Hydrobiologia 513: 205–218, 2004.© 2004 Kluwer Academic Publishers. Printed in the Netherlands.

205

Interannual variability in the seasonal plankton succession of a shallow,warm-water lake

Daniel Roelke, Yesim Buyukates, Mike Williams & Jason JeanTexas A&M University, Wildlife and Fisheries Sciences, 2258 TAMUS, College Station, TX 77843-2258, U.S.A.Tel: 979-845-0169. Fax: 979-845-4096. E-mail: droelke@tamu.edu

Received 11 February 2003; in revised form 23 July 2003; accepted 6 August 2003

Key words: warm-water lake, seasonal plankton succession

Abstract

Common seasonal plankton succession patterns in temperate lakes are well understood, and were described in thepopular PEG-model. Seasonal plankton succession in warm-water lakes, however, is not as well known. Recenttheory suggests that some lake systems are characteristic of having alternate system-states, where one of thesystem-states is characterized by dominance of cyanobacteria, and transition between system-states can be abruptand undeterminable. Lake Somerville, a shallow, well-mixed, warm-water reservoir located in eastern TX, U.S.A.,experiences occasional periods of cyanobacteria dominance. To increase our understanding of seasonal planktondynamics in warm-water systems, we analyzed 14-years of plankton data spanning a 22-year period. Duringthis period, succession dynamics characteristic of those described by the PEG-model were observed, as well assuccession dynamics expected during periods of cyanobacteria dominance, i.e., greater accumulated phytoplanktonbiovolume, low secondary productivity, and low light penetration. In addition to the PEG-model and cyanobacteriatype system-states, other states of the system that were intermediate between these were observed. Therefore, weconclude the lake does not behave according to the alternate system-states model. The change from year to year inearly-year cyanobacteria dominance was abrupt and non-monotonic during this period. In addition, the early yearperformance of cyanobacteria appeared to influence the plankton succession trajectory for the remainder of theseason. While the magnitude of lake-flushing early in the year accounted for ∼37% of variability in cyanobacteriaprevalence, many of the traditional factors impacting cyanobacteria dominance appeared insignificant.

Introduction

Efforts to improve water quality and protect hu-man health often focus on phytoplankton biology andfactors that influence the dynamics of phytoplanktonsuccession (Paerl, 1988b; Reynolds, 1994; Roelke &Buyukates, 2001, 2002; VanDolah, et al., 2001). Inlakes these efforts are assisted through use of variouspredictive models that are founded on our understand-ing of foodweb linkages and interactions betweenbiota and the abiotic environment.

One such model, coined the PEG-model, detailsthe seasonal succession of phytoplankton in temper-ate lakes. In this model, early spring is dominatedby highly edible, rapidly growing, r-selected species.

As the season progresses this community gives wayto less edible, slower growing, k-selected species.Factors that influence the succession pattern includelimitation by multiple nutrients and preferential graz-ing (Sommer et al., 1986; Reynolds, 1988; Sommer,1989b; Sterner, 1989). The seasonal succession pat-tern culminates with the onset of fall holomixis fol-lowed by ice cover (Horne & Goldman, 1994; Kalff,2002).

Our knowledge of seasonal succession patterns andcausative mechanisms is not as extensive for warm-water lakes as it is for temperate lakes. While sometrends observed in warm-water lakes are consistentwith descriptions in the PEG-model, deviations areknown to occur. For example, in some systems winter

206

is not a time of low phytoplankton biomass, and nutri-ents can become limiting before onset of stratification(Grover et al., 1999). In addition, seasonal successionoften terminates through a combination of increasedlake-flushing and decreased temperature during thefall and winter months (Paerl, 1988a; Pollingher et al.,1998; Scheffer, 1998).

Another model, complementary to the PEG-model,describes various competing system-states that dictatethe type of seasonal succession that will occur in agiven year (Scheffer et al., 1997; Scheffer, 1998; Car-penter et al., 1999, 2001). For example, a system-stateof high water-quality might exist that is characteristicof low water column nutrients, low phytoplankton,high secondary productivity, and higher water trans-parency. Succession dynamics in this system-statewould likely be similar to dynamics described by thePEG-model. In the same system, however, anothersystem-state of low water-quality might also occur thatis characteristic of high water column nutrients, dom-inance of cyanobacteria, low secondary productivity,and low light penetration. Plankton dynamics in thissystem-state would be very unlike dynamics describedin the PEG-model.

Both system-states appear to be self-sustainingover the course of a season. For example, throughnon-selective and highly effective grazing some clado-cerans help to maintain conditions of deeper lightpenetration, which tends to select against many formsof cyanobacteria because of the greater light pen-etration to mixing depth ratio (Scheffer, 1998). Inturn, this may promote phytoplankton communitiesof higher quality to consumers. The resulting in-creased zooplankton productivity then helps to keepphytoplankton biomass cropped, and maintains deeperlight penetration. Conversely, dominance of cyanobac-teria forms often results in diminished grazing ratesand grazer populations (Schindler, 1971; Gliwicz &Lampert, 1990; Haney et al., 1994), allowing ac-cumulation of phytoplankton biomass and causingdecreased light penetration, a condition which fa-vors continued growth of cyanobacteria over otherphytoplankton (Scheffer, 1998).

Factors that influence which system-state occursin a lake are debated, and include sediment phos-phorus content, magnitude of flushing, and the ratioof light penetration to mixing depth (Scheffer et al.,1997; Scheffer, 1998; Carpenter et al., 1999, 2001). Intheory, transitional values for these factors must existwhere a lake system is situated on the edge of compet-ing system-states. In other words, which system-state

is selected in a given year becomes very sensitive toenvironmental conditions early in the year. Indeed,this has been documented in some lakes, where thelake abruptly changed back and forth between thesystem-states (Scheffer, 1998).

Anecdotal evidence from Lake Somerville, TX,suggested that the lake might behave in accordancewith the alternate system-states model. For example,an abrupt change from the typical plankton succes-sion pattern to dominance of cyanobacteria occurredin 1998, although no system level-disturbances thatmight have caused this change were observed (Khan,pers. commun.). The lake reverted back to typical suc-cession in 1999, again with no accompanying system-level changes observed. System behavior of this natureis consistent with a lake situated on the edge of com-peting system-states. Our purpose here is to test thishypothesis, as well as to increase our understandingof plankton succession patterns in warm-water lakes.We use both newly collected data and historical datathat combined represent 14-years of plankton dataspanning a period of 22-years. We structure our ana-lyses within the framework of the PEG and alternatesystem-states models.

Materials and methods

Lake Somerville is a reservoir located in eastern Texasconstructed by the Army Corps of Engineers in 1967for purposes of flood control. Typically, the lake’ssurface area is ∼11 460 acres, mean depth is ∼4 m,and maximum depth is ∼9 m. For this research, waterquality and plankton data were analyzed from one sta-tion located at the lower end of the lake, 30◦ 19.08′latitude, 96◦ 31.31′ longitude. Our recent samplingperiod occurred over 4-years (1999–2002) with tripsconducted monthly. The time of sampling rangedbetween 9:30 a.m. and 10:30 a.m. for all trips. We alsocompiled 11-years of historical data from this station(1980–1990, winter, spring, and summer sampling),as described below.

Sampling of the plankton was from surface wa-ters only, i.e., ∼0.5 m depth. Phytoplankton andzooplankton were collected using a sampling bottleand 12-l Schindler trap, respectively. Phytoplanktonsamples were preserved in 2% glutaraldehyde, andzooplankton samples were preserved in 2% bufferedformalin. Both were enumerated using inverted light-microscopy (Utermohl, 1958). For phytoplankton, ap-propriate dimensions were measured and biovolume

207

calculated using formulas of corresponding geomet-ric shapes (Wetzel & Likens, 1991), and identificationwas at least to the taxonomic level of genus (Prescott,1978). Zooplankton was categorized into copepods(adults and nauplii), cladocerans (Daphnia and Bos-mina), rotifers, and ciliates. Historical phytoplanktondata were made available through the Army Corps ofEngineers with identification at least to the taxonomiclevel of genus.

Water-quality parameters were also determined atthe time of plankton sampling, which included nu-trients, temperature and light penetration. Nutrientsamples were filtered through 47 mm GF/F filters andfrozen for transport to the laboratory. Nutrient ana-lyses included nitrate (NO3), nitrite (NO2), ammonia(NH4), urea, soluble reactive phosphorus (SRP), andsilicate (SiO2) using autoanalyzer methodology (Arm-strong & Sterns, 1967; Harwood & Kuhn, 1970).Temperature was measured using a water quality mul-tiprobe (Hydrolab H20), and profiles were approx-imated by collecting data at 0.5-m (towards surface)and 1-m intervals. Light penetration was estimated bytaking the secchi depth.

Samples for determination of chlorophyll a andphaeophytin a were also collected. Typically, 50 mlsamples were taken in triplicate and filtered onto 47mm GF/F filters using gentle vacuum, then frozen fortransport to the laboratory. Chlorophyll a and phaeo-phytin a samples were extracted in 10 ml 90% acetoneand analyzed using a fluorometric method (APHA,1998).

Lake flushing was determined for a 20-year period(1983–2002) spanning the historical and more recentperiods of study. Daily records of total inflow andreservoir volume were obtained from the Army Corpsof Engineers and U.S. Geological Survey. Flushingwas calculated by dividing the total inflow by the lakevolume. The mean flushing rate over a period of 90-days prior to each of the sampling dates was alsocalculated.

In addition to investigating phytoplankton com-munity structure, we analyzed diversity at the taxo-nomic level of genus. Diversity was calculated usingthe Shannon–Weaver index:

H′ =x∑

i=1

pi log 2(pi ), (1)

where pi was the proportion of biovolume of gen-era i relative to the total biovolume on a given date,and x was the total number of phytoplankton generaobserved.

Linear and nonlinear relationships were investig-ated between flushing and light penetration early inthe year with cyanobacteria dominance using linear,power, and logarithmic regression curve fitting (Syn-ergy & Software, 1999). We used the mean 90-dayflushing values when attempting to correlate flushingwith cyanobacteria dominance. For the analysis fo-cusing on light penetration, winter secchi depths wereplotted against spring cyanobacteria dominance.

Results

Seasonal hydrology in Lake Somerville for the periodof 1983 through 2002 was erratic (Fig. 1a). In someyears flushing was greatest in the fall and wintermonths, but in other years maximum flushing occurredin the summer or spring. Periods of high flushing werefew and short-lived, typically lasting only 2–3-days.Flushing magnitude reached as high as ∼0.35 d−1, andon average was 0.004 ± 0.011 d−1.

Focusing on the period of 1999 through 2002 (Fig.1b), it can be seen that late 1999 through mid-year2000 was a relatively dry period. The mean flushingfor the winter period of January through March was0.0015 ± 0.0023 d−1. Conversely, late 2000 through2001 was a relatively wet period, with flushing for thesame winter period averaging 0.0082 ± 0.0106 d−1.Winter flushing during late 2001 through mid-2002was intermediate, and had a mean value of 0.0021 ±0.0028 d−1.

There is a chance that we underestimated lake-flushing because we used the entire volume of thelake in our calculation. For example, if flow throughthe lake were confined to areas near the historical ri-verbed flushing in this portion of the lake would bemuch higher. We do not believe this was the case,however. The historical riverbed runs from west toeast, and the predominant winds are south to north.Indeed, windrows spanning the width of the lake arefrequently observed orthogonal to the riverbed, whichare indicative of Langmuir circulation churning thelake.

Temperature trends in Lake Somerville for theperiod spanning late 1999 through 2002 showed arange of ∼20 ◦C, with minimum and maximum val-ues of ∼10 and ∼30 ◦C, respectively (Fig. 2). BecauseLake Somerville is shallow, there was no consequen-tial seasonal thermal stratification, and the lake wassubject to frequent and complete mixing events. In ouranalyses below we use secchi depth as a surrogate for

208

Figure 1. Flushing in Lake Somerville, TX for a 20-year period (a), which spanned the more recent (b) and historical periods of study.Consistent seasonal trends were not apparent. The period from late-1999 through 2000 was relatively dry, 2001 was relatively wet, and 2002was intermediate.

secchi depth to mixing depth ratio, because mixingdepth in Lake Somerville was constant, i.e., the entirewater column.

In the more recent data, some seasonal succes-sion trends consistent with the PEG-model were ob-served in Lake Somerville, but only during 2001 and2002. In these years a spring phytoplankton bloom oc-curred dominated by diatoms (Fig. 3a). Chain-formingMelosira spp. dominated the diatom community dur-ing the spring bloom of 2001 resulting in decreased

diversity. During the spring bloom of 2002 multiple di-atom species prospered and diversity was maintained(Figs 3b and 4a).

The spring 2001 bloom of phytoplankton appearedto be highly edible, despite the large size of theMelosira chains, which were typically between 300and 600 µm in length (see Sterner, 1989). Evidencesupporting this notion were the dramatic increases inrotifer, cladoceran, and copepod populations (Fig. 5a,b) that were synchronous with a decrease in phyto-

209

Figure 2. Temperature profiles in Lake Somerville, TX for the late-1999 through 2002 period. Thermal stratification was inconsequentialduring this period and complete mixing of the water-column was frequent.

plankton biovolume (Fig. 3a). In addition, a spike inthe phaeophytin a to chlorophyll a ratio, which is anindicator of grazing activity (Mantoura & Llewellyn,1983; Roelke et al., 1997), shortly followed the zo-oplankton population peaks (Fig. 5c). Finally, gutcontents of gizzard shad, Dorosoma cepedianum, werefilled with Melosira spp. at this time (Fejes et al.,2003). While no grazing experiments were conductedduring this research, we feel that the phytoplanktonand zooplankton population demographics, and coin-cident changes in the phaeophytin a to chlorophyll aratio are strong indicators of active grazing.

The spring 2002 bloom of phytoplankton appearedto be less edible compared to 2001. Cyanobacteriaabundance, which included Microcyctis spp., a gen-era known to inhibit grazers (see Horne & Goldman,1994), was greater in 2002 (Figs 3a and 4b). Inaddition, rotifer, cladoceran, and copepod popula-tions were not as abundant, and the phaeophytin a tochlorophyll a ratio was not as high (Fig. 5).

The impact of grazing activity, which we deducedfrom observed population demographics and phae-ophytin a to chlorophyll a ratio, in the spring of2001 and 2002 altered the water-column environment.The deepest secchi depths observed in this study oc-curred after the termination of these spring blooms,which we now refer to as clear-water phases (Fig. 3c).Inorganic nutrients increased during the clear-waterphases, presumably due to grazer egestion and excre-tion processes (Sommer et al., 1986; Sommer, 1989b;

Sterner, 1989), with the increase quite pronounced in2001 (Fig. 6). The increase in DIN was most dramaticduring 2001, with almost all of it in the form of NO3(Fig. 6a). The DIN to SRP ratio spiked at this time aswell (Fig. 6c). In 2002, again DIN increased more thanSRP, with most of the nitrogen in the form of NH4.

It appears that the demise of the spring bloom ofdiatoms in 2001 was not just a function of heavy graz-ing activity. SiO2 concentrations dropped below 3 µM(Fig. 6d), which is below the kS value for Si-limitedgrowth for many diatoms (Horne & Goldman, 1994).Consequently, it is likely that SiO2 became limitingin Lake Somerville in the spring of 2001. During thewinter and early spring, DIN and SRP did not ap-pear to be limiting, as ambient concentrations weremuch higher than typical kS values for N-and P-limitedgrowth.

Zooplankton populations declined during theclear-water phases, but did not totally disappear, i.e.,rotifers persisted (Fig. 5a, b). This allowed for asecond phytoplankton bloom to occur that was morediverse and was comprised of a mix of genera that rep-resented edible and ‘less’ edible forms (Figs 3 and 4).For example, based on cell-size, morphology, nutri-tional content, and results from previous research, taxabelonging to the genera Clamydomonus, Chlorella,Scenedesmus, and Crucigenia, as well as forms ofcentric diatoms, are deemed edible and are even con-sidered preferred prey items, while taxa belonging toMicrocystis are thought of as ‘less’ edible (Sommer

210

Figure 3. Phytoplankton bulk community structure (a) and diversity (b), and secchi depth (c). Phytoplankton biovolume was much greater in2000 compared to 2001 and 2002, and was dominated by cyanobacteria. In 2001 a spring bloom dominated by diatoms was followed by aclear-water phase that gave way to a second more diverse bloom. By late summer cyanobacteria dominated the phytoplankton community. In2002 a spring bloom occurred, again rich with diatoms but also cyanobacteria. A clear-water phase occurred followed by increased prevalenceof cyanobacteria late in the summer. For the years 2001 and 2002, arrows indicate the times of zooplankton population and phaeophytin a tochlorophyll a ratio maxima.

211

Figure 4. Phytoplankton community structure at the taxonomic level of genus divided into diatoms (a), cyanobacteria (b), and green algae (c).During 2000, cyanobacteria dominated the phytoplankton community, and showed population shifts from dominance of Microcystis spp. inthe winter to co-dominance of Aphanocapsa spp. and Aphanizominon spp. during the spring, and finally co-dominance of Aphanocapsa spp.and Oscillatoria spp. in the summer (note that the y-axis is scaled differently for panel b). During 2001, Melosira spp. dominated the springbloom. This bloom gave way to a clear-water phase that was followed by a second more diverse bloom. Towards the late summer Phormidiumspp. became dominant. In 2002, the spring bloom was comprised of multiple diatom species, and Microcystis spp., which persisted through theclear-water phase. Again, towards late summer Phormidium spp. became dominant. For the years 2001 and 2002, arrows indicate the times ofzooplankton population and phaeophytin a to chlorophyll a ratio maxima.

212

Figure 5. Zooplankton community structure divided into rotifers,ciliates, and copepod nauplii (a) and cladocerans and adult copepods(b), and the phaeophytin a to chlorophyll a ratio as an indicator ofgrazing activity (c). Population maxima occurred for all zooplank-ton following the spring bloom in 2001 and 2002, although smallerpeaks occurred in 2002. Heavy grazing activity in 2001, as indicatedby the elevated phaeophytin a to chlorophyll a ratio, contributedto the clear-water phase that occurred at that time. During 2000,populations of large zooplankton were non-existent.

et al., 1986; Sterner, 1989; Sterner & Hessen, 1994;Horne & Goldman, 1994). As the summer progressedthe community eventually shifted to dominance of cy-anobacteria from the genus Phormidium. This patternwas more pronounced in 2001 than in 2002 (Figs 3aand 4b).

The succession pattern in 2000 was very differ-ent from 2001 and 2002, and inconsistent with thePEG-model. During 2000 cyanobacteria dominatedthe phytoplankton community most of the time (Fig.3a). Early in the spring Microcystis spp. dominated,and this population appeared to be carry-over fromthe autumn and winter of 1999 (Fig. 4b). Opposite ofwhat was observed in 2001 and 2002, phytoplanktonbiovolume continued to increase through the springmonths and into the early summer, and reached con-centrations ∼2-fold greater than what was observed in2001 and 2002. Cyanobacteria continued to dominate,but the community shifted to dominance of species

from the genera Aphanocapsa and Aphanizominon. Acentric diatom (Stephanodiscus-like) also became pre-valent. Seasonal SiO2 reached its minimum at thistime, but was not as depleted as it was in 2001 (Fig.6). Similarly, rotifer populations increased during thistime, similar to 2002 but not to the same degree as in2001, and larger zooplankton were scarce (Fig. 5a, b).

A dramatic decrease in the phytoplankton biovolumeoccurred in the early summer of 2000, and it is unclearwhat might have caused it. It is not likely that graz-ing activity was a significant factor because there wereno corresponding increases in grazer populations, thephaeophytin a to chlorophyll a ratio was low (Fig. 5),and there were no increases in nutrient concentrations(Fig. 6). It is not likely that pathogens significantlycontributed either because signs of infection duringmicroscopic examination were not detected.

The phytoplankton quickly recovered, however,and increased in biovolume through the remain-ing summer months and into the autumn. Again,biovolume was ∼2-fold higher in 2000 compared to2001 and 2002 during this period. Cyanobacteria con-tinued to dominate the phytoplankton community, andthe composition again shifted with Aphanocapsa spp.and Oscillatoria spp. sharing dominance (Figs 3aand 4b). Through the autumn and winter months thephytoplankton biovolume diminished (Fig. 3a), rotiferpopulations increased slightly (Fig. 5a), and nutrientconcentrations increased (Fig. 6).

Light penetration, as estimated from secchi depth,varied between 2000, 2001, and 2002. All yearsshowed a similar pattern of deeper light penetrationin the spring and early summer months, and less inthe late summer and autumn months (Fig. 3c). Butsecchi depths were much less during the late-winterand spring in 2000, e.g., light penetration in 2000 wasonly about half of that in 2001.

The historical data shows no consistent trend withpertinent aspects of the PEG-model. For example, adiatom-dominated spring bloom was not apparent in1982 and 1989. Instead, green algae (Tetradron spp.)and cyanobacteria (Oscillatoria spp.) co-dominated in1982, and a euglenoid (Trachelomonas spp.) dom-inated 1989 (Table 1). In addition, diatoms of thegenera Melosira, a meroplanktonic strategist that isexpected to become dormant during summer months,often persisted into the summer as a major contributorto the total phytoplankton biovolume. Also, summer-time prevalence of cyanobacteria, observed in all yearsof our recent sampling, was not always observed inthe historical data. For example, cyanobacteria only

213

Figure 6. Inorganic nutrient concentrations divided into species of nitrogen (a), soluble reactive phosphorus (b), N:P ratio (c), and silicate (d).Remineralization of all nutrients occurred in 2001 and 2002 during the clear-water phase, although less so in 2002. Nitrogen was returned tothe water column at greater proportions than phosphorus because of the presence of cladocerans, which have high demand for phosphorus. Thespring bloom of diatoms became silica-limited only in 2001, which contributed to the demise of the spring bloom in that year.

214

Figure 7. A nonlinear relationship between early-year lake flushing and early-year cyanobacteria prevalence was observed using a powerfunction regression curve, which accounted for ∼37% of the variance. Note that many intermediate values were observed regarding the percentcyanobacteria composition.

accounted for 5%, 2%, and 19% of the total phyto-plankton biovolume in 1982, 1988, and 1989, respect-ively. Finally, decreased light penetration as the seasonprogresses from spring to summer, again observed inall years of our more recent sampling, was seldomobserved in the historical data.

The 3-years of monthly sampling in LakeSomerville indicated that cyanobacteria prevalence inthe winter and spring does occur, another phenomenonnot consistent with the PEG-model, but not everyyear. Historical data support this observation. Forexample, 51%, 76% and 41% of the phytoplank-ton biovolume was comprised of cyanobacteria in thewinter samplings of 1980, 1988 and 1990, respectively(Table 1). Only once in the historical data was thespringtime cyanobacteria contribution significant, i.e.,32% in 1982.

A nonlinear relationship between the early sea-son mean 90-d flushing and cyanobacteria prevalencewas observed (Fig. 7), i.e., a power-function fit in-dicated that 37% of the variance in cyanobacteriaprevalence could be explained by variations in lake

flushing. No significant relationships, linear or non-linear, were detected between winter secchi depth andspring cyanobacteria prevalence.

Discussion

During 2001 the plankton succession pattern in LakeSomerville followed predictions made by the PEG-model and observations from other warm-water lakes.For example, a spring bloom occurred which wasdominated by diatoms. This is an early-stage of suc-cession as described in the PEG-model for temperatelakes (Sommer et al., 1986; Sommer, 1989a), andis also a common occurrence in warm-water lakes(Porter et al., 1996; Phlips et al., 1997; Grover et al.,1999). In addition, it appeared that the stimulation ofsecondary productivity was a result of the dominanceof highly edible phytoplankton forms, and that a coup-ling of SiO2-limition and heavy grazing losses was themechanism resulting in the rapid decrease of diatombiovolume. Both are well-documented events in lakes(Sommer et al., 1986; Sommer, 1989b; Horne & Gold-

215

Table 1. Historical records. Dates of sampling, seasonal categorization (w – winter, sp – spring, su – summer), secchi depth,% of totalphytoplankton biovolume comprised of cyanobacteria, and phytoplankton genera comprising >10% of total phytoplankton biovolume withpercent contribution in parentheses

1980 30-Jan w 1.0 51% Cyclotella (34), Anacystis (34), Synechococcus (17), Ankistrodesmus (13)

21-May sp 0.9 3% Melosira (68), Cyclotella (11)

29-Aug su 0.6 89% Oscillatoria (40), Anabaenopsis (39)

1981 6-Mar w 1.0 17% Synedra (24), Cyclotella (22), Scenedesmus (12), Anacystis (11)

30-Apr sp 0.7 1% Melosira (70)

24-Aug su 0.8 65% Oscillatoria (56), Scenedesmus (18), Cyclotella (15)

1982 18-Feb w 0.6 <1% Trachelomonas (84)

2-June sp 0.9 32% Tetraedron (49), Oscillatoria (22)

12-Aug su 0.7 5% Trachelomonas (93)

1983 25-Jan w 0.9 <1% Trachelomonas (61), Melosira (26)

4-May sp 0.4 1% Cyclotella (60), Melosira (20)

1984 5-Jan w 1.0 17% Melosira (53), Chroococcus (14)

2-May sp 0.5 1% Melosira (89)

1-Aug su 0.6 72% Psuedoanabaena (55), Melosira (15), Trachelomonas (11)

1985 9-Jan w 0.6 4% Melosira (79)

23-Apr sp 0.7 6% Melosira (71), Cyclotella (16)

1-Aug su 0.7 41% Trachelomonas (41), Anabaena (14), Oscillatoria (12)

1986 4-Mar w 0.5 27% Melosira (38), Synechococcus (11), Mesotaenium (10)

14-May sp 1.1 5% Melosira (66)

14-Aug su 1.1 75% Synechococcus (38), Chroococcus (15), Melosira (13), Anabaenopsis (10)

1987 26-Jan w 0.6 18% Melosira (46)

16-Apr sp 0.5 <1% Stephanodiscus (79)

19-Aug su 0.5 39% Trachelomonas (41), Psuedoanabaena (18), Melosira (13), Anabaenopsis (12)

1988 26-Jan w 0.3 76% Oscillatoria (70), Stephanodiscus (10)

26-Apr sp 0.7 10% Melosira (87)

19-Jul su 0.7 2% Trachelomonas (89)

1989 20-Jan w 0.8 17% Stephanodiscus (29), Melosira (29)

2-May sp 1.1 10% Trachelomonas (63)

16-Aug su 0.8 19% Melosira (45), Stephanodiscus (16), Psuedoanabaena (11)

1990 10-Jan w 0.8 41% Chroococcus (39), Stephanodiscus (29)

17-Apr sp 0.6 8% Stephanodiscus (63), Cyclotella (14), Scenedesmus (10)

18-Jul su 0.6 52% Chroococcus (27), Melosira (21), Psuedoanabaena (16), Stephanodiscus (15)

man, 1994). Finally, a clear-water phase occurred thatwas followed by a second more diverse phytoplanktonbloom, which gradually gave way to the predomin-ance of less edible phytoplankton forms due to thepersistence of some grazers. Again, this sequence ofevents is thoroughly described in the PEG-model. Theless edible phytoplankton form that eventually becamedominant was a cyanobacterium, which is a commontrend observed in other warm-water lakes (Scheffer,1998; Grover et al., 1999).

In addition to the bulk trends described above,there were more subtle events that occurred in 2001that fit well with other predictive models. The highestobserved DIN to SRP ratio was observed during the

clear-water phase, and this appeared to be the res-ult of cladoceran grazing activity. Cladocerans have ahigh demand for phosphorus relative to nitrogen, andthe stoichiometry of zooplankton in general is strictlyregulated (Sterner & Hessen, 1994). Taken together,the abundance of cladocerans and their grazing on thespring bloom in 2001 resulted in greater amounts ofDIN returned to the water column relative to SRP, andincreased light penetration. The subsequent and rapidchange in DIN to SRP ratio, and light availability,might have contributed to the lack of cyanobacteriadominance and greater diversity in the second phyto-plankton bloom that followed the clear-water phase

216

(Tilman, 1977; Sommer, 1989b; Sterner & Hessen,1994; Oliver & Ganf, 2000).

While the seasonal succession pattern in 2001 fitwell with our understanding of general successiontrends in temperate lakes, the succession pattern in2000 did not. During this year cyanobacteria, whichincluded species from the genera Microcystis and Os-cillatoria, dominated the phytoplankton communitymost of the time, and this resulted in low secondaryproductivity and diminished light penetration. Manyforms of cyanobacteria are known to be poor foodsources to zooplankton (Schindler, 1971; Ganf, 1983;Nizan et al., 1986). And some blooms of cyanobac-teria are known to become self-sustaining by creatinglight-limited environments for competitors (Schefferet al., 1997; Scheffer, 1998). In other words, thesuccession pattern during 2000 resembled that of analternate system-state, as described by the alternatesystem-states model.

However, the succession pattern observed in 2002appeared to be something intermediate between thetwo previous years. For example, the spring bloomwas rich with diatoms, but also prevalent with Micro-cystis spp. The bloom was grazed down, a clear-waterphase was apparent, and phytoplankton biomass didnot accumulate unchecked, but grazing activity wasnot as high, and grazer biomass was reduced, butnot decimated. An intermediate state, such as this, isnot consistent with the alternate system-states model.Rather it suggests that the lake dynamics follow alonga gradient between the two system-states. Indeed,combining the more recent data with the historicaldata reveals that early in the year there exists a gradi-ent of assemblage structures where the contribution ofcyanobacteria to the total biovolume ranges between<1% and 76%, with many intermediate values. If thelake behaved according to the alternate system-statesmodel there should have been two distinct clusters ateither end of the spectrum.

The 1999 through 2002 data showed that cy-anobacteria performance early in the year influencedthe seasonal plankton succession trajectory, especiallyin regards to zooplankton performance. So under-standing factors that influence cyanobacteria early inthe year seem to be essential for understanding sea-sonal patterns. Might there be a gradient of envir-onmental conditions that correlate with the gradientof plankton assemblage structures? Changes in lightpenetration early in the year, a factor known to influ-ence eventual cyanobacteria dominance (Scheffer etal., 1997; Scheffer, 1998), did not seem to influence

the performance of cyanobacteria. As stated previ-ously, lake flushing, another factor known to influencecyanobacteria performance (Paerl, 1988b; Grover etal., 1999), accounted for only ∼37% of this variab-ility. Nitrogen and phosphorus concentrations earlyin the year for the period from 1999 through 2002did not appear to be limiting, similar nutrient concen-trations were observed in the historical data as well(Roelke et al., In Preparation). What other factorsmight have influenced the early season performanceof cyanobacteria in this lake?

Unlikely factors include pathogens and pollutants.For example, in the 3+ years of microscopic exam-ination, up to 1000× magnification, signs of infec-tion or cell lysis were never observed for any of thephytoplankton taxa. Similarly, atrizine, a widely usedherbicide in this agriculturally-dominated watershed,was never detected. Finally, iron, manganese, sulf-ide, chloride and total dissolved solids never exceededwater-quality standards (Roelke, unpublished data).

Other factors, which might have had an impact onplankton dynamics in Lake Somerville, but were notaccounted for in this study, include nutrient loading.While the direct impact of flushing appeared to belimited, the nutrient load associated with the flush-ing might have been significant. Nutrient loading isnot likely to correlate well with ambient nutrient con-centrations because of the reactivity of some nutrientswith the lake’s biotic and abiotic constituents.

Another factor is over-wintering plankton dynam-ics, or the persistence of some phytoplankton pop-ulations. When considering ‘resetting’ of the sea-sonal succession trajectory, how significant are factorssuch as decreasing temperature and increasing turbu-lence during the winter? There was a clear differencebetween the persistent populations that over-winteredin 1999–00 and 2001–02 that eventually became a partof the spring bloom community, compared to the com-munity that disappeared at the end of 2000 and gaveway to a new community in 2001.

Finally, non-linear dynamics might have played arole. Complex behavior arising from competition forresources, and/or predator prey interactions are welldescribed in theory. Both have been shown to pro-duce non-linear, sometimes chaotic, system-behavior(Ebenhoh, 1988; Huisman & Weissing, 2001; Pet-rovskii et al., 2001). Furthermore, some non-lineardynamics appear to be fragile. For example, usingnumerical models and laboratory experiments on nat-ural plankton assemblages complex plankton behaviorwas shown to disappear when disturbances of large

217

magnitude, e.g., flushing and nutrient pulses, oc-curred (Roelke et al., 2003). Flushing losses in LakeSomerville for the period of this study were muchless than what was required to suppress potentialcomplex behavior. In addition, because the lake iscontinuously well-mixed disturbances associated withnutrient pulses that follow the breakdown of thermalstratification would be negated.

In summary, the seasonal plankton succession pat-tern in Lake Somerville at times resembled the sea-sonal succession pattern of many temperate lakes, asdescribed by the PEG-model. But significant devi-ations from plankton succession trajectories consistentwith the PEG-model were often observed, e.g., nospring bloom of diatoms, significant persistence ofMelosira populations into the summer, no summerdominance of cyanobacteria, and increased secchidepths in the summer. Seasonal plankton succes-sion trajectories were not consistent with the altern-ate system-states model because many intermediatesystem-states occurred. Abrupt and non-monotonicchanges in phytoplankton community composition,especially in regards to the percent contribution ofcyanobacteria, occurred from year to year. In addi-tion, the prevalence of cyanobacteria early in the yearmight impact the plankton dynamics for the remainderof the season. Unfortunately, factors influencing earlyyear cyanobacteria performance are still largely un-known. Future research should focus on the role ofnutrient loading, over-wintering plankton dynamics,and potential complex trophic interactions.

Acknowledgements

The authors are grateful to the U.S. Army Corps ofEngineers and the U.S. Geological Survey for makinghistorical data available for this research. We are alsothankful to reviewers for their critiques on a previousiteration of this manuscript. This research was funded,in part, by the National Science Foundation’s Re-search Education for Undergraduates Program, awardnumber EEC-9912278, and the U.S. Army Corps ofEngineers, contract number DACW63-00-P-0508.

References

APHA, 1998. Standard Methods for the Examination of Water andSewage. American Public Health Association, Boston: 144 pp.

Armstrong, F. A. & C. R. Sterns, 1967. The measurement of up-welling and subsequent biological processes by means of the

Technicon Autoanalyzer and associated equipment. Deep SeaResearch I 14: 381–389.

Carpenter, S., B. Walker, J. M. Anderies & N. Abel, 2001.From Metaphor to Measurement: Resilience of What to What?Ecosystems 4: 765–781.

Carpenter, S. R., R. C. Lathrop & W. A. Brock, 1999. Manage-ment of eutrophication for lakes subject to potentially irreversiblechange. Ecological Applications 9: 751–771.

Ebenhoh, W, 1988. Coexistence of an unlimited number of algalspecies in a model system. Theoretical Population Biology 34:130–144.

Fejes, E., J. Birnbaum, F. Gelwick & D. Roelke, 2003. Vertical dis-tribution of herbivorous zooplankton in a well-mixed lake systemin which the main predator is a non-selective filter-feeding fish.Journal of Freshwater Research 18: 333–336.

Ganf, G. G., 1983. An ecological relationship between Aphanizo-menon and Daphnia pulex. Australian Journal of Marine andFreshwater Research 34: 755–773.

Gliwicz, Z. M. & W. Lampert, 1990. Food thresholds in Daph-nia species in the absence and presence of blue-green filaments.Ecology 71: 691–702.

Grover, J. P., R. W. Sterner & J. L. Robinson, 1999. Algal growthin warm temperate reservoirs: nutrient-dependent kinetics of in-dividual taxa and seasonal patterns of dominance. Archiv fürHydrobiologie 145: 1–23.

Haney, J. F., D. J. Forsyth & M. R. James, 1994. Inhibitionof zooplankton filtering rates by dissolved inhibitors producedby naturally occurring cyanobacteria. Archiv für Hydrobiologie132: 1–13.

Harwood, J. E. & A. L. Kuhn, 1970. A colorimetric method forammonia in natural waters. Water Research 4: 805–811.

Horne, A. J. & C. R. Goldman, 1994. Limnology. McGraw-Hill.Inc., New York: 576 pp.

Huisman, J. & F. J. Weissing, 2001. Fundamental unpredictabilityin multispecies competition. The American Naturalist 157: 488–494.

Kalff, J., 2002. Limnology. Prentice Hall. Upper Saddle River: 592pp.

Mantoura, R. F. C. & C. A. Llewellyn, 1983. The rapid determ-ination of algal chlorophyll and carotenoid pigments and theirbreakdown products in natural waters by reverse-phase high per-formance liquid chromatography. Analytica Chimica Acta 151:297–314.

Nizan, S., C. Dimentman & M. Shilo, 1986. Acute toxic effects ofthe cyanobacterium Microcystis aeruginosa on Daphnia magna.Limnology and Oceanography 31: 497–502.

Oliver, R. L. & G. G. Ganf, 2000. Freshwater blooms. In Whitton,B. A. & M. Potts (eds), The Ecology of Cyanobacteria. KluwerAcedemic Publishers, Dordrecht, The Netherlands: 149–194.

Paerl, H. W., 1988a. Growth and reproductive strategies of fresh-water blue-green algae (cyanobacteria). In Sandgren, C. D. (ed.),Growth and Reproductive Strategies of Freshwater Phytoplank-ton. Cambridge University Press, Cambridge: 261–315.

Paerl, H. W., 1988b. Nuisance phytoplankton blooms in coastal,estuarine, and inland waters. Limnology and Oceanography 33:823–847.

Petrovskii, S., K. Kawasaki, F. Takasu & N. Shigesada, 2001. Dif-fusive waves, dynamical stabilization and spatio-temporal chaosin a community of three competitive species. Japan Journal ofIndustrial and Applied Mathematics 18: 459–481.

Phlips, E. J., M. Cichra, K. Havens, C. Hanlon, S. Badylak, B.Rueter, M. Randall and P. Hansen, 1997. Relationships betweenphytoplankton dynamics and the availability of light and nutri-

218

ents in a shallow sub-tropical lake. Journal of Plankton Research19: 319–342.

Pollingher, U., O. Hadas, Y. Z. Yacobi, T. Zohary & T. Berman,1998. Aphanizomenon ovalisporum (Forti) in Lake Kinneret,Israel. Journal of Plankton Research 20: 1321–1339.

Porter, K. G., P. A. Saunders, K. A. Haberyan, A. E. Macubbin, T. R.Jacobsen & R. E. Hodson, 1996. Annual cycle of autotrophic andheterotrophic production in a small, monomictic Piedmont lake(Lake Oglethorpe): Analog for the effects of climatic warming ondimictic lakes. Limnology and Oceanography 41: 1041–1051.

Prescott, G. W., 1978. How to Know the Freshwater Algae. W.C.Brown Company Publishers, Dubuque (I.O.): 293 pp.

Reynolds, C. S., 1988. The concept of ecological succession ap-plied to seasonal periodicity of freshwater phytoplankton. Ver-handlungen der Internationalen Vereinigung für Limnologie 23:683–691.

Reynolds, C. S., 1994. The ecological basis for the successful bio-manipulation of aquatic communities. Archiv für Hydrobiologie130: 1–33.

Roelke, D. L. & Y. Buyukates, 2001. The diversity of harm-ful algal bloom-triggering mechanisms and the complexity ofbloom initiation. Human and Ecological Risk Assessment 7:1347–1362.

Roelke, D. L. & Y. Buyukates, 2002. Dynamics of phytoplanktonsuccession coupled to species diversity as a system-level toolfor study of Microcystis population dynamics in eutrophic lakes.Limnology and Oceanography 47: 1109–1118.

Roelke, D. L., L. A. Cifuentes & P. M. Eldridge, 1997. Nutrientand phytoplankton dynamics in a sewage impacted gulf coastestuary: a field test of the PEG-model and Equilibrium ResourceCompetition theory. Estuaries 20: 725–742.

Roelke, D.L., S. Augustine & Y. Buyukates, 2003. Fundamentalpredictability in multispecies competition: The influence of largedisturbance. The American Naturalist 162: 615–623.

Scheffer, M., 1998, Ecology of Shallow Lakes, Chapman & Hall,London: 357 pp.

Scheffer, M., S. Rinaldi & Y. A. Kuznetsov, 1997. On the dominanceof filamentous cyanobacteria in shallow turbid lakes. Ecology 78:272–282.

Schindler, D. E., 1971. Food quality and zooplankton nutrition.Journal of Animal Ecology 40: 589–595.

Sommer, U., 1989a. Plankton Ecology, Springer-Verlag, Berlin: 364pp.

Sommer, U., 1989b. The role of competition for resources in phyto-plankton succession. In Sommer, U. (ed.), Plankton Ecology.Springer-Verlag, Berlin: 57–106.

Sommer, U., Z. M. Gliwicz, W. Lampert & A. Duncan, 1986. ThePEG-model of seasonal succession of plankton events in freshwaters. Archiv für Hydrobiologie 106: 436–440.

Sterner, R. W., 1989. The role of grazers in phytoplankton succes-sion. In Sommer, U. (ed.), Plankton Ecology. Springer-Verlag,Berlin: 107–170.

Sterner, R. W. & D. O. Hessen, 1994. Algal nutrient limitation andthe nutrition of aquatic herbivores. Annual Review of Ecologyand Systematics 25: 1–29.

Synergy and Software, 1999. KaleidaGraph 3.08. 2457 PerkiomenAvenue, Reading, PA 19606–2049.

Tilman, D., 1977. Resource competition between planktonic algae:an experimental and theoretical approach. Ecology 58: 338–348.

Utermohl, H., 1958. Zur Vervollkommnung der quantitativen Phyto-plankton Methodik. Mitteilungen Internationale Vereinigung fürTheoretische und Angewandte Limnologie 9: 263–272.

VanDolah, F. M., D. L. Roelke & R. M. Greene, 2001. Healthand ecological impacts of harmful algal blooms: risk assessmentneeds Human and Ecological Risk Assessment 7: 1329–1345.

Wetzel, R. G. & G. E. Likens, 1991. Limnological Analysis.Springer-Verlag, New York: 391 pp.