<?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>James Sheppard</dc:contributor>
  <dc:contributor>Jun Zhu</dc:contributor>
  <dc:contributor>Fu-Wen Wei</dc:contributor>
  <dc:contributor>Ronald R. Swaisgood</dc:contributor>
  <dc:contributor>Robert N. Fisher</dc:contributor>
  <dc:creator>Jeff A. Tracey</dc:creator>
  <dc:date>2014</dc:date>
  <dc:description>Advances in digital biotelemetry technologies are enabling the collection of bigger and more accurate data on the movements of free-ranging wildlife in space and time. Although many biotelemetry devices record 3D location data with &lt;i&gt;x, y&lt;/i&gt;, and &lt;i&gt;z&lt;/i&gt; coordinates from tracked animals, the third z coordinate is typically not integrated into studies of animal spatial use. Disregarding the vertical component may seriously limit understanding of animal habitat use and niche separation. We present novel movement-based kernel density estimators and computer visualization tools for generating and exploring 3D home ranges based on location data. We use case studies of three wildlife species – giant panda, dugong, and California condor – to demonstrate the ecological insights and conservation management benefits provided by 3D home range estimation and visualization for terrestrial, aquatic, and avian wildlife research.</dc:description>
  <dc:format>application/pdf</dc:format>
  <dc:identifier>10.1371/journal.pone.0101205</dc:identifier>
  <dc:language>en</dc:language>
  <dc:publisher>Public Library of Science</dc:publisher>
  <dc:title>Movement-based estimation and visualization of space use in 3D for wildlife ecology and conservation</dc:title>
  <dc:type>article</dc:type>
</oai_dc:dc>