• TABLE OF CONTENTS
HIDE
 Title Page
 Acknowledgement
 Table of Contents
 List of Tables
 List of Figures
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Summary and conclusions
 Appendix
 Literature Cited
 Biographical sketch
 Copyright















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NUTRIENT,CARBON,ANDWATERDYNAMICSOFA TITISHRUBSWAMPECOSYSTEMINAPALACHICOLA,FLORIDAByLARRYNEALSCHWARTZADISSERTATIONPRESENTEDTOTHEGRADUATESCHOOLOFTHEUNIVERSITYOFFLORIDAINPARTIALFULFILLMENTOFTHEREQUIREMENTSFORTHEDEGREEOFDOCTOROFPHILOSOPHYUNIVERSITYOFFLORIDA1989

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ACKNOWLEDGMENTSSpecialappreciationgoestomysupervisorycommittee.Dr.G.R.Bestprovidedguidanceandsupportthroughoutthiswork.Dr.H.T.Odumgreatlyinfluencedmyapproachandstimulatedmyinterestinevapotranspiration.Dr.K.C.Ewelprovidedfocusandmuchneedededitorialassistance.Dr.D.A.Graetzprovidedguidanceandlaboratorysupportforthesoilswork.Dr.C.L.Montagueprovidedmanythought-provokingdiscussionsaswellasfriendship.ThisprojectwassupportedbytheStateofFlorida,DepartmentofEnvironmentalRegulation,projectnumberLR-46,"Low-EnergyWastewaterRecyclingthroughWetlandEcosystems:ApalachicolaStudy-ExperimentalUseofaFreshwaterShrubSwamp,"PrincipalInvestigatorG.R.Best.Numerouspersonsmustbethankedfortheirparticipationinfieldwork,sampleprocessing,dataanalysis,andmanuscriptpreparation.LucindaSonnenberg,SheridanKiddHaack,andCharlottePezeshki-Wolfedidconcurrentresearchatthestudysite.JerryLovellandDaleCronwellprovidedendlessfieldandlaboratoryassistance.JohnHigman,RobWolfe,DarylJoyner,AlfonsoHernandez,BillSargent,PeggyAnderson,andMelvinRectorassistedinfieldwork.ArtWatsonflewa"majesticbird"foraerialphotography,andJohnBossertprovidedvaluablecomputerassistance.Ken McMurryandJonBarbourdraftedthefigures,andLindaCrowderandCarolCoxassistedwiththemanuscript.SpecialthanksgotoJennyCarterfortypingandretypingthisdissertationandtoPeteWallace,BillDunn,andJimFeiertagforallii

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theireffortsanddeepfriendship.SpecialthanksarealsoextendedtoPierre Walle, Wilbur,Mike McGurk,Rudy,Buzee,LordMelvin,Pie,and,ofcourse,MadMoe. Iwouldalsoliketothankmyparents.Onceagain,withtheirsupportandencouragement,Ihavebeenabletoaccomplishmygoal.Finally,Iwouldliketothankmywife,Jamie.Herloveandsupporthavebeenmygreatestasset.iii

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TABLEOFCONTENTSACKNOWLEDGMENTSLISTOFTABLESLISTOFFIGURESABSTRACTCHAPTERS1INTRODUCTIONGeologyandPhysiographyVegetationinTitiShrubSwampsBiomassinForestedWetlandsChemistryinAcidicWatersPhosphorusAdsorptioninSoilsWastewaterDischargetoWetlandsEvapotranspirationinForestedWetlandsFreshwaterWetlandModelsandtheirUseinSimulatingWastewaterAddition2METHODSVegetationAnalysisBiomassandNutrientStandingStockEstimatesWaterChemistry.......SoilsandPhosphorusAdsorptionHydrology....,....PrecipitationandRunoffGroundwater....EvapotranspirationTranspiration. ModelDevelopmentandSimulation3RESULTS.....VegetationAnalysisBiomassandNutrientStandingStockEstimatesWaterChemistry...Soils....PhosphorusAdsorptionHydrologyPrecipitationandRunoffGroundwater.iviivixxii1510 131420263438444446505254555657 596567 67 7993103 106119 119120

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EvapotranspirationWaterBudgetTranspiration. ModelDevelopmentandSimulation4DISCUSSIONVegetationAnalysisBiomassandNutrientStandingStockEstimatesWaterChemistry......SoilsinTitiShrubSwampsPhosphorusAdsorptionHydrology........Runoff......EvapotranspirationWaterBudgetTranspirationandTotalWaterLossModelDevelopmentandSimulation5SUMMARYANDCONCLUSIONS.....APPENDICES:127130130 156 172 172 173 178 182 184 186 187 187 190 190 194 198ABCCOMPUTERPROGRAMTOINTEGRATEHOURLYTRANSPIRATIONRATESTOOBTAINADAILYTRANSPIRATIONRATE(DTR). ASAMPLEOUTPUTIS INCLUDED. ....REGRESSIONEQUATIONSUSEDTOESTIMATETHEBIOMASSOFTHETITISHRUBSWAMPINAPALACHICOLA,FLORIDA.pbd-PRIMARYBRANCHDIAMETER,dbh DIAMETERATBREASTHEIGHT...........ANNUALWATERBUDGETSFOR1982-1986ANDFORTHEWATERBUDGETYEAR(WBY)FORTHETITISHRUBSWAMPSTUDYSITE. AKEYTOTERMSISINCLUDED.... 202 205 207DSPREADSHEETSFORTRANSPIRATIONRUNS.TERMSISINCLUDED.......... AKEYTO215EFBASICCOMPUTERPROGRAMTOSIMULATETHEDISCHARGEOFWASTEWATERTOTHETITISHRUBSWAMP.....CALCULATIONSOFTHESTORAGESANDFLOWSFORTHESIMULATIONMODELOFTHETITISHRUBSWAMPINAPALACHICOLA,FLORIDA,PRESENTEDINFIGURE24 228 232LITERATURECITEDBIOGRAPHICALSKETCHv243 259

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Table1LISTOF TABLESChambervolumeandnumberofturnoversperminuteinfourstudieswheremetabolismandtranspirationweremeasured...........602Thedimension,volume,turnovertimemodelequation)andtheairflowthatmetabolismorenhancetranspiration,chambersusedinthisstudy....(calculatedwithwouldnotlimitforthethree62345 6789Characteristicsofwoodyvegetation(>1.3mhigh)inatitiphaseofthetitiswampinApalachicola,FloridaCharacteristicsofwoodyvegetation(>1.3mhigh)inahollyphaseofthetitiswampinApalachicola,FloridaCharacteristicsofwoodyvegetation(>1.3mhigh)inamixedswampphaseofthebayswampinApalachicola,Florida..... ....Characteristicsofwoodyvegetation(>1.3mhigh)intheblackgumswampinApalachicola,FloridaCharacteristicsofwoodyvegetation(>1.3mhigh)inthetitishrubswampinApalachicola,FloridaImportance.valuesforwoodyvegetationspecies(>1.3mhigh)inthetitishrubswampinApalachicola,Florida.AllspeciescombinedregardlessofsizeclassPercentgroundcoverinthefourcommunitytypesinthetitishrubswampinApalachicola,Florida7072 73747576 7810Thedbh,estimatedbole,branch,leafbiomassforblacktiti,redtiti,andatthestudysiteandabovegroundsweetbaysampled801112Abovegroundbiomassestimateofwoodyvegetation(>1.3mhigh)inatitiphaseofthetitiswampinApalachicola,Florida.Abovegroundbiomassestimateofwoodyvegetation(>1.3mhigh)inahollyphaseofthetitiswampinApalachicola,Florida....................vi8283

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13Abovegroundbiomassestimatehigh)inamixedswampphaseApalachicola,Floridaofwoodyvegetation(>1.3mofthebayswampin8414151617Abovegroundbiomassestimateofwoodyvegetations(>1.3mhigh)intheblackgumswampinApalachicola,FloridaHerbaceousbiomassandlitterestimatesofthefourcommunitytypesinthetitishrubswampinApalachicola,Florida.....AbovegroundbiomassestimatesofthefourcommunitytypesinthetitishrubswampinApalachicola,FloridaTheleafbiomasstoarearatioofblacktiti,redtiti,andsweetbayattwoverticalintervals(9to12metersand3to9meters)atthestudysite....85868789 18Estimatedleafbiomasswoodyvegetation(>1.3communitypergroundarea(LBGA)ofthemhigh)inthebayswamp90 192021222324Leaflitterfall(g/m2 )inthefourcommunitiesinthetitishrubswampinApalachicola,Florida,fromMay1982throughApril1983. x -mean,sstandarddeviation,c.v. = coefficientofvariation.Totalnitrogenandtotalphosphorusconcentrations(mg/g)ofthebole,branchandleafofblacktiti,redtiti,andsweetbaysampledatthestudysite. x mean,s standarddeviation,c.v. coefficientofvariationTotalnitrogenandtotalphosphorusconcentrations(mg/g)oftheherbaceouscomponent,littercomponentandleaflitterfallinthefourcommunitiesinthetitishrubswampinApalachicola,Florida. x mean, s standarddeviation,c.v. coefficientofvariationTotalnitrogenandtotalphosphorusintheabovegroundbiomassinthefourcommunitiesinthetitishrubswampinApalachicola,Florida....TotalnitrogenandtotalphosphorusinlitterandleaflitterfallinthefourcommunitiesinthetitishrubswampinApalachicola,FloridaChemicalanalysisofprecipitationatthetitishrubswampinApalachicola,Florida91 929495 969725ChemicalanalysisofshallowgroundwaterinthetitishrubswampinApalachicola,Florida98 26MonthlysurfacewaterparametersinthetitishrubswampinApalachicola,Florida..100vii

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27ClassificationofsoilsofthetitishrubswampinApalachicola,Florida10428CharacteristicsofsoilsofthetitishrubswampinApalachicola,Florida10529Coefficientsofdetermination(R)betweentheadsorptionofaddedphosphorusbystudysitesoilsandtheequilibriumphosphorusconcentrations(EPC)insolutionsfortheLangmuir,Fruendlich,Tempkin,andquadraticequations......... ......11530Phosphorusadsorptionmaximaofstudysitesoilscalculatedbysubstitutionoftheequilibriumphosphorusconcentration(EPC)derivedfromquadraticequationintodifferentequations......11731Measuredsoilpropertiesforthestudysitesoilsandthecoefficientofdetermination(R)betweenthesepropertiesand1)theadsorptionmaximaderivedbysubstitutionintotheTempkinequation,and2)thephosphorussorptionindex..11832Averageannualprecipitation(P),estimatedrunoff(R),panevaporation(PE),potentialevapotranspiration(PET),actualevapotranspiration(AET)andwaterbudgetresidual(RES)forthestudysitefrom1982through1986andforthewaterbudgetyear(WBY)..12133Waterdepth(m)forthreestationswiththetitishrubswampinApalachicola,Florida..12634Theverticaldistributionleafareaindex(LAI)forbayswampcommunityofleafbiomass(VDLB)andtheblacktitiandsweetbayinthe..15435Dailytranspirationrate(DTR) ,dailytranspirationperleafarea(DTRLA)anddailytranspirationratepergroundarea(DTRGA)foreleventranspirationruns..15536DifferentialequationsforeachstatevariableusedinthesimulationmodelofthetitishrubswampinApalachicola,Florida,presentedinFigure24..16037InitialconditionsforthestoragesforthesimulationmodelofthetitishrubswampinApalachicola,Florida.SourcesforthevaluesarepresentedinAppendixF..16138FlowratesforthesimulationmodelofthetitishrubswampinApalachicola,Florida.SourcesofthevaluesaregiveninAppendixF.............16239StandingstockoftotalphosphorusinabovegroundbiomassinFloridacypressforests(Brown1981),andintitishrubswampcommunitiesinApalachicola,Florida.viii

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Thestandingstockoftotalnitrogeninabovegroundbiomassinthetitishrubswampcommunitiesarealsopresented......17740Precipitation(P),potentialevapotranspiration(PET),PET/Pratio,actualevapotranspiration(AET)andAET/PETratioforMiltonandTallahassee,Florida,reportedbyDohrenwend(1977)andforApalachicolacalculatedinthisstudy............."..18941Leafareaindex(LAI) ,dailytranspirationrateperleafarea(DTRLA)dailytranspirationratepergroundarea(DTRGA),forestfloorwaterloss (FFWL) andtotalwaterloss (TWL) forthedwarfcypressforest,AustinCarycypressdomeandfloodplainforestreportedbyBrown(1981)andforthebayswamp communityatthestudysite.191ix

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LISTOFFIGURESFigure1ConceptualsystemsdiagramofthetitishrubswampinApalachicola,Florida. Wwater,B-biomass, Llitter,S-soil,N-nitrogen, Pphosphorus,M microbes...423LocationofthetitishrubswampstudysiteinApalachicola,Florida.....ThetitishrubswampstudysiteinApalachicola,Florida,includingsurfacewaterandgroundwatersamplingstations. 7..9 4MapofthevegetationofthetitishrubswampstudysiteinApalachicola,Florida,includingsurfacewatersamplingstations695Meantotalnitrogen(TN)andmeantotalphosphorus(TP)concentrationsinprecipitation(P),surfacewater(S)andgroundwater(G)atthetitishrubswampstudysiteinApalachicola,Florida.SourcesofdataareTables24,25,and26 .......1026Phosphorusadsorptionisothermsforthemineralsoil(RutlegeSeries)atadepthof0-5em.Plots:regular,Langmuir,FruendlichandTempkin... .1087Phosphorusadsorptionisothermsforthemineralsoil(RutlegeSeries)atadepthof15-20em.Plots:regular,Langmuir,FruendlichandTempkin.......1108Phosphorusadsorptionisothermsforthe(PamlicoSeries)atadepthof0-5em.Langmuir,FruendlichandTempkinorganicsoilPlots:regular,..1129Phosphorusadsorptionisothermsfortheorganicsoil(PamlicoSeries)atadepthof15-20em.Plots:regular,Langmuir,FruendlichandTempkin...11410PotentiometricsurfaceofthesurficialaquiferatthetitishrubswampstudysiteinApalachicola,Florida;July30,1982(highgroundwater).... ..12311PotentiometricsurfaceofthesurficialaquiferatthetitishrubswampstudysiteinApalachicola,Florida;May30,1982(lowgroundwater)..125x

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12Naturalgammalogofawelllocated2.0milesnortheastofthe titi shrubswampstudysite in Apalachicola,Florida12813TranspirationrunOctober21,1984(sweetbay)13314TranspirationrunNovember2,1984(blacktiti)13515TranspirationrunApril21,1985(sweetbay)13716TranspirationrunOctober5,1985(sweetbay)13917TranspirationrunDecember14,1985(sweetbay)14118TranspirationrunMarch3,1986(sweetbay)14319TranspirationrunApril19,1986(sweetbay)14520TranspirationrunMay24,1986(sweetbay)147 21TranspirationrunJune28,1986(sweetbay)149 22TranspirationrunAugust20,1986(sweetbay)15123TranspirationrunSeptember14,1986(sweetbay)153 24Systemsdiagramofthesimulationmodelofthe titi shrubswamp in Apalachicola,Florida. Wwater,B-biomass,L-litter,S-soil,N-nitrogen,P-phosphorus15825MaterialandenergybUdgetsforthe titi shrubswamp in Apalachicola,Florida.Calculationofstoragesandflowspresented in AppendixF.Storageofwaterm3/m2 ,flowofwaterm/yr,storageofcarbonkcal/m2 ,flowofcarbonkcal/m2-yr,storageofnitrogenandphosphorusg/m2 ,flowofnitrogenandphosphorusg/m2.yr. 166 26Materialandenergybudgetsforthe titi shrubswamp in Apalachicola,Florida,after100yearsofwastewaterdischarge.Calculationofstoragesandflowspresented in AppendixF.Storageofwaterm3/m2 ,flowofwaterm/yr,storageofcarbonkcal/m2 ,flowofcarbonkcal/m2-yr,storageofnitrogenandphosphorusg/m2 ,flowofnitrogenandphosphorusg/m2-yr.Z-wastewater. 168 27Resultsofthesimulationmodelofthe titi shrubswamp in Apalachicola,Floridaafter100yearsofwastewaterdischarge.ValuesaregN/m2 ,g P/m2andkcal/m2fornitrogen,phosphorus,andcarbon,respectively171 xi

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AbstractofDissertationPresentedtotheGraduateSchooloftheUniversityofFloridainPartialFulfillmentoftheRequirementsfortheDegreeofDoctorofPhilosophyNUTRIENT,CARBON,ANDWATERDYNAMICSOFATITISHRUBSWAMPECOSYSTEMINAPALACHICOLA,FLORIDAByLARRYNEALSCHWARTZDecember1989Chairman:G.RonnieBestMajorDepartment:EnvironmentalEngineeringSciencesThemaincomponentsandprocessesofatitishrubswampwerequantifiedforincorporationintoasimulationmodeltopredicttheirlong-termresponsestowastewaterdischarge.Themaincomponentswerevegetation,water,andsoil;andtheprocesseswerecarbon,nitrogenandphosphoruscycling,andwaterflow.Quantificationofmodelcompartmentsindicatedthat1)abovegroundbiomassisinthelowtointermediaterangeofvaluescitedforforestedwetlands,2)precipitationis the principalsourceofwaterandnutrientstothissystem,and3)relativeconcentrationsofnitrogenandphosphorusinprecipitation,surfacewaterandgroundwaterindicatethatnutrientsareconservedwithinthesystem.Therefore,smallamountsofnutrientswerecycledwithinthissystem,andlownutrientinputlimitedthesimulatedproductivity.Thesimulatedresponsetoincreasednutrientswasanincreaseinannualbiomassandlitterandincreasedstorageofnutrientsinbiomass,litterandsoil,andtheratesoftheseincreasesdecreasedwithtime.xii

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Wastewaterdischargedtowetlandswitha N:Pratiosimilartothatstoredinvegetationwouldmaximizethelifetimeofthesystemforphosphorusassimilation.Therefore,nutrientloadingcriteriashouldbebasedonmaximizingthelongevityofthesystem,whichcanbeestimatedbydeterminationofthephosphorusadsorptioncapacityofthesoil.Mineralsoilsdominatedbytitihadalowcapacityforphosphorusadsorptionwhileorganicsoilsdominatedbyblackgumhadahighercapacityforphosphorusadsorption.Theadsorptioncapacitiesofthesesoilswererelatedtothecontentandavailabilityofamorphousandpoorlycrystallineoxidesofaluminum.Sweetbayhadlowratesoftranspirationperleafarearelativetootherforestedwetlandspecies.Anincreaseoccurredfromtheindividualtothecommunitylevelduetohighleafareaindexinthebayswamp.Thiscommunitytranspiresatarategreaterthanopenwaterevaporationwhenwaterisreadilyavailableasindicatedbythepanratio.Thereisvariabilityamongforestedwetlandcommunitiesandamongseasonsandthesesystemsevapotranspireatlowrateswhenwaterisscarceandathigherrateswhenwaterisreadilyavailable.Therefore,thesesystemsareadaptedforwaterconservationduringdryperiods.xiii

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CHAPTER1INTRODUCTIONAneedhasemergedtoincludewetlandsintheoverallstrategyofmanagingourenvironment.Wetlandscanbeusedtotreatwastewaterandwemustdeterminehowtomanagethesesystemsforthispurposetothebenefitofnatureandhumanity.Inordertoproperlymanageandoptimizetheroleofthesecomplexecosystemsinthelandscape,wemustunderstandquantitativelyhowthesesystemsfunction.Duetotheincreasingamountofdomesticwastewatergeneratedeveryday,newalternativesforwastewatertreatmentmeritconsideration.Thetreatmentofdomesticwastewaterinnaturalwetlandsisonesuchalternative.Althoughmanykindsofwetlandshavebeenshowntotreatwastewater,theeffectsofwastewaterdischargetowetlandsandtheirtreatmentcapacitymustbeevaluatedsothattheappropriateloadingcanbeselectedthatwillmaintaintheirtype,nature,andfunction.Onlythencanthesuitabilityofusingaspecificwetlandforwastewatertreatmentbeevaluated.Theneedhasemergedforreliabledesignproceduresforwetlandtreatmentsystems(Hammer1984).Asimple,tractablemodelmustbedevelopedtopredictthelong-termperformanceofwetlandtreatmentsystems.Inordertodevelopsuchamodel,themaincomponentsandprocessesofwetlandsmustbequantified.Priorto1985,theCityofApalachicola,Florida,dischargedmunicipalwastewatertotheApalachicolaRiver.Thedischargeviolated1

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2stateandfederalwaterqualitystandards.Dischargeofthemunicipalwastewatertoanearbytitishrubswampwassuggestedasanappropriateandcosteffectivetreatmentalternative.Thiswasinaccordancewithsection17-4.243(4)oftheFloridaAdministrativeCode,whichprovidesanexemptionfromwaterqualitystandardstoallowtheexperimentaluseofwetlandsforlow-energywaterandwastewaterrecycling.Thedischargermustmonitorthelong-termecologicaleffectsofwastewaterdischargetothewetlandandevaluatethewastewaterrecyclingefficiencyofthewetland.AnexemptionwasgrantedtotheCityofApalachicola,Florida,fortheuseofatitishrubswampforwastewatertreatment.AresearchprogrambeganattheCenterforWetlands,UniversityofFlorida,toinsurecompliancewiththeabovestatedprovisionsoftheexemption.TheobjectivesofthisstudyweretocharacterizeandquantifythemaincomponentsandprocessesofthetitishrubswampecosysteminApalachicola,Florida,necessarytopredicttheirlong-termresponsestowastewaterdischarge.Themaincomponentswerevegetation,waterandsoil;andtheprocesseswerecarbon,nitrogenandphosphoruscycling,andwaterflow.Thisinformationwasincorporatedintoasimulationmodel(Figure1)topredictthelong-termresponsesofthesecomponentsandprocessestowastewaterdischarge.Phosphorusretentioninsoilhasbeenshowntooccurinwetlandsusedforwastewatertreatmentbutthecapacityforthisretentionhasnotbeendetermined.Therefore,thepotentialforphosphorusadsorptionintitishrubswampsoilswasamanagementissueevaluatedinthisstudy.Inordertomanagewetlandsproperly,wemustquantifytheirprocesses.Thisincludestheirrateofevapotranspiration,overwhich

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Figure1.ConceptualsystemsdiagramofthetitishrubswampinApalachicola,Florida.W=water,B=biomass,L=litter,s=soil,N=nitrogen,P=phosphorus,M=microbes.

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4

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5thereisgreatdebate.Therefore,therateofforestedwetlandplantevapotranspirationwasanadditionalmanagementissueevaluatedinthisstudy.GeologyandPhysiographyTheCityofApalachicolaislocatedatthewesternedgeoftheBigBendregionofthestate(Figure2).Thetitishrubswampstudysiteislocated1kmwestoftheCityofApalachicola,Florida,andfrom1to2kmnorthofSt.VincentSound(Figure3).TheentireBigBendregionofFloridaisunderlainbyabedrockoflimestone,whichdatesbacknolaterthantheearlyMioceneage(Clewell1971).LimestoneisencounteredbeneaththeApalachicolaareaapproximately40mbelowthesurface(Schmidt1978).AbovethelimestoneliesanassortmentofvariousMioceneclasticsandabovethemaveneerofPleistocenesands.Thesematerialsweredepositedduringancientsealevelfluctuations.Usuallythereisashellbedinasandandclayeymatrix,overlainbyagravelandcoarsesandunit,byaclayeysand,andfinallybya mediumfinesandcomposedofsand,siltandclay,andorganicdebris.Inadditiontopeatdepositstherearebedsofhumatealongthecoast(upto1mthick).ThehumateisdarkbrowntoblackfirmlycementedsandoflatePleistocenetoRecentageandwasprobablyformedinanancientswamp whensealevelwas afewfeethigherthanthepresent.ThewesternportionoftheBigBendregionliesintheApalachicolaCoastalLowlandsunitoftheGulfCoastalLowlandsPhysiographicProvince(Schmidt1978).Thesecoastallowlandsarelowinelevationduetothereworkingbycoastalprocessesandaregenerallypoorlydrained.Muchofthelandareainthisunitiscoveredbyswamp. The

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Figure2.LocationofthetitishrubswampstudysiteinApalachicola,Florida.

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7 N\ FranklinCounty:.".,IBaY '.', ': '., ',.St.VIncentSouod '.' ..,..",':::' . ;7:,,.1.'-:.. ..,:'\",hi c01a.....: .... 1 1/2o ';':",-\,,'.. ....: .. .. ..

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Figure3.ThetitishrubswampstudysiteinApalachicola,Florida,includingsurfacewaterandgroundwatersamplingstations.

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ST.VINCENTSSOUND N1APALACHICOLA AIRPORTUsROUTE98 GW: GROUNDWATER WELL Q. SAMPLING STATION X. PROPOSEOPOINTOFWASTEWATER WETLAND .GWli eGW 4 I: 24000eGW3mil .. WHORTLEBERRY CREEKFRON USGS 15NINUTE, WESTPASSAGE QUADRANGLEAPALACHICOLAaAY '"

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10impermeableclasticscontainfinegrainedclayandsilt(asindicatedabove),whichretardwatermovement. Thepermeabilityislowandgroundwaterisperchednearthesurface.Thisisenhancedbylowrelief,makingitdifficultforsurfacewatertorunoff.The swampsoccupyirregularlyshapedshallowdepressionsthatmostlydonotjointoformdrainages(Clewell1971).ThesedepressionsarelikelytheresultofgentleundulationsofaformerPleistocenesea-bottom.Theseswamps mayhavebeenaccentuatedbymorerecentlocalizedslumpingofthesurfacethatwouldslowlyformadepressionhavingahigherwatertablethanthesurroundinglands.Thesegeomorphicfeaturesareinterleveeswamps,orientedparalleltothecoast,indicatingtheirformationthroughmarineforces(Schmidt1978).Thesetypesofsystemsarereferredtoasbogsandbog-fedstreamsbyWhartonetal.(1982).Thedepressionsthatfeedthestreamsareareasofinternalpercheddrainageunderlainbyclayaquicludes.Surfacedrainageoccursthroughslowmovingstreamsoriginatingfromflatswampareas.Thesestreamshavelimiteddistributionandgenerallyoccupythelineardepressionsorswalesbetweenadjacentsandridgesandreworkedrelictcoastallowlanddeposits.VegetationinTitiShrubSwamps Thevegetationintitiswampsisoftenundifferentiatedintostrata(Clewell1981).Broad-leavedevergreenorsemi-deciduousshrubsandsmalltreesaredominant,especiallyoneofthreespeciescommonlycalledtiti:Cliftoniamonophylla(blacktitiorbuckwheattree),Cyrillaracemiflora(redtitiorswamptiti)andCyrillaparviflora(little-leaftiti).Allthreespeciesoccurinthesamehabitats,

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11sometimesindividuallybutoftentogether.BlacktitiisusuallymoreabundantthanthetwospeciesofCyrillaandtendstooccupyslightlyhighersitesthanredtiti(Clewell1981).Infrequentbutdestructivecrownfiresoccurintitiswamps.Thesefiresserveahomeostaticfunction,rejuvenatingandperpetuatingthecommunity.Thevegetationisrarelygreaterthan25 minheight.Thetallerthevegetation,thelowerthefrequencyoffire,oratleastthelongersincethelastdestructivefireoccurred(Clewell1981).Titiswampsborderpineflatwoods(whichfrequentlyburn)andonlyburnattheirfringe,servingasafirebufferforbayswamps(Clewell1971).Groundwaterseldomfluctuatesfarbelowthesurfaceintitiswamps(Whartonetal.1977).Occasionallytitiswampsborderpondcypressorblackgumswamps,protectingtheseareasfromfireaswell(Clewell1971).Irregularfiresdestroytheaerialportionofthevegetationintitiswamps,andcoppicingafterfireisverycommon,leadingtomultipletrunks(Clewell1981).Indiscussingthedistributionofthethreespeciesoftiti,Clewell(1981)statedthattheydonotsegregateaccordingtosubtlegradientsinthehabitat.Theirdistributionappearsrandom,asifonceatitiplant,regardlessofspecies,bychance becomes establishedatagivenlocation,itpersistsindefinitely,survivingfirebycoppicingandregeneratingthestandwithoutinterveningsuccessionalstages.Titiswampsgradeimperceptiblyintobayswamps(Clewell1981).Bay swampsoccupythoseportionsofacidswampsthatarewetterandlessfrequentlyburnedthantitiswamps(Clewell1981).Thedominantsoftitiswampsoftenmake uptheunderstoryofbayswamps,andwhen afire

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12doesconsumeabayswamp,theunderstoryspeciessuchasblacktitiappeartogrowfasterthandotheoverstoryspeciessuchassweetbay(Clewell1971).Asaresult,thesitebecomesatitiswampforperhaps10to25yrs,untiltheoverstoryofsweetbaytreesforms(Clewell1971).ItwassuggestedbyClewell(1971)thattitiswamps,therefore,seemtobesuccessionaltobayswamps. MonkandBrown(1965)alsosuggestedthatbayswampsareclimaxcommunities.Pondcypressandblackgumoccupythedeepestswampsinthepanhandle,andfewspeciesarepresentinanygivenstand(Clewell1971).Theunderstoryspeciesofpondcypressfblackgumswamps,suchastiti,usuallydominateothercommunitiesofacidswampsystems(Clewell1981).Also,fireisrare.Theseswampshavebeenwidelydrained,loweringthewatertableandallowinginvasionofotheracidswampspecies.Theseswampsusuallyoccupypeatyaciddepressionsinthedeeperinteriorsites,andbayswampsoccupytheshallowerexteriorsites.Intergradationssometimesoccur,particularlybetweenpondcypressswampsandbayswamps.Pondcypressfblackgumswampscanalsointergradewithbayswampsalongtheupperreachesofstreams.Blackgumswamps,whicharealsoreferredtoasgumponds,areusuallyborderedbypondcypressswamps,whichoccupyslightlyhigherelevations.Clewell(1971)raisedthepossibilitythatblackgumissuccessionaltopondcypressorviceversa.Blackgumconsistentlyoccupiesthelowestandwettestsitesandtheseareasareborderedbypondcypressatslightlyhigherelevations.MonkandBrown(1965)alsofoundthatblackgumimportanceincreasedsharplyandpondcypressimportancedecreasedsharplywithdecreasingdepthofmaximumflooding.

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13Inaddition,withincreasinglevelsofcalcium,theimportanceofblackgumincreasedsharplyandthatofpondcypressdecreasedsharply(MonkandBrown1965).Initiallypondcypressisfavoredinthelowersites,whicharesurroundedbybayswamps,which,whensurroundedbytitiswamps,burninfrequently(Clewell1971).Peatformationisrelativelyrapid,andcalciumreleasedfrompeatdecompositionpromotestheestablishmentofblackgumoverpondcypress(Clewell1971).Swampsthatcontainalargeproportionofblackgumandparticularlypondcypressmayrepresenttransitionalphasesbetweenapondcypressfblackgumsystemandanacidswampsystemor,assuggestedbyClewell(1981),maybeincludedasadistinctandimportantpartoftheacidswampsystem.BiomassinForestedWetlandsForestedwetlandsmaybegroupedintothreecategoriesbasedonwatermovementanddifferencesinnutrientinputs:still-waterwetlands,slow-flowingwaterwetlands,andflowingwaterwetlands(Brown1981).Still-waterwetlandsreceivenutrientsandwaterpredominantlyfromprecipitation.Slow-flowingwetlandsreceivewaterandnutrientsfromgroundwaterandsurfacewaterrunoff.Flowingwaterwetlandsreceivewaterandnutrientsfromfloodingstreams.Theabovegroundbiomassofforestedwetlandsrangesfrom3.6kg/m2foradwarfcypressforestto45.2kg/m2foracypresstupeloalluvialriverswamp(Brown1981;ConnerandDay1982).Largebiomassexistsinbothstill-waterandflowingwaterwetlands.Smallbiomassinthedwarfcypressforestappearstobeduetonutrientlimitationsorotherstressorsratherthanthepatternofwaterdelivery.However,themajor

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14sourceofwaterisprecipitation,andfloodwaterstendtobestagnantandgenerallyshallow(BrownandLugo1982).Thereisarelationshipbetweenproductivityandhydrologicandnutrientsources. Wood productionandlitterfallarehighestinflowingwaterwetlands,lessinslow-flowingwetlands,andlowestinstill-waterwetlands(Brinsonetal.1981;BrownandLugo1982).Theleaflitterfallportionoftotallitterfallhasbeenreportedforonlyafewfreshwaterforestedwetlandsites.IntheDismalSwamptheaverageleaflitterfallforcypressandmixedhardwoodspeciesis492 g/m2 yr,withthepeakintheautumn(Day1983).Averagelitterfallfor2yrsinAustinCarycypressdome was420g/m2 yr(Deghietal.1980).ThepeaklitterfallperiodwasinNovemberandDecember.LeaflitterfallforthefloodplainforestoftheApalachicolaRiverwas464gjm2 yr(ElderandCairns1982).Seasonalvariabilityinleaflitterfallwasobserved. Maximum leaflitterfalloccurredinNovemberandotherhighvaluesoccurredinautumnmonths.Maximumleaflitterfallmayoccurinthespringinassociationwiththedevelopmentofnewleaves(BrayandGorham1964).Thisbimodalseasonalcycleforleaflitterfall(autumnandspringpeak)wasalsofoundinaMississippicoastalstream(PostanddelaCruz1977).ChemistryinAcidicWatersMostnaturalwatersarebufferedprincipallybyacarbondioxide-bicarbonatesystem.Byobservingtheequilibriumchemistry(dissociationrelationships)ofasystem,theproportionsofcarbonicacid(plusdissolvedcarbondioxide),bicarbonate,andcarbonateatvariouspHvaluescanbeevaluatedinordertodeterminewhatbuffers

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thesystem.Becauseoftheubiquitousnatureofcarbonaterocksand15theequilibriumreactionsofcarbondioxide,bicarbonateandcarbonatearepresentasbasesinmostnaturalwaters(StummandMorgan1981),butallwaterswithapHlessthan8.5containacidity(SawyerandMcCarty1978).Uncombinedcarbondioxide,organicacids(suchastannicorfulvic),andsaltsofstrongacidsareresponsiblefortheacidityofnaturalwaters(Wetzel1975).InwaterswithapHbelow5,carbonicacid(plusdissolvedcarbondioxide)dominatesthecarbonateequilibria(Wetzel1975),butdepressionofpHbelow4.5isduetomineralaciditywhichisexhibitedbywaterscontainingacidsstrongerthancarbonicacid(StummandMorgan1981).AtapHof3to4.5,carbonateandbicarbonatearenotbufferingthewater;rather,organicacidsarethebuffer(Thurman1985).Theproportionsofcarbonateinsurfacewaterscomefromtheweatheringofrocks,andthesolubilityofcarbondioxideinwaterincreasesmarkedlyinwaterthatcontainscarbonate(Wetzel1975).IfsurfacewatersareisolatedfromthecarbonaterichFloridanAquifer(FernaldandPatton1984),thenthereisprobablyverylittlefreecarbondioxidepresentinthosesurfacewaters.Conductivityisausefulindicatorofwhetherthewaterenteringapeatlandisprimarilyfromprecipitationandshallowmineralsoilinflow(andthereforenotincontactwithcarbonatecontainingparentmaterial)orgroundwater(Verry1975).Valueslessthan80 indicateaperchedwatertable.Valuesgreaterthan80 indicateagroundwatertable.ThecarbonateequilibriaforAustinCarycypressdome (meanpH 4.5)wasexaminedbyDierberg(1980).Onlytraceamountsofbicarbonateexistedinthewaterastherewas notitratablealkalinity.Therefore,

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16itisappropriatetomeasurephenolphthaleinacidityratherthanalkalinityinacidicwaters.Phenolphthaleinacidityisameasureofthefree(oruncombined)carbondioxideandthemineralaciditypresentinthesurfacewater(SawyerandMcCarty1978).HighlycolorednaturalsurfacewaterstypicallyhavelowpHduetotheacidicnatureofhumicsubstancesthatarepresent.Thecolorisprincipallyduetotannins,humicacid,humates,andthedecompositionoflignins(SawyerandMcCarty1978),butcolorinsurfacewatersinFloridastreamsandcanalsmaybeoforganicormineralorigin(Kaufman1975b).Theinorganicsourcesaremetallicsubstancessuchasironandmanganesecompounds(Christmanetal.1967).LowpHvaluesarefoundinnaturalwatersrichindissolvedorganicmatter,especiallyinsystemsthatcontainlargeamountsofsphagnum(Wetzel1975).Inwetlands,dissolvedorganicmatterusuallyexceedsdissolvedinorganicmatter,whichisnottheusualcaseinsurfacewaters(Thurman1985).ThemostlikelymajorsourcesofhydrogenionsinthesewatersarethedissociationofH2S04derivedfromH2S (Gorham1956)andtheactivecationexchangeinthecellwallsofsphagnumwherethereleaseofhydrogenionsoccurs(Clymo1964).Hydrogenionsarealsoproducedbyorganicdecomposition(Clymo1967).Increasesinacidityoccurwhenevertheproductionoforganicmatterisgreaterthandecomposition,asinpeatsystems(StummandMorgan1981).Thisisbecausetheassimilationofammoniumproduceshydrogenions.Thechemicalnatureoftheplanttissuesformingthepeat(humicacids)tendstomakethispeatmaterialacid,andthemostacidpeatsarethoseformedfromswampplantsandsphagnummoss(Davis

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171946).Inaddition,thepoorbufferingcapacityofprecipitationreachingawetlandcanfurtherlowerthepH(Thurman1985).Informationonnitrogentransformationsinacidic,highlyorganicfloodedsoilsislimited,andtheseprocessesmayoccurinuniqueways(Haack1984).Compoundsfoundinnaturallyoccurringhumic-coloredwatersreducedissolvedoxygenlevelsand,therefore,thesewatersactasasinkfordissolvedoxygen(Dierberg1980).Lowdissolvedoxygencanleadtoanaerobicconditionswherenetammonification(thereleaseofammoniumduringmicrobialdecompositionoforganicmatter)isoftennoted(TusneemandPatrick1971).Inaddition,lowpHaswellasthepresenceoforganiccompoundsinhibitthenitrificationofammoniumtonitrate(Dierberg1980).Therefore,lowdissolvedoxygen,lowpHandthepresenceoforganiccompoundscontributetothedominanceofammoniumratherthannitrateplusnitriteinthesewaters.Throughtheinhibitionofnitrification,ammoniumbecomesthedominantinorganicnitrogenspecies,andthisleadstoconservationofnitrogeninthesystem(Dierberg1980).Nitrateplusnitriteconcentrationsmayalsobelowinthesewatersduetorapidplantuptakeanddenitrification,althoughdenitrificationisinhibitedatlowpH(Mitchell1974;Brezonik1977).NitratewasaddedtojarandcoremicrocosmscomposedofwaterandsoilfromthetitishrubswampinApalachicola,Florida(Haack1984).Nitratelossdidoccurinboththejarandcoremicrocosmsbutsedimentwasnecessaryforthenitrateloss.Nomechanismfornitratelosswassubstantiated,althoughitmaybeduetodenitrification,whichoccursinwetlands.ChemicalreductionofnitrateatlowpHmayoccurthroughseveralpathways.Wetlandswithlow pH,highorganicmatter,andhumic

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18compoundshavepathwaysofnitratelossotherthanbiologicaldenitrification(Haack1984).Underhighlyreducedconditions,nitratereductiontoammoniumandorganicnitrogenispossible(BureshandPatrick1978).Theseprocesseswouldalsoaccountforthedominanceofammoniuminthesewaters.Theshallowsurfacewaterincypressdomesandhencethecloseproximityofsoilandwatersuggeststhatthephosphoruscontentofthesurfacewatermaybecontrolledbytheinteractionofphosphoruswiththesoil(Dierberg1980).Soil/phosphorusreactionsarecomplex.Ingeneral,theinorganicphosphorusispartitionedbetweenthesolutionphase(smallfractionoftotalsystemphosphorus)andthesolidphase(alargerportionoftotalsystemphosphorus).Thechemicalspeciesofsolutionphosphorusareafunctionofthereactionsofprotonationandsolublemetalliccomplexionformation(Bohneta1.1979).AtlowpH,ironandaluminumionsonsolid(soil)surfacesformbondswithsolutionspecies(StummandMorgan1981).Theresultingprecipitateremovesphosphorusfromthewatercolumn.Theoxygencontentofthewaterandsoilalsoaffectstheamountofphosphorusinsolutionasphosphorusbecomesmoresolubleunderreducedanaerobicconditions(StummandMorgan1981).Therefore,solublemetallicioncomplexformation(phosphateandhydrousoxidesofironandaluminum)playsagreatroleincontrollingphosphoruslevelsinnaturalwaters.Thelimitforthephosphorusconcentrationinsolutionissetbythedissolutionandprecipitationofthesesparinglysolublephosphoruscompoundsandtheadsorptionofphosphorusonthesurfaceofsoilparticles.IngeneraltheoverallsolubilityofthesemetalphosphatecomplexesisinverselyrelatedtopHwhileadsorptionandprecipitation

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19ofphosphorusaredirectlyrelatedtopH(StummandMorgan1981).Therefore,thelowerthepHthegreaterthesolubilityofthemetalphosphatecomplexesandthegreatertheadsorptionandprecipitationofphosphorusinthesoil.RemovalofphosphatesfromsolutioncanalsobelinkedtopHbecauseofthedependencyofthereactionsuponsoilaluminum(Dubucetal.1986).AtalowpHincypressdomesstudiedbyDierberg(1980)aluminumratherthanironcontrolledphosphorussolubility.Inaddition,atapHlessthan6,organicphosphorusprecipitatesasacomplexwithironandaluminum(Dubucetal.1986).Solubilizationofthesparinglysolublecompoundscanalsooccurduetotheproductionoforganicacids.Theseorganicacidsexistinwaterasnegativelychargedcolloidsthatholdmetallicionssuchasironandaluminum(Kaufman1975b).Thesorptionofphosphatebytheseorganometalliccomplexesoccursbutthedynamicsofthetransformationsarestillunclear.Phosphatecanreactwithmetalionstoformcomplexesinthepresenceoforganicligandssuchasfulvicandhumicacids(BotoandPatrick1978).Phosphateionsmaybeactingasligandsinorganometalliccompounds(Sinha1971).IneithercasetheretentionisafunctionofpH.Biologicalimmobilizationofphosphorusalsooccursinwetlands(Chanetal.1982).Wetlandtreesassimilatephosphorus(Brownetal.1975;Nesseletal.1982;DierbergandBrezonik1983b).Inadditionhighcationexchangecapacityexhibitedbypeatcanleadtotheabsorptionofphosphateanions(MooreandBellamy1974).Therefore,itappearsthatthroughbiologicalandchemicalprocessesinwetlands,lowlevelsofphosphorusaremaintainedinsurfacewaters.

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20PhosphorusAdsorptioninSoilsPhosphorusretentionbysoilsmaybeanadvantageofusingwetlandsasanalternativeforwastewatertreatment.Therefore,emphasishasbeenplacedonusingadsorptionisothermsinordertopredictsoiltypesthatwouldbeamenabletoreceivingwastewater(SommersandSutton1980).Aphosphorusadsorptionisothermdescribestherelationshipbetweentheamountofphosphorussorbedandthatremaininginsolutionatconstanttemperature.Severalequationsdevelopedforgas-solidsystemshavebeenusedtointerpretthesorptionofphosphateonchargedsurfaces.Theadsorptiondataarefittoisothermsdescribedbytheequations.Theisothermscanbeusedtogivearelativeadsorptionmaximum,interpretedasa"quantityllfactor,indicatingthecapacityofthesoiltoadsorbandthusretainphosphorus.TheLangmuirequationisbasedontheassumptionsthatadsorptionisonafinitenumberoflocalizedsites,theenergyofadsorptionisconstant,andmaximumadsorptioncorrespondstoacompletemonolayer.Thustheequationdescribesafinitelimittoadsorptionsothata maximumvaluemaybeobtained.TheLangmuirequationisdescribedasfollows:x/m KCb/(l+KC)whereKisaconstantrelatedtotheadsorptionenergy,Cistheequilibriumphosphorusconcentration andx/mandbarephosphorusadsorbedandmaximumphosphorusadsorptionperunitweightofsoil respectively.Inthelinearformtheequationbecomes:

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21Cm/x (CIb)+(l/Kb)andaplotofCm/xversusCshouldgiveastraightlineofslopelibfromwhichb,theadsorptionmaximumcanbecalculated.StraightlineisothermshavebeenobtainedwhenresultsfromalimitedconcentrationrangeareplottedaccordingtotheLangmuirequation(OlsenandWatanabe1957).AlthoughtheLangmuirequationinitslinearformhasbeenusedfrequentlyinphosphorusadsorptionstudiestheadsorptioncurvesmaynotbelinearoverawideconcentrationrange(OlsenandWatanabe1957;RennieandMekecher1959;Gurney1970;BacheandWilliams1971;FitterandSutton1975).Therearemanypossibleexplanationsforthenonlinearity,butwhereitdoesoccurtheFruendlichandotherequationsmaybeusedtofittheadsorptiondata.TheFruendlichequationisbasedontheassumptionthatthesurfaceconsistsofsitesatwhichtheadsorbatemoleculesinteractlaterally,resultinginacontinuousdistributionofbondingenergiesthatdecreaseexponentiallywithincreasingsaturationofthesurface.TheFruendlichequationcanbedescribedasfollows:wherex/mandCareasbeforeandaandbareconstantsthatvaryamongsoils.Inthelinearformtheequationbecomes:logx/m loga + blogCandaplotoflogx/mversuslogCshouldgiveastraightline.TheFruendlichequationhasbeenfoundtogiveagoodfitoverawiderange

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22ofsoilsandconcentrations(Gurney1970;FitterandSutton1975;BarrowandShaw1975;Barrow1978).TheTempkinequationisderivedfromtheLangmuirequationbut,liketheFruendlichequation,isbasedontheassumptionofacontinuousdistributionofbondingenergies.Inthiscasetheenergyofadsorptiondecreaseslinearlywithincreasingsurfacecoverage.TheTempkinequationcanbedescribedasfollows:xb/m(RT/B)logACwherex,b,andCareasbeforeandAandBareconstants.Aplotofx/mversuslogCshouldgiveastraightline.ThephosphorusadsorptionmaximaofsoilscanbecalculatedfromtheslopeoftheregressionlinesaccordingtotheLangmuirequation.TheFruendlichequationdoesnothavethischaracteristicandthereforeaquadraticregressionanalysisoftheadsorptiondatadevelopedbyYuanandLucas(1982)canbeusedasanalternativetoobtaintheadsorptionmaxima.IfYisthephosphorusadsorbedandXtheequilibriumphosphorusconcentration,thenthequadraticequationisasfollows:andthefirstderivativeofthisequationisequaltozerowhen Yreachesthemaximum,ordY/dX a,+2a2X O.Thereforethephosphorusconcentration(C)attheadsorptionmaximumwouldbeC X

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23Theadsorptionmaximumisobtainedbysubstituting-al/2azforXinthequadraticequation.Ifthisequilibriumphosphorusconcentrationandthecorrespondingadsorptionmaximumderivedfromthequadraticequationarecorrect,thensubstitutionoftheCvaluesintheotherequationsshouldgivecomparativeadsorptionmaxima(YuanandLucas1982).Therehasbeenagooddealofresearchonthenatureofphosphorusadsorptioninsoils,andtherehasbeendebateastowhetherornotorganicmatterincreasesphosphorusadsorption.Anumberofresearchersreportedadecreaseinphosphorusadsorptionbysoilsinthepresenceoforganicmatter,thedecompositionofwhichproducesorganicacidsthatformstablecomplexeswithaluminumandironandconsequentlyblockphosphorusretention(SinghandJones1976).Otherworkersreportedthatorganicmatterincreasesphosphorusretentionbythesoil,possiblyasaresultofmicrobialassimilation.AdsorptionandleachingofphosphorusinacidorganicsoilsandhighorganicmattersandwasdeterminedbyFoxandKamprath(1971).Thesesoilsinwhichthecolloidswereorganichadrelativelylowphosphorusadsorptioncapacitiesrelativetomineralsoils.Phosphorusadsorptionbyorganicmatterwasnegligiblebecauseanyadsorptionthatoccurredwasduetothecationsassociatedwith matter(Wild1950).Organicsoilswithonlyatraceofinorganicmineralshavelittlealuminumorirontobereleasedforboundingwithaddedphosphorus.Thus,althoughtheinfluenceoforganicmatteronphosphorusadsorptionhasbeendebated,organicmatterappearstoaffectphosphorusadsorptioninanindirectmanner(Berkheiseretal.1980).Solubleinorganicphosphorusisreadilyimmobilizedinsoilsbyadsorptionandprecipitationreactionswithaluminumandironunderacid

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24conditions(NurandBates1979;Nichols1983).Lowphosphorusadsorptionhasbeenobservedinsandysoilswithlowclaycontentandisprimarilycorrelatedwithlowcontentofextractableironandaluminum(BallardandFiskell1974;YuanandLucas1982).Layersilicatemineralshavelowphosphorusfixingpotentialbutamorphouscolloidsandsesquioxidesareeffectiveatfixingphosphorus.Thelesscrystallinetheformofthesesquioxides,thegreatertheircapacitytosorbphosphorus.Phosphateionsarethoughttobechemicallyadsorbedontothesurfacesofhydrousoxidesofironandaluminumbyligandexchange,thedisplacementofwatermoleculesandhydroxylgroupscoordinatedwiththeironandaluminumatomsandthecoordinationofoxygenatomsinthephosphateionswiththeironandaluminum(Nichols1983).Inadditiontothischemicaladsorption,RydenandSyers(1977)presentedevidencefora morephysicaltypeofadsorptionthatbecomesoperationalasthechemicaladsorptionsitesapproachsaturationathigherequilibriumconcentrationsofphosphorusinsolution(Nichols1983).Thechemicalandphysicaladsorptionofphosphateontothesurfaceofsoilmineralsisarapidprocess,butslowerphosphatefixationdoesoccurandhasbeenattributedtotheshiftofphysicallyadsorbedphosphorustochemicallyadsorbedforms,thediffusionofphosphorusadsorbedonthesurfaceofporousoxidesofaluminumandirontopositionsinsidethesoilmatrix,andtheprecipitationofcrystallinealuminumandironphosphates(Nichols1983).Theexactmechanismsinvolvedinphosphorusretentioninthesoilareunknown.Therearecontinuumofreactionmechanismsandthereislittleconcernfordistinguishingbetweenadsorptionandprecipitationreactionsasbothphenomenacanbeconsideredtogetherassorption(Berkheiseretal.

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251980).Adsorptionandprecipitationofphosphorusbysoilsarenotnecessarilyapermanentsinkforaddedphosphorus;thereareatleastpartiallyreversible.Areductioninthephosphorusconcentrationinthesolutionincontactwiththesoilmayreleasesomephosphorusintosolution(Nichols1983).Efforthasbeendirectedtowardsidentifyingmeasurablesoilparametersthatcanberelatedtothephosphorusadsorptioncapacityofasoil.Theactive(exchangeable+amorphous)formsofaluminumprovidethebestsingleindexofphosphorusretentioninCoastalPlainforestsoils(BallardandFiskell1974).Thecontributionofactiveformsofirontophosphorusretentionwasatleasttheequalofaluminumonaperunitweightbasis.Poorlycrystallineandamorphousoxidesandhydroxidesofaluminumandironwerepostulatedtoplayaprimaryroleinphosphorusretentioninfloodedsoils(Khalidetal.1977).Anorganicmatteraluminumpeatcomplexinacidsoilsstronglyadsorbedorthophosphateions(Bloom1981).Phosphorusadsorptionwashighlycorrelatedwithorganicmattercontentandexchangeablealuminumcontentinastudythatevaluatedthephosphorusretentioncapacityofretention-detentionwetlandsoils(Sompongse1982).Sheproposed,inlightofBloom's(1981)findings,retentionthroughanorganicaluminumcomplexinthesoilswithhighaluminumcontent.Insoilswithhighironcontent,ironseemedtoplayanimportantroleinphosphorusretention.TarnmoxalateextractablealuminumandinsomecasesTarnmoxalateextractableironhavethebestcorrelationwithphosphorussorptioninmineralsoils(Lopez-HernandezandBurnham1974;BallardandFiskell1974).Similarresultswerefoundinsomewetlandorganicsoils

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26(Richardson1985).TheTammoxalateextractiondissolvestheamorphousandpoorlycrystallineoxidesofaluminumandironthathavebeenpostulatedtoplayaprimaryroleinphosphorusretentioninfloodedsoils.WastewaterDischargetoWetlands Wetlandsareoftenviewedashighlydynamicandadaptableecosystems.Nutrienttransformationprocessesmayenablesomewetlandstoassimilateandstoreincreasedlevelsofnutrientsandothercontaminantsfromwastewater(USEPA1983).Manywetlandshavebeenshowntoprocesswastewaterefficiently (Whigham 1982),toleratinganoxicconditionsassociatedwithBODremovalandeutrophication,andtoremovenutrientsfromwastewatereffectively(Eweletal.1982).Innearlyallinstances,wetlandsrenovateorimprovewaterqualitytosomeextent,butpollutantremovalefficienciesareextremelyvariable(Chanetal.1982).Thereisgreatpromisefortheuseofsomewetlandecosystemsasaneffectivemediumofwastewaterorganiccarbonremoval(Khalidetal.1982).Thecomponentsremaininginwastewaterthatwillexertoxygendemand,measuredasBOD,areveryeffectivelyremovedinwetlandsystemsbythemicrobialflora(KadlecandTilton1979).OptimalBODremovaliscorrelatedwithhighsurfaceareaavailableformicrobialgrowth,andshallowvegetatedwetlandsmaximizethisremovalcapability(Chanetal.1982).BODremovalinnaturalwetlandsrangesfrom70%to96%(TchobanoglousandCulp1980).Wetlandsmayalsoprovideahighdegreeofremovalofsuspendedsolidsthatoriginateinwastewater(KadlecandTilton1979).Long

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27detentiontimesandthickvegetationfiltersuspendedsolids.Removalrangesfrom60%to90%inwetlands(TchobanoglousandCulp1980).Pathogens(bacteriaandviruses)inwastewaterarereducedbyanyprocessesthatpromotesedimentationorfiltrationandincreasedetentiontime(Chanetal.1982;USEPA1983).Thus,large,shallow,non-channelizedwetlandsencouragedie-offofmicrobes(Chanetal.1982).Kadlec(1981)reviewedstudiesthatdocumentedtheintroductionofsignificantlyelevatedlevelsoffecalcoliformsintowetlands.Thelevelsoffecalcoliformswerereducedwithpassageofwastewaterthroughthesewetlands.Ithasbeenamplydemonstratedthatsomewetlandsarecapableofremovingnitrogenandphosphoruscompoundsviaavarietyofmechanisms(KadlecandTilton1979).Whereasnitrogenprocessingislargelybiologicallymediated,redistributionofphosphorustointernalsinksisaresultofadsorption/precipitationreactions(Eweletal.1982).Adsorptionandprecipitationbysoilsarenotnecessarilypermanentsinksforwastewaterphosphorus,astheseprocessesareatleastpartiallyreversible(RichardsonandNichols1985).Therefore,somewetlandsmayeventuallylosetheirabilitytoimmobilizelargequantitiesofphosphorus,but'mayretaintheirabilitytoimmobilizeordissipatelargequantitiesofnitrogen(KadlecandKadlec1979).Wetlandremovalefficienciesfortotalnitrogenandtotalphosphorusarevariable,rangingfrom10%to90%(Richardson1985).Thecapacityfornitrogenremovalinwetlandsislarge(Chanetal.1982);processesincludevolatilization,plantuptake,soiluptake,microbialuptake,sedimentation,nitrification,anddenitrification.

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28 Themajormechanismforremovingnitrogenfromwastewaterappliedtowetlandsseemstobedenitrification(Sloeyetal.1978;KadlecandTilton1979;Nichols1983),butRichardsonandNichols(1985)suggestthatthedisappearanceofnitrogenfromacidorganicsoilsmaybedueasmuchtothechemicalbreakdownofnitriteastodenitrification.Becausethephosphoruscyclehasnogaseousphase,lessphosphorusisremovedfromwastewateraddedtowetlands,althoughhigh,short-termremovalefficiencieshavebeenobserved(Nichols1983).Themagnitudeofphosphorusretentioncapacityvariesconsiderablyamongwetlandtypes(RichardsonandNichols1985;KellyandHarwell1985).Successfulphosphorusimmobilizationbywetlandsoilsisrelatedtocontacttimewithorganicmatter(KadlecandTilton1979),butthequantityofphosphorusadsorbeddependsontheexchangeequilibriumwiththedissolvedphase(Kadlec1987).Plantuptakeisgenerallylessimportantthansoiladsorption/precipitationreactionsforretainingphosphorusinwetlandecosystems(Eweletal.1982),butthebestpossibilitiesforusingwetlandplantsfornutrientremovalappeartooccurwhenthenutrientsarestoredinwoodyplants(EwelandQdum1978).FlowthroughawetlandinnorthernCanadareducedorthophosphatebymorethan95%(Hartland-RoweandWright1975).Asimilarreductionofphosphorusoccurredinanorthernpeatlandreceivingsewage(Richardsonetal.1976).GreaterexportsofphosphatefromchannelizedascomparedwithnaturalCoastalPlainstreamsoccurredasaresultofareductioninthesoil'scapacitytoassimilatephosphate(Kuenzleretal.1977).MostofthephosphorusaddedtosurfacewateraccumulatedinthesedimentsinanalluvialswampforestintheNorthCarolinaCoastalPlain(Holmes1977).ThefloodplainofasmallCoastalPlainstreamin

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29NorthCarolinawas asinkforphosphorus(Yarbro1979).IntheSanteeRiverSwamp,phosphoruswasadsorbedordepositedassedimentsaswatercoursedthroughthefloodplainfromtheriver(Kitchensetal.1975).PhosphorusaccumulatedinthefloodplainofatupeloswampinsouthernIllinois(Mitschetal.1979).InWildwood,Florida,secondarilytreatedwastewaterhasbeenreleasedforover20yrsintoaseriesofthreewetlands.ThewetlandthatdirectlyreceivesthewastewaterisdominatedbyTyphalatifolia(cattail)andSalixsp.(willow).ThismarshiscoveredbyLemnasp.(duckweed).ThedischargefromthiswetlandflowsthroughaditchtoamixedhardwoodswampdominatedbyFraxinusprofunda(ash),Taxodiumdistichum(baldcypress),andNyssabiflora(blackgum).Thedischargefromthiswetlandflowsthroughanotherditchtoa muchlargermixedhardwoodswampwithsimilarspeciescomposition.Thefirsttwowetlandsreceivehighernutrientloadingsthanthethirdwetland(Brownetal.1975).Afterflowingthroughthewetlands,theconcentrationofnutrientsinthewaterwasreducedtovaluesequaltoorlessthanthosefoundinacontrolswamp(Boytetal.1977).Reductionsintermsofmassloadingwerecalculatedtobe87%forphosphorus.Novisiblestressordamagetothenaturalsystemwasevident.Dilutionratherthanchemicalorbiologicalprocessesplayedthekeyroleinreducingnutrientandorganicloads.Nobuildupofnutrientsinsedimentswasindicated.Treeboringsshowedsignificantincreasesintreegrowthfora19-yrperiodascomparedtotheprevious19-yrperiod.Therefore,treesdidplayanactiveroleinremovingnutrients(Brownetal.1975).Inaddition,thenumberof

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30fecalcoliformsdeclinedtobackgroundlevelswithin1kmofthepointofwastewaterdischargetothewetland(Boytetal.1977).AcypressstrandinWaldo,Florida,dominatedbyTaxodiumascendens(pondcypress),blackgum,andAcerrubrum(redmaple)hasbeenreceivingwastewatersince1934fromoverflowofacommunityseptictank.Thiswetlandreducednutrientconcentrationstobackgroundlevelsduetophosphorusretentioninthesediments(Nessel1978).Totalphosphorusconcentrationswerereducedby 51% insurfacewatersleavingthiscypressstrandand 77% afterpassingthroughthesoilprofileintoshallowgroundwater(Nessel1978).Infiltrationwas amajorrouteforwaterleavingthissystem.Thisfacilitatesphosphorusremovalandexplainsthelong-termeffectivenessofthiswetlandintermsofphosphorusassimilation(RichardsonandDavis1987).Pondcypresstreegrowthwasstimulatedandincreasednutrientconcentrationsinwoodandfoliagewererecorded(Nesseletal.1982),butthisrepresentedonly 1% oftheestimatedphosphorusinflowtothesystem(NesselandBayley1984).Bacteriahadlowsurvivalrates; 99% reductionwasachievedin32daysforthevirusestested(ButnerandBitton1982).Anothercypressstrand,BasinSwamp,inJasper,Florida,hasbeenreceivingrawwastewaterorprimaryorsecondarilytreatedwastewatersince1914(Tuschalletal.1981).Totalnitrogenandphosphorusconcentrationsinthesurfacewaterwereeffectivelyreducedby 69% and36%,respectively,betweentheinflowandoutflowoftheswamp. Aportionofthereductionwasattributedtodilutionbysurfacerunoffintotheswamp.Dischargeofrawandprimarywastewater in theswampdecreasedgrowthratesinpondcypress;however,dischargeofsecondarilytreatedwastewaterenhancedgrowthovercontrols(Lemlich

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31andEwel1984).Therateoffecalcoliformexportdependedonthedetentiontimeofthestrand(Brezoniketal.1981).BasedontheirfindingsattheJaspersite,FritzandHelle(1981)indicatedthattheuseofaflow-throughwetlandsystemforadditionaltreatmentofsecondarilytreatedwastewaterisaworkableandeconomicalalternativetoconventionalphysical-chemicaltreatmentmethods.Mostofthewastewaterfromthe Walt Disney World Complexhasbeendischargedintoamixedhardwoodswampsince1977.Thesiteisdominatedbyredmaple,blackgum,baldcypress,andPinuselliottii(slashpine).Thiswetlandwasisolatedbybermsandthedischarge,whichultimatelyreachesReedyCreek,wasartificiallycontrolled.Thiswasthelargestfull-scaleforestedwetlandeffluentdischargesystemthathasbeenextensivelymonitoredintheU.S.(Knightetal.1987).Thelong-termaverageremovalratewas75%forBODand80%forsuspendedsolids.Totalnitrogenconcentrationwasreduced88%butnototalphosphorusreductionwasobserved(KohlandMcKim1981).Anetreleaseofphosphorusfromthissystemoccurred,probablybecausetheretentioncapacityoftheswamphadbecomesaturated(McKim1982).Removalefficiencydependedoninputconcentrationaslowerremovalefficienciesresultedfromlowerinputconcentrationsovertherangeofvaluesobserved(Knightetal.1987).PottsburgCreekSwamp, amixedhardwoodswampinJacksonville,Florida,hasbeenreceivingsecondarilytreatedwastewatersince1967.Thiswetlandisvegetatedbyamixtureofspeciesincludingash,redmaple,blackgum,pondcypressandLiguidambarstyraciflua(sweetgum).Basedonmassbalancecalculations,totalnitrogenloadingswerereducedby87%andtotalphosphorusloadingsby62%(WinchesterandEmenhiser

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321983).Therewerenonetconcentratingordilutingeffectsand,therefore,nutrientreductionwasduetoinfiltrationwithintheswamp.Cypressdomesarea commontypeofswampinFlorida.Theseforestedwetlandsaredominatedbypondcypressandoftenhavelargenumbersofblackgum.Theterm"dome"comesfromthecharacteristicprofileofthesewetlands,becausethetreesaretallerinthecenteranddecreaseinsizetowardtheedges.Astudyoftheuseofcypressdomesfortheadvancedtreatmentofdomesticwastewaterwasconductedfrom1975to1979.Biochemicaloxygendemandwasnotsubstantiallyreducedasthewastewatertraveledfromthecentertotheedgeofthedomes(DierbergandBrezonik1978).Incontrasttothis,theconcentrationsofnutrientsweregenerallylowerinthesurfacewatersattheedgesofdomesreceivingwastewaterthanatthecenter,buttheoverallreductionofnutrientconcentrationsinthesurfacewaterswaslessthan33%(DierbergandBrezonik1983a).Infiltrationofsecondarilytreatedeffluentthroughorganicsedimentsliningthebasinsofthecypressdomesreducednitrogenandphosphorusconcentrationstobackgroundlevels(DierbergandBrezonik1983a).Eightysevenpercentofthetotalnitrogenenteringthesystemwasstoredinpeat,roots,andwood,orwasreleasedtotheatmospherebydenitrification,andapproximately92%ofthephosphorusenteringthesystemwasremovedbyplantuptakeorsedimentdeposition(DierbergandBrezonik1983b).Basedonleachingstudiesusinglaboratorycolumns,organicsoilsinthedomeshavealargephosphorusadsorptioncapability(Dierberg1980)andthisremovalcapabilitycouldcontinueforalongtime(DierbergandBrezonik1983a).Thecypresstreesaccountedfor

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33storageof24%oftheestimatednitrogeninflowbutonly 1% oftheestimatedphosphorusinflowtothesystem(DierbergandBrezonik1984).After5.5yrsofwastewaterdisposal,theunderstoryvegetationandexistingtreesshowednodetrimentaleffects(Eweletal.1981).Themoststrikingresponseofunderstoryvegetationwasthedevelopmentandpersistenceofathicklayerofduckweedovertheentiresurfaceofthedomesreceivingwastewater(Ewel1984).Initially,itwasreportedthattreegrowthrateswereunaffected(Eweletal.1981),butfurtherinvestigationindicatedthatcypresstreesgrewfasterundertheinfluenceofsewageeffluentandthattheresponsewasalmostimmediate(BrownandvanPeer1989).Thenumberoffecalcoliforms(Foxetal.1984)andviruses(Scheuerman1978)werereducedduringinfiltrationofsurfacewatertotheshallowgroundwateraquifer.Bindingofvirusesmaynotbepermanent(Scheuerman1978)andthedomesubstratemaynotbeaperfectfilter(Wellingsetal.1975).Insummary,thecypressdomesstudiedandtheirassociatedsedimentscanreducethelevelsofmajorwastewaterconstituentstolevelscomparabletothoseofconventionaltertiarytreatmentprocesses(DierbergandBrezonik1983b)andcanthusserveasanaturaltertiarytreatmentsystem(DierbergandBrezonik1983a).Resultsfromthesestudiesaredifficulttogeneralizequantitatively.However,somequalitativeconclusionsaboutwetlandtransformationandassimilationofdifferentformsofnitrogenandphosphoruscanbereached(RichardsonandDavis1987).First,nitrogenremovalfromwater was consistentandsubstantialoverarangeofloadingrates.Removalefficiencywasgenerally75%ormoreonamassloadingbasis.Soilsprovidedafiniteandreversiblesinkforammonium

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34andphosphorus,andretentioncapacitydependedonacomplexoffactors.Incontrasttonitrogenremoval,efficiencyofphosphorusremovalvariedgreatly.Naturalwetlandscanprocesssignificantamountsofnitrogen,andcanbemanagedtoassimilateevenmore(RichardsonandDavis1987).Phosphorusretentionishighlyvariableandhighlydependentonthecharacteristicsofthewetlandecosysteminvolvedandtheloadingrates.Wetlandsdifferintheirabilitytostoreandreleasenutrients.Sometypesofwetlandsdominatedbywoodyplants(swamps)maybecapableofassimilatingexcessnutrientsthroughmicrobialprocessesandlong-termstorageinthesoilandinvegetation.Cautionmustbeusedwhenmakinggeneralizationsaboutnutrientremovalefficienciesfromadiverseandsparsedatasetthatincludesavarietyofwetlandtypesandawiderangeofyearsofapplication(RichardsonandNichols1985).However,trendsfromthemostcompletestudiesshow ageneralpatternofdecreasednutrientremovalefficiencywithtimeandwithhigherloadingrates(RichardsonandNichols1985).EvapotranspirationinForestedWetlandsEvaporationistheconversionofwaterfromtheliquidstateintovapor,anditsdiffusionintotheatmosphere.Transpirationisthereturnofwatertotheatmospherebyplants.Evapotranspirationthenistheevaporationfromallmoistsurfacestotheatmosphere.Evapotranspirationincludesseveralprocessesthataredifficulttoquantifyseparately;therefore,potentialevapotranspirationisusuallyestimated.Potentialevapotranspirationisdefinedastheevaporativefluxthatwillnotexceedtheavailableenergyfrombothradiantandconvectivesources(SaxonandMcGuinness1982).Indetermining

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35potentialevapotranspiration,atmosphericvariablesareconsideredseparatelyfromplantandsoileffects.Oftenwaterisnotfreelyavailableandactualevapotranspirationislessthanpotentialevapotranspiration.Therefore,potentialevapotranspirationisestimatedfirst,basedonmeteorologicalfactors,andtheamountofthatpotentialusedbytheactualevapotranspirationprocessesisthenestimated.AwaterbudgetfortheOkefenokeeSwampwasdevelopedbyRykiel(1977).Evapotranspirationwasestimatedasaresidualterm.Anindependentestimateofpotentialevapotranspirationwas madewiththeThornthwaitemethodforcomparisonwiththeresidualestimate.Potentialevapotranspirationwasfoundtounderestimateevapotranspirationandthereforeshouldbeusedasa minimumvaluewithnormalrainfall(Rykiel1977).Estimatesofpotentialevapotranspirationwerecomparedtofieldmeasurements(groundwaterlevelfluctuation)ofevapotranspirationinacypressstrand(Carteretal.1973).Evapotranspirationmeasuredinthismannerwashigherthanestimatedpotentialevapotranspirationexceptwhenthegroundwaterlevelwaswellbelowthelandsurfaceandwaterwasunavailabletoplants.EvapotranspirationvaluesmeasuredinthesamemannerinthesecypressstrandswerereportedbyBurns(1978). When thegroundwaterlevelwashigh,fieldevapotranspirationapproachedpanevaporation.Thesestudiessuggestthatestimatesofpotentialevapotranspirationmayunderestimateevapotranspirationwhenwateravailabilityishigh.Inorderforevapotranspirationtooccur,asourceofenergyandavaporpressuregradientbetweentheevaporatingsurfaceandthe

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36atmospheremustexist.Solarenergyisthemainsourceofenergyandadvectionofenergyfromoutsideanareamayincreaseevapotranspiration(oasiseffect).Evapotranspirationisinfluencedbyanumberoffactorsincludingsolarradiation,airtemperature,vaporpressuregradient,windandairturbulence.Inadditiontothemeteorologicalfactorsthenatureoftheevapotranspiringsurfaceandavailabilityofwaterareimportant.Forexample,theheightandroughnessofvegetationinfluenceairturbulence,andtranspirationcanattimesexceedopenwaterevaporation(Linacre1976).Ontheotherhand.theshelteringeffectandhighalbedoofvegetationaswellastheresistancetowatermovementindryperiodscoulddecreasetherateofwaterlossduringdryperiods(Linacre1976).ThepresenceofvegetationinawoodedswampinsouthernOntarioreducedwaterlossinrelationtothatfromandopenwatersurface(Monro1979).Swampvegetationwasefficientinconvertingnetradiationintoturbulentenergyexchange,thusminimizingwaterloss. Wetlands mayevapotranspireata lowratewhenwaterislimitingandatahigherratewhenwaterisreadilyavailable.EvapotranspirationinthreecypressswampsinWithlacoocheeStateForestwasmeasuredbyEwel(1985)bydeterminingchangesinwaterlevels.Daytimereductionsinwaterlevel due toevapotranspirationandinfiltrationcouldbedistinguishedfromnighttimereductionsinwaterlevel,duetoinfiltrationonly.Evapotranspirationrateswerecalculatedasthedifferencebetweenthedaytimeandnighttimewaterlevelchangesconvertedtoavolumebasis.Averageannualevapotranspirationwasestimatedtobe31in.duringthe3yrsforwhichdatawereavailable.Averageannualprecipitationforthe3-yrperiodwas 59in.

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37Therefore,evapotranspiration was 52%ofprecipitationatthesesites.EvapotranspirationinslashpineflatwoodsinnorthFlorida was estimatedoverthesame3-yrperiodtobe41in./yr,or74%ofprecipitation.Theestimatedevapotranspirationrate was 77%ofthisrate.Thiscomparisonconfirmedearlierreportsof low evapotranspirationratesforcertaincypressswamps. Adecreaseintherateofwaterlosswouldbeawaterconservationmechanismandanydiscussionofwaterconservationbywetlandvegetationshouldincludereferencetoxeromorphy.Plantsofacidhabitatsareoftenstructurallyadaptedtoconservewater,asareplantsfromxerichabitats(Clewell1981).Suchplantsinacidhabitatsarecalledphysiologicalxerophytes(Clewell1981).Xeromorphiccharacteristicsinplantsincludethickcuticles,deeplysunkenstomata,andhighlyreflectivesurfaces.Thesearethecharacteristicsofevergreensclerophyllousleavessuchasthoseoftitiandsweetbay.Thesecharacteristicshaveevolvedindesertplantsinresponsetodroughtbutsomexeromorphicspecieshavea"bimodal"distribution,i.e.,theyarefoundinbothwetanddryhabitatsbutnotinintermediatehabitats(Larsen1982).Aspeciescouldundergoselectionforcharacteristicsthatadaptitmoreeffectivelytobothwetanddryhabitatsthanforthehabitatsbetweentheseextremes.Intheprocessofevolvingcharacteristicspermittingsurvivalinwetareas,theplantscouldhaveacquiredcharacteristicsfittingthemforsurvivalindryareas.Thesecharacteristicsmaydevelopinresponseto low fertilityandpotentialwaterdeficiency,butwaterlossisthekeyfactor(Brunig1971).Ontheotherhand,xeromorphyinplantsmaybeanadaptationtolowfertilityandwaterconservationfeaturesmaybefortuitous(Larsen

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1982).38Ifxeromorphyisanadaptationtodryconditionsthereductionoftranspirationlossescouldbeanecessaryadaptationforsurvivalduringdryperiods.Lowtranspirationratesforcypressdomes maylikewisebeanadaptationforsurvivalwhenwaterbecomeslimitingduringdryperiods(Brown1981).Evapotranspirationcanbedeterminedbyvariousdirectmeasuressuchasthemeasurementoftheincreaseinwatervaporinairflowingthroughgasexchangechambers(Odumetal.1970;OdumandJordan1970;Cowles1975;Brown1978;Burns1978).ThemetabolismandtranspirationofsomeplantsinatropicalrainforestweremeasuredbyOdumetal.(1970),andtheeffectofairvelocityonleafmetabolismwasevaluated.Airvelocityinlowrangeslimitedmetabolismoflivingforestcomponents.Inaddition,transpirationincreasedasymptoticallywithairflowoverleafsurfaces(Odumetal.1970).Therefore,flowratesinchambersshouldnotminimizemetabolismorenhancetranspiration.Airflowrates were adjustedbyBrown(1978)soasnottolimitmetabolismorenhancetranspiration,andtoinsurethatthemaximumdifferenceintemperaturebetweentheambientandexhaustairneverexceeded 3C. FreshwaterWetlandModelsandtheirUseinSimulating Wastewater AdditionThe numberofmodelsoffreshwaterwetlandsintheliteratureislarge(CostanzaandSklar1985).Theseauthorsprovidedasystematicreviewoffreshwaterwetlandmodelsthatusesomekindofformalmathematicaldescription,eitherexplicitequationsorsystemdiagramswithimpliedequations.Therepresentativebutnotexhaustivereviewlisted87modelsin59differentstudies.Therewere18forestedswamp

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39models,9bottomlandhardwoodmodels,14emergentmarshmodels,5floatingmarshmodels,30shallowlakemodels,2bogorfenmodels,4tundramodels,and5combinationmodels.Morethan60%ofthemodelswerenon-linear.Thereare two majortypesofecologicalmodels,whichcanbeclassifiedforconvenienceasanalyticmodelsandsimulationmodels(HallandDay1977).Analyticmodelsusemathematicalprocedures to findexactsolutions to differentialandotherequations.Thesemodelsarenotgenerallyused to studywholeecosystemsbecausetheycannotbeused to solvemanynon-linearsystemsofequations that mayprovideabetterdescriptionofanecosystem.Simulationmodels,ontheotherhand,donotgiveanexactsolutiontoanequationovertime,and,therefore,onetypeoferrorassociatedwiththesemodelsisrelated to theinexactnatureofthesolutiontechniqueused.Simulationmodelscansolvemanyequationsnearlysimultaneouslyandcanincorporatenon-linearity(HallandDay1977).Awidediversityoftypesofmodelsdescribeandsimulatewetlanddynamics(Mitsch et al.1982).Themajortypeswereclassifiedfortheirpurposesas:energy/nutrientecosystemmodels,hydrologymodels,spatialecosystemmodels, tree growthmodels,processmodels,causalmodels,andregionalenergymodels.Inenergy/nutrientecosystemmodels,materialspassthroughorcycleamongbioticandabioticcomponentsandexchangewiththesurroundings.Thesemodelsaregenerallynon-spatial,aggregatedmodelswithfeedbacksand cnteractions amongcomponents.Bothenergyflowandnutrientcyclingcanbecombinedintoonemodel.Inspatialecosystemmodelstheattributesofecosystemmodelsarecombined with spatial

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40transportmodels(hydrodynamictransportmodels)describingwetlandhydrologyandpollutanttransportovershortperiodsandlargeareas.Althoughthedynamicsofwetlandshavebeenrepresentedbyavarietyofecologicalmodels,ofteninvolvinggreatdetailandcomplexity,fewspatiallydistributedmodelshaveemerged(Mitsch1983).Hydrodynamictransportmodelsdescribingstreamflowandstormrunoffhavebeendevelopedforwetlands(HopkinsonandDay1980),andamodelhasbeendevelopedforoverlandflowthroughvegetatedareas(HammerandKadlec1986).Someoftheenergy/nutrientandspatialecosystemmodelsdescribedbyMitschetal.(1982)weredevelopedtosimulatetheeffectsoftheadditionofwastewateronwetlandcomponents.Thesearedescribedinmoredetailbelow.SimulationmodelsweredevelopedaspartofalongrangestudyinnorthcentralMichigantoinvestigatethefeasibilityofusingpeatlandsfordisposaloftreatedwastewater(KadlecandTilton1979).Morespecifically,themodelspredictedlong-termchangesinbiomassandnutrientconcentrationsinthismarsh/bogpeatlandecosystem.Initially,Dixon(1974)developedamodelemphasizingthebiomassdynamicsofthesystem.Thiswascombinedwithmodelsofwaterandnutrientcomponentsintoamacromodeltopredicttheeffectsoftheadditionofwastewateronthesewetlandcomponents(Parker1974).Theecosystemwasdividedintoblocks,whichwerefurtherdividedintounitsorcompartments,eachofwhichrepresentedthebehaviorofabioticorabioticvariable.Eachunitorcompartmentwasrepresentedbyatimevaryingdifferentialequation.Therefore,asetofordinary,first-order,non-lineardifferential,massbalanceequationscomprisedthemodel(DixonandKadlec1975).Thiswasthefirstspatially

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41distributedmodelofawetlandecosystemusedtopredicttheimpactsofwastewateraddition.Aseriesofsimulationswasrunvaryingnitrogenandwaterparameterstodeterminetheeffectsonthebiomass,waterandnutrientcomponents.Thesimulationswereintendedtoindicatetherelativeeffectsofaddedwaterandnutrientsonthewetlandandnotpredictactualresults.DixonandKadlec(1975)pointedoutthatactualpredictionsshouldawaitcompleteupdatingandvalidationofthemodel.HammerandKadlec(1983)thendevelopedasimplifiedmodelofwastewater/wetlandinteractionsthataccountedforthemovementofsurfacewaterinresponsetogradientandvegetationflowresistance,andallowedmaterialbalancestobedeterminedinawetlandecosystemreceivingwastewater(Hammer1984).Thismodelalso concained partialdifferentialequations(Hammer1984).Theresultantanalyticalsolutiontothedifferential-integralequationdescribedthesolutebalanceinthesurfacewatersheetforthisidealizedsystem(Hammer1984).Inthismodel,thesimulatedremovalofdissolvednutrientsfromsurfacewatersisatwo-stepprocess,consistingofdeliveryandconsumption.Deliveryisaccomplishedbyconvectivemasstransferwithinsurfacewatersorbydownwardflowduetowaterinfiltration.Consumptionoccursprincipallyatthesurfaceofsoilandplants.Inaddition,twotreatmentregimesexistinthewetland.Inthevicinityofwastewaterdischargeasaturatedregionexists.Here component removalratesarequiteslow,comprisedofuptakedue to adsorptioninthedeepsoil,incorporationofmaterialintonewsoilandwoodyplants,andmicrobialreleaseofgases to theatmosphere.Outsidethissaturatedregion,surfacewaterconcentrationsofwastewatercomponentsdropexponentiallywithdistance.Inthiszoneofrapidremoval,the

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42transportofdissolvedcomponentsthroughthewatersheetlimitstheoverallrate(Hammer1984).Thecombinedtotalarearequiredforassimilationofpollutantsovertimedeterminesthetreatmentcapacityofthesystem.Tofacilitatetheuseofthemodeloverlongperiodsoftime,alltransfersbetweenunitsorcompartmentsweretakenastheannualnetaccumulationineachcompartmentand,therefore,thecyclingofnutrientsandothermaterialsonaseasonalbasiswasnotexplicitlyaddressed(HammerandKadlec1983).Thisspatiallydistributedhydrologicalmodelprovidesaconvenientmeansbywhichtheresponseofnaturalorconstructedwetlandscomponentscanbepredictedusingsitespecificinformation(Hammer1984).SimulationmodelsweredevelopedforacypressdomeinFloridatoinvestigatemanagementissues(Mitsch1975a,1975b;Odumetal.1977;Deghi1977;DeghiandEwel1984).Themodelsweredevelopedinparttoindicatelong-term(100yrs)dynamicsofacypressdomereceivingwastewater.ThemodeldescribedbyMitsch(1975a,1975b)andOdumetal.(1977)wasdesignedtodealwithseveralmanagementquestionsinvolvingcypressdomes,includingtheoptimumrateofharvesting,possibleeffectsoffire,andtheirwastewatertreatmentcapability.Themodelincludedtwoautotrophiccomponents,thecypresstreesandtheunderstory.Thesedimentcomponentconsistedofnitrogen,phosphorus,organicpeatandwater.Themodelwasdesignedtorunfor10to100yrs;therefore,annualvariationsinsolarradiationwereignored.Flowssuchaslitterfallandgrossprimaryproductionweredeterminedfromyearlyaverages.Primaryproductivitywasmodeledwitha

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43non-stratifiedapproach(equalcompetitionforsunlightbetweenthetwoautotrophiccompartments)andwithastratifiedapproach(cypresscanopyhavingacompetitiveadvantage).Eachplantcompartmentcouldutilize5%oftheflowthatwasavailabletoit.Twopathwaysfordecompositionweredesignedintothemodel,theiroperationdependentonwaterlevel.Severallimitingnutrientschemeswereutilizedinthemodel.ThemodeldescribedbyDeghi(1977)andDeghiandEwel(1984)examinedthelong-termbehaviorofphosphorusinthecypressdomesubsequenttowastewateraddition.Fourautotrophiccomponentsweredistinguishedinthemodel:cypresstrees,hardwoodtrees,understoryvegetation,andduckweed.Themodelwasdesignedtorunfor50yrs;therefore,annualandseasonalvariationsinforcingfunctionswereignored.Theamount of sunlightreachinganyofthethreestratawithinthe domewasrelatedtothebiomassofvegetationaboveit.Incorporatingaspectsofthemodelsdescribedabove,asimpletractableecosvstemsimulationmodelwasdevelopedtopredictthelongtermresponsesofthemaincomponentsandprocessesofthetitishrubswampinApalachicola,Florida,towastewaterdischarge.Themaincomponentswerevegetation,waterandsoil,andtheprocesseswerecarbon,nitrogenandphosphoruscycling,andwaterflow.ThesecomponentsandprocesseswerequantifiedinordertodeterminetheirresponsestowastewaterdischargeandtoaddbasicinformationtothestudyofforestedwetlandsinFlorida.

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CHAPTER2METHODSVegetationAnalysisA mapofthevegetationofthetitishrubswampstudysitewasmadeutilizingbothhighandlowaltitudeaerialphotographs.Quantitativeinformationaboutthestructureandcompositionofthevegetationatthetitishrubswampstudysite was obtained with avariationofthequadratsamplingtechnique(Smith1978).Belttransectswerelaidoutineachoffourwetlandcommunitytypesdelineatedonthemap.Aspeciesareacurvewasusedtodeterminetheminimumnumberofmultipleplotsneededforasatisfactorysample(Smith1978).Theidentificationanddiameteratbreastheight(dbh)ofindividualsinthetreesizeclass(dbhgreaterthanorequalto10cm)wererecordedineachoffour10mx20mquadratswithineachtransect.Theidentificationanddbhofindividualsintheshrubsizeclass(dbhlessthan10cmandgreaterthanorequalto4 cm,andheightgreaterthan1.3m) were recordedineachoffour5mx10mquadrats(onewithineachtree-size-classquadrat).Thedbhvaluesoftheindividualswerethenconvertedtobasalarea.Thedensity,dominance,andfrequencyvaluesweredeterminedforeachspeciesasfollows(Cox1976):44

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45density numberofindividuals/areasampled,dominance totalbasalarea/areasampled,frequency numberofplotsinwhichspeciesoccurs/totalnumberofplotssampled.Thesevalueswerethenconvertedtoahectarebasis.Foraparticularspecies,thesevalueswerethenexpressedinarelativeform,whichshowsthepercentageofthatspeciesamongallspecies(Cox1976):relativedensity=(densityforaspecies/totaldensityforallspecies)x100,relativedominance = (dominanceforaspecies/totaldominanceforallspecies)x100,relativefrequency (frequencyforaspecies/totaloffrequencyvaluesforallspecies)x100.Relativevaluesfordensity,dominance,andfrequencywereaddedtogethertogiveasingleimportancevalueforeachspecies.Eachimportancevaluewasconvertedtoapercentagebasisandexpressedforboththe stratum (sizeclass)andthecommunity.Alineinterceptmethod(Smith1978)wasusedalongthe80-mpermanenttransectsineachofthefourcommunitiestodeterminethepercentgroundcoverofthevegetationlessthan1.3min height. Thisincludesherbaceousandwoodyvegetation.Thetotallineardistancecoveredbyeachspecies(orbarehummock)alongthetransectwasrecorded.Thepercentcoverwascalculatedasthetotalinterceptlengthofeachspecies(orbarehummock),dividedbythetotaltransectlength,multipliedby100.

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46BiomassandNutrient StockEstimatesBiomassofthetitishrubswampatthestudysitewasestimatedusingregressionequationsdescribingbiomassasafunctionofselectedphysicaldimensions.Forthreespeciesharvestedatthestudysite,acomputerprogram(CURFIT:Spain1982)forfittingtenbasicmodelequationstoasetofx,ydatawasusedtodeterminetheappropriatelinearregressionequations.Statisticsonthebestfittingmodelequationareprovided.RegressionequationsdevelopedbyBrown(1978)wereusedforspeciesnotharvestedatthestudysite.Tendifferentsizedindividualsofthreespecieswerefelled:blacktiti,redtiti,and (sweetbay).Thedbh,height,location(height),anddiameterofallprimarybranches(anybranchesextendingfromthebolewithadiameterlessthanthebole)ofeachindividualwererecorded.Thediametersofthetwoprimarybranchesattheendofthebolewerealsorecorded.Thediametersatthebaseofeachindividual(BD)andatalocationwherebuttswellnolongeroccurred(SID)wererecorded.Thelengthofthisfirstsection(SlL),withbuttswell,wasrecorded.Beginningatthis'pointandmovingtowardstheendofthebole,theindividualwasdividedintoadditionalsections.Thesectionlength(SL)wasdeterminedbyselectingasectionwithapproximatelythesamediameterateachend.Thelengthofeachsectionandthediameteroftheindividualatthetopofeachsection(SD)wererecorded.Adiscatthetopofeachsectionwasharvestedandeachdisclength(DL)wasrecorded.Thediscsweredriedtoaconstantmassinthelaboratoryandtheirdryweights(DW)weredetermined.

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47Thefollowingformulawasusedtoestimatethedryweight(SW)ofallbutthefirstsection. SW -SLx DW /DL.Thedryweightofthefirstsection(SlW),withbuttswell,wasestimatedwiththefollowingformula. SlW -(SlLx DlW / DlL) +{(SlLx DlW / DlL)x(BD-SID)]/(SIDx2).Thebolebiomasswasestimatedbysummingtheestimateddryweightsofallsections.Theprimarybranchesofeachindividualweredividedintothreesizeclasses(small,mediumandlarge)basedondiameter.Oneprimarybranchineachsizeclasswasrandomlyselectedfromeachtreeandharvested(i.e.,threepertree).Eachprimarybranchwasseparatedintoleafandbranchmaterial.TwohundredleavesweresubsampledfromeachprimarybranchthatwasharvestedandtheirareawasdeterminedinthelaboratorywithaHayashiDenko Companymodel leafareameter.Leafandbranchmaterialweredriedtoaconstantmassinthelaboratoryandtheirdryweightsweredetermined.Theleafareaandthedryweightof the 200subsampledleaveswere used tocalculatetheleafbiomasstoarearatio.Aleafbiomasstoarearatio was calculatedforeachspeciesbasedontreeheightfortwoverticalintervals(9to12mand3to9m).Thedryweightofbranchmaterial predictedusingprimarybranchdiameterastheindependentvariable.Inthesamemanner,the

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48dryweightofleafmaterialwaspredictedusingprimarybranchdiameterastheindependentvariable.Theestimatedbole,branch,andleafbiomassesforeachindividualweresummedtoobtaintheestimatedabovegroundbiomassforeachindividual.Theestimatedabovegroundbiomassandthedbhofthetenindividualsforeachspecieswereusedtopredicttheabovegroundbiomassusingdbhastheindependentvariable.Theregressionequationforeachspecieswasusedforindividualsofthatspeciesgreaterthan4cmdbhsampledinvegetationanalysisquadratstoestimatetheirabovegroundbiomassonanarealbasis.Theestimatedleafbiomassandthedbhofthetenindividualsforeachspecieswereusedtopredicttheleafbiomassusingdbhastheindependentvariable.Theregressionequationforeachspecieswasusedforindividualsofthatspeciesgreaterthan4cmdbhsampledinvegetationanalysisquadratsinthebayswampcommunitytoobtainanestimateoftheirleafbiomassonanarealbasis.Theestimatedabovegroundbiomassandthedbhofthesmallestindividualforeachofthethreespecieswereusedtopredicttheabovegroundbiomassusingdbhastheindependentvariable.Theregressionequationwasfittedthroughtheorigin.Thisregressionequationwasusedforallindividualslessthan4cmdbhsampledinvegetationanalysisquadratstoobtainanestimateoftheirabovegroundbiomassonanarealbasis.RegressionequationsdevelopedbyBrown(1978)wereusedforblackgum,pondcypressandslashpinetrees.Herbaceousbiomassandlitterwereestimatedbycollectingallthematerialinfive0.5m2circularplotsrandomlysampledwithineach200 m2vegetationanalysisquadrat(20percommunitytype).Thematerial

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49wasseparatedintolive(herbaceous)anddead(litter)components.Leaflitterfallsampleswerecollectedmonthlyfor1yrfromthree0.1m2basketslocatedat10mintervalsineachcommunity.Asubsampleofeachdisc(bole),leafandbranchmaterialofeachharvestedprimarybranch,eachherbaceousplotandofeachlitterplot,andtriplicatesubsamplesoftheyearlycompositeofleaflitterfallfromeachcommunityweregroundinaWileyMill.AO.l-gsampleofthegroundmaterialwasdigestedwithamixtureofK2S0 4 ,CUS04andseleniuminaratioof100:10:1,and2 mlofH2S0 4(NelsonandSommers1972).Thesampleswereheatedonablockdigester,cooled,anddilutedto50 mlwithdeionizeddistilledwater,andthenanalyzedbyautomatedcolorimetricanalysisforammoniumnitrogenandtotalphosphorus(USEPA1980).Bole,branchandleafbiomasswereestimatedastheproductoftheaveragepercentofthetotalbiomassofthesecomponentsforthethreespeciesintensivelystudiedandtheabovegroundtreebiomassforeachcommunitytype.Thetotalnitrogenandtotalphosphorusinthebole,branchandleafmaterialweredeterminedastheproductoftheestimatedbole,branchandleafbiomassandtheaverageconcentrationforthesecomponents.Thetotalnitrogenandtotalphosphorusintheherbaceouscomponentforeachcommunitytypeweredeterminedastheproductoftheherbaceousbiomassandtheaverageconcentrationofthiscomponentineachcommunitytype.Thetotalnitrogenandtotalphosphorusofthebole,branchandleafmaterial,andtheherbaceouscomponentofeachcommunitytypeweresummedtoobtainthecotalnitrogenandtotalphosphorusintheabovegroundbiomassofeachcommunitytype.

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50 Thetotalnitrogenandtotalphosphorusinlitterforeachcommunitytypeweredeterminedastheproductofthedryweightoflitterandtheaverageconcentrationoftotalnitrogenandtotalphosphorusinlitterineachcommunitytype.Thetotalnitrogenandtotalphosphorusinleaflitterfallforeachcommunitytypeweredeterminedastheproductofthedryweightofleaflitterfallandtheaverageconcentrationoftotalnitrogenandtotalphosphorusinleaflitterfallineachcommunitytype.WaterChemistrvAcompositeprecipitationsamplewastakenquarterlyfor1yr.EachsamplewaspreservedinthefieldwithmercuricchlorideandthenstoredoniceduringtransporttothelaboratoryinGainesville.Partofthesamplewasfrozenforfutureanalysisoftotalphosphorus,andtherestofthesamplewasrefrigeratedatapproximately4'CforfutureanalysisofKjeldahlnitrogenandnitrate-nitritenitrogen.Eightshallowgroundwaterwellsweresampledthreetimesduring1yr.Eachwellwaspumpedoutapproximately24hrspriortosampling.EachsamplewasanalyzedinthefieldforpHandthenstoredoniceduringtransporttothelaboratoryinGainesville.Partofthesamplewasfrozenforfutureanalysisoftotalphosphorus,andtherestofthesamplewasrefrigeratedatapproximately4'CforfutureanalysisofKjeldahlnitrogen,nitrate-nitritenitrogen.conductivity,andchloride.Allprecipitationandgroundwatersamples preservedaccordingtoAPHA(1980)andwerefilteredwithaGelman0.45 membranefilterpriortoanalysis.

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51Surfacewatersamplesweretakenatsevenstationsinthestudysite(Figure3).Adissolvedoxygensamplewastakenatmiddepth,thewatertemperaturewasrecorded,andpHwasmeasuredinthefieldateachstationmonthlyfor1yr.Asamplewastakenmonthlyandfilteredinthefieldwitha Gelman0.45 membranefilterforanalysisoforthophosphate,ammoniumnitrogen,nitrate-nitritenitrogen,andtotalorganiccarbon.Anunfilteredsamplewastakenmonthlyforanalysisoftotalphosphorus,Kjeldahlnitrogen,biochemicaloxygendemand,conductivityandturbidity.Anunfilteredsamplewastakenquarterlyforanalysisofacidity,chloride,andcolor.AllsampleswerestoredoniceduringtransporttothelaboratoryinGainesvilleandpreservedaccordingtoAPHA(1980).AnOrionModel 399AIonanalyzerwithaglasselectrodewasusedtomeasurepH.DissolvedoxygenwasdeterminedusingtheWinklermethod(azidemodification)for first6moandwithaYSImodel54oxygenmeterforthesubsequent6-moperiod.ColorwasmeasuredincentrifugedsamplesatpH7withaPerkinElmerModel552spectrophotometer.TurbiditywasmeasuredwithaHachAnalyticalNephelometerusingaHach10NTUcalibrationstandard.ConductivitywasmeasuredwithaYSI Model 31conductivitybridge.Totalorganiccarbon(TOC)wasanalyzedwitha BeckmanModel915TotalOrganicCarbonAnalyzer.Chemicaloxygendemand(COD)wasdeterminedusingasemi-micromethodofdichromateoxidationwithferrousammoniumsulfatetitrationusingferroinindicator.Biochemicaloxygendemand(BODs)wasdeterminedwithfullstrength,non-seeded,aeratedsamplesincubatedin125 mlBODbottlesat20Cfor5days.InitialandfinaldissolvedoxygenwasmeasuredinthesesamplesusingtheWinklermethod(azidemodification).Phenolphthalein

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52aciditywasdeterminedelectrometricallyatroomtemperatureaccordingtoAPHA(1980).Nitrate-nitritenitrogen(cadmiumreductionmethod),ammoniumnitrogen(alkalinephenolmethod),Kjeldahlnitrogen(semi-micropersulfatedigestionfollowedbyammoniumanalysis),orthophosphorus(molybdatemethod),totalphosphorus(sulfuricaciddigestionfollowedbyorthophosphorusanalysis),andchloride(ferricthiocyanatemethod),analyseswereperformedusingautomatedcolorimetricmethodsaccordingtoUSEPA(1980)andAPHA(1980).SoilsandPhosphorusAdsorptionReplicatesoilcoresweretakenwithacrylictubing(4cmi.d.)atfoursamplingstations(2,4,5and6,Figure3)representingthefourwetlandcommunitytypes.Each20-cm-longcorewasdividedinto5-cmincrements.Each5-cmincrementwasplacedinanindividualurinecupandthenstoredoniceduringtransporttothelaboratoryinGainesville.TotalorganiccarbonwasdeterminedbytheWalkey-Blackmethodandpercentcarbonwasassumedtobe58%oforganicmatter(Allison1965).AnOrionModel399AIonanalyzerwithaglasselectrodewasusedtomeasurepHindeionizedwaterwithasoil:liquidratioof1:1(v:v)(Peech1965).Totalnitrogenincludingnitratewasdeterminedbythesemi-microKjeldahlmethod(Bremner1965).Totalphosphoruswasdeterminedbytheignitionmethodand0.1NHCLextraction(Anderson1976).Thisprocedureconvertsallthephosphorustotheorthophosphateformwhichwasdeterminedcolorimetricallywiththeascorbicacidmethod(MurphyandRiley1962).

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53Phosphorusadsorptionwasmeasuredforsoilssampled at twostations(4and5) at twodepths(0-5cmand15-20cm).Duplicate1gair-driedsampleswereshakenfor24hrs at 22Cwith25mlofa O.OlM CaCl zelectrolytesolution.Onemloftoluenewasadded to eliminatemicrobialactivity.Varyingconcentrationsofphosphoruswereaddedasfollows:0,2.5,5,7.5,10,15,20,30,40,and50mg/lasCa(HZP04)z.Theaverageconcentrationofphosphorusinsecondarilytreatedwastewatereffluentiswithinthisrange.Thesampleswerethencentrifugedandthesupernatantsolutionswereanalyzedforphosphorusbytheascorbicacidmethod(MurphyandRiley1962).Theamountofphosphorusremovedbythesoilfromthesolutionwasconsideredadsorbed.Theadsorptiondataareplottedinfourways:theregularplot(x/mversusC),linearLangmuirplot(Cm/xversusC),linearFruendlichplot(logx/mversuslogC),andTempkin plot (x/mversuslogC),wherex/mandCrepresent the amountofphosphorusadsorbedby unit massofsoil andequilibriumphosphorusconcentrationinthesolution respectively.Linearregressionanalysiswasperformedonthelastthreeplottypes to obtainregressionlinesandcoefficientsofdetermination(R).Thesoilsevaluatedforphosphorusadsorptionwerealsoanalyzedforextractablephosphorus,extractableironandextractablealuminumby0.1 N HCLextraction(Mestan1986)andtheTammoxalatemethod(Saunders1965).Phosphoruswasmeasuredbytheascorbicacidmethod(MurphyandRiley1962),andironandaluminumwereanalyzedusingflameatomicabsorptionspectrophotometry(Mestan1986).TheTempkinequationhadthehighestcorrelationwhenbothsoiltypeswereconsidered together.

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54Therefore,theadsorptionmaximaobtainedbysubstitutionoftheequilibriumphosphorusconcentrationderivedfromthequadraticequationintotheTempkinequationwascorrelatedwithmeasuredsoilproperties.Thephosphorussorptionindexwascomputedfromasingle-pointuptakeadsorptionvalue(x/m)correspondingtoanequilibriumphosphorusconcentrationof10 Thissingle-pointvaluewascomputedfromtheindividualquadraticequationsforeachsoil.Thisindexwaschosenonthebasisofsimplicity,andthe10 equilibriumphosphorusconcentrationiswithintherangeofphosphorusconcentrationsfoundinsecondarilytreatedwastewater.Linearregressionanalysiswasperformedtorelatetheadsorptionmaximaandthephosphorussorptionindexwithmeasuredsoilproperties.HvdrologyThegeneralhydrologicequationfordeterminingthewaterbUdgetinawetlandisInflow Outflow (changeinstorage).ThespecificcomponentsofawetlandwaterbudgethavebeenfurtherdescribedbyCarteretal.(1979)as:P +SWI+GWI ET+SWO+GWO+ wherePisprecipitation,SWIissurfacewaterinflow(includingoverlandrunoff),GWIisgroundwaterinflow,ETisevapotranspiration,SWOissurfacewateroutflow, GWO isgroundwateroutflow(dischargethroughaquifers,seepage),and is the changeinstorage.

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55Determinationofindividualwaterbudgetcomponentsmaynotbeasimplematter(Carteretal.1979).Severalassumptionsweremadetosimplifyestimationofwaterbudgetcomponents.ThebasinstoragewasassumedtobeconstantovertheperiodoftimeforwhichthebUdgetwascalculated;therefore,thechangeinstorage (6S) wasassumedtobezero.Therearenotributariesprovidingsurfacewaterinflowtothesite.Therefore, SWI waseliminatedfromtheequation.Thewaterbudgetwasestimatedonadepthbasisratherthanonavolumebasis;therefore,wetlandareaisnottakenintoaccount,andthelinearnatureofshrubswampsinthepanhandleprecludesanysignificantwatershedinterceptionofprecipitationbeyondthatfallingdirectlyonthesystem(Whartonetal.1982).Therefore,inthissimplifiedwaterbUdgetthereisnooverlandrunofftothesite,andoverlandrunoffandgroundwaterflowareassumedtobeoutflowcomponents. GWI isthuseliminatedfromtheequation.ThesimplifiedwaterbudgetequationforthisstudysiteisP R+G+ET,whereRisrunoffandGisgroundwaterflow.Anannualwaterbudgetforthestudysitewascalculatedusingdataforthe5-yrperiodfrom1982through1986andforOctober1985throughSeptember1986whentranspirationmeasurements were made,hereafterreferredtoasthewaterbudgetyear.AllwaterdataarereportedinEnglishSystemUnits(inches)as is commoninthehydrologyfield.PrecipitationandRunoffDailyprecipitationrecordsarekeptattheApalachicolaweatherstationapproximately1kmeastofthestudysite(NOAA1982-1986).Runoff was calculatedfromdailyprecipitationusingtheSCScurve

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56numbermethodpresentedinsection4oftheNationalEngineeringHandbook (SCS1972).Chow(1973)describedthemethodthatusesthefollowingequation:Q-[(P-0.2S)2]/(p+0.8S),whereQistherunoffininches,Pisthestormprecipitationininches,andSisthepotentialinfiltrationininches,whichisdeterminedasfollows:S(1000/Cn) -10whereCnisthecurvenumberpreviouslydeterminedbytheSCS(1972)forhydrologicsoil-covercomplexesthatareacombinationofsoiltypeandcover.Thecurvenumbercanbedeterminedforantecedentmoisturecondition(AMC)classesbasedontotalantecedentprecipitation.Konyhaetal.(1982)describedfivemodificationsfordeterminingpotentialinfiltrationinaccordancewiththeSCScurvenumbermethodinordertopredictrunoffinflathighwatertablewatershedsinFlorida.Twoofthemethods(AMCIIandAMCIII)wereusedtoestimaterunofffromprecipitationatthestudysitefor1982through1986.Inadditionthesetwomethodswereutilizedtoestimaterunofffromprecipitationatthestudysiteduringthewaterbudgetyear.GroundwaterWaterlevelsinshallowgroundwaterwellsweremeasuredmonthlyfor1yrtoconstructmapsofthepotentiometricsurfaceofthestudysiteforhighandlowwaterperiods.Waterdepthatstations2,3and5(Figure3)withinthewetlandwereconcurrentlymeasured.

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57Groundwaterflowiscomposedoftwocomponentsatthestudysite,infiltrationthroughasemi-impermeableorganiclayerandsurfacesands,anddeepseepagethroughclayeysands.Theformerishighlyvariableandnodatawerecollectedtoestimatethisflow.Therefore,anestimatewas madeofthemaximumgroundwaterflowthatcouldoccurfromtheuppersurfacesandstothelowerclayeysandsusingasimplificationofDarcy'slaw:v-K wherevisthevelocityofthewaterpassingfromthesurfacesandzonetotheclayeysandzone,Kisthehydraulicconductivityoftheclayeysandzone,and isthehydraulicgradientbetweenthetwozones. isthechangeinpiezometricheadbetweenthetwozonesand isthethicknessoftheclayeysandzone.EvanotransnirationDepressionalwatershedsaredominatedbyflatslopesandlong-termseasonalprecipitationandflooding(Bedient1975).Theyaredominatedby ratherthanverticalsoilwatermovement,andthelateralmovementisdifficulttomeasureduetopoorlydefineddrainagepaths.Thetitishrubswampisinadepressionalwatershed,anditsanalysisrequiresanemphasisonsoilstoragesandevapotranspirationchangesoverlongperiodsoftimeaswellassomequantificationoflateralwatermovement.ThewaterbalancetechniqueofThornthwaiteandMather(1957)fordeterminingevapotranspirationisidealforanalyzingdepressionalwatersheds(Bedient1975).Evapotranspirationwasdeterminedwithanempiricalformularelatingclimatevariablesthatdriveevapotranspiration(Thornthwaite

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58andMather1957).TheThornthwaitemethodusesmeanmonthlyairtemperaturestodetermineanannualheatindex.MeanmonthlyairtemperaturesfortheApalachicolaweatherstationwerereportedbyNOAA(1982-1986).Unadjustedmonthlypotentialevapotranspirationisdeterminedfromthemeanmonthlyairtemperaturebasedontheannualheatindex.Adjustedmonthlypotentialevapotranspirationisdeterminedbymultiplyingtheunadjustedvaluesbythemonthlydurationofsunlight(12hrbasis)atthestation'slatitude. When precipitationwasgreaterthanpotentialevapotranspiration,actualevapotranspirationwastakentobeequaltopotentialevapotranspiration.Inmonthswhenprecipitationwaslessthanpotentialevapotranspiration,waterwaslostfromthesoil.Theactualwaterlossvarieswiththeamountofmoistureinthesoil.Thismonthlysoilwaterlosswasdeterminedasthedifferencebetweenthemaximumsoilmoisturestorageandthemonthlysoilmoistureretainedfortheaccumulatedmonthlywaterloss.The maximumsoilmoisturewasdeterminedusingthefollowingformula:maximumsoilmoisture (1000/ Cn) -10whereCnisthecurvenumberpreviouslydeterminedbytheSCS(1972)forhydrologicsoil-covercomplexesthatareacombinationofsoiltypeandcover.Themonthlysoilmoistureretainedfortheaccumulatedmonthlywaterlosswasdeterminedusingsoilmoisturedepletioncurves(Bedient1975).Themonthlysoilwaterlosswasaddedtothemonthlyprecipitationtoobtainanestimateofmonthlyactualevapotranspirationforthosemonthswhenpotentialevapotranspirationwasgreaterthanprecipitation.

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59Panevaporationcanalsobeusedtoestimatepotentialevapotranspiration.PanevaporationvaluesfromU.S.WeatherBureauClassALandPansaremeasuredatselectedNOAAweatherstations.TheclosestNOAAweatherstationmeasuringpanevaporationisinMilton,Florida,160kmnorthwestofthestudysite.PanevaporationdatafortheMiltonweatherstationwerereportedbyNOAA(1982-1986).Brown(1978)measuredsurfaceevaporationforsoilandwatersurfacesaswellastranspirationfromplantsinseveralwetlandsinFlorida.Hersurfaceevaporationvalueswereusedinthisstudytoestimatetheportionofevapotranspiredwaterlossduetosurfaceevaporation.TranspirationTranspirationatthestudysitewasdeterminedusingthegasexchangechambermethod.Infivestudieswherechamberswereusedtomeasuremetabolismandtranspiration,airflowswereselectedsoasnottolimitmetabolismorenhancetranspiration.ThevolumeandthenumberofturnoversperminuteofsixchambersofwiderangingsizeusedinthesefivestudiesaregiveninTable1.ThecomputerprogramCURFIT(Spain1982)wasusedtofitthedataonchambervolumeandturnovertime.Thebestfittingequationforthesedatawasapowerfunction(y Ax")wherey numberofturnoversperminute,andx chambervolume.Thisequationwasusedtodeterminethenumberofturnoversperminuteandthustheairflowinthechambersusedinthisstudythatwouldnotlimitmetabolismorenhancetranspiration.Threechamberswereusedinthisstudy.Thedimension,volume,turnovertime(calculatedwiththemodelequation),andtheairflowthat

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Table1.Chamber volume and numberofturnoversperminuteinfourstudieswheremetabolismandtranspirationweremeasured.Chamber Volume 1/ ofTurnoversSource(m')(perminute)0.000273.0Odumetal.19700.000430.0Brown 19780.0528.0Brown 19780.8985.0Burns19788.01.35Cowles 19754000.00.19OdumandJordan197060

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61wouldnotlimitmetabolismorenhancetranspirationaregiveninTable2.Allthreechambers'volumeswerewithintherangeofthechambervolumesused to developthemodelequation.Inthefield,airflowinthechamberwasset at thelevelcalculatednot to limitmetabolismorenhancetranspiration.Theairflowwasincreasedwhenthetemperatureinsidethechamberincreasedabovethetemperatureoutsidethechamber.Flow-throughcylindricalchamberswereconstructedwithwoodenhoopsandpolyethylene.Flowwasprovidedbyavariablespeedfanmounted at oneend.Theotherendwasleftopen.Acanopybranchwasinsertedintothechamber.Transpirationratesweredeterminedbymonitoringwatervaporchanges,witha dewpointhygrometer,intheairpassingthroughthechamber.Every attempt was made to maintainsimilarconditionsinsideandoutsidethechamber.Transpirationofsweetbayandblack titi wasmeasuredinabayswampfroma 9-mtower.Thechambersweresuspendedfromthetowerwithanadjustableboomandpulleysystem.Measurementswererecordedevery15minfrombeforetranspirationbeganinthemorning to aftertranspirationendedintheevening.Thistimeperiodrepresentedonerun.Thetemperatureinsidethechamberandtheambienttemperatureoutsidethechamberweremeasuredwithmercurythermometers.Anelectricpumppulledeitheranintakeorexhaustairsamplefromthechamberthroughthedewpointhygrometer.TheintakedewpointtemperatureandtheexhaustdewpointtemperatureweremeasuredwithaEGandGModel880dewpointhygrometer.Theflowthroughthechamberwasmeasuredwithabatteryoperated Weather MeasureModel W14lAhotwireanemometerandthesolarinputwasmeasuredwithaMatrixMark VI

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62Table2.Thedimension,volume,turnovertime(calculatedwithmodelequations)andtheairflowthatwouldnotlimitmetabolismandtranspiration,forthethreechambersusedinthisstudy.ChamberIIIIIIdiameter(m)0.580.580.58radius(m)0.29 0.290.29length(m)2.001.001.40volume (m')0.5280.2640.370 il turnovers(permin)*3.975.014.47minimumairflow(mjsec)1.751.101.38*calculatedwithmodelequationy-Ax" A326.5n--.3344

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63solarradiometer.Attheendofeachrunthebranchinsidethechamberwasharvestedandtheleafbiomasswasdetermined.Thesemeasurementswerethebasisforthefollowingcalculationsperformedwithacomputerspreadsheetprogram.TheambienttemperatureandtheintakeandexhaustdewpointtemperatureswereconvertedtosaturationvaporpressurewiththeClausius-Clapeyronrelationship,asfollows:saturationvaporpressure(mb) 6.841EXP(0.0608)xT (OC). Thesaturationvaporpressurewasconvertedtoabsolutehumiditywithamanipulatedformofthegaslaw,asfollows:absolutehumidity(g/m') saturationvaporpressurex MW x(10'erg'cm-3 mb-1 106cm' m-')/RxTKwhere MW Rmolecularweightofwater(18g/mole)gasconstant(8.31x10'erg/oKmole),andTK ambienttemperatureinOK.Relativehumiditysaturationdeficitwerecalculatedasfollows:relativehumidity ambientabsolutehumidity/intakeabsolutehumidityatsaturationx100.saturationdeficit(1(ambientsaturationvaporpressure)relativehumidity).Theflowratewascalculatedastheproductofthecross-sectionalareaofthefanductandthemeasuredflow.Theratewaterwasreleased(thetranspirationrate)was.calculatedasfollows:

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64transpirationrateingH20(hr (flowrate)(exhaustabsolutehumidityatsaturation-intakeabsolutehumidityatsaturation).Thesehourlytranspirationrateswereintegratedwithacomputerprogramusingtrapezoidalintegration(AppendixA)toobtainthetotaldailytranspirationrate.Theleafareawasdeterminedastheproductoftheleafbiomassmeasuredattheendoftherunandtheleafbiomasstoarearatiofortheverticalintervalwheretranspirationwasmeasured(9to12m).Thetranspirationrateperleafareawascalculatedasthedividendofthetranspirationrateandtheleafarea.Thetotaldailytranspirationrateperleafareawascalculatedasthedividendofthetotaldailytranspirationrateandtheleafarea.Thetranspirationrateperbiomasswascalculatedasthedividendofthetranspirationrateperleafareaandtheleafbiomasstoareafortheverticalintervalwheretranspirationwasmeasured(9to12m).Inordertoextrapolatethetranspirationmeasurementstotheecosystemlevelthetotaldailytranspirationratepergroundareawasdeterminedastheproductoftotaldailytranspirationrateperleafareaandtheleafareaindex.Inordertocalculatetheleafareaindextheverticaldistributionofleafbiomasswasdeterminedwiththeplumb-bobmethodsimilartothemethodusedbyBenedict(1975)andBrown(1978).Amarkedlinewasloweredthroughthevegetationfromthetowerwheretranspirationwasmeasured,withathreepartextensionpole.Thenumberofleaveshittingthelineandtheirspeciesandlocationalongthelinewererecorded.Thiswasperformedat16compasspointsandatthreepoleextensiondistancesforatotalof48samples.Thenumberofleavesofeachspecieshittingthelineatagivenverticalinterval(9

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65to12mor3to9m)intermsofthepercentof48sampleswasmultipliedbytheleafbiomasstoarearatioforagivenverticalintervalforthatspecies.Thepercentofthetotalleafbiomassforeachspeciesateachgivenverticalintervalwastheverticaldistributionofleafbiomassforthatspecies.Theleafareaindexforeachspecieswascalculatedastheratiooftheestimatedleafbiomasspergroundareaforthatspeciesandtheleafbiomasstoarearatioforagivenverticalintervalforthatspecies.multipliedbytheverticaldistributionofleafbiomassforthatspecies.Theestimatedleafbiomasspergroundareawasdeterminedwithdimensionanalysisoftentreesofeachspeciesappliedtotreessampledincommunityanalysisquadrats.ModelDevelopmentandSimulationAnecosystemmodelwasdevelopedtocharacterizeandquantifythemaincomponentsandprocessesofthetitishrubswampwetlandecosysteminApalachicola,Florida.ThisecosystemmodelwasdevelopedusingadiagrammaticlanguagepresentedbyOdum(1971,1972).Thisenergy-flowormaterial-flowsymboliclanguageisbasedonaseriesofmodulesthatrepresentbothsystemsprocessesandmathematicalfunctionsconnectedbylinesrepresentingtransferpathwaysofenergy,materialsorinformation(HallandDay1977).Themodularcomponentscanbeusedtoconstructcompartmentalmodelsofecosystems.Thelanguageisalsoatoolfordevelopingcomputerprogramstosimulateasystemoffirstordernonlineardifferentialequations(CostanzaandSklar1985)andwasusedtodevelopacomputerprogramtosimulatethedischargeofwastewaterto

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66thetitishrubswampinordertopredictthelong-termeffectsoftheadditionofwastewateronwetlandcomponents.Themodelwascomposedofforcingfunctionsandstoragecompartmentsorstatevariables.Theforcingfunctionsweresolarradiation,precipitationandwastewater.Thestoragecompartmentsorstatevariablesweresurfacewater,biomass,litterandsoil,andthewater,carbon,nitrogenandphosphorusinthesecompartments.Theinitialconditionofeachstatevariablewasspecifiedandtransfercoefficientsweredeterminedfromthevaluesofthestoragesandflows.Thesimulationmodelwasdevelopedtoindicatelong-term(100yrs)dynamicsofthetitishrubswampreceivingwastewater.Inordertofacilitatetheuseofthemodeloverlongperiodsoftime,alltransfersbetweencompartmentsorstatevariablesweretakenastheannualnetaccumulationineachcompartmentand,therefore,thecyclingofnutrientsandothermaterialsonaseasonalbasiswasnotaddressed.Annualandseasonalvariationsintheforcingfunctionswerealsoignored.Therewasonlyoneautotrophiccomponent(biomass),andproductionwasmodeledastheinteractionofanexternallimitingfactor(aflowlimitedsource,solarradiation)andinternallimitingfactors(nutrients).Therefore,productionwaslimitedbytherateofsupplyoftheexternalfactorandbytherecyclingofinternalfactors.ThecomputerprogramwaswritteninBASIC.Integrationintervalofthedifferentialequationswas0.1yr.

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CHAPTER3RESULTSVegetationAnalysisThetitishrubswampstudysite(Figure4)isborderedbyflatwoodsthatwereloggedandthenplantedwithslashpine.Thissilviculturalactivityincludedanattempttodrainthewetlandwithaperimeterditch.Fourwetlandcommunitytypesoccurwithinthetitishrubswampstudysite;titiswamp-titiphase,titiswamp-hollyphase,bayswamp-mixedswampphase,andblackgumswamp.FivephasesoftitiswampsweredescribedbyClewell(1971).Twophases,titiandholly,occuratthestudysite.Inthetitiphaseeitherredtitiorblacktitiisdominant.Pinesandtheoverstoryareusuallyabsent(Clewell1971).Inthetitiphaseatthestudysite,redtitiisdominant,makingup28%ofthecommunityandblacktitimake up16%ofthecommunity(Table3).Togetherthetitispeciesmake up45%ofthecommunity.Slashpinemake uplessthan3%andshrub-size-classindividualsmake up83%ofthecommunity.Inthehollyphase,Ilexmyrtifolia(myrtle-leafholly)isdominantandanoverstoryisabsent(Clewell1971).Also,insmallswampsattheheadsofminordrainageslittle-leafcyrillaandmyrtle-leafhollytendtogrowtogether(Clewell1971).Intheholly67

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Figure4.MapofthevegetationofthetitishrubswampstudysiteinApalachicola,Florida,includingsurfacewatersamplingstations.

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---St.Vincent's Sound r .2,5 '10mil.. x ;;: proposed pointof waslewat(lrdis.charUBsampling stationsnumberedTolalaraa3.88E6rn2J BQ'o"",19112 us-Route981.0'E4 m2rz:::n TitJSWampholly phose 2.28E6,.2liirii Tlli SWQIllP -IItiphase6.Z1E4m2 IiliiiiiIBlockQUm Swamp 3.63 E4 m 2BoySwC1T9 rrUxedswarJ1>j:ilo5e'"'"

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70Table3.Speciescharacteristicsofwoodyvegetation(>1.3mhigh)inatitiphaseofthetitiswampinApalachicola.Florida.Dominance il.>l!tlll ImportanceValueRelativeActualRelativeBasalRelativeBasisof100% Frequency AreaSpecies t StratumStems/he % Stratum m'/ha% Stratum t Stratum CommunityTREE SIZE CUSS Taxod1umascendens20.012.53.35.3051.1624.826.95Cyrillaracemiflora20.0250.066.72.9128.0938.264.54 elligt.tii20.012.53.30.949.0710.792.15Magnoliavirginiana20,050.013.30.686.5613.291.90 biilora20.050.013.30.535.1212.811. 75 TreeTotal100.0375.0100.010.36100.0100.017.28SHRUllSIZECLASS racemiflou16.08150.022.710.9454.a931.2023.98 l...Y.tl2.! 16.09000.025.11.075.3715.4913.90Cliftoniamonophvlla12.08400.023.44.6223.1819.5311.15Clethraalniiolia16.02150.06.00.190.957.656.63 l.l.u: carioe,a4.03100.08.60.291.457.386.51Leucothoeaxillaris4.01800.05.00.522.623,873.34 !!Y.nA biflora12.02400.06.71.758.783.472.96Rhododendron 8.0700.02.00.080.403.472.96Magnoliavirginiana4.0150.00.40.472.362.251.76ShrubTotal100.035850.0100.019.93100.0100.082.72GRANDTOTAL36225.030.29100.0

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71phaseatthestudysite,titispeciestogethermakeup35%ofthecommunity,butmyrtle-leafhollymake up20%ofthecommunity(Table4).Blacktitimake up18%ofthecommunityandlittle-leafcyrillamake up13%ofthecommunity.Threeotherspeciesmakeupatleast10%ofthecommunity.Therearenotree-size-classindividuals.Inthemixedswampphaseofbayswampsdominanceissharedbetweensweetbayandotherspecies(Clewell1971).Theunderstoryisusuallyundifferentiatedfromtheoverstoryandiscomposedofwoodyspeciescommonintitiswamps.Inthebayswampatthestudysite,sweetbaymake up35%ofthecommunityandblacktitimake up58%ofthecommunity(Table5).Shrub-size-classindividualsmake up64%ofthecommunityofwhich63%aretitispecies.Inblackgumswamps,blackgumisdominantandpondcypressisusuallypresent.Theunderstoryisabsentorcomposedofsaplingsofoverstoryspecies(Clewell1971).Intheblackgumswampatthestudysiteblackgummake up26%ofthecommunityandpondcypressmake up20%ofthecommunity(Table6).Shrub-size-classindividualsmake up62%ofthecommunity.Tree-size-classindividualsmake up16%ofthevegetationatthestudysite,butshrub-size-classindividualsarethemajorcomponent,makingup84%(Table7).Blacktitihasthehighestimportancevalueofanyspeciesatthestudysite(21%)andthetitispeciestogethermake up39%ofthevegetationatthestudysite(Table8).Thegroundcoverintitiswampsiscontinuouswiththeunderstoryandherbaceousspeciesareabsentexceptwheretheseswampsborderflatwoods.Sphagnumsp.(sphagnumorpeatmoss)mayalsobepresent(Clewell1971).Inthetitiphaseatthestudysite,noherbaceous

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Table4.72Speciescharacteristicsofwoodyvegetation(>1.3mhigh)inahollyphaseofthetitiswampinApalachicola,Florida.DominanceDensityImportanceValueRelativeActualRelativeBasalRelativeBasisof100%Frequency Axe. Species % StratumStems/ha % Stratumm'/hatStratum % Stratum CommunitySBRUB SIZECLASS .l.il.! my rtif 01ia7.694350.21.4333.5614.8719.6619.66CliftoniamODophylla15.383000.14.7853.7223.8117.9917.99Cyrillaparyiflora7.692450.12.0742.7318.9412.9012.90Magnoliavirginiana15.383650.17.9810.724.7512.7012.70 WW1.Y..lli 15.382350.11.589.924.4010.4510.45 t:ta.i.!a cerifera15.38800.3.9426.1711.6010.3110.31Hypericumreductum3.862050.10.1022.7710.098.028.02 l!.Y..uA bifIon7.69850.4.186.653.044.974.97Cyrillaracemiflora7.69450.2.225.332.364.094.09Perseaborbonia3.66350.1.7213.866.143.91 3.91ShrubTctal100.0020300.00100.00225.63110.00100.00100.00

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Table5.73Speciescharacteristicsofwoodyvegetation(>1.3mhigh)inamixedswampphaseoftheBaySwampinApalachicola.Florida.DominanceDensityImportanceValueRelativeActualRelativeBasalRelativeBasisoflOOtFrequencyAre.Species X StratumStems/ha % Stratumml/ha % Stratum % Stratum Community TREESIZECLASSClifton!amODophylla50.001025.71.3016.5267.0962.8021.49Magnoliavirginiana37,50400.27.797.3129.6931.6611.59Iaxodiumascendens12.5012.50,910.793.215.542.39TreeIotal100.001437.5100.0024,62100.00100.0035.47SHRUBSIZE ClASS Cliftoniamonophylla40.004900.63.6418.3564.0955.9136.77Magnoliavirginiana40.002650.34.419.6833.8136.07Z3.13Cyrilla[acemiflara20.00150.1.950.602.108.024.63 Shrub Total100.007700.0100.0028.63100.00100.0064.53GRANDTOTAL9137.553.Z5100.00

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Table6.74Speciescharacteristicsofwoodyvegetation(>1.3mhigh)intheb1ackgum swampinApalachicola,Florida.DominanceRensityImportanceValueRelativeActualRelativeBasalRelativeBasisof1001FrequencyAreaSpecies t StratumStems/hatStratumml/ha t Stratum t Stratum CommunityTREE SIZE ClASS Taxgdiumascendens30.77487.531.5014.3047.3436.5415.97 Hn.ll biflora30.77725.046.6010.2333.8637.1413.04Cyrillaracemiflora30.77325.021.004.9716.4532.718.00Pinuselliottii7.6912.50.800.712.353.611.44TreeTotal100.001550.0100.0030.21100.00100.0038.45SHRUBSIZE ClASS biflora14.813350.019.503.94038.21024.7012.54Lyonialucida14.814250.024.800.4164.05014.5611.25Cyrillaracemiflora14.812200.012.802.97028.84018.839.70Clethraalnifo11a14.811800.010.500.4544.4009.906.93 coriacea7.402250.013.100.2332.2607.595.87Leucothoeaxi11ari511.111850.010.800.1621.5707.835.93Iaxodiumascendens 7.40 850.05.001.61815.6909.36 4.51ll.u myrtifolia7.40350.02.000.1861.8003.73 2.44 C1iftoniamonophy11a3.70150.00.900.3213.1102.571.36Magnoliavirginiana3.70100.00.600.0050.0481.461.02ShrubTotal100.0017150.0100.0010.310100.000100.0061.55GRANDTOTAL18700.040.520100.00

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Table7.75Speciescharacteristicsofwoodyvegetation(>1.3mhigh)inthetitishrubswampinApalachicola,Florida.DominanceDensityImportance Values RelativeActualRelativeBasalRelativeBasisof 100% FrequencyAreaSpecies % StratumStems/he % Stratumml/ha % Stratum % Stratum CommunityTREE SIZECLASSIaxodiumascendens20.9512.515.220.431.322.53.8Cliftonlemonophylla18.61025.030.516.525.324.83.5 17.5775.023.010.8 16.519.02.8Magnoliavirginiana18.7450.013.47.812.3 14 .82.5Cyrillaracemiflora17.5575.017.17.812.115.62.4Pinuselliottii6.825.00.81.62.53.30.7TreeTotal100.03362.5100.065.3100.0 100.015.7SHRUBSIZE C!ASS Cliftoniamanophylla13.716450.020.477.027.1 20.317.4 Wn!.! lucida13.715600.019.411.44.012.310.7Cyrillarecemiflora13.710950.013.519.87.011.49.7Hagnoliavirginiana11.36400.07.920,47.28.87.3 lfn!!I2.W..2.t! 10.26600.08.212.54.47.66.4 1..l.!.!.myr tif0Iia4.64700.05.833.811.97.46.2 paryifIo;a2.22450.03.042.715.06.85.6 !ti..ti..!ceri fera4.6800.01.026.29.24.94.0 lliY!u alnifolia9.13950.04.90.6 0.24.83.9 coriacea5.7 5350.0 6.60.50.24.23.8Hypericumreductum1.12050.a2.522.88.04.03.3Leucothoeaxillaris4.63650.04.50.7 0.23.12.7 barbonia 1.1350.00.413.94.92.11.7Taxodiumascendens2.2850.01.11.60.61.31.0Rhododendroncanascens2.2700.a0.90.10.11.00.8Shrub Tots! 100.080850.0100.0284.0100.0 100.084.3 GRANO TOTAL84212.5349.2100.a

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Table8.76Importancevaluesforwoodyvegetationspecies(>1.3mhigh)inthetitishrubswampinApalachicola.Florida.Allspeciescombinedregardlessofsizeclass.SpeciesCliftoniamonoohyllaCyrillaracemifloraLyonialucida biflora lin myrtifoliaCyrillaparvifoliaTaxodiumascendensMyricaceriferaClethraalnifolia .ll.mI coriaceaHypericumreductumLeucothoeaxillarisPerseaborboniaRhododendronsp. .tin.I.l.. elli0ttiiTOTALImportanceValue20.912.110.79.89.16.25.64.94.03.93.63.32.71.70.80.7100.0

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77speciesarepresent,sphagnumisabundant(63%)(Table9),andshrubgroundcoverspeciesarepredominantlythesameasthoseintheunderstory(Table3).Thehollyphaseisborderedbyflatwoods(Figure4)whichaccountsforthepresenceofherbaceousspeciessuchasHypericumreductum,Xyrissp.(yellow-eyedgrass),andLachnanthestinctoria.Sphagnumisabundant(56%)andshrubgroundcoverspeciesareprimarilythesameasthevegetationgreaterthan1.3minheight(Table4).Thegroundcoverinbayswampsisalsocontinuouswiththeunderstoryorelsesparseandpatchy.Bedsofpeatmossareoftenconspicuousandsedgesmaybescattered(Clewell1971).Sphagnumisabundant(46%)inthebayswamp,yellow-eyedgrass,asedge,ispresent,andtheshrubgroundcoverspeciesareprimarilythesameasthoseintheunderstory(Table5).Groundcoverinblackgumswampsisabsent(Clewell1971).Sphagnumisveryabundantintheblackgum swamp(94%)andtheshrubgroundcoverspeciesareprimarilythesameasthoseintheunderstory(Table6).Aquaticmacrophytes,includingemergents,floatingleavedplants,andsubmergents,arenotasignificantcomponentofthetitishrubswamp.Shadingprevents growthbutUtriculariasp.(bladderwort)doesoccurinthedeepwaterareas.Althoughnotasignificantcomponent,aquaticmacrophytesdoexistinopenareasofflatwooddepressionsandalongthemarginsofdeeperswamps.SpeciesfoundintheseareasatthestudysiteincludeHypericumreductum,Lachnanthestinctoria,yellow-eyedgrass,Rhynchosporasp.,Scleriasp.,bladderwort,Eriocaulonsp.,Sarraceniasp.,andDroserasp.

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78Table9.PercentgroundcoverinthefourcommunitytypesinthetitishrubswampinApalachicola.Florida.Titiswamp -titiphaseSphagnumsp.LyonialucidaBarehummockClethraalnifolia .ll..gz corriaceaRhododendronsp.CyrillaracemifloraPjetyspjllyreifoljaLeucothoeaxjllarjsCljftonjamonophyllaBay swamp -mixedswampphaseBarehummockLyonialucidaXyrissp.Sphagnumsp.CyrjllaracemifloraClethraalnifoliaCliftoniamonophylla6322132 221 1<1<146371141 1<1Titiswamp-hollyphaseSphagnumsp.LyonialucidaHypericumreductum Xvtl.s. sp.CliftoniamonophyllaCyrillaparvifoljaMyricaceriferaLachnanthestinctoria!lexmyrtifoliaSabalpalmettoBlackgumswampSphagnumsp. hummock!lexcorrjaceaCyrillaracemifloraLyonjalucidaRhododendronsp.562015128663 3 3947 763<1

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79BiomassandNutrientStandingStockEstimatesForthethreespeciesmeasured,thebole,branchandleafbiomassmakeup69%,28%and3%ofthetotalabovegroundbiomass,respectively(Table10).Theregressionequationsusedtoestimatebranchandleafbiomassbasedonprimarybranchdiameter,andabovegroundbiomassandleafbiomassbasedonthedbhofindividualsinvegetationanalysisquadratsarepresentedinAppendixB.Abovegroundestimatesofthewoodyvegetation(greaterthan1.3mhigh)inthefourcommunitytypesarepresentedinTables11,12,13and14.HerbaceousbiomassandlitterestimatesinthefourcommunitytypesarepresentedinTable15.A summaryoftheabovegroundbiomassestimateofthefourcommunitytypesispresentedinTable16.Thehollyphaseofthetitiswamphasthesmallestabovegroundbiomassofthefourcommunitytypes.Thisisnotsurprisingasnotreesize-classindividualsarepresent.Theherbaceouscomponentmakes up24%ofthebiomassofthiscommunity,alargeportionofwhichissphagnum(Table9).Inthetitiphaseofthetitiswamp,tree-sizeclassindividualsmake up58%andshrub-size-classindividualsmake up41%ofthebiomass.Theherbaceouscomponentmakesuplessthan1.5%ofthebiomassofthiscommunity.Intheblackgum swamp,tree-size-classindividualsmakeup76%andshrub-size-classindividualsmake uponly21%ofthebiomassofthiscommunity.Theherbaceouscomponentmakesup3%ofthebiomassofthiscommunityandisalmostentirelycomposedofsphagnum(Table9).Verylittlelitterwasrecordedintheblackgumswampascomparedtotheothercommunitytypes.Thebayswamphasthelargestabovegroundbiomassofthefourcommunitytypes.Treesmake up52%andshrubsmake up48%ofthebiomassofthiscommunity.The

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Table10.Thedbh,estimatedbole,branch,leafandabovegroundbiomassfortenindividualsforblacktiti,redtiti,andsweetbaysampledatthestudysite.dbhheightbolebranchleafabove(cm) (m)(kg)(kg) (kg)groundbiomassSpecies(kg)Blacktiti18.511.490.535.46.5132.516.815.074.318.82.996.115.013.157.525.43.786.612.511.431.915.62.149.78.610.217.35.40.823.56.98.610.87.71.019.46.57.47.03.70.411.14.55.63.00.60.13.83.95.51.90.6 0.12.63.64.81.80.50.12.4Total296.0113.717.8427.7 % 69.027.04.0100.0Redtiti22.08.640.252.93.496.518.28.324.317.10.742.214.98.731.517.91.050.412.87.720.915.40.837.010.47.916.112.10.428.77.66.94.71.30.26.25.26.13.10.994.14.15.06.83.10.90.24.2 4.05.51.90.2 0.12.33.45.02.00.37.12.4Total147.8119.07.0274.0 % 54.044.02.0100.080

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Table10.Continued.dbhheightbolebranchleafabove(cm)(kg)(kg)(kg)groundbiomassSpecies(kg)Sweetbay17.611.761.516.62.880.813.912.749.03.81.154.013.512.044.65.31.251.110.510.823.23.50.727.49.112.017.40.60.218.17.48.39.10.70.310.16.89.68.91.10.410.46.29.47.20.70.38.24.47.43.40.20.13.64.16.22.90.40.13.4Total227.232.97.2267.1 % 85.012.03.0100.081Average % forthreespecies69.028.03.0

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Table11.Abovegroundbiomassestimateofwoodyvegetation(>1.3mhigh)inatitiphaseofthetitiswampinApalachicola,Florida.SpeciesSizeClassRegressionIIBiomass(cmdbh)inAppendixB(g/m')Cyrillaracemiflora 8669.2Cyrillaracemiflora10< 8470.2Cyrillaracemiflora<4 10473.01612.4Cliftoniamonophyl1a10< 7661.7Cliftoniamonophylla<4 10 645 11306.8Magnoliavirginiana 9209.4Magnoliavirginiana10< 9 103 2312.6Nyssabiflora 11191.4Nyssabiflora10< 11145.3Nyssabiflora<4 10303.7640.4Taxodiumascendens 132575.8Pinuselliottii 121223.0Leucothoeaxillaris<4 10146.9Clethraalnifolia<4 1054.2 llix coriacea<4 1086.4Lyonialucida<4 10295.7Rhododendronsp.<4 10 22 6Total8276.882

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Table12.Abovegroundbiomassestimateofwoodyvegetation(>1.3mhigh)inahollyphaseofthetitiswampinApalachicola,Florida.83SpeciesSizeClassRegression II Biomass(cmdbh)inAppendixB (g/m' )Magnoliavirginiana<410299.1Cliftoniamonophylla<410147.4Cyrillaparviflora<410146.5Cyrillaracemiflora<41017.6Ilexmyrtifolia<410113.2Myricacerifera<41072.0Lyonialucida<4 1038.8 biflora<41022.0Perseaborbonia<41037.9Hypericumreductum<410 J..Q....&. Total965.1

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Table13.Abovegroundbiomassestimateofwoodyvegetation(>1.3mhigh)ina mixedswampphaseofthebayswampinApalachicola,Florida.SpeciesSizeClassRegression 1/ Biomass (cmdbh)inAppendixB (g/m' ) Mai:noliavirziniana 92245.2 Mai:noliavirginiana 10< 92435.0 Mai:noliavirziniana <4 10 4756.8Cliftoniamonophylla 77277.7Cliftoniamonophylla10< 7 6669 013946.7Taxodiumascendens 13301.2 Cyrilla racemiflora10< 847.8Cyrillaracemiflora<4109.9 li.... Total19120.084

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Table14.Abovegroundbiomassestimateofwoodyvegetations(>1.3mhigh)intheblackgumswampinApalachicola,Florida.SpeciesSizeClassRegression 11 Biomass (cmdbh)inAppendixB(gjm')Nyssabiflora 114012.8Nyssabiflora10< 11901. 7Nyssabiflora<410244 95159.4Pinuselliottii 12791.4Taxodiumascendens 134509.4Taxodiumascendens10< 13475.3Taxodiumascendens<410 l..2...2 5057.2Cyrillaracemiflora 81171.2Cyrillaracemiflora10< 8459.8Cyrillaracemiflora<410 UQ.....l 1787.1 Ma&nolia virginiana10< 965.3 Ma&nolia vireiniana<410 lQ...i!. 75.7Cliftoniamonophylla10< 7107.8Cliftoniamonophylla<410 U 117.1Clethraalnjfolia<410124.7 myrtifolia<41044.6 coriacea<4 1092.0LyQuialucida<410132.8Leucothoeaxj11aris<4 1049,4Total13431.485

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Table15.Herbaceousbiomassandlitterestimatesofthefourcommunitytypesinthe titi shrubswampinApalachicola,Florida.Community TypeHerbaceousBiomassLitter(g/m')(g/m')Titiswamp titi phase123.7750.4 Titi swamp -hollyphase301.5511.5 Bayswamp-mixedswampphase10.7878.2Blackgumswamp459.490.7Averagefor titi shrubswamp(n-20)224 55886

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Table16.Aboveground biomassestimsteofthefourcommunitytypesinthetitishrubswsmpinApalachicola,Florida.Biomass(g/m')TreeSizeShrubSizeClassHerbaceousTotal TotalClassCommunity Type em dbh 10 $4em dbh<4 em dbh kg/m'Titiswamptitiphase 4868.81380.42027.6123.78400.58.4Titiswamp-hollyphase 0 0965.1301.51266.61.3Bayswampmixedswampphase 9824.1 9151.786.410.719072.919.1Blackgumswamp10484.7 2009.9936.8459.413890.813.9 (Xl-.J

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88herbaceouscomponentmakesuplessthan0.1%ofthebiomassofthiscommunity.Theleafbiomasstoarearatiosforblacktitiandsweetbayweregreaterforthe9to12mverticalintervalthanforthe3to9mverticalinterval(Table17).Redtitididnotoccurinthe9to12mverticalinterval.Theestimatedleafbiomasspergroundareaofthewoodyvegetationinthebayswampcommunitywas582g/m2(Table18).Thetitiswampshadthelowestleaflitterfall(283and265g/m2yr)andthebayswampthehighestleaflitterfall(584g/m2 yr)(Table19).Thevalueforthebayswampcommunityissimilartotheestimatedleafbiomasspergroundarea(582g/m2 )(Table18).Theblackgum swamphadanintermediateleaflitterfallvalue.Theaverageleaflitterfallforthetitishrubswampis359.3g/m2 yr(Table19),butthevariabilityofthesamplesishighasindicatedbycoefficientsofvariation.Fortyfivepercentoftheannualleaflitterfalloccurredinautumn(SeptemberthroughDecember),withthepeakoccurringinNovember.ThesecondhighestvaluewasinthemonthofMay.Forthethreespeciesmeasuredtheconcentrationsoftotalnitrogenandtotalphosphoruswereasfollows:leaf>branch>bole(Table20).Sweetbayhadthegreatestconcentrationofnitrogenandphosphorusofallthreespeciessampledatthestudysiteforallcomponents(Table20).Thehollyphaseofthetitiswamphadthegreatestconcentrationofnitrogenandphosphorusforherbaceous,litter

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89Table17.Theleafbiomasstoarearatioofblacktiti.redtiti.andsweetbayattwoverticalintervals(9to12meters.and3to9meters)atthestudysite.Leafbiomasstoarearatio(gbiomass/m'leafarea)numbernumberSpecies9-12metersoftrees3-9metersoftreesBlacktiti140.45126.85 Redtiti0142.510Sweetbay109.4798.43

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Table18.Estimatedleafbiomasspergroundarea(LBGA)ofthewoodyvegetation(>1.3mhigh)inthebayswampcommunity.90SpeciesSizeClass(cmdbh)Regression 1/ inAppendixBLeafBiomass(g/m')Cliftoniamonophylla 14255.9Cliftoniamonophylla10< 14178.2434.2 Ma!;noliavirziniana 1686.9 Magnoliaviriiniana 10< 16 141.9 Taxodiumascendens 174.1Gyr;llaracemiflora10< 150.8Cyrillaracemiflora<415 Q....l Total581.7

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Table19.Leaflitterfall(g/m")inthefourcommunitiesinthetitishrubswampinApalachicola,FloridafromMay1982throughApril1983. i =mean. a=atandarddeviation.c.v.=coefficientofvariation.TitiswampTitiswampBayswampBlackgumswamptitiphasehollyphasemixedswampphase--Monthx sc.v.xsc.v.x sc.v.x sC.v.1983Jan26.920.174.714.07.150.724.65.120.712.05.848.3Feb21.421.098.110.92.623.813.76.446.713.45.440.3Mar15.410.266.215.73.824.234.413.840.118.27.239.6Apr25.710.038.923.69.941.950.322.143.925.93.413.11982Hay50.615.129.830.97.423.9111.749.844.612.54.536.0Jun16.97.242.610.23.534.344.328.363.96.35.790.5Jul8.71.719.58.45.464.319.913.266.38.01.518.8Aug12.84.031.212.25.242.659.120.134.018.03.117.2Sep17.53.218.328.112.444.160.113.923.128.215.153.5Oct19.92.211.132.24.313.350.732.764.548.929.460.1Nov49.813.527.145.610.823.776.220.8 27.378.839.450.0Oec17.72.715.233.66.820.238.815.941.029.520.469.2Total283.0110.939.2265.079.229.9584.0232.139.7305.0140.946.2 IDt-'

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Table 20.Totalnitrogenandtotalphosphorusconcentrations(mg/g)ofthebole,branchandleafofblacktiti,redtitiandsweetbsysampledatthestudyaite. x= mean, s =standarddeviation,c.v. = coefficientofvariation. Bhck.tit.!Redtl t1 SM they3 .pee! averas. -----z c.v.n z c.v.n z c.v.n z C .9. n Total BUfano Boh 1.790.39 21.8 92.91 1.48 11 3.4214.7 102.71 1.1442.1 30Branch7.85 3.6248.1 309.09 5.252812.64 10.06 19.8 27 9.86 6.9970.9 85Leaf8.88 2.32 28.1 2910.32 3.40 32.926 28.576.3522.2 30 15.9210.1563.885 TotalPhosphoryl Bole 0.080.05 62.5 90.110.0763.611 0.15 0.06 40.0 100.120.06 50.0 30Branch0.200.13 65.0 300.19 D.H 73.7 28 0.730.61 83.6 270.37 0.24 64.9 65 Leaf0.300.1136.72"0.300.1240.026 1.560.42 26.9300.720.6466.9 85\Dtv

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93andleaflitterfall(Table21).Totalnitrogenandtotalphosphorusstandingstocksintheabovegroundbiomassatthestudysitewereasfollows:bayswamp>blackgumswamp>titiswamp-titiphase>titiswamp-hollyphase(Table22).Totalnitrogenandtotalphosphorusstandingstocksinlitterandleaflitterfallweregreaterinthebayswampthanintheothercommunitiesatthestudysite(Table23).WaterChemistryFernaldandPatton(1984)presentedamapofannualpHvaluesforprecipitationbasedonbiweeklyormorefrequentsamplingat24sitesfor2yrs(1978-79).ThemapindicatesthatthepHofrainfallatthestudysiteaverages4.7.Nutrientsinprecipitationvaryseasonally(HendryandBrezonik1980)asisthecaseatthisstudysite(Table24),anddependlargelyonlocalfactorssuchasagriculturalactivity,soilpH,andvegetativecover(FernaldandPatton1984).NutrientlevelsinprecipitationatthestudysitewerecomparabletolevelsfoundatsimilarruralsitesinFlorida(Brezoniketal.1983)astheaveragetotalnitrogenandtotalphosphorusofprecipitationatthestudysitewere0.94mg/land0.05mg/l,respectively(Table24).GroundwaterintheupperFloridanAquiferapproximately120ftbelowthestudysite(Schmidt1978)isveryhardintermsofbothtotalandnoncarbonatehardness(greaterthan180mg/1).Thedominantionsaresodiumandchloride.Highconcentrationsofnoncarbonatehardness,totaldissolvedsolids,sodium,chlorideandsulfateareindicativeofthepredominantlymarinedepositsinthiscoastalarea(FernaldandPatton1984).Thechemistryofshallowgroundwateringeneralreflectssurfacewatervaluesanddoesexhibitseasonalvariation(Table25).

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Table21.Totalnitrogenandtotalphosphorusconcentrations(mg/g)oftheherbsceouscomponent,littercomponentsndleaflitterfsllinthefourcommunitiesinthetitishrubswampinApalachicola,Florida. x =mean, s=standarddeviation,C.v.=coefficientofvariation. fohl.it,rol.PM_phoru,b.rbloeoalUtterhd 11 ttl.,fdlb.rl:tlo_,Uthl'hittntedlUC_ltJt.ype 0 .... 0 ... I ..... 0 .... 0 ---rlu..... UUpbl" 7.7' S.41U.S" t.to1.77 .... S.1.l.It, 11.0, D.,. 0.20 ,. .. 0.170.01 41.1 0.21 .oe 31.'tlU.... -boll,. ph .... 3.", ... "U.323.U30.3 "'.10'.31,.., 0.480.23 SO.O O.ZI0.12 U.' "0.3110.0122.2II., ....,..h.dpIl ...'.10 ..11,'.0.. I. ,.2."30.11 "7." O.tO '.1,0.3' D.Usa.'.. 0.230.01 31.1 "0.230.01 Ihck........1.13:I .ZI ., ..17...' J.1ll SO. 1177.111 .... '.1,0.23o.tl n . 11 0.210.014Z.'170.110.0'22,2 \D""

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Table22.Totalnitrogenandtotalphosphorusintheabovegroundbiomassbiomassinthefourcommunitiesinthetitishruswampin95Apalachicola,Florida. total bolebranchleafabovegroundherbaceoustotalaboveground COlDDUIlityType biomassbiomassbiomasstreebiomassbiomassstandingstock slot slotslotslot slotgN/ot sP/ot Tit! swamp 5744.1 2276.1256.68276.8123.7Uti phase 15.622.''.1 sN/ot 1.043.10.70.8 0.2 sP/ot <0.11.7 Tit.!swamp -669.8 265.4 29.9965.1301.5hollyphase1.82.60.5gN/m'3.07.90.10.1<0.1 sP/ot 0.10.3Bay swamp -13269.3525S592.719120.010.7mixedswampphase36.051.89.' gN/ml 0.197.31.61.90.4 sP/ot <0.13.9Blackgum swamp 9321.43693.6416.4 13lt31. 4459.425.336.46.6 gN/m' 3.3 71.6 1.1 1.40.3 gP/rIi 0.12.9

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Table23.96TotalnitrogenandtotalphosphorusinlitterandleaflitterfallinthefourcommunitiesinthetitishrubswampinApalachicola.Florida.LitterLeafLitt.rfallTotalstandingstockTotal standinsstockCoamunity typegN/m' gH/m! gP/mlTit!swamp titiphase4.58(2.02-8.14)0.13(0.04-0.26)1.63(0.8-2.69)0.06(0.02-0.12)Titiswamp-bollyphase5.79(2.68-10.08)0.15(0.OS-0.28) 2.41 (1.63-3.24)0.10(0.05-0.15)Bayswampmixedswampphase7.54(3.73-12.68)0.20(0.09-0.36)4.61(0.27-6.78)0.15(0.08-0.21)Blackgum swamp 0.60(0.13-1,32)0.02(0.003-0.05)2.14(1.12-3.23)0.05(0.02-0.10)

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Table24.ChemicalanalysisofprecipitationatthetitishrubswampinApalachicola,Florida.97QuarterTI
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Tabl@ 25.Ch@micalanalyaiaofahallowgroundwaterin the titiahrubawampinApalachicola,Florida. lIill....t 4 6 7 Quarter (1982)AprJul Oot AprJul O,t AprJul O,t pH'.54.54.24.44.44.14.04.24.24.13.94.1Conduct.!vltY 61.061.061.061.062.064.076.067.072.0 64.0 80.072.0 TI
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99 Thechemicalcharacterizationofsurface water atthisstudysiteincludesphysicalandchemicalproperties,nutrientconcentrations,anddemandlevels(Table26).Therearenosurface water qualitydataintheliteratureonwetlandsdominatedbytiti.Thesurface water inthistitishrub swamp canbecharacterizedashighlycoloredandacidic(meancolor306c.u.,meanpH-3.9units).Thebufferingcapacity,asassessedbyphenolphthaleinacidity,isminimal(meanacidity 39.1mgCaC03/1).The meanconductivity(66.2 is low, asarethemeanlevelsofdissolvedoxygen(2.8mg/l),BOD5(2.8mg/l),TOC(41.6mg/l),andCOD(90.8mg/l).The meansurface water nutrientconcentrationsatthestudysite were 0.99mg/lfortotalnitrogenand0.01mg/lfortotalphosphorus.Ninetypercentofthemeanconcentrationoftotalnitrogeninthesurface water isorganic(0.89mg/l).The meanconcentrationoforganicnitrogeninthesurface water isalmostanorderofmagnitudegreaterthanthemeanconcentrationofinorganicnitrogen(0.09mg/l).Ammoniuminthesurface water atthestudysiteisthegreatestinorganicnitrogenform.Themeanammoniumconcentrationinthesurfacewater(0.08mg/l)isalmostanorderofmagnitudegreaterthanthemeanconcentrationofnitrateplusnitrite(0.01mg/l)inthesurfacewater.The meanorthophosphateconcentrationinthesurface water isvery low (0.01mg/l).The meantotalnitrogenandmeantotalphosphorusconcentrationsinprecipitationrelativetosurfacewaterssuggestthatprecipitationistheprimarynutrientinputtothissystem(Figure5).Thisisconsistent with thefactthattherearenopointsourcesofsurface

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Table 26. MonthlysurfacewsterparametersinthetitishrubswampinApalachicola,Florida. SIn 1 2 3 4 5 6 7All -------nnnnnnn nmin.. ..Temperature ("'C) 19.8 1319.01321.01022.11020.51221.012 23.8 521.075 8.8 32.4pH 4.114 3.9 143.8 13 3.8 12 4.0 15 4.0144.0 63.9 88 3.0 4.7 Conductivity(umbos/em)51.2 1883.01887.51485.714 52.5 18 62.71560.7 868.2 9729.0 128.0 Turbid!ty(JTU)1.2 14 1.3 141.4 122.2122.7 141.8 130.9 81.885 0.3 7.8 Color (Pt/i)209 6 333 8 406 5 428 5 182 8 254 8 3<9 2 306 36 72 480 Acidity (mg C.CO,/1) 27.4 8 41.4 848.29 41.1 533.6728.38 1j7.9 339.1 48 21.068.9Dissolved Oxysen(mg/1) 3.113 1.4 133.611 4.0 10 2.4 123.5121.352.872<0.17.1 PercentSaturation eX)32.01315.013 41.0 1147.01025.01137.011 14 .0 4 30.169<0.191.0BOD (018/1 0.>3.2112.9112.7103.092.3112.3112.952.6 68 0.35.9COO(mel1a.)14.81396.313 115.8 10113.91156.513 75.B 13100.76 90.8 7930.3166.B roc(mg/10,> 35.55 4B.1 5 51.8445.64 25.1533.2551.91 41.634 B.963.1 NH,-Nems N/l)0.01 14 0.01 14 0.01120.02120.02 14 0.01130.0160.01B5<0.010.10Ro,-R (018 RIll0.09130.06120.08110.08110.07130.01130.1150.0676<0.010.42 TKII(018 HIll0.9270.98 6 1.0661.1260.627 0.87 71.3060.98 47 0.032.28OrgR (mg N/l)0.8061.0560.1051.0050.5150.6761.2150.89390.392.19TN (018 RIll0.9460.1071.0851.115 0.154 60.8361.3350.99 40 0.042.26TP (018 PIll0.0111<.01100.01 9 0.01 9 0.01110.01110.0360.0167<0.010.01OP (018 P/1)0.01 9 0.00310<0.01 8 <0.01 8 0.0110<0.01100.0160.01 81 <0.010.07H:P96.0 109.0 4 135.03109.0343.02 108.0 358.0394,0226.0234.0C1 (OI8/ll5.654 5.333 7.4547.854 5.15 4 5.97 4 6.018.17 24 3.3012.2 ..... 0 0

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Figure5.Meantotalnitrogen(TN)andmeantotalphosphorus(TP)concentrationsinprecipitation(P),surfacewater(S)andgroundwater(G)atthetitishrubswampstudysiteinApalachicola,Florida.SourcesofdataareTables24,25,and26.

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a.. Vl Z .... II I I I I IIN ..Q!:q..... O. '"en"!.."! ...,,,, Vl a.. Q..... 102 .. ..N

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103watersupplyingthesystem.The meantotalnitrogenandmeantotalphosphorusconcentrationsinshallowgroundwaterareslightlyhigherthaninsurfacewater.SoilsTherearetwosoiltypesatthestudysite(Table27).Thecommunitiesdominatedbyspeciesoftiti(titiswampsandbayswampatthestudysite)occuronTypicHumaqueptsoftheRutlegeSeries.TheseInceptisolsarenearlyblackorpeaty,stronglyacidic,verypoorlydrainedsandysoils(SCS1975).TheblackgumswampoccursonTerrieMedisapristsofthePamlicoSeries.TheseHistosolsareextremelyacidic,verypoorlydrainedorganicsoils(SCS1975).Bothsoilsoccurwherethewatertableisatornearthesurfaceforlongperiodsoftheyearandpondingiscommon.Aquepts(thesuborderofInceptisolsatthestudysite)andSaprists(thesuborderofHistosolsatthestudysite)havebulkdensitiesgreaterthan0.2g/cm3and0.85g/cm3 ,respectively(SCS1975).Thisisthecaseforthesesoilsatthestudysite(Table28).Histosolsthataresaturatedwithwatercontainatleast12to18%organiccarbondependingontheclaycontentofthemineralfractionandkindofmaterials(SCS1975).Thesoilsatthestudysitedominatedbyblackgummeetthiscriterion;theyhavefrom24to50%organiccarbonandarethereforeorganicsoils(Table28).Thesoilsatthestudysitedominatedbythespeciesoftitiallhavelessthan12%organiccarbonandarethereforemineralsoils.Bulkdensityincreasedwithdepth

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Table27.104ClassificationofsoilsofthetitishrubswampinApalachicola,Florida.Order Suborder GreatGroupSubgroup Family Series Coamuni tyTypeInceptiso!sAqueptsBumaqueptsTypicSandy.siliceous.RutlegeTiti swamp, Bumaquepts thermic tit!ph ... bollyphBay ,wampmixedphu. HistosolsSapristsMedisapristsTerrieSandy,siliceous,Pamlico BlackgUIDaw8IDP Medisapristsdysic.thermic

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Table28.105CharacteristicsofsoilsofthetitishrubswampinApalachicola,Florida.Depth Bulk OrganicOrganicOrganicpH TN TP Coa:rnunity emDensityCarbonCarbonMatter ... /8 ... /8 Typ. Stationsteml %.../8%Titi swamp-S0,869.797.016.73.8 2.45 90.63titiphase2 101.007.877.0 13.4 3.82.0659.00151.305.353.29.23.91.4046.14201.433.535.36.14.00.4245.13 Titi swamp-50.907.069.712.04.13.0864.19hollyphase4 101.124.039.86.94.21.6942.62 15 1.173.736.66.34.21.2038.75201.413.333.45.84.20.9537.13Bay swamp -51.024.645.57.64.51.1638.37mixedphase6 101.163.636.26.24.60.85 27.50 151.532.727.34.74.80.5016.87201.682.121.03.64.80.3614.63Blackgumswamp50.6550.0499.786.13.73.54180.005100.9936.8368.463.53.92.46182.25151.1929.0289.649.94.21.90204.00201.2424.0240.541.54.21.53224.87

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106whilepercentorganicmatterdecreasedwithdepthforallsoilsatthestudysite(Table28).ThepHalsoincreasedwithdepth(Table28).Totalnitrogeninthesoilswasgreatestatthesurfacewhereorganicmatterwasgreatestanddecreasedwithdepthasdidorganicmatter(Table28).Totalphosphoruswashighestinthesurfacelayersofthemineralsoilsatthestudysite,butincreasedwithdepthintheorganicsoils.Overall,soilsinthestudysitewerelowinnitrogenandphosphorus.PhosphorusAdsorptionTheamountofphosphorusadsorbedbythesoilvariedwithsoiltype(Figures6through9).Theregularplotsforthesitefourmineralsoilsarecurved,whichsuggestsafinitelimittoadsorption,characteristicoftheLangmuirequation.Theregularplotsfortheorganicsoilsarestraightlines,whichsuggestsadecreaseintheenergyofadsorptionwithincreasingsurfacecoverage,characteristicoftheFruendlichandTempkinequations.Thefitoftheseequationscanbeevaluatedbycomparingthecoefficientsofdeterminationoftheirregressionlines(Table29).ThesitefourmineralsoilsshowhighcorrelationwhenplottedwiththeLangmuirequationandlowercorrelationwhenplottedwithboththeFruendlichandTempkinequations.ThesitefiveorganicsoilsshowthehighestcorrelationwhenplottedwiththeFruendlichequation,highcorrelationwhenplottedwiththeTempkinequation,andnocorrelationwhenplottedwiththeLangmuirequation.TheadsorptionmaximaobtaineddirectlyfromtheslopeofthelinearLangmuirequationandtheadsorptionmaximacalculatedby

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Figure6.Phosphorusadsorptionisothermsforthemineralsoil(RutlegeSeries)atadepthof0-5em.Plots:regular,Langmuir,FruendliehandTempkin.

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1081070 :::E 10 ... X 10 0W 40 III a: 030 (/) 0<20 Q. 10020 40 100EPCeC)uglml1 R. 111105 0.1X ...:::EUQ.I 00WIII 0.4a: 00 (/) 00.20 0<0 Q. LANGMUIR020 40 10 0 :::E EPCeC)ug/mJ ... X2.2 0 R '".1185 FRUENDLICH01.8...J0..,00 1.4 0WIIIa: 100 (/)1.5 '200 0.5 1 < LOGCug/mJ Q. 10R .a910 TEMPKIN 10:::E... X 40 00W30III0 a: 0 (/) 200< Q. 100 0 0.5 1 1.5 2LOGCug/ml

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Figure7.PhosphorusadsorptionisothermsSeries)atadepthof15-20em.FruendliehandTempkin.forthemineralsoil(RutlegePlots:regular,Langmuir,

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Figure8.Phosphorusadsorptionisothermsfortheorganicsoil(PamlicoSeries)atadepthof0-5cm.Plots:regular,Langmuir,FruendlichandTempkin.

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Figure9.PhosphorusadsorptionisothermsSeries)atadepthof15-20em.FruendliehandTempkin.fortheorganicsoil(PamlieoPlots:regular,Langmuir,

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Table29.115Coefficientsofdetermination(R)betweentheadsorptionofaddedphosphorusbystudysitesoilsandtheequilibriumphosphorusconcentrations(EPC)insolutionforthelangmuirFruendlich,Tempkin,andquadraticequations.Soil45depth(cm)0-515-200-515-20Langmuir.9905 .9500 .8017.4955Fruendlich.8185 .9067 .9074.9723 Tempkin.8960 .9728.9527 .9032Quadratic.8845 .8409.9990.9895

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116substitutingtheequilibriumphosphorusconcentrationintothequadratic,Langmuir,Fruendlich,andTempkinequationsaresimilar(Table30).Theadsorptionmaximaforthesitefourmineralsoilswerelessthan230 soils.Theadsorptionmaximaforthesitefiveorganicsoilswerefrom294to2888 soil.Theadsorptionmaximaallincreasedwithdepth.Tammoxalateextractablephosphorusconcentrationswerehigherthanthe0.1NHClextractablephosphorusconcentrations(Table31)butlessthantotalphosphorusconcentrations.TheTammoxalateextractablealuminumandironconcentrationswerealsohigherthanthe0.1N HClextractablealuminumandironconcentrations(Table31).Inaddition,thedryweightofaluminumpergramofsoilismuchgreaterthanthedryweightofphosphoruspergramofsoil,andaluminumconcentrationsinthesoilincreasewithdepth(Table31).Linearregressionoftheadsorptionmaxima,phosphorussorptionindex,andthemeasuredsoilpropertiesindicatethatthehighestcorrelationobtainedforboththeadsorptionmaximaandthephosphorussorptionindexwaswithTammoxalateextractablealuminum(R .9852and.9469respectively)and0.1N HClextractablealuminum(R .9838and.9389,respectively)(Table31).TherewasalsohighcorrelationbetweentheadsorptionmaximaandthephosphorussorptionindexwithTammoxalateextractablephosphorus(R .9825and.8454,respectively),butonlytheadsorptionmaximahadhighcorrelationwithtotalphosphorus(R .9266)(Table31).Therewas lowcorrelationforboththeadsorptionmaximaandthePSIwithTammoxalateextractableiron(R .2851and.2004,respectively),0.1N HClextractableiron(R .1715

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Table30.117Phosphorusadsorptionmaximaofstudysitesoilscalculatedbysubstitutionoftheequilibriumphosphorusconcentration(EPC)derivedfromquadraticequationintodifferentequations.adsorptionmaxima SoilDepth(em)EPCQuadraticFruendlichTempkin LangmuirLangmuir' ).40-529.384.649.5 47.1 45.251.0(mineral)15-2036.3229.2174.4148.6132.3153.850-5238.81715.72887.2380.1437.2294.1(organic)15-2048.21726.11442.3722.01093.92500.0EPCatadsorptionmaximumobtainedfromquadraticequationAdsorptionmaximumobtainedfromslopeoflinearLangmuirequation

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Table31. Measuredsoilpropertiesforthestudysitesoilaandthecoefficientofdetermination(R) betweenthesepropertiesand1)theadsorptionmaximaderivedbysubstitutionintotheTempkinequation,and 2)thephosphorussorptionindex.Dept.h1TP 11:1ez P 18II1IIez P 8:1ex1.1Tmrmex 1.1 actex F. Taaraas Fe Coanunity typeSit.(em) QlUS/s Tit! swamp - 0-5 11.06'.2 14.5 3'.0 318.'"6.0H.D 103.0bolly pha..15-205.8 37.12.028.0 885.0925.0 28.0 68.5BlackgUlllswamp50-5 88.1180.0 33.5 85.0518.52252.0217.0372.015-20 41.5224.9 38.0 143.04035.'5700.046.5 138.0Adsorption maxima aubstitutioninto equation R.5197 .9268 .8130 .9825 .9838.9852.1715 .2851 Pha.pharus sorptionindex 10 (quadraticequatlon)R.0553.677'.5192 .8.,. .9389.9.89 .3146 .200' i-' i-' (Xl

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119and.3146,respectively),andpercentorganicmatter(R .5197and.0553,respectively)(Table31).HydrologyPrecipitationandRunoffTheclimateinthelocalityoftheApalachicolaweatherstationistypicalofthatexperiencedonthenorthernGulfofMexico(NOAA1982-1986).Temperaturesareusuallymildandsubtropicalinnature.Averageannualprecipitationisabout56in.,butactualmonthlyandyearlytotalsvarywidely.Thunderstormsoccurinallmonths,butabout75%occurduringthesummermonths.MonthlyprecipitationdataattheApalachicolaweatherstationforthe5-yrperiodfrom1982through1986andfortheWaterBudgetYeararepresentedinAppendixC.Theaverageannualprecipitationforthe5-yrperiodfrom1982through1986was 66in.(Table32).Thiswasalmost10in.greaterthanthepreceding74yraverageof56in.forthisweatherstation(Kennedy1982)andwassimilartoprecipitationforthewaterbudgetyear(65in.).SoilsatthestudysiteareGroup DtypesoilsintheSCS(1972)hydrologicsoilgroupclassificationsystem.Soilsinthisgrouparecharacterizedbyhighrunoffpotential,veryslowwatertransmissionratesandahighpermanentwatertable.Thecurvenumbers(Cn)forthesesoilsassumingaverage(AMCII)andwet(AMCIII)watershedconditionswere77and89.5,respectively.Monthlyestimated

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120Table32.Averageannualprecipitation(P),estimatedrunoff(R),panevaporation(PE),potentialevapotranspiration(PET),actualevapotranspiration(AET)andwaterbudgetresidual(RES)forthestudysitefrom1982through1986andforthewaterbudgetyear(WBY).Year P RPEPET AI:! R+AEIR+PETRESIRESII(in)(in) (in) (1n){in}(in) (in) (in)(in)196271.9623.6056.9140.8338.6762.2764.439.697.53198364.3816.4957.8440.0534,4250.9156.6413.477.74198456.5016,8262.1439.8432.9049.7256.666.78-0.16198568.5720.9254.9141.2739.0559.9762.198.606.38198666.8121.3557.9343.4237.3558.7064.778.112.04Average(in)65.6419.8457.9541.0836.4656.3160.949.334.72(ID)1.670.501.471.040.931.431.540.240.13(%)100.030.288.362.655.685.892.814.27.2 WBY(in) 64.7121.1658.0043.2037.1458.3064.366.410.36(%)100,032.789.666.857.490.199.59.90.5

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121runoffatthestudysiteforthe5-yrperiodfrom1982through1986andforthewaterbudgetyearusingmethodsassumingaverage(AMCII)andwet(AMCIII)watershedconditionsarepresentedinAppendixC.Assumingaverage(AMCII)watershedconditionsunderpredictlargerunoffeventsandassumingwet(AMCIII)watershedconditionsoverpredictssmallrunoffevents(Konyhaetal.1982).Theestimateofrunoffassumingwet(AMeIII)watershedconditionswasatleast45%greaterthantheestimateofrunoffassumingaverage(AMCII)watershedconditions.Theaverageofthetwomethodswasthereforeselected.Theaverageannualestimatedrunoffforthe5-yrperiodfrom1982through1986was 20in.(Table32).Thiswas30%oftheaverageannualprecipitationatthestudysiteforthisperiod.Estimatedrunoffforthewaterbudgetyearwassimilar(21in.).GroundwaterThepotentiometricsurfacesforhighandlowgroundwaterperiodsarepresentedinFigures10and11,respectively.Thedifferencebetweenpotentiometriccontoursofthewetlandis4ftforboththehighandlowperiods(16'to12'and14'to10',respectively).Duringlowwater,flowwasinthesouthwestdirection,shiftingtowardsthenorthwestduringhighwaterflow.Theaveragewaterdepthandfluctuationforallthreestationswithinthewetlandwere0.51mand0.93m,respectively(Table33).Thenaturalgammalogforawelllocated2kmnortheastofthestudysiteindicatesthatthereisazoneofsurfacesandsextendingto

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Figure10.PotentiometricsurfaceofthesurficialaquiferatthetitishrubswampstudysiteinApalachicola,Florida;July30,1982(highgroundwater).

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17o ---iTIl -------o.2' .-,'0 I Imil51.VINCENT'SSOUND ".,--/". --------------------.......-....-........ -"-/ -4o4.3N 1 u.s.16WELLNO.o16.7 ALTITUDE OF WATERLEVEL DATUN ISMEANSEALEVEL A SURFACE WATERSTATION-16__POTENTIOMETRICCONTOURFLOW LINE16o16.72.015.6 t-"Nw

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Figure11.PotentiometricsurfaceofthesurficialaquiferatthetitishrubswampstudysiteinApalachicola,Florida;May30,1982(lowgroundwater).

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.... N lJ> 212.5ALTITUDEOFwATERLEVELWELL No. I. 14.3 DATUMIS MEAN SEALEVEL SURFACE wATER STATION5 ,,'12 usROUTE98__14__POTENTIOMETRIC CONTOURFLOWLINE16 >!k I-14-I 113.71 I I / 11.4II/12/i4.7I.ST.VINCENT'S SOUND10 / o.25 .50 I.' .. mIles

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Table33.Waterdepth(m)forthreestationswiththetitishrubswampinApalachicola,Florida.Depth(m)DateStation2Station3Station5 Mar30,19820.620.430.73Apr29,19820.540.350.62May30,19820.150.030.39Jun29,19820.200.230.66Jul29,19820.950.761.53Aug29,19820.710.550.80Sep29,19820.620.380.69Oct29, 19820.600.380.31Nov28,19820.430.080.26Dec30,19820.510.320.62Jan30,19830.470.410.54Feb28,19830.550.460.67126AverageRangeFluctuation0.530.15-0.950.800.360.03-0.760.730.650.26-1.531.27Averagewaterdepthforallsites-0.51metersAveragefluctuationforallsites-0.93metersAveragehighwaterforallsites-1.08meters

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127adepthof42ftoverlyingazoneofclayeysandsextendingtoadepthof178ft(Figure12).Hydraulicconductivitiesforsimilarzonation(asemi-impermeableorganiclayerandsurfacesandsunderlainbyclayeysands)beneathcypressdomesinAlachuaCountyrangedfrom0.01to0.1ft/wkforthesemi-impermeableorganiclayer,from1to10ft/wkforthesurfacesandsandfrom0.001to0.01ft/wkfortheclayeysands(Cutright1974).Inestimatingtheupperlimitofdeepseepagethroughtheclayeysandzone,thehighendofthehydraulicconductivityrangemeasuredbyCutright(1974)forclayeysandswasused(K 0.01ft/wk).Thechangeinthepiezometrichead 6h betweenthetwozonesis178ftandthethicknessoftheclayeysandzone 6z is136ft(178-42).Therefore,themaximumvelocity(v K ofthewaterpassingfromthesurfacesandzonetotheclayeysandzoneis0.013ft/wk;atmost0.676ftor8in.passthroughtheclayeysandzoneperyear.EvapotranspirationMonthlyvaluesfortheS-yrperiodfrom1982through1986andtheWaterBudgetYearforpanevaporation,meantemperature,heatindex,un-adjustedpotentialevapotranspiration,meansunlight,adjustedpotentialevapotranspiration,accumulatedwaterloss,soilmoistureretained,soilwaterlossandactualevapotranspirationarepresentedinAppendixC.Themaximumsoilmoistureusedtocalculatethesoilwaterlossandtheactualevapotranspirationwas2.01in.Thiswasdeterminedfromanaveragecurvenumber(Cn)of83.25(AMCII Cn-77 III Cn-89.S) forthesoilsatthestudysite.Theaveragecurvenumber(Cn)wasusedbecauseannualestimatedrunoffwasdeterminedbasedontheaverageofthetworunoffestimatemethods.

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'"0 'Cc:IIIenGloIII'S 80'" 'Cc:IIIen>-Gl>120 IIIC3 160178200204060Counts/Second (natural gamma)80128100Figure12.Naturalgammalogofawelllocated2.0milesnortheastofthetitishrubswampstudysiteinApalachicola,Florida.

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129Duringmonthswhenprecipitationwasgreaterthanpotentialevapotranspiration,actualevapotranspirationwastakentobeequaltopotentialevapotranspiration.Thedifferencebetweenprecipitationandpotentialevapotranspirationisthewatersurplus.AwatersurplusoccurredfromNovemberthroughMarchexceptforDecember1984,whenverylowprecipitation(0.91in.)wasrecorded(74yraverageforDecemberforthisweatherstation 3.79in.;Kennedy1982).Thesearethecoldestmonths,andtranspirationislow. When precipitationwaslessthanpotentialevapotranspiration,waterwaslostfromthesoil.Thedifferencebetweenthepotentialevapotranspirationandactualevapotranspirationisthewaterdeficit.AwaterdeficitalwaysoccurredinMayduringthe5-yrstudyperiodandinJunefor4ofthe5yrsthatwereanalyzed.Thiswaterdeficitcoincideswiththespringburstofproductivity. water deficitsalsooccurredatvarioustimesfrom1982through1986inApril,July,August,SeptemberandOctober.Forthe5-yrperiodfrom 1982 through1986theannualaveragepotentialevapotranspirationwas41in.,or63%ofprecipitation,andtheannualaverageactualevapotranspirationwas36in.tor56%ofprecipitation(Table32).Thepotentialevapotranspirationandtheactualevapotranspiration for thewaterbudgetyearweresimilar(43in.and37in.)toannualaveragevaluesforthe5-yrperiodfrom1982through1986.AnnualaveragepanevaporationfortheMiltonweatherstationforthe5-yrperiodfrom1982through1986was58in.AnnualaveragepotentialevapotranspirationfortheApalachicolaweatherstationforthe5-yrperiodfrom1982through1986was41in.Therefore,potentialevapotranspirationwas0.71ofpanevaporation.

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130WaterBudgetThewaterbudgetforthewaterbudgetyearissimilartothewaterbudgetforthe5-yrperiodfrom1982through1986.Allvaluespresentedbelowaretheaverageforthe5-yrperiod.Precipitationwas66in.Estimatedrunoffwas20in.,or 30% ofprecipitationreachingthestudysite.Estimatedactualevapotranspirationwas36in.,or 56% ofprecipitationreachingthestudysite.Estimatedpotentialevapotranspirationwas41in.,or 63% ofprecipitationreachingthestudysite.Runoffandestimatedactualevapotranspirationtogether(56in.)accountfor86%ofprecipitationreachingthestudysite.ThedifferencebetweenthesecomponentsandprecipitationreachingthestudysiteiswaterbudgetresidualI(RES-I),whichwas10in.,or15%ofprecipitationreachingthestudysite.Runoffandestimatedpotentialevapotranspirationtogether(61in.)accountfor93%ofprecipitationreachingthestudysite.ThedifferencebetweenthesecomponentsandprecipitationreachingthestudysiteiswaterbudgetresidualII(RES-II),whichwas5in.,or7%ofprecipitationreachingthestudysite.Thisvalueistheestimateofgroundwaterflow.TranspirationTranspirationwasmeasuredon11days.Therewasstandingwaterpresentanditneverrainedwhentranspirationwasmeasured.ChamberIwasusedonOctober21,1984,andNovember2,1984.ChamberII,ashorterchamber,wasusedonApril21,1985,andwasdestroyedbyahurricaneinAugust1985.ChamberIIIwasusedfortheremainingruns,betweenOctober5,1985,andSeptember14,1986.Transpirationofblack

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131titiwasmeasuredonNovember2,1984.Transpirationofsweetbaywasmeasuredontheother10days.AspreadsheetforeachrunispresentedinAppendixD.Transpirationneverbeganbefore8:45AMandalwaysendedby6:15PM.Theshortestperiodoftranspirationwas 7hrsonDecember14,1985,andthelongestperiodswere9hrsonJune28,1986,andAugust20,1986.Ingeneral,forallruns,assolarinput,ambienttemperatureandsaturationdeficitincreased,transpirationincreased(Figures13-23).Conversely,assolarinput,ambienttemperatureandsaturationdeficitdecreased,transpirationdecreased.Aninverserelationshipexistedbetweenrelativehumidityandtranspiration.Theverticaldistributionofleafbiomassforblacktitiandsweetbayinthebayswampcommunitywaslargestintheverticalintervalfrom9to12 m(Table34).Mostoftheleafbiomasswasconcentratedinthecanopywheretranspirationwasmeasured.Dailytranspirationratesrangedfrom412to1924g HzO/day(Table35).Therewas adefiniteseasonalityintheresults;thelowestvaluesoccurredinDecemberandMarch,andthehighestvaluesoccurredinMayandJune.Theaveragedailytranspirationrateforthetensweetbayrunswas1154g HzO/day. Thedailytranspirationratefortheblacktitirunwas 1073 g HzO/day.Dailytranspirationratesperleafarearangedfrom651to3124 gHzO/mzleafarea'day(Table35).Theaveragedailytranspirationrateperleafareaforthetensweetbayrunswas1593gHzO/mzleafarea'day.Thedailytranspirationrateperleafareafortheblacktitirunwas801gHzO/mzleafareaday.DailytranspirationrateSpergroundarearangedfrom866to4155gHzO/mzgroundareaday(Table35).Theaveragedailytranspiration

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Figure13.TranspirationrunOctober21,1984(sweetbay).

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133 102184 (.) 36 0.E32 ell..... -28 c:ell]524 E 6 5E ....IU>4:::::"0OSell 3 <.l-""0c:'" 2 .!!!I o. en 80 E70 '"Iell 60 II: 50 12 J:l E10 ell 8 Cl -6 osen4 100100 IIN.... 8080E0 ....IN 0 NOl 6060 IOlell 40!os40II:osU>c:c: 2020 U>osc:os..... 0 ..... 7AMTime7PM

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Figure14.TranspirationrunNovember2,1984(blacktiti).

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13512682105070908060E :::>J:Qj c:110284 () 32 0-E28 -24c: Q):c 20E < 3 C''<:::>J:III15en 06050 40 3020 J: 40 N E ...... 300 NJ:C> 20 CD'" c:10 en c: III... Time7PM

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Figure15.TranspirationrunApril21,1985(sweetbay).

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042185137 P32 E 28c:24.c E < 20 7 6 .... 5 ::::Vl"0i6a> 4 u-'""0c:" 3 .!!!:I: 02 (/) 9080 E70 j!a; 60 c: 50 10 Qj 80 0; 6 en 4 :I:.... 20 :I:'" 40, :I:'"C> 50E 30 ....a> -40C'll c:C> C'll ;0 I-10 20 c:Vl 10 c: C'll0 7AMI-Time7PM

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Figure16.TranspirationrunOctober5,1985(sweetbay).

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139 100585 e 36 32 281 24 5 4 3 2 190 80 70 60504012 10 8c\!l 6 4120140 } 100120 80N'100 .EJI1 6080 l2 60 40 JI1 40 l2 2020 07AM TIfTl9 ?PM

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Figure17.TranspirationrunDecember14,1985(sweetbay).

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141121485 e 16 12 I 8 6 5E4 jJ 3 2 1J504030 3.2 3 82.8Jii 2.64080 N' 030 80 N N 2040 .Sl .Slr!220r!2 10 1'! 0 7N1iTme?PM

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Figure18.Transpirationrun Harch 3,1986(sweetbay).

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14303018624 () 20 L-0. E16 12 j 8 4 6 (\j 5E ....:I:'" 4 :::,-gOJ"3""OJc 2 "0(/) 40 30:I: 20 0; a:103.2 3.0 2.8 2.6OJ 2.4 (/) 2.2 3030I'? ,25 25 (\j0:: E020 ....N 200 N 15 15 (ij 10"10-a: OJ'" a: c 5 5 '"OJc.= 0f-lAMTIme?PM

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Figure19.TranspirationrunApril19,1986(sweetbay).

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G 32041986145 i.." 28 -24 I 20 6 C\J E5 3:'@::::al 4 '"...:1 I55J50 il'! 45 540J: 353087 s:40s:.... 700 C\J 60 C\J 30E .9.... 500 C\J'" 20 40 J: a: S'" 30 CI>c 10'" 20 ... I-0 10 7AMTime t=

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Figure20.Transpirationrun May 24,1986(sweetbay).

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147 (3 36052486 e.., 32 Q) le: 28 Q):l5 245 C\lE 4....J:'"...." 3 2 80 70 60 a; 50a: 40 3012 10 .0 E -8 8 -6 '"en4140 120 140 s:J: 120C\l .... 0100EC\l100 ....J: 800 Cl C\l 60 J: 060 Cl '" 60a: Q) '"4040'"ea:'"'" 2020le 0 7AMTIme7PM

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Figure21.TranspirationrunJune28,1986(sweetbay).

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149 G 38062886 e.. 0-36E '" I-34c:I 32305 ......'" E4 ,......J:'",-0 3 0 2 "0(/) 75 70 ...... 65 E60 '"J:Q; 55a:504514 ...... 12 a; 10 (/) 8 100 180 ......J:'" 80140E , 0 060 N'" 100 J:J:SCl 40 .,.so 60'" '" a: a: 1:! 20 '"c:'" 40 l-I-07AMTime7PM

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Figure22.TranspirationrunAugust20,1986(sweetbay).

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151 U 36082086 L! 343230Iii 28265 C\J E4 ::::al 3 co...10J: 2 Jj.... 90 80 .... 70 605014 12 .... 10 8c)1l 6 480 2 60 2 50 C\J 60E ........ 0400 C\J C\JJ: J:.B30.B.9l .9l 20 20 10 CO COt= a t= 7AM Time 7PM

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Figure23.TranspirationrunSeptember14,1986(sweetbay).

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091486153 0 36 L! 32 1:.9:.0 28E 24 5 C\I E4 ......:I:V>......as 3 :t 2 705014 ] 12 10 8 65060 s: 40 C\I Ea ......C\I 4030a C\I:I:Q) 20 .31ii.sc: 20 8!V>c:: 10 coto7AM7PMTIme

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Table34.Theverticaldistributionofleafbiomass(VDLE)andtheleafareaindex(LA!)forblacktitiandsweetbayinthebayswampcommunity.154LBAR'VDLBLBGA' lAI' Speciesintervalhits/ ..t g/m' ..t of 8/0101lea! areal (m) intervalsof48leafareatotalgroundarea 01 groundareaSweetbay9-12 23/48 0.48109.4 74 141.900.963-99/480.1998.426141.900.371.33Elacktiti9-12 35/48 0.73 hO.4 84434.152.603-97/480.15126.816434.160.553.15TOTAL4.48LBAR from Table17 lLBGA fromTable18, lAI. (LBGA/LBAR)x VDLB

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Table35.Dailytranspirationrate(DTR).dailytranspirationperleafarea(DTRLA)anddailytranspirationratepergroundarea(DTRGA)foreleventranspirationruns.155DTRLA'DTRGA'gH,O/m'gH,O/m'PEatDTRLAleafareagroundareaMilton.FLDateChamber gH,O/daym'-day -day (in)Oct21.1984 I 14150.971459 19400.21Nov02.1984I*10731.34801 25230.14Apr21.1985II7300.731000 13300.22Oct05,1985III17780.732436 32400.16Dec14.1985III4120.361144 15220.20Mar01.1986III5140.79651 8660.13Apr19.1986III7610.491553 20650.18May24.1986III19240.832318 30830.25Jun28,1986III15930.513124 41550.19Aug20,1986III13480.871549 20600.22Sep14,1986III10681.54694 9230.18,DTRLA DTR/LA,DTRGA-DTRLAxLAI(Table35)OTROTRLAOTRGA(meanofall(meanofall(meanofallsweetbay)sweetbay) sweetbay)-1154gH,O/day 1593 gH,O/m'leafarea-day2118 gH,O/m'groundarea-day*-C1iftoniamonophy11a-b1acktitiallotherruns Mainolia PEaverageofallruns-0.19in.-4.8rom

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156ratepergroundareaforthetensweetbayrunswas2118gH20/m2groundarea'day.Thedailytranspirationratepergroundareafortheblacktitirunwas2523gH20/m2groundarea'day.Therefore,thedailytranspirationratepergroundareaforthebayswampcommunitywas4641gH20/m2groundarea'day.Dailytranspirationratespergroundareaforaspeciesineachruncanalsobecalculatedastheproductofthedailytranspirationrateperleafareaandtheleafareaindexforthatspeciesintheverticalintervalwheretranspirationwasmeasured(9to12m)(Table34).Thisseemsappropriatebecause, as Brownetal.(1984)indicated,transpirationratesdecreasedforleaveslowerinthecanopyinthewetlandsinvestigated. When calculatedin.thismanner,theaveragedailytranspirationratepergroundareaforthetensweetbayrunswas1529gH20/m2groundarea'day,andthedailytranspirationrategroundareafortheblacktitirunwas2083gH20/m2groundarea'day.Therefore,ifthemeasuredrateofcrar.spirationoccursonlyinthecanopy,thenthedailytranspirationratepergroundareaforthebayswampcommunitywas3612gH20/m2groundarea'day.SoilsurfaceandwatersurfacewaterlossesinAustinCarycypressdomewere460and973gH20/m'ground area' day,respectively(Brown1981).Theaverageofthesetwovalues(717gH20/m2groundarea'day) was usedinthisstudyasanestimateofforestfloorevaporationinthebayswampcommunity. Model DevelopmentandSimulationThesimulationmodeloftheticishrubswampreceivingwastewaterispresentedinFigure24.Thedifferentialequationsforthesimula-

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Figure24.systemsdiagramofthesimulationmodelofthetitishrubswampinApalachicola,Florida.w=water,B=biomass,L=litter,S=soil,N=nitrogen,P=phosphorus.

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T=010aOgJr a'r...:0...;..0.,---Jr; K2TKa K 2 TK4K 2 T ----BK 5 0 1 Kg0 4Kla07 I-'en00

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159tionmodelarepresentedinTable36.Initialconditionsofthestor-agesforthesimulationmodelarepresentedinTable37.FlowratesforthesimulationmodelarepresentedinTable38.TheBASICcomputerprogramtosimulatethedischargeofwastewatertothetitishrubswampispresentedinAppendixE.Thisincludestransfercoefficientswhichweredeterminedfromstoragesandflows.Resultsofmodeldevelopmentandsimulationincludematerial(water,carbon,nitrogen,phosphorus)andenergybudgetsforthetitishrubswamp.ThecalculationsofstoragesandflowsforthesimulationmodelandforthematerialandenergybudgetsarepresentedinAppendixF.Storagesofcarbon,nitrogenandphosphorusinbiomass,leaflitterfal1,litterandsoilweredeterminedforeachcommunitytypeonanarealbasisandpresentedasasinglevalueforthetitishrubswamp.Theannualwaterbudget(Table32)wasmodifiedtoincludewastewaterflowandanupperlimitofdeepseepage(groundwaterflow).Runoffwasthencalculatedasthebalanceofthebudget.Theamountofnitrogeninsurfacewaterwasheldconstant,andtheamountofphosphorusinsurfacewaterwasheldconstantuntilmaximumphosphorusadsorptioninthesoilwasreached.Thebiomasscomponentcoulduse 5% ofthesolarradiationthatwasavailabletoit(Odum1971).Theaverageefficiencyofgrossprimaryproductivityinthecypressdomeswas0.335%(Mitsch1975b).Alowervalueof0.3%wasusedforthissystemwithlowerbiomass.Plantrespirationinthecypressdomewas 52% ofgrossprimaryproductivity (Mitsch 1975b).Lowerrespirationoccurredinnutrient-poorsystems(Brown1978).Therefore,alowervalueof 40% ofgrossprimaryproductivitywasusedforchisnutrient-poorsystem.Allofthenitrogenandphosphorusdepositedinlitterwasassumedtoremaininthe

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Table36.160DifferentialequationsforeachstatevariableusedinthesimulationmodelofthetitishrubswampinApalachicola,Florida,presentedinFigure24.dQ,/dtk,Q,Q,Q,J. -k,Q,k,Q, dQ,/dtk,k,Q,Q,Q,J.k,Q,dQ,/dt k,k,Q,Q,Q,J. k,Q,dQ./dt k,Q,k,Q. k1OQ4dQ,/dtk,Q,k"Q,dQ,/dt k,Q, k"Q.dQ,/dtk1nQ4k13Q1 dQ,/dt k"Q5 +k1.Ql1k,k,Q,Q,Q,J.-k ..Q. kl6GQa dQ,/dtk"Q. + k2oQ12 k,k,Q, Q,Q,J. k"GQ. dQIO/dt -P+ZET-G-RdQ,,/dtNP+NZk14RQII k19QIl dQ,,/dt-PP+PZk,,RQll k20Q12

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Table37.161InitialconditionsforthestoragesforthesimulationmodelofthetitishrubswampinApalachicola,Florida.SourcesforthevaluesarepresentedinAppendixF.NoteinStorageDescriptionValueAppendixFQ,Abovegroundbiomass4.4E4kcaljm'1Q,Ninbiomass45.4g Njm'1Q,Pinbiomass1.9g Pjm' 1Q.Dryweightoflitter3.1E3kcaljm'2Q,Ninlitter4.53g Njm'2Q.Pinlitter0.13g Pjm'2Q,Carboninsoil1.99E5kcaljm'3Q.Ninsoil338.7g Njm' 3Q.Pinsoil15.8g Pjm' 3 Q" Surfacewater1.08m'jm' 4 Q" Ninsurfacewater1.07g Njm' 5Q"Pinsurfacewater0.01g Pjm'6

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Table38.162FlowratesforthesimulationmodelofthetitishrubswampinApalachicola,Florida.SourcesofthevaluesaregiveninAppendixF.FlowPNPPPRDescriptionPrecipitationNinprecipitationPinprecipitationRunoffValue1.67m/yr1.57g N/m'0.08gP/m'3.98m/yryryrNoteinAppendixF7897k"RQ" k,,RQ,, Gk"GQ. NinrunoffPinrunoffGroundwaterflowNingroundwater3.30g N/m'yr0.4gP/m'yr0.21m/yro.28gN/m' .yr10 11712 k"GQ. k,Q,Q.Q,J, k,Q,Q,Q,J, k,k,Q,Q.Q,J, k.k,Q,Q,Q,J, k,Q, k.Q,k,Q,k,Q, k,Q, k"Q, Pingroundwater0.01gP/m'yrJ7.3E4kcal/m'yrGPP2.78E3kcal/m2yrNuptakebyvegetation2.86g N/m'yrPuptakebyvegetation0.12gP/m'yrPlantrespiration1.11E3kcal/m'yrLeaflitterfall1.55E3kcal/m'yrNdepositedbylitterfa112.11g N/m'yrPdepositedbylitterfa110.08gP/m'yrLitterrespiration7.75E2kcal/m'yrLitterremaininginsoil7.75E2kcal/m'yrSoilrespiration3.88E2kcal/m'yr13 1414151617 18 18 181919 20

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Table38.continued.163FlowZDescriptionLitterN rema1n1ng insoilLitterPremaininginsoilWastewaterflowValue2.11gN/m'0.08gP/m'3.56m/yrNoteinAppendixF21217NZNinwastewaterflow16.0gN/m'yr22PZPinwastewaterflowDenitrificationMovementofNinsurfacewatertosoilPhosphorusadsorption7.0gP1m'.yr2.01g N/m' yr14.3gN/m'yr6.68gP1m'yruptoa maximumof96.6g/m'inQ.23242526

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164soil,andthemovementofnitrogenfromsurfacewaterintothesoilwasassumedtobeatsteadystate.Themaximumamountofphosphorusadsorbedinthesoilwasafunctionoftheadsorptionmaximaofthetwosoiltypes(onanarealbasis)andthepercentofTAMMextractablealuminuminthesoil.Aswitchpreventedphosphorusadsorptioninthesoilwhenmaximumadsorptionwasreached.Annualbudgetsweredevelopedforwater,carbon,nitrogen,andphosphorusinthetitishrubswamppriortowastewaterdischargeandafter100yrsofwastewaterdischarge.Therelativeamountsofcarbon,nitrogen,andphosphoruswithinthecompartmentspriortowastewaterdischargewereasfollows:soil>biomass>litter(Figure25).Thetotalamountsofnitrogenandphosphorusenteringandleavingthesystemwerelow.Therelativeamountsofcarbonandphosphoruswithinthecompartmentsafter100yrsofwastewaterdischargewereasfollows:soil>biomass>litter(Figure26).Therelativeamountsofnitrogenwithinthecompartmentswereasfollows:biomass>soil>litter(Figure26).Thebiomassandlittercompartmentsincreased19-fold,andthesoilcarboncompartmentincreasedfivefold.Thebiomassandlitterphosphoruscompartmentsincreased26-fold,andthesoilphosphoruscompartmentincreasedsixfold.Thebiomassandlitternitrogencompartmentsincreased24-fold,andthesoilnitrogencompartmentincreasedtwofold.After100yrsofwastewaterdischarge 58%,36% and6%ofthestorednitrogenwasinbiomass,soilandlitter,respectively.After100yrsofwastewaterdischarge 33%,65% and 2% ofthestoredphosphoruswasinbiomass,soilandlitter,respectively.Although

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Figure25.MaterialandenergybudgetsforthetitishrubswampinApalachicola,Florida.CalculationofstoragesandflowspresentedinAppendixF.Storageofwaterm3/m2 ,flowofwaterm/yr,storageofcarbonE4kcal/m2 ,flowofcarbonE4kcal/m2-yr,storageofnitrogenandphosphorusg/m2 ,flowofnitrogenandphosphorusg/m2-yr.

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Water1.04166Phosphorus W ...::0",.O"-''--_-'''R-tO .. 0.01 )" IIIICarbon 139 NitrogenpOn1.677.3P1.57oB45.62.112.860.12RG0.42 0'0 o0.5R..S15.8'0 "cS' 0.17G0.01GE4

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Figure26.MaterialandenergybudgetsforthetitishrubswampinApalachicola,Florida,after100yearsofwastewaterdischarge.CalculationofstoragesandflowspresentedinAppendixF.Storageofwaterm3/m2 ,flowof water m/yr,storageofcarbonE4kcal/m2 ,flowofcarbonE4kcal/m2-yr,storageofnitrogenandphosphorusg/m2 ,flowofnitrogenandphosphorusg/m2-yr. z wastewater.

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1681397.3NitrogenR0.067G0.04/27.12.22 <. '0P0.08Phosphorus

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169nitrogenwasprimarilystoredinbiomass,phosphoruswasprimarilystoredinsoil.Ataphosphorusloadingof2mg/l,themodelpredictedthatphosphorusadsorptioninthesoilwillendafter11.7yrsofwastewaterdischargetothetitishrubswamp.Theplotsofbiomass,litterandsoilcarbonovertimeandthenitrogenandphosphorusinbiomassandlitterovertimearelimitingfactorhyperbolas(Figure27).Thedynamicsofnitrogenandphosphorusstorageinthesoildidnotfollowthispattern.Phosphoruswasrapidlyadsorbedinthesoiluntilmaximumadsorptionwasreached.Thentheamountofphosphorusinthesoilremainedconstant.Verylittlenitrogenwasstoredinthesoiluntilalimit to productionwasreached.Thentheamountofnitrogenenteringthesystemwasgreaterthanrequiredtomaintainthatlevelofproductionandstorageofnitrogeninthesoilincreased.

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Figure27.ResultsofthesimulationmodelofthetitishrubswampinApalachicola,Florida,after100yearsofwastewaterdischarge.Valuesareg N/m2 ,gP/m2andE4kcal/m2fornitrogen,phosphorus,andcarbon,respectively.

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171108Litter----------"I-<;'0\\/""'" 671 -;/ 5__ .-----B' Phosphorus1102---6Litter __--50 --...--. .-----./" Bioma ..... "109 /0 I100Soil.__--------83/20 L,...o/ _o--Years

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CHAPTER4 DISCUSSIONVegetationAnalysisIngeneral,thecommunitiesatthisstudysitearewhatClewell(1981)describedasacidswampsystems.Thisincludesahollyphaseofatitiswamp, atitiphaseofatitiswamp, amixedswampphaseofabayswampborderedbypondcypressandtiti,andablackgumswampborderedbypondcypressandtiti.Althoughblacktitimakesup58%ofthecommunityinthebayswamp,sweetbayisthedominantoverstoryspecies.Therefore,asClewell(1971)suggested,titiswampsseemtobesuccessionaltobayswamps.Althoughblackgumhasthelargestimportancevalueintheblackgumswampatthestudysite(26%),pondcypressmakes up asignificantportionofthecommunity(20%).Therefore,theblackgumswampmaybetransitionalinascenarioinwhichthereisinitialdominanceofpondcypressinthelowestsitesfollowedbytheestablishmentandeventualdominanceofblackgumthroughtime.Thisisconsistentwiththehighpercentcoverofsphagnum(94%)foundatthissite.Theblackgumswampisadistinctandimportantcomponentofthetitishrubswamp.Shrubclassindividualsmake up84%ofthevegetationatthestudysiteandtitispeciesmake up38%.Thus,thissitecanbedescribedasatitishrubswampeventhoughthecentralanddeepestportionsofthe172

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173sitearedominatedbytree-size-classindividualsthatarenottitispecies.BiomassandNutrientStandingStockEstimatesTheabovegroundbiomassestimateofthehollyphaseofthetitiswamp(1.3kg/m2 )ismuchlessthanvaluesreportedbyBrown(1981)andConnerandDay(1982)butthiscommunityexperiencedarecentfireandisthereforeinanearlysuccessionalstageofdevelopment.Theabovegroundbiomassestimatesofthetitiphaseofthetitiswamp(8.4kg/m2 )andtheblackgumswamp(13.9kg/m2 )areinthelowrangeofvaluescitedbyBrown(1981)andConnerandDay(1982),whilethemixedswampphaseofthebayswamp(19.1kg/m2 )isintheintermediaterange.Thetitiphaseofthetitiswampandtheblackgumswamp communitiescanbecharacterizedasstill-waterwetlandsandtheabovegroundbiomassestimatesforthesecommunitiesarelow.Fireisanimportantcomponentlimitingbiomassaccumulationinthetitiswampsbutitrarelyreachestheblackgumswamp(Clewell1971).Largetreessurviveandthebiomassisgreaterintheblackgumswampthaninthetitiswamp.Ingeneral,thebayswampcommunitymaybecharacterizedasaslow-flowingwetlandasitislocatedalongtheupperreachesofastream.Bay swampsingeneralappeartobemaintainedbyseepagefromhigherterrain,andmayreceivesomenutrientinputfromthesehigherareasthatmaybeunavailabletomoreisolatedsystems(Whartonetal.1977).Sweetbayhadthegreatestconcentrationofnutrientsinvegetationsampledatthestudysite(Table20)andthebayswamphadthegreateststandingstocksofnutrientsinabovegroundbiomassofallthe

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174communitiesatthestudysite(Table22).Thehighlevelofnutrientsinthebayswamprelativetotheothercommunitiesmayexplainwhythiscommunityhasthegreatestabovegroundbiomassatthestudysite.Inaddition,thegreatestleaflitterfallatthestudysiteisinthebayswampcommunity,(Table19),andtheestimatedleafbiomassofthewoodyvegetationinthebayswampcommunitywassimilartothevaluereportedbyBrown(1978)forafloodplainforestwithhighbiomass(Table18).Eventhoughthereissomerapidwaterflowduringcertaintimesoftheyear,whichmaycontributetogreaterproductivityandthesubsequentaccumulationofbiomassinthebavswampcommunityrelativetotheothercommunitiesatthestudysite,thebiomassisintheintermediaterangeofvaluescitedaboveforforestedwetlandsbecauseoflowoverallnutrientinputtothesystem.Nutrientinputisprimarilyfromprecipitationatthestudysite(Figure5),asisthecaseforthedwarfcypresscommunitycitedabove.Lownutrientinputaccountsfortheoveralllowbiomassinthiswetland.Theleafbiomasstoarearatiosforthethreespeciesmeasuredatthestudysiteatallverticalintervals(98.4to142.5)arelowerthanleafbiomasstoarearatiosreportedby Drown (1978)forcypressinthedwarfcypressforestandinAustinCarycypressdomeatallverticalintervals(150to403),buttheyaresimilartothevalueof135reportedbyBrown(1978)forfetterbush(anevergreenspecies)inAustinCarycypressdome. Theestimatedleafbiomasspergroundareaofthewoodyvegetationinthebayswampcommunity(582g/m2 )isgreaterthanthevaluereportedbyBrown(1978)forAustinCarycypressdome(465g/m2 ),andlessthanthevaluereportedbyBrown(1978)foraflOOdplainforest(663g/m2).

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175Asisthecaseinthetitishrubswamp,cypresstreesintheOkefenokeeSwamp(Schlesinger1978)andspeciesanalyzedincypressdomes(PostandStraub1974)hadconcentrationsofnitrogenandphosphorusasfollows:leaf>branch>bole.Totalnitrogenconcentrationsofbranch(12.64mg/g)andleaf(28.59mg/g)materialofsweetbayweresimilartovaluesforbranch(11.30mg/g)andleaf(21.0mg/g)materialofthisspeciesinacypressdome(PostandStraub(1974).Totalnitrogen(10.32mg/g)andtotalphosphorus(0.29mg/g)concentrationsintheleavesofredtitiweresimilartovaluesforcurrentgrowthofthisspeciesintheOkefenokeeSwamp(TN-12.3mg/g,TP 0.48mg/g)(Schlesinger1978).Theaverage(threespecies)totalphosphorusconcentrationsofthebole(0.11mg/g),branch(0.38mg/g)andleaf(0.72mg/g)materialweresimilartovaluesforbole(0.06mg/g),branch(0.40mg/g)andleaf(0.63mg/g)materialofblackgum(ahardwoodspecies)inAustinCarydome(Deghi1977).Theaverage(threespecies)totalphosphorusconcentrationoftheleaf(0.72mg/g)materialisintermediatebetweenvaluesforcypressleaf(0.52mg/g)materialinadwarfcypresscommunity(Brown1978)andforcypressleaf(0.84mg/g)materialinAustinCarycypressdome(StraubandPost1977).Althoughtheaverage(threespecies)totalphosphorusconcentrationofthebole(0.11mg/g)materialisgreaterthanthevaluesforcypressbole(0.034mg/g)materialinAustinCarycypressdome(StraubandPost1977)andforcypressbole(0.042mg/g)materialinadwarfcypresscommunity(Brown1978),thisvalueissimilartovaluesforcypressbole(0.09mg/g)materialintheOkefenokeeSwamp(Schlesinger1978).Theaveragetotalphosphorusconcentrationforleaf1itterfa11(0.25mg/g)atthestudysitewas

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176similartovaluesforlitterfallatAustinCarydome(0.36mg/g)(Deghi1977).ThestandingstocksoftotalphosphorusinabovegroundbiomassinFloridacypressswampsassummarizedbyBrown(1981)andintitishrubswampcommunitiesarepresentedinTable39.Thestandingstocksoftotalnitrogeninabovegroundbiomassintitishrubswampcommunitiesarealsopresented.Thestandingstockoftotalphosphorusinabovegroundbiomassofdifferentsystemswaspositivelyrelatedtothephosphorusinputtothosesystems(Brown1981).Totalphosphorusinputsincreasedinthefollowingorder:dwarfcypressforest,AustinCarycypressdome,floodplainforest.Therewasacorrespondingincreaseinthestandingstocksoftotalphosphorusintheabovegroundbiomassinthesesystems.Asimilarrelationshipmayexistatthestudysiteasthestandingstocksoftotalphosphorusandtotalnitrogenintheabovegroundbiomassincreasedalongagradientwithinthesystem(Figure4)fromthetitiswampstotheblackgum swampandultimatelytothebayswamp.Theannualaverageleaflitterfallatthistitishrubswampwas359g/m2 yrandislessthantheotherswampsystemscitedabove.Thisisprobablyduetolowoverallnutrientinputtothissystemrelativetotheotherswampsystemscitedabove.ThehighestleaflitterfallatthestudysiteoccurredinNovember,butthesecondhighestvalueoccurredinMay(Table19).Thereforethereisabimodalseasonalcycleatthestudysitewhichmaybeduetothereplacementofleavesinthespring.

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Table39.StandingstockoftotalphosphorusinFloridacypressforests(Brown1981),communitiesinApalachicola,Florida.totalnitrogeninabovegroundbiomasscommunitiesarealsopresented.177abovegroundbiomassinandintitishrubswamp ThestandingstockofintitishrubswampTP*TP*TNglm' glm' glm' Dwarfcypress0.26Titiswamp1.025.5AustinCarydome2.45Blackgumswamp2.971.6Floodplainforest4.78Bayswamp3.997.3*source:Table22

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178WaterGhemistryIngeneral,thechemicalcompositionofsurfacewatervarieswithtimetoa muchgreaterextentthandoesthatofdeepgroundwater(Fetter1980),Thisisbecausethesourceofsurfacewaterisfromoverlandrunoffandbaseflow,thechemistryofwhichvarieswithmeteorologicalandseasonalconditions.Variationsinthechemicalcompositionofshallowgroundwatermaybesimilartosurfacewater(Fetter1980),asisthecaseatthestudysitebecauseinwetlandswherethewaterlevelseldomfluctuatesbelowthegroundsurface,groundwaterandsurfacewaterarecloselyrelated(LichtlerandWalker1974).A meanconductivityof66.2 atthestudysiteindicatesthissystemhasaperchedwatertableandisnotincontactwithcarbonatecontainingparentmaterial.Thereforethereisverylittlefreecarbondioxidepresentinthesesurfacewaters.Thisissubstantiatedbya low meanacidity(39.1mgGaG03!1),whichissimilartovaluesreportedbyVerry(1975)forfiveperchedpeatlandsinMinnesota(meanacidity 48.2mgGaG03!1).Thesepeatlandsareisolatedfromgroundwaterandderivemostoftheirwaterfromion-poorrainfall(Verry1975).Lowmeanconductivityalsoindicatesthatthesurfacewaterislowindissolvedsolidsandthereforelowintheamountofinorganicandorganicmaterialinsolution(FernaldandPatton1984). While lowdissolvedoxygenindicatesahighdegreeofbiologicaldecomposition,lowdemandlevelscoupledwithlowinorganicconstituentlevelssuggestthatdecompositionislowandoutweighedbyproductivityinthissystem.Thepresenceofsphagnumandthehighlevelofproductionrelativetodecompositionatthestudysiteasindicatedbylowdemandlevels

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179coupledwithlowdissolvedoxygenlevelscontributetotheacidicnatureofthissystem.The meansurfacewaternutrientconcentrationsatthestudysite(TN-0.99mg/landTP 0.01mg/l)weresimilartobutlowerthanthemeansurfacewaternutrientconcentrationsofanunimpactedcypressdome(AustinCary)innorthcentralFlorida(TN 1.6mg/landTP 0.18mg/l,Dierberg1980)andthedwarfcypressforestintheBigCypressSwamp(TN 1.98mg/landTP-0.04mg/l,Flohrschutz1978).The meansurfacewaterpHofAustinCarycypressdome(4.5)wasslightlyhigherthanthemeansurfacewaterpHatthestudysite(3.9)butthemeanconductivityvaluesofthesurfacewatersweresimilar(60and66.2 respectively).The meansurfacewaterpHofthedwarfcypressforest(8.9)WasmuchhigherthanthemeansurfacewaterpHatthestudysite.Thesurfacewateratthestudysiteisalsosimilartosurfacewaterinpocosinwetlandsofmorenorthernclimates.Pocosinsresemblebogsofmorenorthernclimates,whichhavenutrient-poor,acidconditions(MitschandGosselink1986).Thesurfacewaterleavingpocosinsislowindissolvedsolids,loworacidicinpH,andhighlycoloredbyorganiccompounds(Daniel1981).OrganicnitrogenisthedominantnitrogenspeciesatpracticallyallsurfacewaterstationsthroughoutFlorida(SlackandGoolsby1976),asisthecaseatthestudysite.The meanconcentrationoforganicnitrogeninthesurfacewaterisalmostanorderofmagnitudegreaterthanthemeanconcentrationofinorganicnitrogen(0.09mg/l)inthesurfacewater.SimilarresultswerefoundatAustinCarycypressdome(Dierberg1980).Abundanceofammoniumalongwithlowdissolvedoxygenlevelsindicatesthereducednatureofthissystem.

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180A mapofthegeneralizeddistributionandconcentrationofortho-phosphateinFloridastreamsindicatesthatintheregionincludingthestudysitethemaximumorthophosphateconcentrationislessthan0.2mg/1(Kaufman1975a).Resultsfromthestudysiteareconsistentwiththisfinding(meanorthophosphate<0.01mg/1).Amapofthegeneralizeddistributionofdissolvedphosphorus(totalphosphorus)inFloridawatersindicatesthatintheregionincludingthestudysitethemaximumdissolvedphosphorusconcentrationisapproximately0.05mg/1 (Odum1953).Resultsfromthestudysiteareconsistentwiththisfindingasthemeantotalphosphorusconcentrationinthesurfacewateris0.01mg/l.Thelowmeantotalphosphorusconcentrationandthehighmeannitrogentophosphorusratio(94:1)isindicativeofphosphorus-limited,unenrichednaturalwaters.Anevaluationoftherelativeconcentrationofnutrientsinprecipitation,surfacewaterandgroundwaterprovidesinsightintotheirfluxthroughthesystem.The meantotalnitrogenandmeantotalphosphoruslevelsinprecipitationrelativetosurfacewaterssuggestthatprecipitationistheprimarynutrientinputtothissystem.SimilarresultswerefoundinAustinCarycypressdome(Dierberg1980).NitrateplusnitritenitrogenandtotalphosphoruslevelswerelowerinthesurfacewaterofAustinCarycypressdomethaninprecipitation(asisthecaseatthestudysite).PrecipitationisamajorcontributorofnitrogentoThoreau'sBoginMassachusetts(Hemond1983).Thefactthatsurfacewaterhadlowertotalphosphorusthanprecipitation(andthephosphoruscyclehadnogaseousphase)suggestedtoDierberg(1980)thatthesystemactedasabiologicaland/orchemicalsinkforphosphorus.Thisisthecaseatthestudysiteasthemeantotalnitrogenandmean

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181totalphosphorusconcentrationsinshallowgroundwaterareslightlyhigherthaninsurfacewater.Surfacewateratthestudysitehasalowermeantotalphosphorusconcentrationthaninprecipitation.Thus,phosphorusisimportantinbiologicalandchemicalprocesseswithinthesystem,andthesystemisactingasasinkforphosphorus.Thedominanceofammoniacalnitrogenandthelowlevelofphosphorusdissolvedinsurfacewatersindicatethatnutrientsareconservedwithinthissystem.Thechemicalcompositionofsurfacewatersisinfluencedbymanyfactors,includingchemicalcompositionofprecipitationandthereactionofwaterwithsoils,bedmaterials,decomposingorganicmatterandsurficialrocks(Kaufman1972).Floridastreamscanbedelineatedintermsofthedominantcationsandanions(Kaufman1972).Watercontainingnopredominantcation(calcium,magnesium,sodium)orinorganicanion(bicarbonate,chloride,sulfate)isconsideredtobeamixedtype.Themajoranionsinacidicwetlandsareorganicacids(Thurman1985).Surfacewatersintheareawherethestudysiteislocatedareofthemixedtype(Kaufman1972).Waterofthistypeisassociatedwithnoncarbonateterranesandreflectsthechemicalcharacteristicsofprecipitation,soils,anddecomposedorganicmatterinnaturalswamplandareas(Kaufman1972).Thisisconsistentwithfindingsfromothersystemssuchasbogsorpocosins.Inthesesystemsthewetlandisisolatedfromdeepgroundwatersothatnutrientconcentrationsofthesurfacewateranditsacidityreflectprimarilyinputfromprecipitationanddecomposition(MooreandBellamy1974;Richardson1981).

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182SoilsinTitiShrubSwampsPrecisedescriptionsofthesoilsaregenerallylackingforacidswampsoftheCoastalPlain(Coultasetal.1979).SoilsinlowelevationtitiswampsintheApalachicolaNationalForestwereintheHumaqueptsgreatgroup,soilsinhighelevationsintheApalachicolaNationalForestwereintheHaplaquodgreatgroup(Coultas1977).ThegeneralmorphologicalcharacteristicsofthesesoilsweredescribedbyCoultas(1977).Theyhadsandyandloamysandytexturethroughoutthesolum(surfacelayerinwhichtopsoilforms)becausetheyweredevelopedinsandsofmarineoriginofthePleistoceneSeries.Sphagnumoccurredabovemostofthesoilsintheseswampsandathinorganiclayeroccurredatthesurfaceofmostofthesoilsintheseswamps.Inthelowestareastheorganichorizonwasthickerandtextureswerefinerwithsandyclayloamscommon.StructuraldevelopmentwasessentiallyabsentinthesesoilsexceptforthepresenceofaweakgranularstructureintheAlhorizon.MineralsoilswerefoundundercypressbutnotblackgumincypressandgumswampsintheApalachicolaNationalForest,andorganicsoilsrarelyoccurredundertiti(Coultas1978).Thisisthecaseatthestudysite,assoilsatthestudysitedominatedbyblackgumhadfrom24%to50%organiccarbon.OrganicsoilsinblackgumswampsintheApalachicolaNationalForesthadfrom44%to53%organiccarbon(Coultas1978).Soilsatthestudysitedominatedbythespeciesoftitiallhadlessthan12%organiccarbon.The HumaqueptmineralsoilsdominatedbyspeciesoftitiintheApalachicolaNationalForesthadfrom10%to13%organiccarbon.Organicmaterialsaredepositedonthesoilsurface,andpoordrainageandslowerdecompositionresultinhigherthannormalorganic

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183mattercontent,particularlyatthesurface.Bulkdensity(weightpergivenvolume)islowfororganicmaterials.Itincreasedwithdepthandpercentorganicmatterdecreasedwithdepthforallsoilsatthestudysite.Thesesoilstendtobemoreacidatthesoilsurface(Coultas1978;Coultaseta1.1979).TitiandbayforestpeatshadsimilarpHvalues(Davis1946)asthoseatthestudysite.Soilsoftitiswampsandgumpondswereverylowinextractablebases(Ca,Mg, K,Na)andrelativelyhighintermsoftheircationexchangecapacity(CEC),whichwashighestinorganichorizonsanddecreasedwithdepth(titiswamps93.7-114.7meq/100g,b1ackgumswamps73.8-165.7meq/100g)(Coultas1977,1978).Over90%oftotalnitrogeninsoilisintheorganicfraction(KadlecandTilton1979).Asimilarrelationshipexistsinthesoilsatthestudysiteastotalnitrogenisgreatestatthesurfacewhereorganicmatterisgreatestanddecreaseswithdepthasdoesorganicmatter.Organicnitrogencomplexeswithlignin,po1ypheno1sandbasicacidsatapHbelow6(OvercashandPal1979).TotalphosphorusinthesoilsofthetitiswampsintheApalachicolaNationalForestinvestigatedwashighestinthesurfacelayers(Coultas1977).Thisisthecaseforthemineralsoilsatthestudysite,whicharedominatedbyspeciesoftiti.SoilsofthetitiswampsintheApalachicolaNationalForestwereextremelylowinplantnutrientsaswasthecaseforthestudysitesoils(Coultas1977).Totalnitrogenconcentrationsrangedfrom0.2to12.5mg/gforaHumaqueptdominatedbyspeciesoftitiintheApalachicolaNationalForest.ThetotalnitrogenconcentrationsoftheHumaqueptsatthestudysiteareinthelowendofthisrange(0.36to

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1843.08mg/g).Totalnitrogenconcentrationswereinarangefrom1.1to20.5mg/gforaMedisapristdominatedbyblackgum(Coultas1978).ThetotalnitrogenconcentrationsoftheMedisapristsatthestudysiteareinthelowendofthisrange(1.53to3.54mg/g).Totalphosphorusconcentrationswereinarangefrom26to232 foraHumaqueptmineralsoildominatedbyspeciesoftitiintheApalachicolaNationalForest(Coultas1977).Totalphosphorusconcentrationswereinarangefrom1to230 for30FloridasandysoilsincludingaHumaquept(YuanandLucas1982).Thetotalphosphorusconcentrationsofthesoilsatthestudysitewerewithinthisrange(14to225 PhosphorusAdsorptionTheadsorptionmaximaareusefulindescribingthesoilphosphorusretentioncapacityalthoughathigherphosphorusconcentrationsthesevaluesmaybeexceededbytheactualadsorption(YuanandLucas1982).Thisparameterisindicativeofthephosphorusretentionpotentialbutmayoverestimatetheactualfieldadsorptionmaximumbecausechannelizedwatermovementwillreducecontactwithalargeportionofthesoilmatrix(Richardson1985).Theadsorptionmaximaforthesitefourmineralsoilsaregenerallylow(lessthan230 soil)suggestingalimitedcapacityforphosphorusadsorption.Thesitefiveorganicsoilshavehigheradsorptionmaxima(294-2888 soil)suggestingagreatercapacityforphosphorusadsorption.YuanandLucas(1982)reportedadsorptionmaximacalculatedinthesamemannerfrom82to1148 for30FloridasandymineralsoilsincludingaHumaquept.Krottjeetal.(1982)reportedadsorptionmaximainarangefrom62to775 forfourFloridasoils

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185withlessthan19%organicmatter.Theyalsoreportedanadsorptionmaximumof2000 foraFloridasoilwith67.2%organicmatter.TheadsorptionmaximaofthesefivesoilswerecalculatedastheslopeoftheLangmuirequation.Phosphorusadsorptionwashighlycorrelatedwithorganicmatterandexchangeablealuminumcontent(Krottjeetal.1982).The0.1N HClextractablephosphorusmaybeconsideredsurfaceactivephosphorusorthelabilesoilphosphorus(BacheandWilliams1971).TheTarnrnoxalateextractisastrongerreagent,disturbingmorethanjustthesurfaceactive(labile)phosphorus.ThereforeTarnrnoxalateextractablephosphorusconcentrationswerehigherthanthe0.1N HClextractablephosphorusconcentrationsbutlessthanthetotalphosphorusconcentrationswhichincludemoretightlyboundformsof phos phorus.Theadsorptionmaximaandaphosphorussorptionindexwerecorrelatedwithmeasuredsoilpropertiesinordertoindicatewhichsoilfactorsarebestrelatedtophosphorusadsorptioninthesoil.Therelativelylowphosphorusadsorptioncapacityofthesitefourmineralsoilsandthemuchhigherphosphorusadsorptioncapacityofthesitefiveorganicsoilsarerelatedtothecontentandavailabilityofaluminuminthesesoilsratherthantheamountoforganicmatterpresent.Thedryweightofaluminumpergramofsoilismuchgreaterthanthedryweightofphosphoruspergramofsoil,andaluminumconcentrationsinthesoilaswellasthephosphorusadsorptionmaximaincreasedwithdepth.Thehighcorrelationofextractablealuminumwithboththeadsorptionmaximaandthephosphorussorptionindexaswellastheincreaseintheadsorptionmaximaandaluminumconcentrationswithdepthindicatetheimportanceofaluminuminphosphorusadsorptionin

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186thestudysitesoils.ThehighcorrelationoftheadsorptionmaximaandthephosphorussorptionindexwithTammoxalateextractablealuminumindicatesthatphosphorusadsorptionisrelatedtotheamorphousandpoorlycrystallineoxidesofaluminum.Pre-treatmenttoremovephosphorusfromwastewaterenteringflowthroughwetlandsinparticularwillbenecessaryunlesssite-specificinformationisavailabletoindicateacapacityforitsretentioninthesystem.Thephosphorusadsorptionmaximaforsoilsatthistitishrubswampindicatequantitativelythepotentialforphosphorusretentioninthesoil.Thesitefiveorganicsoilshaveahighcapacityforphosphorusadsorption.Thecapacityforphosphorusadsorptionismuchlowerinthesitefourmineralsoils.ThefindingbyFoxandKamprath(1970)thatsoilsthathavelowcapacitytoadsorbphosphorusrequireveryhighconcentrationsofphosphorusinsolutiontocompensateforalackoftotalavailablephosphorussuggeststhat,althoughasoilmayhavealowphosphorusadsorptioncapacity,itmayindirectlycontributetoanetuptakeofphosphorusinthesystemthroughplantimmobilization.Therefore,whetherthroughadsorptionorimmobilizationthisstudysiteappearstohavepotentialforphosphorustreatmentofaddedwastewater.HydrologyHydrologyistheprimarydeterminantofwetlandecosystemsandthemostimportantfactorinfluencingwetlandbiogeochemistry(GosselinkandTurner1978).Despitetherecognizedimportanceofthehydrologicregimetothestructureandfunctionofwetlands,itisoftenthecomponentofwetlandecosystemresearchwhichisleastthoroughlyinvestigated(LaBaugh1986).Inordertoassessimpactstoawetland

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187properly,awaterbudgetmustbeprepared.Onlywhenthewaterbudgetiscombinedwithmeasurementsofnutrientconcentrationscananinter-pretationofwetlandtreatmentsystemperformancebemade (HammerandKadlec1983).Awaterbudgetforthewetlandstudysitewasdeterminedforuseinthesimulationmodelofthetitishrubswampreceivingwastewater.RunoffEstimatesofrunoffusing5-dayantecedentprecipitationtodetermineantecedentmoistureclass(AMC)arenotrecommendedforuseinFlorida(Konyhaetal.1982).Themethodpredictserratically,sometimespredictingwithreasonableaccuracyandsometimesunderpredictingrunoffbymorethan3in.Themethodthatassumesaverage(AMCII)watershedconditionsalsounderpredictslargerunoffevents. When wet(AMCIII)watershedconditionsareassumedthepredictionsareacceptableforlargerunoffevents,butmostsmallrunoffeventsareoverpredicted.Itmayhavebeenbesttoassumeaverage(AMCII)watershedconditionsforsmallrunoffeventsandwet(AMCIII)watershedconditionsforlargerunoffevents,butthiswouldhaverequiredselectingacutoffpointforrunoffeventsintermsofprecipitation,forwhichthereisnobasis.EvapotranspirationMethodstoestimateactualevapotranspirationincorporatefactorsthatreflectdifferentlevelsofwateravailability.IntheThornthwaitemethod,ifmonthlyprecipitationislessthanpotentialevapotranspirationthenwaterislostfromthesoil,andactualevapotranspirationislessthanpotentialevapotranspiration.TheThornthwaite

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188methoddoesnotcorrectforchangesinrelativehumidity,cloudcoverandothersolarradiationeffects,windorcovertype.Therefore,resultsfromthismethodcanonlybeinterpretedasaveragevalues,particularlyforestimatesofactualevapotranspirationwhenwateravailabilityishigh.Predictionformulaearegeneralequationsthatdonotcompensateforvariationintranspirationamongspecies(Scheffe1978).AveragepotentialevapotranspirationandactualevapotranspirationwerecalculatedbyDohrenwend(1977)usingtheHoldridgemethodfor21weatherstationsinFloridafora5-yrperiod.Theprecipitation,potentialevapotranspiration,potentialevapotranspirationtoprecipitationratio,actualevapotranspirationandtheactualevapotranspirationtopotentialevapotranspirationratioreportedbyDohrenwend(1977)forweatherstationsinMiltonandTallahassee,Florida,arepresentedinTable40.ThesearethecloseststationstotheApalachicolaweatherstationforwhichdataarereported.TheaverageannualprecipitationattheApalachicolaweatherstation,forthe5-yrperiodanalyzed,wasgreaterthantheaverageannualprecipitationreportedbyDohrenwend(1977)fortheothertwostations.Therefore,thepotentialevapotranspirationandtheactualevapotranspirationvalueswerealsogreater.AlthoughthesevaluesweregreaterattheApalachicolaweatherstation,boththepotentialevapotranspirationtoprecipitationandactualevapotranspirationtopotentialevapotranspirationratiosfortheApalachicolaweatherstationweresimilartotheratiosreportedbyDohrenwend(1977)fortheothertwostations.Therefore,theestimateoftheseparametersinthisstudyareconsistentwithwhatmaybeconsideredaveragevaluesforthisregionofthestate.

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Table40.Precipitation(P),potentialevapotranspiration(PET),PET/Pratio,actualevapotranspiration(AET)andAET/PETratioforMiltonandTallahasse,FloridareportedbyDohrenwerd(1977)andforApalachicolacalculatedinthisstudy.189P(in)PET(in)PET/PratioAETAET/PET (X) Milton59.0939.210.6632.5683Tallahassee56.8539.680.6832.9583Apalachicola65.6441.080.6336.4889(1982-1986)Apalachicola64.7143.200.6737.1486(WBY)

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190WaterBudgetInfiltrationinthiswetlandislowduetothesemi-impermeableorganichumatelayer.Waterisheldabovethislayerandleavesthewetlandpredominantlythroughrunoffandevapotranspiration,whichaccountfor86to93%ofprecipitationreachingthestudysitedependingonwhetheractualorpotentialevapotranspirationisusedinthecalculation.Theannualupperlimitofdeepseepagegroundwateroutflowfromthestudysitewascalculatedtobe8in.ThiswaslessthanwaterbUdgetresidualI(RESI 10in.).Thedifferencecouldbeduetoeitheranincreaseinstoragewithinthestudysiteoranunderestimateofevapotranspiration.Someincreaseinstoragewithinthestudysitemightbeexpectedbecausetheannualaverageprecipitationforthe5-yrperiodanalyzedwasalmost10in.greaterthanthe74yraveragefortheApalachicolaweatherstation.ThewaterbudgetresidualII(RESII-5in.)waslessthantheupperlimitofdeepseepagegroundwateroutflow.Therefore,ifevapotranspirationisgreaterthanestimatedactualevapotranspirationinthesimplifiedwaterbudgetandapproachestheestimatedpotentialevapotranspirationvalue,thenthewaterbudgetresidualcanbeaccountedforthroughdeepseepagegroundwaterflow.Avaluefordeepseepagegroundwaterflowlessthantheestimatedupperlimitisconsistentwithlowinfiltrationinthesystem.TranspirationandTotalWaterLossThedailytranspirationrateperleafareaforblacktitiinthebayswamp wassimilartovaluesforhardwoodspeciesinthefloodplainforest(Table41).Theaveragedailytranspirationrateperleafareaforsweetbayinthebayswampwaslowerthanvaluesforcypressinthe

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191Table41.Leafareaindex(LAI),dailytranspirationrateperleafarea(DTRLA)dailytranspirationratepergroundarea(DTRGA),forestfloorwaterloss(FFWL)andtotalwaterloss(TWL)forthedwarfcypressforest,AustinCarycypressdomeandfloodplainforestreportedbyBrown(1981)andforthebayswampcommunityatthestudysite.DwarfcypressAustinCaryBayFloodplainCommunityforestCypressDomeswampforestLAI0.53.44.68.5Transpiration Vet:etation DTRLAcypress1840 2125 544 gH,O/m' hardwood 527 868leafarea/dayblacktiti801sweetbay1593DTRGAcypress932 1679 2106 gH,O/m'hardwood1394 3099groundarea/dayblacktiti2083sweetbay1529TOTAL932 30733612 5205EvaporationFFWLgH,O/m' 333 717 717 363groundarea/dayTotalWater Loss(TWL)gH,O/m'groundarea/day1265 3790 4329 5568mm/d1.273.794.335.57PanRatio(PR) TWL/panevaporation0.19 0.660.900.95

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192dwarfcypressforestandinAustinCarycypressdome.Thisindicatesrelativelylowlevelsoftranspirationperleafareaforthesespecies.DailytranspirationratespergroundareaforthebayswampweregreaterthanvaluesforthedwarfcypressforestandAustinCarycypressdome. TheincreasefromthespeciesleveltothecommunitylevelisreflectedingreaterleafareaindexvaluesinthebayswampascomparedtothedwarfcypressforestandAustinCarycypressdome.TotalwaterlossforthebayswampisgreaterthanforthedwarfcypressforestandAustinCarycypressdomebutlessthanforthefloodplainforest.Theestimatedleafbiomassofthewoodyvegetationinthebayswamp communitywheretranspirationwasmeasured(Table18)wassimilartothevaluereportedbyBrown(1978)forthefloodplainforest.Therefore,thiscommunitymaybestructurallysimilartoafloodplainforestandmaytranspireatahighratewhenwaterisreadilyavailable. When transpirationdataarecollectedunderdifferentconditionsofhumidity,windandsunlight(aswasthecaseinthisstudy),thepanratioisausefulindextocompareevapotranspirationbetweensites(Brown1981).Thepanratioistheratiooftotalwaterlosstopanevaporation. averagepanevaporationforthe11dayswhentranspirationwasmeasuredwas0.19 in. (4.8mm).Openwaterevaporationistypically0.7to0.8ofpanevaporation(Veihmeyer1973).ThepanratiosofthedwarfcypressforestandAustinCarycypressdomewerelowerthanthepanratioofopenwater,suggestingthattheseswampsmayconservewater.Thepanratioofthebayswampandthefloodplainforestwerehigherthanthepanratioofopenwater.Potentialevapotranspirationwas71%ofpanevaporationsuggestingthat,onaverage,evapotranspirationwassimilartoopenwater

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193evaporation.Butincommunitieswherethepanratioexceedsthepanratioofopenwater,totalwaterlossmaybegreaterthantheaveragecalculatedforallthecommunitieswithinthesystem.Consideringthatestimatesofpotentialevapotranspirationmayunderestimateevapotranspirationforcertainsystemswhenwateravailabilityishigh,andthattranspirationmayexceedopenwaterevaporation,asareindicatedabove,itisnotsurprisingthatthetotalwaterlossfromcertainwetlandcommunitiesisgreaterthantheaveragecalculatedforallthecommunitieswithinthesystem.Therelativeabovegroundbiomass(Table16)andestimatedleafbiomass(Table22)forthetitiandblackgum swampsatthestudysitewerelowerthanforthebayswamp.Thereforelesstotalwaterlossisexpectedfromthesecommunitiesbutthiscanonlybesubstantiatedwithfieldmeasurements.TherangeofdailyevapotranspirationratesinthreecypressswampsstudiedbyEwel(1985)wasfrom0.2mm/day(inJanuary)to5.9mm/day(inSeptember),ThesedailymaximumevapotranspirationratesweregreaterthantheevapotranspirationratesforthefloodplainforestmeasuredbyBrown(1978)andforthebayswampcommunityatthestudysite,expressedinTable41astotalwaterloss.Evapotranspirationincypressdomes wasmeasuredbyHeimburg(1976)bydeterminingthechangeinwaterlevels.Evapotranspirationvariedseasonallyinthecypressdomesandinthisstudy.Therefore,thereisvariabilityinevapotranspirationratesamongforestedwetlandcommunitiesandamongseasons,anditappearsthatforestedwetlandsevapotranspireatlowrateswhenwaterisscarceandathigherrateswhenwaterisreadilyavailable.

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194 When wetlandsgodry,plantsthatlimitwaterlossmayhaveanadaptiveadvantageinthesesystems. When waterisscarce,wetlandvegetationmayhavetheabilitytoamelioratewaterlossandevensurvivedroughtperiodsthroughmorphologicalandphysiologicaladaptations.Aspeciesmayrequireanincreaseinreflectance,asoccursinxeromorphicleaves,inordertomaintainreasonableleaftemperaturesassuggestedbyOdum(1984).Astrategyofconservingwaterduringdryseasonsisachievedbyincreasingreflectanceandreducingtranspiration(Odum1984).Italsoappearsthatduringwetseasonsahighrateofevapotranspirationcanoccur,andthereforethesespecieshavebimodaladaptationinthattheyarewelladaptedtobothwetanddryconditions.Therefore,althoughcertainforestedwetlandcommunitiesevapotranspireatahighratewhenwaterisreadilyavailable,thesesystemsareadaptedforwaterconservationduringdryperiods.ModelDevelopmentandSimulationIntrasystemcyclingofnutrientsinwetlandsdependsontheavailabilityofthenutrientsandthedegreetowhichprocessessuchasprimaryproductivityanddecompositionarecontrolledbythewetlandenvironment(MitschandGosselink1986).Forestedwetlandscanbearrangedaccordingtothevolumeofwaterflowingtothewetlandandtheaccompanyingnutrients(Brown1981;Odum1984).Manyisolatedwetlandssuchasthewetlandsatthestudysitehavealownutrientinputandthereforelowbiomass.Quantificationofinitialmodelcompartmentconditionsindicatedthatasmallamountofnutrientswerecycledwithinthesystem.Lownutrientinputlimitedthesimulatedproductivityin

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195thissystemsasindicatedintheannualbudgetsdeterminedduringmodeldevelopment(Figure25).Wetlandsinwhichprecipitationistheprimarynutrientinputdependonintrasystemcyclingfornutrients(MitschandGosselink1986).Therefore,ifprimaryproductivityanddecompositioninthewetlandarelimitedbyhydrologicandnutrientconditions,thenintrasystemcyclingofnutrientsishighandnutrientsmaybeconserved,aswasindicatedaboveforthisstudysite.Thesimulatedresponseofthewetlandtotheincreaseinnutrientswasanincreaseinannualbiomassandlitterandincreasedstorageofnutrientsinbiomass,litterandsoil,andtheratesoftheseincreasesdecreasedwithtime.Thisisconsistentwiththeresultsfromothermodelsusedtosimulatetheadditionofwastewatertowetlands(DixonandKadlec1975;Mitsch1975b;DeghiandEwel1984;Hammer1984)andwiththeresultsfromresearchinwhichaquantitativedeterminationwas madeofthestorageinwetlandcompartments(Nessel1978;KadlecandTilton1979;DierbergandBrezonik1983b).Naturalwetlandsretainedandstoredmuchoftheirnutrientinputsevenwhenloadingincreased200-foldovernaturalinputs(DierbergandBrezonik1983b).AswithinitialmodelsdevelopedtopredicttheadditionofwastewatertopeatlandsinMichigan,thesimulationswereintendedtoindicaterelativeeffectsofaddedwaterandnutrientsonthewetlandandshouldawaitcompletemodelvalidationbeforebeinginterpretedasactualresults.Withoutthesimulatedadditionofwastewaterthetitishrubswamp was aphosphoruslimitedsystem.Thevegetationstorednitrogenandphosphorusata N:Pratio(weightbased)of25:1(Figure25).

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196Wastewaterwasaddedtothesystemata N:Pratio(weightbased)of2.26:1(Figure26).Therefore,therewas asimulatedoverabundanceofphosphorusaddedtothesystemrelativetonitrogen.Productionandstorageinbiomassincreasedaslongasphosphoruswasavailabletodrivetheprocess. When phosphorusadsorptioninthesoilended(11.7yrs),theamountofnitrogenenteringthesystemwasgreaterthanthatrequiredtomaintainthesamelevelofproduction,andstorageofnitrogeninthesoilincreased.Agreaterrateofdenitrificationthanwasusedinthemodelcouldaccountforanoveralllowerlevelofnitrogenstorageinthesoil.Also,whenphosphorusadsorptioninthesoilended,phosphorusdischargeinrunoffgreatlyincreasedandthewetlandwouldnolongerassimilateenoughphosphorustoprotectdownstreamreceivingwaterquality.Wastewaterdischargedtowetlandswitha N:Pratiosimilartothatstoredinvegetationwouldmaximizethelifetimeofthesystemforphosphorusassimilation,andnitrogenassimilationcouldbeaccountedforthroughstorageanddenitrification.Therefore,nutrientloadingcriteriashouldbebasedonmaximizingthelongevityofthesystem,whichcanbeestimatedbydeterminingthephosphorusadsorptioncapacityofthesoil.Inthissimulationmodel,productionwas afunctionoftheinteractionofanexternallimitingfactor(solarradiation)andinternallimitingfactors(nutrients).Therefore,productionwasstronglyaffectedatlowconcentrationsbutbecomeslessaffectedasonefactorbecomesrelativelymorelimiting.Incertainsituations,thelimitingfactormaynotbecomerelativelymorelimiting.Gilliland(1973)foundthattheeffectofagreatexcessofonelimitingfactor(phosphorusinaFloridaestuary)loweredthestorageofanotherfactor(nitrogen)so

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197lowthatproductionwasinhibited.Therefore,theN:Pratiochangedtotheextentthatnitrogenandnotphosphoruswaslimiting.Mitsch(1976b)consideredthiswhileevaluatingtheeffectsofmultiplicativeinteractionsandsuggestedthatifnutrientsbecomeenrichedbeyondtheinternallimitations,thenitmaybebesttomodelproductionasifonlysolarradiationwerelimiting.Thismaybeamorerealisticapproachformodelingsystemswithexcessivenutrientinputs.Anenergy/nutrientecosystemmodelwasdevelopedtocharacterizeandquantifythemaincomponentsandprocessesofatitishrubswampnecessarytopredicttheirlong-termresponsestowastewaterdischarge.Thismodelcanbeusedtosimulatecarbon,nitrogenandphosphoruscycling,andwaterflowinaforestedwetland.QuantificationofmodelcompartmentshasaddedbasicinformationtothestudyofforestedwetlandsinFlorida.Manyofthemodelcompartmentscanbemoreaccuratelyestimatedforthesesystemsandthecapacityforphosphorusadsorptioninsoilscanbeincorporatedintothemodelwithminimallaboratoryanalysis.Themodelcanbeimproveduponforevaluatingthelong-termresponsesofthemaincomponentsandprocessesofwetlandstowastewaterdischargebyincorporatingmoreappropriatedynamicsfortheinteractionoflimitingfactorsofasystemreceivingexcessivenutrients.

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CHAPTER5SUMMARYANDCONCLUSIONSWetlandscanbeusedtotreatwastewaterifmanagedproperly.Inordertomanagethesesystemsproperly,wemustunderstandquantita-tivelyhowtheyfunction.Anenergy/nutrientsystemmodelwasusedtosimulatecarbon,nitrogenandphosphoruscycling,andwaterflowofatitishrubswampandtopredictthelong-termresponsesofthemaincomponentsandprocessestowastewaterdischarge.Quantificationofmodelcompartmentsindicatedthat:1)theabovegroundbiomassinthetitishrubswampisinthelowtointermediaterangeofvaluescitedforforestedwetlands.2)precipitationistheprincipalsourceofwaterandnutrientstothissystem,and3)therelativeconcentrationsofnitrogenandphosphorusinprecipitation,surfacewaterandgroundwaterandthedominanceofammoniacalnitrogenandlowlevelofphosphorusdissolvedinsurfacewaterindicatethatnutrientsareconservedwithinthesystem.Therefore,smallamountsofnutrientswerecycledwithinthissystemandlownutrientinputlimitedthesimulatedproductivity.Thesimulatedresponseofthewetlandtotheincreaseinnutrientswasanincreaseinannualbiomassandlitterandincreasedstorageofnutrientsinbiomass,litterandsoil,andtheratesoftheseincreases198

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199decreasedwithtime.WastewaterdischargedtowetlandswithaN:Pratiosimilartothatstoredinvegetationwouldmaximizethelifetimeofthesystemforphosphorusassimilation.Therefore,nutrientloadingcriteriashouldbebasedonmaximizingthelongevityofthesystem,whichcanbeestimatedbydeterminationofthephosphorusadsorptioncapacityofthesoil.Thephosphorusadsorptioncapacityofsoilsatthestudysitewerequantitativelydetermined.Themineralsoilsdominatedbytitihadalowcapacityforphosphorusadsorptionwhiletheorganicsoilsdominatedbyblackgumhadahighercapacityforphosphorusadsorption.Theadsorptioncapacitiesofthesesoilswererelatedtothecontentandavailabilityofamorphousandpoorlycrystallineoxidesofaluminum.Transpirationstudiesindicatedthatsweetbayhadlowratesoftranspirationperleafarearelativetootherforestedwetlandspecies.Anincreaseoccurredfromtheindividualtothecommunitylevelduetothehighleafareaindexinthebayswamp.Thiscommunitytranspiresatarategreaterthanopenwaterevaporationwhenwaterisreadilyavailableasindicatedbythepanratio.Thereisvariabilityamongforestedwetland,communitiesandamongseasonsanditappearsasthoughthesesystems lowrateswhenwaterisscarceandathigherrateswhenwaterisreadilyavailable.Therefore,thesesystemsareadaptedforwaterconservationduringdryperiods.QuantificationofmodelcompartmentshasaddedbasicinformationtothestudyofforestedwetlandsinFlorida,Theenergy/nutrientecosystemmodelcanbeimproveduponforevaluatingthelong-termresponsesofthemaincomponentsandprocessesofwetlandstowastewater

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200dischargebyincorporatingmoreappropriatedynamicsfortheinteractionoflimitingfactorsofasystemreceivingexcessnutrients.

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APPENDIXACOMPUTERPROGRAMTOINTEGRATEHOURLYTRANSPIRATIONRATESTOOBTAINADAILYTRANSPIRATIONRATE(DTR). ASAMPLEOUTPUTISINCLUDED

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10CLS'CLEAR 20 DIM CLOK(49).TR(49) 25 ISPUT "FILE:to,FILES26 LPRIST 30 OPES "I",II,"B: "...FILES...". PRN" 'OPENDATAFILE 40RE."1iHHILOOPTO READIN DATA .. SOFOR L. ITO 49 60 LISE INPUTII,CFS :RE."1 READDATAFILEONELINE ATA T70CLOK(L).VAL(MIDS(CFS.9.4 ASSIGNSVAWETO VARIABLES 80TR(L).VAL(MIDS(CFS,15,7IOCPRINTCLOK(L).TR(L)101LPRINTCLOK(L),TR(L)110NEXTL120 RfJ'l-COUNTIOF PANALS-l30P .. 0 140 FORL1TO 49 150IFTR(L)>.aTHENPP...l160NEXTL170PANALSP-l180 PRINT:PRINT:PRINT "PANAlS: ";PANALS181 LPRINT:LPRINT:LPRINT"PANALS: ";PANALS 185 REM-FINDSSTARTAND LAST OF DATA........ 190FORL1TO 49 20CIFTR(Ll>0 n1EN 210ELSE220210START L:LAST". L...PANALS:GOfO2.30 220NEXTL 230PRINT "START: ";START. "LAST: ";LAST 231LPRINT"START:"iSTART."LAST:"iLAST 235 REM--SUMSSTART ANDLAST VALUES FORTRF1JNcrION --240 ESTR TR(START)+TR(LAST) 260PRINT"ENDSUM: ";F.STR 261" LPRIST"END SUM:":STR 270PSTR.. 0 275 RE'l.....SUMS VALUESFORTREX F1JNcrION...... 280FORXSTART+1TOLAST-l 290PSTR .. PSTR+TR(X) 310NEXTX 320PRINT"PANALSUM:":PSTR 321LPRINT "PANALSUM: ";PSTR 325 REM... INTEGRATES ...... 330ITR .. (ESTR+2PSTR)-.5360PRINT"TRANSPIRATIONRATE.":ITR; "ftH20/DAY" 361LPRINT"TRANSPIRATIONRATE..":ITR:gH20/DAY"202

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091486Z 700 0 715 0 730 0 745 0 800 0 815 0 830 0 845 0 900 0 915 0 93027.3994528.19100028.86101529.7103029.65104529.56110030.42111530.27113031.2114531.1120031.1121531.96 123031.85124531.85 10032.78US66.4713066.4714533.7420033.821566.5823032.9424532.9430032.8931532.0133032.0134561.4740030.3741530.3743029.4644529.5650029.56515 0 530 0 545 0 600 0 615 0 630 0 645 0 700 0PANALS:30START:11LAST:41ENDSUM:56.95PANALSUM:1039.57TRANSPIRATIONRATE=1068.045gH20/DAY203

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APPENDIXBREGRESSIONEQUATIONSUSEDTOESTIMATETHEBIOMASSOFTHETITISHRUBSWAMPINAPALACHICOLA,FLORIDA.pdb PRIMARYBRANCHDIAMETER,dbh DIAMETERATBREASTHEIGHT

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AppendixB.RegressionequationsusedtoestimatethebiomassofthetitishrubswampinApalachicola,Florida.pbd ; primarybranchdiameter,dbh ; diameterbreastheight. Rllr ...lon, Sped !qo.IaUon..... Soure " ,..dry ..t. branch_techl 1 Ibe'"Utl,-A/(I+III. I lipoid 10,000 1123.5302thhlwetr0.95 RedUti""/11 + 8J:" I IIJIDCIld 100,000 '05'.5114-3.0351rbllIt.l.ldy0.95 s. tb.,.,tAx,-maxi...tUDctlon5.4282 .9778 ThilItUd)' 0.81 ,.. dry war.. 1 r... t.'rl,lIlllcrr. Uti,.,....function 5 .585 1 2.71ilUDbItUdy .", bdUti ,.fA: .... .. :1:.1 .. f\BI .. t1on 1.e03 12.323 this It.udy." s. tb.,.,,"I.I:+B mod. poooertunr.t1on" .0013I2.11197 rbh Itudy 0.75db' U_tedabove ,round, iliac'" till r-"'O+lIr' I IIPlDloS 1,000,000 10''''.88''1-2.5''1Tbllstud, .09 blcm ... (dbh > 0 CIll) RedUti'"'"pOoMctlmctloa143.1'17 2.09.e ThilItudy ." s. t.b.,. ,.AJ{1+II'I IxponlUalI11DlO14 100,000 llO.S1l511Tbil,tudJ IDO '" 0 dbb.au_tedahov.around 10 oil...-function256.1128 1. lion Thll Itudy 1.00 lJ1 blOlll... (dbb <'.0em' db. .. UlMt.dahOY.&E:ouM 10a,.. -Atll101."doubt.10&ult.... to-.870 2.380lIE:cMh1878 0.99 bi""" .. (dbh:> 0 elll) 12 SI.. hp1n.10&,,.-AHIlOB'"doubh10'II'It.hmll1 -1. 5853.088DU_Ir Ul170.99 (ethel1110Ill:own1871)" Pond ""'1'.1110&,.-11+11 10 cloubh10lulll'm11l -0 8002.258HllI..b1975 0.99 (clt.ct in lroooa19711)dbb.IUllI't..d 1,,( blOl1l'I."Ih.. kUUy+b.'-fWlcUCI1l20.5118 1558Ttll tulb ." R.d UUy--'1I/8+:II:bypIIrbolh.1151.9083-2.11 .1177ThhIt.ulb 0.70I. s. ..t b,yy+A,-IlI:pOfllUdIrO'rt.b.ll7 .IlZ56o2323 TbhIludy 0.90 POl'ld cypu 101 ..-A+1101".daub1,10larlttDic 1237 1.568HUlchJe15 0.83 (clt.-.1 III IIrcMh1918)

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APPENDIXCANNUALWATERBUDGETSFOR1982-1986ANDFORTHEWATERBUDGETYEAR(WBY)FORTHETITISHRUBSWAMPSTUDYSITE. AKEYTOTERMSISINCLUDED

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1982, Month PAHCIIAHCIII PE.KAT ,UPET HHS PET P-PETAWL STSWL AnJAN 2.640.070.38 2.3752.6 3.500.0227.30.5462.09402.01 0.546 FE'6.21I.)) 2.75 3.2159.1 5.310.0526.11.305 4.905 02.011.305.A' 8.022.764.714.2761.76.100.0630.91.8546.16602.011.854 AP' 3.340.57I .51 5.74 66.8 1. 750.0832.12.5680.77202.012.568 .AY1.48 0.010.197.1173.410.080.1336.14.693-3.213-3.2130.431.583.060JUN5.561.032.397.7980.612.850.1834.86.264-0.704-0.7041.380.636.190JUL10.841.894.435.8480.412.770.18 3 'L7 6.426 4.414 02.016.426 AUG4.54 0.060.665.8581.213.090.1833.96.102-1.562 -1.502 0.901.115.650SEP15.376.039.305.2076.811.350.1530.94.63510.73502.014.635OCT6.881. 563.41 4.3070.28.920.1129.43.2343.64602.013.234NOV2.180.070.512.8763.96.790.0726.71.8690.31102.011.869 DI::C 4.900.23 1.35 2.3659.95.550.0526.71.3353.5650 2.01 1.)35T01'AL71.9615.61 31. 5956.91104.0640.83138.672 N o '"

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1983MonthP ;.HC IIAHCIII POIIltAT 1 U'ETMMS PETP-PET AWL ST SWL AET JAN 4.300.221.092.0150.9 3.08 .0327.30.8193.48102.010.819 FEB 5.490.571.893.1954.23.92.0'26.11.0444.44602.011.644 HA' 4.970.050.814.2257.04.69.0'30.9I.5453.4250 2,011.545APR 12.143.937.116.34 62.7 6.101 .0732.12.2479.89302.01-2.247 HAY 0.250.000.00 7.02 72.89.85.Il 36.1 4.693-4.443-4.8430.311.70 1.950 JUN8.030.97 3.01 6.2878.211.85.1734.85.9162.1140 2.01 5.916Jue2.240.000.157.6881.713.29.1936.76.783-4.543-4.5430.31I.70 3.940AUG 5.370.451. 59 6.2781.8 13.33 .19 )).9 6.441-1.071-1.0711.180.836.200 SU'6.89 0.682.356.1376.511.24 .Il 30.94.6352.25502.014.635 OCT 2.050.030.364.3671.49.34.1229.43.528-1.478 -1.478.0.941.013.120 NOV 6.691.443.173.0459.45.40.0026.11.602 5.08802.01-1.602 DlC 5.960.832.282.3052.03.35.0326.70.8015.15902.010.801 lOTAL 64.389.1724.8151.8495.1540.054 34.1019tv a '"

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1984 0HoothPAHCIIAHCIIIPE It>IAT 1 UPET.. SPET P-PETAWL ST SWL AIT JAN4.730.401.45 2.48 50.1 2.89.0'27.3 0.546 4.18402.010.546HiS 3.93 0.541.45 3.38 53.4 3.71.0326.10.783 3.1lt.7 02.01-0.783 NAB 6.080.602.49 5.10 51.8 4.92.0'30.9 1.5454.535 02.011.545 APO9.16 4.15 6.18 5.86 69.91.12.0832.12.5666.61202.012.568 HAY 0.320.000.007.2912.89.85.1336.14.693-4.31]-4.371 0.35 1.661.980JUN 3.37 0.050.517.5617.311.54.1.34.85.568-2.198-2.1980.59 1.42 4.790JUL18.073.678.266.70 76.5 12.01.11]6.76.06912.00102.016.069AUG4.720.671.696.0680.6 12.85 .1833.96.102-1.382-1.]821.020.995.710 l.25 0.070.356.1476.911.39.1.30.94.944-3.694-3.694o.]91.622.870OCTI.780.10 0.445.51 72.89.85.13 29.4 ].822-2.042-2.0420.75 1.26 3.040NOV2.160.000.273.1458.95.25.0'26.71.3]50.82502.011.335 OIC 0.910.000.102.9262.8 6.44 .0126.71.869-0.959-0.9591.260.751.660 l'OTAL56.5010.45 2].1962.1497.8239.84432.896 N...... a

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1985 Honth AHC II AHC IIIPI lIllAT U'ET... 5 ...,P-PETAWL ST SWL AiTJAN5.58 1.29 2.56 2.59 1t8.12.ltl .01 21.3 0.2735.30702.010.273FEB 1. 780.06 0.35 3.26 55.1It .16.0326.10.7830.9970 2.01 -0.783 MAR2.55 0.150.734.6264.06.82.0130.92.1630.38102.012.163 Ai'k 0.860.000.006.0266.2 7.55 .0832.12.568-1.708-1.7080.831.182.040 NAY 2.720.230.906.78 74.5 10.48.1336.14.693-1.973 -1.9730.71l.304.020JUN3.910.090.61 1.27 79.9 12. 57.18 31t.8 6.264 -2.3:14 -2.3540.671.34 5.250 .JUL 1.66 0.822.585.1680.412.71.1835.7 6.U6 1.21402.016.426 AUG 16.184.478.265.7880.412.17.'83].96.10210.07802.016.102 SI::P 5.380.852.045.3l77.511.62.1.30.94.9440.43602.01-4.944OCT Il.B 3.216.103.33 H.1t 10.82.1'29.44.1167.Il402.01-4.Il6 NUV6.4tl 2.053.602.4968.58.33.0026.72.4034.01102.012.403DEC 4.240.100.78 2.2852.5 3.48.0226.70.5343.70602.01-0.534 TOTAL 6tl.57 n.n 28.51 54.91103.7841.269 39.051tNt-'t-'

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1':186 Honth,AMC11 !He III,. MMAr iUPET MHSPETP-PE'IAWL ST SWLAIlTJAN3.82 0.261.11 2.93 52.23.400.0227.30.5463.27402.010.546 FEB 5.410.221.133.62 59.2 5.340.0426.11.0444.36602.01 1.044 .AR 2.23 0.23 0.704.8860.35.67010530.9 1.545 0.68502.011.5115APR 0.260.000.006.6066.57.320.0832.1 2.568 -12.308-2.3080.67 1.34 1.660 .....r 4.362.093.201.0173.810.220.1336.1 11.693 -0.373-0.373 1.73 0.284.640JUN2.010.020.216.4481. 5 13.210.1934.86.612 -11.602-4.602 0.311.703.710JUL3.340.100.598.0183.113.850.2035.77.140-3.800-3.80.351.665.000Aue12.042.955.165.54 81.11 13.700.19 33.9 6.4415.59902.01-6.441SEP9.293.79 11.83 4.8180.512.810.1830.9 5.562 3.12802.015.562OCT9.192.294.41 4.011 72.29.640.1229.43.5289.66202.01-3.528NOV5.180.701.742.3768.88.440.1026.72.6702.51002.012.670 DEC 9.68 2. 513.871.62 58.2 5.040.0426.71.0688.61202.011.066 TOTAL66.tll 15.16 27.55 57.93108.6443.417 37.354 tv.....tv

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WBY MonthP "He II "He IIIP. llItAT UPEtHHSPET(l-(I.t.:T AWLSTSWL AET OCT1985 11. 23:).216.10 3.337S.4 10.820.1429.4 .1167.il402.014.116NOV 6.48 2.053.602.4968.5 8.33 0.0926.72.403 ". .0710 2.01-2.40)OEC4.240.100.782.2852.53.480.0226.70.5343.70602.01-0.534JAN 11)86 3.820.261.112.9352.23,400.0227.30.5463.27402.010.546 H: 5.410.22 1.13 3.6259.2 5:34 0.0426.1 1.0"4 4.)6602.011.044 MAR 2.230.230.104.88'60.35.670.0530.91.5450.68502.01-1. 545 APH 0.260.000.006.6066.51.320.0832.12.568-2.]08-2.3080.67 I. 341.500 N" ".362.093.207.017).810.22 0.13 36.14.693-0.]13-0.3731.730.284.640JUN2.010.020.216.44 81. 513.21 0.19 34.86.612-4.602-4.6020.311.703.710JUL3.340.100.598.0183.113.880.2035.77.140-3.800-3.8000.351.665.000 AUG 12.04 2.955.76 5.54 81.413.700.19 D.9 6.4415.59902.016.441SEP9.293.794.834.8180.512.810.1830.9 5.562 3.72802.015.562TOTAL64.71 15.02 27.3158.00 108.15 43.20437.141 N,....w

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APPENDIXDSPREADSHEETSFORTRANSPIRATIONRUNS.AKEYTOTERMSISINCLUDED

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UNITSTRANSPIRATIONPROGRAMPARAMETER* * *** *TICTAMDTINDTEXESTAMESDTINESDTEXAHTAMAHINAHEXRHSDSESFLFRTRDTRLBLATRLADTRLALBARTRBLBGALAIDTRGACCCcmbmb mbg/m'g/m'giro' % robBtujhr/ft'kcaljhr/ro'm/secm'jhrgH,OjhrgH,O/daygro'gH,O/m'-hr gH,O/ro'-daygiro'leafareagH,O/g-hrgiro'-groundaream2jm'gH,O/m'-dayTemperatureInsidetheChamberAmbientTemperatureOutsidetheChamberDewPointTemperatureIntakeDewPointTemperatureExhaustAmbientSaturationVaporPressureIntakeSaturationVaporPressureExhaustSaturationVaporPressureAmbientAbsoluteHumidityAbsoluteHumidityatSaturationIntakeAbsoluteHumidityatSaturationExhaustRelativeHumiditySaturationDeficitSolarInput(englishunits)SolarInput(metricunits)MeasuredFlow FlowRateTranspirationRateDailyTranspirationRateLeafBiomassLeafAreaTranspirationRateperLeafAreaDailyTranspirationRateperLeafAreaLeafBiomassAreatoRatioTranspirationRateperBiomassLeafBiomasstoGroundAreaLeafAreaIndexDailyTranspirationRateperGroundArea*Measuredinthefield215

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i I, oooOOOOOOQoooooooooooooooooooooooodooooo;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; 216 :I !;::IjI::..........4IS...:ri..."" ...... #. :?: =:::::: :::! :::! ---il';"" .. ,.. ... :1" ............ ., ., :t; ......... ;:;:iI I

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odddddcodddddddododddooooddddddddddddodd; ---------------------------------------, ... ... ....... .. ............ ...... .....=................ ---------------------------------------ii;.!: __ J'= !I I :.s ', 444..."1!!...... 217

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218 ddddddddddddddddddddddddddddddddddddddd i I I, ... ......._e.ee_.. .... i I !IIi I II !SI" I:1 jO:: ......... illS ... :.1...... ..... g2:: :::.::: ---...'" .. ,'""'"...M ...4-u.':Jj ... ;0..;<;:: I !

PAGE 238

I II E IIIi I I I 219 i i! I m!!

PAGE 239

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APPENDIXEBASICCOMPUTERPROGRAMTOSIMULATETHEDISCHARGEOFWASTEWATERTOTHETITISHRUBSWAMP

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10SIMMODEL TITIWWTR 20 : HCOLOR= 725 O,0 TO 0,159 TO 100,159 TO 100,0 TO 0,030 HPLOT 0,50TO100,50 32HPLOT 0,110 TO 100,11050REMSCALING FACTORS 55 DT=.1 50TI2I =1 11210AS = .00005110BS = .01120 CS=.8 130 DS= .0005l40 ES=.25 150 FS=4 150 GS= .000015 170HS=.07180IS=..5 i9121 JS=5 200 KS= 10210 LS=1 300 KA =2.232 10305KB = B.49E 12 310 KC= 1.03E3315KD = 4 _.-,--5.. 320KE=2.52E2 "'::''jC" KF=3.52E-2 330KG = 4.55E 2 335 KH=4.21E-2 340 KI =2.5E-1 345 KJ=2.5E-1 350 KK= 4.55E 1 355 KL= t:" -1 350KIYi =l.95E .,.355 KN= 7.75E 1 370 KO= 10.05375 KP= 3.94E .,380 KQ= 3.32E -3 3'3:11 KR= 5.93E -3 450 KX= 13.35450 KY= 51Zi0QA =4.4E4 51IIIQB =45.4 520 QC= 1 .. '3530 QO= .,lE3540 QE=4.53 QF= 0.13560QG= 1.99E5570 QH=338.7 580 QI =15.8 5'3eJ QJ=1. 08500 QK= L07610 QL= 0.01620"' = : .. 57 228

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63121 R= 3.98 229 EA0 ET = l.12I4550 G = 0.21S61l' Z = 3.5567121NP =1.57 575 NZ= 15.068121pp = 0.08685 PZ = 7.0693 TH= 805694AL = 12 695JO= 1.46E6700 REMPLOTTING 708 REMBIOMASS+CONTENTS-NPC 709 HCOLOR= 5 710 HPLOT T0.,., T,50-BS .,., QB711HPLOT T0.,., T. 110 -CS .,., OC712HPLOT T0.,.,T,160 AS.,., OA 743 REMLITTER+CONTENTS-NPC714HCOLOR= ;;; 715HPLOT T0.,., T,50-ES .,., OE 716 HPLOT T0.,., T. 110 -FS .,., QF717HPLOT T0.,., T, 160 -DS .,., OD718 REM SOIL+CONTENTS-NPC719HCOLOR= 272121 HPLOT T0.,.,T,50HS .,., QH72lHPLOT TI2I.,.,T,ll121 -IS .,., 01 HPLOTT0.,.,T,160 -GS .,., QG 79121 IFQII AL lTHTHENX= 121 795IF01IAL(THTHEN X = 1799JR=JOI(1 +KA.,.,OA.,., OH .,., 01> 81210 DA=KB .,.,QA.,., QH .,., 01 .,., JRKE .,.,QAKF .,.,QA81121 DEI=KC .,., KB .,., QA .,.,QH.,., QI .,., JR KG .,.,OB620 DC= KD.,., KB .,.,G.A.,., QH .,., 0.1 .,., JRKH.,., QC 830 DD= KF.,., QAKI .,., OD KJ .,., GD 84121 DE= KG.,.,QBKK...Q850 DF=KH .,., QCKL .,.,OF 860DG= KJ.,., QD KM.,., QG 870 DH=KK .,., QE + KX..QKKC.,., KB .,., OA .,., QH .,., Q1 .,., JR-KR .,., QH-KP .,., G .,., QH875IFDH( 0THi::N DH= 12168121 DI=KL..QF-KD... KB ...QA .,., QH .,., QI .,., JR + KY .,.,Qi...,., XKO .,., G...QI 881 IFDI< IIITHEN DI = 0890 DJ= P+ Z-ET-R G 90:21 DK= NP+ NZ-KN...R .,., QKKX...OK 910DL = pp+i='Z KO ...R ..QL. KY.. QL .. X 915 IFDL( 121 THENDL..= 121l0il,12I QA=QA + DA .,., DT te'l'" QB=QB + DB .,., DT

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llZl2!ZlQS =QC ;DC *DT1030 QD=QD or DO DT230 1040 QE=QE+DE DT 1050 QF=QF+OF DT 1060 QG=QG+DG DT 1070 QH=QH+DH DT 1080 QI=QI+01 DT 1090 QJ=QJ+DJ DT 1100 QK=QK+DK*DT1110QL=QL+DL*DT 1120 T=T+DT 2000 IF T0 *T< 100 GOTO 7002100 PRINTQA 0=:110 PRINTQB2120PRINTac 0=:130 PRINTQD 0=:140 PRINT 2150PRINTQF 2160 PRINTQG 0=:170 PRINTQH 2180 PRINTQI 2190 PRINTQJ 221210 PRINT QK 2210PRINTQL 222121 PRINTKN*R*QK 2230 PRINT KO *R QL

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APPENDIXFCALCULATIONOFSTORAGESANDFLOWSFORTHESIMULATIONMODELOFTHETITISHRUBSWAMPINAPALACHICOLA,FLORIDA,PRESENTEDINFIGURE24

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AppendixF.CalculationsofthestoragesandflowsforthesimulationmodelofthetitishrubswampinApalachicola,Florida,presentedinFigure24.1.AbovegroundBiomass.NinBiomass.PinBiomassSource:Figure4Table16Table22Table22StudysiteStudyStudygbio-gbio-sitesite%ofAreamass/m2mass/m2gN/m2gN/m2g P/m2g P/m2Titiswamp-titiphase59.18400.54964.743.125.51.71.0Titiswamp-hollyphase18.21266.6230.57.91.40.30.1Bayswamp9.119072.91735.697.38.83.90.4Blackgumswamp13.613890.71889.171.69.72.90.4Total100.08819.945.41.9(8819.9g/m2 )x (5kcal/g)4.4x10'kcal/m2 .2.Litter.NinLitter.P in LitterSource:Figure4Table15Table23Table24StudysiteStudyStudygdrywtgdrywtsitesite%ofArealitter/m2litter/m2gN/m2gN/m2g P/m2g P/m2Titiswamp-titiphase59.1750.4443.54.582.710.130.08232

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233Titiswamp-hollyphase18.2511.593.15.791.050.150.03Bay swamp9.1878.279.97.540.69 0.200.02Blackgumswamp 13.690.712.30.600.08 0.02<0.01Total100.0628.84.530.13(628.8g/m2 )x(5kcal/g) 3.1x103kcal/m2 3.CarboninSoil.NinSoil.PinSoilTitiSwamp TitiPhaseSource:Table28Table28Table28Table28SoilDepth(cm)BulkDensityg/cm3CarbonContentmg/gNContentmg/gPContent j1.g/g gP /m2+ 0-5 0.8697.041712.45105.490.633.95-101.0077.738852.06103.059.003.010-151.3053.234581.4091.046.143.015-201.4335.325240.4230.045.133.2Total14038329.413.1*(gsoil/cm3 )(mg/gsoil)(lx 106cm3/m3)(.05m)(lgilx103mg)+(gsoil/cm3 ) (j1.g/g soil)(lx106cm3/m3 )(.05m)(1gilx103mg)(lmg/lx103 j1.g)

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234TitiSwamp HollyPhaseSource:Table29Table28Table28Table28SoilBulkCarbonDepthDensityContentNContentPContent(em)g/em3mg/g gC/m2*mg/ggN/m2*jJg/gg P/m2+0-50.9069.731563.08138.664.192.95-101.1239.822291.6994.642.622.410-151.1736.621411.2070.238.752.315-201.4133.423550.9567.037.132.6Total9881370.410.2*Samecalculationasabove.+Samecalculationasabove.BaySwampSource:Table28Table28Table28Table28SoilBulkCarbonDepthDensityContentNContentPContent(em)g/em3mg/g gC/m2*mg/g gN/m2*jJg/gg P/m2+ 0-5 1.0245.523201.1659.238.372.05-101.1636.221000.8549.327.501.610-151.5327.320880.5038.216.871.315-201.6821.017640.3630.214.631.2Total8272176.96.1*Samecalculationasabove.+Samecalculationasabove.

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235BlackgumSwampSource:Table28Table28Table28Table28SoilDepth(cm)0-55-1010-1515-20TotalBulkDensityg/cm30.65 0.991.191.24CarbonContentmg/g499.7368.4289.6 240.51624018236172311491166618NContentmg/g3.542.461.901.53115.0121.8113.094.9444.7PContent }Jg/g 180.00182.25204.00 224.87gP/m2+5.89.012.113.940.8*Samecalculationasabove.+Samecalculationasabove.Total TitiShrubSwampSource:Figure4 % ofAreaTitiSwamp titiphase59.1TitiSwamp hollyphase18.2Above gdrywtC/m2140389881StudysitegdrywtC/m28296 1798 AbovegN/m2329.4370.4StudysitegN/m2194.767.4AbovegP/m213.110.2StudysitegP/m27.71.9BayswampBlackgumswampTotal9.113.6100.08272 66618 753 9060 19907176.9444.716.160.5338.76.140.80.65.615.8(19907gC/m2 )x(10kca1/gC) 1.99X105kca1/m2 .

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236Source4.SurfaceWaterAveragehighwaterforallsites:1.08m 1.08m3/m2Table335.NinSurfaceWaterWithoutwastewater:AverageTN0.99mgN/l(0.99gN/m3 )Table26Averagedepth0.51metersTable330.50gN/m2Withwastewater:AverageTN0.99mgN/l(0.99gN/m3 )Table26Averagedepth1.08metersTable331.07gN/m26.PinSurfaceWaterWithoutwastewater:AverageTP0.01mgP/l(0.01g P/m3 )Table26Averagedepth0.51metersTable330.01g P/m2Withwastewater:AverageTP0.01mgP/l(0.01g P/m3 )Table26Averagedepth1.08metersTable330.01g P/m27.AnnualWaterBudgetWithoutwastewater:P = R+G+ETTable32 P1.67 m R 0.50mG. 0.13mET 1.04mWithwastewater:P+Z R+G+ETP-1.67mZ 3.56m [1MGD 1.38x106m3/3.88x 105 m2 ]ET 1.04 m G 0.21m(upperlimitofdeepseepage)Table32MOR'sApalachicola WWTP (9/857/86)Table32

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237 RIN -OUT-(P+ Z)-(ET +G) (1.67 m +3.56m)-(1.04m +0.21m)3.98m.8.NinPrecipitationPrecipitation1.67m!yrTable32AVGTNinprec.0.94mgNil(0.94gN/m3 )Table241.57 gN!m2yr9.PinPrecipitationPrecipitation1.67m!yrTable32AVGTPinprec.0.05mgP/1(0.05gP/m3 )Table240.08g P!m2yr10.NinRunoffWithoutwastewater:Runoff0.50m!yrTable32AVGTNSta.60.83mgNil(0.83gN/m')Table26(mostdownstreamstation)0.42gN!m2yr With wastewater:Runoff3.98m!yrNote7,Appx FAVGTNSta.60.83mgNil(0.83gN/m3 )Table263.30gN!m2yr11.PinRunoffWithoutwastewater:Runoff0.50m!yrTable32AVGTPSta.60.01mgP/1(0.01g P1m3 )Table26(mostdownstreamstation)0.01g P!m2yrWithwastewater:Runoff3.98m!yrNote7,Appx FAVGTPSta.60.01mgP/l(0.01gP1m')Table260.04g P!m2yr12.NinGroundwaterFlowWithoutwastewater:Groundwaterflow0.13m!yrTable32AVGTNinground-waterwells1.33mgNil(1.33 gN/m')Table250.17gN!m2yr

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238Withwastewater:Groundwaterflow0.21m/yrAVGTNinground-waterwells1.33mgNil(1.33 gN/m3 )0.28gN/m2yr13.PinGroundwaterFlowWithoutwastewater:Groundwaterflow0.13m/yrAVGTPinground-waterwells0.04mgP/1(0.04gP/m')0.01g P/m2yrWithwastewater:Groundwaterflow0.21m/yrAVGTPinground-waterwells0.04mgP/1(0.04g P1m3 )0.01g P/m2yr14.SolarRadiationandGPPNote7,Appx FTable25Table32Table25Note7,Appx FTable25 -.3% x(8/12)ofJO-2.78X103kca1/m2 .yrOdum1971*Mitsch1975b1.46X106kcal/m2 .yr -5% ofJO 7.3X104kca1/m2 yr 1.39x 106kca1/m2 .yrAVGSolarRad.,JOSolarradconvertedasGPP,JJR JO-JAVGefficiencyofGPP*Mitsch(1975b)presentsavalueof.335% x(8/12)ofJOforcypressdomes. Alowervaluewasassumedforthislowbiomass(productivity)system.15.NUptakebyVegetationNinbiomassAbovegroundbiomassGPP45.4gN/m2+8819.9g/m25.15X10-3gN/gbiomassx2.78X103kca1/m2 .yr+5kcallgNote1,Appx FNote1,Appx FNote14,Appx F2.86gN/m2 .yr

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23916.PUptakebyVegetationPinBiomassAbovegroundBiomassGPP17.PlantRespirationGPP1.9gP/m2+8819.9g/m22.15X10-4gPigbiomassx2.78X103kca1/m2 .yr+5kcallg0.12gN/m2 .yr2.78X103kca1/m2 yr40%ofGPP1.11X103kca1/m2yrNote1,Appx FNote1,Appx FNote14,Appx FNote14,Appx F**Mitsch(1975b)presentsavalueof52%ofGPPforcypressdomes. Brown(1978)indicatedlowrespirationinnutrientpoorsystems.Alowervaluewasassumedforthisnutrientpoorsystem.18.LeafLitterfa11.NinLeafLitterfall,PinLeafLitterfallSource:Figure4Table19Table21Table21StudySitegdrywt.gdrywt.LeafLeafLitter-Litter% ofAreafa11/m2fa11/m2NContentmg/gStudysitegN/m2StudyPContentsite !,g/g g P/m2Titiswamptitiphase59.1Titiswamphollyphase18.2BaySwamp9.1Blackgumswamp13.6Total100.0283.3205.4583.8304.7.167.448.353.141.4310.25.749.107.90 7.020.960.440.42 0.292.110.22 0.36 0.25 0.180.040.020.01 0.01 0.08(310.2g/m2 )x(5kca1/g) 1.55x 103kcal/m2 .yr

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19.LitterRespirationandLitterRemaininginSoil240LeaflitterfallApprox50%ofleaflitterfallremainsinsoil20.SoilRespirationLitterremaininginsoilAssume50%oflitterremainsinsoil1.55X103kcal/m2 yr0.507.75X102kcal/m2 .yr7.75X102kcal/m2 .yr0.53.88X102kcal/m2 .yrNote18,Appx FDeghi1977Note19,AppxF2l.LitterNRemaininginSoil,LitterPRemaininginSoilAssume100%ofleaflitterfa11NandPremaininsoilNdepositedbyleaflitterfa11 2.11gN/m2Note18 Appx F Pdepositedbyleaflitterfa11 0.08g P/m2Note18 AppxF22.NinWastewaterFlowWastewaterflowNinwastewater23.PinWastewaterFlowWastewaterflowPinwastewater3.56m/yr4.5mgNil(4.5gN/m3 )16.0gN/m2 yr3.50m/yr2.0mg/l(2.0gP/m3 )7.0gP/m2 yrNote7,AppxFMORsfromApalachicolaWWTP9/85-7/86Note7, Appx FMORsfromApalachicolaWWTP2/86

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24124.DenitrificationDenitrificationinacypressdomereceivingwastewater2.01gN/m2 .yr25.MovementofNoutofSurfaceWaterAssumesteadystateinsurfacewaternitrogenNP+NZk1,RQu 1.57+16.0-3.3014.3gN/m2 .yr26.PAdsorptioninSoilDierberg1980atsteadystatePP+PZ-k15RQ127.04g P/m 2 .yr0.08+7.0-0.04 Source:Figure4Table28Table27Adsorp-kgPBulktionadsorbedatAreaVolumeDensityGramsofSoilMaximaAdsorptionm 2cm3*g/cm3+SoilType !"g/g# MaximaTitiSwamp-titiphase2.29xl054.58xl01O1.155.27xl01OM102.45393.4TitiSwamp-hollyphase7.06xlO'1.41xl01O1.151.62xl01OM102.41662.8Bayswamp3.53xlO'7.06xl091.359.53xl09M102.4976.0Blackgumswamp5.28xlO'1.06xl01O1.021.08xl01O02164.823317.5Total31349.7*+#Areamultipliedby0.2mdepth.Averageof4depthintervals.Adsorptionmaxima.FormineralsoilslopeofLangmuirequationused4(0-5) 51.0(Table30),4(15-20) 153.8(Table30),average 102.4.FororganicsoilEPCderivedfromquadraticequation

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242substitutedintoFruendichequation5(0-5) 2887.2(Table30),5(15-20) 1442.3(Table30),average 2164.8.31349.7kgP/3.88x105m2 80.8g P/m2Threshold maximumadsorbed+initialstorage 80.8g P/m2+15.8g P/m2(Note3,AppendixF) 96.6g P/m2 .27.PercentAluminumSource:Table27Table31Figure4TitiSwamphollyphase(usedforallmineralsoils)SoilTypeMineralDepth(cm)0-515-20TammexAl %ofArea556.0925.0StudySite AVGBlackgumSwampAVGTotalOrganic 0-5 15-20740.52252.05700.03976.086.413.6639.8540.71180.5**1180.5 0.12%.

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255Parker,P.E.1974.Adynamicecosystemsimulator.Ph.D.dissertation.UniversityofMichigan,AnnArbor.Peech,M.1965.Hydrogen-ionactivity.Pages914-926inC.A.Black(ed.),Methodsofsoilsanalysis,PartII.AmericanSocietyofAgronomyInc.,Madison,Wisconsin.Post,D.M.andP.A.Straub.1974.Ratesofgrowthandnutrientconcentrationsoftreesincypressdomes.Pages420-444inH.T.OdumandK. C.Ewel(eds.),Cypresswetlandsforwatermanagement,recyclingandconservation.FirstAnnualReporttotheNationalScienceFoundationandTheRockefellerFoundation.CenterforWetlands,UniversityofFlorida,Gainesville.Post,H. A.andA. A.delaCruz.1977.Litterfall,littercomposition,andfluxofparticularorganicmatterinacoastalplanstream.Hydrobiologia55(3):201-208.Rennie,D. A.andC. W. McKercher.1959.AdsorptionofphosphorusbyfourSaskatchewansoils.CanadianJournalofSoilScience39:64-75.Richardson,C.J.(ed.).1981.Pocosinwetlands.HutchinsonRossPublishingCompany,Stroudsburg,Pennsylvania.Richardson,C.J.1985.Mechanismscontrollingphosphorusretentioncapacityinfreshwaterwetlands.Science228:1424-1427.Richardson,C.J.andJ.A.Davis.1987.Naturalandartificialwetlandecosystems:ecologicalopportunitiesandlimitations.Pages819-854inK.R.Reddyand W. H.Smith(eds.),Aquaticplantsforwatertreatmentandresourcerecovery.MagnoliaPublishingInc.,Orlando,Florida.Richardson,C.J.andD.S.Nichols.1985.Ecologicalanalysisofwastewatermanagementcriteriainwetlandecosystems.Pages351391inP.J.Godfrey,E.R.Kaynor,S.Pelczarski,andJ.Benforado(eds.),Ecologicalconsiderationsinwetlandstreatmentofmunicipalwastewaters.VanNostrandReinholdCo.,NewYork.Richardson,C.J., W. A.Wentz,J.P.Chamie,J.A.Kadlec,andD.L.Tilton.1976.Plantgrowth,nutrientaccumulationanddecompositioninacentralMichiganpeatlandusedforeffluenttreatment.Pages77-117inD.L.Tilton,R. H.Kadlec,andC.J.Richardson(eds.),Freshwaterwetlandsandsewageeffluentdisposal.TheUniversityofMichigan,AnnArbor.Ryden,J.C.andJ.K.Syers.1977.Originofthelabilephosphatepoolinsoils.SoilScience123:353-361.Rykiel,E.J.,Jr.andnutrientAthens.1977.TheOkefenokeeSwampwatershed:waterbalancebudgets.Ph.D.dissertation.UniversityofGeorgia,

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BIOGRAPHICALSKETCHLarryNealSchwartzwasbornOctober31,1954,inProvidence,RhodeIsland.HeattendedHollimanElementarySchool,AldrichJuniorHighSchool,andPilgrimHighSchoolinWarwick,RhodeIsland.HereceivedhisB.S.innaturalresourcesfromtheUniversityofRhodeIslandinKingston,RhodeIsland,in1977,andhisM.A.inbiologyfromtheStateUniversityofNewYorkinPlattsburgh,NewYork,in1980.HebeganhisdoctoralstudiesattheUniversityofFloridainthefallof1980.Since1985hehasbeenemployedbytheFloridaDepartmentofEnvironmentalRegulationinTallahassee,Florida.259

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IcertifythatIconformstoacceptableadequate,inscopeandDoctorofPhilosophy.IcertifythatIconformstoacceptableadequate,inscopeandDoctorofPhilosophy.IcertifythatIconformstoacceptableadequate,inscopeandDoctorofPhilosophy.IcertifythatIconformstoacceptableadequate,inscopeandDoctorofPhilosophy.havereadthisstudyandthatinmyopinionitstandardsofscholarlypresentationandisfullyquality,asadissertationforthedegreeofG.RonnieBest,ChairmanAssociateResearchScientistofEnvironmentalEngineeringScienceshavereadthisstudyandthatinmyopinionitstandardsofscholarlypresentationandisfullyquality,asadissertationforthedegreeofKatherineC. Ewel ProfessorofForestResourcesandConservationhavereadthisstudyandthatinmyopinionitstandardsofscholarlypresentationandisfullyquality,asadissertationforthedegreeofAssociateProfessorofSoilSciencehavereadthisstudyandthatinmyopinionitstandardsofscholarlypresentationandisfullyquality,asadissertationforthedegreeofClayMontagueAsciateProfessorofEnvironmentalEngineeringSciencesIcertifythatIconformstoacceptableadequate,inscopeandDoctorofPhilosophy.havereadthisstudyandthatinmyopinionitstandardsofscholarlypresentationandisfullyquality,asadissertationforthedegreeofHoward T.QdumGraduateResearchProfessorofEnvironmentalEngineeringSciences

PAGE 284

Thisdissertation was submittedtotheGraduateFacultyoftheCollegeofEngineeringandtotheGraduateSchoolandwasacceptedaspartialfulfillmentoftherequirmentsforthedegreeofDoctorofPhilosophy.December1989Dean,CollegeofEngineeringDean,GraduateSchool


Nutrient, carbon, and water dynamics of a titi shrub swamp ecosystem in Apalachicola, Florida
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Table of Contents
    Title Page
        Page i
    Acknowledgement
        Page ii
        Page iii
    Table of Contents
        Page iv
        Page v
    List of Tables
        Page vi
        Page vii
        Page viii
        Page ix
    List of Figures
        Page x
        Page xi
    Abstract
        Page xii
        Page xiii
    Introduction
        Page 1
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    Methods
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    Results
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    Discussion
        Page 172
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    Summary and conclusions
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    Appendix
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    Literature Cited
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    Biographical sketch
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    Copyright
        Copyright
Full Text















NUTRIENT, CARBON, AND WATER DYNAMICS OF A
TITI SHRUB SWAMP ECOSYSTEM IN APALACHICOLA, FLORIDA













By

LARRY NEAL SCHWARTZ


A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE
UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE
REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA


1989
















ACKNOWLEDGMENTS


Special appreciation goes to my supervisory committee. Dr. G. R.

Best provided guidance and support throughout this work. Dr. H. T. Odum

greatly influenced my approach and stimulated my interest in evapo-

transpiration. Dr. K. C. Ewel provided focus and much needed editorial

assistance. Dr. D. A. Graetz provided guidance and laboratory support

for the soils work. Dr. C. L. Montague provided many thought-provoking

discussions as well as friendship.

This project was supported by the State of Florida, Department of

Environmental Regulation, project number LR-46, "Low-Energy Wastewater

Recycling through Wetland Ecosystems: Apalachicola Study-Experimental

Use of a Freshwater Shrub Swamp," Principal Investigator G. R. Best.

Numerous persons must be thanked for their participation in

fieldwork, sample processing, data analysis, and manuscript preparation.

Lucinda Sonnenberg, Sheridan Kidd Haack, and Charlotte Pezeshki-Wolfe

did concurrent research at the study site. Jerry Lovell and Dale

Cronwell provided endless field and laboratory assistance. John Higman,

Rob Wolfe, Daryl Joyner, Alfonso Hernandez, Bill Sargent, Peggy

Anderson, and Melvin Rector assisted in fieldwork. Art Watson flew a

"majestic bird" for aerial photography, and John Bossert provided

valuable computer assistance. Ken McMurry and Jon Barbour drafted the

figures, and Linda Crowder and Carol Cox assisted with the manuscript.

Special thanks go to Jenny Carter for typing and retyping this

dissertation and to Pete Wallace, Bill Dunn, and Jim Feiertag for all

ii










their efforts and deep friendship. Special thanks are also extended to

Pierre Walle, Wilbur, Mike McGurk, Rudy, Buzee, Lord Melvin, Pie, and,

of course, Mad Moe.

I would also like to thank my parents. Once again, with their

support and encouragement, I have been able to accomplish my goal.

Finally, I would like to thank my wife, Jamie. Her love and support

have been my greatest asset.



















TABLE OF CONTENTS


Page


ACKNOWLEDGMENTS

LIST OF TABLES

LIST OF FIGURES


. . . . vi


S . . . . . . x


. . xii


ABSTRACT . . . . . . . .

CHAPTERS

1 INTRODUCTION . . . . . . . .


. . . 1


Geology and Physiography . . . .
Vegetation in Titi Shrub Swamps . .
Biomass in Forested Wetlands . . .
Chemistry in Acidic Waters . . .
Phosphorus Adsorption in Soils . .
Wastewater Discharge to Wetlands . .
Evapotranspiration in Forested Wetlands
Freshwater Wetland Models and their Use
Simulating Wastewater Addition


. . . . . 5
. . . . . 10
. . . . . 13
. . . . . 14
. . . . . 20
. . . . . 26
. . . . . 34

. . . . . 38


2 METHODS


Vegetation Analysis . . . .
Biomass and Nutrient Standing Stock
Water Chemistry . . . . .
Soils and Phosphorus Adsorption .
Hydrology . . . . . . .
Precipitation and Runoff .
Groundwater . . . . .
Evapotranspiration . . .
Transpiration . . . .
Model Development and Simulation


Estimates



. . .
- * *


3 RESULTS . . . . . . . . . ..


Vegetation Analysis . . . .
Biomass and Nutrient Standing Stock
Water Chemistry . . . . .
Soils . . . .
Phosphorus Adsorption . . . .
Hydrology . . . . . .
Precipitation and Runoff .
Groundwater . . . . .


. . 67


Estimates


. 67
S79
S93
103
106
119
119
120









Evapotranspiration . . . . .
Water Budget . . . . . . .
Transpiration . . . . . . .
Model Development and Simulation . . .


4 DISCUSSION . . . . . . . . . . . .

Vegetation Analysis . . . . . . . . . .
Biomass and Nutrient Standing Stock Estimates . . . .
Water Chemistry . . . . . . . . . . .
Soils in Titi Shrub Swamps . . . . . . . .
Phosphorus Adsorption . . . . . . . . . .
Hydrology . . . . . . . . . . . . .
Runoff . . . . . . . . . . . .
Evapotranspiration . . . . . . . . .
Water Budget . . . . . . . . . .
Transpiration and Total Water Loss . . . . .
Model Development and Simulation . . . . . . .

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


APPENDICES:


A COMPUTER PROGRAM TO INTEGRATE HOURLY TRANSPIR-
ATION RATES TO OBTAIN A DAILY TRANSPIRATION RATE
(DTR). A SAMPLE OUTPUT IS INCLUDED . . . .

B REGRESSION EQUATIONS USED TO ESTIMATE THE
BIOMASS OF THE TITI SHRUB SWAMP IN APALACHICOLA,
FLORIDA. pbd PRIMARY BRANCH DIAMETER, dbh -
DIAMETER AT BREAST HEIGHT . . . . . .

C ANNUAL WATER BUDGETS FOR 1982-1986 AND FOR THE
WATER BUDGET YEAR (WBY) FOR THE TITI SHRUB SWAMP
STUDY SITE. A KEY TO TERMS IS INCLUDED . . .

D SPREAD SHEETS FOR TRANSPIRATION RUNS. A KEY TO
TERMS IS INCLUDED . . . . . . . .

E BASIC COMPUTER PROGRAM TO SIMULATE THE DISCHARGE
OF WASTEWATER TO THE TITI SHRUB SWAMP . . .

F CALCULATIONS OF THE STORAGE AND FLOWS FOR THE
SIMULATION MODEL OF THE TITI SHRUB SWAMP IN
APALACHICOLA, FLORIDA, PRESENTED IN FIGURE 24 .

LITERATURE CITED . . . . . . . . . . .

BIOGRAPHICAL SKETCH . . . . . . . . . .


172
173
178
182
184
186
187
187
190
190
194

198


. . 202


205


. 207


215


228


243

259


I I I I I I
















LIST OF TABLES


Table Page

1 Chamber volume and number of turnovers per minute in
four studies where metabolism and transpiration were
measured . . . . . . . . . . . . 60

2 The dimension, volume, turnover time (calculated with
model equation) and the airflow that would not limit
metabolism or enhance transpiration, for the three
chambers used in this study ... .. . . . . . 62

3 Characteristics of woody vegetation (>1.3 m high) in a
titi phase of the titi swamp in Apalachicola, Florida . 70

4 Characteristics of woody vegetation (>1.3 m high) in a
holly phase of the titi swamp in Apalachicola, Florida 72

5 Characteristics of woody vegetation (>1.3 m high) in a
mixed swamp phase of the bay swamp in Apalachicola,
Florida . . . . . . . . . . . ... 73

6 Characteristics of woody vegetation (>1.3 m high) in the
black gum swamp in Apalachicola, Florida . . . ... 74

7 Characteristics of woody vegetation (>1.3 m high) in the
titi shrub swamp in Apalachicola, Florida . . . ... .75

8 Importance values for woody vegetation species (>1.3 m
high) in the titi shrub swamp in Apalachicola, Florida.
All species combined regardless of size class . . .. 76

9 Percent ground cover in the four community types in the
titi shrub swamp in Apalachicola, Florida . . . .. 78

10 The dbh, estimated bole, branch, leaf and above ground
biomass for black titi, red titi, and sweetbay sampled
at the study site . . . . .... . . . . 80

11 Aboveground biomass estimate of woody vegetation (>1.3 m
high) in a titi phase of the titi swamp in Apalachicola,
Florida . . . . . . . . . . . . . 82

12 Aboveground biomass estimate of woody vegetation (>1.3 m
high) in a holly phase of the titi swamp in Apalachi-
cola, Florida . . . . . . . . . . . 83










13 Aboveground biomass estimate of woody vegetation (>1.3 m
high) in a mixed swamp phase of the bay swamp in
Apalachicola, Florida . . . . . . . .... 84

14 Aboveground biomass estimate of woody vegetations (>1.3
m high) in the black gum swamp in Apalachicola, Florida 85

15 Herbaceous biomass and litter estimates of the four
community types in the titi shrub swamp in Apalachicola,
Florida . . . . . . . . . . . . . 86

16 Aboveground biomass estimates of the four community
types in the titi shrub swamp in Apalachicola, Florida 87

17 The leaf biomass to area ratio of black titi, red titi,
and sweetbay at two vertical intervals (9 to 12 meters
and 3 to 9 meters) at the study site . . . . .. 89

18 Estimated leaf biomass per ground area (LBGA) of the
woody vegetation (>1.3 m high) in the bay swamp
community . . . . . . . . . . . . 90

19 Leaf litterfall (g/m2) in the four communities in the
titi shrub swamp in Apalachicola, Florida, from May 1982
through April 1983. x mean, s standard deviation,
c.v. = coefficient of variation . . . . . .... 91

20 Total nitrogen and total phosphorus concentrations
(mg/g) of the bole, branch and leaf of black titi, red
titi, and sweetbay sampled at the study site. R mean,
s standard deviation, c.v. coefficient of variation 92

21 Total nitrogen and total phosphorus concentrations
(mg/g) of the herbaceous component, litter component and
leaf litterfall in the four communities in the titi
shrub swamp in Apalachicola, Florida. R mean, s =
standard deviation, c.v. coefficient of variation . . 94

22 Total nitrogen and total phosphorus in the aboveground
biomass in the four communities in the titi shrub swamp
in Apalachicola, Florida . . . . . . . . .95

23 Total nitrogen and total phosphorus in litter and leaf
litterfall in the four communities in the titi shrub
swamp in Apalachicola, Florida . . . . . . .. 96

24 Chemical analysis of precipitation at the titi shrub
swamp in Apalachicola, Florida . . . . . .... 97

25 Chemical analysis of shallow groundwater in the titi
shrub swamp in Apalachicola, Florida . . . . . 98

26 Monthly surface water parameters in the titi shrub swamp
in Apalachicola, Florida .. . . . . . . 100









27 Classification of soils of the titi shrub swamp in
Apalachicola, Florida . . . . . . . . .. 104

28 Characteristics of soils of the titi shrub swamp in
Apalachicola, Florida . . . . . . . . . 105

29 Coefficients of determination (R) between the adsorption
of added phosphorus by study site soils and the
equilibrium phosphorus concentrations (EPC) in solutions
for the Langmuir, Fruendlich, Tempkin, and quadratic
equations . . . . . . . . . . . . 115

30 Phosphorus adsorption maxima of study site soils
calculated by substitution of the equilibrium phosphorus
concentration (EPC) derived from quadratic equation into
different equations . . . ..... . . . . 117

31 Measured soil properties for the study site soils and
the coefficient of determination (R) between these
properties and 1) the adsorption maxima derived by
substitution into the Tempkin equation, and 2) the
phosphorus sorption index . . . . .... . . . 118

32 Average annual precipitation (P), estimated runoff (R),
pan evaporation (PE), potential evapotranspiration
(PET), actual evapotranspiration (AET) and water budget
residual (RES) for the study site from 1982 through 1986
and for the water budget year (WBY) . . . . . .. 121

33 Water depth (m) for three stations with the titi shrub
swamp in Apalachicola, Florida . . . . . . .. 126

34 The vertical distribution of leaf biomass (VDLB) and the
leaf area index (LAI) for black titi and sweetbay in the
bay swamp community . . . .... . . . . 154

35 Daily transpiration rate (DTR), daily transpiration per
leaf area (DTRLA) and daily transpiration rate per
ground area (DTRGA) for eleven transpiration runs ... .155

36 Differential equations for each state variable used in
the simulation model of the titi shrub swamp in
Apalachicola, Florida, presented in Figure 24 ...... 160

37 Initial conditions for the storage for the simulation
model of the titi shrub swamp in Apalachicola, Florida.
Sources for the values are presented in Appendix F . . 161

38 Flow rates for the simulation model of the titi shrub
swamp in Apalachicola, Florida. Sources of the values
are given in Appendix F . . . . .... .. . . 162

39 Standing stock of total phosphorus in aboveground
biomass in Florida cypress forests (Brown 1981), and in
titi shrub swamp communities in Apalachicola, Florida.


viii









The standing stock of total nitrogen in aboveground
biomass in the titi shrub swamp communities are also
presented . . . . .... . . . . . . 177

40 Precipitation (P), potential evapotranspiration (PET),
PET/P ratio, actual evapotranspiration (AET) and AET/PET
ratio for Milton and Tallahassee, Florida, reported by
Dohrenwend (1977) and for Apalachicola calculated in
this study . . . . .. . . . . . . 189

41 Leaf area index (LAI), daily transpiration rate per leaf
area (DTRLA) daily transpiration rate per ground area
(DTRGA), forest floor water loss (FFWL) and total water
loss (TWL) for the dwarf cypress forest, Austin Cary
cypress dome and floodplain forest reported by Brown
(1981) and for the bay swamp community at the study site 191















LIST OF FIGURES


Figure Page

1 Conceptual systems diagram of the titi shrub swamp in
Apalachicola, Florida. W- water, B- biomass, L- litter,
S- soil, N- nitrogen, P- phosphorus, M microbes . . . 4

2 Location of the titi shrub swamp study site in
Apalachicola, Florida . . . . . . . . . . 7

3 The titi shrub swamp study site in Apalachicola,
Florida, including surface water and groundwater
sampling stations. . . .. .. . . . * * 9

4 Map of the vegetation of the titi shrub swamp study site
in Apalachicola, Florida, including surface water
sampling stations . . . .... . . . . . 69

5 Mean total nitrogen (TN) and mean total phosphorus (TP)
concentrations in precipitation (P), surface water (S)
and groundwater (G) at the titi shrub swamp study site
in Apalachicola, Florida. Sources of data are Tables
24, 25, and 26 . . . . . . . . . . 102

6 Phosphorus adsorption isotherms for the mineral soil
(Rutlege Series) at a depth of 0-5 cm. Plots:
regular, Langmuir, Fruendlich and Tempkin . . . .. 108

7 Phosphorus adsorption isotherms for the mineral soil
(Rutlege Series) at a depth of 15-20 cm. Plots:
regular, Langmuir, Fruendlich and Tempkin . . . .. .110

8 Phosphorus adsorption isotherms for the organic soil
(Pamlico Series) at a depth of 0-5 cm. Plots: regular,
Langmuir, Fruendlich and Tempkin . . . . .... 112

9 Phosphorus adsorption isotherms for the organic soil
(Pamlico Series) at a depth of 15-20 cm. Plots:
regular, Langmuir, Fruendlich and Tempkin . . . ... 114

10 Potentiometric surface of the surficial aquifer at the
titi shrub swamp study site in Apalachicola, Florida;
July 30, 1982 (high groundwater) . . . .... . . 123

11 Potentiometric surface of the surficial aquifer at the
titi shrub swamp study site in Apalachicola, Florida;
May 30, 1982 (low groundwater) . . . . . . .125










12 Natural gamma log
of the titi shrub
Florida . . .


of a well located 2.0 miles northeast
swamp study site in Apalachicola,
. . . . . . . . . . 128


13 Transpiration run October 21, 1984 (sweetbay) .

14 Transpiration run November 2, 1984 (black titi)

15 Transpiration run April 21, 1985 (sweetbay) . .

16 Transpiration run October 5, 1985 (sweetbay) .

17 Transpiration run December 14, 1985 (sweetbay)

18 Transpiration run March 3, 1986 (sweetbay) . .

19 Transpiration run April 19, 1986 (sweetbay) . .

20 Transpiration run May 24, 1986 (sweetbay) . .

21 Transpiration run June 28, 1986 (sweetbay) . .

22 Transpiration run August 20, 1986 (sweetbay) .

23 Transpiration run September 14, 1986 (sweetbay)


. . 133

. . . 135

. . 137

. . 139


. . . 143

. . . 145

. . . 147

. . . 149


. 151


. . 153


24 Systems diagram of the simulation model of the titi
shrub swamp in Apalachicola, Florida. W= water, B-
biomass, L- litter, S- soil, N- nitrogen, P- phosphorus 158

25 Material and energy budgets for the titi shrub swamp in
Apalachicola, Florida. Calculation of storage and
flows presented in Appendix F. Storage of water m3/m2,
flow of water m/yr, storage of carbon E4 kcal/m2, flow of
carbon E4 kcal/m2-yr, storage of nitrogen and phosphorus
g/m2, flow of nitrogen and phosphorus g/m2-yr . . ... 166

26 Material and energy budgets for the titi shrub swamp in
Apalachicola, Florida, after 100 years of wastewater
discharge. Calculation of storage and flows presented
in Appendix F. Storage of water m3/m2, flow of water
m/yr, storage of carbon E4 kcal/m2, flow of carbon E4
kcal/m2-yr, storage of nitrogen and phosphorus g/m2, flow
of nitrogen and phosphorus g/m2-yr. Z wastewater . . 168

27 Results of the simulation model of the titi shrub swamp
in Apalachicola, Florida after 100 years of wastewater
discharge. Values are g N/m2, g P/m2 and E4 kcal/m2 for
nitrogen, phosphorus, and carbon, respectively . . .. .171

















Abstract 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


NUTRIENT, CARBON, AND WATER DYNAMICS OF A
TITI SHRUB SWAMP ECOSYSTEM IN APALACHICOLA, FLORIDA

By

LARRY NEAL SCHWARTZ

December 1989

Chairman: G. Ronnie Best
Major Department: Environmental Engineering Sciences

The main components and processes of a titi shrub swamp were

quantified for incorporation into a simulation model to predict their

long-term responses to wastewater discharge. The main components were

vegetation, water, and soil; and the processes were carbon, nitrogen and

phosphorus cycling, and water flow.

Quantification of model compartments indicated that 1) aboveground

biomass is in the low to intermediate range of values cited for forested

wetlands, 2) precipitation is the principal source of water and

nutrients to this system, and 3) relative concentrations of nitrogen and

phosphorus in precipitation, surface water and groundwater indicate that

nutrients are conserved within the system. Therefore, small amounts of

nutrients were cycled within this system, and low nutrient input limited

the simulated productivity.

The simulated response to increased nutrients was an increase in

annual biomass and litter and increased storage of nutrients in biomass,

litter and soil, and the rates of these increases decreased with time.

xii









Wastewater discharged to wetlands with a N:P ratio similar to that

stored in vegetation would maximize the lifetime of the system for

phosphorus assimilation. Therefore, nutrient loading criteria should be

based on maximizing the longevity of the system, which can be estimated

by determination of the phosphorus adsorption capacity of the soil.

Mineral soils dominated by titi had a low capacity for phosphorus

adsorption while organic soils dominated by black gum had a higher

capacity for phosphorus adsorption. The adsorption capacities of these

soils were related to the content and availability of amorphous and

poorly crystalline oxides of aluminum.

Sweetbay had low rates of transpiration per leaf area relative to

other forested wetland species. An increase occurred from the

individual to the community level due to high leaf area index in the bay

swamp. This community transpires at a rate greater than open water

evaporation when water is readily available as indicated by the pan

ratio. There is variability among forested wetland communities and

among seasons and these systems evapotranspire at low rates when water

is scarce and at higher rates when water is readily available.

Therefore, these systems are adapted for water conservation during dry

periods.


xiii


















CHAPTER 1
INTRODUCTION



A need has emerged to include wetlands in the overall strategy of

managing our environment. Wetlands can be used to treat wastewater and

we must determine how to manage these systems for this purpose to the

benefit of nature and humanity. In order to properly manage and

optimize the role of these complex ecosystems in the landscape, we must

understand quantitatively how these systems function.

Due to the increasing amount of domestic wastewater generated

every day, new alternatives for wastewater treatment merit

consideration. The treatment of domestic wastewater in natural wetlands

is one such alternative. Although many kinds of wetlands have been

shown to treat wastewater, the effects of wastewater discharge to

wetlands and their treatment capacity must be evaluated so that the

appropriate loading can be selected that will maintain their type,

nature, and function. Only then can the suitability of using a specific

wetland for wastewater treatment be evaluated. The need has emerged for

reliable design procedures for wetland treatment systems (Hammer 1984).

A simple, tractable model must be developed to predict the long-term

performance of wetland treatment systems. In order to develop such a

model, the main components and processes of wetlands must be quantified.

Prior to 1985, the City of Apalachicola, Florida, discharged

municipal wastewater to the Apalachicola River. The discharge violated










state and federal water quality standards. Discharge of the municipal

wastewater to a nearby titi shrub swamp was suggested as an appropriate

and cost effective treatment alternative. This was in accordance with

section 17-4.243(4) of the Florida Administrative Code, which provides

an exemption from water quality standards to allow the experimental use

of wetlands for low-energy water and wastewater recycling. The

discharger must monitor the long-term ecological effects of wastewater

discharge to the wetland and evaluate the wastewater recycling

efficiency of the wetland. An exemption was granted to the City of

Apalachicola, Florida, for the use of a titi shrub swamp for wastewater

treatment. A research program began at the Center for Wetlands,

University of Florida, to insure compliance with the above stated

provisions of the exemption.

The objectives of this study were to characterize and quantify the

main components and processes of the titi shrub swamp ecosystem in

Apalachicola, Florida, necessary to predict their long-term responses to

wastewater discharge. The main components were vegetation, water and

soil; and the processes were carbon, nitrogen and phosphorus cycling,

and water flow. This information was incorporated into a simulation

model (Figure 1) to predict the long-term responses of these components

and processes to wastewater discharge.

Phosphorus retention in soil has been shown to occur in wetlands

used for wastewater treatment but the capacity for this retention has

not been determined. Therefore, the potential for phosphorus adsorption

in titi shrub swamp soils was a management issue evaluated in this

study. In order to manage wetlands properly, we must quantify their

processes. This includes their rate of evapotranspiration, over which
























Figure 1. Conceptual systems diagram of the titi shrub swamp in Apalachicola, Florida. W=
water, B= biomass, L= litter, S= soil, N= nitrogen, P= phosphorus, M = microbes.















recl ast
nation water
P NN



N N P









~6611 1 Uptak


N #Al
Solar B \// P P
RadiationN



LI





m N









there is great debate. Therefore, the rate of forested wetland plant

evapotranspiration was an additional management issue evaluated in this

study.



Geology and Physiography


The City of Apalachicola is located at the western edge of the Big

Bend region of the state (Figure 2). The titi shrub swamp study site is

located 1 km west of the City of Apalachicola, Florida, and from 1 to 2

km north of St. Vincent Sound (Figure 3). The entire Big Bend region of

Florida is underlain by a bedrock of limestone, which dates back no

later than the early Miocene age (Clewell 1971). Limestone is

encountered beneath the Apalachicola area approximately 40 m below the

surface (Schmidt 1978). Above the limestone lies an assortment of

various Miocene clastics and above them a veneer of Pleistocene sands.

These materials were deposited during ancient sea level fluctuations.

Usually there is a shell bed in a sand and clayey matrix, overlain by a

gravel and coarse sand unit, by a clayey sand, and finally by a medium

fine sand composed of sand, silt and clay, and organic debris. In

addition to peat deposits there are beds of humate along the coast (up

to 1 m thick). The humate is dark brown to black firmly cemented sand

of late Pleistocene to Recent age and was probably formed in an ancient

swamp when sea level was a few feet higher than the present.

The western portion of the Big Bend region lies in the Apalachi-

cola Coastal Lowlands unit of the Gulf Coastal Lowlands Physiographic

Province (Schmidt 1978). These coastal lowlands are low in elevation

due to the reworking by coastal processes and are generally poorly

drained. Much of the land area in this unit is covered by swamp. The







































Location of the titi shrub swamp study site in Apalachicola,
Florida.


Figure 2.



















Franklin County


.. o -. ,o













Study Site





98

. . *. .. o

St. Vincent Sound -. ..

o 1/2 1 ..' oDalachicola


Miles


Bay

























Figure 3. The titi shrub swamp study site in Apalachicola, Florida, including surface
water and groundwater sampling stations.














WHORTLEBERRY










*eE'"GWI^ l Xz PROPOSED POINT OF WASTEWATER DISCHARGE
6 WETLAND














*GW3 GW4 GW5 APALACHICOLA AIRPORT





miles---.....
1 24000
ST. VINCENT'SSOUND


OUADRANGLE PACHICOLA
\P WEASAY










impermeable clastics contain fine grained clay and silt (as indicated

above), which retard water movement. The permeability is low and

groundwater is perched near the surface. This is enhanced by low

relief, making it difficult for surface water to run off.

The swamps occupy irregularly shaped shallow depressions that

mostly do not join to form drainages (Clewell 1971). These depressions

are likely the result of gentle undulations of a former Pleistocene

sea-bottom. These swamps may have been accentuated by more recent

localized slumping of the surface that would slowly form a depression

having a higher water table than the surrounding lands. These

geomorphic features are interlevee swamps, oriented parallel to the

coast, indicating their formation through marine forces (Schmidt 1978).

These types of systems are referred to as bogs and bog-fed streams

by Wharton et al. (1982). The depressions that feed the streams are

areas of internal perched drainage underlain by clay aquicludes.

Surface drainage occurs through slow moving streams originating from

flat swamp areas. These streams have limited distribution and generally

occupy the linear depressions or swales between adjacent sand ridges and

reworked relict coastal lowland deposits.



Vegetation in Titi Shrub Swamps


The vegetation in titi swamps is often undifferentiated into

strata (Clewell 1981). Broad-leaved evergreen or semi-deciduous shrubs

and small trees are dominant, especially one of three species commonly

called titi: Cliftonia monophylla (black titi or buckwheat tree),

Cyrilla racemiflora (red titi or swamp titi) and Cyrilla parviflora

(little-leaf titi). All three species occur in the same habitats,










sometimes individually but often together. Black titi is usually more

abundant than the two species of Cyrilla and tends to occupy slightly

higher sites than red titi (Clewell 1981).

/Infrequent but destructive crown fires occur in titi swamps.

These fires serve a homeostatic function, rejuvenating and perpetuating

the community. The vegetation is rarely greater than 25 m in height.

The taller the vegetation, the lower the frequency of fire, or at least

the longer since the last destructive fire occurred (Clewell 1981).

Titi swamps border pine flatwoods (which frequently burn) and only

burn at their fringe, serving as a fire buffer for bay swamps (Clewell

1971). Groundwater seldom fluctuates far below the surface in titi

swamps (Wharton et al. 1977). Occasionally titi swamps border pond

cypress or black gum swamps, protecting these areas from fire as well

(Clewell 1971). Irregular fires destroy the aerial portion of the

vegetation in titi swamps, and coppicing after fire is very common,

leading to multiple trunks (Clewell 1981). In discussing the

distribution of the three species of titi, Clewell (1981) stated that

they do not segregate according to subtle gradients in the habitat.

Their distribution appears random, as if once a titi plant, regardless

of species, by chance becomes established at a given location, it

persists indefinitely, surviving fire by coppicing and regenerating the

stand without intervening successional stages.

Titi swamps grade imperceptibly into bay swamps (Clewell 1981).

Bay swamps occupy those portions of acid swamps that are wetter and less

frequently burned than titi swamps (Clewell 1981). The dominants of

titi swamps often make up the understory of bay swamps, and when a fire










does consume a bay swamp, the understory species such as black titi

appear to grow faster than do the overstory species such as sweetbay

(Clewell 1971). As a result, the site becomes a titi swamp for perhaps

10 to 25 yrs, until the overstory of sweetbay trees forms (Clewell

1971). It was suggested by Clewell (1971) that titi swamps, therefore,

seem to be successional to bay swamps. Monk and Brown (1965) also

suggested that bay swamps are climax communities.

Pond cypress and black gum occupy the deepest swamps in the

panhandle, and few species are present in any given stand (Clewell

1971). The understory species of pond cypress/black gum swamps, such as

titi, usually dominate other communities of acid swamp systems (Clewell

1981). Also, fire is rare. These swamps have been widely drained,

lowering the water table and allowing invasion of other acid swamp

species. These swamps usually occupy peaty acid depressions in the

deeper interior sites, and bay swamps occupy the shallower exterior

sites. Intergradations sometimes occur, particularly between pond

cypress swamps and bay swamps. Pond cypress/black gum swamps can also

intergrade with bay swamps along the upper reaches of streams. Black

gum swamps, which are also referred to as gum ponds, are usually

bordered by pond cypress swamps, which occupy slightly higher

elevations.

Clewell (1971) raised the possibility that black gum is

successional to pond cypress or vice versa. Black gum consistently

occupies the lowest and wettest sites and these areas are bordered by

pond cypress at slightly higher elevations. Monk and Brown (1965) also

found that black gum importance increased sharply and pond cypress

importance decreased sharply with decreasing depth of maximum flooding.








13

In addition, with increasing levels of calcium, the importance of black

gum increased sharply and that of pond cypress decreased sharply (Monk

and Brown 1965). Initially pond cypress is favored in the lower sites,

which are surrounded by bay swamps, which, when surrounded by titi

swamps, burn infrequently (Clewell 1971). Peat formation is relatively

rapid, and calcium released from peat decomposition promotes the

establishment of black gum over pond cypress (Clewell 1971). Swamps

that contain a large proportion of black gum and particularly pond

cypress may represent transitional phases between a pond cypress/black

gum system and an acid swamp system or, as suggested by Clewell (1981),

may be included as a distinct and important part of the acid swamp

system.



Biomass in Forested Wetlands


Forested wetlands may be grouped into three categories based on

water movement and differences in nutrient inputs: still-water wetlands,

slow-flowing water wetlands, and flowing water wetlands (Brown 1981).

Still-water wetlands receive nutrients and water predominantly from

precipitation. Slow-flowing wetlands receive water and nutrients from

groundwater and surface water runoff. Flowing water wetlands receive

water and nutrients from flooding streams.

The aboveground biomass of forested wetlands ranges from 3.6 kg/m2

for a dwarf cypress forest to 45.2 kg/m2 for a cypress tupelo alluvial

river swamp (Brown 1981; Conner and Day 1982). Large biomass exists in

both still-water and flowing water wetlands. Small biomass in the dwarf

cypress forest appears to be due to nutrient limitations or other

stressors rather than the pattern of water delivery. However, the major









source of water is precipitation, and floodwaters tend to be stagnant

and generally shallow (Brown and Lugo 1982). There is a relationship

between productivity and hydrologic and nutrient sources. Wood

production and litterfall are highest in flowing water wetlands, less in

slow-flowing wetlands, and lowest in still-water wetlands (Brinson et

al. 1981; Brown and Lugo 1982).

The leaf litterfall portion of total litterfall has been reported

for only a few freshwater forested wetland sites. In the Dismal Swamp

the average leaf litterfall for cypress and mixed hardwood species is

492 g/m2 yr, with the peak in the autumn (Day 1983). Average

litterfall for 2 yrs in Austin Cary cypress dome was 420 g/m2 yr

(Deghi et al. 1980). The peak litterfall period was in November and

December. Leaf litterfall for the floodplain forest of the Apalachicola

River was 464 g/m2 yr (Elder and Cairns 1982). Seasonal variability

in leaf litterfall was observed. Maximum leaf litterfall occurred in

November and other high values occurred in autumn months. Maximum leaf

litterfall may occur in the spring in association with the development

of new leaves (Bray and Gorham 1964). This bimodal seasonal cycle for

leaf litterfall (autumn and spring peak) was also found in a Mississippi

coastal stream (Post and de la Cruz 1977).



Chemistry in Acidic Waters


Most natural waters are buffered principally by a carbon

dioxide-bicarbonate system. By observing the equilibrium chemistry

(dissociation relationships) of a system, the proportions of carbonic

acid (plus dissolved carbon dioxide), bicarbonate, and carbonate at

various pH values can be evaluated in order to determine what buffers










the system. Because of the ubiquitous nature of carbonate rocks and

the equilibrium reactions of carbon dioxide, bicarbonate and carbonate

are present as bases in most natural waters (Stumm and Morgan 1981), but

all waters with a pH less than 8.5 contain acidity (Sawyer and McCarty

1978). Uncombined carbon dioxide, organic acids (such as tannic or

fulvic), and salts of strong acids are responsible for the acidity of

natural waters (Wetzel 1975). In waters with a pH below 5, carbonic

acid (plus dissolved carbon dioxide) dominates the carbonate equilibria

(Wetzel 1975), but depression of pH below 4.5 is due to mineral acidity

which is exhibited by waters containing acids stronger than carbonic

acid (Stumm and Morgan 1981). At a pH of 3 to 4.5, carbonate and

bicarbonate are not buffering the water; rather, organic acids are the

buffer (Thurman 1985).

The proportions of carbonate in surface waters come from the

weathering of rocks, and the solubility of carbon dioxide in water

increases markedly in water that contains carbonate (Wetzel 1975). If

surface waters are isolated from the carbonate rich Floridan Aquifer

(Fernald and Patton 1984), then there is probably very little free

carbon dioxide present in those surface waters. Conductivity is a

useful indicator of whether the water entering a peatland is primarily

from precipitation and shallow mineral soil inflow (and therefore not in

contact with carbonate containing parent material) or groundwater (Verry

1975). Values less than 80 pmhos/cm indicate a perched water table.

Values greater than 80 pmhos/cm indicate a groundwater table.

The carbonate equilibria for Austin Cary cypress dome (mean pH =

4.5) was examined by Dierberg (1980). Only trace amounts of bicarbonate

existed in the water as there was no titratable alkalinity. Therefore,










it is appropriate to measure phenolphthalein acidity rather than

alkalinity in acidic waters. Phenolphthalein acidity is a measure of

the free (or uncombined) carbon dioxide and the mineral acidity present

in the surface water (Sawyer and McCarty 1978). Highly colored natural

surface waters typically have low pH due to the acidic nature of humic

substances that are present. The color is principally due to tannins,

humic acid, humates, and the decomposition of lignins (Sawyer and

McCarty 1978), but color in surface waters in Florida streams and canals

may be of organic or mineral origin (Kaufman 1975b). The inorganic

sources are metallic substances such as iron and manganese compounds

(Christman et al. 1967).

Low pH values are found in natural waters rich in dissolved

organic matter, especially in systems that contain large amounts of

sphagnum (Wetzel 1975). In wetlands, dissolved organic matter usually

exceeds dissolved inorganic matter, which is not the usual case in

surface waters (Thurman 1985). The most likely major sources of

hydrogen ions in these waters are the dissociation of H2SO4 derived from

H2S (Gorham 1956) and the active cation exchange in the cell walls of

sphagnum where the release of hydrogen ions occurs (Clymo 1964).

Hydrogen ions are also produced by organic decomposition (Clymo 1967).

/ Increases in acidity occur whenever the production of organic

matter is greater than decomposition, as in peat systems (Stumm and

Morgan 1981). This is because the assimilation of ammonium produces

hydrogen ions. The chemical nature of the plant tissues forming the

peat humicc acids) tends to make this peat material acid, and the most

acid peats are those formed from swamp plants and sphagnum moss (Davis










1946). In addition, the poor buffering capacity of precipitation

reaching a wetland can further lower the pH (Thurman 1985).

Information on nitrogen transformations in acidic, highly organic

flooded soils is limited, and these processes may occur in unique ways

(Haack 1984). Compounds found in naturally occurring humic-colored

waters reduce dissolved oxygen levels and, therefore, these waters act

as a sink for dissolved oxygen (Dierberg 1980). Low dissolved oxygen

can lead to anaerobic conditions where net ammonification (the release

of ammonium during microbial decomposition of organic matter) is often

noted (Tusneem and Patrick 1971). In addition, low pH as well as the

presence of organic compounds inhibit the nitrification of ammonium to

nitrate (Dierberg 1980). Therefore, low dissolved oxygen, low pH and

the presence of organic compounds contribute to the dominance of

ammonium rather than nitrate plus nitrite in these waters. Through the

inhibition of nitrification, ammonium becomes the dominant inorganic

nitrogen species, and this leads to conservation of nitrogen in the

system (Dierberg 1980).

Nitrate plus nitrite concentrations may also be low in these

waters due to rapid plant uptake and denitrification, although

denitrification is inhibited at low pH (Mitchell 1974; Brezonik 1977).

Nitrate was added to jar and core microcosms composed of water and soil

from the titi shrub swamp in Apalachicola, Florida (Haack 1984).

Nitrate loss did occur in both the jar and core microcosms but sediment

was necessary for the nitrate loss. No mechanism for nitrate loss was

substantiated, although it may be due to denitrification, which occurs

in wetlands. Chemical reduction of nitrate at low pH may occur through

several pathways. Wetlands with low pH, high organic matter, and humic










compounds have pathways of nitrate loss other than biological

denitrification (Haack 1984). Under highly reduced conditions, nitrate

reduction to ammonium and organic nitrogen is possible (Buresh and

Patrick 1978). These processes would also account for the dominance of

ammonium in these waters.

The shallow surface water in cypress domes and hence the close

proximity of soil and water suggests that the phosphorus content of the

surface water may be controlled by the interaction of phosphorus with

the soil (Dierberg 1980). Soil/phosphorus reactions are complex. In

general, the inorganic phosphorus is partitioned between the solution

phase (small fraction of total system phosphorus) and the solid phase (a

larger portion of total system phosphorus). The chemical species of

solution phosphorus are a function of the reactions of protonation and

soluble metallic complex ion formation (Bohn et al. 1979). At low pH,

iron and aluminum ions on solid (soil) surfaces form bonds with solution

species (Stumm and Morgan 1981). The resulting precipitate removes

phosphorus from the water column. The oxygen content of the water and

soil also affects the amount of phosphorus in solution as phosphorus

becomes more soluble under reduced anaerobic conditions (Stumm and

Morgan 1981). Therefore, soluble metallic ion complex formation

(phosphate and hydrous oxides of iron and aluminum) plays a great role

in controlling phosphorus levels in natural waters.

SThe limit for the phosphorus concentration in solution is set by

the dissolution and precipitation of these sparingly soluble phosphorus

compounds and the adsorption of phosphorus on the surface of soil

particles. In general the overall solubility of these metal phosphate

complexes is inversely related to pH while adsorption and precipitation










of phosphorus are directly related to pH (Stumm and Morgan 1981).

Therefore, the lower the pH the greater the solubility of the metal

phosphate complexes and the greater the adsorption and precipitation of

phosphorus in the soil. Removal of phosphates from solution can also be

linked to pH because of the dependency of the reactions upon soil

aluminum (Dubuc et al. 1986). At a low pH in cypress domes studied by

Dierberg (1980) aluminum rather than iron controlled phosphorus

solubility. In addition, at a pH less than 6, organic phosphorus

precipitates as a complex with iron and aluminum (Dubuc et al. 1986).

Solubilization of the sparingly soluble compounds can also occur

due to the production of organic acids. These organic acids exist in

water as negatively charged colloids that hold metallic ions such as

iron and aluminum (Kaufman 1975b). The sorption of phosphate by these

organometallic complexes occurs but the dynamics of the transformations

are still unclear. Phosphate can react with metal ions to form

complexes in the presence of organic ligands such as fulvic and humic

acids (Boto and Patrick 1978). Phosphate ions may be acting as ligands

in organometallic compounds (Sinha 1971). In either case the retention

is a function of pH.

Biological immobilization of phosphorus also occurs in wetlands

(Chan et al. 1982). Wetland trees assimilate phosphorus (Brown et al."

1975; Nessel et al. 1982; Dierberg and Brezonik 1983b). In addition

high cation exchange capacity exhibited by peat can lead to the

absorption of phosphate anions (Moore and Bellamy 1974). Therefore, it

appears that through biological and chemical processes in wetlands, low

levels of phosphorus are maintained in surface waters.










Phosphorus Adsorption in Soils


Phosphorus retention by soils may be an advantage of using

wetlands as an alternative for wastewater treatment. Therefore,

emphasis has been placed on using adsorption isotherms in order to

predict soil types that would be amenable to receiving wastewater

(Sommers and Sutton 1980).

A phosphorus adsorption isotherm describes the relationship

between the amount of phosphorus sorbed and that remaining in solution

at constant temperature. Several equations developed for gas-solid

systems have been used to interpret the sorption of phosphate on charged

surfaces. The adsorption data are fit to isotherms described by the

equations. The isotherms can be used to give a relative adsorption

maximum, interpreted as a "quantity" factor, indicating the capacity of

the soil to adsorb and thus retain phosphorus.

The Langmuir equation is based on the assumptions that adsorption

is on a finite number of localized sites, the energy of adsorption is

constant, and maximum adsorption corresponds to a complete monolayer.

Thus the equation describes a finite limit to adsorption so that a

maximum value may be obtained. The Langmuir equation is described as

follows:


x/m = KCb/(l + KC)


where K is a constant related to the adsorption energy, C is the

equilibrium phosphorus concentration (pg/ml), and x/m and b are

phosphorus adsorbed and maximum phosphorus adsorption per unit weight of

soil (Ag/g), respectively. In the linear form the equation becomes:










Cm/x (C/b) + (1/Kb)


and a plot of Cm/x versus C should give a straight line of slope 1/b

from which b, the adsorption maximum can be calculated.

Straight line isotherms have been obtained when results from a

limited concentration range are plotted according to the Langmuir

equation (Olsen and Watanabe 1957). Although the Langmuir equation in

its linear form has been used frequently in phosphorus adsorption

studies the adsorption curves may not be linear over a wide

concentration range (Olsen and Watanabe 1957; Rennie and Mekecher 1959;

Gurney 1970; Bache and Williams 1971; Fitter and Sutton 1975). There

are many possible explanations for the nonlinearity, but where it does

occur the Fruendlich and other equations may be used to fit the

adsorption data.

The Fruendlich equation is based on the assumption that the

surface consists of sites at which the adsorbate molecules interact

laterally, resulting in a continuous distribution of bonding energies

that decrease exponentially with increasing saturation of the surface.

The Fruendlich equation can be described as follows:


x/m = aCb


where x/m and C are as before and a and b are constants that vary among

soils. In the linear form the equation becomes:


log x/m = log a + b log C


and a plot of log x/m versus log C should give a straight line. The

Fruendlich equation has been found to give a good fit over a wide range








22
of soils and concentrations (Gurney 1970; Fitter and Sutton 1975; Barrow

and Shaw 1975; Barrow 1978).

The Tempkin equation is derived from the Langmuir equation but,

like the Fruendlich equation, is based on the assumption of a continuous

distribution of bonding energies. In this case the energy of adsorption

decreases linearly with increasing surface coverage. The Tempkin

equation can be described as follows:


xb/m (RT/B) log AC


where x, b, and C are as before and A and B are constants. A plot of

x/m versus log C should give a straight line.

The phosphorus adsorption maxima of soils can be calculated from

the slope of the regression lines according to the Langmuir equation.

The Fruendlich equation does not have this characteristic and therefore

a quadratic regression analysis of the adsorption data developed by Yuan

and Lucas (1982) can be used as an alternative to obtain the adsorption

maxima. If Y is the phosphorus adsorbed and X the equilibrium

phosphorus concentration, then the quadratic equation is as follows:


Y ao + a1X + a2X2


and the first derivative of this equation is equal to zero when Y

reaches the maximum, or


dY/dX ai + 2a2X 0.


Therefore the phosphorus concentration (C) at the adsorption maximum

would be


C X -al/2a2.








23
The adsorption maximum is obtained by substituting -a1/2a2 for X in the

quadratic equation. If this equilibrium phosphorus concentration and

the corresponding adsorption maximum derived from the quadratic equation

are correct, then substitution of the C values in the other equations

should give comparative adsorption maxima (Yuan and Lucas 1982).

There has been a good deal of research on the nature of phosphorus

adsorption in soils, and there has been debate as to whether or not

organic matter increases phosphorus adsorption. A number of researchers

reported a decrease in phosphorus adsorption by soils in the presence of

organic matter, the decomposition of which produces organic acids that

form stable complexes with aluminum and iron and consequently block

phosphorus retention (Singh and Jones 1976). Other workers reported

that organic matter increases phosphorus retention by the soil, possibly

as a result of microbial assimilation. Adsorption and leaching of

phosphorus in acid organic soils and high organic matter sand was

determined by Fox and Kamprath (1971). These soils in which the

colloids were organic had relatively low phosphorus adsorption

capacities relative to mineral soils. Phosphorus adsorption by organic

matter was negligible because any adsorption that occurred was due to

the cations associated with organic matter (Wild 1950). Organic soils

with only a trace of inorganic minerals have little aluminum or iron to

be released for bounding with added phosphorus. Thus, although the

influence of organic matter on phosphorus adsorption has been debated,

organic matter appears to affect phosphorus adsorption in an indirect

manner (Berkheiser et al. 1980).

Soluble inorganic phosphorus is readily immobilized in soils by

adsorption and precipitation reactions with aluminum and iron under acid










conditions (Nur and Bates 1979; Nichols 1983). Low phosphorus

adsorption has been observed in sandy soils with low clay content and is

primarily correlated with low content of extractable iron and aluminum

(Ballard and Fiskell 1974; Yuan and Lucas 1982). Layer silicate

minerals have low phosphorus fixing potential but amorphous colloids and

sesquioxides are effective at fixing phosphorus. The less crystalline

the form of the sesquioxides, the greater their capacity to sorb

phosphorus. Phosphate ions are thought to be chemically adsorbed onto

the surfaces of hydrous oxides of iron and aluminum by ligand exchange,

the displacement of water molecules and hydroxyl groups coordinated with

the iron and aluminum atoms and the coordination of oxygen atoms in the

phosphate ions with the iron and aluminum (Nichols 1983). In addition

to this chemical adsorption, Ryden and Syers (1977) presented evidence

for a more physical type of adsorption that becomes operational as the

chemical adsorption sites approach saturation at higher equilibrium

concentrations of phosphorus in solution (Nichols 1983).

The chemical and physical adsorption of phosphate onto the surface

of soil minerals is a rapid process, but slower phosphate fixation does

occur and has been attributed to the shift of physically adsorbed

phosphorus to chemically adsorbed forms, the diffusion of phosphorus

adsorbed on the surface of porous oxides of aluminum and iron to

positions inside the soil matrix, and the precipitation of crystalline

aluminum and iron phosphates (Nichols 1983). The exact mechanisms

involved in phosphorus retention in the soil are unknown. There are

continuum of reaction mechanisms and there is little concern for

distinguishing between adsorption and precipitation reactions as both

phenomena can be considered together as sorption (Berkheiser et al.










1980). Adsorption and precipitation of phosphorus by soils are not

necessarily a permanent sink for added phosphorus; there are at least

partially reversible. A reduction in the phosphorus concentration in

the solution in contact with the soil may release some phosphorus into

solution (Nichols 1983).

Effort has been directed towards identifying measurable soil

parameters that can be related to the phosphorus adsorption capacity of

a soil. The active (exchangeable + amorphous) forms of aluminum provide

the best single index of phosphorus retention in Coastal Plain forest

soils (Ballard and Fiskell 1974). The contribution of active forms of

iron to phosphorus retention was at least the equal of aluminum on a per

unit weight basis. Poorly crystalline and amorphous oxides and

hydroxides of aluminum and iron were postulated to play a primary role

in phosphorus retention in flooded soils (Khalid et al. 1977). An

organic matter aluminum peat complex in acid soils strongly adsorbed

orthophosphate ions (Bloom 1981). Phosphorus adsorption was highly

correlated with organic matter content and exchangeable aluminum content

in a study that evaluated the phosphorus retention capacity of

retention-detention wetland soils (Sompongse 1982). She proposed, in

light of Bloom's (1981) findings, retention through an organic aluminum

complex in the soils with high aluminum content. In soils with high

iron content, iron seemed to play an important role in phosphorus

retention.

Tamm oxalate extractable aluminum and in some cases Tamm oxalate

extractable iron have the best correlation with phosphorus sorption in

mineral soils (Lopez-Hernandez and Burnham 1974; Ballard and Fiskell

1974). Similar results were found in some wetland organic soils








26

(Richardson 1985). The Tamm oxalate extraction dissolves the amorphous

and poorly crystalline oxides of aluminum and iron that have been

postulated to play a primary role in phosphorus retention in flooded

soils.



Wastewater Discharge to Wetlands


Wetlands are often viewed as highly dynamic and adaptable

ecosystems. Nutrient transformation processes may enable some wetlands

to assimilate and store increased levels of nutrients and other

contaminants from wastewater (USEPA 1983). Many wetlands have been

shown to process wastewater efficiently (Whigham 1982), tolerating

anoxic conditions associated with BOD removal and eutrophication, and to

remove nutrients from wastewater effectively (Ewel et al. 1982). In

nearly all instances, wetlands renovate or improve water quality to some

extent, but pollutant removal efficiencies are extremely variable (Chan

et al. 1982).

There is great promise for the use of some wetland ecosystems as

an effective medium of wastewater organic carbon removal (Khalid et al.

1982). The components remaining in wastewater that will exert oxygen

demand, measured as BOD, are very effectively removed in wetland systems

by the microbial flora (Kadlec and Tilton 1979). Optimal BOD removal is

correlated with high surface area available for microbial growth, and

shallow vegetated wetlands maximize this removal capability (Chan et al.

1982). BOD removal in natural wetlands ranges from 70% to 96%

(Tchobanoglous and Gulp 1980).

Wetlands may also provide a high degree of removal of suspended

solids that originate in wastewater (Kadlec and Tilton 1979). Long








27

detention times and thick vegetation filter suspended solids. Removal

ranges from 60% to 90% in wetlands (Tchobanoglous and Gulp 1980).

Pathogens (bacteria and viruses) in wastewater are reduced by any

processes that promote sedimentation or filtration and increase

detention time (Chan et al. 1982; USEPA 1983). Thus, large, shallow,

non-channelized wetlands encourage die-off of microbes (Chan et al.

1982). Kadlec (1981) reviewed studies that documented the introduction

of significantly elevated levels of fecal coliforms into wetlands. The

levels of fecal coliforms were reduced with passage of wastewater

through these wetlands.

It has been amply demonstrated that some wetlands are capable of

removing nitrogen and phosphorus compounds via a variety of mechanisms

(Kadlec and Tilton 1979). Whereas nitrogen processing is largely

biologically mediated, redistribution of phosphorus to internal sinks is

a result of adsorption/precipitation reactions (Ewel et al. 1982).

Adsorption and precipitation by soils are not necessarily permanent

sinks for wastewater phosphorus, as these processes are at least

partially reversible (Richardson and Nichols 1985). Therefore, some

wetlands may eventually lose their ability to immobilize large

quantities of phosphorus, but may retain their ability to immobilize or

dissipate large quantities of nitrogen (Kadlec and Kadlec 1979).

Wetland removal efficiencies for total nitrogen and total phosphorus are

variable, ranging from 10% to 90% (Richardson 1985).

The capacity for nitrogen removal in wetlands is large (Chan et

al. 1982); processes include volatilization, plant uptake, soil uptake,

microbial uptake, sedimentation, nitrification, and denitrification.










The major mechanism for removing nitrogen from wastewater applied to

wetlands seems to be denitrification (Sloey et al. 1978; Kadlec and

Tilton 1979; Nichols 1983), but Richardson and Nichols (1985) suggest

that the disappearance of nitrogen from acid organic soils may be due as

much to the chemical breakdown of nitrite as to denitrification.

Because the phosphorus cycle has no gaseous phase., less phosphorus

is removed from wastewater added to wetlands, although high, short-term

removal efficiencies have been observed (Nichols 1983)..... The magnitude

of phosphorus retention capacity varies considerably among wetland types

(Richardson and Nichols 1985; Kelly and Harwell 1985). Successful

phosphorus immobilization by wetland soils is related to contact time

with organic matter (Kadlec and Tilton 1979), but the quantity of

phosphorus adsorbed depends on the exchange equilibrium with the

dissolved phase (Kadlec 1987). Plant uptake is generally less important

than soil adsorption/precipitation reactions for retaining phosphorus in

wetland ecosystems (Ewel et al. 1982), but the best possibilities for

using wetland plants for nutrient removal appear to occur when the

nutrients are stored in woody plants (Ewel and Odum 1978).

Flow through a wetland in northern Canada reduced orthophosphate

by more than 95% (Hartland-Rowe and Wright 1975). A similar reduction

of phosphorus occurred in a northern peatland receiving sewage

(Richardson et al. 1976). Greater exports of phosphate from channelized

as compared with natural Coastal Plain streams occurred as a result of a

reduction in the soil's capacity to assimilate phosphate (Kuenzler et

al. 1977). Most of the phosphorus added to surface water accumulated in

the sediments in an alluvial swamp forest in the North Carolina Coastal

Plain (Holmes 1977). The floodplain of a small Coastal Plain stream in










North Carolina was a sink for phosphorus (Yarbro 1979). In the Santee

River Swamp, phosphorus was adsorbed or deposited as sediments as water

coursed through the floodplain from the river (Kitchens et al. 1975).

Phosphorus accumulated in the floodplain of a tupelo swamp in southern

Illinois (Mitsch et al. 1979).

In Wildwood, Florida, secondarily treated wastewater has been

released for over 20 yrs into a series of three wetlands. The wetland

that directly receives the wastewater is dominated by Typha latifolia

(cattail) and Salix sp. (willow). This marsh is covered by Lemna sp.

(duckweed). The discharge from this wetland flows through a ditch to a

mixed hardwood swamp dominated by Fraxinus profunda (ash), Taxodium

distichum (bald cypress), and Nyssa biflora (black gum). The discharge

from this wetland flows through another ditch to a much larger mixed

hardwood swamp with similar species composition.

The first two wetlands receive higher nutrient loadings than the

third wetland (Brown et al. 1975). After flowing through the wetlands,

the concentration of nutrients in the water was reduced to values equal

to or less than those found in a control swamp (Boyt et al. 1977).

Reductions in terms of mass loading'were calculated to be 87% for

phosphorus. No visible stress or damage to the natural system was

evident ..- Dilution rather than chemical or biological processes played

the key role in reducing nutrient and organic loads. No buildup of

nutrients in sediments was indicated. Tree borings showed significant

increases in tree growth for a 19-yr period as compared to the pre-

vious 19-yr period. Therefore, trees did play an active role in

removing nutrients (Brown et al. 1975). In addition, the number of










fecal coliforms declined to background levels within 1 km of the point

of wastewater discharge to the wetland (Boyt et al. 1977).

A cypress strand in Waldo, Florida, dominated by Taxodium

ascendens (pond cypress), black gum, and Acer rubrum (red maple) has

been receiving wastewater since 1934 from overflow of a community septic

tank. This wetland reduced nutrient concentrations to background levels

due to phosphorus retention in the sediments (Nessel 1978). Total

phosphrus concentrations were reduced by 51% in surface waters leaving

this cypress strand and 77% after passing through the soil profile into

shallow groundwater (Nessel 1978). Infiltration was a major route for

water leaving this system. This facilitates phosphorus removal and

explains the long-term effectiveness of this wetland in terms of

phosphorus assimilation (Richardson and Davis 1987). Pond cypress tree

growth was stimulated and increased nutrient concentrations in wood and

foliage were recorded (Nessel et al. 1982), but this represented only 1%

of the estimated phosphorus inflow to the system (Nessel and Bayley

1984). Bacteria had low survival rates; 99% reduction was achieved in

32 days for the viruses tested (Butner and Bitton 1982).

Another cypress strand, Basin Swamp, in Jasper, Florida, has been

receiving raw wastewater or primary or secondarily treated wastewater

since 1914 (Tuschall et al. 1981). Total nitrogen and phosphorus

concentrations in the surface water were effectively reduced by 69% and

36%, respectively, between the inflow and outflow of the swamp. A

portion of the reduction was attributed to dilution by surface runoff

into the swamp. Discharge of raw and primary wastewater in the swamp

decreased growth rates in pond cypress; however, discharge of

secondarily treated wastewater enhanced growth over controls (Lemlich










and Ewel 1984). The rate of fecal coliform export depended on the

detention time of the strand (Brezonik et al. 1981). Based on their

findings at the Jasper site, Fritz and Helle (1981) indicated that the

use of a flow-through wetland system for additional treatment of

secondarily treated wastewater is a workable and economical alternative

to conventional physical-chemical treatment methods.

Most of the wastewater from the Walt Disney World Complex has been

discharged into a mixed hardwood swamp since 1977. The site is

dominated by red maple, black gum, bald cypress, and Pinus elliottii

(slash pine). This wetland was isolated by berms and the discharge,

which ultimately reaches Reedy Creek, was artificially controlled. This

was the largest full-scale forested wetland effluent discharge system

that has been extensively monitored in the U.S. (Knight et al. 1987).

The long-term average removal rate was 75% for BOD and 80% for suspended

solids. Total nitrogen concentration was reduced 88% but no total

phosphorus reduction was observed (Kohl and McKim 1981). A net release

of phosphorus from this system occurred, probably because the retention

capacity of the swamp had become saturated (McKim 1982). Removal

efficiency depended on input concentration as lower removal efficiencies

resulted from lower input concentrations over the range of values

observed (Knight et al. 1987).

Pottsburg Creek Swamp, a mixed hardwood swamp in Jacksonville,

Florida, has been receiving secondarily treated wastewater since 1967.

This wetland is vegetated by a mixture of species including ash, red

maple, black gum, pond cypress and Liquidambar stvraciflua (sweetgum).

Based on mass balance calculations, total nitrogen loadings were reduced

by 87% and total phosphorus loadings by 62% (Winchester and Emenhiser










1983). There were no net concentrating or diluting effects and,

therefore, nutrient reduction was due to infiltration within the swamp.

Cypress domes are a common type of swamp in Florida. These

forested wetlands are dominated by pond cypress and often have large

numbers of black gum. The term "dome" comes from the characteristic

profile of these wetlands, because the trees are taller in the center

and decrease in size toward the edges. A study of the use of cypress

domes for the advanced treatment of domestic wastewater was conducted

from 1975 to 1979.

Biochemical oxygen demand was not substantially reduced as the

wastewater traveled from the center to the edge of the domes (Dierberg

and Brezonik 1978). In contrast to this, the concentrations of

nutrients were generally lower in the surface waters at the edges of

domes receiving wastewater than at the center, but the overall reduction

of nutrient concentrations in the surface waters was less than 33%

(Dierberg and Brezonik 1983a). Infiltration of secondarily treated

effluent through organic sediments lining the basins of the cypress

domes reduced nitrogen and phosphorus concentrations to background

levels (Dierberg and Brezonik 1983a).

:',-Eighty seven percent of the total nitrogen entering the system was

stored in peat, roots, and wood, or was released to the atmosphere by

denitrification, and approximately 92% of the phosphorus entering the

system was removed by plant uptake or sediment deposition (Dierberg and

Brezonik 1983b). Based on leaching studies using laboratory columns,

organic soils in the domes have a large phosphorus adsorption capability

(Dierberg 1980) and this removal capability could continue for a long

time (Dierberg and Brezonik 1983a). The cypress trees accounted for










storage of 24% of the estimated nitrogen inflow but only 1% of the

estimated phosphorus inflow to the system (Dierberg and Brezonik 1984).

After 5.5 yrs of wastewater disposal, the understory vegetation

and existing trees showed no detrimental effects (Ewel et al. 1981).

The most striking response of understory vegetation was the development

and persistence of a thick layer of duckweed over the entire surface of

the domes receiving wastewater (Ewel 1984). Initially, it was reported

that tree growth rates were unaffected (Ewel et al. 1981), but further

investigation indicated that cypress trees grew faster under the

influence of sewage effluent and that the response was almost immediate

(Brown and van Peer 1989). The number of fecal coliforms (Fox et al.

1984) and viruses (Scheuerman 1978) were reduced during infiltration of

surface water to the shallow groundwater aquifer. Binding of viruses

may not be permanent (Scheuerman 1978) and the dome substrate may not be

a perfect filter (Wellings et al. 1975). In summary, the cypress domes

studied and their associated sediments can reduce the levels of major

wastewater constituents to levels comparable to those of conventional

tertiary treatment processes (Dierberg and Brezonik 1983b) and can thus

serve as a natural tertiary treatment system (Dierberg and Brezonik

1983a).

Results from these studies are difficult to generalize

quantitatively. However, some qualitative conclusions about wetland

transformation and assimilation of different forms of nitrogen and

phosphorus can be reached (Richardson and Davis 1987). First, nitrogen

removal from water was consistent and substantial over a range of

loading rates. Removal efficiency was generally 75% or more on a mass

loading basis. Soils provided a finite and reversible sink for ammonium








34

and phosphorus, and retention capacity depended on a complex of factors.

In contrast to nitrogen removal, efficiency of phosphorus removal varied

greatly. Natural wetlands can process significant amounts of nitrogen,

and can be managed to assimilate even more (Richardson and Davis 1987).

Phosphorus retention is highly variable and highly dependent on the

characteristics of the wetland ecosystem involved and the loading rates.

Wetlands differ in their ability to store and release nutrients.

Some types of wetlands dominated by woody plants (swamps) may be capable

of assimilating excess nutrients through microbial processes and

long-term storage in the soil and in vegetation. Caution must be used

when making generalizations about nutrient removal efficiencies from a

diverse and sparse data set that includes a variety of wetland types and

a wide range of years of application (Richardson and Nichols 1985).

However, trends from the most complete studies show a general pattern of

decreased nutrient removal efficiency with time and with higher loading

rates (Richardson and Nichols 1985).



Evapotranspiration in Forested Wetlands


Evaporation is the conversion of water from the liquid state into

vapor, and its diffusion into the atmosphere. Transpiration is the

return of water to the atmosphere by plants. Evapotranspiration then is

the evaporation from all moist surfaces to the atmosphere. Evapotrans-

piration includes several processes that are difficult to quantify

separately; therefore, potential evapotranspiration is usually

estimated. Potential evapotranspiration is defined as the evaporative

flux that will not exceed the available energy from both radiant and

convective sources (Saxon and McGuinness 1982). In determining










potential evapotranspiration, atmospheric variables are considered

separately from plant and soil effects. Often water is not freely

available and actual evapotranspiration is less than potential

evapotranspiration. Therefore, potential evapotranspiration is

estimated first, based on meteorological factors, and the amount of that

potential used by the actual evapotranspiration processes is then

estimated.

A water budget for the Okefenokee Swamp was developed by Rykiel

(1977). Evapotranspiration was estimated as a residual term. An

independent estimate of potential evapotranspiration was made with the

Thornthwaite method for comparison with the residual estimate.

Potential evapotranspiration was found to underestimate evapotrans-

piration and therefore should be used as a minimum value with normal

rainfall (Rykiel 1977).

Estimates of potential evapotranspiration were compared to field

measurements (groundwater level fluctuation) of evapotranspiration in a

cypress strand (Carter et al. 1973). Evapotranspiration measured in

this manner was higher than estimated potential evapotranspiration

except when the groundwater level was well below the land surface and

water was unavailable to plants. Evapotranspiration values measured in

the same manner in these cypress strands were reported by Burns (1978).

When the groundwater level was high, field evapotranspiration approached

pan evaporation. These studies suggest that estimates of potential

evapotranspiration may underestimate evapotranspiration when water

availability is high.

In order for evapotranspiration to occur, a source of energy and a

vapor pressure gradient between the evaporating surface and the










atmosphere must exist. Solar energy is the main source of energy and

advection of energy from outside an area may increase evapotranspiration

(oasis effect). Evapotranspiration is influenced by a number of factors

including solar radiation, air temperature, vapor pressure gradient,

wind and air turbulence. In addition to the meteorological factors the

nature of the evapotranspiring surface and availability of water are

important. For example, the height and roughness of vegetation

influence air turbulence, and transpiration can at times exceed open

water evaporation (Linacre 1976).

On the other hand, the sheltering effect and high albedo of

vegetation as well as the resistance to water movement in dry periods

could decrease the rate of water loss during dry periods (Linacre 1976).

The presence of vegetation in a wooded swamp in southern Ontario reduced

water loss in relation to that from and open water surface (Monro 1979).

Swamp vegetation was efficient in converting net radiation into

turbulent energy exchange, thus minimizing water loss. Wetlands may

evapotranspire at a low rate when water is limiting and at a higher rate

when water is readily available.

Evapotranspiration in three cypress swamps in Withlacoochee State

Forest was measured by Ewel (1985) by determining changes in water

levels. Daytime reductions in water level due to evapotranspiration and

infiltration could be distinguished from nighttime reductions in water

level, due to infiltration only. Evapotranspiration rates were

calculated as the difference between the daytime and nighttime water

level changes converted to a volume basis. Average annual evapotrans-

piration was estimated to be 31 in. during the 3 yrs for which data were

available. Average annual precipitation for the 3-yr period was 59 in.










Therefore, evapotranspiration was 52% of precipitation at these sites.

Evapotranspiration in slash pine flatwoods in north Florida was

estimated over the same 3-yr period to be 41 in./yr, or 74% of

precipitation. The estimated evapotranspiration rate was 77% of this

rate. This comparison confirmed earlier reports of low evapotrans-

piration rates for certain cypress swamps.

A decrease in the rate of water loss would be a water conservation

mechanism and any discussion of water conservation by wetland vegetation

should include reference to xeromorphy. Plants of acid habitats are

often structurally adapted to conserve water, as are plants from xeric

habitats (Clewell 1981). Such plants in acid habitats are called

physiological xerophytes (Clewell 1981). Xeromorphic characteristics in

plants include thick cuticles, deeply sunken stomata, and highly

reflective surfaces. These are the characteristics of evergreen

sclerophyllous leaves such as those of titi and sweetbay. These

characteristics have evolved in desert plants in response to drought but

some xeromorphic species have a bimodall" distribution, i.e., they are

found in both wet and dry habitats but not in intermediate habitats

(Larsen 1982). A species could undergo selection for characteristics

that adapt it more effectively to both wet and dry habitats than for the

habitats between these extremes. In the process of evolving charac-

teristics permitting survival in wet areas, the plants could have

acquired characteristics fitting them for survival in dry areas.

These characteristics may develop in response to low fertility and

potential water deficiency, but water loss is the key factor (Brunig

1971). On the other hand, xeromorphy in plants may be an adaptation to

low fertility and water conservation features may be fortuitous (Larsen








38

1982). If xeromorphy is an adaptation to dry conditions the reduction

of transpiration losses could be a necessary adaptation for survival

during dry periods. Low transpiration rates for cypress domes may

likewise be an adaptation for survival when water becomes limiting

during dry periods (Brown 1981).

Evapotranspiration can be determined by various direct measures

such as the measurement of the increase in water vapor in air flowing

through gas exchange chambers (Odum et al. 1970; Odum and Jordan 1970;

Cowles 1975; Brown 1978; Burns 1978). The metabolism and transpiration

of some plants in a tropical rain forest were measured by Odum et al.

(1970), and the effect of air velocity on leaf metabolism was evaluated.

Air velocity in low ranges limited metabolism of living forest

components. In addition, transpiration increased asymptotically with

airflow over leaf surfaces (Odum et al. 1970). Therefore, flow rates in

chambers should not minimize metabolism or enhance transpiration. Air

flow rates were adjusted by Brown (1978) so as not to limit metabolism

or enhance transpiration, and to insure that the maximum difference in

temperature between the ambient and exhaust air never exceeded 3C.



Freshwater Wetland Models and their Use in
Simulating Wastewater Addition


The number of models of freshwater wetlands in the literature is

large (Costanza and Sklar 1985). These authors provided a systematic

review of freshwater wetland models that use some kind of formal

mathematical description, either explicit equations or system diagrams

with implied equations. The representative but not exhaustive review

listed 87 models in 59 different studies. There were 18 forested swamp










models, 9 bottomland hardwood models, 14 emergent marsh models, 5

floating marsh models, 30 shallow lake models, 2 bog or fen models, 4

tundra models, and 5 combination models. More than 60% of the models

were non-linear.

There are two major types of ecological models, which can be

classified for convenience as analytic models and simulation models

(Hall and Day 1977). Analytic models use mathematical procedures to

find exact solutions to differential and other equations. These models

are not generally used to study whole ecosystems because they cannot be

used to solve many non-linear systems of equations that may provide a

better description of an ecosystem. Simulation models, on the other

hand, do not give an exact solution to an equation over time, and,

therefore, one type of error associated with these models is related to

the inexact nature of the solution technique used. Simulation models

can solve many equations nearly simultaneously and can incorporate

non-linearity (Hall and Day 1977).

A wide diversity of types of models describe and simulate wetland

dynamics (Mitsch et al. 1982). The major types were classified for

their purposes as: energy/nutrient ecosystem models, hydrology models,

spatial ecosystem models, tree growth models, process models, causal

models, and regional energy models.

In energy/nutrient ecosystem models, materials pass through or

cycle among biotic and abiotic components and exchange with the

surroundings. These models are generally non-spatial, aggregated models

with feedbacks and interactions among components. Both energy flow and

nutrient cycling can be combined into one model. In spatial ecosystem

models the attributes of ecosystem models are combined with spatial









transport models hydrodynamicc transport models) describing wetland

hydrology and pollutant transport over short periods and large areas.

Although the dynamics of wetlands have been represented by a variety of

ecological models, often involving great detail and complexity, few

spatially distributed models have emerged (Mitsch 1983). Hydrodynamic

transport models describing stream flow and storm runoff have been

developed for wetlands (Hopkinson and Day 1980), and a model has been

developed for overland flow through vegetated areas (Hammer and Kadlec

1986). Some of the energy/nutrient and spatial ecosystem models

described by Mitsch et al. (1982) were developed to simulate the effects

of the addition of wastewater on wetland components. These are

described in more detail below.

Simulation models were developed as part of a long range study in

north central Michigan to investigate the feasibility of using peatlands

for disposal of treated wastewater (Kadlec and Tilton 1979). More

specifically, the models predicted long-term changes in biomass and

nutrient concentrations in this marsh/bog peatland ecosystem.

Initially, Dixon (1974) developed a model emphasizing the biomass

dynamics of the system. This was combined with models of water and

nutrient components into a macromodel to predict the effects of the

addition of wastewater on these wetland components (Parker 1974). The

ecosystem was divided into blocks, which were further divided into units

or compartments, each of which represented the behavior of a biotic or

abiotic variable. Each unit or compartment was represented by a time

varying differential equation. Therefore, a set of ordinary,

first-order, non-linear differential, mass balance equations comprised

the model (Dixon and Kadlec 1975). This was the first spatially








41

distributed model of a wetland ecosystem used to predict the impacts of

wastewater addition. A series of simulations was run varying nitrogen

and water parameters to determine the effects on the biomass, water and

nutrient components. The simulations were intended to indicate the

relative effects of added water and nutrients on the wetland and not

predict actual results. Dixon and Kadlec (1975) pointed out that actual

predictions should await complete updating and validation of the model.

Hammer and Kadlec (1983) then developed a simplified model of

wastewater/wetland interactions that accounted for the movement of

surface water in response to gradient and vegetation flow resistance,

and allowed material balances to be determined in a wetland ecosystem

receiving wastewater (Hammer 1984). This model also contained partial

differential equations (Hammer 1984). The resultant analytical solution

to the differential-integral equation described the solute balance in

the surface water sheet for this idealized system (Hammer 1984).

In this model, the simulated removal of dissolved nutrients from

surface waters is a two-step process, consisting of delivery and

consumption. Delivery is accomplished by convective mass transfer

within surface waters or by downward flow due to water infiltration.

Consumption occurs principally at the surface of soil and plants. In

addition, two treatment regimes exist in the wetland. In the vicinity

of wastewater discharge a saturated region exists. Here component

removal rates are quite slow, comprised of uptake due to adsorption in

the deep soil, incorporation of material into new soil and woody plants,

and microbial release of gases to the atmosphere. Outside this

saturated region, surface water concentrations of wastewater components

drop exponentially with distance. In this zone of rapid removal, the










transport of dissolved components through the water sheet limits the

overall rate (Hammer 1984). The combined total area required for

assimilation of pollutants over time determines the treatment capacity

of the system.

To facilitate the use of the model over long periods of time, all

transfers between units or compartments were taken as the annual net

accumulation in each compartment and, therefore, the cycling of

nutrients and other materials on a seasonal basis was not explicitly

addressed (Hammer and Kadlec 1983). This spatially distributed

hydrological model provides a convenient means by which the response of

natural or constructed wetlands components can be predicted using site

specific information (Hammer 1984).

Simulation models were developed for a cypress dome in Florida to

investigate management issues (Mitsch 1975a, 1975b; Odum et al. 1977;

Deghi 1977; Deghi and Ewel 1984). The models were developed in part to

indicate long-term (100 yrs) dynamics of a cypress dome receiving

wastewater.

The model described by Mitsch (1975a, 1975b) and Odum et al.

(1977) was designed to deal with several management questions involving

cypress domes, including the optimum rate of harvesting, possible

effects of fire, and their wastewater treatment capability. The model

included two autotrophic components, the cypress trees and the

understory. The sediment component consisted of nitrogen, phosphorus,

organic peat and water. The model was designed to run for 10 to 100

yrs; therefore, annual variations in solar radiation were ignored.

Flows such as litterfall and gross primary production were determined

from yearly averages. Primary productivity was modeled with a








43

non-stratified approach (equal competition for sunlight between the two

autotrophic compartments) and with a stratified approach (cypress canopy

having a competitive advantage). Each plant compartment could utilize

5% of the flow that was available to it. Two pathways for decomposition

were designed into the model, their operation dependent on water level.

Several limiting nutrient schemes were utilized in the model.

The model described by Deghi (1977) and Deghi and Ewel (1984)

examined the long-term behavior of phosphorus in the cypress dome

subsequent to wastewater addition. Four autotrophic components were

distinguished in the model: cypress trees, hardwood trees, understory

vegetation, and duckweed. The model was designed to run for 50 yrs;

therefore, annual and seasonal variations in forcing functions were

ignored. The amount of sunlight reaching any of the three strata within

the cypress dome was related to the biomass of vegetation above it.

Incorporating aspects of the models described above, a simple

tractable ecosystem simulation model was developed to predict the long-

term responses of the main components and processes of the titi shrub

swamp in Apalachicola, Florida, to wastewater discharge. The main

components were vegetation, water and soil, and the processes were

carbon, nitrogen and phosphorus cycling, and water flow. These

components and processes were quantified in order to determine their

responses to wastewater discharge and to add basic information to the

study of forested wetlands in Florida.
















CHAPTER 2
METHODS



Vegetation Analysis


A map of the vegetation of the titi shrub swamp study site was

made utilizing both high and low altitude aerial photographs.

Quantitative information about the structure and composition of the

vegetation at the titi shrub swamp study site was obtained with a

variation of the quadrat sampling technique (Smith 1978). Belt

transects were laid out in each of four wetland community types

delineated on the map. A species area curve was used to determine the

minimum number of multiple plots needed for a satisfactory sample (Smith

1978). The identification and diameter at breast height (dbh) of

individuals in the tree size class (dbh greater than or equal to 10 cm)

were recorded in each of four 10 m x 20 m quadrats within each transect.

The identification and dbh of individuals in the shrub size class (dbh

less than 10 cm and greater than or equal to 4 cm, and height greater

than 1.3 m) were recorded in each of four 5 m x 10 m quadrats (one

within each tree-size-class quadrat). The dbh values of the individuals

were then converted to basal area. The density, dominance, and

frequency values were determined for each species as follows (Cox 1976):









density number of individuals/area sampled,

dominance = total basal area/area sampled,

frequency = number of plots in which species occurs/total

number of plots sampled.


These values were then converted to a hectare basis. For a particular

species, these values were then expressed in a relative form, which

shows the percentage of that species among all species (Cox 1976):


relative density = (density for a species/total

density for all species) x 100,

relative dominance (dominance for a species/total

dominance for all species) x 100,

relative frequency (frequency for a species/total

of frequency values for all species) x 100.


Relative values for density, dominance, and frequency were added

together to give a single importance value for each species. Each

importance value was converted to a percentage basis and expressed for

both the stratum (size class) and the community.

A line intercept method (Smith 1978) was used along the 80-m

permanent transects in each of the four communities to determine the

percent ground cover of the vegetation less than 1.3 m in height. This

includes herbaceous and woody vegetation. The total linear distance

covered by each species (or bare hummock) along the transect was

recorded. The percent cover was calculated as the total intercept

length of each species (or bare hummock), divided by the total transect

length, multiplied by 100.









Biomass and Nutrient Standing Stock Estimates


Biomass of the titi shrub swamp at the study site was estimated

using regression equations describing biomass as a function of selected

physical dimensions. For three species harvested at the study site, a

computer program (CURFIT: Spain 1982) for fitting ten basic model

equations to a set of x,y data was used to determine the appropriate

linear regression equations. Statistics on the best fitting model

equation are provided. Regression equations developed by Brown (1978)

were used for species not harvested at the study site.

Ten different sized individuals of three species were felled:

black titi, red titi, and Magnolia virginiana (sweetbay). The dbh,

height, location (height), and diameter of all primary branches (any

branches extending from the bole with a diameter less than the bole) of

each individual were recorded. The diameters of the two primary

branches at the end of the bole were also recorded.

The diameters at the base of each individual (BD) and at a

location where butt swell no longer occurred (SlD) were recorded. The

length of this first section (SlL), with butt swell, was recorded.

Beginning at this point and moving towards the end of the bole, the

individual was divided into additional sections. The section length

(SL) was determined by selecting a section with approximately the same

diameter at each end. The length of each section and the diameter of

the individual at the top of each section (SD) were recorded. A disc at

the top of each section was harvested and each disc length (DL) was

recorded. The discs were dried to a constant mass in the laboratory and

their dry weights (DW) were determined.








47
The following formula was used to estimate the dry weight (SW) of

all but the first section.


SW SL x DW / DL.


The dry weight of the first section (S1W), with butt swell, was

estimated with the following formula.


SIW (SlL x D1W / D1L) + {[(S1L x D1W / D1L)

x (BD SlD)] / (S1D x 2)).


The bole biomass was estimated by summing the estimated dry weights of

all sections.

The primary branches of each individual were divided into three

size classes (small, medium and large) based on diameter. One primary

branch in each size class was randomly selected from each tree and

harvested (i.e., three per tree). Each primary branch was separated

into leaf and branch material. Two hundred leaves were subsampled from

each primary branch that was harvested and their area was determined in

the laboratory with a Hayashi Denko Company model AAM-5 leaf area meter.

Leaf and branch material were dried to a constant mass in the laboratory

and their dry weights were determined. The leaf area and the dry weight

of the 200 subsampled leaves were used to calculate the leaf biomass to

area ratio. A leaf biomass to area ratio was calculated for each

species based on tree height for two vertical intervals (9 to 12 m and 3

to 9 m).

The dry weight of branch material was predicted using primary

branch diameter as the independent variable. In the same manner, the







48

dry weight of leaf material was predicted using primary branch diameter

as the independent variable.

The estimated bole, branch, and leaf biomasses for each individual

were summed to obtain the estimated aboveground biomass for each

individual. The estimated aboveground biomass and the dbh of the ten

individuals for each species were used to predict the aboveground

biomass using dbh as the independent variable. The regression equation

for each species was used for individuals of that species greater than 4

cm dbh sampled in vegetation analysis quadrats to estimate their

aboveground biomass on an areal basis. The estimated leaf biomass and

the dbh of the ten individuals for each species were used to predict the

leaf biomass using dbh as the independent variable. The regression

equation for each species was used for individuals of that species

greater than 4 cm dbh sampled in vegetation analysis quadrats in the bay

swamp community to obtain an estimate of their leaf biomass on an areal

basis.

The estimated aboveground biomass and the dbh of the smallest

individual for each of the three species were used to predict the

aboveground biomass using dbh as the independent variable. The

regression equation was fitted through the origin. This regression

equation was used for all individuals less than 4 cm dbh sampled in

vegetation analysis quadrats to obtain an estimate of their aboveground

biomass on an areal basis. Regression equations developed by Brown

(1978) were used for black gum, pond cypress and slash pine trees.

Herbaceous biomass and litter were estimated by collecting all the

material in five 0.5 m2 circular plots randomly sampled within each 200

m2 vegetation analysis quadrat (20 per community type). The material







49

was separated into live (herbaceous) and dead (litter) components. Leaf

litterfall samples were collected monthly for 1 yr from three 0.1 m2

baskets located at 10 m intervals in each community.

A subsample of each disc (bole), leaf and branch material of each

harvested primary branch, each herbaceous plot and of each litter plot,

and triplicate subsamples of the yearly composite of leaf litterfall

from each community were ground in a Wiley Mill. A 0.1-g sample of the

ground material was digested with a mixture of K2S04, CuS04 and selenium

in a ratio of 100:10:1, and 2 ml of H2SO4 (Nelson and Sommers 1972).

The samples were heated on a block digester, cooled, and diluted to 50

ml with deionized distilled water, and then analyzed by automated

colorimetric analysis for ammonium nitrogen and total phosphorus (USEPA

1980).

Bole, branch and leaf biomass were estimated as the product of the

average percent of the total biomass of these components for the three

species intensively studied and the aboveground tree biomass for each

community type. The total nitrogen and total phosphorus in the bole,

branch and leaf material were determined as the product of the estimated

bole, branch and leaf biomass and the average concentration for these

components. The total nitrogen and total phosphorus in the herbaceous

component for each community type were determined as the product of the

herbaceous biomass and the average concentration of this component in

each community type. The total nitrogen and total phosphorus of the

bole, branch and leaf material, and the herbaceous component of each

community type were summed to obtain the total nitrogen and total

phosphorus in the aboveground biomass of each community type.









The total nitrogen and total phosphorus in litter for each

community type were determined as the product of the dry weight of

litter and the average concentration of total nitrogen and total

phosphorus in litter in each community type. The total nitrogen and

total phosphorus in leaf litterfall for each community type were

determined as the product of the dry weight of leaf litterfall and the

average concentration of total nitrogen and total phosphorus in leaf

litterfall in each community type.



Water Chemistry


A composite precipitation sample was taken quarterly for 1 yr.

Each sample was preserved in the field with mercuric chloride and then

stored on ice during transport to the laboratory in Gainesville. Part

of the sample was frozen for future analysis of total phosphorus, and

the rest of the sample was refrigerated at approximately 4C for future

analysis of Kjeldahl nitrogen and nitrate-nitrite nitrogen. Eight

shallow groundwater wells were sampled three times during 1 yr. Each

well was pumped out approximately 24 hrs prior to sampling. Each sample

was analyzed in the field for pH and then stored on ice during transport

to the laboratory in Gainesville. Part of the sample was frozen for

future analysis of total phosphorus, and the rest of the sample was

refrigerated at approximately 4*C for future analysis of Kjeldahl

nitrogen, nitrate-nitrite nitrogen, conductivity, and chloride. All

precipitation and groundwater samples were preserved according to APHA

(1980) and were filtered with a Gelman 0.45 ym membrane filter prior to

analysis.









Surface water samples were taken at seven stations in the study

site (Figure 3). A dissolved oxygen sample was taken at mid depth, the

water temperature was recorded, and pH was measured in the field at each

station monthly for 1 yr. A sample was taken monthly and filtered in

the field with a Gelman 0.45 pm membrane filter for analysis of

orthophosphate, ammonium nitrogen, nitrate-nitrite nitrogen, and total

organic carbon. An unfiltered sample was taken monthly for analysis of

total phosphorus, Kjeldahl nitrogen, biochemical oxygen demand,

conductivity and turbidity. An unfiltered sample was taken quarterly

for analysis of acidity, chloride, and color. All samples were stored

on ice during transport to the laboratory in Gainesville and preserved

according to APHA (1980).

An Orion Model 399A lonanalyzer with a glass electrode was used to

measure pH. Dissolved oxygen was determined using the Winkler method

(azide modification) for the first 6 mo and with a YSI model 54 oxygen

meter for the subsequent 6-mo period. Color was measured in centrifuged

samples at pH 7 with a Perkin Elmer Model 552 spectrophotometer.

Turbidity was measured with a Hach Analytical Nephelometer using a Hach

10 NTU calibration standard. Conductivity was measured with a YSI Model

31 conductivity bridge. Total organic carbon (TOC) was analyzed with a

Beckman Model 915 Total Organic Carbon Analyzer. Chemical oxygen demand

(COD) was determined using a semi-micro method of dichromate oxidation

with ferrous ammonium sulfate titration using ferroin indicator.

Biochemical oxygen demand (BOD5) was determined with full strength,

non-seeded, aerated samples incubated in 125 ml BOD bottles at 20*C for

5 days. Initial and final dissolved oxygen was measured in these

samples using the Winkler method (azide modification). Phenolphthalein








52
acidity was determined electrometrically at room temperature according

to APHA (1980).

Nitrate-nitrite nitrogen (cadmium reduction method), ammonium

nitrogen (alkaline phenol method), Kjeldahl nitrogen (semi-micro

persulfate digestion followed by ammonium analysis), orthophosphorus

(molybdate method), total phosphorus (sulfuric acid digestion followed

by orthophosphorus analysis), and chloride (ferric thiocyanate method),

analyses were performed using automated colorimetric methods according

to USEPA (1980) and APHA (1980).



Soils and Phosphorus Adsorption


Replicate soil cores were taken with acrylic tubing (4 cm i.d.) at

four sampling stations (2, 4, 5 and 6, Figure 3) representing the four

wetland community types. Each 20-cm-long core was divided into 5-cm

increments. Each 5-cm increment was placed in an individual urine cup

and then stored on ice during transport to the laboratory in

Gainesville. Total organic carbon was determined by the Walkey-Black

method and percent carbon was assumed to be 58% of organic matter

(Allison 1965).

An Orion Model 399A lonanalyzer with a glass electrode was used to

measure pH in deionized water with a soil:liquid ratio of 1:1 (v:v)

(Peech 1965). Total nitrogen including nitrate was determined by the

semi-micro Kjeldahl method (Bremner 1965). Total phosphorus was

determined by the ignition method and 0.1 N HCL extraction (Anderson

1976). This procedure converts all the phosphorus to the orthophosphate

form which was determined colorimetrically with the ascorbic acid method

(Murphy and Riley 1962).









Phosphorus adsorption was measured for soils sampled at two

stations (4 and 5) at two depths (0-5 cm and 15-20 cm). Duplicate 1 g

air-dried samples were shaken for 24 hrs at 22C with 25 ml of a 0.01M

CaC12 electrolyte solution. One ml of toluene was added to eliminate

microbial activity. Varying concentrations of phosphorus were added as

follows: 0, 2.5, 5, 7.5, 10, 15, 20, 30, 40, and 50 mg/l as Ca(H2PO4)2.

The average concentration of phosphorus in secondarily treated

wastewater effluent is within this range. The samples were then

centrifuged and the supernatant solutions were analyzed for phosphorus

by the ascorbic acid method (Murphy and Riley 1962). The amount of

phosphorus removed by the soil from the solution was considered

adsorbed.

The adsorption data are plotted in four ways: the regular plot

(x/m versus C), linear Langmuir plot (Cm/x versus C), linear Fruendlich

plot (log x/m versus log C), and Tempkin plot (x/m versus log C), where

x/m and C represent the amount of phosphorus adsorbed by unit mass of

soil (pg/g) and equilibrium phosphorus concentration in the solution

(ug/ml), respectively. Linear regression analysis was performed on the

last three plot types to obtain regression lines and coefficients of

determination (R).

The soils evaluated for phosphorus adsorption were also analyzed

for extractable phosphorus, extractable iron and extractable aluminum by

0.1 N HCL extraction (Mestan 1986) and the Tamm oxalate method (Saunders

1965). Phosphorus was measured by the ascorbic acid method (Murphy and

Riley 1962), and iron and aluminum were analyzed using flame atomic

absorption spectrophotometry (Mestan 1986). The Tempkin equation had

the highest correlation when both soil types were considered together.









Therefore, the adsorption maxima obtained by substitution of the

equilibrium phosphorus concentration derived from the quadratic equation

into the Tempkin equation was correlated with measured soil properties.

The phosphorus sorption index was computed from a single-point uptake

adsorption value (x/m) corresponding to an equilibrium phosphorus

concentration of 10 pg/ml. This single-point value was computed from

the individual quadratic equations for each soil. This index was chosen

on the basis of simplicity, and the 10 pg/ml equilibrium phosphorus

concentration is within the range of phosphorus concentrations found in

secondarily treated wastewater. Linear regression analysis was

performed to relate the adsorption maxima and the phosphorus sorption

index with measured soil properties.



Hydrology


The general hydrologic equation for determining the water budget

in a wetland is


Inflow = Outflow AS (change in storage).


The specific components of a wetland water budget have been further

described by Carter et al. (1979) as:


P + SWI + GWI = ET + SWO + GWO + AS


where P is precipitation, SWI is surface water inflow (including

overland runoff), GWI is groundwater inflow, ET is evapotranspiration,

SWO is surface water outflow, GWO is groundwater outflow (discharge

through aquifers, seepage), and AS is the change in storage.









Determination of individual water budget components may not be a

simple matter (Carter et al. 1979). Several assumptions were made to

simplify estimation of water budget components. The basin storage was

assumed to be constant over the period of time for which the budget was

calculated; therefore, the change in storage (AS) was assumed to be

zero. There are no tributaries providing surface water inflow to the

site. Therefore, SWI was eliminated from the equation. The water

budget was estimated on a depth basis rather than on a volume basis;

therefore, wetland area is not taken into account, and the linear nature

of shrub swamps in the panhandle precludes any significant watershed

interception of precipitation beyond that falling directly on the system

(Wharton et al. 1982). Therefore, in this simplified water budget there

is no overland runoff to the site, and overland runoff and groundwater

flow are assumed to be outflow components. GWI is thus eliminated from

the equation. The simplified water budget equation for this study site

is P R + G + ET, where R is runoff and G is groundwater flow. An

annual water budget for the study site was calculated using data for the

5-yr period from 1982 through 1986 and for October 1985 through

September 1986 when transpiration measurements were made, hereafter

referred to as the water budget year. All water data are reported in

English System Units (inches) as is common in the hydrology field.


Precipitation and Runoff

Daily precipitation records are kept at the Apalachicola weather

station approximately 1 km east of the study site (NOAA 1982-1986).

Runoff was calculated from daily precipitation using the SCS curve









number method presented in section 4 of the National Engineering

Handbook (SCS 1972). Chow (1973) described the method that uses the

following equation:


Q [(P 0.2 S)2]/(P + 0.8 S),


where Q is the runoff in inches, P is the storm precipitation in inches,

and S is the potential infiltration in inches, which is determined as

follows:


S (1000 / Cn) 10


where Cn is the curve number previously determined by the SCS (1972) for

hydrologic soil-cover complexes that are a combination of soil type and

cover. The curve number can be determined for antecedent moisture

condition (AMC) classes based on total antecedent precipitation. Konyha

et al. (1982) described five modifications for determining potential

infiltration in accordance with the SCS curve number method in order to

predict runoff in flat high water table watersheds in Florida. Two of

the methods (AMC II and AMC III) were used to estimate runoff from

precipitation at the study site for 1982 through 1986. In addition

these two methods were utilized to estimate runoff from precipitation at

the study site during the water budget year.


Groundwater

Water levels in shallow groundwater wells were measured monthly

for 1 yr to construct maps of the potentiometric surface of the study

site for high and low water periods. Water depth at stations 2, 3 and 5

(Figure 3) within the wetland were concurrently measured.








57
Groundwater flow is composed of two components at the study site,

infiltration through a semi-impermeable organic layer and surface sands,

and deep seepage through clayey sands. The former is highly variable

and no data were collected to estimate this flow. Therefore, an

estimate was made of the maximum groundwater flow that could occur from

the upper surface sands to the lower clayey sands using a simplification

of Darcy's law:


v K Ah/Az


where v is the velocity of the water passing from the surface sand zone

to the clayey sand zone, K is the hydraulic conductivity of the clayey

sand zone, and Ah/Az is the hydraulic gradient between the two zones.

Ah is the change in piezometric head between the two zones and Az is the

thickness of the clayey sand zone.


Evapotranspiration

Depressional watersheds are dominated by flat slopes and long-term

seasonal precipitation and flooding (Bedient 1975). They are dominated

by lateral rather than vertical soil water movement, and the lateral

movement is difficult to measure due to poorly defined drainage paths.

The titi shrub swamp is in a depressional watershed, and its analysis

requires an emphasis on soil storage and evapotranspiration changes

over long periods of time as well as some quantification of lateral

water movement. The water balance technique of Thornthwaite and Mather

(1957) for determining evapotranspiration is ideal for analyzing

depressional watersheds (Bedient 1975).

Evapotranspiration was determined with an empirical formula

relating climate variables that drive evapotranspiration (Thornthwaite









and Mather 1957). The Thornthwaite method uses mean monthly air

temperatures to determine an annual heat index. Mean monthly air

temperatures for the Apalachicola weather station were reported by NOAA

(1982-1986). Unadjusted monthly potential evapotranspiration is

determined from the mean monthly air temperature based on the annual

heat index. Adjusted monthly potential evapotranspiration is determined

by multiplying the unadjusted values by the monthly duration of sunlight

(12 hr basis) at the station's latitude.

When precipitation was greater than potential evapotranspiration,

actual evapotranspiration was taken to be equal to potential evapotrans-

piration. In months when precipitation was less than potential evapo-

transpiration, water was lost from the soil. The actual water loss

varies with the amount of moisture in the soil. This monthly soil water

loss was determined as the difference between the maximum soil moisture

storage and the monthly soil moisture retained for the accumulated

monthly water loss. The maximum soil moisture was determined using the

following formula:


maximum soil moisture = (1000 / Cn) 10


where Cn is the curve number previously determined by the SCS (1972) for

hydrologic soil-cover complexes that are a combination of soil type and

cover. The monthly soil moisture retained for the accumulated monthly

water loss was determined using soil moisture depletion curves (Bedient

1975). The monthly soil water loss was added to the monthly precipi-

tation to obtain an estimate of monthly actual evapotranspiration for

those months when potential evapotranspiration was greater than


precipitation.










Pan evaporation can also be used to estimate potential evapo-

transpiration. Pan evaporation values from U.S. Weather Bureau Class A

Land Pans are measured at selected NOAA weather stations. The closest

NOAA weather station measuring pan evaporation is in Milton, Florida,

160 km northwest of the study site. Pan evaporation data for the Milton

weather station were reported by NOAA (1982-1986).

Brown (1978) measured surface evaporation for soil and water

surfaces as well as transpiration from plants in several wetlands in

Florida. Her surface evaporation values were used in this study to

estimate the portion of evapotranspired water loss due to surface

evaporation.


Transpiration

Transpiration at the study site was determined using the gas

exchange chamber method. In five studies where chambers were used to

measure metabolism and transpiration, airflows were selected so as not

to limit metabolism or enhance transpiration. The volume and the number

of turnovers per minute of six chambers of wide ranging size used in

these five studies are given in Table 1. The computer program CURFIT

(Spain 1982) was used to fit the data on chamber volume and turnover

time. The best fitting equation for these data was a power function (y

= Ax") where y = number of turnovers per minute, and x chamber volume.

This equation was used to determine the number of turnovers per minute

and thus the airflow in the chambers used in this study that would not

limit metabolism or enhance transpiration.

Three chambers were used in this study. The dimension, volume,

turnover time (calculated with the model equation), and the airflow that










Table 1. Chamber volume and number of turnovers per minute in four
studies where metabolism and transpiration were measured.



Chamber Volume # of Turnovers Source
(m') (per minute)


0.0002 73.0 Odum et al. 1970

0.0004 30.0 Brown 1978

0.052 8.0 Brown 1978

0.898 5.0 Burns 1978

8.0 1.35 Cowles 1975

4000.0 0.19 Odum and Jordan 1970









would not limit metabolism or enhance transpiration are given in

Table 2. All three chambers' volumes were within the range of the

chamber volumes used to develop the model equation. In the field,

airflow in the chamber was set at the level calculated not to limit

metabolism or enhance transpiration. The airflow was increased when the

temperature inside the chamber increased above the temperature outside

the chamber.

Flow-through cylindrical chambers were constructed with wooden

hoops and polyethylene. Flow was provided by a variable speed fan

mounted at one end. The other end was left open. A canopy branch was

inserted into the chamber. Transpiration rates were determined by

monitoring water vapor changes, with a dew point hygrometer, in the air

passing through the chamber. Every attempt was made to maintain similar

conditions inside and outside the chamber.

Transpiration of sweetbay and black titi was measured in a bay

swamp from a 9-m tower. The chambers were suspended from the tower with

an adjustable boom and pulley system. Measurements were recorded every

15 min from before transpiration began in the morning to after

transpiration ended in the evening. This time period represented one

run. The temperature inside the chamber and the ambient temperature

outside the chamber were measured with mercury thermometers. An

electric pump pulled either an intake or exhaust air sample from the

chamber through the dew point hygrometer. The intake dew point

temperature and the exhaust dew point temperature were measured with a

EG and G Model 880 dew point hygrometer. The flow through the chamber

was measured with a battery operated Weather Measure Model W141A hot

wire anemometer and the solar input was measured with a Matrix Mark VI









Table 2. The dimension, volume, turnover time (calculated with model
equations) and the airflow that would not limit metabolism
and transpiration, for the three chambers used in this study.




Chamber I II III


diameter (m) 0.58 0.58 0.58

radius (m) 0.29 0.29 0.29

length (m) 2.00 1.00 1.40

volume (m') 0.528 0.264 0.370

# turnovers (per min)* 3.97 5.01 4.47

minimum airflow (m/sec) 1.75 1.10 1.38


*calculated with model equation y= Ax"

A- 326.5
n- -.3344








63

solar radiometer. At the end of each run the branch inside the chamber

was harvested and the leaf biomass was determined. These measurements

were the basis for the following calculations performed with a computer

spread sheet program.

The ambient temperature and the intake and exhaust dew point

temperatures were converted to saturation vapor pressure with the

Clausius-Clapeyron relationship, as follows:


saturation vapor pressure (mb) 6.841 EXP(0.0608) x T ("C).


The saturation vapor pressure was converted to absolute humidity with a

manipulated form of the gas law, as follows:


absolute humidity (g/m3) = saturation vapor

pressure x MW x (103 erg cm-3 mb-1 106 cm3 m-3)/R x TK


where MW = molecular weight of water (18 g/mole)

R = gas constant (8.31 x 107 erg/*K mole), and

TK = ambient temperature in "K.

Relative humidity saturation deficit were calculated as follows:


relative humidity ambient absolute humidity/intake absolute

humidity at saturation x 100.


saturation deficit (ambient saturation vapor pressure)

(1 relative humidity).


The flow rate was calculated as the product of the cross-sectional area

of the fan duct and the measured flow.

The rate water was released (the transpiration rate) was

calculated as follows:









transpiration rate in g H20/hr (flow rate)(exhaust absolute

humidity at saturation intake absolute humidity at saturation).


These hourly transpiration rates were integrated with a computer

program using trapezoidal integration (Appendix A) to obtain the total

daily transpiration rate. The leaf area was determined as the product

of the leaf biomass measured at the end of the run and the leaf biomass

to area ratio for the vertical interval where transpiration was measured

(9 to 12 m). The transpiration rate per leaf area was calculated as the

dividend of the transpiration rate and the leaf area. The total daily

transpiration rate per leaf area was calculated as the dividend of the

total daily transpiration rate and the leaf area. The transpiration

rate per biomass was calculated as the dividend of the transpiration

rate per leaf area and the leaf biomass to area for the vertical

interval where transpiration was measured (9 to 12 m).

In order to extrapolate the transpiration measurements to the

ecosystem level the total daily transpiration rate per ground area was

determined as the product of total daily transpiration rate per leaf

area and the leaf area index.

In order to calculate the leaf area index the vertical

distribution of leaf biomass was determined with the plumb-bob method

similar to the method used by Benedict (1975) and Brown (1978). A

marked line was lowered through the vegetation from the tower where

transpiration was measured, with a three part extension pole. The

number of leaves hitting the line and their species and location along

the line were recorded. This was performed at 16 compass points and at

three pole extension distances for a total of 48 samples. The number of

leaves of each species hitting the line at a given vertical interval (9









to 12 m or 3 to 9 m) in terms of the percent of 48 samples was

multiplied by the leaf biomass to area ratio for a given vertical

interval for that species. The percent of the total leaf biomass for

each species at each given vertical interval was the vertical distri-

bution of leaf biomass for that species. The leaf area index for each

species was calculated as the ratio of the estimated leaf biomass per

ground area for that species and the leaf biomass to area ratio for a

given vertical interval for that species, multiplied by the vertical

distribution of leaf biomass for that species. The estimated leaf

biomass per ground area was determined with dimension analysis of ten

trees of each species applied to trees sampled in community analysis

quadrats.



Model Development and Simulation


An ecosystem model was developed to characterize and quantify the

main components and processes of the titi shrub swamp wetland ecosystem

in Apalachicola, Florida. This ecosystem model was developed using a

diagrammatic language presented by Odum (1971, 1972). This energy-flow

or material-flow symbolic language is based on a series of modules that

represent both systems processes and mathematical functions connected by

lines representing transfer pathways of energy, materials or information

(Hall and Day 1977). The modular components can be used to construct

compartmental models of ecosystems. The language is also a tool for

developing computer programs to simulate a system of first order

nonlinear differential equations (Costanza and Sklar 1985) and was used

to develop a computer program to simulate the discharge of wastewater to










the titi shrub swamp in order to predict the long-term effects of the

addition of wastewater on wetland components.

The model was composed of forcing functions and storage

compartments or state variables. The forcing functions were solar

radiation, precipitation and wastewater. The storage compartments or

state variables were surface water, biomass, litter and soil, and the

water, carbon, nitrogen and phosphorus in these compartments. The

initial condition of each state variable was specified and transfer

coefficients were determined from the values of the storage and flows.

The simulation model was developed to indicate long-term (100 yrs)

dynamics of the titi shrub swamp receiving wastewater. In order to

facilitate the use of the model over long periods of time, all transfers

between compartments or state variables were taken as the annual net

accumulation in each compartment and, therefore, the cycling of

nutrients and other materials on a seasonal basis was not addressed.

Annual and seasonal variations in the forcing functions were also

ignored. There was only one autotrophic component (biomass), and

production was modeled as the interaction of an external limiting factor

(a flow limited source, solar radiation) and internal limiting factors

(nutrients). Therefore, production was limited by the rate of supply of

the external factor and by the recycling of internal factors.

The computer program was written in BASIC. Integration interval

of the differential equations was 0.1 yr.


















CHAPTER 3
RESULTS



Vegetation Analysis


The titi shrub swamp study site (Figure 4) is bordered by

flatwoods that were logged and then planted with slash pine. This

silvicultural activity included an attempt to drain the wetland with a

perimeter ditch.

Four wetland community types occur within the titi shrub swamp

study site: titi swamp-titi phase, titi swamp-holly phase, bay swamp-

mixed swamp phase, and black gum swamp.

Five phases of titi swamps were described by Clewell (1971). Two

phases, titi and holly, occur at the study site. In the titi phase

either red titi or black titi is dominant. Pines and the overstory are

usually absent (Clewell 1971). In the titi phase at the study site, red

titi is dominant, making up 28% of the community and black titi make up

16% of the community (Table 3). Together the titi species make up 45%

of the community. Slash pine make up less than 3% and shrub-size-class

individuals make up 83% of the community.

In the holly phase, Ilex myrtifolia (myrtle-leaf holly) is

dominant and an overstory is absent (Clewell 1971). Also, in small

swamps at the heads of minor drainages little-leaf cyrilla and

myrtle-leaf holly tend to grow together (Clewell 1971). In the holly























Figure 4. Map of the vegetation of the titi shrub swamp study site in Apalachicola,
Florida, including surface water sampling stations.











7.04 E4 m2 ~ Titi Swamp holly phase
2.28 ES m2 E31Titi Swoamp- titi phase
6.28 E4 m2 51 Blockgum Swamp
8.58 E4 m2 d Bay Swamp mixed swamp phase

X = proposed point of wastewater discharge
sampling stations numbered
Total area 3.88 E5 m2


%o
p.


-,I-










70
Table 3. Species characteristics of woody vegetation (>1.3 m high) in a titi
phase of the titi swamp in Apalachicola, Florida.




Dominance
Density
Importance Value
Relative Actual Relative Basal Relative Basis of 100%
Frequency Area
Species I Stratum Stems/ha % Stratum m'/ha % Stratum I Stratum Community


TREE SIZE CLASS

Taxodium ascendens 20.0 12.5 3.3 5.30 51.16 24.82 6.95
Cvrilla racemiflora 20.0 250.0 66.7 2.91 28.09 38.26 4.54
Pinus elliottii 20.0 12.5 3.3 0.94 9.07 10.79 2.15
Magnolia virginiane 20.0 50.0 13.3 0.68 6.56 13.29 1.90

vssa biflora 20.0 50.0 13.3 0.53 5.12 12.81 1.75

Tree Total 100.0 375.0 100.0 10.36 100.0 100.0 17.28


SHRUB SIZE CLASS

Crilla racemiflora 16.0 8150.0 22.7 10.94 54.89 31.20 23.98
Lvonia lucida 16.0 9000.0 25.1 1.07 5.37 15.49 13.90
Cliftonia monophvlla 12.0 8400.0 23.4 4.62 23.18 19.53 11.15
Clethra alnifolia 16.0 2150.0 6.0 0.19 0.95 7.65 6.63
Ilex coriacea 4.0 3100.0 8.6 0.29 1.45 7.38 6.51
Leucothoe axillaris 4.0 1800.0 5.0 0.52 2.62 3.87 3.34
Nyssa biflora 12.0 2400.0 6.7 1.75 8.78 3.47 2.96
Rhododendron e. 8.0 700.0 2.0 0.08 0.40 3.47 2.96
Magnolia virginiana 4.0 150.0 0.4 0.47 2.36 2.25 1.76

Shrub Total 100.0 35850.0 100.0 19.93 100.0 100.0 82.72


36225.0 30.29


GRAND TOTAL


100.0









phase at the study site, titi species together make up 35% of the

community, but myrtle-leaf holly make up 20% of the community (Table 4).

Black titi make up 18% of the community and little-leaf cyrilla make up

13% of the community. Three other species make up at least 10% of the

community. There are no tree-size-class individuals.

In the mixed swamp phase of bay swamps dominance is shared between

sweetbay and other species (Clewell 1971). The understory is usually

undifferentiated from the overstory and is composed of woody species

common in titi swamps. In the bay swamp at the study site, sweetbay

make up 35% of the community and black titi make up 58% of the community

(Table 5). Shrub-size-class individuals make up 64% of the community of

which 63% are titi species.

In black gum swamps, black gum is dominant and pond cypress is

usually present. The understory is absent or composed of saplings of

overstory species (Clewell 1971). In the black gum swamp at the study

site black gum make up 26% of the community and pond cypress make up 20%

of the community (Table 6). Shrub-size-class individuals make up 62% of

the community.

Tree-size-class individuals make up 16% of the vegetation at the

study site, but shrub-size-class individuals are the major component,

making up 84% (Table 7). Black titi has the highest importance value of

any species at the study site (21%) and the titi species together make

up 39% of the vegetation at the study site (Table 8).

The ground cover in titi swamps is continuous with the understory

and herbaceous species are absent except where these swamps border

flatwoods. Sphagnum sp. (sphagnum or peat moss) may also be present

(Clewell 1971). In the titi phase at the study site, no herbaceous











Table 4. Species characteristics of woody vegetation (>1.3 m high) in a
holly phase of the titi swamp in Apalachicola, Florida.





Dominance
Density
Importance Value
Relative Actual Relative Basal Relative Basis of 1002
Frequency Area
Species % Stratum Stems/ha % Stratum m'/ha % Stratum % Stratum Community


SHRUB SIZE CLASS

Ilex mvrtifolia 7.69 4350. 21.43 33.56 14.87 19.66 19.66
Cliftonia monophvlla 15.38 3000. 14.78 53.72 23.81 17.99 17.99
Cvrilla parviflora 7.69 2450. 12.07 42.73 18.94 12.90 12.90
Magnolia virniniana 15.38 3650. 17.98 10.72 4.75 12.70 12.70
Lyonia lucida 15.38 2350. 11.58 9.92 4.40 10.45 10.45
Mvric cerifera 15.38 800. 3.94 26.17 11.60 10.31 10.31
Hypericum reductu 3.86 2050. 10.10 22.77 10.09 8.02 8.02
Nvssa biflora 7.69 850. 4.18 6.85 3.04 4.97 4.97
Cvrilla racemiflora 7.69 450. 2.22 5.33 2.36 4.09 4.09
Persea borbonia 3.86 350. 1.72 13.86 6.14 3.91 3.91

Shrub Total 100.00 20300.00 100.00 225.63 110.00 100.00 100.00












Table 5. Species characteristics of woody vegetation (>1.3 m high) in
a mixed swamp phase of the Bay Swamp in Apalachicola,
Florida.





Dominance
Density
Importance Value
Relative Actual Relative Basal Relative Basis of 100%
Frequency Area
Species % Stratum Stems/ha % Stratum m2/ha I Stratum I Stratum Community


TREE SIZE CLASS

Cliftonia monophvlla 50.00 1025. 71.30 15.52 67.09 62.80 21.49
Magnolia virainiana 37.50 400. 27.79 7.31 29.69 31.66 11.59
Taxodium ascendens 12.50 12.5 0.91 0.79 3.21 5.54 2.39

Tree Total 100.00 1437.5 100.00 24.62 100.00 100.00 35.47


SHRUB SIZE CLASS

Cliftonia monophvlla 40.00 4900. 63.64 18.35 64.09 55.91 36.77
Magnolia virAiniana 40.00 2650. 34.41 9.68 33.81 36.07 23.13
Cvrilla racemiflora 20.00 150. 1.95 0.60 2.10 8.02 4.63

Shrub Total 100.00 7700.0 100.00 28.63 100.00 100.00 64.53


9137.5 53.25


GRAND TOTAL


100.00











Table 6.


Species characteristics of woody vegetation (>1.3 m high) in the
blackgum swamp in Apalachicola, Florida.


Dominance
Density
Importance Value
Relative Actual Relative Basal Relative Basis of 100%
Frequency Area

Species Z Stratum Stems/ha % Stratum m'/ha % Stratum % Stratum Community



TREE SIZE CLASS

Taxodium ascendens 30.77 487.5 31.50 14.30 47.34 36.54 15.97
Nvssa biflora 30.77 725.0 46.80 10.23 33.86 37.14 13.04
Cyrilla racemiflora 30.77 325.0 21.00 4.97 16.45 32.71 8.00
Pinus elliottii 7.69 12.5 0.80 0.71 2.35 3.61 1.44

Tree Total 100.00 1550.0 100.00 30.21 100.00 100.00 38.45

SHRUB SIZE CLASS

Nvssa biflora 14.81 3350.0 19.50 3.940 38.210 24.70 12.54
Lvonia lucida 14.81 4250.0 24.80 0.418 4.050 14.56 11.25
Cyrilla racemiflora 14.81 2200.0 12.80 2.970 28.840 18.83 9.70
Clethra alnifolia 14.81 1800.0 10.50 0.454 4.400 9.90 6.93
Ilex coriacea 7.40 2250.0 13.10 0.233 2.260 7.59 5.87
Leucothoe axillaris 11.11 1850.0 10.80 0.162 1.570 7.83 5.93
Taxodium ascendens 7.40 850.0 5.00 1.618 15.690 9.36 4.51
Ilex mvrtifolia 7.40 350.0 2.00 0.186 1.800 3.73 2.44
Cliftonia monophylla 3.70 150.0 0.90 0.321 3.110 2.57 1.36
Magnolia virginiana 3.70 100.0 0.60 0.005 0.048 1.46 1.02

Shrub Total 100.00 17150.0 100.00 10.310 100.000 100.00 61.55


GRAND TOTAL 18700.0 40.520 100.00












Table 7. Species characteristics of woody vegetation (>1.3 m high) in
the titi shrub swamp in Apalachicola, Florida.






Dominance

Density
Importance Values
Relative Actual Relative Basal Relative Basis of 100%
Frequency Area
Species % Stratum Stems/ha Z Stratum m'/ha % Stratum % Stratum Community


TREE SIZE CLASS

Taxodium ascendens 20.9 512.5 15.2 20.4 31.3 22.5 3.8
Cliftonia monophvlla 18.6 1025.0 30.5 16.5 25.3 24.8 3.5
Nvssa biflora 17.5 775.0 23.0 10.8 16.5 19.0 2.8
Magnolia virginiana 18.7 450.0 13.4 7.8 12.3 14.8 2.5
Cyrilla racemiflora 17.5 575.0 17.1 7.8 12.1 15.6 2.4
Pinus elliottii 6.8 25.0 0.8 1.6 2.5 3.3 0.7

Tree Total 100.0 3362.5 100.0 65.3 100.0 100.0 15.7

SHRUB SIZE CLASS

Cliftonia monophylla 13.7 16450.0 20.4 77.0 27.1 20.3 17.4
Lvonia lucida 13.7 15600.0 19.4 11.4 4.0 12.3 10.7
Cvrilla recemiflora 13.7 10950.0 13.5 19.8 7.0 11.4 9.7
Magnolia virginiana 11.3 6400.0 7.9 20.4 7.2 8.8 7.3
Nvssa biflora 10.2 6600.0 8.2 12.5 4.4 7.6 6.4
Ilex myrtifolia 4.6 4700.0 5.8 33.8 11.9 7.4 6.2
Cvrilla parviflora 2.2 2450.0 3.0 42.7 15.0 6.8 5.6
Myrica cerifera 4.6 800.0 1.0 26.2 9.2 4.9 4.0
Clethra alnifolia 9.1 3950.0 4.9 0.6 0.2 4.8 3.9

Ilex coriacea 5.7 5350.0 6.6 0.5 0.2 4.2 3.6
ypericum reductum 1.1 2050.0 2.5 22.8 8.0 4.0 3.3
Leucothoe axillaris 4.6 3650.0 4.5 0.7 0.2 3.1 2.7
Persea borbonia 1.1 350.0 0.4 13.9 4.9 2.1 1.7
Taxodium ascendens 2.2 850.0 1.1 1.6 0.6 1.3 1.0
Rhododendron canascens 2.2 700.0 0.9 0.1 0.1 1.0 0.8

Shrub Total 100.0 80850.0 100.0 284.0 100.0 100.0 84.3


84212.5 349.2


100.0


GRAND TOTAL










Table 8. Importance values for woody vegetation species (>1.3 m high)
in the titi shrub swamp in Apalachicola, Florida. All
species combined regardless of size class.




Species Importance Value


Cliftonia monophylla 20.9
Cyrilla racemiflora 12.1
Lyonia lucida 10.7
Magnolia virginiana 9.8
Nyssa biflora 9.1
Ilex myrtifolia 6.2
Cyrilla parvifolia 5.6
Taxodium ascendens 4.9
Myrica cerifera 4.0
Clethra alnifolia 3.9
Ilex coriacea 3.6
Hypericum reductum 3.3
Leucothoe axillaris 2.7
Persea borbonia 1.7
Rhododendron sp. 0.8
Pinus elliottii 0.7


100.0


TOTAL










species are present, sphagnum is abundant (63%) (Table 9), and shrub

ground cover species are predominantly the same as those in the

understory (Table 3). The holly phase is bordered by flatwoods (Figure

4) which accounts for the presence of herbaceous species such as

Hypericum reductum, Xyris sp. (yellow-eyed grass), and Lachnanthes

tinctoria. Sphagnum is abundant (56%) and shrub ground cover species

are primarily the same as the vegetation greater than 1.3 m in height

(Table 4).

The ground cover in bay swamps is also continuous with the under-

story or else sparse and patchy. Beds of peat moss are often conspic-

uous and sedges may be scattered (Clewell 1971). Sphagnum is abundant

(46%) in the bay swamp, yellow-eyed grass, a sedge, is present, and the

shrub ground cover species are primarily the same as those in the

understory (Table 5). Ground cover in black gum swamps is absent

(Clewell 1971). Sphagnum is very abundant in the black gum swamp (94%)

and the shrub ground cover species are primarily the same as those in

the understory (Table 6).

Aquatic macrophytes, including emergents, floating leaved plants,

and submergents, are not a significant component of the titi shrub

swamp. Shading prevents their growth but Utricularia sp. (bladderwort)

does occur in the deep water areas. Although not a significant

component, aquatic macrophytes do exist in open areas of flatwood

depressions and along the margins of deeper swamps. Species found in

these areas at the study site include Hypericum reductum, Lachnanthes

tinctoria, yellow-eyed grass, Rhynchospora sp., Scleria sp.,

bladderwort, Eriocaulon sp., Sarracenia sp., and Drosera sp.










Table 9. Percent ground cover in the four community types in the titi shrub
swamp in Apalachicola, Florida.


Titi swamp titi phase

Sphagnum sp.
Lyonia lucida
Bare hummock
Clethra alnifolia
Ilex corriacea
Rhododendron sp.
Cyrilla racemiflora
Pierus pillyreifolia
Leucothoe axillaris
Cliftonia monophylla


Bay swamp mixed swamp phase


Bare hummock
Lyonia lucida
Xyris sp.
Sphagnum sp.
Cyrilla racemiflora
Clethra alnifolia
Cliftonia monophylla


Titi swamp holly phase

Sphagnum sp.
Lyonia lucida
Hypericum reductum
Xyris sp.
Cliftonia monophylla
Cyrilla parvifolia
Myrica cerifera
Lachnanthes tinctoria
Ilex myrtifolia
Sabal palmetto


Black gum swamp


Sphagnum sp.
Bare hummock
Ilex corriacea
Cyrilla racemiflora
Lyonia lucida
Rhododendron sp.










Biomass and Nutrient Standing Stock Estimates


For the three species measured, the bole, branch and leaf biomass

make up 69%, 28% and 3% of the total aboveground biomass, respectively

(Table 10). The regression equations used to estimate branch and leaf

biomass based on primary branch diameter, and aboveground biomass and

leaf biomass based on the dbh of individuals in vegetation analysis

quadrats are presented in Appendix B.

Aboveground estimates of the woody vegetation (greater than 1.3 m

high) in the four community types are presented in Tables 11, 12, 13 and

14. Herbaceous biomass and litter estimates in the four community types

are presented in Table 15. A summary of the aboveground biomass

estimate of the four community types is presented in Table 16.

The holly phase of the titi swamp has the smallest aboveground

biomass of the four community types. This is not surprising as no tree-

size-class individuals are present. The herbaceous component makes up

24% of the biomass of this community, a large portion of which is

sphagnum (Table 9). In the titi phase of the titi swamp, tree-size-

class individuals make up 58% and shrub-size-class individuals make up

41% of the biomass. The herbaceous component makes up less than 1.5% of

the biomass of this community. In the black gum swamp, tree-size-class

individuals make up 76% and shrub-size-class individuals make up only

21% of the biomass of this community. The herbaceous component makes up

3% of the biomass of this community and is almost entirely composed of

sphagnum (Table 9). Very little litter was recorded in the black gum

swamp as compared to the other community types. The bay swamp has the

largest aboveground biomass of the four community types. Trees make up

52% and shrubs make up 48% of the biomass of this community. The










Table 10. The dbh,estimated bole, branch, leaf and above ground
biomass for ten individuals for black titi, red titi,
and sweetbay sampled at the study site.



dbh height bole branch leaf above
(cm) (m) (kg) (kg) (kg) ground
biomass
Species (kg)


Black titi 18.5 11.4 90.5 35.4 6.5 132.5
16.8 15.0 74.3 18.8 2.9 96.1
15.0 13.1 57.5 25.4 3.7 86.6
12.5 11.4 31.9 15.6 2.1 49.7
8.6 10.2 17.3 5.4 0.8 23.5
6.9 8.6 10.8 7.7 1.0 19.4
6.5 7.4 7.0 3.7 0.4 11.1
4.5 5.6 3.0 0.6 0.1 3.8
3.9 5.5 1.9 0.6 0.1 2.6
3.6 4.8 1.8 0.5 0.1 2.4

Total 296.0 113.7 17.8 427.7
% 69.0 27.0 4.0 100.0


Red titi


22.0
18.2
14.9
12.8
10.4
7.6
5.2
5.0
4.0
3.4


Total
%X


8.6
8.3
8.7
7.7
7.9
6.9
6.1
6.8
5.5
5.0


40.2
24.3
31.5
20.9
16.1
4.7
3.1
3.1
1.9
2.0


52.9
17.1
17.9
15.4
12.1
1.3
0.9
0.9
0.2
0.3


147.8 119.0
54.0 44.0


3.4
0.7
1.0
0.8
0.4
0.2
94.1
0.2
0.1
7.1

7.0
2.0


96.5
42.2
50.4
37.0
28.7
6.2
4.1
4.2
2.3
2.4

274.0
100.0










Table 10. Continued.


dbh height bole branch leaf above
(cm) (kg) (kg) (kg) ground
biomass
Species (kg)


Sweet bay 17.6 11.7 61.5 16.6 2.8 80.8
13.9 12.7 49.0 3.8 1.1 54.0
13.5 12.0 44.6 5.3 1.2 51.1
10.5 10.8 23.2 3.5 0.7 27.4
9.1 12.0 17.4 0.6 0.2 18.1
7.4 8.3 9.1 0.7 0.3 10.1
6.8 9.6 8.9 1.1 0.4 10.4
6.2 9.4 7.2 0.7 0.3 8.2
4.4 7.4 3.4 0.2 0.1 3.6
4.1 6.2 2.9 0.4 0.1 3.4

Total 227.2 32.9 7.2 267.1
% 85.0 12.0 3.0 100.0


Average % for
three species


69.0 28.0


3.0










Table 11.


Aboveground biomass estimate of woody vegetation
(>1.3m high) in a titi phase of the titi swamp in
Apalachicola, Florida.


Species Size Class Regression # Biomass
(cm dbh) in Appendix B (g/m2)


Cyrilla racemiflora
Cyrilla racemiflora
Cyrilla racemiflora



Cliftonia monophylla
Cliftonia monophylla


Magnolia virginiana
Magnolia virginiana


Nyssa biflora
Nyssa biflora
Nyssa biflora


Taxodium ascendens
Pinus elliottii
Leucothoe axillaris
Clethra alnifolia
Ilex coriacea
Lyonia lucida
Rhododendron sp.


>10
10< >4
<4



10< >4
<4


>10
10< >4


>10
10< >4
<4


>10
>10
<4
<4
<4
<4
<4


669.2
470.2
473.0
1612.4


661.7
645.1
1306.8

209.4
103.2
312.6

191.4
145.3
303.7
640.4

2575.8
1223.0
146.9
54.2
86.4
295.7
22.6


8276.8


Total










Table 12.


Aboveground biomass estimate of woody vegetation (>1.3m
high) in a holly phase of the titi swamp in Apalachicola,
Florida.


Species Size Class Regression # Biomass
(cm dbh) in Appendix B (g/m')


Magnolia virginiana <4 10 299.1

Cliftonia monophylla <4 10 147.4

Cyrilla parviflora <4 10 146.5

Cyrilla racemiflora <4 10 17.6

Ilex myrtifolia <4 10 113.2

Myrica cerifera <4 10 72.0

Lyonia lucida <4 10 38.8

Nyssa biflora <4 10 22.0

Persea borbonia <4 10 37.9

Hypericum reductum <4 10 70.6


Total 965.1











Table 13.


Aboveground biomass estimate of woody vegetation (>1.3m
high) in a mixed swamp phase of the bay swamp in
Apalachicola, Florida.


Species Size Class Regression # Biomass
(cm dbh) in Appendix B (g/m2)


Magnolia virginiana >10 9 2245.2
Magnolia virginiana 10< >4 9 2435.0
Magnolia virginiana <4 10 76.6
4756.8

Cliftonia monophylla >10 7 7277.7
Cliftonia monophylla 10< >4 7 6669.0
13946.7

Taxodium ascendens >10 13 301.2

Cyrilla racemiflora 10< >4 8 47.8
Cyrilla racemiflora <4 10 9.9
571.

Total 19120.0











Table 14. Aboveground biomass estimate of woody vegetations
(>1.3m high) in the black gum swamp in Apalachicola,
Florida.



Species Size Class Regression # Biomass
(cm dbh) in Appendix B (g/m2)


Nvssa biflora <10 11 4012.8
Nyssa biflora 10< >4 11 901.7
Nyssa biflora <4 10 244.9
5159.4

Pinus elliottii >10 12 791.4

Taxodium ascendens 210 13 4509.4
Taxodium ascendens 10< >4 13 475.3
Taxodium ascendens <4 10 72.5
5057.2

Cyrilla racemiflora 210 8 1171.2
Cyrilla racemiflora 10< 24 8 459.8
Cyrilla racemiflora <4 10 156.1
1787.1

Magnolia virginiana 10< >4 9 65.3
Magnolia virginiana <4 10 10.4
75.7

Cliftonia monophylla 10< >4 7 107.8
Cliftonia monophylla <4 10 9.3
117.1

Clethra alnifolia <4 10 124.7
Ilex myrtifolia <4 10 44.6
Ilex coriacea <4 10 92.0
Lvonia lucida <4 10 132.8
Leucothoe axillaris <4 10 49.4


Total 13431.4


13431.4


Total










Table 15.


Herbaceous biomass and litter estimates of the four
community types in the titi shrub swamp in Apalachicola,
Florida.


Community Type Herbaceous Biomass Litter
(g/m') (g/m')


Titi swamp titi phase 123.7 750.4

Titi swamp holly phase 301.5 511.5

Bay swamp mixed swamp phase 10.7 878.2

Black gum swamp 459.4 90.7


Average for titi shrub swamp
(n-20) 224 558









Table 16. Aboveground biomass estimate of the four community types in the titi shrub swamp in Apalachicola,
Florida.


Biomass (g/m')

Tree Size Shrub Size Class Herbaceous Total Total
Class
Community Type _10 cm dbh 10 <4 cm dbh <4 cm dbh kg/mr


Titi swamp -
titi phase 4868.8 1380.4 2027.6 123.7 8400.5 8.4

Titi swamp -
holly phase 0 0 965.1 301.5 1266.6 1.3

Bay swamp -
mixed swamp phase 9824.1 9151.7 86.4 10.7 19072.9 19.1

Black gum swamp 10484.7 2009.9 936.8 459.4 13890.8 13.9




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