Drivers and annual estimates of marine wildlife entanglement rates: A long-term case study with Australian fur seals

Methods of calculating wildlife entanglement rates are not standardised between studies and often ignore the influence of observer effort, confounding comparisons. From 1997–2013 we identified 359 entangled Australian fur seals at Seal Rocks, south-eastern Australia. Most entanglement materials orig...

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Published inMarine pollution bulletin Vol. 101; no. 2; pp. 716 - 725
Main Authors McIntosh, Rebecca R., Kirkwood, Roger, Sutherland, Duncan R., Dann, Peter
Format Journal Article
LanguageEnglish
Published England Elsevier Ltd 30.12.2015
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Abstract Methods of calculating wildlife entanglement rates are not standardised between studies and often ignore the influence of observer effort, confounding comparisons. From 1997–2013 we identified 359 entangled Australian fur seals at Seal Rocks, south-eastern Australia. Most entanglement materials originated from commercial fisheries; most frequently entangling pups and juveniles. Using Generalized Additive Mixed Models, which incorporated observer effort and survey frequency, we identified that entanglements were observed more frequently amongst pups from July to October as they approached weaning. Neither the decline in regional fishing intensity nor changing seal population size influenced the incidence of entanglements. Using the models, we estimated that 302 (95% CI=182–510) entangled seals were at Seal Rocks each year, equivalent to 1.0% (CI=0.6–1.7%) of the site population. This study highlights the influence of observer effort and the value of long-term datasets for determining the drivers of marine debris entanglements. •We modelled long-term drivers of Australian fur seal entanglement rates.•Applying GAMM models also allowed the estimation of total entanglements per year.•Observer effort was a stronger driver than fishing intensity and population size.•More pups were entangled as they approached weaning each year.•Estimated annual rates were an order of magnitude higher than observed rates.
AbstractList Methods of calculating wildlife entanglement rates are not standardised between studies and often ignore the influence of observer effort, confounding comparisons. From 1997-2013 we identified 359 entangled Australian fur seals at Seal Rocks, south-eastern Australia. Most entanglement materials originated from commercial fisheries; most frequently entangling pups and juveniles. Using Generalized Additive Mixed Models, which incorporated observer effort and survey frequency, we identified that entanglements were observed more frequently amongst pups from July to October as they approached weaning. Neither the decline in regional fishing intensity nor changing seal population size influenced the incidence of entanglements. Using the models, we estimated that 302 (95% CI=182-510) entangled seals were at Seal Rocks each year, equivalent to 1.0% (CI=0.6-1.7%) of the site population. This study highlights the influence of observer effort and the value of long-term datasets for determining the drivers of marine debris entanglements.
Methods of calculating wildlife entanglement rates are not standardised between studies and often ignore the influence of observer effort, confounding comparisons. From 1997–2013 we identified 359 entangled Australian fur seals at Seal Rocks, south-eastern Australia. Most entanglement materials originated from commercial fisheries; most frequently entangling pups and juveniles. Using Generalized Additive Mixed Models, which incorporated observer effort and survey frequency, we identified that entanglements were observed more frequently amongst pups from July to October as they approached weaning. Neither the decline in regional fishing intensity nor changing seal population size influenced the incidence of entanglements. Using the models, we estimated that 302 (95% CI=182–510) entangled seals were at Seal Rocks each year, equivalent to 1.0% (CI=0.6–1.7%) of the site population. This study highlights the influence of observer effort and the value of long-term datasets for determining the drivers of marine debris entanglements. •We modelled long-term drivers of Australian fur seal entanglement rates.•Applying GAMM models also allowed the estimation of total entanglements per year.•Observer effort was a stronger driver than fishing intensity and population size.•More pups were entangled as they approached weaning each year.•Estimated annual rates were an order of magnitude higher than observed rates.
Author Sutherland, Duncan R.
Kirkwood, Roger
Dann, Peter
McIntosh, Rebecca R.
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Keywords Arctocephalus pusillus doriferus
Plastic
Ghost nets
Otariid
Fisheries interactions
Marine debris
Language English
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Snippet Methods of calculating wildlife entanglement rates are not standardised between studies and often ignore the influence of observer effort, confounding...
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SubjectTerms Age Factors
Animals
Arctocephalus pusillus doriferus
Australia
Environmental Monitoring - methods
Environmental Monitoring - statistics & numerical data
Female
Fisheries - instrumentation
Fisheries interactions
Fur Seals
Ghost nets
Longitudinal Studies
Male
Marine
Marine debris
Models, Theoretical
Otariid
Plastic
Population Density
South Australia
Water Pollutants, Chemical
Water Pollution - adverse effects
Title Drivers and annual estimates of marine wildlife entanglement rates: A long-term case study with Australian fur seals
URI https://dx.doi.org/10.1016/j.marpolbul.2015.10.007
https://www.ncbi.nlm.nih.gov/pubmed/26475026
https://search.proquest.com/docview/1751195516
https://search.proquest.com/docview/1758248014
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