Applications - nwfsc-assess/geostatistical_delta-GLMM Wiki


I would love to keep track of stock assessments, reports, and papers that either used or explored using SpatialDeltGLMM or VAST, to help make decisions about investment in maintaining and improving the software. Some documents listed below used code that was branched from SpatialDeltGLMM or VAST and is now independently maintained.

Used in stock assessment

I first list instances where VAST (or its precursors) was used and documented as base case for a stock assessment

  1. Canary rockfish, Pacific FMC, 2015 (link here)
  2. Darkblotched rockfish, Pacific FMC, 2015 (link here)
  3. Dusky rockfish, North Pacific FMC, 2015 (link here)
  4. Lingcod, Pacific FMC, 2017 (link here)
  5. Yellowtail rockfish, Pacific FMC, 2017 (link here)
  6. California Scorpionfish, Pacific FMC, 2017 (link here)
  7. Yelloweye rockfish, Pacific FMC, 2017 (link here)
  8. Pacific Ocean perch, Pacific FMC, 2017 (link here)
  9. Arrowtooth flounder, Pacific FMC, 2017 (link here)
  10. Albacore tuna, Secretariat of the Pacific Commission, 2018 (link here)
  11. The 2017 assessment of Snoek (Thyrsites atun) for the South African linefishery, 2017 (link here, see Fig 2.)
  12. Northern shrimp, New England FMC, 2018 (link here, see Fig. 3.4-3.6)
  13. Northern rockfish, North Pacific FMC, 2018 (link here, see e.g., pg. 20-21)
  14. Lophius budegassa, ICES, 2019 (link here, see e.g., Fig. 3.3.5 on pg. 74)
  15. SW Striped Marlin, Western and Central Pacific Fisheries Commission, 2019 (link here, see Fig. 6)
  16. Big skate, Pacific FMC, 2019 (link here, see Fig. 9-11 and 13-18)
  17. Longnose skate, Pacific FMC, 2019 (link here, see Fig. 21-25 and 37-40)
  18. Petrale, Pacific FMC, 2019 (link here, see Fig. 8-11, 18-26)
  19. Sablefish, Pacific FMC, 2019 (link here, Fig. 5-6, 12-13, 19-20, 23-24, 27-28, A7)
  20. Widow, Pacific FMC, 2019 (link here, Fig. 11-12, E1)
  21. Pacific cod in Bering Sea, North Pacific FMC, 2019 (link here, see Fig. 2.6-2.7, 2.11)
  22. Soupfin shark Galeorhinus galeus in South Africa, 2019. (link here,see Section 2.1.4, Fig. 4a)
  23. Smoothhound Mustelus mustelus in South Africa, 2019. (link here, see Section 2.1.4, Fig. 4a)
  24. Walleye pollock in Bering Sea, North Pacific FMC, 2019 (link here, see Fig. 17-18, 25-29, 32, 59-66)
  25. Yellowfin tuna in Western and Central Pacific Ocean, 2020. (link here)
  26. Bigeye tuna in Western and Central Pacific Ocean, 2020. (link here)
  27. Pacific cod in Bering Sea, North Pacific FMC, 2020 (link here, see e.g., 2.7-2.8)
  28. Walleye pollock in Bering Sea, North Pacific FMC, 2020 (link here, see e.g. Fig. 34-36)
  29. Dusky rockfish in the Gulf of Alaska, North Pacific FMC, 2020 (link here, see e.g., Fig. 12.4)
  30. Northern rockfish in the Gulf of Alaska, North Pacific FMC, 2020 (link here, see e.g. Fig. 10-4)
  31. Celtic Sea cod, haddock and whiting, ICES, 2020 (link here, see e.g. Fig. 9-10)
  32. Celtic Sea plaice, ICES, 2020 (link here)
  33. Lingcod north, Pacific FMC, 2021
  34. Lingcod south, Pacific FMC, 2021
  35. Dover sole, Pacific FMC, 2021
  36. Spiny dogfish, Pacific FMC, 2021

Explored and documented in assessment report

  1. Walleye pollock in Eastern Bering Sea, North Pacific FMC, 2016 (link here, see Fig. 1.9)
  2. Hake complex in South Africa: Design-based vs. Geostastical GLMM (2 species), 2017 (link here)
  3. Hake complex in South Africa: Impacts on Stratification (2 species), 2017 (link here)
  4. St. Matthews Island Blue King Crab, North Pacific FMC, 2017 (link here, pg. 1172)
  5. 10 groundfish species in South and West Coast of South Africa, 2017 (link here)
  6. Bocaccio, Pacific FMC, 2017 (link here)
  7. Arrowtooth flounder in Gulf of Alaska, North Pacific FMC, 2017 (link here, see Fig. 7.4)
  8. Bigeye tuna in West and Central Pacific Ocean, Secretariat of the Pacific Commission, 2017 (link here)
  9. Yellowfin tuna in Western and Central Pacific Ocean, Secretariat of the Pacific Commission, 2017 (link here)
  10. Walleye pollock in Eastern Bering Sea, North Pacific FMC, 2018 (link here, see Fig. 60)
  11. Cowcod, Pacific FMC, 2019 (link here, see Fig. 18)
  12. Hake complex in South Africa: Estimating changes in survey catchability q for OMP robustness tests. (link here, p.
  13. Pacific cod in Gulf of Alaska, North Pacific FMC, 2019 (link here, see Fig. 1A.8)
  14. Yellowfin sole in the Bering Sea, North Pacific FMC, 2020 (link here, see e.g., 4.25)
  15. Pacific cod in the Gulf of Alaska, North Pacific FMC, 2020 (link here, see e.g. Appendix Fig. 2.1.5a)
  16. Walleye pollock in the Gulf of Alaska, North Pacific FMC, 2020 (link here, see e.g., Appendix Figure 1A.3a)

Used in ecosystem assessment or report

  1. Eastern Bering Sea ecosystem status report for forage fishes, groundfishes, jellyfish, and salmons (4 separate contributions), NPFMC, 2017 (Yasumiishi et al.) (link here)
  2. Gulf of Alaska ecosystem status report for forage fishes, groundfishes, and salmon (3 separate contributions), NPFMC, 2017 (Moss et al.) (link here)
  3. Eastern Bering Sea ecosystem status report for jellyfishes, groundfishes, and copepods (3 separate contributions), NPFMC, 2018 (link here, see Fig. 42/43/66/67; pg. 93/94/98)
  4. Eastern Bering Sea ecosystem status report for forage fish & groundfishes and copepods (2 separate contributions), NPFMC, 2019 (Yasumiishi et al., Eisner et al.) (link here, see Fig. 54/80/81; pg. 89/90/122/123)
  5. Eastern Bering Sea ecosystem status report for copepods (1 contribution), NPFMC, 2020 (Yasumiishi et al.) (link here, see Fig. 60/61; pg. 109/110)

Used in climate assessment or report

  1. NOAA Arctic Report Card, 2019. Comparison of Near-bottom Fish Densities Show Rapid Community and Population Shifts in Bering and Barents Seas (link here, see Fig. 3)
  2. American Meteorological Society, State of the Climate in 2020. Chapter 5, Arctic (link here, see Fig. SB5.1)

Tech memos or white-papers

  1. Strasburger, Moss, Siwicke, Yasumiishi, Pinchuk, Fenske. Eastern Gulf of Alaska Ecosystem Assessment, July through August 2017. 2018. Available at:
  3. Winker, H., Thorson, J.T., Fairweather, T., Leslie, R., Durholtz, D. (2017). Towards improving precision in South African demersal trawl survey indices using geostatistical GLMMs. International Stock Assessment Review Workshop, Cape Town. MARAM/IWS/2018/Hake/BG5. Available here
  4. Tremblay-Boyer, L. and McKechnie, S. (2018). Background analyses for the 2018 stock assessment of South Pacific albacore tuna. WCPFC-SC14-2018/SA-IP-07. Available at:
  5. Tremblay-Boyer, L. and Pilling, G. (2017). Exploratory geostatistical analyses of Pacific-wide operational longline CPUE data for WCPO tuna assessments. WCPFC-SC13-2017/SA-WP-03, Rarotonga, Cook Islands, 9–17 August 2017. Accessible here:
  6. Minte-Vera, C., Xu, H., Maunder, M.N., 2019. Stock status indicators for yellowfin tuna in the eastern Pacific Ocean (No. SAC-10-08). Inter-American Tropical Tuna Commission, San Diego, CA. Available at: (i.e., Fig. 5)
  7. Durcharme-Barth, N., Pilling, G. Background analyses for the 2019 stock assessment of SW Pacific striped marlin. Western and Central Pacific Fisheries Commission, SA-IP-07, 2019. Available at: (i.e., Fig. 21
  8. Kinoshita, J., Aoki, Y., Ducharme-Barth, N. and Kiyofuji, H. 2019. Standardized catch per unit effort (CPUE) of skipjack tuna of the Japanese pole-and-line fisheries in the WCPO from 1972 to 2018. WCPFC-SC15-2019/SA-WP-14. (link here, i.e., Fig. 11)
  9. Hashimoto, M., Tsukahara, Y., Fuji, T., Nakayama, I., Suyama, S., Naya, M., Oshima, K., Kai, M., 2019. Application of spatiotemporal model to fishery-independent survey data for Pacific saury (No. NPFC-2019-SSC PS05-WP17). North Pacific Fishery Commission.
  10. Chang, S-K., Yuan, T-L., Liu, H-I. and Xu, H.. Abundance index of Taiwanese PBF fisheries based on traditional and spatiotemporal delta-generalized linear mixed models ISC Pacific bluefin tuna Working Group, International Scientific Committee for Tuna and Tuna-Like Species in the North Pacific Ocean (ISC). ISC/20/PBFWG-1/03. (link here)
  11. Ducharme-Barth, N., Vincent, M., 2020. Analysis of Pacific-wide operational longline dataset for bigeye and yellowfin tuna catch-per-unit-effort (CPUE). Technical Report WCPFC-SC16-2020/SC16-SA-IP-07
  12. Vidal, T., Hamer, P., 2020. Developing yellowfin tuna recruitment indices from drifting FAD purse seine catch and effort data.
  13. Vidal, T., Hamer, P., Escalle, L., Pilling, G., 2020. Assessing trends in skipjack tuna abundance from purse seine catch and effort data in the WCPO.
  14. Sawada, K., Okuda, T., 2020. Spatial modeling of bycatch patterns for research fishing operations in Subarea 48.6 using VAST. CCAMLR.
  15. Hsu, J., Chang, Y.-J., 2021. CPUE standardization of blue marlin (Makaira nigricans) for the Taiwanese distant-water tuna longline fishery in the Pacific Ocean during 1971-2019 (No. ISC/20/BILLWG-03/03). Institute of Oceanography, National Taiwan University, Taipei, Taiwan.
  16. Manabe, A., Nishijima, S., Yukami, R., 2020. Review and update on fishery-independent and fishery-dependent indices of the chub mackerel of Japan (No. NPFC-2020-TWG CMSA03-WP03). North Pacific Fisheries Commission, Tokyo, Japan.
  17. ICES. 2020. ICES Workshop on evaluating survey information Celtic Sea gadoids (WKESIG). ICES Scientific Reports. 2:107. 26 pp.
  18. Yuan, T, Chang, S., Liu, H., and Huang, C. 2021. ISC Pacific bluefin tuna Working Group, International Scientific Committee for Tuna and Tuna-Like Species in the North Pacific Ocean (ISC)., e.g., Fig. 9-14.
  19. Sawada, K., Okuda, T., 2021. Progress on the spatial modeling of bycatch patterns for research fishing operations in Subarea 48.6 using VAST (No. WG-FSA-2021/48). CCAMLR, Hobart, Australia.

Journal articles

Finally, I list instances of peer-reviewed journal articles using VAST (or its precursors: SpatialDeltaGLMM and SpatialDFA)

  1. Adams, C.F., Brooks, E.N., Legault, C.M., Barrett, M.A., Chevrier, D.F., n.d. Quota allocation for stocks that span multiple management zones: analysis with a vector autoregressive spatiotemporal model. Fish. Manag. Ecol. n/a.

  2. Akia, S., Amandé, M., Pascual, P., Gaertner, D., 2021. Seasonal and inter-annual variability in abundance of the main tropical tunas in the EEZ of Côte d’Ivoire (2000-2019). Fish. Res. 243, 106053.

  3. Bell, R.J., McManus, M.C., McNamee, J., Gartland, J., Galuardi, B., McGuire, C., In press. Perspectives from the water: Utilizing fishers observations to inform SNE/MA windowpane science and management. Fish. Res.

  4. Cao, J., Thorson, J.T., Richards, R.A., Chen, Y., 2017. Spatiotemporal index standardization improves the stock assessment of northern shrimp in the Gulf of Maine. Can. J. Fish. Aquat. Sci. 74, 1781–1793.

  5. Carroll, G., Holsman, K.K., Brodie, S., Thorson, J.T., Hazen, E.L., Bograd, S.J., Haltuch, M.A., Kotwicki, S., Samhouri, J., Spencer, P., Willis‐Norton, E., Selden, R.L., 2019. A review of methods for quantifying spatial predator–prey overlap. Glob. Ecol. Biogeogr. 28, 1561–1577.

  6. Currie, J.C., Thorson, J.T., Sink, K.J., Atkinson, L.J., Fairweather, T.P., Winker, H., 2019. A novel approach to assess distribution trends from fisheries survey data. Fish. Res. 214, 98–109.

  7. Dolder, P.J., Thorson, J.T., Minto, C., 2018. Spatial separation of catches in highly mixed fisheries. Sci. Rep. 8, 13886.

  8. Duffy‐Anderson, J.T., Stabeno, P., Andrews, A.G., Cieciel, K., Deary, A., Farley, E., Fugate, C., Harpold, C., Heintz, R., Kimmel, D., Kuletz, K., Lamb, J., Paquin, M., Porter, S., Rogers, L., Spear, A., Yasumiishi, E., 2019. Responses of the Northern Bering Sea and Southeastern Bering Sea Pelagic Ecosystems Following Record-Breaking Low Winter Sea Ice. Geophys. Res. Lett. 46, 9833–9842.

  9. Eisner, L.B., Yasumiishi, E.M., Andrews, A.G., O’Leary, C.A., 2020. Large copepods as leading indicators of walleye pollock recruitment in the southeastern Bering Sea: Sample-Based and spatio-temporal model (VAST) results. Fish. Res. 232, 105720.

  10. Gao, J., Thorson, J.T., Szuwalski, C., Wang, H.-Y., 2020. Historical dynamics of the demersal fish community in the East and South China Seas. Mar. Freshw. Res.

  11. Grüss, A., Biggs, C., Heyman, W.D., Erisman, B., 2018a. Prioritizing monitoring and conservation efforts for fish spawning aggregations in the U.S. Gulf of Mexico. Sci. Rep. 8, 8473.

  12. Grüss, A., Biggs, C.R., Heyman, W.D., Erisman, B., n.d. Protecting juveniles, spawners or both: A practical statistical modelling approach for the design of marine protected areas. J. Appl. Ecol. 0.

  13. Grüss, A., Drexler, M.D., Ainsworth, C.H., Babcock, E.A., Tarnecki, J.H., Love, M.S., 2018b. Producing Distribution Maps for a Spatially-Explicit Ecosystem Model Using Large Monitoring and Environmental Databases and a Combination of Interpolation and Extrapolation. Front. Mar. Sci. 5.

  14. Grüss, A., Gao, J., Thorson, J.T., Rooper, C.N., Thompson, G., Boldt, J.L., Lauth, R., 2020a. Estimating synchronous changes in condition and density in eastern Bering Sea fishes. Mar. Ecol. Prog. Ser. 635, 169–185.

  15. Grüss, A., Perryman, H.A., Babcock, E.A., Sagarese, S.R., Thorson, J.T., Ainsworth, C.H., Anderson, E.J., Brennan, K., Campbell, M.D., Christman, M.C., Cross, S., Drexler, M.D., Marcus Drymon, J., Gardner, C.L., Hanisko, D.S., Hendon, J., Koenig, C.C., Love, M., Martinez-Andrade, F., Morris, J., Noble, B.T., Nuttall, M.A., Osborne, J., Pattengill-Semmens, C., Pollack, A.G., Sutton, T.T., Switzer, T.S., 2018c. Monitoring programs of the U.S. Gulf of Mexico: inventory, development and use of a large monitoring database to map fish and invertebrate spatial distributions. Rev. Fish Biol. Fish. 28, 667–691.

  16. Grüss, A., Rose, K.A., Justić, D., Wang, L., 2020b. Making the most of available monitoring data: A grid-summarization method to allow for the combined use of monitoring data collected at random and fixed sampling stations. Fish. Res. 229, 105623.

  17. Grüss, A., Thorson, J.T., 2019. Developing spatio-temporal models using multiple data types for evaluating population trends and habitat usage. ICES J. Mar. Sci. 76, 1748–1761.

  18. Grüss, A., Thorson, J.T., Babcock, E.A., Tarnecki, J.H., 2018d. Producing distribution maps for informing ecosystem-based fisheries management using a comprehensive survey database and spatio-temporal models. ICES J. Mar. Sci. 75, 158–177.

  19. Grüss, A., Thorson, J.T., Carroll, G., Ng, E.L., Holsman, K.K., Aydin, K., Kotwicki, S., Morzaria-Luna, H.N., Ainsworth, C.H., Thompson, K.A., 2020c. Spatio-temporal analyses of marine predator diets from data-rich and data-limited systems. Fish Fish. 21, 718–739.

  20. Grüss, A., Thorson, J.T., Sagarese, S.R., Babcock, E.A., Karnauskas, M., Walter, J.F., Drexler, M., 2017. Ontogenetic spatial distributions of red grouper (Epinephelus morio) and gag grouper (Mycteroperca microlepis) in the U.S. Gulf of Mexico. Fish. Res. 193, 129–142.

  21. Grüss, A., Thorson, J.T., Stawitz, C.C., Reum, J.C.P., Rohan, S.K., Barnes, C.L., 2021. Synthesis of interannual variability in spatial demographic processes supports the strong influence of cold-pool extent on eastern Bering Sea walleye pollock (Gadus chalcogrammus). Prog. Oceanogr. 194, 102569.

  22. Grüss, A., Walter, J.F., Babcock, E.A., Forrestal, F.C., Thorson, J.T., Lauretta, M.V., 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.

  23. Guan, L., Jin, X., Wu, Q., Shan, X., 2019. Statistical modelling for exploring diel vertical movements and spatial correlations of marine fish species: a supplementary tool to assess species interactions. ICES J. Mar. Sci. 76, 1776–1783.

  24. Guan, L., Shan, X., Jin, X., Gorfine, H., Yang, T., Li, Z., 2020. Evaluating spatio-temporal dynamics of multiple fisheries-targeted populations simultaneously: A case study of the Bohai Sea ecosystem in China. Ecol. Model. 422, 108987.

  25. Han, Q., Grüss, A., Shan, X., Jin, X., Thorson, J.T., 2021. Understanding patterns of distribution shifts and range expansion/contraction for small yellow croaker (Larimichthys polyactis) in the Yellow Sea. Fish. Oceanogr. 30, 69–84.

  26. Hodgdon, C.T., Tanaka, K.R., Runnebaum, J., Cao, J., Chen, Y., 2020. A framework to incorporate environmental effects into stock assessments informed by fishery-independent surveys: a case study with American lobster (Homarus americanus). Can. J. Fish. Aquat. Sci. 1–11.

  27. Hovel, R.A., Thorson, J.T., Carter, J.L., Quinn, T.P., 2017. Within-lake habitat heterogeneity mediates community response to warming trends. Ecology 98, 2333–2342.

  28. Hsu, J., Chang, Y.-J., Kitakado, T., Kai, M., Li, B., Hashimoto, M., Hsieh, C., Kulik, V., Park, K.J., 2021. Evaluating the spatiotemporal dynamics of Pacific saury in the Northwestern Pacific Ocean by using a geostatistical modelling approach. Fish. Res. 235, 105821.

  29. Johnson, K.F., Thorson, J.T., Punt, A.E., 2019. Investigating the value of including depth during spatiotemporal index standardization. Fish. Res. 216, 126–137.

  30. 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.

  31. Kanamori, Y., Nishijima, S., Okamura, H., Yukami, R., Watai, M., Takasuka, A., 2021. Spatio-temporal model reduces species misidentification bias of spawning eggs in stock assessment of spotted mackerel in the western North Pacific. Fish. Res. 236, 105825.

  32. Kanamori, Y., Takasuka, A., Nishijima, S., Okamura, H., 2019. Climate change shifts the spawning ground northward and extends the spawning period of chub mackerel in the western North Pacific. Mar. Ecol. Prog. Ser. 624, 155–166.

  33. Lowman, B.A., Jones, A.W., Pessutti, J.P., Mercer, A.M., Manderson, J.P., Galuardi, B., 2021. Northern Shortfin Squid (Illex illecebrosus) Fishery Footprint on the Northeast US Continental Shelf. Front. Mar. Sci. 8.

  34. Marshall, K.N., Duffy-Anderson, J.T., Ward, E.J., Anderson, S.C., Hunsicker, M.E., Williams, B.C., 2019. Long-term trends in ichthyoplankton assemblage structure, biodiversity, and synchrony in the Gulf of Alaska and their relationships to climate. Prog. Oceanogr. 170, 134–145.

  35. Maureaud, A.A., Frelat, R., Pécuchet, L., Shackell, N., Mérigot, B., Pinsky, M.L., Amador, K., Anderson, S.C., Arkhipkin, A., Auber, A., Barri, I., Bell, R.J., Belmaker, J., Beukhof, E., Camara, M.L., Guevara‐Carrasco, R., Choi, J., Christensen, H.T., Conner, J., Cubillos, L.A., Diadhiou, H.D., Edelist, D., Emblemsvåg, M., Ernst, B., Fairweather, T.P., Fock, H.O., Friedland, K.D., Garcia, C.B., Gascuel, D., Gislason, H., Goren, M., Guitton, J., Jouffre, D., Hattab, T., Hidalgo, M., Kathena, J.N., Knuckey, I., Kidé, S.O., Koen‐Alonso, M., Koopman, M., Kulik, V., León, J.P., Levitt‐Barmats, Y., Lindegren, M., Llope, M., Massiot‐Granier, F., Masski, H., McLean, M., Meissa, B., Mérillet, L., Mihneva, V., Nunoo, F.K.E., O’Driscoll, R., O’Leary, C.A., Petrova, E., Ramos, J.E., Refes, W., Román‐Marcote, E., Siegstad, H., Sobrino, I., Sólmundsson, J., Sonin, O., Spies, I., Steingrund, P., Stephenson, F., Stern, N., Tserkova, F., Tserpes, G., Tzanatos, E., Rijn, I. van, Zwieten, P.A.M. van, Vasilakopoulos, P., Yepsen, D.V., Ziegler, P., Thorson, J.T., 2021. Are we ready to track climate-driven shifts in marine species across international boundaries? - A global survey of scientific bottom trawl data. Glob. Change Biol. 27, 220–236.

  36. McClatchie, S., Gao, J., Drenkard, E.J., Thompson, A.R., Watson, W., Ciannelli, L., Bograd, S.J., Thorson, J.T., 2018. Interannual and Secular Variability of Larvae of Mesopelagic and Forage Fishes in the Southern California Current System. J. Geophys. Res. Oceans 123, 6277–6295.

  37. McGowan, D., Horne, J., Rogers, L., 2019. Effects of temperature on the distribution and density of capelin in the Gulf of Alaska. Mar. Ecol. Prog. Ser.

  38. McGowan, D.W., Horne, J.K., Thorson, J.T., Zimmermann, M., 2019. Influence of environmental factors on capelin distributions in the Gulf of Alaska. Deep Sea Res. Part II Top. Stud. Oceanogr., Understanding Ecosystem Processes in the Gulf of Alaska: Volume 2 165, 238–254.

  39. Monnahan, C.C., Thorson, J.T., Kotwicki, S., Lauffenburger, N., Ianelli, J.N., Punt, A.E., 2021. Incorporating vertical distribution in index standardization accounts for spatiotemporal availability to acoustic and bottom trawl gear for semi-pelagic species. ICES J. Mar. Sci.

  40. 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. 221, 105381.

  41. Ng, E.L., Deroba, J.J., Essington, T.E., Grüss, A., Smith, B.E., Thorson, J.T., 2021. Predator stomach contents can provide accurate indices of prey biomass. ICES J. Mar. Sci.

  42. O’Leary, C.A., Thorson, J.T., Ianelli, J.N., Kotwicki, S., 2020. Adapting to climate-driven distribution shifts using model-based indices and age composition from multiple surveys in the walleye pollock (Gadus chalcogrammus) stock assessment. Fish. Oceanogr. 29, 541–557.

  43. Oyafuso, Z.S., Barnett, L.A.K., Kotwicki, S., 2021. Incorporating spatiotemporal variability in multispecies survey design optimization addresses trade-offs in uncertainty. ICES J. Mar. Sci.

  44. 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.

  45. Robertson, M.D., Gao, J., Regular, P.M., Morgan, M.J., Zhang, F., 2021. Lagged recovery of fish spatial distributions following a cold-water perturbation. Sci. Rep. 11, 9513.

  46. Runnebaum, J., Guan, L., Cao, J., O’Brien, L., Chen, Y., 2017. Habitat suitability modeling based on a spatiotemporal model: an example for cusk in the Gulf of Maine. Can. J. Fish. Aquat. Sci. 75, 1784–1797.

  47. Satoh, K., Xu, H., Minte-Vera, C.V., Maunder, M.N., Kitakado, T., 2021. Size-specific spatiotemporal dynamics of bigeye tuna (Thunnus obesus) caught by the longline fishery in the eastern Pacific Ocean. Fish. Res. 243, 106065.

  48. Sculley, M.L., Brodziak, J., 2020. Quantifying the distribution of swordfish (Xiphias gladius) density in the Hawaii-based longline fishery. Fish. Res. 230, 105638.

  49. Selden, R.L., Thorson, J.T., Samhouri, J.F., Bograd, S.J., Brodie, S., Carroll, G., Haltuch, M.A., Hazen, E.L., Holsman, K.K., Pinsky, M.L., Tolimieri, N., Willis-Norton, E., 2020. Coupled changes in biomass and distribution drive trends in availability of fish stocks to US West Coast ports. ICES J. Mar. Sci. 77, 188–199.

  50. Smart, T.I., Bubley, W.J., Glasgow, D.M., Reichert, M.J.M., 2020. Spatial Distribution Changes and Habitat Use in Red Porgy in Waters off the Southeast U.S. Atlantic Coast. Mar. Coast. Fish. 12, 381–394.

  51. Thorson, J.T., 2019a. Guidance for decisions using the Vector Autoregressive Spatio-Temporal (VAST) package in stock, ecosystem, habitat and climate assessments. Fish. Res. 210, 143–161.

  52. Thorson, J.T., 2019b. Measuring the impact of oceanographic indices on species distribution shifts: The spatially varying effect of cold-pool extent in the eastern Bering Sea. Limnol. Oceanogr. 64, 2632–2645.

  53. Thorson, J.T., 2018. Three problems with the conventional delta-model for biomass sampling data, and a computationally efficient alternative. Can. J. Fish. Aquat. Sci. 75, 1369–1382.

  54. Thorson, J.T., 2015. Spatio-temporal variation in fish condition is not consistently explained by density, temperature, or season for California Current groundfishes. Mar. Ecol. Prog. Ser. 526, 101–112.

  55. Thorson, James T, Adams, C.F., Brooks, E.N., Eisner, L.B., Kimmel, D.G., Legault, C.M., Rogers, L.A., Yasumiishi, E.M., 2020. Seasonal and interannual variation in spatio-temporal models for index standardization and phenology studies. ICES J. Mar. Sci. 77, 1879–1892.

  56. Thorson, J.T., Adams, G., Holsman, K., 2019. Spatio-temporal models of intermediate complexity for ecosystem assessments: A new tool for spatial fisheries management. Fish Fish. 20, 1083–1099.

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