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Summary Biogenic methane as an alternative carbon and energy source for freshwater organisms has been receiving increasing attention, but the phenomenon is still poorly understood for shallow lakes. We measured the carbon and nitrogen stable isotope signatures (δ13C, δ15N) for key groups of pelagic and benthic organisms, including crustacean zooplankton, chironomid larvae, young‐of‐the‐year and adult fish, to assess whether biogenic methane contributes to pelagic and benthic food webs in a large, shallow lake, Lake Võrtsjärv, Estonia. In the southern part of the lake, covered by macrophytes, crustacean zooplankton showed strong seasonal variation of δ13C, with the lowest values occurring in the period of oxygen depletion. Chironomid (Chironomus plumosus) larvae showed high isotopic variability within the lake, with strongly 13C‐depleted and 15N‐depleted signatures (down to δ13C −64.0‰ and δ15N −2.6‰) in the macrophyte‐covered area. Our results indicate that carbon derived from biogenic methane can contribute seasonally to the benthic food web and, to some extent, also to the pelagic food web, where the lake is covered by macrophytes. Moreover, δ13C values for roach (Rutilus rutilus), perch (Perca fluviatilis) and pike (Esox lucius) from the macrophyte‐dominated area were on average 3.5‰ lower than those for the same fish from the plankton‐dominated lake area, suggesting some carbon derived from methane is transferred up through the food web. Although no direct evidence is available, our results, together with previous studies of the lake, suggest that protozoans could be a potentially important link from methane‐oxidising bacteria to animals higher in the web.

The biologic effects of the oil shale industry on caged rainbow trout (Oncorhynchus mykiss) as well as on feral perch (Perca fluviatilis) and roach (Rutilus rutilus) were studied in the River Narva in northeast Estonia. The River Narva passes the oil shale mining and processing area and thus receives elevated amounts of polycyclic aromatic hydrocarbons (PAHs), heavy metals, and sulfates. The effects of the chemical load were monitored by measuring cytochrome P4501A (CYP1A)-dependent monooxygenase (MO) activities [7-ethoxyresorufin O-deethylase and aryl hydrocarbon hydroxylase (AHH)] as well as conjugation enzyme activities [glutathione S-transferase (GST) and UDP-glucuronosyltransferase] in the liver of fish. CYP1A induction was further studied by detecting the amount and occurrence of the CYP1A protein. Histopathology of tissues (liver, kidney, spleen, and intestine) and the percentage of micronuclei in fish erythrocytes were also determined. Selected PAHs and heavy metals (Cd, Cu, Hg, and Pb) were measured from fish muscle and liver. In spite of the significant accumulation of PAHs, there was no induction of MO activities in any studied fish species. When compared to reference samples, AHH activities were even decreased in feral fish at some of the exposed sites. Detection of CYP1A protein content and the distribution of the CYP1A enzyme by immunohistochemistry also did not show extensive CYP1A induction. Instead, GST activities were significantly increased at exposed sites. Detection of histopathology did not reveal major changes in the morphology of tissues. The micronucleus test also did not show any evidence of genotoxicity. Thus, from the parameters studied, GST activity was most affected. The lack of catalytic CYP1A induction in spite of the heavy loading of PAHs was not studied but has been attributed to the elevated content of other compounds such as heavy metals, some of which can act as inhibitors for MOs. Another possible explanation of this lack of induction is that through adaptation processes the fish could have lost some of their sensitivity to PAHs. Either complex pollution caused by oil shale processing masked part of the harmful effects measured in this study, or oil shale industry did not have any severe effects on fish in the River Narva. Our study illustrates the difficulties in estimating risk in cases where there are numerous various contaminants affecting the biota.ImagesFigure 1Figure 2

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The present study describes the use of a fish hepatoma cell line (PLHC-1) in monitoring the biological effects of sediments collected from recipient waters of the oil shale industry. Sampling sites were located in River Purtse and River Kohtla in northeast Estonia. The effects of pure oil shale on the PLHC-1 cells were also studied. The cells were exposed to n-hexane-extracted samples in 48-well plates for 24 h, and 7-ethoxyresorufin O-deethylase (EROD) activity, total protein, and porphyrin content were measured in the exposed cells. Polycyclic aromatic hydrocarbon (PAH) contents in the samples were measured by high-performance liquid chromatography (HPLC). All the sediment and oil shale samples induced CYP1A activity and led to porphyrin accumulation in the cells. The most potent inducers were the sediments collected near the oil shale processing plants (site Lüganuse in River Purtse and Kohtla in River Kohtla), as well as those at the most downstream site in River Purtse (Purtse). These samples possessed high total PAH contents, ranging from 4,270 to nearly 150,000 microg/kg dry sediment. The presence of other lipophilic organic contaminants in the samples was not determined in this study. Both EROD activity and porphyrin content exhibited biphasic induction curves, and the ED(50)(1) values for EROD activity were lower than the ED(50)s for porphyrin content. 2,3,7, 8-Tetrachlorodibenzo-p-dioxin induction equivalents (TCDD-EQs) calculated from EROD induction potencies correlated well with total PAHs (r(2) = 0.827 and p = 0.003 for log-transformed data) and also with individual PAHs. TCDD-EQs for porphyrin content did not correlate significantly with total PAHs (log-log r(2) = 0.785, p = 0. 116). The biological potency and PAH contamination of the samples showed the same rank order, except at Lüganuse, where sediment extracts induced CYP1A and porphyrins more than could have been expected based on PAH contents. Bioassay-derived induction EQs (normalized to dibenz(a,h)anthracene) were 20- to 3,200-fold greater than EQs calculated from the concentrations of five PAHs, suggesting important contributions from other compounds or nonadditive effects. The PLHC-1 cells proved to be a sensitive bioanalytical tool for sediments contaminated with PAH-type pollutants in the oil shale processing area. We suggest further use of this bioassay in screening and monitoring waters with similar background of pollution as in northeast Estonia.

Important drivers of gross primary production (GPP) and ecosystem respiration (ER) in lakes are temperature, nutrients, and light availability, which are predicted to be affected by climate change. Little is known about how these three factors jointly influence shallow lakes metabolism and metabolic status as net heterotrophic or autotrophic. We conducted a pan‐European standardized mesocosm experiment covering a temperature gradient from Sweden to Greece to test the differential temperature sensitivity of GPP and ER at two nutrient levels (mesotrophic or eutrophic) crossed with two water levels (1 m and 2 m) to simulate different light regimes. The findings from our experiment were compared with predictions made according the metabolic theory of ecology (MTE). GPP and ER were significantly higher in eutrophic mesocosms than in mesotrophic ones, and in shallow mesocosms compared to deep ones, while nutrient status and depth did not interact. The estimated temperature gains for ER of ~ 0.62 eV were comparable with those predicted by MTE. Temperature sensitivity for GPP was slightly higher than expected ~ 0.54 eV, but when corrected for daylight length, it was more consistent with predictions from MTE ~ 0.31 eV. The threshold temperature for the switch from autotrophy to heterotrophy was lower under mesotrophic (~ 11°C) than eutrophic conditions (~ 20°C). Therefore, despite a lack of significant temperature‐treatment interactions in driving metabolism, the mesocosm's nutrient level proved to be crucial for how much warming a system can tolerate before it switches from net autotrophy to net heterotrophy.