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.
Abstract. Species' responses to seasonal environmental variation can influence trophic interactions and food web structure within an ecosystem. However, our ability to predict how species' interactions will vary spatially and temporally in response to seasonal variation unfortunately remains inadequate within most ecosystems. Fish assemblages in the Tonle Sap Lake (TSL) of Cambodia-a dynamic flood-pulse ecosystem -were studied for five years (2010-2014) using stable isotope and Bayesian statistical approaches to explore both within-and among-species isotopic niche variation associated with seasonal flooding. Roughly 600 individual fish specimens were collected during 19 sampling events within the lake. We found that fishes within the same species tended to have a broader isotopic niche during the wet season, likely reflecting assimilation of resources from either a wider range of isotopically distinct prey items or a variety of habitats, or both. Furthermore, among-species isotopic niches tended to overlap and range more broadly during the wet season, suggesting that floodplain inundation promotes exploitation of more diverse and similar resources by different species in the fish community. Our study highlights that the flood-pulse dynamic that is typical of tropical aquatic ecosystems may be an essential element supporting freshwater fish community structure and the fish diversity that underpins the TSL food web. This flow regime is currently threatened by regional dam development, which may in turn impact the natural function and structure of the fishery food web.
Nearshore (littoral) habitats of clear lakes with high water quality are increasingly experiencing unexplained proliferations of filamentous algae that grow on submerged surfaces. These filamentous algal blooms (FABs) are sometimes associated with nutrient pollution in groundwater, but complex changes in climate, nutrient transport, lake hydrodynamics, and food web structure may also facilitate this emerging threat to clear lakes. A coordinated effort among members of the public, managers, and scientists is needed to document the occurrence of FABs, to standardize methods for measuring their severity, to adapt existing data collection networks to include nearshore habitats, and to mitigate and reverse this profound structural change in lake ecosystems. Current models of lake eutrophication do not explain this littoral greening. However, a cohesive response to it is essential for protecting some of the world's most valued lakes and the flora, fauna, and ecosystem services they sustain.
Lake thermal regimes are frequently decoupled from rising air temperature trends in their watersheds because interactions among climate factors and local features affect net heat gain or loss. Although snowpack has been empirically linked to temperature and warming rates in mountain lakes, the mechanisms governing this relationship remain unclear and untested, despite predicted declines in mountain snow across the world. We quantified how snowpack and ice cover regulate lake warming in summer primarily by controlling when and how long lakes receive solar radiation, and we demonstrate the relative role of snowmelt on the lake heat budget. We contrast lake thermal responses between extremely wet and dry years and illustrate the increasing importance of other climate factors in the absence of snow. AbstractMountain lakes experience extreme interannual climate variation as well as rapidly warming air temperatures, making them ideal systems to understand lake-climate responses. Snowpack and water temperature are highly correlated in mountain lakes, but we lack a complete understanding of underlying mechanisms. Motivated by predicted declines in snowfall with future temperature increases, we investigated how surface heat fluxes and lake warming responded to variation in snowpack, ice-off, and summer weather patterns in a high elevation lake in the Sierra Nevada, California. Ice-off timing determined the phenology of lake exposure to solar radiation, and was the dominant mechanism linking snowpack to lake temperature. The relative importance of heat loss fluxes (longwave radiation, latent and sensible heat exchange) varied among wet and dry years. Declines in snowpack and ice cover in mountain systems will reduce variability in lake thermal responses and increase the responsiveness of lake warming to atmospheric forcing.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.