<?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>Russell W. Perry</dc:contributor>
  <dc:contributor>Patricia L. Brandes</dc:contributor>
  <dc:contributor>Noah S. Adams</dc:contributor>
  <dc:creator>Christopher M. Holbrook</dc:creator>
  <dc:date>2013</dc:date>
  <dc:description>&lt;p&gt;In telemetry studies, premature tag failure causes negative bias in fish survival estimates because tag failure is interpreted as fish mortality. We used mark-recapture modeling to adjust estimates of fish survival for a previous study where premature tag failure was documented. High rates of tag failure occurred during the Vernalis Adaptive Management Plan&amp;rsquo;s (VAMP) 2008 study to estimate survival of fall-run Chinook salmon (&lt;i class="EmphasisTypeItalic "&gt;Oncorhynchus tshawytscha&lt;/i&gt;) during migration through the San Joaquin River and Sacramento-San Joaquin Delta, California. Due to a high rate of tag failure, the observed travel time distribution was likely negatively biased, resulting in an underestimate of tag survival probability in this study. Consequently, the bias-adjustment method resulted in only a small increase in estimated fish survival when the observed travel time distribution was used to estimate the probability of tag survival. Since the bias-adjustment failed to remove bias, we used historical travel time data and conducted a sensitivity analysis to examine how fish survival might have varied across a range of tag survival probabilities. Our analysis suggested that fish survival estimates were low (95% confidence bounds range from 0.052 to 0.227) over a wide range of plausible tag survival probabilities (0.48&amp;ndash;1.00), and this finding is consistent with other studies in this system. When tags fail at a high rate, available methods to adjust for the bias may perform poorly. Our example highlights the importance of evaluating the tag life assumption during survival studies, and presents a simple framework for evaluating adjusted survival estimates when auxiliary travel time data are available.&lt;/p&gt;</dc:description>
  <dc:format>application/pdf</dc:format>
  <dc:identifier>10.1007/s10641-012-0016-3</dc:identifier>
  <dc:language>en</dc:language>
  <dc:publisher>Kluwer Academic Publishers</dc:publisher>
  <dc:title>Adjusting survival estimates for premature transmitter failure: A case study from the Sacramento-San Joaquin Delta</dc:title>
  <dc:type>article</dc:type>
</oai_dc:dc>