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 in | Marine pollution bulletin Vol. 101; no. 2; pp. 716 - 725 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
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. |
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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. |
Author_xml | – sequence: 1 givenname: Rebecca R. surname: McIntosh fullname: McIntosh, Rebecca R. email: rmcintosh@penguins.org.au organization: Phillip Island Nature Parks, P.O. Box 97, Cowes, VIC 3922, Australia – sequence: 2 givenname: Roger surname: Kirkwood fullname: Kirkwood, Roger organization: IMARES Wageningen UR, Postbus 57, 1780 AB Den Helder, The Netherlands – sequence: 3 givenname: Duncan R. surname: Sutherland fullname: Sutherland, Duncan R. organization: Phillip Island Nature Parks, P.O. Box 97, Cowes, VIC 3922, Australia – sequence: 4 givenname: Peter surname: Dann fullname: Dann, Peter organization: Phillip Island Nature Parks, P.O. Box 97, Cowes, VIC 3922, Australia |
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Keywords | Arctocephalus pusillus doriferus Plastic Ghost nets Otariid Fisheries interactions Marine debris |
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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 |
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