Data from: The article Euclimatch: An R package for climate matching with Euclidean distance metrics

Climate matching, a tool for predicting non-native species survival in
target (recipient) regions, is commonly used in invasive species
frameworks such as horizon scanning and screening-level risk assessment
protocols. Screening-level risk assessments often require the analysis of
many species with limited resources, and climate matching can be
advantageous to identify a reduced number of species for more detailed
analyses. Additionally, risk screening may require examination of
non-native species’ source pools where species occurrence records are not
used in model training data. In these instances, climate matching is an
effective method for assessing the survival of non-native species or their
source pools in a target region and has practical advantages over species
distribution models. We introduce the R package Euclimatch for
quantitative climate matching with the Euclidean distance algorithm
Climatch. The package provides tools for creating a streamlined
data-agnostic climate-matching workflow. First, climate data are extracted
for species occurrence records or regions. Second, climate match is
modelled between two regions as a similarity score per grid cell or
summarized across a target region. Third, visualizations of the climate
match model outputs are created. We demonstrate the use of the Euclimatch
package with the climate match of two popular aquarium trade species and a
region-to-region analysis. We also demonstrate differences in results
between Euclidean distance metric standardization methods when
incorporating climate-change projections. The scale of each example is
global, under historical and projected climates. Euclimatch provides a
scripting interface for Euclidean climate matching for the screening
assessment of non-native species or regions under any climatic conditions.
Euclimatch can be downloaded from the comprehensive R archive network
(CRAN).