SAUP. Sea Around Us. http://www.seaaroundus.org/data/ (2020).
Coll, M., Navarro, J., Olson, R. J. & Christensen, V. Assessing the trophic position and ecological role of squids in marine ecosystems by means of food-web models. Deep Sea Res. Part II Top. Stud. Oceanogr. 95, 21–36 (2013).
Hastie, L. et al. Cephalopods in the north-eastern Atlantic: Species, biogeography, ecology, exploitation and conservation. In Oceanography and Marine Biology (eds. Gibson, R., Atkinson, R. & Gordon, J.) vol. 20092725, 111–190 (CRC Press, Boca Raton, 2009).
Piatkowski, U. & Pierce, G. J. Impact of cephalopods in the food chain and their interaction with the environment and fisheries: An overview. Fish. Res. 6, 5–10 (2001).
Pierce, G. J. et al. A review of cephalopod–environment interactions in European Seas. Hydrobiologia 612, 49–70 (2008).
André, J., Haddon, M. & Pecl, G. T. Modelling climate-change-induced nonlinear thresholds in cephalopod population dynamics. Glob. Change Biol. 16, 2866–2875 (2010).
Jereb, P. et al. Cephalopod biology and fisheries in Europe: II. Species Accounts. ICES Cooper. Res. Rep. 325, 1–360 (2015).
Sims, D. W., Genner, M. J., Southward, A. J. & Hawkins, S. J. Timing of squid migration reflects North Atlantic climate variability. Proc. R. Soc. Lond. Ser. B Biol. Sci. 268, 2607–2611 (2001).
Dorey, N. et al. Ocean acidification and temperature rise: Effects on calcification during early development of the cuttlefish Sepia officinalis. Mar. Biol. 160, 2007–2022 (2013).
Rodhouse, P. G. K. et al. Environmental effects on cephalopod population dynamics. In Advances in Marine Biology vol. 67, 99–233 (Elsevier, Amsterdam, 2014).
Millar, R. J. et al. Emission budgets and pathways consistent with limiting warming to 1.5 °C. Nat. Geosci. 10, 741–747 (2017).
Otto, F. E. L., Frame, D. J., Otto, A. & Allen, M. R. Embracing uncertainty in climate change policy. Nat. Clim. Change 5, 917–920 (2015).
Meinshausen, M. et al. The RCP greenhouse gas concentrations and their extensions from 1765 to 2300. Clim. Change 109, 213–241 (2011).
van Vuuren, D. P. et al. The representative concentration pathways: An overview. Clim. Change 109, 5–31 (2011).
Gissi, E. et al. A review of the combined effects of climate change and other local human stressors on the marine environment. Sci. Total Environ. 755, 142564 (2021).
Beaugrand, G. et al. Prediction of unprecedented biological shifts in the global ocean. Nat. Clim. Change 9, 237–243 (2019).
Jorda, G. et al. Ocean warming compresses the three-dimensional habitat of marine life. Nat. Ecol. Evol. 4, 109–114 (2020).
Vidal, E. A. G., DiMarco, F. P., Wormuth, J. H. & Lee, P. G. Influence of temperature and food availability on survival, growth and yolk utilization in hatchling squid. Bull. Mar. Sci. 71, 915–931 (2002).
Doubleday, Z. A. et al. Global proliferation of cephalopods. Curr. Biol. 26, R406–R407 (2016).
van der Kooij, J., Engelhard, G. H. & Righton, D. A. Climate change and squid range expansion in the North Sea. J. Biogeogr. 43, 2285–2298 (2016).
Jin, Y., Jin, X., Gorfine, H., Wu, Q. & Shan, X. Modeling the oceanographic impacts on the spatial distribution of common cephalopods during autumn in the yellow sea. Front. Mar. Sci. 7, (2020).
Pang, Y. et al. Variability of coastal cephalopods in overexploited China Seas under climate change with implications on fisheries management. Fish. Res. 208, 22–33 (2018).
Le Marchand, M. et al. Climate change in the Bay of Biscay: Changes in spatial biodiversity patterns could be driven by the arrivals of southern species. Mar. Ecol. Prog. Ser. 647, 17–31 (2020).
Lima, F. D., Ángeles-González, L. E., Leite, T. S. & Lima, S. M. Q. Global climate changes over time shape the environmental niche distribution of Octopus insularis in the Atlantic Ocean. Mar. Ecol. Prog. Ser. 652, 111–121 (2020).
Xavier, J. C., Peck, L. S., Fretwell, P. & Turner, J. Climate change and polar range expansions: Could cuttlefish cross the Arctic?. Mar. Biol. 163, 78 (2016).
Selig, E. R. et al. Mapping global human dependence on marine ecosystems. Conserv. Lett. 12, e12617 (2019).
Blasiak, R. et al. Climate change and marine fisheries: Least developed countries top global index of vulnerability. PLoS ONE 12, e0179632 (2017).
FAO. The State of Mediterranean and Black Sea Fisheries. (General Fisheries Commission for the Mediterranean, 2016).
Lam, V. W. Y., Cheung, W. W. L., Reygondeau, G. & Sumaila, U. R. Projected change in global fisheries revenues under climate change. Sci. Rep. 6, 32607 (2016).
Badjeck, M.-C., Perry, A., Renn, S., Brown, D. & Poulain, F. The vulnerability of fishing-dependent economies to disasters. FAO Fish. Aquac. Circ. 1081, 1–19 (2013).
Allison, E. H. et al. Vulnerability of national economies to the impacts of climate change on fisheries. Fish Fish. 10, 173–196 (2009).
Adloff, F. et al. Mediterranean Sea response to climate change in an ensemble of twenty first century scenarios. Clim. Dyn. 45, 2775–2802 (2015).
Alexander, M. A. et al. Projected sea surface temperatures over the 21st century: Changes in the mean, variability and extremes for large marine ecosystem regions of Northern Oceans. Elementa Sci. Anthropocene 6, 9 (2018).
Gaines, S. D. et al. Improved fisheries management could offset many negative effects of climate change. Sci. Adv. 4, eaao1378 (2018).
Pierce, G. J. et al. Status and trends of European cephalopod stocks. In ASC 2019 ICES Conference, Gothenburg, Sweden 1 (2019).
Hutchinson, G. E. Concluding remarks. Cold Spring Harb. Symp. Quant. Biol. 22, 415–427 (1957).
Hutchinson, G. E. An Introduction to Population Ecology (Yale University Press, New Haven, 1978).
Peterson, A. & Soberón, J. Species distribution modeling and ecological niche modeling: Getting the concepts right. Natureza e Conservação 10, 1–6 (2012).
Colwell, R. K. & Rangel, T. F. Hutchinson’s duality: The once and future niche. Proc. Natl. Acad. Sci. 106, 19651–19658 (2009).
Buisson, L., Thuiller, W., Casajus, N., Lek, S. & Grenouillet, G. Uncertainty in ensemble forecasting of species distribution. Glob. Change Biol. 16, 1145–1157 (2010).
Araújo, M. B. & New, M. Ensemble forecasting of species distributions. Trends Ecol. Evol. 22, 42–47 (2007).
Hao, T., Elith, J., Guillera-Arroita, G. & Lahoz-Monfort, J. J. A review of evidence about use and performance of species distribution modelling ensembles like BIOMOD. Divers. Distrib. https://doi.org/10.1111/ddi.12892 (2019).
Goberville, E., Beaugrand, G., Hautekèete, N.-C., Piquot, Y. & Luczak, C. Uncertainties in the projection of species distributions related to general circulation models. Ecol. Evol. 5, 1100–1116 (2015).
Leroy, B. et al. Forecasted climate and land use changes, and protected areas: The contrasting case of spiders. Divers. Distrib. 20, 686–697 (2014).
Schickele, A. et al. Modelling European small pelagic fish distribution: Methodological insights. Ecol. Model. 416, 108902 (2020).
Araújo, M. B. et al. Standards for distribution models in biodiversity assessments. Sci. Adv. 5, eaat4858 (2019).
Barbet-Massin, M., Thuiller, W. & Jiguet, F. How much do we overestimate future local extinction rates when restricting the range of occurrence data in climate suitability models?. Ecography 33, 878–886 (2010).
Beaugrand, G., Luczak, C., Goberville, E. & Kirby, R. Marine biodiversity and the chessboard of life. PLoS ONE 13, e0194006 (2018).
Støa, B., Halvorsen, R., Mazzoni, S. & Gusarov, V. I. Sampling bias in presence-only data used for species distribution modelling: Theory and methods for detecting sample bias and its effects on models. Sommerfeltia 38, 1–53 (2018).
Dufresne, J.-L. et al. Climate change projections using the IPSL-CM5 Earth System Model: from CMIP3 to CMIP5. Clim. Dyn. 40, 2123–2165 (2013).
Voldoire, A. et al. The CNRM-CM5.1 global climate model: Description and basic evaluation. Clim. Dyn. 40, 2091–2121 (2013).
Hourdin, F. et al. Impact of the LMDZ atmospheric grid configuration on the climate and sensitivity of the IPSL-CM5A coupled model. Clim. Dyn. 40, 2167–2192 (2013).
Friedlingstein, P. et al. Uncertainties in CMIP5 climate projections due to carbon cycle feedbacks. J. Clim. 27, 511–526 (2013).
Wiens, J. A., Stralberg, D., Jongsomjit, D., Howell, C. A. & Snyder, M. A. Niches, models, and climate change: Assessing the assumptions and uncertainties. PNAS 106, 19729–19736 (2009).
Martinez-Meyer, E. Climate change and biodiversity: Some considerations in forecasting shifts in species’ potential distributions. Biodivers. Inform. 2, 42–55 (2005).
Levitus, S. Climatological atlas of the world ocean. Eos Trans. Am. Geophys. Union 64, 962–963 (2011).
Cabanes, C. et al. The CORA dataset: Validation and diagnostics of in-situ ocean temperature and salinity measurements. Ocean Sci. 9, 1–18 (2013).
Giorgetta, M. A. et al. Climate and carbon cycle changes from 1850 to 2100 in MPI-ESM simulations for the Coupled Model Intercomparison Project phase 5: Climate Changes in MPI-ESM. J. Adv. Model. Earth Syst. 5, 572–597 (2013).
Stevens, B. et al. Atmospheric component of the MPI-M Earth System Model: ECHAM6. J. Adv. Model. Earth Syst. 5, 146–172 (2013).
Jones, C. D. et al. The HadGEM2-ES implementation of CMIP5 centennial simulations. Geosci. Model Dev. Discuss. 4, 689–763 (2011).
Schmidt, G. A. et al. Configuration and assessment of the GISS ModelE2 contributions to the CMIP5 archive: GISS MODEL-E2 CMIP5 SIMULATIONS. J. Adv. Model. Earth Syst. 6, 141–184 (2014).
Beaugrand, G., Lenoir, S., Ibañez, F. & Manté, C. A new model to assess the probability of occurrence of a species, based on presence-only data. Mar. Ecol. Prog. Ser. 424, 175–190 (2011).
Raybaud, V., Bacha, M., Amara, R. & Beaugrand, G. Forecasting climate-driven changes in the geographical range of the European anchovy (Engraulis encrasicolus). ICES J. Mar. Sci. 74, 1288–1299 (2017).
Thuiller, W., Lafourcade, B., Engler, R. & Araújo, M. B. BIOMOD—A platform for ensemble forecasting of species distributions. Ecography 32, 369–373 (2009).
Thuiller, W., Georges, D., Engler, R. & Breiner, F. Ensemble Platform for Species Distribution Modelling. (2016).
Dormann, C. F. et al. Collinearity: A review of methods to deal with it and a simulation study evaluating their performance. Ecography 36, 27–46 (2013).
Lenoir, J. et al. Species better track climate warming in the oceans than on land. Nat. Ecol. Evol. https://doi.org/10.1038/s41559-020-1198-2 (2020).
Smith, W. H. F. & Sandwell, D. T. Global sea floor topography from satellite altimetry and ship depth soundings. Science 277, 1956–1962 (1997).
NASA Goddard Space Flight Center, Ocean Ecology Laboratory, Ocean Biology Processing Group. Distance to the nearest coast. https://oceancolor.gsfc.nasa.gov/docs/distfromcoast/ (01/03/2018) (2009).
Hattab, T. et al. Towards a better understanding of potential impacts of climate change on marine species distribution: A multiscale modelling approach. Glob. Ecol. Biogeogr. 23, 1417–1429 (2014).
Varela, S., Anderson, R. P., García-Valdés, R. & Fernández-González, F. Environmental filters reduce the effects of sampling bias and improve predictions of ecological niche models. Ecography 37, 1084–1091 (2014).
Ben Rais Lasram, F. et al. An open-source framework to model present and future marine species distributions at local scale. Ecol. Inform. 59, 101130 (2020).
Montgomery, D. C. Design and Analysis of Experiments (Wiley, Hoboken, 2005).
Getz, W. M. & Wilmers, C. C. A local nearest-neighbor convex-hull construction of home ranges and utilization distributions. Ecography 27, 489–505 (2006).
Cornwell, W. K., Schwilk, D. W. & Ackerly, D. D. A trait-based test for habitat filtering: Convex hull volume. Ecology 87, 1465–1471 (2004).
Hirzel, A. H., Le Lay, G., Helfer, V., Randin, C. & Guisan, A. Evaluating the ability of habitat suitability models to predict species presences. Ecol. Model. 199, 142–152 (2006).
Leroy, B. et al. Without quality presence–absence data, discrimination metrics such as TSS can be misleading measures of model performance. J. Biogeogr. 45, 1994–2002 (2018).
Faillettaz, R., Beaugrand, G., Goberville, E. & Kirby, R. R. Atlantic Multidecadal Oscillations drive the basin-scale distribution of Atlantic bluefin tuna. Sci. Adv. 5, eaar6993 (2019).
Elith, J., Ferrier, S., Huettmann, F. & Leathwick, J. The evaluation strip: A new and robust method for plotting predicted responses from species distribution models. Ecol. Model. 186, 280–289 (2005).
VanDerWal, J. et al. Focus on poleward shifts in species’ distribution underestimates the fingerprint of climate change. Nat. Clim. Change 3, 239–243 (2013).
Taylor, K. E. Summarizing multiple aspects of model performance in a single diagram. J. Geophys. Res. Atmos. 106, 7183–7192 (2001).
Cristofari, R. et al. Climate-driven range shifts of the king penguin in a fragmented ecosystem. Nat. Clim. Change 8, 245–251 (2018).
Péron, C., Weimerskirch, H. & Bost, C.-A. Projected poleward shift of king penguins’ (Aptenodytes patagonicus) foraging range at the Crozet Islands, southern Indian Ocean. Proc. Biol. Sci. 279, 2515–2523 (2012).
Bloor, I. S. M., Attrill, M. J. & Jackson, E. L. Chapter One—A Review of the Factors Influencing Spawning, Early Life Stage Survival and Recruitment Variability in the Common Cuttlefish (Sepia officinalis). In Advances in Marine Biology (ed. Lesser, M.) vol. 65, 1–65 (Academic Press, Cambridge, 2013).
Vidal, E. A. G., Roberts, M. J. & Martins, R. S. Yolk utilization, metabolism and growth in reared Loligo vulgaris reynaudii paralarvae. Aquat. Living Resour. 18, 385–393 (2005).
Bouchaud, O. Energy consumption of the cuttlefish Sepia officinalis L. (Mollusca: Cephalopoda) during embryonic development, preliminary results. Bull. Mar. Sci. 49, 333–340 (1991).
Laptikhovsky, V. Latitudinal and bathymetric trends in egg size variation: A new look at Thorson’s and Rass’s rules. Mar. Ecol. 27, 7–14 (2006).
Hengl, T., Sierdsema, H., Radović, A. & Dilo, A. Spatial prediction of species’ distributions from occurrence-only records: Combining point pattern analysis, ENFA and regression-kriging. Ecol. Model. 220, 3499–3511 (2009).
Clarke, M. R. The role of cephalopods in the world’s oceans: general conclusions and the future. Philos. Trans. R. Soc. Lond. Ser. B Biol. Sci. 351, 1105–1112 (1996).
Marmion, M., Parviainen, M., Luoto, M., Heikkinen, R. K. & Thuiller, W. Evaluation of consensus methods in predictive species distribution modelling. Divers. Distrib. 15, 59–69 (2009).
Kissling, W. D. et al. Towards novel approaches to modelling biotic interactions in multispecies assemblages at large spatial extents: Modelling multispecies interactions. J. Biogeogr. 39, 2163–2178 (2012).
Clark, J. S., Gelfand, A. E., Woodall, C. & Zhu, K. More than the sum of the parts: Forest climate response from joint species distribution models. Ecol. Appl. 24, 990–999 (2014).
Harris, D. J. Generating realistic assemblages with a joint species distribution model. Methods Ecol. Evol. 6, 465–473 (2015).
Nogués-Bravo, D. Predicting the past distribution of species climatic niches. Glob. Ecol. Biogeogr. 18, 521–531 (2009).
Lee, Q., Thorson, J. T., Gertseva, V. V. & Punt, A. E. The benefits and risks of incorporating climate-driven growth variation into stock assessment models, with application to Splitnose Rockfish (Sebastes diploproa). ICES J. Mar. Sci. 75, 245–256 (2018).
Colléter, M., Gascuel, D., Ecoutin, J.-M. & Tito de Morais, L. Modelling trophic flows in ecosystems to assess the efficiency of marine protected area (MPA), a case study on the coast of Sénégal. Ecol. Model. 232, 1–13 (2012).
Allen, K. R. Relation between production and biomass. J. Fish. Res. Board Can. 28, 1573–1581 (1971).
FAO. Review of the state of world marine fishery resources. FAO Fish. Aquac. Tech. Pap. 334 (2011).
Cheung, W. W. L. et al. Transform high seas management to build climate resilience in marine seafood supply. Fish Fish. 18, 254–263 (2016).
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, 449–456 (2011).
Barange, M. et al. Impacts of climate change on marine ecosystem production in societies dependent on fisheries. Nat. Clim. Change 4, 211–216 (2014).
Ojea, E., Lester, S. E. & Salgueiro-Otero, D. Adaptation of fishing communities to climate-driven shifts in target species. One Earth 2, 544–556 (2020).
Source: Ecology - nature.com
