Imbalance of plankton community metabolism in ...

Journal of Great Lakes Research 37 (2011) 650–655

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Imbalance of plankton community metabolism in eutrophic Lake Taihu, China Xia Liu a, b, Qinglong Wu b, Yuwei Chen b,⁎, Martin T. Dokulil c a b c

School of Environmental Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China Institute of Limnology, Austrian Academy of Sciences, 5310 Mondsee, Austria

a r t i c l e

i n f o

Article history: Received 15 December 2010 Accepted 16 September 2011 Available online 22 October 2011 Communicated by Marley Waiser Keywords: Plankton community respiration Gross primary production Eutrophic

a b s t r a c t Studies suggest that oligotrophic lakes are net heterotrophic and act as net sources of CO2, whereas eutrophic lakes are net autotrophic and act as net CO2 sinks. Data on plankton community metabolism in Lake Taihu contradict this hypothesis. Here, the ratios of depth integrated gross primary production (GPP) to plankton community respiration (PCR) were less than one on 75% of the study sampling dates, indicating that this system was net heterotrophic. Partial pressure estimated for CO2 also indicated that the lake was a net source of CO2. Net heterotrophic conditions here may be related to limitation of phytoplankton photosynthesis by the poor underwater light climate (due to elevated suspended solids (SS) and nutrients originating in the catchment) and the preferential enhancement of respiration by high water temperatures. GPP and PCR were significantly correlated (PCR = 1.22GPP + 0.46, r 2 = 0.80) indicating a partial dependence of heterotrophs on algal derived carbon. The slope of the regression line relating PCR to GPP was more similar to slopes found in rivers than in lakes, likely due to the large nutrient and SS load to the lake. © 2011 International Association for Great Lakes Research. Published by Elsevier B.V. All rights reserved.

Introduction Recent literature regarding the metabolic balance in aquatic ecosystems has revealed that plankton community respiration (PCR) tends to dominate over gross primary production (GPP) in many rivers, estuaries, oligotrophic to mesotrophic lakes, reservoirs, and oligotrophic regions of the ocean (Caffrey, 2004; del Giorgio and Peters, 1994; Dodds and Cole, 2007; Duarte and Agustí, 1998; Smith and Hollibaugh, 1993). Half a century ago, GPP and PCR were proposed as powerful, synthetic descriptors of ecosystem functioning (Odum, 1956). Aquatic and marine ecosystems are characterized as net autotrophic when GPP is greater than PCR, and hence are net sinks for CO2, and net heterotrophic when GPP is less than PCR, and hence are net sources of CO2. However, studies to date have focused on oceans, rivers, and oligotrophic lakes (Carignan et al., 2000; Depew et al., 2006; Marie-Helene et al., 2009; Urban et al., 2005). Few studies have been conducted in eutrophic waters including those in China (Chen et al., 2005). Lakes contribute 87% of the world's surface waters and are commonly assumed to be sources rather than sinks of atmospheric CO2 (Cole et al., 1994) but this assumption may not apply to mesotrophic and eutrophic lakes. The methods used for estimating planktonic the ratio between GPP and PCR can lead to differing conclusions regarding lake trophic status (Hanson et al., 2003). For example, different analyses have

⁎ Corresponding author. Tel.: + 86 13951695436. E-mail address: [email protected] (Y. Chen).

led to dissimilar characterizations of GPP:PCR ratios in ocean waters (Williams, 1998). Ideally, depth-integrated calculations of GPP and PCR can overcome some of the bias in the data sets and give a more accurate picture of the metabolism balance of aquatic ecosystems. However, this approach has rarely been used. Lake Taihu is the third largest freshwater lake in China, with an area of 2338 km 2, a catchment area of 36,500 km 2, and an average depth of ca. 2.0 m (Chen et al., 2003a). The watershed is the most densely populated (about 1100 inhabitants km −2) and economically developed (contributing about 13% of the Gross Domestic Product) region in China (Huang et al., 2001). The lake is important for fisheries, tourism and waste-water discharge, in addition to its role as a source of drinking water. Since the 1980s, the lake has become eutrophic due to its multiple uses. Concomitant predictable increases in cyanobacteria biomass, mainly Microcystis, which can comprise more than 50% of summer phytoplankton biomass in Lake Taihu, have ensued (Chen et al., 2003a; Liu et al., 2011). Lake Taihu can serve as an example for many other shallow lakes in China and worldwide which have become heavily eutrophic or are naturally eutrophic and for which little is known about their metabolic balance. The objectives of our Lake Taihu study are to investigate (1) the relationship between GPP and PCR; (2) the relationships between lake plankton community metabolism and environmental factors such as light and temperature; and (3) the possible reasons causing the imbalance between GPP and PCR in this large, shallow, eutrophic lake. We present monthly measurements of GPP and PCR rates made in Lake Taihu from October 2002 to September 2003 and then examine the CO2 balance in its waters by comparing integral daily rates of production and respiration.

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X. Liu et al. / Journal of Great Lakes Research 37 (2011) 650–655

Methods The morphological, hydrological and biological properties of Lake Taihu, including Meiliang Bay, have been summarized by Chen et al. (2003a). Two sampling stations were selected for comparing the different trophic regions of the lake. The center station was located in the less productive open lake center and had an average depth of 2. 2 m; the bay station was located in the middle of eutrophic Meiliang Bay and had an average depth of 1.8 m (Fig. 1). Sampling was conducted monthly from October 2002 to September 2003. Physical and chemical parameters such as water temperature (WT), suspended solids (SS), dissolved oxygen concentration (DO), total phosphorus concentration (TP) and other environmental factors were analyzed following the Chinese standard methods for lake eutrophication surveys (Jin and Tu, 1990). Integrated water samples for all analytical parameters as well as for GPP and PCR measurements were taken using a 2 m-long and 10 cm-wide plastic Van Dorn bottle. Underwater photosynthetically active radiation (PAR) was measured using a LI-COR flat sensor (Li-192, Li-Cor, America). Vertical attenuation coefficients were calculated from the underwater PAR measurements (Kirk, 1983). For phytoplankton chlorophyll a concentration (Chla) analysis, water samples were filtered through Whatman GF/C glass fiber filters (nominal pore size, 1.2 μm). Chla was calculated according to Lorenzen (1967) from spectrophotometric measurements after extraction in 90% hot ethanol. The oxygen light–dark bottle method was employed to measure phytoplankton GPP and PCR rates and calculated as daily integral rates (Vollenweider, 1974). Partial data sets on GPP and PCR from 1991 to 2001 were applied to explain historical changes in GPP and PCR in the lake following methods utilized in Vollenweider (1974). Detailed calculations of GPP and PCR were as follows: (1) Paired clear bottles for measuring the photosynthesis rate were incubated in situ at depths 0.0 m, 0.2 m, 0.4 m, 0.6 m, 1.0 m and 1.5 m (0.0 m = water surface). Triplicate opaque bottles for measuring the PCR were incubated at 1.0 m depth for 4 h from 10:00–14:00. To our knowledge, there was no variation of the vertical distribution of phytoplankton biomass. (2) GPP rates (Pv, mgO2 m −3 h −1) were calculated from DO differences between clear and opaque bottles, and

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PCR rates (Rv, mgO2 m −3 h −1) were calculated from DO differences between initial and opaque bottles. No significant differences in DOC concentrations were detected between the initial and final DO readings in the opaque bottles. (3) The integral GPP rates for the entire water column (Ph, mgO2 m −2 h −1) were calculated planimetrically from the vertical profiles of Pv. The integral PCR rates for the entire water column (Rh, mgO2 m −2 h −1) were calculated by multiplying Rv by the water depth of each sampling station. (4) Areal daily integral phytoplankton GPP rates (GPP, mgO2 m −2 d −1) were then converted by extrapolating the hourly Ph based on the fraction of total daily PAR occurring during the course of the incubation. Areal daily PCR rates (PCR, mgO2 m −2 d −1) were calculated as the hourly respiration rate (Rh) multiplied by 24 h. Plankton ratios were then calculated. All statistical analyses were performed with Statistical Program for Social Sciences (SPSS—IBM, New York, NY) 11.0 software and SigmaPlot 10.0 (Systat Software, Chicago, Ill). Regression analysis was used to identify relationships between single factors and planktonic GPP and PCR (p = 0.05). Data were normalized when necessary by means of logarithmic transformation. Results Concentrations of suspended solids (SS) in Lake Taihu from 1991 to 2003 ranged between 8.4 and 649 mg l− 1. Accordingly, vertical attenuation coefficients ranged from 1.3 to 6.7 m − 1 (Fig. 4). The vertical attenuation coefficients were strongly but non-linearly correlated with SS, with 97% explained variance (Fig. 4). Water temperature (WT) ranged between 3.8 and 30.0 °C, Chla from 2.2 to 85.1 mg m − 3, and TP from 26 to 172 mg m − 3 (Fig. 5). Highest biomass occurred in summer (usually August) coinciding with cyanobacteria-Microcystis blooms. This cyanobacterial bloom was followed a month later by a diatom (Aulacoseira spp.) bloom; Cryptomonas spp. appeared either shortly before or after the Aulacoseira peak (Chen et al., 2003a). Phytoplankton GPP and PCR rates varied seasonally and spatially (Fig. 2). In the lake center, GPP:PCR ratios were usually less than 1.0, ranging from 0.25 to 0.95, except for several occasions, such as January and February when they increased up to 2.01; these higher ratios usually appeared in winter, when water temperatures were

Fig. 1. Site map of Lake Taihu, China. Cited from Chen et al., 2003a.

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Fig. 2. Monthly variations of phytoplankton gross primary production to plankton community respiration ratios in the Bay and the open lake of Taihu. Horizontal line represents the point where GPP:PCR ratio equals 1.0. Ratios above this denote net autotrophy, while those below represent net heterotrophy.

low (Fig. 2, Table 2). In eutrophic Meiliang Bay, GPP:PCR ratios were slightly above 1. GPP ranged from 0.24 to 8.81 gO2 m − 2 d − 1 with an annual mean of 2.28 gO2 m − 2 d − 1, while PCR varied from 0.35 to 12.65 gO2 m − 2 d − 1 with an annual mean of 3.39 gO2 m − 2 d − 1 (Fig. 3). GPP and PCR were highly correlated with each other (r 2 = 0.80, p b 0.0001, n = 44). The intercept of the best fit regression was 0.46 gO2 m − 2 d − 1 (Fig. 3). GPP and PCR also were positively correlated with WT (GPP and WT: p b 0.0001, n = 44; PCR and WT: p b 0.0001, n = 44), and the slope of the regression line between PCR and WT was higher than that between GPP and WT (PCR and WT: b = 1.66 ± 0.33; GPP and WT: 1.39 ± 0.36; Fig. 5A). GPP and PCR were also positively correlated with Chla, the two regression lines were more or less parallel but with different intercepts (GPP and Chla: p b 0.0001, a = 0.31, b = 0.68 ± 0.14, n = 44; PCR and Chla: p b 0.0001, a = 0.43, b = 0.69 ± 0.13, n = 44; Fig. 5B). In contrast, neither GPP nor PCR was significantly correlated with TP (Table 2, Fig. 5C). GPP:PCR ratios were significantly negatively correlated with WT (p b 0.05, n = 44). Correlations between GPP:PCR ratios and Chla as well as GPP:PCR ratios and TP were not significant (Table 2).

Fig. 3. Relationship between phytoplankton gross primary production and plankton community respiration in Lake Taihu. The solid line represents the best fit regression (together with the equation, r2 and p values) and the dashed line represents GPP = PCR.

Discussion The significant positive correlations between GPP and PCR noted in the Lake Taihu study appear to be a common feature of aquatic systems (Duarte and Agustí, 1998) and reflect the importance of autochthonous production in supplying organic matter to sustain heterotrophic activity within the ecosystem (Fig. 3) (Blight et al., 1995). From the GPP and PCR regression equation (PCR = 1.22GPP + 0.46), one can easily calculated that, on average, GPP was about 80% of PCR (Fig. 3). Phytoplankton in Lake Taihu, therefore, can produce about 80% of the organic matter required to support PCR, a figure about 10% less than the estimate of del Giorgio et al. (1999) for northern temperate lakes. The positive intercept of the regression line (Fig. 3) indicates that the baseline PCR rate in Lake Taihu was 0.46 gO2 m − 2 d− 1 (168 gO2 m− 2 y− 1), a rate four times higher than that found in the same del Giorgio et al. (1999). Although the majority of this rate in Lake Taihu is fuelled by autochthonous carbon as noted above, high nutrient loading from the heavily populated catchment area (approximately 62,254 t/a (1987–1988) and 81,700 t/a (1994–1995) of total organic carbon (TOC) entered the lake from its rivers — Huang et al., 2001) likely supplied the remaining carbon to maintain this high baseline respiration rate (Chen et al., 2003b). Interestingly, the slope of the regression line between logtransformed GPP and PCR (b= 0.83 ± 0.08 — Table 2, Fig. 6) for Lake Taihu was more similar to slopes from rivers (b= 0.85 ± 0.07) than those from lakes (b= 0.65 ± 0.04) (as cited from Duarte and Agustí, 1998). The high carbon load from rivers and elevated nutrients from waste-water discharge into Meiliang Bay also likely contribute to the excessive turbidity noted in the lake (Chen et al., 2003b). In turn,

Fig. 4. The relationship between suspended solids and vertical attenuation coefficients in Lake Taihu. The best fit regression line and the equation are shown in the figure.


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Fig. 5. Phytoplankton gross primary production and plankton community respiration as functions of water temperature (°C), chlorophyll a concentration (mg m− 3) and total phosphorus concentration (mg m− 3) in Lake Taihu. The triangle symbols refer to production and the square symbols refer to respiration. Data are log-transformed and lines of best fit are plotted (the dashed line refers to production and the solid line refers to respiration). The parameters of the regression equations appear in Table 2.

excessive turbidity may explain why the GPP and PCR regression slope is closer to that of rivers and shallow, turbid Neusiedler See (Dokulil, 1994). In some aquatic ecosystems, shifts between heterotrophy and autotrophy can take place at moderate increases or decreases in dissolved organic carbon (DOC)(Jansson et al., 2000), while in some unproductive lakes this balance may be determined by N:P ratios (Karlsson et al., 2002). In other systems (e.g. Chesapeake Bay), important linkages have been found between the size distribution of primary producers and the balance between net hetero- and autotrophy (Smith and Kemp, 2001). Research into eutrophic aquatic ecosystems indicates that net autotrophic conditions tend to predominate. Here, autotrophs are better competitors at high nutrient concentrations and also have a greater capacity for nutrient storage than their heterotrophic counterparts (Cotner and Biddanda, 2002). Studies over the past decade have also shown that many unproductive aquatic ecosystems are net heterotrophic (e.g., del Giorgio et al., 1997). Aquatic systems with high DOC concentrations and low total phosphorus concentrations tend to be net heterotrophic, while those exhibiting low DOC and high TP tend toward net autotrophy (Cole et al., 2000; Hanson et al., 2003). Recent studies have also indicated that DOC concentrations below 10 mg l− 1

favor autotrophy while heterotrophy prevails at DOC concentrations above that (Hanson et al., 2003; Prairie et al., 2002). There are systems, however, like Lake Taihu and prairie wetlands (Waiser and Robarts, 2004), which have high DOC and total phosphorus concentrations and therefore fall outside these established boundaries. In 2004 DOC concentrations in Lake Taihu ranged from 11.57 to 20.19 mg l− 1, with a value of 13.99 mg l− 1 for the middle of Meiliang Bay and 10.26 mg l− 1 for the open lake (Zhang et al., 2005). Prairie wetlands, although net autotrophic based on seasonal means of the ratio of primary production to bacterial production (PP:BP), experienced significant periods of net heterotrophy during the ice free season (Waiser and Robarts, 2004). Lake Taihu, however, is somewhat different. Close examination of the GPP:PCR data indicated that for both study sites, net heterotrophy was present on 75% of the sampling dates (Fig. 2). In this lake, contrary to what has been reported for other eutrophic ecosystems, the plankton community was net heterotrophic. There are also other clues which point to the presence of net heterotrophy in Lake Taihu. Variations in the partial pressure of CO2 (PCO2) provide one of the most sensitive indicators of biogeochemical carbon cycling in freshwater lakes (Herczeg, 1987). Studies have indicated, for example, that most oligotrophic lakes tend to be supersaturated

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Fig. 6. The relationship between gross primary production and plankton community respiration in Lake Taihu as compared to other aquatic ecosystems. The open circles are the data from this study, the shaded area indicates the data range of other lakes as summarized by Duarte and Agustí (1998). Lines of best fit are plotted (The thick solid line refers to the data from Lake Taihu, the thin solid line refers to the data from the rivers as summarized by Duarte and Agustí (1998) and the dashed line refers to the data of other lakes as summarized by Duarte and Agustí (1998). The regression equations are listed in Table 2.

with CO2 (Cole et al., 1994). Although CO2 supersaturation is usually associated with net heterotrophy it has been observed in net autotrophic systems (Lake Croche recorded during thermal stratification — Carignan et al., 2000). Interestingly, PCO2 in the surface water of eutrophic Lake Taihu was about 4 to 11 times the atmospheric value; the mean pH was 8.4 ± 0.3 in the bay and 8.4 ± 0.1 in center (Fan et al., 2003; Table 1) indicating that the lake was supersaturated and likely a net source of CO2. Other studies have indicated that such excess CO2 may originate from CO2-rich groundwaters, which can contain up to 100 times more free CO2 than lakewaters (Stumm and Morgan, 1996). This seems an unlikely explanation for Lake Taihu where groundwater inflow to the lake is assumed to discharge predominantly within the littoral zone via upward and lateral seepage from the unconfined aquifer through the lake bottom sediments. As well, groundwater flow velocity is low compared with that of inflowing rivers. A more likely explanation is that excess CO2 in the lake is reflective of the net heterotrophic conditions indicated by the GPP:PCR ratios. There are a number of factors which may contribute to the net heterotrophic conditions observed in Lake Taihu. First, previous studies have demonstrated that water temperature is an important factor affecting plankton metabolism in aquatic ecosystems (e.g., Robinson,

Table 1 Means, SDs and ranges in concentrations of Chlorophyll a, TP, Phosphate P (PO4-P), total dissolved P (TDP), nitrate plus nitrite N (NO2-N + NO3-N), ammonium N (NH4N), total dissolved N (TDN), DO, SS, water temperature (WT) and values for alkalinity and pH in Bay and Center Station. Data presented are means from October 2002 to September 2003. All concentrations are in mg l− 1, except for Chla (μg l− 1). Alkalinity is expressed as mmol l− 1 CaCO3. Bay

TP PO4-P TDP NO2-N + NO3-N NH4-N TDN DO pH Alkalinity Chla SS

Center

Mean ± SDs

Range

Mean ± SD

Range

0.27 ± 0.59 0.01 ± 0.006 0.03 ± 0.017 1.05 ± 0.61 0.56 ± 0.44 2.56 ± 1.43 9.28 ± 2.04 8.4 ± 0.3 2.04 ± 0.17 59.9 ± 146.3 39.1 ± 30.3

0.04–2.13 0–0.021 0.016–0.072 0.06–1.92 0.03–1.54 0.45–4.63 6.38–12.3 8.2–9.3 1.67–2.21 1.7–521.7 9.6–123.1

0.07 ± 0.02 0 ± 0.04 0.02 ± 0.013 0.84 ± 0.64 0.09 ± 0.07 1.65 ± 1.02 9.19 ± 1.77 8.4 ± 0.1 1.7 ± 0.07 8.9 ± 4.0 68.2 ± 44.9

0.06–0.12 0–0.012 0.01–0.057 0.06–1.76 0.02–0.25 0.3–3.29 6.86–12.5 8.2–8.7 1.58–1.8 3.8–16.1 20.2–170.1

2000). As an example, greater respiration rates in shallow Neusiedler See were associated with high GPP and water temperatures (Dokulil, 1994). The significant correlation between GPP:PCR ratios and water temperature observed in Lake Taihu suggests that, along a gradient of increasing WT, PCR increased more rapidly than GPP (Table 2, Fig. 5). Thus, the preferential enhancement of PCR over phytoplankton production by high water temperatures may be one reason why PCR exceeded GPP here. Secondly, light is a critical variable controlling phytoplankton production, especially in turbid, nutrient rich ecosystems (Cole et al., 1992). In the Hudson River, for example, high inputs of allochthonous organic matter and the associated turbidity limited algal production (Findlay et al., 1991) while in the Neusiedler See, phytoplankton photosynthesis was largely controlled by turbidity and concomitant light attenuation (Dokulil, 1984). According to data from the Lake Taihu study, the underwater light penetration was poor which likely resulted in GPP not only lower than in other eutrophic lakes but also lower than in some mesotrophic aquatic ecosystems (e.g., Berman et al., 2004). Another factor which has been shown to depress algal biomass and production is heavy zooplankton grazing (Caraco et al., 1997; Jeppesen et al., 1990). In Lake Søbygård, for example, the ratio of PP:BP decreased with increasing grazing pressure (Jeppesen et al., 1992). Although zooplankton in Lake Taihu have been studied, numbers of algal grazing crustaceans were found to be low (Ke et al., 2008). Additionally, it is known that zooplankton do not feed on colonial cyanobacteria due to colony size, potential toxicity, and/or gelatinous envelopes (Dokulil and Teubner, 2000). It seems unlikely, therefore, that the imbalance between GPP and PCR in Lake Taihu was due to zooplankton grazing especially in light of the fact that colonial cyanobacteria dominate here. According to the literature, most oligotrophic aquatic ecosystems tend to be net heterotrophic and conversely eutrophic systems net autotrophic. Based on a comparative analysis of plankton metabolism in 20 southern Québec lakes, for example, del Giorgio and Peters (1994) found that planktonic P:R ratios were positively related to Chl a and total phosphorus. Moreover, during the growing season, R tended to exceed P in all oligotrophic and mesotrophic study lakes (net heterotrophic). In our data set, PCR was highly correlated with Chl a, implying, as noted above, that phytoplankton play an important role in plankton community metabolism (Fig. 5). Neither Chl a nor TP, however, was significantly correlated with GPP:PCR ratios (Table 2). The existence of net heterotrophy in eutrophic Lake Taihu suggests that assumptions of net autotrophy in eutrophic systems do not always hold. Furthermore, our study underlines the importance of abiotic factors like turbidity and water depth and temperature in determining whether an aquatic system will be net auto- or heterotrophic. Table 2 Parameters of regression equations for the model log (y) = b log (x) + a, where y is the dependent variable, x is the independent variable, b is the slope, and a is the intercept. All variables are log-transformed. The proportion of variance explained (r2) and the p values for each equation are given, together with b ± 95% confidence intervals for the parameter estimates. The variables of Lake Taihu are as defined in the text. The data from the rivers and lakes are those summarized by DUARTE and AGUSTí (1998). x

y

r2

p

a

b

WT WT Chla Chla TP TP WT Chla TP GPP * Rivers-P * Lakes-P

GPP PCR GPP PCR GPP PCR GPP:PCR ratio GPP:PCR ratio GPP:PCR ratio PCR Rivers-R Lakes-R

0.41 0.57 0.36 0.40 0.04 0.07 0.12 0.004 0.06 0.81 0.68 0.81

b 0.0001 b 0.0001 b 0.0001 b 0.0001 N.S N.S 0.02 N.S N.S b 0.0001 b 0.01 b 0.01

0.04 0.03 0.31 0.43 0.24 0.14 1.63 0.83 2.17 1.74 1.1 1.0

1.39 ± 0.36 1.66 ± 0.33 0.68 ± 0.14 0.69 ± 0.13 0.51 ± 0.37 0.70 ± 0.36 − 0.29 ± 0.11 − 0.04 ± 0.09 − 0.25 ± 0.16 0.83 ± 0.08 0.85 ± 0.07 0.65 ± 0.04

“N.S” means no statistical significant.


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