Data, Models, and Decisions in U.S. Marine Fisheries Management: Lessons for Ecologists

▪ Abstract Ecological and fisheries approaches to population modeling share many common tools and issues, yet they have developed quite independently over the past decades. The Sustainable Fisheries Act has pushed fisheries modeling into forecasting for management decision-making, which is an area where ecological modeling appears to be headed. We summarize how marine fisheries are managed in the United States, and how data and models are used to make the required forecasts. The recent management deliberations of red grouper in the Gulf of Mexico provide a case study of the sensitive relationship among data, models, and management decisions. We use the U.S. marine fisheries experience and the case study to discuss six lessons that ecologists should consider as they proceed toward forecasting for management. The need for forecasting is accelerating both in ecology and fisheries, while the margin for mistakes is getting smaller.

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

[2]  Suam Kim,et al.  Walleye pollock recruitment in Shelikof Strait: applied fisheries oceanography , 1996 .

[3]  P. Armsworth.  Effects of fishing on a protogynous hermaphrodite , 2001 .

[4]  D. Ludwig,et al.  Ecology, Conservation, and Public Policy , 2001 .

[5]  J. Roughgarden,et al.  Why fisheries collapse and what to do about it. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[6]  Gregg Hartvigsen,et al.  Applied Population Ecology , 1997 .

[7]  Robin Cook,et al.  Ecosystem approaches to fishery management , 2001 .

[8]  D. L. Alverson.  Factors influencing the scope and quality of science and management decisions , 2002 .

[9]  H. Caswell.  Matrix population models : construction, analysis, and interpretation , 2001 .

[10]  John C. Field,et al.  Climate change impacts on U.S. Coastal and Marine Ecosystems , 2002 .

[11]  Charles F. Cole,et al.  Sustaining Marine Fisheries , 2000 .

[12]  Ray Hilborn,et al.  Current Trends in Including Risk and Uncertainty in Stock Assessment and Harvest Decisions , 1993 .

[13]  P. Mace,et al.  Relationships between Common Biological Reference Points Used as Thresholds and Targets of Fisheries Management Strategies , 1994 .

[14]  William E. Ricker.  Handbook of computations for biological statistics of fish populations , 1960 .

[15]  A. Hastings.  Population Biology: Concepts and Models , 1996 .

[16]  P. Sale,et al.  Density dependence at some time and place? , 2000, Oecologia.

[17]  F. Coleman,et al.  Long-lived Reef Fishes: The Grouper-Snapper Complex , 2000 .

[18]  R. Richards,et al.  An Empirical Comparison of Stock Identification Techniques Applied to Striped Bass , 1997 .

[19]  R. Beverton,et al.  On the dynamics of exploited fish populations , 1993, Reviews in Fish Biology and Fisheries.

[20]  S. D. Cooper,et al.  How to Avoid Train Wrecks When Using Science in Environmental Problem Solving , 2002 .

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

[22]  H. Resit Akçakaya,et al.  Predictive accuracy of population viability analysis in conservation biology , 2000, Nature.

[23]  Marjorie J. Wonham,et al.  Invasion of Coastal Marine Communities in North America: Apparent Patterns, Processes, and Biases , 2000 .

[24]  Ray Hilborn,et al.  Compensatory density dependence in fish populations: importance, controversy, understanding and prognosis , 2001 .

[25]  K. Bjorndal,et al.  Historical Overfishing and the Recent Collapse of Coastal Ecosystems , 2001, Science.

[26]  Kenneth Patterson,et al.  Fisheries for small pelagic species: an empirical approach to management targets , 1992, Reviews in Fish Biology and Fisheries.

[27]  Francisco P. Chavez,et al.  From Anchovies to Sardines and Back: Multidecadal Change in the Pacific Ocean , 2003, Science.

[28]  R. Myers,et al.  Is catch-per-unit-effort proportional to abundance? , 2001 .

[29]  Paul J. B. Hart,et al.  Reinventing fisheries management , 1998 .

[30]  K. Frank,et al.  Fisheries Ecology in the Context of Ecological and Evolutionary Theory , 1994 .

[31]  G. Huntsman,et al.  Simulation of the Impact of Fishing on Reproduction of a Protogynous Grouper, the Graysby , 1994 .

[32]  Ray Hilborn,et al.  THE DARK SIDE OF REFERENCE POINTS , 2002 .

[33]  J. Jackson,et al.  Measuring Past Biodiversity , 2001, Science.

[34]  Andrew A. Rosenberg,et al.  Uncertainty and Risk Evaluation in Stock Assessment Advice for U.S. Marine Fisheries , 1994 .

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

[36]  Edward J. Rykiel,et al.  Testing ecological models: the meaning of validation , 1996 .

[37]  C. Walters,et al.  Uncertainty, resource exploitation, and conservation: lessons from history. , 1993, Science.

[38]  C. Krebs.  Beyond population regulation and limitation , 2002 .

[39]  Peter Turchin,et al.  Population Regulation" Old Arguments and a New Synthesis , 1995 .

[40]  P. H. Flournoy.  Marine Protected Areas: Tools for Sustaining Ocean Ecosystems , 2003 .

[41]  Villy Christensen,et al.  Trophic models of aquatic ecosystems , 1993 .

[42]  Robert V. O'Neill,et al.  Ecological Risk Estimation , 1992 .

[43]  E. Houde.  Fish early life dynamics and recruitment variability , 1987 .

[44]  Malcolm Haddon,et al.  Modelling and quantitative methods in fisheries , 2001 .

[45]  C. Walters,et al.  Quantitative fisheries stock assessment: Choice, dynamics and uncertainty , 2004, Reviews in Fish Biology and Fisheries.

[46]  R. Hilborn,et al.  Learning to Enhance Salmon Production: Lessons from the Salmonid Enhancement Program , 1993 .

[47]  C. Needle.  Recruitment models: diagnosis and prognosis , 2001, Reviews in Fish Biology and Fisheries.

[48]  S. Carpenter,et al.  Ecological forecasts: an emerging imperative. , 2001, Science.

[49]  J. Castilla,et al.  The management of fisheries and marine ecosystems , 1997 .

[50]  Albert J. Hermann,et al.  Applied and theoretical considerations for constructing spatially explicit individual-based models of marine larval fish that include multiple trophic levels , 2001 .

[51]  Murdoch K. McAllister,et al.  A Bayesian estimation and decision analysis for an age-structured model using biomass survey data , 1994 .

[52]  D. Wilson,et al.  The effects of legal mandates on fisheries science deliberations: the case of Atlantic bluefish in the United States , 2002 .