Accepted: 23 March 2018

DOI: 10.1111/fwb.13116

ORIGINAL ARTICLE

Mechanisms preventing a decrease in biomass after phosphorus reductions in a German drinking water reservoir—results from more than 50 years of observation

Valerie Carolin Wentzky1,2 | Jorg€ Tittel1 | Christoph Gerald Jager€ 2 | Karsten Rinke1

1Department of Lake Research, Helmholtz Centre for Environmental Research, Abstract Magdeburg, 1. To counteract the severe consequences of eutrophication on water quality and 2Department of Aquatic ecosystem health, nutrient inputs have been reduced in many lakes and reser- Analysis, Helmholtz Centre for Environmental Research, Magdeburg, voirs during the last decades. Contrary to expectations, in some lakes phyto- Germany plankton biomass did not decrease in response to oligotrophication (nutrient Correspondence reduction). The underlying mechanisms preventing a decrease in biomass in these Valerie Wentzky, Department of Lake lakes are the subject of ongoing discussion. Research, Helmholtz Centre for Environmental Research, Magdeburg, 2. We used a hitherto unpublished long-term data set ranging from 1961 until Germany. 2016 from a German drinking water reservoir (Rappbode Reservoir) to investi- Email: [email protected] gate the underlying mechanisms preventing a decrease in biomass. Total phos- Funding information phorus (TP) concentrations in the Rappbode Reservoir dropped abruptly in 1990 Deutsche Forschungsgemeinschaft, Grant/ Award Number: JA 2146/2-1, RI 2040/2-1 from 0.163 to 0.027 mg/L within three consecutive years, as a result of banning phosphate-containing detergents. Despite substantial reductions in TP, total annual phytoplankton biomass did not decline in the long-run, and therefore, the yield of total phytoplankton biomass per unit phosphorus largely increased. 3. Regression analysis revealed a positive association between the yield and poten- tially phagotrophic (R2 = .465, p < .001). We infer that by ingesting bacteria, mixotrophic species were capable of exploiting additional P sources that are not accessible to obligate autotrophic phytoplankton, eventually preventing a decrease in algal biomass after TP reductions. 4. Long-term epilimnetic phosphorus concentrations during the winter mixing per- iod decreased to a greater degree than summer phosphorus concentrations. Apparently, TP losses over the season were less intense. Spring biomass also markedly decreased after oligotrophication. In fact, spring diatom biomass was positively related to the TP loss over the season suggesting play an important role in P reduction. However, this intraannual P processing was not the primary factor when focusing on the average yearly yield, which remained to be fully explained by mixotrophs. 5. Our study demonstrates this ecosystem’s ability to compensate for changes in resource availability through changes in phytoplankton community composition and functional strategies. We conclude that an increase in mixotrophy and the ability to make bacterial phosphorus available for phytoplankters were the main

| Freshwater Biology. 2018;63:1063–1076. wileyonlinelibrary.com/journal/fwb © 2018 John Wiley & Sons Ltd 1063 1064 | WENTZKY ET AL.

factors that allowed the phytoplankton community of the Rappbode Reservoir to adapt to lower nutrient levels without a loss in total biomass.

KEYWORDS community composition, long-term monitoring, mixotrophy, oligotrophication, sedimentation

1 | INTRODUCTION a phosphorus concentration of 50 lg/L is associated with chloro- phyll content in a confidence interval from 7.5 to 60 lg Chl/L. Based The growth and production of phytoplankton in lakes and reservoirs on these statistical findings, we argue that there is a considerable is known to be limited by inorganic nutrients, most importantly plasticity of algal abundance at a given nutrient content. Accordingly, phosphorus (P), causing eutrophication when overly supplied (Correll, ecological properties and trophic interactions of the plankton com- 1998; Schindler, 2012). Therefore, the implicit assumption of many munity can be expected to shape the algal biomass yield per unit of scientific and regulatory frameworks is that aquatic phosphorus. This was already demonstrated by Mazumder and impacted by eutrophication can be reverted to its original condition Havens (1998) who showed chlorophyll–TP relationships to be by a reduction in phosphorus concentration, which hereafter we dependent on the presence or absence of large herbivores. Microbial refer to as “oligotrophication,” although an oligotrophic status is not food-web architectures are another influential component affecting achieved at the end of our observations. A decrease in nutrients nutrient and carbon fluxes in pelagic environments (Mitra et al., towards a lower trophic state can be generally called oligotrophica- 2014). tion (Jeppesen et al., 2005). In fact, the majority of case studies While a weak (or no) responsiveness of phytoplankton biomass about oligotrophication show a decline in phytoplankton biomass to decreasing nutrient concentrations has been observed in several after phosphorus reductions, supporting the assumption that the tra- lakes, the underlying mechanisms are often not known. In fact, lim- jectory of an ecosystem is reversible (Cooke, Welch, Peterson, & nologists are puzzled by the phenomenon that some lake ecosystems Nichols, 2016; Edmondson, 1994; Jeppesen, Jensen, & Søndergaard, are highly resilient against changes in nutrient conditions, while 2002; Jeppesen et al., 2005; Schindler, 2012). However, there are others react promptly (Carpenter & Cottingham, 1997; Jeppesen also a substantial number of exceptions where a reduction in nutri- et al., 2005). However, understanding the driving factors for the dis- ents was not followed by a drop in biomass. A review by Jeppesen connection between nutrient reductions and phytoplankton biomass et al. (2005) revealed that 25% of the studied lakes did not show is of great importance for setting reliable restoration targets in water the expected response. Phytoplankton biomass showed no response management in such systems. This study investigates the mecha- to reduced nutrient loadings in four of the study lakes (Damhussøen, nisms that could prevent a drop in biomass after P reductions. Denmark; Bryrup, Denmark; Maggiore, Italy; V€attern, Sweden), while We use an exceptionally long data set ranging from 1961 until an increase in biomass was even observed in three lakes (Vortsj~ €arv, today from Germany’s largest drinking water reservoir, the Rappbode Estonia; Peipsi, Estonia; Tystrup, Denmark). In addition, an increase Reservoir. This deep reservoir is located in a mountain range in for- in algal biomass after oligotrophication was evident in Lake Geneva, mer East Germany. The data were collected by the local water sup- Switzerland (Anneville & Pelletier, 2000; Tadonleke, Lazzarotto, ply works and have never been used for scientific purposes. It has Anneville, & Druart, 2009), in Sweden’s largest lake, Lake Vanern€ been documented that phosphorus concentrations in the Rappbode (Weyhenmeyer & Broberg, 2014) and in Germany’s Saidenbach Reservoir decreased strongly within a few years after the reunifica- Reservoir (Horn, Paul, Horn, Uhlmann, & Roske,€ 2015). These find- tion of East and West Germany in 1990, mainly due to the reduced ings are in conflict with the assumption that biomass forms a linear use of phosphate-containing detergents (Germanus, Krings, & Stelter, relationship with phosphorus, and that is, the yield of biomass per 1995; Skibba & Matthes, 2005; Umweltbundesamt, 1994). Contrary unit phosphorus should be constant (representing the slope of this to expectations, phytoplankton biomass did not significantly decline relationship) and independent of the absolute nutrient concentra- in the long-run and the yield of phosphorus per unit phytoplankton tions (Vollenweider, 1971). biomass even increased after oligotrophication. Since the nutrient The relationship between phosphorus concentration, for example reduction took place in a rather sudden shift, that is the time scale as given by the total phosphorus concentration during spring over- of this change was very short, this data set offers an excellent turn, and summer chlorophyll concentration has been intensively opportunity to study the resistance, adaptability and regulatory studied (Canfield & Bachmann, 1981; Dillon & Rigler, 1974; Jones & mechanisms of ecosystems. Long-term case histories of lake recov- Bachmann, 1976). Several authors showed linear relationships on a ery are very important, because they provide the only reliable evi- double-log scale with relatively high coefficients of determination dence about the response to reduced nutrient concentrations (around 0.9). Back-transformed to the original scale, however, a sub- (Schindler, 2012). Here we explore the long-term trends in the main stantial variation of chlorophyll content is notable at a given nutrient nutrients, water temperature, light conditions and phytoplankton bio- concentration. In the work of Dillon and Rigler (1974), for example, mass in the Rappbode Reservoir. Moreover, we analyse which WENTZKY ET AL. | 1065 mechanisms could have prevented the decrease in biomass after million people. It is located in central northern Germany in the small phosphorus reductions and enabled the increase in phytoplankton mid-mountain reach of the Mountains, at a crest elevation of yield after 1990. 423.6 m a.s.l. (Figure 1). The annual precipitation in the mainly In this study, we first present the long-term trends observed in forested Harz region is higher than in the surrounding areas and at the monitoring data for the Rappbode Reservoir. We found a strong some places exceeds 1,000 mm/year (Rinke et al., 2013). The Rapp- decline in phosphorus concentrations in 1990. While total annual Reservoir was constructed between 1952 and 1959 and has phytoplankton biomass did not decrease in response to this nutrient the tallest dam wall (106 m) in Germany. It is fed by three pre-dams reduction, phytoplankton community composition did change. Based (Konigsh€ utte€ Reservoir, pre-reservoir and Rappbode pre- on these findings, we examine the following observations and reservoir) (Tittel, Muller,€ Schultze, Musolff, & Knoller,€ 2015), which explore possible reasons leading to the unexpected response of algal were constructed for the purpose of sediment and nutrient trapping. biomass to phosphorus concentrations: The water of the Rappbode Reservoir discharges into the Wende- furth Reservoir, where it is used for energy production and energy 1. More mixotrophs: The phytoplankton community changed storage by a pump storage station (Friese et al., 2014). The Rapp- towards phagotrophic mixotrophs, which have a competitive bode Reservoir is elongated in shape with a length of 8 km, a maxi- advantage under low nutrient conditions, since they can use bac- mum surface area of 3.95 km2, an inflow volume of 120 9 106 m3/ teria as an alternative energy and nutrient source (Isaksson, a and a residence time of 344 days. The mean depth is 28.6 m, and Bergstrom,€ Blomqvist, & Jansson, 1999; Nygaard & Tobiesen, the maximum depth is 89 m. As a dimictic waterbody, it stratifies in 1993). By exploiting additional P sources, they make nutrient summer, in some years freezes in winter and completely mixes in sources available which are otherwise not accessible to phyto- spring and autumn. The water level fluctuates during the year by plankton. Therefore, the overall yield of phytoplankton biomass about 15 m (Bocaniov, Ullmann, Rinke, Lamb, & Boehrer, 2014). per unit phosphorus can increase (Bird & Kalff, 1987; Mitra et al., After its construction, it took until 1964 to completely fill the reser- 2014). voir to its full storage capacity. 2. More motile species: The phytoplankton community changed towards species that are motile and can thus optimise light and 2.2 | Sampling and sample analysis nutrient limitation. Using flagella or the ability to adjust the posi- tion in the water column (buoyancy), motile species can migrate The data presented here cover the period from 1961 to 2016 and to the hypolimnion to overcome nutrient limitation or to the sur- were collected and analysed by the local water supply works face to overcome light limitation (J€ager, Diehl, & Schmidt, 2008; Wasserwerk Wienrode (today belonging to the company Fern- Klausmeier & Litchman, 2001). By transporting nutrients from the wasserversorgung Elbaue-Ostharz GmbH) for the purpose of drink- nutrient-rich hypolimnion to the epilimnion, they increase the ing water quality control. Over the whole investigation period, yield in the epilimnion. measurements were conducted at the deepest point of the basin 3. Less nutrient losses in spring due to declining diatom biomass: close to the dam wall (N51.73891° E10.89147°, Figure 1). Data Lower nutrient concentrations during mixing lead to reduced dia- were collected approximately six times a year from 1961 to 2016, tom blooms in spring. Diatoms suffer from higher sinking veloci- usually between March and October in monthly intervals, at up to ties compared to other taxa and are therefore very efficient in 11 different depths (0, 5, 10, 15, 20, 30, 40, 50, 60, 70, 80 m), removing nutrients from the photic zone (Reynolds, 2006; Som- depending on the water level. Samples were collected at the desired mer, 1984). Hence, when diatom biomass decreases, less nutri- depth with an open cylinder sampler (2-L standard water sampler ents are removed from the epilimnion by sedimenting algal cells, according to Ruttner from Hydro-Bios GmbH). In addition to this and consequently, more nutrients stay available for the summer base sampling programme, from 1980 to 2016 samples were taken period (Benndorf, 1968; Frassl, Rothhaupt, & Rinke, 2014; Horn once a week in the upper water column as a mixed sample from 0 et al., 2015). A more even distribution of resources over the to 10 m, except for phytoplankton, of which the time series ends in entire growing season results in biomass also being more evenly 2008. Samples were taken using a pipe, which was lowered to a distributed. This affects the seasonal variability of phytoplankton depth of 10 m and then closed at the bottom, in order to get a rep- biomass. Increasing biomass in summer compensates in part for resentative integral sample of the upper water column. The total decreasing biomass in spring, and consequently, the overall number of sampling dates was 1,538 for plankton and 1,942 for annual phytoplankton biomass does not drop after P reductions. water chemistry data. In addition to these sampling dates, the sur- face water temperature was monitored on a daily basis since 1980 at a sampling point close to the shore. Water transparency was mea- 2 | METHODS sured with a Secchi disc from 1972 onwards. Air temperature mea- surements were conducted by the German weather service (DWD) 2.1 | Study site at the station Harzgerode. The Rappbode Reservoir is Germany’s largest drinking water reser- The following variables were used for data analysis: total phos- voir (in terms of volume) and supplies drinking water for over one phorus (TP), soluble reactive phosphorus (SRP), dissolved inorganic 1066 | WENTZKY ET AL.

FIGURE 1 Map of Germany with its federal states (top left). The red point indicates the location of the Rappbode Reservoir within Germany. Bathymetric map of the Rappbode Reservoir (right). The red point indicates the sampling site (N51.73891° E10.89147°). Geologic data are taken from GeoBasis-DE/LVermGeo LSA (2016) nitrogen (DIN), silica (Si), light availability (Secchi depth), water tem- in the method used before 2000. However, for the data analysis in perature, phytoplankton biomass, and community composition. this study, algae smaller than 3 lm were not relevant. The cell num- Nutrients (total phosphorus, soluble reactive phosphorus, silica, ber of filamentous and colonial algae was estimated by measuring ammonia, nitrate, and nitrite) were analysed by accredited methods the dimensions of one filament or colony and dividing by an average according to German standards (see Legler, 1988). DIN was calcu- number of cells per unit. The specific cell volumes of each taxonomic lated as the sum of ammonia, nitrate, and nitrite concentrations. unit (mostly at species level) were derived from average cell dimen- Water temperature at different depth was measured with a ther- sion measurements and simple geometric approximations (Hillebrand, mometer inside the sampler before 2009 and with a multiparameter Durselen,€ Kirschtel, Pollingher, & Zohary, 1999). Using the specific probe from 2009 onwards (both methods were compared and gave cell volumes, cell numbers could be converted to phytoplankton bio- similar results). Daily surface temperature was measured using a volume or wet-weight biomass, respectively, assuming a specific manual thermometer. density of 1.0. Algae samples were preserved with Lugol’s solution for micro- scopic cell counting. For concentrating the plankton sample, the sed- 2.3 | Data preparation and statistical analysis imentation technique developed by Utermohl€ (1958) was used from 2002 onwards. Before 2002, a first phytoplankton subsample was For data analysis, data collected at depths of 0, 5 and 10 m were either directly counted (if >1,000 cells/ml) or concentrated by sedi- combined to average epilimnion values (depth-weighted) in order to mentation and subsequent decantation (from 10 ml to 5 ml). A sec- allow comparison with the mixed water samples taken from 0 to ond subsample for the quantification of larger microplankton 10 m. Since the measurements of the depth-integrated and depth- organisms was concentrated using gauze with a mesh opening of resolved data-series fit well together, merging them appeared rea- 55 lm (Breitig, 1982; Von Tumpling€ & Friedrich, 1999). From 1961 sonable. Values exceeding four times the interquartile range were to 2000, taxonomic composition and species abundance were deter- considered as extreme outliers (e.g. typing error) and were removed mined under a conventional microscope using Kolkwitz counting from the TP and DIN data. The extreme outliers accounted for less chambers. At least four chambers (two chambers from the first sub- than 0.5% of the data. Data were aggregated to either annual sample and two chambers from the second subsample) were means, spring means, summer means or mean values during the mix- counted with a minimum of 15 fields of view each. After 2000, phy- ing period. Annual means were calculated using data from March toplankton was counted under an inverted light microscope, using until October, because this period is the growing season for phyto- the common plankton sedimentation and counting chambers (Hydro- plankton and because the winter period was not always (in 19 of Bios GmbH) according to Utermohl€ (1958). In 1998, a methodologi- 56 years) sampled. Including the winter months (when present) in cal study including several other laboratories revealed that results the annual mean would have lowered the phytoplankton biomass by from the method used before 2000 were comparable to the results 13% on average. Spring was defined as the period from March until obtained by the Utermohl€ method, except for the smallest algae. May, summer from July until October and the mixing period from Algae in the size range between 1 and 3 lm were underrepresented January until April (spring mixing typically finished in the end of WENTZKY ET AL. | 1067

April). The onset of stratification was calculated from daily tempera- not depend on any assumptions regarding the distribution between ture data and was defined as the day when the surface water tem- dependent and independent variables. The test gives a rank correla- perature exceeds 7°C and the waterbody remains stratified. In the tion coefficient (Kendall’s s, ranging from À1 to 1), which is expected Rappbode Reservoir, the hypolimnion temperature remains close to to be approximately 0 when there is no change over time. Moreover, 4°C, while surface water temperature rises steeply from the onset of the time series of TP during spring mixing was statistically analysed stratification onwards. In addition, we visually assessed the tempera- for significant shifts using the breakpoints method from the package ture development over the season for each year, to ensure that the strucchange (Zeileis, Kleiber, Kr€amer, & Hornik, 2003; Zeileis, Leisch, calculation was not affected by outliers (e.g. see Figure S2). The day Hornik, & Kleiber, 2001). Number and timing of significant shifts of stratification onset could be calculated only from 1980 onwards, were identified using the Bayesian Information Criteria (BIC). The since no daily surface temperature data were available prior to that. structural change was tested by the method sctest from the same To assess the relative importance of phosphorus and nitrogen as lim- package, using a linear model approach based on F-statistics as out- iting nutrients, the N:P ratio was used. As an indicator for discrimi- lined in Zeileis et al. (2001). To identify single factors and processes nating between N and P limitation, we used the DIN:TP ratio, which controlling phytoplankton biomass, linear regression analysis was car- has been identified as the best predictor for phytoplankton nutrient ried out. For analysing the combined effect of different processes in limitation (Bergstrom,€ 2010; Dolman, Mischke, & Wiedner, 2016; controlling phytoplankton biomass, the relevant factors (mixotrophs, Ptacnik, Andersen, & Tamminen, 2010). Above a ratio of 3.4, phyto- diatoms in spring and air temperature as a climate signal) were used plankton usually shifts from nitrogen to phosphorus limitation. DIN: as explanatory variables in a multiple regression model with the yield TP mass ratios were evaluated for all sampling dates to allow the of phytoplankton biomass per unit phosphorus as a response vari- detection of short-term nutrient limitation. The yield of phytoplank- able. Competing models were compared in a standard model selec- ton biomass per unit phosphorus was calculated by dividing annual tion procedure by selecting the most informative model based on phytoplankton biomass by TPmix. the Bayesian information criterion (BIC). The lower the BIC value, For assessing changes in community composition, species were the better the model. All data analysis and graphics were performed grouped into chlorophytes, chrysophytes, cryptophytes, cyanobacte- using the R statistics program version 3.3.2 (R Core Team, 2016) ria, dinoflagellates and diatoms. Moreover, we classified algal species with a significance level of a = 0.05. according to the functional trait mixotrophy. We define mixotrophy as the ability to perform phototrophy and phagotrophy within a sin- 3 | RESULTS gle cell, but we did not consider osmotrophy, that is the uptake of dissolved organics, here. The biomass of mixotrophs was calculated 3.1 | Long-term trends as the sum of all species considered potentially mixotrophic. We only included species that have been proven to be able to ingest A significant increase was detected for air temperatures (Figure 2a) bacteria in laboratory experiments. Species of the following genera as well as for surface water temperatures (see Figure S1b) in the were characterised as mixotrophs: Cryptomonas, Dinobryon, Gymno- Rappbode Reservoir, especially in summer, pointing to significant cli- dinium, Peridinium, Pseudopedinella and Uroglena (Gerea et al., 2016; matic warming over the past decades (Kendall’s s test, Table 1). As a Sanders, 1991; Tranvik, Porter, & Sieburth, 1989). Even though food direct consequence of this warming, the statistical analysis further- vacuoles and feeding have been reported in Ceratium hirundinella, more revealed an earlier onset of stratification (day 141 in 1980 to this species was not categorised as a phagotroph, since existing day 96 in 2016, Figure S1f). In contrast to summer surface water reports are questionable (Stoecker, 1999). Moreover, we classified temperatures, the hypolimnion temperatures in summer (measured algal species according to their motility. We characterised species as at a depth of 50 m) showed a slightly decreasing trend (Table 1, Fig- motile that are able to actively adjust their position in the water col- ure S1e). This suggests an increase in stratification stability in sum- umn. Therefore, species that either possess flagella or can regulate mer. The light conditions in the surface layer, as indicated by the their buoyancy were included in the biomass of motile organisms. Secchi depth, showed decreasing water clarity from 1972 until 1985 For time series analysis, generalised additive models (GAM) were and stayed at a rather constant level thereafter (see Figure S1a). fitted to the data using the method gam from the R-package mgcv The results of Kendall’s s test revealed a strongly decreasing (Wood, 2017). GAMs are a common tool used for analysing environ- trend in total phosphorus concentrations during the spring mixing mental and plankton time series, allowing nonlinear relationships by period (Table 1, Figure 2b). The development of TPmix over time was fitting smoothing functions (Jochimsen, Kummerlin,€ & Straile, 2013; characterised by a significant shift between 1991 and 1992 (break- Thackeray, Jones, & Maberly, 2008). The smooth terms fitted to the point analysis: BIC = À159.2163, sctest: p < .001), no other shifts data as well as their confidence intervals are visualised in Figure 2. were detected before or after this major change. Until 1991, TPmix For further statistical testing, only data after 1970 were included in remained at a high concentration with an average concentration of the analysis to ensure that a stable phytoplankton community had 0.163 mg/L. From 1992 onwards, TPmix dropped to an average con- established after the reservoir was filled to full capacity. The signifi- centration of 0.027 mg/L and remained at this lower level until the cance of long-term trends in the studied variables was investigated end of the observation period. The maximum observed TPmix value using Kendall’s s test. As a nonparametric test, Kendall’s s test does was found in 1973 (0.305 mg/L) and the minimum value in 2011 1068 | WENTZKY ET AL.

FIGURE 2 Long-term development of air temperature, mineral nutrients and phytoplankton at the Rappbode Reservoir. The solid, coloured lines are the smoothers from the generalised additive models fitted to the data, and the shades are the confidence intervals of these fits. (a)

Mean air temperatures. (b) Mean concentrations of total phosphorus during mixing (TPmix). The horizontal lines show the average value of the two periods identified by breakpoint analysis. (c) Mean concentrations of dissolved inorganic nitrogen during mixing (DINmix). (d) DIN:TP ratio of all surface samples. The red line indicates a ratio of 3.4, above which no nitrogen limitation is expected (Bergstrom,€ 2010). (e) Difference in total phosphorus concentrations between the mixing and the summer period. (f) Annual mean phytoplankton biomass. (g) Difference in phytoplankton biomass between spring and summer period. (h) Yield of phytoplankton biomass per unit phosphorus. (i) Diatom biomass in spring. (j) Annual mean biomass of motile species (red) and potentially mixotrophic species (blue)

(0.004 mg/L). Similar to TPmix, SRPmix values decreased strongly after above the critical value of 0.109 mg/L (Reynolds, 2006). In conclu- 1990 (Figure S1k). Total dissolved inorganic nitrogen concentrations sion, we focused on phosphorus as the primary limiting nutrient for during mixing slowly increased until 1988 and showed a moderately phytoplankton growth. Similar to TPmix and SRPmix, the TP and SRP decreasing trend thereafter (Figure 2c). The DIN:TP mass ratio was concentrations during summer (TPsummer, SRPsummer) also strongly above the critical DIN:TP ratio of 3.4 for all sampling dates (Fig- decreased since 1990, but to a lesser extent, as indicated by a s ure 2d), suggesting phosphorus as the main limiting nutrient in the value closer to zero (Table 1). Hence, the difference between TPmix

Rappbode Reservoir. Also, silicate was usually not limiting the and TPsummer (SRPmix and SRPsummer, respectively) decreased over growth of diatoms, as in 99.8% of the sampling dates silicate was time, indicating a higher availability of phosphorus in summer relative WENTZKY ET AL. | 1069

TABLE 1 Means (ÆSD) of the variables over the period 1971–2016, results of the Kendall’s s statistics for detection of long-term trends (Kendall’s s) and probability of the Kendall’s test (p-value). Results of generalised additive models (GAM) from 1961 to 2016, giving the deviance explained (Dev. exp.) in per cent, the estimated degrees of freedom (edf) and statistical significance judged by F tests (p-value)

Kendall’s s GAM

Variables Overall mean (SD) Kendall’s s p-value Dev. exp. edf p-value Air temperature (°C) 11.9 (0.7) 0.436 <.001 33.4 2.05 <.001 Surface water temperature (°C) 12.4 (1.9) 0.382 <.001 29.8 2.55 <.001

Surface water temperaturespring (°C) 7.0 (1.4) 0.292 .004 26.3 2.57 <.001

Surface water temperaturesummer (°C) 16.59 (1.5) 0.581 <.001 62.7 2.63 <.001

Hypolimnion water temperaturesummer (°C) 5.5 (0.7) À0.264 .010 13.7 2.00 <.001 Stratification onset (days) 119.7 (11.03) À0.564 <.001 57.3 1 <.001 Secchi depth (m) 3.690 (0.596) À0.266 .010 48 6.33 <.001

TPmix (mg/L) 0.090 (0.076) À0.626 <.001 83.4 7.50 <.001

SRPmix (mg/L) 0.013 (0.010) À0.591 <.001 74.1 7.43 <.001 Dissolved inorganic nitrogen (mg/L) 6.476 (0.976) À0.417 <.001 56.1 7.57 <.001

TPsummer (mg/L) 0.065 (0.053) À0.565 <.001 84.3 7.08 <.001

SRPsummer (mg/L) 0.006 (0.005) À0.540 <.001 54.0 3.78 <.001

TPmix À TPsummer (mg/L) 0.024 (0.037) À0.393 <.001 44.1 7.12 <.001

SRPmix À SRPsummer (mg/L) 0.007 (0.007) À0.477 <.001 53.1 4.22 <.001 Phytoplankton biomass (mg/L) 1.164 (0.643) À0.109 .291 55.9 7.90 <.001

Phytoplankton biomassspring (mg/L) 1.869 (1.50) À0.270 .008 35 4.44 <.001

Phytoplankton biomasssummer (mg/L) 0.757 (0.537) 0.228 .027 47.7 7.95 <.001

Phytoplanktonspring À Phytoplanktonsummer (mg/L) 1.092 (1.647) À0.388 <.001 25.5 3.66 <.001 Max. phytoplankton biomass (mg/L) 5.470 (4.667) À0.230 .023 30.1 2.67 .001

Yield (Biomass: TPmix) 39.08 (67.26) 0.462 <.001 59.0 6.98 <.001

Yield excluding mixotrophs (Biomassexcluding mixotrophs:TPmix) 30.59 (47.78) 0.406 <.001 50.3 5.01 <.001

Diatomsspring (mg/L) 1.648 (1.426) À0.386 <.001 38.2 4.15 <.001 Mixotrophic species (mg/L) 0.135 (0.210) 0.602 <.001 81.6 8.20 <.001 Motile species (mg/L) 0.294 (0.320) 0.347 <.001 61.5 8.49 <.001 Motile species excluding mixotrophs (mg/L) 0.159 (0.187) 0.059 .572 2.14 1 <.001

to spring after oligotrophication (Figure 2e, Figure S1l). Similar to annual phytoplankton biomass, the yield of biomass per phosphorus surface phosphorus concentrations, TP and SRP concentrations in dramatically increased after 1990, both when excluding and including the hypolimnion in summer also strongly decreased after 1990 (Fig- mixotrophs in the calculation of total biomass (Figure 2h, Table 1). ure S1m,n). Moreover, the hypolimnion never went anoxic in sum- Diatoms during spring markedly decreased after oligotrophication mer during the investigation period (Figure S1o). Both variables from 1995 to 2005. In the past decade, however, spring diatoms suggest that internal loading of phosphorus from the sediment was steadily increased in biomass (Figure 2i). This changing trend was not significant in the Rappbode Reservoir. associated with species replacements within the diatom community Despite the substantial reductions in phosphorus, total annual (Table S1). While Tabellaria fenestrata and Urosolenia longiseta, which phytoplankton biomass did not decrease in the long term and even are rather tolerant towards nutrient deficiency (Reynolds, Huszar, increased during the last decade (Figure 2f, Table 1). Algal biomass Kruk, Naselli-Flores, & Melo, 2002), became more dominant during showed no significant relationship with TPmix (Table 2). While bio- the last two decades, Asterionella formosa and Stephanodiscus mass during spring slightly decreased, biomass in summer signifi- hantzschii, which are diatoms typical for eutrophic lakes, got less cantly increased (Table 1, see Figure S1g). Hence, also the difference important. Mixotrophs and motile organisms significantly increased between spring and summer algal biomass exhibited a significant after nutrient reductions (Figure 2j, for information on species com- decline over time (Figure 2g, Table 1). While phytoplankton biomass position see Table S1). However, when mixotrophs were excluded was more equally distributed over the entire growing season after from the biomass of motile organisms, no detectable long-term trend 2000, the maximum algal biomass slightly decreased (Figure S1p). As for motile species remained (Table 1, see Figure S1i). a consequence of strongly reducing TP and not changing total were never a dominant algae group in the Rappbode Reservoir (they 1070 | WENTZKY ET AL. usually accounted for <10% of the total phytoplankton biomass), by the lower diatom abundances during these years. It is interesting even during the period with high nutrient concentrations. to note that the difference between spring and summer phytoplank-

ton biomass was also associated with differences between TPmix and TP (R2 = .288, p < .001, Table 2) and likewise with diatoms in 3.2 | Potential mechanisms preventing a decrease summer spring (R2 = .846, p < .001, Table 2). According to these findings, we in total biomass conclude that lowered TP losses in spring due to sedimenting diatom cells resulted in higher TP availability in summer, promoting more 3.2.1 | Observations 1 and 2: More mixotrophic intense phytoplankton growth during the summer period. Increasing and motile species algal biomass in summer compensated for decreasing biomass in Regression analysis revealed a significant negative relationship spring, and consequently, the overall annual phytoplankton biomass between phosphorus concentrations and the biomass of mixotrophs did not drop after P reductions (Table 1). (Table 2). In line with our observation, the ratio of total phytoplank- ton biomass to total phosphorus (yield) was positively related to the 3.2.3 | Analysis of combined effects biomass of potentially mixotrophic species (R2 = .465, p < .001, Table 2). In contrast, there is no evidence for any influence of mobil- Regression analysis revealed a significant positive effect of the bio- ity on the yield, since the influence of mobility disappeared when mass of potentially mixotrophic species on the ratio of total phyto- mixotrophic species were excluded from this group (Table 2). We plankton biomass to total phosphorus (yield) (Table 2). In a multiple also found no evidence that motile, non-mixotrophic species linear regression model, we tested whether the addition of diatom increased over time, indicating that mixotrophy, and not motility, is biomass in spring and air temperature as a climate signal would con- the relevant trait here (compare Table 1). tribute to explaining the variation in yield (Table 3). This turned out not to be the case, and they were not significantly related to the yield. Using the difference between TP and TP or the 3.2.2 | Observation 3: Less nutrient losses in spring mix summer difference between the spring and summer biovolume instead of dia- due to declining diatom biomass tomsspring as a factor in the model did not give significant results Reduced phosphorus concentrations during mixing were associated either. Therefore, as indicated by BIC, the variability in yield was 2 with lower diatom biomass in spring (R = .306, p < .001, Table 2). As best explained by mixotrophs alone. Diatomsspring and air tempera- mentioned above, the difference between TPmix and TPsummer ture added no further information to the model. decreased after oligotrophication (Figure 2e). Obviously, less nutrients could be removed from the epilimnion by phosphorus sedimentation 4 | DISCUSSION in spring, and hence, more nutrients remained available for the sum- mer period. Differences between TP and TP were positively mix summer 4.1 | Response of phytoplankton biomass to related to diatom biomass in spring (R2 = .354, p < .001, Table 2). phosphorus reductions Hence, cellular P uptake by diatoms mediates not only the transfer of dissolved P into particulate P but also facilitates a subsequent, fast P The hitherto unstudied long-term data set on phytoplankton dynam- sedimentation. The more efficient P recycling over the season in years ics in the Rappbode Reservoir adds a valuable case study to the with lower phosphorus concentrations might therefore be explained research on the responsiveness of algal communities to nutrient

TABLE 2 Results of linear regressions, testing the predictions of observations. Reported are the equation of the linear models (Estimate Æ SE), the proportion of the variability in the dependent variable explained by the independent variable (R2) as well as a significance statement, including the degrees of freedom (df) and the significance level (p-value)

Dependent variable Explanatory variable Estimate (ÆSE) df R2 p-value

Phytoplankton biomass TPmix 2.008 (1.318) 41 .054 .135

Mixotrophs TPmix À1.228 (0.370) 41 .212 .002 Yield Mixotrophs 225.920 (37.873) 41 .465 <.001 Yield Motile species 102.448 (28.088) 41 .245 <.001 Yield Motile species excluding mixotrophs 40.93 (54.24) 41 .014 .455

Diatomsspring TPmix 9.987 (2.348) 41 .306 <.001

TPmix À TPsummer Diatomsspring 0.016 (0.003) 41 .354 <.001

Phytoplanktonspring À Phytoplanktonsummer TPmix À TPsummer 22.844 (5.674) 40 .288 <.001

Phytoplanktonspring À Phytoplanktonsummer Diatomsspring À0.627 (0.149) 43 .846 <.001 WENTZKY ET AL. | 1071

TABLE 3 Results of multiple linear regressions, testing the combined effect of different processes on the ratio of total phytoplankton biomass to total phosphorus (yield). Reported are the equation of the models (Estimate ÆSE), the proportion of the variability in the dependent variable explained by the independent variable (R2) as well as a significance statement, including the degrees of freedom (df) and the significance level (p-value). Different models are compared using the Bayesian information criterion (BIC)

Dependent variable Explanatory variables Estimate (ÆSE) Single p-values Overall p-value Overall df Overall R2 Overall BIC Yield Mixotrophs 201.916 (42.104) <.001 <.001 39 .492 472.7

Diatomsspring 4.384 (5.840) .457 Air temperature 16.601 (11.935) .172 Yield Mixotrophs 203.25 (41.84) <.001 <.001 40 .4844 469.5 Air temperature 14.16 (11.42) .222 Yield Mixotrophs 225.920 (37.873) <.001 <.001 41 .465 467.4

reductions because of its unusual response. The Rappbode Reservoir concentrations moreover decreased in the hypolimnion after 1990, underwent a strong and abrupt shift in phosphorus concentrations indicating that internal loading did not play a significant role. from approximately 0.163 mg/L to 0.027 mg/L after 1990, as a result of banning phosphate-containing detergents after the reunifi- 4.2 | Mixotrophs increase yield cation of East and West Germany. The construction of a wastewater treatment plant in 2000 led to even slightly lower phosphorus con- In line with our observation, we found that the higher yield of bio- centrations during the last two decades, sometimes with TP concen- mass per phosphorus after oligotrophication could be partly trations below 0.01 mg/L during mixing. These P concentrations explained by an increase in potentially mixotrophic species. Mixo- seem sufficient to reduce phytoplankton biomass. Substantial decli- trophs make use of nutrient resources that would not be accessible nes in chlorophyll were observed in several lakes with intermediately otherwise, by ingesting bacteria as an additional P source. Predation high P concentrations (Jeppesen et al., 2002; Kohler,€ Behrendt, & of bacteria by phytoplankton seems to be a powerful strategy for Hoeg, 2000). Also in Lake Constance (Germany), a response of phy- gaining nutrients under P-depleted conditions, since bacteria are toplankton biomass was found at TP concentrations below 0.04 mg/ very phosphorus rich particles (Nygaard & Tobiesen, 1993; Vadstein, L (Jochimsen et al., 2013). The TP concentrations in the Rappbode Olsen, Reinertsen, & Jensen, 1993). Besides their ability to use bac- Reservoir fell below this threshold already from 1991 onwards. teria as a supplementary resource, mixotrophs also have the compet- However, in the Rappbode Reservoir the phytoplankton biomass itive advantage of possessing flagella. By actively moving along the does not follow the expected patterns after nutrient concentrations opposing vertical gradient of nutrient and light availability, motile were reduced. Despite reductions in P by a factor of 5 within species can adjust their position to a depth with optimised growth 3 years, total annual biomass did not decline in the long-run and conditions and can select the appropriate environment in the water even increased during the last decade. Annual mean biomass was column (J€ager et al., 2008; Klausmeier & Litchman, 2001). Hence, unrelated to phosphorus concentrations during mixing. This is in they are able to increase the yield by transporting nutrients from the contrast to classical eutrophication models and loading concepts hypolimnion to the surface. However, since the biomass of other, (Vollenweider, 1971) and to most previous studies of oligotrophica- non-mixotrophic motile species did not change over time we infer tion in lakes, which found a decline in phytoplankton biomass usually that the trait of mobility was less important than phagotrophy in within 10 years after P reductions (Jeppesen et al., 2005). Our study providing additional P sources for phytoplankton under nutrient- sought to reveal the mechanisms preventing such a reduction in depleted conditions. phytoplankton biomass in response to declining phosphorus. Our results match well with other studies showing the relation Limnologists differentiate between external and internal P load- between trophic state and the importance of mixotrophic species in ing and numerous studies documented that a reduction in external the phytoplankton community. The competitive advantage of phago- phosphorus load is ineffective on algal standing stocks when internal trophic species when dissolved nutrients are low has been shown in loading is intense (e.g. Cymbola, Ogdahl, & Steinman, 2008; Sønder- experimental studies (Isaksson et al., 1999; Katechakis & Stibor, gaard, Jensen, & Jeppesen, 1999). Internal loading is usually associ- 2006; Palsson, 2004) as well as in studies comparing aquatic systems ated with critically low redox potentials at the sediment–water of differing trophic status (Saad, Unrein, Tribelli, Lopez, & Izaguirre, interface, for example during anoxia in summer. This can be excluded 2016; Stoecker, Hansen, Caron, & Mitra, 2017). In accordance with as a possible explanation in case of the Rappbode Reservoir since the data from the Rappbode Reservoir, an increase in potentially the hypolimnion never went anoxic during summer. Moreover, our mixotrophic species (mainly cryptophytes, dinophytes and chryso- data refer to P concentrations. Any internal loading from the sedi- phytes) was also observed in other lakes after oligotrophication, ment would have become immediately detectable in hypolimnetic P including those where no decrease in total biomass was found after concentrations. In the Rappbode Reservoir, summer phosphorus nutrient reductions (Anneville, Gammeter, & Straile, 2005; Anneville, 1072 | WENTZKY ET AL.

Ginot, & Angeli, 2002; Findlay, Kasian, Stainton, Beaty, & Lyng, for its own photosynthesis and did not stimulate other phytoplank- 2001; Gaedke, 1998; Jeppesen et al., 2002, 2005; Kamjunke, Hen- ton species. richs, & Gaedke, 2006; Weyhenmeyer & Broberg, 2014). While these studies clearly show the relation between trophic state and impor- 4.3 | Less nutrient losses in spring due to declining tance of the mixotrophic strategy, the mechanism by which mixo- diatom biomass trophs increase with oligotrophication remains partly unclear: Due to their ability to prey on bacteria, mixotrophs are relieved from direct In agreement with our observation, we identified a positive relation- competition for inorganic phosphorus with obligate phototrophs. ship between diatom abundance and removal rates of phosphorus However, the reason why they do not build up high abundances in during summer. During the oligotrophication phase in the Rappbode eutrophic waters remains open and to be tested experimentally. Reservoir, we observed a decrease in diatom biomass in spring, Even though our results show that mixotrophs significantly probably caused by lower TP concentrations during spring turnover explain the observed increased yield after oligotrophication, they are and to some extent also an earlier onset of stratification (possible not the only explanation for the missing response of biomass to effects of climate change are discussed below). Diatoms have high nutrient reductions. When calculating the yield while excluding mixo- sinking velocities due to their siliceous frustules (Reynolds, 2006; trophic species from the total biomass, the yield showed an increas- Sommer, 1984; Trimbee & Harris, 1984) but are relatively slowly re- ing trend too, indicating that obligate autotrophic species also mineralised (Elster, 1963; Krause, 1964). As a result of both traits, contributed to the increase in yield. Possibly the presence of mixo- diatom cells sink out of the photic zone before they can be re- trophs stimulated the growth of other species by making nutrients mineralised and therefore lead to high nutrient losses by sedimenta- available to the autrotrophs. One possible mechanism could be their tion. Empirical evidence for the effect of sinking algae on phospho- low sinking velocity, keeping P in the photic zone for a longer time rus concentrations is, for example, also given by Benndorf (1968) (Findlay et al., 2001; Ptacnik, Diehl, & Berger, 2003; Reynolds, and Horn et al. (2015). Due to the decreasing dominance of diatoms 2006). Moreover, it has been shown that mixotrophs can either during oligotrophication, the P removal by sedimentation in the retain or release phosphorus (Rothhaupt, 1996). By releasing nutri- Rappbode Reservoir has most probably diminished. ents into the environment, they could facilitate the growth of pho- In a modelling study, Frassl et al. (2014) demonstrated that the totrophs. Some evidence for a positive effect of mixotrophs on the uptake of phosphorus by sedimenting algae has an effect on phos- standing stock of non-mixotrophic algae is provided by the increas- phate depletion in Lake Constance. They showed that the depletion ing phytoplankton biomass in the Rappbode Reservoir in the past of phosphate in the surface layer was highest during the season decade. The continuous increase in total phytoplankton biomass when phytoplankton species with high phosphorus storage capacities since 2005 (about 2 mg/L in magnitude) is not entirely realised by and settling velocities, mainly belonging to the group of diatoms, the mixotrophic community. In fact, about half of the biomass dominated. In line with their modelling results, the reduced diatom increase can be directly assigned to increasing biomass of mixo- biomass in spring in the Rappbode Reservoir may explain the lower trophs and the other half is attributable to changing non-mixotrophic removal of nutrients from the productive zone by sedimentation pro- algal groups, for example diatoms that increased in spring biomass cesses, and hence, more P resources stayed available for the summer (Figure 2i). This increase in non-mixotrophs that goes parallel to period. As a result, higher phytoplankton biomass was realised in increasing biomass may be taken as an indication for summer during the oligotrophic phase compensating for biomass nutrient recycling by mixotrophs. In this respect, the access of mixo- losses in spring. As a consequence, phytoplankton biomass was more trophs on bacterial phosphorus has enhanced the P-flux towards equally distributed over the season. This documents the importance mixotrophs and the non-mixotrophs can partly profit from this phos- of interactions between phytoplankton traits, phytoplankton commu- phorus by nutrient recycling by the mixotrophs. In addition, increas- nity dynamics and biogeochemical processing. ing protozoan biomass in the past years could also have contributed The reduction in seasonal variability of biomass in nutrient-poor to P recycling towards obligate autotrophs (see below). However, waters is in line with general observations from lakes of different whether phototrophs benefit from P recycling by mixotrophs is con- trophic status (Smith, 1990) as well as with the classical model of troversial in the literature. In experiments, Sanders, Caron, Davidson, seasonal succession of plankton in fresh waters, the PEG (Plankton Dennett, and Moran (2001) observed that phosphate and ammonia Group) model. The PEG model expects that under olig- were rapidly released by the mixotrophic flagellate Ochromonas otrophic conditions, that is when resources for a pronounced spring grown on bacteria in the light and in the dark. They concluded that bloom formation are lacking, the resources are more evenly available Ochromonas was unable to store or utilise N and P in excess of the over the season, leading to a more even distribution of biomass over quantities required for heterotrophic growth. Also, Grover (2000) the year (Sommer, Gliwicz, Lampert, & Duncan, 1986). saw some evidence for an increase in phototrophs in response to Moreover, the PEG model predicts more successive stages in recycling of bacteria nutrients because in four of five cultures the eutrophic lakes compared to oligotrophic ones, since nutrient limita- net growth rate of the phototroph was higher in the presence than tion in eutrophic lakes occurs at shorter intervals in the season in the absence of Ochromonas. In contrast to this, Rothhaupt (1997) resulting in a higher heterogeneity of nutrient conditions and thus found that under nutrient-limited situations, Ochromonas retained P ecological niches (Sommer et al., 1986). A changing seasonal WENTZKY ET AL. | 1073 development of phytoplankton species has also been observed in phytoplankton taxonomic composition and seasonal dynamics in dif- Lake Geneva and the Saidenbach Reservoir (Anneville et al., 2002; ferent ways (Winder & Sommer, 2012). Climate change can directly Horn et al., 2015). A feature they have in common with the Rapp- affect phytoplankton via physiology or indirectly by altering the bode Reservoir is that phytoplankton biomass resisted nutrient physical structure of the waterbody (Winder & Sommer, 2012). As reductions and even increased after nutrient concentrations an indicator of climate change, an increase in air temperature was dropped. While this study demonstrated that the seasonal develop- observed during the last decades at the Rappbode Reservoir. In ment of biomass has changed during oligotrophication, future studies agreement with observations from other lakes and reservoirs, we should investigate the change in seasonal dynamics of algal func- found an earlier onset of thermal stratification and higher surface tional traits (Weithoff & Gaedke, 2016) as well as potential self-sta- water temperatures, probably resulting in an increased stability of bilising mechanisms (Jochimsen et al., 2013) in more detail. stratification (Adrian et al., 2009; Jones & Brett, 2014). Besides the Although we clearly identified associations between diatom bio- effects on the physical structure, climate warming has a strong effect mass in spring, P recycling over the season and a changed seasonal on the duration of the stratified season, during which the phyto- development of biomass, it is important to note that these observa- plankton biomass is generally higher than during the non-stratified tions were not significantly related to the yield (Table 3). This sug- period (Sommer et al., 1986). In the case of the Rappbode Reservoir, gests that, in contrast to the effect of mixotrophs, the effect of P the growing season—defined as the time between stratification sedimentation by diatoms was not the major mechanism preventing onset and winter mixing—is about 2 months longer nowadays than a decrease in total annual phytoplankton biomass over the course of in the 1970s. Therefore, a prolongation of the growing seasons nec- oligotrophication. essarily leads to higher annually averaged phytoplankton biomass. By altering the position of algae cells in the water column relative to light and nutrients, vertical mixing has been shown to strongly 4.4 | The role of zooplankton affect the performance of phytoplankton species (Winder & Sommer, So far, we focused our analysis of the mechanisms preventing a phy- 2012). In the Rappbode Reservoir, the earlier onset of stratification toplankton biomass decline on bottom-up effects. However, top- might have negatively or positively affected diatom biomass in spring, down effects by higher trophic levels on the structure and produc- resulting in reduced P sedimentation losses in spring (see paragraph tivity of aquatic ecosystems must also be taken into consideration above). Diatoms are well adapted to low light conditions and cold (Kerimoglu, Straile, & Peeters, 2013; Mazumder & Havens, 1998; temperatures and accordingly may profit when the growing season Urabe, Nakanishi, & Kawabata, 1995). In the Rappbode Reservoir, starts earlier in the year. On the other hand, diatoms have high sinking total zooplankton biomass and the most important grazer groups velocities and therefore depend on turbulence to remain suspended in (Daphnia and other crustaceans) varied largely from year to year, but the photic zone (Huisman et al., 2004; J€ager et al., 2008; Ptacnik showed no significant trend over time (Wentzky, unpublished data). et al., 2003). Intensified stratification strengths and earlier onset of Since zooplankton biomass and hence grazing did not decrease since stratification are associated with reduced mixing intensity. As a conse- 1990, it appears unlikely that they prevented the decrease in phyto- quence, diatoms have a competitive disadvantage and can be outcom- plankton biomass after P reductions or contributed to the increase peted by algae better adapted to stratified waterbodies. The diatom in algal biomass during the last decade. However, a significant dynamics in Rappbode Reservoir in fact showed strong reductions increase in protozoan biomass was detected since 2003 (Kendall’s and similarly strong increases in the times after nutrient reduction s = 0.463, p < .001). Protozoa efficiently graze on bacteria and have took place (see Figure 2i). These dynamics are associated with species been shown to strongly increase the remineralisation of mineral replacements in the diatom community (see above), and it remains to nutrients, particularly phosphorus, which is then available for phyto- be analysed which physiological traits are associated with these com- plankton growth (Bloem, Albert, B€ar-Gillissen, Berman, & Cappen- munity changes and in which respect these trait dynamics may explain berg, 1989; Hambright, Zohary, & Gude,€ 2007). Increased excretion the observed dynamics in diatom biomass. of nutrients by protozoa possibly contributed to the lower difference between TP and TP after 1990, in addition to reduced P mix summer 4.6 | Combined effects and conclusions losses from the productive zone due to sedimentation of diatoms. Thus, higher protozoan biomass in the Rappbode Reservoir might An increase in potentially mixotrophic species capable of exploiting have enhanced summer phytoplankton production through a more additional P sources was speculated to be the main mechanism efficient P recycling. The start of the protozoan biomass increase, explaining why overall phytoplankton biomass did not drop after P however, does not fit to the start of phytoplankton biomass increase reductions. Furthermore, we found that reduced P losses by diatoms making a major influence of protozoans rather unlikely. sedimenting out of the photic zone led to higher biomass in summer compared to spring biomass. Climate change, manifested as increased air and surface water temperature, an earlier onset of ther- 4.5 | Effects of climate change mal stratification and stronger stratification stability might have sup- Climate change has the potential to contribute to the resilience of ported these processes via effects on community composition. phytoplankton biomass. It can alter primary productivity, However, the combined analysis of the mentioned mechanisms on 1074 | WENTZKY ET AL. the yield of phytoplankton biomass per unit of phosphorus revealed Benndorf, J. (1968). Untersuchungen uber€ die Remineralisierung des that only mixotrophs significantly affected the yield. This suggests Phosphors in der Freiwasserregion der Saidenbachtalsperre. Interna- tionale Revue der Gesamten Hydrobiologie und Hydrographie, 53, 635– that losses in total biomass were primarily prevented by changes in 650. https://doi.org/10.1002/(ISSN)1522-2632 the microbial food web including the mixotrophs and their ability to Bergstrom,€ A.-K. (2010). The use of TN:TP and DIN:TP ratios as indica- make bacterial phosphorus available for photosynthetic organisms tors for phytoplankton nutrient limitation in oligotrophic lakes (Rothhaupt, 1992; Vadstein et al., 1993). Changes in seasonal bio- affected by N deposition. Aquatic Sciences, 72, 277–281. https://doi. org/10.1007/s00027-010-0132-0 geochemical cycling of nutrients within the pelagic zone as well as Bird, D. F., & Kalff, J. (1987). Algal phagotrophy: Regulating factors and climate change are evident, but play a minor part in preventing importance relative to photosynthesis in Dinobryon (Chrysophyceae). losses in total biomass. In conclusion, the results show that the phy- Limnology and Oceanography, 32, 277–284. https://doi.org/10.4319/ toplankton community in the Rappbode Reservoir was able to adapt lo.1987.32.2.0277 Bloem, J., Albert, C., B€ar-Gillissen, M.-J. B., Berman, T., & Cappenberg, T. to lower nutrient levels without a loss in total biomass. This study E. (1989). Nutrient cycling through phytoplankton, bacteria and pro- ’ demonstrates the ecosystem s ability to compensate for changes in tozoa, in selectively filtered Lake Vechten water. Journal of Plankton resource availability through changes in internal processes and func- Research, 11, 119–131. https://doi.org/10.1093/plankt/11.1.119 tional strategies. Bocaniov, S. A., Ullmann, C., Rinke, K., Lamb, K. G., & Boehrer, B. (2014). Internal waves and mixing in a stratified reservoir: Insights from three-dimensional modeling. Limnologica – Ecology and Management ACKNOWLEDGMENTS of Inland Waters, 49,52–67. https://doi.org/10.1016/j.limno.2014.08. 004 We thank the water supply works Wasserwerk Wienrode and Breitig, G. (1982). Ausgewahlte€ Methoden der Wasseruntersuchung: Biolo- Talsperren Betrieb Sachsen-Anhalt for sharing their monitoring data gische, mikrobiologische und toxikologische Methoden/[von e. € with us. Special thanks go to Jan Donner and Wolf-Dieter Skibba Autorenkollektiv unter d. Red. von G. Breitig u. W. von Tumpling], Fis- cher. (Wasserwerk Wienrode) for providing us with information about the Canfield, D. E. Jr, & Bachmann, R. W. (1981). Prediction of total phos- analytical and biological methods used during the 50 years of moni- phorus concentrations, chlorophyll a, and Secchi depths in natural toring. Thanks to Detlef Coster€ (Talsperren Betrieb Sachsen-Anhalt) and artificial lakes. Canadian Journal of Fisheries and Aquatic Sciences, – for providing daily water temperature data. We also thank Sabrina 38, 414 423. https://doi.org/10.1139/f81-058 Carpenter, S. R., & Cottingham, K. L. (1997). Resilience and restoration of Eichler, Eva Meyer, Yuhan Xie and Thomas Plumbohm for digitalising lakes. Conservation Ecology, 1, 2. http://www.consecol.org/vol1/iss1/ the monitoring data and Marieke Frassl, Karoline Morling, Katja art2/ Westphal, Bertram Boehrer and Martin Schultze (Helmholtz Centre Cooke, G. D., Welch, E. B., Peterson, S., & Nichols, S. A. (2016). Restora- for Environmental Research) for constructive discussions. Thanks to tion and management of lakes and reservoirs. Boca Raton, FL: CRC Press. Philipp Keller (Helmholtz Centre for Environmental Research) for Correll, D. L. (1998). The role of phosphorus in the eutrophication of preparing the bathymetric map. This research was supported by receiving waters: A review. Journal of Environmental Quality, 27, 261– grants JA 2146/2-1 and RI 2040/2-1 from the German Research 266. https://doi.org/10.2134/jeq1998.00472425002700020004x Foundation (DFG) within the priority program 1704 “DynaTrait.” Cymbola, J., Ogdahl, M., & Steinman, A. D. (2008). Phytoplankton response to light and internal phosphorus loading from sediment release. Freshwater Biology, 53, 2530–2542. https://doi.org/10.1111/ j.1365-2427.2008.02079.x ORCID Dillon, P., & Rigler, F. (1974). The phosphorus-chlorophyll relationship in lakes. Limnology and Oceanography, 19, 767–773. https://doi.org/10. Valerie Carolin Wentzky http://orcid.org/0000-0002-8774-1287 4319/lo.1974.19.5.0767 Dolman, A. M., Mischke, U., & Wiedner, C. (2016). Lake-type-specific seasonal patterns of nutrient limitation in German lakes, with target REFERENCES nitrogen and phosphorus concentrations for good ecological status. Freshwater Biology, 61, 444–456. https://doi.org/10.1111/fwb.12718 Adrian, R., O’Reilly, C. M., Zagarese, H., Baines, S. B., Hessen, D. O., Kel- Edmondson, W. (1994). Sixty years of Lake Washington: A curriculum ler, W., ... Van Donk, E. (2009). Lakes as sentinels of climate change. vitae. Lake and Reservoir Management, 10,75–84. https://doi.org/10. Limnology and Oceanography, 54, 2283. https://doi.org/10.4319/lo. 1080/07438149409354178 2009.54.6_part_2.2283 Elster, H. (1963). Die Stoffwechseldynamik der Binnengew€asser. Verhand- Anneville, O., Gammeter, S., & Straile, D. (2005). Phosphorus decrease lungen der Deutschen Zoologischen Gesellschaft, 27, 335–387. and climate variability: Mediators of synchrony in phytoplankton Findlay, D., Kasian, S., Stainton, M., Beaty, K., & Lyng, M. (2001). Climatic changes among European peri-alpine lakes. Freshwater Biology, 50, influences on algal populations of boreal forest lakes in the Experi- 1731–1746. https://doi.org/10.1111/j.1365-2427.2005.01429.x mental Lakes Area. Limnology and Oceanography, 46, 1784–1793. Anneville, O., Ginot, V., & Angeli, N. (2002). Restoration of Lake Geneva: https://doi.org/10.4319/lo.2001.46.7.1784 Expected versus observed responses of phytoplankton to decreases Frassl, M. A., Rothhaupt, K.-O., & Rinke, K. (2014). Algal internal nutrient in phosphorus. Lakes & Reservoirs: Research & Management, 7,67–80. stores feedback on vertical phosphorus distribution in large lakes. https://doi.org/10.1046/j.1440-169X.2002.00179.x Journal of Great Lakes Research, 40, 162–172. https://doi.org/10. Anneville, O., & Pelletier, J. P. (2000). Recovery of Lake Geneva from 1016/j.jglr.2013.11.001 eutrophication: Quantitative response of phytoplankton. Archiv fur€ Friese, K., Schultze, M., Boehrer, B., Buttner,€ O., Herzsprung, P., Koschor- Hydrobiologie, 148, 607–624. https://doi.org/10.1127/archiv-hydrob reck, M., ... Rinke, K. (2014). Ecological response of two hydro-mor- iol/148/2000/607 phological similar pre-dams to contrasting land-use in the Rappbode WENTZKY ET AL. | 1075

reservoir system (Germany). International Review of Hydrobiology, 99, re-oligotrophication. Journal of Plankton Research, 29,39–46. 335–349. https://doi.org/10.1002/iroh.201301672 https://doi.org/10.1093/plankt/fbl054 Gaedke, U. (1998). Functional and taxonomical properties of the phyto- Katechakis, A., & Stibor, H. (2006). The mixotroph Ochromonas tubercu- plankton community: Interannual variability and response to re-oligo- lata may invade and suppress specialist phago- and phototroph trophication. Archiv fur€ Hydrobiologie, Special Issues: Advances in plankton communities depending on nutrient conditions. Oecologia, Limnology, 53, 119–141. 148, 692–701. https://doi.org/10.1007/s00442-006-0413-4 Geobasis-De/Lvermgeo Lsa (2016). https://www.lvermgeo.sachsen-anhalt. Kerimoglu, O., Straile, D., & Peeters, F. (2013). Seasonal, inter-annual and de/de/download/Geotopographie/main.htm long term variation in top-down versus bottom-up regulation of pri- Gerea, M., Saad, J. F., Izaguirre, I., Queimalinos,~ C., Gasol, J. M., & Unrein, F. mary production. Oikos, 122, 223–234. https://doi.org/10.1111/j. (2016). Presence, abundance and bacterivory of the mixotrophic algae 1600-0706.2012.20603.x Pseudopedinella (Dictyochophyceae) in freshwater environments. Aqua- Klausmeier, C. A., & Litchman, E. (2001). Algal games: The vertical distri- tic Microbial Ecology, 76, 219–232. https://doi.org/10.3354/ame01780 bution of phytoplankton in poorly mixed water columns. Limnology Germanus, J., Krings, P., & Stelter, N. (1995). Untersuchungsergebnisse and Oceanography, 46, 1998–2007. https://doi.org/10.4319/lo.2001. zu waschmittelrelevanten Inhaltsstoffen in ostdeutschen 46.8.1998 Fließgew€assern. CLEAN – Soil, Air, Water, 23, 289–297. Kohler,€ J., Behrendt, H., & Hoeg, S. (2000). Long-term response of Grover, J. P. (2000). Resource competition and community structure in phytoplankton to reduced nutrient load in the flushed Lake aquatic micro-organisms: Experimental studies of algae and bacteria Muggelsee€ (Spree system, Germany). Archiv fur€ Hydrobiologie – along a gradient of organic carbon to inorganic phosphorus supply. Hauptbande€ , 148, 209–229. https://doi.org/10.1127/archiv-hydrob Journal of Plankton Research, 22, 1591–1610. https://doi.org/10. iol/148/2000/209 1093/plankt/22.8.1591 Krause, H. (1964). Zur Chemie und Biochemie der Zersetzung von Suss-€ Hambright, K. D., Zohary, T., & Gude,€ H. (2007). Microzooplankton domi- wasserorganismen, unter besonderer Berucksichtigung€ des Abbaues nate carbon flow and nutrient cycling in a warm subtropical freshwa- der organischen Phosphorkomponenten. Verhandlungen Internationale ter lake. Limnology and Oceanography, 52, 1018–1025. https://doi. Vereinigung fur€ Theoretische und Angewandte Limnologie, 15, 549–561. org/10.4319/lo.2007.52.3.1018 Legler, C. (1988). Ausgewahlte€ Methoden der Wasseruntersuchung: Chemis- Hillebrand, H., Durselen,€ C. D., Kirschtel, D., Pollingher, U., & Zohary, T. che, physikalisch-chemische und physikalische Methoden/wiss. Red.: Ch. (1999). Biovolume calculation for pelagic and benthic microalgae. Legler. Unter Mitarb. von G. Breitig, Fischer. Journal of Phycology, 35, 403–424. https://doi.org/10.1046/j.1529- Mazumder, A., & Havens, K. E. (1998). Nutrient-chlorophyll-Secchi rela- 8817.1999.3520403.x tionships under contrasting grazer communities of temperate versus Horn, H., Paul, L., Horn, W., Uhlmann, D., & Roske,€ I. (2015). Climate subtropical lakes. Canadian Journal of Fisheries and Aquatic Sciences, change impeded the re-oligotrophication of the Saidenbach Reser- 55, 1652–1662. https://doi.org/10.1139/f98-050 voir. International Review of Hydrobiology, 100,43–60. https://doi. Mitra, A., Flynn, K. J., Burkholder, J. M., Berge, T., Calbet, A., Raven, J. A., org/10.1002/iroh.201401743 ... Zubkov, M. V. (2014). The role of mixotrophic protists in the bio- Huisman, J., Sharples, J., Stroom, J. M., Visser, P. M., Kardinaal, W. E. A., logical carbon pump. Biogeosciences, 11, 995–1005. https://doi.org/ Verspagen, J. M., & Sommeijer, B. (2004). Changes in turbulent mix- 10.5194/bg-11-995-2014 ing shift competition for light between phytoplankton species. Ecol- Nygaard, K., & Tobiesen, A. (1993). Bacterivory in algae: A survival strat- ogy, 85, 2960–2970. https://doi.org/10.1890/03-0763 egy during nutrient limitation. Limnology and Oceanography, 38, 273– Isaksson, A., Bergstrom,€ A.-K., Blomqvist, P., & Jansson, M. (1999). Bacte- 279. https://doi.org/10.4319/lo.1993.38.2.0273 rial grazing by phagotrophic phytoflagellates in a deep humic lake in Palsson, C. (2004). Nutrient limitation of autotrophic and mixotrophic northern Sweden. Journal of Plankton Research, 21, 247–268. phytoplankton in a temperate and tropical humic lake gradient. Jour- https://doi.org/10.1093/plankt/21.2.247 nal of Plankton Research, 26, 1005–1014. https://doi.org/10.1093/pla J€ager, C. G., Diehl, S., & Schmidt, G. M. (2008). Influence of water-col- nkt/fbh089 umn depth and mixing on phytoplankton biomass, community com- Ptacnik, R., Andersen, T., & Tamminen, T. (2010). Performance of the position, and nutrients. Limnology and Oceanography, 53, 2361–2373. Redfield ratio and a family of nutrient limitation indicators as thresh- https://doi.org/10.4319/lo.2008.53.6.2361 olds for phytoplankton N vs. P limitation. Ecosystems, 13, 1201– Jeppesen, E., Jensen, J. P., & Søndergaard, M. (2002). Response of phyto- 1214. https://doi.org/10.1007/s10021-010-9380-z plankton, zooplankton, and fish to re-oligotrophication: An 11 year Ptacnik, R., Diehl, S., & Berger, S. (2003). Performance of sinking and study of 23 Danish lakes. Aquatic Ecosystem Health & Management, 5, nonsinking phytoplankton taxa in a gradient of mixing depths. Limnol- 31–43. https://doi.org/10.1080/14634980260199945 ogy and Oceanography, 48, 1903–1912. https://doi.org/10.4319/lo. Jeppesen, E., Sondergaard, M., Jensen, J. P., Havens, K. E., Anneville, O., 2003.48.5.1903 Carvalho, L., ... Winder, M. (2005). Lake responses to reduced nutri- R Core Team (2016). A language and environment for statistical computing. ent loading – an analysis of contemporary long-term data from 35 Vienna, Austria: R Foundation for statistical computing. case studies. Freshwater Biology, 50, 1747–1771. https://doi.org/10. Reynolds, C. S. (2006). The ecology of phytoplankton. Cambridge, 1111/j.1365-2427.2005.01415.x UK: Cambridge University Press. https://doi.org/10.1017/ Jochimsen, M. C., Kummerlin,€ R., & Straile, D. (2013). Compensatory CBO9780511542145 dynamics and the stability of phytoplankton biomass during four dec- Reynolds, C. S., Huszar, V., Kruk, C., Naselli-Flores, L., & Melo, S. (2002). ades of eutrophication and oligotrophication. Ecology Letters, 16,81– Towards a functional classification of the freshwater phytoplankton. 89. https://doi.org/10.1111/ele.12018 Journal of Plankton Research, 24, 417–428. https://doi.org/10. Jones, J. R., & Bachmann, R. W. (1976). Prediction of phosphorus and 1093/plankt/24.5.417 chlorophyll levels in lakes. Water Pollution Control Federation, 48, Rinke, K., Kuehn, B., Bocaniov, S., Wendt-Potthoff, K., Buttner,€ O., Tittel, 2176–2182. J., ... Friese, K. (2013). Reservoirs as sentinels of catchments: The Jones, J., & Brett, M. T. (2014). Lake nutrients, eutrophication, and cli- Rappbode Reservoir Observatory (Harz Mountains, Germany). Envi- mate change. In B. Freedman (Ed.), Global environmental change (pp. ronmental Earth Sciences, 69, 523–536. https://doi.org/10.1007/ 273–279). Dordrecht, the Netherlands: Springer. s12665-013-2464-2 Kamjunke, N., Henrichs, T., & Gaedke, U. (2006). Phosphorus gain by Rothhaupt, K. (1992). Stimulation of phosphorus-limited phytoplankton bacterivory promotes the mixotrophic flagellate Dinobryon spp. during by bacterivorous flagellates in laboratory experiments. Limnology and 1076 | WENTZKY ET AL.

Oceanography, 37, 750–759. https://doi.org/10.4319/lo.1992.37.4. of diatoms and recruitment of summer bloom-forming blue-green 0750 algae. Journal of Plankton Research, 6, 897–918. https://doi.org/10. Rothhaupt, K. O. (1996). Utilization of substitutable carbon and phospho- 1093/plankt/6.5.897 rus sources by the mixotrophic chrysophyte Ochromonas sp. Ecology, Umweltbundesamt (1994). Daten zur Umwelt 1990/91. Berlin, Germany: 77, 706–715. https://doi.org/10.2307/2265495 Erich Schmidt Verlag. Rothhaupt, K. O. (1997). Nutrient turnover by freshwater bacterivorous Urabe, J., Nakanishi, M., & Kawabata, K. (1995). Contribution of meta- flagellates: Differences between a heterotrophic and a mixotrophic zoan plankton to the cycling of nitrogen and phosphorus in Lake chrysophyte. Aquatic Microbial Ecology, 12,65–70. https://doi.org/10. Biwa. Limnology and Oceanography, 40, 232–241. https://doi.org/10. 3354/ame012065 4319/lo.1995.40.2.0232 Saad, J. F., Unrein, F., Tribelli, P. M., Lopez, N., & Izaguirre, I. (2016). Utermohl,€ H. (1958). Zur vervollkommnung der quantitativen phytoplank- Influence of lake trophic conditions on the dominant mixotrophic ton methodik. Mitteilungen der Internatinalen Vereinigung fur€ Theoretis- algal assemblages. Journal of Plankton Research, 38, 818–829. che und Angewandte Limnologie, 9,1–38. https://doi.org/10.1093/plankt/fbw029 Vadstein, O., Olsen, Y., Reinertsen, H., & Jensen, A. (1993). The role of Sanders, R. W. (1991). Trophic strategies among heterotrophic flagellates. planktonic bacteria in phosphorus cycling in lakes-Sink and link. Lim- In D. J. Patterson, & J. Larsen (Eds.), The biology of free-living hetero- nology and Oceanography, 38, 1539–1544. https://doi.org/10.4319/ trophic flagellates (pp. 21–38). Oxford, UK: Clarendon Press. lo.1993.38.7.1539 Sanders, R. W., Caron, D. A., Davidson, J. M., Dennett, M. R., & Moran, Vollenweider, R. A. (1971). Scientific fundamentals of the eutrophication of D. M. (2001). Nutrient acquisition and population growth of a mixo- lakes and flowing waters, with particular reference to nitrogen and phos- trophic alga in axenic and bacterized cultures. Microbial Ecology, 42, phorus as factors in eutrophication. Paris, France: Organisation for eco- 513–523. https://doi.org/10.1007/s00248-001-1024-6 nomic co-operation and development. Schindler, D. W. (2012). The dilemma of controlling cultural eutrophica- Von Tumpling,€ W., & Friedrich, G. N. (1999). Biologische Gewasserunter-€ tion of lakes. Proceedings of the Royal Society B: Biological Sciences, suchung. Jena, Germany: Gustav Fischer Verlag. 279, 4322–4333. https://doi.org/10.1098/rspb.2012.1032 Weithoff, G., & Gaedke, U. (2016). Mean functional traits of lake phyto- Skibba, W.-D., & Matthes, M. (2005). Tiefer ist besser: Trinkwasserauf- plankton reflect seasonal and inter-annual changes in nutrients, cli- bereitung aus der Rappbodetalsperre. Gas- und Wasserfach. Wasser, mate and herbivory. Journal of Plankton Research, 39, 509–517. Abwasser, 146, 874–879. Weyhenmeyer, G. A., & Broberg, N. (2014). Increasing algal biomass in Smith, V. H. (1990). Phytoplankton responses to eutrophication in Lake V€anern despite decreasing phosphorus concentrations: A lake- inland waters. In I. Akatsuka (Ed.), Introduction to applied phycology specific phenomenon? Aquatic Ecosystem Health & Management, 17, (pp. 231–249). The Hague, the Netherlands: SPB Academic 341–348. https://doi.org/10.1080/14634988.2014.976532 Publishing. Winder, M., & Sommer, U. (2012). Phytoplankton response to a changing Sommer, U. (1984). Sedimentation of principal phytoplankton species in climate. Hydrobiologia, 698,5–16. https://doi.org/10.1007/s10750- Lake Constance. Journal of Plankton Research, 6,1–14. https://doi. 012-1149-2 org/10.1093/plankt/6.1.1 Wood, S. (2017). Package ‘mgcv’. R package version, 1.7-29. https://cran. Sommer, U., Gliwicz, Z. M., Lampert, W., & Duncan, A. (1986). The PEG- r-project.org/web/packages/mgcv/index.html model of seasonal succession of planktonic events in fresh waters. Zeileis, A., Kleiber, C., Kramer,€ W., & Hornik, K. (2003). Testing and dat- Archiv fur€ Hydrobiologie, 106, 433–471. ing of structural changes in practice. Computational Statistics & Data Søndergaard, M., Jensen, J. P., & Jeppesen, E. (1999). Internal phosphorus Analysis, 44, 109–123. https://doi.org/10.1016/S0167-9473(03) loading in shallow Danish lakes. Hydrobiologia, 408, 145–152. 00030-6 https://doi.org/10.1023/A:1017063431437 Zeileis, A., Leisch, F., Hornik, K., & Kleiber, C. (2001). strucchange. An R Stoecker, D. K. (1999). Mixotrophy among dinoflagellates. Journal of package for testing for structural change in linear regression models. Eukaryotic Microbiology, 46, 397–401. https://doi.org/10.1111/j. Journal of Statistical Software, 7,1–38. https://doi.org/10.18637/jss. 1550-7408.1999.tb04619.x v007.i02 Stoecker, D. K., Hansen, P. J., Caron, D. A., & Mitra, A. (2017). Mixotro- phy in the Marine Plankton. Annual Review of Marine Science, 9, 311– 335. https://doi.org/10.1146/annurev-marine-010816-060617 Tadonleke, R. D., Lazzarotto, J., Anneville, O., & Druart, J. C. (2009). Phy- SUPPORTING INFORMATION toplankton productivity increased in Lake Geneva despite phosphorus Additional Supporting Information may be found online in the loading reduction. Journal of Plankton Research, 31, 1179–1194. https://doi.org/10.1093/plankt/fbp063 supporting information tab for this article. Thackeray, S. J., Jones, I. D., & Maberly, S. C. (2008). Long-term change in the phenology of spring phytoplankton: Species-specific responses to nutrient enrichment and climatic change. Journal of Ecology, 96, € 523–535. https://doi.org/10.1111/j.1365-2745.2008.01355.x How to cite this article: Wentzky VC, Tittel J, Jager CG, Tittel, J., Muller,€ C., Schultze, M., Musolff, A., & Knoller,€ K. (2015). Fluvial Rinke K. Mechanisms preventing a decrease in phytoplankton radiocarbon and its temporal variability during contrasting hydrologi- biomass after phosphorus reductions in a German drinking cal conditions. Biogeochemistry, 126,57–69. https://doi.org/10.1007/ water reservoir—results from more than 50 years of s10533-015-0137-9 – Tranvik, L. J., Porter, K. G., & Sieburth, J. M. N. (1989). Occurrence of observation. Freshwater Biol. 2018;63:1063 1076. bacterivory in Cryptomonas, a common freshwater phytoplankter. https://doi.org/10.1111/fwb.13116 Oecologia, 78, 473–476. https://doi.org/10.1007/BF00378736 Trimbee, A. M., & Harris, G. (1984). Phytoplankton population dynamics of a small reservoir: Use of sedimentation traps to quantify the loss