Projecting changes in the distribution and productivity of living marine resources: A critical review of the suite of modelling approaches used in the large European project VECTORS

Estuarine, Coastal and Shelf Science

Volumn 201, Issue , 2018, Pages 40-55

  Peck, Myron A ^a   Arvanitidis, Christos ^b   Butenschön, Momme ^c   Canu, Donata Melaku ^d   Chatzinikolaou, Eva ^b   Cucco, Andrea ^e   Domenici, Paolo ^e   Fernandes, Jose A ^c   Gasche, Loic ^f   Huebert, Klaus B ^a,m   Hufnagl, Marc ^a   Jones, Miranda C ^g,n   Kempf, Alexander ^h   Keyl, Friedemann ^h   Maar, Marie ⁱ   Mahévas, Stéphanie ^f   Marchal, Paul ^f   Nicolas, Delphine ^j   Pinnegar, John K ^g   Rivot, Etienne ^k   Rochette, Sébastien ^f   Sell, Anne F ^h   Sinerchia, Matteo ^e   Solidoro, Cosimo ^d   Somerfield, Paul J ^c   Teal, Lorna R ^l   Travers Trolet, Morgan ^f   van de Wolfshaar, Karen E ^l   more..

^a UNIVERSITY OF HAMBURG   (Germany)

^b INSTITUTE OF OCEANOGRAPHY   (Greece)

^c PLYMOUTH MARINE LABORATORY   (United Kingdom)

^d ISTITUTO NAZIONALE DI OCEANOGRAFIA E DI GEOFISICA SPERIMENTALE OGS   (Italy)

^e Marino Costiero   (Italy)

^f IFREMER   (France)

^g CENTRE FOR ENVIRONMENT   (United Kingdom)

^h INSTITUT FÜR SEEFISCHEREI   (Germany)

ⁱ AARHUS UNIVERSITY   (Denmark)

^j THE LABORATORY   (United Kingdom)

^k AGROCAMPUS OUEST   (France)

^l WAGENINGEN UNIVERSITY   (Netherlands)

^m UNIVERSITY OF MARYLAND CENTER FOR ENVIRONMENTAL SCIENCE   (United States)

ⁿ UNIVERSITY OF BRITISH COLUMBIA   (Canada)

more..

Author keywords

Distribution; Habitat; Man induced effects; Modelling; Resources

Indexed keywords

ACIDIFICATION; ANTHROPOGENIC EFFECT; CLIMATE EFFECT; EUTROPHICATION; EXPLOITATION; HABITAT; INVASIVE SPECIES; LIVING RESOURCE; MARINE RESOURCE; MODEL; MODELING; RESOURCE ASSESSMENT; SPATIAL DISTRIBUTION; TEMPERATURE; WATER QUALITY;

EID: 84975129749     PISSN: 02727714     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ecss.2016.05.019     Document Type: Article

References (168)

1. Allen, J.I., Blackford, J.C., Holt, J., Proctor, R., Ashworth, M., Siddorn, J., A highly spatially resolved ecosystem model for the North West European Continental Shelf. Sarsia 86 (2001), 423–440.
2. Allen, J.I., Somerfield, P.J., Gilbert, F.J., Quantifying uncertainty in high-resolution coupled hydrodynamic-ecosystem models. J. Mar. Syst. 64 (2007), 3–14.
3. Altieri, A.H., Dead zones enhance key fisheries species by providing predation refuge. Ecology 89 (2008), 2808–2818.
4. Anderson, B.J., Akçakaya, H.R., Araújo, M.B., Fordham, D.A., Martinez-Meyer, E., Brook, B.W., Dynamics of range margins for metapopulations under climate change. Proc. R. Soc. B 276 (2009), 1415–1420.
5. Barange, M., Perry, R.I., Physical and ecological impacts of climate change relevant to marine and inland capture fisheries and aquaculture. Cochrane, K., De Young, C., Soto, D., Bahri, T., (eds.) Climate Change Implications for Fisheries and Aquaculture. Overview of Current Scientific Knowledge, 2009, FAO Fisheries, 7–106.
6. Bax, N., Williamson, A., Aguero, Gonzalez, E., Geeves, W., Marine invasive alien species: a threat to global biodiversity. Mar. Policy 27 (2003), 313–323.
7. Beare, D.J., Burns, F., Greig, A., Jones, E.G., Peach, K., Kienzle, M., McKenzie, E., Reid, D.G., Longterm increases in prevalence of North Sea fishes having southern biogeographic affinities. Mar. Ecol. Prog. Ser. 284 (2004), 269–278.
8. Beaugrand, G., Reid, P.C., Long-term changes in phytoplankton, zooplankton and salmon related to climate. Glob. Change Biol. 9:6 (2003), 801–817.
9. Beaugrand, G., Brander, K.M., Lindley, J.A., Souissi, S., Reid, P.C., Plankton effect on cod recruitment in the North Sea. Nature 426 (2003), 661–664.
10. Blanchard, J.L., Jennings, S., Holmes, R., Harle, J., Merino, G., Allen, J., Barange, M., Potential consequences of climate change for primary production and fish production in large marine ecosystems. Philos. Trans. R. Soc. B Biol. Sci. 367:1605 (2012), 2979–2989.
11. Blanchard, J.L., Law, R., Castle, M.D., Jennings, S., Coupled energy pathways and the resilience of size-structured food webs. Theor. Ecol. 4:3 (2011), 1–12.
12. Brodeur, R.D., Ruzicka, J.J., Steele, J.H., Investigating alternate trophic pathways through gelatinous zooplankton and planktivorous fishes in an upwelling ecosystem using end-to-end models. Omori, K., Guo, X., Yoshie, N., Fujii, N., Handoh, I.C., Isobe, A., Tanabe, S., (eds.) Interdisciplinary Studies on Environmental Chemistry—Marine Environmental Modeling & Analysis, TERRAPUB, 2011, 57–63.
13. Brown, J.H., Gillooly, J.F., Allen, A.P., Savage, V.M., West, G.B., Toward a metabolic theory of ecology. Ecology 85 (2004), 1771–1789.
14. Canu, D.M., Solidoro, C., Cossarini, G., Giorgi, F., Effect of global change on bivalve rearing activity and the need for adaptive management. Clim. Res. 42 (2010), 13–26.
15. Cheung, W.W.L., Dunne, J., Sarmiento, J.L., Pauly, D., Integrating ecophysiology and plankton dynamics into projected maximum fisheries catch potential under climate change in the Northeast Atlantic. ICES J. Mar. Sci. 68 (2011), 1008–1018.
16. Cheung, W.W.L., Lam, V.W.Y., Sarmiento, J.L., Kearney, K., Watson, R., Pauly, D., Projecting global marine biodiversity impacts under climate change scenarios. Fish. Fish. 10 (2009), 235–251.
17. Chown, S.L., Slabber, S., McGeoch, M.A., Janion, C., Leinaas, H.P., Phenotypic plasticity mediates climate change responses among invasive and indigenous arthropods. Proc. R. Acad. Sci. B 274 (2007), 2531–2537.
18. Christensen, V., Walters, C.J., Ecopath with Ecosim: methods, capabilities and limitations. Ecol. Model 172 (2004), 109–139.
19. Christensen, V., Coll, M., Steenbeek, J., Buszowski, J., Chagaris, D., Walters, C.J., Representing variable habitat quality in a spatial food web model. Ecosystems 17 (2014), 1397–1412.
20. Clark, R.A., Frid, C.L., Long-term changes in the North Sea ecosystem. Environ. Rev. 9 (2001), 131–187.
21. Cooke, S.J., Hinch, S.G., Donaldson, M.R., Clark, T.D., Eliason, E.J., Crossin, G.T., Raby, G.D., Jeffries, K.M., Lapointe, M., Miller, K., Patterson, D.A., Farrell, A.P., Conservation physiology in practice: how physiological knowledge has improved our ability to sustainably manage Pacific salmon during up-river migration. Philos. Trans. R. Soc. B 367 (2012), 1757–1769.
22. Cucco, A., Sinerchia, M., Lefrançois, C., Magni, P., Ghezzo, M., Georg Umgiesser, G., Angelo Perilli, A., Domenici, P., A metabolic scope based model of fish response to environmental changes. Ecol. Model 237/238 (2012), 132–141.
23. Daewel, U., Peck, M.A., Schrum, C., Life history strategy and impacts of environmental variability on early life stages of two marine fishes in the North Sea: an individual-based modelling approach. Can. J. Fish. Aquat. Sci. 68 (2011), 426–443.
24. Daewel, U., Peck, M.A., Schrum, C., St John, M.A., How best to include the effects of climate-driven forcing on prey fields in larval fish individual-based models. J. Plankton Res. 30 (2008), 1–5.
25. Daewel, U., Sætre Hjøllo, S., Huret, M., Ji, R., Maar, M., Niiranen, S., Travers-Trolet, M., Peck, M.A., van de Wolfshaar, K.E., Predation control off zooplankton dynamics: a review on of observations and models. ICES J. Mar. Sci. 71 (2014), 254–271.
26. Degnbol, P., The Ecosystem Approach and Fisheries Management Institutions: the Noble Art of Addressing Complexity and Uncertainty with All Onboard and on a Budget. IIFET 2002 paper. no 171, 2002.
27. Díaz, R.J., Rosenberg, R., Spreading dead zones and consequences for marine ecosystems. Science 321 (2008), 926–929.
28. Doney, S.C., The growing human footprint on coastal and open-ocean biogeochemistry., 328, 2010, 1512–1516.
29. Dulvy, N.K., Rogers, S.I., Jennings, S., Stetzenmıller, V., Dye, S.R., Skjoldal, H.R., Climate change and deepening of the North Sea fish assemblage: a biotic indicator of warming seas. J. Appl. Ecol. 45 (2008), 1029–1039.
30. Durbin, A.G., Durbin, E.G., Effects of menhaden predation on plankton populations in Narragansett Bay, Rhode Island. Estuaries 21 (1998), 449–465.
31. FAO, The State of World Fisheries and Aquaculture 2006. 2007, FAO, Fisheries and Aquaculture Department.
32. FAO, Fisheries management. 2. The ecosystem approach to fisheries. 2.1 Best practices in ecosystem modelling for informing an ecosystem approach to fisheries. FAO Fish. Tech. Guidel. Responsible Fish., 4(Suppl. 2), 2008 Add. 1.
33. Fernandes, J.A., Cheung, W.W.L., Jennings, S., Butenschön, M., de Mora, L., Frölicher, T.L., Barange, M., Grant, A., Modelling the effects of climate change on the distribution and production of marine fishes: accounting for trophic interactions in a dynamic bioclimate envelope model. Glob. Change Biol. 19:8 (2013), 2596–2607.
34. Fernandes, J.A., Lozano, J.A., Inza, I., Irigoien, X., Rodríguez, J.D., Pérez, A., Supervised pre-processing approaches in multiple class-variables classification for fish recruitment forecasting. Environ. Model. Softw. 40 (2013), 245–254.
35. Fielding, A.H., Bell, J.F., A review of methods for the assessment of prediction errors in conservation presence/absence models. Environ. Conserv. 24:1 (1997), 38–49.
36. Frank, K.T., Petrie, B., Choi, J.S., Leggett, W.C., Trophic cascades in a formerly cod-dominated ecosystem. Science 308 (2005), 1621–1623.
37. Freitas, V., Cardoso, J.F.M.F., Lika, K., Peck, M.A., Campos, J., Kooijman, S.A.L.M., van der Veer, H.W., Temperature tolerance and energetics: a dynamic energy budget-based comparison of North Atlantic marine species. Phil. Trans. R. Soc. B 365 (2011), 3553–3565.
38. Fry, F.E.J., The aquatic respiration of fish. Brown, M.E., (eds.) The Physiology of Fishes, vol. 1, 1957, Academic Press, New York, USA, 1–63.
39. Fry, F.E.J., The effect of environmental factors on the physiology of fish. Hoar, W.S., Randall, D.J., Brett, J.R., (eds.) Fish Physiology, vol. 6, 1971, Academic Press, New York, 1–98.
40. Fulton, E.A., Approaches to end-to-end ecosystem models. J. Mar. Syst. 81 (2010), 171–183.
41. Fulton, E.A., Interesting times: winners, losers, and system shifts under climate change around Australia. ICES J. Mar. Sci. 68:6 (2011), 1329–1342.
42. 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.M., Smith, D.C., Lessons in modelling and management of marine ecosystems: the Atlantis experience. Prog. Oceanogr. 12 (2011), 171–188.
43. Fulton, E.A., Smith, A.D.M., Johnson, C.R., Effect of complexity on marine ecosystem models. Mar. Ecol. Prog. Ser. 253 (2003), 1–16.
44. Gårdmark, A., Lindegren, M., Neuenfeldt, S., Blenckner, T., Heikinheimo, O., Müller-Karulis, B., Niiranen, S., Tomczak, M.T., Aro, E., Wilström, A., Möllmann, C., Biological ensemble modelling to evaluate potential futures of living marine resources. Ecol. Appl. 23 (2013), 742–754.
45. Galil, B.S., Marchini, A., Occhipinti-Ambrogi, A., Minchin, D., Naršcˇius, A., Ojaveer, H., Olenin, S., International arrivals: widespread bioinvasions in European Seas. Ethol. Ecol. Evol., 2014, 1–20, 10.1080/03949370.2014.897651.
46. Garcia, S.M., Zerbi, A., Aliaume, C., Do Chi, T., Lasserre, G., The Ecosystem Approach to Fisheries. Issues, Terminology, Principles, Institutional Foundations, Implementation and Outlook. FAO Fisheries Technical Paper. 443, 2003.
47. Gasche, L., Mahévas, S., Marchal, P., Supporting fisheries management by means of complex models: can we point out isles of robustness in a sea of uncertainty?. PLoS One, 8(10), 2013, e77566, 10.1371/journal.pone.0077566.
48. Gaston, K.J., Blackburn, T.M., A critique for macroecology. Oikos 84:3 (1999), 353–368.
49. Griffith, G.P., Fulton, E.A., Gorton, R., Richardson, A., Predicting interactions among fishing, ocean warming, and ocean acidification in a marine system with whole-ecosystem models. Conserv. Biol. 26:6 (2012), 1145–1152.
50. Guénette, S., Heymans, J.J., Christensen, V., Trites, A.W., Ecosystem models show combined effects of fishing, predation, competition, and ocean productivity on Steller sea lions (Eumetopias jubatus) in Alaska. Can. J. Fish. Aquatic Sci. 63 (2006), 2495–2517.
51. Hanson, P., Johnson, T., Kitchell, J., Schindler, D.E., Fish Bioenergetics 3.0. Report WISCU-T-97–001, 1997, University of Wisconsin Sea Grant Institute, Madison.
52. Hare, S.R., Mantua, N.J., Empirical evidence for North Pacific regime shifts in 1977 and 1989. Prog. Oceanogr. 47 (2000), 103–145.
53. Hengl, T., A Practical Guide to Geostatistical Mapping. 2009, Office for Official Publications of the European Communities, Luxembourg.
54. Herborg, L.M., Jerde, C.J., Lodge, D.M., Ruiz, G.M., MacIsaac, H.J., Predicting invasion risk using measures of introduction effort and environmental niche model. Ecol. Appl. 17 (2007), 663–674.
55. Hiddink, J.G., Burrows, M.T., Molinos, J.G., Temperature tracking by North Sea benthic invertebrates in response to climate change. Glob. Change Biol. 21 (2015), 117–129.
56. Hobbs, R.J., Higgs, E., Harris, J.A., Novel ecosystems: implications for conservation and restoration. Trends Ecol. Evol. 24 (2009), 599–605.
57. Hufnagl, M., Peck, M.A., Physiological-based modelling of larval Atlantic herring (Clupea harengus) foraging and growth: insights on climate-driven life history scheduling. ICES J. Mar. Sci. 68:6 (2011), 1170–1188.
58. Hufnagl, M., Peck, M.A., Nash, R.D.M., Dickey-Collas, M., Unravelling the Gordian knot! Key processes impacting overwintering larval survival and growth: a North Sea herring case study. Prog. Oceanogr. 138 (2015), 486–503.
59. Hulme, P.E., Roy, D.B., Cunha, T., Larsson, T.-B., A pan-European inventory of alien species: rationale, implementation and implications for managing biological invasions. DAISIE, (eds.) The Handbook of European Alien Species, 2008, Springer, Dordrecht.
60. Hunt, G.L., Stabeno, P., Walters, G., Sinclair, E., Brodeur, R.D., Napp, J.M., Bond, N.A., Climate change and control of the southeastern Bering Sea pelagic ecosystem. Deep Sea Res. II 49 (2002), 5821–5853.
61. Huntley, B., Barnard, P., Altwegg, R., Chambers, L., Coetzee, B.W.T., Gibson, L., Hockey, P.A.R., Hole, D.G., Midgley, G.F., Underhill, L.G., Willis, S.G., Beyond bioclimatic envelopes: dynamic species’ range and abundance modelling in the context of climate change. Ecography 33 (2010), 621–626.
62. Huret, M., Sourisseau, M., Petitgas, P., Struski, C., Leger, F., Lazure, P., A multidecadal hindcast of a physical-biogeochemical model and derived oceanographic indices in the Bay of Biscay. J. Mar. Syst. 109–110 (2013), S77–S94.
63. Huse, G., Ellingsen, I., Capelin migrations and climate change – a modelling analysis. Clim. Change 87 (2008), 177–197.
64. Hyder, K., Rossberg, A.G., Allen, J.I., Austen, M.C., Barciela, R.M., Bannister, H.J., Blackwell, P.G., Blanchard, J.L., Burrows, M.T., Defriez, E., Dorrington, T., Edwards, K.P., Garcia-Carreras, B., Heath, M.R., Hembury, D.J., Heymans, J.J., Holt, J., Houle, J.E., Jennings, S., Mackinson, S., Malcolm, S.L., McPike, R., Mee, L., Mills, D.K., Montgomery, C., Pearson, D., Pinnegar, J.K., Pollicino, M., Popova, E.E., Rae, L., Rogers, S.I., Speirs, D., Spence, M.A., Thorpe, R., Turner, R.K., van der Molen, J., Yool, A., Paterson, D.M., Making modelling count - increasing the contribution of shelf-seas community and ecosystem models to policy development and management. Mar. Policy 61 (2015), 291–302.
65. IPCC, Stocker, T.F., Qin, D., Plattner, G.-K.m, et al. (eds.) Climate Change 2013: the Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, 2013, Cambridge University Press, Cambridge, United Kingdom 1535 pp.
66. Jackson, D.J., Degnan, S.M., Degnan, B.M., Variation in rates of early development in Haliotis asinina generate competent larvae of different ages. Front. Zoology, 9.2, 2012 http://www.frontiersinzoology.com/content/9/1/2.
67. Jennings, S., Brander, K., Predicting the effects of climate change on marine communities and the consequences for fisheries. J. Mar. Syst. 79 (2010), 418–426.
68. Jennings, S., Me´lin, F., Blanchard, J.L., Forster, R.M., Dulvy, N.K., Wilson, R.W., Global-scale predictions of community and ecosystem properties from simple ecological theory. Proc. R. Soc. B 275 (2008), 1375–1383.
69. Jolliff, J.K., Kindle, J.C., Shulman, I., Penta, B., Friedrichs, M.A.M., Helber, R., et al. Summary diagrams for coupled hydrodynamic-ecosystem model skill assessment. J. Mar. Syst. 76 (2009), 64–82.
70. Jones, M.C., Cheung, W.W.L., Multi-model ensemble projections of climate change effects on global marine biodiversity. ICES J. Mar. Sci., 2014, 10.1093/icesjms/fsu172.
71. Jones, M.C., Dye, S.R., Fernandes, J.A., Frölicher, T.L., Pinnegar, J.K., Warren, R., Cheung, W.W.L., Predicting the impact of climate change on threatened species in UK waters. PLoS One, 8(1), 2013, e54216, 10.1371/journal.pone.0054216.
72. Jones, M.C., Dye, S.R., Pinnegar, J.K., Warren, R., Cheung, W.W.L., Modelling commercial fish distributions: prediction and assessment using different approaches. Ecol. Model. 225 (2012), 133–145.
73. Jørgensen, C., Peck, M.A., Antognarelli, F., Azzurro, E., Burrows, M.T., Cheung, W.W.L., Cucco, A., Holt, R.E., Huebert, K.B., Marras, S., McKenzie, D., Julian Metcalfe, J., Perez-Ruzafa, A., Sinerchia, M., Steffensen, J.F., Teal, L.R., Domenici, P., Conservation physiology of marine fish: Advancing the predictive capacity of models. Biol. Lett., 2012, 10.1098/rsbl.2012.0609.
74. Kaplan, I.C., Gray, I.A., Levin, P.S., Cumulative impacts of fisheries in the California current. Fish Fish., 2012, 10.1111/j.1467–2979.2012.00484.x.
75. Kempf, A., Stelzenmüller, V., Akimova, A., Floeter, J., Spatial assessment of predator–prey relationships in the North Sea: the influence of abiotic habitat properties on the spatial overlap between 0-group cod and grey gurnard. Fish. Oceanogr. 22:3 (2013), 174–192.
76. Kerr, S.R., Dickie, L.M., The Biomass Spectrum. A Predator-prey Theory of Aquatic Production. 2001, University Press 344 pp.
77. Kishi, M.J., Ito, S.-i., Megrey, B.A., Rose, K.A., Werner, F.E., A review of the NEMURO and NEMURO.FISH models and their application to marine ecosystem investigations. J. Oceanogr. 67 (2011), 3–16.
78. Koenigstein, S., Mark, F.C., Gößling-Reisemann, S., Reuter, H., Poertner, H.-O., Modelling climate change impacts on marine fish populations: process-based integration of ocean warming, acidification and other environmental drivers. Fish Fish., 2016, 10.1111/faf.12155.
79. Kooijman, S.A.L.M., Dynamic Energy Budget Theory for Metabolic Organisation, Vol. 2010, Cambridge University Press, Cambridge.
80. Kraus, G., Tomkiewicz, J., Köster, F.W., Egg production of Baltic cod (Gadus morhua) in relation to variable sex ratio, maturity, and fecundity. Can. J. Fish. Aquatic Sci. 59 (2002), 1908–1920.
81. Kühn, W., Peck, M.A., Hinrichsen, H.-H., Daewel, U., Moll, A., Stegert, C., Tamm, S., Defining habitats suitable for larval fish in the German Bight (southern North Sea): an IBM approach using spatially and temporally resolved, size-structured prey fields. J. Mar. Syst. 74 (2008), 329–342.
82. Lam, V.W., Cheung, W.W.L., Swartz, W., Sumaila, U.R., Climate change impacts on fisheries in West Africa: implications for economic, food and nutritional security. Afr. J. Mar. Sci. 34:1 (2012), 103–117.
83. Lehodey, P., Senina, I., Murtugudde, R., A spatial ecosystem and populations dynamics model (SEAPODYM) – modeling of tuna and tuna-like populations. Prog. Oceanogr. 78 (2008), 304–318.
84. Lehuta, S., Mahévas, S., Petitgas, P., Pelletier, D., Combining sensitivity and uncertainty analysis to evaluate the impact of management measures with ISIS–Fish: marine protected areas for the Bay of Biscay anchovy (Engraulis encrasicolus) fishery. ICES J. Mar. Sci. 67 (2010), 1063–1075.
85. Lehuta, S., Mahévas, S., Petitgas, P., LeFloch, P., A simulation-based approach to assess sensitivity and robustness of fisheries management indicators for the pelagic fishery in the Bay of Biscay. Can. J. Fish. Aquatic Sci., 70, 2013 2013-0066.
86. Lehuta, S., Petitgas, P., Mahevas, S., Huret, M., Vermard, Y., Uriarte, A., Record, N.R., Selection and validation of a complex fishery model using an uncertainty hierarchy. Fish. Res. 143 (2013), 57–66.
87. Libralato, S., Coll, M., Tempesta, M., Santojanni, A., Spoto, M., Palomera, I., Arneri, E., Solidoro, C., Food-web traits of protected and exploited areas of the Adriatic Sea biological conservation., 143, 2012, 2182–2194.
88. Lindeboom, H.J., Kouwenhoven, H.J., Bergman, M.J.N., Bouma, S., Brasseur, S., Daan, R., Fijn, R.C., de Haan, D., Dirksen, S., van Hal, R., Hille Ris Lambers, R., terHofstede, R., Krijgsveld, K.L., Leopold, M., Scheidat, M., Short-term ecological effects of an offshore wind farm in the Dutch coastal zone; a compilation. Environ. Res. Lett., 6, 2011, 035101, 10.1088/1748-9326/6/3/03510.
89. Littell, J.S., O‘Niel, E.E., McKenzie, D., Hicke, J.A., Lutz, J.A., Norheim, R.A., Elsner, M.M., Forest ecosystems, disturbance,and climatic change in Washington State, USA. Clim. Change 102 (2010), 129–158.
90. Llope, M., Licandro, P., Chan, K.-S., Stenseth, N.C., Spatial variability of the plankton trophic interaction in the North Sea: a new feature after the early 1970s. Glob. Change Biol. 18:1 (2012), 106–117.
91. Luisetti, T., Turner, R.K., Bateman, I.J., Morse-Jones, S., Adams, C., Fonseca, L., Coastal and marine ecosystem services valuation for policy and management: managed realignment case studies in England. Ocean Coast. Manag. 54 (2011), 212–224.
92. Mackinson, S., Daskalov, G., Heymans, J.J., Neira, S., Arancibia, H., Zetina-Rejón, M., Jiang, H., Cheng, H.Q., Coll, M., Arreguin-Sanchez, F., Which forcing factors fit? Using ecosystem models to investigate the relative influence of fishing and changes in primary productivity on the dynamics of marine ecosystems. Ecol. Model. 220 (2009), 2972–2987.
93. Mahévas, S., Pelletier, D., ISIS-Fish, a generic and spatially explicit simulation tool for evaluating the impact of management measures on fisheries dynamics. Ecol. Model. 171 (2004), 65–84.
94. Marshall, C.T., Yaragina, B., Adlandsvik, A., Dolgov, A.V., Reconstructing the stock-recruit relationship for North east Arctic cod using a bioenergetic index of reproductive potential. Can. J. Fish. Aquatic Sci. 57 (2000), 1–10.
95. Marzloff, M., Shin, Y.-J., Tam, J., Travers, M., Bertrand, A., Trophic structure of the Peruvian marine ecosystem in 2000–2006: insights on the effects of management scenarios for the hake fishery using the IBM trophic model Osmose. J. Mar. Syst. 75:1–2 (2009), 290–304.
96. Maunder, M.N., Harley, S.J., Hampton, J., Including parameter uncertainty in forward projections of computationally intensive statistical dynamic models. ICES J. Mar. Sci. 63 (2006), 969–979.
97. Merino, G., Barange, M., Mullon, C., Climate variability and change scenarios for a marine commodity: modelling small pelagic fish, fisheries and fishmeal in a globalized market. J. Mar. Syst. 81 (2010), 196–205.
98. Merino, G., Barange, M., Blanchard, J.L., Harle, J., Holmes, R., Allen, I., Allison, E.H., Badjeck, M.C., Dulvy, N.K., Holt, J., Jennings, S., Mullon, C., Rodwell, L.D., Can marine fisheries and aquaculture meet fish demand from a growing human population in a changing climate?. Glob. Environ. Change 22:4 (2012), 795–806.
99. Metcalfe, J.D., Le Quesne, W.J.F., Cheung, W.W.L., Righton, D.A., Conservation physiology for applied management of marine fish: perspectives on the role and value of telemetry. Philos. Trans. R. Soc. B 367 (2012), 1746–1756.
100. Metcalfe, K., Vaz, S., Engelhard, G.H., Villanueva, M.C., Smith, R.J., Mackinson, S., Evaluating conservation and fisheries management strategies by linking spatial prioritization software and ecosystem and fisheries modelling tools. J. Appl. Ecol. 52 (2015), 665–674.
101. Milly, P.C.D., Betancourt, J., Falkenmark, M., Hirsch, R.M., Kundzewicz, Z.W., Lettenmaier, D.P., Stouffer, R.J., Stationarity is dead: Whither water management?. Science 319 (2008), 573–574.
102. Möller, K.O., St John, M., Temming, A., Floeter, J., Sell, A.F., Herrmann, J.P., Möllmann, C., Marine snow, zooplankton and thin layers: indications of a trophic link from small-scale sampling with the Video Plankton Recorder. Mar. Ecol. Prog. Ser. 468 (2012), 57–69.
103. Morzari-Luna, H.N., Aninsworth, C., Kaplin, I., Levin, P., Fulton, E.A., Exploring trade-offs between fisheries and conservation of the Baquita porpoise (Phocoena sinus) using an Atlantis ecosystem model. PLoS One, 7(8), 2012, e42917, 10.1371/journal.pone.0042917.
104. Mueter, F.J., Ladd, C., Palmer, M.C., Norcross, B.L., Bottom-up and top-down controls of walleye pollock (Theragra chalcogramma) on the Eastern Bering Sea shelf. Prog. Oceanogr. 68 (2006), 152–183.
105. Nicolas, D., Rochette, S., Llope, M., Licandro, P., Spatio-temporal variability of the North Sea cod recruitment in relation to temperature and zooplankton. PLoS One, 9(2), 2014, e88447, 10.1371/journal.pone.0088447.
106. Nisbet, R.M., Jusup, M., Klanjscek, T., Pecquerie, L., Integrating dynamic energy budget (DEB) theory with traditional bioenergetic models. J. Exp. Biol. 215 (2012), 892–902.
107. O'Connor, M.I., Bruno, J.F., Gaines, S.D., Halpern, B.S., Lester, S.E., Kinlan, B.P., Weiss, J.M., Temperature control of larval dispersal and the implications for marine ecology, evolution, and conservation. Proc. Natl. Acad. Sci. U. S. A. 104 (2007), 1266–1271.
108. Parent, E., Rivot, E., Introduction to Hierarchical Bayesian Modeling for Ecological Data. 2012, Chapman & Hall/CRC Col. Applied Environmental Statistics, 427 pp.
109. Pearce, J., Ferrier, S., Evaluating the predictive performance of habitat models developed using logistic regression. Ecol. Model. 133 (2000), 225–245.
110. Pearson, R.G., Dawson, T.P., Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful?. Glob. Ecol. Biogeogr. 12 (2003), 361–371.
111. Peck, M.A., Hufnagl, M., Can IBMs explain why most larvae die in the sea? Model scenarios and sensitivity analyses reveal research needs. J. Mar. Syst. 93 (2012), 77–93.
112. Peck, M.A., Reglero, P., Takahashi, M., Catalán, I.A., Life cycle ecophysiology of small pelagic fish and climate-driven changes in populations. Prog. Oceanogr. 116 (2013), 220–245.
113. Pelletier, D., Mahévas, S., Drouineau, H., Vermard, Y., Thebaud, O., Guyader, O., Poussin, B., Evaluation of the bioeconomic sustainability of multi-species multi-fleet fisheries under a wide range of policy options using ISIS-Fish. Ecol. Model. 220:7 (2009), 1013–1033.
114. Perry, A.L., Low, P.J., Ellis, J.R., Reynolds, J.D., Climate change and distribution shifts in marine fishes. Science 308 (2005), 1912–1915.
115. Perry, R.I., Cury, P., Brander, K., Jennings, S., Möllmann, C., Planque, B., Sensitivity of marine systems to climate and fishing: concepts, issues and management responses. J. Mar. Syst. 79 (2010), 427–435.
116. Petitgas, P., Alheit, J., Peck, M.A., Raab, K., Irigoien, X., Huret, M., van der Kooij, J., Pohlmann, T., Wagner, C., Zarraonaindia, I., Dickey-Collas, M., Anchovy population expansion in the North Sea. Mar. Ecol. Prog. Ser. 444 (2012), 1–13.
117. Petitgas, P., Rijnsdorp, A.D., Dickey-Collas, M., Engelhard, G.H., Peck, M.A., Pinnegar, J.K., Drinkwater, K., Huret, M., Nash, R.D.M., Impacts of climate change on the complex life cycles of fish. Fish. Oceanogr. 22:2 (2012), 121–139.
118. Phillips, S.J., Dudik, M., Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation. Ecography 31 (2008), 161–175.
119. Pikitch, E.K., Santora, C., Babcock, C.A., Bakun, A., Bonfil, R., Conover, D.O., Dayton, P., Doukakis, P., Fluharty, D., Heneman, B., Houde, E.D., Link, J., Livingston, P.A., Mangel, M., McAllister, M.K., Pope, J., Sainsbury, K.J., Ecology: ecosystem-based fishery management. Science 305 (2004), 346–347.
120. Pinnegar, J.K., Tomczak, M.T., Link, J.S., How to determine the likely indirect food-web consequences of a newly introduced non-native species: a worked example. Ecol. Model. 272 (2014), 379–387.
121. Piroddi, C., Teixeira, H., Lynam, C.P., Smith, C., Alvarez, M.C., Mazik, K., Andonegi, E., Churilova, T., Tedesco, L., Chifflet, M., Chust, G., Galparsoro, I., Garcia, A.C., Maria Kämäri, M., Kryvenko, O., Lassalle, G., Neville, S., Niquil, N., Papadopoulou, N., Rossberg, A.G., Suslin, V., Uyarra, M.C., Using ecological models to assess ecosystem status in support of the European Marine Strategy Framework Directive. Ecol. Indic. 58 (2015), 175–191.
122. Plagányi, É.E., Models for an Ecosystem Approach to Fisheries. 2007 FAO Fisheries Technical Paper. No. 477 Rome, FAO. 108 pp.
123. Planque, B., Bellier, E., Loots, C., Uncertainties in projecting spatial distributions of marine populations. ICES J. Mar. Sci. 68:6 (2011), 1045–1050.
124. Planque, B., Loots, C., Petitgas, P., Lindstrom, U., Vaz, S., Understanding what controls the spatial distribution of fish populations using a multi-model approach. Fish. Oceanogr. 20 (2011), 1–17.
125. Platt, T., Denman, K.L., Organization in the pelagic ecosystem. Helgolander Wissenschaftliche Meeresuntersuchungen 30 (1977), 575–581.
126. Pörtner, H.-O., Integrating climate-related stressor effects on marine organisms: unifying principles linking molecule to ecosystem-level changes. Mar. Ecol. Prog. Ser. 470 (2012), 273–290.
127. Pörtner, H.O., Knust, R., Climate change affects marine fishes through the oxygen limitation of thermal tolerance. Science 315 (2007), 95–97.
128. Pörtner, H.O., Peck, M.A., Climate change impacts on fish and fisheries: towards a cause and effect understanding. J. Fish Biol. 77 (2010), 1745–1779.
129. Rabalais, N.N., Díaz, R.J., Levin, L.A., Turner, R.E., Gilbert, D., Zhang, J., Dynamics and distribution of natural and human-caused coastal hypoxia. Biogeosciences 7 (2010), 585–619.
130. Rijnsdorp, A., Peck, M.A., Engelhard, G.H., Möllmann, C., Pinnegar, J.K., Resolving the effect of climate change on fish populations. ICES J. Mar. Sci. 66 (2009), 1570–1583.
131. Robinson, L.M., Elith, J., Hobday, A.J., Pearson, R.G., Kendall, B.E., Possingham, H.P., Richardson, A.J., Pushing the limits in marine species distribution modelling: lessons from the land present challenges and opportunities. Glob. Ecol. Biogeogr. 20 (2011), 789–802.
132. Rochette, S., Le Pape, O., Vigneau, J., Rivot, E., A hierarchical Bayesian model for embedding larval drift and habitat models in integrated life cycle for exploited fish. Ecol. Appl. 23 (2013), 1659–1676.
133. Rombouts, I., Beaugrand, G., Artigas, L.F., Dauvin, J.-C., Gevaert, F., Goberville, E., Kopp, D., Lefebvre, S., Luczak, C., Spilmont, N., Travers-Trolet, M., Villanueva, M.C., Kirby, R.R., Evaluating marine ecosystem health: case studies of indicators using direct observations and modelling methods. Ecol. Indic. 24 (2013), 353–365.
134. Rose, K.A., Allen, J.I., Artioli, Y., Barange, M., Blackford, J., Carlotti, F., Cropp, R., Daewel, U., Edwards, K., Flynn, K., Hill, S.L., HilleRisLambers, R., Huse, G., Mackinson, S., Megrey, B., Moll, A., Rivkin, R., Salihoglu, B., Schrum, C., Shannon, L., Shin, Y.-J., Smith, S.L., Smith, C., Solidoro, C., St John, M., Zhou, M., End-to-end models for the analysis of marine ecosystems: challenges, issues, and next steps. Mar. Coast. Fish. Dyn. Manag. Ecosyst. Sci. 2 (2010), 115–130.
135. Rose, K.A., James, H., Cowan Jr., Houde, E.D., Wang, S.B., Young, J., An individual-based model of bay anchovy population dynamics in the mesohaline region of Chesapeake Bay. Mar. Ecol. Prog. Ser. 185 (1999), 113–132.
136. Rose, K.A., Fiechter, J., Curchitser, E., et al. Demonstration of a fully-coupled end-to-end model for small pelagic fish using sardine and anchovy in the California Current. Prog. Oceanogr. 138 (2015), 348–380.
137. Seebacher, F., Franklin, C.E., Determining environmental causes of biological effects: the need for a mechanistic physiological dimension in conservation biology. Philos. Trans. R. Soc. B 367 (2012), 1607–1614.
138. Sheldon, R.W., Prakash, A., Sutcliff, W.H. Jr., The size distribution of particles in the ocean. Limnol. Oceanogr. 17:3 (1972), 327–339.
139. Shin, Y.-J., Cury, P., Exploring fish community dynamics through size-dependent trophic interactions using a spatialized individual-based model. Aquat. Living Resour. 14 (2001), 65–80.
140. Shin, Y.-J., Shannon, L.J., Cury, P.M., Simulations of fishing effects on the southern Benguela fish community using an individual-based model: learning from a comparison with ECOSIM. Shannon, L.J., Cochrane, K.L., Pillar, S.C., (eds.) Ecosystem Approaches to Fisheries in the Southern Benguela, 26, 2004, 95–114 African Journal of marine Science.
141. Shurin, J.B., Borer, E.T., Seabloom, E.W., Anderson, K., Blanchette, C.A., Broitman, B., Cooper, S.D., Halpen, B.S., A cross-ecosystem comparison of the strength of trophic cascades. Ecol. Lett. 5 (2002), 785–791.
142. Simons, S.L., Döring, R., Temming, A., Combining area closures with catch regulations in fisheries with spatio-temporal variation: bio-economic implications for the North Sea saithe fishery. Mar. Policy 51 (2015), 281–292.
143. Simpson, S.D., Jennings, S., Johnson, M.P., Blanchard, J.L., Schön, P.J., Sims, D.W., Genner, M.J., Continental shelf-wide response of a fish assemblage to rapid warming of the sea. Curr. Biol. 21:18 (2011), 1565–1570.
144. Soberón, J., Grinnellian and Eltonian niches and geographic distributions of species. Ecol. Lett. 10 (2007), 1115–1123.
145. Solidoro, C., Pastres, R., Melaku Canu, D., Pellizzato, M., Rossi, R., Modelling the growth of Tapes philippinarum in Northern Adriatic lagoons. Mar. Ecol. Prog. Ser. 199 (2000), 137–148.
146. Speirs, D.C., Guirey, E.J., Gurney, W.S.C., Heath, M.R., A length-structured partial ecosystem model for cod in the North Sea. Fish. Res. 106:3 (2010), 474–494.
147. Steenbeek, J., Coll, M., Gurney, L., Mélin, F., Hoepffner, N., Buszowski, J., Christensen, V., Bridging the gap between ecosystem modelling tools using geographic information systems: driving a food-web model with spatial-temporal primary production data. Ecol. Model. 263 (2013), 139–151.
148. Stips, A., Bolding, K., Pohlman, T., Burchard, H., Simulating the temporal and spatial dynamics of the North Sea using the new model getm, General Estuarine Transport Model. Ocean. Dyn. 54 (2004), 266–283.
149. Stock, C.A., Alexander, M.A., Bond, N.A., Brander, K.M., Cheung, W.W.L., Curchitser, E.N., et al. On the use of IPCC-class models to assess the impact of climate on Living Marine Resources. Prog. Oceanogr. 88 (2011), 1–27.
150. Sugihara, G., May, R., Ye, H., Hsieh, C.-h., Deyle, E., Fogarty, M., Munch, S., Detecting causality in complex ecosystems. Science 338 (2012), 496–500.
151. Sumaila, U.R., Cheung, W.W.L., Lam, V.W.Y., Pauly, D., Herrick, S., Climate change impacts on the biophysics and economics of world fisheries. Nat. Clim. Change 1 (2011), 449–456.
152. Sunday, J.M., Bates, A.E., Dulvy, N.K., Thermal tolerance and the global redistribution of animals. Nat. Clim. Change 2 (2012), 686–690.
153. Sundby, S., Recruitment of Atlantic cod stocks in relation to temperature and action of copepod populations. Sarsia 85 (2000), 277–298.
154. Sykes, M.T., Prentice, I.C., Cramer, W., A bioclimatic model for the potential distributions of north European tree species under present and future climates. J. Biogeogr. 23 (1996), 203–233.
155. Taylor, A., Allen, J., Clark, P., Extraction of a weak climatic signal by an ecosystem. Nature 416 (2002), 629–632.
156. Teal, L., Marras, S., Peck, M.A., Domenici, P., Physiological-based approaches to characterize fish habitat suitability: their usefulness and limitations. Estuar. Coast. Shelf Sci., 2016, 10.1016/j.ecss.2015.11.014 (in press).
157. Teal, L.R., Van Hal, R., Van Kooten, T., Ruardij, P., Rijnsdorp, A.D., Bio-energetics underpins the spatial response of North Sea plaice (Pleuronectes platessa L.) and sole (Solea solea L.) to climate change. Glob. Change Biol. 18 (2012), 3291–3305.
158. Temming, A., Floeter, J., Ehrich, S., Predation hot spots: large scale impact of local aggregations. Ecosystems 10 (2007), 865–876.
159. Thomas, L., Buckland, S.T., Newman, K.B., Harwood, J., A unified framework for modelling wildlife population dynamics. Aust. N. Z. J. Stat. 47 (2005), 19–34.
160. Thuiller, W., BIOMOD – optimizing predictions of species distributions and projecting potential future shifts under global change. Glob. Change Biol. 9 (2003), 1353–1362.
161. Travers, M., Shin, Y.-J., Jennings, S., Machu, E., Huggett, J.A., Field, J., Cury, P., Two-way coupling versus one-way forcing of plankton and fish models to predict ecosystem changes in the Benguela. Ecol. Model. 220 (2009), 3089–3099.
162. Travers, M., Shin, Y.-J., Jennings, S., Cury, P., Towards end-to-end models for investigating the effects of climate and fishing in marine ecosystems. Prog. Oceanogr. 75 (2007), 751–770.
163. Travers, M., Watermeyer, K., Shannon, L.J., 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. Mar. Syst. 79 (2010), 101–111.
164. van der Veer, H.W., Cardoso, J.F.M.F., Peck, M.A., Kooijman, S.A.L.M., Physiological performance of plaice Pleuronectes platessa (L.): a comparison of static and dynamic energy budgets. J. Sea Res. 62 (2009), 83–92.
165. VECTORS, Scenario Modelling of the North Sea under the Influence of Multiple Drivers with Recommendations for Regional Adaptive Management Strategies Addressing EU Policies. VECTORS Deliverable Report 4.2.2, 2014 www.marine-vectors.eu/deliverables/D4_2_2.pdf.
166. Walters, C., Martell, S.J.D., Christensen, V., Mahmoudi, B., An Ecosim model for exploring Gulf of Mexico ecosystem management options: implications of including multistanza life-history models for policy predictions. Bull. Mar. Sci. 83 (2008), 251–271.
167. Werner, F., Quinlan, J., Lough, R., Lynch, D., Spatially-explicit individual based modeling of marine populations: a review of the advances in the 1990s. Sarsia 86 (2001), 411–421.
168. Yemane, D., Shin, Y.-J., Field, J., Exploring the effect of marine protected areas on the dynamics of fish communities in the southern Benguela: an Individual Based Modelling approach. ICES J. Mar. Sci. 66 (2009), 378–387.