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Elevated temperature and browning increase dietary methylmercury, but decrease essential fatty acids at the base of lake food webs


Climate change scenarios predict increases in temperature and organic matter supply from land to water, which affect trophic transfer of nutrients and contaminants in aquatic food webs. How essential nutrients, such as polyunsaturated fatty acids (PUFA), and potentially toxic contaminants, such as methylmercury (MeHg), at the base of aquatic food webs will be affected under climate change scenarios, remains unclear. The objective of this outdoor mesocosm study was to examine how increased water temperature and terrestrially-derived dissolved organic matter supply (tDOM; i.e., lake browning), and the interaction of both, will influence MeHg and PUFA in organisms at the base of food webs (i.e. seston; the most edible plankton size for zooplankton) in subalpine lake ecosystems. The interaction of higher temperature and tDOM increased the burden of MeHg in seston (< 40 μm) and larger sized plankton (microplankton; 40–200 μm), while the MeHg content per unit biomass remained stable. However, PUFA decreased in seston, but increased in microplankton, consisting mainly of filamentous algae, which are less readily bioavailable to zooplankton. We revealed elevated dietary exposure to MeHg, yet decreased supply of dietary PUFA to aquatic consumers with increasing temperature and tDOM supply. This experimental study provides evidence that the overall food quality at the base of aquatic food webs deteriorates during ongoing climate change scenarios by increasing the supply of toxic MeHg and lowering the dietary access to essential nutrients of consumers at higher trophic levels.


With climate change, warming is expected1 along with altered precipitation patterns in freshwater ecosystems2. Increase in precipitation often leads to increasing dissolved organic carbon (DOC) concentrations and water colour in boreal aquatic ecosystems3. Significant increases in the amount of terrestrially-derived dissolved organic matter (tDOM) has already occurred with a doubling of DOC during the past 25 years in some systems, often termed browning (or brownification)4,5. Warming and browning of aquatic ecosystems have important consequences for both ecosystem function and the dietary quality of aquatic resources, starting at the base of the food web. Despite there being a widely accepted recognition that increases in temperature and tDOM will be occurring, there is little knowledge on how effects of warming and/or browning will affect the dietary quality of aquatic resources, particularly from an ecotoxicological point of view. Climate change may present both changed risk levels to organisms from environmental pollutants, such as the potent neurotoxin, mercury (Hg) and its highly bioavailable form methylmercury (MeHg)6, as well as altered benefits from essential dietary compounds, such as polyunsaturated fatty acids (PUFA), which are crucial for somatic growth, development, and survival of biota7,8. Both the bioconcentration of MeHg and biosynthesis of PUFA at the base of the food web greatly impact the health and survival of organisms at higher trophic levels9,10.

So far, there have been claims of changes in MeHg bioaccumulation due to climate warming or browning. For example, experimental and empirical work have shown warming leading to increases of fish Hg11,12, as well as similar temperature effects on MeHg bioaccumulation in macroinvertebrates in experimental estuary ecosystems13,14. No evidence, however, has been presented about temperature effects on MeHg at the base of the food web in freshwaters, even though this is an essential link in Hg bioaccumulation9. The influence of increasing tDOM has been tested on zooplankton in brackish waters which resulted in increased MeHg bioaccumulation15. On the other hand, a study conducted in Arctic lakes showed that higher DOC concentrations in lakes inhibited bioaccumulation of both total Hg and MeHg in aquatic microbiota16, and there was an indication that DOC reduces fish Hg bioaccumulation17. A similar finding that high DOC levels lower MeHg bioavailability to stream macroinvertebrates and fish was observed in stream ecosystems from the Northeast United States18. As for the climate effects on the dietary quality at the base of the food web, only a few studies have been conducted. A significant loss of phytoplankton diversity and evenness was noted under warming and temperature fluctuations, leading to dominance by Cyanobacteria19. This suggests a loss of dietary quality with decreasing omega-3 PUFA resulting in nutritional deterioration for higher consumers.

The effects of browning and the simultaneous influence of increasing temperatures on MeHg and PUFA at the base of the food web have not been examined yet. Therefore, we conducted an outdoor mesocosm experiment to investigate how the MeHg content and dietary quality (as assessed by PUFA) would change in organisms at the base of the aquatic food web with increased water temperature and/or increased supply of terrestrial organic matter. We predicted that the combined effects of warming and browning would increase the MeHg content and decrease the dietary quality19. We also expected that zooplankton biomass would increase due to higher algal biomass that is caused by higher temperature and browning, with the latter also increasing the nutrient supply20,21.

We used 24 polyethylene containers (400 L each) as experimental enclosures (mesocosms) for the experiment to test the effect of four treatments. Six containers were used to mimic ambient temperature and light conditions (controls; C treatment), whereas in another treatment we increased the temperature by 3 °C above ambient22 (temperature increase; T treatment). In the browning (B) treatment we added an extracted tDOM solution on a weekly basis to create a two-fold increase in DOC concentrations, which was similar to the lower range of DOC concentrations found in Scandinavian freshwater ecosystems23. This mimics a possible future scenario of episodic/seasonal floods with increased inputs of allochthonous organic compounds to lakes24. The final treatment combined the T and B treatments (mixed conditions; TB treatment) to represent another likely future scenario of simultaneous warming and browning within a century at similar nutrient levels.

The temperature was steered by a computerized system that maintained the temperature in the heated treatment 3 °C above the controls. Each treatment was replicated six times. The nutrient levels and spiked MeHg concentrations were identical among treatments throughout the study. Phytoplankton and zooplankton were added in equal mass volume to each enclosure at the beginning of the study. Water samples were taken weekly for aqueous MeHg, DOC, and nutrient analysis from 2 July to 13 August 2018. Organisms of two different size classes were sampled: (a) seston (0.7–40 μm), which is considered the most consumed particle size range by zooplankton25,26; and (b) microplankton (40–200 μm), which contained a mix of algae and very few small-sized zooplankton. Thus, it was possible to capture the temperature and browning effects at the base of the food web, specifically the algal-animal interface27. Seston and microplankton were sampled at the end of the experiment (14 August to 16 August 2018) for analysis of biomass, as well as MeHg and FA contents. We normalized for ambient (control) conditions, calculated a Cohen’s d effect size for each treatment, and used a completely randomized and fully replicated factorial analysis of variance (ANOVA) to assess the expected direction and level of change in seston and microplankton biomass, MeHg content (both measured concentration and calculated biomass burden) and PUFA.

Results and discussion

The additions of extracted tDOM solution gradually darkened mesocosm water in the browning (B) and mixed treatments (TB) as determined by colour (absorbance at 420 nm, A420). This mainly resulted from an increase in more aromatic DOM compounds (indicated by specific UV absorbance at 254 nm, SUVA254) (Fig. 1). The increase in DOC concentrations (filtered through 0.2 μm) was less than the increase in water colour (Fig. 1), indicating that tDOM additions increased the proportion of organic matter molecules in the mesocosm water with high aromaticity28.

Figure 1
figure 1

Temporal dynamics in water column aromaticity. Top to bottom: Specific UV absorbances at 254 nm (SUVA254), water colour indicated by absorbance at 420 nm (A420), and dissolved organic carbon (DOC) concentrations filtered through 0.2 µm. All marked with means ± 1 s.d.

Methylmercury in the ambient lake water was below detection limit. The initial MeHg spike raised the aqueous (< 0.2 μm) MeHg concentration. Additional MeHg spikes were made each week, but the mesocosm MeHg still decreased slowly across all treatments during the experiment (Fig. S4 and S5). This could result from uptake of dissolved MeHg by seston, and/ or photodegradation of aqueous MeHg (Gilmour et al. 1998). Towards the end of the experiment, the aqueous MeHg concentrations were highest in the mixed treatment mesocosms compared to other treatments (p < 0.05) (Table 1).

Table 1 Summary of analysed methylmercury and fatty acids from  sampling at the end of the mesocosm experiment. Contents (means ± 1 s.d.) of methylmercury (MeHg), lipids and polyunsaturated fatty acids (PUFA) in aqueous (< 0.2 μm), seston (0.7–40 μm), microplankton (40–200 μm), and zooplankton (> 55 μm) as well as plankton biomass at the end of the mesocosm experiment. “n” = number of replicates of each treatment. Fatty acids are determined as fatty acid methyl esters (FAME).

Our future scenario for organisms at the base of food webs in aquatic ecosystems, with temperature elevated by 3 °C and an increase of the tDOM, revealed major effects on MeHg burden, total lipids, and PUFA contents for both size fractions at the base of the food web. This suggests that both potential food risk and dietary quality were strongly influenced by increased temperature and browning (Fig. 2). The influence of increased temperature on seston MeHg burden was more pronounced compared to microplankton, contrasting with the influence of browning that was significant on seston and microplankton PUFA contents, but not seston MeHg burden. This indicated that the uptake of MeHg differs from the retention of essential dietary compounds when plankton is exposed to warming or browning scenarios. Under combined warming and browning treatments, increased biomass with constant or increasing aqueous MeHg concentrations resulted in an increased MeHg burden for organisms of both size fractions, and thus an increase in the amount of MeHg available for uptake at the base of food web.

Figure 2
figure 2

Cohen’s d effect sizes for response variables based on results from sampling at the end of the mesocosm experiment. Response variables: seston and microplankton biomass, MeHg content and bioconcentration factors, as well as fatty acids. Mean effect sizes (± higher/lower confidence intervals; ± CI) of 0.7–40 μm seston were analysed at the end of the experiment for biomass, MeHg concentrations, MeHg burden (MeHg in seston biomass per unit volume) and BCF (log transformed ratio of MeHg in seston versus aqueous MeHg; < 0.2 μm), total lipids, omega-3 (n-3) and omega-6 (n-6) PUFA concentrations, as well as ratios of MeHg:n-3 PUFA, and n-3:n-6 in seston (left panel). Effect sizes of the same response variables for 40–200 μm microplankton sampled and analysed at the end of the experiment are shown in the right panel. Treatments included in the mesocosm experiment: increased temperature (3 °C; T; upper panel), browning (B; continuous increase of tDOM solution; middle panel), and the interaction of temperature and browning (mixed treatment; TB; lower panel). The bars show how a future scenario will push ( ±) each response compared with the ambient situation Control (C). The y axis states Cohen’s d effect sizes (d). Dark grey bars indicate statistically significant (p < 0.05) and large effect sizes (d ≥ 0.8) that are more meaningful28 compared to unfilled bars with smaller effect sizes (d < 0.8). Dotted bars indicate responses with large effect sizes (d ≥ 0.8) but with less statistical significance (p < 0.10).

Combined increases in temperature and browning increased seston biomass significantly in the mixed treatment (TB) (F1,20 = 9.84, p < 0.01, Table 2; Fig. 2), and a simultaneous increase of MeHg burden was observed, while aqueous MeHg concentrations remained stable (Fig. 2). Higher seston biomass and MeHg burden in seston in the temperature (T) and browning (B) treatments indicate that organisms in both treatments increased aqueous MeHg transfer to the base of the food web relative to the Control (C), even though aqueous MeHg concentrations were similar. The exact mechanisms remain speculative: it may be due to aqueous MeHg being increasingly adsorbed to increasing seston biomass under temperature increase, which also provides more binding sites for MeHg. Another possibility is shading by tDOM in the water column allowing aqueous MeHg to avoid photodegradation longer29, which likely preserved MeHg concentrations in the browning treatments.

Table 2 Statistics from the factorial ANOVA of the response variables based on results from sampling at the end of the mesocosm experiment. Response variables: seston and microplankton biomass, MeHg and MeHg burden, and bioconcentration factors, total lipids, and omega-3 polyunsaturated fatty acids (n-3 PUFA), omega-6 polyunsaturated fatty acids (n-6 PUFA), under the 2-factor Treatment (T, B, and TB). The values of p were adjusted for multiple comparisons (FDR p values), and the p values in bold indicate statistical significance level p < 0.05.

The MeHg burden in microplankton increased under the browning (B and TB) treatment (p < 0.01, Table 1). However, the treatment condition and their interaction had no significant additive effect on microplankton biomass, BCF, or aqueous MeHg concentrations. This suggests a consistent aqueous MeHg transfer across the algal-animal interface, which is critical for further bioaccumulation and trophic transfer9.

It is important to note that seston MeHg bioconcentration factors (BCF) showed no significant change in any of the treatments, even though in the browning (B) and mixed treatments (TB) the BCF was lower than that of the Control (C). Previous studies have shown that increases in DOC inhibit biological uptake of MeHg6,16, likely due to more binding sites for MeHg that reduce uptake by biota directly from the aqueous phase30. Our experimental results with elevated MeHg burden in plankton when DOC increased in the mixed treatment (TB) contradicted with this previous work that suggests decreasing MeHg bioavailability to the food web when DOC increases. We would suggest instead that increasing DOC content does not offset the general pattern of higher MeHg uptake by plankton under higher temperature. Our results revealed that temperature and browning factors have implications for MeHg burden in seston at the base of the food web, as well as MeHg burden in microplankton. This will have direct bearing on consumers at higher trophic levels.

However, even as MeHg burdens increased, the concentration of total lipids, omega-3 (n-3) PUFA, and omega-6 (n-6) PUFA in seston decreased in browning (B) and mixed treatments (TB) (Table 2). The PUFA decrease under the browning treatment (B) was most significant for n-3 PUFA (F1,20 = 14.05, p = 0.01; Fig. 2, Table 2) and n-6 PUFA (F1,20 = 14.42, p < 0.01; Fig. 2, Table 2). These changes indicate low diet quality that may subsequently lower somatic growth and reproduction of zooplankton and other consumers, likely due to altered taxonomic seston composition19,31. Nevertheless, we were able to observe microplankton PUFA increases in the browning treatment (B) regarding n-3 PUFA (F1,20 = 13.20, p < 0.01; Table 2, Fig. 2). Such increase of PUFA in microplankton may not all become readily available for subsequent nutrient transfer to the next trophic level, considering that the microplankton size fraction (40–200 μm) is largely inaccessible for zooplankton25,32.

To get a better understanding of the change in fatty acid quality and relevant dietary benefit/risk quantitatively, we explored the n-3:n-6 PUFA ratios, which is useful in assessing the relative contribution of autochthonous versus allochthonous matter in food sources33, as well as the MeHg:n-3 PUFA ratio in both seston and microplankton (Fig. 2, Table 2). The ratio of MeHg:n-3 PUFA in seston increased slightly in the mixed treatment (TB) (F1,20 = 0.2, p < 0.10; Table 2, Fig. 2), suggesting relatively elevated dietary exposure to MeHg, yet decreased supply of PUFA to aquatic consumers from seston. The n-3:n-6 were the lowest in the temperature treatment (T) for both seston and microplankton, but they increased in the browning treatment (B) (Fig. 2), indicating enhanced dietary availability of n-3 PUFA for aquatic consumers under tDOM addition. Similarly, the isopod Asellus utilized algal resources best when feeding on algae under terrestrial organic matter dominated conditions34. However, this result seems to contrast with findings from other previous studies where terrestrial taxa contain higher n-6 PUFA that differentiate them from aquatic OM that contains relatively more n-3 PUFA35. While additional nutrients associated with tDOM input in the browning treatment could have stimulated autochthonous OM production in the experiment, the increased SUVA suggests the opposite. Alternatively, the higher n-6 PUFA from sites with more terrestrial inputs in other studies could be related to particulate organic carbon which was not added in our study36.

The MeHg mass balance was estimated from measurements on aqueous MeHg, seston, microplankton, and zooplankton (Fig. 3a). This led to an estimated distribution of the MeHg mass in the mesocosms relative to the total amount of spiked MeHg (Fig. 3b). A larger proportion was recovered in the brownified (B and TB) mesocosms (65% to 70% recovery of the spiked MeHg, relative to the control and temperature treatments (C and T) where 40% and 30% of the respective MeHg spike was recovered in the water column or biota (Fig. 3b). This suggests a loss of MeHg that was larger in the non-brownified (C and T) treatments. This could be due to the darker water colour attenuating light penetration in the open mesocosms, decreasing dissolved MeHg photodegradation processes by UV light37. Within browning and mixed treatments, there is also a possibility of higher microbial Hg methylation, stimulated by organic matter remineralization38. Another possibility of not-recovered MeHg could be due to aqueous MeHg lost to the walls of mesocosms39, but it is not clear why such losses would be lower in the brownified treatments. The proportions of MeHg distributed to seston under all treatment conditions, as well as microplankton in the mixed treatment (Fig. 3b), are substantially higher compared to the control (C) condition, presumably driven by plankton biomass increase. The microplankton comprised mostly of filamentous algae is, however, not readily bioavailable for consumers at higher trophic levels due to particle size limitations25,32.

Figure 3
figure 3

Estimated MeHg mass balance per mesocosm (a) and MeHg distribution across aqueous and biological phases (b) across treatments based on average estimations. Aqueous phase (dark blue), seston (orange), microplankton (grey), and zooplankton (yellow). “Not recovered” in light blue colours represent the proportion of MeHg that was not retrieved in either aqueous phase or solid phase at the end of the mesocosm experiment.

Mesocosms have higher surface to volume ratios than natural systems and the “wall-effect” is common to mesocosm experiments40. The “wall effect” in this current study may have increased the amount of microplankton relative to what might be expected in nature. We observed that this effect was comparable across the different treatments so we do not expect the effects of the treatments compared to controls (Fig. 2) to change from the current conclusions. However, the “wall effect” could change the mass balance such that there would be a lower mass percent of the total MeHg mass in the microplankton. In addition, the “wall effect” could have also resulted in biomass dilution of the MeHg concentrations in the microplankton fraction shown in Table 1, resulting in lower MeHg concentrations comparing to where no or less “wall effect” occurred.

Here we demonstrate that the expected biomass increases created by increased temperature and browning in the combined (TB) treatment was accompanied by contrasting changes in MeHg and PUFA content, with increasing MeHg burden and decreasing contents of highly required dietary PUFA in both the seston and microplankton. The sensitivity of the base of the food web to large-scale climate changes has important consequences for all consumers at higher trophic levels. This was apparent from the responses (or lack thereof) for seston biomass, MeHg burden and lipid contents, as well as PUFA to the temperature and tDOM increases in the separate T and B treatments (Fig. 2, Table 2): In the temperature (T) treatment, it was only the MeHg burden in the seston that increased significantly, while in the browning (B) treatment it was only the PUFA that decreased significantly in the seston.

The microplankton fraction maintained its biomass, MeHg and PUFA contents under the increased temperature scenario, suggesting that larger size phytoplankton is less responsive to temperature hikes than seston. However, microplankton MeHg responded to tDOM addition. The browning scenario increased the lipid and PUFA contents in microplankton (Table 2), corresponding to higher content of n-3 PUFA under tDOM-rich conditions34. Elevated MeHg burden in the mixed (TB) treatment was a common response for seston and microplankton in the mixed treatment (Fig. 2), despite their different responses with respect to MeHg and PUFA by adding tDOM alone (B treatment). Consequently, we conclude that climate change scenarios with increasing lake temperature and browning affect MeHg uptake and dietary PUFA at the aquatic plant/animal interface: A warming scenario without browning increases aqueous MeHg uptake by seston, thus increasing dietary MeHg for consumers, while lake browning increases PUFA contents in microplankton, which may not be readily available for zooplankton.

Our study was designed to compare effects of two climate change variables to ambient (control) conditions, in order to simulate responses at the base of aquatic food webs in subalpine lake ecosystems. We investigated these effects under subalpine conditions that are highly prone to climate change effects, and relatively tDOM-poor compared to many other limnic systems. More and more lakes and reservoirs, especially those in boreal regions, are facing both temperature increase (with fewer winter ice days) and browning (higher tDOM content in water)5. Little has been done to observe the combination of the two climate change factors simultaneously, although warnings have been given about the threats from warming11 as well as the role of tDOM for MeHg bioavailability in some situations41,42. Hence, we are here able to add a mechanistic understanding of the combined effects of warming and browning to the observations on MeHg bioavailability and lipid content under climate change. Moreover, we connect predicted climate-change factors with environmental consequences in aquatic ecosystems. This places the basal food web investigations of the present study in the scope of global change processes, thereby providing a scenario for better understanding the biogeochemical cycles of MeHg and essential nutrient lipids in future aquatic ecosystems.

Materials and methods

Experimental setup and treatments

The mesocosm facility at WasserCluster Lunz (47°51′N, 15°01′E, elevation: 608 m) was utilized for this experiment. Modelled ecosystems with oligotrophic subalpine lake water from Lake Lunz41 were constructed in thermally insulated high-density polyethylene cylinder mesocosms (n = 24, 400 L volume, 1 m × 0.74 m Ø). The subalpine lake water is characterized by high pH (> 8), low DOC (< 2 mg/L) and low nutrition concentrations (total nitrogen < 9 μg/L and total phosphorous < 7 μg/L). Methylmercury in surface water is under the detection limit of 0.0001 ng/L, and so is total mercury.

The mesocosm experiment consisted of four treatments (six replicates for each treatment): 1. Control treatment (“C”, ambient temperature); 2. An elevated temperature treatment (“T”, 3 °C above control temperature average); 3. Browning treatment (“B”, with weekly addition of tDOM solution until one week before the end of the experiment); 4. Mixture of browning and elevated temperature treatment (“TB”, simulated warming and browning with both + 3 °C above control temperature average and addition of terrestrial DOC). The mesocosm system was controlled with respect to temperature, dissolved organic carbon (DOC), light exposure, aeration, and nutrient additions during an experimental period of 42 days. Mounted nylon mesh on top of each mesocosm was set up to protect from invasion of external particles, beetles, or birds, while light exposure was kept to a maximum degree. Each mesocosm was also aerated by an air diffuser to prevent stratification inside the barrel during the experiment. Allocation of treatment for each mesocosm was completely randomized.

Each mesocosm was filled with lake water collected using a submerged water pump connected to a pipe with the inlet located 50 m from lake shore at a water depth of between 2 and 10 m. Then each mesocosm was filled with an equivalent volume (2.5 L) of 100 µm filtered lake water, containing similar distributions of plankton communities. Isotopically enriched MeHg tracers as labile aqueous Me201Hg and soil extracted DOC complex were added to the surface water to simulate Hg inputs to the water phase from atmospheric deposition and catchment runoff. Details of tDOM extraction and the mesocosm facility can be retrieved in the supplementary information (SI). Given the extremely low MeHg (below detection limit 0.0001 ng/L) in the water column at the initial stage of the experiment from Lake Lunz, we added an initial MeHg spike to achieve a starting MeHg concentration of 0.05 ng/L in the mesocosm, approximately 10 times higher than the instrumental detection limit, also corresponding to previous MeHg spiked mesocosm experiments35. It is also suspected that subalpine lake ecosystems will receive more Hg and possibly MeHg input from either atmospheric40 or glacier melt under climate change scenarios41, which may result in aqueous MeHg concentrations closer to those currently seen in higher latitude systems. It should be noted that our experimental design has a primary focus on shallow-water lakes, which means we take little consideration in water mixing and upwelling of in-situ produced MeHg as in deeper lakes.

Maintenance of treatments

From the start (1 July 2018) and throughout the study the temperature was 3 °C higher in the temperature elevated (T and TB treatments) than in the non-temperature regulated enclosures (C and B treatments) (Fig. S1). The DOC concentration was initially 2.21 mg/L in the added water of the control (C) treatments from Lake Lunz and gradually increased to 3.32 mg/L by the end of the experiment. Water colour was measured at least once every week spectrophotometrically (420 nm wavelength) and the browning (B) treatment was maintained by adding weekly the extracted tDOM solution weekly to reach a 2–threefold higher DOC compared to the control. The browning treatments (B and TB) contained DOC concentrations up to 5 mg/L, almost doubled compared to the control treatment. All enclosures were found with algal growth on the wall shortly before the end of the experiment. The enclosure walls were scrubbed at the end of the experiment for collecting biomass and sample analyses.

Sampling and analysis

Throughout the experiment weekly measurements were taken in both filtered (< 0.2 µm) and unfiltered surface water, of MeHg and total Hg concentrations (Table 2 and Fig. S4). The analysis of aqueous MeHg and total Hg was done using a Tekran Model 2700 (pre-programmed to run EPA Method 1630) and Model 2600 (pre-programmed to run EPA Method 1631), respectively. At the same time, weekly samples of surface water were filtered through 0.7 µm GF/F and analysed for DOC concentrations (GE Healthcare TOC (Total Organic Carbon) Analyzer) and absorbance (UV-1700 Pharmaspec UV–VIS Spectrophotometer) (Fig. 1), total nitrogen (N) using a continuous flow analysis instrument (Alliance instruments) (Fig. S2), chlorophyll a (Chl a) by first extracting samples for Chl a using 90% acetone and then analysing the digested filtrate using a fluorescence spectrophotometer (Hitachi, f-7000 Fluorescence Spectrophotometer) (Fig. S3).

We sampled plankton in different size fractions (seston 0.7–40 µm, microplankton 40–200 µm, zooplankton > 55 µm) at the end of the mesocosm experiment. Besides analysing MeHg in both the water columns and organisms, we also calculated bioconcentration factors (BCF: log10 transformed MeHg concentration ratio between MeHg concentrations in the seston or microplankton (ng/g dry weight, d.w.) and the aqueous MeHg detected in the water column (ng/L) that passed a 0.2 µm filter). The plankton samples were analysed for fatty acid composition, especially fatty acid groups relevant for dietary quality, e.g., omega-3 polyunsaturated fatty acids (n-3 PUFA), and omega-6 polyunsaturated fatty acids (n-6 PUFA). Lipids were first extracted using chloroform:methanol (2:1 v/v) from freeze-dried plankton samples and then methylated to fatty acid methyl esters, which were separated and quantified by gas chromatography46. The procedure for lipid analyses of plankton samples is described in the Supplementary Information of this paper. We focused on the seston samples collected on GF/F filters with a size fraction between 0.7 and 40 µm, and microplankton samples collected using 40 µm meshes with a size fraction bigger than 40 µm. The sampled microplankton contained mostly colonial and filamentous Cyanobacteria and small zooplankton (Daphnia and rotifers), which were difficult to separate from the co-occurring algae.


The treatment effects on MeHg and PUFA were tested using a fully replicated factorial ANOVA design. Mean effect sizes (± CI) based on Cohen’d47,48 calculated from least square regression model for seston and microplankton are shown in Fig. 2. Differences in the measured values of MeHg and PUFA were tested with one-way ANOVA with Tukey HSD post-hoc test (Table 2). All statistics were performed using JMP Pro 15.

Data availability

The data sets generated during and/or analysed for this study are available in supplementary information. Further details and description for the data sets are available from the corresponding author on reasonable request.


  1. Santer, B. D. et al. A search for human influences on the thermal structure of the atmosphere. Nature 382, 39–46. (1996).

    ADS  CAS  Article  Google Scholar 

  2. Hulme, M., Osborn, T. J. & Johns, T. C. Precipitation sensitivity to global warming: Comparison of observations with HadCM2 simulations. Geophys. Res. Lett. 25, 3379–3382. (1998).

    ADS  Article  Google Scholar 

  3. Hongve, D., Riise, G. & Kristiansen, J. F. Increased colour and organic acid concentrations in Norwegian forest lakes and drinking water - a result of increased precipitation?. Aquat. Sci. 66, 231–238. (2004).

    CAS  Article  Google Scholar 

  4. Hansson, L.-A. et al. Food-chain length alters community responses to global change in aquatic systems. Nat. Clim. Change 3, 228. (2012).

    ADS  Article  Google Scholar 

  5. Creed, I. F. et al. Global change-driven effects on dissolved organic matter composition: Implications for food webs of northern lakes. Global Change Biol. 24, 3692–3714. (2018).

    ADS  Article  Google Scholar 

  6. Le Faucheur, S., Campbell, P. G. C., Fortin, C. & Slaveykova, V. I. Interactions between mercury and phytoplankton: Speciation, bioavailability, and internal handling. Environ. Toxicol. Chem. 33, 14 (2014).

    Article  Google Scholar 

  7. Kainz, M. J., Perga, M. E., Arts, M. T. & Mazumder, A. Essential fatty acid concentrations of different seston sizes and zooplankton: a field study of monomictic coastal lakes. J. Plankton Res. 31, 635–645. (2009).

    CAS  Article  Google Scholar 

  8. Pilecky, M., Závorka, L., Arts, M. T. & Kainz, M. J. Omega-3 PUFA profoundly affect neural, physiological, and behavioural competences – implications for systemic changes in trophic interactions. Biol. Rev. (2021).

    Article  PubMed  Google Scholar 

  9. Wu, P. et al. The importance of bioconcentration into the pelagic food web base for methylmercury biomagnification: A meta-analysis. Sci. Total Environ. 646, 357–367. (2019).

    ADS  CAS  Article  PubMed  Google Scholar 

  10. Kainz, M., Arts, M. T. & Mazumder, A. Essential versus potentially toxic dietary substances: A seasonal comparison of essential fatty acids and methyl mercury concentrations in the planktonic food web. Environ. Pollut. 155, 262–270. (2008).

    CAS  Article  PubMed  Google Scholar 

  11. Schartup, A. T. et al. Climate change and overfishing increase neurotoxicant in marine predators. Nature 572, 648–650. (2019).

    ADS  CAS  Article  PubMed  Google Scholar 

  12. Dijkstra, J. A. et al. Experimental and natural warming elevates mercury concentrations in estuarine fish. PLoS ONE 8, e58401. (2013).

    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

  13. Buckman, K. L. et al. Sediment organic carbon and temperature effects on methylmercury concentration: A mesocosm experiment. Sci. Total Environ. 666, 1316–1326. (2019).

    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

  14. Curtis, A. N. et al. Effects of temperature, salinity, and sediment organic carbon on methylmercury bioaccumulation in an estuarine amphipod. Sci. Total Environ. 687, 907–916. (2019).

    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

  15. Jonsson, S. et al. Terrestrial discharges mediate trophic shifts and enhance methylmercury accumulation in estuarine biota. Sci. Adv. 3, e1601239. (2017).

    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

  16. French, T. D. et al. Dissolved organic carbon thresholds affect mercury bioaccumulation in Arctic Lakes. Environ. Sci. Technol. 48, 3162–3168. (2014).

    ADS  CAS  Article  PubMed  Google Scholar 

  17. Rolfhus, K., Hall, B., Monson, B., Paterson, M. & Jeremiason, J. Assessment of mercury bioaccumulation within the pelagic food web of lakes in the western Great Lakes region. Ecotoxicology 20, 1520–1529. (2011).

    CAS  Article  PubMed  Google Scholar 

  18. Broadley, H. J. et al. Factors affecting MeHg bioaccumulation in stream biota: the role of dissolved organic carbon and diet. Ecotoxicology 28, 949–963. (2019).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  19. Rasconi, S., Winter, K. & Kainz, M. J. Temperature increase and fluctuation induce phytoplankton biodiversity loss—Evidence from a multi-seasonal mesocosm experiment. Ecol. Evol. 7, 2936–2946. (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  20. Robarts, R. D. & Zohary, T. Temperature effects on photosynthetic capacity, respiration, and growth rates of bloom-forming cyanobacteria. N.Z. J. Mar. Freshw. Res. 21, 391–399. (1987).

    CAS  Article  Google Scholar 

  21. Klausmeier, C. A., Litchman, E. & Levin, S. A. Phytoplankton growth and stoichiometry under multiple nutrient limitation. Limnol. Oceanogr. 49, 1463–1470. (2004).

    ADS  Article  Google Scholar 

  22. IPCC. Climate Change 2007: The physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (eds Solomon, S. et al.) (Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 2007).

  23. Köhler, S. J., Kothawala, D., Futter, M. N., Liungman, O. & Tranvik, L. In-lake processes offset increased terrestrial inputs of dissolved organic carbon and color to lakes. PLoS ONE 8, e70598. (2013).

    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

  24. Johansson, M. E. & Nilsson, C. Responses of riparian plants to flooding in free-flowing and regulated boreal rivers: an experimental study. J. Appl. Ecol. 39, 971–986. (2002).

    Article  Google Scholar 

  25. Burns, C. W. The relationship between body size of filter-feeding cladocera and the maximum size of particle ingested. Limnol. Oceanogr. 13, 675–678. (1968).

    ADS  Article  Google Scholar 

  26. Vanderploeg, H. A., Paffenhöfer, G.-A. & Liebig, J. R. Diaptomus vs. net phytoplankton: Effects of algal size and morphology on selectivity of a behaviorally flexible, omnivorous copepod. Bull. Mar. Sci. 43, 377–394 (1988).

    Google Scholar 

  27. Sieburth, J. M., Smetacek, V. & Lenz, J. Pelagic ecosystem structure: Heterotrophic compartments of the plankton and their relationship to plankton size fractions. Limnol. Oceanogr. 23, 1256–1263. (1978).

    ADS  Article  Google Scholar 

  28. Weishaar, J. L. et al. Evaluation of specific ultraviolet absorbance as an indicator of the chemical composition and reactivity of dissolved organic carbon. Environ. Sci. Technol. 37, 4702–4708. (2003).

    ADS  CAS  Article  PubMed  Google Scholar 

  29. Gilmour, C. C. et al. Methylmercury concentrations and production rates across a trophic gradient in the northern Everglades. Biogeochemistry 40, 327–345. (1998).

    CAS  Article  Google Scholar 

  30. Dutton, J. & Fisher, N. S. Influence of humic acid on the uptake of aqueous metals by the killifish Fundulus heteroclitus. Environ. Toxicol. Chem. 31, 2225–2232. (2012).

    CAS  Article  PubMed  Google Scholar 

  31. von Elert, E. Determination of limiting polyunsaturated fatty acids in Daphnia galeata using a new method to enrich food algae with single fatty acids. Limnol. Oceanogr. 47, 1764–1773. (2002).

    ADS  Article  Google Scholar 

  32. Havens, K. E. Size structure and energetics in a plankton food web. Oikos 81, 346–358. (1998).

    Article  Google Scholar 

  33. Torres-Ruiz, M., Wehr, J. D. & Perrone, A. A. Trophic relations in a stream food web: importance of fatty acids for macroinvertebrate consumers. J. N. Am. Benthol. Soc. 26, 509-522,514 (2007).

    Article  Google Scholar 

  34. Grieve, A. & Lau, D. C. P. Do autochthonous resources enhance trophic transfer of allochthonous organic matter to aquatic consumers, or vice versa?. Ecosphere 9, e02307. (2018).

    Article  Google Scholar 

  35. Hixson, S. M., Sharma, B., Kainz, M. J., Wacker, A. & Arts, M. T. Production, distribution, and abundance of long-chain omega-3 polyunsaturated fatty acids: a fundamental dichotomy between freshwater and terrestrial ecosystems. Environ. Rev. 23, 414–424. (2015).

    CAS  Article  Google Scholar 

  36. Gladyshev, M. I. et al. Differences in organic matter and bacterioplankton between sections of the largest Arctic river: Mosaic or continuum?. Limnol. Oceanogr. 60, 1314–1331. (2015).

    ADS  Article  Google Scholar 

  37. Poste, A. E., Braaten, H. F. V., de Wit, H. A., Sørensen, K. & Larssen, T. Effects of photodemethylation on the methylmercury budget of boreal Norwegian lakes. Environ. Toxicol. Chem. 34, 1213–1223. (2015).

    CAS  Article  PubMed  Google Scholar 

  38. Jonsson, S. et al. Differentiated availability of geochemical mercury pools controls methylmercury levels in estuarine sediment and biota. Nat. Commun. (2014).

    Article  PubMed  Google Scholar 

  39. Parker, J. L. & Bloom, N. S. Preservation and storage techniques for low-level aqueous mercury speciation. Sci. Total Environ. 337, 253–263. (2005).

    ADS  CAS  Article  PubMed  Google Scholar 

  40. Dzialowski, A. et al. Are the abiotic and biotic characteristics of aquatic mesocosms representative of in situ conditions. J. Limnol. 73, 2014 (2014).

    Article  Google Scholar 

  41. Herrero Ortega, S. et al. High methylmercury formation in ponds fueled by fresh humic and algal derived organic matter. Limnol. Oceanogr. 63, S44–S53. (2017).

    CAS  Article  Google Scholar 

  42. Tsui, M. T. K. & Finlay, J. C. Influence of dissolved organic carbon on methylmercury bioavailability across Minnesota stream ecosystems. Environ. Sci. Technol. 45, 5981–5987. (2011).

    ADS  CAS  Article  PubMed  Google Scholar 

  43. Kainz, M. J., Ptacnik, R., Rasconi, S. & Hager, H. H. Irregular changes in lake surface water temperature and ice cover in subalpine Lake Lunz, Austria. Inland Waters 7, 27–33. (2017).

    Article  Google Scholar 

  44. Fahnestock, M. F. et al. Mercury reallocation in thawing subarctic peatlands. Geochem. Perspect. Lett. 11, 33–38. (2019).

    Article  Google Scholar 

  45. St. Pierre, K. A. et al. Drivers of mercury cycling in the rapidly changing glacierized watershed of the high Arctic’s largest lake by volume (Lake Hazen, Nunavut, Canada). Environ. Sci. Technol. 53, 1175–1185. (2019).

    ADS  CAS  Article  PubMed  Google Scholar 

  46. Heissenberger, M., Watzke, J. & Kainz, M. J. Effect of nutrition on fatty acid profiles of riverine, lacustrine, and aquaculture-raised salmonids of pre-alpine habitats. Hydrobiologia 650, 243–254. (2010).

    CAS  Article  Google Scholar 

  47. Cohen, J. Statistical Power Analysis for the Behavioral Sciences 2nd edn, (Lawrence Erlbaum Associates, 1988).

  48. Sawilowsky, S. New effect size rules of thumb. J. Mod. Appl. Stat. Methods 8, 26 (2009).

    Article  Google Scholar 

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Technical support from Hannes Hager and Michael Mayr for setting up the mesocosms is greatly appreciated. The study was financed by the Swedish Research Council (VR) through the Sino-Swedish Mercury Management Research Framework (Contract Number: 2013-6978).


Open access funding provided by Swedish University of Agricultural Sciences.

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P.W., K.B., B.B. and M.K. conceptualized the study, P.W. and M.K. designed the methodology. P.W., M.K., K.W., F.V., and S.Z. performed the study. P.W. and M.K. analysed the data. P.W. wrote the paper. All authors commented on the manuscript.

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Correspondence to Pianpian Wu.

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Wu, P., Kainz, M.J., Valdés, F. et al. Elevated temperature and browning increase dietary methylmercury, but decrease essential fatty acids at the base of lake food webs. Sci Rep 11, 16859 (2021).

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