Combining multiple data sources in species distribution models while accounting for spatial dependence and overfitting with combined penalized likelihood maximization
Abstract
The increase in availability of species datasets means that approaches to species distribution modelling that incorporate multiple datasets are in greater demand. Recent methodological developments in this area have led to combined likelihood approaches, in which a log-likelihood comprised of the sum of the log-likelihood components of each data source is maximized. Often, these approaches make use of at least one presence-only dataset and use...
Paper Details
Title
Combining multiple data sources in species distribution models while accounting for spatial dependence and overfitting with combined penalized likelihood maximization
Published Date
Oct 3, 2019
Volume
10
Issue
12
Pages
2118 - 2128
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