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dc.contributor.author
Lantschner, María Victoria
dc.contributor.author
de la Vega, Gerardo José
dc.contributor.author
Corley, Juan Carlos
dc.date.available
2020-02-10T21:44:38Z
dc.date.issued
2018-11
dc.identifier.citation
Lantschner, María Victoria; de la Vega, Gerardo José; Corley, Juan Carlos; Predicting the distribution of harmful species and their natural enemies in agricultural, livestock and forestry systems: An overview; Taylor & Francis; International Journal of Pest Management; 65; 3; 11-2018; 190-206
dc.identifier.issn
0967-0874
dc.identifier.uri
http://hdl.handle.net/11336/97140
dc.description.abstract
Predicting the potential distribution of harmful species to agriculture, livestock and forestry is decisive to prevent their impacts, especially when these are expanding their range due to global change. Recent advances in species distribution modelling (SDM) have made these tools widely used for biosecurity studies. We reviewed the available literature of SDM for pest, weeds, pathogen species and biological-control agents, with the aims of synthesizing and quantifying the available information, and identifying gaps in the knowledge and future perspectives. SDMs for 420 species were collected from 220 publications. Insect pests were the most frequently studied organisms. CLIMEX and MaxEnt were the most commonly used modelling tools, while pure mechanistic approaches were rarely applied. Most studies covered broad scales, and focused on predicting the distribution of invasive species and/or the effects of climate change. The challenge remains for models to include disturbance, resource availability, and biotic factors, as well as to better quantify uncertainty. This future directions will be fundamental to improve the predictive power of SDMs for productive systems in the context of a rapidly changing World.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Taylor & Francis
dc.relation
http://hdl.handle.net/11336/184935
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
PATHOGENS
dc.subject
PESTS
dc.subject
SPECIES DISTRIBUTION MODELS (SDMS)
dc.subject
WEEDS
dc.subject.classification
Ecología
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Ciencias Biológicas
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CIENCIAS NATURALES Y EXACTAS
dc.title
Predicting the distribution of harmful species and their natural enemies in agricultural, livestock and forestry systems: An overview
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2019-10-15T17:56:31Z
dc.identifier.eissn
1366-5863
dc.journal.volume
65
dc.journal.number
3
dc.journal.pagination
190-206
dc.journal.pais
Reino Unido
dc.journal.ciudad
Londres
dc.description.fil
Fil: Lantschner, María Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria; Argentina
dc.description.fil
Fil: de la Vega, Gerardo José. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria; Argentina
dc.description.fil
Fil: Corley, Juan Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria; Argentina. Universidad Nacional del Comahue; Argentina
dc.journal.title
International Journal of Pest Management
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.tandfonline.com/doi/full/10.1080/09670874.2018.1533664
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1080/09670874.2018.1533664
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