Experimental Whole-Ecosystem Warming Enables Novel Estimation of Snow Cover and Depth Sensitivities to Temperature, and Quantification of the Snow-Albedo Feedback Effect

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Abstract

Climate change is reducing the amount, duration, and extent of snow across high-latitude ecosystems. But, in landscapes where persistent winter snow cover develops, experimental platforms to specifically investigate interactions between warming and changes in snowpack, and impacts on ecosystem processes, have been lacking. We leveraged a whole-ecosystem warming experiment in a boreal peatland forest to quantify how snow duration, depth, and fractional cover vary with warming of up to +9°C. We found that every snow-related quantity we examined declined precipitously as the amount of warming increased. The importance of deep, continuous snow cover for moderating shallow soil temperature is highlighted by an increase in soil temperature variance and the frequency of short-duration freeze-thaw cycles in the warmer plots. We used a paired-plot approach to estimate the magnitude of the snow-albedo feedback effect, and demonstrate that albedo-driven warming linked to reduced snow cover varies between December (+0.4°C increase in maximum air temperature) and March (+1.2°C increase) because of differences in insolation. Overall, results show that even modest future warming will have profound impacts on northern winters and cold-season ecosystem processes. Plot-level data from this warming experiment, and emergent relationships between warming and quantities related to snow cover and duration, could be of enormous value for testing and improving the representation of snow processes in simulation models, especially under future climate scenarios that are outside of the range of historically observed variability.

Original languageEnglish
Article numbere2023JG007833
JournalJournal of Geophysical Research: Biogeosciences
Volume129
Issue number3
DOIs
StatePublished - Mar 2024

Funding

This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research. Oak Ridge National Laboratory is managed by UT-Battelle, LLC, for the U.S. Department of Energy under contract DE-AC05-00OR22725. Support for the development and maintenance of PhenoCam network infrastructure has come from the National Science Foundation, through the Macrosystems Biology program, awards EF-1065029 and EF-1702697. The Northern Research Station of the USDA Forest Service funded the long-term research and monitoring program at the Marcell Experimental Forest and the contributions of S.D.S. to this manuscript. We thank Nina Lany (USDA Forest Service), Jeff Riggs (DOE ORNL), and Kyle Pearson (DOE ORNL) for providing access to data for this analysis, and for assistance with interpretation. Mostafa Javadian provided feedback on a draft manuscript. This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research. Oak Ridge National Laboratory is managed by UT‐Battelle, LLC, for the U.S. Department of Energy under contract DE‐AC05‐00OR22725. Support for the development and maintenance of PhenoCam network infrastructure has come from the National Science Foundation, through the Macrosystems Biology program, awards EF‐1065029 and EF‐1702697. The Northern Research Station of the USDA Forest Service funded the long‐term research and monitoring program at the Marcell Experimental Forest and the contributions of S.D.S. to this manuscript. We thank Nina Lany (USDA Forest Service), Jeff Riggs (DOE ORNL), and Kyle Pearson (DOE ORNL) for providing access to data for this analysis, and for assistance with interpretation. Mostafa Javadian provided feedback on a draft manuscript.

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