Status of Stocks & Multispecies Assessment Program
Award Winning Talk Given at the
Alaska Marine Science Symposium
Ingrid Spies, a stock assessment scientist and geneticist in the Status of Stocks and Multispecies Assessment (SSMA) Program, won the “Best Student Paper” award at the 2011 Alaska Marine Science Symposium for the presentation “A Landscape Genetics Approach to Pacific cod (Gadus macrocephalus) Population Structure in the Bering Sea and Aleutian Islands Reveals Multiple Distinct Populations.”
Landscape genetics of Pacific cod (Gadus macrocephalus) within the Bering Sea/Aleutian Islands (BSAI) management area of Alaska was examined at nine spawning locations, with one temporal sample, using 17 microsatellite DNA markers. This fine-scaled study of genetic population structure tested the hypothesis that more than one discrete population of Pacific cod exists within the BSAI and examined oceanographic and landscape features that may act as barriers to migration. Samples were taken from spawning fish collected from the western Aleutian Islands east to Unimak Pass and as far north as the Pribilof Island area. The data provide evidence for limited connectivity among spawning groups; in particular, there is strong evidence that a barrier exists at Samalga pass. There is further evidence that within the Bering Sea, the Unimak and Pribilof spawning groups are distinct from each other, and that samples west of Amchitka Pass in the western Aleutians are distinct from those of the eastern Aleutians. Overall, distance between samples is proportional to genetic differentiation between them, but barriers exist within the system and dispersal is not continuous.
By Ingrid Spies and Julie Pearce
How Can Genetics Be Used in Stock Assessment?
Figure 2. Three types of population structure: one population (upper row), a distinct break resulting in two populations (middle row), and isolation-by-distance/continuous change (lower row). Different colors represent different genetic sub-populations.”
Ingrid Spies, SSMA program, is undertaking a project to simulate the consequences and benefits of incorporating genetics into fisheries management. Although genetic population structure has been documented in marine fish species, no clear method exists to translate this information into a meaningful management strategy. This is particularly true when no distinct boundary is present, as in the case of an isolation-by-distance pattern, or a cline in gene frequencies (Fig. 2). In many cases, it is unclear what effect splitting a management area to match population units would have on the future size of the fish populations or on the value of the catch.
Several simulation studies have emphasized the importance of managing at an appropriate spatial scale. In one study, two populations with limited migration were managed as a single stock for 100 years; fishing was spatially biased, carrying capacity varied between the populations, and population persistence was evaluated. Depletion occurred in one of the two populations, regardless of the rate of dispersal or carrying capacity of the two populations. Another study examined the consequences of management areas that encompass many fish populations with limited mobility, differing growth rates, and localized fishing pressure. They found that managing at a biological scale that matched life history parameters resulted in reductions in the probabilities of overfishing and collapse.
Ingrid’s project is a simulation study which extends these ideas to an evaluation of the ability of genetic methods to identify stocks. Genetic data associated with a particular type of population structure are simulated, then standard genetic methods are used to determine where a boundary should be drawn between management areas. Population growth and management of the fishery, both as one management area and with management areas as determined by genetic analysis, are then simulated for 100 years. Performance measures such as total catch and population size will be compared under both management scenarios. This project is a work in progress with results expected in 2012.
