Utilizing digitized occurrence records of Midwestern feral Cannabis sativa to develop ecological niche models
Abstract Hemp (Cannabis sativa L.) has historically played a vital role in agriculture across the globe. Feral and wild populations have served as genetic resources for breeding, conservation, and adaptation to changing environmental conditions. However, feral populations of Cannabis, specifically i...
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| Format: | Article |
| Language: | English |
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Wiley
2024-07-01
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| Series: | Ecology and Evolution |
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| Online Access: | https://doi.org/10.1002/ece3.11325 |
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| _version_ | 1849420615514062848 |
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| author | Tori Ford Ademola Aina Shelby Ellison Tyler Gordon Zachary Stansell |
| author_facet | Tori Ford Ademola Aina Shelby Ellison Tyler Gordon Zachary Stansell |
| author_sort | Tori Ford |
| collection | DOAJ |
| description | Abstract Hemp (Cannabis sativa L.) has historically played a vital role in agriculture across the globe. Feral and wild populations have served as genetic resources for breeding, conservation, and adaptation to changing environmental conditions. However, feral populations of Cannabis, specifically in the Midwestern United States, remain poorly understood. This study aims to characterize the abiotic tolerances of these populations, estimate suitable areas, identify regions at risk of abiotic suitability change, and highlight the utility of ecological niche models (ENMs) in germplasm conservation. The Maxent algorithm was used to construct a series of ENMs. Validation metrics and MOP (Mobility‐oriented Parity) analysis were used to assess extrapolation risk and model performance. We also projected the final projected under current and future climate scenarios (2021–2040 and 2061–2080) to assess how abiotic suitability changes with time. Climate change scenarios indicated an expansion of suitable habitat, with priority areas for germplasm collection in Indiana, Illinois, Kansas, Missouri, and Nebraska. This study demonstrates the application of ENMs for characterizing feral Cannabis populations and highlights their value in germplasm conservation and breeding efforts. Populations of feral C. sativa in the Midwest are of high interest, and future research should focus on utilizing tools to aid the collection of materials for the characterization of genetic diversity and adaptation to a changing climate. |
| format | Article |
| id | doaj-art-e64feac147d04cdaa702209ccd033eaa |
| institution | Kabale University |
| issn | 2045-7758 |
| language | English |
| publishDate | 2024-07-01 |
| publisher | Wiley |
| record_format | Article |
| series | Ecology and Evolution |
| spelling | doaj-art-e64feac147d04cdaa702209ccd033eaa2025-08-20T03:31:42ZengWileyEcology and Evolution2045-77582024-07-01147n/an/a10.1002/ece3.11325Utilizing digitized occurrence records of Midwestern feral Cannabis sativa to develop ecological niche modelsTori Ford0Ademola Aina1Shelby Ellison2Tyler Gordon3Zachary Stansell4USDA‐Agricultural Research Service, Plant Genetic Resources Unit Geneva New York USADepartment of Plant and Agroecosystem Sciences University of Wisconsin‐Madison Madison Wisconsin USADepartment of Plant and Agroecosystem Sciences University of Wisconsin‐Madison Madison Wisconsin USAUSDA‐Agricultural Research Service, Plant Genetic Resources Unit Geneva New York USAUSDA‐Agricultural Research Service, Plant Genetic Resources Unit Geneva New York USAAbstract Hemp (Cannabis sativa L.) has historically played a vital role in agriculture across the globe. Feral and wild populations have served as genetic resources for breeding, conservation, and adaptation to changing environmental conditions. However, feral populations of Cannabis, specifically in the Midwestern United States, remain poorly understood. This study aims to characterize the abiotic tolerances of these populations, estimate suitable areas, identify regions at risk of abiotic suitability change, and highlight the utility of ecological niche models (ENMs) in germplasm conservation. The Maxent algorithm was used to construct a series of ENMs. Validation metrics and MOP (Mobility‐oriented Parity) analysis were used to assess extrapolation risk and model performance. We also projected the final projected under current and future climate scenarios (2021–2040 and 2061–2080) to assess how abiotic suitability changes with time. Climate change scenarios indicated an expansion of suitable habitat, with priority areas for germplasm collection in Indiana, Illinois, Kansas, Missouri, and Nebraska. This study demonstrates the application of ENMs for characterizing feral Cannabis populations and highlights their value in germplasm conservation and breeding efforts. Populations of feral C. sativa in the Midwest are of high interest, and future research should focus on utilizing tools to aid the collection of materials for the characterization of genetic diversity and adaptation to a changing climate.https://doi.org/10.1002/ece3.11325climateecological niche modelingferal cannabisgermplasm |
| spellingShingle | Tori Ford Ademola Aina Shelby Ellison Tyler Gordon Zachary Stansell Utilizing digitized occurrence records of Midwestern feral Cannabis sativa to develop ecological niche models Ecology and Evolution climate ecological niche modeling feral cannabis germplasm |
| title | Utilizing digitized occurrence records of Midwestern feral Cannabis sativa to develop ecological niche models |
| title_full | Utilizing digitized occurrence records of Midwestern feral Cannabis sativa to develop ecological niche models |
| title_fullStr | Utilizing digitized occurrence records of Midwestern feral Cannabis sativa to develop ecological niche models |
| title_full_unstemmed | Utilizing digitized occurrence records of Midwestern feral Cannabis sativa to develop ecological niche models |
| title_short | Utilizing digitized occurrence records of Midwestern feral Cannabis sativa to develop ecological niche models |
| title_sort | utilizing digitized occurrence records of midwestern feral cannabis sativa to develop ecological niche models |
| topic | climate ecological niche modeling feral cannabis germplasm |
| url | https://doi.org/10.1002/ece3.11325 |
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