Seasonal grassland productivity forecast for the U.S. Great Plains using Grass-Cast

Authors

Melannie D. Hartman, Colorado State University - Fort CollinsFollow
William J. Parton, Colorado State University - Fort CollinsFollow
Justin D. Derner, USDA ARS, Cheyenne, WYFollow
Darin K. Schulte, Colorado State University - Fort CollinsFollow
William K. Smith, University of ArizonaFollow
Dannele E. Peck, USDA Northern Plains Climate Hub, Fort CollinsFollow
Ken A. Day, Department of Environment and Science, BrisbaneFollow
Stephen J. Del Grosso, USDA ARS, Fort Collins, COFollow
Susan Lutz, Colorado State University - Fort CollinsFollow
Brian Fuchs, National Drought Mitigation CenterFollow
Maosi Chen, Colorado State University - Fort CollinsFollow
Wei Gao, USDA Natural Resource Ecology Laboratory, Fort Collins, COFollow

ORCID IDs

MELANNIE D. HARTMAN https://orcid.org/0000-0002-0675-2292

JUSTIN D. DERNER https://orcid.org/0000-0001-8076-0736

DARIN K. SCHULTE https://orcid.org/0000-0001-8564-6473

WILLIAM K. SMITH https://orcid.org/0000-0002-5785-6489

DANNELE E. PECK https://orcid.org/0000-0001-5464-8097

KEN A. DAY https://orcid.org/0000-0003-0089-1141

MAOSI CHEN https://orcid.org/0000-0002-2718-5477

Document Type

Article

Date of this Version

11-2020

Citation

Hartman, M. D., W. J. Parton, J. D. Derner, D. K. Schulte, W. K. Smith, D. E. Peck, K. A. Day, S. J. Del Grosso, S. Lutz, B. A. Fuchs, M. Chen, and W. Gao. 2020. Seasonal grassland productivity forecast for the U.S. Great Plains using Grass-Cast. Ecosphere 11(11):e03280.

doi:10.1002/ecs2.3280

Comments

Copyright: © 2020 The Authors. This is an open access article under the terms of the Creative Commons Attribution License,

Abstract

Every spring, ranchers in the drought-prone U.S. Great Plains face the same difficult challenge —trying to estimate how much forage will be available for livestock to graze during the upcoming summer grazing season. To reduce this uncertainty in predicting forage availability, we developed an innovative new grassland productivity forecast system, named Grass-Cast, to provide science-informed estimates of growing season aboveground net primary production (ANPP). Grass-Cast uses over 30 yr of historical data including weather and the satellite-derived normalized vegetation difference index (NDVI)—combined with ecosystem modeling and seasonal precipitation forecasts—to predict if rangelands in individual counties are likely to produce below-normal, near-normal, or above-normal amounts of grass biomass (lbs/ac). Grass-Cast also provides a view of rangeland productivity in the broader region, to assist in largerscale decision-making—such as where forage resources for grazing might be more plentiful if a rancher’s own region is at risk of drought. Grass-Cast is updated approximately every two weeks from April through July. Each Grass-Cast forecast provides three scenarios of ANPP for the upcoming growing season based on different precipitation outlooks. Near real-time 8-d NDVI can be used to supplement Grass-Cast in predicting cumulative growing season NDVI and ANPP starting in mid-April for the Southern Great Plains and mid-May to early June for the Central and Northern Great Plains. Here, we present the scientific basis and methods for Grass-Cast along with the county-level production forecasts from 2017 and 2018 for ten states in the U.S. Great Plains. The correlation between early growing season forecasts and the end-ofgrowing season ANPP estimate is >50% by late May or early June. In a retrospective evaluation, we compared Grass-Cast end-of-growing season ANPP results to an independent dataset and found that the two agreed 69% of the time over a 20-yr period. Although some predictive tools exist for forecasting upcoming growing season conditions, none predict actual productivity for the entire Great Plains. The Grass-Cast system could be adapted to predict grassland ANPP outside of the Great Plains or to predict perennial biofuel grass production.