Resolving spatial complexities of hybridization in the context of the gray zone of speciation in North American ratsnakes (Pantherophis obsoletuscomplex)

Abstract

Inferring the history of divergence between species in a framework that permits the presence of gene flow has been crucial for characterizing the “gray zone” of speciation, which is the period of time where lineages have diverged but have not yet achieved strict reproductive isolation. However, estimates of both divergence times and rates of gene flow often ignore spatial information, for example when considering the location and width of hybrid zones with respect to changes in the environment between lineages. Using population genomic data from the North American ratsnake complex (Pantherophis obsoletus), we connected phylogeographic estimates of lineage structure, migration, historical demography, and timing of divergence with hybrid zone dynamics. We examined the spatial context of diversification by linking migration and timing of divergence to the location and widths of hybrid zones. Artificial neural network approaches were applied to understand how landscape features and past climate have influenced population genetic structure among these lineages. We found that rates of migration between lineages were associated with the overall width of hybrid zones. Timing of divergence was not related to migration rate or hybrid zone width across species pairs but may be related to the number of alleles weakly introgressing through hybrid zones. This research underscores how incomplete reproductive isolation can be better understood by considering differential allelic introgression and the effects of historical and contemporary landscape features on the formation of lineages as well as overall genomic estimates of migration rates through time.

Contemporary Philosophy and Methods for Studying Speciation and Delimiting Species

“…This topology and the support for each of these four species would be consistent with our knowledge until~2001 (see Conant and Collins, 1998). Exploring population structure within each species across their geographic ranges using coalescent-based species delimitation methods would find additional structure consistent with what has subsequently been described as species within Pantherophis obsoletus, P. guttatus, and P. vulpinus (Burbrink et al, 2000(Burbrink et al, , 2021Burbrink, 2001Burbrink, , 2002Crother et al, 2011;Myers et al, 2020). Whether these additional delimitations represent species or populations may be difficult to answer using the MSC alone, though morphology and ecology have aided delimitation in some of these.…”

“…For instance, effective estimates of migration surfaces (EEMS; Petkova et al, 2016) can visualize where genetic similarity by migration decays faster than expected by IBD, thus highlighting areas of reduced gene flow at geographic boundaries. This method has been used successfully in studies on reptiles and amphibians to identify areas of low migration (Homola et al, 2019;Myers et al, 2019b;Chan and Brown, 2020;Burbrink et al, 2021). Modeling population structure given continuous (geographic) and discrete (reproductive isolation) processes can be used to separate clines vs. geographic clusters using programs such as conStruct (Bradburd et al, 2018).…”

“…Modeling population structure given continuous (geographic) and discrete (reproductive isolation) processes can be used to separate clines vs. geographic clusters using programs such as conStruct (Bradburd et al, 2018). Additionally, redundancy analyses or machine learning can be used to isolate nonspatial effects on genetic structure, fully supplanting reliance on incorrect Mantel tests (Diniz-Filho et al, 2013;Burbrink et al, 2021;Martin et al, 2021). Resistance or conductive surfaces representing spatial and environmental covariates on genetic dissimilarity between mapped individuals can also partial out the effects of space of population structure (Peterman and Pope, 2021), though these methods may only indicate that genetic changes are occurring over environmental gradients.…”

“…Once taxa are established, dissecting how and when contemporary and historical landscapes isolated populations and facilitated speciation through time is achievable. Biologically relevant information, including ecology, physical barriers, gene flow, historical climate, landscape resistance, and geographic space can be used to predict the causes of species formation when using techniques such as redundancy analyses, conductance surface techniques, generalized dissimilarity modeling, and machine learning approaches (Ferrier et al, 2007;Zhang, 2010;Diniz-Filho et al, 2013;Burbrink and Gehara, 2018;Burbrink et al, 2021;Peterman and Pope, 2021). Such methods allow us to understand how predictor variables (e.g., environment, physical barriers) influence resulting population and species structure.…”

Phylogenomic Assessment of Biodiversity Using a Reference-Based Taxonomy: An Example With Horned Lizards (Phrynosoma)

“…However, as shown in the current study, even sparse sampling throughout parapatric population borders can reveal gene flow between putative taxa, complicating our understandings of species boundaries. Introgression more generally poses a challenge for species delimitation (Burbrink et al, 2021;Jiao and Yang, 2021). An influx of genomic data has revealed that introgression is common during population divergence and between species (Edwards et al, 2016).…”