MODELING FOR DATA-LIMITED FISHERIES
Washington Sea Grant-supported fellow investigates common fishery stock-assessment methods that may bias managers’ fishery catch decisions.
Cole Monnahan, University of Washington, Quantitative Ecology and Resource Management
Trevor Branch, University of Washington, School of Aquatic and Fishery Sciences
James Thorson, NOAA Fisheries, Northwest Fisheries Science Center
This project will pursue four objectives: identify methods to decrease runtime for data-rich stock assessments, apply new analysis guidelines to past stock assessments in order to speed up future evaluations and compare management implications of different approaches, identify strategies for the optimal allocation of scarce resources toward data gathering and stock assessment of species that have not been assessed, and evaluate the long-term implications of managing stocks using harvest levels set with data-limited methods.
Monnahan, C.C., J.T. Thorson, and T.A. Branch. (2017). Faster estimation of Bayesian models in ecology using Hamiltonian Monte Carlo. Methods in Ecology and Evolution 10.1111/2041-210x.12681.10.1111/2041-210x.12681
Stewart, I.J. and C.C. Monnahan. (2016). Implications of process error in selectivity for approaches to weighting compositional data in fisheries stock assessments. Fisheries Research 10.1016/j.fishres.2016.06.018.10.1016/j.fishres.2016.06.018