Using seasonal climate scenarios in the ForageAhead annual forage production model for early drought impact assessment
Abstract High interannual variability of forage production in semiarid grasslands leads to uncertainties when livestock producers make decisions, such as buying additional feed, relocating animals, or using flexible stocking. Within‐season predictions of annual forage production (i.e., yearly produc...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-05-01
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| Series: | Ecosphere |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/ecs2.4496 |
| _version_ | 1827939089476747264 |
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| author | Markéta Poděbradská Bruce K. Wylie Michael J. Hayes Deborah J. Bathke Yared A. Bayissa Stephen P. Boyte Jesslyn F. Brown Brian D. Wardlow |
| author_facet | Markéta Poděbradská Bruce K. Wylie Michael J. Hayes Deborah J. Bathke Yared A. Bayissa Stephen P. Boyte Jesslyn F. Brown Brian D. Wardlow |
| author_sort | Markéta Poděbradská |
| collection | DOAJ |
| description | Abstract High interannual variability of forage production in semiarid grasslands leads to uncertainties when livestock producers make decisions, such as buying additional feed, relocating animals, or using flexible stocking. Within‐season predictions of annual forage production (i.e., yearly production) can provide specific boundaries for producers to make these decisions with more information and possibly with higher confidence. In this study, we use a recently developed forage production model, ForageAhead, that uses environmental and seasonal climate variables to estimate the annual forage production as approximated by remotely sensed vegetation data. Because, among other variables, this model uses observed summer climate data, the model output cannot be produced early enough in the year (e.g., spring months) to inform within‐season management decisions. To address this issue, we developed summer climate scenarios (e.g., extremely warm and dry and moderately cool and wet) that serve as an input in the model in combination with observed winter and spring climate data from a particular year. The summer climate scenarios used historical summer precipitation and temperature data (1950–2018) categorized into three, five, and seven percentile categories. These percentile values were then combined to represent summer climate scenarios, which were further used as the ForageAhead model input. We tested the optimal number of percentile categories to be used as the model input to obtain accurate prediction of forage production while also minimizing the number of possible temperature and precipitation combinations, which increases with the number of percentile categories. For the 19‐year period analysis (2000–2018), we also determined the most and least common scenarios that occurred in the western United States. When using five percentile categories for summer precipitation and temperature, we were able to capture the interannual variability in the spatial extent of abnormally low and high biomass production. The ForageAhead predictions captured similar spatial patterns of forage anomalies as another similar model (Grass‐Cast). This method can be made available in a user‐friendly automated system that can be used by livestock producers and rangeland managers to inform within‐season management decisions. This method can be especially valuable for flexible stocking as it provides a range of possible annual forage production scenarios by the end of May. |
| first_indexed | 2024-03-13T08:47:16Z |
| format | Article |
| id | doaj.art-a748405560b748b4b2771696763b4f61 |
| institution | Directory Open Access Journal |
| issn | 2150-8925 |
| language | English |
| last_indexed | 2024-03-13T08:47:16Z |
| publishDate | 2023-05-01 |
| publisher | Wiley |
| record_format | Article |
| series | Ecosphere |
| spelling | doaj.art-a748405560b748b4b2771696763b4f612023-05-30T00:04:33ZengWileyEcosphere2150-89252023-05-01145n/an/a10.1002/ecs2.4496Using seasonal climate scenarios in the ForageAhead annual forage production model for early drought impact assessmentMarkéta Poděbradská0Bruce K. Wylie1Michael J. Hayes2Deborah J. Bathke3Yared A. Bayissa4Stephen P. Boyte5Jesslyn F. Brown6Brian D. Wardlow7School of Natural Resources University of Nebraska‐Lincoln Lincoln Nebraska USAU.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center Sioux Falls South Dakota USASchool of Natural Resources University of Nebraska‐Lincoln Lincoln Nebraska USASchool of Natural Resources University of Nebraska‐Lincoln Lincoln Nebraska USADepartment of Ecology and Conservation Biology Texas A&M University College Station Texas USAU.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center Sioux Falls South Dakota USAU.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center Sioux Falls South Dakota USASchool of Natural Resources University of Nebraska‐Lincoln Lincoln Nebraska USAAbstract High interannual variability of forage production in semiarid grasslands leads to uncertainties when livestock producers make decisions, such as buying additional feed, relocating animals, or using flexible stocking. Within‐season predictions of annual forage production (i.e., yearly production) can provide specific boundaries for producers to make these decisions with more information and possibly with higher confidence. In this study, we use a recently developed forage production model, ForageAhead, that uses environmental and seasonal climate variables to estimate the annual forage production as approximated by remotely sensed vegetation data. Because, among other variables, this model uses observed summer climate data, the model output cannot be produced early enough in the year (e.g., spring months) to inform within‐season management decisions. To address this issue, we developed summer climate scenarios (e.g., extremely warm and dry and moderately cool and wet) that serve as an input in the model in combination with observed winter and spring climate data from a particular year. The summer climate scenarios used historical summer precipitation and temperature data (1950–2018) categorized into three, five, and seven percentile categories. These percentile values were then combined to represent summer climate scenarios, which were further used as the ForageAhead model input. We tested the optimal number of percentile categories to be used as the model input to obtain accurate prediction of forage production while also minimizing the number of possible temperature and precipitation combinations, which increases with the number of percentile categories. For the 19‐year period analysis (2000–2018), we also determined the most and least common scenarios that occurred in the western United States. When using five percentile categories for summer precipitation and temperature, we were able to capture the interannual variability in the spatial extent of abnormally low and high biomass production. The ForageAhead predictions captured similar spatial patterns of forage anomalies as another similar model (Grass‐Cast). This method can be made available in a user‐friendly automated system that can be used by livestock producers and rangeland managers to inform within‐season management decisions. This method can be especially valuable for flexible stocking as it provides a range of possible annual forage production scenarios by the end of May.https://doi.org/10.1002/ecs2.4496annual forage productiondroughtforage modelforage predictionForageAheadrange decision‐making |
| spellingShingle | Markéta Poděbradská Bruce K. Wylie Michael J. Hayes Deborah J. Bathke Yared A. Bayissa Stephen P. Boyte Jesslyn F. Brown Brian D. Wardlow Using seasonal climate scenarios in the ForageAhead annual forage production model for early drought impact assessment Ecosphere annual forage production drought forage model forage prediction ForageAhead range decision‐making |
| title | Using seasonal climate scenarios in the ForageAhead annual forage production model for early drought impact assessment |
| title_full | Using seasonal climate scenarios in the ForageAhead annual forage production model for early drought impact assessment |
| title_fullStr | Using seasonal climate scenarios in the ForageAhead annual forage production model for early drought impact assessment |
| title_full_unstemmed | Using seasonal climate scenarios in the ForageAhead annual forage production model for early drought impact assessment |
| title_short | Using seasonal climate scenarios in the ForageAhead annual forage production model for early drought impact assessment |
| title_sort | using seasonal climate scenarios in the forageahead annual forage production model for early drought impact assessment |
| topic | annual forage production drought forage model forage prediction ForageAhead range decision‐making |
| url | https://doi.org/10.1002/ecs2.4496 |
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