An Evaluation of the Grass-Cast Seasonal Rangeland Productivity Forecast for the Southwest U.S.
Keywordsaboveground net primary productivity
DayCent ecosystem model
satellite remote sensing
AdvisorSmith, William K.
MetadataShow full item record
PublisherThe University of Arizona.
RightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction, presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
AbstractIncreasing precipitation variability and extremes driven by climate change are already having significant impacts on semi-arid rangelands of the Southwest US, with critical consequences for livestock grazing and wildlife. Monitoring and forecasting the seasonal productivity of these vulnerable agroecosystems is needed to support effective resource management and conservation efforts. The United States Department of Agriculture (USDA) Grass-Cast rangeland productivity forecast tool was recently expanded to the Southwest U.S. (hereafter termed Grass-Cast Southwest) and provides short-term seasonal forecasts of rangeland productivity for Arizona and New Mexico starting two to three months in advance of the spring (April to June) and summer (June to October) growing season with the major objective of providing early decision support for rangeland managers. Here, we present an initial assessment of the 2020 to 2022 Grass-Cast Southwest rangeland forecasts for the spring and summer growing seasons. Importantly, this time period spans multiple anomalous wet and dry seasons and thus provides an opportunity to assess model performance during climatic extremes. We found that the Grass-Cast Southwest earliest spring forecasts produced in April were very accurate for all years evaluated (R = 0.6 to 0.9 ; RMSE = 106.6 to 5.5 lb/acre). Spring forecasts are accurate since in the Southwest rangeland productivity is driven by antecedent winter precipitation and relatively predictable increases in temperatures in the spring . By contrast, the earliest summer forecasts in produced in June were much less accurate (R = -0.5 to 0.7; RMSE = 81.3 to 315.7), since in the Southwest summer rangeland productivity depends on summer precipitation from the North America Monsoon (NAM), which is much more difficult to predict. As a next step we explore the relationship between Southwest rangeland productivity and the El Nino Southern Oscillation (ENSO) and we provide evidence that ENSO indices could improve Grass-cast forecasts the both the spring and summer growing season. We find a positive relationship between Southwest ANPP and ENSOJFM (January to March) for the spring season (R2 > 0.3; p < 0.001) and a negative linear relationship between ANPP and ENSOMAM (March to May) for the summer season (R2 > 0.1; p < 0.05). The ongoing improvement and advancement of ecological models, such as Grass-Cast, can play a crucial role in promoting the conservation and sustainable use of natural resources in the Southwest.
Degree ProgramGraduate College