{"id":"CONICETDig_31f269f8f8a77eb5f0a6645917ef4e4a","dc:title":"Revisi\u00f3n de trabajos en los que se estudi\u00f3 la distribucion potencial de plagas agropecuarias y forestales a escala global","dc:creator":"Corley, Juan Carlos","dc:date":"2024","dc:description":["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\/vnd.openxmlformats-officedocument.spreadsheetml.sheet","application\/vnd.openxmlformats-officedocument.wordprocessingml.document"],"dc:language":["eng"],"dc:type":"dataset","dc:rights":["info:eu-repo\/semantics\/openAccess","https:\/\/creativecommons.org\/licenses\/by-nc-sa\/2.5\/ar\/"],"dc:relation":["info:eu-repo\/grantAgreement\/Ministerio de Ciencia. Tecnolog\u00eda e Innovaci\u00f3n Productiva. Agencia Nacional de Promoci\u00f3n Cient\u00edfica y Tecnol\u00f3gica\/PICT 2016-705","info:eu-repo\/grantAgreement\/\/PICT 2016-705"],"dc:identifier":"https:\/\/repositoriosdigitales.mincyt.gob.ar\/vufind\/Record\/CONICETDig_31f269f8f8a77eb5f0a6645917ef4e4a"}