<?xml version='1.0' encoding='utf-8'?>
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:contributor>Tyler Wagner</dc:contributor>
  <dc:contributor>B.H. Tracy</dc:contributor>
  <dc:creator>S.R. Midway</dc:creator>
  <dc:date>2016</dc:date>
  <dc:description>&lt;p&gt;&lt;span&gt;The southeastern USA is home to one of the richest&amp;mdash;and most imperiled and threatened&amp;mdash;freshwater fish assemblages in North America. For many of these rare and threatened species, conservation efforts are often limited by a lack of data. Drawing on a unique and extensive data set spanning over 20&amp;nbsp;years, we modeled occurrence probabilities of 126 stream fish species sampled throughout North Carolina, many of which occur more broadly in the southeastern USA. Specifically, we developed species-specific occurrence probabilities from hierarchical Bayesian multispecies models that were based on common land use and land cover covariates. We also used index of biotic integrity tolerance classifications as a second level in the model hierarchy; we identify this level as informative for our work, but it is flexible for future model applications. Based on the partial-pooling property of the models, we were able to generate occurrence probabilities for many imperiled and data-poor species in addition to highlighting a considerable amount of occurrence heterogeneity that supports species-specific investigations whenever possible. Our results provide critical species-level information on many threatened and imperiled species as well as information that may assist with re-evaluation of existing management strategies, such as the use of surrogate species. Finally, we highlight the use of a relatively simple hierarchical model that can easily be generalized for similar situations in which conventional models fail to provide reliable estimates for data-poor groups.&lt;/span&gt;&lt;/p&gt;</dc:description>
  <dc:format>application/pdf</dc:format>
  <dc:identifier>10.1080/00028487.2014.931745</dc:identifier>
  <dc:language>en</dc:language>
  <dc:publisher>American Fisheries Society</dc:publisher>
  <dc:title>A hierarchical community occurrence model for North Carolina stream fish</dc:title>
  <dc:type>article</dc:type>
</oai_dc:dc>