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Reducing uncertainty in the assessment and management of fish resources following an environmental impact
Author(s) -
Douglas Rotherham,
William G. Macbeth,
Steven J. Kennelly,
Charles A. Gray
Publication year - 2011
Publication title -
ices journal of marine science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.348
H-Index - 117
eISSN - 1095-9289
pISSN - 1054-3139
DOI - 10.1093/icesjms/fsr079
Subject(s) - fishing , estuary , fishery , environmental resource management , geography , flood myth , fauna , sampling (signal processing) , fish <actinopterygii> , fish stock , fisheries management , environmental science , ecology , computer science , biology , archaeology , filter (signal processing) , computer vision
The limitations of using information from commercial fisheries for assessing and managing resources and ecosystems are well known. Although fishery-independent data may overcome many such limitations, few studies have examined how incorporating data from different sources affects assessments and subsequent management decisions. Here, the value of integrating data from two types of sampling survey to assess the recovery of faunal populations following a severe fish-kill event in the Richmond River (New South Wales, Australia) in 2008 is evaluated. There is occasional large-scale mortality of fish and invertebrates in certain estuaries of eastern Australia following major flood events. In extreme cases, the management response involves closing an entire estuary to all fishing, to facilitate the recolonization and recovery of fish and other fauna. Decisions to resume normal fishing activities have environmental, economic, and social implications. Using lessons learned from a similar fish-kill event in 2001, it is shown how, in 2008, fisheryindependent sampling, combined with improved sampling by commercial fishers, reduced uncertainty in decision-making and led to greatly improved socio-economic outcomes for stakeholders. The work highlights the need to examine the value of different sources of information to improve management decisions.

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