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

Abstract

Understanding the drivers of divergence in historically dynamic systems, such as sky islands, therefore rests on addressing key questions about the genetic consequences of different types of movement. Here we leverage recent conceptual and computational advances to capture variation in movement that can occur among individuals, over time, and across landscapes, under different hypotheses about the processes structuring genetic variation. Specifically, we use an integrative model-based approach (Fig. 1) that employs spatially explicit models of distributions in the present and past in a montane grasshopper from the Rocky Mountains, Melanoplus oregonensis (Orthoptera: Acrididae) to test hypotheses about the processes driving genetic divergence. Because this region was heavily impacted by Pleistocene glaciations (Fig. 2), and given that the grasshoppers are flightless montane specialists, we focus on two hypotheses: 1) restricted movement associated with the geographic isolation of contemporary sky islands, versus 2) movement related to colonization during shifting species distributions, may drive patterns of genetic divergence. Given the limited dispersal capability and habitat specificity of the species, we also consider alternative determinants of population connectivity (i.e. dispersal determined either by geographic distance or by differences in habitat suitability across the Rocky Mountain

Linking micro‐ and macroevolutionary perspectives to evaluate the role of Quaternary sea‐level oscillations in island diversification

“…A and S6), suggesting elevation does not currently appear as a major barrier to gene flow for Amphiacusta , although past population connectedness related to shifts in climatic conditions through time due to glacial cycles may have been mediated by elevation (e.g., Massatti and Knowles ; Lanier et al. ; Knowles and Massatti ). Climatic fluctuations across a topographically complex landscape may repeatedly divide and merge populations (McCormack 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

“…To make inferences using x ‐ origin that considers the effects of spatial and temporal environmental heterogeneity on the expansion process, x ‐ origin models the impact of this environmental heterogeneity on the expansion process. Specifically, heterogeneity in habitat suitability might be derived from ecological niche models (ENMs) for the present or the past (Sindato et al., ; Waltari et al., ), or from information on known barriers (e.g., mountain ranges, glaciers and bodies of water; Boehm et al., ; Knowles & Massatti, ; Waltari & Hickerson, ). These suitability maps are used to inform demographic dynamics associated with the expansion process by specifying different likely migration events as a function of spatial and/or temporal environmental heterogeneity.…”

“…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, ).…”

The origins and maintenance of global species endemism

“…Furthermore, biotic factors can strongly influence local species distributions (Jablonski, ), and some studies have shown macroecological signals of such species interactions (Gotelli, Graves, & Rahbek, ). Further research may integrate biotic factors including species interactions such as competition (Mordecai, Jaramillo, Ashford, Hechinger, & Lafferty, ), specialization (Fjeldså & Lovett, ), population and community dynamics (Locey & Lennon, ; Ralston, DeLuca, Feldman, & King, ), distributional shifts (Knowles & Massatti, ) and niche differentiation (Brown et al, ). A key question is whether and how such factors contribute to the origins and maintenance of species endemism in some areas and not in others that share similar environmental characteristics.…”