Monitoring Climate Impacts on Annual Forage Production across U.S. Semi-Arid Grasslands
The ecosystem performance approach, used in a previously published case study focusing on the Nebraska Sandhills, proved to minimize impacts of non-climatic factors (e.g., overgrazing, fire, pests) on the remotely-sensed signal of seasonal vegetation greenness resulting in a better attribution of it...
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MDPI AG
2021-12-01
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Online Access: | https://www.mdpi.com/2072-4292/14/1/4 |
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author | Markéta Poděbradská Bruce K. Wylie Deborah J. Bathke Yared A. Bayissa Devendra Dahal Justin D. Derner Philip A. Fay Michael J. Hayes Walter H. Schacht Jerry D. Volesky Pradeep Wagle Brian D. Wardlow |
author_facet | Markéta Poděbradská Bruce K. Wylie Deborah J. Bathke Yared A. Bayissa Devendra Dahal Justin D. Derner Philip A. Fay Michael J. Hayes Walter H. Schacht Jerry D. Volesky Pradeep Wagle Brian D. Wardlow |
author_sort | Markéta Poděbradská |
collection | DOAJ |
description | The ecosystem performance approach, used in a previously published case study focusing on the Nebraska Sandhills, proved to minimize impacts of non-climatic factors (e.g., overgrazing, fire, pests) on the remotely-sensed signal of seasonal vegetation greenness resulting in a better attribution of its changes to climate variability. The current study validates the applicability of this approach for assessment of seasonal and interannual climate impacts on forage production in the western United States semi-arid grasslands. Using a piecewise regression tree model, we developed the Expected Ecosystem Performance (EEP), a proxy for annual forage production that reflects climatic influences while minimizing impacts of management and disturbances. The EEP model establishes relations between seasonal climate, site-specific growth potential, and long-term growth variability to capture changes in the growing season greenness measured via a time-integrated Normalized Difference Vegetation Index (NDVI) observed using a Moderate Resolution Imaging Spectroradiometer (MODIS). The resulting 19 years of EEP were converted to expected biomass (EB, kg ha<sup>−1</sup> year<sup>−1</sup>) using a newly-developed relation with the Soil Survey Geographic Database range production data (R<sup>2</sup> = 0.7). Results were compared to ground-observed biomass datasets collected by the U.S. Department of Agriculture and University of Nebraska-Lincoln (R<sup>2</sup> = 0.67). This study illustrated that this approach is transferable to other semi-arid and arid grasslands and can be used for creating timely, post-season forage production assessments. When combined with seasonal climate predictions, it can provide within-season estimates of annual forage production that can serve as a basis for more informed adaptive decision making by livestock producers and land managers. |
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issn | 2072-4292 |
language | English |
last_indexed | 2024-03-10T03:24:37Z |
publishDate | 2021-12-01 |
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spelling | doaj.art-f8fcb12e932f49589e76d96112287fab2023-11-23T12:11:39ZengMDPI AGRemote Sensing2072-42922021-12-01141410.3390/rs14010004Monitoring Climate Impacts on Annual Forage Production across U.S. Semi-Arid GrasslandsMarkéta Poděbradská0Bruce K. Wylie1Deborah J. Bathke2Yared A. Bayissa3Devendra Dahal4Justin D. Derner5Philip A. Fay6Michael J. Hayes7Walter H. Schacht8Jerry D. Volesky9Pradeep Wagle10Brian D. Wardlow11School of Natural Resources, University of Nebraska-Lincoln, 811 Hardin Hall, 3310 Holdrege Street, Lincoln, NE 68583, USARetired from U.S. Geological Survey (USGS), Earth Resources Observation and Science (EROS) Center, 47914 252nd Street, Sioux Falls, SD 57198, USASchool of Natural Resources, University of Nebraska-Lincoln, 811 Hardin Hall, 3310 Holdrege Street, Lincoln, NE 68583, USADepartment of Ecology and Conservation Biology, Texas A&M University, College Station, TX 77843, USAKBR, Contractor to the U.S. Geological Survey, Earth Resources and Observation Science Center, Sioux Falls, SD 57198, USAUSDA, Agricultural Research Service, Rangeland Resources and Systems Research Unit, Cheyenne, WY 82009, USAUSDA, Agricultural Research Service, Grassland, Soil and Water Research Laboratory, Temple, TX 76502, USASchool of Natural Resources, University of Nebraska-Lincoln, 811 Hardin Hall, 3310 Holdrege Street, Lincoln, NE 68583, USAAgronomy and Horticulture Department, University of Nebraska-Lincoln, 202 Keim Hall, Lincoln, NE 68583, USAAgronomy and Horticulture Department, West Central Research and Extension Center, University of Nebraska-Lincoln, 402 West State Farm Rd, North Platte, NE 69101, USAUSDA, Agricultural Research Service, Grazinglands Research Laboratory, El Reno, OK 73036, USASchool of Natural Resources, University of Nebraska-Lincoln, 811 Hardin Hall, 3310 Holdrege Street, Lincoln, NE 68583, USAThe ecosystem performance approach, used in a previously published case study focusing on the Nebraska Sandhills, proved to minimize impacts of non-climatic factors (e.g., overgrazing, fire, pests) on the remotely-sensed signal of seasonal vegetation greenness resulting in a better attribution of its changes to climate variability. The current study validates the applicability of this approach for assessment of seasonal and interannual climate impacts on forage production in the western United States semi-arid grasslands. Using a piecewise regression tree model, we developed the Expected Ecosystem Performance (EEP), a proxy for annual forage production that reflects climatic influences while minimizing impacts of management and disturbances. The EEP model establishes relations between seasonal climate, site-specific growth potential, and long-term growth variability to capture changes in the growing season greenness measured via a time-integrated Normalized Difference Vegetation Index (NDVI) observed using a Moderate Resolution Imaging Spectroradiometer (MODIS). The resulting 19 years of EEP were converted to expected biomass (EB, kg ha<sup>−1</sup> year<sup>−1</sup>) using a newly-developed relation with the Soil Survey Geographic Database range production data (R<sup>2</sup> = 0.7). Results were compared to ground-observed biomass datasets collected by the U.S. Department of Agriculture and University of Nebraska-Lincoln (R<sup>2</sup> = 0.67). This study illustrated that this approach is transferable to other semi-arid and arid grasslands and can be used for creating timely, post-season forage production assessments. When combined with seasonal climate predictions, it can provide within-season estimates of annual forage production that can serve as a basis for more informed adaptive decision making by livestock producers and land managers.https://www.mdpi.com/2072-4292/14/1/4droughtecosystem performanceforage productionMODISNDVIregression tree model |
spellingShingle | Markéta Poděbradská Bruce K. Wylie Deborah J. Bathke Yared A. Bayissa Devendra Dahal Justin D. Derner Philip A. Fay Michael J. Hayes Walter H. Schacht Jerry D. Volesky Pradeep Wagle Brian D. Wardlow Monitoring Climate Impacts on Annual Forage Production across U.S. Semi-Arid Grasslands Remote Sensing drought ecosystem performance forage production MODIS NDVI regression tree model |
title | Monitoring Climate Impacts on Annual Forage Production across U.S. Semi-Arid Grasslands |
title_full | Monitoring Climate Impacts on Annual Forage Production across U.S. Semi-Arid Grasslands |
title_fullStr | Monitoring Climate Impacts on Annual Forage Production across U.S. Semi-Arid Grasslands |
title_full_unstemmed | Monitoring Climate Impacts on Annual Forage Production across U.S. Semi-Arid Grasslands |
title_short | Monitoring Climate Impacts on Annual Forage Production across U.S. Semi-Arid Grasslands |
title_sort | monitoring climate impacts on annual forage production across u s semi arid grasslands |
topic | drought ecosystem performance forage production MODIS NDVI regression tree model |
url | https://www.mdpi.com/2072-4292/14/1/4 |
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