Possible solutions to some challenges facing fisheries scientists and managers

The purpose of this paper is to review recent work on four key challenges in fisheries science and management: (1) dealing with pervasive uncertainties and risks; (2) estimating probabilities for uncertain quantities; (3) evaluating performance of proposed management actions; and (4) communicating technical issues. These challenges are exacerbated in fisheries that harvest multiple stocks, and various methods provide partial solutions to them: (i) risk assessments and decision analyses take uncertainties into account by permitting several alternative hypotheses to be considered at once. (ii) Hierarchical models applied to multi-stock data sets can improve estimates of probability distributions for model parameters compared with those derived through single-stock analyses. (iii) Operating models of complete fishery systems provide comprehensive platforms for testing management procedures. (iv) Finally, results from research in such other disciplines as cognitive psychology can facilitate better communication about uncertainties and risks among scientists, managers, and stakeholders.

[1]  Laurence T. Kell,et al.  An evaluation of management procedures for implementing a precautionary approach in the ICES context for North Sea plaice (Pleuronectes platessa L.) , 1999 .

[2]  K. Radway Allen,et al.  Proceedings of the International Symposium on Management Strategies for Exploited Fish Populations , 1996 .

[3]  P. A. Blight.  The Analysis of Time Series: An Introduction , 1991 .

[4]  Carl J. Walters,et al.  Adaptive Management of Renewable Resources , 1986 .

[5]  Zhenming Su,et al.  A comparison of salmon escapement estimates using a hierarchical Bayesian approach versus separate maximum likelihood estimation of each year's return , 2001 .

[6]  Russell B. Millar,et al.  Non‐linear state space modelling of fisheries biomass dynamics by using Metropolis‐Hastings within‐Gibbs sampling , 2000 .

[7]  Ray Hilborn,et al.  Fleet Dynamics and Individual Variation: Why Some People Catch More Fish than Others , 1985 .

[8]  Randall M. Peterman,et al.  Use of the Kalman filter to reconstruct historical trends in productivity of Bristol Bay sockeye salmon (Oncorhynchus nerka) , 2003 .

[9]  Randall M. Peterman,et al.  Spatial covariation in survival rates of northeast pacific chum salmon , 2002 .

[10]  Anthony Charles,et al.  Canadian Marine Fisheries in a Changing and Uncertain World , 1999 .

[11]  Randall M. Peterman,et al.  Preseason Forecasts of Sockeye Salmon (Oncorhynchus nerka): Comparison of Methods and Economic Considerations , 1988 .

[12]  Sean Pascoe,et al.  Influence of trends in fishing power on bioeconomics in the North Sea flatfish fishery regulated by catches or by effort quotas , 2002 .

[13]  Éric Parent,et al.  How robust are Bayesian posterior inferences based on a Ricker model with regards to measurement errors and prior assumptions about parameters , 2001 .

[14]  Jake C. Rice,et al.  A Framework for Reducing Implementation Uncertainty in Fisheries Management , 1996 .

[15]  Murdoch K. McAllister,et al.  Accounting for structural uncertainty to facilitate precautionary fishery management: illustration with Namibian orange roughy , 2002 .

[16]  Ransom A. Myers,et al.  What is the carrying capacity for fish in the ocean? A meta-analysis of population dynamics of North Atlantic cod , 2001 .

[17]  Massimiliano Cardinale,et al.  Risk of collapse in the eastern Baltic cod fishery , 2002 .

[18]  R. Beamish,et al.  Effects of ocean variability on recruitment and an evaluation of parameters used in stock assessment models , 2004, Reviews in Fish Biology and Fisheries.

[19]  K. Brink,et al.  Benguela trophic functioning , 2004, Reviews in Fish Biology and Fisheries.

[20]  Randall M. Peterman,et al.  Comparison of parameter estimation methods for detecting climate-induced changes in productivity of Pacific salmon (Oncorhynchus spp.) , 2000 .

[21]  Gerd Gigerenzer,et al.  Adaptive Thinking: Rationality in the Real World , 2000 .

[22]  Ray Hilborn,et al.  Depensation in fish stocks : a hierarchic Bayesian meta-analysis , 1997 .

[23]  Kenneth H. Reckhow,et al.  Water quality simulation modeling and uncertainty analysis for risk assessment and decision making , 1994 .

[24]  Chris Chatfield,et al.  The Analysis of Time Series: An Introduction, 4th edn. , 1990 .

[25]  Randall M. Peterman,et al.  Spatial correlation patterns in coastal environmental variables and survival rates of salmon in the north‐east Pacific Ocean , 2002 .

[26]  Randall M. Peterman,et al.  Application of Bayesian decision analysis to management of a sockeye salmon (Oncorhynchus nerka) fishery , 1998 .

[27]  Judith L. Anderson.  Embracing Uncertainty: The Interface of Bayesian Statistics and Cognitive Psychology , 1998 .

[28]  Murdoch K. McAllister,et al.  Using demographic methods to construct Bayesian priors for the intrinsic rate of increase in the Schaefer model and implications for stock rebuilding , 2001 .

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

[30]  Jeremy S. Collie,et al.  Estimating Population Size from Relative Abundance Data Measured with Error , 1983 .

[31]  Russell B. Millar,et al.  Bayesian stock assessment using a state-space implementation of the delay difference model , 1999 .

[32]  Max Henrion,et al.  Uncertainty: A Guide to Dealing with Uncertainty in Quantitative Risk and Policy Analysis , 1990 .

[33]  S. M. McKinnell,et al.  Spatial and temporal covariation in the recruitment and abundance of Atlantic salmon populations in the Baltic Sea , 1999 .

[34]  J. J. Hunt,et al.  Workshop on risk evaluation and biological reference points for fisheries management , 2004, Reviews in Fish Biology and Fisheries.

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

[36]  Zhenming Su,et al.  A hierarchical Bayesian model for estimating historical salmon escapement and escapement timing , 2001 .

[37]  Russell B. Millar.  Reference priors for Bayesian fisheries models , 2002 .

[38]  R. Hilborn,et al.  Fisheries stock assessment and decision analysis: the Bayesian approach , 1997, Reviews in Fish Biology and Fisheries.

[39]  André E. Punt,et al.  Experiences in the evaluation and implementation of management procedures , 1999 .

[40]  Jon T. Schnute,et al.  A General Framework for Developing Sequential Fisheries Models , 1994 .

[41]  Randall M. Peterman,et al.  Spatial covariation in survival rates of Northeast Pacific pink salmon (Oncorhynchus gorbuscha) , 2001 .

[42]  Judith L. Anderson,et al.  Decision Analysis: A Method for Taking Uncertainties into Account in Risk-Based Decision Making , 1999 .

[43]  Michael Power,et al.  Trends in the Development of Ecological Risk Assessment and Management Frameworks , 2002 .

[44]  Ransom A. Myers,et al.  Maximum reproductive rate of fish at low population sizes , 1999 .

[45]  S. Kuikka,et al.  Modeling environmentally driven uncertainties in Baltic cod (Gadus morhua) management by Bayesian influence diagrams , 1999 .

[46]  Randall M. Peterman,et al.  Opposite effects of ocean temperature on survival rates of 120 stocks of Pacific salmon (Oncorhynchus spp.) in northern and southern areas , 2002 .

[47]  Carl J. Walters,et al.  Patterns of covariation in survival rates of British Columbian and Alaskan sockeye salmon (Oncorhynchus nerka) stocks , 1998 .

[48]  Jake C. Rice,et al.  Patterns of change in the size spectra of numbers and diversity of the North Sea fish assemblage, as reflected in surveys and models , 1996 .

[49]  Peter G. Kevan,et al.  The Economic Impacts of Pollinator Declines: An Approach to Assessing the Consequences , 2001 .

[50]  Abstr Am.  SOME PROBLEMS IN ESTIMATING POPULATION SIZES FROM CATCH-ATAGE DATA , 1988 .

[51]  S. Frederick,et al.  Choosing fisheries harvest policies : when does uncertainty matter? , 1995 .

[52]  Carl J. Walters,et al.  Nonstationarity of Production Relationships in Exploited Populations , 1987 .

[53]  Terrance J. Quinn,et al.  Quantitative Fish Dynamics , 1999 .

[54]  Gerd Gigerenzer,et al.  How to Improve Bayesian Reasoning Without Instruction: Frequency Formats , 1995 .

[55]  D. Rubin.  Using the SIR algorithm to simulate posterior distributions , 1988 .

[56]  W. Mare,et al.  Tidier Fisheries Management Requires a New MOP (Management-oriented Paradigm) , 1998, Reviews in Fish Biology and Fisheries.

[57]  Derek Ellis,et al.  Pacific salmon : management for people , 1977 .

[58]  R. I. C. C. Francis,et al.  "Risk" in fisheries management: a review , 1997 .

[59]  R. Myers.  Stock and recruitment: generalizations about maximum reproductive rate, density dependence, and variability using meta-analytic approaches , 2001 .

[60]  Ding-Geng Chen,et al.  A regional meta-model for stock-recruitment analysis using an empirical Bayesian approach , 2002 .

[61]  J. Cooke,et al.  Improvement of fishery-management advice through simulation testing of harvest algorithms , 1999 .

[62]  André E. Punt,et al.  A Bayesian Approach to Stock Assessment and Harvest Decisions Using the Sampling/Importance Resampling Algorithm , 1994 .

[63]  Terrance J. Quinn,et al.  Fishery Stock Assessment Models , 1998 .

[64]  P. Todd,et al.  Simple Heuristics That Make Us Smart , 1999 .

[65]  Fred A. Johnson,et al.  BAYESIAN INFERENCE AND DECISION THEORY—A FRAMEWORK FOR DECISION MAKING IN NATURAL RESOURCE MANAGEMENT , 2003 .

[66]  Robert T. Clemen,et al.  Making Hard Decisions: An Introduction to Decision Analysis , 1997 .

[67]  Keith Sainsbury,et al.  Living Marine Resource Assessment for the 21st Century: What Will Be Needed and How Will It Be Provided? , 1998 .

[68]  Carl J. Walters,et al.  Calculation of Bayes Posterior Probability Distributions for Key Population Parameters , 1994 .

[69]  Aaron M. Ellison,et al.  AN INTRODUCTION TO BAYESIAN INFERENCE FOR ECOLOGICAL RESEARCH AND ENVIRONMENTAL , 1996 .

[70]  P. Slovic.  Perception of risk. , 1987, Science.

[71]  Zhenming Su,et al.  Spatial hierarchical Bayesian models for stock-recruitment analysis of pink salmon (Oncorhynchus gorbuscha) , 2004 .

[72]  G. P. Kirkwood,et al.  Applying multivariate conjugate priors in fishery-management system evaluation: how much quicker is it and does it bias the ranking of management options? , 1999 .

[73]  André E. Punt,et al.  Selecting management methodologies for marine resources, with an illustration for southern African hake , 1992 .

[74]  Ransom A. Myers,et al.  Spatial scales of interannual recruitment variations of marine, anadromous, and freshwater fish , 1997 .

[75]  David R. Marmorek,et al.  Finding a PATH toward Scientific Collaboration: Insights from the Columbia River Basin , 2002 .

[76]  M. Dorn.  Fishing behavior of factory trawlers: a hierarchical model of information processing and decision-making , 2001 .

[77]  André E. Punt,et al.  Evaluation of management tools for Australia's South East Fishery.2. How well can management quantities be estimated? , 2002 .

[78]  David R. Marmorek,et al.  Application of decision analysis to evaluate recovery actions for threatened Snake River spring and summer chinook salmon (Oncorhynchus tshawytscha) , 2001 .