Publications
CAPAM staff/members highlighted in bold
2024 2023 2022 2021 2020 2019 2018 2017 2016 2015 2014 2013
Special Issues:
Data weighting - Growth - Selectivity - Recruitment - Spatio-temporal models -
Spatial stock assessments - General stock assessment models -
Natural mortality - Good Practices
Lee, H.H., Maunder, M.N., Piner, K.R. 2024. Good Practices for estimating and using length-at-age in integrated stock assessments. Fisheries Research 106883. https://www.sciencedirect.com/science/article/pii/S016578362300276X
Schaub, M. Maunder, M.N., Kéry, M., Thorson, J.T., Jacobson, E.K., Punt, A.E. 2024. Lessons to be learned by comparing integrated fisheries stock assessment models (SAMs) with integrated population models (IPMs). Fisheries Research 106925. Article: https://www.sciencedirect.com/science/article/pii/S0165783623003181 Supplementary material: Link
Hoyle, S.D., Campbell, R.A., Ducharme-Barth, N.D., Grüss, A., ... Maunder, M.N. 2023. Catch per unit effort modelling for stock assessment: A summary of good practices. Fish. Res. 106860. https://www.sciencedirect.com/science/article/pii/S0165783623002539
Maunder, M.N., Hamel, O.S., Lee, H-H., Piner, K.R., Cope, J.M., Punt, A.E., Ianelli, J.N., Castillo-Jordan, C., Kapur, M.S., 2023. A review of estimation methods for natural mortality and their performance in the context of fishery stock assessment. Fish. Res. 257, 106489. https://www.sciencedirect.com/science/article/pii/S0165783622002661?dgcid=author
Hoyle, S.D., Williams, A.J., Minte-Vera, C.V. Maunder, M.N. 2023. Approaches for estimating natural mortality in tuna stock assessments: Application to global yellowfin tuna stocks. Fish. Res. 257, 106498. https://www.sciencedirect.com/science/article/pii/S0165783622002752?dgcid=coauthor
Majumdar, A., Lennert-Cody, C.E., Maunder, M.N., Aires-da-Silva, A. 2023. Spatio-temporal modeling for estimation of bigeye tuna catch in the presence of pandemic-related data loss using parametric adjacency structures. Fisheries Research 268, 106813 https://www.sciencedirect.com/science/article/pii/S0165783623002060
Fisch, N., Shertzer, K., Camp, E., Maunder, M.N., Ahrens, R. 2023. Process and sampling variance within fisheries stock assessment models: estimability, likelihood choice, and the consequences of incorrect specification. ICES Journal of Marine Science, fsad138 https://academic.oup.com/icesjms/advance-article/doi/10.1093/icesjms/fsad138/7260034
Lennert-Cody, C.E., Lopez, J., Maunder, M.N. 2023. An automatic purse-seine set type classification algorithm to inform tropical tuna management. Fisheries Research 262, 106644 https://www.sciencedirect.com/science/article/pii/S0165783623000371
Hamel, O.S., Ianelli, J.N., Maunder, M.N., Punt, A.E. 2023. Natural mortality: Theory, estimation and application in fishery stock assessment models. Fisheries Research 261, 106638 https://www.sciencedirect.com/science/article/pii/S0165783623000310
Fajardo-Yamamoto, A, Aalbers, S., Sepulveda, C., Valero, J. L., Sosa-Nishizaki, O. 2022. Balancing the asymmetry of knowledge of the transboundary white seabass (Atractoscion nobilis) fishery resource: landings reconstruction along the west coast of the Baja California Peninsula. Regional Studies in Marine Science. https://doi.org/10.1016/j.rsma.2022.102708
Hoyle, S.D., Maunder, M.N., Punt, A.E., Mace, P.M., Devine, J.A., A’mar, Z.T. 2022. Preface: Developing the next generation of stock assessment software. Fish. Res. 246, 106176 https://www.sciencedirect.com/science/article/abs/pii/S0165783621003040
Maunder, M.N. 2022. Stock-recruitment models from the viewpoint of density-dependent survival and the onset of strong density-dependence when a carrying capacity limit is reached. Fis. Res. 249, 106249 https://www.sciencedirect.com/science/article/abs/pii/S0165783622000261
Lennert-Cody, C.E., McCracken, M., Siu, S., Oliveros-Ramos, R., Maunder, M.N., ... 2022. Single-cluster systematic sampling designs for shark catch size composition in a Central American longline fishery. Fish. Res. 251, 106320 https://www.sciencedirect.com/science/article/abs/pii/S0165783622000972
Carvalho, F., Winker, H., Courtney, D., Kapur, M., Kell, L., Cardinale, M, Schirripa, M., Kitaka, T., Yemane, D., Piner, K.R., Maunder, M.N., Taylor, I., Wetzel, C.R., Doering, K., Johnson, K.F., Methot, R.D. 2021. A cookbook for using model diagnostics in integrated stock assessments. Fish. Res. 240, 105959 https://www.sciencedirect.com/science/article/pii/S0165783621000874
Punt, A.E., Castillo-Jordán, C., Hamel, O.S., Cope, J.M., Maunder, M.N., Ianelli, J.N. 2021. Consequences of error in natural mortality and its estimation in stock assessment models. Fish. Res. 233, 105759 https://www.sciencedirect.com/science/article/abs/pii/S0165783620302769
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=false
Cadrin, S.X., Maunder, M.N., Punt, A.E. 2020. Spatial Structure: Theory, estimation and application in stock assessment models. Fish. Res. 105608. https://www.sciencedirect.com/science/article/abs/pii/S0165783620301259
Thorson, J.T., Maunder, M.N., Punt, A.E. 2020. The development of spatio-temporal models of fishery catch-per-unit-effort data to derive indices of relative abundance. Fish. Res. 105611. https://www.sciencedirect.com/science/article/abs/pii/S0165783620301284
Maunder, M.N., Thorson, J.T., Xu, H., Oliveros-Ramos, R., … 2020. 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
Punt, A.E., Dunn, A., Elvarsson, B., Hampton, J., … 2020. Essential features of the next-generation integrated fisheries stock assessment package: A perspective. Fish. Res. 105617. https://www.sciencedirect.com/science/article/abs/pii/S016578362030134X
Lennert-Cody, C.E., Maunder, M.N., Román, M.H., Xu, H., Minami, M., Lopez, J. 2020. Cluster analysis methods applied to daily vessel location data to identify cooperative fishing among tuna purse-seiners. Environmental and Ecological Statistics 27 (4), 649-664 https://link.springer.com/article/10.1007/s10651-020-00451-7
Crone, P. R., Maunder, M. N., Lee, H. H., Piner, K. R. 2019. Good practices for including environmental data to inform spawner-recruit dynamics in integrated stock assessments: Small pelagic species case study. Fisheries Research. 217: 122-132. Link
Sun, C.H., Maunder, M.N., Pan, M., Aires-da-Silva, A., Bayliff, W.H. Compeán, G.A. 2019. Increasing the economic value of the eastern Pacific Ocean tropical tuna fishery: Tradeoffs between longline and purse-seine fishing. Deep Sea Research Part II: Topical Studies in Oceanography 169, 104621 https://www.sciencedirect.com/science/article/pii/S0967064518303072
Lennert-Cody, C. E., Buckland, S. T, Gerrodette, T., Webb, A., Barlow, J., Fretwell, P., Maunder, M. N., Kitakado, T., Moore, J. E., Scott, M. D., Skaug, H. J. 2018. Review of potential line-transect methodologies for estimating abundance of dolphin stocks in the eastern tropical Pacific. Journal of Cetacean Research and Management, 19. 9-21. Link
Lennert-Cody, C.E. Moreno, G., Restrepo, V., Román, M.H., Maunder, M.N. 2018. Recent purse-seine FAD fishing strategies in the eastern Pacific Ocean: what is the appropriate number of FADs at sea? ICES Journal of Marine Science 75 (5), 1748-1757. Link
Lennert-Cody, C.E., Clarke, S.C., Aires-da-Silva, A., Maunder, M.N., Franks, P.J.S., Román, M., Miller, A.J., Minami, M., 2018. The importance of environment and life stage on interpretation of silky shark relative abundance indices for the equatorial Pacific Ocean. Fish. Oceanogr. 28, 43-53. doi:10.1111/fog.12385 Link
Maunder, M.N., Deriso, R.B., Schaefer, K.M., Fuller, D.W., Aires-da-Silva, A.M., Minte‑Vera, C.V., Campana, S.E. 2018. The growth cessation model: a growth model for species showing a near cessation in growth with application to bigeye tuna (Thunnus obesus). Marine Biology (2018) 165:76. Link
Carvalho, F., Punt, A. E., Chang, Y. J., Maunder, M. N., Piner, K. R. 2017. Can diagnostic tests help identify model misspecification in integrated stock assessments? Fisheries Research. 192: 28-40. Link
Chang S-K, Liu H-I, Fukuda, H, Maunder, M. N. 2017. Data reconstruction can improve abundance index estimation: An example using Taiwanese longline data for Pacific bluefin tuna. PLoS ONE 12(10): e0185784. https://doi.org/10.1371/journal.pone.0185784
Kai, M., Thorson, J.T., Piner, K.R., Maunder, M.N. 2017. Spatiotemporal variation in size-structured populations using fishery data: an application to shortfin mako (Isurus oxyrinchus) in the Pacific Ocean. Canadian Journal of Fisheries and Aquatic Sciences, 2017, 74(11): 1765-1780, https://doi.org/10.1139/cjfas-2016-0327
Kai, M., Thorson, J.T., Piner, K.R, Maunder, M.N. 2017. Predicting the spatio-temporal distributions of pelagic sharks in the western and central North Pacific. Fish Oceanogr. 2017;26:569–582. https://doi.org/10.1111/fog.12217
Lee, H.H., Thomas, L.R., Piner, K.R. and Maunder, M.N., 2017. Effects of age‐based movement on the estimation of growth assuming random‐at‐age or random‐at‐length data. Journal of Fish Biology, 90: 222-235.
Lee, H-H., Piner, K.R., Maunder, M.N., Taylor, I.G., Methot Jr., R.D. 2017. Evaluation of alternative modelling approaches to account for spatial effects due to age-based movement. Canadian Journal of Fisheries and Aquatic Sciences, 2017, 74(11): 1832-1844, https://doi.org/10.1139/cjfas-2016-0294
Maunder, M.N., Crone, P.R, Punt, A.E., Valero, J.L., Semmens B. X. 2017. Data conflict and weighting, likelihood functions and process error. Fisheries Research. 192: 1-4. Link
Maunder, M. N. and Piner, K. R. 2017. Dealing with data conflicts in statistical inference of population assessment models that integrate information from multiple diverse data sets. Fisheries Research. 192: 16-27. Link
Minte-Vera, C. V., Maunder, M. N., Aires-da-Silva, A. M., Satoh, K., Uosaki, K. Get the biology right, or use size-composition data at your own risk. 2017. Fisheries research. 192: 114-125. Link
Pons, M., Branch, T.A., Melnychuk, M.C., Jensen, O.P., Brodziak, J., Fromentin, J.M., Harley, S.J., Haynie, A.C., Kell, L.T., Maunder, M.N. and Parma, A.M., 2017. Effects of biological, economic and management factors on tuna and billfish stock status. Fish and Fisheries, 18: 1-21.
Squires, D., Maunder, M.N., Allen, R., Andersen, P., Astorkiza, K., Butterworth, D., Caballero, G., Clarke, R., Ellefsen, H., Guillotreau, P., Hampton, J., Hannesson, R., Havice, E., Helvey, M., Herrick, S., Hoydal, K., Maharaj, V., Metzner, R., Mosqueira, I., Parma, A., Prieto-Bowen, I., Restrepo, V., Sidique, S. F., Steinsham, S. I., Thunberg, E., del Valle, I. and Vestergaard, N. 2017. Effort rights-based management. Fish and Fisheries, 18: 440-465.
Wang, S-P and Maunder, M. N. Is down-weighting composition data adequate for dealing with model misspecification, or do we need to fix the model? Fisheries Research. 192: 41-51. Link
Carruthers, T.R., Kell, L.T., Butterworth, D.D., Maunder, M.N., Geromont, H.F., Walters, C., McAllister, M.K., Hillary, R., Levontin, P., Kitakado, T. and Davies, C.R., 2016. Performance review of simple management procedures. ICES Journal of Marine Science: Journal du Conseil, 73(2), pp.464-482.
Francis, C., Aires-da-Silva, A., Maunder, M. N., Schaefer, K. M., Fuller, D. W. 2016. Estimating fish growth for stock assessments using both age–length and tagging-increment data. Fisheries Research, 180: 113-118. Link
Kell, L.T., Levontin, P., Davies, C.R., Harley, S., Kolody, D.S., Maunder, M.N., Mosqueira, I., Pilling, G.M. and Sharma, R., 2016. The quantification and presentation of risk. Management Science in Fisheries: An Introduction to Simulation-based Methods, p.348.
Lennert-Cody, C.E., Maunder, M.N., Fiedler, P.C., Minami, M., Gerrodette, T., Rusin, J., Minte-Vera, C.V., Scott, M. and Buckland, S.T., 2016. Purse-seine vessels as platforms for monitoring the population status of dolphin species in the eastern tropical Pacific Ocean. Fisheries Research, 178: 101-113.
Aires-da-Silva, A., Maunder, M.N., Schaefer, K.M., Fuller, D.W. 2015. Improved growth estimates from integrated analysis of direct aging and tag-recapture data: an illustration with bigeye tuna (Thunnus obesus) of the eastern Pacific Ocean with implications for management. Fisheries Research, 163: 119-126.
Deroba, J.J., Butterworth, D.S., Methot, R.D. Jr., De Oliveira, J.A.A. Fernandez, C., Nielsen, A., Cadrin, S.X., Dickey-Collas, M., Legault, C.M., Ianelli, J., Valero, J.L., Needle, C.L., O’Malley, J.M., Chang, Y-J., Thompson, G.G., Canales, C., Swain, D.P., Miller, D.C.M., Hintzen, N.T., Bertignac, M., Ibaibarriaga, L., Silva, A., Murta, A., Kell, L.T., de Moor, C.L., Parma, A.M., Dichmont, C.M., Restrepo, V.R., Ye, Y., Jardim, E., Spencer, P.D., Hanselman, D.H., Blaylock, J., Mood, M., Hulson, P.-J. F. 2015. Simulation testing the robustness of stock assessment models to error: some results from the ICES Strategic Initiative on Stock Assessment Methods. ICES Journal of Marine Science. 72 (1): 19-30 doi:10.1093/icesjms/fst237. Link
Hurtado-Ferro, F., Szuwalski, C., Valero, J. L., Anderson, S., Cunningham, C., Johnson, K., Licandeo, R., McGilliard, C., Monnahan, C., Muradian, M., Ono, K., Vert-pre, K., Whitten, A.R. 2015. What generates retrospective patterns in statistical catch-at-age stock assessment models?. ICES Journal of Marine Science. 72 (1): 99-110 doi:10.1093/icesjms/fsu198.
Hyun, S.Y., Maunder, M.N., Rothschild, B.J. 2015. Importance of modeling hetero-scedasticity of survey index data in fishery stock assessments. ICES Journal of Marine Science. 72 (1): 130-136 doi:10.1093/icesjms/fsu046.
Johnson, K. F., Monnahan, C. C., McGilliard, C. R., Vert-pre, K. A., Anderson, S. C., Cunningham, C. J., Hurtado-Ferro, F., Licandeo, R., Muradian, M., Ono, K., Szuwalski, C. S., Valero, J. L., Whitten, A. R., Punt, A. E. 2015. Time-varying natural mortality in fisheries stock assessment models: identifying a default approach. ICES J. Mar. Sci. 72 (1): 137-150 doi:10.1093/icesjms/fsu055. Link
Martínez-Ortiz, J., Aires-da-Silva, A.M., Lennert-Cody, C.E. and Maunder, M.N., 2015. The Ecuadorian Artisanal Fishery for Large Pelagics: Species Composition and Spatio-Temporal Dynamics. PloS one, 10(8), p.e0135136.
Maunder, M.N., Deriso, R.B., and Hanson, C.H. 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). Fisheries Research, 164: 102–111. Link
Maunder, M.N., Piner, K.R. 2015. Contemporary fisheries stock assessment: many issues still remain. ICES Journal of Marine Science. 72 (1): 7-18 doi:10.1093/icesjms/fsu015. Link
Ono, K., Licandeo R., Muradian, M. L., Cunningham, C. R., Anderson, S. C., Hurtado-Ferro, F., Johnson, K. F., McGilliard, C. F., Monnahan, C. F., Szuwalski, C. S, Valero, J. L., Vert-pre, K. A., Whitten, A. R., Punt, A. E. 2015. The importance of length and age composition data in statistical age-structured models for marine species. ICES Journal of Marine Science. 72 (1): 31-43 doi:10.1093/icesjms/fsu007. Link
Anderson, S. C., Monnahan, C. C., Johnson, K. F., Ono, K., Valero, J. L. 2014. ss3sim: An R package for Fisheries stock assessment simulation with Stock Synthesis. PLoS ONE. 9(4): e92725. doi:10.1371/journal.pone.0092725. Link
Anderson, S. C., Monnahan, C. C., Johnson, K. F., Ono, K., Valero, J. L. 2014. ss3sim: Fisheries stock assessment simulation testing with Stock Synthesis. R package version 0.8.1. Link
Carvalho, F., Ahrens, R., Murie, D., Ponciano, J.M., Aires-da-Silva, A., Maunder, M.N., and Hazin, F. 2014. Incorporating specific change points in catchability in fisheries stock assessment models: An alternative approach applied to the blue shark (Prionace glauca) stock in the south Atlantic Ocean. Fisheries Research 154: 135-146.
Crone, P. R., Valero, J. L. 2014. Evaluation of length- vs. age- composition data and associated selectivity assumptions used in stock assessments based on robustness of derived management quantities. Fisheries Research, 158: 165-171. Link
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. Link
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. Link
Sippel, T., Eveson, J.P., Galuardi, B., Lam, C., Hoyle, S., Maunder, M., Kleiber, P., Carvalho, F., Tsontos, V., Teo, S.L.H., Aires-da-Silva, A., Nicol, S. (in press) Using movement data from electronic tags in fisheries stock assessment: A review of models, technology and experimental design. Fisheries Research.
Wang, S. P., Maunder, M. N., Aires-da-Silva, A. 2014. Selectivity's distortion of the production function and its influence on management advice from surplus production models. Fisheries Research, 158: 181-193. Link
Wang, S. P., Maunder, M. N., Piner, K. R., Aires-da-Silva, A. Lee, H. H. 2014. Evaluation of virgin recruitment profiling as a diagnostic for selectivity curve structure in integrated stock assessment models. Fisheries Research, 158: 158-164. Link
Wang, S. P., Maunder, M. N., Nishida, T., Chen,Y. R. (in press). Influence of model misspecification, temporal changes, and data weighting in stock assessment models: Application to swordfish (Xiphias gladius) in the Indian Ocean. Fisheries Research.
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. Link
Crone, P. R., Maunder, M. N., Valero, J. L., McDaniel, J. D., Semmens, B. X. (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. Link
Haltuch, M. A., Ono, K., Valero, J. L. 2013. Status of the U.S. petrale sole resource in 2012. Pacific Fishery Management Council. 7700 Ambassador Place NE, Suite 200, Portland, OR 97220. Link
Maunder, M. N., Deriso, R. B. 2013. A stock–recruitment model for highly fecund species based on temporal and spatial extent of spawning. Fisheries Research, 146: 96-101. Link
Special Issue on Good Practices (Fisheries Research) [In Progress] Link
Thorson, J.T., Monnahan, C.C., Hulson, P-J. F. 2023. Data weighting: An iterative process linking surveys, data synthesis, and population models to evaluate mis-specification. Fish. Res. 106762 https://www.sciencedirect.com/science/article/abs/pii/S0165783623001558
Punt, A.E. 2023. Those who fail to learn from history are condemned to repeat it: A perspective on current stock assessment good practices and the consequences of not following them. Fish. Res. 106642 https://www.sciencedirect.com/science/article/pii/S0165783623000358
Cadrin, S.X., Goethel, D.R., Berger, A., Jardim, E. 2023. Best practices for defining spatial boundaries and spatial structure in stock assessment. Fish. Res. 106650 https://www.sciencedirect.com/science/article/pii/S0165783623000437
Goethel, D.R., Berger, A.M., Cadrin, S.X. 2023. Spatial awareness: Good practices and pragmatic recommendations for developing spatially structured stock assessments. Fish. Res. 106703 https://www.sciencedirect.com/science/article/abs/pii/S0165783623000966
Hoyle, S.D., Campbell, R.A., Ducharme-Barth, N.D., Grüss, A., ... Maunder, M.N. 2023. Catch per unit effort modelling for stock assessment: A summary of good practices. Fish. Res. 106860. https://www.sciencedirect.com/science/article/pii/S0165783623002539
Sellinger, E.L., Szuwalski, C., Punt, A.E. 2023. The robustness of our assumptions about recruitment: A re-examination of marine recruitment dynamics with additional data and novel methods. Fish. Res. 106862. https://www.sciencedirect.com/science/article/pii/S0165783623002552
Lee, H.H., Maunder, M.N., Piner, K.R. 2024. Good Practices for estimating and using length-at-age in integrated stock assessments. Fisheries Research 106883. https://www.sciencedirect.com/science/article/pii/S016578362300276X
Brooks, E.N. 2024. Pragmatic approaches to modeling recruitment in fisheries stock assessment: A perspective. Fisheries Research 106896. https://www.sciencedirect.com/science/article/pii/S0165783623002898
Schaub, M. Maunder, M.N., Kéry, M., Thorson, J.T., Jacobson, E.K., Punt, A.E. 2024. Lessons to be learned by comparing integrated fisheries stock assessment models (SAMs) with integrated population models (IPMs). Fisheries Research 106925. https://www.sciencedirect.com/science/article/pii/S0165783623003181
Special Issue on Natural Mortality (Fisheries Research) [In Progress] Link
Mace, M.M., Doering, K.L., Wilberg, M.J., Larimer, A., Marenghi, F., Sharov, A., Tarnowski, M. 2021. Spatial population dynamics of eastern oyster in the Chesapeake Bay, Maryland. Fish. Res. 237, 105854 https://www.sciencedirect.com/science/article/abs/pii/S0165783620303714
Pope, J.G., Gislason, H., Rice, J.C., Daan, N. 2021. Scrabbling around for understanding of natural mortality. Fish. Res. 240, 105952 https://www.sciencedirect.com/science/article/abs/pii/S0165783621000801
Perreault, A.M.J., Cadigan, N.G. 2021. Natural mortality diagnostics for state-space stock assessment models. Fish. Res. 243, 106062 https://www.sciencedirect.com/science/article/abs/pii/S0165783621001909
Aldrin, M., AanesaI, F.L., Tvete, F., Aanes, S., Subbey, S. 2021. Caveats with estimating natural mortality rates in stock assessment models using age aggregated catch data and abundance indices. Fish. Res. 243, 106071 https://www.sciencedirect.com/science/article/pii/S0165783621001995
Regular, P.M., Buren, A.D., Dwyer, K.S., Cadigan, N.G., Gregory, R.S., Koen-Alonso, M., Rideout, R.M., Robertson, G.J., Robertson, M.D., Stenson, G.B., Wheeland, L.J., Zhang, F. 2022. Indexing starvation mortality to assess its role in the population regulation of Northern cod. Fish. Res. 247, 106180 https://www.sciencedirect.com/science/article/pii/S0165783621003088
Clark, W.G. 2022. Why natural mortality is estimable, in theory if not in practice, in a data-rich stock assessment. Fish. Res. 248, 106203 https://www.sciencedirect.com/science/article/abs/pii/S0165783621003313
Plagányi, E.E., Blamey, L.K. Rogers, J.G.D., ulloch, V.J.D. 2022. Playing the detective: Using multispecies approaches to estimate natural mortality rates. Fish. Res. 249, 106229 https://www.sciencedirect.com/science/article/pii/S0165783622000066
Maunder, M.N. 2022. Stock-recruitment models from the viewpoint of density-dependent survival and the onset of strong density-dependence when a carrying capacity limit is reached. Fis. Res. 249, 106249 https://www.sciencedirect.com/science/article/abs/pii/S0165783622000261
Sagarese, S.R., Harford, W.J. 2022. Evaluating the risks of red tide mortality misspecification when modeling stock dynamics. Fish. Res. 250, 106271 https://www.sciencedirect.com/science/article/abs/pii/S0165783622000480
Cao, J. Chen, Y. 2022. Modeling time-varying natural mortality in size-structured assessment models. Fish. Res. 250, 106290 https://www.sciencedirect.com/science/article/abs/pii/S0165783622000674
Cronin-Fine, L., Punt, A.E. Factors influencing size-structured models’ ability to estimate natural mortality. Fish. Res. 250, 106292 https://www.sciencedirect.com/science/article/abs/pii/S0165783622000698
Szuwalski, C. 2022. Estimating time-variation in confounded processes in population dynamics modeling: A case study for snow crab in the eastern Bering Sea. Fish. Res. 251, 106298 https://www.sciencedirect.com/science/article/abs/pii/S0165783622000753
Adams, G.D. Holsman, K.K., Barbeaux, S.J., Dorn, M.W., Ianelli, J.N., SpiesbIan, I., Stewart, J. Punt, A.E. An ensemble approach to understand predation mortality for groundfish in the Gulf of Alaska. Fish. Res. 251, 106303 https://www.sciencedirect.com/science/article/abs/pii/S0165783622000807
Siddeek, M.S.M., Daly, B., Vanek, V. Siddon, Z.C. 2022. Length-based approaches to estimating natural mortality using tagging and fisheries data: The example of the eastern Aleutian Islands, Alaska golden king crab (Lithodes aequispinus). Fish. Res. 251, 106304 https://www.sciencedirect.com/science/article/abs/pii/S0165783622000819
Lorenzen, K., Camp, E.V., Garlock, T.M. 2022. Natural mortality and body size in fish populations. Fish. Res. 252, 106327 https://www.sciencedirect.com/science/article/abs/pii/S0165783622001047
Dorn, M.W., Barnes, S.L. 2022. Time-varying predation as a modifier of constant natural mortality for Gulf of Alaska walleye pollock. Fish. Res. 254, 06391 https://www.sciencedirect.com/science/article/pii/S0165783622001680
Hart, D.R., Chang, J-H. 2022. Estimating natural mortality for Atlantic Sea scallops (Placopecten magellenicus) using a size-based stock assessment model. Fish. Res. 254, 106423 https://www.sciencedirect.com/science/article/abs/pii/S0165783622002004
Lorenzen, K. Size- and age-dependent natural mortality in fish populations: Biology, models, implications, and a generalized length-inverse mortality paradigm. Fish. Res. 255, 106454 https://www.sciencedirect.com/science/article/abs/pii/S0165783622002314
Peatman, T. Vincent, M.T., Scutt Phillips, J. Nicol, S. 2022. Times are changing, but has natural mortality? Estimation of mortality rates for tropical tunas in the western and central Pacific Ocean. Fish. Res. 256, 106463 https://www.sciencedirect.com/science/article/pii/S0165783622002405
Maunder, M.N., Hamel, O.S., Lee, H-H., Piner, K.R., Cope, J.M., Punt, A.E., Ianelli, J.N., Castillo-Jordan, C., Kapur, M.S., 2023. A review of estimation methods for natural mortality and their performance in the context of fishery stock assessment. Fish. Res. 257, 106489. https://www.sciencedirect.com/science/article/pii/S0165783622002661?dgcid=author
Hoyle, S.D., Williams, A.J., Minte-Vera, C.V. Maunder, M.N. 2023. Approaches for estimating natural mortality in tuna stock assessments: Application to global yellowfin tuna stocks. Fish. Res. 257, 106498. https://www.sciencedirect.com/science/article/pii/S0165783622002752?dgcid=coauthor
Special Issue on General stock assessment models (Fisheries Research) resulting from CAPAM's Workshop on General stock assessment models. Link
Hoyle, S.D., Maunder, M.N., Punt, A.E., Mace, P.M., Devine, J.A., A’mar, Z.T. 2022. Preface: Developing the next generation of stock assessment software. Fish. Res. 246, 106176 https://www.sciencedirect.com/science/article/abs/pii/S0165783621003040
Albertsen, C.M., Trijoulet, V. 2020. Model-based estimates of reference points in an age-based state-space stock assessment model. Fish. Res. 105618. https://www.sciencedirect.com/science/article/abs/pii/S0165783620301351
Aldrin, M., Tvete, I.F., Subbey, S. 2020. The specification of the data model part in the SAM model matters. Fish. Res. 105585. https://www.sciencedirect.com/science/article/pii/S0165783620301028
Punt, A.E., Dunn, A., Elvarsson, B., Hampton, J., … 2020. Essential features of the next-generation integrated fisheries stock assessment package: A perspective. Fish. Res. 105617. https://www.sciencedirect.com/science/article/abs/pii/S016578362030134X
Dichmont, C.M., Deng, R.A., Dowling, N., Punt, A.E. 2021. Collating stock assessment packages to improve stock assessments. Fish. Res. 236, 105844 https://www.sciencedirect.com/science/article/abs/pii/S0165783620303611
Stock, B.C., Xu, H. Miller, T.J., Thorson, J.T., Nyed, J.A. 2021. Implementing two-dimensional autocorrelation in either survival or natural mortality improves a state-space assessment model for Southern New England-Mid Atlantic yellowtail flounder. Fish. Res. 237, 105873 https://www.sciencedirect.com/science/article/pii/S0165783621000011
Taylor, I.G., Doering, K.L., Johnson, K.F., Wetzel, C.R., Stewart, I.J. 2021. Beyond visualizing catch-at-age models: Lessons learned from the r4ss package about software to support stock assessments. Fish. Res. 239, 105924 https://www.sciencedirect.com/science/article/abs/pii/S0165783621000527
Cronin-Fine, L., Punt, A.E. 2021. Modeling time-varying selectivity in size-structured assessment models. Fish. Res. 239, 105927 https://www.sciencedirect.com/science/article/abs/pii/S0165783621000552
Babyn, J., Varkey, D., Regular, P. Ings, D., Mills Flemming, J. 2021. A gaussian field approach to generating spatial age length keys. Fish. Res. 240, 105956 https://www.sciencedirect.com/science/article/abs/pii/S0165783621000849
Carvalho, F., Winker, H., Courtney, D., Kapur, M., Kell, L., Cardinale, M, Schirripa, M., Kitaka, T., Yemane, D., Piner, K.R., Maunder, M.N., Taylor, I., Wetzel, C.R., Doering, K., Johnson, K.F., Methot, R.D. 2021. A cookbook for using model diagnostics in integrated stock assessments. Fish. Res. 240, 105959 https://www.sciencedirect.com/science/article/pii/S0165783621000874
Stock, B.C., Miller, T.J. 2021. The Woods Hole Assessment Model (WHAM): A general state-space assessment framework that incorporates time- and age-varying processes via random effects and links to environmental covariates. Fish. Res. 240, 105967 https://www.sciencedirect.com/science/article/pii/S0165783621000953
Hayashi, A., Ichinokawa, M., Kinoshita, J., Manabe, A. 2021. Optimizing stock assessment workflows by applying software development methodology. Fish. Res. 244, 106108 https://www.sciencedirect.com/science/article/abs/pii/S0165783621002368
Kapura, M.S. Siple, M.C., Olmos, M. Privitera-Johnson, K.M., Adams, G., Best, J., Castillo-Jordán, C., Cronin-Fine, L., Havron, A.M., Lee, Q., Methot, R.D., Punt, A.E. 2021. Equilibrium reference point calculations for the next generation of spatial assessments. Fish. Res. 244, 106132 https://www.sciencedirect.com/science/article/abs/pii/S0165783621002605
Special Issue on Spatial Stock Assessment Models (Fisheries Research) resulting from CAPAM's Workshop on Spatial Stock Assessment Models. Link
Goethel, D.R., Bosley, K. M. Hanselman, D.H., Berger, A.M., Deroba, J.J., Langseth, B.J., Schueller, A.M. 2019. Exploring the utility of different tag-recovery experimental designs for use in spatially explicit, tag-integrated stock assessment models. Fish. Res. 105320. https://www.sciencedirect.com/science/article/abs/pii/S0165783619301675
Hoyle, S.D., Langley, A.D. 2020. Scaling factors for multi-region stock assessments, with an application to Indian Ocean tropical tunas. Fish. Res. 105586. https://www.sciencedirect.com/science/article/abs/pii/S016578362030103X
Moore, B.R., Bell, J.D., Evans, K., Farley, J. … 2020. Defining the stock structures of key commercial tunas in the Pacific Ocean I: Current knowledge and main uncertainties. Fish. Res. 105525. https://www.sciencedirect.com/science/article/pii/S0165783620300424
Mormede, S. Parker, S.J., Pinkerton, M.H. 2020. Comparing spatial distribution modelling of fisheries data with single-area or spatially-explicit integrated population models, a case study of toothfish in the Ross Sea region. Fish. Res. 105381. https://www.sciencedirect.com/science/article/abs/pii/S016578361930236X
Punt, A.E. 2019. Spatial stock assessment methods: A viewpoint on current issues and assumptions. Fish. Res. 213: 132-143. https://www.sciencedirect.com/science/article/abs/pii/S0165783619300177
Punt, A.E., Dalton, M.G., Foy, R.J. 2020. Multispecies yield and profit when exploitation rates vary spatially including the impact on mortality of ocean acidification on North Pacific crab stocks. Fish. Res. 105481. https://www.sciencedirect.com/science/article/abs/pii/S0165783619303364
Vincent, M.T., Brenden, T.O., Bence, J.R. 2020. Parameter estimation performance of a recapture-conditioned integrated tagging catch-at-age analysis model. Fish. Res. 105451. https://www.sciencedirect.com/science/article/abs/pii/S0165783619303066
Watson, F.M., Hepburn, L.J., Cameron, T., Le Quesne, W.J.F, Codling, E.A. 2019. Relative mobility determines the efficacy of MPAs in a two species mixed fishery with conflicting management objectives. Fish. Res. 105334. https://www.sciencedirect.com/science/article/abs/pii/S0165783619301894
Special Issue on Spatio-temporal models (Fisheries Research) resulting from CAPAM's Workshop on Spatio-temporal models. link
Currie, J.C., Thorson, J.T., Sink, K.J., Atkinson, L.J., Winker, H., Fairweather, T.P. 2019. A novel approach to assess distribution trends from fisheries survey data. Fish. Res. 214: 98-109. https://www.sciencedirect.com/science/article/abs/pii/S0165783619300414
Grüss, A. Walter, J.F., Babcock, E.A., Forrestal, F.C., Schirripa, M.J. 2019. Evaluation of the impacts of different treatments of spatio-temporal variation in catch-per-unit-effort standardization models. Fish. Res. 213: 75-93. https://www.sciencedirect.com/science/article/abs/pii/S0165783619300086
Hashimoto, M. Nishijima, S., Yukami, R. Watanabe, Kamimura, Y., C., Furuichi, S., Ichinokawa, M. Okamura, H. 2019. Spatiotemporal dynamics of the Pacific chub mackerel revealed by standardized abundance indices. Fish. Res. 105315. https://www.sciencedirect.com/science/article/pii/S0165783619301626
Johnson, K.F., Thorson, J.T., Punt, AE. 2019. Investigating the value of including depth during spatiotemporal index standardization. Fish. Res. 216: 126-137. https://www.sciencedirect.com/science/article/abs/pii/S0165783619300955
Kai, M. 2019. Spatio-temporal changes in catch rates of pelagic sharks caught by Japanese research and training vessels in the western and central North Pacific. Fish. Res. 216: 177-195. https://www.sciencedirect.com/science/article/abs/pii/S016578361930058X
Maunder, M.N., Thorson, J.T., Xu, H., Oliveros-Ramos, R., … 2020. 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
Murphy, J.T. 2020. Climate change, interspecific competition, and poleward vs. depth distribution shifts: Spatial analyses of the eastern Bering Sea snow and Tanner crab (Chionoecetes opilio and C. bairdi). Fish. Res. 105417. https://www.sciencedirect.com/science/article/abs/pii/S0165783619302723
Perretti, C.T., Thorson, J.T. 2019. Spatio-temporal dynamics of summer flounder (Paralichthys dentatus) on the Northeast US shelf. Fish. Res. 215: 62-68. https://www.sciencedirect.com/science/article/abs/pii/S0165783619300712
Thorson, J.T., Maunder, M.N., Punt, A.E. 2020. The development of spatio-temporal models of fishery catch-per-unit-effort data to derive indices of relative abundance. Fish. Res. 105611. https://www.sciencedirect.com/science/article/abs/pii/S0165783620301284
Thorson, J.T. 2019. Guidance for decisions using the Vector Autoregressive Spatio-Temporal (VAST) package in stock, ecosystem, habitat and climate assessments. Fish. Res. 210: 143-161. https://www.sciencedirect.com/science/article/abs/pii/S0165783618302820
Xu, H. Lennert-Cody, C.E., Maunder, M.N., Minte-Vera, C.V. 2019. Spatiotemporal dynamics of the dolphin-associated purse-seine fishery for yellowfin tuna (Thunnus albacares) in the eastern Pacific Ocean. Fish. RFRes. 213: 121-131. https://www.sciencedirect.com/science/article/abs/pii/S016578361930013X
Special Issue on Recruitment (Fisheries Research) resulting from CAPAM's Recruitment Workshop. Link
Berger, A.M. 2019. Character of temporal variability in stock productivity influences the utility of dynamic reference points. Fisheries Research. 217: 185-197. https://www.sciencedirect.com/science/article/abs/pii/S0165783618303424
Brooks, E.N., Thorson, J.T., Shertzer, K.W., Nash, R.D.M., Brodziak, J.K.T., Johnson, K.F., Klibansky, N., Wells, B.K., White, K. 2019. Paulik revisited: Statistical framework and estimation performance of multistage recruitment functions. Fisheries Research. Fisheries Research. 217: 58-70. https://www.sciencedirect.com/science/article/pii/S0165783618301887
Cadrin, S.X., Goethel, D.R., Morse, M.R., Fay, G., Kerr, L.A. 2019. "So, where do you come from?" The impact of assumed spatial population structure on estimates of recruitment. Fisheries Research. 217: 156-168. https://www.sciencedirect.com/science/article/pii/S0165783618303448
Canales, C.M., Cubillos, L.A., Cuevas, M.J., Adasme, N., Sanchez, N. 2019. Applying a separability assumption in a length-based stock assessment model to evaluate intra-annual effects of recruitment process error of small-pelagic fish. Fisheries Research. 217: 108-121. https://www.sciencedirect.com/science/article/abs/pii/S0165783618302911
Crone, P. R., Maunder, M. N., Lee, H. H., Piner, K. R. 2019. Good practices for including environmental data to inform spawner-recruit dynamics in integrated stock assessments: Small pelagic species case study. Fisheries Research. 217: 122-132. https://www.sciencedirect.com/science/article/abs/pii/S0165783618303825
Haltuch, M. A., Brooks, E. N., Brodziak, J., Devine, J.A., ... Wells, B.K. 2019. Unraveling the recruitment problem: A review of environmentally-informed forecasting and management strategy evaluation. Fisheries Research. 217: 198-216. https://www.sciencedirect.com/science/article/abs/pii/S0165783618303606
He, X., Field, J.C. 2019. Effects of recruitment variability and fishing history on estimation of stock-recruitment relationships: Two case studies from U.S. West Coast fisheries. Fisheries Research. 217: 21-34. https://www.sciencedirect.com/science/article/pii/S0165783618301656
Kinzey, D. Watters, G.M., Reiss, C.S. 2019. Estimating recruitment variability and productivity in Antarctic krill. Fisheries Research. 217: 98-107. https://www.sciencedirect.com/science/article/pii/S0165783618302686
Kolody, D.S., Everson, J.P., Preece, A.L., Davies, C.R., Hillary, R.M. 2019. Recruitment in tuna RFMO stock assessment and management: A review of current approaches and challenges. Fisheries Research. 217: 217-234. https://www.sciencedirect.com/science/article/abs/pii/S0165783618303412
Lorenzen, K., Camp, E.V. 2019. Density-dependence in the life history of fishes: When is a fish recruited? Fisheries Research. 217: 5-10. https://www.sciencedirect.com/science/article/pii/S0165783618302650
Maunder M.N., Thorson, J.T. 2019. Modeling temporal variation in recruitment in fisheries stock assessment: A review of theory and practice. Fisheries Research. 217: 71-86. https://www.sciencedirect.com/science/article/abs/pii/S0165783618303564
Minte-Vera, C.V., Maunder, M.N., Schaefer, K.M., Aires-da-Silva, A.M. 2019. The influence of metrics for spawning output on stock assessment results and evaluation of reference points: An illustration with yellowfin tuna in the eastern Pacific Ocean. Fisheries Research. 217: 35-45. Link
Plagányi, E. E., Haywood, M. D. E., Gorton, R. J., Siple, M. C., Deng, R. A. 2019. Management implications of modelling fisheries recruitment. Fisheries Research. 217: 35-45
Punt, A.E. 2019. Modelling recruitment in a spatial context: A review of current approaches, simulation evaluation of options, and suggestions for best practices. Fisheries Research. 217: 140-155. https://www.sciencedirect.com/science/article/pii/S0165783617302424
Punt, A.E., Cope, J.M. 2019. Extending integrated stock assessment models to use non-depensatory three-parameter stock-recruitment relationships. Fisheries Research. 217: 46-57. https://www.sciencedirect.com/science/article/pii/S0165783617301819
Sharma, R., Porch, C. E., Babcock, E. A., Maunder, M. N., Punt, A. E. 2019. Recruitment: Theory, estimation, and application in fishery stock assessment models. Fisheries Research. 217: 1-4. Link
Thorson, J. T. 2019. Perspective: Let’s simplify stock assessment by replacing tuning algorithms with statistics. Fisheries Research. 217: 133-139. Link
Thorson, J.T., Dorn, M.W., Hamel, O.S. 2019. Steepness for West Coast rockfishes: Results from a twelve-year experiment in iterative regional meta-analysis. Fisheries Research. 217: 11-20. https://www.sciencedirect.com/science/article/pii/S0165783618300882
Thorson, J.T., Rudd, M.B., Winker, H. 2019. The case for estimating recruitment variation in data-moderate and data-poor age-structured models. Fisheries Research. 217: 87-97. https://www.sciencedirect.com/science/article/pii/S0165783618301978
Special Issue on Data Weighting (Fisheries Research) resulting from CAPAM's Data Weighting Workshop. Link
Maunder, M.N., Crone, P.R, Punt, A.E., Valero, J.L., Semmens B. X. 2017. Data conflict and weighting, likelihood functions and process error. Fisheries Research. 192: 1-4. Link
Carvalho, F., Punt, A. E., Chang, Y. J., Maunder, M. N., Piner, K. R. 2017. Can diagnostic tests help identify model misspecification in integrated stock assessments? Fisheries Research. 192: 28-40. Link
Francis, R. I. C. C. 2017. Revisiting data weighting in fisheries stock assessment models. Fisheries Research. 192: 5-15. Link
Maunder, M. N. and Piner, K. R. 2017. Dealing with data conflicts in statistical inference of population assessment models that integrate information from multiple diverse data sets. Fisheries Research. 192: 16-27. Link
Minte-Vera, C. V., Maunder, M. N., Aires-da-Silva, A. M., Satoh, K., Uosaki, K. Get the biology right, or use size-composition data at your own risk. 2017. Fisheries research. 192: 114-125. Link
Punt, A. E. 2017. Some insights into data weighting in integrated stock assessments. Fisheries Research. 192: 52-65. Link
Punt, A. E., Deng, R. A., Siddeek, M. S. M., Buckworth, R. C., Vanek, V. 2017. Data weighting for tagging data in integrated size-structured models. Fisheries Research. 192: 94-102. Link
Siddeek, M.S.M., Zheng, J., A.E. Punt, A. E., and Pengilly, D. 2017. Effect of data weighting on the mature male biomass estimate for Alaskan golden king crab. 192: 103-113. Link
Sippel, T., Lee, H. H., Piner, K. Teo, S.L.H. 2017. Searching for M: Is there more information about natural mortality in stock assessments than we realize? Fisheries Research. 192: 135-140. Link
Stewart, I.J., Monnahan, C.C. 2017. Implications of process error in selectivity for approaches to weighting compositional data in fisheries stock assessments. Fisheries Research. 192: 126-134. Link
Thorson, J. T., Johnson, K. F., Methot, R. D., Taylor, I. G. 2017. Model-based estimates of effective sample size in stock assessment models using the Dirichlet-multinomial distribution. Fisheries Research. 192: 84-93. Link
Truesdell, S. B., Bence, J. R., Syslo, J. M., Ebener, M. P. 2017. Estimating multinomial effective sample size in catch-at-age and catch-at-size models. Fisheries Research. 192: 66-83. Link
Wang, S-P and Maunder, M. N. Is down-weighting composition data adequate for dealing with model misspecification, or do we need to fix the model? Fisheries Research. 192: 41-51. Link
Special Issue on Growth (Fisheries Research) resulting from CAPAM's Growth Workshop. Volume 180, Pages 1-194 (August 2016). Edited by M.N. Maunder, A.E. Punt, P.R. Crone, J.L. Valero and B.X. Semmens. Link
Francis, C. 2016. Growth in age-structured stock assessment models. Fisheries Research, 180: 77-86. Link
Special Issue on Selectivity (Fisheries Research) resulting from CAPAM's Selectivity Workshop. Fisheries Research, Volume 158, Pages 1-204 (October 2014). Edited by M.N. Maunder, P.R. Crone, J.L. Valero and B.X. Semmens. Link
Butterworth, D. S., Rademeyer, R. A., Brandão, A., Geromont, H. F., Johnston, S. J. 2014. Does selectivity matter? A fisheries management perspective. Fisheries Research, 158: 194-204. Link
Clark, W. G. 2014. Direct calculation of relative fishery and survey selectivities. Fisheries Research, 158: 135-137. Link
Crone, P. R., Valero, J. L. 2014. Evaluation of length- vs. age- composition data and associated selectivity assumptions used in stock assessments based on robustness of derived management quantities. Fisheries Research, 158: 165-171. Link
Hulson, P. J. F, Hanselman, D. H. 2014. Tradeoffs between bias, robustness, and common sense when choosing selectivity forms. Fisheries Research, 158: 63-73. Link
Hurtado-Ferro, F., Punt, A. E., Hill, K. T. 2014. Use of multiple selectivity patterns as a proxy for spatial structure. Fisheries Research, 158: 102-115. Link
Ichinokawaa, M., Okamura, H., Takeuchi, Y. 2014. Data conflict caused by model mis-specification of selectivity in an integrated stock assessment model and its potential effects on stock status estimation. Fisheries Research, 158: 147-157. Link
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. Link
Legault, C.M. 2014. The ability of two age composition error distributions to estimate selectivity and spawning stock biomass in simulated stock assessments. Fisheries Research, 158: 172-180. Link
Martell, S.J.D., Stewart, I.J. 2014. Towards defining good practices for modeling time-varying selectivity. Fisheries Research, 158: 84-95. Link
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. Link
Nielsen, A., Berg. C. W. 2014. Estimation of time-varying selectivity in stock assessments using state-space models. Fisheries Research, 158: 96-101. Link
Okamura, H., McAllister, M.K, Ichinokawa, M., Yamanaka, L., Holt, K. 2014. Evaluation of the sensitivity of biological reference points to the spatio-temporal distribution of fishing effort when seasonal migrations are sex-specific. Fisheries Research, 158: 116-123. Link
Punt, A. E., Hurtado-Ferro, F., Whitten, A. R. 2014. Model selection for selectivity in fisheries stock assessments. Fisheries Research, 158: 124-134. Link
Sampson, D. B. 2014. Fishery selection and its relevance to stock assessment and fishery management. Fisheries Research, 158: 5-14. Link
Schueller, A. M., Williams, E. H., Cheshire, R. T. 2014. A proposed, tested, and applied adjustment to account for bias in growth parameter estimates due to selectivity. Fisheries Research, 158: 26-39. Link
Sharma, R., Langley, A., Herrera, M., Geehan, J., Hyun, S-Y. 2014. Investigating the influence of length–frequency data on the stock assessment of Indian Ocean bigeye tuna. Fisheries Research, 158: 50-62. Link
Stewart, I. J., Martell, S. J. D. 2014. A historical review of selectivity approaches and retrospective patterns in the Pacific halibut stock assessment. Fisheries Research, 158: 40-49. Link
Thorson, J. T., Taylor, I. G. 2014. A comparison of parametric, semi-parametric, and non-parametric approaches to selectivity in age-structured assessment models. Fisheries Research, 158: 74-83. Link
Wang, S. P., Maunder, M. N., Aires-da-Silva, A. 2014. Selectivity's distortion of the production function and its influence on management advice from surplus production models. Fisheries Research, 158: 181-193. Link
Wang, S. P., Maunder, M. N., Piner, K. R., Aires-da-Silva, A. Lee, H. H. 2014. Evaluation of virgin recruitment profiling as a diagnostic for selectivity curve structure in integrated stock assessment models. Fisheries Research, 158: 158-164. Link
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. Link
