Does Microbial Biomass Affect Pelagic Ecosystem Efficiency? an Experimental Study

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

Abstract. Bacteriaand other microorganisms in the pelagiczone participate in the recyclingof organicmatter and nutrientswithin the watercolumn. The microbialloop is thoughtto enhanceecosystem efficiency through rapid recycling andreduced sinking rates, thus reducing the loss of nutrientscontained in organismsremaining within the photic zone. We conductedexperiments with lakecommunities in 5400-litermesocosms, and measured the flux of materials and nutrientsout of the water column. A factorial design manipulated8 nutrienttreatments: 4 phosphoruslevels x 2 nitrogenlevels. Totalsedimenta- tion rateswere greatestin high-N mesocosms;within N-surplus communities, 3 1,UM P resultedin 50%increase in totalparticulate losses. P additionswithout addedN had small effects on nutrientlosses from the photic zone; +2 jLM P tanks received 334 mg P per tank, yet after 14 days lost only 69 mg more particulate-Pthan did control communities.Nutrient treatments resulted in markeddifferences in phytoplanktonbiomass (twofold N effect, fivefold P effect in +N mesocosmsonly), bacterioplanktondensities (twofold N-effect, twofoldP effects in -N and +N mesocosms),and the relativeimportance of autotrophicpicoplankton (maximum in highN:P mesocosms).Multiple regression analysisfound that of 8 planktonand waterchemistry variables, the ratio of autotrophicpicoplankton to totalphytoplankton (measured as chlorophylla) explainedthe largestportion of the total variationin sedimentationloss rates (65%of P-flux, 57%of N-flux, 26%of totalflux). In each case, systemswith greaterrelative importance of autotrophicpicoplankton had significantlyre- duced loss rates. In contrast,greater numbers of planktonicbacteria were associatedwith increasedsedimentation rates and lower systemefficiency. We suggest that differentmicrobial components may have contrastingeffects on the presumedenhanced efficiency provided by the microbialloop.

Correspondenceto: J.D. Wehr. 2 J.D. Wehr et al.

Introduction

The loss of planktonicmaterials to the sedimentsof lakesis one of the fundamental processesin freshwaterecosystems. These losses leadtoward the immobilizationof organicmatter and nutrients to the sediments,and the eventualrecycling of material followingdecomposition and turnover. Despite the fact thatmost of the sedimented organic matterproduced by phytoplanktonis decomposed[45], autochthonous sinkingparticles (dead phytoplankton,fecal pellets, organicdetritus) represent a net loss of nutrientsfrom the photic zone in most stratifiedlakes, until after turnover.Traditionally, nutrient cycling in lakes is thus thoughtof in termsof a phytoplankton-zooplankton-fishmodel, in which the returnof nutrientsdepends on settled particlesbeing decomposedand remixedinto the watercolumn in the spring or autumn.Factors affecting the flux rate of planktonicmaterials may includesystem productivity, plankton particle size, andbasin morphometry. How- ever, within a given productivityrange, other biotic processesmay enhancethe regenerationof nutrientswithin the watercolumn and reducesystem losses to the sediments.Bacteria and otherpelagic microorganismsparticipate in the recycling of organicmatter [3, 5, 6]. It has been proposedthat a microbialfood web consisting of bacteria,pico- phytoplankton,and herbivorousflagellates and ciliates can act to shuntprimary productionand nutrients away from a "linear"metazoan food chainto a morerapid and efficientrecycling mechanism [3, 33]. The importanceof this microbialloop for pelagic ecosystem efficiency and the retentionof inorganicnutrients in the photic zone needs to be quantified.Arguments have followed that predictthat microorganisms,due to theirhigh surfacearea to volumeratios, rapid growth rates, and slower sinking rates, will enhance the likelihood of nutrientscontained in organismsremaining within the photic zone [37]. Thus, a yardstickfor pelagic ecosystemefficiency may be measuredaccording to reducedrates of downward nutrientflux (="losses"), and may be comparedwith recentlyproposed measures of bacterialand other microbial biomass and growth. Based on the ideas representedin microbialloop theory,rapid growth rates and efficient remineralizationof nutrientscan be maintainedonly if there is tight couplingbetween protist grazers and theirbacterial prey [18, 37]. However,it is not clear whetherthis predictionconsiders both heterotrophicbacteria and autotrophicpicoplankton in this size range.These two components,while physiolog- ically quitedistinct, compete for some of the same resources.Recent experiments indicate that the growth of heterotrophicbacteria may at times be limited by inorganicnutrients [15, 40], suggestingthat these microorganismsmay at times become a sink for nutrientswithin the microbialloop. Indeed, Caron [14] has shownthat phytoplankton typically have C:N and C:P ratioshigher than the Red- field ratio of 106C:16N:iP, while planktonicbacteria tend to have C:N and C:P ratiosbelo -v this ratio. Studieshave shown that the relativeabundance of autotrophicpicoplankton tends to be greatestin oligotrophic(typically P-limited in freshwater)ecosystems [13, 35, 43], but apparentlyis not limitedby the supplyof dissolvedinorganic phosphorus (DIP)in eithereutrophic or oligotrophiclakes [41, 44]. Surprisingly,the growthof heterotrophicbacterioplankton was shownto be directlylimited by DIP availability in the samesystem [40]. Theseexperiments raise questions concerning the apparent MicrobialLoop Efficiency 3 universalimportance of P limitationin freshwaters[32]. The ecosystemimpact of moreefficient processing by certainmicroorganisms and protozoa may thus depend not only on the total productionof microbialorganisms, but also on the differing nutrientconstraints that affect the compartmentswithin the microbialloop. In this study we propose that differencesin total microbialbiomass and the relativeimportance of heterotrophicand autotrophic picoplankton within the photic zone will affectsystem efficiency. Basedon earlierresults indicating differences in nutrientlimitation, we predictthat autotrophic picoplankton in particularwill have a positive effect on the retentionof nutrientsin the water column (i.e., reduced nutrientsedimentation). We testedthis idea by manipulatingpelagic lake communities in largemesocosms, and measuringthe flux of materialsand nutrients out 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,outdoor mesocosms (1.9 m diam;2.1 m high; filled to 5400 litersper tank)that are directlypump-fed with CalderLake water[see 41, 42 for detailson the lake] throughprewashed, opaque polyethylene pipe. Mesocosms were filled in darknessduring an 8h periodon 1 June 1992, when CalderLake was weaklystratified (AT 2?C/m).Night collectionensured that verticallymigrating zooplankton (principally Daphnia pulicaria)occurred in all ELFtanks at similarlevels. Nylon netting(1 cm mesh)was placedover each to minimizeinputs of leaves andwoody debris. A factorialdesign consisted of 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 each block replicatedthree times. The intentof this design was to manipulatenutrient levels and N:P ratiossuch that phytoplanktonproduction and communitysize structurevaried over the full rangeobserved in earlierstudies [41]. Nutrientswere addedon day 0 duringfilling to allow sufficientmixing, anda secondidentical set was appliedon day 14 followingthe thirdweekly sampling(see below);the experimentran for 28 days. The primarygoal was to examinewhether losses of planktonicmaterials from the watercolumn increase or decreaseas a functionof nutrientconditions and microbialprocesses. The basic models tested include (1) an ANOVAmodel, in whichmanipulated variables (N, P, N x P) areclassified as treatments,and (2) a regressionmodel, in which observedplankton variables (levels of planktonicbacteria and "algal" picoplankton,nanoplankton, and microplankton) are classified as independentvariables (see also later 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. Water and planktonsamples were collectedby peristalticpump from 0.5 m depth.Pairs of waterchemistry samples were filtered in line (WhatmanGF/F); one set was acidifiedto pH 2 (withH2SO4), andthe otherset was frozen(- 15?C). Planktonchlorophyll was collectedin 1-literbottles while prefilteringmicroplankton through 20-p.m meshsize Nitex. The remainingfiltrate was keptrefrigerated (-4?C) untilreturned to the lab. To measurerates of planktonand otherparticulate losses, a free-standing,vertical sediment trap (withweighted bottom) was placed in the center-bottomof each ELF tank (retrievedby two nylon stringsattached to the rimof the tanks).The cylindricaldesign followed general recommendations of Hargraveand Burns [20] and Bloesch and Burns [8], with a length/widthratio of about 5.5:1 (total 4 J.D. Wehret al. volume550 ml) to minimizeturbulence. Traps were constructedfrom 55 mm ID white PVC, with a polypropylenefunnel fitted inside at the bottomto focus the settledsediment. A clampedplastic tube was attachedto each funnelso thatweekly samplesof trappedsediment could be siphonedinto sample bottles(stored at 4?C)and the trapsreturned to each ELFtank immediately after sampling. Following Kirchner[24], 90 ml of 5% NaCl was first placed into the bottomof each trapto createa density gradientand preventmaterial loss while traps were raised to the surface. Tests with saline plus methyleneblue indicatedlittle or no loss duringtransfer.

Laboratory Methods

Waterchemistry samples were analyzed for concentrationsof soluble-reactivephosphorus (SRP) using the antimony-ascorbate-molybdatemethod [1, 91 andfor totaldissolved P as above, followingpersul- fate digestion[29]. NH4+-Nconcentrations were measuredby the phenol-hypochloritemethod, and NO3- (afterreduction to NO2- in a Cd-Cucolumn) via reactionwith sulfanilamide-NNED [ 1, 10, 11]. Soluble-reactiveSi (as Si02) was measuredby the molybdosilicatemethod [1, 12]. Methodswere modifiedfor automatedanalysis and run on a Traacs800 automatedanalyzer (Bran+Luebbe Technol- ogies, Inc., BuffaloGrove, IL). Sediment-trapsamples (in water)were mixed thoroughly,split into four parts, and filteredonto either25 mm (for particulateN, P) or 47 mm (totaldry weight, pigments)diameter Whatman GF/F glass fiberfilters (volumes recorded). Portions of filteredresidue used for N, P, andpigment analysis were immediatelyfrozen until digestion; total dry mass sampleswere placedin a dryingoven (105?C) for48h, thencooled in a desiccator.Particulate N andP weredigested (30 min)under pressure (120?C, 15 psi) in Pyrextubes using acid (H2SO4) perchlorate[29]. Dry mass accumulationwas measuredto the nearest0.1 mg. Sedimentedpigments (chlorophyll a and pheophytina) concentrationswere measuredfollowing extraction in glass tissue grinderswith -4 ml neutral90% acetone(+MgCO3). Extractswere poured into graduated centrifuge tubes, made up to knownvolume, and further extracted in the dark (<4?C) for 18-24 h. Samples were centrifugedand measuredspectrophotometrically (Shimadzumodel UV-160) [1, 27]. The majorityof measuredpigment in the sedimenttraps (;80% on average)consisted of pheophytin. Bacterioplanktonin watersamples (=5 ml) werepreserved with glutaraldehyde (to 2%), stainedfor fluorescentmicroscopy using DAPI, filteredonto Irgalanblack stained25-mm polycarbonate filters (0.2 p.mporesize; Poretics Corp.), and storedat - 15?Cuntil later observation [22, 31]. Countswere made at x 1250 magnificationusing a Nikon Labophotepifluorescence microscope, using 365 nm excitationand 520 nm barriersets. A minimumof 10 grids and 300 cells were countedper sample replicate.Phytoplankton biomass (measured as chlorophylla) was size fractionated(using polycarbonate filters) accordingto categoriesdefined previously [34, 41]. Briefly, microplanktonare cells or colonies20-200 ,im, nanoplanktonare 2-20 jim, andpicoplankton are 0.2-2 ,um.Filtering methods havebeen described previously [41, 42]; chlorophylla was measuredby spectrophotometer(corrected for pheophytin),as describedabove.

Data Analysis

Datawere compiled and analyzed using the SYSTAT4.2 program[46]. Two typesof hypothesistests were set up to evaluatethe models(nutrient and plankton effects) outlinedin the experimentaldesign section. For both, the dependentvariables were particulatelosses out of the water column to the sediment,measured as (1) total dry weight, (2) particulateP, (3) particulateN, and (3) pheophytin deposition.The first hypothesistests were conductedusing two-wayANOVA of manipulatedvariables. Treatmentswere (a) nitrogen(2 levels) and(b) phosphorus(4 levels) treatments,and (a x b) an interactionterm (N x P),-as categoricalvariables. Effects were judged to be significantif the probability (oa)of an eventoccurring due to chance(P) was less than0.05. A secondset of testswas usedto derivepredictions about how measuredkey water-columnvariables affect sedimentationrates, using stepwisemultiple linear regression (MLR). In these, 8 independent MicrobialLoop Efficiency 5

Table 1. Physicaland chemical conditions measured in 24 experimentalmesocosms at the startof the experiment,classified accordingto fertilizationtreatment. Temperature was measuredin ?C, and chemistryvalues are expressed in ,umol/l 1 SD (n = 3; SRP, soluble-reactivephosphorus)

Phosphorustreatment (>M) 0P 0.5 P 1.0P 2.0P NO N ADDED Temp 18.5 ? 0.1 18.8 ? 0.9 18.4 ? 0.2 18.6 ? 0.1 pH 7.56 ? 0.12 7.56 ? 0.14 7.54 ? 0.29 7.49 ? 0.08 SRP 0.04 ? 0.01 0.38 ? 0.02 0.81 ? 0.06 1.71 ? 0.05 NH4 6.7 ? 1.9 6.7 ? 0.4 6.1 ? 0.2 6.0 +0.1 NO3 0.34 ? 0.01 0.31 ? 0.02 0.30 ? 0.04 0.29 ? 0.04 SiO2 11.7 ? 0.3 11.1 0.1 11.1 0.1 11.4 0.03 +10 FM NH4NO3 Temp 18.8 ? 0.5 18.6 ? 0.1 18.3 ? 0.5 18.4 ? 0.6 pH 7.54 ? 0.27 7.54 ? 0.12 7.53 ? 0.22 7.58 ? 0.22 SRP 0.03 ? 0.01 0.34 ? 0.02 0.80 ? 0.02 1.76 ? 0.04 NH4 10.6 ? 0.5 14.8 ? 0.7 9.7 ? 0.5 14.6 ? 0.3 NO3 11.5 ? 0.3 11.4 0.2 11.6 0.3 11.6 ? 0.3 SiO2 10.9?0.1 11.4?0.1 11.3?0.4 11.3?0.1

variableswere testedfor theireffects on sedimentationlosses: bacterioplanktondensity, autotrophic picoplankton,autotrophic nanoplankton, autotrophic microplankton, ratio of pico: SChla, ratio of bacteria:lChla,[SRP], and dissolvedinorganic N ([DIN]). Ratiosof pico:lChla and bacteria:lChla were includedto test whethera predominance(rather than simple density)of microbialcells, both autotrophicand heterotrophic, alter systems losses andecosystem efficiency. The maximumcriterion for inclusionof independentvariables into the model was (x = 0.05, and the minimumfor exclusion was a = 0.10. All datawere checked for assumptionsof normalityand homogeneity of variancesprior to analysis. In summary,the two modelsmake different biological assumptions about the proximateand ultimate factorsleading to particulatelosses to the benthos.The ANOVAmodels examine solely the effect of manipulations(i.e., N and P loadings),which may have directeffects on sedimentation,or indirect effects throughchanges in planktonbiomass or shifts in communityand size structure.The MLR modelsidentify which of severalmeasured variables in the watercolumn, singly or collectivelyexplain the differencesin sedimentationlosses over time. These factorsmay be thoughtof as havingmore immediateand directeffects on sedimentationrates, despite having not been directlymanipulated. Each approachhas its limitations,but both are useful startingpoints for makingpredictions about ecosystemefficiency under different nutrient and plankton community conditions.

Results

Physical and Chemical Conditions The measuredconcentrations of SRP at the startof the experimentwere somewhat below nominaltreatment levels for P added(about 80%), but N treatmentswere close to targetvalues (Table 1). Nutrientswere nonethelesssignificantly different acrosstreatments (ANOVA; P < 0.01 in all cases) and not significantlydifferent withintreatments (ANOVA; P > 0.5 in all cases). ActualP treatmentsthus repre- senteda gradientof about1 x, 0x, 25 x, and50 x of ambientconditions in Calder 6 J.D. Wehret al.

No Nitrogen Added +10 FtMNH4NO3 *No P Added 8 - * +0.5 [M P -8 Z + 1.0 1MP 7

?ojNg60 - ?6

WE4 R - 4 UW c6m3 3 -J3 2 2 0 1 1 0 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 water column to the sedimentsas a functionof nitrogenand phosphorusmanipulations, measured weekly in CalderLake mesocosms. Rates are measured in terms of total dry weight (upper panel), and pheophytin a accumulation (lower panet). All dataare average rates from three replicate mesocosms for each nutrienttreatment.

Lake.All non-manipulatedvariables measured, such as temperature,pH, andother chemicalconditions, remained similar among all 24 tanksthroughout the study.

SedimentationLosses The firstgoal was to determinewhether manipulations of nitrogenand phosphorus levels affect total and specific losses of materialsout of the euphotic zone. A particularinterest was whetherlosses observed differ from those predictedby simple increasesin planktonbiomass. Over 28 days, sedimentationproceeded at markedlydifferent rates accordingto treatmentconditions (Fig. 1). Each pair of treatmentgroups (no N addedvs. 10 ,umolNH4NO3 added per liter) is presentedin two plots representingthe effect of P additionson particulatelosses to the sedi- MicrobialLoop Efficiency 7 ments. Sedimentationof planktonicmaterials (dry weight) out of the watercolumn was not differentacross a wide P-treatmentgradient in mesocosmswithout added N (Fig. 1, upper panel). However, losses overall were nearly twice as great in systemswith 10 ,umolNH4NO3 added per liter, whichcorrespond with a doubling in surfaceplankton biomass (see below). Within these N-fertilizedmesocosms, phosphorustreatments 1 ,Iumol/lresulted in about 50% greatertotal plankton losses thancontrol-P tanks. This effect was apparentby day 14 of the study. Phytoplanktondeath and sinking rates, as judgedby the weekly accumulationof pheophytina, weredramatically affected by bothaqueous N andP conditions(Fig. 1, lower panel). Nitrogen-fertilized mesocosms received up to three times more deadalgal materialthan the sedimentsof N-limitedsystems, althoughthis was not observedin communitieslacking a P addition.The P treatmentsalso elicitedearlier (by day 14) and strongerresponses than were observedfor total or particulate nutrientsedimentation. The rangeof 0 to 2.0 ,umolP addedper liter (z0.4 to 1.8 FIMP measured)resulted in an averageincrease in the cumulativeloss ratefrom 3.9 to 18.8 [ig pheophytinper cm2 of sedimentsurface, nearly fivefold (i.e., 500%) greater.This greatlyaccelerated pigment accumulation corresponds with only a 50%increase in the totalmass of sedimentedplanktonic materials. Particulatenutrient losses were not necessarilyrelated to increasedloadings of those nutrients.In CalderLake water, P additionsalone had no apparenteffect on losses of this nutrientto sediments(Fig. 2, upperpanel). Particulate-Paccumulated in the sedimentsof N-limitedsystems at similarrates across the wide rangeof P treatments.This meansthat a 50-fold increasein DIP loadinghad little effect on P losses in these mesocosms.Because the totalvolume of each mesocosmis known, differencesin the retentionof P withinthe euphoticzone can be estimatedaccu- rately.Systems supplied with 2.0 ,umolP/I received on day 0 an additional334 mg of P (as K2HPO4).After 14 days these communitieslost only 69 mg moreparticu- late-P (24.9% greater)than did control communities.However, the additionof inorganicN greatlyaccelerated P sedimentation,with maximumlosses observedat high N andintermediate P (0.5-1.0 ,umolP addedper liter)treatments. By the end of the experiment,sediment traps in phosphorus-limitedmesocosms received about 28%less particulate-P(- 16.8 [Lg/cm2)than those receiving2.0 ptmolP/1 (=23.3 pLg/cm2).Nitrogen losses exhibiteda similarpattern (Fig. 2, lower panel), although P treatmentshad apparentlylittle effect on N retentionor N loss in most systems. The significanceof direct nutrientmanipulations on sedimentationrates was consideredfor each dateby two-wayanalysis of variance(Table 2). The total loss of materials(as dryweight) was not significantlyaffected by eitherN or P untilday 14, and by P treatmentsonly by day 28. Nitrogenclearly was the most important treatmentvariable controlling total 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(and N x P interactions)in the watercolumn by the end of the experiment. Systemlosses of N were significantlyaffected by N additionsthroughout the study, but the analysisindicated that P additionshad no significanteffects. Unlike the othervariables measured, pheophytin sedimentation was significantlyaffected by both N and P treatments,and exhibited significantlytreatment interactions. Fromthis perspective,P treatmentsresulted in significantlygreater loss of algal materialwhen N was also added, even on day 7. The importanceof N x P 8 J.D. Wehret al.

No Nitrogen Added +10 FiMNH4NO3 * No P Added 30 - * + 0.5 FM P - 30 A + 1.0 RM P 225 4 7 280 P7 2- 25 ZEz 20 -20 z 15 w ~- 15 -

7510 -10 077

O.0 5- 0 0 0 7 14 21 28 0 7 14 21 28 70 - -70 - 60 --60 zZE

04 20 20

0 -0 z1-1 07-4 1 280 74421 2

TIME (Days) Fig. 2. Cumulative,particulate nutrient flux fromthe watercolumn to the sedimentsas a functionof nitrogenand phosphorusmanipulations, measured weekly in CalderLake mesocosms. Rates are measuredin termsof particulateP (upperpanel), and particulateN accumulation(lower panel). All dataare average rates from three replicate mesocosms for each nutrienttreatment. interactionon algal losses contrastswith the repeatednonsignificance of such an interactioneffect on totalsedimentation rates.

Microbial Biomass and Sedimentation A secondobjective of this studywas to examinethe relationshipbetween microbial planktonbiomass (algal and bacterial) and system efficiency. Directmanipulations of N and P supplyto the euphoticzone alteredtotal biomasslevels as well as the relativeimportance of varioussize fractionswithin the plankton(Fig. 3). Control (no P or N added)densities of phytoplanktonand bacteriawere not significantly differentfrom levels in CalderLake. Phytoplanktonand bacterioplanktonproduc- tion levels weregreatest in N-supplementedsystems, but only bacteriaincreased in responseto P additionswithout added N. Biomass responsesto P additionsin MicrobialLoop Efficiency 9

Table 2. Effectsof fertilizationon planktonsedimentation in experimentalmesocosms, as character- ized by total(dry mass), phosphorus,nitrogen, and pheophytin loss rates(see Fig. 1 for details).Data arefrom a two-wayanalysis of varianceof the effects of N addition(none or 10 FAMNH4NO3) and/or P addition(none, 0.5, 1, or 2 FM K2HPO4)on ratesof totaldry mass (g dry wt/cm2 per day), P, N (p.g nutrient/cm2per day), and pheophytin(p.g pheo a/cm2 per day) accumulationmeasured at weekly intervals(a nominalP level of "0.000"is some unknownprobability less than0.001)

Day 7 Day 14 Day 21 Day 28 Treatment F-ratio P-value F-ratio P-value F-ratio P-value F-ratio P-value Total sedimentation N 0.327 0.576 15.346 0.001 6.867 0.019 38.607 0.000 P 0.488 0.696 0.914 0.456 2.335 0.115 4.112 0.024 N x P 0.830 0.497 1.820 0.184 0.866 0.086 2.795 0.074 Phosphorussedimentation N 7.798 0.013 12.763 0.003 15.706 0.001 64.374 0.000 P 3.299 0.047 3.931 0.028 0.424 0.739 8.553 0.001 N x P 1.102 0.377 1.338 0.294 1.112 0.373 5.002 0.012 Nitrogensedimentation N 6.394 0.022 9.343 0.008 9.101 0.008 46.280 0.000 P 0.676 0.580 1.272 0.318 0.319 0.812 2.630 0.086 N x P 1.434 0.270 2.356 0.110 0.466 0.710 0.014 0.014 Pheophytinsedimentation N 47.069 0.000 89.321 0.000 12.549 0.003 14.106 0.002 P 6.089 0.006 16.628 0.000 5.841 0.008 4.273 0.021 N x P 6.136 0.006 17.955 0.000 3.123 0.057 3.936 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, Cera- tium 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- 10 J.D. Wehret al.

-0-Microplankton 0- Nanoplankton No N Added --- Picoplankton 10 imol NH4NO3 0 Bacterioplankton added / L

6- No P Added 1-6

42- 4.A'

- 2 ...... 2t

60- [0.5 Imol P added / 6

4 - C (U 4~~~~~~~~~~~0 oL 4X

0. 2 - 2 2 0 4 2 8 4 2 28 0 NII~~20olPade

0 - ~ ~ ~ ~ ~ ~ 7 m~~~~/~ o ~ ~ ~ ~ ~~Tm (days phosphous (tretments noe ., .,ad umolP0 . addeprlir)mnuatosn / .....4

0 7 14 21 28 0 7 14 21 28 Time (days) Fig. 3. Effects of nitrogen(treatments = no N addedvs. 10 p.molNH4NO3 added per 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 CalderLake mesocosms (n = 3; errorbars = ?1 SE; errorbars smaller than symbol size not shown). planktonas a percentageof totalchlorophyll a. As thesebiological (and several key chemical) variablesmay collectively influence ecosystem processes, and may themselvesbe autocorrelated,a multipleregression analysis was used to identify the mostimportant factors (+ or -) affectingsedimentation rates, and to producea morecomplete model that could describethe controlson systemefficiency. A stepwise multipleregression model evaluatedthe effect of 8 water-column variables:(1) bacterialdensity, (2) autotrophicmicroplankton (>20 ,um), (3) MicrobialLoop Efficiency 11

Table 3. Relationshipsbetween microbial plankton biomass in mesocosmsand particulate losses out of the watercolumn. Data are Pearson product-moment correlations between sedimentation rates (total dry mass, particulateP, particulateN, and pheopigments)biomass levels of the autotrophicand bacterialplankton community in CalderLake; relativemicrobial dominance estimated by the ratio betweenbacteria and total chlorophyll a, andthe ratioof autotrophicpicoplankton and total chlorophyll a (n = 24)

Sedimentationvariables Total dry mass ParticulateP ParticulateN Pheophytin Planktonfactors (mg/cm2per day) (pug/cm2per day) (pLg/cm2per day) (jig/cm2per day) Bacteria 0.499* 0.721*** 0.499* 0.744*** AutotrophicPico 0.051 -0.096 -0.253 0.219 AutotrophicNano 0.449* 0.734*** 0.626** 0.845*** AutotrophicMicro 0.514* 0.612** 0.593** 0.653** Auto-Pico:IChla -0.515* -0.804*** -0.755*** -0.764*** Bact: IChla -0.099 -0.039 -0.101 -0.300

*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(labeled as "%Pico"), (7) measuredSRP concentration,and (8) measureddissolved inorganic N (DIN) concentration.The variables bacteria: IChla andpico:lChla wereused to characterizecommunities with greater or lesser importanceof microbialbiomass. Total sedimentationrates were consideredfirst (Table4). With a greaterpercentage of the phytoplanktonbiomass in small cells, total sedimentationrates were significantly less. The variable"% Pico" was identifiedas the primaryvariable explaining total system loss, althoughthe completemodel, with the inclusionof aqueousDIN concentration,could explain less than half of this response.In contrast,over 80%of the variationin particulateP losses couldbe predictedby a model including% Pico (-), bacterialdensity (+), and autotrophic microplankton(-); nearly60% of the N-loss rateswere explained by %Pico alone. In bothinstances, a greaterimportance of picoplanktonresulted in reducedlosses of nutrientelements. Planktonicbacteria are predictedto have no such effect on enhancedecosystem efficiency. In fact, greaterbacterial biomass was identifiedas a factorthat may lead to increasedP losses. Algal pigmentsedimentation (measuredas pheophytin)rates were stronglyinfluenced by greaterautotrophic nano- planktonlevels, with the complete model predictingmore than 75% of this response. All 4 sedimentationrates responded significantly to N andP manipulations (Table2), yet theirrelationship to biotic factorsfrom within the planktonwere not alike. Pigmentlosses, unlikethe othersedimentation variables, were not relatedto indexesof microbialprocesses (e.g., % Pico, or bact:lChla). Differencesin these relationshipsare clearlyrevealed in bivariateplots of the 4 measuresof sedimentationloss against the primaryindependent water-column variableidentified by each multiple regressionmodel (Fig. 4). In 3 out of 4 measures,the most importantpredictor (% Pico) exerteda negativeinfluence on systemlosses. Thesemodels predict that a greaterretention of materialswithin the euphoticzone resultsfrom a picoplankton-dominatedphytoplankton community. 12 J.D. Wehret al.

Table 4. Resultsof multipleregression analysis of the combinedeffects of biologicaland chemical characteristicsin surfacewaters on ratesof sedimentationlosses. Eight independentvariables tested were bacteriadensity, autotrophicpicoplankton, autotrophic nanoplankton, autotrophic microplankton, ratio of pico:lChla, ratio of bacteria:lChla, [SRP], and [DIN]. The minimumcriterion for inclusionof independentvariables into the model was a = 0.05, and0.10 to removethem. Indepen- dentvariables are listed in orderof inclusion,with the firstin each set explainingthe largestproportion of the total variance(n = 24; coef, coefficientof slope; SE, standarderror; t, Student'st-score; P, probability;F, F-ratiofrom ANOVA; r2, finalcoefficient of determination

Step:indep var coef SE t P Dependentvariable = total sedimentation 1: % Pico -0.002 0.0005 -3.189 0.004 2: [DIN] 0.001 0.0002 3.031 0.006 Y-intercept 0.232 0.032 7.291 <0.001 completemodel F = 10.045 P = 0.001 r = 0.489 Dependentvariable = pheo sedimentation 1: Nano 0.412 0.085 4.827 <0.001 2: Bacteria 0.176 0.065 2.698 0.013 Y-intercept -0.329 0.157 -2.099 0.048 completemodel F = 39.041 P = <0.001 r = 0.788 Dependentvariable = P sedimentation 1: % Pico -0.010 0.002 -5.463 <0.001 2: Bacteria 0.066 0.016 4.235 <0.001 3: Auto-Micro -0.194 0.066 -2.953 0.008 Y-intercept 0.969 0.138 7.038 <0.001 completemodel F = 34.663 P = <0.001 r = 0.839 Dependentvariable = N sedimentation 1: % Pico -0.014 0.003 -5.396 <0.001 Y-intercept 2.421 0.149 16.202 <0.001 completemodel F = 29.117 P = <0.001 r = 0.570

Planktonicbacteria did not, however,exhibit this relationship.Total sedimentation rateswere less effectivelymodeled, but morethan 50% of the variationin both N and P retentionor loss could be predictedby % Pico alone. In contrast,reduced ecosystemretention of phytoplanktonpigments was predictedto be the resultof a greaterbiomass of autotrophicnanoplankton.

Discussion

Nutrientmanipulations in lake mesocosms,consisting of two pulses (on day 0 and day 14) of nitrogenand/or phosphorus, affected the biomassand size structureof the planktoncommunity, and also the flux of sedimentexported out of the water column. Maximumloss rateswere observedin high N (10 ,umolNH4NO3 added perliter and P (2 ,umolK2HPO4 added per liter) systems, with N exertingthe larger effect. Because fertilizationwill often result in greaterplankton biomass, it is expectedto some degreethat nutrient-surplus conditions can lead to greaterrates of sedimentation[e.g., 7]. Otherstudies have shownthat phosphorus sedimentation in lakes can be partiallypredicted by levels of epilimneticP, but also by the amounts of particulateP containedwithin planktonicmaterials >20 ,m in size [28]. The MicrobialLoop Efficiency 13

TotalSedimentation P Sedimentation 0.4 1.0 2 2 r.=0.265l0 r =0.646 0. SedimentPi

E sO 0.2

0.0 0.0 0 20 40 60 80 100 0 20 40 60 80 100 Autotrophic-Pico: E Chia Autotrophic-Piao ( Chi a

N Sedimentation Pheophytin Sedimentation 2.5 2.5 r= 0.570 * ~~P< 0.001 N2.0- E 2.0E Z 01.5- co1.5 C. Co.1.0 0 ~~1.0 o..~~~~~~E0.5 *r=0.715 * P < 0.001 E 0.5 0.0 0 20 40 60 80 100 0 1 2 3 4 Autotrophic-Pica: y- Chia Autotrophic-Nano(jug Chi a/I L)

Fig. 4. Bivariateregression plots of thekey watercolumn predictors (independent variables) versus 4 measuresof particleflux into sedimenttraps in CalderLake mesocosms. The mostimportant independent variablein each case was extractedby stepwisemultiple regression (n = 24; lines fit by least squaresregression; P, probability;r2, coefficientof determination).For detailsof each independent variable,see text. mechanismbehind these dynamicsmay not simplybe a matterof greaterplankton biomass,but also enhancedecosystem efficiency. Ourexperiments, which directly manipulated short-term nutrient concentrations (two discretepulses), were designedto cause a shift in the biologicalcommunity andin longer-termchemical conditions within the euphoticzone. These character- istics, particularlyphytoplankton size structureand the relativeimportance of a pelagicmicrobial loop, shouldbe given particularattention, as they arebelieved to play a centralrole in regulatingecosystem efficiency [3, 33]. The theorystates that materialsthat pass througha microbialloop are moreefficiently remineralized and fed back into solublepools. Experimentalstudies support this theory.The uptake and regenerationof both N and P within surfacewaters has been shown to be regulatedmainly by planktonicorganisms <3 pumin size [4, 16, 17], and less by herbivorouszooplankton, such as cladocerans.Other studies have shown that smaller protist grazers, such as heterotrophicnanoflagellates and ciliates, can acceleratemicrobial regeneration of nutrients,particularly P, within the water 14 J.D. Wehr et al. column[5, 6]. Sedimentationstudies in a tropicalmarine system have shownthat picoparticlesdo not tend to settle out over 24h, while significantpercentages of autotrophicnanoplankton (- 15%)and microplankton (-30%) are exportedto the benthos daily [23]. For these reasons, it has been specifically suggested that nutrientscycled within the microbialloop should have a greaterprobability of remainingwithin the photiczone [37]. Hence, whole-systemmanipulations which lead towardgreater microbial processing may be used to test whetherecosystem efficiencyis trulyenhanced. This study demonstratesthat changes in the size structureof a phytoplankton community,that is, a shift frompredominantly large-celled to small-celledassem- blages, correspondwith a greaterretention of materialswithin the photic zone, includingboth P and N. Sedimentationrates of particulateP regress negatively against a simple index of microbial dominance, the ratio of autotrophic picoplankton:lChla.The slope predictsthat for every 10%increase in the predominanceof picoplankton,the system(on an arealbasis) will retain7.4 pugmore P and 13.6 ,ugmore N/M2 perday. The ecosystemsignificance of this effect in lakeswill furtherdepend in parton protozoangrazing activity, but also the depthof the photic zone that will supportautotrophic picoplankton. There are data that suggest that phycoerythrin-richpicoplankters, such as some species of Synechococcus,may utilize reducedlight field more efficiently than other autotrophs[e.g., 19, 26], which may favor their greaterrelative abundance with depth [44]. Thus, low-P (high N:P ratios), deep lakes may be those ecosystems with greatestpelagic, microbialrecycling and nutrient retention. Ourdata support earlier studies indicating that greater N:P ratiosin freshwaters not only alter phytoplanktonproduction levels, but may result in communities dominatedby bacterial-sizedcyanobacteria, such as Synechococcus[36, 41, 44]. Suttleand Harrison [38] have shownthat a high affinityfor DIP in Synechococcus spp. may be criticalin favoringsmaller autotrophs in P-limitedsystems. Ourdata revealthat the ecosystemimplications of thishigher affinity for P arereduced losses of nutrientsout of the watercolumn, as well as significantlylower total sedimentation rates.The lack of a similareffect by planktonic,heterotrophic bacteria (Tables 3, 4), whichalso fall into this size range(or even smaller),is not easily explained. Recentstudies have shown, however, thatproduction rates of planktonicbacteria may be directlylimited by inorganicP in freshwaters[15, 40], and this limitation may occur independentlyof a phytoplanktonresponse [25]. It has been suggested that DIP uptakeby planktonicbacteria may exceed demandsand resultin P04-P becoming immobilized,unless there is considerableprotozoan activity [2, 39]. Similardata have led some researchersto state thatplanktonic bacteria may be a phosphorussink [6]. It is still difficult to explain how in the same communities from CalderLake, that greaternumbers of autotrophicpicoplankton will lead to increasedP retention,while presumablymore rapidly-growing (and grazed) bacteria may have the opposite effect (Table 4). Effectiveness and mechanismsof nutrientturnover by heterotrophic(and mixotrophic) flagellates may perhaps differ accordingto food item, withmore rapid mineralization occurring with herbivory on autotrophiccells such as Synechococcus. Further,the ratioof recycledC:N:P resulting from zooplankton herbivory is the resultnot only of the grazingrate and the nutrientcomposition of food items, butis also affected by differentnutrient demands among various zooplanktonspecies MicrobialLoop Efficiency 15

[21]. For example, low P:C ratiosin P-starvedbacteria may lead to still lower P releaserates by grazingflagellates that have high P demands.Phosphorus reminer- alizationmay even approachzero duringactive grazing if P:Cratios of bacteriaand phytoplanktonfall below critical levels [30]. Net mineralizationmeasurements [e.g., 6] and sedimentationefflux measurements(the presentstudy) reflect the combinedeffects of nutrientturnover (leakage, excretion, grazing effects) and utilization(uptake, storage, growth) by each microbialcomponent. Our data suggest that heterotrophicbacteria and autotrophicpicoplankton must differ in some criticalbut not fully knownways thatlead to theirroles as eithersinks or sourcesfor P andN withinthe photiczone.

Acknowledgments.This studywas fundedin partby the NSF, grant# DIR-9002145,and by the Louis CalderCenter, Fordham University. We thankKen Cavassifor helpfulassistance in the field.

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