Ice cover plays a critical role in physical, biogeochemical, and ecological processes in lakes. Despite its importance, winter limnology remains relatively understudied. Here, we provide a primer on the predominant drivers of freshwater lake ice cover and the current methodologies used to study lake ice, including in situ and remote sensing observations, physical based models, and experiments. We highlight opportunities for future research by integrating these four disciplines to address key knowledge gaps in our understanding of lake ice dynamics in changing winters. Advances in technology, data integration, and interdisciplinary collaboration will allow the field to move toward developing global forecasts of lake ice cover for small to large lakes across broad spatial and temporal scales, quantifying ice quality and ice thickness, moving from binary to continuous ice records, and determining how winter ice conditions and quality impact ecosystem processes in lakes over winter. Ultimately, integrating disciplines will improve our ability to understand the impacts of changing winters on lake ice.

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Lake ice depth provides important information about local and regional climate change, weather patterns, and recreational safety, as well as impacting in situ ecology and carbon cycling. However, it is challenging to measure ice depth continuously from a remote location, as existing methods are too large, expensive, and/or time-intensive. Therefore, we present a novel application that resolves size, cost, and automation issues using commercially-available soil water content reflectometer sensors from multiple manufactures. Analysis of sensors deployed in an environmental chamber using a scale model of a lake demonstrated accurate measure of the change in ice depth over any time period to within 1 cm, through sensor response of liquid-to-solid phase change. A robust correlation exists between volumetric water content in time as a function of environmental temperature and ice growth. This relationship allows us to convert volumetric water content into ice depth. An array of these sensors can be used in lake or river settings to create a temporally high-resolution ice depth record, which fills in a needed gap for ecological or climatological studies as well as increasing public recreational safety.

Climate change is expected to decrease ice coverage and thickness globally while increasing the variability of ice coverage and thickness on midlatitude lakes. Ice thickness affects physical, biological, and chemical processes as well as safety conditions for scientists and the general public. Measurements of ice thickness that are both temporally frequent and spatially extensive remain a technical challenge. Here new observational methods using repurposed soil moisture sensors that facilitate high spatial–temporal sampling of ice thickness are field tested on Lake Mendota in Wisconsin during the winter 2015/16 season. Spatial variability in ice thickness was high, with differences of 10 cm of ice column thickness over 1.05 km of horizontal distance. When observational data were compared with manual measurements and model output from both the Freshwater Lake (FLake) model and General Lake Model (GLM), ice thickness from sensors matches manual measurements, whereas GLM and FLake results showed a thinner and thicker ice layer, respectively. The FLake-modeled ice column temperature effectively remained at 0°C, not matching observations. We also show that daily ice dynamics follows the expected linear function of ice thickness growth/melt, improving confidence in sensor accuracy under field conditions. We have demonstrated a new method that allows low-cost and high-frequency measurements of ice thickness, which will be needed both to advance winter limnology and to improve on-ice safety.

Although previously overlooked, winter is now seen as a period of significant biological activity in the annual cycle of north‐temperate lakes. Research suggests a future of reduced ice cover duration and altered snow conditions could significantly change the functioning of aquatic ecosystems. This study seeks to explore the possible repercussions of changing ice and snow dynamics on aquatic biological communities, particularly at lower trophic levels. To explore plankton community responses to changing under‐ice light conditions, we performed a whole‐lake manipulation by removing all of the snow from the surface of a north temperate bog lake in northern Wisconsin. Over three winters, samples were collected under ice in the study lake, South Sparkling Bog. The first winter, 2018–2019, served as a reference year during which snow was not removed from the lake and was followed by two subsequent winters of snow removal during 2019–2020 and 2020–2021. Data collected included phytoplankton and zooplankton abundances and taxa, chlorophyll a, dissolved organic carbon, light, Secchi depth, and ice and snow thickness. In our snow removal years, increased light availability in the water column shifted the phytoplankton community from low‐biomass, mixed community of potential mixotrophs, unicellular cyanobacteria and Chlorophytes to dominance by photoautotrophs, and rotifer zooplankton densities increased. Ice condition, specifically the thickness of white ice vs. black ice, was a major driver in the magnitude of change between years. This research improves our understanding of how plankton communities might respond to climate‐change driven shifts in winter dynamics for north temperate systems.