Publications

CAPAM staff/members highlighted in bold

2017   2016   2015   2014   2013   Special Issues:   Data weighting  -  Growth  -  Selectivity

 

2017

Maunder, M.N., Crone, P.R, Punt, A.E., Valero, J.L., Semmens B. X. (In Press). Data conflict and weighting, likelihood functions and process error. Fisheries Research. Link

Maunder, M. N. and Piner, K. R. (In Press). Dealing with data conflicts in statistical inference of population assessment models that integrate information from multiple diverse data sets. Fisheries Research. 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. (In Press). Fisheries research. Link

 


2016

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.

Carvalho, F., Punt, A. E., Chang, Y. J., Maunder, M. N., Piner, K. R. (In Press). Can diagnostic tests help identify model misspecification in integrated stock assessments? Fisheries Research. Link

Francis, C., Aires-da-Silva, A., MaunderM. 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.

Kuriyama, P. T., Ono, K., Hurtado-Ferro, F., Hicks, A. C., Taylor, I. G., Licandeo, R. R., Johnson, K. F., Anderson, S. C., Monnahan, C. C., Rudd, M. B., Stawitz, C. C., Valero, J. L. 2016. An empirical weight-at-age approach reduces estimation bias compared to modeling parametric growth in integrated, statistical stock assessment models when growth is time varying. Fisheries Research, 180: 119-127. Link
 
Maunder, M.N., Crone, P.R, Punt, A.E., Valero, J.L., Semmens B. X.  2016. Growth: Theory, estimation, and application in fishery stock assessment models. Fisheries Research, 180: 1-3. Link
 
Minte-Vera, C. V., Maunder, M. N., Casselman, J. M., Campana, S. E. 2016. Growth functions that incorporate the cost of reproduction. Fisheries Research, 180: 31-44. Link
 
Monnahan, C. C., Ono, K., Anderson, S. C., Rudd, M. B., Hicks, A. C., Hurtado-Ferro, F., Johnson, K. F., Kuriyama, P. T., Licandeo, R. R., Stawitz, C. C., Taylor, I. G., Valero, J. L. 2016. The effect of length bin width on growth estimation in integrated age-structured stock assessments. Fisheries Research, 180: 103-112. Link
 
Piner, K. R., Lee, H. H. and Maunder, M. N. 2016. Evaluation of using random-at-length observations and an equilibrium approximation of the population age structure in fitting the von Bertalanffy growth function, 180: 128-137. 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., Parma, A.M., Restrepo, V.R., Sharma, R., Ahrens, R. and Hilborn, R. In press. Effects of biological, economic and management factors on tuna and billfish stock status. Fish and Fisheries.

 

Wang, S-P and Maunder, M. N. (In Press). Is down-weighting composition data adequate for dealing with model misspecification, or do we need to fix the model? Fisheries Research. Link

 
Zhu, J., Maunder, M. N., Aires-da-Silva, A. M., Chen, Y. 2016. Estimation of growth within Stock Synthesis models: Management implications when using length-composition data. Fisheries Research, 180: 87-91. Link
 

2015

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., ValeroJ. 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/fsu055Link

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., Crone, P.R., Valero, J.L., and Semmens, B. X. (Editors). 2015. Growth: theory, estimation, and application in fishery stock assessment models. Center for the Advancement of Population Assessment Methodology (CAPAM). NOAA/IATTC/SIO, 8901 La Jolla Shores Dr., La Jolla, CA 92037. 55 p. Link

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/fsu015Link

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

 

2014

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. 2014Use 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. 2014Evaluation 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

 


2013

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 Data Weighting (Fisheries Research) resulting from CAPAM's Data Weighting Workshop. 

Maunder, M.N., Crone, P.R, Punt, A.E., Valero, J.L., Semmens B. X. (In Press). Data conflict and weighting, likelihood functions and process error. Fisheries Research. Link

Carvalho, F., Punt, A. E., Chang, Y. J., Maunder, M. N., Piner, K. R. (In Press). Can diagnostic tests help identify model misspecification in integrated stock assessments? Fisheries Research. Link

Francis, R. I. C. C. (In Press). Revisiting data weighting in fisheries stock assessment models. Fisheries Research. Link

Maunder, M. N. and Piner, K. R. (In Press). Dealing with data conflicts in statistical inference of population assessment models that integrate information from multiple diverse data sets. Fisheries Research. 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. (In Press). Fisheries research. Link

Punt, A. E. (In Press). Some insights into data weighting in integrated stock assessments. Fisheries Research. Link

Punt, A. E., Deng, R. A., Siddeek,  M. S. M., Buckworth, R. C., Vanek, V. (In Press). Data weighting for tagging data in integrated size-structured models. Fisheries Research. Link

Siddeek, M.S.M., Zheng, J., A.E. Punt, A. E., and Pengilly, D. (In Press). Effect of data weighting on the mature male biomass estimate for Alaskan golden king crab. Link

Sippel, T., Lee, H. H., Piner, K. Teo, S.L.H. (In Press). Searching for M: Is there more information about natural mortality in stock assessments than we realize? Fisheries Research. Link

Stewart, I.J., Monnahan, C.C. (In Press). Implications of process error in selectivity for approaches to weighting compositional data in fisheries stock assessments. Fisheries Research. Link

Thorson, J. T., Johnson, K. F., Methot, R. D., Taylor, I. G. (In Press). Model-based estimates of effective sample size in stock assessment models using the Dirichlet-multinomial distribution. Fisheries Research. Link

Truesdell, S. B., Bence, J. R., Syslo, J. M., Ebener, M. P. (In Press). Estimating multinomial effective sample size in catch-at-age and catch-at-size models. Fisheries Research. Link

Wang, S-P and Maunder, M. N. (In Press). Is down-weighting composition data adequate for dealing with model misspecification, or do we need to fix the model? Fisheries Research. 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

 
Francis, C., Aires-da-Silva, A., MaunderM. 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
 
He, X., Field, J. C., Pearson, D. E., Lefebvre, L. S. 2016. Age sample sizes and their effects on growth estimation and stock assessment outputs: Three case studies from U.S. West Coast fisheries. Fisheries Research, 180: 92-102. Link
 
Kolody, D. S., Eveson, J. P., Hillary, R. M. 2016. Modelling growth in tuna RFMO stock assessments: Current approaches and challenges. Fisheries Research, 180: 177-193. Link
 
Kuriyama, P. T., Ono, K., Hurtado-Ferro, F., Hicks, A. C., Taylor, I. G., Licandeo, R. R., Johnson, K. F., Anderson, S. C., Monnahan, C. C., Rudd, M. B., Stawitz, C. C., Valero, J. L. 2016. An empirical weight-at-age approach reduces estimation bias compared to modeling parametric growth in integrated, statistical stock assessment models when growth is time varying. Fisheries Research, 180: 119-127. Link
 
Lorenzen, K. 2016. Toward a new paradigm for growth modeling in fisheries stock assessments: Embracing plasticity and its consequences. Fisheries Research, 180: 4-22. Link
 
Maunder, M.N., Crone, P.R, Punt, A.E., Valero, J.L., Semmens B. X.  2016. Growth: Theory, estimation, and application in fishery stock assessment models. Fisheries Research, 180: 1-3. Link
 
Minte-Vera, C. V., Maunder, M. N., Casselman, J. M., Campana, S. E. 2016. Growth functions that incorporate the cost of reproduction. Fisheries Research, 180: 31-44. Link
 
Monnahan, C. C., Ono, K., Anderson, S. C., Rudd, M. B., Hicks, A. C., Hurtado-Ferro, F., Johnson, K. F., Kuriyama, P. T., Licandeo, R. R., Stawitz, C. C., Taylor, I. G., Valero, J. L. 2016. The effect of length bin width on growth estimation in integrated age-structured stock assessments. Fisheries Research, 180: 103-112. Link
 
Ortiz de Zárate, V., Babcock, E. A. 2016. Estimating individual growth variability in albacore (Thunnus alalunga) from the North Atlantic stock: Aging for assessment purposes. Fisheries Research, 180: 54-66. Link
 
Piner, K. R., Lee, H. H. and Maunder, M. N. 2016. Evaluation of using random-at-length observations and an equilibrium approximation of the population age structure in fitting the von Bertalanffy growth function, 180: 128-137. Link
 
Punt, A. E., Haddon, M., McGarvey, R. 2016. Estimating growth within size-structured fishery stock assessments: What is the state of the art and what does the future look like?. Fisheries Research, 180: 147-160. Link
 
Siddeek, M.S.M., Zheng, J., Punt, A.E. and Vanek, V. 2016. Estimation of size-transition matrices with and without moult probability for Alaska golden king crab using tag-recapture data. Fisheries Research, 180: 161-168. Link         
 
Szuwalski, C.S. 2016. Biases in biomass estimates: The effect of bin width in size-structured stock assessment methods. Fisheries Research. 180: 169-176. Link
 
Thorson, J. T., Minte-Vera, C. V. 2016. Relative magnitude of cohort, age, and year effects on size at age of exploited marine fishes. Fisheries Research, 180: 45-53. Link
 
van Poorten, B. T., Walters, C. J. 2016. How can bioenergetics help us predict changes in fish growth patterns?. Fisheries Research, 180: 23-30. Link
 
Webber, D. N., Thorson, J. T. 2016. Variation in growth among individuals and over time: A case study and simulation experiment involving tagged Antarctic toothfish. Fisheries Research, 180: 67-76. Link
 
Xu, Y., Teo, S. T. H., Piner, K. R., Chen, K. S., Wells, R. J. 2016. Using an approximate length-conditional approach to estimate von Bertalanffy growth parameters of North Pacific albacore (Thunnus alalunga). Fisheries Research, 180: 138-146. Link
 
Zhu, J., Maunder, M. N., Aires-da-Silva, A. M., Chen, Y. 2016. Estimation of growth within Stock Synthesis models: Management implications when using length-composition data. Fisheries Research, 180: 87-91. 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.  2014Direct 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. 2014Use 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. 2014Evaluation 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