This data release presents input data for plot- and landscape-scale models of Prairie Pothole Region wetland methane emissions as a function of explanatory variables and remotely sensed predictors. Field data for the plot- and landscape-scale models span the years 2003-2016 and 2005-2016, respectively. The data release also includes R programming code to run the generalized additive model (GAM; plot scale) and random forest (RF; landscape scale) model of methane flux rates. Input data were extracted and modified from existing sources, and combined to facilitate model development, as well as six scenario-based model runs (two historical, four future). Briefly, a bottom-up approach was used to develop a spatially explicit, temporally dynamic model of methane emissions from Prairie Pothole Region (PPR) wetlands. A dataset of greater than 18,000 static-chamber flux measurements along with environmental covariates was used to develop a chamber-based (plot) model of methane flux, which was then used to inform a landscape-model using remotely sensed predictors. Covariates for the chamber-based model included soil water-filled pore space, soil temperature, wetland size, hydroperiod, land cover, growing season interval, and normalized difference vegetation index (NDVI). Predictors for upscaling included the Dynamic Surface Water Extent based on Landsat 4, 5, 7, and 8 for the presence, permanence, and extent of surface water, ClimateNA for historical and future temperatures, and the North American Land Change Monitoring System for land cover. Model runs included historical dry (1991) and wet (2011) years, as well as future Socioeconomic Pathways emissions scenarios (SSP2-4.5, SSP5-8.5).
|Title||Methane flux model for wetlands of the Prairie Pothole Region of North America: Model input data and programming code|
|Authors||Sheel Bansal, Brian Tangen|
|Product Type||Data Release|
|Record Source||USGS Digital Object Identifier Catalog|
|USGS Organization||Northern Prairie Wildlife Research Center|
Sheel Bansal, PhD
Sheel Bansal, PhD