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The role of high-biodiversity regions in preserving Nature’s Contributions to People

Nature Sustainability volume 6, pages 1385–1393 (2023)Cite this article

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Abstract

Increasing human pressures are driving a global loss of biodiversity and of Nature’s Contributions to People (NCP)—the contributions of living nature to people’s quality of life. Understanding the spatial relationship between biodiversity and NCP is essential for securing Earth’s life support systems. Here we estimate the importance of high-biodiversity regions in maintaining the provision of three NCP under four scenarios of climate change. We focus on critical regulatory NCP which are currently facing decline: regulation of air quality, climate and freshwater quantity. We estimate the current and future value of NCP using a suite of environmental indicators and evaluate whether risk from environmental change is higher or lower within high-biodiversity regions compared with control regions. We find higher levels of NCP within high-biodiversity regions both in the present and the future for all indicators, which highlights the spatial congruence between biodiversity and NCP. Moreover, air quality and climate regulation indicators show rapidly increasing levels within high-biodiversity regions, especially under higher-emission scenarios. Our results point to a substantial contribution of high-biodiversity areas to the provision of NCP. Protecting areas of high biodiversity value will synergistically contribute to the preservation of many of nature’s contributions humanity depends on.

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Fig. 1: Projections of change in the value of NCP at 10 km resolution between the baseline period 1985–2014 and the future 2041–2070 under scenario SSP5–8.5.
Fig. 2: Barplots of the mean global levels of three NCP in the baseline period and under different future scenarios.

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Data availability

All input data used in these analyses were obtained from published sources cited in Methods. The CMIP6 datasets analysed during the current study are available from https://esgf-node.llnl.gov/search/cmip6/, while WorldClim data are available from https://www.worldclim.org/data/index.html. We retrieved land-use data from the LUH2 dataset33 available at http://luh.umd.edu/data.shtml, while land-cover data were dowloaded from the ESA CCI Land Cover (CCI-LC) project (https://www.esa-landcover-cci.org/). The maps of high-biodiversity regions refer to the map of scientific consensus score from ref. 25 and are available on Zenodo at https://doi.org/10.5281/zenodo.8036779.

Code availability

Codes and datasets used for the analyses are openly available on Zenodo at https://doi.org/10.5281/zenodo.7351590.

References

  1. First Draft of the Post-2020 Global Biodiversity Framework (Convention on Biological Diversity, 2021).

  2. Chaplin-Kramer, R. et al. Mapping the planet’s critical natural assets. Nat. Ecol. Evol. 7, 1–11 (2022).

    Article  Google Scholar 

  3. Jung, M. et al. Areas of global importance for conserving terrestrial biodiversity, carbon and water. Nat. Ecol. Evol. 5, 1499–1509 (2021).

    Article  Google Scholar 

  4. Pereira, H. M. et al. Global trends in biodiversity and ecosystem services from 1900 to 2050. Preprint at bioRxiv https://doi.org/10.1101/2020.04.14.031716 (2020).

  5. Di Marco, M. et al. Synergies and trade-offs in achieving global biodiversity targets. Conserv. Biol. 30, 189–195 (2016).

    Article  Google Scholar 

  6. Loarie, S. R. et al. The velocity of climate change. Nature 462, 1052–1055 (2009).

    Article  CAS  Google Scholar 

  7. Ecosystems and Human Well-being: Health Synthesis (WHO, 2005).

  8. Costanza, R. et al. The value of the world’s ecosystem services and natural capital. Nature 387, 253–260 (1997).

    Article  CAS  Google Scholar 

  9. Díaz, S. et al. Assessing nature’s contributions to people. Science 359, 270–272 (2018).

    Article  Google Scholar 

  10. Brauman, K. A. et al. Global trends in nature’s contributions to people. Proc. Natl Acad. Sci. USA 117, 32799–32805 (2020).

    Article  CAS  Google Scholar 

  11. Díaz, S. et al. (eds) Summary for Policymakers of the Global Assessment Report on Biodiversity and Ecosystem Services (IPBES, 2019).

  12. Balvanera, P. et al. Linking biodiversity and ecosystem services: current uncertainties and the necessary next steps. Bioscience 64, 49–57 (2014).

    Article  Google Scholar 

  13. Hooper, D. U. et al.Effects of biodiversity on ecosystem functioning: a consensus of current knowledge. Ecol. Monogr. 75, 3–35 (2005).

    Article  Google Scholar 

  14. Le Provost, G. et al. The supply of multiple ecosystem services requires biodiversity across spatial scales. Nat. Ecol. Evol. https://doi.org/10.1038/s41559-022-01918-5 (2022).

  15. Cardinale, B. J. et al. Biodiversity loss and its impact on humanity. Nature 486, 59–67 (2012).

    Article  CAS  Google Scholar 

  16. Balvanera, P. et al. Quantifying the evidence for biodiversity effects on ecosystem functioning and services. Ecol. Lett. 9, 1146–1156 (2006).

    Article  Google Scholar 

  17. Cardinale, B. J. et al. The functional role of producer diversity in ecosystems. Am. J. Bot. 98, 572–592 (2011).

    Article  Google Scholar 

  18. Scheffers, B. R. et al. The broad footprint of climate change from genes to biomes to people. Science 354, aaf7671 (2016).

    Article  Google Scholar 

  19. Di Marco, M. et al. Projecting impacts of global climate and land-use scenarios on plant biodiversity using compositional-turnover modelling. Glob. Change Biol. 25, 2763–2778 (2019).

    Article  Google Scholar 

  20. Newbold, T. Future effects of climate and land-use change on terrestrial vertebrate community diversity under different scenarios. Proc. R. Soc. B 285, 20180792 (2018).

    Article  Google Scholar 

  21. Chaplin-Kramer, R. et al. Global modeling of nature’s contributions to people. Science 366, 255–258 (2019).

    Article  CAS  Google Scholar 

  22. O’Connor, L. M. J. et al. Balancing conservation priorities for nature and for people in Europe. Science 372, 856–860 (2021).

    Article  Google Scholar 

  23. Soto-Navarro, C. et al. Mapping co-benefits for carbon storage and biodiversity to inform conservation policy and action. Phil. Trans. R. Soc. B. 375, 20190128 (2020).

    Article  CAS  Google Scholar 

  24. Smith, A. C. et al. How natural capital delivers ecosystem services: a typology derived from a systematic review. Ecosyst. Serv. 26, 111–126 (2017).

    Article  Google Scholar 

  25. Cimatti, M., Brooks, T. M. & Di Marco, M. Identifying science-policy consensus regions of high biodiversity value and institutional recognition. Glob. Ecol. Conserv. 32, e01938 (2021).

    Google Scholar 

  26. O’Neill, B. C. et al. The roads ahead: narratives for shared socioeconomic pathways describing world futures in the 21st century. Glob. Environ. Change 42, 169–180 (2017).

    Article  Google Scholar 

  27. Zhu, Z. et al. Global data sets of vegetation leaf area index (LAI)3g and fraction of photosynthetically active radiation (FPAR)3g derived from global inventory modeling and mapping studies (GIMMS) normalized difference vegetation index (NDVI3g) for the period 1981 to 2011. Remote Sens. 5, 927–948 (2013).

    Article  Google Scholar 

  28. Isbell, F. et al. Linking the influence and dependence of people on biodiversity across scales. Nature 546, 65–72 (2017).

    Article  CAS  Google Scholar 

  29. Chaplin-Kramer, R. et al. Mapping the planet’s critical natural assets. Nat. Ecol. Evol. 7, 51–61 (2023).

  30. Friend, A. D. et al. Carbon residence time dominates uncertainty in terrestrial vegetation responses to future climate and atmospheric CO2. Proc. Natl Acad. Sci. USA 111, 3280–3285 (2014).

    Article  CAS  Google Scholar 

  31. Pugh, T. A. M. et al. Understanding the uncertainty in global forest carbon turnover. Biogeosciences 17, 3961–3989 (2020).

    Article  CAS  Google Scholar 

  32. Shao, P., Zeng, X., Sakaguchi, K., Monson, R. K. & Zeng, X. Terrestrial carbon cycle: climate relations in eight CMIP5 Earth system models. J. Clim. 26, 8744–8764 (2013).

    Article  Google Scholar 

  33. Hurtt, G. et al. Harmonization of global land-use change and management for the period 850–2100 (LUH2) for CMIP6. Geosci. Model Dev. https://doi.org/10.5194/gmd-2019-360 (2020).

  34. Runde, I., Zobel, Z. & Schwalm, C. Human and natural resource exposure to extreme drought at 1.0 °C–4.0 °C warming levels. Environ. Res. Lett. 17, 064005 (2022).

    Article  Google Scholar 

  35. Feng, X. et al. How deregulation, drought and increasing fire impact Amazonian biodiversity. Nature 597, 516–521 (2021).

    Article  CAS  Google Scholar 

  36. Keys, P. W., Wang-Erlandsson, L. & Gordon, L. J. Revealing invisible water: moisture recycling as an ecosystem service. PLoS ONE 11, e0151993 (2016).

    Article  Google Scholar 

  37. Di Marco, M., Watson, J. E. M., Currie, D. J., Possingham, H. P. & Venter, O. The extent and predictability of the biodiversity–carbon correlation. Ecol. Lett. 21, 365–375 (2018).

    Article  Google Scholar 

  38. Isbell, F. et al. Biodiversity increases the resistance of ecosystem productivity to climate extremes. Nature 526, 574–577 (2015).

    Article  CAS  Google Scholar 

  39. Gonzalez, A. et al. Scaling-up biodiversity–ecosystem functioning research. Ecol. Lett. 23, 757–776 (2020).

    Article  Google Scholar 

  40. Ricketts, T. H. et al. Disaggregating the evidence linking biodiversity and ecosystem services. Nat. Commun. 7, 13106 (2016).

    Article  CAS  Google Scholar 

  41. Turner, W. R. et al. Global conservation of biodiversity and ecosystem services. Bioscience 57, 868–873 (2007).

    Article  Google Scholar 

  42. Song, X., Wang, D. Y., Li, F. & Zeng, X. D. Evaluating the performance of CMIP6 Earth system models in simulating global vegetation structure and distribution. Adv. Clim. Change Res. 12, 584–595 (2021).

    Article  Google Scholar 

  43. Zhao, Q., Zhu, Z., Zeng, H., Zhao, W. & Myneni, R. B. Future greening of the Earth may not be as large as previously predicted. Agric. Meteorol. 292–293, 108111 (2020).

    Article  Google Scholar 

  44. Anav, A. et al. Evaluation of land surface models in reproducing satellite derived leaf area index over the high-latitude Northern Hemisphere. Part II: Earth system models. Remote Sens. 5, 3637–3661 (2013).

    Article  Google Scholar 

  45. Piao, S. et al. Characteristics, drivers and feedbacks of global greening. Nat. Rev. Earth Environ. 1, 14–27 (2020).

    Article  Google Scholar 

  46. Kim, D. et al. Intercomparison of terrestrial carbon fluxes and carbon use efficiency simulated by CMIP5 Earth system models. Asia Pac. J. Atmos. Sci. 54, 145–163 (2018).

    Article  Google Scholar 

  47. Chausson, A. et al. Mapping the effectiveness of nature-based solutions for climate change adaptation. Glob. Change Biol. 26, 6134–6155 (2020).

    Article  Google Scholar 

  48. Di Marco, M. et al. Changing trends and persisting biases in three decades of conservation science. Glob. Ecol. Conserv. 10, 32–42 (2017).

    Google Scholar 

  49. Faith, D. P. et al. Evosystem services: an evolutionary perspective on the links between biodiversity and human well-being. Curr. Opin. Environ. Sustain. 2, 66–74 (2010).

    Article  Google Scholar 

  50. Anderson, C. B. et al. Determining nature’s contributions to achieve the sustainable development goals. Sustain. Sci. 14, 543–547 (2019).

    Article  Google Scholar 

  51. Hole, D. G. et al. Make nature’s role visible to achieve the SDGs. Glob. Sustain. https://doi.org/10.1017/sus.2022.5 (2022).

    Article  Google Scholar 

  52. Saatchi, S. S. et al. Benchmark map of forest carbon stocks in tropical regions across three continents. Proc. Natl Acad. Sci. USA https://doi.org/10.1073/pnas.1019576108 (2011).

  53. Trabucco, A., Zomer, R. J., Bossio, D. A., van Straaten, O. & Verchot, L. V. Climate change mitigation through afforestation/reforestation: a global analysis of hydrologic impacts with four case studies. Agric. Ecosyst. Environ. 126, 81–97 (2008).

    Article  Google Scholar 

  54. Eyring, V. et al. Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geosci. Model Dev. https://doi.org/10.5194/gmd-9-1937-2016 (2016).

  55. Fick, S. E. & Hijmans, R. J. WorldClim 2: new 1-km spatial resolution climate surfaces for for global land areas. Int. J. Climatol. 37, 4302–4315 (2017).

    Article  Google Scholar 

  56. Erb, K. H. et al. Unexpectedly large impact of forest management and grazing on global vegetation biomass. Nature 553, 73–76 (2018).

    Article  CAS  Google Scholar 

  57. Potter, C. S. et al. Terrestrial ecosystem production: a process model based on global satellite and surface data. Global Biogeochemical Cycles 7, 811–841 (1993).

    Article  Google Scholar 

  58. Konapala, G., Mishra, A. K., Wada, Y. & Mann, M. E. Climate change will affect global water availability through compounding changes in seasonal precipitation and evaporation. Nat. Commun. 11, 3044 (2020).

    Article  CAS  Google Scholar 

  59. Guo, D., Westra, S. & Maier, H. R. Sensitivity of potential evapotranspiration to changes in climate variables for different Australian climatic zones. Hydrol. Earth Syst. Sci. 21, 2107–2126 (2017).

    Article  Google Scholar 

  60. Wang, X., Jiang, D. & Lang, X. Future changes in Aridity Index at two and four degrees of global warming above preindustrial levels. Int. J. Climatol. 41, 278–294 (2020).

    Article  CAS  Google Scholar 

  61. Park, C. E. et al. Keeping global warming within 1.5 °C constrains emergence of aridification. Nat. Clim. Change 8, 70–74 (2018).

    Article  Google Scholar 

  62. Tadese, M., Kumar, L. & Koech, R. Long-term variability in potential evapotranspiration, water availability and drought under climate change scenarios in the Awash River Basin, Ethiopia. Atmosphere 11, 883 (2020).

    Article  Google Scholar 

  63. Nooni, I. K. et al. Future changes in simulated evapotranspiration across continental Africa based on CMIP6 CNRM-CM6. Int. J. Environ. Res. Public Health 18, 6760 (2021).

    Article  Google Scholar 

  64. Liu, X., Li, C., Zhao, T. & Han, L. Future changes of global potential evapotranspiration simulated from CMIP5 to CMIP6 models. Atmos. Ocean. Sci. Lett. 13, 568–575 (2020).

    Article  Google Scholar 

  65. Allen, R. G., Pereira, L. S., Raes, D. & Smith, M. FAO Irrigation and Drainage Paper No. 56: Crop Evapotranspiration (FAO, 1998).

  66. Zarei, A. R. & Mahmoudi, M. R. Assessment of the effect of PET calculation method on the Standardized Precipitation Evapotranspiration Index (SPEI). Arab. J. Geosci. 13, 182 (2020).

    Article  Google Scholar 

  67. Hargreaves, G. H. Defining and using reference evapotranspiration. J. Irrig. Drain. Eng. 120, 1132–1139 (1994).

    Article  Google Scholar 

  68. Jia, H. & Chong, A. epwshiftr: Create Future ‘EnergyPlus’ Weather Files using ‘CMIP6’ Data. R package v.0.1.3 (2021); https://CRAN.R-project.org/package=epwshiftr

  69. Leutner, B. & Horning, N. RStoolbox: Tools for Remote Sensing Data Analysis v.0.1 (CRAN, 2017).

  70. Mittermeier, R. A. et al. Wilderness and biodiversity conservation. Proc. Natl Acad. Sci. USA 100, 10309–10313 (2003).

    Article  CAS  Google Scholar 

  71. Negret, P. J. et al. Effects of spatial autocorrelation and sampling design on estimates of protected area effectiveness. Conserv. Biol. https://doi.org/10.1111/cobi.13522 (2020).

  72. Stuart, E. A. Matching methods for causal inference: a review and a look forward. Stat Sci. 25, 1–21 (2010).

  73. Schleicher, J. et al. Statistical matching for conservation science. Conserv. Biol. 34, 538–549 (2019).

    Article  Google Scholar 

  74. Weiss, D. J. et al. A global map of travel time to cities to assess inequalities in accessibility in 2015. Nature 553, 333–336 (2018).

    Article  CAS  Google Scholar 

  75. Stuart, E. A., Lee, B. K. & Leacy, F. P. Prognostic score-based balance measures can be a useful diagnostic for propensity score methods in comparative effectiveness research. J. Clin. Epidemiol. 66, S84–S90.e1 (2013).

    Article  Google Scholar 

  76. Olmos, A. & Govindasamy, P. Propensity scores: a practical introduction using R. J. Multidiscip. Eval. 11, 68–88 (2015).

    Article  Google Scholar 

  77. Stürmer, T. et al. A review of the application of propensity score methods yielded increasing use, advantages in specific settings, but not substantially different estimates compared with conventional multivariable methods. J. Clin. Epidemiol. 59, 437.e1–437.e24 (2006).

    Article  Google Scholar 

  78. Franklin, J. M., Rassen, J. A., Ackermann, D., Bartels, D. B. & Schneeweiss, S. Metrics for covariate balance in cohort studies of causal effects. Stat. Med. 33, 1685–1699 (2014).

    Article  Google Scholar 

  79. Haukoos, J. S. & Lewis, R. J. The propensity score. JAMA 314, 1637–1638 (2015).

    Article  CAS  Google Scholar 

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Acknowledgements

M.D.M. acknowledges support from the MIUR Rita Levi Montalcini programme.

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Authors and Affiliations

  1. Department of Biology and Biotechnologies “Charles Darwin”, Sapienza University of Rome, Rome, Italy

    Marta Cimatti & Moreno Di Marco

  2. Natural Capital Project, Stanford University, Stanford, CA, USA

    Rebecca Chaplin-Kramer

  3. Institute on the Environment, University of Minnesota, Minneapolis, MN, USA

    Rebecca Chaplin-Kramer

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  1. Marta Cimatti
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Contributions

M.C. and M.D.M. designed the study. M.C. drafted the paper and performed statistical analysis with the support of M.D.M. R.C.-K. gave conceptual advice and commented extensively on the paper. All authors contributed to review and editing, and approved the final version.

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Correspondence to Marta Cimatti.

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Nature Sustainability thanks Stenseke Marie, Ole Mertz, Zuzana Harmáčková and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Cimatti, M., Chaplin-Kramer, R. & Di Marco, M. The role of high-biodiversity regions in preserving Nature’s Contributions to People. Nat Sustain 6, 1385–1393 (2023). https://doi.org/10.1038/s41893-023-01179-5

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