Data from: Correlation between genetic diversity and environmental suitability: taking uncertainty from ecological niche models into account
The hindcast of shifts in the geographical ranges of species as estimated by ecological niche modelling (ENM) has been coupled with phylogeographical patterns, allowing the inference of past processes that drove population differentiation and genetic variability. However, more recently, some studies...
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Zusammenfassung: | The hindcast of shifts in the geographical ranges of species as estimated
by ecological niche modelling (ENM) has been coupled with
phylogeographical patterns, allowing the inference of past processes that
drove population differentiation and genetic variability. However, more
recently, some studies have suggested that maps of environmental
suitability estimated by ENM may be correlated to species' abundance,
raising the possibility of using environmental suitability to infer
processes related to population demographic dynamics and genetic
variability. In both cases, one of the main problems is that there is a
wide variation in ENM development methods and climatic models. In this
study, we analyse the relationship between heterozygosity (He) and
environmental suitability from multiple ENMs for 25 population estimates
for Dipteryx alata, a widely distributed, endemic tree species of the
Cerrado region of central Brazil. We propose a new approach for generating
a statistical distribution of correlations under randomly generated ENM.
The confidence intervals from these distributions indicate how model
selection with different properties affects the ability to detect a
correlation of interest (e.g. the correlation between He and suitability).
Additionally, our approach allows us to explore which particular ensemble
of ENMs produces the better result for finding an association between
environmental suitability and He. Caution is necessary when choosing a
method or a climatic data set for modelling geographical distributions,
but the new approach proposed here provides a conservative way to evaluate
the ability of ensembles to detect patterns of interest. |
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DOI: | 10.5061/dryad.3cp3t |