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Towards climate-smart, three-dimensional protected areas for biodiversity conservation in the high seas

Nature Climate Change volume 12, pages 402–407 (2022)Cite this article

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Abstract

Marine species are moving rapidly in response to warming, often in different directions and with variations dependent on location and depth. Given the current impetus to increase the area of protected ocean to 30%, conservation planning must include the 64% of the ocean beyond national jurisdictions, which in turn requires associated design challenges for conventional conservation to be addressed. Here we present a planning approach for the high seas that conserves biodiversity, minimizes exposure to climate change, retains species within reserve boundaries and reduces conflict with fishing. This is developed using data from across four depth domains, considering 12,932 vertebrate, invertebrate and algal species and three climate scenarios. The resultant climate-smart conservation areas cover 6% of the high seas and represent a low-regret option that provides a nucleus for developing a full network of high-seas marine reserves.

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Fig. 1: The degree of agreement between the climate-smart MPA networks for different planning domains and climate scenarios.
Fig. 2: Climate-smart networks in the high seas.
Fig. 3: Low-regret climate-smart networks in the high seas.

Data availability

The data used in this study (except the AquaMaps biodiversity and geomorphic features data) are available at Zenodo95 under the identifier https://doi.org/10.5281/zenodo.5912047. The AquaMaps77 data are freely available via www.aquamaps.org. The geomorphic features78 data are freely available via www.bluehabitats.org.

Code availability

All the scripts are available at Zenodo95 under the identifier https://doi.org/10.5281/zenodo.5912047.

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Acknowledgements

I.B.-M. was supported by the Advanced Human Capital Program of the Chilean National Research and Development Agency (ANID Grant No. 72170231). C.J.K. was supported by an ARC Future Fellowship (no. FT200100314). J.D.E. was funded by Australian Research Council Discovery Project No. DP19010229. We thank K. Kaschner, C. Garilao and K. Kesner-Reyes for providing the AquaMaps marine biodiversity data.

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Authors and Affiliations

  1. School of Earth and Environmental Sciences, The University of Queensland, St Lucia, Queensland, Australia

    Isaac Brito-Morales, Carissa J. Klein, Daniel C. Dunn, Kristine Camille V. Buenafe & Rosa Mar Dominguez

  2. Queensland Biosciences Precinct (QBP), Commonwealth Scientific and Industrial Research Organisation (CSIRO) Oceans and Atmosphere, St Lucia, Queensland, Australia

    Isaac Brito-Morales, Jason D. Everett & Anthony J. Richardson

  3. School of Mathematics and Physics, The University of Queensland, St Lucia, Queensland, Australia

    Isaac Brito-Morales, Jason D. Everett, Kristine Camille V. Buenafe & Anthony J. Richardson

  4. Betty and Gordon Moore Center for Science, Conservation International, Arlington, VA, USA

    Isaac Brito-Morales

  5. Global-Change Ecology Research Group, School of Science, Technology and Engineering, University of the Sunshine Coast, Maroochydore, Queensland, Australia

    David S. Schoeman

  6. Centre for African Conservation Ecology, Department of Zoology, Nelson Mandela University, Gqeberha, South Africa

    David S. Schoeman

  7. Centre for Marine Science and Innovation (CMSI), The University of New South Wales, Sydney, New South Wales, Australia

    Jason D. Everett

  8. Centre for Biodiversity and Conservation Science (CBCS), The University of Queensland, St Lucia, Queensland, Australia

    Carissa J. Klein, Daniel C. Dunn, Rosa Mar Dominguez & Hugh P. Possingham

  9. Arctic Research Center, Hokkaido University, Sapporo, Japan

    Jorge García Molinos

  10. Global Station for Arctic Research, Global Institution for Collaborative Research and Education, Hokkaido University, Sapporo, Japan

    Jorge García Molinos

  11. Graduate School of Environmental Science, Hokkaido University, Sapporo, Japan

    Jorge García Molinos

  12. Scottish Association for Marine Science, Oban, UK

    Michael T. Burrows

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Contributions

I.B.-M., D.S.S. and A.J.R. conceived the research. J.D.E. generated the fishing cost layer. I.B.-M. analysed the data. I.B.-M. wrote the first draft with input from D.S.S., A.J.R., C.J.K. and D.C.D. I.B.-M., D.S.S., A.J.R., C.J.K., D.C.D., J.D.E., J.G.M., M.T.B., K.C.V.B., R.M.D. and H.P.P. contributed equally to the discussion of ideas and analyses, and all authors commented on the manuscript.

Corresponding author

Correspondence to Isaac Brito-Morales.

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The authors declare no competing interests.

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Nature Climate Change thanks Rafael Magris, Derek Tittensor and Qianshuo Zhao for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Map of monetary value of fishing and biodiversity in the high seas.

Opportunity cost of fishing (a, b, c, d) and species richness (number of species) with a probability of occurrence > 0.5 (d, e, f, g) in the high seas at four depth domains. Polygons represent Longhurst provinces for the epipelagic domain (a, e), Glasgow provinces for the mesopelagic (b, f) and bathyabyssopelagic domains (c, g), and the GOOD provinces for seafloor domain (d, h).

Extended Data Fig. 2 Geomorphic conservation features in the seafloor domain78.

For each map, green hexagons indicate the presence of each geomorphic feature in each planning unit. Polygons represent the GOODS provinces87.

Extended Data Fig. 3 Prioritised climate-smart networks in the high seas.

Prioritised networks for the high seas at three pelagic depth domains and the seafloor, under three IPCC Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5 and SSP5-8.5). For each map, green hexagons represent selected planning units while light blue hexagons represent non-selected planning units. Polygons in each map represent Longhurst provinces for the epipelagic domain (a, b, c), Glasgow provinces for the mesopelagic (d, e, f) and bathyabyssopelagic (g, h, i) domains, and the GOODS provinces for seafloor domain (j, k, l).

Extended Data Fig. 4 The relationship between climate-smart networks with and without the cost layer.

Total Opportunity cost among the prioritised base scenario (that is, no cost) and the climate-smart prioritisation scenarios under three IPCC emission pathways (SSP1-2.6, SSP2-4.5 and SSP5-8.5).

Extended Data Fig. 5 Prioritised climate-smart networks in the high seas for the base scenario.

Prioritised networks for a base scenario (that is, no cost) for the high seas at three pelagic depth domains and the seafloor, under three IPCC Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5 and SSP5-8.5). For each map, green hexagons represent selected planning units while light blue hexagons represent non-selected planning units. Polygons in each map represent Longhurst provinces for the epipelagic domain (a, b, c), Glasgow provinces for the mesopelagic (d, e, f) and bathyabyssopelagic (g, h, i) domains, and the GOODS provinces for seafloor domain (j, k, l).

Extended Data Fig. 6 Biodiversity representation for climate-smart networks in the high seas.

Average taxonomic group representation (%) in low-regret conservation areas for three pelagic depth domains and the seafloor (a), and throughout the water column for the pelagic domains and pelagic plus the seafloor domain under three IPCC Shared Socioeconomic Pathways: SSP1-2.6, SSP2-4.5, and SSP5-8.5.

Extended Data Fig. 7 Climate velocity in the high seas.

Climate velocity (km decade−1) in the high seas for projected sea temperatures (2050–2100) at three pelagic depth domains and the seafloor, under three IPCC Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5 and SSP5-8.5). Polygons in each map represent Longhurst provinces for the epipelagic domain (a, b, c), Glasgow provinces for the mesopelagic (d, e, f) and bathyabyssopelagic (g, h, i) domains, and the GOODS provinces for the seafloor domain (j, k, l).

Extended Data Fig. 8 Relative Climate Exposure (RCE) index in the high seas.

RCE index (years) in the high seas for projected sea temperatures (2050–2100) at three pelagic depth domains and the seafloor, under three IPCC Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5 and SSP5-8.5). Polygons in each map represent Longhurst provinces for the epipelagic domain (a, b, c), Glasgow provinces for the mesopelagic (d, e, f) and bathyabyssopelagic (g, h, i) domains, and the GOODS provinces for the seafloor domain (j, k, l).

Extended Data Fig. 9 The degree of agreement between the climate-smart MPA networks for different sets of conservation targets.

The Kappa index for the relationship between each prioritised climate-smart network MPA for different area-based protection targets under four depth domains: Epipelagic, Mesopelagic, Bathyabyssopelagic and the Seafloor. The percentages represent the minimum and maximum targets of protection in each prioritisation analysis.

Extended Data Fig. 10 Process for setting climate-smart conservation targets.

Schematic representation for setting targets for conservation features in the climate-smart prioritisation planning approach.

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Brito-Morales, I., Schoeman, D.S., Everett, J.D. et al. Towards climate-smart, three-dimensional protected areas for biodiversity conservation in the high seas. Nat. Clim. Chang. 12, 402–407 (2022). https://doi.org/10.1038/s41558-022-01323-7

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