Home Mission Who We Are Contact Search
Projects Events Media Resources Publications Stay Informed Partners & Sponsors Contribute

The mission of the Institute for Ocean Conservation Science is to advance ocean conservation through science. More..

2015    |    2014    |    2013    |    2012    |    2011    |    2010    |    2009    |    2008    |    2007    |    2006    |    2005    |    2004

Conference of the American Association for the Advancement of Science

February 12, 2004 - February 17, 2004
Seattle, WA
Booth at this event.


The 2004 AAAS meeting included a series of symposia on “Living Oceans and Coastlines”. The symposium “Tough Decisions: Dealing with Uncertainty in Managing Marine Fisheries” brought together scientists and policy experts to discuss the implications of scientific uncertainty in fisheries policy and management. As an expert in decision analysis, Dr. Pikitch of Pew Institute for Ocean Science was invited to give a talk on how decision theory can be used to help managers make better decisions in the face of uncertainty about the possible consequences of their decisions.

Using Decision Analysis To Improve Stock Assessment And Management

Ellen K. Pikitch , Elizabeth A. Babcock
Fisheries managers rely on the results of stock assessments to help them choose the catch quotas and other regulations that have the highest likelihood of achieving management objectives such as rebuilding overfished populations. Traditionally, fisheries stock assessment science has not excelled at accounting for and communicating scientific uncertainty. Managers are often presented with either a single “base case” assessment, ignoring the risks associated with mis-specification of the model, or a else a suite of model runs with no guidance as to which are most credible. Decision theory provides better methods to address the consequences of management actions in the presence of uncertainty. For western Atlantic bluefin tuna in the late 1990s, there was uncertainty about the relationship between spawning stock biomass and recruitment of juvenile fish. Of the two recruitment hypotheses, one predicted a population decline if the current quota continued, and one predicted a population increase. Because both hypotheses were credible, the managers were presented with a decision table showing the probability of the population rebuilding under each quota, for each recruitment hypothesis. This allowed managers to choose a quota based on a correct understanding of the uncertainty about recruitment. Where data are available, Bayesian statistical methods can be used to calculate the relative credibility of alternative hypotheses so that the probability of population rebuilding can be integrated across the hypotheses. Decision analysis is particularly useful when there are competing hypotheses about the underlying biology of the fish, such as its migratory behavior, growth or fecundity.

Authors highlighted in blue are staff of the Institute for Ocean Conservation Science.

Stay Connected
Facebook space Twitter space You Tube space Make A Gift
Stony Brook University space
© 2010 Institute for Ocean Conservation Science | Website Design by Academic Web Pages