<?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>Mark T. Wiltermuth</dc:contributor>
  <dc:contributor>Mark H. Sherfy</dc:contributor>
  <dc:contributor>Terry L. Shaffer</dc:contributor>
  <dc:creator>Michael J. Anteau</dc:creator>
  <dc:date>2014</dc:date>
  <dc:description>Measuring habitat and understanding habitat dynamics have become increasingly important for wildlife conservation. Using remotely-sensed data, we developed procedures to measure breeding habitat abundance for the federally listed piping plover (Charadrius melodus) at Lake Sakakawea, North Dakota, USA. We also developed a model to predict habitat abundance based on past and projected water levels, vegetation colonization rates, and topography. Previous studies define plover habitat as flat areas (&lt;10% slope) with ≤30% obstruction of bare substrate. Compared to ground-based data, remotely-sensed habitat classifications (≤30/&gt;30% bare-substrate obstruction) were 76% correct and omission and commission errors were equal. Due to water level fluctuations, habitat abundance varied markedly among years (1986–2009) ranging from 9 to 5195 ha. The proportion bare substrate declined with the number of years since a contour was inundated until 5 years (&amp;beta; = -0.65, SE = 0.05), then it stabilized near zero, and the decline varied by shoreline segment (5, 50, and 95 percentile were &amp;beta; = -0.19, SE = 0.05, &amp;beta; = -0.63, SE = 0.05, and &amp;beta; = -0.91, SE = 0.05, respectively). Years since inundated predicted habitat abundance well at shoreline segments (R&lt;sup&gt;2&lt;/sup&gt; = 0.77), but it predicted better for the whole lake (R&lt;sup&gt;2&lt;/sup&gt; = 0.86). The vastness and dynamics of plover habitat on Lake Sakakawea suggest that this is a key area for conservation of this species. Model-based habitat predictions can benefit resource conservation because they can (1) form the basis for a sampling stratification, (2) help allocate monitoring efforts among areas, and (3) help inform management through simulations or what-if scenarios.</dc:description>
  <dc:format>application/pdf</dc:format>
  <dc:identifier>10.1016/j.ecolmodel.2013.08.020</dc:identifier>
  <dc:language>en</dc:language>
  <dc:publisher>Elsevier</dc:publisher>
  <dc:title>Measuring and predicting abundance and dynamics of habitat for piping plovers on a large reservoir</dc:title>
  <dc:type>article</dc:type>
</oai_dc:dc>