|Document Type:||Journal Article|
|Title:||A new role for effort dynamics in the theory of harvested populations and data-poor stock assessment|
|Author:||James T. Thorson, Coilin Minto, Carolina Minte-Vera, Kristin Kleisner, Katie Longo|
|Journal:||Canadian Journal of Fisheries and Aquatic Sciences|
|Keywords:||Effort-dynamics, Takens Theorem, state-space model, stock assessment, stability analysis, data-poor, meta-analysis,|
Research shows that stock status can be predicted using catch data, but there is little theoretical justification for why these predictions work or how they account for changes in fisheries management. We demonstrate that stock biomass can be reconstructed from catch data whenever fishing mortality follows predictable dynamics over time (which we call effort dynamics), and develop a state-space catch only model (SSCOM) for this purpose. We use theoretical arguments and simulation modeling to demonstrate that SSCOM can in some cases estimate current and historical status from catch data. Next, we use meta-analysis to estimate effort dynamics for U.S. West Coast groundfishes before and after fisheries management changes in the mid-1990s. We then apply the SSCOM using these meta-analytic results to data for eight assessed species, and compare results with stock assessment and data-poor methods. Results indicate general agreement between all three methods. We conclude that effort dynamics provides a theoretical basis for using catch data to reconstruct biomass, and has potential for conducting data-poor assessments. However, we still recommend that index and compositional data be collected to allow application of data-rich methods.
|Full Text URL:||http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2013-0280#.UpT3A8Rju-0|
|Theme:||Recovery, Rebuilding and Sustainability of Marine and Anadromous Species|
Describe the relationship among human activities and species stock status, recovery, rebuilding and sustainability.
Develop methods to use physiological and biological information to predict population-level processes.