the six designated phylogenetic

clusters, only Cluster VI sequences were similar to nirS of previously characterized









denitrifiers, and shared 71 to 75% of predicted amino acids with organisms of the alpha-

proteobacterial genera Thauera and Azoarcus, or the beta-proteobacterial

Magnetospirillum spp. Cluster VI was comprised of sequences from all HID sites.

However, sequence similarity is too low to confidently conclude that Cluster VI nirS

genotypes obtained in this study belong to organisms within these genera. Sequences

from all other clusters showed low similarity to cultivated denitrifiers based on both

nucleotide and putative amino acid BLAST searches. With the exception of Cluster III

sequences, which showed ca. 95% similarity to uncultivated organisms from wetland

soils, nirS genotypes obtained in this study shared less than 85% similarity with

previously reported sequences, and may be indicative of a unique assemblage of

denitrifying bacteria in HID soils.

nirK phylogeny

Phylogenetic diversity was apparent from analysis of the 158 obtained nirK

sequences (Figure 3-2). Clones obtained from all study sites grouped into 12 distinct

phylogenetic clusters; within cluster sequence similarities ranged from 85 to 98% (Figure

3-3). Additionally, nirK clone libraries, more so than nirS, contained a number of deeply

branching divergent singletons from all sites: REF (7), R89 (3), R97 (6), ROO (5), R01

(4), and R03 (5). The relative percentages of sequence types within each cluster are

presented in Figure 3-3. Of the 158 sequences included in the phylogenetic analysis, 66

(42%) shared 90 to 91% similarity with environmental clones previously obtained from a

wetland soil; these sequences comprised clusters A through E, and were obtained from all

restoration sites (Figure 3-3). The remaining clusters (F through L) each formed distinct,

deeply branching clades. Cluster F sequences were 84 to 92% similar to nirK genes









obtained from a potentially novel group of uncultured denitrifiers in fertilized upland

soils (Wolsing and Prieme, 2004). Cluster G clones were 82% similar to environmental

sequences obtained from peat (Throback et al., 2004), and shared 79 to 80% similarity

with nirK ofAlcaligenes xylosoxidans. Cluster H sequences shared greatest similarity

with uncultivated denitrifiers obtained from forest soils (Prieme, 2002). Sequences

comprising Cluster I were 93% similar to those in Bradyrhizobiumjaponicum. Cluster J

clones were 92% similar to nirK ofEnsifer sp. 2FB8. Clusters K and L clones were 73 to

84% similar to environmental clones from municipal wastewater (Throback et al., 2004).

Those comprising Cluster L were also 81 to 87% identical to sequences reported for

Sinorhizobium meliloti.

Overall, the majority of both nirS and nirK sequences obtained in this study

shared less than 90% sequence similarity with previously reported environmental

sequences. While the exact cut-off of sequence similarity to previously reported

environmental clones or cultivated isolates for either gene is not known, previous reports

have employed a cut off of 75% nucleotide similarity as the threshold for claiming

recovery of novel nir genes. This is based on the observation of an approximately 75%

shared nucleotide identity between the alpha-, beta-, and gamma-proteobacteria (Yan et

al., 2003). In consideration of this, and the fact that the majority of sequences obtained in

this study shared no significant similarity to cultivated organisms upon BLAST search, it

may be likely that our sequences represent several lineages of novel denitrifying

organisms. However, the existence of denitfying bacteria from previously characterized

lineages within the alpha- and beta-Proteobacteria are evident in both clone libraries

(Cluster IV in Figure 3-1; Clusters I and J in Fig 3-2).









While the occurrence of novel lineages of denitrifiers based on studies of both

nirS and nirK have been reported (Yan et al., 2001; Prieme et al., 2002; Liu et al., 2003),

the uniqueness of such results may not be uncommon when certain factors are taken into

consideration: i) functional gene diversity is generally greater than 16S rRNA diversity

(Ward, 2002); and (ii) the ability to denitrify spans all three kingdoms of life (Ward,

2002). The pertinent point regarding novel groups to this study is not their existence, but

that soils from each of the HID study sites appear to harbor uniquely divergent

populations of denitrifiers.

Richness and Diversity of nirS and nirK Populations

Rarefaction analysis was used to compare richness of nir clone libraries in the

context of restoration stage. OTUs were defined by DOTUR using a 97% DNA sequence

similarity cutoff. Rarefaction indicated nirK and nirS richness to be approximately

similar between all restoration sites; however, there was a clear difference in OTU

richness between populations in UND soils. With the exception of the UND nirS curve,

which was nearing a plateau, curves for all libraries were steeply sloped at the respective

cut off points for sequences obtained from each site, suggesting that our clone libraries do

not represent the entire diversity of the denitrifying populations. Coverage values for

nirS and nirK clone libraries for each site are presented in Table 3-3. Coverage for nirS

libraries ranged from 45 to 90%, R01 and R03 libraries had the highest and lowest

coverage values, respectively. nirK coverage values ranged from 45 to 100%, and were

highest for the UND library and lowest for the R01 library.

Both Simpson and Shannon diversity indices indicate nirS libraries to be the most

diverse in restoration study sites; UND soils maintain greater nirK diversity (Table 3-3).









Greater diversity of nirS relative to nirK has been previously observed in wetland soils

(Prieme et al., 2002), groundwaters (Yan et al., 2001; Santoro et al., 2006), and sediments

from a marine oxygen minimum zone (Liu et al., 2003). Differences in diversity are more

clearly pronounced in Simpson values versus Shannon values (Table 3-3); this difference

may be due to the stronger influence of library eveness on Shannon values (Magurran,

2004). Further, the log-transformed Simpson values presented in Table 3-3 are sample

size independent estimates (Magurran, 2004). There is a clear inverse relationship

between nirS and nirK population diversities within sites. This relationship has also been

observed in both marine (Braker et al., 2000) and terrestrial environments (Prieme, 2002;

Yan et al, 2003), and may suggest that different environmental parameters alter

abundances of organisms containing nirS or nirK, and that community dynamics of each

group may alter dynamics of the other (Yan et al., 2003). However, detailed discussion

of HID site parameters controlling diversity of nir genotypes using the presented

diversity and richness estimates must consider that fact that the estimates presented here

are based on clone libraries that do not represent the entire diversity of nir populations.

Attempts to correlate measures of diversity or richness with geochemical parameters or

restoration age yielded no significance. Previous studies have also failed to make

significant correlations between diversity or richness measures and environmental

variables (Yan et al., 2003; Santoro et al., 2006). The inability to correlate statistical

measures of community composition with geochemical parameters may be due in part to

the relatively poor understanding we have of factors controlling diversity of nir

genotypes in the environment, or that community structure is controlled by less

quantifiable factors (Santoro et al., 2006).









Population-Based Library Compositions

Iterative statistical analyses were employed to assess significant differences in

population composition between restoration sites. UND sequences for either nir genes

were excluded, as the focus of this study was to assess nir population dynamics in the

context of disturbance recovery. Not only was the UND site never disturbed, it is not at

the same successional stage as the restoration study sites.

To assess gross differences in nir populations represented by our clone libraries, J-

Libshuff (Singleton et al., 2001; Schloss et al., 2004) was employed. By comparing

random permutations of sequences from two libraries, determination of whether two

clone libraries are likely to represent samples drawn from statistically distinct populations

can be made. The asymmetrical nature of the test allows for the determination of clone

libraries as distinctly different, drawn from the same population, or if one library is the

subset of another. If libraries X and Y do not share common ancestry, comparisons of

both will result in significant P values (bold in Table 3-4). However, if library X is

statistically different from library Y, but Y versus X is not, Y is a subset of X. In cases

where homologous (within one library) and heterologous (between two libraries)

coverages differ significantly, one can be reasonably certain that the samples are drawn

from different populations (Schloss et al., 2004). Advantages of the method are that it

operates on an individual sequence level, rather than the arbitrary assignment of OTUs,

and does not consider clone frequency (Singleton et al., 2001; Schloss et al., 2004). This

method of community differentiation was developed for 16S rRNA gene libraries, but has

been used to differentiate functional gene libraries (Horn et al., 2006; Yannarell et al.,









2006;), including nirS and nirK (Santoro et al., 2006), obtained from sites at different

successional stages (Dunfield and King, 2004; Nanba et al., 2004).

Further, to test whether observed phylogenetic structures are the result of random

variation, parsimony tests were employed. The test assesses the probability that

phylogenetic patterns observed in user-constructed trees varies from randomly

constructed trees after multiple iterations (Schloss and Handelsman, 2006). If the

observed patterns are due to random variation, than user-generated trees would have

similar parsimony scores as randomly generated tress. The null hypothesis of the analysis

is that the compared communities share an ancestral community structure and observed

patterns are due to accumulation of random variation; significance indicates observed

phylogenetic differences between two communities to be the result of selective pressures,

such as perturbation, that force differentiation within treatment populations (i.e gain or

loss of groups) (Schloss and Handelsman, 2006).

The approach of the two tests differs and must be noted. J-Libshuff is based on a

continuous statistic, measures community membership (the presence or absence of

individuals within a population), and is relatively less sensitive to library size (Schloss et

al., 2004). The parsimony (P) test is based on a discrete statistic, measures community

structure (the distribution and abundances of individuals within a population), and is

more sensitive to library size (Schloss and Handelsman, 2006). However, library sample

sizes approximately equal to those employed by this study have been proven effectively

large enough for both tests (Singleton et al., 2001; Dunfield and King, 2004; Nanba et al.,

2004; Schloss et al., 2004; Schloss and Handelsman, 2006).









Results of the nirS analysis indicate that most sequences obtained from each site

are site-specific (Table 3-4). Further, the shared similarity between sites most closely

related in time since restoration do not differ significantly; this may indicate a succession

of shared lineages between the most closely related or all restoration sites. As seen in the

phylogenetic analysis, several clusters were comprised of sequences obtained from all

sites. However, the deeply divergent taxa appear to be unique to each site, and are likely

responsible for much of the difference between restoration sites. Analysis of community

covariance with phylogeny, as implemented in TreeClimber, confirms that community

structures from each site are significantly different (P < 0.02); removal of any site from

the analysis did not lead to loss of significance, and pairwise comparisons of all sites

were significantly different (P < 0.02). Prior studies that removed distinct groups for P

test analysis discerned groups responsible for differentiation (Martin, 2002; Schloss and

Handelsman, 2006). However, the consistency of P values upon library removal in this

study suggests that each site harbors distinct and unique divergent lineages.

Succession of shared sequence types was not as clear when nirK clone libraries

were analyzed with J-Libshuff (Table 3-4). R03 and R01 clone libraries were drawn from

the same population, which is a subset of the R00 library. The R00 library differed

significantly from R97 and R89 libraries, however, R89 and R97 libraries had shared

lineages. A P test including all populations indicated significant differences (P = 0.032),

and pairwise comparisons for all sites were also significant (P < 0.02). Thus, while the

"more recovered" sites (R89 and R97) share an underlying community, both harbor

unique lineages of denitrifiers, possibly selected for by disturbance recovery stage. A

comparison of sites grouped into two data sets consisting of "more" and "less" recovered









clone libraries yield the lowest significance value of any nirK library comparisons (P =

0.012). Removal of R97 or R00 libraries from analysis lead to loss of significance

between groups (P = 0.08 for R97 and P=0.06 for R00), however when the two libraries

were compared they were significantly different. Thus, consistent with J-Libshuff

analysis, this indicates a divide in population composition between early (< 6 yr) and late

(> 6 yr) restoration sites, and suggests that R97 and R00 sites harbor more divergent

lineages or that populations differ significantly from R89, R01, or R03.

Statistical analyses of nirS suggest shared lineages along the restoration

chronosequence. Though it was not addressed in this study, it is likely that Cluster A

sequences, which were obtained from all sites represent a group of denitrifiers native to

HID soils, regardless of disturbance stage. Interestingly, analysis of nirK libraries

indicates a bimodal response to recovery stage, with sites closer in disturbance recovery

sharing similar, but distinct, communities of denitrifiers. Alternatively, ROO and R97

sites, for which these analyses suggest harbor different populations, may be

representative of intermediate states of disturbance. According to the "Intermediate

Disturbance Hypothesis", ecosystems at intermediate stages of recovery from disturbance

harbor the greatest species diversity (Connell, 1978).

Consistent with nirK variation, geochemical data show a similar, but

insignificant, trend. Soils in later succession sites share similar related organic matter,

nitrate, and ammonium contents (Table 3-1) than sites at early stages of recovery. While

it may seem contrived, the variability in the data should not hinder inferences based on

geochemical trends. Geochemical analyses were conducted on triplicate composite soil

samples; each representative sample was comprised of three soil samples taken at relative









depth intervals (shallow, medium, deep) within each site. Compositing of samples was

done in this manner to account for variations in both bedrock surface topography and

spatial differences in regions of soil accretion. At successional stages as early as those in

the HID, spatial patchiness is inevitable, and likely to overwhelm statistical

differentiability. Several previous studies have observed different responses of nirS-and

nirK-type denitrifying communities to environmental gradients; in several cases nirK

showed greater habitat selectivity (Throback et al., 2004; Wolsing and Prieme, 2004;

Santoro et al., 2006), however, the opposite has also been reported (Liu et al., 2003, Yan

et al., 2003).

Variance within nirK Clone Libraries

To further test the observed trends in genetic variation in denitrifier communities

among restoration sites, analysis of molecular variance (AMOVA) was implemented

(Excoffier et al., 1992); AMOVA has been previously applied for differentiation between

community structures based on functional genes (Dunfield and King, 2004; Nanba et al.,

2004; Yannarell et al., 2006). Only nirK libraries were chosen for this level of analysis,

due both to the observed difference in response to recovery and discrepancies in nirS

phylogenetic analysis in previous studies. Some studies correlating nirS response to

environmental gradients have included (Braker et al., 2000; Prieme et al., 2002) or

excluded (Santoro et al., 2006) regions of insertion or deletion for sequence alignments

and phylogenetic analysis. AMOVA estimates the significance of differences in

population pairwise fixation indices (FST). FST values for a population, or group of

populations, are an indication of genetic differentiation; in the case of molecular ecology,

it is a representation of within population diversity relative to total population diversity









(in this case, diversity of pooled sequences to diversity of libraries from each site)

(Martin, 2002). Pairwise comparisons of FST values for each site reveal whether genetic

diversity between sites differs (Martin, 2002). In relation to total population diversity,

low FST values indicate that diversity of the individual community is similar to that of the

two communities combined (Martin, 2002).

Variation of nirK populations within sites accounted for approximately 98% of

variance, only 2% was due to variation between libraries from each site. The large

percentage of variation within population further confirms the uniqueness of nirK

communities from each site. Although small, variance in diversity between populations

differed significantly from pooled populations (P = 0.013), consistent with results of the

parsimony test, and further confirms the existence of unique lineages of denitrifiers

within each restoration site.

FST values for each site declined with time since restoration; these values are

measures of genetic diversity within population compared to the total population. The

general decline in values with time since restoration suggests that populations of

denitrifiers become more reflective of total observed diversity in HID soils as recovery

progresses. Further, FST values confirm the results of J-Libshuff analysis: FST values

between sites nearer in recovery stages are closely related. Values for R89 and R97 range

from 0.030 to 0.033 and values for ROO, R01, and R03 range from 0.045 to 0.042. This

bimodal trend is also evident in average pairwise sequence similarity (09[7]) and

nucleotide diversity (Table 3-6).

Pairwise comparison of population FST and 9[7i] values are presented in Table 3-6.

Results for comparison of both values between sites are identical, as both are defacto









measures of within-population diversity. Significance of both tests implies genetic

diversity within sites is less than for sites combined, but that each harbors distinct

phylogenetic lineages; this is the case for the R89 community. Insignificance of FsT

paired with significant P tests, which is the case for pairwise comparison of R97, R00,

R01, and R03, is indicative of high diversity within each of these populations and that

each harbors different phylogenetic lineages; this can occur when each population is

comprised of many ancient lineages that do no overlap (Martin, 2002).

A Mantel (Mantel, 1967; Mantel and Valand, 1970; Dutilleul et al., 2000) test was

used to examine the correlation between pairwise differences in nirK population-specific

FST values between sites to matrices of pairwise differences in geochemical parameters.

Such analyses have been used previously to test whether observed differences in

functional gene diversity correlated with geochemical variables between sampling sites

(Francis et al., 2003). The Mantel test judges whether closeness of one set of variables is

related to closeness in another set of variables. In the context of this study, the test was

employed to determine correlations between observed differences in nirK diversity

between sites and measured environmental parameters along the chronosequence, and to

ultimately gain an understanding of environmental factors most likely controlling the

observed differences in nirK-type denitrifier populations in HID soils. Pairwise FST

matrices were tested for correlation with environmental factors most likely controlling

denitrifier activity: organic matter (loss on ignition), moisture content, and soil oxygen

demand. Differences in nirK FST values between sites were strongly correlated with

differences in soil moisture content (r = 0.895, P=0.017), and marginally with differences

in organic matter content (r = 0.61, P = 0.05). The results suggest that soil moisture plays









a strong role on nirK population diversity within each site, and may be used to explain

differences in populations between sites.

Conclusions

Little work to has been done to characterize denitrifying microbial communities in

wetland ecosystems. Further, this is the first study to characterize the development of

wetland communities of denitrifying bacteria in response to severe disturbance. While

geochemical data in sites of varying stages of recovery since complete soil removal

suggest loose trends associated with time since restoration, several lines of evidence

indicate the existence of significantly different populations of denitrifying bacterial

communities at each of the study sites. nirS clone libraries suggest an approximately

linear response with time since disturbance, while nirK sequences appear to respond

bimodally. In either case, this suggests that diversity of functionally redundant enzymes

results from adaptation to particular environments. The factors governing community

diversity are not entirely clear. However, the most obvious variable is recovery stage, the

gradual accumulation of nutrients, soil and associated moisture, and the maturing of plant

communities. Further, results of AMOVA indicate population diversity within sites to

decline with time since restoration, which may indicate a gradual decrease in species

recruitment as conditions within each site converge toward stability. These results

highlight the sensitivity of denitrifying bacterial communities to environmental

conditions, and provide insight into microbial community dynamics in response to

ecosystem recovery.









Table 3-1. Biogeochemical parameters of HID soils as measured in November 2005.


Soil Depth
Site (cm)
UND 10(2-15)
R89 6(1-17)
R97 5 (3-11)
ROO 3 (1-4)
R01 3 (1-7)
R03 1 (0-3)


Moisture
(%)
43.8(0.6)
59.6 (2.4)
58.8 (4.5)
48.3 (1.4)
41.6(1.1)
43.5 (10.1)


LOI
(%)
16.71
14.38
14.19
23.90
23.58
18.86


NH4 -N
(mg kg-1)
9.9 (0.9)
46.9 (1.9)
49.5(10.8)
25.1 (7.7)
15.2(5.1)
26.9(9.2)


"Values in parentheses are standard deviations of the mean


NO3--N Denitrification
(mg kg-1) Potential
6.8 (0.5) 0.51 (0.14)
3.1 (0.5) 0.48 (0.14)
1.8(0.6) 1.01 (0.27)
7.8(2.8) 0.12(0.03)
6.5(2.8) 1.15(0.33)
5.1 (2.8) 0.77 (0.11)
of three replicate samples.


tPotential denitrifying enzyme activity expressed as milligrams of N20-N per kilogram
soil per hour.


Table 3-2. Distribution of nirS sequences from each study site within designated
phylogenetic clusters.
Relative abundance of sequences from each clone Average No. of
Cluster library (%) similarity sequences
UND R89 R97 ROO R01 R03 (%)a

I 32 11 7 27 9 14 97(4) 44
II 36 0 18 18 0 27 92(12) 11
III 0 0 16 32 32 21 97(4) 19
IV 0 13 25 13 25 25 83 (20) 8
V 9 36 14 23 5 14 79(18) 22
VI 8 23 15 8 15 31 72(16) 13
aBased on pairwise comparison of deduced amino acid sequences within each cluster,
values in parenthesis are standard deviations












Table 3-3. Values ofnirS and nirK diversity and richness in HID soils, as estimated by Shannon diversity index, Simpson index, and
Chaol richness calculated using DOTUR (Schloss and Handelsman, 2005).
No. of clones No. of bNo. of Coveraged
Site and gene sequenced OTUSa Shannon index Diversity Richness singletons (

nirK
UND 28 13 2.3 (1.9, 2.6) 2.5 20 (13, 54) 6 100
R89 28 12 2.3 (1.8, 2.5) 2.2 22 (14, 66) 7 69
R97 25 11 2.0 (1.7, 2.4) 1.9 21(13,65) 7 86
ROO 30 16 2.4 (1.9, 2.8) 2.1 38 (21, 102) 12 72
R01 24 12 2.3 (1.9, 2.6) 2.4 19 (13, 48) 7 45
R03 23 12 2.2 (1.9, 2.6) 2.3 26 (15, 79) 8 71
ALL 158

NirS
UND 21 8 1.8(1.4,2.1) 1.8 11(8,31) 4 48
R89 17 10 2.2 (1.8, 2.5) 2.7 15 (11,39) 6 56
R97 15 16 2.7 (2.4, 3.0) 3.7 32 (20, 80) 12 67
ROO 27 16 2.6 (2.2, 2.9) 2.8 82 (38, 212) 12 76
R01 15 12 2.4 (2.1, 2.7) 3.1 16 (13, 34) 7 90
R03 22 18 2.8 (2.5, 3.1) 3.8 53 (27, 144) 15 45
ALL 117

aEstimates of OTUs, Shannon index, diversity and richness are all based on 3% differences in nucleic acid sequence alignments;
values in parentheses are upper and lower bounds of 95% confidence intervals as calculated by DOTUR.

bSample size independent estimate of diversity based on negative natural log transformation of Simpson's index values as calculated
in DOTUR.

"Chaol values, a non-parametric estimate of species richness.


dCoverage values for at distance = 0.01, as calculated by I-Libshuff (Schloss et al., 2004).









Table 3-4. Population similarity P values for comparison of nirK and nirS clone libraries
determined using Cramer-von Mises test statistic, implemented in J-Libshuff
(Schloss et al., 2004).
Site for P values for comparison of heterologous
Gene (n) homologous library (Y) with X'
library (X) R89 R87 R00 R01 R03
nirK (158) R89 0.036 0.000 0.000 0.000
R97 0.400 0.000 0.000 0.000
R00 0.000 0.000 0.000 0.000
R01 0.000 0.000 0.040 0.957
R03 0.000 0.000 0.000 0.304

nirS (117)
R89 0.421 0.000 0.000 0.000
R97 0.125 0.040 0.000 0.000
ROO 0.000 0.210 0.056 0.000
R01 0.000 0.000 0.269 0.000
R03 0.000 0.000 0.000 0.000
aValues in bold indicate significant P values (P < 0.0017)after Bonferroni correction for
multiple pairwise comparisons. Libraries are distinct from one another if both
comparisons (X versus Y and Y versus X) are significant. Values in italics indicate that
library Y is a subset of library X.









Table 3-5. Corrected average pairwise differences (E[vr]), above diagonal) and pairwise
fixation indices (FST, below diagonal) for nirK.
Site Result for study site:
R89 R97 ROO R01 R03
R89 4.312 1.344 3.201 4.564
R97 0.060 3.021 1.569 1.825
ROO 0.029 0.049 0.905 0.922
R01 0.048 0.028 0.015 -1.031
R03 0.069 0.034 0.016 -0.023
aBold values are significant at P < 0.05.








Table 3-6. Fixation indices, average pairwise differences (O[R]), nucleotide diversity, and
shared haplotypes of nirK clone libraries as calculated by Arlequin (Excoffier
et al., 1992).

Nucleotide No. of No. of shared haplotypes
Site FST [7] Diversity unique
haplotypes R89 R97 ROO R01 R03
R89 0.030 89 (44) 0.25 (0.12)a 23 1 1 2 1
R97 0.033 83(37) 0.24 (0.11)a 21 2 4 3 3
ROO 0.042 66(29) 0.19 (0.01)b 28 1 4 3 4
R01 0.043 64(27) 0.18 (0.01)b 17 2 3 3 3
R03 0.045 62 (28) 0.17 (0.09)b 18 1 3 4 3
IValues sharing same letter notation are not statistically different, based on pairwise
Student's t-test (P < 0.05).











76




w Hid-HiN;rS-IRH 10-R"
0.1 subsIitulions 7 Hld-NkrS-2HOO-R3
1?5 H id-.N iAS. I RCIND
Hid.NirS-1 R O.UNO
SHid-NirS.205.ROO
Hld-NirS-lCO1-R97
iid.-Nitl"- 071-R97
"111M-Nib-2O09-RO3



SHd-NhiS-2A05-RO0

lHid-NirS-2103-R03
lid-NirS-RRCOY-.LND
ltid-NirS-IRFOI-R9
1H id-NlrS-2BO I -ROD
Hid-NirS-2FO-RO I
HI I d-NirS-1. RF R9 1
l Hid-NIrS-2A0 R2-
H id- Nir O i L C-R

Hid-NirS-2F01-ROI
L Hd-NirS-RA 12-LND
Hid-NISr-1B04-UND
I1tid.NirK.2A09.RoI
DHid-NiS-240 3-R
IHid-NirS-2Al-ROO
lid-NirS-2010-R03
Hid-NiSF -00IIRO
,3 Hid-NirS-2B02-RO0
Hid-NirS- RCOO.R0R
94 i-Hi-Ni i- 201-ROO
S Hkd-NirS- RA -UN D
lhdid.N I A.M-UN D
| id-Nir--lRC0l4-iJN O
Hid-Nuir S-2E -RO
| H d-NiurS--l07-RR97
HkNir I HI-Nhr-iRh'I2-R97
Hid-NitS-IC03-UND
S Hid-Nil,-1 B0.UJN
I U lId-N1-I RBl 2-UND
| Hid-Ni2S-3H2- A10
HidI.NiiSN.2FIRR0O
0 ll Hid.Nitr .2AI 12RO


nculuod iTlcoriuiiin cldou 556 (AY 121597)
M Uncultd bccriu iiM loe 14 (AYI2IS99)
| Ilid-Nir-.2II.-ROO
fid-Ni i.2F1(-ROO



elid-NS-2C0plings
1Hi-NiO-20 100-ROO
I -Nir F I .R0
Hid-NirS-2Ei4-ROI
Hd-NurS-2A12A-RO
SIkI-Niro2'C IA R 03I
HId-NirS-2E04-R01
Hid- N 21004-001
^Hid-Ni i.I2CR R7RO
I I d-N ,I ".C 03.R03
I IHid-N .IS-2I 9-RO I
I|id.kNiir I 5 l K.R97
I.i........ .... lf-9a

61 I ^ InNI-NSirDt-ROI
IlddNh -l11-l-iR?
Illid-NirS-I RM-
I V
61 | II,| J..Nir-2H15o-R0

Hid-Nir IIid Nir RFI-R
9ir -N lid-NiR F. lKR
S4HNd-N rS-2F 0 3-R OO

HiId-NirS-I-RAIO I -ND
6| ^ 10,Hid-NirS. I H04-R97
| |0 Hid.NirS.21F R03
9 tlHid-NirS-ICR-ROI
I4 I id-NilOS-2a103-1RO0 V
| ^ -N Hid-Ni-RG -4-R03R
I N3I l.Nir2F7R03
Sllid.iiNiNSNI O UND


"30 I I -N wHIdr I NlrS_ O4R7
I- Ii H-d-NirS- IL07-R.
I lid-NirS. IRC ID-R"
|6 I lIk-NirS-2AO4-ROO
Ir lid;Mir-1I RED7R879-
Th- sinin 2dFB6 (AY027272)










_I, on = r IAY0R89 )
w JiliurJ olr Ajiin clom U03-03-211 (AF A4 Y 276 7










Paroocoxas diniiroics (-AM2754313)M
SHi FI resamplings.-R
I Hl--NiTS-22 1-R-0



| Hi H N d-N'it-G I R O2-ROI
^I l-Hid-NirS-2G -R9-RQ3
T d l M1c# tw ( clo6S3 (AY 121599)


T u |a |o r .,
|- fo 2' i (AY078260)




Paracr-, d-fteniUrificin. (U1175413)




Figure 3-1. Neighbor-joining tree of nirS sequences obtained from wet season soils.

Values on nodes are bootstrap scores based on percent occurrence of 1000

resamplings.










77




0 ] substitutlon site -Hid-NirK-2FO7-R3 (+1)

id-NirK-2A07-R00 (+3)

Hid-NirK-2F12
Hld-NirK-2C05
lhd.NirK-2 D10
Hid-NirK-2D03
Hid-NIrK-FIO
-Hid-NirK-2E07
Hd-NirK-2D12
Hid-NrK-IFI


Hid-NirK- 12C8


Hid-NirK-2A (+-
Hid-NirK- IEl2
id-NrK-2AO4
Hid-NitK- 204
Hid MNicK-206 (+1)
|Hid-NirK-2BOS (+1)
Hid-NilK-IE07
Hid.NjTK.21C0
Hid-NirK-ID2C
Hid-NirK-2H06 (+1)
-- id-NirK-d N 3
SHid-NirK-2D4O.R0
lid-NieK-1EOI -R89 (+2)
Hid-NirK- H06-R7
Hidl-NirK-2H06-R03
S Hid-NirK2H 11 -R03 (+3)
Hid-Nic- F1 I-R1 I
Hid-NirK-2E04-R01
79 Hi -NicK 1 13
77 HidtNicK-0-A B, C, D, E

Hid-NirK- 2D 1-ROI )
Hid -NrK 2H09-R03
Hid-NicK-2A02-100
| Hid-NirK-1B04-UNI
Hid-NifK- 1C06-UND
Hid-NirK-IB0l-UND(+) 2)
17d-NirKj G8K-lRI
dHNirK-2IC1-R-2I(+
i7 Hid-NirK-F1D3-R89(+
Hid-rNiK-I OS-RO (
Hid-NirK-1G02-R97
U ltied balemi K-A24 (AB162336)
Uncuilured baclenum done M63 (AY IS214$)
SI U JtWed bacerm r A8 AJ487546
.| 1_.pd 7ci ic noeM7AYI1217)
SUncultured bacteria clone M 10 (AY 121569)
Hid-NirK-2GOI-R03
Hid-N K-2GO4-R03
9 icrH-GK.2o@1j 2 P-.03

Hid-Nic 11- 0-r+7
SHid-NirK- IH03-R97 F
Hid-NirK-2A10-R00





Hid-NwK-IB06-UND(+3) I G
-NIKHid-NirK-2C1--R
Hid-NNK-K- IB0--UND
K -IDBIarie D (+23 ) H

|HHidNi -Nc K-lK 2A9


YHid-NDK-I9O-103 'I)
Hid-NK-2i1-R0KIC ( .R'

-IdI"Hid-NirK- I-BN0-UND (+3) G
I- Ne d one iNiNKI2AllA- 1 )-R97
Hrhd-N.DK-2IBO-UND

Hi iK-I 6- (+2)-I -
Hidd-Nir K-1B6-.R9




Figure 3-2. Neighbor-joining tree of nirK sequences obtained from wet season soils.
| ..-a -- ^ o s a ^y
-NIrid-N-1K-2F-9-R03 I



| -I Hid--NiK-lC07-UND(+
| i--idK-1NiFK- 2 I-RO O (l
| 65 -_ H Ift g -- A9-R)

r,,,,,,,,, iHid-N- I rK-U O 10-R 1 (+])

i-- HIC -NiK IS-UND


U db 1terium NR(-.g19K3 (R O 6936O
HkL--2CiRK-1G1-R7
L------" d-NK-2ABI-7UND(+1) UND

Hid-Nir-ICI id I- -R89R



I HHlNiK- r06-89 1+2)
Hid-Nd-NrK-I 2 K-R2



L m -,_.osp-, GmI "|9- (M(A17 94)





Figure 3-2. Neighbor-joining tree of nirK sequences obtained from wet season soils.

Values on nodes are bootstrap scores after 1000 resamplings.










% of each cluster


198
196
195 75


0.15 0.10 0.05 0.00


A
B
C
D
E


UND
10
29


F -
G 100
H 83
68 I

J 40
K 10
60 L 21
7
Total (n): 28


Figure 3-3. Sequence analysis ofnirK clones obtained from wet season soils. Sequences
were grouped into clusters (A to L) based on inspection of alignments,
distance data, and neighbor-joining trees. Percent similarity is based on
comparison of putative amino acids and was determined between all members
of each groupss. The percentage of each nirK sequence types recovered from
each site is listed in the table next to the figure. Asterisk represents sequences
that could not be readily assigned to a cluster (singletons).


17
33
20 20
10
- 29
6 5
25 30


33 17
- 20
40 10

3 5
24 23


% Similarity














CHAPTER 4
SEASONAL DIVERSITY AND FUNCTION OF AMMONIA OXIDIZING BACTERIA
ALONG A SHORT-TERM RESTORATION CHRONOSEQUENCE

As the linking process between organic nitrogen mineralization and loss of

biologically preferable forms of inorganic nitrogen, nitrification is a determinate process

in the availability of N within an ecosystem, and an influential factor on productivity of

plant and microbial communities. Nitrification is a two-step process involving two

distinct groups of bacteria. The first, the conversion of ammonium to nitrite is mediated

by ammonia oxidizing bacteria (AOB); the second step is the conversion of nitrite to

nitrate, and is mediated by nitrite oxidizing bacteria (NOB). The most common rate-

limiting step is the conversion of ammonium to nitrate, carried out by AOB. The first

step involves conversion of ammonia to hydroxylamine by ammonia monooxygenase

(AMO), while hydroxylamine oxidoreductase converts hydroxylamine to nitrite (Hooper

et al., 1997). Nitrate production due to heterotrophic bacterial activity has also been

observed, though it is generally limited to conditions of high carbon-to-nitrogen ratios or

acidic soils (Pedersen et al., 1999; Bothe et al., 2000; Kowalchuck and Stephen, 2001).

Chemolithotrophic AOB are thought to be the major contributors to nitrification in soil,

sediment, marine, freshwater, and estuarine environments (Belser, 1979; Bothe et al.,

2000).

All AOB possess amoA, which codes for the alpha-subunit of AMO. Early

characterization of AOB diversity within the environment involved the use of 16S rRNA

gene specific primers (Stephen et al., 1996; Kowalkchuk and Stephen, 2001); these









studies revealed significant patterns in phylogenetic clustering of AOB sequences

putatively in response to environmental parameters. However, ribosomal DNA does not

provide significant evidence of function. Functional genes maintained by an organism

define its interaction with the environment. They evolve faster and may provide greater

phylogenetic resolution. Recent work by Purkhold et al. (2000) revealed a congruence of

phylogenetic clustering between amoA and 16S rRNA genes of AOB, allowing for

correlation of amoA clusters with established 16S rRNA clusters, and subsequently

providing further insight into possible mechanisms controlling the ecology of organisms

within the established clusters. Since the initial identification of amoA as a molecular

marker of AOB diversity in the environment (Rotthuwae et al., 1997), diversity and

structure of AOB populations have been studied along environmental gradients and

correlated with shifts in environmental variables in successional grasslands (Kowalchuk

et al., 2000), estuarine sediments (Francis et al., 2003), wastewater bioreactors

(Rotthuwae et al., 1997), marine environments (Mullan and Ward, 2005), and in response

to global change (Horz et al., 2004).

Despite clear evidence of AOB activity in wetlands and other anoxic systems

(Reddy and Patrick, 1984; Laanbroek and Woldendorp, 1995), relatively little work has

been done to characterize dynamics of AOB populations or nitrification activity in

wetland soils (Duncan and Groffmann, 1994; White and Reddy, 2003). To date, the only

study to characterize wetland AOB using molecular approaches was conducted in a

manure-impacted treatment wetland (Ibekwe et al., 2003).

Oxygen transport by aerenchymatous plant tissues to saturated soils establishes

oxygenated microsites within the rhizosphere conducive to AOB activity (Reddy and









Patrick, 1984; Kowalchuk et al., 1998). Diffusion gradients of reduced and oxidized

compounds between aerobic microsites and anoxic bulk soil, or between sediment-

surface water column exchange, may provide sufficient supply of resources to maintain

nitrifying activity under flooded conditions (Reddy et al., 1989). Further, seasonal

inundation provides a unique opportunity to study the response of nitrification and AOB

in concert with shifts in availability of regulatory substrates such as oxygen and

ammonium.

Primary succession is the development of plant and microbial communities on

bare substrate. Parent substrate usually contains sufficient amounts of mineral nutrients,

such as phosphorous, but generally harbors negligible amounts of bioavailable N

(Vitousek et al., 1989). Thus, nitrogen inputs to developing ecosystems likely originate

from exogenous sources, such as atmospheric fixation and rainwater. Successional

changes in the availability of N have received much attention, in particular because N

most often limits primary production in terrestrial ecosystems (Vitousek and Howarth,

1991). It has been hypothesized that successional changes in nitrate production have

substantial effects on ecosystem level N losses. Nitrification has been implicated as the

primary mechanism of N loss during succession in upland soils (Robertson and Vitousek,

1982). Further, Rice and Panchloy (1972) hypothesized that nitrification generally

decreases with successional stage due to inhibition of nitrifying bacteria by plant

allelochemicals in later successional stages. While several studies have proven this

hypothesis to be true in the context of primary to secondary succession (Rice and

Pancholy, 1972; Robertson, 1982; Robertson, 1989), nitrification rates in ecosystems









undergoing primary succession have indicated the opposite (Robertson and Vitousek,

1981).

Sequential development of microbial and plant communities in concert with soil

accretion in HID sites at differing stages of disturbance recovery provides an excellent

opportunity to characterize the dynamics of nitrification and AOB during a critical stage

of initial ecosystem recovery. Specifically, this study sought to: (i) explore nitrification

activity during early stages of primary succession, by assessing the activity of AOB

concurrent with the development of soils; and (ii) characterize the activity and population

genetic structure of specific genotypes of AOB across seasons and time since restoration,

in hopes of elucidating factors that control activity and guild composition within and

between seasons both within each site and along the restoration gradient.

Materials and Methods

Site Description, Sampling, and Biogeochemical Characterization

Samples were collected in November 2004 and May 2005. Plots 20 x 20 m2 were

established in sites restored in 1989, 1997, 2000, 2001, and 2003 (R89, R97, ROO, R01,

and R03, respectively), and in an undisturbed site (UND). The range of elevation for the

five plots was 0.5 to 0.6 m. Within each sampling area, 2 x 2 m2 grids were used to

establish 81 sampling nodes, which were monitored for soil depth, ground coverage, and

elevation. Nine nodes were chosen based on relative range of soil depth within each site,

3 from each depth range (shallow, intermediate, deep). Sampling nodes were color coded

and marked for future sampling efforts. Soil samples were taken with a plastic coring

device; however, due to non-uniform soil cover in recently restored sites, grab samples

were collected where appropriate. Individual samples from each depth range were

combined to make three representative soil samples, which were used for molecular and









geochemical analyses. Soil samples were kept on ice and transported to the laboratory

within 72 h of the collection, where they were manually mixed and large roots removed.

Subsamples for DNA analysis were stored at -70 OC until analysis. Biogeochemical

analyses were conducted at the Wetland Biogeochemistry Laboratory (D'Angelo and

Reddy, 1999; White and Reddy, 1999). Values for select parameters are presented in

Table 4-1.

Determination of Potential Nitrification Rates

Nitrification potential activities of HID soils were determined using the shaken

soil slurry method of Hart et al. (1994). Nine random samples were taken from 20 x 20

m2 plots within each study site. Samples were sieved through 2 mm mesh, and nine 50 g

sub-samples were combined to make a composite for each site. Composite samples were

divided into five 15 g replicates. Each soil sample was suspended in ImM phosphate

buffer (pH 7.2) and amended with 1.5mM (NH4)2S04. Samples were shaken in

autoclaved, acid rinsed 250 mL Erlenmeyer flasks in the dark for 24 h at 180 rpm and

24C. Aliquots (10 mL) of soil slurry were taken for NO3 analysis at 5 time points (0, 2,

4, 8, 20, 24 h) and frozen at -800C until analysis.

Nitrate concentrations were determined by conversion to nitrite by shaking with

cadmium (Jones, 1984). For determination of nitrate, 10 ml samples from each time point

and replicates were centrifuged at 5000 rpm for 5 min to separate soil particles from

buffer solution. Then, 2 to 2.5 mg of spongy cadmium and 1 ml of 0.7 M ammonium

chloride (pH 8.5) were added to 5 ml aliquots of buffer from each sample, in 10% HC1-

rinsed 15 ml conical centrifuge tubes (BD Biosciences, San Jose, CA, USA), and shaken

on a rotary shaker at 100 rpm for 1.5 h.









Spongy cadmium was generated by reaction of 20% (w/v) cadmium sulfate with

one zinc bar (Sigma-Aldrich, St. Louis, MO, USA) for 8 h; spongy cadmium which

precipitated on the surface of the zinc bar, was scrapped off into a clean container,

acidified with 3 drops of 6N HC1, and washed with 18 MQ distilled deionized water

(DDW) six times. Until use, spongy cadmium was stored under DDW. Activated

cadmium was prepared by washing with 6N HC1 solution for five minutes, and then

rinsed ten times with DDW (at which point the pH of decanted waters was approximately

pH 5 or greater).

Colorimetric determination of nitrite concentrations were done by reacting 5 ml of

sample solution with 100 [l of combined diazotizing and coloring agents (0.05 g

sulfanilamide, 0.05 g N-(1-naphthyl) ethylenediamine, 5 ml of 85% phosphoric acid, and

water to final volume of 50 ml) in acid washed 7ml plastic scintillation vials; color was

allowed to develop for 15 min, with periodic swirling, prior to analysis. Following color

development, 1 ml of sample was transferred to 1.5 ml polystyrene disposable cuvettes

(10 mm path length, Fisher Scientific) and nitrite concentrations were determined as a

function of absorbance intensity at 540 nm, with a Shimadzu UV 1201 spectrophotometer

(Shimadzu, Kyoto, Japan). Nitrate standards prepared by serial dilution of 1000 ppm

nitrate solution (Fisher Scientific, Pittsburg, PA, USA) were run during each series of

cadmium-reduction reactions. To determine conversion efficiency, nitrite concentrations

in standards after shaking were compared to values of nitrite standards; conversion

efficiencies for cadmium shaken samples compared to nitrite standards in this study

ranged from 95 to 102%, consistent with those reported by Jones (1984). To standardize

for differences in initial nitrate concentrations in replicate samples, time zero values were









subtracted from values at each time point, prior to rate determination. Nitrification

potentials were determined by the slope of a linear regression of cumulative nitrate

concentrations with time (Hart et al., 1994).

Extraction of Nucleic Acids and PCR

Nucleic acids were extracted from approximately 0.25 g soil using the PowerSoil

DNA Kit (MoBio, Solana Beach, CA) following the manufacturer's instructions.

Extracts were examined by electrophoresis through 1% agarose gels made with tris-

acetate-EDTA buffer, staining with ethidium bromide, and visualization under UV light.

In an effort to fully characterize communities within HID soils and account for spatial

variability, equal volumes of bulk DNA extracts from three replicate soil samples per

study site were pooled prior to PCR analysis.

A 491 bp fragment of amoA was amplified using primer set amoAlf (5'-

GGGGTTTCTACTGGTGGT-3') and amoA2r (5'-CCCCTCKGSAAAGCCTTCTTC-3')

developed by Rottauwe et al. (1997). Each 25 [l reaction contained 12.5 [l of HotStar

Taq Master Mix (QIAGEN, Valencia, CA, USA), 8.75 [tl of distilled water, 1.25 [tl of

each primer (20 pmol [t-1'), and 1 [tl of undiluted template DNA. PCR amplification was

carried out in GeneAMP PCR system 9600 (Perkin-Elmer, Applied Biosystems,

Norwalk, CN, USA). Initial enzyme activation and denaturation were performed at 95 C

for 15 min, followed by 35 cycles of 95C for 30s, 55C for 45s and 72C for 45 s, with

a final extension step at 720C for 7 min.

Cloning and Sequencing

Fresh PCR products from all samples were ligated into pCRII-TOPO cloning

vector and transformed into chemically competent Escherichia coli TOP10F' cells









according to manufacturer's recommendations (Invitrogen, Carlsbad, Calif.). Randomly

picked white or light blue clones were inoculated into 96 well plates containing 200 [tl of

LB broth with kanamycin (50 |tg ml1) and grown overnight at 37C. Live clones were

screened directly for inserts using live cell PCR and SP6 and T7 vector primers. Clones

containing the correct insert size were transferred to 96 well plates containing LB broth

amended with kanamycin (50ug ml) and 8% (v/v) glycerol and incubated for 24 h at

37C. Overnight cultures were submitted to the Genome Sequencing Core Laboratory at

the University of Florida.

Phylogenetic Analysis

Nucleotide sequences were manually aligned in Se-Al version 2.0al 1 (Rambaut,

1996) and aligned with ClustalX version.1.81 (Thompson et al., 1997). Phylogenetic

trees were produced from a 450 bp amoA fragment, using Jukes and Cantor corrected

distance matrices in the TREECON software package (van de Peer and de Wachter,

1994). Bootstrap analysis (1000 resamplings) was used to estimate reproducibility of

phylogenies. Bayesian analysis was conducted using ClustalX generated alignments in

Mr. Bayes (Huelsenbeck and Ronquist, 2001; Ronquist and Huelsenbeck, 2003) software

under default model parameters for 2.5 million generations. Due to high redundancy in

sequence similarity, only sequences sharing less than 97% sequence similarity were

included in the final cladogram.

Statistical Analysis of Phylogenetic Data

To assess whether observed AOB clone libraries between sites represented

statistically different populations, well-aligned subsets of each gene fragment were

chosen for analysis using J-Libshuff (Schloss et al., 2004) with 1,000,000 randomizations