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Climate change poses a threat to biodiversity, and it is unclear whether species can adapt to or tolerate new conditions, or migrate to areas with suitable habitats. Reconstructions of range shifts that occurred in response to environmental changes since the last glacial maximum (LGM) from species distribution models (SDMs) can provide useful data to inform conservation efforts. However, different SDM algorithms and climate reconstructions often produce contrasting patterns, and validation methods typically focus on accuracy in recreating current distributions, limiting their relevance for assessing predictions to the past or future. We modeled historically suitable habitat for the threatened North American tree green ashFraxinus pennsylvanicausing 24 SDMs built using two climate models, three calibration regions, and four modeling algorithms. We evaluated the SDMs using contemporary data with spatial block cross‐validation and compared the relative support for alternative models using a novel integrative method based on coupled demographic‐genetic simulations. We simulated genomic datasets using habitat suitability of each of the 24 SDMs in a spatially‐explicit model. Approximate Bayesian computation (ABC) was then used to evaluate the support for alternative SDMs through comparisons to an empirical population genomic dataset. Models had very similar performance when assessed with contemporary occurrences using spatial cross‐validation, but ABC model selection analyses consistently supported SDMs based on the CCSM climate model, an intermediate calibration extent, and the generalized linear modeling algorithm. Finally, we projected the future range of green ash under four climate change scenarios. Future projections using the SDMs selected via ABC suggest only minor shifts in suitable habitat for this species, while some of those that were rejected predicted dramatic changes. Our results highlight the different inferences that may result from the application of alternative distribution modeling algorithms and provide a novel approach for selecting among a set of competing SDMs with independent data. 

Abstract AimBiogeographers have used three primary data types to examine shifts in tree ranges in response to past climate change: fossil pollen, genetic data and contemporary occurrences. Although recent efforts have explored formal integration of these types of data, we have limited understanding of how integration affects estimates of range shift rates and their uncertainty. We compared estimates of biotic velocity (i.e. rate of species' range shifts) using each data type independently to estimates obtained using integrated models. LocationEastern North America. TaxonFraxinus pennsylvanicaMarshall (green ash). MethodsUsing fossil pollen, genomic data and modern occurrence data, we estimated biotic velocities directly from 24 species distribution models (SDMs) and 200 pollen surfaces created with a novel Bayesian spatio‐temporal model. We compared biotic velocity from these analyses to estimates based on coupled demographic‐coalescent simulations and Approximate Bayesian Computation that combined fossil pollen and SDMs with population genomic data collected across theF. pennsylvanicarange. ResultsPatterns and magnitude of biotic velocity over time varied by the method used to estimate past range dynamics. Estimates based on fossil pollen yielded the highest rates of range movement. Overall, integrating genetic data with other data types in our simulation‐based framework reduced apparent uncertainty in biotic velocity estimates and resulted in greater similarity in estimates between SDM‐ and pollen‐integrated analyses. Main ConclusionsBy reducing uncertainty in our assessments of range shifts, integration of data types improves our understanding of the past distribution of species. Based on these results, we propose further steps to reach the integration of these three lines of biogeographical evidence into a unified analytical framework. 

Abstract The genomic variation of an invasive species may be affected by complex demographic histories and evolutionary changes during the invasion. Here, we describe the relative influence of bottlenecks, clonality, and population expansion in determining genomic variability of the widespread red macroalgaAgarophyton vermiculophyllum. Its introduction from mainland Japan to the estuaries of North America and Europe coincided with shifts from predominantly sexual to partially clonal reproduction and rapid adaptive evolution. A survey of 62,285 SNPs for 351 individuals from 35 populations, aligned to 24 chromosome‐length scaffolds indicate that linkage disequilibrium (LD), observed heterozygosity (H_o), Tajima's D, and nucleotide diversity (Pi) were greater among non‐native than native populations. Evolutionary simulations indicate LD and Tajima's D were consistent with a severe population bottleneck. Also, the increased rate of clonal reproduction in the non‐native range could not have produced the observed patterns by itself but may have magnified the bottleneck effect on LD. Elevated marker diversity in the genetic source populations could have contributed to the increasedH_oand Pi observed in the non‐native range. We refined the previous invasion source region to a ~50 km section of northeastern Honshu Island. Outlier detection methods failed to reveal any consistently differentiated loci shared among invaded regions, probably because of the complexA. vermiculophyllumdemographic history. Our results reinforce the importance of demographic history, specifically founder effects, in driving genomic variation of invasive populations, even when localized adaptive evolution and reproductive system shifts are observed. 

Abstract Plant‐soil feedback (PSF) theory provides a powerful framework for understanding plant dynamics by integrating growth assays into predictions of whether soil communities stabilise plant–plant interactions. However, we lack a comprehensive view of the likelihood of feedback‐driven coexistence, partly because of a failure to analyse pairwise PSF, the metric directly linked to plant species coexistence. Here, we determine the relative importance of plant evolutionary history, traits, and environmental factors for coexistence through PSF using a meta‐analysis of 1038 pairwise PSF measures. Consistent with eco‐evolutionary predictions, feedback is more likely to mediate coexistence for pairs of plant species (1) associating with similar guilds of mycorrhizal fungi, (2) of increasing phylogenetic distance, and (3) interacting with native microbes. We also found evidence for a primary role of pathogens in feedback‐mediated coexistence. By combining results over several independent studies, our results confirm that PSF may play a key role in plant species coexistence, species invasion, and the phylogenetic diversification of plant communities.