Modelling long-term ecological time series – Insights from shallow lakes

Presentation at the 11th International Shallow Lakes Conference, Estonia 11.-16.06.2023.This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 951963. I am thankful to the Estonian Ministry of Education and Research for funding this work (grant P210160PKKH) and to my colleagues and friends for their great ideas and support.This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 951963. I am thankful to the Estonian Ministry of Education and Research for funding this work (grant P210160PKKH) and to my colleagues and friends for their great ideas and support

Transfert de méthylmercure et structure des réseaux trophiques chez les macroinvertébrés littoraux

Dans le cadre de l'étude de cas du fleuve St Laurent du réseau COMERN, l'objectif général de la thèse était de déterminer le rôle des macro invertébrés littoraux dans le transfert de méthylmercure (MeHg) dans l'écosystème du lac St Pierre. Le premier chapitre était consacré à la contribution quantitative des invertébrés non consommables («impasses trophiques») au transfert de MeHg vers les poissons. Pour cela, les concentrations en mercure total (THg) et en MeHg chez quatre groupes fonctionnels de macroinvertébrés littoraux (brouteurs, détritivores, prédateurs consommables, prédateurs non consommables) ont été mesurées. Les résultats ont montré que les prédateurs non consommables présentaient les plus fortes concentrations en THg, en MeHg ainsi que la plus forte proportion de MeHg/THg de tous les groupes fonctionnels. La charge (concentration x biomasse) de MeHg des prédateurs non consommables représentait de 10 à 36% du réservoir de MeHg des invertébrés phytophiles. Cette proportion élevée de MeHg séquestrée dans des impasses trophiques pourrait contribuer à expliquer les faibles concentrations en Hg mesurées chez les poissons du lac St Pierre. Nos résultats montrent que les organismes non consommables doivent être pris en compte dans les modèles prédictifs de contamination des écosystèmes par le Hg afin d'éviter de surestimer les quantités de MeHg biodisponibles pour les poissons. Dans le deuxième chapitre, l'objectif était de déterminer les liens entre la source de matière organique (MO) et la contamination au MeHg chez les macro invertébrés littoraux consommateurs primaires. Une approche isotopique a été appliquée pour répondre à cet objectif. Les sources autochtones (épiphytes et macrophytes) étaient majoritaires dans la MO assimilée par les consommateurs primaires, avec une proportion plus faible de MO allochtone (matières particulaires en suspension notamment). Le MeHg/THg chez les macroinvertébrés était corrélé positivement avec les proportions d'épiphytes, alors ces dernières étaient corrélées négativement avec la fraction de Hg inorganique. Cette découverte peut faire supposer que la voie d'entrée principale du MeHg dans les réseaux trophiques littoraux se situe dans les épiphytes. Les consommateurs primaires pourraient alors moduler le transfert de MeHg vers les niveaux trophiques supérieurs suivant qu'ils s'alimentent de sources de MO à forte ou à faible concentration en MeHg. Le troisième chapitre traitait de l'influence du groupe fonctionnel (brouteur, collecteur, fragmenteur, omnivore, prédateur, prédateur-hématophage, piqueur-suceur) et des variables spatiotemporelles (année, mois, station d'échantillonnage) sur la signature de δ

How warming and other stressors affect zooplankton abundance, biomass and community composition in shallow eutrophic lakes

We aimed to investigate the influence of environmental factors and predict zooplankton biomass and abundance in shallow eutrophic lakes. We employed time series of zoo- plankton and environmental parameters that were measured monthly during 38 years in a large, shallow eutrophic lake in Estonia to build estimates of zooplankton community metrics (cladocerans, copepods, rotifers, ciliates). The analysis of historical time series revealed that air temperature was by far the most important variable for explaining zooplankton biomass and abundance, followed, in decreasing order of importance, by pH, phytoplankton biomass and nitrate concentration. Models constructed with the best predicting variables explained up to 71% of zooplankton biomass variance. Most of the predictive variables had opposing or antagonistic interactions, often mitigating the effect of temperature. In the second part of the study, three future climate scenarios were developed following different Intergovernmental Panel on Climate Change (IPCC) tem- perature projections and entered into an empirical model. Simulation results showed that only a scenario in which air temperature stabilizes would curb total metazooplankton biomass and abundance. In other scenarios, metazooplankton biomass and abundance would likely exceed historical ranges whereas ciliates would not expand. Within the metazooplankton community, copepods would increase in biomass and abundance, whereas cladocerans would lose in biomass but not in abundance. These changes in the zooplankton community will have important consequences for lake trophic structure and ecosystem functioning.This research was supported by the Estonian Research Council Grants PSG32, PRG709 and institutional research funding IUT 21-2 of the Estonian Ministry of Education and Research.This research was supported by the Estonian Research Council Grants PSG32, PRG709 and institutional research funding IUT 21-2 of the Estonian Ministry of Education and Research

Keystone species Chydorus sphaericus in shallow eutrophic Lake Võrtsjärv (Estonia) – 56 years of continuous zooplankton monitoring and research

Presentation at the 11th International Shallow Lakes Conference, Estonia 11.-16.06.2023.This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 951963, by Estonian Ministry of the Environment through the state monitoring programme, and also from the Estonian Research Council grant PRG1167.This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 951963, by Estonian Ministry of the Environment through the state monitoring programme, and also from the Estonian Research Council grant PRG1167

Predicting multiple stressor effect on zooplankton abundance, biomass and community composition in two large eutrophic lakes : [presentation]

Presentation at the BIOGEOMON 2022, 10th International Symposium on Ecosystem Behavior, June 26–30, 2022, Tartu, Estonia.We are grateful to Tartu Environmental Research Ltd (Estonia) for water chemistry data and to the Estonian Environment Board for providing long-term air temperature data and supporting lake monitoring. This research was financed by Estonian Research Council Grant PRG709, PRG1167, and institutional research funding P210160PKKH of the Estonian Ministry of Education and Research. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 951963. Data collection within the frames of the state monitoring programme were supported by the Estonian Ministry of the Environment

An estimation of diel metabolic rates of eight limnological archetypes from Estonia using high-frequency measurements

We employed a Bayesian model to assess the metabolic state of 8 Estonian lakes representing the 8 lake types according to the European Union Water Framework Directive. We hypothesized that long-term averages of light-related variables would be better predictors of lake metabolism than nutrient-related variables. Model input parameters were in situ high-frequency measurements of dissolved oxygen, temperature, and irradiance. Model simulations were conducted for several (5–12) diel cycles for each lake during the summer season. Accounting for uncertainty, the results from the Bayesian model revealed that 2 lakes were autotrophic for the duration of the experiment, 1 was heterotrophic, and 5 were balanced or had an ambiguous metabolic state. Cross-comparison with a traditional bookkeeping model showed that the majority of lakes were in metabolic balance. A strong coupling between primary production and respiration was observed, with the share of autochthonous primary production respired by consumers increasing with light extinction and nutrient-related variables. Unlike gross primary production, community respiration was strongly related to light extinction, dissolved organic carbon (DOC) and total phosphorus. These findings suggest that a drastic decrease in light-limited primary production along the DOC gradient counter-balanced nutrient supply in the darker lakes and thus blurred the relationship between primary production and nutrients. Thus, contrary to our hypothesis, both light and nutrient-related variables seemed to be good predictors of lake respiration and its coupling to lake primary production

Summer greenhouse gas fluxes in different types of hemiboreal lakes

Lakes are considered important regulators of atmospheric greenhouse gases (GHG). We estimated late summer open water GHG fluxes in nine hemiboreal lakes in Estonia classified under different lake types according to the European Water Framework Directive (WFD). We also used the WFD typology to provide an improved estimate of the total GHG emission from all Estonian lakes with a gross surface area of 2204 km2 representing 45,227 km2 of hemiboreal landscapes (the territory of Estonia). The results demonstrate largely variable CO2 fluxes among the lake types with most active emissions from Alkalitrophic (Alk), Stratified Alkalitrophic (StratAlk), Dark Soft and with predominant binding in Coastal, Very Large, and Light Soft lakes. The CO2 fluxes correlated strongly with dissolved CO2 saturation (DCO2) values at the surface. Highest CH4 emissions were measured from the Coastal lake type, followed by Light Soft, StratAlk, and Alk types; Coastal, Light Soft, and StratAlk were emitting CH4 partly as bubbles. The only emitter of N2O was the Alk type. We measured weak binding of N2O in Dark Soft and Coastal lakes, while in all other studied lake types, the N2O fluxes were too small to be quantified. Diversely from the common viewpoint of lakes as net sources of both CO2 and CH4, it turns out from our results that at least in late summer, Estonian lakes are net sinks of both CO2 alone and the sum of CO2 and CH4. This is mainly caused by the predominant CO2 sink function of Lake Peipsi forming ¾ of the total lake area and showing negative net emissions even after considering the Global Warming Potential (GWP) of other GHGs. Still, by converting CH4 data into CO2 equivalents, the combined emission of all Estonian lakes (8 T C day−1 ) is turned strongly positive: 2720 T CO2 equivalents per day.This research was inspired by GLEON (Global Lake Ecological Observatory Network) and was funded by Estonian Research Council (PSG32, PUT1598, PSG10, PRG709, PRG1167 and ETF8486), the European Union H2020 WIDESPREAD (TREICLAKE 951963) and the Swiss Program “Enhancing public environmental monitoring capacities”.This research was inspired by GLEON (Global Lake Ecological Observatory Network) and was funded by Estonian Research Council (PSG32, PUT1598, PSG10, PRG709, PRG1167 and ETF8486), the European Union H2020 WIDESPREAD (TREICLAKE 951963) and the Swiss Program “Enhancing public environmental monitoring capacities”

Generalist invasion in a complex lake food web

Invasive species constitute a threat not only to native populations but also to the structure and functioning of entire food webs. Despite being considered as a global problem, only a small number of studies have quantitatively predicted the food web-level consequences of invasions. Here, we use an allometric trophic network model parameterized using empirical data on species body masses and feeding interactions to predict the effects of a possible invasion of Amur sleeper (Perccottus glenii), on a well-studied lake ecosystem. We show that the modeled establishment of Amur sleeper decreased the biomasses o ftop predator fishes by about 10%–19%. These reductions were largely explained by increased larval competition for food and Amur sleeper predation on fish larvae. In contrast, biomasses of less valued fish of lower trophic positions increased by about 0.4%–9% owing to reduced predation pressure by top piscivores. The predicted impact of Amur sleeper establishment on the biomasses of native fish species vastly exceeded the impacts of current-dayfishing pressures.H2020 European Research Council, Grant/Award Number: COMPLEX-FISH770884; Academy of Finland, Grant/Award Numbers: 317495, 325107,340901; Natural Sciences and Engineering Research Council of Canada; Estonian Research Council, Grant/Award Numbers: PSG32, PRG1167, PRG709, MOBJD29; Estonian University of Life Sciences, Grant/Award Number: P190254PKKH; European Union's Horizon 2020 Research and Innovation Programme, Grant/Award Number: TREICLAKE 951963H2020 European Research Council, Grant/Award Number: COMPLEX-FISH770884; Academy of Finland, Grant/Award Numbers: 317495, 325107,340901; Natural Sciences and EngineeringResearch Council of Canada; EstonianResearch Council, Grant/Award Numbers: PSG32, PRG1167, PRG709, MOBJD29; Estonian University of Life Sciences, Grant/Award Number: P190254PKKH; European Union's Horizon 2020 Research and Innovation Programme, Grant/AwardNumber: TREICLAKE 95196

The future depends on what we do today – projecting Europe’s surface water quality into three different future scenarios

There are infinite possible future scenarios reflecting the impacts of anthropogenic multiple stress on our planet. These impacts include changes in climate and land cover, to which aquatic ecosystems are especially vulnerable. To assess plausible developments of the future state of European surface waters, we considered two climate scenarios and three storylines describing land use, management and anthropogenic development (‘Consensus’, ‘Techno’ and ‘Fragmented’, which in terms of environmental protection represent best-, intermediate- and worst-case, respectively). Three lake and four river basins were selected, representing a spectrum of European conditions through a range of different human impacts and climatic, geographical and biological characteristics. Using process-based and empirical models, freshwater total nitrogen, total phosphorus and chlorophyll-a concentrations were projected for 2030 and 2060. Under current conditions, the water bodies mostly fail good ecological status. In future predictions for the Techno and Fragmented World, concentrations further increased, while concentrations generally declined for the Consensus World. Furthermore, impacts were more severe for rivers than for lakes. Main pressures identified were nutrient inputs from agriculture, land use change, inadequately managed water abstractions and climate change effects. While the basins in the Continental and Atlantic regions were primarily affected by land use changes, in the Mediterranean/Anatolian the main driver was climate change. The Boreal basins showed combined impacts of land use and climate change and clearly reflected the climate-induced future trend of agricultural activities shifting northward. The storylines showed positive effects on ecological status by classical mitigation measures in the Consensus World (e.g. riparian shading), technical improvements in the Techno World (e.g. increasing wastewater treatment efficiency) and agricultural extensification in the Fragmented World. Results emphasize the need for implementing targeted measures to reduce anthropogenic impacts and the importance of having differing levels of ambition for improving the future status of water bodies depending on the societal future to be expected

Effects of environmental stressors and their interactions on zooplankton biomass and abundance in a large eutrophic lake

We assessed long-term impacts of multi- ple stressors and their interaction on the zooplankton community of the large, eutrophic, cyanobacteria- dominated Lake Peipsi (Estonia, Russia). Stressor dataset consisted in time series (1997–2018) of temperature, nutrients, pH, water transparency, phy- toplankton biomass and taxonomic richness. The best predictors were selected with random forests machine- learning algorithms and the subsequent models were constructed with generalized linear modeling. We also aimed to identify graphical thresholds representing non-linear, marked responses of abundance or bio- mass to stressors. Temperature was the dominant stressor for explaining zooplankton abundance and biomass, followed by cyanobacteria biomass, total nitrogen concentration and water transparency. The effect of water temperature was positive, whereas the effect of cyanobacteria became negative after their biomass exceeded a threshold of * 2 mg l-1 . How- ever, the two stressors together had antagonistic effects on zooplankton, causing a decrease in biomass and abundance. For zooplankton, critical thresholds of total nitrogen (* 700 lg l-1 ), total phosphorus (* 70 lg l-1 ), and water transparency (* 1.4 m) after which zooplankton metrics changed drastically, were determined. These findings show that although lake warming alone could be positive for zooplankton, the necessity of reducing interacting stressors that influence harmful cyanobacteria growth and biomass, especially nitrogen loads, must be considered.Funding was provided by Estonian Research Council PSG32.Funding was provided by Estonian Research Council PSG32