An uncertainty-based decision support tool to evaluate the southern king crab (Lithodes santolla) fishery in a scarce information context

Bené, 2007, 125 Berkes, 2003, Alternatives to conventional management: lessons from small-scale fisheries, Environments, 31, 5 Bockstael, 1983, Discrete modelling of supply response under uncertainty: the case of the fishery, J. Environ. Econ. Manage., 10, 125, 10.1016/0095-0696(83)90021-9 Bozzeda, 2016, Assessing sandy beach macrofaunal patterns along large-scale environmental gradients: a Fuzzy Naïve Bayes approach, Estuarine Coastal Shelf Sci., 175, 70, 10.1016/j.ecss.2016.03.025 Brander, 2007, Global fish production and climate change, Proc. Natl. Acad. Sci., 104, 19709, 10.1073/pnas.0702059104 Britten, 2016, Changing recruitment capacity in global fish stocks, Proc. Natl. Acad. Sci., 113, 134, 10.1073/pnas.1504709112 Brooks, 2015, When “data” are not data: the pitfalls of post hoc analyses that use stock assessment model output, Can. J. Fish. Aquat. Sci., 72, 634, 10.1139/cjfas-2014-0231 Bundy, 2008, If science is not the answer, what is? An alternative governance model for the world's fisheries, Front. Ecol. Environ., 6, 152, 10.1890/060112 Carruthers, 2014, Evaluating methods for setting catch limits in data-limited fisheries, Fish. Res., 153, 48, 10.1016/j.fishres.2013.12.014 Chen, 1998, Can a more realistic model error structure improve the parameter estimation in modelling the dynamics of fish populations?, Fish. Res., 38, 9, 10.1016/S0165-7836(98)00115-5 Chen, 2000, A fuzzy logic model with genetic algorithm for analyzing fish stock-recruitment relationships, Can. J. Fish. Aquat. Sci., 57, 1878, 10.1139/f00-141 Cheung, 2016, Structural uncertainty in projecting global fisheries catches under climate change, Ecol. Model., 325, 57, 10.1016/j.ecolmodel.2015.12.018 Chrysafi, 2015, Assessing abundance of populations with limited data: lessons learned from data-poor fisheries stock assessment, Environm. Rev., 24, 25, 10.1139/er-2015-0044 Cinner, 2009, Socioeconomic factors that affect artisanal fishers’ readiness to exit a declining fishery, Conserv. Biol., 23, 124, 10.1111/j.1523-1739.2008.01041.x Costello, 2012, Status and solutions for the world’s unassessed fisheries, Science, 338, 517, 10.1126/science.1223389 Daza, E., Almonacid, E., Hernández, R., 2016. Programa de Seguimiento Pesquería Crustáceos Bentónicos en la Región de Magallanes. Informe Final. Subsecretaría de Economía. 275pp. De Boor, 1978, A Practical Guide to Splines, vol. 27, 325 Dempster, 1983, Rounding error in regression: the appropriateness of Sheppard's corrections, J. R. Stat. Soc.: Ser. B (Methodol.), 51 Fabinyi, 2015, Managing inequality or managing stocks? An ethnographic perspective on the governance of small-scale fisheries, Fish Fish., 16, 471, 10.1111/faf.12069 FAO, 2016. The State of World Fisheries and Aquaculture 2016. Contributing to food security and nutrition for all. Rome, 200pp. FAO, 1995 Francis, 2017, Revisiting data weighting in fisheries stock assessment models, Fish. Res., 192, 5, 10.1016/j.fishres.2016.06.006 Fromentin, 2014, The spectre of uncertainty in management of exploited fish stocks: the illustrative case of Atlantic bluefin tuna, Mar. Policy, 47, 8, 10.1016/j.marpol.2014.01.018 Fu, 2016, The development and performance of a length-based stock assessment of Foveaux Strait oysters (Ostrea chilensis, OYU 5) in southern New Zealand, and application to management, Fish. Res., 183, 506, 10.1016/j.fishres.2016.05.003 Fulton, 2011, Human behaviour: the key source of uncertainty in fisheries management, Fish Fish., 12, 2, 10.1111/j.1467-2979.2010.00371.x Fournier, 2011, AD Model Builder: using automatic differentiation for statistical inference of highly parameterized complex nonlinear models, Optim. Methods Softw., 27, 233, 10.1080/10556788.2011.597854 Gavaris, 2002, Statistical issues in fisheries' stock assessments, Scand. J. Stat., 29, 245, 10.1111/1467-9469.00282 Gordon, 1954, The economic theory of a common-property resource: the fishery, 178 Guan, 2016, Application of a Bayesian method to data-poor stock assessment by using Indian Ocean albacore (Thunnus alalunga) stock assessment as an example, Acta Oceanologica Sinica, 35, 117, 10.1007/s13131-016-0814-0 Hall, 2009, Global bottlenecks in the distribution of marine Crustacea: temperature constraints in the family Lithodidae, J. Biogeogr., 36, 2125, 10.1111/j.1365-2699.2009.02153.x Hernandez, 2016, 160 Hilborn, 2014, Reflections on the success of traditional fisheries management, ICES J. Mar. Sci., 71, 1040, 10.1093/icesjms/fsu034 Hilborn, 2003, The state of the art in stock assessment: where we are and where we are going, Scientia Marina, 67, 15, 10.3989/scimar.2003.67s115 Hilborn, 2003, Biocomplexity and fisheries sustainability, Proc. Natl. Acad. Sci., 100, 6564, 10.1073/pnas.1037274100 Hilborn, 1992, Quantitative fisheries stock assessment: choice, dynamics and uncertainty, Rev. Fish Biol. Fish., 2, 177, 10.1007/BF00042883 Hilborn, 1979, Comparison of fisheries control systems that utilize catch and effort data, J. Fish. Board Canada, 36, 1477, 10.1139/f79-215 Hobday, 2011, Ecological risk assessment for the effects of fishing, Fish. Res., 108, 372, 10.1016/j.fishres.2011.01.013 Hughes, 2005, New paradigms for supporting the resilience of marine ecosystems, Trends Ecol. Evol., 20, 380, 10.1016/j.tree.2005.03.022 Ianelli, 2016, Multi-model inference for incorporating trophic and climate uncertainty into stock assessments, Deep Sea Res. Part II, 134, 379, 10.1016/j.dsr2.2015.04.002 IFOP, 2017. Estatus y posibilidades de explotación biológicamente sustentables de los principales recursos pesqueros nacionales 2017. Jaiba y Centolla, 2017, 250pp. Jiao, 2016, Integrating spatial synchrony/asynchrony of population distribution into stock assessment models: a spatial hierarchical Bayesian statistical catch-at-age approach, ICES J. Mar. Sci., 73, 1725, 10.1093/icesjms/fsw036 Kittinger, 2013, Emerging frontiers in social-ecological systems research for sustainability of small-scale fisheries, Curr. Opin. Environ. Sustain., 5, 352, 10.1016/j.cosust.2013.06.008 Mangel, 1983, Uncertainty, search, and information in fisheries, ICES J. Mar. Sci., 41, 93, 10.1093/icesjms/41.1.93 Maunder, 2017, Dealing with data conflicts in statistical inference of population assessment models that integrate information from multiple diverse data sets, Fish. Res., 192, 16, 10.1016/j.fishres.2016.04.022 Mapstone, 2004, The effects of line fishing on the Great Barrier Reef and evaluations of alternative potential management strategies, 205 McAllister, 1999, Formulating quantitative methods to evaluate fishery-management systems: what fishery processes should be modelled and what trade-offs should be made?, ICES J. Mar. Sci., 56, 900, 10.1006/jmsc.1999.0547 Megrey, 1989, Exploitation of walleye pollock resources in the Gulf of Alaska, 1964–88: portrait of a fishery in transition, 89 Nahuelhual, 2018, On super fishers and black capture: Images of illegal fishing in artisanal fisheries of southern Chile, Mar. Policy, 95, 36, 10.1016/j.marpol.2018.06.020 Nicholson, 2007, Making conservation decisions under uncertainty for the persistence of multiple species, Ecol. Appl., 17, 251, 10.1890/1051-0761(2007)017[0251:MCDUUF]2.0.CO;2 Patterson, 2001, Estimating uncertainty in fish stock assessment and forecasting, Fish Fish., 2, 125, 10.1046/j.1467-2960.2001.00042.x Plagányi, 2016, Using simulation evaluation to account for ecosystem considerations in fisheries management, 460 Punt, 1997, Fisheries stock assessment and decision analysis: the Bayesian approach, Rev. Fish Biol. Fish., 7, 35, 10.1023/A:1018419207494 Quinn, 1999 Regan, 2002, A taxonomy and treatment of uncertainty for ecology and conservation biology, Ecol. Appl., 12, 618, 10.1890/1051-0761(2002)012[0618:ATATOU]2.0.CO;2 Restrepo, 1999, Precautionary control rules in US fisheries management: specification and performance, ICES J. Mar. Sci., 56, 846, 10.1006/jmsc.1999.0546 Rosenberg, 2018, Applying a new ensemble approach to estimating stock status of marine fisheries around the world, Conserv. Lett., 11, e12363, 10.1111/conl.12363 Roughgarden, 1996, Why fisheries collapse and what to do about it, Proc. Natl. Acad. Sci., 93, 5078, 10.1073/pnas.93.10.5078 Ross, 1896, Social control, Am. J. Sociol., 1, 513, 10.1086/210551 Schnute, 2001, Use and abuse of fishery models, Can. J. Fish. Aquat. Sci., 58, 10, 10.1139/f00-150 Shelton, 2012, Estimating species composition and quantifying uncertainty in multispecies fisheries: hierarchical Bayesian models for stratified sampling protocols with missing data, Can. J. Fish. Aquat. Sci., 69, 231, 10.1139/f2011-152 Thompson, 1993, A proposal for a threshold stock size and maximum fishing mortality rate, Can. Spec. Publ. Fish. Aquat. Sci., 120, 303 Walters, 1998, Designing fisheries management systems that do not depend upon accurate stock assessment, 279 Worm, 2009, Rebuilding global fisheries, Science, 325, 578, 10.1126/science.1173146 Zeller, 2018, The ‘presentist bias’ in time-series data: implications for fisheries science and policy, Mar. Policy, 90, 14, 10.1016/j.marpol.2018.01.015