Where were they from? Modelling the source stock of dolphins stranded after the Deepwater Horizon oil spill using genetic and stable isotope data

L. Thomas*, C. G. Booth, P. E. Rosel, A. Hohn, J. Litz, L. H. Schwacke

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)
4 Downloads (Pure)

Abstract

Understanding the source stock of common bottlenose dolphins Tursiops truncatus that stranded in the northern Gulf of Mexico subsequent to the Deepwater Horizon oil spill was essential to accurately quantify injury and apportion individuals to the appropriate stock. The aim of this study, part of the Natural Resource Damage Assessment (NRDA), was to estimate the proportion of the 932 recorded strandings between May 2010 and June 2014 that came from coastal versus bay, sound and estuary (BSE) stocks. Four sources of relevant information were available on overlapping subsets totaling 336 (39%) of the strandings: genetic stock assignment, stable isotope ratios, photo-ID and individual genetic-ID. We developed a hierarchical Bayesian model for combining these sources that weighted each data source for each stranding according to a measure of estimated precision: the effective sample size (ESS). The photo- and genetic-ID data were limited and considered to potentially introduce biases, so these data sources were excluded from analyses used in the NRDA. Estimates were calculated separately in 3 regions: East (of the Mississippi outflow), West (of the Mississippi outflow through Vermilion Bay, Louisiana) and Western Louisiana (west of Vermilion Bay to the Texas-Louisiana border); the estimated proportions of coastal strandings were, respectively 0.215 (95% CI: 0.169-0.263), 0.016 (0.036-0.099) and 0.622 (0.487-0.803). This method represents a general approach for integrating multiple sources of information that have differing uncertainties.

Original languageEnglish
Pages (from-to)253-264
Number of pages12
JournalEndangered Species Research
Volume33
Issue number1
DOIs
Publication statusPublished - 31 Jan 2017

Keywords

  • Bayesian hierarchical model
  • Data integration
  • Deepwater Horizon
  • Genetic assignment
  • Stable isotope ratios
  • Stranding

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