Publication release: How well do species distribution models predict occurrences in exotic ranges?

Species distribution models (SDMs) are widely used predictive tools to
forecast potential biological invasions. However, the reliability of SDMs
extrapolated to exotic ranges remains understudied, with most analyses
restricted to few species and equivocal results. We examined the spatial
transferability of SDMs for 647 non-indigenous species extrapolated across
1,867 invaded ranges, and identify what factors may help differentiate
predictive success from failure. We performed a large-scale assessment of
the transferability of SDMs using two modelling approaches: generalized
additive models (GAMs) and MaxEnt. We fitted SDMs on the native ranges of
species and extrapolated them to exotic ranges. We examined the influence
of general factors and factors related to biological invasions on spatial
transferability. Here, we provide the code and data for publication in
Global Ecology and Biogeography as part of Nguyen and Leung 2022 "How
well do species distribution models predict occurrences in exotic
ranges?". Provided are the files and scripts necessary to fit and
validate the SDMs using distirbutional data from their native and exotic
ranges, respectively, formulated as generalized additive models (GAMs) or
MaxEnt models. Additionally, provided is a script to validate the SDMs on
their native fitting range using 10-fold cross-validation, and to fit the
transferability model, as a linear mixed model (LMM), with a provided
cleaned data.frame. The dataset provided includes a full species list with
GBIF occurrence records, target-group background (TGB) records to use with
model fitting and validation, as well as environmental data associated
with the sightings.