Selectivity

Research Summary

Mark and his colleagues have been involved in extensive research into modelling selectivity ranging from developing diagnostics and estimation methods to the influence of misspecification on management advice. In 2013 he co-organized and chaired the CAPAM workshop on selectivity and acted as a guest editor for the Fisheries Research special issue (Maunder et al. 2014). He has highlighted the impact of selectivity misspecification on the fit to composition data and estimation of management quantities, and how this interacts with data weighting (Wang et al., 2009; Maunder and Piner, 2015; Wang et al, 2015). His collaborations have shown how the areas as fisheries approach is likely to result in dome-shape and time varying selectivity (Waterhouse et al., 2014). This has led to the recommendation that fisheries, including those representing areas as fleets, be modeled using flexible time varying selectivities, while indices of abundance be based on the whole stock and potentially use asymptotic time-invariant selectivities (Maunder et al., 2020a). He has also collaborated on research developing methods to define fisheries based on regression tree analysis of composition data that determine areas of common selectivity to use in the areas as fisheries approach (Lennert-Cody et al., 2010; 2013). He developed the empirical selectivity diagnostic that can be used to determine if selectivity assumptions are appropriate and how it can be used to define the appropriate selectivity (Maunder et al. 2020b). Other collaborations have included the illustration of why selectivity invalidates the use of surplus production models (Wang et al., 2014a), using cross validation to determine the shape of nonparametric selectivity curves within stock assessment models (Maunder and Harley, 2011), and using the R0 likelihood component profile (Lee et al., 2014; Wang et al. 2014b) and catch curve (Minte-Vera et al. 2021) diagnostics to identify selectivity misspecification. Finally, he has researched the implications of selectivity on yield (Maunder 2002) and economic benefits (Sun et al., 2020).

Relevant Papers

Minte-Vera, C.V., Maunder, M.N., Aires-da-Silva, A.M. 2021. Auxiliary diagnostic analyses used to detect model misspecification and highlight potential solutions in stock assessments: application to yellowfin tuna in the eastern Pacific Ocean. ICES Journal of Marine Science 78 (10), 3521-3537. https://academic.oup.com/icesjms/article/78/10/3521/6430633?login=true

Sun, C.H., Maunder, M.N., Pan, M., Aires-da-Silva, A., Bayliff, W.H., Compeán, G.A. 2020. Increasing the economic value of the eastern Pacific Ocean tropical tuna fishery: Tradeoffs between longline and purse-seine fishing. Deep Sea Res. Part II: Topical Stud. Oceanog. 169, 104621. https://www.sciencedirect.com/science/article/pii/S0967064518303072

Maunder, M.N., Thorson, J.T., Xu, H., Oliveros-Ramos, R., … 2020a. The need for spatio-temporal modeling to determine catch-per-unit effort based indices of abundance and associated composition data for inclusion in stock assessment models. Fish. Res. 105594. https://www.sciencedirect.com/science/article/abs/pii/S0165783620301119

Maunder, M.N., Xu, H., Lennert-Cody, C.E., Valero, J.L., Aires-da-Silva, A., Minte-Vera, C. 2020b. Implementing reference point-based fishery harvest control rules within a probabilistic framework that considers multiple hypoetheses. IATTC Document SAC-11 INF-F REV. https://www.iattc.org/getattachment/46edbd8e-22f9-4bb3-8d26-d4cfd24a472c/SAC-11-INF-F_Implementing-risk-analysis.pdf

Wang, S. P., Maunder, M. N., Nishida, T., Chen,Y. R. 2015.  Influence of model misspecification, temporal changes, and data weighting in stock assessment models: Application to swordfish (Xiphias gladius) in the Indian Ocean. Fisheries Research, 166: 119-128. https://www.sciencedirect.com/science/article/abs/pii/S0165783614002483

Maunder, M.N., Piner, K.R. 2015. Contemporary fisheries stock assessment: many issues still remain. ICES Journal of Marine Science. 72 (1): 7-18. https://academic.oup.com/icesjms/article/72/1/7/819352

Lee, H. H., Piner, K. R., Methot, R. D., Maunder, M. N. 2014. Use of likelihood profiling over a global scaling parameter to structure the population dynamics model: An example using blue marlin in the Pacific Ocean. Fisheries Research, 158: 138-146. https://www.sciencedirect.com/science/article/abs/pii/S0165783613003111

Maunder, M. N., Crone, P. R., Valero, J. L., Semmens, B. X. 2014. Selectivity: Theory, estimation, and application in fishery stock assessment models. Fisheries Research, 158: 1-4. https://www.sciencedirect.com/science/article/abs/pii/S0165783614001106

Wang, S. P., Maunder, M. N., Aires-da-Silva, A. 2014a. Selectivity's distortion of the production function and its influence on management advice from surplus production models. Fisheries Research, 158: 181-193. https://www.sciencedirect.com/science/article/abs/pii/S0165783614000253

Wang, S. P., Maunder, M. N., Piner, K. R., Aires-da-Silva, A. Lee, H. H. 2014b. Evaluation of virgin recruitment profiling as a diagnostic for selectivity curve structure in integrated stock assessment models. Fisheries Research, 158: 158-164. https://www.sciencedirect.com/science/article/abs/pii/S0165783613003032

Waterhouse, L., Sampson, D. B., Maunder, M. Semmens, B. X. 2014. Using areas-as-fleets selectivity to model spatial fishing: Asymptotic curves are unlikely under equilibrium conditions. Fisheries Research, 158: 15-25. https://www.sciencedirect.com/science/article/abs/pii/S0165783614000174

Lennert-Cody, C.E., Maunder, M.N., Aires-da-Silva, A., Minami, M. 2013. Defining population spatial units: simultaneous analysis of frequency distributions and time series. Fisheries Research 139: 85-93. https://www.sciencedirect.com/science/article/abs/pii/S0165783612002974

Maunder, M.N. and Harley, S.J. 2011. Using cross validation model selection to determine the shape of nonparametric selectivity curves in fisheries stock assessment models. Fisheries Research 110: 283-288. https://www.sciencedirect.com/science/article/abs/pii/S0165783611001664

Lennert-Cody, C.E. Minami, M., Tomlinson, P.K. and Maunder, M.N. 2010. Exploratory analysis of spatial-temporal patterns in length-frequency data: an example of distributional regression trees. Fisheries Research, 102(3): 323-326. https://www.sciencedirect.com/science/article/abs/pii/S0165783609003166

Wang, S-.P., Maunder, M.N., and Aires-da-Silva, A. 2009. Implications of model and data assumptions: An illustration including data for the Taiwanese longline fishery into the eastern Pacific Ocean bigeye tuna (Thunnus obesus) stock assessment. Fisheries Research 97 (2009) 118–126. https://www.sciencedirect.com/science/article/abs/pii/S0165783609000344

Maunder, M.N. 2002. The relationship between fishing methods, fisheries management and the estimation of MSY. Fish and Fisheries, 3: 251-260. https://onlinelibrary.wiley.com/doi/epdf/10.1046/j.1467-2979.2002.00089.x

Workshop reports

Crone, P. R., M. N. Maunder, J. L. Valero, J. D. McDaniel?, and B. X. Semmens (Editors). Selectivity: theory, estimation, and application in fishery stock assessment models. Workshop Series Report 1. Center for the Advancement of Population Assessment Methodology (CAPAM). NOAA/IATTC/SIO, 8901 La Jolla Shores Dr., La Jolla, CA 92037. 46 p.

Reports