Submitted to: Rangeland Ecology and Management
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/3/2023
Publication Date: 2/2/2023
Citation: Schantz, M., Hardegree, S.P., James, J., Sheley, R.L., Becchetti, T. 2023. Modeling weather effects on plant production in the California Annual Grassland. Rangeland Ecology and Management. 87:177-184. https://doi.org/10.1016/j.rama.2023.01.002.
DOI: https://doi.org/10.1016/j.rama.2023.01.002

Interpretive Summary: The California Annual Grassland provides forage for livestock and wildlife, but is annual production is highly sensitive to weather variability. Our objective was to update previous weather/production models to provide a more accurate predictions of forage availability relative to seasonal climate variables. In this study, we used multivariate analysis to optimize predictions of annual grass production as a function of seasonal precipitation, temperature, degree-day accumulation, season length and prior-year precipitation and plant production. We found that previously available models that emphasized degree-day accumulation oversimplified the process of biomass production, and that separating model years into low, moderate and high precipitation increased the degree of predictive model fit. Improved production models can now be used in conjunction with seasonal climate forecasts to predict seasonal biomass growth in this ecoregion. These forecasts can be used to help producers inform stocking rate decisions, the grazing season length, and need for supplemental forage, all of which can affect the profitability of grazing systems in the California Annual Grassland.

Technical Abstract: Weather drives plant community assembly and seasonal plant production in most rangeland ecosystems. Previous models in the California Annual Grassland have indicated that plant production is largely determined by the thermal accumulation, or degree days, between the start and end of the growing season. These models, however, were relatively limited in spatial and temporal scope and did not include seasonal parameters commonly used in more current production-system models. The purpose of this study is to develop models that account for the annual and seasonal effects of weather inputs on plant production. Weather variables for these models included annual and seasonal effects of accumulated degree days, total precipitation, average temperature, season length, past year’s precipitation, and past year’s plant production. Our results indicated that sorting precipitation years into low, moderate, and high groupings resulted in better production-model fit compared to a full-suite analysis of all precipitation years. In addition, we found that precipitation, temperature, past year’s precipitation, and past plant production significantly improved model fit over models that considered only accumulated degree days and season length. Linking these models to seasonal forecasting applications across western rangeland ecosystems could significantly enhance management of grazing production systems in this environment.