Articles | Volume 5-opsr
https://doi.org/10.5194/sp-5-opsr-13-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/sp-5-opsr-13-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Numerical models for monitoring and forecasting ocean ecosystems: a short description of the present status
Simone Libralato
CORRESPONDING AUTHOR
Department of Oceanography, Istituto Nazionale di Oceanografia e di Geofisica Sperimentale – OGS, Trieste, Italy
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Cited articles
Agnetta, D., Badalamenti, F., Colloca, F., Cossarini, G., Fiorentino, F., Garofalo, G., Patti, B., Pipitone, C., Russo, T., Solidoro, C., and Libralato, S.: Interactive effects of fishing effort reduction and climate change in a central Mediterranean fishing area: Insights from bio-economic indices derived from a dynamic food-web model, Front. Mar. Sci., 8, 909164, https://doi.org/10.3389/fmars.2022.909164, 2022.
Anderson, S. C., Monnahan, C. C., Johnson, K. F., Ono, K., and Valero, J. L.: ss3sim: an R package for fisheries stock assessment simulation with Stock Synthesis, PLoS One, 9, e92725, https://doi.org/10.1371/journal.pone.0092725, 2014.
Andonegi, E., Fernandes, J. A., Quincoces, I., Irigoien, X., Uriarte, A., Pérez, A., Howell, D., and Stefánsson, G.: The potential use of a Gadget model to predict stock responses to climate change in combination with Bayesian networks: the case of Bay of Biscay anchovy, ICES J. Marine Science, 68, 1257–1269, https://doi.org/10.1093/icesjms/fsr087, 2011.
Blanchard, J. L., Jennings, S., Law, R., Castle, M. D., McCloghrie, P., Rochet, M. J., and Benoît, E.: How does abundance scale with body size in coupled size-structured food webs?, J. Anim. Ecol., 78, 270–280, https://doi.org/10.1111/j.1365-2656.2008.01466.x, 2009.
Bocci, M., Coffaro, G., and Bendoricchio, G.: Modelling biomass and nutrient dynamics in eelgrass (Zostera marina L.): applications to the Lagoon of Venice (Italy) and Øresund (Denmark), Ecol. Model., 102, 67–80, https://doi.org/10.1016/S0304-3800(97)00095-1, 1997.
Brodie, S. J., Thorson, J. T., Carroll, G., Hazen, E. L., Bograd, S., Haltuch, M. A., Holsman, K. K., Kotwicki, S., Samhouri, J. F., Willis-Norton, E., and Selden, R. L.: Trade-offs in covariate selection for species distribution models: a methodological comparison, Ecography, 43, 11–24, https://doi.org/10.1111/ecog.04707, 2020.
Butenschön, M., Clark, J., Aldridge, J. N., Allen, J. I., Artioli, Y., Blackford, J., Bruggeman, J., Cazenave, P., Ciavatta, S., Kay, S., Lessin, G., van Leeuwen, S., van der Molen, J., de Mora, L., Polimene, L., Sailley, S., Stephens, N., and Torres, R.: ERSEM 15.06: a generic model for marine biogeochemistry and the ecosystem dynamics of the lower trophic levels, Geosci. Model Dev., 9, 1293–1339, https://doi.org/10.5194/gmd-9-1293-2016, 2016.
Catucci, E., Panzeri, D., Libralato, S., Cossarini, G., Garofalo, G., Maina, I., Kavadas, S., Quattrocchi, F., Cipriano, G., Carlucci, R., and Vitale, S.: Modeling the spatial distribution and abundance of deep-water red shrimps in the Mediterranean Sea: a machine learning approach, Fish. Res., 281, 107257, https://doi.org/10.1016/j.fishres.2024.107257, 2025.
Cheung, W. W., Lam, V. W., Sarmiento, J. L., Kearney, K., Watson, R., and Pauly, D.: Projecting global marine biodiversity impacts under climate change scenarios, Fish Fish., 10, 235–251, https://doi.org/10.1111/j.1467-2979.2008.00315.x, 2009.
Cheung, W. W., Sarmiento, J. L., Dunne, J., Frölicher, T. L., Lam, V. W., Deng Palomares, M. L., Watson, R., and Pauly, D.: Shrinking of fishes exacerbates impacts of global ocean changes on marine ecosystems, Nat. Clim. Change, 3, 254–258, https://doi.org/10.1038/nclimate1691, 2013.
Christensen, V. and Pauly, D.: ECOPATH II – a software for balancing steady-state ecosystem models and calculating network characteristics, Ecol. Model., 61, 169–185, https://doi.org/10.1016/0304-3800(92)90016-8, 1992.
Christensen, V. and Walters, C.J.: Ecopath with Ecosim: methods, capabilities and limitations, Ecol. Model., 172, 109–139, https://doi.org/10.1016/j.ecolmodel.2003.09.003, 2004.
Colloca, F., Garofalo, G., Bitetto, I., Facchini, M. T., Grati, F., Martiradonna, A., Mastrantonio, G., Nikolioudakis, N., Ordinas, F., Scarcella, G., Tserpes, G., Tugores, M. P., Valavanis, V., Carlucci, R., Fiorentino, F., Follesa, M. C., Iglesias, M., Knittweis, L., Lefkaditou, E., Lembo, G., Manfredi, C., Massuti, E., Pace, M. L., Papadopoulou, N., Sartor, P., Smith, C. J., and Spedicato, M. T.: The seascape of demersal fish nursery areas in the North Mediterranean Sea, a first step towards the implementation of spatial planning for trawl fisheries, PLoS ONE, 10, e0119590, https://doi.org/10.1371/journal.pone.0119590, 2015.
Cowen, R. K. and Sponaugle, S.: Larval dispersal and marine population connectivity, Annu. Rev. Mar. Sci., 1, 443–466, https://doi.org/10.1146/annurev.marine.010908.163757, 2009.
Cowen, R. K., Gawarkiewicz, G., Pineda, J., Thorrold, S. R., and Werner, F. E.: Population connectivity in marine systems an overview, Oceanography, 20, 14–21, https://doi.org/10.5670/oceanog.2007.26, 2007.
deYoung, B., Heath, M. R., Werner, F., Chai, F., Megrey, B. A., and Monfray, P.: Challenges of modelling ocean basin ecosystems, Science, 304, 1463–1466, https://doi.org/10.1126/science.1094858, 2004.
Dolder, P. J., Thorson, J. T., and Minto, C.: Spatial separation of catches in highly mixed fisheries, Scientific Reports, 8, 13886, https://doi.org/10.1038/s41598-018-31881-w, 2018.
Elith, J. and Leathwick, J. R.: Species distribution models: ecological explanation and prediction across space and time. Annual review of ecology, evolution, and systematics, Annual Reviews, 40, 677–697, https://doi.org/10.1146/annurev.ecolsys.110308.120159, 2009.
Fennel, K., Mattern, J. P., Doney, S. C., Bopp, L., Moore, A. M., Wang, B., and Yu, L.: Ocean biogeochemical modelling, Nature Reviews Methods Primers, 2, 76, https://doi.org/10.1038/s43586-022-00154-2, 2022.
Faugeras, B. and Maury, O.: An advection-diffusion-reaction size-structured fish population dynamics model combined with a statistical parameter estimation procedure: application to the Indian Ocean skipjack tuna fishery, Math. Biosci. Eng., 2, 719–741, https://doi.org/10.3934/mbe.2005.2.719, 2005.
Froese, R., Winker, H., Coro, G., Palomares, M. L., Tsikliras, A. C., Dimarchopoulou, D., Touloumis, K., Demirel, N., Vianna, G., Scarcella, G., and Schijns, R.: New developments in the analysis of catch time series as the basis for fish stock assessments: The CMSY method, Acta Ichthyol. Piscat., 53, 173–189, https://doi.org/10.3897/aiep.53.105910, 2023.
Fulton, E. A., Link, J. S., Kaplan, I. C., Savina-Rolland, M., Johnson, P., Ainsworth, C., Horne, P., Gorton, R., Gamble, R. J., Smith, A. D., and Smith, D. C.: Lessons in modelling and management of marine ecosystems: the Atlantis experience, Fish Fish., 12, 171–188, https://doi.org/10.1111/j.1467-2979.2011.00412.x, 2011.
Gasche, L. and Gascuel, D.: EcoTroph: a simple model to assess fishery interactions and their impacts on ecosystems, ICES J. Mar. Sci., 70, 498–510, https://doi.org/10.1093/icesjms/fst016, 2013.
Gawarkiewicz, G., Monismith, S., and Largier, J.: Observing larval transport processes affecting population connectivity: progress and challenges, Oceanography, 20, 40–53, https://doi.org/10.5670/oceanog.2007.28, 2007.
Gislason, H.: Single and multispecies reference points for Baltic fish stocks, ICES J. Mar. Sci., 56, 571–583, https://doi.org/10.1006/jmsc.1999.0492, 1999.
Grüss, A., Drexler, M., and Ainsworth, C. H.: Using delta generalized additive models to produce distribution maps for spatially explicit ecosystem models, Fish. Res., 159, 11–24, https://doi.org/10.1016/j.fishres.2014.05.005, 2014.
Heymans, J. J., Coll, M., Libralato, S., Morissette, L., and Christensen, V.: Global patterns in ecological indicators of marine food webs: a modelling approach, PLoS One, 9, e95845, https://doi.org/10.1371/journal.pone.0095845, 2014.
Hilborn, R. and Walters, C. J. (Eds.): Quantitative fisheries stock assessment: choice, dynamics and uncertainty, Springer Science & Business Media, https://doi.org/10.1007/978-1-4615-3598-0, 2013.
Hollowed, A. B., Barange, M., Beamish, R. J., Brander, K., Cochrane, K., Drinkwater, K., Foreman, M. G., Hare, J. A., Holt, J., Ito, S. I., and Kim, S.: Projected impacts of climate change on marine fish and fisheries, ICES J. Mar. Sci., 70, 1023–1037, https://doi.org/10.1093/icesjms/fst081, 2013.
Hollowed, A. B., Bax, N., Beamish, R., Collie, J., Fogarty, M., Livingston, P., Pope, J., and Rice, J. C.: Are multispecies models an improvement on single-species models for measuring fishing impacts on marine ecosystems?, ICES J. Mar. Sci., 57, 707–719, https://doi.org/10.1006/jmsc.2000.0734, 2000.
Itoh, S., Takeshige, A., Kasai, A., and Kimura, S.: Modeling the coastal ecosystem complex: present situation and challenges, Fisheries Sci., 84, 293–307, https://doi.org/10.1007/s12562-018-1181-x, 2018.
Jardim, E., Millar, C. P., Mosqueira, I., Scott, F., Osio, G. C., Ferretti, M., Alzorriz, N., and Orio, A.: What if stock assessment is as simple as a linear model? The a4a initiative, ICES J. Marine Science, 72, 232–236, https://doi.org/10.1093/icesjms/fsu050, 2014.
Jones, M. C., Dye, S. R., Pinnegar, J. K., Warren, R., and Cheung, W. W.: Modelling commercial fish distributions: Prediction and assessment using different approaches, Ecol. Modell., 225, 133–145, https://doi.org/10.1016/j.ecolmodel.2011.11.003, 2012.
Kooijman, S. A. L. M.: The standard dynamic energy budget model has no plausible alternatives, Ecol. Model., 428, 109106, https://doi.org/10.1016/j.ecolmodel.2020.109106, 2020.
Kooijman, S. A. L. M.: Dynamic energy budget theory for metabolic organisation, Cambridge University Press, ISBN 978-0-521-13191-9, 2010.
Laurent, C., Querin, S., Solidoro, C., and Melaku Canu, D.: Modelling marine particle dynamics with LTRANS-Zlev: Implementation and validation, Environ. Modell. Softw., 125, 104621, https://doi.org/10.1016/j.envsoft.2020.104621, 2020.
Lehodey, P., Chai, F., and Hampton, J.: Modelling climate-related variability of tuna populations from a coupled ocean–biogeochemical-populations dynamics model, Fish. Oceanogr., 12, 483–494, https://doi.org/10.1046/j.1365-2419.2003.00244.x, 2003.
Lehodey, P., Senina, I., Nicol, S., and Hampton, J.: Modelling the impact of climate change on South Pacific albacore tuna, Deep-Sea Res. Pt. II, 113, 246–259, https://doi.org/10.1016/j.dsr2.2014.10.028, 2015.
Lett, C., Verley, P., Mullon, C., Parada, C., Brochier, T., Penven, P., and Blanke, B.: A Lagrangian tool for modelling ichthyoplankton dynamics, Environ. Modell. Softw., 23, 1210–1214, https://doi.org/10.1016/j.envsoft.2008.02.005, 2008.
Libralato, S. and Solidoro, C.: Bridging biogeochemical and food web models for an End-to-End representation of marine ecosystem dynamics: The Venice lagoon case study, Ecol. Model., 220, 2960–2971, https://doi.org/10.1016/j.ecolmodel.2009.08.017, 2009.
Libralato, S., Caccin, A., and Pranovi, F.: Modeling species invasions using thermal and trophic niche dynamics under climate change, Front. Mar. Sci., 2, 29, https://doi.org/10.3389/fmars.2015.00029, 2015.
Maravelias, C. D., Haralabous, J., and Papaconstantinou, C.: Predicting demersal fish species distributions in the Mediterranean Sea using artificial neural networks, Mar. Ecol. Prog. Ser., 255, 249–258, https://doi.org/10.3354/meps255249, 2003.
Maunder, M. N. and Punt, A. E.: A review of integrated analysis in fisheries stock assessment, Fish. Res., 142, 61–74, https://doi.org/10.1016/j.fishres.2012.07.025, 2013.
Maury, O.: An overview of APECOSM, a spatialized mass balanced “Apex Predators ECOSystem Model” to study physiologically structured tuna population dynamics in their ecosystem, Prog. Oceanogr., 84, 113–117, https://doi.org/10.1016/j.pocean.2009.09.013, 2010.
Melaku Canu, D., Laurent, C., Morello, E. B., Querin, S., Scarcella, G., Vrgoc, N., Froglia, C., Angelini, S., and Solidoro, C.: Nephrops norvegicus in the Adriatic Sea: Connectivity modeling, essential fish habitats, and management area network, Fish. Oceanogr., 30, 349–365, https://doi.org/10.1111/fog.12522, 2021.
Melo-Merino, S. M., Reyes-Bonilla, H., and Lira-Noriega, A.: Ecological niche models and species distribution models in marine environments: A literature review and spatial analysis of evidence, Ecol. Modell., 415, 108837, https://doi.org/10.1016/j.ecolmodel.2019.108837, 2020.
Methot, R. D. and Wetzel, C. R.: Stock Synthesis: a biological and statistical framework for fish stock assessment and fishery management, Fish. Res., 142, 86–99, https://doi.org/10.1016/j.fishres.2012.10.012, 2013.
Morello, E. B., Plagányi, É. E., Babcock, R. C., Sweatman, H., Hillary, R., and Punt, A. E.: Model to manage and reduce crown-of-thorns starfish outbreaks, Mar. Ecol. Prog. Ser., 512, 167–183, https://doi.org/10.3354/meps10858, 2014.
Nielsen, J. R., Thunberg, E., Holland, D. S., Schmidt, J. O., Fulton, E. A., Bastardie, F., Punt, A. E., Allen, I., Bartelings, H., Bertignac, M., and Bethke, E.: Integrated ecological–economic fisheries models–Evaluation, review and challenges for implementation, Fish Fish., 19, 1–29, https://doi.org/10.1111/faf.12232, 2018.
Nisbet, R. M., Jusup, M., Klanjscek, T., and Pecquerie, L.: Integrating dynamic energy budget (DEB) theory with traditional bioenergetic models, J. Exp. Biol., 215, 892–902, https://doi.org/10.1242/jeb.059675, 2012.
North, E. W., Schlag, Z., Hood, R. R., Li, M., Zhong, L., Gross, T., and Kennedy, V. S.: Vertical swimming behavior influences the dispersal of simulated oyster larvae in a coupled particle-tracking and hydrodynamic model of Chesapeake Bay, Mar. Ecol. Prog. Ser., 359, 99–116, https://doi.org/10.3354/meps07317, 2008.
Panzeri, D., Bitetto, I., Carlucci, R., Cipriano, G., Cossarini, G., D'Andrea, L., Masnadi, F., Querin, S., Reale, M., Russo, T., Scarcella, G., Spedicato, M. T., Teruzzi, A., Vrgoč, N., Zupa, W., and Libralato, S.: Developing spatial distribution models for demersal species by the integration of trawl surveys data and relevant ocean variables, in: Copernicus Marine Service Ocean State Report, J. Oper. Oceanogr., 14, s114–s123, https://doi.org/10.1080/1755876X.2021.1946240, 2021.
Panzeri, D., Russo, T., Arneri, E., Carlucci, R., Cossarini, G., Isajlović, I., Krstulović Šifner, S., Manfredi, C., Masnadi, F., Reale, M., Scarcella, G.,Solidoro C., Spedicato M.T., Vrgoč N., Zupa, W., and Libralato, S.: Identifying priority areas for spatial management of mixed fisheries using ensemb le of multi-species distribution models, Fish Fish., 25, 187–204, https://doi.org/10.1111/faf.12802, 2024.
Paris, C. B., Helgers, J., Van Sebille, E., and Srinivasan, A.: Connectivity Modeling System: A probabilistic modeling tool for the multi-scale tracking of biotic and abiotic variability in the ocean, Environ. Modell. Softw., 42, 47–54, https://doi.org/10.1016/j.envsoft.2012.12.006, 2013.
Pastres, R., Pranovi, F., Libralato, S., Malavasi, S., and Torricelli, P.: “Birthday effect” on the adoption of alternative mating tactics in Zosterisessor ophiocephalus: evidence from a growth model, J. Mar. Biol. Assoc. UK, 82, 333–337, https://doi.org/10.1017/S0025315402005520, 2002.
Pedersen, M. W. and Berg, C. W.: A stochastic surplus production model in continuous time, Fish Fish., 18, 226–243, https://doi.org/10.1111/faf.12174, 2017.
Piroddi, C., Akoglu, E., Andonegi, E., Bentley, J. W., Celić, I., Coll, M., Dimarchopoulou, D., Friedland, R., de Mutsert, K., Girardin, R., Garcia-Gorriz, E., Grizzetti, B., Hernvann, P.-Y., Heymans, J. J., Müller-Karulis, B., Libralato, S., Lynam, C. P., Macias, D., Miladinova, S., Moullec, F., Palialexis, A., Parn, O., Serpetti, N., Solidoro, C., Steenbeek, J., Stips, A., Tomczak, M. T., Travers-Trolet, M., and Tsikliras, A. C.: Effects of nutrient management scenarios on marine food webs: a Pan-European Assessment in support of the Marine Strategy Framework Directive, Front. Mar. Sci., 8, 596797, https://doi.org/10.3389/fmars.2021.596797, 2021.
Pirotta, E., Booth, C. G., Calambokidis, J., Costa, D. P., Fahlbusch, J. A., Friedlaender, A. S., Goldbogen, J. A., Harwood, J., Hazen, E. L., New, L., and Santora, J. A.: From individual responses to population effects: Integrating a decade of multidisciplinary research on blue whales and sonar, Animal Conservation, 25, 796–810, https://doi.org/10.1111/acv.12785, 2022.
Pittman, S. J. and Brown, K. A.: Multi-scale approach for predicting fish species distributions across coral reef seascapes, PLoS One, 6, e20583, https://doi.org/10.1371/journal.pone.0020583, 2011.
Plagányi, É. E.: Models for an ecosystem approach to fisheries, FAO Fisheries Technical Paper, 477, 1–108, https://www.fao.org/4/a1149e/a1149e.pdf (last access: 28 July 2024), 2007.
Plagányi, É. E., Punt, A. E., Hillary, R., Morello, E. B., Thébaud, O., Hutton, T., Pillans, R. D., Thorson, J. T., Fulton, E. A., Smith, A. D., and Smith, F.: Multispecies fisheries management and conservation: tactical applications using models of intermediate complexity, Fish Fish., 15, 1–22, https://doi.org/10.1111/j.1467-2979.2012.00488.x, 2014.
Pollock, L. J., Tingley, R., Morris, W. K., Golding, N., O'Hara, R. B., Parris, K. M., Vesk, P. A., and McCarthy, M. A.: Understanding co-occurrence by modelling species simultaneously with a Joint Species Distribution Model (JSDM), Methods Ecol. Evol., 5, 397–406, https://doi.org/10.1111/2041-210X.12180, 2014.
Privitera-Johnson, K. M., Methot, R. D., and Punt, A. E.: Towards best practice for specifying selectivity in age-structured integrated stock assessments, Fish. Res., 249, 106247, https://doi.org/10.1016/j.fishres.2022.106247, 2022.
Punt, A. E.: Spatial stock assessment methods: a viewpoint on current issues and assumptions, Fish. Res., 213, 132–143, https://doi.org/10.1016/j.fishres.2019.01.014, 2019.
Reiss, H., Cunze, S., König, K., Neumann, H., and Kröncke, I.: Species distribution modelling of marine benthos: a North Sea case study, Mar. Ecol. Prog. Ser., 442, 71–86, https://doi.org/10.3354/meps09391, 2011.
Rose, K. A., Fiechter, J., Curchitser, E. N., Hedstrom, K., Bernal, M., Creekmore, S., Haynie, A., Ito, S. I., Lluch-Cota, S., Megrey, B. A. and Edwards, C. A.: Demonstration of a fully-coupled end-to-end model for small pelagic fish using sardine and anchovy in the California Current, Prog. Oceanogr., 138, 348–380, https://doi.org/10.1016/j.pocean.2015.01.012 2015.
Rose, K. A., Holsman, K., Nye, J. A., Markowitz, E. H., Banha, T. N., Bueno-Pardo, J., Deslauriers, D., Fulton, E. A., Huebert, K. B., Huret, M., and Ito, S. I.: Advancing bioenergetics-based modeling to improve climate change projections of marine ecosystems, Mar. Ecol. Prog. Ser., 732, 193–221, https://doi.org/10.3354/meps14535, 2024.
Senina, I., Lehodey, P., Sibert, J., and Hampton, J.: Integrating tagging and fisheries data into a spatial population dynamics model to improve its predictive skills, Can. J. Fish. Aquat. Sci., 77, 576–593, https://doi.org/10.1139/cjfas-2018-0470, 2020.
Serpetti, N., Baudron, A. R., Burrows, M. T., Payne, B. L., Helaouet, P., Fernandes, P. G., and Heymans, J. J.: Impact of ocean warming on sustainable fisheries management informs the Ecosystem Approach to Fisheries, Scientific Reports, 7, 13438, https://doi.org/10.1038/s41598-017-13220-7, 2017.
Shin, Y. J. and Cury, P.: Using an individual-based model of fish assemblages to study the response of size spectra to changes in fishing, Can. J. Fish. Aquat. Sci., 61, 414–431, https://doi.org/10.1139/f03-154, 2004.
Sibert, J. R., Hampton, J., Fournier, D. A., and Bills, P. J.: An advection–diffusion–reaction model for the estimation of fish movement parameters from tagging data, with application to skipjack tuna (Katsuwonus pelamis), Can. J. Fish. Aquat. Sci., 56, 925–938, https://doi.org/10.1139/f99-017, 1999.
Steenbeek, J., Coll, M., Gurney, L., Mélin, F., Hoepffner, N., Buszowski, J., and Christensen, V.: Bridging the gap between ecosystem modeling tools and geographic information systems: Driving a food web model with external spatial–temporal data, Ecol. Modell., 263, 139–151, https://doi.org/10.1016/j.ecolmodel.2013.04.027, 2013.
Steenbeek, J., Buszowski, J., Christensen, V., Akoglu, E., Aydin, K., Ellis, N., Felinto, D., Guitton, J., Lucey, S., Kearney, K., and Mackinson, S.: Ecopath with Ecosim as a model-building toolbox: source code capabilities, extensions, and variations, Ecol. Modell., 319, 178–189, https://doi.org/10.1016/j.ecolmodel.2015.06.031, 2016.
Stock, C. A., Alexander, M. A., Bond, N. A., Brander, K. M., Cheung, W. W., Curchitser, E. N., Delworth, T. L., Dunne, J. P., Griffies, S. M., Haltuch, M. A., and Hare, J. A.: On the use of IPCC-class models to assess the impact of climate on living marine resources, Prog. Oceanogr., 88, 1–27, https://doi.org/10.1016/j.pocean.2010.09.001, 2011.
Thorson, J. T., Shelton, A. O., Ward, E. J., and Skaug, H. J.: Geostatistical delta-generalized linear mixed models improve precision for estimated abundance indices for West Coast groundfishes, ICES J. Mar. Sci., 72, 1297–1310, https://doi.org/10.1093/icesjms/fsu243, 2015.
Thorson, J. T., Ianelli, J. N., Larsen, E. A., Ries, L., Scheuerell, M. D., Szuwalski, C., and Zipkin, E. F.: Joint dynamic species distribution models: a tool for community ordination and spatio-temporal monitoring, Global Ecol. Biogeogr., 25, 1144–1158, https://doi.org/10.1111/geb.12464, 2016.
Tittensor, D. P., Novaglio, C., Harrison, C. S., Heneghan, R. F., Barrier, N., Bianchi, D., Bopp, L., Bryndum-Buchholz, A., Britten, G. L., Büchner, M., and Cheung, W. W.: Next-generation ensemble projections reveal higher climate risks for marine ecosystems, Nat. Clim. Change, 11, 973–981, https://doi.org/10.1038/s41558-021-01173-9, 2021.
Travers, M., Watermeyer, K., Shannon, L. J., and Shin, Y. J.: Changes in food web structure under scenarios of overfishing in the southern Benguela: comparison of the Ecosim and OSMOSE modelling approaches, J. Marine Syst., 79, 101–111, https://doi.org/10.1016/j.jmarsys.2009.07.005, 2010.
Walters, C., Pauly, D., and Christensen, V.: Ecospace: prediction of mesoscale spatial patterns in trophic relationships of exploited ecosystems, with emphasis on the impacts of marine protected areas, Ecosystems, 2, 539–554, https://doi.org/10.1007/s100219900101, 1999.
Walters, C., Pauly, D., Christensen, V., and Kitchell, J. F.: Representing density dependent consequences of life history strategies in aquatic ecosystems: EcoSim II, Ecosystems, 3, 70–83, https://doi.org/10.1007/s100210000011, 2000.
Short summary
This work examines the current classification of numerical models of increasing complexity – from individuals and population and stock assessment models to models representing the whole ecosystem by covering all trophic levels – and presents examples and their operational maturity, finally demonstrating their use for supporting marine resource management, conservation, planning, and mitigation actions.
This work examines the current classification of numerical models of increasing complexity –...
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