Unraveling natural versus anthropogenic effects on genetic diversity within the southeastern beach mouse (Peromyscus polionotus niveiventris)

Using high-throughput sequencing to investigate the factors structuring genomic variation of a Mediterranean grasshopper of great conservation concern

Inferring the demographic history of species is fundamental for understanding their responses to past climate/landscape alterations and improving our predictions about the future impacts of the different components of ongoing global change. Estimating the time-frame at which population fragmentation took place is also critical to determine whether such process was shaped by ancient events (e.g. past climate/geological changes) or if, conversely, it was driven by recent human activities (e.g. habitat loss). We employed genomic data (ddRAD-Seq) to determine the factors shaping contemporary patterns of genetic variation in the Iberian cross-backed grasshopper Dociostaurus crassiusculus, an endangered species with limited dispersal capacity and narrow habitat requirements. Our analyses indicate the presence of two ancient lineages and three genetic clusters resulted from historical processes of population fragmentation (~18-126 ka) that predate the Anthropocene. Landscape genetic analyses indicate that the limits of major river basins are the main geographical feature explaining large-scale patterns of genomic differentiation, with no apparent effect of human-driven habitat fragmentation. Overall, our study highlights the importance of detailed phylogeographic, demographic and spatially-explicit landscape analyses to identify evolutionary significant units and determine the relative impact of historical vs. anthropogenic factors on processes of genetic fragmentation in taxa of great conservation concern.

Preventing Tracking-Tube False Detections in Occupancy Modeling of Southeastern Beach Mouse

Quantifying habitat occupancy of the southeastern beach mouse Peromyscus polionotus niveiventris is important for managing this threatened species throughout its limited range. Tracking tubes were used to detect the southeastern beach mouse in coastal areas on the federal lands of the Kennedy Space Center, Cape Canaveral Air Force Station, and Canaveral National Seashore. Because this method relied on observations of footprints, detections of beach mice were confounded by the co-occurrence of cotton mice Peromyscus gossypinus, which have wider but slightly overlapping footprint widths. Mice of both species were captured and footprinted using tracking tubes to collect a database of footprints of known identity. These data were used to develop a Bayesian hierarchical model of the cutoff width at which a print could be assigned as a beach mouse with a known probability of error. Specifically, within the model, observed footprint widths were used to estimate a mean and variance of footprint width for each species, while accounting for variation between individual mice. Then, a distribution of new footprint widths was generated for each species by drawing from their modeled distributions. Finally, the new footprints were compared with a range of potential cutoff widths to evaluate the proportion of times the correct decision to exclude or accept the footprint was made. We graphically evaluated the performance of the cutoff widths and chose one that traded off between reducing false positives and retaining more correct detections for use in occupancy models. We explored the use of the cutoff width using occupancy models that allow for false-positive detections, and found that the use of the cutoff performed as expected. Over 40% of primary dune habitat on the Kennedy Space Center was occupied by beach mice during the period sampled. The proportion of vegetated habitat at a site had a negative influence on detection probability. No ecological covariates had a measurable influence on beach mouse occupancy, probably due to the limited range of environmental variation in the sampled region. The use of a cutoff for footprint width resulted in a reliable method to deal with false-positive detections in tracking tubes with small mammals and allowed the use of occupancy models that rely on certain detection.