A gap analysis modeling framework to prioritize collecting for ex situ conservation of crop landraces
Aim: The conservation and effective use of crop genetic diversity is crucial to overcome challenges related to human nutrition and agricultural sustainability. Farmers’ traditional varieties (“landraces”) are major sources of genetic variation. The degree of representation of crop landrace diversity...
| Autores principales: | , , , , , , , |
|---|---|
| Formato: | Conjunto de datos |
| Lenguaje: | Inglés |
| Publicado: |
2021
|
| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/116572 |
| _version_ | 1855524309039054848 |
|---|---|
| author | Ramírez Villegas, Julián Armando Khoury, Colin K. Achicanoy Estrella, Harold Armando Mendez Alzate, Andres Camilo Sosa, Chrystian C. Debouck, Daniel G. Kehel, Zakaria Guarino, Luigi |
| author_browse | Achicanoy Estrella, Harold Armando Debouck, Daniel G. Guarino, Luigi Kehel, Zakaria Khoury, Colin K. Mendez Alzate, Andres Camilo Ramírez Villegas, Julián Armando Sosa, Chrystian C. |
| author_facet | Ramírez Villegas, Julián Armando Khoury, Colin K. Achicanoy Estrella, Harold Armando Mendez Alzate, Andres Camilo Sosa, Chrystian C. Debouck, Daniel G. Kehel, Zakaria Guarino, Luigi |
| author_sort | Ramírez Villegas, Julián Armando |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Aim: The conservation and effective use of crop genetic diversity is crucial to overcome challenges related to human nutrition and agricultural sustainability. Farmers’ traditional varieties (“landraces”) are major sources of genetic variation. The degree of representation of crop landrace diversity in ex situ conservation is poorly understood, partly due to a lack of methods that can negotiate both the anthropogenic and environmental determinants of their geographic distributions. Here we describe a novel spatial modeling and ex situ conservation gap analysis modeling framework for crop landraces, using common bean (Phaseolus vulgaris L.) as a case study.
Location: The Americas
Methods: The modeling framework includes five main steps: (1) determining relevant landrace groups using literature to develop and test classification models; (2) modeling the potential geographic distributions of these groups using occurrence (landrace presences) combined with environmental and socioeconomic predictor data; (3) calculating geographic and environmental gap scores for current genebank collections; (4) mapping ex situ conservation gaps; and (5) compiling expert inputs.
Results: Modeled distributions and conservation gaps for the two genepools of common bean (Andean and Mesoamerican) were robustly predicted and align well with expert opinions. Both genepools are relatively well conserved, with Andean ex situ collections representing 78.5% and Mesoamerican 98.2% of their predicted geographic distributions. Modelling revealed additional collection priorities for Andean landraces occur primarily in Chile, Peru, Colombia and, to a lesser extent, in Venezuela. Mesoamerican landrace collecting priorities are concentrated in Mexico, Belize, and Guatemala.
Conclusions: The modeling framework represents an advance in tools that can be deployed to model the geographic distributions of cultivated crop diversity, to assess the comprehensiveness of conservation of this diversity ex situ, and to highlight geographic areas where further collecting may be conducted to fill gaps in ex situ conservation. |
| format | Conjunto de datos |
| id | CGSpace116572 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| record_format | dspace |
| spelling | CGSpace1165722025-12-02T10:59:51Z A gap analysis modeling framework to prioritize collecting for ex situ conservation of crop landraces Ramírez Villegas, Julián Armando Khoury, Colin K. Achicanoy Estrella, Harold Armando Mendez Alzate, Andres Camilo Sosa, Chrystian C. Debouck, Daniel G. Kehel, Zakaria Guarino, Luigi common bean analysis plant genetic resources fríjol analísis recursos genéticos vegetales Aim: The conservation and effective use of crop genetic diversity is crucial to overcome challenges related to human nutrition and agricultural sustainability. Farmers’ traditional varieties (“landraces”) are major sources of genetic variation. The degree of representation of crop landrace diversity in ex situ conservation is poorly understood, partly due to a lack of methods that can negotiate both the anthropogenic and environmental determinants of their geographic distributions. Here we describe a novel spatial modeling and ex situ conservation gap analysis modeling framework for crop landraces, using common bean (Phaseolus vulgaris L.) as a case study. Location: The Americas Methods: The modeling framework includes five main steps: (1) determining relevant landrace groups using literature to develop and test classification models; (2) modeling the potential geographic distributions of these groups using occurrence (landrace presences) combined with environmental and socioeconomic predictor data; (3) calculating geographic and environmental gap scores for current genebank collections; (4) mapping ex situ conservation gaps; and (5) compiling expert inputs. Results: Modeled distributions and conservation gaps for the two genepools of common bean (Andean and Mesoamerican) were robustly predicted and align well with expert opinions. Both genepools are relatively well conserved, with Andean ex situ collections representing 78.5% and Mesoamerican 98.2% of their predicted geographic distributions. Modelling revealed additional collection priorities for Andean landraces occur primarily in Chile, Peru, Colombia and, to a lesser extent, in Venezuela. Mesoamerican landrace collecting priorities are concentrated in Mexico, Belize, and Guatemala. Conclusions: The modeling framework represents an advance in tools that can be deployed to model the geographic distributions of cultivated crop diversity, to assess the comprehensiveness of conservation of this diversity ex situ, and to highlight geographic areas where further collecting may be conducted to fill gaps in ex situ conservation. 2021-02-06 2021-12-07T10:23:29Z 2021-12-07T10:23:29Z Dataset https://hdl.handle.net/10568/116572 en https://hdl.handle.net/10568/108131 Open Access Ramirez-Villegas, J.; Khoury, C.K.; Achicanoy, H.A.; Mendez, A.C.; Diaz, M.V.; Sosa, C C.; Debouck, D.G.; Kehel, Z.; Guarino, L. (2021) A gap analysis modeling framework to prioritize collecting for ex situ conservation of crop landraces. https://doi.org/10.5061/dryad.866t1g1n0 |
| spellingShingle | common bean analysis plant genetic resources fríjol analísis recursos genéticos vegetales Ramírez Villegas, Julián Armando Khoury, Colin K. Achicanoy Estrella, Harold Armando Mendez Alzate, Andres Camilo Sosa, Chrystian C. Debouck, Daniel G. Kehel, Zakaria Guarino, Luigi A gap analysis modeling framework to prioritize collecting for ex situ conservation of crop landraces |
| title | A gap analysis modeling framework to prioritize collecting for ex situ conservation of crop landraces |
| title_full | A gap analysis modeling framework to prioritize collecting for ex situ conservation of crop landraces |
| title_fullStr | A gap analysis modeling framework to prioritize collecting for ex situ conservation of crop landraces |
| title_full_unstemmed | A gap analysis modeling framework to prioritize collecting for ex situ conservation of crop landraces |
| title_short | A gap analysis modeling framework to prioritize collecting for ex situ conservation of crop landraces |
| title_sort | gap analysis modeling framework to prioritize collecting for ex situ conservation of crop landraces |
| topic | common bean analysis plant genetic resources fríjol analísis recursos genéticos vegetales |
| url | https://hdl.handle.net/10568/116572 |
| work_keys_str_mv | AT ramirezvillegasjulianarmando agapanalysismodelingframeworktoprioritizecollectingforexsituconservationofcroplandraces AT khourycolink agapanalysismodelingframeworktoprioritizecollectingforexsituconservationofcroplandraces AT achicanoyestrellaharoldarmando agapanalysismodelingframeworktoprioritizecollectingforexsituconservationofcroplandraces AT mendezalzateandrescamilo agapanalysismodelingframeworktoprioritizecollectingforexsituconservationofcroplandraces AT sosachrystianc agapanalysismodelingframeworktoprioritizecollectingforexsituconservationofcroplandraces AT debouckdanielg agapanalysismodelingframeworktoprioritizecollectingforexsituconservationofcroplandraces AT kehelzakaria agapanalysismodelingframeworktoprioritizecollectingforexsituconservationofcroplandraces AT guarinoluigi agapanalysismodelingframeworktoprioritizecollectingforexsituconservationofcroplandraces AT ramirezvillegasjulianarmando gapanalysismodelingframeworktoprioritizecollectingforexsituconservationofcroplandraces AT khourycolink gapanalysismodelingframeworktoprioritizecollectingforexsituconservationofcroplandraces AT achicanoyestrellaharoldarmando gapanalysismodelingframeworktoprioritizecollectingforexsituconservationofcroplandraces AT mendezalzateandrescamilo gapanalysismodelingframeworktoprioritizecollectingforexsituconservationofcroplandraces AT sosachrystianc gapanalysismodelingframeworktoprioritizecollectingforexsituconservationofcroplandraces AT debouckdanielg gapanalysismodelingframeworktoprioritizecollectingforexsituconservationofcroplandraces AT kehelzakaria gapanalysismodelingframeworktoprioritizecollectingforexsituconservationofcroplandraces AT guarinoluigi gapanalysismodelingframeworktoprioritizecollectingforexsituconservationofcroplandraces |