Appendix A. Derivation of Brownian bridge probability distribution when location errors are normally distributed.

Derivation of Brownian bridge probability distribution when location errors are normally distributed

Supplement 1. Visual Basic source code containing the algorithms described in this paper.

<h2>File List</h2><blockquote> <h3><i>All files at once</i></h3> <p><a href="BBridgeCode.zip">BBridgeCode.zip</a> -- zip file containing Visual Basic executable, source code, and example input file.</p> <h3><i>Individual files</i></h3> <p><a href="BrownianBridgeExecutable.exe">BrownianBridgeExecutable.exe</a> – Executable Visual Basic program<br> <a href="ProjBrownianBridge.vbp.txt">ProjBrownianBridge.vbp.txt</a> – Source code for Visual Basic program<br> <a href="ProjBrownianBridge.vbw.txt">ProjBrownianBridge.vbw.txt</a> – Source code for Visual Basic program<br> <a href="FrmBBAnalysis.frm.txt">FrmBBAnalysis.frm.txt</a> – Source code for Visual Basic program<br> <a href="FrmGridExtent.frm.txt">FrmGridExtent.frm.txt</a> – Source code for Visual Basic program<br> <a href="FrmOpenFileBB.frm.txt">FrmOpenFileBB.frm.txt</a> – Source code for Visual Basic program<br> <a href="FrmSaveASBrownBridge.frm.txt">FrmSaveASBrownBridge.txt</a> – Source code for Visual Basic program<br> <a href="Mod1DMinimization.bas.txt">Mod1DMinimization.bas.txt</a> – Source code for Visual Basic program<br> <a href="ModFileManagement.bas.txt">ModFileManagement.bas.txt</a> – Source code for Visual Basic program<br> <a href="ModPublicVariablesBB.bas.txt">ModPublicVariablesBB.bas.txt</a> – Source code for Visual Basic program<br> <a href="ExampleInput.txt">ExampleInput.txt</a>  – Example input file<br> </p> </blockquote><h2>Description</h2><blockquote> <p>BrownianBridgeExeecutable.exe calculates the utilization distribution (i.e., probability function) based on temporally explicit location data. Algorithms are described in the original paper. The user loads a location file containing tab-delimited columns representing the <i>x</i>-coordinate, <i>y</i>-coordinate, and time of each location. The input file should have column headings such as “<i>x</i>-coordinate”, “<i>y</i>-coordinate” and “RunningClock”.  An example input data file, ExampleInput.txt, is available from the file list. Output grid is a text file containing <i>x</i> and <i>y</i> coordinates of the grid along with associated probability-of-occurrence at that grid location.</p> </blockquote

Appendix B. Results of mark-resight models (Tables B1–B12) and occupancy models (Tables B13–B16) for bobcats and pumas on the Western Slope and Front Range, Colorado, USA.

Results of mark-resight models (Tables B1–B12) and occupancy models (Tables B13–B16) for bobcats and pumas on the Western Slope and Front Range, Colorado, USA

Appendix A. Comparing support of the covariates weight and sex in mark-resight models.

Comparing support of the covariates weight and sex in mark-resight models

Supplement 1. Data used for mark-resight, density, and occupancy analyses.

<h2>File List</h2><div> <p><a href="data.txt">data.txt</a> (MD5: 2763d8f75c752f0e190815df66121618) </p> </div><h2>Description</h2><div> <p>The data.txt is a tab-separated file. It contains the data for the mark-resight, density, and occupancy analyses for bobcats, pumas, and their prey on the Western Slope (exurban grid 1 and wildland grid 2) and Front Range (WUI grid 1 and wildland grid 2) grids.</p> <p>Column headings and definitions</p> <ol> <li>ch = capture history</li> <li>Time spent on grid (TSOG) = time spent on grid for individual animal based on telemetry locations</li> <li>Weight = weight (kg) of animal                </li> <li>Grid = urbanized (0) or wildland (1) sampling grid area</li> <li>HumDev = amount of human influence associated with camera location                                                                                                                                                     </li> </ol> For values of TSOG used in mark resight analysis, if telemetry data was not available for a particular individual (due to collar malfunction), then the mean value of TSOG across all other animals with functioning collars was used for an individual as a covariate value, but the mean value of TSOG for an animal was excluded when estimating density. For pumas that were captured and marked during camera surveys, their photos were counted as unmarked in mark-resight models, but their telemetry data was used to estimate TSOG for density. Please see manuscript for further details and notes about calculations and data used.                                                         </div

The effects of demographic, social, and environmental characteristics on pathogen prevalence in wild felids across a gradient of urbanization

<div><p>Transmission of pathogens among animals is influenced by demographic, social, and environmental factors. Anthropogenic alteration of landscapes can impact patterns of disease dynamics in wildlife populations, increasing the potential for spillover and spread of emerging infectious diseases in wildlife, human, and domestic animal populations. We evaluated the effects of multiple ecological mechanisms on patterns of pathogen exposure in animal populations. Specifically, we evaluated how ecological factors affected the prevalence of <i>Toxoplasma gondii</i> (Toxoplasma), <i>Bartonella spp</i>. (Bartonella), feline immunodeficiency virus (FIV), and feline calicivirus (FCV) in bobcat and puma populations across wildland-urban interface (WUI), low-density exurban development, and wildland habitat on the Western Slope (WS) and Front Range (FR) of Colorado during 2009–2011. Samples were collected from 37 bobcats and 29 pumas on the WS and FR. As predicted, age appeared to be positively related to the exposure to pathogens that are both environmentally transmitted (Toxoplasma) and directly transmitted between animals (FIV). In addition, WS bobcats appeared more likely to be exposed to Toxoplasma with increasing intraspecific space-use overlap. However, counter to our predictions, exposure to directly-transmitted pathogens (FCV and FIV) was more likely with decreasing space-use overlap (FCV: WS bobcats) and potential intraspecific contacts (FIV: FR pumas). Environmental factors, including urbanization and landscape covariates, were generally unsupported in our models. This study is an approximation of how pathogens can be evaluated in relation to demographic, social, and environmental factors to understand pathogen exposure in wild animal populations.</p></div

Predictions of how demographic, social, and environmental characteristics will influence exposure of pathogens in bobcat and puma populations.

<p>For each pathogen, the transmission model is included in parentheses. For each factor (demographic, social, and environment), the expected relative effect strength of each prediction is included in parentheses.</p

Variable importance values (VIV) for demographic, social (intraspecific and interspecific), and environmental (urban and landscape) categories for bobcats and pumas on the Western Slope (WS) and Front Range (FR) of Colorado, USA.

<p>VIV were used to assess the relative importance of groups of covariates in models evaluating pathogens in felid populations. A dash (i.e., -) indicates that models with this covariate could not be evaluated (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0187035#sec002" target="_blank">Methods</a>).</p

Model-averaged parameter estimates with associated standard errors for demographic, social (intraspecific and interspecific), and environmental (urban and landscape) categories for bobcats and pumas on the Western Slope (WS) and Front Range (FR) of Colorado, USA.

<p>A dash (i.e., -) indicates that models with this covariate could not be evaluated (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0187035#sec002" target="_blank">Methods</a>).</p

Locations of two study areas in Colorado, USA, which exhibited varying levels of urbanization, where bobcats and pumas were fit with telemetry collars.

<p>The more rural Western Slope (WS) was characterized by an exurban development south grid and a wildland north grid during 2009–2010. The more urbanized Front Range (FR) study area was characterized by a wildland-urban interface (WUI) south grid and wildland north grid during 2010–2012.</p