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Strategic planning could reduce farm-scale mariculture impacts on marine biodiversity while expanding seafood production

Nature Ecology & Evolution volume 9, pages 565–575 (2025)Cite this article

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Abstract

Mariculture is one of the fastest growing global markets. Although it has potential to improve livelihoods and facilitate economic growth, it can negatively impact marine biodiversity. Here we estimate local cumulative environmental impacts from current and future (2050) mariculture production on marine biodiversity (20,013 marine fauna), while accounting for species range shifts under climate change. With strategic planning, the 1.82-fold increase in finfish and 2.36-fold increase in bivalve production needed to meet expected global mariculture demand in 2050 could be achieved with up to a 30.5% decrease in cumulative impact to global marine biodiversity. This is because all future mariculture farms are strategically placed in sea areas with the lowest cumulative impact. Our results reveal where and how much mariculture impacts could change in the coming decades and identify pathways for countries to minimize risks under expansion of mariculture and climate change through strategic planning.

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Fig. 1: Distribution of CIM on marine biodiversity in 2020.
Fig. 2: Changes in nitrogen and phosphorus emissions and CIM between 2020 and 2050.
Fig. 3: Global distribution of CIM in 2050 under the best-case and worst-case scenarios.
Fig. 4: Changes in impacts of mariculture by taxonomic groups between 2020 and 2050.
Fig. 5: Relationship between changes in CIM and changes in factors including total mariculture production and marine species richness for each country.

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Data availability

Data on the distribution of current mariculture farms were obtained from ref. 24. Data on the distribution of potential mariculture areas in 2050 were obtained from ref. 6. Data on the current and future distributions of marine species were obtained from AquaMaps23. Species vulnerability data were obtained from ref. 22. Source data are provided with this paper.

Code availability

The code used to conduct the analysis are archived via Figshare at https://doi.org/10.6084/m9.figshare.27132759 (ref. 58).

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Acknowledgements

We thank J. A. Gephart for providing raw data on greenhouse gas, nitrogen and phosphorus emissions per farm. We also thank J. Ruesink for providing comments on mariculture pressures. We acknowledge financial support from University of Michigan’s School for Environment and Sustainability and Institute for Global Change Biology. B.S.H. and M.F. were supported by funding from the National Science Foundation (Federal Award Number (FAIN) 2019902). J.G.M was supported by funding from the Japan Science and Technology Agency (JST SICORP grant JPMJSC20E5).

Author information

Authors and Affiliations

  1. Institute for Global Change Biology, School for Environment and Sustainability, University of Michigan, Ann Arbor, MI, USA

    Deqiang Ma, Brian C. Weeks & Neil H. Carter

  2. Bren School of Environmental Science and Management, University of California, Santa Barbara, CA, USA

    Benjamin S. Halpern

  3. National Center for Ecological Analysis and Synthesis, University of California, Santa Barbara, CA, USA

    Benjamin S. Halpern & Melanie Frazier

  4. Department of Biology, Center for Ecosystem Sentinels, University of Washington, Seattle, WA, USA

    Briana Abrahms

  5. Institute for Global Change Biology, Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI, USA

    Jacob Allgeier

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

    Jorge García Molinos

  7. Marine Science Institute, Bren School of Environmental Science and Management, University of California, Santa Barbara, CA, USA

    Christopher M. Free

  8. Department of Biometry and Environmental System Analysis, University of Freiburg, Freiburg, Germany

    Kristin Kaschner

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  1. Deqiang Ma
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Contributions

D.M., B.S.H. and N.H.C. conceived this study. D.M., B.S.H., C.M.F., J.G.M., M.F. designed the methods, with input from B.A., J.A., B.C.W. and N.H.C. D.M. collected data, performed the analysis and drafted the initial manuscript. D.M., B.S.H., B.A., J.A., J.G.M., C.M.F., B.C.W., M.F., K.K. and N.H.C. edited the manuscript. N.H.C., B.A., J.A. and B.C.W. acquired the funding.

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Correspondence to Deqiang Ma.

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Extended data

Extended Data Fig. 1 Distribution of changes in CIM between the best-case and worst-case scenarios and each randomized mariculture scenario.

(a and b): RCP 8.5 scenario; (c and d): RCP 4.5 scenario.

Source data

Extended Data Fig. 2 Global distribution of CIM in 2050 under the best-case and worst-case scenarios under RCP 4.5.

(a) best-case scenario estimated at the global scale, (b) worst-case scenario estimated at the global scale, (c) best-case scenario estimated at the country level, (d) worst-case scenario estimated at the country level. The distribution of CIM was divided into five categories using quintiles.

Extended Data Fig. 3 Global distribution of CIM per unit farm across all potential mariculture areas in 2050 under RCP 8.5.

(a) general marine fish. (b) Salmonidae fish. (c) bivalve. The distribution of CIM per unit farm was divided into five categories using quintiles.

Extended Data Fig. 4 Global distribution of CIM per unit farm across all potential mariculture areas in 2050 under RCP 4.5.

(a) general marine fish. (b) Salmonidae fish. (c) bivalve. The distribution of CIM per unit farm was divided into five categories using quintiles.

Supplementary information

Supplementary Information

Supplementary results under RCP 4.5 climate scenario, results of sensitivity analyses, Supplementary Figs. 1–10 and Supplementary Tables 1–10.

Reporting Summary

Source data

Source Data Fig. 5

Statistical source data.

Source Data Extended Data Fig. 1

Statistical source data.

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Ma, D., Halpern, B.S., Abrahms, B. et al. Strategic planning could reduce farm-scale mariculture impacts on marine biodiversity while expanding seafood production. Nat Ecol Evol 9, 565–575 (2025). https://doi.org/10.1038/s41559-025-02650-6

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