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...

Full description

Saved in:
Bibliographic Details
Main Authors: Tori Ford, Ademola Aina, Shelby Ellison, Tyler Gordon, Zachary Stansell
Format: Article
Language:English
Published: Wiley 2024-07-01
Series:Ecology and Evolution
Subjects:
Online Access:https://doi.org/10.1002/ece3.11325
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849420615514062848
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
work_keys_str_mv AT toriford utilizingdigitizedoccurrencerecordsofmidwesternferalcannabissativatodevelopecologicalnichemodels
AT ademolaaina utilizingdigitizedoccurrencerecordsofmidwesternferalcannabissativatodevelopecologicalnichemodels
AT shelbyellison utilizingdigitizedoccurrencerecordsofmidwesternferalcannabissativatodevelopecologicalnichemodels
AT tylergordon utilizingdigitizedoccurrencerecordsofmidwesternferalcannabissativatodevelopecologicalnichemodels
AT zacharystansell utilizingdigitizedoccurrencerecordsofmidwesternferalcannabissativatodevelopecologicalnichemodels