THE CENTER FOR STOCK ASSESSMENT RESEARCH (CSTAR)

Marc Mangel (UCSC)

Link to NOAA Strategic Plan: NOAA's Mission Goal 1: Protect, Restore, and Manage the Use of Coastal and Ocean Resources Through an Ecosystem Approach to Management; Goal 2: Understand Climate Variability and Change to Enhance Society's Ability to Plan and Respond

RESEARCH OBJECTIVES AND SPECIFIC PLANS TO ACHIEVE THEM

The objective of CSTAR is undergraduate, graduate and post-graduate training in the basic science associated with the problems of assessing the numerical abundance, spatial distribution, size distribution and reproductive status of commercially important fish species. A broad and deep understanding of population processes is critical to the development and management of sustainable fisheries.

Finding means to conserve fish populations and to achieve sustainable fisheries requires understanding the effects of fishing on behavior, life history and population biology of exploited fishes. At CSTAR, work focuses on using mathematical, statistical and computer models to solve important environmental and ecological problems. The work is grounded in data, and also seeks to expand the base of basic knowledge that supports rigorous application of science to real-world problems. Furthermore, research on marine fisheries conducted at CSTAR allows testing theoretical predictions via natural and human experiments on a scale that is appropriate for understanding the dynamics of ecosystems. Such large-scale experiments are rarely available to the scientific community.

CSTAR provides a level of core support, which is then leveraged by teaching assistantships and graduate research assistantships from other grants or contracts. This enables us to create a relatively large and interactive group of quantitative scientists working on a wide range of problems in fishery management.

RESEARCH ACCOMPLISHMENTS

In 2006-2007, three graduate students associated with CSTAR (Sigrunn Eliassen [who visited CSTAR from the University of Bergen], Yasmin Lucero, and Nicholas Wolf) completed their Ph.D. work. One of them assumed a post-doctoral position at the University of Bergen, another was offered a position at the Fisheries Centre at UBC (where he and his partner, a plant biologist, are moving for post-docs,) and the third is expecting to join the NWFSC as a NRC postdoctoral fellow at the end of summer 2007. Eliassen worked on how animals gather information while foraging, and what that means for population dynamics. Lucero studied the implications of an age dependent maternal effect in rockfish. Wolf used behavioral and population dynamic models to compare ten hypotheses about the causes of the decline of Steller sea lions in the western Gulf of Alaska and Bering Sea.

CSTAR involves many students, post-docs, and faculty in research on quantitative population biology for fishery Management. During this period, CSTAR members included Ms. C. Boone (Ph.D. student Archeology), Ms. Jacqueline Campos (Assistant to Marc Mangel), Dr. Stephanie Carlson (NSF Bioinformatics Postdoctoral Fellow), Dr. Katherine Cresswell (Post-doctoral scholar), Mr. Edward (EJ) Dick (Staff member, NMFS Santa Cruz Laboratory and Ph.D. student, Ocean Sciences), Dr. Xi He (Staff member, NMFS Santa Cruz Laboratory), Ms. Meisha Key (Staff member, California Department of Fish and Game), Prof. Thanassis Kottas (Faculty, UCSC), Ms. Yasmin Lucero (Ph.D. student, Ocean Sciences and NMFS/Sea Grant Fellow), Dr. Alec MacCall (Staff member, NMFS Santa Cruz Laboratory, Co-director), Prof. Marc Mangel (Faculty UCSC, Co-director), Mr. Anand Patil (Ph.D. student, Statistics and Stochastic Modeling), Dr. Steve Ralston (Staff member, NMFS Santa Cruz Laboratory), Prof. Bruno Sanso (Faculty, UCSC), Dr. David Swank (Post-doctoral scholar), Dr. George Watters Staff member, Pacific Fisheries Environmental Laboratory), Mr. John Wiedenmann (Ph.D. student, Ocean Sciences, UCSC), Dr. Will Satterthwaite (Post-doctoral scholar).

CSTAR faculty, students and post-docs continued work on two major grants that CSTAR funds helped leverage: one concerning the implications of climate change on southern ocean krill life histories, krill predators and krill fishery management; the other concerning life history variation in steelhead trout and the implications of water policy for the conservation and recovery of steelhead trout. We also continued to develop Bayesian hierarchical and Bayesian nonparametric methods for quantitative fishery biology. Especially in Bayesian nonparametric methods for fishery problems, we have established a group that has no parallel in terms of depth or breadth.

 

Fig. 1 Comparison of three methods for estimating length at age (from Siefried and Sanso): the classical least squares, a full Bayesian model (in which length at age data are assumed), and a length-based Bayesian model (in which only length data are assumed).

 

Fig. 1 The frequency distribution of the change time to recovery (TTR) of a depleted population that has maternal effects in any of fecundity, density independent survival or density dependent survival of offspring relative to one without a maternal effect (from Lucero, 2007). This theory shows that a maternal effect is more likely to accelerate recovery than decelerate it.