Seasonal grassland productivity forecast for the U.S. Great Plains using Grass‐Cast
Author
Hartman, Melannie D.Parton, William J.
Derner, Justin D.
Schulte, Darin K.
Smith, William K.
Peck, Dannele E.
Day, Ken A.
Del Grosso, Stephen J.
Lutz, Susan
Fuchs, Brian A.
Chen, Maosi
Gao, Wei
Affiliation
Univ Arizona, Sch Nat Resources & EnvironmIssue Date
2020-11-20Keywords
actual evapotranspirationadaptive management
DayCent model
decision-making
forecast
Grass-Cast
grassland production
Great Plains
NDVI
rangelands
Metadata
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WILEYCitation
Hartman, M. D., Parton, W. J., Derner, J. D., Schulte, D. K., Smith, W. K., Peck, D. E., ... & Gao, W. (2020). Seasonal grassland productivity forecast for the US Great Plains using Grass‐Cast. Ecosphere, 11(11), e03280.Journal
ECOSPHERERights
© 2020 The Authors. This is an open access article under the terms of the Creative Commons Attribution License.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.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 larger-scale 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-of-growing 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.Note
Open access journalISSN
2150-8925EISSN
2150-8925Version
Final published versionae974a485f413a2113503eed53cd6c53
10.1002/ecs2.3280
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Except where otherwise noted, this item's license is described as © 2020 The Authors. This is an open access article under the terms of the Creative Commons Attribution License.

