Abstract
Climate change is impacting virtually all marine life. Adaptation strategies will require a robust understanding of the risks to species and ecosystems and how those propagate to human societies. We develop a unified and spatially explicit index to comprehensively evaluate the climate risks to marine life. Under high emissions (SSP5-8.5), almost 90% of ~25,000 species are at high or critical risk, with species at risk across 85% of their native distributions. One tenth of the ocean contains ecosystems where the aggregated climate risk, endemism and extinction threat of their constituent species are high. Climate change poses the greatest risk for exploited species in low-income countries with a high dependence on fisheries. Mitigating emissions (SSP1-2.6) reduces the risk for virtually all species (98.2%), enhances ecosystem stability and disproportionately benefits food-insecure populations in low-income countries. Our climate risk assessment can help prioritize vulnerable species and ecosystems for climate-adapted marine conservation and fisheries management efforts.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$209.00 per year
only $17.42 per issue
Rent or buy this article
Prices vary by article type
from$1.95
to$39.95
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
Code availability
Statistical analyses were conducted using the R statistical computing platform115, and the code is available upon request to the corresponding author.
References
Urban, M. C. Accelerating extinction risk from climate change. Science 348, 571–573 (2015).
Brown, S. C., Wigley, T. M. L., Otto-Bliesner, B. L., Rahbek, C. & Fordham, D. A. Persistent Quaternary climate refugia are hospices for biodiversity in the Anthropocene. Nat. Clim. Change 10, 244–248 (2020).
O’Hara, C. C., Frazier, M. & Halpern, B. S. At-risk marine biodiversity faces extensive, expanding, and intensifying human impacts. Science 372, 84–87 (2021).
Halpern, B. S. et al. An index to assess the health and benefits of the global ocean. Nature 488, 615–620 (2012).
Free, C. M. et al. Impacts of historical warming on marine fisheries production. Science 363, 979–983 (2019).
Costello, C. et al. The future of food from the sea. Nature 588, 95–100 (2020).
Lotze, H. K., Bryndum-Buchholz, A. & Boyce, D. G. in The Impacts of Climate Change: Comprehensive Study of the Physical, Societal and Political Issues (ed. Letcher, T.) 205–231 (Elsevier, 2021); https://doi.org/10.1016/B978-0-12-822373-4.00017-3
Boyce, D. G., Lotze, H. K., Tittensor, D. P., Carozza, D. A. & Worm, B. Future ocean biomass losses may widen socioeconomic equity gaps. Nat. Commun. 11, 2235 (2020).
Tittensor, D. P. et al. Integrating climate adaptation and biodiversity conservation in the global ocean. Sci. Adv. 5, 2235 (2019).
Wilson, K. L., Tittensor, D. P., Worm, B. & Lotze, H. K. Incorporating climate change adaptation into marine protected area planning. Glob. Change Biol. 26, 3251–3267 (2020).
Barange, M. et al. (eds) Impacts of Climate Change on Fisheries and Aquaculture: Synthesis of Current Knowledge, Adaptation and Mitigation Options FAO Fisheries and Aquaculture Technical Paper No. 627 (FAO, 2018).
Hare, J. A. et al. A vulnerability assessment of fish and invertebrates to climate change on the northeast U.S. continental shelf. PLoS ONE 11, 1–654 (2016).
Boyce, D. G., Fuller, S., Karbowski, C., Schleit, K. & Worm, B. Leading or lagging: how well are climate change considerations being incorporated into Canadian fisheries management? Can. J. Fish. Aquat. Sci. 78, 1120–1129 (2021).
IPCC Climate Change 2014: Impacts, Adaptation, and Vulnerability (eds Field, C. B. et al.) (Cambridge Univ. Press, 2014).
Pacifici, M. et al. Assessing species vulnerability to climate change. Nat. Clim. Change 5, 215–225 (2015).
de los Ríos, C., Watson, J. E. M. & Butt, N. Persistence of methodological, taxonomical, and geographical bias in assessments of species' vulnerability to climate change: a review. Glob. Ecol. Conserv. 15, e00412 (2018).
Foden, W. B. et al. Climate change vulnerability assessment of species. WIREs Clim. Change 10, e551 (2019).
Comte, L. & Olden, J. D. Climatic vulnerability of the world’s freshwater and marine fishes. Nat. Clim. Change 7, 718–722 (2017).
Albouy, C. et al. Global vulnerability of marine mammals to global warming. 1–12 (2020).
Foden, W. B. et al. Identifying the world’s most climate change vulnerable species: a systematic trait-based assessment of all birds, amphibians and corals. PLoS ONE 8, e65427 (2013).
Kesner-Reyes, K. et al. AquaMaps: algorithm and data sources for aquatic organisms. In FishBase v.04/2012 (eds. Froese, R. & Pauly, D.) www.fishbase.org (2016).
Stuart-Smith, R. D., Edgar, G. J., Barrett, N. S., Kininmonth, S. J. & Bates, A. E. Thermal biases and vulnerability to warming in the world’s marine fauna. Nature 528, 88–92 (2015).
Trisos, C. H., Merow, C. & Pigot, A. L. The projected timing of abrupt ecological disruption from climate change. Nature 580, 496–501 (2020).
Cheung, W. W. L., Watson, R., Morato, T., Pitcher, T. J. & Pauly, D. Intrinsic vulnerability in the global fish catch. Mar. Ecol. Prog. Ser. 333, 1–12 (2007).
IPCC Climate Change 2021: The Physical Science Basis (eds Masson-Delmotte, V. et al.) (Cambridge Univ. Press, in the press).
IPCC Climate Change 2001: Impacts, Adaptation, and Vulnerability (eds McCarthy, J. J. et al.) (Cambridge Univ. Press, 2001).
The IUCN Red List of Threatened Species v.2021-1 (IUCN, 2021); https://www.iucnredlist.org
Tittensor, D. P. et al. Global patterns and predictors of marine biodiversity across taxa. Nature 466, 1098–1101 (2010).
Rogers, A. et al. Critical Habitats and Biodiversity: Inventory, Thresholds and Governance. Sci. Rep. 10, 548 (World Resources Institute, 2020).
Sala, E. et al. Protecting the global ocean for biodiversity, food and climate. Nature 592, 397–402 (2021).
Halpern, B. S. et al. Spatial and temporal changes in cumulative human impacts on the world’s ocean. Nat. Commun. 6, 7615 (2015).
Pontavice, H., Gascuel, D., Reygondeau, G., Stock, C. & Cheung, W. W. L. Climate‐induced decrease in biomass flow in marine food webs may severely affect predators and ecosystem production. Glob. Change Biol. 27, 2608–2622 (2021).
Estes, J. A., Heithaus, M., McCauley, D. J., Rasher, D. B. & Worm, B. Megafaunal impacts on structure and function of ocean ecosystems. Annu. Rev. Environ. Res. 41, 83–116 (2016).
Jenkins, C. N., Pimm, S. L. & Joppa, L. N. Global patterns of terrestrial vertebrate diversity and conservation. Proc. Natl Acad. Sci. USA 110, E2602–E2610 (2013).
Moilanen, A., Kujala, H. & Mikkonen, N. A practical method for evaluating spatial biodiversity offset scenarios based on spatial conservation prioritization outputs. Methods Ecol. Evol. 11, 794–803 (2020).
Ceballos, G. & Ehrlich, P. R. Global mammal distributions, biodiversity hotspots, and conservation. Proc. Natl Acad. Sci. USA 103, 19374–19379 (2006).
Williams, P. H., Gaston, K. J. & Humphries, C. J. Mapping biodiversity value worldwide: combining higher-taxon richness from different groups. Proc. R. Soc. Lond. B 264, 141–148 (1997).
Blanchard, J. L. et al. Linked sustainability challenges and trade-offs among fisheries, aquaculture and agriculture. Nat. Ecol. Evol. 1, 1240–1249 (2017).
Robiou Du Pont, Y. et al. Equitable mitigation to achieve the Paris Agreement goals. Nat. Clim. Change 7, 38–43 (2017).
Payne, N. L. et al. Fish heating tolerance scales similarly across individual physiology and populations. Commun. Biol. 4, 264 (2021).
First Draft of the Post-2020 Global Biodiversity Framework (Convention on Biological Diversity, 2021).
Keppel, G. et al. Refugia: identifying and understanding safe havens for biodiversity under climate change. Glob. Ecol. Biogeogr. 21, 393–404 (2012).
Bryndum‐Buchholz, A., Tittensor, D. P. & Lotze, H. K. The status of climate change adaptation in fisheries management: policy, legislation and implementation. Fish Fish. https://doi.org/10.1111/faf.12586 (2021).
Maureaud, A. et al. 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 (2021).
Boyce, D. G. et al. Operationalizing climate risk for fisheries in a global warming hotspot. Preprint at: https://doi.org/10.1101/2022.07.19.500650 (2022).
Estes, J. A. et al. Trophic downgrading of planet Earth. Science 333, 301–306 (2011).
Olden, J. D., Hogan, Z. S. & Vander Zanden, M. J. Small fish, big fish, red fish, blue fish: size-biased extinction risk of the world’s freshwater and marine fishes. Glob. Ecol. Biogeogr. 16, 694–701 (2007).
Tittensor, D. P. et al. A mid-term analysis of progress toward international biodiversity targets. Science 346, 241–244 (2014).
Pinsky, M. L., Eikeset, A. M., McCauley, D. J., Payne, J. L. & Sunday, J. M. Greater vulnerability to warming of marine versus terrestrial ectotherms. Nature https://doi.org/10.1038/s41586-019-1132-4 (2019).
Sunday, J. M., Bates, A. E. & Dulvy, N. K. Thermal tolerance and the global redistribution of animals. Nat. Clim. Change 2, 686–690 (2012).
Laidre, K. L. et al. Quantifying the sensitivity of Arctic marine mammals to climate-induced habitat change. Ecol. Appl. 18, S97–S125 (2008).
Rosset, V. & Oertli, B. Freshwater biodiversity under climate warming pressure: identifying the winners and losers in temperate standing waterbodies. Biol. Conserv. 144, 2311–2319 (2011).
Peters, R. L. The greenhouse effect and nature reserves. Biosciences 35, 707–717 (1985).
Garcia, R. A. et al. Matching species traits to projected threats and opportunities from climate change. J. Biogeogr. 41, 724–735 (2014).
IUCN Red List Categories and Criteria: Version 3.1 (IUCN, 2012).
Worm, B. et al. Impacts of biodiversity loss on ocean ecosystem services. Science 314, 787–790 (2006).
Worm, B., Lotze, H. K., Hillebrand, H. & Sommer, U. Consumer versus resource control of species diversity and ecosystem functioning. Nature 417, 848–851 (2002).
Worm, B. & Duffy, J. E. Biodiversity, productivity, and stability in real food webs. Trends Ecol. Evol. 18, 628–632 (2003).
Halpern, B. S. et al. A global map of human impact on marine ecosystems. Science 319, 948–952 (2008).
Ottersen, G., Hjermann, D. O. & Stenseth, N. C. Changes in spawning stock structure strengthen the link between climate and recruitment in a heavily fished cod (Gadus morhua) stock. Fish. Oceanogr. 15, 230–243 (2006).
Le Bris, A. et al. Climate vulnerability and resilience in the most valuable North American fishery. Proc. Natl Acad. Sci. USA 115, 1831–1836 (2018).
Henson, S. A. et al. Rapid emergence of climate change in environmental drivers of marine ecosystems. Nat. Commun. 8, 14682 (2017).
Bates, A. E. et al. Climate resilience in marine protected areas and the ‘Protection Paradox’. Biol. Conserv. 236, 305–314 (2019).
Xu, C., Kohler, T. A., Lenton, T. M., Svenning, J.-C. & Scheffer, M. Future of the human climate niche. Proc. Natl Acad. Sci. USA 117, 11350–11355 (2020).
Davies, T. E., Maxwell, S. M., Kaschner, K., Garilao, C. & Ban, N. C. Large marine protected areas represent biodiversity now and under climate change. Sci. Rep. 7, 9569 (2017).
MacKenzie, B. R. et al. A cascade of warming impacts brings bluefin tuna to Greenland waters. Glob. Change Biol. 20, 2484–2491 (2014).
Shackell, N. L., Ricard, D. & Stortini, C. Thermal habitat index of many Northwest Atlantic temperate species stays neutral under warming projected for 2030 but changes radically by 2060. PLoS ONE 9 (2014).
Boyce, D. G., Frank, K. T., Worm, B. & Leggett, W. C. Spatial patterns and predictors of trophic control across marine ecosystems. Ecol. Lett. 18, 1001–1011 (2015).
Boyce, D. G., Frank, K. T. & Leggett, W. C. From mice to elephants: overturning the ‘one size fits all’ paradigm in marine plankton food chains. Ecol. Lett. 18, 504–515 (2015).
Frank, K. T., Petrie, B., Shackell, N. L. & Choi, J. S. Reconciling differences in trophic control in mid-latitude marine ecosystems. Ecol. Lett. 9, 1096–1105 (2006).
Frank, K. T., Petrie, B. & Shackell, N. L. The ups and downs of trophic control in continental shelf ecosystems. Trends Ecol. Evol. 22, 236–242 (2007).
Loarie, S. R. et al. The velocity of climate change. Nature 462, 1052–1056 (2009).
Burrows, M. T. et al. The pace of shifting climate in marine and terrestrial ecosystems. Science 334, 652–655 (2011).
Mora, C. et al. The projected timing of climate departure from recent variability. Nature 502, 183–187 (2013).
Poloczanska, E. S. et al. Responses of marine organisms to climate change across oceans. Front. Mar. Sci. 3, 62 (2016).
Boyce, D. G., Lewis, M. L. & Worm, B. Global phytoplankton decline over the past century. Nature 466, 591–596 (2010).
Burek, K. A., Gulland, F. M. D. & O’Hara, T. M. Effects of climate change on Arctic marine mammal health. Ecol. Appl. 18, S126–S134 (2008).
Staude, I. R., Navarro, L. M. & Pereira, H. M. Range size predicts the risk of local extinction from habitat loss. Glob. Ecol. Biogeogr. 29, 16–25 (2020).
Moore, S. E. & Huntington, H. P. Arctic marine mammals and climate change: impacts and resilience. Ecol. Appl. 18, S157–S165 (2008).
Kaschner, K., Watson, R., Trites, A. & Pauly, D. Mapping world-wide distributions of marine mammal species using a relative environmental suitability (RES) model. Mar. Ecol. Prog. Ser. 316, 285–310 (2006).
Gonzalez-Suarez, M., Gomez, A. & Revilla, E. Which intrinsic traits predict vulnerability to extinction depends on the actual threatening processes. Ecosphere 4, 6 (2013).
Rogan, J. E. & Lacher, T. E. in Reference Module in Earth Systems and Environmental Sciences (Elsevier, 2018); https://doi.org/10.1016/B978-0-12-409548-9.10913-3
Warren, M. S. et al. Rapid responses of British butterflies to opposing forces of climate and habitat change. Nature 414, 65–69 (2001).
Chessman, B. C. Identifying species at risk from climate change: traits predict the drought vulnerability of freshwater fishes. Biol. Conserv. 160, 40–49 (2013).
Davidson, A. D. D. et al. Drivers and hotspots of extinction risk in marine mammals. Proc. Natl Acad. Sci. USA 109, 3395–3400 (2012).
Cheung, W. W. L., Pauly, D. & Sarmiento, J. L. How to make progress in projecting climate change impacts. ICES J. Mar. Sci. 70, 1069–1074 (2013).
Fenchel, T. Intrinsic rate of natural increase: the relationship with body size. Oecologia 14, 317–326 (1974).
Healy, K. et al. Ecology and mode-of-life explain lifespan variation in birds and mammals. Proc. R. Soc. B 281, 20140298 (2014).
Carilli, J., Donner, S. D. & Hartmann, A. C. Historical temperature variability affects coral response to heat stress. PLoS ONE 7, e34418 (2012).
Guest, J. R. et al. Contrasting patterns of coral bleaching susceptibility in 2010 suggest an adaptive response to thermal stress. PLoS ONE 7, e33353 (2012).
Donner, S. D. & Carilli, J. Resilience of Central Pacific reefs subject to frequent heat stress and human disturbance. Sci. Rep. 9, 3484 (2019).
Rehm, E. M., Olivas, P., Stroud, J. & Feeley, K. J. Losing your edge: climate change and the conservation value of range‐edge populations. Ecol. Evol. 5, 4315–4326 (2015).
Ready, J. et al. Predicting the distributions of marine organisms at the global scale. Ecol. Modell. 221, 467–478 (2010).
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. Modell. 225, 133–145 (2012).
Froese, R. & Pauly, D. FishBase v.02/2022 www.fishbase.org (2022).
Palomares, M. L. D. & Pauly, D. SeaLifeBase v.11/2014 www.sealifebase.org (2022).
van Buuren, S. Flexible Imputation of Missing Data (Chapman & Hall/CRC, 2012).
Dahlke, F. T., Wohlrab, S., Butzin, M. & Portner, H.-O. Thermal bottlenecks in the life cycle define climate vulnerability of fish. Science 369, 65–70 (2020).
Stortini, C. H., Shackell, N. L., Tyedmers, P. & Beazley, K. Assessing marine species vulnerability to projected warming on the Scotian Shelf, Canada. ICES J. Mar. Sci. 72, 1713–1743 (2015).
Reynolds, R. W. et al. Daily high-resolution-blended analyses for sea surface temperature. J. Clim. 20, 5473–5496 (2007).
Meinshausen, M. et al. The shared socio-economic pathway (SSP) greenhouse gas concentrations and their extensions to 2500. Geosci. Model Dev. 13, 3571–3605 (2020).
Samhouri, J. F. et al. Sea sick? Setting targets to assess ocean health and ecosystem services. Ecosphere 3, art41 (2012).
Rao, T. R. A curve for all reasons. Resonance 5, 85–90 (2000).
Mora, C. et al. Biotic and human vulnerability to projected changes in ocean biogeochemistry over the 21st century. PLoS Biol. 11, 10 (2013).
Lotze, H. K. et al. Ensemble projections of global ocean animal biomass with climate change. Proc. Natl Acad. Sci. USA https://doi.org/10.1073/pnas.1900194116 (2019).
Eyring, V. et al. Taking climate model evaluation to the next level. Nat. Clim. Change 9, 102–110 (2019).
Oppenheimer, M., Little, C. M. & Cooke, R. M. Expert judgement and uncertainty quantification for climate change. Nat. Clim. Change 6, 445–451 (2016).
Budescu, D. V., Por, H. H. & Broomell, S. B. Effective communication of uncertainty in the IPCC reports. Climatic Change 113, 181–200 (2012).
Swart, R., Bernstein, L., Ha-Duong, M. & Petersen, A. Agreeing to disagree: uncertainty management in assessing climate change, impacts and responses by the IPCC. Climatic Change 92, 1–29 (2009).
NAFO Annual Fisheries Statistics Database (NAFO, 2021).
Horton, T. et al. World Register of Marine Species (WoRMS) https://www.marinespecies.org (2020).
Total Wealth per Capita, 1995 to 2014 (World Bank, 2022); https://ourworldindata.org/grapher/total-wealth-per-capita
Depth of the Food Deficit in Kilocalories per Person per Day, 1992 to 2016 (World Bank, 2022); https://ourworldindata.org/grapher/depth-of-the-food-deficit
Boyce, D. G. et al. A climate risk index for marine life. Dryad https://doi.org/10.5061/dryad.7wm37pvwr (2022).
R Core Team R: A Language and Environment for Statistical Computing Version 4.0.4 (R Foundation for Statistical Computing, 2021).
Acknowledgements
Financial support to D.G.B. was provided by the Ocean Frontier Institute (Module G) and Oceans North. D.P.T. acknowledges support from the Jarislowsky Foundation and NSERC. S.H. acknowledges support from the National Environmental Research Council (grant no. NE/R015953/1) and from the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement no. 820989 (COMFORT). This research was enabled in part by support provided by ACENET (www.ace-net.ca) and Compute Canada (www.computecanada.ca).
Author information
Authors and Affiliations
Contributions
D.G.B. conceived and designed the study with input from B.W., D.P.T. and N.L.S. C.G., S.H., K.K., K.K.-R., R.B.R. and P.S.-Y. provided the data. D.G.B. wrote the computer code with input from A.P. D.G.B. conducted the analyses. D.G.B., B.W. and D.P.T. drafted the manuscript. All authors reviewed the methods and edited subsequent drafts.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Peer review
Peer review information
Nature Climate Change thanks Joseph Maina and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data
Extended Data Fig. 1 Data availability.
a) The pie chart displays the proportion of assessed species across kingdoms. Colours show the numbers of species within each animal phylum and shading within the bars shows the number of species in each taxonomic class. b) Spatial distribution in the number of assessed species. Colours depict the number of species assessed per 1 × 1° cell. The gray shaded area in the right margin shows the total number of species assessed along latitude. The red line and axis are the average species richness of all marine taxa by latitude reported in Tittensor et al.180.
Extended Data Fig. 2 General overview of the steps in estimating the climate vulnerability and risk for species and ecosystems.
Thick arrow and numbers denote the sequence of analyses used to estimate climate risk from the input data layers. Red depicts the sensitivity and quality-control analyses that were completed.
Extended Data Fig. 3 Correlations between climate indices used to calculate climate vulnerability and risk.
Colours and numbers are the correlations between climate indices calculated for each species. Colour shading and text are the direction and strength of the relationships: red are positive and blue negative correlations.
Supplementary information
Supplementary Information
Supplementary Figs. 1–58, Tables 1–4 and Discussion.
Rights and permissions
About this article
Cite this article
Boyce, D.G., Tittensor, D.P., Garilao, C. et al. A climate risk index for marine life. Nat. Clim. Chang. 12, 854–862 (2022). https://doi.org/10.1038/s41558-022-01437-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41558-022-01437-y
This article is cited by
-
Thermal vulnerability of sea turtle foraging grounds around the globe
Communications Biology (2024)
-
Targeting ocean conservation outcomes through threat reduction
npj Ocean Sustainability (2024)
-
A stakeholder-guided marine heatwave hazard index for fisheries and aquaculture
Climatic Change (2024)
-
Multiple dimensions of extreme weather events and their impacts on biodiversity
Climatic Change (2023)