Please use this identifier to cite or link to this item: https://repositorio.uti.edu.ec//handle/123456789/3607
Title: A new spin on a compositionalist predictive modelling framework for conservation planning: A tropical case study in Ecuador
Authors: Mateo, Rubén
De-la-Estrella, Manuel
Felicísimo, Ángel
Muñoz, Jesús
Guisan, Antoine
Issue Date: 2013
Publisher: Biological Conservation. Volume 160, Pages 150 - 161
Abstract: Knowledge about spatial biodiversity patterns is a basic criterion for reserve network design. Although herbarium collections hold large quantities of information, the data are often scattered and cannot supply complete spatial coverage. Alternatively, herbarium data can be used to fit species distribution models and their predictions can be used to provide complete spatial coverage and derive species richness maps. Here, we build on previous effort to propose an improved compositionalist framework for using species distribution models to better inform conservation management. We illustrate the approach with models fitted with six different methods and combined using an ensemble approach for 408 plant species in a tropical and megadiverse country (Ecuador). As a complementary view to the traditional richness hotspots methodology, consisting of a simple stacking of species distribution maps, the compositionalist modelling approach used here combines separate predictions for different pools of species to identify areas of alternative suitability for conservation. Our results show that the compositionalist approach better captures the established protected areas than the traditional richness hotspots strategies and allows the identification of areas in Ecuador that would optimally complement the current protection network. Further studies should aim at refining the approach with more groups and additional species information. © 2013 Elsevier Ltd.
URI: https://www.sciencedirect.com/science/article/abs/pii/S0006320713000244
http://repositorio.uti.edu.ec//handle/123456789/3607
Appears in Collections:Artículos Científicos Indexados

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