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      Predicting the Risk of Exotic Plant Invasions in the Orinoco Region: Importance of Distribution Models, Climatic Niche and Functional Richness

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          Abstract

          The process of biological invasions resulting from the introduction of exotic species is one of the most critical components of global environmental change. Although many hypotheses try to explain the processes underlying biological invasions, changes in land use are essential drivers mediating the colonization of exotic species at the landscape level. We used potential species distribution models developed in Maxent and a database of nine functional traits associated with invasion success for 18 exotic species with a high risk of establishment and difficulty of control in the Orinoco region from Colombia. We found that 67% of the species differed from the centroid in the climatic niche when comparing native and invaded localities. Overall, the native distribution localities showed a more restricted dispersal in their climatic niche, and for most species, native distribution was found within the broad environmental gradients of the invaded localities. Additionally, we found high climatic suitability for all exotic species across all the biomes and ecosystems; however, transformed ecosystems showed exotic plant species’ higher potential functional richness. Our research allowed us to identify key geographical areas that are highly susceptible to invasions and prioritize species that need control in particular ecosystems and biomes. This work provides early warnings on the potential risks of invasion of exotic species, and it will improve the monitoring and management efforts in the Orinoco region of Colombia.

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                Author and article information

                Journal
                Frontiers in Environmental Science
                Front. Environ. Sci.
                Frontiers Media SA
                2296-665X
                May 16 2022
                May 16 2022
                : 10
                Article
                10.3389/fenvs.2022.687723
                1f72d43b-73a7-492b-a9fe-27c06e73ef63
                © 2022

                Free to read

                https://creativecommons.org/licenses/by/4.0/

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