Model predictions that can be tested with genetic data
Integrating ENMs and SDMs with genomic data can be used to test whether
our inferences about species responses to climate change are accurate
and relevant and hence, make better predictions of potential responses
to future climate change. The independent assessment of habitat quality
in ecological niche models constitutes an improvement since, in addition
to the inferences about changes in the species’ distribution ranges, by
analyzing changes in niche marginality between LGM and present day we
can infer changes in population fitness and selection pressure within a
species’ distribution (Figure 5a).
An example is the northern clade of Plestiodon (i.e.Plestiodon skiltonianus , highland species) which shows a
contraction of its distribution from LGM to present (Figure 5b, Figure
5c), in addition to a decrease in habitat quality (i.e. increased
marginality) at its northernmost distribution. Populations of this
species at these locations should show signatures of a bottleneck along
with increased selection pressure associated with higher temperatures
and lower precipitation in present day climate (Figure 1, Figure 5d).
This could be evidenced by adaptations in thermoregulation or water
physiology, and positive selection should be focused to genes associated
with these processes such as aquaporins (e.g. Araya-Donoso et al., 2021)
or heat shock proteins (Chen et al., 2018). An example of a lowland
desert adapted taxon is the southern clade of the packrat Neotoma
bryanti (Figure 5e), which exhibits a geographical expansion towards
the north from LGM to present (Figure 5f), associated with increased
habitat quality (i.e. decreased marginality) in the central populations
(Figure 5g). Stable populations between LGM and present for this species
should reflect an increase in effective population size, and could show
signatures of natural selection associated with LGM climate (Figure 5f,
Figure 5g) while the northern part of the range may be expected to have
lower diversity as a consequence of range expansion as well as surfing
of deleterious alleles (Escoffier et al., 2008; Gilbert et al., 2018).
These predictions can be tested with genomic data, evaluating if the
patterns of genetic variation reflect the expected changes in effective
population size and signatures of selection predicted by our models.
According to published genetic data, the mammals Chaetodipus
spinatus (Álvarez-Castañeda & Murphy, 2014), Spilogale gracilis(Ferguson et al., 2017), and Otospermophilus becheeyi (Phuong et
al., 2017) show population size reduction during LGM, which is in
agreement with our prediction of reduced suitable area or increased
marginality in the LGM distribution models (except for C.
spinatus ). Whole genome sequencing data from populations across the
peninsula would be required to evaluate the selection pressure
predictions from this study. An example of this approach is Farleigh et
al. (2021), who used genomic data to infer changes in population size
and potential genes under selection for the lizard Phrynosoma
platyrhinos across the North American deserts, formally testing
previous hypotheses about demographic changes and adaptation to
different climates (Jezkova et al., 2016).