Inferring past refugia and range dynamics through the integration of fossil, niche modelling and genomic data

Abstract

Aim Reconstructing species' glacial refugial history and demographic changes over time has greatly relied on comparing inferences from multiple methods while not sufficiently acknowledging their limitations. Here, we aim to integrate as fully as possible complementary methods in ecology, genomics and palaeobiology to improve the reconstruction of species biogeographical history. Location South‐western Europe. Taxon Cabrera vole (Microtus cabrerae). Methods We compiled and mapped the raw fossil data of the Cabrera vole for the Last Glacial Maximum (LGM) and Mid‐Holocene (MH). Alongside, we projected the calibrated ecological niche model (ENM) of the species' current distribution for the LGM, the Younger Dryas and the MH. Complementarily, we used previously obtained Genotyping‐by‐Sequencing data to evaluate the demographic history and range expansion patterns of all four Evolutionarily Significant Units of the species, in an integrative framework. Results ENM‐inferred refugial areas and genomic modelling consistently supported northern Iberian glacial refugia for the Cabrera vole. This contrasted with the higher fossil abundance of the species in southern and eastern Iberia and southern France from the LGM to the MH. Our results suggest that populations in areas with high fossil abundance went extinct, and were later replaced by northern Iberian populations such that they did not contribute significantly to the current gene pool. Main conclusions Our integrative approach indicates how the range of the Cabrera vole fluctuated in response to environmental change during and following the LGM. Despite methodological limitations, the ENM and genomic approaches produced generally congruent results. Instead, the fossil record may misrepresent the ancestral distribution of this species and should be considered cautiously for ancestral distribution reconstruction, considering that it also reflects the fossilization conditions. Overall, our study supports the idea that integrative approaches are essential to provide an accurate and well‐supported picture of historical refugial areas and range dynamics.

Boundary Effects Cause False Signals of Range Expansions in Population Genomic Data

“…Instead, the geographic patterns in the magnitude of ψ (or similar statistics that reflect asymmetries in SFS) have been interpreted in relation to other summary statistics (e.g. H E , Tajima's D, and IBD and overall patterns of genetic structuring) and independent sources of information regarding REs, such as historical records ( Ioannidis et al 2021 ; Bringloe et al 2022 ; Hemstrom et al 2022 ; Jaya et al 2022 ; Mestre et al 2022 ; Pierce et al 2014 ).…”

“…While many of the limitations of ψ are often discussed ( Riginos et al 2016 ; He et al 2017 ; Ioannidis et al 2021 ; Mestre et al 2022 ), the possibility of BEs causing high false positive rates when testing for REs has, until now, been largely ignored. More importantly, while the effects of BEs on spatial patterns of ψ were reported in Peter and Slatkin (2013 , 2015 ), the problem of BEs, as demonstrated here, appears to be much more severe than originally claimed.…”

Boundary effects cause false signals of range expansions in population genomic data

“…Instead, the geographic patterns in the magnitude of ψ (or similar statistics that reflect asymmetries in SFS) have been interpreted in relation to other summary statistics (e.g. H E , Tajima's D and IBD and overall patterns of genetic structuring) and independent sources of information regarding range expansions, such as historical records (Jaya et al 2022;Ioannidis et al 2021;Mestre et al 2022;Pierce et al 2014;Bringloe et al 2022;Hemstrom et al 2022).…”

“…While many of the limitations of ψ are often discussed (Ioannidis et al 2021; He, Prado, and Knowles 2017; Mestre et al 2022; Riginos et al 2016), the possibility of BEs causing high false positive rates when testing for REs has, until now, been largely ignored. More importantly, while the effects of BEs on spatial patterns of ψ were reported in Peter and Slatkin (2013; 2015), the problem of BEs, as demonstrated here, appears to be much more severe than originally claimed.…”

Species distribution modelling supports the study of past, present and future biogeographies

“…Inference is gained by searching for congruent evidence from these disparate data sources and methodologies, each with their own limitations. In one example, SDMs and genomic data both pointed to the same glacial refugium location for a small mammal in Europe, whereas fossil evidence was not sufficient to construct range dynamics (Mestre et al, 2022). Another recent study triangulated between palaeodistribution models, migration simulations and molecular data to identify the origin of the central European steppe flora and glacial refugia in southern Europe (Divíšek et al, 2022).…”