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      Phylogeographic structure is strong in the Atlantic Forest; predictive power of correlative paleodistribution models, not always

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          Ecological niche modeling in Maxent: the importance of model complexity and the performance of model selection criteria.

          Maxent, one of the most commonly used methods for inferring species distributions and environmental tolerances from occurrence data, allows users to fit models of arbitrary complexity. Model complexity is typically constrained via a process known as L1 regularization, but at present little guidance is available for setting the appropriate level of regularization, and the effects of inappropriately complex or simple models are largely unknown. In this study, we demonstrate the use of information criterion approaches to setting regularization in Maxent, and we compare models selected using information criteria to models selected using other criteria that are common in the literature. We evaluate model performance using occurrence data generated from a known "true" initial Maxent model, using several different metrics for model quality and transferability. We demonstrate that models that are inappropriately complex or inappropriately simple show reduced ability to infer habitat quality, reduced ability to infer the relative importance of variables in constraining species' distributions, and reduced transferability to other time periods. We also demonstrate that information criteria may offer significant advantages over the methods commonly used in the literature.
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            The effect of the extent of the study region on GIS models of species geographic distributions and estimates of niche evolution: preliminary tests with montane rodents (genus Nephelomys) in Venezuela

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              Integrating phylogenetics and environmental niche models to explore speciation mechanisms in dendrobatid frogs.

              We developed an approach that combines distribution data, environmental geographic information system layers, environmental niche models, and phylogenetic information to investigate speciation processes. We used Ecuadorian frogs of the family Dendrobatidae to illustrate our methodology. For dendrobatids there are several cases for which there is significant environmental divergence for allopatric and parapatric lineages. The consistent pattern that many related taxa or nodes exist in distinct environmental space reinforces Lynch and Duellman's hypothesis that differential selection likely played an important role in species differentiation of frogs in the Andes. There is also some evidence that the Río Esmeraldas basin is a geographic barrier to species distributed in low to middle elevations on the western side of the Andes. Another useful aspect of this approach is that it can point to common environmental parameters that correlate with speciation. For dendrobatids, sister clades generally segregate along temperature/elevational and/or seasonality axes. The joint analysis of environmental and geographic data for this group of dendrobatid frogs has identified potentially important speciation mechanisms and specific sister lineages that warrant intensive study to test hypotheses generated in this investigation. Further, the method outlined in this paper will be increasingly useful as knowledge of distribution and phylogeny of tropical species increases.
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                Author and article information

                Journal
                Journal of Zoological Systematics and Evolutionary Research
                J Zoolog Syst Evol Res
                Wiley
                09475745
                May 2013
                May 2013
                February 17 2013
                : 51
                : 2
                : 114-121
                Affiliations
                [1 ]Laboratório de Mastozoologia e Biogeografia; Departamento de Ciências Biológicas; Universidade Federal do Espírito Santo; Vitória; ES; Brazil
                [2 ]Department of Biology; City College of New York; City University of New York; New York; NY; USA
                Article
                10.1111/jzs.12014
                863d21a2-c2bb-4a19-be56-a08861cf4534
                © 2013

                http://doi.wiley.com/10.1002/tdm_license_1.1

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