Guidelines for developing formal harvest strategies for data-poor species and fisheries

There has been extensive literature discussion regarding data-poor assessments, but considerably less on harvest strategies for data-poor fisheries. There is also a large body of work around harvest strategy development for data-rich fisheries. However, there has been little discussion or specific guidance regarding the process of developing and implementing formal harvest strategies for data-poor fisheries. We outline such a process, illustrated using case studies of data-poor Australian Commonwealth fisheries. The process comprises: (1) compile and review available information; (2) identify possibly indicators; (3) identify reference points for key indicators; (4) select an appropriate harvest strategy and decision rules; (5) if possible, formally evaluate whether the harvest strategy options are likely to achieve the management objectives; and (6) implementation. While this approach is similar to that for data-rich cases, there is less statistical or estimation detail within each step. Even with minimal capacity, the guidelines outlined here, backed by even the simplest form of management strategy evaluation, provide an approach that should enable harvest strategies to be proposed and associated monitoring to be implemented. Monitoring requirements may be explicitly built into harvest strategies via trigger reference points and control rules related to data-collection. While prior formal evaluation provides the best basis for testing the efficacy of a harvest strategy, there remains disparity between the corresponding required capacity and what many agencies and institutions worldwide are capable of providing. Thus, the extent to which harvest strategies may be effectively evaluated and implemented remains an unresolved challenge for data-poor fisheries, but one whose resolution is predicated, at least in the first instance, on adequate monitoring.

[1]  K. Cochrane,et al.  Overview of World Status of Data-Limited Fisheries: Inferences from Landings Statistics , 2005 .

[2]  Natalie Dowling,et al.  Developing harvest strategies for low-value and data-poor fisheries: Case studies from three Australian fisheries , 2008 .

[3]  C. Dichmont,et al.  A Case Study in Successful Management of a Data-Poor Fishery Using Simple Decision Rules: the Queensland Spanner Crab Fishery , 2010 .

[4]  R. Hilborn,et al.  Contrasting Global Trends in Marine Fishery Status Obtained from Catches and from Stock Assessments , 2011, Conservation biology : the journal of the Society for Conservation Biology.

[5]  David C. Smith,et al.  Implementing harvest strategies in Australia: 5 years on , 2014 .

[6]  André E. Punt,et al.  Experience in implementing harvest strategies in Australia's south-eastern fisheries , 2008 .

[7]  Cóilín Minto,et al.  Trends in the abundance of marine fishes , 2010 .

[8]  A. Constable,et al.  MANAGING FISHERIES EFFECTS ON MARINE FOOD WEBS IN ANTARCTICA: TRADE-OFFS AMONG HARVEST STRATEGIES, MONITORING, AND ASSESSMENT IN ACHIEVING CONSERVATION OBJECTIVES , 2004 .

[9]  S. E. Wayte,et al.  An effective harvest strategy using improved catch-curves , 2010 .

[10]  Panayiota Apostolaki,et al.  Assessment and Management of Data‐Poor Fisheries , 2009 .

[11]  Natalie Dowling,et al.  Risk management tools for sustainable fisheries management under changing climate: a sea cucumber example , 2013, Climatic Change.

[12]  Martin A. Pastoors,et al.  Precautionary harvest policies and the uncertainty paradox , 2008 .

[13]  M. Haddon,et al.  Using a spatially structured model to assess the Tasmanian fishery for banded morwong ( Cheilodactylus spectabilis ) , 2005 .

[14]  André E. Punt,et al.  Design of operational management strategies for achieving fishery ecosystem objectives , 2000 .

[15]  Anthony D. M. Smith,et al.  Implementing effective fisheries-management systems – management strategy evaluation and the Australian partnership approach , 1999 .

[16]  James T. Thorson,et al.  Using model-based inference to evaluate global fisheries status from landings, location, and life history data , 2012 .

[17]  Luiz Barbieri,et al.  Calculating Acceptable Biological Catch for Stocks That Have Reliable Catch Data Only: Only Reliable Catch Stocks - Orcs , 2013 .

[18]  S. Martell,et al.  A simple method for estimating MSY from catch and resilience , 2013 .

[19]  G. M. Branch,et al.  Recommendations for the management of subsistence fisheries in South Africa , 2002 .

[20]  C. Dichmont,et al.  Management objectives of Queensland fisheries: Putting the horse before the cart , 2013 .

[21]  André E. Punt,et al.  Evaluating methods for setting catch limits in data-limited fisheries , 2014 .

[22]  André E. Punt,et al.  Evaluation of management tools for Australia's South East Fishery.3. Towards selecting appropriate harvest strategies , 2002 .

[23]  C. Dichmont,et al.  Choosing a fishery's governance structure using data poor methods , 2013 .

[24]  Carrie V. Kappel,et al.  A Global Map of Human Impact on Marine Ecosystems , 2008, Science.

[25]  David C. Smith,et al.  Scientific tools to support the practical implementation of ecosystem-based fisheries management , 2007 .

[26]  André E. Punt,et al.  Reconciling Approaches to the Assessment and Management of Data-Poor Species and Fisheries with Australia's Harvest Strategy Policy , 2009 .

[27]  Recent advances in the evaluation and implementation of harvest policies , 2008 .

[28]  Terence I. Walker,et al.  Hierarchical approach to the assessment of fishing effects on non-target chondrichthyans: case study of Squalus megalops in southeastern Australia , 2006 .

[29]  Dharmadi,et al.  Elasmobranchs in southern Indonesian fisheries: the fisheries, the status of the stocks and management options , 2009, Reviews in Fish Biology and Fisheries.

[30]  Doug S Butterworth,et al.  Why a management procedure approach? Some positives and negatives , 2007 .

[31]  M. Wilberg,et al.  An Evaluation of Harvest Control Rules for Data-Poor Fisheries , 2013 .

[32]  D. Pauly,et al.  What catch data can tell us about the status of global fisheries , 2012 .

[33]  André E. Punt,et al.  Development and evaluation of a cpue-based harvest control rule for the southern and eastern scalefish and shark fishery of Australia , 2011 .

[34]  W. Cheung,et al.  Retrospective evaluation of data-limited fisheries: a case from Hong Kong , 2004, Reviews in Fish Biology and Fisheries.

[35]  Nokome Bentley,et al.  Moving Fisheries from Data-Poor to Data-Sufficient: Evaluating the Costs of Management versus the Benefits of Management , 2009 .

[36]  N. Rayns The Australian government's harvest strategy policy , 2007 .

[37]  André E. Punt,et al.  The role of harvest control laws, risk and uncertainty and the precautionary approach in ecosystem-based management. , 2003 .

[38]  M. E. Conners,et al.  Managing non‐target, data‐poor species using catch limits: lessons from the Alaskan groundfish fishery , 2010 .

[39]  R. Hilborn,et al.  Status and Solutions for the World’s Unassessed Fisheries , 2012, Science.

[40]  David C. Smith,et al.  From low- to high-value fisheries: Is it possible to quantify the trade-off between management cost, risk and catch? , 2013 .

[41]  A. Maccall,et al.  Estimates of Sustainable Yield for 50 Data-Poor Stocks in the Pacific Coast Groundfish Fishery Management Plan , 2013 .

[42]  Ray Hilborn,et al.  THE GOOD, THE BAD, AND THE UGLY: LEARNING FROM EXPERIENCE TO ACHIEVE SUSTAINABLE FISHERIES , 2006 .

[43]  B. Worm,et al.  The future of fish. , 2012, Trends in ecology & evolution.

[44]  J. Thorson,et al.  Assessing the quality of life history information in publicly available databases. , 2014, Ecological applications : a publication of the Ecological Society of America.

[45]  Susan W. Kim,et al.  Can additional abundance indices improve harvest control rules for New Zealand rock lobster (Jasus edwardsii) fisheries? , 2005 .