Evaluating multimodel ensemble seasonal climate forecasts on rangeland plant production in the California Annual Grassland

Authors: Schantz, Merilynn; Hardegree, Stuart; JAMES, JEREMY - California Polytechnic State University; BECCHETTI, THERESA - University Of California; ABATZOGLOU, JOHN - University Of California; HEGEWISCH, KATHERINE - University Of California; Sheley, Roger

Submitted to: Rangeland Ecology and Management
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/27/2023
Publication Date: 4/2/2023
Citation: Schantz, M., Hardegree, S.P., James, J., Becchetti, T., Abatzoglou, J., Hegewisch, K., Sheley, R.L. 2023. Evaluating multimodel ensemble seasonal climate forecasts on rangeland plant production in the California Annual Grassland. Rangeland Ecology and Management. 88:135-142. https://doi.org/10.1016/j.rama.2023.02.013.
DOI: https://doi.org/10.1016/j.rama.2023.02.013

Interpretive Summary: Annual forage production in the California Annual Grassland is highly sensitive to weather variability. Skillful seasonal climate forecasts, therefore, would greatly enhance our ability to plan and manage livestock production systems in this region. The objective of this study was to evaluate the skill of currently available seasonal climate forecasting models from the North American Multi-Model Ensemble (NMME) program. We then used these models to provide input into climate/forage-production models to establish the utility of seasonal forecasts for predicting peak-seasonal forage production. We confirmed significant climate-forecast skill across this region, and found significant forage-production forecast skill at most sites that improved as forecasts were made over the course of the growing season. Our procedural description for site-specific seasonal forecasting applications provides a step-by-step guide for assessing plant production forecasts over a wide range of agricultural and rangeland management systems. These procedures may lead to additional application development of forecast modeling in this and other managed ecosystems in the conterminous United States.

Technical Abstract: Seasonal precipitation and temperature directly affect total plant production in the California Annual Grassland (CAG). Technological advances have resulted in skillful seasonal climate forecasts that could be input into plant production models to inform stocking and other rangeland management decisions. This study presents a procedure for forecasting plant production in the CAG ecosystem to predict annual plant production for grazing, restoration, or other rangeland management practices using a combination of historical gridMET climate data and seasonal hindcasts i.e., retrospective forecasts, from the North American Multi-Model Ensemble (NMME) program. The results of this study first confirmed high forecast skill, i.e., correlations between actual and forecasted climate, throughout the growing season at all sites. We also identified skillful plant production forecasts across most of the growing season at two sites and in three of the seven forecasting months at one study site. Forecasting climate and end of year plant production across the growing season at three CAG sites allowed us to identify the places and times in the growing season when forecasting might be most helpful in informing management decisions. Integrating plant production forecasting into rangeland management practices, consequently, will likely improve rangeland management outcomes. These procedures, furthermore, provide a user guide for creating plant production forecasts for any given area of interest that is likely applicable across a wide range of agricultural and rangeland management systems.