Doser_etal_2024_JABES

Add Doser_etal_2024_JABES front face page

index.html

@@ -343,7 +343,31 @@ <h1>Integrated community occupancy models: A framework to assess occurrence and
 <!-- Project  -->
 <h2 id="unmarked">Unmarked population models</h2>
 <p>We develop models to estimate the abundance, distribution, and demographic rates of populations using unmarked data, or data types that do not track individuals. These efforts allow us to quantitatively evaluate important life history parameters with less sampling effort than is traditionally required with mark-recapture studies.</p>
-<p><h3> <em><a href="#unmarked2024D">Doser_etal_2024_GEB</a></em> | <em><a href="#unmarked2022F">Farr_etal_2022_ConsBio</a></em> | <em><a href="#unmarkedrevD">DiRenzo_etal_2019_EcolAndEvol</a></em> | <em><a href="#unmarked2018D">DiRenzo_etal_2018_EcoApps</a></em> | <em><a href="#unmarked2018S">Saunders_etal_2018_Ecog</a></em> | <em><a href="#unmarked2016R">Rossman_etal_2016_Ecol</a></em> | <em><a href="#unmarked2016S">Saunders_etal_2016_GEB</a></em> | <em><a href="#unmarked2014Z">Zipkin_etal_2014_Ecol</a></em> | <em><a href="#unmarked2014Z2">Zipkin_etal_2014_EcolAndEvol</a></em></p>
+<p><h3> <em><a href="#unmarked2024D">Doser_etal_2024_JABES</a></em> | <em><a href="#unmarked2024D">Doser_etal_2024_GEB</a></em> | <em><a href="#unmarked2022F">Farr_etal_2022_ConsBio</a></em> | <em><a href="#unmarkedrevD">DiRenzo_etal_2019_EcolAndEvol</a></em> | <em><a href="#unmarked2018D">DiRenzo_etal_2018_EcoApps</a></em> | <em><a href="#unmarked2018S">Saunders_etal_2018_Ecog</a></em> | <em><a href="#unmarked2016R">Rossman_etal_2016_Ecol</a></em> | <em><a href="#unmarked2016S">Saunders_etal_2016_GEB</a></em> | <em><a href="#unmarked2014Z">Zipkin_etal_2014_Ecol</a></em> | <em><a href="#unmarked2014Z2">Zipkin_etal_2014_EcolAndEvol</a></em></p>
+
+<br><br>
+<h3 id="unmarked2024D">Doser_etal_2024_JABES</h3>
+<section class="example">
+    <section class="title">
+    <h1>Guidelines for the use of spatially-varying coefficients in species distribution models</h1>
+    <img class="modal-img" src="assets/images/Farr2022_ConsBio.png" alt="TBD" height="200" width="200">
+	      <div class="modal" id="Doser et al. 2024">
+		      <span class="close">&times;</span>
+		      <img class="modal-content">
+		      <div class="modal-caption"></div>
+	      </div>    
+    </section>
+    <section class="content">
+    <p>
+      <strong>Citation</strong> - <a href="https://github.com/doserjef">Doser, J.W.</a>, Finley, A.O., Saunders, S.P., Kéry, Weed, A.S., and <a href="https://github.com/ezipkin"> Zipkin E.F.</a> (2024) Modeling complex species-environment relationships through spatially-varying coefficient occupancy models. <em>Journal of Agricultural, Biological and Environmental Statistics</em>. <a href=https://conbio-onlinelibrary-wiley-com.proxy2.cl.msu.edu/doi/10.1111/cobi.13934>DOI: TBD </a>
+    </p>
+    <p>
+      <strong>Abstract</strong> -  Occupancy models are frequently used by ecologists to quantify spatial variation in species distributions while accounting for observational biases (e.g., false-negative errors) in collection of detection-nondetection data. However, the common assumption that a single set of regression coefficients can adequately explain species-environment relationships is often biologically unrealistic across large spatial domains. Here we develop computationally-efficient single-species (i.e., univariate) and multi-species (i.e., multivariate) spatially-varying coefficient (SVC) occupancy models to account for spatially-varying species-environment relationships. Our models are particularly relevant for quantifying species-environment relationships using detection-nondetection data from large-scale monitoring programs, which are becoming increasingly prevalent for answering macroscale ecological questions regarding wildlife responses to global change.    </p>
+    <p>
+      <strong>Code and Data</strong> - <a href="https://github.com/zipkinlab/Doser_etal_2024_JABES">Link to repo</a>
+    </p>
+  </section>
+</section>
 
 <br><br>
 <h3 id="unmarked2024D">Doser_etal_2024_GEB</h3>