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Plant Soil Feedbacks with Changing Vegetation Structure and Composition in a Warming Arctic

Permanent Link: http://ufdc.ufl.edu/UFE0043741/00001

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Title: Plant Soil Feedbacks with Changing Vegetation Structure and Composition in a Warming Arctic
Physical Description: 1 online resource (142 p.)
Language: english
Creator: Demarco, Jennie
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2011

Subjects

Subjects / Keywords: arctic -- carbon -- mineralization -- nitrogen -- shrubs
Biology -- Dissertations, Academic -- UF
Genre: Botany thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Climate warming in the arctic may shift vegetation from currently grass dominated system to a more deciduous shrub dominance system. A change in the type of plants present in the arctic could alter the function of the ecosystem through influences on the abiotic and biotic controls over carbon (C) and nitrogen (N) cycling. Shrubs may influence the soil microclimate and litter inputs to the soil, altering the rate at which nutrients are cycled back to soil and available to plants. In arctic tundra near Toolik Lake, Alaska, we experimentally manipulated snow depth across three arctic plant communities that varied in their initial shrub abundance to test whether the snow that accumulates around arctic deciduous shrubs alters the soil microclimate enough to increase soil N availability and nutrient turnover. Specifically, we tested whether the addition of snow provides a more favorable microclimate for N mineralization and litter decomposition. In addition we investigated the influence of soil organic matter (SOM) and litter quality on N availability and nutrient turnover. We found that winter snow addition increased soil N availability in the summer only through increased rates of N mineralization but had no effect on litter decomposition rates. In addition, SOM quality was greatest in the plant community with the highest abundance of shrubs resulting in faster turnover and greater N availability. In contrast, litter decomposition rates were slower in shrub dominant communities resulting in slower nutrient turnover and higher retention of N on the litter. We conclude, that on a short time scale shrub interactions with snow increase N availability, at least in the summer, at a time when plants are more active. In addition, our study suggests that a transition to a shrubbier arctic could lead to retention of N in the litter layer and an increase in N availability in the soil potentially leading to a positive feedback to increased shrub growth.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Jennie Demarco.
Thesis: Thesis (Ph.D.)--University of Florida, 2011.
Local: Adviser: Mack, Michelle C.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2013-12-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2011
System ID: UFE0043741:00001

Permanent Link: http://ufdc.ufl.edu/UFE0043741/00001

Material Information

Title: Plant Soil Feedbacks with Changing Vegetation Structure and Composition in a Warming Arctic
Physical Description: 1 online resource (142 p.)
Language: english
Creator: Demarco, Jennie
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2011

Subjects

Subjects / Keywords: arctic -- carbon -- mineralization -- nitrogen -- shrubs
Biology -- Dissertations, Academic -- UF
Genre: Botany thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Climate warming in the arctic may shift vegetation from currently grass dominated system to a more deciduous shrub dominance system. A change in the type of plants present in the arctic could alter the function of the ecosystem through influences on the abiotic and biotic controls over carbon (C) and nitrogen (N) cycling. Shrubs may influence the soil microclimate and litter inputs to the soil, altering the rate at which nutrients are cycled back to soil and available to plants. In arctic tundra near Toolik Lake, Alaska, we experimentally manipulated snow depth across three arctic plant communities that varied in their initial shrub abundance to test whether the snow that accumulates around arctic deciduous shrubs alters the soil microclimate enough to increase soil N availability and nutrient turnover. Specifically, we tested whether the addition of snow provides a more favorable microclimate for N mineralization and litter decomposition. In addition we investigated the influence of soil organic matter (SOM) and litter quality on N availability and nutrient turnover. We found that winter snow addition increased soil N availability in the summer only through increased rates of N mineralization but had no effect on litter decomposition rates. In addition, SOM quality was greatest in the plant community with the highest abundance of shrubs resulting in faster turnover and greater N availability. In contrast, litter decomposition rates were slower in shrub dominant communities resulting in slower nutrient turnover and higher retention of N on the litter. We conclude, that on a short time scale shrub interactions with snow increase N availability, at least in the summer, at a time when plants are more active. In addition, our study suggests that a transition to a shrubbier arctic could lead to retention of N in the litter layer and an increase in N availability in the soil potentially leading to a positive feedback to increased shrub growth.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Jennie Demarco.
Thesis: Thesis (Ph.D.)--University of Florida, 2011.
Local: Adviser: Mack, Michelle C.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2013-12-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2011
System ID: UFE0043741:00001


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1 PLANT SOIL FEEDBACKS WITH CHANGING VEGETATION STRUCTU RE AND COMPOSITION IN A WARMING ARCTIC By JENNIE DEMARCO A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUI REMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2011

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2 2011 Jennie DeMarco

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3 To my parents, Tom and Janet, who taught me to work hard and be passionate about the work I do: two traits that are essential for getting through g raduate school and completing a dissertation. To my husband, Ben, for his unwavering patience, love, and support during this time and to my sons, Elias and Leonid, whose persistent curiosity and questions about the world around them is a constant reminder to me of why science is so important and so much fun!

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4 ACKNOWLEDGMENTS I would like to thank my advisor, Dr. Michelle Mack for all of her intellectual guidance during the construction, implementation, and completion of this dissertation and to my c ommittee members, Dr. Ted Schurr, Dr. Ramesh Reddy, and Dr. Max Teplitski for their helpful comments. I would also like to thank Charmagne Wasykowski, Grace Crummer, Julia Reiskind, Yi Wei Cheng, Anne Baker, Leslie Boby, Faye Belshe, Hanna Lee, Caitlin Hi cks, Mark Burton, the numerous volunteer pluckers who assisted with the biomass harvest, and the many undergraduates at the University of Florida for their assistance in sampling and processing the thousands of plant and soils needed to complete this disse rtation. I also thank Martin Lavoie and Grace Crummer for their comments on earlier drafts of this manuscript. This research was supported by NSF grants DEB 0516041, DEB 0516509 and the Arctic LTER (DEB 0423385).

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ ............ 8 LIST OF FIGURES ................................ ................................ ................................ ........ 10 ABSTRACT ................................ ................................ ................................ ................... 12 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .... 14 2 THE EFFECTS OF SNOW, SOIL MICROENVIRONMENT, AND SOIL ORGANIC MATTER QUALITY ON N AVAILABILITY IN THREE ALASKAN ARCTIC PLANT COMMUNITIES 1 ................................ ................................ .......... 20 Background ................................ ................................ ................................ ............. 20 Methods ................................ ................................ ................................ .................. 24 Study Area ................................ ................................ ................................ ........ 24 Snow Manipulation ................................ ................................ ........................... 26 Characterizing ecosystem structure ................................ ................................ 28 Soil N dynamics ................................ ................................ ................................ 29 Statistical Analyses ................................ ................................ .......................... 32 Results ................................ ................................ ................................ .................... 33 Ecosystem structure across the shrub gradient ................................ ................ 33 Snow manipulation ................................ ................................ ........................... 34 Reciprocal soil core transplant exper iment ................................ ....................... 36 Discussion ................................ ................................ ................................ .............. 36 Snow addition effects on N availability ................................ ............................. 3 6 Soil organic matter quality effects on N availability ................................ ........... 39 Soil microclimate versus soil organic matter quality effects on N availability .... 40 Implications for feedbacks to climate change ................................ ................... 42 3 CONTROLS OVER LITTER DECOMPOSITION IN THREE ARCTIC PLANT COMMUNITIES ................................ ................................ ................................ ...... 49 Background ................................ ................................ ................................ ............. 49 Methods ................................ ................................ ................................ .................. 54 Study Area ................................ ................................ ................................ ........ 54 Snow Manipulation ................................ ................................ ........................... 56 Common Substrate Experiment ................................ ................................ ....... 57 Common Environment Experiment ................................ ................................ ... 58 Calculations ................................ ................................ ................................ ...... 59 Initial Litter Quality ................................ ................................ ............................ 59

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6 Community Weighted Decomposition ................................ .............................. 60 Statistical Analysis ................................ ................................ ............................ 62 Results ................................ ................................ ................................ .................... 63 Effect of added snow on soil temperature ................................ ........................ 63 Common Substrate Experiment ................................ ................................ ....... 63 Common Environment Experiment ................................ ................................ ... 64 Deciduous shrub litter collected across the shrub gradient sites ................ 64 Initial litter quality and decay constants across species with and without fertilization ................................ ................................ ............................... 65 The relationship between initial litter quality and decay constants ............. 67 Community Weighted Decomposition ................................ .............................. 68 Discussion ................................ ................................ ................................ .............. 68 Microenvironment controls over litter decomposition ................................ ........ 68 Litter quality controls over litter decomposition ................................ ................. 72 Litter quality/quantity versus microclimate controls over litter decomposition ... 74 4 PLANT AND ECOSYSTEM RESPONSE TO LONG TERM EXPERIMENTAL WARMING AND NUTR IENT ADDITIONS IN ARCTIC SHRUB TUNDRA .............. 85 Background ................................ ................................ ................................ ............. 85 Methods ................................ ................................ ................................ .................. 88 Study Site and Treatments ................................ ................................ ............... 88 Environment ................................ ................................ ................................ ..... 89 Biomass ................................ ................................ ................................ ............ 90 Abovegr ound Net Primary Production ................................ .............................. 91 Species Diversity ................................ ................................ .............................. 92 Soil Properties ................................ ................................ ................................ .. 92 Carbon and Nitrogen Pools ................................ ................................ .............. 92 Statistical Analysis ................................ ................................ ............................ 93 Results ................................ ................................ ................................ .................... 93 Environmental Data ................................ ................................ .......................... 93 Biomass ................................ ................................ ................................ ............ 94 Aboveground Net Primary Production ................................ .............................. 94 Species Diversity ................................ ................................ .............................. 95 Soil Properties ................................ ................................ ................................ .. 95 Carbon and Nitrogen pools ................................ ................................ ............... 95 Allocation ................................ ................................ ................................ .......... 96 Discussion ................................ ................................ ................................ .............. 97 Controls over biomass and productivity ................................ ............................ 97 Changes in C and N pools ................................ ................................ ................ 99 Species diversity ................................ ................................ ............................ 100 Shifts in allocation ................................ ................................ .......................... 100 Changing C balance ................................ ................................ ....................... 101 5 CONCLUSION ................................ ................................ ................................ ...... 114

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7 APPENDIX A Supplementary material for Chapter 2 ................................ ................................ .. 116 A.1 Additional methods: Characterizing ecosystem structure ............................... 116 B Supplementary material for Chapter 3 ................................ ................................ .. 119 LIST OF REFERENCES ................................ ................................ ............................. 131 BIOGRAPHICAL SKETCH ................................ ................................ .......................... 142

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8 LIST OF TABLES Table page 2 1 Vegetation and soil characteristics for three arctic plant communiti es located near Toolik Lake, AK ................................ ................................ .......................... 44 2 2 Soil characteristics from the top 10 cm of the organic soil at three sites near Toolik Lake, AK. ................................ ................................ ................................ 45 3 1 Initial mass remaining (IMR), initial carbon remaining (ICR), initial N remaining (INR), and decay constants for the common substrate, Betula pap yrifera var. neoalaskan ................................ ................................ ................ 76 3 2 Two way ANOVA results comparing k, INR, ICR, and the proportion of ICR:INR after three years of incubation across all sites and treatments. ............ 76 3 3 Initial litter quality of senesced leaves of Betula nana collected in both unfertilized plots and plots that had been fertilized for five, 14, and 20 years ..... 77 4 1 Soil properties measured across all four treatments. Different letters indicate significance across treatments. ................................ ................................ ........ 110 4 2 Vascular plant species rank by treatment based on aboveground biomass ..... 111 4 3 Aboveground biomass (g/m 2 ) for the most abundant species and funct ional groups ................................ ................................ ................................ .............. 112 4 4 Three way ANOVA results compari ng aboveground biomass among treatments. ................................ ................................ ................................ ........ 113 4 5 Two way ANOVA results comparing N or C pool across treatments (C, NP, T, NP + T) withi n the same component ................................ ............................ 113 4 6 Two way ANOVA results comparing biomass, C, or N allocation across treatments (C, NP, T, NP + T) within the same plant part ................................ 113 A 1 Belowground biomass at each site ................................ ................................ ... 117 A 2 K 2 SO 4 extractable soil nutrients down to 10 cm within the organic layer. ......... 118 B 1 Soil temperature at 5 cm during the growing s eason (62 days) and winter (272 days) for the three year period our litter decomposition bags were incubated ................................ ................................ ................................ .......... 125 B 2 Three way repeated measures ANOVA comparing differences in soil temperature be tween vegetation type, treatment, and year. ............................ 126

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9 B 3 Initial litter quality for senesced leaves and stems of Betula nana and Salix pulchra collected in each of our three plant communities and incu bated at a commo n site ................................ ................................ ................................ ..... 127 B 4 Results from two Betula nana and Salix pulchra collected in each of our three plant communities and incubated at a common site. ................................ ................................ ............. 128 B 5 Initial litter quality for senesced leaves of seven species of vascular plants and three moss species collected from control and fertilized plots in a moist acidic tundra community and incu bated in a common site ............................... 130

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10 LIST OF FIGURES Figure page 1 1 Potential pathways by which shrubs en hance their dominance through a positi ve feedback mechanism where shrubs alter the biophysical and biogeochemical environment resulting in increased nutrient availability. ............ 19 2 1 Soil temperature and snow depth across three s ites near Toolik Lake, AK. a) Weekly mean, maximum, and minimum air temperature at 5 m. b) Weekly mean ( SE) soil temperature measured at 5 cm depth within the organic layer under ambient and snow addition treatments at each site (n = 3 4). c) Mean ( S E) ambient and manipulated snow depth during the winter of 2005 2006 and 2006 2007. ................................ ................................ ......................... 46 2 2 Mean ( SE) net N mineralization in intact, resin capped organic soil cores incubated in the con trol and snow addition treatments at each of the three sites during the summer (mid June Sept 2006; 74 days) and winter (S ept 2006 June 2007; 280 days). ................................ ................................ .............. 47 2 3 Mean ( SE) net N mineralization in intact, resin capped organic soil cores incubated in the control treatment or reciprocally transplanted and incubated in one of the other sites ................................ ................................ ...................... 48 3 1 Initial mass, C, and N remaining of the common substrate ( Betula papyrifera var. neoalaskana ) ................................ ................................ ............................... 78 3 2 Decay constants, initial C and N remaining, and the proportion of initial C:N remaining for the common substrate ................................ ................................ .. 79 3 3 Percent initial leaf litter N collected from plants that were unfertilized and fertilized with 10 g N/m 2 /yr for 5 year s ................................ ................................ 80 3 4 Leaf litter decay constants (k) vs. leaf percent C, cell solubles, and cellulose for 11 vascular plants species ................................ ................................ ............ 81 3 5 (Left) Percent initial leaf litter lignin of Betula nana collected from four sites that have been fertilized for zero, five, 14, or 20 years. (Right). Decay constant, k, of Betula nana leaves ................................ ................................ ...... 82 3 6 Comparison of the influence of litter quality/quantity and litter quality/quantity with microenvironment in mean communit y weighted litter decay constant (k, 1/yr) across three arctic plant communities. ................................ ....................... 83 3 7 Soil % N for each site vs. decay constant (k), initial C remaining, initial N remaining, and the proportion of initial C to N remaining of the common substrate ................................ ................................ ................................ ............. 84

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11 4 1 Aboveground biomass (g/m 2 ) from shrub tundra harvested in the eighteenth year of treatment (C = control, NP = Nitrogen and phosphorus additions, T = warming manipulation, and NP + T = Nitrogen an d phosphorus additions plus warming manipulation) ................................ ................................ ..................... 103 4 2 Aboveground vascular net primary production (ANPP) across treatments and separated by plant parts ................................ ................................ ................... 104 4 3 Vascular plant biomass dominance diversity curves sampled 18 years after initiation of treatments. ................................ ................................ ..................... 104 4 4 Total ecosystem C a nd N pools separated by above and belowground for each treatment. ................................ ................................ ............................... 105 4 5 Ecosystem C and N pools after 18 years of experimental manipulati on of nutrients and temperature ................................ ................................ ................ 106 4 6 Proportional allocation of vascular plant biomass, C, and N to different plan t parts across each treatment ................................ ................................ ............. 107 4 7 Carbon to nitrogen ratios of pl a nt tissues across treatments. .......................... 108 4 8 Percent biomass, C, and N allocation am ional group across treatments. ................................ ................................ ................................ ........ 109 A 1 Annual ambient snow d epth for each plant community. ................................ .... 117 B 1 Initial ma ss, C, and N remaining from litter bags that contained either natura l or fertilized plant species ................................ ................................ .................. 119 B 2 Initial mass, C, and N remaining from litter bags that contained either natu ral or fertilized pl ant species ................................ ................................ .................. 120 B 3 Initial mass, C, and N remaining from litter bags that contained either natura l or fertilized plant species ................................ ................................ .................. 121 B 4 Initial mass, C, and N remaining from litter bags that contained either natu ral or fertilized plant species ................................ ................................ .................. 122 B 5 Leaf litter decay constants (k) vs. leaf percent C, cell soluble, and cellulose for 11 vascular plant species ................................ ................................ ............ 123 B 6 Stem litter decay constants (k) vs. percent cellulose for four deciduous shrub species incubated for t hree years in a common garden ................................ ... 124

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12 Abstrac t of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy PLANT SOIL FEEDBACKS WITH CHANGING VEGETATION STRUCTURE AND COMPOSITION IN A WARMING ARCTIC By Jennie DeMarco December 2011 Chair: Alice Harmon Major: Botany Climate warming in the arctic may shift vegetation from graminoids to deciduous shrub dominance, potentially altering the structure and function of the ecosystem through in fluences on the abiotic and biotic controls over carbon (C) and nitrogen (N) cycling. Shrubs may influence the soil microclimate and litter inputs to the soil, altering the rate at which nutrients are cycled back to soil and thus become available to plant s. In the arctic tundra near Toolik Lake, Alaska, we experimentally manipulated snow depth across three arctic plant communities that varied in their initial shrub abundance to test whether the snow that accumulates around arctic deciduous shrubs alters t he soil microclimate enough to increase soil N availability and nutrient turnover. Specifically, we tested whether the addition of snow provides a more favorable microclimate for N mineralization and litter decomposition. In addition we investigated the influence of soil organic matter (SOM) and litter quality on N availability and nutrient turnover. We found that winter snow addition increased soil N availability in the summer only through increased rates of N mineralization but had no effect on litter decomposition rates. In addition, SOM quality was greatest in the plant community with the highest abundance of shrubs resulting in faster turnover and greater N availability.

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13 In contrast, litter decomposition rates were slower in shrub dominant communi ties resulting in slower nutrient turnover and higher retention of N on the litter. We conclude, that on a short time scale shrub interactions with snow increase N availability, at least in the summer, at a time when plants are more active. In addition, our study suggests that a transition to a shrubbier arctic could lead to retention of N in the litter layer and an increase in N availability in the soil potentially leading to a positive feedback to increased shrub growth.

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14 CHAPTER 1 INTRODUCTION The gl obal climate is warming with the arctic region warming at a faster rate (Overpeck et al. 1997, Serreze and Francis 2006, Kaufman et al. 2009). Warmer temperatures in the arctic may alter ecosystem structure and function and lead to a positive feedback to global and regional climate change. Arctic systems are nitrogen (N) limited due to slow decomposition rates driven by cold temperatures. Manipulation experiments within this region have shown that increase d temperature stimulates decomposition which can result in more nutrients available for plants (Chapin et al. 1995, Hobbie 1996, Aerts et al. 2006a). Fertilization experiments have shown that arctic plants resp ond positively to added (N) however, plant species respond differently with the deciduous shr ub Betula nana having a more positive response (Chapin and Shaver 1996). Thus an increase in t emperature can drive decomposition of soil organic matter (SOM) increasing nutrient availability leading to a shift in plant species composition that is dominat ed more with deciduous shrubs. Warming can also lead to increase in shrubs indirectly by causing thawing of permanently frozen soil (Schuur et al. 2007). There is evidence that shrubs are expanding into the arctic region. Current and historical photo s of Northern Alas ka show that deciduous shrubs ( Betula Salix and Alder ) have increased in abundance and/or size ov er the last 50 years (Sturm et al. 2001b, Tape et al. 2006) Satellite data have recorded an increase in photosynthetic activity of terrest rial vegetation in northern latit udes over the past two decades and some of this enhanced productivity has been attributed to an increase in growth of shrubs (Jia and Epstein 2003, Stowe et al. 2004, Jia e t al. 2009, Forbes et al. 2010)

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15 Pollen records in dicate that past warming has led to movement of trees and shrubs north (Payette et al. 1989, Oswald et al. 1999). What are the implications of increased shrubs in the arctic? Changes in species composition to more shrub dominance can have dramatic affec ts on how the arctic will influence the global carbon (C) cycle. In the past, the arctic region has been a sink for C because litter inputs have exceeded decomposition rates. Cold temperatures limit decomposition of SOM resu lting in a buildup of organic C that can be greater than 12,000 years old (Ping et al. 1997). However, with a shift to more shrub dominated tundra, it is unclear whether the arctic will continue to serve as a sink for C and may even switch to a source of C to the atmosphere. An increa se in shrubs could lead to an increase in plant productivity and biomass resulting in more uptake of atmospheric CO 2 and the storage of more C aboveground in woody tissue or belowground in rhizomes (Shaver and Chapin 1991), roots, and ectomycorrhizal fungi (Clemmensen et al. 2006) resulting in a negative feedback to climate change. In addition, more woody stems associated with shrubs could mean more C stored in the soil because stems decompose slowly (Hobbie 1996). However, shrub lands have a lower albe do than tundra which can lead to an increase in absorbed solar radiation during the snow free period resulting in a positive feedback to climate change (Chapin et al. 2005) In addition, it has also been shown that d eciduous shru bs in fertilized tundra cycl ed C and N faster than control tundra resulting in a net loss of deep soil C over a 20 year period (Mack et al. 2004). Thus, there is a potential for a positive feedback to warming with increased shrub cover. Since the arctic stores 20 30 percent of the total amount of

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16 terrestrial soil bound C (McGuire et al. 2009) it is important to better understand the mechanisms behind these potential feedbacks to climate change. The mechanisms that drive shrub growth and expansion are not well understood. The snow s hrub hypothesis suggests that shrubs enhance their dominance through a positive feedback mechanism where shrubs increase winter soil temperatures and enhance decomposition by trapping snow and thus increase mineralization and nutrient availability (Sturm e t al. 2001a) (Fig. 1 1) Because, shrubs respond positively to increased nutrient availability (Chapin and Shaver 1996), increased shrub growth and expansion may create a positive feedback. The degree of the positive feedback is increased with warming be cause warmer temperatures accelerate decomposition (Hobbie 1996) resulting in more nutrients available leading to further shrub growth. Although it has been well document that snow around shrubs is deeper than non shrubby areas and deeper snow results in warmer soil temperatures, it has not been directly tested that soil under snow trapped by shrubs mineralizes more N than non shrubby systems. It is also not clear whether shrubs utilize the N that has been mineralized over the winter. Alternatively, shr ubs may also have effects on N release that are independent of their effects on winter soil temperatures and may differ in the direction of their effects. In moist acidic tundra the deciduous shrub, Betula nana allocates 79 percent of its total biomass t o new and old stems (Shaver et al. 2001) which decompose three times slower than their leaves and one to eight times slower than leaves and stems from graminoids and evergreen shrubs found within the Alaskan arctic tundra (Hobbie 1996). Thus a species comp osition shift to more deciduous shrub dominance may alter nutrient

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17 turnover through biotic controls by producing larger quantities of litter that is of lower quality (Hobbie, 1992; Buckeridge et al., 2010) possibly slowing nutrient turnover in litter resul ting in a decrease in plant available N and a negative plant soil feedback that does not promote further shrub expansion (Fig. 1 1) These two potential mechanisms lead to the question of whether changes in microclimate or changes in the chemical composi tion ( quality ) and the amount ( quantity ) of litter will have a stronger control on litter decomposition and nutrient release. In arctic and boreal systems, differences in litter quality among species and SOM quality across different vegetation types can have a larger effect on N mineralization than differences in temperature (Flanagan and Van Cleve, 1983; Giblin et al., 1991; Nadelhoffer et al., 1991; Hobbie, 1996 ). This pattern has also been seen in alpine tundra of the South Western French Alps, where Baptist (2010) found that species specific differences in litter quality had a stronger control over decomposition rates than differences in timing of snowmelt which is associated with differences in snow depth and soil temperature. Although there is much evidence to suggest that shrubs can influence their environment to alter key biogeochemical processes that control plant nutrient supply, there have been no published studies to date that have directly tested the effect of added snow (at the depth that wo uld be trapped by shrubs) or increased shrub cover on N turnover in soil or litter The goal of the study for the second and third chapters of this dissertation w ere to understand the relative importance of mechanisms through which arctic deciduous shrub s affect N dynamics by investigating how differences in soil microclimate, litter quality, and nutrient availability influence net N mineralization and litter decomposition

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18 two of the main pathways by which organic N is made available for plant uptake. Th is study used experimental manipulations of snow across three different arctic plant communities to directly test these potential mechanisms In addition to understanding mechanisms that drive shrub expansion, I was also interested in understanding how c limate driven changes in environment such as nutrient availability and warming would influence ecosystem structure and function in currently established riparian shrub tundra. There are few, if any, studies that directly test shrub tundra responses to war ming and added nutrient s in Alaskan shrub tundra even though shrub dominated communities make up 22% of the land cover in the Arctic tundra ecosystems of Alaska and 36.5% of the non glaciated Pan Arctic tundra biome (Walker et al. 2005). Those studies tha t have tested the response of shrub tundra to warming and nutrient additions have been concentrated in sub arctic systems in Northern Sweden where the dominate shrubs are evergreen and are compositionally more similar to heath tundra communities in Alaska than riparian shrub communities (Parsons et al. 1994, Michelsen et al. 1996, Molau and Alatalo 1998). In contrast, shrub tundra communities in Northern Alaska are dominated by deciduous shrubs, whose functional traits may allow them to respond more rapidl y to environmental change compared to evergreen shrubs. Understanding how Alaskan shrub tundra communities will respond to environmental change is becoming even more critical as these communities are currently expanding (Tape et al. 2006, Forbes et al. 20 10) and are expected to continue to increase with future warming (Walker et al. 2006). The objective of the fourth chapter of this dissertation was to understand controls over plant productivity and C and N storage in shrub tundra ecosystems in order to

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19 make inferences about how these systems will respond to environmental change. To investigate whether plant productivity is limited by temperature, nutrients, or an interaction between the two we examined the plant and ecosystem response from the longest r unning (18 years) nutrient and warming experiment in Alaskan arctic riparian shrub tundra ecosystems. In addition, we tested whether these environmental changes altered total ecosystem N and C storage. Figure 1 1. Potential pathways by which shrubs enhance their dominance through a positive feedback mechanism where shrubs alter the biophysical and biogeochemical environment resulting in increased nutrient availability.

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20 CHAPTER 2 THE EFFECTS OF SNOW, SOIL MICROENVIRONMENT, AND SOIL ORGANIC MATTER QUA LITY ON N AVAILABILITY IN THREE ALASKAN ARCTIC PLANT COMMUNITIES 1 Background Arctic air temperatures in the last decade have been the warmest on record and are expected to continue to rise at a faster rate than the rest of the world (Overpeck et al. 1997, ACIA 2004, Serreze and Francis 2006) Warmer temperatures can have profound effects on biogeochemical processes important for ecosystem function, potentially leading to changes in species composition and ecosystem structure (Chapin et al. 1995, Walker et al. 2006). Warmer air temperatures can cause an increase in deciduous shrub growth (Bret Harte et al. 2001) both directly and indirectly through stimulation of SOM decomposition and mineralization of organically bound nitrogen (N), resulting in more plant available N (Nadelhoffer et al. 1991, Hobbie and Chapin 1996) Arctic plant species respond differently to N fertilization: the deciduous shrub Betula nana responded more strongly over a five to 20 year time scale than graminoids such as Eriophorum vagina tum the tussock forming sedge typic of upland tundra ecosystems throughout the arctic (Chapin et al. 1995, Chapin and Shaver 1996, Shaver et al. 2000, Mack et al. 2004) In addition, warming can also cause thawing of permanently frozen soil, leading to c hanges in topography that may promote the establishment of deciduous shrubs (Schuur et al. 2007) 1 Reprinted with permission from DeMarco, J., M. C. Mack, and M. S. Bret Harte. 2011. The effects of snow, soil microenvironment, and soil organic matter q uality on N availability in three Alaskan Arcitic plant communities. Ecosystems 14 :804 817.

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21 Changes in vegetation composition from graminoid dominance to increasing shrub dominance within the arctic may already be underway (Payette et al. 1989, Myneni et al. 1997, Oswald et al. 1999, Sturm et al. 2001b, Zhou et al. 2001, Stowe et al. 2004) and it has been hypothesized (Sturm et al. 2001a) that these changes are due to increased shrub growth in response to increased soil temperatures, which enhance N miner alization. Changes in ecosystem structure and function could result in a positive feedback that accelerates the transition to shrub tundra. Plant species traits can influence nutrient cycling by altering some of the major controls over soil N transforma tions: chemical composition of SOM and soil microclimate (Chen and Stark 2000, Mack and D'Antonio 2003) Species specific differences in the quality and quantity of plant litter inputs to the soil can influence SOM quality (Pastor and Post 1986, Hobbie 19 92, Wedin and Pastor 1993) Plant species can alter the soil microclimate by changes in canopy architecture, rooting depth, and litter depth deposition (Van Cleve et al. 1983, Matson and Boone 1984, Burke 1989, Wedin and Pastor 1993, Seastedt and Adams 20 01) Arctic shrubs may influence nutrient cycling by altering abiotic and/or biotic controls over soil N transformations. The snow shr ub hypothesis suggests that shrubs can alter the abiotic soil environment via their interactions with snow (Sturm et al 2001a) Tundra areas with taller and more abundant shrubs accumulated greater snow depth due to greater retention of snow fall (e.g. less snow lost to wind events) and trapping of wind distributed snow than tundra areas with less shrubs (Sturm et al. 20 01a, Pomeroy et al. 2006) Snow acts as an insulator that can increase soil

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22 temperature (Brooks et al. 1996, 1998, Grogan and Jonasson 2003, Schimel et al. 2004, Wahren et al. 2005) and the availability of water to soil microorganisms (Coxson and Parkins 1987, Romanovsky and Osterkamp 2000, Mikan et al. 2002) and therefore, potentially regulate the rate at which microbes can mineralize N over the winter. Indeed, winter CO 2 emissions and N mineralization have been found to be higher in soils that had deepe r snow cover (Brooks et al. 1996, Schimel et al. 2004) Furthermore, increasing evidence suggests that microbial activity and mineralization over the winter can provide available nutrients during spring thaw that may influence soil and plant communities t hrough the growing season (Grogan and Jonasson 2003, Buckeridge and Grogan 2008) Therefore, snow accumulation by shrubs could indirectly influence N availability by maintaining warmer soil temperatures in winter, allowing soil microbes to stay active lon ger to mineralize organic substrates and thus potentially supply more N to shrub growth. Snow manipulation studies in the arctic that have increased snow depth 5.5 times ambient show an increase in N mineralization (Schimel et al. 2004, Borner et al. 200 8) ; however, it has not been directly tested whether the moderate amount of snow (< 1 m) that is trapped by deciduous shrubs is enough to result in an increase in available N. Alternatively, shrubs may enhance N availability independent of their effects on winter soil temperatures by altering the quantity and quality of litter and SOM substrates for microbial decomposition and nutrient release (Hobbie 1992, Buckeridge et al. 2010) Furthermore, we know little about the relative importance of snow mediat ed effects versus SOM quality mediated effects on soil nutrient dynamics in arctic shrub tundra systems. In arctic tussock tundra and boreal systems, differences in litter quality among

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23 species and SOM quality across different vegetation types can have a larger effect on N mineralization than differences in temperature (Flanagan and Van Cleve 1983, Giblin et al. 1991, Nadelhoffer et al. 1991, Hobbie 1996) Abiotic influences through changes in the soil microenvironment or biotic influences through changes in the quality and quantity of litter inputs may both be important in influencing N mineralization rates; h owever, the magnitude and time scale of their influence may differ. Changes in microenvironment may occur over relatively short time scales, within a few years, while changes in litter quality inputs and SOM quality would occur over a relatively longer time scale, decades to centuries, as it would take more time for litter inputs to accumulate and be incorporated into the SOM (Shaver et al. 2000) U nderstanding the time scale and relative magnitude of these mechanisms is crucial for understanding how a shrubbier arctic may influence N dynamics and feedback to the global C cycle The goal of my study was to understand the relative importance of mechani sms through which arctic deciduous shrubs could affect N dynamics under realistic levels of snow addition by investigating how di fferences in soil microclimate and SOM quality influence N availability across three different arctic plant communities. My in tent was to isolate the effects of snow from the effects of shrubs on N mineralization. My objectives were three fold: (1) to test whether realistic levels of snow accumulation maintain winter soil temperatures high enough to stimulate microbial activity and increase N availability (2) to compare the relative effects of snow versus shrubs on N availability via effects on the main drivers of N mineralization: SOM quality versus microclimate, and (3) to better understand how shrubs and snow addition influenc e N availability over winter and summer seasons. I hypothesized that 1) the addition of snow would slow temperature

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24 decline in the winter and lead to greater N availability, 2) SOM quality will have a greater effect on N availability than changes in soil microclimate, and 3) the microclimate effects of shrubs on N mineralization would be more pronounced in the winter than in the summer. To test my hypotheses, I measured SOM quality and N availability across three plant communities that represented natural variation across the landscape in shrub abundance. Here I consider SOM quality as an integrative variable that includes both the soil organic matter and the soil microbial community. As an index of N availability, I measured net N mineralization using in situ intact soil cores (DiStefano and Gholz 1986) Incubating cores in situ gives us an estimate of N mineralization under natural field moisture and temperature conditions. To test the effects of snow depth on N availability, I directly manipulated sno w depth, via snow fences, at each of the three sites. To compare the influence of site differences in microenvironment and shrub abundance on the controls over N mineralization, I conducted a reciprocal soil core transplant of intact soil cores between th e three sites. This experimental design enables us to determine the relative long term effect of SOM quality (including the soil microbial community) versus the short term effect of mic roclimate on N mineralization. To understand the importance of season ality on N availability, I measured N mineralization in both the summer and winter, in the snow fence treatments and in the reciprocally transplanted soil cores. Methods Study Area elevation 760m) and the Arctic Long Term Ecological Research (LTER) program sites

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25 in the foothills region of the North Slope of Brooks Range, Alaska, USA. This area was glaciated during the late Pleistocene and includes large areas of Itkillik I (deg laciated ca. 60 000 yr) and Itkillik II (deglaciated about 10 000 yr) glacial drifts (Hamilton 1986) The entire foothills region of the Brooks Range is treeless and underlain by continuous permafrost, 250 300 m thick (Osterkamp and Payne 1981) Mean annu al air temperature is around 10C, with monthly mean summer temperatures from 7 12 C. Annual precipitation is 318 mm, with 43% falling in the winter as snow (http://ecosystems.mbl.edu/ARC). Average snow depth is 50 cm, although snow distribution is var iable due to redistribution by wind. Snow melt usually occurs in May. In the fall of 2005, three sites were selected that varied primarily in deciduous shrub abundance, hereafter referred to as low, medium and high shrub sites. Sites were chosen to h ave similar state factors (climate, relief, parent material, and time) but varied in the abundance of deciduous shrubs (Jenny 1994) The sites represent a natural gradient of increasing shrub abundance because the same species of deciduous shrubs ( Betula nana and Salix pulchra ) are found at all three sites (except S. richardsonii which is found only at the medium shrub site); however, their percent cover increases from 15 to 94 % (Table 1) My sites are within 1 km of each other, and have similar parent material, and time since last glaciation (Itkillik I, deglaciated ca. 60 000 yr), and regional climate, although microclimates vary across sites due to differences in slope and aspect. The low shrub site is located on top of gently rolling hills, while th e medium and high shrub sites are located in depressions along water tracks of ephemeral streams fed by spring snowmelt. Elevation changes from about 764 m at the

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26 low shrub site to 741 m at the medium and high shrubs sites. My selection of sites is usefu l to aid in understanding how a shrubbier arctic may influence nutrient cycling. My low shrub abundance site is located in moist acidic tussock tundra where the vegetation consists of approximately equal biomass of graminoids ( Eriophorum vaginatum and C a rex bigelowii ), dwarf deciduous shrubs ( B. nana Vaccinium uliginosum and S. pulchra ), evergreen shrubs ( Ledum palustre ssp. decumbens and V. vitis idea ), and mosses ( Hylocomium splendens Au l acomnium turgidum Dicranum spp., and Sphagnum spp .) (Shaver a nd Chapin 1991) In Alaskan upland tundra, tussock tundra is the most abundant vegetation type. In my medium shrub abundance site, vegetation consists of graminoids (primarily C. bigelowii ), deciduous shrubs ( B. nana V. uliginosum S. pulchra and S. ric hardsonii ), and mosses ( H. splendens and Dicranum spp. ) My high shrub abundance site has predominantly deciduous shrubs ( B. nana S. pulchra and some Potentilla fruticosa ) with some evergreen or wintergreen shrubs ( V. vitis idaea and Linnaea borealis ), forbs ( Polygonum bistorta Petasites frigidus Stellaria longipes Valeriana capitata and Artemisia alaskana ), graminoids ( Poa arctica C. bigelowii and Calamagrostis canadensis ), and mosses ( Sphagnum spp. and H. splendens ). Snow Manipulation To determin e the influence of increased snow depth on N availability, snow fences (1.5 m high and 62 m long) were set up in the fall of 2005 at the low and medium si tes to manipulate snow depth. For the high site, the patchy nature of the shrub stands made it necess ary to set up two separate snow fences (1.5 m high and 32 m long) in patches with similar shrub composition and density. My purpose for adding snow was to simulate the amount of snow that might be trapped by deciduous shrubs; therefore,

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27 the height of the snow fences was selected to match the maximum shrub height within the region Winds are predominantly from the south in the winter, so the fences were oriented E W, and snow drifts accumulated on the northern side of the fences. Two treatments (control=amb ient snow and drift=manipulated snow) were set up at each site. The drift plots were set up 4 m from the fence on the northern side of the fence, because this was the zone of maximum snow accumulation. At the low and medium sites, the control plots were set up on the southern (non drift) side of the fence, 10 m from the fence at the low site, and 7 m from the fence at the medium site. These buffer zones were left to prevent the control from being exposed to snow trapped by the fence. At the high shrub s ites, control plots were located in line with one of the fences, beginning 5 m from its end, and in 3 discontinuous blocks of tall shrubs to the south (control side) of the fence, beginning approximately 15 m from the fence. This arrangement was chosen be cause the cover of tall shrubs was discontinuous on the southern (control) side of the fences. For all sites, plots on the drift side of the fences were located in the zone of maximum snow accumulation, which was relatively uniform. Within each treatment 18 2 by 10 m plots, with 1 m buffer strips between, were established. For this study, six plots per treatment (n=6) were randomly assigned to measure N mineralization and nitrification. Remaining plots were used for additional experiments. Maximum s now depth was measured every meter in April of 2006 and every 2 m in 2007 along two 12 m transects running parallel to the snow fences at the control and drift plots for each site. Values from the two transects were then averaged. In 2007,

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28 snow depth was not measured on the control side for one of the snow fences from the high site. Only values for the vicinity of the experimental plots are presented here. Annual depth of soil thaw was measured in 2005, using a metal probe, at every meter along a 60 m transect within the control and snow addition plots at the low and medium shrub sites (n=60). For the high shrub site, thaw depth was measured every meter along two separate 30 m transects that were along the two 30 m long snow fences located at both the control and snow addition plots. Soil temperature, at 5 cm within the organic layer, was measured continuously (1 3 h intervals) from June 2006 June 2007 in each study plot (n= 3 4) by using Ibutton temperature data loggers (IButtonLink, LLC, East Troy, W I). Weekly mean soil temperatures were calculated from mid June 2006 through mid May 2007 for all treatments and sites. Annual so il temperatures were calculated for each site and treatment and included 336 days of measurements. Characterizing ecosystem s tructure Live aboveground biomass in each site was determined by harvesting all plant species within 12 10 by 40 cm quadrants at the low shrub site. For both the medium and high shrub sites, the understory was removed from six similar 10 by 40 cm quadrant s nested within a 50 by 50 cm quadrant, from which the overstory was removed (See Appendix). From the harvested species, we separated out height responsive deciduous shrubs from those shrubs that do not have the physiological ability to substantially incr ease their height. It is these tall shrubs that have the potential Betula nana Salix pulchra S. glauca and S. richardsonii are the only species that have the capacity to grow tall. Only total biomass and deciduo us tall shrub biomass are presented here.

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29 To estimate belowground biomass, rhizome biomass was determined by harvesting the same 10 x 40 cm quadrants used to determine aboveground biomass according to methods described i n (Bret Harte et al. 2008); while r oot biomass within the organic layer of each plot was measured in 5 by 5 cm soil monolith s that extended down to the surface of the mineral layer (see Appendix). All biomass was dried at 60 C for a minimum of 48 hours before weighing and is expressed on an area basis. Soil bulk density was determin ed using a separate set of soil monoliths sampled in July of 2007. Soil pH was measured on mineral soils, collected in June and July of 2007, by mixing a 1 to 2 slurry of soil and DI water and measuring withi n 30 minutes using a pH meter (Thermo Orion 250A+, Orion Research, Inc, Boston, Massachusetts, USA). Soil N dynamics I used the in situ soil incubation method (DiStefano and Gholz 1986, Hart and Firestone 1989) to assess (1) site differences in net N min eralization and nitrification, (2) snow effects on net N mineralization and nitrification, and (3) SOM versus microclimate effects on net N mineralization and nitrification. At each site (Low, Medium, and High) and within each treatment (Ambient and Snow addition) at each plot (n = 6), five soil cores were removed from the top 10 cm of the organic layer in either June or September of 2006. Soils were sampled with a 5 cm diameter metal corer; new frost boils and Eriophorum vaginatum tussocks were avoided. One core (initial) was removed from the ground, chilled, and processed (within 48 h of sampling) for pools of inorganic N (N NH 4 + and N NO 3 ), dissolved organic N (DON), chloroform fumigated microbial biomass N (MB N), bulk soil percent C and N, and soil moisture. The other four cores (final) were placed in a 12 cm long and 5 cm diameter PVC tube and capped

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30 at the top with one resin bag, and at the bottom with two resin bags. Resin bags were made of nylon that was soaked in 1.2M HCl for 2 h before filli ng with ion exchange resins. Bags contained 17 g fresh weight (49.4% moisture, 8.28 g oven dry equivalent) of mixed bed ion exchange resins (IONAC NM 60 H + /OH form, type I beads 16 50 mesh; J. T. Baker, Phillipsburg, New Jersey, USA). One core was then returned to its original hole in the control plot, one core was transplanted to a randomly assigned snow addition plot within the same site for incubation, while the other two remaining cores were each transplanted to a randomly assigned control plot from one of the other two sites for incubation. By doing this, I held the substrate constant but altered the environment of the incubation. All final cores were incubated for 74 days in the summer (mid June 2006 Sept 2006) and 280 days in the winter (Sept 20 06 mid June 2007) to look at seasonal affects on N availability. At the end of the incubation periods, soil cores were removed and the soil was processed (within 48 hours of sampling) for pools of N NH 4 + and N NO 3 DON, MB N, bulk soil percent C and N, a nd soil moisture in exactly the same way as the initial core. Resin bags were removed from cores and frozen until processing (see below). Net N mineralization was calculated as the difference between the DIN (NH 4 + and NO 3 ) in the initial soil core and t he DIN in the final soil core plus the DIN accumulated on the middle resin bag. Net N nitrification was calculated as the difference between the nitrate in the initial soil core and the nitrate in the final soil core plus the nitrate accumulated on the mi ddle resin bag. The percent of mineralized N that was nitrified was calculated by dividing the N nitrified by the amount of N that was mineralized and multiplying by 100. Nutrient pool sizes and annual net N

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31 mineralization were calculated using the soil bulk density obtained from soil harvest conducted in 2007. Prior to analysis, soils were homogenized by hand and the >2 mm diameter fraction (e.g., roots, rhizomes, course woody debris, and rocks) was removed. Soil water content was calculated by subtract ing the dry weight of the soil (60 C for 48 h) from the wet weight of the soil and then dividing by the dry weight of the soil. To determine bulk soil percent C and N, a subsample of <2mm soil fraction was dried at 60 C for 48 h, ground to a fine powder on a Wiley mill with a #40 mesh screen, and then analyzed using an ECS 4010 elemental analyzer (Costech Analytical, Valencia, California, USA). Pools of dissolved inorganic N (N NH 4 + and N NO 3 ) were measured by extracting 10 g of fresh soil with 50 ml of 0.5 M K 2 SO 4 The soil slurry was agitated on a shaker table for 2 h, allowed to sit overnight in a cooler, and then vacuum filtered through a Whatman GF/A filter. Filtrate was frozen until analyzed colorimetrically, on segmented flow autoanalyzer (Astor ia analyzer, Astoria Pacific, Inc, Clackamas, Oregon, USA). Dissolved organic N (DON) was measured on a subsample of the K 2 SO 4 extract that was digested with a persulfate oxidation digestion procedure (Sollins et al. 1999) prior to colorimetric analysis. Because this digestion procedure converts all forms of N to NO 3 DON was calculated by subtracting the DIN measured previously from the total N that was determined in the digestion procedure. Microbial biomass N was determined using the chloroform fumig ation method. Ten grams of fresh soil was incubated with 100 ml of pentene stabilized chloroform in a glass dessicator for 24 h. Post incubation, soils were extracted with 0.5 M K 2 SO 4

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32 exactly the same way as for DIN. Fumigated extracts were digested usi ng the same persulfate oxidation procedure used for DON analysis. Nitrate was then measured colorimetrically. Chloroform labile N was calculated by subtracting the DON and DIN concentrations from the initial, un fumigated sample from the total N that was extracted from the post fumigated sample. After incubation, resin bags were rinsed with deionized water to remove soil and then extracted with 50 ml of 2N KCl. Resins and KCl were agitated for 1 h and then filtered through a pre leached Whatman #1 filter Filtrate was immediately frozen. At time of analysis, extracts were thawed and measured for N NH 4 + and N NO 3 colorimetrically. Statistical Analyses Properties of ecosystem structure across sites were analyzed using a One way Analysis of Variance (ANOV A) with site as the main effect (JMP 7.0, 2007, SAS) These include aboveground and belowground biomass, soil bulk density, soil percent N and C, C:N ratio, soil C and N stocks, and soil pH. The F statistic, degrees of freedom, and p values are reported. Potassium sulfate extractable soil nutrients (NH 4 + NO 3 DON, and MB N) and seasonal net N mineralization were analyzed using a Two way ANOVA with site and season as the main effects and site by season as the interaction term. Differences in snow depth soil temperature, soil moisture, and net N mineralization across sites and between treatments were analyzed using a Two way ANOVA with site and treatment (ambient and snow addition) as the main effects and site by treatment as the interaction term. Soil organic matter quality effects on net N mineralization were analyzed using a two way ANOVA with soil origin and incubation location as the main effects and soil origin by incubation location as the interaction term.

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33 as used when significance was obtained from ANOVAs. Data were tested for normality (Shapiro Wilks), and ln transformed when necessary to meet the assumptions of ANOVA. Data sets of ammonium and nitrate pools were not normal ly distributed, even when ln tr ansformed and were analy zed using Kruskal Wallis tests. Separate comparisons were made across sites within the same season and across seasons within each site. Results Ecosystem structure across the shrub gradient Aboveground biomass was almost twice as large in the high shrub site than in the medium or the low shrub sites (One way ANOVA, Table 2 1, F 2,21 = 19.39, P <0.0001), primarily due the greater biomass of deciduous shrubs ( Table 2 1, F 2,21 = 63.68, P <0.0001). Total belowground biomass was also g reatest in the high shrub site (F 2,21 = 3.75, P = 0.04). Rhizomes made up the largest portion of the belowground biomass, with the high site having the greatest rhizome biomass (F 2,21 = 5.80, P <0.01). Root biomass did not differ among sites and most bel owground biomass was found in the organic layer (Appendix A 1). The medium and high shrub sites had SOM C and N stocks that were 2 3 times greater than stocks of the SOM C and N in the low shrub site (Table 2 2). This difference was primarily driven by di fferences in soil bulk density among the sites, since concentrations of SOM C (Table 2 2) and soil depth (Table 2 1) did not differ among sites. The C:N ratio was twice as high (41 3) at the low shrub site than at the medium (22 1) and high (18 1) sh rub sites. Mineral soil pH was 0.5 units more acidic at the low shrub site than at the medium and high shrub sites (Table 1, F 2,27 = 7.07, P <0.01).

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34 There was both a site difference (Appendix A 2; F 2,30 = 50.82 P <0.0001) and a seasonal difference (F 1, 30 = 18.79 P <0.001) in the ammonium (NH 4 + ) concentrations. The medium and high shrub sites had 8 19 times respectively higher soil (NH 4 + ) concentrations than the low shrub site in June and 4 10 times higher concentrations than the low shrub site in Sept ember leading to a 14 28 fold difference in standing NH 4 + pools in June and a 7 14 fold difference in standing NH 4 + pools in September (Appe ndix A 2 2 2 2 = 12.29, P <0.01). Dissolved organic nitrogen (DON) and microbial biomass nitrogen (MB N) concentrations followed a similar pattern as NH 4 + concentrations with both a site (F 2,30, = 8.67, P <0.003; F 2,30 = 5.38, P <0.01 ) and a season difference (F 1,30 = 5.42, P <0.01; F 1,30 = 7.11, P <0.01), and site by season interaction (Appendix A 2, F 2,30 = 4.49, P = 0.02; F 2,30 = 3.62, P = 0.04). Nitrate (NO 3 ) concentrations were low and did not differ among sites or between samp ling dates. The high shrub site mineralized more N in both the summer and the winter than the low and medium shrub sites (Two way ANOVA, site: F 2,28 = 24.85, P <0.0001; Table 2 1). More N was mineralized over the winter than over the summer for the high shrub site only (season: F 2,28 = 13.11, P = 0.001; Table 2 1 ). There was no significant site by season interaction (site x season: F 2,28 = 1.11, P = 0.34). Net N nitrification and the percent of mineralized N that was nitrified did not differ among site s or seasons (data not shown). Snow manipulation The snow fence produced a maximum (ambient plus addition) snow pack in our plots that was, on average 149 158 and 172 cm deep in 2006 and 166, 175, and 133 deep in 2007 for the low, medium and high shrub sites, respectively (Fig. 2 1 ). In both years there was a significant difference between treatments within the same site but no

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35 difference across sites within the same treatment ( Two way ANOVA, 2006 site: F 2, 1 8 = 0.26 P = 0.78 ; treatment: F 1 1 8 = 430.39 P < 0.0001; 2007 site: F 2,8 = 1.54 P = 0.27 ; treatment: F 1 ,8 = 76.02 P < 0.0001). There was however a significant site by treatment interaction for 2006 data only (2006 site x treatment: F 2 1 8 = 11.61 P < 0.001; 2007 site x treatment: F 2 ,8 = 2.12 P = 0.18). Snow addition increased average winter soil temperatures by 3 1, and 0.5 C ( 4.8 0.11, 2.7 0.72, 2.9 0.82; Mean SE) and summer soil temperatures by 0, 1, and 2C (4.9 0.44, 7.0 0.62, 8.0 0.33; Mean SE) in the low, medium, and h igh shrubs sites, respectively (Fig. 2 1; Winter site: F 2, 14 = 17.33 P = 0.0001 ; treatment: F 1 14 = 15.44 P < 0.01; site x treatment: F 2 14 = 2.80 P = 0.09; Summer site: F 2, 14 = 8.00 P < 0.01 ; treatment: F 1 14 = 5.63 P = 0.03; site x treatment: F 2 14 = 2.16 P = 0.15). Soil moisture in the snow addition treatments was only measured in June 2006 and showed a trend of increased soil moisture (5.9 1.6, 4.2 0.3, and 5.5 0.3 g H 2 O.g 1 soil; mean SE) at the low, medium, and high shrub sites) compare d to the ambient snow sites ( 3.1 0.4, 4.0 0.3, and 5.1 0.4 g H 2 O.g 1 soil; mean SE) with the low shrub site having the largest increase in soil moisture (2 Way ANOVA, site F 2,29 = 1.4, P = 0.25; treatment F 1,29 = 3.6, P = 0.07; site x treatment F 2, 29 = 1.9, P = 0.17) The addition of snow increased N mineralization in the summer (F 1,2 = 6.0, P = 0.02) but did not affect N mineralization in the winter (F 1,2 = 1.0, P = 0.29) and did not interact with site (Summer F 1,2 = 0.9, P = 0.42, Winter F 1,2 = 0.2, P = 0.80; Fig. 2 ). Net nitrification was not altered by the addition of snow during either season, but within the 2 2 = 8.05, P = 0.02). With the addition of snow, the C:N ratio became ne gatively correlated

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36 with summer net n mineralization (r 2 = 0.303, p = 0.01); while, the positive relationship found in the control between summer nitrate pool, C pool, soil moisture and net N mineralization no longer held true (Appendix A 3 ). Reciprocal soil core transplant experiment During both summer and winter, SOM quality, but not soil microclimate, had a significant effect on N mineralization rates (soil origin effect: Summer F 2,6 = 32.2, P = 0.001, Winter F2,6 = 0.5, P = 0.0008). There was no sig nificant interaction between soil origin or site of incubation during either season (Summer F 1,2 = 1.4, P = 0.24, Winter F2,6 = 0.5, P = 0.71). Soils from the high shrub site mineralized more N than soils from the medium and low sites, regardless of wher e they were incubated (Fig. 2 3). Soils from the high shrub site also mineralized more N in the winter when compared to the soils from the medium and low shrub sites but only when high shrub soils were incubated at the medium and high shrub sites (Fig. 2 3). Net nitrification and the percent of mineralized nitrogen that was nitrified were also not significantly different when incubated in the other sites (data not shown). Discussion Snow addition effects on N availability Contrary to the snow shrub hypoth esis I was unable to detect an effect of snow addition on winter ne t N mineralization at any of my experimental sites despite the fact that the addition of snow increased winter soil temperatures by an average of 3, 1 and 0.5 C at the low, medium, and hi gh shrub sites, respectively. Surprisingly, I found that summer, not winter, net N mineralization was positively affec ted by adding snow at two of my three sites. The effect of snow on summer mineralization was microclimatic: by transplanting soil from am bient snow plots to s now addition plots in spring, I controlled

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37 for any changes to the SOM that may have occurred by winter snow additions, isolating the effects of moisture and temperature. The effects of added winter snow on summer mineralization have been variable in other arctic studies. Schimel et al. (2004) found that after 4 years of adding snow at levels 5 times ambient, soils that had experienced increased snow cover over the entire experiment switched from immobilizing to mineralizing N during the growing season. By contrast, Borner et al. (2008), after 6 years of adding snow at 6 times ambient, found no effect of added snow on summer N mineralization rates These studies differ from mine in that they measured the integrated effects of winter an d summer snow addition, while I isolated the microclimate effects of snow addition by moving ambient soils into snow addition plots, showing that on a short time scale changes in microclimate can result in changes in soil nutrient turnover. The lack of response of N mineralization rates to winter soil warming was unexpected and may be explained by a number of different factors. First, inorganic N released during mineralization may have been immediately remobilized by microbes during the winter incubati on or at the time of spring thaw (Schimel et al. 2004) Second, the moderate increase in temperature may not have been enough to drive significant changes in microbial activity and result in an increase in N mineralization rates. Even with the addition o f snow, soil temperatures were still very cold and remained at or below 5C for most of the winter at all three sites, reaching as low as 8C at the medium and high sites and 10C at the low sites. Schimel et al. (2004) measured an increase in winter N mineralization with the addition of snow, but, their total snow pack of 3 m maintained soil temperatures at 5C or above for most of the winter.

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38 I was surprised to find that during the winter of 2006 the ambient snow depth at my high shrubs site was ac tually lower than the ambient snow depths at the low and medium shrub sites, which is counterintuitive to the idea that t aller shrubs trap more snow. I analyzed two additional years following the transplant experiment and found that out of all four years only in 2006 was the snow depth lower at the high shrub site compared to the low shrub site. In 2007 and 2008 there was no difference in snow depth across the sites and in 2009 the high shrub site had substantially higher depths than both the medium and h igh shrub site (Fig. A may vary interannually depending on the amount of snow fall and the number or intensity of wind events that can redistribute snow. Regardless of the differences in ambient snow depths, I have sh own that when the snow level is brought up to the same depth across all sites it has no effect on winter and a positive effect on summer net N mineralization at least two of my sites. My net N mineralization values are higher than what others have reporte d for in situ incubations from similar ecosystem type within this region (Giblin et al. 1991, Schimel and Bennett 2004, Schimel et al. 2004, Borner et al. 2008) and may reflect differences in methodologies used to determine net N mineralization. The burie d bag technique can provide lower rates of net N mineralization than the intact soil core method (Hart and Firestone 1989) because inorganic nutrients released from mineralization cannot be leached from the soil and are therefore available to be remobilize d by soil microbes. In addition, the length of incubation can influence net N mineralization rates because nutrients are simultaneously being mineralized and immobilized during the incubation making it difficult to compare rates across studies.

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39 My data su ggest that on a short time scale moderate snow addition is important in influencing N dynamics not because of the direct effects it may have on winter soil temperatures but because of the carryover effect winter snow ha s on summer soil microclimate. Warme r soil temp eratures may help explain why I found higher rates of net N mineralization in the snow addition treatment. Warmer winter soil temperatures under deeper snow could be carried over into the summer, resulting in warmer summer soil temperatures beca use less energy is required to warm and thaw the soil during the summer (Seppala 1994, Stieglitz et al. 2003, Sturm et al. 2005) Although, there was no significant difference in mean summer soil temperature between treatments there were differences in tr eatments early in the season following spring thaw. Because my soil cores were incubated for the entire season I am unable to separate out the effect that early season warming may have on net N mineralization. Alternatively, the h igher rates of N mineral ization measured in the snow addition site may have been driven by differences in soil moisture associated with adding snow or an interaction between soil temperature and moisture. Soil moisture in June was greatest in the snow addition treatment at the l ow shrub site supporting this potential mechanism. How this realistic snow increase will influence N mineralization over a longer time scale is unknown. Soil organic matter quality effects on N availability In my reciprocal soil tr ansplant experiment, I i solated the SOM from each plant community and incubated it in another microenvironment to separate out the short term microclimate effects on N dynamics from more long term SOM effects. Given the difficulties of measuring and separating out microbia l comm unity from SOM quality, I chose to consider the SOM as an integrative factor which includes nutrient pool size, relative decomposability as indexed by C:N ratio, and microbial community. Across all

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40 sites and over both seasons, soil from the high shrub sit e mineralized more N than the medium and low shrub sites regardless of where it was incubated. Mineralization rates were low for the medium shrub soil across all the sites it was incubated, despite having a similar soil C:N ratio as the high shrub site. This difference may be attributed to differences in C quality between the soils and/or differences in microbial communities or activity. Although not significant, the high shrub soils mineralized more N in the low shrub site in the summer, but during the winter mineralized more in their site of origin. This suggests that the summer soil microclimate at the low shrub site may be more favorable for mineralization once SOM quality limitations are removed. Soil microclimate versus soil organic matter quality effects on N availability My study demonstrates that differences in SOM quality can drive larger differences in net N mineralization than changes in soil microcli mate of the magnitude of what I saw across our three sites. Microclimate differences across m y sites were small. The soil temperatures at the medium and high shrub sites were 1 C warmer in the summer and 4 C warmer in the winter compared to the low shrub site. This small change in microclimate was not enough to increase net N mineralization ra tes once we controlled for differences in SOM quality. The changes in soil temperature I saw with the addition of snow were similar in magnitude to the differences I saw across our unmanipulated sites. With the addition of snow, winter soil temperatures increased by 3C at the low shrub site resulting in soil temperatures close to soil temperatures in the ambient high shrub site. If net N mineralization was limited by temperature alone I would expect that net N mineralization rates in the snow addition a t the low shrub site to be similar to net N mineralization rates at the ambient high site. This is not the case. Results from both my snow manipulation and my SOM reciprocal transplant experiments both suggest that

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41 net N mineralization is more strongly l imited by SOM quality than temperature. This is consistent with incubation studies, which show larger effects of site SOM quality on N mineralization than temperature (Nadelhoffer et al. 1991, Weintraub and Schimel 2003) Across our sites I was unable to control for differences in topography. Changes in topography can influence microclimate, hydrology, nutrient movement, and snow distribution, potentially influencing vegetation growth and nutrient cycling (Schimel et al. 1985, Burke 1989) ; indeed, changi ng water movement on an arctic slope was found to alter plant productivity and nutrient content (Chapin et al. 1988, Oechel 1989). My reciprocal soil core transplant results suggest that the quality of SOM has stronger influence on net N mineralization ra tes than the small differences in microclimate that might be due to differences in topography among the sites. These findings are consistent with other studies comparing mineralization rates across vegetation types incubated at different temperatures (Nad elhoffer et al. 1991) and along a toposequenc e (Giblin et al. 1991). In my study, I did not separate site effects from species effects on soil organic matter quality. It is likely that both of these effects are important at different time scales. Topogr aphical influences on hydrology, microclimate, and snow distribution may lead to favorable habitat (such as better soil drainage, warmer temperatures, and greater snow cover) for initial establishment of deciduous shrubs However, over time vegetation inf luences on the abiotic and biotic controls over biogeochemical cycling of nutrients may ensure that shrubs will remain in that area via positive feedbacks to nutrient cycling, such as better quality litter, SOM, and soil microclimate. Understanding these controls is becoming more important with current and future warming within the Arctic because warmer arctic temperatures may increase

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42 growth of already existing shrubs, but also lead to changes in topography (due to thawing of permanently frozen soil), tha t may promote the establishment of deciduous shrubs (Schuur et al. 2007) Implications for feedbacks to climate change Results from my experimental manipulations suggest that changes in arctic deciduous shrub abundance can affect N dynamics through both ab iotic and biotic controls. These controls, however, play out at different time scales. On a short time scale, microclimate had an effect on soil N dynamics, but only during the summer. The summer season is when plants are most actively taking up nutrients so a stimulation of summer N mineralization rather than winter mineralization should increase the coupling of plant and soil processes by synchronizing nutrient availability and plant growth. Thus, the addition of snow could lead to changes in plant com munities by shifting the timing of nutrient availability. Although my study was short term, my results can still be useful to make inferences about how snow and shrubs can influence N mineralization in a changing climate. If these sites are representati ve of the transitions that might occ ur in a warming arctic, then my study suggests that increased dominance of large shrubs could lead to an increase in plant productivity and aboveground biomass, which can increase uptake of atmospheric CO 2 and the storag e of more C aboveground in woody tissue or belowground in rhizomes (Shaver and Chapin 1991) roots, and ectomycorrhizal fungi (Clemmensen et al. 2006) These effects could result in a negative feedback to climate change. My results also suggest, however, that increased dominance of large shrubs may also lead to increased decomposition of SOM and thus a faster cycling of C and N. Thus, there is also a potential for a positive feedback to warming with increased shrub

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43 cover if decomposition of SOM occurs at a faster rate than plant uptake of atmospheric CO 2 Because the arctic stores 20 50% of the total amount of terrestrial soil bound C (McGuire et al. 2009) it is important to better understand the mechanisms behind these potential feedbacks to climate cha nge. In addition, climate change scenarios predict an increase in arctic winter precipitation (ACIA 2004) which could complicate these feedbacks. My results suggest that on a short time scale, increases in winter precipitation can lead to higher rates of summer net N mineralization and nutrients available for plant uptake, potentially leading to greater shrub abundance and a positive plant soil microbial feedback that favors shrub dominance. How an increase in winter precipitation will influence N and C cycling on a longer time scale is still unknown. Here I conclude that on a short time scale, shrub int eractions with snow may play a role in increasing plant available N, primarily through effects on the summer soil microenvironment that increase N availab ility when plants are most active. The quality of SOM matter, however, which can be linked to species specific traits such as litter allocation and litter quality, may be more of a limiting factor in determining mineralization rates of N. Assuming that o ur natural shrub gradient represents the structure and function of future clim ate driven shrub communities, I would expect a shrubbier arctic to have greater aboveground and belowground biomass, higher soil temperatures, and higher quality of SOM that favo rs higher rates of N fluxes. More research is needed to better understand the differences in SOM quality across shrub communities and their controls on N turnover.

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44 Table 2 1. Vegetation and soil characteristics for three arctic plant communities located near Toolik Lake, AK. Means (SE). Superscript letters indicate a significant difference (p<0.05) Sites Ecosystem Characteristics Low Med High Vegetation Canopy height (cm) 4.4 (0.94) 33.6 (1.92) 51.9 (3.23) Deciduous Tall Shrub Biomass (g/m 2 ) 123 a (13) 407 b (74) 927 c (68) Other Biomass (g/m 2 ) 551 (32) 275 (63) 202 (24) Total Aboveground Biomass (g/m 2 ) 674 a (29) 682 a (66) 1128 b (72) Ambient snow depth (cm) 69.7 (4.6) 68.5 (1.5) 52.6 (4.7) Soil Properties Thaw depth (cm) 48.4 (1.04) 33.7 (1.46) 55.2 (2.13) Surface o rgan ic layer depth (cm) 15.6 (2.86) 11.5 (1.11) 14.1 (1.16) Mineral layer depth (cm) 15.6 (4.11) 13.5 (1.55) 11.9 (1.34) pH (mineral) 4.7 a (0.08) 5.2 b (0.14) 5.1 b (0.10) Organic layer s oil moisture (gH 2 0/g ode soil) 4.7 (1.03) 3.4 (0.25 ) 4.4 (0.30) An nual Soil Temperature at 0 5 cm (C) 5.5 a (0.13) 1.8 b (0.63) 1.7 b (0.51) Summer (69 days) 5.0 a (0.48) 5.9 ab (0.85) 5.9 ab (0.39) Winter (267 days) 8.3 a (0.11) 3.8 b (0.56) 3.6 b (0.58) Annual N mineralization (g N/m 2 /yr) 0.6 (0.13) 1.8 (0.35) 3.8 (0.85) Summer 0.1 b (0.10) 0.8 ab (0.19) 1.3 a (0.34) Winter 0.4 ab (0.16) 1.4 a (0.18) 3.2 c (0.75)

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45 Table 2 2. Soil characteristics from the top 10 cm of the organic soil at three sites near Toolik Lake, AK that varied in shrub abundance (low, medium, and high) Bulk Soil Low Medium High F P Bd (g /c m 3 ) 0.03 a (0.01) 0.06 b (0.02) 0 .0 5 ab (0.01) 4.42 0.03 C (%) 39.62 a (1.28) 38.95 a (0.77) 37.77 a (0.81) 0.94 0.40 N (%) 1.01 a (0.07) 1.81 b (0.05) 2.10 c (0.08) 65.50 <0.001 C:N 40.98 a (3.13) 21.65 b (0.58) 18.36 b (1.00) 43.20 <0.001 Pools (g/m 2 ) C 1331.60 a (39.36) 2211.00 b (43.50) 1873.07 c (40.08) 116.95 <0.001 N 34.57 a (2.18) 102.84 b (3.05) 104.24 b (4.04) 23.36 <0.001 Bulk density

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46 Fig ure 2 1 Soil temperature and snow depth across three sites near Toolik Lake, AK. a) Weekly mean, maximum, and minimum air tempera ture at 5 m. b) Weekly mean ( SE) soil temperature measured at 5 cm depth within the organic layer under ambient and snow addition treatments at each site (n = 3 4). c) Mean ( SE) ambient and manipulated snow depth during the winter of 2005 2006 and 20 06 2007.

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47 Figure 2 2 Mean ( SE) net N mineralization in intact, resin capped organic soil cores incubated in the control and snow addition treatments at each of the three sites during the summer (mid June Sept 2006; 7 4 days) and winter (Sept 2006 June 2007; 280 days). Capita l letters indicate a significant difference between control treatments across sites. Lower case letters indicate a significant difference between snow treatments across sites. Asterices indicate a significant difference between treatments within each site.

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48 Fig ure 2 3 Mean ( SE) net N mineralization in intact, resin capped organic soil cores incubated in the control treatment or reciprocally transplanted and incubated in one of the other si tes during the summer (June Sept 2006; 74 days) and winter (Sept 2006 June 2007; 280 days).

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49 CHAPTER 3 CONTROLS OVER LITTER DECOMPOSITION IN THR EE ARCTIC PLANT COMMUNITIES Background Temperatures in the arctic region are warming at almost twice the rate of the rest of the globe (Overpeck et al. 1997, ACIA 2004, Serreze and Francis 2006, Kaufman et al. 2009, Screen and Simmonds 2010) and are expected to cause an increase in the availability of soil nutrients by warming soils and stimulating microbial break down of soil organic matter (SOM) (Nadelhoffer et al. 1991, Hobbie 1996). In experimental manipulations within the Alaskan arctic, an increase in plant available N can lead to an increase in plant productivity and a shift in species composition: from gram inoid to deciduous shrub dominance (Chapin et al. 1995, Chapin and Shaver 1996, Shaver et al. 2000, Mack et al. 2004). Increased photosynthetic activity, as detected by time series of normalized differenced vegetation index (NDVI) from satellite images, h as occurred in the Alaskan, Canadian, and Siberian arctic tundra systems over the past two decades and some of this enhanced activity has been attributed to an increase in growth of shrubs (Jia and Epstein 2003, Stowe et al. 2004, Jia et al. 2009, Forbes e t al. 2010). In addition, repeat aerial photography comparing historic with current photos in Northern Alaska show that deciduous shrubs have expanded their cover over the last 50 years (Tape et al. 2006). Understanding the mechanisms that drive shrub ex pansion are important because increasing shrub dominance will affect feedbacks between the arctic land surface and regional to global climate (Chapin et al. 2005). An increase in shrubs could lead to an increase in plant productivity and biomass resulting in more uptake of atmospheric CO 2 and the storage of more C aboveground in woody tissue or belowground in rhizomes (Shaver and Chapin 1991), roots, and

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50 ectomycorrhizal fungi (Clemmensen et al. 2006) resulting in a negative feedback to climate change. In a ddition, more woody stems associated with shrubs could mean more C stored in the soil because stems decompose slowly (Hobbie 1996). However, shrub lands have a lower albedo than tundra which can lead to an increase in absorbed solar radiation during the s now free period, resulting in a positive feedback to climate change (Chapin et al. 2005). In addition, deciduous sh rubs in fertilized tundra cycle C and N faster than in unfertilized tundra resulting in a net loss of deep soil C over a 20 year period (Mack et al. 2004). Soils in naturally occurring shrub tundra similarly store less C than those in graminoid tundra (Ping et al. 1998). Thus, positive feedback s to warming are possible, if increased shrub cover alters ecosystem structure and function so that soil C stocks decrease Since the arctic stores 20 30 percent of the total amount of terrestrial soil bound C (McGuire et al. 2009) it is important to understand better the mechanisms behind these potential feedbacks to climate change. The mechanisms that drive shrub expansion are not well understood. It has been hypothesized that shrubs may enhance thei r dominance and growth by altering abiotic and/or biotic controls over litter decomposition a key control over the recycling of nutrients within terrestri al ecosystems because it converts N in plant litter to organic and inorganic forms that can be readily taken up by plants The snow shr ub hypothesis suggests that shrubs can alter the abiotic soil environment via their interactions with snow (Sturm et al. 2001a). Tundra areas with taller and more abundant shrubs accumulate greater snow depth due to greater retention of snow fall (e.g. less snow lost to wind events) and trapping of wind distributed snow than tundra areas with fewer shrubs (Sturm et al., 2001a; Pomeroy et al., 2006). It has not been directly tested

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51 whether the amount of snow trapped by deciduous shrubs alters the environment enough to stimulate litter decomposition and increase litter nutrient release. Previous studies have shown that s n ow acts as an insulator that can increase soil temperature (Brooks et al., 1996, 1998; Grogan and Jonasson, 2003; Schimel et al., 2004; Wahren et al., 2005) and the availability of water to soil microorganisms (Coxson and Parkins, 1987; Romanovsky and Oste rkamp, 2000; Mikan et al., 2002) and therefore, potentially regulate the rate at which microbes and fungi can break down litter over the winter Indeed, litter decomposition has been found to occur in the winter and under snow (Stark 1972, Hobbie and Chap in 1996, Uchida et al. 2005, McLaren and Turkington 2010) and to be higher in areas that have deeper snow cover (Baptist et al. 2010) In only the Stark (1972) study was it clear that biological activity was responsible for mass lost in the winter with th ( Pinus jeffreyi ) litter occurred during the winter months by black fungal hyphae and other animals and bacteria living under the snow at 0 to 1 C. In the rest of the studies it is unclear whether biological activity or physical processes such as fragmentation or leaching were responsible for winter mass loss. If faster turnover of N bound in litter resulted in an increase in plant available N then snow accumulation by shrubs could indirect ly influence N availability by maintaining warmer soil temperatures in fall and winter, allowing a longer window for microbial breakdown of litter substrates increased N release, and higher rates of N supply to plants resulting in a positive plant soil fe edback that promotes further shrub expansion. Shrubs may also have effects on decomposition and N release that are independent of their effects on winter soil temperatures and may differ in the direction of

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52 their effects. In moist acidic tundra the decid uous shrub, Betula nana allocates 79 percent of its total biomass to new and old stems (Shaver et al. 2001), which decompose three times slower than their leaves and one to eight times slower than leaves and stems from graminoids and evergreen shrubs foun d within the Alaskan arctic tundra (Hobbie 1996). Thus a species composition shift to more deciduous shrub dominance may alter nutrient turnover through biotic controls by producing larger quantities of litter that is of lower quality (Hobbie, 1992; Bucker idge et al., 2010) possibly slowing nutrient turnover in litter resulting in a decrease in plant available N and a negative plant soil feedback that does not promote further shrub expansion. These two potential mechanisms lead to the question of whether changes in microclimate or changes in litter chemical composition ( quality ) and the amount of litter ( quantity ) will have a stronger control on litter decomposition and nutrient release. In arctic and boreal systems, differences in litter quality among species and the quality of the soil organic matter (SOM) across different vegetation types can have a larger effect on N mineralization than differences in temperature (Flanagan and Van Cleve, 1983; Giblin et al., 1991; Nadelhoffer et al., 1991; Hobbie, 19 96 ). This pattern has also been seen in alpine tundra of the southwestern French Alps, where Baptist (2010) found that species specific differences in litter quality had a stronger control over decomposition rates than differences in timing of snowmelt, w hich is associated with differences in snow depth and soil temperature. Although there is much evidence to suggest that shrubs can influence their environment to alter key biogeochemical processes that control plant nutrient supply, there have been no pub lished studies to date that have directly tested the effect of added snow (at the depth that would be trapped by shrubs)

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53 or increased shrub cover on litter decomposition. In addition, within the Alaskan arctic all the decomposition studies have largely oc curred in graminoid dominated moist acidic or non acidic tundra, therefore we know nothing about how the environment in shrub dominated tundra may influence litter decomposition. The goal of our stud y was to understand the mechanisms through which arctic deciduous shrubs affect N dynamics This was done by investigating how differences in soil microclimate, litter quality, and nutrient availability influence litter decomposition across three different arctic plant communities where snow depth was experim entally manipulated Our objectives were three fold: (1) to test whether realistic levels of snow accumulation altered the environment for decomposition enough to stimulate rates of litter mass and N release ; (2) to compare how litter C quality and the re lative availability of C to N influenced the rate of litter mass and N loss; and (3) to better understand how changes in species composition could influence community decomposition and nutrient turnover We hypothesized that across the three plant communi ties that 1) the addition of snow would slow temperature decline in the winter and lead to faster decomposition and net N release from litter 2) decomposition and net N release would covary positively with lignin:N and 3) community weighted decomposition rates would be lowest in the shrub dominated sites because of the greater abundance of less decomposable litter To test our hypotheses, we measured litter quality, quantity and decomposition across three plant communities that represented natural variat ion in shrub abundance across the landscape. We used a common substrate to test for site and snow treatment effects on decomposition and net N release. We decomposed litter that varied in litter

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54 quality in a common environment to control for differences i n microclimate and directly test the effect of litter quality on decomposition. We then combined these studies with litter production estimates to calculate a community weighted decomposition rate and determine how changes in species composition could alt er ecosystem decomposition and nutrient turnover. Methods Study Area All sites are located near Toolik Field Station at the Arctic Long Term Ecological in the foothills region on the north s lope of Brooks Range, Alaska, USA. This area is a younger landscape glaciated during the late Pleistocene and includes large areas of Itkillik I (deglaciated ca. 60 000 yr) and Itkillik II (deglaciated about 10 000 yr) glacial drifts (Hamilton 1986 ). The entire foothills region of the Brooks Range is treeless and underlain by continuous permafrost, 250 300 m thick (Osterkamp and Payne 1981). Mean annual air temperature is around 10C, with average summer temperatures from 7 12 C. Annual precipit ation is 318 mm, with 43% of falling in the winter (http://ecosystems.mbl.edu/ARC). Average snow depth is 50 cm, although snow distribution can be variable due to redistribution by wind. Snow melt occurs in early May. In the fall of 2005, three sites we re selected for the snow manipulation experiment that varied primar ily in deciduous shrub abundance hereafter referred to as low, medium and high shrub abundance sites and are described in detail in DeMarco et al. (2011). In short, sites were chosen to h ave similar state factors (climate, relief, parent

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55 material, time) but varied in the abundance of deciduous shrubs (Jenny 1994). The same species of deciduous shrubs ( Betula nana and Salix pulchra ) are found at all three sites (except S. richardsonii wh ich is found only at the medium shrub site); however, their percent cover increases from 15 to 94 % and their canopy height increases from 4 cm to 50 cm across sites. Our sites are within 1 km of each other, and ha ve similar parent material, time since la st glaciation (Itkillik I, deglaciated ca. 60 000 yr), and regional climate, although microclimates vary across sites due to differences in slope and aspect. Elevation changes from about 764 m at the low shrub site to 741 m at the medium and high shrubs si tes. Our low shrub abundance site is located in moist acidic tussock tundra where the vegetation consists of approximately equal biomass of graminoids ( Eriophorum vaginatum and C. bigelowii ), dwarf deciduous shrubs ( B. nana Vaccinium uliginosum and S. pulchra ), evergreen shrubs ( Ledum palustre ssp. decumbens and V. vitis idea ), and mosses ( Hylocomium splendens Au l acomnium turgidum Dicranum spp., and Sphagnum spp .) (Shaver and Chapin 1991). In our medium shrub abundance site, vegetation consists of g raminoids (primarily C. bigelowii ), deciduous shrubs ( B. nana V. uliginosum S. pulchra and S. richardsonii ), and mosses ( H. splendens and Dicranum spp. ) Our high shrub abundance site has predominantly deciduous shrubs ( B. nana S. pulchra and some Pot entilla fruticosa ) with some evergreen or wintergreen shrubs ( V. vitis idaea and Linnaea borealis ), forbs ( Polygonum bistorta Petasites frigidus Stellaria longipes Valeriana capitata and Artemisia alaskana ), graminoids ( Poa arctica C. bigelowii and C alamagrostis canadensis ), and mosses ( Sphagnum spp. and H. splendens ).

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56 Snow Manipulation To determine the influence of increased snow depth on litter decomposition snow fences that represented maximum regional shrub height (1.5 m high and 62 m long) wer e set up in the fall of 2005 at the low and medium sites to manipulate snow depth (DeMarco et al. 2011). Two treatments (control = ambient snow and drift = manipulated snow) were set up at each site. For all sites, subplots on the drift side of the fence s were located in the zone of maximum snow accumulation, which was relatively uniform. Within each treatment, 18 2 by 10 m plots, with 1 m buffer strips between, were established. For this study, six plots per treatment (n = 6) were randomly assigned to measure litter decomposition Remaining plots were used for additional experiments. Soil temperature at 5 cm within the organic layer, was measured continuously (1 3 h intervals) from J uly 2006 May 200 9 in each study plot (n = 3 4) by using Ibutton tem perature data loggers (IButtonLink, LLC, East Troy, WI). Mean daily soil temperatures were calculated for all plots within each treatment and site for each year. Mean growing season and winter temperatures were calculated from the mean daily temperatures from each plot within each treatment and site. Growing season included measurements taken from July 1 st to August 1 st of that year and includes years 2006, 2007, and 2009. Winter growing season includes measurements taken from September 1 st through May 1 st of the following year and includes winters from 2006 2007, 2007 2008, and 2008 2009. The snow fence produced a snow pack in our plots that was, on average 87, 96, and 104 cm deeper than ambient snow depth for the low, medium and high shrub sites, resp ectively. Snow addition increased average winter soil temperatures by 3C and summer soil temperatures by 2C in the high shrub site; the medium and low shrub sites

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57 showed similar trends, although the differences between treatments were smaller in magnitu de (DeMarco et al. 2011). Common Substrate Experiment To test directly the effect of microclimate and snow addition on litter decomposition rates we incubated the senesced leaves from a common substrate, Betula papyrifera var. neoalaskan in the ambie nt and snow manipulated plots across all three sites. Senesced leaves were collected while still attached to the trees but when the petiole had already started to abscise. Leaves were air dried at 45 C well mixed, and then subsampled for litter bags. O ne gram of leaves was sewn into two mm mesh bags, 8 x 8 cm in size. Litter bags were incubated beneath the live moss and litter layer in early June of 2006. The moss and litter in this system are well mixed so bags were inserted in this layer. Four ident ical bags were strung together for four time points to be removed annually. Bags were replicated six times per treatment per site with an additional three replicates per each of the s ix plots. Bags were removed after one, two, and three years in July of 2007, 2008, and 2009 and were kept frozen for approximately 6 months until they could be processed. At time of processing, bags were thawed and then gently rinsed with deionized (DI) water to remove dirt and loose litter attached to the outside of the b ag. All original leaf litter was removed, dried at 45C for a minimum of 48 hours and weighed. To determine the percent C and N of the litter samples were ground on a Wiley mill, with a #40 mesh screen, and then analyzed using an ECS 4010 elemental anal yzer (Costech Analytical, Valencia, California, USA). Percent of initial mass remaining was calculated by dividing the incubated mass by the initial mass and multiplying by 100. Percent of initial C and N remaining was calculated by the following equation :

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58 ICR = ( t 1mass x t 1C ) ( t 0mass x t 0C ) x 100 100 100 Common Environment Experiment To compare the effect of the individual plant species on litter decomposition rates, we collected litter from 13 different specie s at seven different sites located in the arctic foothills region on the north s lope of Brooks Range, Alaska, USA. Three of the sites were the control plots at the low, medium, and high shrub sites. Four sites were dominated by alder shrubs ( Alnus crispa ): two near the Sagavanirktok R iver and two along the Dalton Highway ~ 32 km north of Toolik Field Station. In addition, we decomposed litter collected from seven different species growing in long term fertilization experiments, in a mesh bags in a commo n environment to understand better the influence of litter quality on litter decomposition rates. All three sites (Historic, LTER, and Species Removal) are located in moist acidic tundra and were fertilized annually with both 10 g of N and 5 g of P m 2 ye ar 1 for 20, 14, and five years, respectively (Chapin et al. 1995, Bret Harte et al. 2001). These bags were installed in the field in July of 2003, removed in one, two, four, and five years in July of 2004, 2005, 2007, and 2008 and were kept frozen until t hey could be processed. Across all sites senesced leaves were collected while still attached but when the petiole had already started to abscise. Stems from deciduous shrubs Betula nana Salix pulchra S. richardsonii and Alnus crispa were also c ollected. Leaves and stems were air dried, well mixed, and then subsampled for litter bags. One gram of litter was sewn into 1.6 mm mesh bags, 4 x 8 cm in area. Litter bags were incubated beneath the live moss and litter layer, in early June of 2006. Fo ur identical bags were strung together for

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59 four time points to be removed annually. Leaf bags were replicated six times per site and stem bags were replicated three times per site. Bags were removed in one, two, and three years in July of 2007, 2008, and 2009 and were kept frozen until they could be processed. Bags were processed in the same manner as the litter bags for the common substrate experiment. Calculations The exponential decay constant, k, was determined by assuming a single exponential deca y model (Olson 1963): Mt = Moe kt Where Mt = litter mass at time t, and MO = initial mass. The slope of regressions of the proportion of initial mass remaining plotted against time was used to determine decay constants for each substrate at each site. Ini tial Litter Quality A su bsample of all samples of leaf and stem litter collected was analyzed for C, N, and C fractions to determine the quality of the litter substrates prior to decomposition. Carbon and N was determined on samples that had been ground t o a fine powder on a Wiley mill, with a #40 mesh screen, and then analyzed using an ECS 4010 elemental analyzer C fractions were determined using fiber forage techniques on an ANKOM fiber analyzer (Ankom Technology, Macedon, N. Y.). The following C fra ctions were determined: cell soluble (carbohydrates, lipids, pectin, starch, and soluble protein), hemicelluloses plus bound proteins, cellulose, and lignin plus other recalcitrants (Ryan et al. 1990).

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60 Community Weighted Decomposition To determine how ch anges in species composition (litter quality/quantity) alter community decomposition, we used biomass harvests collected in July of 2007 from the ambient treatment across all three sites (DeMarco et al. 2011). Total aboveground net primary production ( ANP P ) (g/m 2 /yr) per plot (n = 12) was calculated by summing new biomass (g/m 2 ) for that year for each plot. We calculated species specific ANPP per plot by summing all the new biomass per species per plot. The proportion that each species contributed to the total community ANPP was then calculated by dividing species ANPP by total ANPP per plot. This proportion was then multiplied by the species specific decomposition constant, k, to get a species weighted k value. All species weighted k values for each pl ot were summed to obtain a decomposition k constant for the entire community. Community weighted k values were calculated for each replicated plot within each site. To determine how changes in species composition (litter quality/quantity) and environment altered community decomposition, we used the same calculated species specific k values, weighted by the proportion that each specie s contributed to total community ANPP, for each plot but then adjusted them for site specific differences in decomposition r ates indexed by the common substrate decomposition experiment. Site mean k values for the common substrate, Betula papyrifera var. neoalaskan were subtracted from the mean common garden k value for that substrate. Species specific k values were multipli ed by this difference and then the adjusted values were summed to obtain a decomposition k constant for the entire community. The community weighted k values for all 12 plots within each site was calculated. This method assumes that all species and parts respond the same way as Betula papyrifera var. neoalaskan when

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61 decomposed in different environments and does not take into account any site by species interactions. The ANPP calculations were only for vascular plants and thus do not include mosses and li chen or any belowground parts such as rhizomes or roots. We estimated the contribution of secondary stems to ANPP by multiplying the ANPP of species likely to produce woody tissue by a proportion determined by Bret Harte et al. (2002). These were 0.158, 0.181, and 0.079 for Betula nana Salix pulchra and Ledum palustre ssp. Decumbens respectively. We followed the methods outline d in Hobbie and Gough (2004) and assumed that Cassiope tetragona and Vaccinium uligonosum resembled L. palustre in their prop ortional secondary growth and S. reticulate S. glauca and S. richardsonii all resembled S. pulchra in their proportional secondary growth. We also assumed that Andromeda polifolia Arctostaphylos alpina Dryas integrifolia Empetrum nigrum Rubus chamae morus V. vitis idaea and Linnaea borealis had negligible secondary growth. We did not decompose all the species found at our sites in our common garden site, so we used k values from other published studies within the region or substituted k values for s pecies with similar growth forms. These species contributed less than 7% of the total ANPP For all forbs we used the decay constant for Polygonum bistorta from Hobbie and Gough (2004) which was also decomposed in the same environment as our common gard en. For Calamagrostis spp. Poa arctica and Juncus we used an average of k values from Carix spp and Eriophorum spp (k = 0.18) from our common garden. For Empetrum L borealis and Cassiope leaves we used an average of k values from Ledum and V. viti s idaea from our common garden. For Empetrum L. borealis and

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62 Cassiope stems we used an average of k values from B. nana and S. pulchra stems (k = 0.08 ). We excluded Equisetum from our NPP and weighted k values because it was found in only one plot and only contributed 2 g/m 2 /yr in that plot. Statistical Analysis To test our hypotheses regarding snow additions on decomposition we used two way Analysis of Variances (ANOVA) with site and snow addition as the main effect and site by snow addition as the int eraction term (JMP 7.0, 2007, SAS) To test our hypothesis regarding site effects on decomposition we used two way ANOVAs with site and species as the main effect and site by species as the interaction term. To test our hypotheses regarding the effect of species and fertilization on initial litter quality indices and decomposition we used two way ANOVAs with species and treatment (control vs. fertilized) as the main effect and species by treatment as the interaction term. The effect of time since fertili zation on initial litter quality indices and decomposition was tested using a one way ANOVA with time since fertilized (0, 5, 14, or 20 years) as the main effect. Relationships between the litter decay constant, k, and initial litter quality indices for n ine of the species decomposed in the common garden were tested using regression analysis with the litter decay constant, k, as the dependent variable, as the litter quality indices of interest as the independent variable. The effect of litter quality/qua ntity on community decomposition and the effect of litter quality/quantity and environment on decomposition were tested using two separate one way ANOVAs with site as the main effect. ere used when significance was obtai ned from ANOVAs. Data were tested for normality (Shapiro Wilks), and ln transformed when necessary to meet the assumptions of ANOVA.

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63 Results Effect of added snow on soil temperature Snow addition significantly increased winter soil temperatures by an average of 1 4 C across all three sites. Winter soil temperatures across sites and among years were also significantly different (Appendix B Table B 1 and B 2). There was a significant interaction between vegetation type and year. Snow addition had no significant effect on growing season soil temperatures for any of the three years measured; however, there was a significant difference in growing season soil temperature across the three sites with warmer temperatures at the medium and high shrub sites c ompared to the low shrub site. There was also a significant effect of year on soil temperature but no significant interactions across all combinations (Appendix B Table B 1 and B 2). Common Substrate Experiment After three years, the addition of snow r esulted in a significant interaction between site and treatment ( F 2, 30 = 3. 5, P = 0.0 4) but no significant main effect of snow addition on litter mass loss at any of the three sites ( F 1 30 = 1 5 P = 0. 23). Mass remaining was greater in the control treatm ent than the snow treatment in all sites except the low site where the mass remaining in the snow treatment was greater than mass remaining in the control treatment. Snow addition also had no significant effect on litter C loss at any of the three sites a nd there was no significant interaction between site and treatment. There was also a significant interaction between site and treatment on litter N loss but no significant main effect. In contrast to mass remaining, litter N remaining was greatest in the snow treatment compared to the control for all sites except the Medium shrub site where N remaining was greater in the control compared to the snow

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64 treatment. Snow addition had no effect on C:N or litter decay rates at any of the three sites and there wa s no significant interaction between site and treatment (Fig.3 1, Table 3 2). After three years of incubation, Betula papyrifera var. neoalaskan leaf litter incubated in the low shrub site lost 10 and 6 % more mass when incubated in the low shrub site th an in the medium and high shrub sites, respectively (Fig. 3 1, Table 3 1; F 2, 30 = 1 3. 2 P <0.0001 ). Initial carbon (C) remaining followed the same pattern as initial mass remaining with 8 and 6 % more C loss occurring at the low shrub site compared to the medium and high shrub sites, respectively (Fig. 3 1 and 3 2, Table 3 1 and 3 2). Initial nitrogen (N) remaining followed a very different pattern as initial mass and C remaining with mineralization of litter N occurring at the low site only, but immobi lization occurring at both the medium and high shrub sites (Fig 3 1, Table 3 1). The proportion of initial C:N remaining decreased with an increase in shrub abundance. The litter decay rate, k was highest at the low shrub site compared to the medium and high shrub sites (Table 3 1). Common Environment Experiment Deciduous shrub litter collected across the shrub gradient sites After three years of incubation, neither site of origin nor species had an effect on the % initial mass remaining or decay rate of leaf and stem litter from Betula nana and Salix pulchra despite significant differences in their initial litter quality ( Appendix B Table B 3 and Table B 4). The percentage of leaf cell solubles, cellulose, and lignin all significantly differed by site while the percentage of leaf C and cellulose differed significantly by species. For stem litter, only hemicellulose was significantly different

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65 among sites while both percent C and cellulose in stem litter significantly differed between species (T able B 4). Initial litter quality and decay constants across species with and without fertilization Initial litter quality significantly differed across species for all indices measured although species within the same growth form were not always si milar in their initial litter quality (Appendix B Table B 5) After five years of fertilization, initial litter quality changed in all the indices measured except cell solubles and lignin. Deciduous shrubs had up to two times more N in their leaves than evergreen shrubs, graminoids, and mosses. Leaf litter N increased with fertilization in all species except R. chamaemorus (Fig. 3 3; two way ANOVA, species: F 6 65 = 72.4, P < 0.0001, treatment: F 1 65 = 146.7, P < 0.0001, species x treatment: F 6 65 = 4.5, P < 0.001). Evergreen shrubs had the highest percent C in their leaves followed by deciduous shrubs (except R. chamaemorus ), graminoids, mosses, and R chamaemorus Fertilization decreased percent C but only for B. nana (Appendix B, Table B 5; species: F 6 65 = 172.6, P < 0.0001, treatment: F 1 65 = 13.8, P < 0.001, species x treatment: F 6 65 = 3.5, P < 0.01). Evergreen shrubs, mosses, and the graminoid, E. vaginatum all had high C:N ratios in their leaves; while the deciduous shrubs R. chamaemorus and V. uliginosum had the lowest C:N ratios. The C:N ratio in leaf litter decreased in four out of seven species with added N (species: F 6 65 = 82.6, P < 0.0001, treatment: F 1 65 = 172.2, P < 0.0001, species x treatment: F 6 65 = 11.4, P < 0.0001). Both evergre en and deciduous shrubs had similar percentages of cell solubles that were almost double that of graminoids and remained unchanged by fertilization (species: F 6 65 = 105.5, P < 0.0001, treatment: F 1 65 = 0.5, P = 0.49, species x treatment: F 6 65 = 2.1, P = 0.06). Graminoids had 1. 5 to 4

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66 times more hemicellulose in their leaves compared to evergreen and deciduous shrub leaves. Fertilization increased percent hemicellulose in both C. bigelowii and V. uliginosum (species: F 6 65 = 165.6, P < 0.0001, treatment: F 1 65 = 7.3, P < 0.01, species x treatment: F 6 65 = 3.6, P < 0.01). Graminoids also had the highest percentage of cellulose in their leaves that were 2 to 4 times greater than evergreen and deciduous shrubs. B. nana had the least percentage of cellulose in their leaves compared to all six other species. E. vaginatum decreased in percent cellulose with added N while all other species remain unchanged (species: F 6 65 = 217.2, P < 0.0001, treatment: F 1 65 = 8.8, P < 0.01, species x treatment: F 6 65 = 3.7, P < 0.01). B. nana also had the highest percentage of lignin, followed by evergreen shrubs and the deciduous shrubs, R. chamaemorus and V uliginosum Graminoids had the least amount of lignin in their leaves. Fertilization had no significant effect on percent lignin for any of the seven species (species: F 6 65 = 94.3, P < 0.0001, treatment: F 1 65 = 1.5, P = 0.22, species x treatment: F 6 65 = 0.4, P = 0.86). The evergreen shrubs and the deciduous shrub B. nana had lignin:N ratios that were two to four times higher than the deciduous shrubs, R. chamaemorus and V uliginosum and the graminoids. Fertilization decreased the lignin:N ratio of Ledum decumbens V. vitis idaea and B. nana leaf litter (species: F 6 65 = 54.1, P < 0.0001, treatment: F 1 65 = 45 .2, P = < 0.0001, species x treatment: F 6 65 = 3.4, P < 0.01). After five years of incubation, Rubus chamaemorus decomposed one and half to six times faster than litter from the other six species of vascular plants and three species of mosses colle cted at the same moist acidic tundra site and decomposed in the same common garden (Fig. 3 4, see also Appendix Figs. B1 4). Although there was a

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67 significant difference in litter decay constants across species (species: F 6 65 = 15.8, P < 0.0001, treatment : F 1 65 = 0.3, P = 0.58, species x treatment: F 6 65 = 0.9, P = 0.52), species within the same functional group did not always follow the same pattern in their rates of decomposition (Fig. 3 4). The deciduous shrubs, Betula nana and Vaccinium uliginosum ha d similar decay constants as the evergreen shrub Ledum decumbens and the graminoid Eriophorum vaginatum and all had higher decay constants than the evergreen shrub V. vitis idaea and the graminoid Carex bigelowii Mosses had the lowest decay constants c ompared to the other seven vascular plant species decomposed in our experiment. After five years of fertilization, there was no significant difference in litter decay constants (Appendix B, Figs. B1 4). In a comparison within one species, B. nana acro ss four different times since fertilization (0, 5, 14, and 20 years), initial litter quality changed in five out of seven indices measured. Percent C, C:N ratio, and lignin:N ratio decreased after five years of fertilization than remained unchanged at 14 and 20 years of fertilization. Percent hemicelluloses increased after five years but became similar to the control at 14 and 20 years. Percent N significantly increased with the length of fertilization. Percent lignin was only significantly different af ter 20 years of fertilization (Fig. 3 5). The decay constant, k, significantly increased with fertilization but only after 20 years of fertilization (Table 3 3, Fig. 3 5). The relationship between initial litter quality and decay constants In a comp arison with all nine species decomposed in our common garden, leaf litter decay rates were only weakly related to some of the litter quality indices we measured. The percentage of C and cell solubles were positively correlated with decay rates (Appendix B Fig. B 5; r 2 = 0.23, n = 21, p = 0.03; r 2 = 0.23, n = 21, p = 0.03); while

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68 the percent of cellulose in the leaves was negatively correlated with decay rates (Appendix B, B 5; r 2 = 0.23, n = 21, p = 0.04). For stem litter, the percentage of cellulose was the only litter quality index that was found to correlate with decay rates and it explained 55 % of the variation in stem decay rate (Appendix B, B 6; r 2 = 0.55, n = 9, p = 0.01). Community Weighted Decomposition Community weighted k constants that too k into account differences in litter quality and quantity across sites were marginally higher in the medium and high shrub sites compared to the low shrub site (one way ANOVA; F 2,21 = 3, p = 0.06). Community weighted k constants that took into account bot h differences in litter quality/quantity and environment were significantly higher at the low shrub site compared to the medium and high shrub sites (one way ANOVA; F 2,21 = 65, p < 0.0001). Discussion Microenvironment controls over litter decomposition S urprisingly, we were unable to detect any effect of adding snow on litter decomposition of our common substrate after three years of incubation, even though soil temperatures were warmed by up to 2C during the growing season and up to 4C during the winte r. There are only a few studies that directly compare the effects of snow addition on litter decomposition. Walker et al. (1999) also did not find an effect of deeper snow on litter decomposition after two years of decomposing Betula nana leaf litter un der ambient and snow addition of up to 3 meters in tussock tundra near Toolik Lake, Alaska. In contrast, Baptist et al. (2010) found a trend for greater litter mass loss in late snow melt sites presumably due to warmer soil temperatures; although, this wa s

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69 not significantly different. Using the same species of litter as our experiment, Hobbie and Chapin (1996) found differences in litter mass loss between microsites in which summer soil temperatures differed by 4C, with greater mass loss occurring in the warmer microsites. In addition, litter mass loss in lab incubations that included warming treatments of either 2 or 6C above the ambient growing season temperatures resulted in an increase in mass loss with an increase in temperature (Hobbie 1996, Jonas son et al. 2004). Two of the three studies had temperature differences that were twice as high as our study which may explain why they found significant differences in litter mass loss with change in temperature while we did not. Interestingly, litter decomposed faster in the low shrub site compared to the medium and high shrub sites, even though the ambient soil temperatures at the medium and high shrubs sites were actually warmer than at the low shrub site in both the growing season and the winter. S oil temperature differences across these sites are of the same magnitude as the differences in soil temperature we saw when we added snow. This suggests that other factors such as moisture, soil nutrients, litter substrate quality, or the decomposer commu nities may be more important than small (<4C) changes in temperature for driving decomposition at our sites. Soil moisture was not measured over the three year incubation period, but measurements in June of 2006 showed no difference in soil moisture acro ss sites and trend for greater moisture at the low shrub site compared to the medium and high shrub site with the addition of snow ( DeMarco et al. 2011 ). Our data suggests that soil nutrients play an important role in controlling litter decomposition and n utrient release at our sites. Over our three year incubation period,

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70 litter decomposed at the low shrub site mineralized litter N while immobilization of N occurred at the medium and high shrub sites. Previous research from these sites have shown that bu lk soil N at the medium and high shrub sites is twice as high as compared with bulk soil N at the low shrub site ( DeMarco et al. 2011 ) and is highly correlated with initial N remaining, the C:N ratio, and litter k values (Fig. 7). Thus, sites with greater soil N have lower rates of litter decomposition and higher retention of N on the leaves. Greater soil N availability has been found to stimulate (Hobbie 1996, Aerts et al. 2006b), repress (Prescott 1995, Magill and Aber 1998, Aerts et al. 2006b), or have no effect (McClaugherty et al. 1985, Prescott 1995, Hobbie 1996, Aerts et al. 2003, Aerts et al. 2006b) on litter decomposition rates and can lead to N immobilization in some systems (Gallardo and Merino 1992, Magill and Aber 1998, Hobbie 2005, Aerts et a l. 2006b) but see (McClaugherty et al. 1985). Varying responses of litter decomposition to external N may be attributed to initial litter quality. In a meta analysis of 24 litter decomposition studies in which external N was experimentally manipulated, (Knorr et al. 2005) found that external N availability and litter quality interact to influence decay rates with N additions stimulating decomposition of high quality litters (<10% lignin content), while inhibiting decay of low quality (>20% lignin content this pattern occurs because some microbes use labile C to decompose recalcitrant organic matter in order to acquire N (Fontaine and Barot 2005, Moorhead and Sinsabaugh 2006). Therefore we would decomposition of low quality litter when it is incubated in soils with low soil N and be suppressed when litter is incubated in soils with high N. Indeed there is evidence that

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71 this can occur, and this mechanism may help explain why we saw a linear pattern of decreased rates of decomposition and an increase in N immobilization with increasing soil N at our sites (Craine et al. 2007). The Betula papyrifera var. neoalaskana litter we used for our study was of low quali ty with both a high C:N ratio (72 .06) and percent lignin (19 2) content. In addition, high nutrient content in soils can suppress the production of fungal ligninase (Carreiro et al. 2000, Sinsabaugh et al. 2002), which is induced by low N availabili ty (Keyser et al. 1978), resulting in lower rates of decomposition. Low quality litters can also contain higher levels of tannins that can bind to N and become incorporated in the lignin fraction, decreasing decomposition and increasing immobilization of N (Gallardo and Merino 1992, Aerts et al. 2003). Fungal communities between tussock tundra and shrub tundra soils sampled near Toolik Lake, AK differ at the phyla and subphyla level; however, we do not know whether the species responsible for breaking dow n lignin or the production of ligninase differs between these two plant communities (Wallenstein et al. 2007). These tussock tundra soils are dominated by slow growing microbes that have higher affinities for low quality and quantity C substrates. In con trast, shrub tundra soils are dominated by microbes that have high growth rates with high nutritional requirements for higher quality and quantity C (Fierer et al. 2007, Wallenstein et al. 2007). It is possible that microbes at the low shrub site are bett er at decomposing litter that is of low quality than the microbes at the high shrub site, and microbes at the high shrub site immobilize more N because they have a higher nutrient demand when mineralizing C. Although we did not measure tannins in our litt er others have found that Betula spp. leaves can have more

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72 polyphenols when compared to Salix spp. and Populus spp. leaves (Palo 1984). In addition, litter of Betula papyrifera grown under elevated CO 2 increased its tannin content by as much as 81% and wh en decomposed in a common garden had lower rates of decomposition and higher N immobilization compared to litter from ambient CO 2 conditions that had lower tannin levels (Parsons et al. 2004). Our common substrate experiment demonstrates that on a short time scale interactions between soil nutrient content, litter quality, and microbial community composition play a greater role than small changes in soil temperature in regulating nutrient cycling at our sites. The litter quality of B. papyrifera var. neo alaskana was lower than the deciduous shrub litter native to these sites, thus we do not know whether native litter decomposed at the high shrub site would respond in the same way as our common substrate. Litter quality controls over litter decomposition Data from our common garden experiment suggest that changes in litter C quality, and not N content, may be more important in regulating decomposition rates. We found differences in litter N within the same species both across our sites (for Betula nana an d Salix pulchra ) and among litter that had been fertilized for five years; but, we found no differences in decomposition rates nor a significant correlation between initial litter N and decomposition rates. It was not until after 20 years of fertilization that led to a significant decrease in lignin content did we see an increase in decomposition rates. Thus, it appears that lignin content, rather than litter N, controls decomposition rates when incubated in the same low soil N environment. This idea agr ees with data from Hobbie (1996) who found that initial C fractions correlated more with litter decay constants than initial N for similar species, as our study and with data from Baptist et al.

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73 (2010) who showed that plant species with higher lignin conte nt in their leaves decomposed more slowly than leaves with lower lignin content. In contrast, when mosses were excluded Hobbie and Gough (2004) found no relationship between initial leaf litter chemistry and the litter decay constant for the same species studied in the Hobbie (1996) study. Hobbie (2005) found a significant relationship between litter N and decomposition rates across litter from eight species that varied in their initial N by 2.5 %, however litter N was also tightly correlated with litter phosphorus (P) and potassium (K) concentrations, so it is unclear whether decomposition was directly influenced by N or P and K. All species mineralized litter N, regardless of their litter quality. Since our common garden was in a low nutrient soil, thi s suggests site microenvironment may be more important than litter quality in controlling litter N mineralization/immobilization dynamics. Comparisons in litter decomposition among species and functional groups suggest that decomposition rates cannot be generalized using functional group designations, since species within the same functional group did not always follow the same pattern of decomposition and this in contrast with other decomposition studies within this region (Hobbie 1996, Hobbie and Gough 2004), although our study included more species of deciduous and evergreen shrubs. Decomposition rates varied significantly among species. Of the seven species we decomposed, Rubus chamaemorus had the highest quality litter and the faster rate of decompo sition, losing about 70 % of its mass over a three year period. Aerts et al. (2006) also found that R. chamaemorus decomposed more quickly than three other sub arctic bog species. In contrast, mosses had the lowest decomposition rate, only losing about 3 0 % of their

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74 mass over the same period. Although, there were some differences in decomposition between the rest of the species, which included deciduous shrubs, evergreen shrubs, and graminoids, these differences were relatively small. A change in specie s composition within the arctic could lead to alterations in community decomposition rates and nutrient turnover, if the change includes an increase in the relative abundance of R. chamaemorus and a decrease in mosses as seen in fertilized tussock tundra i n Alaska where R. chamaemorus dominates the understory and moss cover is reduced (Chapin et al. 1995). Litter quality/quantity versus microclimate controls over litter decomposition Based on our results, changes in litter quality and quantity via change s in species community composition will have relatively little impact on the total community decomposition rate, however changes in the soil microenvironment could lead to substantial differences in decomposition rates across plant communities. Hobbie an d Gough (2004) also found that site differences had a larger control over community level decomposition compared to changes in species composition alone. We did not include mosses and lichens in this estimate although, we know that their distribution chan ges across our sites and is expected to change with climate warming. In addition, we are assuming that all species will respond similarly to B. papyrifera when incubated across our sites. It is possible that differences in litter quality may interact wit h site environment at the high nutrient site resulting in a different pattern than what we saw with B. papyrifera as Knorr et al. (2005) have shown that species that differ in their litter quality respond differently to high soil N environments. Our stud y suggests that on a short time scale small changes in soil temperature and moisture associated with additional snow trapping by shrubs is unlikely to influence

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75 litter nutrient turnover enough to drive positive snow shrub feedbacks as proposed by Sturm et al. (2001). However, long term changes in litter quality inputs associated with different dominant plant species could lead to alterations in soil nutrients and microbial communities, which, in turn, can significantly alter litter decomposition processes. Assuming that all species respond similarly to Betula papyrifera when incubated at the medium and low shrub sites, an increase in deciduous shrub cover could actually lead to slower rates of litter decomposition and nutrient turnover with concomitant inc rease in C sequestration. Retaining N in litter may be beneficial for soil organic matter (SOM) decomposition and could help explain why we see more soil N and greater N mineralization at the medium and high shrub sites.

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76 Tabl e 3 1. I nitial mass remaining (IMR), initial carbon remaining (ICR), initial N remaining (INR), and decay constants (n = 6) for the common substrate, Betula papyrifera var. neoalaskan decomposed at each site with each treatment and calculated for the enti re three year decomposition period. Means SE n = 6). Table 3 2. Two way ANOVA results comparing k, INR, ICR, and the proportion of ICR:INR after three years of incubation across all sites and treatments. K (1/yr) df F ratio p value Site 2 18.91 <0.0001 Treatment 1 1.45 0.24 Site X Treatment 2 2.09 0.14 Initial C Remaining (%) Site 2 7.27 <0.01 Treatment 1 1.49 0.23 Site X Treatment 2 2.72 0.08 Initial N Remaining (%) Site 2 101.64 <0.0001 Treatment 1 0.48 0.49 Site X Treatment 2 4.07 0.03 Initial C:N Remaining Site 2 36.21 <0.0001 Treatment 1 2.00 0.17 Site X Treatment 2 1.63 0.21 Site Treatment IMR (%) ICR (%) INR (%) K (1/yr) Low Ambient 42.7 c (1.46) 45.4 b (1.47) 78.9 c (1.68) 0.292 a (0.01) Snow Addition 45.4 bc (1.33) 47.9 ab (1.37) 85.3 c (1.81) 0.277 ab (0.01) Me dium Ambient 52.5 a (1.17) 53.9 a (1.34) 102.5 b (2.89) 0.208 c (0.006) Snow Addition 49.2 ab (1.43) 51.1 ab (1.58) 96.6 b (2.58) 0.232 bc (0.01) High Ambient 48.7 ab (0.88) 51.8 ab (1.34) 112.5 a (2.62) 0.238 bc (0.009) Snow Addition 45.6 bc (1.45) 47.5 a b (1.98) 115.9 a (1.58) 0.259 ab (0.01)

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77 Table 3 3. Initial litter quality of senesced leaves of Betula nana collected in bot h unfertilized plots and plots that had been fertilized for five 14, and 20 years. Results are from one fertilized ( Means SE; n = 13, 6, 4, and 4). Years Fertilized ANOVA Results Foliar traits 0 5 14 20 df F stat p value N (%) 1.64 a (0.04) 2.41 b (0.11) 2.09 c (0.09) 2.08 c (0.07) 3 29.95 <0.0001 C (%) 44.44 a (0.08) 43.33 b (0.08) 43.44 b (0.18) 43.39 b (0.18) 3 28.99 <0.0001 C:N 27.29 a (0.59) 18.17 b (0.89) 20.93 b (0.97) 20.95 b (0.73) 3 35.91 <0.0001 C ell soluble (%) 62.49 (0.52) 60.86 (0.74) 62.66 (1.13) 63.80 (0.96) 3 1.26 0.31 Hemicellulose (%) 10.77 a (0.29) 12.71 b (0.39) 12.63 ab (0.86) 11.28 ab (0.35) 3 4.33 0.01 Cellulose (%) 7.79 (0.31) 7.94 (0.19) 7.68 (0.55) 8.59 (0.42) 3 0.57 0.64 Lignin (%) 18.54 a (0.46) 18.17 ab (0.70) 16.60 ab (0.76) 15.79 b (0.31) 3 4.37 0.01 Lignin:N 11.35 a (0.29) 7.63 b (0.55) 8.03 b (0.65) 7.63 b (0.33) 3 25.41 <0.0001 K (1/yr) 0.177 a (0.001) 0.204 ab (0.009) 0.206 ab (0.017) 0.249 b (0.029) 3 3.93 0.02

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78 Figure 3 1. Initial mass, C, and N remaining of the common substrate ( Betula papyrifera var. neoalaskana ) from litter bags incubated over three years in the ambient and s now addition treatments at the low, medium, and h igh shrub site s. (Mean SE, n = 6)

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79 Figure 3 2. D ecay constants, initial C and N remaining, and the proportion of initial C:N remaining for the common substrate, Betula papyrifera var. neoalaskana ), decomposed at each site and tr eatment and calculated for the entire three year decomposition time period. Different letters within a graph represent significant differences at the p < 0.05 level. (Mean SE, n = 6)

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80 Figure 3 3. P ercent initial leaf litter N collected from plants that were unfertilized and fertilized with 10 g N/m 2 /yr for 5 years. Statistical results are from a two way ANOVA. Different letters within the graph represent significant differences at the p < 0.05 level. (Mean SE, n = 6)

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81 Figure 3 4. Leaf litter d ecay constants (k) vs. leaf percent C, cell solubles, and cellulose for 11 vascular plants species collected across nine sites and decomposed for three to five years in the same common garden (n = 3 6). Perce nt C includes three moss species collected at o ne site and incubated for five years in the same common garden (n = 5 6). (Mean SE)

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82 Fig ure 3 5 (Left). P ercent initial leaf litter lignin of Betula nana collected from four sites that have been fertilized for ze ro five 14 or 20 years. (Right). D ecay constant, k, of Betula nana leaves collected from four sites that have been fertilized for zero five 14, or 20 years and incubated in a common garden for five years. Statistical results are from one way ANOVAs. Different letters within a graph represent significant differences at the p < 0.05 level. (Mean SE, n = 6)

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83 Figure 3 6. Comparison of the influence of litter quality/quantity and litter quality/quantity with micro environment in mean community weighted litter decay constant (k, 1/yr) across three arctic plant communities. Different capital letters represent significant differences at the p < 0.05 level across sites in influence of litter quality/quantity on decompo sition. Different lower case letters represent significant differences at the p < 0.05 level across sites in influence of litter quality/quantity and environment on decomposition.

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84 Figure 3 7. S oil % N for each site vs. decay constant (k ), initial C remaining, initial N remaining, and the proportion of initial C to N remaining of the common substrate, Betula papyrifera var. neoalaskana ), decomposed at each site over a three year period. (Mean SE, n = 6)

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85 CHAPTER 4 PLANT AND ECOSYSTEM RE SPONSE TO LONG TERM EXPERIMENTAL WARMING AND NUTRIENT ADDITIONS IN ARCTIC SHRUB TUNDRA Background Temperatures in t he arctic have increased by 1.5 C over the last century and should continue to increase at a faster rate than the rest of the globe (Overpeck et al. 1997, Serreze and Francis 2006, Kaufman et al. 2009). Warmer temperatures can stimulate plant productivity directly in arctic plant communities by providing a warmer environment for plant growth (Chapin et al. 1995, Michelsen et al. 1996, Aerts et al. 2006a) or indirectly by stimulating microbial decomposition of organic matter and releasing more nutrients for plant uptake and growth (Nadelhoffer et al. 1991, Chapin et al. 1995, Schmidt et al. 2002, Aerts et al. 2006a). The Arctic tundra biome in cludes a diverse array of vegetation communities which, due to the variety of plant functional types that dominate, may differ in their response to environmental change (Chapin and Shaver 1989, Baddeley et al. 1994, Schmidt et al. 2002, Walker et al. 2006) Studies in North America tundra that have directly tested plant community and ecosystem responses to environmental changes have been concentrated in communities dominated by graminoids such as tussock tundra, dry heath tundra or wet sedge plant communit ies in the upland Slope. In contrast studies in Northern Europe have been concentrated in communities dominated by shrubs, including subalpine dwarf shrub heath and fellfield in the sub arctic of Sweden. Plant productivity in Ala skan communities as well as dwarf shrub communities in Sweden, respond strongly to nutrient additions and to a lesser degree to temperature increase (Shaver and Chapin 1980, 1991, Parsons et al. 1994, Boelman et al. 2003, Van Wijk et al. 2003). Nitrogen ( N) or N in combination with phosphorus (P)

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86 can limit productivity in upland communities such as tussock moist acidic tundra (Shaver and Chapin 1980, Chapin et al. 1995, Shaver et al. 2001), tussock moist non acidic tundra (Gough and Hobbie 2003), heath tun dra (Gough et al. 2002), and dwarf shrub communities (Baddeley et al. 1994) W et sedge communities tend to be P limited (Shaver and Chapin 1995). There are few, if any, studies that directly test temperature and nutrient controls over productivity and ca rbon (C) storage in Alaskan shrub tundra, even though shrub dominated communities make up 22% of the land cover in the Arctic tundra ecosystems of Alaska and 36.5% of the non glaciated Pan Arctic tundra biome (Walker et al. 2005). Those studies that have tested temperature and nutrient controls over productivity in shrub tundra communities have been concentrated in sub arctic systems in Northern Sweden where the dominate shrubs are evergreen and are compositionally more similar to heath tundra communities in Alaska than riparian shrub communities (Parsons et al. 1994, Michelsen et al. 1996, Molau and Alatalo 1998). In contrast, shrub tundra communities in Northern Alaska are dominated by deciduous shrubs, whose functional traits may allow them to respond m ore rapidly to environmental change compared to evergreen shrubs. Understanding how Alaskan shrub tundra communities will respond to environmental change is becoming even more critical as these communities are currently expanding (Tape et al. 2006, Forbes et al. 2010) and are expected to continue to increase with future warming (Walker et al. 2006). To our knowledge there have been no experimental studies reporting the effects of either short or long term environmental change on Alaska shrub tundra commun ities. Furthermore, previous research has shown that the short term (< 5 years) response of

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87 arctic plant communities to environmental manipulations is not always predictive of long term (> 9 years) response studies (Chapin et al. 1995, Boelman et al. 2003 Mack et al. 2004). In addition, plant communities from different regions within the arctic do not always respond similarly to the same environmental manipulations (Van Wijk et al. 2003). For example, in a meta analysis comparing long term ecosystem lev el experiments at Toolik Lake, Alaska and at Abisko, Northern Sweden, Van Wijk et al. (2003) found that communities from both regions responded to nutrient additions by increasing aboveground plant biomass, particularly the biomass of deciduous and gramino id plants I n addition to our limited knowledge on long term ecosystem responses, we know little about how environmental changes will influence belowground biomass, C and nutrient storage even though the arctic stores 20 30 percent of the total amount of terrestrial soil bound C (McGuire et al. 2009). Much of what we know about North American shrub tundra communities comes from observational studies. These studies show that shrub tundra communities are found along gravelly river bars, well drained floodplains, streams, and in water track areas where the soil temperatures are warmer and nutrient availability is higher (Matthes Sears et al. 1988). These communities are dominated by deciduous shrubs willows ( Salix spp .), birch ( Betula spp .) or a lder ( Alnus spp .) and have the highest plant productivity when compared to other tundra plant communities (Matthes Sears et al. 1988, Shaver and Chapin 1991). In addition, 70 percent of shrub tundra biomass is stored belowground in rhizomes and roots (Chapin et al. 1980, DeMarco et al. 2011). Shrub tundra soils have larger C and N pools (DeMarco et al. 2011) and cycle N in the soil faster than other tundra communities (Weintraub and Schimel 2003, Buckeridge et

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88 al. 2010, Chu and Grogan 2010, DeMarco et al. 2011) At the plant level, deciduous shrubs have higher transpiration (Bliss 1960) photosynthetic (Johnson and Tieszen 1976) and nutrient uptake (Kielland 1994) rates compared to other arctic plant growth forms and have been found to respond more quickly to e nvironmental change than other functional groups (Baddeley et al. 1994, Chapin et al. 1995). The objective of our study was to understand controls over plant productivity and C and N storage in shrub tundra ecosystems in order to make inferences about how these systems will respond to environmental change. To investigate whether plant productivity is limited by temperature, nutrients, or an interaction between the two we examined the plant and ecosystem response from the longest running (18 years) nutrien t and warming experiment in Alaskan arctic riparian shrub tundra ecosystems. In addition, we tested whether these experimental environmental changes altered total ecosystem N and C storage. We hypothesized that productivity, and C and N pools in plant bi omass would increase more strongly and consistently to the alleviation of nutrient limitation than they would to a 1 3 C increase in air temperature an increase chosen to mimic the expected increase in arctic air temperature by the middle of the 21 st cen tury (ACIA 2004). In addition, we predicted that increasing plant productivity in response to nutrients would lead to an increase in C and N pools in soil organic matter due to increased inputs of plant litter. Methods Study Site and Treatments This st udy took place in riparian shrub tundra located near Toolik Field Station at

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89 elevation 760m) in the foothills region on the North Slope of Brooks Range, Alaska, USA. The e ntire northern foothills region of the Brooks Range is treeless and underlain by continuous permafrost, 250 300 m thick (Osterkamp and Payne 1981). Mean annual air temperature is around 10C, with averag e summer temperatures from 7 12 C. Annual prec ipita tion is 318 mm, with 43% falling in the winter (http://ecosystems.mbl.edu/ARC). Average snow depth is 50 cm, although snow distribution can be variable due to redistribution by wind. Snow melt occurs in early May. In 1989, two replicate randomized blo cks were established in riparian shrub tundra with each block containing four 5 m x 10 m plots separated by 1 m buffer strips. Within each block, plots were randomly assig ned to the following treatments: control, nutrient addition, elevated temperature, a nd nutrient addition with elevated temperature. Nutrients have been manipulated annually since 1989 by adding 10 g N/m 2 of Nitrogen (N) as NH 4 NO 3 and 5 g P/m 2 of Phosphorus (P) as P 2 O 5 in the spring immediately following snow melt. Temperature was manipu lated by placing a greenhouse over the shrub tundra during the months of June through August. Greenhouses were built of transparent 0.15 mm (6ml) plastic stretched over an A shaped 2.4 m by 4.9 m wooden frame. Plastic was removed each autumn prior to sno w fall and replaced in the spring. The treatments were similar to those described in Chapin et al. (1995). The sites are currently being maintained by the Arctic Long Term Ecological Research Station and still receive their annual nutrient additions and heating treatments. Environment Two profiles of soil temperature were measured at four depths (moss level 1, 10, 20, 40 cm) within each treatment in block two using copper/constantan thermocouple

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90 wires connected to a data logger (Campbell Scientific CR10, Campbell Scientific, Inc., Logan, Utah, USA). Soil sensors were read every 15 minutes and averaged every three hours. Mean annual soil temperatures during the growing season (June August), and winter season (January May plus September December) were calc ulated using data collected in 2007. Biomass We measured all aboveground and belowground stem biomass by destructively harvesting all shrubs from three separate 50 x 50 cm quadrats within each plot for each treatment within each block. Understory plants and mosses were collected from a 10 x 40 cm area nested within the 50 x 50 cm quadrat. Each quadrat was sorted into species and then into tissue type (ex. inflorescences, new growth, and old growth). The separated samples were then dried for a minimum o f 48 hours at approximately 65 C and then weighed for biomass. Biomass measurements are expressed on a per meter squared basis. Total biomass for each treatment was determined by first calculating the mean total b iomass across the three quadrat s per tre atment and block. The total biomasses per block were then averaged to get a final value for each treatment. To determine total biomass per functional group, biomass for each functional group was averaged across the three quadrats per treatment and block and then averaged again across the two blocks per treatment. Rhizomes within the organic layer were removed from the same 10 x 40 cm quadrats used to determine aboveground understory and moss biomass according to methods described in (Bret Harte et al., 2 008). Root biomass was measured by removing by hand all live roots from soil cores collected from each quadrat within each treatment and block. Two soils cores, adjacent to each other, were removed and

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91 combined to provide enough material for processing. Organic soils were removed in five by five using a five cm diameter mineral core down to the permafrost layer. Roots were coarse (> 2mm diameter) and were dried at 60 C for a minimum of 48 hours before weighing. Roots and rhizomes from the organic and mineral layer were combined to estimate total belowground root and rhizome biomass. All biomass measurements are expressed on a per area basis. Aboveground Net Primary P roduction Net primary production (NPP) was calculated for aboveground vascular plants only and did not include any old leaves, belowground parts, or rhizomes. Aboveground production was separated by parts: l eaves, new stems, secondary stem growth, and inflorescence/fruit. Leaves included new leaves, all aboveground material for forbs, and the blades/sheaths of the graminoids. Secondary stem growth was estimated for stems that were produced in previous years using estimated values of the percentage of secondary growth that contributes to NPP calculated in Bret Harte et al. (2002). For Betula nana 16 percent secondary contribution to NPP was used, for all S alix species an estimate of 18 percent, and for Ledu m palustre 8 percent was used. A mean of Betula nana and Salix pulchra estimates was used for Potentilla fruticosa and came to 16.95 percent. We assumed negligible secondary growth for Dryas integrifolia Empetrum nigrum Rubus chamaemorus Vaccinium vit is idaea and did not include their stem in the ANPP calculation.

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92 Species Diversity Biomass for each species was summed across all replicates within a tre atment for construction of rank abundance curves. Species were ranked within each treatment by their biomass, with number one being the most abundant species within that treatment. Soil P roperties A separate set of soil cores were removed in the exact same way as the root cores in order to examine soil characteristics Prior to analysis, soils were homog enized by hand and the > 2 mm diameter fraction (e.g., roots, rhizomes, co a rse woody debris, and rocks) was removed. Soil water content was calculated by subtracting the weight of th e soil, after being dried at 60 C (organic soils) or 105 C (mineral soil s) for 48 h, from the wet weight of the soil and then dividing by the dry weight of the soil. Soil bulk density was determined by dividing the oven dry equivalent soil by the core volume. Carbon and Nitrogen Pools Dried plant and organic soil samples f rom all qu adrat s, treatments, and blocks were ground to a fine powder on a Wiley mill with a #40 mesh screen. Mineral soils were hand ground using a mortar and pestle. Bulk C and N were determined on all plant parts for each species and for both organic and miner al soil layers using an ECS 4010 elemental analyzer (Costech Analytical, Valencia, California, USA). Pools of dissolved inorganic N (N NH 4 + and N NO 3 ) were measured by extracting 10 g of fresh soil with 50 ml of 0.5 M K 2 SO 4 The soil slurry was agitated on a shaker table for 2 h, allowed to sit overnight in a cooler, and then vacuum filtered through a Whatman GF/A filter. Filtrate was frozen until analyzed colorimetrically, on a

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93 segmented flow autoanalyzer (Astoria analyzer, Astoria Pacific, Inc Clackamas, Oregon, USA). Statistical Analysis Differences in aboveground biomass among treatments and among plant functional groups were tested using a three way ANOVA with fertilization (NP), greenhouse (T), and plant functional group as the main effe cts and block as a random effect. All possible interactions were also tested. Differences in all other variables were tested using separate two way Anova models with Treatment (C, NP, T, and NP+T) as the main effect and block nested within treatment as a showed significance at a level of p < 0.10. We chose this level of significance because of the low level of replication in our experiment. We are constrained by the initial set up of the experiment and due to the long term nature of the experiment and the lac k of experimental manipulation studies in shrub tundra communities within the Arctic we feel that even a significance at the p < 0.10 level c an provide useful information to make inferences on how these communities will respond to environmental change. All statistical analyses were performed using the software package JMP v. 8. Results Environmental D ata The greenhouse warming treatment sign ificantly increased mean annual soil temperature by 0.5 C at a depth of 10 cm compared to the non warming treatments (One way ANOVA with treatment as the main effect: F 3,4 = 2.3, p = 0.06; Table 4 1). The warming treatment in creased temperatures by 0.5 0. 8 C during the growing season

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94 and 0.4 C during the winter season, although, only the winter season was significantly different (F 3,4 = 13.3, p = 0.02; Table 4 1). There was no significant difference among treatments in soil temperature at either the moss layer or at 20 and 40 cm depths (data not shown). Soil moisture did not significantly differ among treatments (Table 4 1). Biomass Total aboveground biomass increased by 43 percent with nutrient addition and 38 percent with increased warming, although onl y the nutrient treatment was statistically significant (Fig. 4 1; Treatment: F 3 16 = 5.5, P < 0.01). There was no significant nutrient by temperature interaction, suggesting that the 74 percent increase in biomass seen in the nutrient plus warming treatme nt was an additive effect of warming and increased temperature (Table 4 3). There was no significant difference between blocks in aboveground biomass. Deciduous shrubs made up the greatest biomass compared to biomass from other growth forms for all treat ments. Fertilization plus warming significantly increased deciduous biomass compared to the control (F 3,4 = 5.0, p = 0.08). Biomass of all other functional groups, except graminoids, declined with the addition of nutri ents and temperature although, due t o small sample size only moss was statistically different (F 3,4 = 5.2, p = 0.07; Fig. 4 1, Table 4 4). Aboveground Net Primary P roduction Total ecosystem aboveground net primary production for vascular plants increased in the nutrient plus temperature tr eatment, although this was only marginally significant (Treatment: F 3,4 = 3.7, p = 0.12). The largest increase in growth occurred in secondary stem growth (F 3,4 = 6.2, p = 0.06; Fig. 4 2). Both new leaves and new stems increased in the nutrient addition treatments although this increase was not statistically

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95 different. Production of inflorescences and fruits declined with nutrient addition and warming (F 3,4 = 5.0, p = 0.08; Fig. 4 2). Species D iversity The control site had a total of 21 different vascu lar plant species (Fig. 4 3 and Table 4 2). After 18 years of adding nutrients or increasing temperature species diversity declined to 12 and 13 species in the nutrient addition and the warming treatments, respectively. The greatest species loss occurre d in the interact ion treatment n utrient addition plus temperature, which resulted in only six different species (Fig. 4 3 and Table 4 2). Deciduous shrubs Betula nana and Salix spp were the most abunda nt species across all four treatments Warming and a dded nutrients resulted in a decline in forb, graminoid and evergreen shrub diversity (Fig. 4 3 and Table 4 2). Soil P roperties There was no significant difference in soil layer depth, bulk density, or concentrations of ammonium among any of the four tr eatments (Table 4 1). Soil nitrate concentrations significantly increased in the NP treatment only (F 3,4 = 13.8, p = 0.01; Table 4 1) Carbon and Nitrogen pools Total ecosystem C pool did not differ across treatments; however, there was a marginally sign ificant increase in aboveground C pool with the nutrient plus temperature treatment having the greatest aboveground C pool (Fig. 4 4). Belowground C pool was not significantly different across treatments. Total ecosystem N pool was also not different ac ross treatments. There was however a significant increase in aboveground N pool for the nutrient plus warming treatment (Treatment: F 3,4 = 4.5, p = 0.09; Fig. 4 4). Belowground N pool was not significantly different across treatment s

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96 The C to N ratio o f the aboveground biomass was greater in the temperature and the nutrient plus temperature treatments and this was marginally significant ly different (F 3,4 = 3.3, p = 0.14). Mean ( SE) C to N ratios ranged from 60 (5), 55 (10), 78 (5), and 72 (0.4) in th e control, NP, T, and NP + T treatments, respectively. Added nutrients plus warming resulted in an increase in C pools in shoots, woody standing dead, and litter by four, four, and eleven times respectively, relative to the control. N pool also increased two times in shoots, four times in woody standing dead, 17 times in litter, and one and half times in roots in the added nutrients plus warming treatment relative to the control. There was no difference in C or N pools across treatments for rhizomes, orga nic soil, or mineral soil (Table 4 5 and Fig. 4 5). Allocation Warming increased biomass, C, and N allocation to aboveground stems (Biomass: F 3,4 = 27.1, p < 0.01; C: F 3,4 = 30.0, p < 0.01; N: F 3,4 = 60.0, p < 0.001) and decreased allocation to belowground stems (Biomass: F 3,4 = 5.1, p = 0.08; C: F 3,4 = 7.1, p < 0.01; N: F 3,4 = 4.8, p = 0.08 ; Table 4 6 ). There was no effect of warming or nutrient addition on biomass, C, or N allocation to leaves or roots (Fig. 4 6). Nutrient addition resulted in a decrease in C to N ratio in leaves (F 3,4 = 4.5, p = 0.09). In contrast, warming caused an increase in C to N ratio in aboveground stems (F 3,4 = 4.6, p = 0.09). There was no difference in C to N ratios in belowground stems or roots with warming or nutrient additi on (Fig. 4 7). With warming and nutrient additions, deciduous shrubs allocated more biomass, C, and N to aboveground stems (Biomass: F 3,4 = 14.3, p = 0.01; C: F 3,4 = 16.5, p = 0.01; N: F 3,4 = 14.4, p = 0.01) and decreased allocation to belowground stems ( Biomass: F 3,4 = 9.0, p = 0.03; C: F 3,4 = 10.0, p = 0.03; N: F 3,4 = 7.5, p = 0.04; Fig. 4 8). Allocation to

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97 leaves did not change with treatments. In contrast, graminiods decreased biomass, C, and N allocation to belowground stems (Biomass: F 3,4 = 4.3, p = 0.10; C: F 3,4 = 4.3, p = 0.09; N: F 3,4 = 6.6, p = 0.05; Fig. 4 8). Allocation to leaves and aboveground stems did not change with treatment. Biomass, C, and N allocation between plant parts within forbs also did not change with treatments. Discussion Controls over biomass and productivity As with other ecosystems in the region, the riparian shrub community responded to long term nutrient additions by increasing biomass and ANPP; however, the magnitude of the response was not as great as seen in moist acidic arctic plant communities, suggesting that riparian shrub communities may not be as N limited as moist acidic tundra communities (Chapin et al. 1995, Mack et al. 2004). It has been estimated that shrub community ANPP requires ~ 4.4 g N per m 2 per ye ar compared to 2 g N per m 2 per year for moist acidic tundra (Shaver and Chapin 1991); thus, our annual addition of 10 g N per m 2 year is only about double the annual requirement and does not consider any immediate N loss from leaching and denitrification or N made unavailable to the plants by immobilization by soil microbes. Therefore we may not be adding enough N to increase production to the magnitude seen in moist acidic tundra, which has a lower N requirement. The warming treatment stimulated an inc rease in both biomass and ANPP. However, the increase was relatively small ; suggesting that the 0.5 C increase in annual soil temperature was not enough to relieve direct temperature limitation that may be occurring in riparian shrub communities or to st imulate enough of an increase in

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98 plant available nutrients. A similar response to warming addition was seen in moist acidic tundra and moist non acidic tundra which showed a decrease in aboveground biomass with no change or a relatively small increase com pared to added nutrients on ANPP (Chapin et al. 1995, Gough and Hobbie 2003). We were surprised to see such a dramatic increase in biomass and ANPP in the nutrient plus warming treatment and to discover that this was an additive and not an interactive ef fect. It is possible that warming caused an increase in plant available nutrients and the additional nutrients plus the nutrients added with fertilization was enough to relieve nutrient limitation result ing in an almost doubling of plant biomass compared with nutrient additions or warming alone. We were unable to detect an increase in inorganic N in the soils in the warming treatment. However, any nutrients made available could have been immediately taken up by plants. In addition, other studies have s hown that warming manipulations can result in early leaf expansion (Chapin and Shaver 1996, Arft et al. 1999). This increased growth and photosynthetic activity would require a higher demand for nutrients early in the growing season soon after the plots w ere fertilized. Results from other tundra manipulation studies have suggested that temperature can constrain early season gr owth while nutrients constrain late season growth (Chapin and Shaver 1996). Thus the potential warming response of early leaf out and measured increase in growth in combination with the increased nutrient availability from fertilization may have contributed to the stronger biomass and ANPP response seen in the nutrient plus warming treatment. Such a large response to nutrients plu s warming compared to warming or nutrients alone has not been seen in the few studies in other ecosystems in this region that have manipulated both nutrients

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99 and temperature together (Chapin et al. 1995, Gough and Hobbie 2003) but has been seen in sub arct ic systems in Sweden (Jonasson et al. 1999). The other ecosystems studied in Alaska vary more in their plant functional type composition than our riparian shrub system or the systems studied in Sweden, which were dominated by shrubs. Shrubs have been sho wn to respond strongly to independent nutrient addition and warming treatments (Jonasson et al. 1999, Dormann and Woodin 2002) suggesting that if we have a system that is dominant ed by a plant functional group that responds positively to nutrients and war ming it would make sense that we would see a greater ecosystem response when nutrients and warming are manipulated together. The increase in biomass seen with nutrient additions and warming resulted in an amplification of the already dominant functional g roup, deciduous shrubs, a reduction in both graminiod and forb biomass, and a complete loss of evergreen shrubs. Changes in nutrients and temperature had no effect on belowground biomass and this lack of response is similar to the few studies that have al so measured belowground biomass with nutrient additions (Mack et al. 2004) or with nutrients and warming (Gough and Hobbie 2003). Changes in C and N pools Surprisingly, there was no detectable change in total ecosystem C or N pools with added nutrients or with warming even though we saw an increase in C and N pools in shoots, woody standing dead, and fine litter. Our low sample size and the heterogeneous nature of the soil prevented us from being able to detect any differences in soil C and N pools that may have occurred across our treatments. Mack et al. (2004) also found that C and N pools in shoots, standing dead, and litter all increased after 19 years of added nutrients in moist acidic tundra located in the same region. However, in

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100 contrast to our study, they were able to detect a decrease in C pools in deeper soil layers that was substantially larger than the increase in aboveground C pools. Similar to biomass and ANPP, the largest responses seen in C and N pools in our study were in the nutrient plus warming treatment. Species diversity The loss of species diversity and functional group representation with increased nutrients and warming is not surprising since this system is dominated by deciduous shrubs that produce a dense canopy allowing o nly shade tolerant species to survive below. Loss of species diversity with environmental manipulations has been seen in other warming (Chapin et al. 1995, Gough and Hobbie 2003, Hollister et al. 2005) and nutrient addition (Chapin et al. 1995, Gough et a l. 2002, Gough and Hobbie 2003) experiments with greater loss seen in nutrient plus warming treatment s for at least one other experiment (Chapin et al. 1995). The complete loss of evergreens with fertilization has also been seen in other nutrient additio n studies, mostly in the Alaskan arctic, and has been attributed to the strong growth and biomass response of deciduous shrubs resulting in the shading out of the understory evergreens (Chapin et al. 1995). In contrast, in sub arctic Sweden evergreen sh rub biomass has been shown to increase while deciduous shrub biomass decrease s with additional nutrients and warming (Jonasson et al. 1999). These Sweden ecosystems were dominated by evergreen shrubs and had few deciduous shrubs present to increase biomas s enough to result in shading of the evergreens. Shifts in allocation Nutrient additions and warming resulted in an increase in aboveground allocati on of biomass, C, and N to long lived woody stems with the greatest increase seen in the

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101 nutrient plus war ming treatments. This pattern was driven by changes in allocation within the deciduous shrubs, which increased allocation to aboveground stems, while changes in aboveground allocation were not detected in the other functional groups present in this system In contrast belowground allocation of biomass, C, and N decreased in belowground stems, primarily in the warming treatments. Again this was driven by changes in allocation within deciduous shrubs although graminoids decreased allocation to belowgroun d stems with nutrient additions as well. Interestingly, C allocation to belowground stems decreased more in the warming only treatment. Temperature enhanced vegetation growth would require additional carbon and nutrient reserves. If these additional requ irements cannot b e met by uptake of nutrients the n reserves from belowground rhizomes may be used which could result in less allocation of biomass, C, or N belowground to rhizomes (Chapin and Shaver 1996), explaining the decline in belowground allocation seen in the warming treatments. Changing C balance An increase in woody production in response to warming and nutrients, as seen in this study, could have important implications for ecosystem C cycling. Woody stems store more C than non woody plant ma terial and can take longer to decompose compared to other plant parts (Hobbie 1996). If there was no simultaneous decrease in belowground soil C stores, future warming in conjunction with increase d nutrients in the North American arctic could result in a negative feedback, where more C is taken up by shrub growth and stored in tissue that has a longer C turnover time. However, more measurements of soil C and N dynamics in warming and nutrient treatments are needed to better understand how the belowground component of the ecosystem will respond and contribute to total ecosystem C and N and feedback to global C cycling.

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102 Our study is another example of how different arctic vegetation types do not always respond the same way to environmental change. Mode ls that try to simulate arctic vegetation response to global climate change need to include a full range of vegetation types across regions and their individual responses. More long term data sets that represent more of the dominant vegetation communities within the arctic are needed to increase our understanding and predictive power of how the arctic will respond to environmental change. Riparian shrubs in the Alaskan arctic responded to long term environmental changes of increased nutrients and warming by increasing biomass and productivity of the dominant functional group, deciduous shrubs, resulting in an increase in C and N stored in aboveground shoots, woody standing dead, and litter. In addition, nutrient addition and warming shifted allocation of biomass, C, and N to aboveground stems and reduced allocation to belowground stems. Species diversity and the representation of other functional groups such as evergreen shrubs and forbs declined with environmental manipulations. In all cases, the effect s of environmental manipulations were more pronounced in the nutrient plus warming treatments. A future arctic that is warmer and has more nutrients has the potential to alter riparian shrub ecosystem structure and function and should be considered when m aking predictions about arctic vegetation responses to future climate change.

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103 Figure 4 1. Aboveground biomass (g/m 2 ) from shrub tundra harvested in the eighteenth year of treatment (C = control, NP = Nitrogen and phosphorus additions, T = warming manipulation, and NP + T = Nitrogen and phosphorus additions plus warming manipulation) separated by functional group and belowground biomass (g/m 2 ) separated by roots and rhizomes. Different letters indica te significance among treatments in total aboveground biomass. (Mean SE, n = 2)

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104 Figure 4 2. Aboveground vascular net primary production (ANPP) across treatments and separated by plant parts. Different letters indi cate significance among treatments in total ANPP. (Mean SE, n = 2) Figure 4 3. Vascular plant biomass dominance diversity curves sampled 18 years after initiation of treatments. The sequence in abundance of growt h forms represented by each species in each treatment is also shown, with the relative number of repeated letters indicating abundance: forb (F), graminoid (G), deciduous (D), and evergreen (E).

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105 Figure 4 4. Total eco system C and N pools separated by above and belowground for each treatment. Different letters indicate significant differences between aboveground N pools across treatments. (Mean SE, n = 2)

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106 Figure 4 5. Ecosystem C and N pools after 18 years of experimental manipulation of nutrients and temperature. Different letters indicate significant differences across treatments within the same component. (Mean SE, n = 2)

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107 Figure 4 6. Proportional allocation of vascular plant biomass, C, and N to different plant parts across each treatment. Different letters indicate significance across treatments within the same plant part.

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108 Figure 4 7. Carbon to nitrogen ratios of plant tissues across treatments. (Mean SE, n = 2)

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109 Figure 4 treatments. Different letters indicate significance across treatments within the same plant part. For total biomass, evergreens, graminoids, and forbs are graphed on the same scale.

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110 Table 4 1. Soil properties measured across all four treatments after 18 years of manipulation Different letters indicate significance across treatments. Soil properties C NP T NP + T Soil temperature ( C) Annual 0.80 (0.10) 1.63 (0.50) 0.28 (0.05) 0.3 4 (0.03) Growing season 5.02 (0.16) 5.01 (1.01) 5.78 (0.16) 5.49 (0.30) Winter 2.77 ab (0.19) 3.88 b (0.32) 2.34 a (0.02) 2.33 a (0.14) Soil moisture (g H20/g soil) Organic 1.68 (0.38) 1.17 (0.08) 0.72 (0.26) 1.47 (0.87) Mineral 1.12 (0.43) 0.85 (0.26) 0.95 (0.50) 0.76 (0.18) Soil layer depth (cm) Organic 15.56 (4.69) 9.17 (2.50) 7.21 (2.54) 11.04 (2.54) Mineral 13.83 (2.42) 9.23 (2.35) 8.04 (3.13) 10.98 (5.35) Bulk density (g/cm3) Organic 0.11 (0.01) 0.10 (0.03) 0.09 (0.03) 0.11 (0.02) Mineral 0.33 (0.01) 0.46 (0.001) 0.40 (0.04) 0.47 (0.17) N NH 4 + (ug/g soil) Organic 56.63 (8.97) 165.71 (75.43) 65.54 (6.11) 94.24 (11.18) Mineral 17.32 (7.69) 22.81 (6.62) 18.48 (2.56) 17.01 (2.99) N NO 3 (ug/g s oil) Organic 1.68 (0.74) 146.48 (74.21) 0.50 (0.05) 6.78 (5.43) Mineral 1.49 (0.28) 32.30 (26.99) 0.38 (0.18) 1.67 (0.91)

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111 Table 4 2. Vascular plant species rank by treatment based on aboveground biomass with number one being the most abundan t species; no number indicates that species was not present in the plot. Functional group Species C NP T NP + T Forb Aconitum delphinifolium 21 Anemone richardsonii 14 Artemesia alaskana 16 6 Petasites frigidus 19 Polygonum sp. 15 6 Polygonum bistorta 11 11 11 Pyrola secunda 17 Senecio lug ens 9 Stellaria longipes 20 3 Valeriana capitata 12 7 12 Graminoid Arctagrostis latifolia 4 Calamagrostis canadensis 8 6 4 5 Calamagrostis lap 8 7 Carex bigelowii 9 12 Carex hyp nophillum 10 Carex pod ocarpa 7 10 Carex vaginatum 9 Poa arctica 10 5 5 Deciduous shrub Betula nana 2 3 2 3 Potentilla fruticosa 4 4 Rubus chamaemorus 18 Salix glauca 1 2 3 1 Evergreen shrub Salix pulchra 3 1 1 2 Empetrum nigrum 5 Ledum palustre 13 Vaccinium vitis idaea 6 8

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112 Table 4 3. A boveground biomass (g/m 2 ) for the most abundan t species and functional groups ( Mean SE n = 2) Total Biomass (g/m 2 ) Growth form/species C NP T NP + T Forb Artemesia alaskana 0.5 0.4 0 4 4 0 Polemonium acutiflorum 0.7 0.7 0 0 2 2 Polygonum bistorta 2 0.5 0.1 0.1 0.2 0.2 0 Valeriana capitata 1 1 3 2 0.03 0.03 0 Total 6 4 3 2 5 3 1 1 Graminoid Arct agrostis latifolia 0 0 0 10 10 Calamagrostis canadensis 3 3 3 0.1 18 18 3 3 Calamagrostis lapponica 0 2 2 2 2 0 Carex bigelowii 2 2 0 0 0 Carex podocarpa 5 5 0 0.2 0.2 0 Poa arctica 2 2 15 15 5 5 0 Tot al 11 3 20 18 25 15 14 14 Deciduous Betula nana 205 41 390 130 573 573 86 86 Potentilla fruiticosa 46 46 31 31 0 0 Rubus chamaemorus 0.4 0.4 0 0 0 Salix glauca 338 338 443 133 109 109 2116 2116 S alix pulchra 169 162 736 230 761 414 1268 1255 Total 758 262 1601 201 1443 269 3470 947 Evergreen Empetrum nigrum 33 33 0 0 0 Ledum palustre 1 1 0 0 0 Vaccinium vitis idaea 10 7 0 1 1 0 Total 43 41 0 1 1 0 Mosses Sphagnum spp. 32 32 0 0 0 Non sphagnum spp. 47 2 1 1 2 2 0 Total 79 34 1 1 2 2 0 Lichen 22 22 0 0 0

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113 Table 4 4. Three way ANOVA results comparing aboveground biomass among treatments. Main Effects df F ratio P value NP 1 7.8 0.05 T 1 6.2 0.07 NP x T 1 1.4 0.30 Growth form 6 54.3 < 0.0001 NP x Growth form 6 8.6 < 0.0001 T x Growth form 6 6.8 < 0.0001 NP x T x Growth form 6 1.5 0.22 Table 4 5. Two way ANOVA results comparing N or C pool across treatments (C, NP, T, NP + T) within the same component. Block = 2 Component Pool (g/m 2 ) F stat df P value Shoots Carbon 4.5 3 0.09 Nitrogen 4.3 3 0.10 Rhizomes Carbon 0.1 3 0.94 Nitrogen 0.5 3 0.71 Total root s Carbon 1.0 3 0.49 Nitrogen 5.2 3 0.07 Woody standing dead Carbon 9.0 3 0.03 Nitrogen 4.7 3 0.09 Fine litter Carbon 4.1 3 0.11 Nitrogen 3.7 3 0.12 Total organic soil Carbon 0.9 3 0.50 Nitrogen 1.0 3 0.48 Mineral soil (0 10 cm) Ca rbon 0.3 3 0.82 Nitrogen 0.3 3 0.80 T able 4 6. Two way ANOVA results comparing biomass, C, or N allocation across treatments (C, NP, T, NP + T) within the same plant part. Block = 2 F stat df P value Biomass allocation Leaves 1.0 3 0.49 Aboveg round stems 27.1 3 < 0.01 Belowground stems 5.1 3 0.08 Roots 2.7 3 0.18 Carbon allocation Leaves 1.3 3 0.39 Aboveground stems 30.0 3 < 0.01 Belowground stems 7.1 3 0.04 Roots 2.6 3 0.19 Nitrogen allocation Leaves 0.6 3 0.65 Aboveground stem s 60.0 3 < 0.001 Belowground stems 4.8 3 0.08 Roots 2.2 3 0.23

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114 CHAPTER 6 CONCLUSION Results from this dissertation showed that on a short time scale, shrub int eractions with snow may play a role in increasing plant available N, primarily through effect s on the summer soil microenvironment that increase s N availability when plants are most active. In contrast, small changes in soil temperature and moisture associated with additional snow trapping by shrubs is unlikely to influence litter nutrient turnov er enough to drive positive snow shrub feedbacks, as proposed by Sturm et al. (2001). However, long term changes in litter quality inputs associated with different dominant plant species could lead to alterations in SOM quality, soil nutrients, and microbi al communities, which in turn, can significantly alter litter decomposition processes. In addition, t h e quality of SOM matter which can be linked to species specific traits such as litter allocation and litter quality, may be more of a limiting factor in determining mineralization rates of N than small changes in temperature Assuming that our natural shrub gradient represents the structure and function of future clim ate driven shrub communities, I would expect a shrubbier arctic to have greater abovegro und and belowground biomass, higher soil temperatures, and higher quality of SOM that favors higher rates of N fluxes. If all species respond similarly to Betula papyrifera when incubated at the medium and low shrub site, an increase in deciduous shrub co ver could actually lead to slower rates of litter decomposition and nutrient turnover and, thus, an increase in C sequestration. Retaining N in litter may be beneficial for soil organic matter (SOM) decomposition and could help explain why we see more soi l N and greater N mineralization at the medium and high shrub sites.

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115 This dissertation also showed that riparian shrubs in the Alaskan arctic responded to long term environmental changes of increased nutrients and warming by increasing biomass and produ ctivity of the dominant functional group, deciduous shrubs, resulting in an increase in C and N stored in aboveground shoots, woody standing dead, and litter. In addition, nutrient addition and warming shifted allocation of biomass, C, and N to abovegroun d stems and reduced allocation to belowground stems. Species diversity and the representation of other functional groups such as evergreen shrubs and forbs declined with environmental manipulations. In all cases, the effects of environmental manipulation s were more pronounced in the nutrient plus warming treatments. A future arctic that is warmer and has more nutrients has the potential to alter riparian shrub ecosystem structure and function, resulting in a system that has low plant species diversity an d is dominated by deciduous shrubs that allocate more biomass, C, and N to long lived woody stems. These responses should be considered when making predictions about arctic vegetation responses to future climate change.

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116 APPENDIX A SUPPLEMENTARY MATERI AL F OR CHAPTER 2 A.1 Additional methods: Characterizing ecosystem structure Live aboveground biomass in each site was determined by harvesting all plant species within 12 10 by 40 cm quadra ts at the low shrub site. Due to the high heterogeneity of the plant co mposition at the low shrub site, two quadra ts were taken next to each and then averaged. For both the medium and high shrub sites, the understory was removed from s ix similar 10 by 40 cm quadra ts nes ted within a 50 by 50 cm quadra t, from which the oversto ry was removed. All plant material was dried at 60 C for a minimum of 48 hours and weighed. From the harvested species, we categorized deciduous shrubs as those shrubs that have the physiological ability to substantially increase their height and biomass including: Betula nana Salix pulchra S. glauca S. richardsonii and V. uliginosum Only total biomass and deciduous shrub biomass are presented here. Rhizomes within the organic layer were removed from the same 10 x 40 cm quadrants used to determine aboveground biomass acc ording to methods described in Bret Harte et al., ( 2008). Root biomass within the organic layer of each plot w as measured in five by five cm soil monoliths that extended down to the surface of the mineral layer. From the mineral su rface to the permafrost layer, both root and rhizome biomass was measured in a five cm diameter core. Roots and rhizomes were hand picked from soil samples and separated into fine (< 2 mm in diameter) roots, coarse (> 2 mm in diameter) roots and all rhiz omes, and dried at 60 C for a minimum of 48 hours and weighed Roots and rhizomes from the organic and mineral layer were combined to estimate total belowground root and rhizome biomass.

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117 Figure A 1 Annual ambient sn ow depth for each plant community. (Mean SE) Table A 1 B elowground biomass at each site. Mean (SE) Note: Lower case letters indicate a signific ant difference when p<0.05. Sites Belowground Biomass (g/m 2 ) n Low Medium High Organic Soil Fine roots 8 405.8 (109.1) 414.8 (78.2) 442.4 (83.2) Coarse roots 1 5 109.6 (55.9) 26 5.6 (NA) 341.9 (151.7) Rhizomes 8 611.0 a (59.5) 1050.9 ab (217.3) 1618.8 b (233.1) Total 8 1071.6 a (140.3) 1499.0 ab (215.8) 2275.0 b (338.5) Mineral Soil Fine roots 7 8 355.8 (128.0) 232.8 (39.4) 252 .6 (62.2) Coarse roots 1 2 26.9 (NA) 54.8 (4.7) 33.1 (22.4) Rhizomes 3 410.4 (308.3) 108.3 (34.4) 109.1 (36.8) Total 7 8 535.5 (244.5) 287.1 (39.1) 308.8 (76.5)

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118 Table A 2 K 2 SO 4 extractable soil nutrients down to 10 cm within the organic layer. Values are means ( SE). DON and MB N were ana lyzed using a 2 way ANOVA; NH 4 + N, and NO 3 N pools were analyzed using Kruskal Wallis. Lower case letters indicate significance among sites within a season, while asterisks indicate significance between seasons within the same site. Capital letters indi cate significance between season and among sites and include interaction effects June Sept (ug/g soil) Low Medium High Low Medium High DIN NH 4 + N 10.2 a (2.10) 81.4 b (11.96) 194.2 b (32.99) 6.9 a (1.06) 30.6 b (9.83) 70.4 b (25.84) NO 3 N 1.8 (1.82) 2.1 (1.03) 5.0 (2.02) 0.9 (0.67) 4 .1 (1.64) 5.6 (2.89) DON 67.9 a (18.34) 139.7 a (29.01) 299.3 b (25.94) 81.9 (13.06) 96.3 (19.09) 178.4 (14.59) MB N 503.2 a (49.16) 631.9 a (28.85) 807.3 b (53.19) 536.8 (51.05) 510.1 (40.95) 569.3 (76.45) Pools (g/m 2 ) DIN NH 4 + N 0.03 a (0.007) 0.46 a (0.068) 0.96 b (0.16) 0.025 a (0.003) 0.17 ab (0.056) 0.35 b (0.13) NO 3 N 0.01 (0.006) 0.01 (0.006) 0.03 (0.010) 0.004 (0.003) 0.02 (0.009) 0.03 (0.014) DON 0.23 A (0.062) 0.79 AB (0.165) 1.48 B (0.129) 0.27 A (0.044) 0 .55 AB (0.108) 0.59 A (0.19) MB N 1.69 A (0.165) 3.59 AB (0.164) 4.00 B (0.264) 1.80 A (0.171) 2.90 A (0.232) 1.41 AB (0.65)

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119 APPENDIX B SUPPLEMENTARY MATERI AL FOR CHAPTER 3 Figure B 1. Initial mass, C, and N remaining from litter bags that contained either n atural or fertilized plant species. Bags were incubated over five years in a common site (moist acidic tussock tundra). (Mean SE ; n = 6 )

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120 Figure B 2. Initial mass, C, and N remaining from litter bags that contained either natural or fertilized plant species. Bags were incubated over five years in a common site (moist acidic tussock tundra). (Mean SE ; n = 6 )

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121 Figure B 3. Initial mass, C, and N remaining from litter bags that contained either natural or fertilize d plant species. Bags were incubated over five years in a common site (moist acidic tussock tundra). (Mean SE ; n = 6 )

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122 Figure B 4. Initial mass, C, and N remaining from litter bags that contained either natural or fertilized plant species. Bags were incubated over five years in a common site (moist acidic tussock tundra). ( Mean SE ; n = 6 )

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123 Figure B 5. Leaf litter decay constants (k) vs. leaf percent C, cell soluble, and cellulose for 11 vascular plant species collected across nine sites and decomposed for three to five years in the same common garden (n = 3 6). Percent C includes three moss species collected at one site and incubated for five years in the same common garden (n = 5 6). ( Mean SE)

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124 Figure B 6. Stem litter decay constants (k) vs. percent cellulose for four deciduous shrub species incubated for three years in a common garden (Mean SE ; n = 3 )

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125 Table B 1. S oil temperature at 5 cm during the growing season (62 days) and winter (272 days) for the three year period our litter decompositi on bags were incubated (Mean SE ; n = 3 4 ) Growing Season Winter Vegetation Type Treatment 2006 2007 2008 2006 2007 2007 2008 2008 2009 Low Ambient 5.0 (0.50) 6.6 (0.50) 2.7 (0.44) 7.4 (0.68) 8.6 (0.36) 3.9 (0.43) Snow Addition 5.0 (0.43) 6.6 (0.89) 3.6 (0.36) 4.7 (0.36) 4.9 (0.06) 2.8 (0.15) Medium Ambient 6.0 (0.86) 6.6 (1.45) 4.6 (1.83) 3.8 (0.57) 3.6 (0.53) 2.7 (0.04) Snow Addition 7.0 (0.63) 7.2 (0.68) 5.9 ( 1.77) 2.7 (0.72) 3.4 (0.10) 1.7 (0.05) High Ambient 5.9 (0.36) 7.9 (0.91) 5.7 (0.58) 3.6 (0.58) 5.8 (0.81) 2.4 (0.80) Snow Addition 7.8 (0.31) 8.7 (0.62) 6.7 (0.34) 2.9 (0.82) 4.8 (0.08) 0.8 (0.54)

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126 Table B 2. Three way repeated measures AN OVA comparing differences in soil temperature between vegetation type, treatment, and year. Growing Season Winter Source df F Prob df F Prob Vegetation Type 2 4.96 0.02 2 12.66 <0.01 Treatment 1 1.97 0.18 1 6.23 <0.01 Year 2 38.30 <0.00 01 2 61.18 <0. 00 1 Vegetation Type X Treatment 2 0.21 0.82 2 0.71 0.52 Vegetation Type X Year 4 2.17 0.10 4 6.08 <0.01 Treatment X Year 2 0.81 0.47 2 1.01 0.42 Vegetation Type X Treatment X Year 4 0.34 0.85 4 2.32 0.12

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127 Table B 3. I nitial litter quality for senesc ed leaves and stems of Betula nana and Salix pulchra collected in each of our three plant communities and incubated at a common site. Different letters within the same foliar trait and part indicate a significant result at the p < 0.05 level and are post hoc results after running two comparing each variable across sites and between species, including site x species interactions. (Mean SE ; n = 6 for leaves, n = 3 for stems ) Site Low Medium High Foliar traits Betula Salix Betula Salix Betula Salix N (%) Leaves 1.16 ab (0.02) 0.92 b (0.03) 1.14 ab (0.07) 0.93 ab (0.06) 0.93 b (0.09) 1.27 a (0.16) Stems 0.90 (0.02) 0.90 (0.21) 1.06 (0.10) 0.95 (0.16) 1.37 (0.19) 1.01 (0.16) C (%) Leaves 49.34 a (0.11) 48.96 b (0.12) 49.42 a (0.39) 47.04 b (1.28) 49.25 a (0.22) 48.96 b (0.16) Stems 53.70 a (1.41) 49.32 bc (0.89) 52.81 ab (0.95) 49.32 c (0.42) 51.20 abc (0.59) 48.00 c (0.38) C:N Leaves 42.70 c (0.92) 53.47 ab (1.49) 44.68 bc (3.61) 51.43 bc (4.42) 55.46 a (5.46) 41.89 c (5.29) Stems 59.49 (0.48) 6 1.07 (13.26) 50.81 (4.61) 54.82 (9.17) 39.49 (4.98) 50.00 (7.51) Cell Solubles (%) Leaves 65.72 a (1.51) 70.65 a (1.25) 65.21 ab (1.33) 66.44 a (1.98) 63.88 ab (0.70) 58.47 b (2.94) Stems 23.13 (3.32) 21.96 (2.51) 27.04 (2.76) 27.14 (1.00) 20.81 (2.79) 22. 28 (0.88) Hemicellulose (%) Leaves 11.52 a (0.60) 9.32 bc (0.26) 10.94 ab (0.70) 10.35 abc (1.37) 10.92 abc (0.25) 8.87 c (0.39) Stems 12.91 ab (1.71) 11.37 ab (1.47) 11.52 ab (0.67) 11.31 b (0.76) 14.34 a (0.67) 12.49 ab (0.85) Cellulose (%) Leaves 8.27 b (0 .72) 8.22 b (0.58) 8.17 b (0.51) 9.91 ab (0.98) 9.25 ab (0.14) 11.57 a (0.99) Stems 22.54 ab (3.04) 28.90 a (1.43) 20.48 b (1.07) 26.70 ab (0.24) 24.57 ab (2.16) 30.15 a (0.75) Lignin (%) Leaves 14.40 b (0.57) 11.67 b (0.79) 15.56 b (0.90) 13.18 b (0.69) 15.88 b (0. 86) 21.08 a (2.12) Stems 41.03 a (1.58) 37.50 ab (1.17) 40.83 a (1.81) 34.35 a (1.73) 40.15 a (1.27) 34.80 b (2.01) Lignin:N Leaves 12.51 (0.74) 12.72 (0.89) 14.31 (1.91) 14.20 (0.21) 17.95 (2.12) 16.95 (0.65) Stems 45.44 (0.92) 46.02 (9.14) 39.00 (2.20) 38.26 (7.14) 31.21 (4.75) 36.01 (4.96) IMR (%) after 3 yrs Leaves 36.92 (2.55) 36.18 (6.57) 47.37 (2.58) 45.11 (7.35) 44.47 (3.91) 49.39 (4.99) Stems 82.09 (4.44) 77.41 (3.94) 85.04 (0.79) 79.15 (2.65) 81.11 (2.33) 80.62 (1.38) K (1/yr) Leaves 0. 33(0.02) 0.36 (0.06) 0.25 (0.02) 0.29 (0.07) 0.27 (0.03) 0.24 (0.03) Stems 0.07 (0.02) 0.08 (0.02) 0.05 (0.003) 0.08 (0.01) 0.07 (0.01) 0.07 (0.004)

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128 Table B 4. Results from two Betula nana and Salix pulchra co llected in each of our three plant communities and incubated at a common site. ANOVA Results Foliar traits Plant part Source df F stat p value N (%) Leaves Site 2 0.5 0.6 Species 1 0.1 0.7 Site x Species 2 5.5 < 0.01 Stems Site 2 1.8 0.2. Sp ecies 1 2.0 0.2 Site x Species 2 0.5 0.6 C (%) Leaves Site 2 0.4 0.7 Species 1 8.7 < 0.01 Site x Species 2 1.2 0.3 Stems Site 2 3.1 0.08 Species 1 42.0 < 0.0001 Site x Species 2 0.4 0.7 C:N Leaves Site 2 0.7 0.5 Species 1 0.1 0.8 S ite x Species 2 5.4 0.01 Stems Site 2 2.0 0.2 Species 1 1.0 0.3 Site x Species 2 0.2 0.9 Cell soluble (%) Leaves Site 2 10.2 < 0.001 Species 1 0.1 0.7 Site x Species 2 5.5 < 0.01 Stems Site 2 1.0 0.4 Species 1 0.3 0.6 Site x Species 2 0.6 0.6 Hemicellulose (%) Leaves Site 2 0.6 0.5 Species 1 22.6 < 0.0001 Site x Species 2 0.5 0.6 Stems Site 2 4.3 0.04

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129 Species 1 4.6 0.06 Site x Species 2 0.01 1.0 Cellulose (%) Leaves Site 2 5.6 < 0.01 Species 1 2.5 0.1 Site x Spec ies 2 1.5 0.2 Stems Site 2 2.7 0.1 Species 1 22.7 < 0.001 Site x Species 2 0.1 0.9 Lignin (%) Leaves Site 2 12.2 0.0001 Species 1 0.2 0.6 Site x Species 2 7.0 < 0.01 Stems Site 2 1.6 0.2 Species 1 5.8 0.03 Site x Species 2 0.9 0.4 L ignin:N Leaves Site 2 7.2 < 0.01 Species 1 0.4 0.5 Site x Species 2 0.2 0.8 Stems Site 2 2.9 0.1 Species 1 1.1 0.3 Site x Species 2 0.2 0.8 K (1/yr) Leaves Site 2 2.5 0.1 Species 1 0.1 0.7 Site x Species 2 0.5 0.6 Stems Site 2 0.5 0. 6 Species 1 2.8 0.1 Site x Species 2 0.2 0.8

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130 Table B 5. I nitial litter quality for senesced leaves of seven species of vascular plants and three moss species collected from control and fertilized plots i n a moist acidic tundra community and inc ubated in a common site. Different letters within the same foliar trait indicate a significant result at the p < 0.05 level and are post hoc results after running two (Mean SE, n = 6 for each species ) Species N (%) C (%) C:N Cell soluble (%) Hemicellulose (%) Cellulose (%) Lignin (%) Lignin:N Graminoids Carex big. C 1.34 efg (0.04) 42.39 def (0.20) 31.91 cd (1.14) 41.87 d (2.61) 28.39 b (1.25) 24.47 ab (0.90) 4.81 e (0.93) 3.6 0 g (0.64) F 1.71 cd (0.05) 42.33 ef (0.35) 24.80 def (0.70) 38.43 d (1.46) 32.65 f (1.61) 23.43 ab (0.92) 5.02 e (0.78) 2.94 g (0.47) Eriophorum vag. C 0.87 h (0.04) 42.15 ef (0.13) 8.90 ab (2.11) 35.79 d (2.38) 30.82 ab (0.66) 27.16 a (0.46) 4.30 e (0.37) 4.91 efg (0.43) F 1.27 fg (0.09) 41.94 fg (0.06) 34.07 c (2.87) 41.24 d (2.59) 28.19 b (1.24) 21.63 b (1.49) 4.48 e (0.82) 3.63 g (0.67) Deciduous Shrub Betula nana C 1.67 de (0.06) 44.59 bc (0.15) 26.94 cde (0.93) 62.76 bc (0.75) 10.15 fg (0.47) 7.39 g ( 0.47) 19.44 a (0.31) 11.72 bc (0.29) F 2.41 a (0.11) 43.33 de (0.09) 18.17 f (0.89) 60.86 bc (0.74) 12.71 ef (0.39) 7.94 fg (0.19) 18.17 a (0.70) 7.63 def (0.55) Rubus cham. C 1.90 bc (0.04) 40.53 h (0.57) 21.32 ef (0.38) 64.98 ab (1.54) 17.87 c (1.12) 9.82 efg (0 .58) 6.78 de (0.57) 3.54 g (0.22) F 2.13 ab (0.09) 40.77 gh (0.20) 19.35 f (0.89) 67.94 ab (2.26) 16.72 cd (1.51) 9.34 efg (0.67) 5.38 de (0.71) 2.55 g (0.34) Vaccinium uli. C 1.74 cd (0.05) 43.63 cd (0.10) 25.15 def (0.79) 69.71 a (0.11) 9.49 g (0.23) 10.52 cdefg (0.09) 8.35 d (0.36) 4.83 efg (0.33) F 2.43 ab 42.04d efg 17.29 f 67.11 a 13.89 de 10.23 defg 7.31 d 3.01 fg Evergreen Shrub Ledum dec. C 1.03 gh (0.03) 47.83 a (0.30) 46.64 b (1.25) 63.29 abc (0.99) 8.14 g (0.41) 12.14 cdef (0.30) 16.08 b (0.36) 15.66 a (0.38) F 1.57 def (0.05) 46.98 a (0.13) 30.16 cd (1.10) 61.82 abc (1.35) 10.31 fg (0.26) 11.13 cde (0.45) 15.99 b (1.19) 10.2 bcd (0.63) Vaccinium vit. C 0.81 h (0.03) 45.15 b (0.16) 56.05 a (2.31) 60.93 c (0.75) 13.29 e (0.85) 13.22 cd (0.27) 11.19 c (1.45) 1 4.09 ab (2.26) F 1.43 def (0.08) 45.23 b (0.24) 32.22 cd (2.26) 59.31 c (1.42) 13.68 de (0.98) 13.97 c (0.72) 11.72 c (1.01) 8.43 cde (1.15)

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142 BIOGRAPHICAL SKETCH Jennie DeMarco lived in Las Vegas, Nevada until she graduated from Western High School in 1996. After high school, Jennie spent time traveling around the southwest region of the United States, interior Alaska, and Montana. During this time she was able t o experience the diverse ecosystems within these regions and wanted to learn more about them. She enrolled in an undergraduate environmental science program at Northern Arizona University, and in 2002 she earned a Bachelors of Science degree in environmen interests in ecosystem ecology began while she was an undergraduate. During this time she was introduced to concepts that were essential to understanding not only how these ecosystems function but how humans are altering these functions. While an undergraduate, she had the unique opportunity to work directly with a graduate student, Aimee Classen, on her research project. Aimee and her advisors, Dr. Steve Hart and Dr. George Koch, introduced he r to the concepts of ecosystem ecology and provided her the opportunity to gain field and laboratory experience needed to address ecological questions at the ecosystem scale. After completing her undergraduate degree, she worked under the direction of Dr. Michelle Mack at the University of Florida as a research and field technician. Her interests in the field of ecosystem ecology grew and in 2006 she began a graduate degree with Dr. Mack as her advisor. She chose to conduct her research in the arctic of Alaska because of the uniqueness of the ecosystems present there and their high vulnerability to climate change.