Rachel S. Crowhurst

Using simulations to evaluate Mantel-based methods for assessing landscape resistance to gene flow

Abstract Mantel‐based tests have been the primary analytical methods for understanding how landscape features influence observed spatial genetic structure. Simulation studies examining Mantel‐based approaches have highlighted major challenges associated with the use of such tests and fueled debate on when the Mantel test is appropriate for landscape genetics studies. We aim to provide some clarity in this debate using spatially explicit, individual‐based, genetic simulations to examine the effects of the following on the performance of Mantel‐based methods: (1) landscape configuration, (2) spatial genetic nonequilibrium, (3) nonlinear relationships between genetic and cost distances, and (4) correlation among cost distances derived from competing resistance models. Under most conditions, Mantel‐based methods performed poorly. Causal modeling identified the true model only 22% of the time. Using relative support and simple Mantel r values boosted performance to approximately 50%. Across all methods, performance increased when landscapes were more fragmented, spatial genetic equilibrium was reached, and the relationship between cost distance and genetic distance was linearized. Performance depended on cost distance correlations among resistance models rather than cell‐wise resistance correlations. Given these results, we suggest that the use of Mantel tests with linearized relationships is appropriate for discriminating among resistance models that have cost distance correlations <0.85 with each other for causal modeling, or <0.95 for relative support or simple Mantel r. Because most alternative parameterizations of resistance for the same landscape variable will result in highly correlated cost distances, the use of Mantel test‐based methods to fine‐tune resistance values will often not be effective.

Genetic relationships of hellbenders in the Ozark highlands of Missouri and conservation implications for the Ozark subspecies (Cryptobranchus alleganiensis bishopi)

The hellbender (Cryptobranchus alleganiensis) is an obligately aquatic salamander that is in decline due to habitat loss and disease. Two subspecies of hellbender have been described based on morphological characteristics: C. a. alleganiensis (eastern subspecies) and C. a. bishopi (Ozark hellbender). Current conservation strategies include captive propagation for restorative releases even though information regarding the current levels of genetic variability and structure within populations is not sufficient to effectively plan for conservation of the genetic diversity of the species. To investigate patterns of population structure in the hellbender, we genotyped 276 hellbenders from eight Missouri River drainages, representing both subspecies. Our results showed low levels of within-drainage diversity but strong population structure among rivers, and three distinct genetic clusters. FST values ranged from 0.00 to 0.61 and averaged 0.40. Our results confirmed previous reports that C. a. bishopi and C. a. alleganiensis are genetically distinct, but also revealed an equidistant relationship between two groups within C. a. bishopi and all populations of C. a. alleganiensis. Current subspecies delineations do not accurately incorporate genetic structure, and for conservation purposes, these three groups should be considered evolutionarily significant units.

Local Extinction and Unintentional Rewilding of Bighorn Sheep (Ovis canadensis) on a Desert Island

Bighorn sheep (Ovis canadensis) were not known to live on Tiburón Island, the largest island in the Gulf of California and Mexico, prior to the surprisingly successful introduction of 20 individuals as a conservation measure in 1975. Today, a stable island population of ∼500 sheep supports limited big game hunting and restocking of depleted areas on the Mexican mainland. We discovered fossil dung morphologically similar to that of bighorn sheep in a dung mat deposit from Mojet Cave, in the mountains of Tiburón Island. To determine the origin of this cave deposit we compared pellet shape to fecal pellets of other large mammals, and extracted DNA to sequence mitochondrial DNA fragments at the 12S ribosomal RNA and control regions. The fossil dung was 14C-dated to 1476–1632 calendar years before present and was confirmed as bighorn sheep by morphological and ancient DNA (aDNA) analysis. 12S sequences closely or exactly matched known bighorn sheep sequences; control region sequences exactly matched a haplotype described in desert bighorn sheep populations in southwest Arizona and southern California and showed subtle differentiation from the extant Tiburón population. Native desert bighorn sheep previously colonized this land-bridge island, most likely during the Pleistocene, when lower sea levels connected Tiburón to the mainland. They were extirpated sometime in the last ∼1500 years, probably due to inherent dynamics of isolated populations, prolonged drought, and (or) human overkill. The reintroduced population is vulnerable to similar extinction risks. The discovery presented here refutes conventional wisdom that bighorn sheep are not native to Tiburón Island, and establishes its recent introduction as an example of unintentional rewilding, defined here as the introduction of a species without knowledge that it was once native and has since gone locally extinct.

Simulating the spread of selection-driven genotypes using landscape resistance models for desert bighorn sheep

Landscape genetic studies based on neutral genetic markers have contributed to our understanding of the influence of landscape composition and configuration on gene flow and genetic variation. However, the potential for species to adapt to changing landscapes will depend on how natural selection influences adaptive genetic variation. We demonstrate how landscape resistance models can be combined with genetic simulations incorporating natural selection to explore how the spread of adaptive variation is affected by landscape characteristics, using desert bighorn sheep (Ovis canadensis nelsoni) in three differing regions of the southwestern United States as an example. We conducted genetic sampling and least-cost path modeling to optimize landscape resistance models independently for each region, and then simulated the spread of an adaptive allele favored by selection across each region. Optimized landscape resistance models differed between regions with respect to landscape variables included and their relationships to resistance, but the slope of terrain and the presence of water barriers and major roads had the greatest impacts on gene flow. Genetic simulations showed that differences among landscapes strongly influenced spread of adaptive genetic variation, with faster spread (1) in landscapes with more continuously distributed habitat and (2) when a pre-existing allele (i.e., standing genetic variation) rather than a novel allele (i.e., mutation) served as the source of adaptive genetic variation. The combination of landscape resistance models and genetic simulations has broad conservation applications and can facilitate comparisons of adaptive potential within and between landscapes.

Polymorphic microsatellite loci for studies of the Ozark hellbender ( Cryptobranchus alleganiensis bishopi )

The hellbender is the only North American member of the aquatic salamander family Cryptobranchidae and is a species of conservation concern across its range. We developed eight polymorphic microsatellite loci for hellbenders using a magnetic bead enrichment protocol and a PCR-based detection technique. Allelic diversity averaged 4.0 (±1.8 SD) per locus and heterozygosity averaged 0.56 (±0.30 SD). The hellbender is rare and difficult to study due to its cryptic life history. These loci will provide a valuable resource for population studies, which could inform future conservation and management decisions.