Oct 12, 1993 - Sedimented pigments (chlorophyll a and pheophytin a) concentrations were measured following extraction in glass tissue grinders with -4 ml ...
Microb Ecol (1994) 27:1-17
MICROBIAL ECOLOGY
?D 1994 Sprnger-VerlagNew York Inc.
Does Microbial Biomass Affect Pelagic Ecosystem Efficiency? An Experimental Study J.D. Wehr,J. Le, L. Campbell Louis Calder Center, Fordham University, PO Box K, Armonk, NY 10504, USA
Received:9 May 1993; Revised:12 October1993
in the pelagiczone participate Abstract. Bacteriaandothermicroorganisms in the recyclingof organicmatterandnutrientswithinthe watercolumn.The microbialloop is thoughtto enhanceecosystemefficiencythroughrapidrecycling andreducedsinkingrates,thusreducingthe loss of nutrientscontainedin organismsremainingwithinthe photiczone. We conductedexperimentswith lakecommunitiesin 5400-litermesocosms,andmeasuredthe flux of materials and nutrientsout of the water column. A factorialdesign manipulated8 4 phosphoruslevels x 2 nitrogenlevels. Totalsedimentanutrienttreatments: tion ratesweregreatestin high-Nmesocosms;withinN-surpluscommunities, 3 1,UM P resultedin 50%increasein totalparticulatelosses. P additionswithout addedN had small effects on nutrientlosses fromthe photiczone; +2 jLM P tanksreceived 334 mg P per tank, yet after 14 days lost only 69 mg more particulate-Pthan did control communities.Nutrienttreatmentsresultedin markeddifferencesin phytoplanktonbiomass (twofold N effect, fivefold P effect in +N mesocosmsonly), bacterioplankton densities(twofoldN-effect, twofoldP effects in -N and +N mesocosms),andthe relativeimportanceof autotrophic picoplankton(maximumin highN:Pmesocosms).Multipleregression analysisfoundthatof 8 planktonandwaterchemistryvariables,the ratio of autotrophic picoplanktonto totalphytoplankton (measuredas chlorophylla) explainedthe largestportionof the total variationin sedimentationloss rates (65%of P-flux, 57%of N-flux, 26%of totalflux). In each case, systemswith greaterrelativeimportanceof autotrophicpicoplanktonhad significantlyreduced loss rates. In contrast,greaternumbersof planktonicbacteriawere associatedwithincreasedsedimentation ratesandlowersystemefficiency.We suggestthatdifferentmicrobialcomponentsmay have contrastingeffects on the presumedenhancedefficiencyprovidedby the microbialloop.
to: J.D. Wehr. Correspondence
2
J.D. Wehr et al.
Introduction The loss of planktonicmaterialsto the sedimentsof lakesis one of the fundamental processesin freshwaterecosystems.Theselosses leadtowardthe immobilizationof organicmatterandnutrientsto the sediments,andtheeventualrecyclingof material followingdecompositionandturnover.Despitethe factthatmostof the sedimented organic matterproducedby phytoplanktonis decomposed[45], autochthonous sinkingparticles(deadphytoplankton,fecal pellets, organicdetritus)representa net loss of nutrientsfrom the photic zone in most stratifiedlakes, until after turnover.Traditionally,nutrientcycling in lakes is thus thoughtof in termsof a phytoplankton-zooplankton-fish model, in which the returnof nutrientsdepends on settledparticlesbeing decomposedand remixedinto the watercolumnin the spring or autumn.Factorsaffecting the flux rate of planktonicmaterialsmay includesystemproductivity,planktonparticlesize, andbasinmorphometry. However, within a given productivityrange, otherbiotic processesmay enhancethe regenerationof nutrientswithinthe watercolumnandreducesystemlosses to the sediments.Bacteriaandotherpelagic microorganisms participatein the recycling of organicmatter[3, 5, 6]. It has been proposedthat a microbialfood web consistingof bacteria,picophytoplankton,and herbivorousflagellatesand ciliates can act to shuntprimary productionandnutrientsawayfroma "linear"metazoanfood chainto a morerapid andefficientrecyclingmechanism[3, 33]. The importanceof this microbialloop for pelagic ecosystem efficiency and the retentionof inorganicnutrientsin the photic zone needs to be quantified.Argumentshave followed that predictthat microorganisms, dueto theirhighsurfaceareato volumeratios,rapidgrowthrates, and slower sinking rates, will enhancethe likelihood of nutrientscontainedin organismsremainingwithin the photic zone [37]. Thus, a yardstickfor pelagic ecosystemefficiency may be measuredaccordingto reducedrates of downward nutrientflux (="losses"), andmay be comparedwith recentlyproposedmeasures of bacterialandothermicrobialbiomassandgrowth. Basedon the ideasrepresentedin microbialloop theory,rapidgrowthratesand efficient remineralizationof nutrientscan be maintainedonly if there is tight couplingbetweenprotistgrazersand theirbacterialprey [18, 37]. However,it is not clear whetherthis predictionconsidersboth heterotrophicbacteriaand autotrophicpicoplanktonin this size range.Thesetwo components,whilephysiologically quitedistinct,competefor some of the sameresources.Recentexperiments indicate that the growth of heterotrophicbacteriamay at times be limited by inorganicnutrients[15, 40], suggestingthat these microorganismsmay at times become a sink for nutrientswithin the microbialloop. Indeed, Caron[14] has shownthatphytoplankton typicallyhave C:N andC:P ratioshigherthanthe Redfield ratioof 106C:16N:iP,while planktonicbacteriatend to have C:N and C:P ratiosbelo-v this ratio. Studieshaveshownthattherelativeabundanceof autotrophic picoplanktontends to be greatestin oligotrophic(typicallyP-limitedin freshwater)ecosystems[13, 35, 43], but apparentlyis not limitedby the supplyof dissolvedinorganicphosphorus (DIP)in eithereutrophicor oligotrophiclakes [41, 44]. Surprisingly,the growthof heterotrophic bacterioplankton was shownto be directlylimitedby DIPavailability in the samesystem[40]. Theseexperimentsraisequestionsconcerningthe apparent
MicrobialLoop Efficiency
3
universalimportanceof P limitationin freshwaters[32]. The ecosystemimpactof andprotozoamaythusdepend moreefficientprocessingby certainmicroorganisms not only on the totalproductionof microbialorganisms,but also on the differing withinthe microbialloop. nutrientconstraintsthataffectthe compartments In this study we proposethat differencesin total microbialbiomass and the relativeimportanceof heterotrophic andautotrophicpicoplanktonwithinthe photic zone will affectsystemefficiency.Basedon earlierresultsindicatingdifferencesin nutrientlimitation,we predictthatautotrophicpicoplanktonin particularwill have a positive effect on the retentionof nutrientsin the watercolumn (i.e., reduced nutrientsedimentation).We testedthis idea by manipulatingpelagiclake communitiesin largemesocosms,andmeasuringthe flux of materialsandnutrientsout of the watercolumn. Materials and Methods Site Description and Design Experimentswere conductedat the ExperimentalLake Facility(ELF) at the Louis CalderCenter, FordhamUniversity(Armonk,NY, USA). The facility contains24 fiberglass,outdoormesocosms (1.9 m diam;2.1 m high;filled to 5400 litersper tank)thatare directlypump-fedwith CalderLake water[see 41, 42 for detailson the lake] throughprewashed,opaquepolyethylenepipe. Mesocosms were filled in darknessduringan 8h periodon 1 June 1992, whenCalderLakewas weaklystratified (AT 2?C/m).Night collectionensuredthatverticallymigratingzooplankton(principallyDaphnia pulicaria)occurredin all ELFtanksat similarlevels. Nylonnetting(1 cm mesh)was placedovereach to minimizeinputsof leavesandwoodydebris. A factorialdesignconsistedof 8 nutrienttreatments: 4 P levels (0, 0.5, 1.0, or 2.0 ,umolK2HPO4/1 added)x 2 N levels (0 or 10 ,umolNH4NO3/l),with eachblockreplicatedthreetimes. The intentof this design was to manipulatenutrientlevels andN:P ratiossuch thatphytoplankton productionand communitysize structurevariedover the full rangeobservedin earlierstudies[41]. Nutrientswere addedon day0 duringfilling to allow sufficientmixing,anda secondidenticalset was appliedon day 14 followingthe thirdweeklysampling(see below);the experimentranfor 28 days. Theprimarygoal was to examinewhetherlosses of planktonicmaterialsfromthe watercolumnincreaseor decreaseas a functionof nutrientconditionsand microbialprocesses. The basic models tested include (1) an ANOVAmodel, in whichmanipulated variables(N, P, N x P) areclassifiedas treatments,and(2) a regressionmodel, in which observedplanktonvariables(levels of planktonicbacteriaand "algal" andmicroplankton) areclassifiedas independentvariables(see also later picoplankton,nanoplankton, in DataAnalysis).
Field Sampling A series of samples were collected weekly startingon day 0 (4h after filling) throughday 28. Temperatureand pH were measuredat the ELF tanks in situ. Waterand planktonsampleswere collectedby peristalticpumpfrom0.5 m depth.Pairsof waterchemistrysampleswerefilteredin line (WhatmanGF/F);one set was acidifiedto pH 2 (withH2SO4), andthe otherset was frozen(- 15?C). Planktonchlorophyllwas collectedin 1-literbottleswhile prefilteringmicroplankton through20-p.m meshsize Nitex. The remainingfiltratewas keptrefrigerated (-4?C) untilreturnedto the lab. To measureratesof planktonand otherparticulatelosses, a free-standing,verticalsedimenttrap (withweightedbottom)was placedin the center-bottomof each ELF tank(retrievedby two nylon stringsattachedto the rimof the tanks).The cylindricaldesignfollowedgeneralrecommendations of Hargraveand Burns[20]and Bloesch and Burns[8], with a length/widthratioof about5.5:1 (total
4
J.D. Wehret al.
volume550 ml) to minimizeturbulence.Trapswere constructedfrom55 mm ID whitePVC, with a polypropylenefunnelfittedinsideat the bottomto focus the settledsediment.A clampedplastictube was attachedto eachfunnelso thatweeklysamplesof trappedsedimentcouldbe siphonedintosample bottles(storedat 4?C)andthe trapsreturnedto eachELFtankimmediatelyaftersampling.Following Kirchner[24], 90 ml of 5% NaCl was first placedinto the bottomof each trapto createa density gradientand preventmaterialloss while traps were raised to the surface. Tests with saline plus methyleneblue indicatedlittleor no loss duringtransfer.
Laboratory Methods Waterchemistrysampleswereanalyzedforconcentrations of soluble-reactive phosphorus(SRP)using theantimony-ascorbate-molybdate method[1, 91 andfor totaldissolvedP as above, followingpersulfate digestion[29]. NH4+-Nconcentrationswere measuredby the phenol-hypochlorite method,and NO3-(afterreductionto NO2-in a Cd-Cucolumn)via reactionwithsulfanilamide-NNED [1, 10, 11]. Soluble-reactiveSi (as Si02) was measuredby the molybdosilicatemethod[1, 12]. Methodswere modifiedfor automatedanalysisandrunon a Traacs800 automatedanalyzer(Bran+LuebbeTechnologies, Inc., BuffaloGrove,IL). Sediment-trap samples(in water)were mixed thoroughly,split into four parts,and filteredonto either25 mm (for particulateN, P) or 47 mm (totaldry weight, pigments)diameterWhatmanGF/F glass fiberfilters(volumesrecorded).Portionsof filteredresidueused for N, P, andpigmentanalysis wereimmediatelyfrozenuntildigestion;totaldrymasssampleswereplacedin a dryingoven (105?C) for48h, thencooledin a desiccator.Particulate N andP weredigested(30 min)underpressure(120?C, 15 psi) in Pyrextubesusingacid (H2SO4) perchlorate[29]. Dry mass accumulationwas measuredto the nearest0.1 mg. Sedimentedpigments(chlorophylla and pheophytina) concentrationswere measuredfollowingextractionin glass tissue grinderswith -4 ml neutral90%acetone(+MgCO3). Extractswerepouredintograduatedcentrifugetubes,madeup to knownvolume,andfurtherextracted in the dark (M) 0.5 P
0P NO N ADDED Temp pH SRP NH4 NO3 SiO2 +10 FM NH4NO3 Temp pH SRP NH4 NO3 SiO2
18.5 ? 7.56 ? 0.04 ? 6.7 ? 0.34 ? 11.7 ?
0.1 0.12 0.01 1.9 0.01 0.3
18.8 ? 0.5 7.54 ? 0.27 0.03 ? 0.01 10.6 ? 0.5 11.5 ? 0.3 10.9?0.1
18.8 ? 7.56 ? 0.38 ? 6.7 ? 0.31 ? 11.1
0.9 0.14 0.02 0.4 0.02 0.1
18.6 ? 0.1 7.54 ? 0.12 0.34 ? 0.02 14.8 ? 0.7 11.4 0.2 11.4?0.1
1.0P 18.4 ? 7.54 ? 0.81 ? 6.1 ? 0.30 ? 11.1
2.0P
0.2 0.29 0.06 0.2 0.04 0.1
18.6 ? 0.1 7.49 ? 0.08 1.71 ? 0.05 6.0 +0.1 0.29 ? 0.04 11.4 0.03
18.3 ? 0.5 7.53 ? 0.22 0.80 ? 0.02 9.7 ? 0.5 11.6 0.3 11.3?0.4
18.4 ? 0.6 7.58 ? 0.22 1.76 ? 0.04 14.6 ? 0.3 11.6 ? 0.3 11.3?0.1
variableswere testedfor theireffects on sedimentationlosses: bacterioplankton density,autotrophic picoplankton,autotrophicnanoplankton,autotrophicmicroplankton,ratio of pico: SChla, ratio of bacteria:lChla,[SRP],anddissolvedinorganicN ([DIN]). Ratiosof pico:lChla andbacteria:lChla were includedto test whethera predominance(ratherthansimple density)of microbialcells, both altersystemslosses andecosystemefficiency.The maximumcriterion autotrophicandheterotrophic, for inclusionof independentvariablesinto the modelwas (x = 0.05, andthe minimumfor exclusion was a = 0.10. All datawerecheckedforassumptionsof normalityandhomogeneityof variancesprior to analysis. Insummary,thetwo modelsmakedifferentbiologicalassumptionsabouttheproximateandultimate factorsleadingto particulatelosses to the benthos.The ANOVAmodelsexaminesolely the effect of manipulations(i.e., N andP loadings),which may have directeffects on sedimentation,or indirect effects throughchangesin planktonbiomassor shifts in communityand size structure.The MLR modelsidentifywhichof severalmeasuredvariablesin thewatercolumn,singlyorcollectivelyexplain the differencesin sedimentationlosses over time. These factorsmay be thoughtof as havingmore immediateand directeffects on sedimentationrates, despitehavingnot been directlymanipulated. Each approachhas its limitations,but both are useful startingpoints for makingpredictionsabout ecosystemefficiencyunderdifferentnutrientandplanktoncommunityconditions.
Results Physical and Chemical Conditions
The measuredconcentrations of SRP at the startof the experimentwere somewhat below nominaltreatmentlevels for P added(about80%), but N treatmentswere close to targetvalues (Table 1). Nutrientswere nonethelesssignificantlydifferent acrosstreatments(ANOVA;P < 0.01 in all cases) andnot significantlydifferent withintreatments(ANOVA;P > 0.5 in all cases). ActualP treatmentsthusrepresenteda gradientof about1x, 0x, 25 x, and50 x of ambientconditionsin Calder
6
J.D. Wehret al.
+10 FtMNH4NO3
No Nitrogen Added 8 -
*
Z
0 ?ojNg6
-
WE4
R -
*No P Added +0.5 [M P + 1.0 1MP
-8
7
?6
4
UWc6m3
3
2
2
1
1
0
0
-J3
0
0
7
14
21
28 0
7
14
21
28
20-
-20
0 TIME
(Dy1s5
a c 10
10
0
0 0
7
14
21
28
0
7
14
21
28
TIME (Days) Fig. 1. Cumulative,total particleflux from the watercolumn to the sedimentsas a functionof nitrogenand phosphorusmanipulations,measuredweekly in CalderLake mesocosms. Rates are measured in terms of total dry weight (upperpanel), and pheophytin a accumulation (lower panet). All
dataareaverageratesfromthreereplicatemesocosmsfor eachnutrienttreatment.
Lake.All non-manipulated variablesmeasured,suchas temperature, pH, andother chemicalconditions,remainedsimilaramongall 24 tanksthroughoutthe study. SedimentationLosses The firstgoal was to determinewhethermanipulations of nitrogenandphosphorus levels affect total and specific losses of materialsout of the euphoticzone. A particularinterestwas whetherlosses observeddiffer from those predictedby simple increasesin planktonbiomass. Over 28 days, sedimentationproceededat markedlydifferentratesaccordingto treatmentconditions(Fig. 1). Each pair of treatmentgroups(no N addedvs. 10 ,umolNH4NO3addedperliter)is presentedin two plots representingthe effect of P additionson particulatelosses to the sedi-
MicrobialLoop Efficiency
7
ments.Sedimentationof planktonicmaterials(dryweight)out of the watercolumn was notdifferentacrossa wideP-treatment gradientin mesocosmswithoutaddedN (Fig. 1, upper panel). However, losses overall were nearly twice as great in systemswith 10 ,umolNH4NO3addedperliter, whichcorrespondwith a doubling in surfaceplanktonbiomass (see below). Withinthese N-fertilizedmesocosms, phosphorustreatments 1 ,Iumol/lresultedin about 50% greatertotal plankton losses thancontrol-Ptanks.Thiseffect was apparentby day 14 of the study. Phytoplankton deathandsinkingrates,as judgedby the weeklyaccumulationof pheophytina, weredramaticallyaffectedby bothaqueousN andP conditions(Fig. 1, lower panel). Nitrogen-fertilized mesocosms received up to three times more
deadalgalmaterialthanthe sedimentsof N-limitedsystems,althoughthis was not observedin communitieslackinga P addition.The P treatmentsalso elicitedearlier (by day 14) and strongerresponsesthan were observedfor total or particulate nutrientsedimentation.The rangeof 0 to 2.0 ,umolP addedper liter (z0.4 to 1.8 resultedin an averageincreasein the cumulativeloss ratefrom3.9 FIMP measured) to 18.8 [ig pheophytinper cm2 of sedimentsurface,nearlyfivefold (i.e., 500%) greater.This greatlyacceleratedpigmentaccumulationcorrespondswith only a 50%increasein the totalmassof sedimentedplanktonicmaterials. Particulatenutrientlosses were not necessarilyrelatedto increasedloadingsof those nutrients.In CalderLakewater,P additionsalonehadno apparenteffect on losses of thisnutrientto sediments(Fig. 2, upperpanel). Particulate-P accumulated in the sedimentsof N-limitedsystemsat similarratesacrossthe wide rangeof P treatments.This meansthata 50-fold increasein DIP loadinghadlittle effect on P losses in thesemesocosms.Becausethe totalvolumeof each mesocosmis known, differencesin the retentionof P withinthe euphoticzone can be estimatedaccurately.Systemssuppliedwith2.0 ,umolP/Ireceivedon day 0 an additional334 mg of P (as K2HPO4).After 14 daysthesecommunitieslost only 69 mg moreparticulate-P (24.9% greater)than did controlcommunities.However, the additionof inorganicN greatlyacceleratedP sedimentation,withmaximumlosses observedat P (0.5-1.0 ,umolP addedperliter)treatments.By the end highN andintermediate of theexperiment,sedimenttrapsin phosphorus-limited mesocosmsreceivedabout 28%less particulate-P(- 16.8 [Lg/cm2)thanthose receiving2.0 ptmolP/1(=23.3 pLg/cm2).Nitrogenlosses exhibiteda similarpattern(Fig. 2, lower panel), although P treatmentshadapparentlylittleeffect on N retentionor N loss in most systems. The significanceof direct nutrientmanipulationson sedimentationrates was consideredfor each dateby two-wayanalysisof variance(Table2). The totalloss of materials(as dryweight)was not significantlyaffectedby eitherN or P untilday 14, andby P treatmentsonly by day 28. Nitrogenclearlywas the most important treatmentvariablecontrollingtotal sedimentationrates. ANOVA was not able to detect any significantN x P interactioneffect (such as N:P ratio in the water column)on these rates. Losses of P, however, were affected by both N and P treatments(andN x P interactions)in the watercolumnby the end of the experiment.Systemlosses of N weresignificantlyaffectedby N additionsthroughoutthe study,butthe analysisindicatedthatP additionshadno significanteffects. Unlike the othervariablesmeasured,pheophytinsedimentationwas significantlyaffected by both N and P treatments,and exhibitedsignificantlytreatmentinteractions. Fromthis perspective,P treatmentsresultedin significantlygreaterloss of algal materialwhen N was also added, even on day 7. The importanceof N x P
J.D. Wehret al.
8
+10 FiMNH4NO3
No Nitrogen Added * *
30 -
A
4
225
z ZE
7
No P Added + 0.5 FM P + 1.0 RMP P7 280
- 30 2- 25
20 -20
z
w ~- 15
15
-
7510 -10 077 5-
O.0
0
0
0
7
14
21
28 0
7
14
21
28
70 -
-70
zZE 60 --60 -
04
20
20 0 z1-1
-0 07-4
1
280
TIME
74421
2
(Days)
nutrientflux fromthe watercolumnto the sedimentsas a functionof Fig. 2. Cumulative,particulate nitrogenand phosphorusmanipulations,measuredweekly in CalderLake mesocosms. Rates are measuredin termsof particulateP (upperpanel), andparticulateN accumulation(lower panel). All dataareaverageratesfromthreereplicatemesocosmsfor eachnutrienttreatment.
interactionon algal losses contrastswith the repeatednonsignificanceof such an interactioneffect on totalsedimentationrates. Microbial Biomass and Sedimentation
A secondobjectiveof this studywas to examinethe relationshipbetweenmicrobial planktonbiomass(algalandbacterial)andsystemefficiency.Directmanipulations of N and P supplyto the euphoticzone alteredtotal biomasslevels as well as the relativeimportanceof varioussize fractionswithinthe plankton(Fig. 3). Control (no P or N added)densitiesof phytoplanktonand bacteriawere not significantly andbacterioplankton producdifferentfromlevels in CalderLake. Phytoplankton systems,butonly bacteriaincreasedin tionlevels weregreatestin N-supplemented responseto P additionswithoutadded N. Biomass responsesto P additionsin
MicrobialLoop Efficiency
9
in experimentalmesocosms,as characterTable 2. Effectsof fertilizationon planktonsedimentation ized by total(drymass),phosphorus,nitrogen,andpheophytinloss rates(see Fig. 1 for details).Data arefroma two-wayanalysisof varianceof theeffectsof N addition(noneor 10 FAMNH4NO3)and/orP addition(none,0.5, 1, or 2 FM K2HPO4)on ratesof totaldrymass (g drywt/cm2 perday), P, N (p.g nutrient/cm2 per day), and pheophytin(p.g pheo a/cm2 per day) accumulationmeasuredat weekly intervals(a nominalP level of "0.000"is some unknownprobabilityless than0.001) Day 7 Treatment F-ratio
P-value
Total sedimentation N 0.327 0.576 P 0.488 0.696 Nx P 0.830 0.497 Phosphorussedimentation N 0.013 7.798 P 0.047 3.299 Nx P 1.102 0.377 Nitrogensedimentation N 6.394 0.022 P 0.676 0.580 Nx P 1.434 0.270 Pheophytinsedimentation N 47.069 0.000 P 6.089 0.006 Nx P 6.136 0.006
Day 14
Day 21
Day 28
F-ratio
P-value
F-ratio
P-value
F-ratio
P-value
15.346 0.914 1.820
0.001 0.456 0.184
6.867 2.335 0.866
0.019 0.115 0.086
38.607 4.112 2.795
0.000 0.024 0.074
12.763 3.931 1.338
0.003 0.028 0.294
15.706 0.424 1.112
0.001 0.739 0.373
64.374 8.553 5.002
0.000 0.001 0.012
9.343 1.272 2.356
0.008 0.318 0.110
9.101 0.319 0.466
0.008 0.812 0.710
46.280 2.630 0.014
0.000 0.086 0.014
89.321 16.628 17.955
0.000 0.000 0.000
12.549 5.841 3.123
0.003 0.008 0.057
14.106 4.273 3.936
0.002 0.021 0.028
N-fertilized mesocosms also differed temporally among the 4 plankton size classes. Autotrophic picoplankton levels peaked on day 7, while bacterioplanktonnumbers tended to increase later in the experiment and remain at enhanced levels over longer periods. Differences in these biomass maxima and minima in turn altered the size spectrum of the community over time. The proportion of total chlorophyll a measured in picoplankton cells ranged between 70% in low-P mesocosms (high N:P ratios), to only about 30% in high-P, high-N mesocosms. Over this spectrum, total algal biomass increased twofold, mainly within the nano- and microplankton size classes. The ratio of bacterial numbers to total phytoplankton chlorophyll a (-bacterial importance) also varied with nutrient treatment. The relative importance of planktonic bacteria was greatest in high-N (50-100% increase) and high-P (80-130% increase) systems, yet the reverse trend was observed for autotrophic picoplankton. These biomass and size shifts had apparenteffects on the quantity and quality of water column materials lost to the sediments (Table 3). Simple bivariate correlations revealed greater overall sedimentation rates in all systems with greater total phytoplankton and bacterial biomass. The most important variables leading to greater total sedimentation and sedimentation of particulate P and N were autotrophic nanoplankton and microplankton, and heterotrophic bacteria. Larger algae and cyanobacteria consisted primarily of Coelosphaerium naeglianum, Ceratium hirundinella, and Anabaena cylindricum. Two marked exceptions to this positive feedback patternwere (1) a nonsignificant relationship with the biomass of autotrophic picoplankton, and (2) a significant negative relationship with pico-
J.D. Wehret al.
10 -0-Microplankton 0- Nanoplankton --10 imol NH4NO3 Picoplankton 0 Bacterioplankton added / L
No N Added
1-6
No P Added
6-
42-
4.A'
2 -
... ... . ............. 2t [0.5
60-
4
Imol
P added /
6
-
C
4~~~~~~~~~~~0
(U
oL
4X
0.
2 -
22
0
~ ~
0 -
4
8 4 NII~~20 2 olPade
0
~
~
~ ~
7
o ~~ ~ ~ phosphous (tretments
0
7
~~Tm noe
14
21
.,
2
28
m~~~~/~
(days
.,ad umolP0 . addeprlir)mnuatosn /
28 0
.....4
7
14
21
28
Time (days) Fig. 3. Effects of nitrogen(treatments= no N addedvs. 10 p.molNH4NO3addedper liter) and phosphorus(treatments= none, 0.5, 1.0, and 2.0 RiMOlPG4 added per liter) manipulationson phytoplanktonbiomass (measuredas chlorophylla) in three size fractions,and bacterioplankton densitiesin CalderLakemesocosms(n = 3; errorbars= ?1 SE;errorbarssmallerthansymbolsize not shown).
planktonas a percentageof totalchlorophylla. As thesebiological(andseveralkey chemical) variablesmay collectively influence ecosystem processes, and may themselvesbe autocorrelated,a multipleregressionanalysiswas used to identify rates,andto producea the mostimportantfactors(+ or -) affectingsedimentation morecompletemodelthatcoulddescribethe controlson systemefficiency. A stepwise multipleregressionmodel evaluatedthe effect of 8 water-column variables:(1) bacterialdensity, (2) autotrophicmicroplankton(>20 ,um), (3)
11
MicrobialLoop Efficiency
Table 3. Relationshipsbetweenmicrobialplanktonbiomassin mesocosmsandparticulatelosses out of thewatercolumn.DataarePearsonproduct-moment correlationsbetweensedimentation rates(total dry mass, particulateP, particulateN, and pheopigments)biomass levels of the autotrophicand bacterialplanktoncommunityin CalderLake;relativemicrobialdominanceestimatedby the ratio andtotalchlorophyll betweenbacteriaandtotalchlorophylla, andtheratioof autotrophic picoplankton a (n = 24)
Sedimentationvariables Totaldry mass ParticulateP ParticulateN Pheophytin per day) (jig/cm2per day) (mg/cm2per day) (pug/cm2per day) (pLg/cm2 0.721*** 0.499* 0.744*** Bacteria 0.499* -0.096 -0.253 0.219 0.051 AutotrophicPico 0.734*** 0.626** 0.845*** 0.449* AutotrophicNano 0.612** 0.593** 0.653** 0.514* AutotrophicMicro -0.804*** -0.755*** -0.764*** Auto-Pico:IChla -0.515* -0.101 -0.300 -0.039 Bact:IChla -0.099 Planktonfactors
*P < 0.05; **P < 0.01; ***P < 0.001
autotrophicnanoplankton(>2-20 ,um), (4) autotrophicpicoplankton(>0.2-2 ,um), (5) the ratio of bacteria:YChla,(6) the ratio of autotrophicpicoplankton:lChla(labeledas "%Pico"), (7) measuredSRP concentration,and (8) measureddissolved inorganicN (DIN) concentration.The variablesbacteria: communitieswithgreateror lesser IChla andpico:lChla wereusedto characterize importanceof microbialbiomass.Total sedimentationrateswere consideredfirst (Table4). With a greaterpercentageof the phytoplanktonbiomass in small cells, total ratesweresignificantlyless. The variable"%Pico"was identifiedas sedimentation the primaryvariableexplainingtotal system loss, althoughthe completemodel, with the inclusionof aqueousDIN concentration,could explainless thanhalf of thisresponse.In contrast,over 80%of the variationin particulateP losses couldbe predictedby a modelincluding%Pico (-), bacterialdensity(+), andautotrophic microplankton (-); nearly60%of theN-loss rateswereexplainedby %Pico alone. Inbothinstances,a greaterimportanceof picoplanktonresultedin reducedlosses of nutrientelements. Planktonicbacteriaare predictedto have no such effect on enhancedecosystemefficiency.In fact, greaterbacterialbiomasswas identifiedas a factorthat may lead to increasedP losses. Algal pigmentsedimentation(measuredas pheophytin)rateswere stronglyinfluencedby greaterautotrophicnanoplanktonlevels, with the completemodel predictingmore than 75% of this reratesrespondedsignificantlyto N andP manipulations sponse.All 4 sedimentation (Table2), yet theirrelationshipto bioticfactorsfromwithinthe planktonwerenot alike. Pigmentlosses, unlikethe othersedimentationvariables,werenot relatedto indexesof microbialprocesses(e.g., %Pico, or bact:lChla). Differencesin these relationshipsare clearlyrevealedin bivariateplots of the 4 measuresof sedimentationloss against the primaryindependentwater-column variableidentifiedby each multiple regressionmodel (Fig. 4). In 3 out of 4 measures,the most importantpredictor(% Pico) exerteda negativeinfluenceon systemlosses. Thesemodelspredictthata greaterretentionof materialswithinthe euphoticzone resultsfrom a picoplankton-dominated phytoplanktoncommunity.
12
J.D. Wehret al.
Table 4. Resultsof multipleregressionanalysisof the combinedeffects of biologicalandchemical in surfacewaterson ratesof sedimentationlosses. Eightindependentvariablestested characteristics were bacteriadensity, autotrophicpicoplankton,autotrophicnanoplankton,autotrophicmicroplankton, ratio of pico:lChla, ratio of bacteria:lChla, [SRP], and [DIN]. The minimumcriterionfor inclusionof independentvariablesinto the modelwas a = 0.05, and0.10 to removethem. Independentvariablesarelistedin orderof inclusion,withthefirstin eachset explainingthe largestproportion of the total variance(n = 24; coef, coefficientof slope; SE, standarderror;t, Student'st-score;P, probability; F, F-ratiofromANOVA;r2, finalcoefficientof determination Step:indepvar Dependentvariable= 1: % Pico 2: [DIN] Y-intercept completemodel Dependentvariable= 1: Nano 2: Bacteria Y-intercept completemodel Dependentvariable= 1: % Pico 2: Bacteria 3: Auto-Micro Y-intercept completemodel Dependentvariable= 1: % Pico Y-intercept completemodel
coef
SE
total sedimentation -0.002 0.0005 0.001 0.0002 0.232 0.032 F = 10.045 pheo sedimentation 0.412 0.085 0.176 0.065 -0.329 0.157 F = 39.041 P sedimentation -0.010 0.002 0.066 0.016 -0.194 0.066 0.969 0.138 F = 34.663 N sedimentation -0.014 0.003 2.421 0.149 F = 29.117
t
P
-3.189 3.031 7.291
0.004 0.006
