Location: Range Management ResearchTitle: Using state-and-transition models to evaluate impacts of land cover change on wind erosion Author
|Webb, Nicholas - New Mexico State University|
|Bleiweiss, Max - New Mexico State University|
|Winters, Craig - Non ARS Employee|
|Ayers, Eldon - New Mexico State University|
|Herrick, Jeffrey - Jeff|
Submitted to: Society for Range Management Meeting Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 1/28/2017
Publication Date: 1/29/2017
Citation: Webb, N., Galloza, M.S., Bleiweiss, M., Winters, C., Ayers, E., Herrick, J.E. 2017. Using state-and-transition models to evaluate impacts of land cover change on wind erosion [abstract]. Society for Range Management. Jan 29-Feb 02, 2017, St. George, Utah.
Technical Abstract: Wind erosion of rangeland soils is a global problem exacerbated by land cover change. Despite efforts to quantify the impacts of land cover change on wind erosion, assessment uncertainty remains large. We address this uncertainty by evaluating the application of ecological sites and state-and-transition models for detecting and describing the impacts of land cover change on wind erosion. We couple a geodatabase of ecological site information with atmospheric data from the Weather Research and Forecasting (WRF) model to run a dust emission model at 1 km spatial resolution over a study area in the northern Chihuahuan Desert, New Mexico, USA. We evaluate spatiotemporal patterns of modelled horizontal sediment mass flux and dust emission in the context of ecological sites and their states; representing a diversity of land cover types. Our results demonstrate how the impacts of land cover change on wind erosion can be quantified, compared across land cover classes, and interpreted in the context of an ecological model that encapsulates land management intensity and change. Results also reveal weaknesses in the dust emission model’s soil characterisation and drag partition scheme, which were largely insensitive to the impacts of land cover change. New models that address these weaknesses, coupled with the ecological site framework and field measurements across land cover types, could significantly reduce assessment uncertainties and provide opportunities for identifying land management options.