Tests of species‐specific models reveal the importance of drought in postglacial range shifts of a Mediterranean‐climate tree: insights from integrative distributional, demographic and coalescent modelling andABCmodel selection

Abstract

Past climate change has caused shifts in species distributions and undoubtedly impacted patterns of genetic variation, but the biological processes mediating responses to climate change, and their genetic signatures, are often poorly understood. We test six species-specific biologically informed hypotheses about such processes in canyon live oak (Quercus chrysolepis) from the California Floristic Province. These hypotheses encompass the potential roles of climatic niche, niche multidimensionality, physiological trade-offs in functional traits, and local-scale factors (microsites and local adaptation within ecoregions) in structuring genetic variation. Specifically, we use ecological niche models (ENMs) to construct temporally dynamic landscapes where the processes invoked by each hypothesis are reflected by differences in local habitat suitabilities. These landscapes are used to simulate expected patterns of genetic variation under each model and evaluate the fit of empirical data from 13 microsatellite loci genotyped in 226 individuals from across the species range. Using approximate Bayesian computation (ABC), we obtain very strong support for two statistically indistinguishable models: a trade-off model in which growth rate and drought tolerance drive habitat suitability and genetic structure, and a model based on the climatic niche estimated from a generic ENM, in which the variables found to make the most important contribution to the ENM have strong conceptual links to drought stress. The two most probable models for explaining the patterns of genetic variation thus share a common component, highlighting the potential importance of seasonal drought in driving historical range shifts in a temperate tree from a Mediterranean climate where summer drought is common.

Distributional shifts – not geographic isolation – as a probable driver of montane species divergence

“…For example, the Euclidean distance between georeferenced locations often does not capture the geographic isolation experience by organisms (McRae 2006). changes in population size and dispersal probabilities) differ across heterogeneous landscapes and/or during colonization (Neuenschwander et al 2008, He et al 2013, Bemmels et al 2016. Likewise, with very little overlap between past and present distributions (Fig.…”

“…Moreover, our tests of which models we are more probable does not mean we have necessarily identified 'the correct' model Maddison 2002, Beaumont et al 2010), even with validation procedures to evaluate that the models are capable of generating the data (Oaks et al 2013, Bemmels et al 2016; this is true for any model-based inference procedure and is not specific to the approach we apply here. Moreover, our tests of which models we are more probable does not mean we have necessarily identified 'the correct' model Maddison 2002, Beaumont et al 2010), even with validation procedures to evaluate that the models are capable of generating the data (Oaks et al 2013, Bemmels et al 2016; this is true for any model-based inference procedure and is not specific to the approach we apply here.…”

Genomic data reveal cryptic lineage diversification and introgression in Californian golden cup oaks (sectionProtobalanus)

“…Canyon live oak is a widely distributed tree in California, with relictual populations in Arizona, Nevada, New Mexico, Oregon and northern Baja California (Thornburgh, ; eFloras, ). Previous microsatellite‐based studies have shown that this species presents a deep genetic structure, with two genetic clusters separating populations located north and south of the Transverse ranges (Ortego et al ., ; Bemmels et al ., ). This phylogeographical subdivision contrasts with the shallow patterns of genetic differentiation found among other Californian oak species with similar distribution ranges, including both red oaks (section Lobatae ; Dodd & Kashani, ) and white oaks (section Quercus ; Ashley et al ., ; Fitz‐Gibbon et al ., ; Ortego et al ., ; but see Gugger et al ., ).…”

“…We hypothesize that interspecific gene flow may have occurred due to increased geographical contact between the two species during the Miocene/Pliocene epochs (23.03–2.58 Myr ago (Ma)), when Q. tomentella was widely distributed in continental California (Axelrod, ,b; Muller, ; eFloras, ), and/or during the Pleistocene glacial periods (2.59–0.01 Ma), when the lower sea levels almost connected the northern Channel Islands (Santa Rosa, Santa Cruz and Anacapa) to the mainland (Johnson, ). We (3) also explore whether the deep genetic structure of Q. chrysolepis reported in previous studies (Ortego et al ., ; Bemmels et al ., ) represents a phylogeographical break driven by the past geological history of the region and/or hides a cryptic history of hybridization or introgression with Q. tomentella (Calsbeek et al ., ; Chatzimanolis & Caterino, ; Vandergast et al ., ). Finally, we (4) test whether lineages/populations involved in hybrid gene flow interactions show higher levels of genetic diversity than those that have not experienced genetic admixture (Nettel et al ., ; Streicher et al ., ).…”

Inferring the geographic origin of a range expansion: Latitudinal and longitudinal coordinates inferred from genomic data in an ABC framework with the program x‐origin

“…However, the x ‐ origin pipeline differs in that (i) it infers a novel model parameter of interest Ω (i.e., the actual latitudinal and longitudinal coordinates), and (ii) it utilizes information from spatial summary statistics, specifically, pairwise population measures of F ST and the directionality index, Ψ (Peter & Slatkin, ). As such, x ‐ origin is an approach that focuses on the estimation of a specific parameter of interest—Ω, whereas the iDDC is an approach for model selection among a set of biologically informed demographic hypotheses, the foci of which vary significantly among studies (e.g., Bemmels, Title, Ortego, & Knowles, ; Knowles & Massatti, ; Massatti & Knowles, ).…”