Microsatellite data of Pseudocheirus occidentalis in Busselton, Western Australia

This file contains microsatellite scores of 145 adult western ringtail possums in Busselton, Western Australia. Genetic samples were collected from 2010 to 2013. Allele scores for 12 microsatellite markers are given in a basic table format and also in FSTAT input file format. Please refer to the published article for more information on the study blocks and microsatellite markers used

A map of a study area near Busselton, Western Australia.

<p>Red lines represent the borders of Caves Road (west to east) and blue lines represent the borders of an artificial waterway (north to south). 1A, 1B, 1-2C, 1D, 2A, 2B and 2D are 200 m × 200 m study blocks where samples from <i>Pseudocheirus occidentalis</i> were collected. 1A, 1-2C and 2A were inside Locke Nature Reserve, and 1B, 1D, 2B and 2D were within partially cleared campsites. The aerial photograph of the study area is used with permission from Western Australian Land Information Authority (Midland, WA Australia).</p

Summary of the Bayesian clustering analysis assuming three admixed populations of <i>Pseudocheirus occidentalis</i> in Busselton, Western Australia.

<p>Each column represents an individual’s estimated membership to three genetic clusters represented by different colours. Vertical dotted lines separate individuals sampled from different blocks. Vertical bold solid lines represent the presence of Caves Road and an artificial waterway.</p

Plot of two-dimensional local spatial autocorrelation analyses of <i>Pseudocheirus occidentalis</i> sampled in Locke Nature Reserve near Busselton, Western Australia.

<p>Red lines represent the borders of Caves Road (west to east) and blue lines represent the borders of an artificial waterway (north to south). The area south of Caves Road and west of the waterway is Locke Nature Reserve. Markers represent geographical locations of the local spatial autocorrelation analyses with significantly positive (solid symbols) or non-significant values (open symbols) based on five nearest neighbours. Coordinates are based on GDA 94 projection (zone 50).</p

Summary of Δ<i>K</i> estimates[30] for varying numbers of genetic clusters (<i>K</i>) derived from the STRUCTURE analysis of 145 adult <i>Pseudocheirus occidentalis</i> from Busselton, Western Australia.

<p>Summary of Δ<i>K</i> estimates[<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0146167#pone.0146167.ref030" target="_blank">30</a>] for varying numbers of genetic clusters (<i>K</i>) derived from the STRUCTURE analysis of 145 adult <i>Pseudocheirus occidentalis</i> from Busselton, Western Australia.</p

(a) A correlogram plot and (b) a multiple distance class plot based on 69 <i>Pseudocheirus occidentalis</i> in continuous habitat in Locke Nature Reserve near Busselton, Western Australia.

<p>Dotted lines (a) and small blue markers (b) represent upper and lower 95% confidence intervals around zero. Red circle markers on the solid line (a) and red markers (b) are the genetic correlation values (<i>r</i>) that differ significantly from zero based on bootstrap resampling. Sample sizes are shown in parentheses.</p

Mean pairwise relatedness values [34] for <i>Pseudocheirus occidentalis</i> individuals sampled from the same block (“Within”), different blocks on the same side of an artificial barrier (“Same”) and opposite sides of an artificial barrier (“Opposite”).

<p>Error bars represent the 95% confidence levels determined by bootstrap resampling, and values in parentheses are the numbers of pairwise comparisons from which the average pairwise relatedness values were calculated. Asterisks represent mean values significantly different to zero determined by a permutation test.</p

Demographic and genetic viability of a medium-sized ground-dwelling mammal in a fire prone, rapidly urbanizing landscape

<div><p>The rapid and large-scale urbanization of peri-urban areas poses major and complex challenges for wildlife conservation. We used population viability analysis (PVA) to evaluate the influence of urban encroachment, fire, and fauna crossing structures, with and without accounting for inbreeding effects, on the metapopulation viability of a medium-sized ground-dwelling mammal, the southern brown bandicoot (<i>Isoodon obesulus</i>), in the rapidly expanding city of Perth, Australia. We surveyed two metapopulations over one and a half years, and parameterized the PVA models using largely field-collected data. The models revealed that spatial isolation imposed by housing and road encroachment has major impacts on <i>I</i>. <i>obesulus</i>. Although the species is known to persist in small metapopulations at moderate levels of habitat fragmentation, the models indicate that these populations become highly vulnerable to demographic decline, genetic deterioration, and local extinction under increasing habitat connectivity loss. Isolated metapopulations were also predicted to be highly sensitive to fire, with large-scale fires having greater negative impacts on population abundance than small-scale ones. To reduce the risk of decline and local extirpation of <i>I</i>. <i>obesulus</i> and other small- to medium-sized ground-dwelling mammals in urbanizing, fire prone landscapes, we recommend that remnant vegetation and vegetated, structurally-complex corridors between habitat patches be retained. Well-designed road underpasses can be effective to connect habitat patches and reduce the probability of inbreeding and genetic differentiation; however, adjustment of fire management practices to limit the size of unplanned fires and ensure the retention of long unburnt vegetation will also be required to ensure persistence. Our study supports the evidence that in rapidly urbanizing landscapes, a pro-active conservation approach is required that manages species at the metapopulation level and that prioritizes metapopulations and habitat with greater long-term probability of persistence and conservation capacity, respectively. This strategy may help us prevent future declines and local extirpations, and currently relatively common species from becoming rare.</p></div

Demographic and population parameters used for the population viability analysis of <i>I</i>. <i>obesulus</i>, and respective data sources.

<p>Demographic and population parameters used for the population viability analysis of <i>I</i>. <i>obesulus</i>, and respective data sources.</p

Sensitivity of population viability to changes in carrying capacity (<i>K</i>), maximum growth rate (<i>Rmax</i>), demographic rates (vital rates means), and environmental stochasticity (vital rates standard deviations) for the Roe Highway (a) and Mandjoogoordap Drive (b) metapopulations.

<p>Sensitivity is represented as the percent change in expected minimum abundance relative to the base model. Note that y-axes have different scales.</p