• Energy Research

Fishes in northern latitude lakes are at risk from climate-induced warming because the seasonality in water temperature is degrading, which can change ecosystem properties and the phenology of life-history events. Temperature-dependent embryo development models were developed for a group of cold, stenothermic fishes (Salmonidae Coregoninae) to assess the potential impacts of climate-induced changes in water temperature on cisco (Coregonus artedi) from two populations in Lake Superior (Apostle Islands [USA] and Thunder Bay [Canada]) and one in Lake Ontario (USA), vendace (C.albula) in Lake Southern Konnevesi (Finland), and European whitefish (C. lavaretus) in lakes Southern Konnevesi, Constance (Germany), Geneva (France), and Annecy (France). Water temperatures for each study group were simulated and changes in reproductive phenology across historic (1900–2006) and three future climatic-warming scenarios (2007–2099) were investigated. Models predicted that increases in water temperatures are likely to cause delayed spawning, shorter embryo incubation durations, and earlier larval hatching. Relative changes increased as warming scenarios increased in severity and were higher for littoral as compared to pelagic populations. Our simulations demonstrated that slower cooling in the autumn and (or) more rapid warming in spring can translate into substantial changes in the reproductive phenology of coregonines among our study groups. We expect that the changes in reproductive phenology predicted by our models, in the absence of thermal or behavioral adaptation, will have negative implications for population sustainability.

In this study, we report on the ability of four one‐dimensional lake models to simulate the water temperature profiles of Lake Geneva, the largest water body in Western Europe, over a 10‐yr period from 1996 to 2005, using lake models driven by a common atmospheric forcing. These lake models have already demonstrated their capability of reproducing the temperature distribution in smaller lakes and include one eddy‐diffusive lake model, the Hostetler model; a Lagrangian model, the one‐dimensional Dynamic Reservoir Simulation Model "DYRESM" a к ‐ ε turbulence model, "SIMSTRAT"; and one based on the concept of self‐similarity (assumed shape) of the temperature‐depth curve, the Freshwater Lake model "FLake." Only DYRESM and SIMSTRAT reproduce the variability of the water temperature profiles and seasonal thermocline satisfactorily. In layers in which thermocline variability is greatest, the temperature root mean square error is ≪2°C and 3°C (at the time of highest stratification) for these models, respectively. It is possible to apply certain one‐dimensional lake models that simulate the behavior of temperature to investigate the potential future warming of the water column in Lake Geneva. Importantly, the metalimnion boundary is successfully modeled, which represents an encouraging step toward demonstrating the feasibility of coupling biogeochemical modules, such as, for example, a phytoplanktonic model, to assess the possible biological responses within lakes to climate change.

AbstractUnderstanding how ecosystems will respond to climate changes requires unravelling the network of functional responses and feedbacks among biodiversity, physicochemical environments, and productivity. These ecosystem components not only change over time but also interact with each other. Therefore, investigation of individual relationships may give limited insights into their interdependencies and limit ability to predict future ecosystem states. We address this problem by analyzing long‐term (16–39 years) time series data from 10 aquatic ecosystems and using convergent cross mapping (CCM) to quantify the causal networks linking phytoplankton species richness, biomass, and physicochemical factors. We determined that individual quantities (e.g., total species richness or nutrients) were not significant predictors of ecosystem stability (quantified as long‐term fluctuation of phytoplankton biomass); rather, the integrated causal pathway in the ecosystem network, composed of the interactions among species richness, nutrient cycling, and phytoplankton biomass, was the best predictor of stability. Furthermore, systems that experienced stronger warming over time had both weakened causal interactions and larger fluctuations. Thus, rather than thinking in terms of separate factors, a more holistic network view, that causally links species richness and the other ecosystem components, is required to understand and predict climate impacts on the temporal stability of aquatic ecosystems.

AbstractThe intensity and frequency of storms are projected to increase in many regions of the world because of climate change. Storms can alter environmental conditions in many ecosystems. In lakes and reservoirs, storms can reduce epilimnetic temperatures from wind‐induced mixing with colder hypolimnetic waters, direct precipitation to the lake's surface, and watershed runoff. We analyzed 18 long‐term and high‐frequency lake datasets from 11 countries to assess the magnitude of wind‐ vs. rainstorm‐induced changes in epilimnetic temperature. We found small day‐to‐day epilimnetic temperature decreases in response to strong wind and heavy rain during stratified conditions. Day‐to‐day epilimnetic temperature decreased, on average, by 0.28°C during the strongest windstorms (storm mean daily wind speed among lakes: 6.7 ± 2.7 m s−1, 1 SD) and by 0.15°C after the heaviest rainstorms (storm mean daily rainfall: 21.3 ± 9.0 mm). The largest decreases in epilimnetic temperature were observed ≥2 d after sustained strong wind or heavy rain (top 5th percentile of wind and rain events for each lake) in shallow and medium‐depth lakes. The smallest decreases occurred in deep lakes. Epilimnetic temperature change from windstorms, but not rainstorms, was negatively correlated with maximum lake depth. However, even the largest storm‐induced mean epilimnetic temperature decreases were typically <2°C. Day‐to‐day temperature change, in the absence of storms, often exceeded storm‐induced temperature changes. Because storm‐induced temperature changes to lake surface waters were minimal, changes in other limnological variables (e.g., nutrient concentrations or light) from storms may have larger impacts on biological communities than temperature changes.

AbstractIn many regions across the globe, extreme weather events such as storms have increased in frequency, intensity, and duration due to climate change. Ecological theory predicts that such extreme events should have large impacts on ecosystem structure and function. High winds and precipitation associated with storms can affect lakes via short‐term runoff events from watersheds and physical mixing of the water column. In addition, lakes connected to rivers and streams will also experience flushing due to high flow rates. Although we have a well‐developed understanding of how wind and precipitation events can alter lake physical processes and some aspects of biogeochemical cycling, our mechanistic understanding of the emergent responses of phytoplankton communities is poor. Here we provide a comprehensive synthesis that identifies how storms interact with lake and watershed attributes and their antecedent conditions to generate changes in lake physical and chemical environments. Such changes can restructure phytoplankton communities and their dynamics, as well as result in altered ecological function (e.g., carbon, nutrient and energy cycling) in the short‐ and long‐term. We summarize the current understanding of storm‐induced phytoplankton dynamics, identify knowledge gaps with a systematic review of the literature, and suggest future research directions across a gradient of lake types and environmental conditions.