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Good practices for including environmental data to inform spawner-recruit dynamics in integrated stock assessments: Small pelagic species case study
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Both the additive-error and survey-index methods of including environmental covariates generated relatively high-quality estimates.
“Both methods generated relatively high-quality estimates, either by including environmental covariates as an additional component of the S–R function or by fitting covariates in the model as a survey index of recruits outside the S–R function.”
From Impacts of phytoplankton availability on bigeye tuna (Thunnus obesus) recruitment in the Indian Ocean (2024) · cites this paper as Crone et al. (2019)
Crone et al. (2019) proposed including environmental information in integrated stock assessments to inform S-R dynamics.
“Crone et al. (2019) proposed including environmental information in the integrated stock assessments to inform the S–R dynamics.”
From Impacts of phytoplankton availability on bigeye tuna (Thunnus obesus) recruitment in the Indian Ocean (2024) · cites this paper as Crone et al. (2019)
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Research works printed but not linked: 42
- Austin, 2002, Decadal Oscillations and Regime Shifts, a Characterization of the Chesapeake Bay Marine Climate. AFS Symposium, vol. 32, 155
- Carruthers, 2012, Evaluating methods that classify fisheries stock status using only fisheries catch data, Fish. Res., 119–120, 66, 10.1016/j.fishres.2011.12.011 · DOI
- Chavez, 2003, From anchovies to sardines and back: multidecadal change in the Pacific Ocean, Science, 299, 217, 10.1126/science.1075880 · DOI · Paper page
- Crone, 2014, Evaluation of length vs. Age-composition data and associated selectivity assumptions used in stock assessments based on robustness of derived management quantities, Fish. Res., 158, 165, 10.1016/j.fishres.2014.02.034 · DOI
- Cushing, 1971, The dependence of recruitment of parent stock on different groups of fishes, J. Cons. Int. Explor. Mer., 33, 340, 10.1093/icesjms/33.3.340 · DOI
- Deriso, 1985, Catch-age analysis with auxiliary information, Can. J. Fish. Aquat. Sci., 42, 185, 10.1139/f85-104 · DOI
- Francis, 2006, Measuring the strength of environment–recruitment relationships: the importance of including predictor screening within cross-validations, ICES J. Mar. Sci., 63, 594, 10.1016/j.icesjms.2006.01.001 · DOI
- Freon, 2005, Sustainable exploitation of small pelagic fish stocks challenged by environmental and ecosystem changes, Bull. Mar. Sci., 76, 385
- Haltuch, 2011, The promises and pitfalls of including decadal-scale climate forcing of recruitment in groundfish stock assessment, Can. J. Fish. Aquat. Sci., 68, 912, 10.1139/f2011-030 · DOI
- Haltuch, 2009, Evaluating the estimation of fishery management reference points in a variable environment, Fish. Res., 100, 42, 10.1016/j.fishres.2009.03.001 · DOI
- Hollowed, 2013, Projected impacts of climate change on marine fish and fisheries, ICES J. Mar. Sci., 70, 1023, 10.1093/icesjms/fst081 · DOI
- Jacobson, 1995, Stock-recruitment models for Pacific sardine (Sardinops sagax), Can. J. Fish. Aquat. Sci., 52, 566, 10.1139/f95-057 · DOI
- Keyl, 2008, Environmental variability and fisheries: what can models do?, Rev. Fish Biol. Fish., 18, 273, 10.1007/s11160-007-9075-5 · DOI
- Koslow, 2013, Fish assemblages in the Southern California current: relationships with climate, 1951–2008, Fish. Oceanogr., 22, 207, 10.1111/fog.12018 · DOI
- Lee, 2011, Estimating natural mortality within a fisheries stock assessment model: an evaluation using simulation analysis based on twelve stock assessments, Fish. Res., 109, 89, 10.1016/j.fishres.2011.01.021 · DOI
- Lee, 2017, Evaluation of alternative modelling approaches to account for spatial effects due to age-based movement, Can. J. Fish. Aquat. Sci., 74, 1832, 10.1139/cjfas-2016-0294 · DOI
- Lehodey, 2006, Climate variability, fish, and fisheries, J. Climate, 19, 5009, 10.1175/JCLI3898.1 · DOI · Paper page
- Lindegren, 2013, Temperature dependence of Pacific sardine (Sardinops sagax) recruitment in the California current Ecosystem revisited and revised, Can. J. Fish. Aquat. Sci., 70, 245, 10.1139/cjfas-2012-0211 · DOI
- Maunder, 2003, Estimation of recruitment in catch-at-age models, Can. J. Fish. Aquat. Sci., 60, 1204, 10.1139/f03-104 · DOI · Paper page
- Maunder, 2010, Dealing with missing covariate data in fishery stock assessment models, Fish. Res., 101, 80, 10.1016/j.fishres.2009.09.009 · DOI
- Maunder, 2001, Bayesian assessment of the SNA1 snapper (Pagrus auratus) stock on the northeast coast of New Zealand, N.Z. J. Mar. and Fresh. Res., 35, 87, 10.1080/00288330.2001.9516980 · DOI
- Maunder, 2003, A general framework for integrating environmental time series into stock assessment models: model description, simulation testing, and example, Fish. Bull., 101, 89
- Maunder, 2006, Including parameter uncertainty in forward projections of computationally intensive statistical population dynamic models, ICES J. Mar. Sci., 63, 969, 10.1016/j.icesjms.2006.03.016 · DOI
- Maunder, 2014, Selectivity: theory, estimation, and application in fishery stock assessment models (Editorial), Fish. Res., 158, 1, 10.1016/j.fishres.2014.03.017 · DOI
- Maunder, 2015, Use of state-space population dynamics models in hypothesis testing: advantages over simple log-linear regressions for modeling survival, illustrated with application to longfin smelt (Spirinchus thaleichthys), Fish. Res., 164, 102, 10.1016/j.fishres.2014.10.017 · DOI
- Maunder, 2016, Growth: theory, estimation, and application in fishery stock assessment models, Fish. Res., 180, 1, 10.1016/j.fishres.2016.03.005 · DOI · Paper page
- Maunder, 2017, Data conflict and weighting, likelihood functions, and process error (Preface), Fish. Res., 192, 1, 10.1016/j.fishres.2017.03.006 · DOI
- Maunder, M.N., Thorson, J.T., this issue. Modeling temporal variation in recruitment in fisheries stock assessment: a review of theory and practice. Fish. Res.
- McClatchie, 2010, Re-assessment of the stock-recruit and temperature-recruit relationships for Pacific sardine (Sardinops sagax), Can. J. Fish. Aquat. Sci., 67, 1782, 10.1139/F10-101 · DOI
- Methot, 2011, Adjusting for bias due to variability of estimated recruitments in fishery assessment models, Can. J. Fish. Aquat. Sci., 68, 1744, 10.1139/f2011-092 · DOI
- Methot, 2013, Stock Synthesis: a biological and statistical framework for fish stock assessment and fishery management, Fish. Res., 142, 86, 10.1016/j.fishres.2012.10.012 · DOI
- Miller, 2016, A state-space approach to incorporating environmental effects on recruitment in an age-structured assessment model with an application to southern New England yellowtail flounder, Can. J. Fish. Aquat. Sci., 73, 1261, 10.1139/cjfas-2015-0339 · DOI · Paper page
- Myers, 1998, When do environment–recruitment correlations work? Rev, Fish Biol. Fish., 8, 285, 10.1023/A:1008828730759 · DOI
- Nielsen, 2014, Estimation of time-varying selectivity in stock assessments using state-space models Fish, Res., 158, 96
- Piner, 2016, Evaluation of using random-at-length observations and an equilibrium approximation of the population age structure in fitting the von Bertalanffy growth function, Fish. Res., 180, 128, 10.1016/j.fishres.2015.05.024 · DOI
- Punt, 2003, Evaluating the efficacy of managing west coast groundfish resources through simulations, Fish. Bull. (Wash. D. C.), 101, 860
- Schirripa, 2009, Testing different methods of incorporating climate data into the assessment of US west coast sablefish, ICES J. Mar. Sci., 66, 1605, 10.1093/icesjms/fsp043 · DOI
- Taylor, 2013, Hiding or dead? A computationally efficient model of selective mortality, Fish. Res., 142, 75, 10.1016/j.fishres.2012.08.021 · DOI
- Walters, 1988, Is research on environmental factors useful to fisheries management?, Can. J. Fish. Aquat. Sci., 45, 1848, 10.1139/f88-217 · DOI
- Xu, 2018, Evaluating the utility of the Gulf Stream Index for predicting recruitment of Southern New England‐Mid Atlantic yellowtail flounder, Fish. Oceanogr., 27, 85, 10.1111/fog.12236 · DOI
- Zwolinski, 2012, A cold oceanographic regime with high exploitation rates in the Northeast Pacific forecasts a collapse of the sardine stock, Proc. Natil. Acad. Sci. U. S. A., 109, 4175, 10.1073/pnas.1113806109 · DOI
- Zwolinski, 2014, Environmental and parental control of Pacific sardine (Sardinops sagax) recruitment, ICES J. Mar. Sci., 71, 2198, 10.1093/icesjms/fst173 · DOI
Cited by
Sorted by citations
Wang, Y., Zhang, Y., Geng, Z., & Zhu, J. (2024) · Frontiers in Marine Science · doi:10.3389/fmars.2024.1392273 · Cited by 2
Metadata
- Authors
- Crone, P. R., Maunder, M. N., Lee, H., & Piner, K. R.
- Affiliations
- NOAA National Marine Fisheries Service (US)
- Inter-American Tropical Tuna Commission (US)
- Corresponding author
- Crone, Paul R.
- Venue
- Fisheries Research
- Publisher
- Elsevier BV
- Published
- 2019-09
- Volume
- 217
- Pages
- 122-132
- ISSN
- 0165-7836 (ISSN-L)
- OpenAlex
- W2913055561
- Cited by
- 28
- References
- 0
- Citations by year
- 2026: 7 · 2025: 1 · 2024: 5 · 2023: 5 · 2022: 3 · 2021: 3 · 2020: 2 · 2019: 1
- FWCI
- 1.16
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Fisheries Research (publishedVersion)
- Funders
- Center for the Advancement of Population Assessment Methodology (CAPAM) in La Jolla CA, USA
- Topics
- Life Sciences › Agricultural and Biological Sciences › Aquatic Science › Marine and fisheries research
- Physical Sciences › Mathematics › Applied Mathematics › Mathematical and Theoretical Epidemiology and Ecology Models
- Physical Sciences › Environmental Science › Nature and Landscape Conservation › Fish Ecology and Management Studies
- Keywords
- environmental variables, recruitment estimation, small pelagic fish, Pacific sardine, Stock Synthesis, depletion, bias correction
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