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A metric for spatially explicit contributions to science-based species targets

Abstract

The Convention on Biological Diversity’s post-2020 Global Biodiversity Framework will probably include a goal to stabilize and restore the status of species. Its delivery would be facilitated by making the actions required to halt and reverse species loss spatially explicit. Here, we develop a species threat abatement and restoration (STAR) metric that is scalable across species, threats and geographies. STAR quantifies the contributions that abating threats and restoring habitats in specific places offer towards reducing extinction risk. While every nation can contribute towards halting biodiversity loss, Indonesia, Colombia, Mexico, Madagascar and Brazil combined have stewardship over 31% of total STAR values for terrestrial amphibians, birds and mammals. Among actions, sustainable crop production and forestry dominate, contributing 41% of total STAR values for these taxonomic groups. Key Biodiversity Areas cover 9% of the terrestrial surface but capture 47% of STAR values. STAR could support governmental and non-state actors in quantifying their contributions to meeting science-based species targets within the framework.

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Fig. 1: Contribution to the global START score of different threats and the potential contribution of habitat restoration.
Fig. 2: Global distribution of START and STARR scores.
Fig. 3: STAR results for the Bukit Tigapuluh Sustainable Landscape and Livelihoods Project.

Data availability

Species’ extinction risk category, threat data, elevation limitations, habitat associations and distribution polygons are publicly available under specified terms and conditions of use from the IUCN Red List website6. Key Biodiversity Area boundaries are available from the World Database of Key Biodiversity Areas43, again under specified terms and conditions of use. The ESA CCI land use and cover maps are available at www.esa-landcover-cci.org39. Forest cover change maps are available from https://glad.umd.edu45. Digital elevation maps are available from https://earthexplorer.usgs.gov46. Global START and STARR scores for amphibians, birds and mammals at a grid cell resolution of 50 km are available in TIFF file format as Supplementary Data 1 and 2.

References

  1. 1.

    Hoffmann, M. et al. The impact of conservation on the status of the world’s vertebrates. Science 330, 1503–1509 (2010).

    CAS  Article  Google Scholar 

  2. 2.

    Butchart, S. H. M. et al. in Global Assessment Report on Biodiversity and Ecosystem Services Ch. 3 (IPBES Secretariat, 2019).

  3. 3.

    Zero Draft of the Post-2020 Global Biodiversity Framework (CBD, 2020).

  4. 4.

    Rounsevell, M. D. A. et al. A biodiversity target based on species extinctions. Science 368, 1193–1195 (2020).

    CAS  Article  Google Scholar 

  5. 5.

    Marques, A. et al. A framework to identify enabling and urgent actions for the 2020 Aichi Targets. Basic Appl. Ecol. 15, 633–638 (2014).

    Article  Google Scholar 

  6. 6.

    The IUCN Red List of Threatened Species Version 2019-3 (IUCN, 2019); https://www.iucnredlist.org

  7. 7.

    Butchart, S. H. M. et al. Improvements to the Red List index. PLoS ONE 2, e140 (2007).

    Article  Google Scholar 

  8. 8.

    Butchart, S. H. M. et al. Measuring global trends in the status of biodiversity: Red List indices for birds. PLoS Biol. 2, 2294–2304 (2004).

    CAS  Article  Google Scholar 

  9. 9.

    Rodrigues, A. S. L. et al. Spatially explicit trends in the global conservation status of vertebrates. PLoS ONE 9, e113934 (2014).

    Article  Google Scholar 

  10. 10.

    Akçakaya, H. R. et al. Quantifying species recovery and conservation success to develop an IUCN Green List of Species. Conserv. Biol. 32, 1128–1138 (2018).

    Article  Google Scholar 

  11. 11.

    A Global Standard for the Identification of Key Biodiversity Areas Version 1.0 (IUCN, 2016).

  12. 12.

    Moilanen, A., Wilson, K. A. & Possingham, H. Spatial Conservation Prioritization: Quantitative Methods and Computational Tools (Oxford Univ. Press, 2009).

  13. 13.

    Sodhi, N. S., Butler, R., Laurance, W. F. & Gibson, L. Conservation successes at micro-, meso- and macroscales. Trends Ecol. Evol. 26, 585–594 (2011).

    Article  Google Scholar 

  14. 14.

    Brown, J. H., Mehlman, D. W. & Stevens, G. C. Spatial variation in abundance. Ecology 76, 2028–2043 (1995).

    Article  Google Scholar 

  15. 15.

    Jones, H. P. et al. Restoration and repair of Earth’s damaged ecosystems. Proc. R. Soc. B Biol. Sci. 285, 20172577 (2018).

    Article  Google Scholar 

  16. 16.

    Strassburg, B. B. N. et al. Global priority areas for ecosystem restoration. Nature 586, 724–729 (2020).

    CAS  Article  Google Scholar 

  17. 17.

    Phalan, B., Onial, M., Balmford, A. & Green, R. E. Reconciling food production and biodiversity conservation: land sharing and land sparing compared. Science 333, 1289–1291 (2011).

    CAS  Article  Google Scholar 

  18. 18.

    Donald, P. F. et al. Important Bird and Biodiversity Areas (IBAs): the development and characteristics of a global inventory of key sites for biodiversity. Bird Conserv. Int. 29, 177–198 (2019).

    Article  Google Scholar 

  19. 19.

    Ricketts, T. H. et al. Pinpointing and preventing imminent extinctions. Proc. Natl Acad. Sci. USA 102, 18497–18501 (2005).

    CAS  Article  Google Scholar 

  20. 20.

    Myers, N., Mittermeier, R. A., Mittermeier, C. G., da Fonseca, G. A. B. & Kent, J. Biodiversity hotspots for conservation priorities. Nature 403, 853–858 (2000).

    CAS  Article  Google Scholar 

  21. 21.

    Ceballos, G., Ehrlich, P. R. & Dirzo, R. Biological annihilation via the ongoing sixth mass extinction signaled by vertebrate population losses and declines. Proc. Natl Acad. Sci. USA 114, E6089 (2017).

    CAS  Article  Google Scholar 

  22. 22.

    SDG Indicators (United Nations, 2020); https://unstats.un.org/sdgs/indicators/database/

  23. 23.

    Strassburg, B. B. N. et al. Strategic approaches to restoring ecosystems can triple conservation gains and halve costs. Nat. Ecol. Evol. 3, 62–70 (2019).

    Article  Google Scholar 

  24. 24.

    Joppa, L. N. et al. Filling in biodiversity threat gaps. Science 352, 416–418 (2016).

    CAS  Article  Google Scholar 

  25. 25.

    Brook, B. W., Sodhi, N. S. & Bradshaw, C. J. A. Synergies among extinction drivers under global change. Trends Ecol. Evol. 23, 453–460 (2008).

    Article  Google Scholar 

  26. 26.

    Ewers, R. M. & Rodrigues, A. S. L. Estimates of reserve effectiveness are confounded by leakage. Trends Ecol. Evol. 23, 113–116 (2008).

    Article  Google Scholar 

  27. 27.

    Sutherland, W. J. et al. Future novel threats and opportunities facing UK biodiversity identified by horizon scanning. J. Appl. Ecol. 45, 821–833 (2008).

    Article  Google Scholar 

  28. 28.

    McGuire, J. L., Lawler, J. J., McRae, B. H., Nuñez, T. A. & Theobald, D. M.Achieving climate connectivity in a fragmented landscape. Proc. Natl Acad. Sci. USA 113, 7195–7200 (2016).

    CAS  Article  Google Scholar 

  29. 29.

    Lenzen, M. et al. International trade drives biodiversity threats in developing nations. Nature 486, 109–112 (2012).

    CAS  Article  Google Scholar 

  30. 30.

    Companies Taking Action (Science Based Targets, 2019); https://sciencebasedtargets.org/companies-taking-action/

  31. 31.

    C40 Cities (C40, 2019); https://www.c40.org/

  32. 32.

    Fawcett, A. A. et al. Can Paris pledges avert severe climate change? Science 350, 1168–1169 (2015).

    CAS  Article  Google Scholar 

  33. 33.

    Keith, D. A. et al. Scientific foundations for an IUCN red list of ecosystems. PLoS ONE 8, e62111 (2013).

    CAS  Article  Google Scholar 

  34. 34.

    Laikre, L. et al. Post-2020 goals overlook genetic diversity. Science 367, 1083–1085 (2020).

    PubMed  Google Scholar 

  35. 35.

    Ostrom, E. Polycentric systems for coping with collective action and global environmental change. Glob. Environ. Change 20, 550–557 (2010).

    Article  Google Scholar 

  36. 36.

    Brooks, T. M. et al. Measuring terrestrial area of habitat (AOH) and its utility for the IUCN Red List. Trends Ecol. Evol. 34, 977–986 (2019).

    Article  Google Scholar 

  37. 37.

    Threats Classification Scheme Version 3.2 (IUCN, 2019).

  38. 38.

    Salafsky, N. et al. A standard lexicon for biodiversity conservation: unified classifications of threats and actions. Conserv. Biol. 22, 897–911 (2008).

    Article  Google Scholar 

  39. 39.

    European Space Agency Climate Change Initiative (ESA CCI, accessed May 2018); https://www.esa-landcover-cci.org/?q=node/158

  40. 40.

    Bird Species Distribution Maps of the World Version 2018.1 (BirdLife International & Handbook of the Birds of the World, 2019); http://datazone.birdlife.org/species/requestdis

  41. 41.

    Mapping Standards and Data Quality for the IUCN Red List Categories and Criteria. Version 1.16 (IUCN, 2018).

  42. 42.

    Garnett, S. T. et al. Metrics of progress in the understanding and management of threats to Australian birds. Conserv. Biol. 33, 456–468 (2018).

    Article  Google Scholar 

  43. 43.

    The World Database of Key Biodiversity Areas (BirdLife International, 2019); http://www.keybiodiversityareas.org

  44. 44.

    Habitats Classification Scheme Version 3.1 (IUCN, 2019).

  45. 45.

    Hansen, M. C. et al. High-resolution global maps of 21st-century forest cover change. Science 342, 850–853 (2013).

    CAS  Article  Google Scholar 

  46. 46.

    USGS EROS Archive - Digital Elevation - Global 30 Arc-Second Elevation (GTOPO30) (US Geological Survey, 2019); https://earthexplorer.usgs.gov/

  47. 47.

    R Core Development Team R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2018).

  48. 48.

    Butchart, S. H. M. et al. Using Red List indices to measure progress towards the 2010 target and beyond. Phil. Trans. R. Soc. B Biol. Sci. 360, 255–268 (2005).

    CAS  Article  Google Scholar 

  49. 49.

    Le Saout, S. et al. Protected areas and effective biodiversity conservation. Science 342, 803–805 (2013).

    CAS  Article  Google Scholar 

Download references

Acknowledgements

We acknowledge funding from the Luc Hoffmann Institute, Vulcan, Synchronicity Earth and the Global Environment Facility, as well as support from the Conservation International GEF Project Agency. We thank L. Genasci (ADM Foundation) for providing technical guidance for the field tests, J. Deutsch for facilitating funding and R. Akçakaya for comments on the manuscript. L.M. is funded by Newcastle University and IUCN, L.P.K. by the National Research Foundation Singapore (NRF-RSS2019-007), M.B. by The Rufford Foundation and A.R. by the ‘Investissements d’Avenir’ programme, which is managed by the French National Research Agency (ANR-10-LABX-14-01).

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Contributions

L.M. led on analysis, development and manuscript drafting. L.A.B., T.M.B., S.H.M.B., F.H. and P.J.K.M. led on design and development and made substantial contributions to manuscript preparation. F.C.B., N.D.B., J.M.M.E., E.J.M.-G., M.H., K.M., N.B.W.M., D.C.R., A.S.L.R., X.S. and B.B.N.S. contributed substantially to conceptual development and manuscript preparation. C.R.B., C.G.-C., A.I., M.I., E.L., B.C.M., K.P. and M.F.T. contributed to conceptual development and data acquisition and analysis. E.L.B., C.B., G.C., A.C., M.E., G.A.B.d.F., R. Galt, A.G., L.G., R. Goedicke, J.M.H.G., R.D.G., S.L.L.H., D.G.H., J. Hughes, J. Hutton, M.P.W.K., L.M.N., E.N.L., A.J.P., P.P., H.P.P., A.R., E.C.R., C.R., J.D.S., J. Siikamäki, C.S., G.S., S.S., A.L.S., C.A.S.-N., S.N.S., H.J.T., A.V., F.V., L.R.V. and J.W. contributed to the conceptual development of the work. S.B., M.B., I.J.B., V.C., C.C., N.A.C., J.F., L.R.G., C.H.-T., R.J., A.J., L.N.J., L.P.K., T.E.L., P.F.L., B.L., D.M., M.P., B.A.P., C.M.P., M.C.R., N.S.R., J.P.R., J. Smart and B.E.Y. contributed to the acquisition of data. F.H. and P.J.K.M. contributed equally to conception and coordination.

Corresponding author

Correspondence to Louise Mair.

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Competing interests

E.C.R. works for Springer Nature, the publisher of Nature Ecology & Evolution. The other authors declare no competing interests.

Additional information

Peer review information Nature Ecology & Evolution thanks Julia Jones, Joseph Bennett and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 STAR threat-abatement scores for amphibians, birds and mammals per country shown as the percentage of the total global STAR threat-abatement score.

The total global STAR threat-abatement score represents the global threat abatement effort needed for all Near Threatened and threatened (Vulnerable, Endangered and Critically Endangered according to the IUCN Red List) amphibian, bird and mammal species to be reclassified as Least Concern. This score can be disaggregated spatially, based on the area of habitat currently available for each species in a particular location.

Extended Data Fig. 2 The percentage of the global STAR threat-abatement score for amphibians (green), birds (yellow) and mammals (blue), that is contributed by each threat type.

The total global STAR threat-abatement score can be calculated for each taxonomic group and then disaggregated by threat type, based on the known contribution of each threat to species’ risk of extinction.

Extended Data Fig. 3 STAR threat-abatement scores per country for (a) amphibians (b) birds and (c) mammals shown as the percentage of the total global STAR threat-abatement score for each taxon.

The total global STAR threat-abatement score for each taxonomic group can be disaggregated spatially, based on the area of habitat currently available for each species in a particular location.

Extended Data Fig. 4 Area of species’ current AOH and percentage of species current AOH per country.

(a) The distribution, and (b) the log10 distribution, of the area of species’ current AOH. (c) the percent of species’ current AOH per country (where species occurring across multiple countries have multiple datapoints) and (d) the largest percentage of current AOH per country for each species (such that there is only one datapoint per species). Colour scale indicates Red List category of species. Note the different y-axis in (b).

Extended Data Fig. 5 The number of Data Deficient species of amphibians, birds and mammals on the IUCN Red List per 50 km grid cell.

Of the 2,235 terrestrial species in these taxonomic groups that were assessed as Data Deficient on the Red List, 1,528 (68.4%) had Area of Habitat maps.

Extended Data Fig. 6 Deviation from ‘true’ STAR threat-abatement scores for birds generated by increasing the proportion of threat data with missing scope and severity scores.

Mean R2 per region across 100 iterations at the proportion of the data degraded (that is proportion of scope and severity data treated as missing) is increased. R2 from linear regression of STAR threat-abatement scores from degraded data against STAR threat-abatement scores from complete data. Each line is a region (N = 250) and regions are grouped based on the number of bird species present.

Extended Data Fig. 7 Variation in STAR threat-abatement scores for birds generated by (a-b) varying Red List category weights, and (c) weighting large AOH proportions more and small AOH proportions less.

The distribution of R2 values per region from regressing STAR threat-abatement scores obtained when species Red List categories were weighted using (a) log steps and (b) no weighting, against scores obtained using equal step weighting. (c) The distribution of R2 values per region from regressing STAR threat-abatement scores obtained when weighting larger AOH proportions per region more and smaller AOH proportions less.

Extended Data Fig. 8 Variation in STAR threat-abatement scores generated by varying the expected percentage population decline from scope and severity scores per threat.

R2 per region across 100 iterations (each box is a region) from regressing STAR threat-abatement scores obtained using varied expected population decline were against scores obtained using the median expected population decline. Regions are grouped by the number of bird species present. Boxplots show the median, with hinges indicating the first and third quartiles, whiskers showing the most extreme datapoint that is no more than 1.5 times the interquartile range from the respective quartile, and outliers beyond this distance shown as points.

Supplementary information

Supplementary Information

Supplementary Tables 1 and 2, Methods and Discussion.

Reporting Summary

Peer Review File

Supplementary Data 1

Global START scores for terrestrial amphibians, birds and mammals at a grid cell resolution of 50 km in TIFF file format.

Supplementary Data 2

Global STARR scores for terrestrial amphibians, birds and mammals at a grid cell resolution of 50 km in TIFF file format.

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Mair, L., Bennun, L.A., Brooks, T.M. et al. A metric for spatially explicit contributions to science-based species targets. Nat Ecol Evol (2021). https://doi.org/10.1038/s41559-021-01432-0

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