Files in this item
Modeling population effects of the Deepwater Horizon oil spill on a long-lived species
Item metadata
dc.contributor.author | Schwacke, Lori H. | |
dc.contributor.author | Marques, Tiago A. | |
dc.contributor.author | Thomas, Len | |
dc.contributor.author | Booth, Cormac | |
dc.contributor.author | Balmer, Brian C. | |
dc.contributor.author | Barratclough, Ashley | |
dc.contributor.author | Colegrove, Kathleen | |
dc.contributor.author | De Guise, Sylvain | |
dc.contributor.author | Garrison, Lance P. | |
dc.contributor.author | Gomez, Forrest M. | |
dc.contributor.author | Morey, Jeanine S. | |
dc.contributor.author | Mullin, Keith D. | |
dc.contributor.author | Quigley, Brian M. | |
dc.contributor.author | Rosel, Patricia | |
dc.contributor.author | Rowles, Teresa K. | |
dc.contributor.author | Takeshita, Ryan | |
dc.contributor.author | Townsend, Forrest I. | |
dc.contributor.author | Speakman, Todd R. | |
dc.contributor.author | Wells, Randall S. | |
dc.contributor.author | Zolman, Eric S. | |
dc.contributor.author | Smith, Cynthia R. | |
dc.date.accessioned | 2022-03-01T16:30:12Z | |
dc.date.available | 2022-03-01T16:30:12Z | |
dc.date.issued | 2022-07-20 | |
dc.identifier.citation | Schwacke , L H , Marques , T A , Thomas , L , Booth , C , Balmer , B C , Barratclough , A , Colegrove , K , De Guise , S , Garrison , L P , Gomez , F M , Morey , J S , Mullin , K D , Quigley , B M , Rosel , P , Rowles , T K , Takeshita , R , Townsend , F I , Speakman , T R , Wells , R S , Zolman , E S & Smith , C R 2022 , ' Modeling population effects of the Deepwater Horizon oil spill on a long-lived species ' , Conservation Biology , vol. 36 , no. 4 , e13878 . https://doi.org/10.1111/cobi.13878 | en |
dc.identifier.issn | 0888-8892 | |
dc.identifier.other | PURE: 277126194 | |
dc.identifier.other | PURE UUID: 5574e07e-2e91-425b-847b-55325e294462 | |
dc.identifier.other | RIS: urn:AD5339E0B3F1B6256492F3CC037A50EB | |
dc.identifier.other | ORCID: /0000-0002-2581-1972/work/109315935 | |
dc.identifier.other | ORCID: /0000-0002-7436-067X/work/109315967 | |
dc.identifier.other | WOS: 000755944700001 | |
dc.identifier.other | Scopus: 85124708803 | |
dc.identifier.uri | https://hdl.handle.net/10023/24971 | |
dc.description | This research was enabled partly by a grant from The Gulf of Mexico Research Initiative (GOMRI). | en |
dc.description.abstract | The 2010 Deepwater Horizon (DWH) oil spill exposed common bottlenose dolphins (Tursiops truncatus) in Barataria Bay, Louisiana to heavy oiling that caused increased mortality and chronic disease and impaired reproduction in surviving dolphins. We conducted photographic surveys and veterinary assessments in the decade following the spill. We assigned a prognostic score (good, fair, guarded, poor, or grave) for each dolphin to provide a single integrated indicator of overall health, and we examined temporal trends in prognostic scores. We used expert elicitation to quantify the implications of trends for the proportion of the dolphins that would recover within their lifetime. We integrated expert elicitation, along with other new information, in a population dynamics model to predict the effects of observed health trends on demography. We compared the resulting population trajectory with that predicted under baseline (no spill) conditions. Disease conditions persisted and have recently worsened in dolphins that were presumably exposed to DWH oil: 78% of those assessed in 2018 had a guarded, poor, or grave prognosis. Dolphins born after the spill were in better health. We estimated that the population declined by 45% (95% CI 14–74) relative to baseline and will take 35 years (95% CI 18–67) to recover to 95% of baseline numbers. The sum of annual differences between baseline and injured population sizes (i.e., the lost cetacean years) was 30,993 (95% CI 6607–94,148). The population is currently at a minimum point in its recovery trajectory and is vulnerable to emerging threats, including planned ecosystem restoration efforts that are likely to be detrimental to the dolphins’ survival. Our modeling framework demonstrates an approach for integrating different sources and types of data, highlights the utility of expert elicitation for indeterminable input parameters, and emphasizes the importance of considering and monitoring long-term health of long-lived species subject to environmental disasters. Article impact statement: Oil spills can have long-term consequences for the health of long-lived species; thus, effective restoration and monitoring are needed. | |
dc.format.extent | 13 | |
dc.language.iso | eng | |
dc.relation.ispartof | Conservation Biology | en |
dc.rights | Copyright © 2022 The Authors. Conservation Biology published by Wiley Periodicals LLC on behalf of Society for Conservation Biology. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. | en |
dc.subject | Dolphin | en |
dc.subject | Expert elicitation | en |
dc.subject | Health assessment | en |
dc.subject | Marine mammal | en |
dc.subject | Oil spill | en |
dc.subject | Population model | en |
dc.subject | Slow-living species | en |
dc.subject | GC Oceanography | en |
dc.subject | GE Environmental Sciences | en |
dc.subject | DAS | en |
dc.subject | SDG 14 - Life Below Water | en |
dc.subject | MCC | en |
dc.subject.lcc | GC | en |
dc.subject.lcc | GE | en |
dc.title | Modeling population effects of the Deepwater Horizon oil spill on a long-lived species | en |
dc.type | Journal article | en |
dc.description.version | Publisher PDF | en |
dc.contributor.institution | University of St Andrews. School of Mathematics and Statistics | en |
dc.contributor.institution | University of St Andrews. Scottish Oceans Institute | en |
dc.contributor.institution | University of St Andrews. Centre for Research into Ecological & Environmental Modelling | en |
dc.contributor.institution | University of St Andrews. Statistics | en |
dc.contributor.institution | University of St Andrews. Marine Alliance for Science & Technology Scotland | en |
dc.contributor.institution | University of St Andrews. School of Biology | en |
dc.identifier.doi | https://doi.org/10.1111/cobi.13878 | |
dc.description.status | Peer reviewed | en |
This item appears in the following Collection(s)
Items in the St Andrews Research Repository are protected by copyright, with all rights reserved, unless otherwise indicated.