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Winter conditions are rapidly changing in temperate ecosystems, particularly for those that experience periods of snow and ice cover. Relatively little is known of winter ecology in these systems, due to a historical research focus on summer 'growing seasons'. We executed the first global quantitative synthesis on under-ice lake ecology, including 36 abiotic and biotic variables from 42 research groups and 101 lakes, examining seasonal differences and connections as well as how seasonal differences vary with geophysical factors. Plankton were more abundant under ice than expected; mean winter values were 43.2% of summer values for chlorophyll a, 15.8% of summer phytoplankton biovolume and 25.3% of summer zooplankton density. Dissolved nitrogen concentrations were typically higher during winter, and these differences were exaggerated in smaller lakes. Lake size also influenced winter-summer patterns for dissolved organic carbon (DOC), with higher winter DOC in smaller lakes. At coarse levels of taxonomic aggregation, phytoplankton and zooplankton community composition showed few systematic differences between seasons, although literature suggests that seasonal differences are frequently lake-specific, species-specific, or occur at the level of functional group. Within the subset of lakes that had longer time series, winter influenced the subsequent summer for some nutrient variables and zooplankton biomass.

Cyanobacteria are predicted to increase due to climate and land use change. However, the relative importance and interaction of warming temperatures and increased nutrient availability in determining cyanobacterial blooms are unknown. We investigated the contribution of these two factors in promoting phytoplankton and cyanobacterial biovolume in freshwater lakes. Specifically, we asked: (1) Which of these two drivers, temperature or nutrients, is a better predictor of cyanobacterial biovolume? (2) Do nutrients and temperature significantly interact to affect phytoplankton and cyanobacteria, and if so, is the interaction synergistic? and (3) Does the interaction between these factors explain more of the variance in cyanobacterial biovolume than each factor alone? We analyzed data from . 1000 U.S. lakes and demonstrate that in most cases, the interaction of temperature and nutrients was not synergistic; rather, nutrients predominantly controlled cyanobacterial biovolume. Interestingly, the relative importance of these two factors and their interaction was dependent on lake trophic state and cyanobacterial taxon. Nutrients played a larger role in oligotrophic lakes, while temperature was more important in mesotrophic lakes: Only eutrophic and hyper-eutrophic lakes exhibited a significant interaction between nutrients and temperature. Likewise, some taxa, such as Anabaena, were more sensitive to nutrients, while others, such as Microcystis, were more sensitive to temperature. We compared our results with an extensive literature review and found that they were generally supported by previous studies. As lakes become more eutrophic, cyanobacteria will be more sensitive to the interaction of nutrients and temperature, but ultimately nutrients are the more important predictor of cyanobacterial biovolume.

Compared to the well-studied open water of the ''growing'' season, under-ice conditions in lakes are characterized by low and rather constant temperature, slow water movements, limited light availability, and reduced exchange with the surrounding landscape. These conditions interact with ice-cover duration to shape microbial processes in temperate lakes and ultimately influence the phenology of community and ecosystem processes. We review the current knowledge on microorganisms in seasonally frozen lakes. Specifically, we highlight how under-ice conditions alter lake physics and the ways that this can affect the distribution and metabolism of auto-and heterotrophic microorganisms. We identify functional traits that we hypothesize are important for understanding under-ice dynamics and discuss how these traits influence species interactions. As ice coverage duration has already been seen to reduce as air temperatures have warmed, the dynamics of the underice microbiome are important for understanding and predicting the dynamics and functioning of seasonally frozen lakes in the near future.The quality of freshwater, which is tightly tied to many essential ecosystem services, is influenced in large part by the activities of microbial communities. In inland waters, as in other ecosystems, microorganisms are at the hub of most biogeochemical processes and largely control ecosystem functioning via their metabolic activities. However, attempts to describe the taxonomy and ecology of the freshwater microbiome mainly involve samples collected during the icefree season and, hence, largely neglect microbial communities and their activities during the ice-covered period. Knowledge about the year-round ecological and biogeochemical traits of typical freshwater microorganisms is required to understand when and where certain microorganisms will appear and how they will influence other organisms or biogeochemical processes and, hence, water quality. Together, this information will improve our ability to predict and model freshwater ecosystem and biogeochemical dynamics and to determine their role in the landscapes in the face of environmental change.A large number of lakes, particularly those situated at high altitude and the numerous high-latitude lakes in the temperate and boreal climate zones, are seasonally covered by ice for more than 40% of the year (Walsh et al. 1998). Despite this, surprisingly little is known about the ecology, diversity, and metabolism of microorganisms that reside under the ice cover in such lakes (Salonen et al. 2009). The traditional view is that ecosystems subjected to low temperatures are ''on hold'' and that cellular adaptations for survival at low temperatures control the composition of the winter microbial community, which awaits environmental conditions more conducive for growth. This traditional concept fails to recognize that the winter season affects the ecology and metabolic features of freshwater microorganisms, as well as their involvement in food webs and global biogeochemical c...

Abstract. The General Lake Model (GLM) is a one-dimensional open-source code designed to simulate the hydrodynamics of lakes, reservoirs, and wetlands. GLM was developed to support the science needs of the Global Lake Ecological Observatory Network (GLEON), a network of researchers using sensors to understand lake functioning and address questions about how lakes around the world respond to climate and land use change. The scale and diversity of lake types, locations, and sizes, and the expanding observational datasets created the need for a robust community model of lake dynamics with sufficient flexibility to accommodate a range of scientific and management questions relevant to the GLEON community. This paper summarizes the scientific basis and numerical implementation of the model algorithms, including details of sub-models that simulate surface heat exchange and ice cover dynamics, vertical mixing, and inflow–outflow dynamics. We demonstrate the suitability of the model for different lake types that vary substantially in their morphology, hydrology, and climatic conditions. GLM supports a dynamic coupling with biogeochemical and ecological modelling libraries for integrated simulations of water quality and ecosystem health, and options for integration with other environmental models are outlined. Finally, we discuss utilities for the analysis of model outputs and uncertainty assessments, model operation within a distributed cloud-computing environment, and as a tool to support the learning of network participants.

The vertical distribution of chlorophyll in stratified lakes and reservoirs frequently exhibits a maximum peak deep in the water column, referred to as the deep chlorophyll maximum (DCM). DCMs are ecologically important hot spots of primary production and nutrient cycling, and their location can determine vertical habitat gradients for primary consumers. Consequently, the drivers of DCM structure regulate many characteristics of aquatic food webs and biogeochemistry. Previous studies have identified light and thermal stratification as important drivers of summer DCM depth, but their relative importance across a broad range of lakes is not well resolved. We analyzed profiles of chlorophyll fluorescence, temperature, and light during summer stratification from 100 lakes in the Global Lake Ecological Observatory Network (GLEON) and quantified two characteristics of DCM structure: depth and thickness. While DCMs do form in oligotrophic lakes, we found that they can also form in eutrophic to dystrophic lakes. Using a random forest algorithm, we assessed the relative importance of variables associated with light attenuation vs. thermal stratification for predicting DCM structure in lakes that spanned broad gradients of morphometry and transparency. Our analyses revealed that light attenuation was a more important predictor of DCM depth than thermal stratification and that DCMs deepen with increasing lake clarity. DCM thickness was best predicted by lake size with larger lakes having thicker DCMs. Additionally, our analysis demonstrates that the relative importance of light and thermal stratification on DCM structure is not uniform across a diversity of lake types.

Managing nitrogen and phosphorus pollution of fresh water may decrease the risk of cyanobacterial blooms, even in the face of warming temperatures.

In 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.