Faculty Mentor: Jonathan A. Wang (School of Biological Sciences, University of Utah)

As the effects of climate change intensify, it is imperative that we gain a comprehensive understanding of the intricate relationships that make up the coupled climate system. While changes in climate impact the vegetated land surface, the reverse is true as well – changes in vegetation can impact the climate system through the water, energy, and carbon cycles. Climate models are essential for understanding how these changes to the land surface cover can lead to changes in both local and remote climate. By comparing the output of climate model simulations to remotely sensed observations of vegetation dynamics, we begin to be able to characterize how vegetation is coupled to climate.

In this study, we evaluate the impact of vegetation change on surface climate. We conduct land surface model simulations forced with NEON Flux Tower data to determine the importance of vegetation cover on the local surface climate; these are compared to coupled Earth System Model simulations using the Community Earth System Model (CESM) that explore the effects of dramatic forest change over the entire Great Basin region of the Western US. While these idealized CESM simulations help us understand the physical connections between vegetation and regional climate, one of our primary goals in this project is to understand the climate effects of observed recent vegetation change. To this end, we use remote sensing-based data sets of tree and shrub cover from the Rangelands Condition, Mapping, and Analysis platform (RCMAP) and land cover type from the National Land Cover Database (NLCD) to characterize multi-decadal (2000-2021) changes in plant functional type distribution. We identify vegetation changes resulting from multiple specific processes, including changes due to wildfires, woody plant encroachment, agricultural development, and logging activities. Wildfires are identified using the Monitoring Trends in Burn Severity dataset, while other processes are identified by analyzing specific land cover change trajectories from NLCD. We then leverage these observational datasets to generate input files for CESM, allowing us to evaluate the impact of vegetation change processes on several aspects of the Earth system including carbon and water flux changes. We expect that processes reducing vegetation cover such as wildfires will lead to temporary declines in local carbon and water fluxes, while processes that increase vegetation cover such as woody plant encroachment may lead to an increase in the fluxes. These predictions provide information on the impacts of past vegetation change on climate which can be used to determine necessary policy actions to take to protect not just the Great Basin, but the broader region as well.

Bibliography

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