TY - JOUR
T1 - Empirical harvest strategies for data-poor fisheries
T2 - A review of the literature
AU - Dowling, N. A.
AU - Dichmont, C. M.
AU - Haddon, M.
AU - Smith, D. C.
AU - Smith, A. D.M.
AU - Sainsbury, K.
N1 - Funding Information:
This work was funded by the Food and Agriculture Organization of the United Nations ( PR 45832 ) and by CSIRO Wealth from Oceans . The Australian Fisheries Management Authority, and Gabriella Bianchi from FAO, are thanked for their support. We also thank two anonymous reviewers whose comments greatly improved the manuscript.
Publisher Copyright:
© 2014.
PY - 2015/11/1
Y1 - 2015/11/1
N2 - Harvest strategy approaches based around empirical indicators and/or control rules are beginning to be accepted in a growing range of data- and capacity-poor fisheries. While there is an increasing body of work around developing empirical indicators and control rules in data-poor contexts, this has typically been done on a case-specific basis. There remains a need for general guidance on formulating control rules that link empirical indicators with suitable management responses. Additionally, in the data-poor context, most literature has focused on empirical indicators and assessments, with less focus on decision rules and the incorporation of indicators and assessments in a harvest strategy framework. This review considers a range of harvest strategy options, focusing on empirical indicators and decision rules available for data-poor species and fisheries. These clearly illustrate that a paucity of information is not a reason to avoid developing harvest strategies, and that a range of pragmatic approaches are available regardless of the available data, life-history of the target species, nature of fishing operations, or the available research capacity. There is considerable scope for further work in this field, but arguably there is a comprehensive repository of approaches and decision rules that, when combined with the guidelines, form a solid foundation and toolkit for all but the most data-poor species and fisheries.
AB - Harvest strategy approaches based around empirical indicators and/or control rules are beginning to be accepted in a growing range of data- and capacity-poor fisheries. While there is an increasing body of work around developing empirical indicators and control rules in data-poor contexts, this has typically been done on a case-specific basis. There remains a need for general guidance on formulating control rules that link empirical indicators with suitable management responses. Additionally, in the data-poor context, most literature has focused on empirical indicators and assessments, with less focus on decision rules and the incorporation of indicators and assessments in a harvest strategy framework. This review considers a range of harvest strategy options, focusing on empirical indicators and decision rules available for data-poor species and fisheries. These clearly illustrate that a paucity of information is not a reason to avoid developing harvest strategies, and that a range of pragmatic approaches are available regardless of the available data, life-history of the target species, nature of fishing operations, or the available research capacity. There is considerable scope for further work in this field, but arguably there is a comprehensive repository of approaches and decision rules that, when combined with the guidelines, form a solid foundation and toolkit for all but the most data-poor species and fisheries.
KW - Data-poor fisheries
KW - Data-poor harvest strategies
KW - Empirical decision rules
KW - Empirical harvest strategies
KW - Harvest strategy framework
KW - Literature review
UR - http://www.scopus.com/inward/record.url?scp=84941196402&partnerID=8YFLogxK
U2 - 10.1016/j.fishres.2014.11.005
DO - 10.1016/j.fishres.2014.11.005
M3 - Article
AN - SCOPUS:84941196402
SN - 0165-7836
VL - 171
SP - 141
EP - 153
JO - Fisheries Research
JF - Fisheries Research
ER -