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Ice phenology has shifted with anthropogenic warming such that many lakes are experiencing a shorter ice season. However, changes to ice quality — the ratio of black and white ice layers — remain little explored, despite relevance to lake physics, ecological function, human recreation and transportation. In this Review, we outline how ice quality is changing and discuss knock-on ecosystem service impacts. Although direct evidence is sparse, there are suggestions that ice quality is diminishing across the Northern Hemisphere, encompassing declining ice thickness, decreasing black ice and increasing white ice. These changes are projected to continue in the future, scaling with global temperature increases, and driving considerable impacts to related ecosystem services. Rising proportions of white ice will markedly reduce bearing strength, implying more dangerous conditions for transportation (limiting operational use of many winter roads) and recreation (increasing the risk of fatal spring-time drownings). Shifts from black to white ice conditions will further reduce the amount of light reaching the water column, minimizing primary production, and altering community composition to favour motile and mixotrophic species; these changes will affect higher trophic levels, including diminished food quantity for zooplankton and fish, with potential developmental consequences. Reliable and translatable in situ sampling methods to assess and predict spatiotemporal variations in ice quality are urgently needed. 

Abstract Dissolved organic matter (DOM), often measured as dissolved organic carbon (DOC), plays a fundamental role in influencing the structure and function of lake ecosystems. Due to the myriad ecosystem effects of DOM, widespread observations of long‐term increasing DOM concentrations have received much attention from ecologists. DOM positively influences primary production and consumer production at low concentrations due to the fertilising influence of bound nutrients. However, beyond a unimodal peak in production, a reduced light environment may result in a negative effect on production. This unimodal model has been largely developed and tested in lakes with low to moderate DOM concentrations (i.e., typically ≤10 mg/L DOC).To understand ecological responses in lakes across a larger range in DOM concentrations, we examined the response of benthic invertebrate communities in 148 Swedish lakes with DOM concentrations ranging between 0.67 and 32.77 mg/L DOC.We found that increasing DOM concentrations had a strong effect on invertebrate community composition belowc.10 mg/L. Across this range, abundances of individual taxa both increased and decreased, probably in response to environmental change induced by DOM. However, in lakes above this concentration, increasing DOM had minimal influence on community composition.As DOM concentrations continue to increase, faunal communities in lakes below this 10 mg/L DOC threshold are likely to undergo substantial change whereas those above this threshold are likely to be minimally impacted. 

Abstract Climate change is contributing to rapid changes in lake ice cover across the Northern Hemisphere, thereby impacting local communities and ecosystems. Using lake ice cover time‐series spanning over 87 yr for 43 lakes across the Northern Hemisphere, we found that the interannual variability in ice duration, measured as standard deviation, significantly increased in only half of our studied lakes. We observed that the interannual variability in ice duration peaked when lakes were, on average, covered by ice for about 1 month, while both longer and shorter long‐term mean ice cover duration resulted in lower interannual variability in ice duration. These results demonstrate that the ice cover duration can become so short that the interannual variability rapidly declines. The interannual variability in ice duration showed a strong dependency on global temperature anomalies and teleconnections, such as the North Atlantic Oscillation and El Niño–Southern Oscillation. We conclude that many lakes across the Northern Hemisphere will experience a decline in interannual ice cover variability and shift to open water during the winter under a continued global warming trend which will affect lake biological, cultural, and economic processes. 

Abstract The rate of technological innovation within aquatic sciences outpaces the collective ability of individual scientists within the field to make appropriate use of those technologies. The process of in situ lake sampling remains the primary choice to comprehensively understand an aquatic ecosystem at local scales; however, the impact of climate change on lakes necessitates the rapid advancement of understanding and the incorporation of lakes on both landscape and global scales. Three fields driving innovation within winter limnology that we address here are autonomous real‐time in situ monitoring, remote sensing, and modeling. The recent progress in low‐power in situ sensing and data telemetry allows continuous tracing of under‐ice processes in selected lakes as well as the development of global lake observational networks. Remote sensing offers consistent monitoring of numerous systems, allowing limnologists to ask certain questions across large scales. Models are advancing and historically come in different types (process‐based or statistical data‐driven), with the recent technological advancements and integration of machine learning and hybrid process‐based/statistical models. Lake ice modeling enhances our understanding of lake dynamics and allows for projections under future climate warming scenarios. To encourage the merging of technological innovation within limnological research of the less‐studied winter period, we have accumulated both essential details on the history and uses of contemporary sampling, remote sensing, and modeling techniques. We crafted 100 questions in the field of winter limnology that aim to facilitate the cross‐pollination of intensive and extensive modes of study to broaden knowledge of the winter period. 

Climate change is reducing winter ice cover on lakes; yet, the full societal and environmental consequences of this ice loss are poorly understood. The socioeconomic implications of declining ice include diminished access to ice-based cultural activities, safety concerns in traversing ice, changes in fisheries, increases in shoreline erosion, and declines in water storage. Longer ice-free seasons allow more time and capacity for water to warm, threatening water quality and biodiversity. Food webs likely will reorganize, with constrained availability of ice-associated and cold-water niches, and ice loss will affect the nature, magnitude, and timing of greenhouse gas emissions. Examining these rapidly emerging changes will generate more-complete models of lake dynamics, and transdisciplinary collaborations will facilitate translation to effective management and sustainability. 

Abstract Understanding controls on primary productivity is essential for describing ecosystems and their responses to environmental change. In lakes, pelagic gross primary productivity (GPP) is strongly controlled by inputs of nutrients and dissolved organic matter. Although past studies have developed process models of this nutrient‐color paradigm (NCP), broad empirical tests of these models are scarce. We used data from 58 globally distributed, mostly temperate lakes to test such a model and improve understanding and prediction of the controls on lake primary production. The model includes three state variables–dissolved phosphorus, terrestrial dissolved organic carbon (DOC), and phytoplankton biomass–and generates realistic predictions for equilibrium rates of pelagic GPP. We calibrated our model using a Bayesian data assimilation technique on a subset of lakes where DOC and total phosphorus (TP) loads were known. We then asked how well the calibrated model performed with a larger set of lakes. Revised parameter estimates from the updated model aligned well with existing literature values. Observed GPP varied nonlinearly with both inflow DOC and TP concentrations in a manner consistent with increasing light limitation as DOC inputs increased and decreasing nutrient limitation as TP inputs increased. Furthermore, across these diverse lake ecosystems, model predictions of GPP were highly correlated with observed values derived from high‐frequency sensor data. The GPP predictions using the updated parameters improved upon previous estimates, expanding the utility of a process model with simplified assumptions for water column mixing. Our analysis provides a model structure that may be broadly useful for understanding current and future patterns in lake primary production. 

Abstract Declining oxygen concentrations in the deep waters of lakes worldwide pose a pressing environmental and societal challenge. Existing theory suggests that low deep‐water dissolved oxygen (DO) concentrations could trigger a positive feedback through which anoxia (i.e., very low DO) during a given summer begets increasingly severe occurrences of anoxia in following summers. Specifically, anoxic conditions can promote nutrient release from sediments, thereby stimulating phytoplankton growth, and subsequent phytoplankton decomposition can fuel heterotrophic respiration, resulting in increased spatial extent and duration of anoxia. However, while the individual relationships in this feedback are well established, to our knowledge, there has not been a systematic analysis within or across lakes that simultaneously demonstrates all of the mechanisms necessary to produce a positive feedback that reinforces anoxia. Here, we compiled data from 656 widespread temperate lakes and reservoirs to analyze the proposed anoxia begets anoxia feedback. Lakes in the dataset span a broad range of surface area (1–126,909 ha), maximum depth (6–370 m), and morphometry, with a median time‐series duration of 30 years at each lake. Using linear mixed models, we found support for each of the positive feedback relationships between anoxia, phosphorus concentrations, chlorophyllaconcentrations, and oxygen demand across the 656‐lake dataset. Likewise, we found further support for these relationships by analyzing time‐series data from individual lakes. Our results indicate that the strength of these feedback relationships may vary with lake‐specific characteristics: For example, we found that surface phosphorus concentrations were more positively associated with chlorophyllain high‐phosphorus lakes, and oxygen demand had a stronger influence on the extent of anoxia in deep lakes. Taken together, these results support the existence of a positive feedback that could magnify the effects of climate change and other anthropogenic pressures driving the development of anoxia in lakes around the world. 

Understanding controls on primary productivity is essential for describing ecosystems and their responses to environmental change. Lake primary production is strongly controlled by inputs of nutrients and colored dissolved organic matter. While past studies have developed mathematical models of this nutrient-color paradigm, broad empirical tests of these models are scarce. We compiled data from 58 diverse and globally distributed and mostly temperate lakes to test such a model and improve understanding and prediction of the controls on lake primary production. These lakes varied widely in size (0.02-2300 km2), pelagic gross primary production (20-8000 mg C m-2 d-1), and other characteristics. The data package includes high-frequency dissolved oxygen, water temperature, wind speed, and solar radiation data as well as daily estimates of GPP and ER derived from those data. In addition, the data package includes median in-lake and stream concentrations of dissolved organic carbon and total phosphorus for a subset of 18 of those lakes.