Figure S1 Mojave clade

Figure S1 Mojave clad

Integrating Multiple Distribution Models to Guide Conservation Efforts of an Endangered Toad

<div><p>Species distribution models are used for numerous purposes such as predicting changes in species’ ranges and identifying biodiversity hotspots. Although implications of distribution models for conservation are often implicit, few studies use these tools explicitly to inform conservation efforts. Herein, we illustrate how multiple distribution models developed using distinct sets of environmental variables can be integrated to aid in identification sites for use in conservation. We focus on the endangered arroyo toad (<i>Anaxyrus californicus</i>), which relies on open, sandy streams and surrounding floodplains in southern California, USA, and northern Baja California, Mexico. Declines of the species are largely attributed to habitat degradation associated with vegetation encroachment, invasive predators, and altered hydrologic regimes. We had three main goals: 1) develop a model of potential habitat for arroyo toads, based on long-term environmental variables and all available locality data; 2) develop a model of the species’ current habitat by incorporating recent remotely-sensed variables and only using recent locality data; and 3) integrate results of both models to identify sites that may be employed in conservation efforts. We used a machine learning technique, Random Forests, to develop the models, focused on riparian zones in southern California. We identified 14.37% and 10.50% of our study area as potential and current habitat for the arroyo toad, respectively. Generally, inclusion of remotely-sensed variables reduced modeled suitability of sites, thus many areas modeled as potential habitat were not modeled as current habitat. We propose such sites could be made suitable for arroyo toads through active management, increasing current habitat by up to 67.02%. Our general approach can be employed to guide conservation efforts of virtually any species with sufficient data necessary to develop appropriate distribution models.</p></div

Aerial imagery of sites modeled as suitable and not suitable for arroyo toads based on current conditions.

<p>All four panels (A-D) depict a 100 m buffer of stream channels (outlined and hatched in blue), overlaid on 2010 aerial imagery. Sites presented in all panels were modeled to be suitable based on relatively static long-term environmental variables. Based on relatively dynamic variables associated with recent land cover, the sites in panels A and D were modeled to be currently suitable, with open, sandy habitats around the streams, but those in panels B and C were not, with considerable vegetation encroachment and anthropogenic development, respectively. The inset (middle) depicts the location of each site, within the focal study area of southwestern California, USA. The imagery is 1 m pixel resolution, and is public domain, courtesy of the U.S. Department of Agriculture, Farm Service Agency.</p

FigS2 Sonoran clade

FigS2 Sonoran clad

Table S1

Tissue samples used in this study including mtDNA lineage/clade and microsatellite cluster assignments, whether morphology was scored, and specific locality information

FigS3 Colorado clade

FigS3 Colorado clad

Modeled current distribution of the arroyo toad in southwestern California.

<p>This map depicts the modeled current distribution of the arroyo toad in streams and stream-side areas of southwestern California. Input data included presence/absence and pseudoabsence data, long-term environmental data representing characteristics of topography, soil, and climate, and indices of Brightness, Greenness, and Wetness, which represent more dynamic characteristics of land cover, derived from 2010 Landsat TM imagery. The Random Forests algorithm was used to develop the model, from which we predicted the probability of arroyo toad presence throughout our study area. The model performed well, with an Area Under the Receiver Operating Curve and True Skill Statistic of 1.0. The lowest modeled probability of arroyo toad presence for a site known to have arroyo toads was 0.492. Sites with modeled probability of presence less than this value were designated as not habitat (blue) and sites with probabilities of occurrence greater than or equal to this value were designated as habitat (yellow). Of 46,305 sample units, arroyo toads were predicted to occur in 10.57% based on relatively static landscape characteristics.</p

Phylogeny for the western shovel-nosed snake (<i>Chionactis occipitalis</i>) based on partitioned Bayesian analysis of mitochondrial DNA sequence data (16S rRNA and ND1 genes) and the geographic distribution of the major lineages (Mojave lineage in blue, Sonoran lineage in red, and Colorado lineage in green).

<p>The geographic distribution of clades within each lineage are outlined with a dashed line, clade E (yellow clade and dots) was routinely placed as sister to the Sonoran lineage, but posterior probabilities supporting this relationship were weak (<i>Pp</i> < 0.50). Black circles at nodes represent Bayesian posterior probabilities of ≥ 0.95. See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0097494#pone.0097494.s001" target="_blank">Figures S1</a>-<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0097494#pone.0097494.s003" target="_blank">3</a> for more detail within each mtDNA lineage.</p

Map of streams and topography of southwestern California.

<p>This map illustrates streams (in blue), overlaid on a hillshade layer of southwestern California, USA, covering five focal watersheds: the Aliso-San Onofre, the San Luis Rey-Escondido, the San Diego, the Santa Margarita, and the U.S. portion of the Cottonwood-Tijuana.</p

CHIONACTIS_mtDNA_ND1_Matrix

ND1 mtDNA sequence data for all samples used in this study. The sequence matrix is aligned and in nexus format