The University of St Andrews

Research@StAndrews:FullText >
University of St Andrews Research >
University of St Andrews Research >
University of St Andrews Research >

Please use this identifier to cite or link to this item:
This item has been viewed 20 times in the last year. View Statistics

Files in This Item:

File Description SizeFormat
Jewell_et_al_2012.pdf411.13 kBAdobe PDFView/Open
Title: Global analysis of cetacean line-transect surveys : detecting trends in cetacean density
Authors: Jewell, Rebecca Lucy
Thomas, Len
Harris, Catriona M
Kaschner, Kristin
Wiff, Rodrigo Alexis
Hammond, Philip Steven
Quick, Nicola Jane
Keywords: Marine mammal density
Population trends
Generalised additive modelling
Power analysis
QL Zoology
QA Mathematics
Issue Date: 7-May-2012
Citation: Jewell , R L , Thomas , L , Harris , C M , Kaschner , K , Wiff , R A , Hammond , P S & Quick , N J 2012 , ' Global analysis of cetacean line-transect surveys : detecting trends in cetacean density ' Marine Ecology Progress Series , vol 453 , pp. 227-240 . , 10.3354/meps09636
Abstract: Measuring the effect of anthropogenic change on cetacean populations is hampered by our lack of understanding about population status and a lack of power in the available data to detect trends in abundance. Often long-term data from repeated surveys are lacking, and alternative approaches to trend detection must be considered. We utilised an existing database of line transect survey records to determine whether temporal trends could be detected when survey effort from around the world was combined. We extracted density estimates for 25 species and fitted generalised additive models (GAMs) to investigate whether taxonomic, spatial or methodological differences among systematic line-transect surveys affect estimates of density and whether we can identify temporal trends in the data once these factors are accounted for. The selected GAM consisted of 2 parts: an intercept term that was a complex interaction of taxonomic, spatial and methodological factors and a smooth temporal term with trends varying by family and ocean basin. We discuss the trends found and assess the suitability of published density estimates for detecting temporal trends using retrospective power analysis. In conclusion, increasing sample size through combining survey effort across a global scale does not necessarily result in sufficient power to detect trends because of the extent of variability across surveys, species and oceans. Instead, results from repeated dedicated surveys designed specifically for the species and geographical region of interest should be used to inform conservation and management.
Version: Publisher PDF
Status: Peer reviewed
ISSN: 0171-8630
Type: Journal article
Rights: © Inter-Research 2012. This is an open access article.
Appears in Collections:NERC Sea Mammal Research Unit (SMRU) Research
University of St Andrews Research
Biology Research
Statistics Research
Centre for Research into Ecological & Environmental Modelling (CREEM) Research
Scottish Oceans Institute Research

This item is protected by original copyright

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.


DSpace Software Copyright © 2002-2012  Duraspace - Feedback
For help contact: | Copyright for this page belongs to St Andrews University Library | Terms and Conditions (Cookies)