Seasonal grassland productivity forecast for the U.S. Great Plains using Grass‐Cast
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 innovat...
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creator | 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 |
description | 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. |
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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.</description><identifier>ISSN: 2150-8925</identifier><identifier>EISSN: 2150-8925</identifier><identifier>DOI: 10.1002/ecs2.3280</identifier><language>eng</language><publisher>Washington: John Wiley & Sons, Inc</publisher><subject>actual evapotranspiration ; adaptive management ; Archives & records ; Biofuels ; Biomass ; DayCent model ; decision-making ; Drought ; Environmental risk ; ENVIRONMENTAL SCIENCES ; Estimates ; forecast ; Grass-Cast ; Grasses ; grassland production ; Grasslands ; Grazing ; Great Plains ; Growth models ; Historical account ; Livestock ; NDVI ; Precipitation ; Primary production ; Probability ; Productivity ; Rangelands ; Remote sensing ; Seasons ; Vegetation ; Weather forecasting</subject><ispartof>Ecosphere (Washington, D.C), 2020-11, Vol.11 (11), p.n/a</ispartof><rights>2020 The Authors.</rights><rights>2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). 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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. 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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</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3590-48c0719565867f728c6985161473170083561653c6af0162caa515a317d7db6c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>actual evapotranspiration</topic><topic>adaptive management</topic><topic>Archives & records</topic><topic>Biofuels</topic><topic>Biomass</topic><topic>DayCent model</topic><topic>decision-making</topic><topic>Drought</topic><topic>Environmental risk</topic><topic>ENVIRONMENTAL SCIENCES</topic><topic>Estimates</topic><topic>forecast</topic><topic>Grass-Cast</topic><topic>Grasses</topic><topic>grassland production</topic><topic>Grasslands</topic><topic>Grazing</topic><topic>Great Plains</topic><topic>Growth models</topic><topic>Historical account</topic><topic>Livestock</topic><topic>NDVI</topic><topic>Precipitation</topic><topic>Primary production</topic><topic>Probability</topic><topic>Productivity</topic><topic>Rangelands</topic><topic>Remote sensing</topic><topic>Seasons</topic><topic>Vegetation</topic><topic>Weather forecasting</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hartman, Melannie D.</creatorcontrib><creatorcontrib>Parton, William J.</creatorcontrib><creatorcontrib>Derner, Justin D.</creatorcontrib><creatorcontrib>Schulte, Darin K.</creatorcontrib><creatorcontrib>Smith, William K.</creatorcontrib><creatorcontrib>Peck, Dannele E.</creatorcontrib><creatorcontrib>Day, Ken A.</creatorcontrib><creatorcontrib>Del Grosso, Stephen J.</creatorcontrib><creatorcontrib>Lutz, Susan</creatorcontrib><creatorcontrib>Fuchs, Brian A.</creatorcontrib><creatorcontrib>Chen, Maosi</creatorcontrib><creatorcontrib>Gao, Wei</creatorcontrib><creatorcontrib>Center for Advanced Bioenergy and Bioproducts Innovation (CABBI), Urbana, IL (United States)</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>Wiley Online Library (Open Access Collection)</collection><collection>CrossRef</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>OSTI.GOV - Hybrid</collection><collection>OSTI.GOV</collection><jtitle>Ecosphere (Washington, D.C)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hartman, Melannie D.</au><au>Parton, William J.</au><au>Derner, Justin D.</au><au>Schulte, Darin K.</au><au>Smith, William K.</au><au>Peck, Dannele E.</au><au>Day, Ken A.</au><au>Del Grosso, Stephen J.</au><au>Lutz, Susan</au><au>Fuchs, Brian A.</au><au>Chen, Maosi</au><au>Gao, Wei</au><aucorp>Center for Advanced Bioenergy and Bioproducts Innovation (CABBI), Urbana, IL (United States)</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Seasonal grassland productivity forecast for the U.S. Great Plains using Grass‐Cast</atitle><jtitle>Ecosphere (Washington, D.C)</jtitle><date>2020-11</date><risdate>2020</risdate><volume>11</volume><issue>11</issue><epage>n/a</epage><issn>2150-8925</issn><eissn>2150-8925</eissn><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. 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subjects | actual evapotranspiration adaptive management Archives & records Biofuels Biomass DayCent model decision-making Drought Environmental risk ENVIRONMENTAL SCIENCES Estimates forecast Grass-Cast Grasses grassland production Grasslands Grazing Great Plains Growth models Historical account Livestock NDVI Precipitation Primary production Probability Productivity Rangelands Remote sensing Seasons Vegetation Weather forecasting |
title | Seasonal grassland productivity forecast for the U.S. Great Plains using Grass‐Cast |
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