These large fluctuations have the potential to affect management strategies, fishermen’s livelihoods, and local economies ( Botsford et al., 1983 Methot, 1986). 1, 2 Variable catch rates have been accompanied by large swings in ex-vessel landing values, e.g. For example, in Washington and Oregon, the lowest commercial crab catches were reported in the early 1980s (11,300 metric tons in Washington >15,000 metric tons in Oregon), with moderate variability observed even across consecutive years. However, this fishery experiences wide inter-annual fluctuations in catch size. The Dungeness crab fishery is one of the most economically important fisheries on the US West Coast, totaling over $200M in 2017 ( Pacific States Marine Fisheries Commission, 2019).
This work is a step toward developing a forecast product to support management of the fishery. Our results highlight the importance of including exposure history in larval occurrence modeling and help provide a method for predicting pelagic megalopae occurrence. When the biological ensemble was used for forecasting, the model showed skill in predicting megalopae occurrence (AUC = 0.94). Of the six swimming behaviors used to simulate megalopae dispersal, five behaviors generated GLMs with superior fits to the observations, so a biological ensemble of these models was constructed. We found that inclusion of exposure history improved the ability of the GLMs to predict megalopae occurrence 98% of the time. GLMs were developed with either in situ ocean conditions or environmental exposure histories generated using particle tracking experiments.
The analysis included variables from J-SCOPE identified in the literature as important for larval crab occurrence: temperature, salinity, dissolved oxygen concentration, nitrate concentration, phytoplankton concentration, pH, aragonite, and calcite saturation state. The modeled ocean conditions were extracted from JISAO’s Seasonal Coastal Ocean Prediction of the Ecosystem (J-SCOPE), a high-resolution coupled physical-biogeochemical model. magister megalopae and regional simulations of ocean conditions to model megalopae occurrence using a generalized linear model (GLM) framework. We combined 8 years of local observations of M. magister megalopae occurrence patterns compared to using “ in situ” conditions alone. Environmental exposure history has been found to be important for some pelagic organisms, so we hypothesized that inclusion of recent environmental exposure history would improve our ability to predict inter-annual variability in M. These pelagic megalopae are exposed to a range of ocean conditions during their dispersal period, which may drive their occurrence patterns. magister megalopae has been linked to recruitment into the adult fishery 4 years later. Although the underlying causes of this wide variability are not well understood, the abundance of M. The Dungeness crab ( Metacarcinus magister) fishery is one of the highest value fisheries in the US Pacific Northwest, but its catch size fluctuates widely across years. 8Southern California Coastal Water Research Project, Costa Mesa, CA, United States.7Applied Physics Laboratory, University of Washington, Seattle, WA, United States.6Whitman College, Walla Walla, WA, United States.5Cooperative Institute for Marine Resources Studies, Oregon State University, Newport, OR, United States.4Pacific Marine Environmental Laboratory, National Oceanic and Atmospheric Administration, Seattle, WA, United States.
3Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, United States.2Department of Marine Sciences, University of Connecticut Groton, Groton, CT, United States.1Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle, WA, United States.Alin 4, Jan Newton 7, Nina Bednaršek 8 and Richard A. Morgan 5, Suzanna Officer 6, Casey Saenger 1, Simone R. Norton 1*, Samantha Siedlecki 2, Isaac C.
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