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Transferability of correlative and process‐based species distribution models revisited: A response to Booth

Here, we respond to Booth's criticism of our paper, “Predictive ability of a process‐based versus a correlative species distribution model.” Booth argues that our usage of the MaxEnt model was flawed and that the conclusions of our paper are by implication flawed. We respond by clarifying that...

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Detalles Bibliográficos
Autores principales: Higgins, Steven I., Larcombe, Matthew J., Beeton, Nicholas J., Conradi, Timo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8495818/
https://www.ncbi.nlm.nih.gov/pubmed/34646495
http://dx.doi.org/10.1002/ece3.8081
Descripción
Sumario:Here, we respond to Booth's criticism of our paper, “Predictive ability of a process‐based versus a correlative species distribution model.” Booth argues that our usage of the MaxEnt model was flawed and that the conclusions of our paper are by implication flawed. We respond by clarifying that the error Booth implies we made was not made in our analysis, and we repeat statements from the original manuscript which anticipated such criticisms. In addition, we illustrate that using BIOCLIM variables in a MaxEnt analysis as recommended by Booth does not change the conclusions of the original analysis. That is, high performance in the training data domain did not equate to reliable predictions in novel data domains, and the process model transferred into novel data domains better than the correlative model did. We conclude by discussing a hidden implication of our study, namely, that process‐based SDMs negate the need for BIOCLIM‐type variables and therefore reframe the variable selection problem in species distribution modeling.