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Annual Review of Environment and Resources

Volume 49, 2024

Global Metrics for Terrestrial Biodiversity

Abstract

Biodiversity metrics are increasingly in demand for informing government, business, and civil society decisions. However, it is not always clear to end users how these metrics differ or for what purpose they are best suited. We seek to answer these questions using a database of 573 biodiversity-related metrics, indicators, indices, and layers, which address aspects of genetic diversity, species, and ecosystems. We provide examples of indicators and their uses within the state–pressure–response–benefits framework that is widely used in conservation science. Considering complementarity across this framework, we recommend a small number of metrics considered most pertinent for use in decision-making by governments and businesses. We conclude by highlighting five future directions: increasing the importance of national metrics, ensuring wider uptake of business metrics, agreeing on a minimum set of metrics for government and business use, automating metric calculation through use of technology, and generating sustainable funding for metric production.

Keyword(s): benefits, biodiversity, metrics, pressure, response, state
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2024-10-18
2025-04-18
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Literature Cited

  1. 1.
    Conv. Biol. Divers. 2022.. Kunming–Montreal Global Biodiversity Framework. Doc. CBD/COP/15/L.25 , Conv. Biol. Divers., Montreal:
     [Google Scholar]
  2. 2.
    Conv. Biol. Divers. 2022.. Monitoring framework for the Kunming–Montreal Global Biodiversity Framework. Doc. CBD/COP/15/L.26 , Conv. Biol. Divers., Montreal:
     [Google Scholar]
  3. 3.
    U. N. Gen. Assem. 2017.. Work of the Statistical Commission pertaining to the 2030 Agenda for Sustainable Development. Doc. 71/313 , U.N. Gen. Assem., New York:
     [Google Scholar]
  4. 4.
    World Econ. Forum. 2023.. Global risks report 2023. Rep. , World Econ. Forum, Cologny, Switz:.
     [Google Scholar]
  5. 5.
    World Econ. Forum. 2024.. Global risks report 2024. Rep. , World Econ. Forum, Cologny, Switz.:
     [Google Scholar]
  6. 6.
    Int. Finance Corp. 2012.. Performance standard 6: biodiversity conservation and sustainable management of living natural resources. Policy, Int. Finance Corp., Washington, DC:
     [Google Scholar]
  7. 7.
    Stephenson PJ, Walls J. 2022.. A new biodiversity paradigm for business. . Amplify 35:(5):6–14
     [Google Scholar]
  8. 8.
    Santini L, Belmaker J, Costello MJ, Pereira HM, Rossberg AG, et al. 2017.. Assessing the suitability of diversity metrics to detect biodiversity change. . Biol. Conserv. 213::341–50
     [Crossref] [Google Scholar]
  9. 9.
    Sparks TH, Butchart SHM, Balmford A, Bennun L, Stanwell-Smith D, et al. 2011.. Linked indicator sets for addressing biodiversity loss. . Oryx J. Fauna Preserv. Soc. 45:(3):411–19
     [Google Scholar]
  10. 10.
    Butchart SHM, Walpole M, Collen B, van Strien A, Scharlemann JPW, et al. 2010.. Global biodiversity: indicators of recent declines. . Science 328:(5982):1164–68
     [Crossref] [Google Scholar]
  11. 11.
    Tittensor DP, Mora C, Jetz W, Lotze HK, Ricard D, et al. 2010.. Global patterns and predictors of marine biodiversity across taxa. . Nature 466:(7310):1098–101
     [Crossref] [Google Scholar]
  12. 12.
    Levrel H, Kerbiriou C, Couvet D, Weber J. 2009.. OECD pressure-state-response indicators for managing biodiversity: a realistic perspective for a French biosphere reserve. . Biodivers. Conserv. 18:(7):1719–32
     [Crossref] [Google Scholar]
  13. 13.
    OECD (Organ. Econ. Co-op. Dev.). 1993.. OECD core set of indicators for environmental performance reviews. Environ. Monogr. 83 , OECD, Paris:
     [Google Scholar]
  14. 14.
    Conv. Biol. Divers. 2011.. Report of the ad hoc technical expert group on indicators for the Strategic Plan for Biodiversity 2011–2020. Rep. , Conv. Biol. Divers., New York:
     [Google Scholar]
  15. 15.
    Hawkins F, Beatty CR, Brooks TM, Church R, Elliott W, et al. 2023.. Bottom-up global biodiversity metrics needed for businesses to assess and manage their impact. . Conserv. Biol. 38:(2):e14183
     [Crossref] [Google Scholar]
  16. 16.
    Díaz S, Malhi Y. 2022.. Biodiversity: concepts, patterns, trends, and perspectives. . Annu. Rev. Environ. Resour. 47::31–63
     [Crossref] [Google Scholar]
  17. 17.
    Collen B, Whitton F, Dyer EE, Baillie JEM, Cumberlidge N, et al. 2014.. Global patterns of freshwater species diversity, threat and endemism. . Glob. Ecol. Biogeogr. 23:(1):40–51
     [Crossref] [Google Scholar]
  18. 18.
    Grill G, Lehner B, Thieme M, Geenen B, Tickner D, et al. 2019.. Mapping the world's free-flowing rivers. . Nature 569:(7755):215–21
     [Crossref] [Google Scholar]
  19. 19.
    Jumani S, Deitch MJ, Kaplan D, Anderson EP, Krishnaswamy J, et al. 2020.. River fragmentation and flow alteration metrics: a review of methods and directions for future research. . Environ. Res. Lett. 15::123009
     [Crossref] [Google Scholar]
  20. 20.
    Tickner D, Opperman JJ, Abell R, Acreman M, Arthington AH, et al. 2020.. Bending the curve of global freshwater biodiversity loss: an emergency recovery plan. . BioScience 70:(4):330–42
     [Crossref] [Google Scholar]
  21. 21.
    Worthington TA, van Soesbergen A, Berkhuysen A, Brink K, Royte J, et al. 2022.. Global Swimways for the conservation of migratory freshwater fishes. . Front. Ecol. Environ. 20:(10):573–80
     [Crossref] [Google Scholar]
  22. 22.
    Teixeira H, Berg T, Uusitalo L, Fürhaupter K, Heiskanen A-S, et al. 2016.. A catalogue of marine biodiversity indicators. . Front. Mar. Sci. 3::207
     [Crossref] [Google Scholar]
  23. 23.
    Smit KP, Bernard ATF, Lombard AT, Sink KJ. 2021.. Assessing marine ecosystem condition: a review to support indicator choice and framework development. . Ecol. Indic. 121::107148
     [Crossref] [Google Scholar]
  24. 24.
    JNCC (Jt. Nat. Conserv. Comm.). 2022.. Marine biodiversity indicators. Fact Sheet, JNCC, Peterborough, UK:. https://jncc.gov.uk/our-work/marine-biodiversity-indicators
    [Google Scholar]
  25. 25.
    Conv. Biol. Divers. 2022.. Compilation of available metadata for the proposed headline indicators of the draft monitoring framework for the Post-2020 Global Biodiversity Framework. Note by the Executive Secretary to the Convention on Biological Diversity for the resumed session of the 24th Meeting of the Subsidiary Body on Scientific, Technical and Technological Advice. Doc. CBD/SBSTTA/24/INF/38 , Conv. Biol. Divers., Montreal:. https://www.cbd.int/doc/c/72c0/7986/05fe89f0ae9898fdc872e144/sbstta-24-inf-38-en.pdf
    [Google Scholar]
  26. 26.
    Conv. Biol. Divers. 2022.. Technical analysis of indicators proposed for the monitoring framework for the Post-2020 Global Biodiversity Framework. Rep. , Conv. Biol. Divers., Montreal:
     [Google Scholar]
  27. 27.
    Conv. Biol. Divers. 2022.. Report of the Expert Workshop on the Monitoring Framework for the Post-2020 Global Biodiversity Framework. Rep. , Conv. Biol. Divers., Montreal:
     [Google Scholar]
  28. 28.
    Conv. Biol. Divers. 2022.. Report of the Conference of the Parties to the Convention on Biological Diversity on the second part of its 15th meeting. Doc. CBD/COP/15/17 , Conv. Biol. Divers., Montreal:
     [Google Scholar]
  29. 29.
    UNEP-WCMC (U. N. Environ. Progr. World Conserv. Monit. Cent.). 2023.. Mapping for nature-based solutions: assessing the utility of global spatial data for national planning. Rep. , UNEP-WCMC, SPACES Coalit., Cambridge, UK:
     [Google Scholar]
  30. 30.
    UNEP-WCMC (U. N. Environ. Progr. World Conserv. Monit. Cent.). 2023.. Remote sensing for monitoring impacts of land-use change on biodiversity and carbon stocks: the role in the spatial planning process. Rep. , UNEP-WCMC, SPACES Coalit., Cambridge, UK:
     [Google Scholar]
  31. 31.
    U. N. Environ. Progr. 2024.. Accountability for nature: comparison of nature-related assessment and disclosure frameworks and standards. Rep. , U. N. Environ. Progr., Nairobi:
     [Google Scholar]
  32. 32.
    Berger J, Choukroun R, Costes A, Mariette J, Rouet-Pollakis S, et al. 2021.. Global Biodiversity Score, update 2021: establishing an ecosystem of stakeholders to measure the biodiversity performance of human activities. Rep. , CDC Biodivers., Paris:
     [Google Scholar]
  33. 33.
    Iceberg Data Lab. 2023.. Corporate biodiversity footprint: methodological guide. Rep. , Iceberg Data Lab, Paris:. https://www.icebergdatalab.com/wp-content/uploads/2023/04/CBF_client_methodological_guide_March_23.pdf
    [Google Scholar]
  34. 34.
    Inst. Sustain. Leadersh. 2020.. Measuring business impacts on nature: a framework to support better stewardship of biodiversity in global supply chains. Rep. , Inst. Sustain. Leadersh., Univ. Cambridge, Cambridge, UK:
     [Google Scholar]
  35. 35.
    IUCN (Int. Union Conserv. Nat.). 2023.. The IUCN Red List of Threatened Species, version 2023-1. Database, IUCN, Gland, Switz:.
     [Google Scholar]
  36. 36.
    Huijbregts MAJ, Steinmann ZJN, Elshout PMF, Stam G, Verones F, et al. 2017.. ReCiPe2016: a harmonised life cycle impact assessment method at midpoint and endpoint level. . Int. J. Life Cycle Assess. 22:(2):138–47
     [Crossref] [Google Scholar]
  37. 37.
    Müller-Wenk R. 1998.. Land use—the main threat to species: how to include land use in LCA. Discuss. Pap. 64 , St. Gallen Univ., St. Gallen, Switz.:
     [Google Scholar]
  38. 38.
    Gov. Neth. 2021.. Biodiversity footprint for financial institutions: exploring biodiversity assessment in 4 cases. Rep. , Gov. Neth., Amsterdam:. https://www.government.nl/documents/reports/2021/07/29/biodiversity-footprint-for-financial-institutions
    [Google Scholar]
  39. 39.
    PRé, Arcadis, CODE. 2022.. BioScope methodology. Rep. , PBAF (Partnersh. Biodivers. Account. Financ.), PRé, Amersfoort, Neth:. https://www.bioscope.info/download?file=%2Fuploads%2FMethodology%20Report_2022.pdf
    [Google Scholar]
  40. 40.
    Mair L, Bennun LA, Brooks TM, Butchart SHM, Bolam FC, et al. 2021.. A metric for spatially explicit contributions to science-based species targets. . Nat. Ecol. Evol. 5:(6):836–44
     [Crossref] [Google Scholar]
  41. 41.
    Bedford J, Brooks S, Dimitrijevic J, Belle E, Santamaria M, et al. 2022.. Recommendations for a standard on corporate biodiversity measurement and valuation: aligning accounting approaches for nature. Slides, UNEP-WCMC (U. N. Environ. Progr. World Conserv. Monit. Cent.), Capitals Coalit., Arcadis, ICF, Cambridge, UK:
     [Google Scholar]
  42. 42.
    UNEP-WCMC (U. N. Environ. Progr. World Conserv. Monit. Cent.). 2017.. Biodiversity indicators for extractive companies: an assessment of needs, current practices and potential indicator models. Rep. , UNEP-WCMC, Cambridge, UK:
     [Google Scholar]
  43. 43.
    Jones SK, Estrada-Carmona N, Juventia SD, Dulloo ME, Laporte MA, et al. 2021.. Agrobiodiversity index scores show agrobiodiversity is underutilized in national food systems. . Nat. Food 2:(9):712–23
     [Crossref] [Google Scholar]
  44. 44.
    Hagan JM, Whitman AA. 2006.. Biodiversity indicators for sustainable forestry: simplifying complexity. . J. For. 104:(4):203–10
     [Google Scholar]
  45. 45.
    Lelli C, Bruun HH, Chiarucci A, Donati D, Frascaroli F, et al. 2019.. Biodiversity response to forest structure and management: comparing species richness, conservation relevant species and functional diversity as metrics in forest conservation. . For. Ecol. Manag. 432::707–17
     [Crossref] [Google Scholar]
  46. 46.
    Seebacher F, White CR, Franklin CE. 2015.. Physiological plasticity increases resilience of ectothermic animals to climate change. . Nat. Clim. Change 5::61–66
     [Crossref] [Google Scholar]
  47. 47.
    Miraldo A, Li S, Borregaard MK, Flórez-Rodríguez A, Gopalakrishnan S, et al. 2016.. An Anthropocene map of genetic diversity. . Science 353:(6307):1532–35
     [Crossref] [Google Scholar]
  48. 48.
    Food Agric. Organ. 2023.. The Agrobiodiversity Index. Fact Sheet, Food Agric. Organ., Rome:. https://www.fao.org/plant-treaty/tools/toolbox-for-sustainable-use/details/en/c/1312762
    [Google Scholar]
  49. 49.
    Schmidt C, Hoban S, Hunter M, Paz-Vinas I, Garroway CJ. 2023.. Genetic diversity and IUCN Red List status. . Conserv. Biol. 37:(4):e14064
     [Crossref] [Google Scholar]
  50. 50.
    Hoban S, da Silva JM, Mastretta-Yanes A, Grueber CE, Heuertz M, et al. 2023.. Monitoring status and trends in genetic diversity for the Convention on Biological Diversity: an ongoing assessment of genetic indicators in nine countries. . Conserv. Lett. 16:(3):e12953
     [Crossref] [Google Scholar]
  51. 51.
    Jetz W, Thomas GH, Joy JB, Redding DW, Hartmann K, Mooers AO. 2014.. Global distribution and conservation of evolutionary distinctness in birds. . Curr. Biol. 24:(9):919–30
     [Crossref] [Google Scholar]
  52. 52.
    Davies TJ, Fritz SA, Grenyer R, Orme CDL, Bielby J, et al. 2008.. Phylogenetic trees and the future of mammalian biodiversity. . PNAS 105:(Suppl. 1):11556–63
     [Crossref] [Google Scholar]
  53. 53.
    Fritz SA, Rahbek C. 2012.. Global patterns of amphibian phylogenetic diversity. . J. Biogeogr. 39:(8):1373–82
     [Crossref] [Google Scholar]
  54. 54.
    Gumbs R, Chaudhary A, Daru BH, Faith DP, Forest F, et al. 2022.. Conserving evolutionary history to safeguard our future: incorporating the Tree of Life into biodiversity policy. . bioRxiv 2021.03.03.433783. https://doi.org/10.1101/2021.03.03.433783
  55. 55.
    Rapacciuolo G, Graham CH, Marin J, Behm JE, Costa GC, et al. 2019.. Species diversity as a surrogate for conservation of phylogenetic and functional diversity in terrestrial vertebrates across the Americas. . Nat. Ecol. Evol. 3:(1):53–61
     [Crossref] [Google Scholar]
  56. 56.
    Qian H, Zhang J, Jiang M. 2023.. Global patterns of taxonomic and phylogenetic diversity of flowering plants: biodiversity hotspots and coldspots. . Plant Divers. 45:(3):265–71
     [Crossref] [Google Scholar]
  57. 57.
    Myers N, Mittermeier RA, Mittermeier CG, da Fonseca GAB, Kent J. 2000.. Biodiversity hotspots for conservation priorities. . Nature 403:(6772):853–58
     [Crossref] [Google Scholar]
  58. 58.
    Enquist BJ, Feng X, Boyle B, Maitner B, Newman EA, et al. 2023.. The commonness of rarity: global and future distribution of rarity across land plants. . Sci. Adv. 5:(11):eaaz0414
     [Crossref] [Google Scholar]
  59. 59.
    Goettsch B, Hilton-Taylor C, Cruz-Piñón G, Duffy JP, Frances A, et al. 2015.. High proportion of cactus species threatened with extinction. . Nat. Plants 1:(10):15142
     [Crossref] [Google Scholar]
  60. 60.
    Nic Lughadha E, Bachman SP, Leão TCC, Forest F, Halley JM, et al. 2020.. Extinction risk and threats to plants and fungi. . Plants People Planet 2:(5):389–408
     [Crossref] [Google Scholar]
  61. 61.
    Ledger SEH, Loh J, Almond R, Böhm M, Clements CF, et al. 2023.. Past, present, and future of the Living Planet Index. . npj Biodivers. 2::12
     [Crossref] [Google Scholar]
  62. 62.
    Moore JL, Balmford A, Brooks T, Burgess ND, Hansen LA, et al. 2003.. Performance of sub-Saharan vertebrates as indicator groups for identifying priority areas for conservation. . Conserv. Biol. 17:(1):207–18
     [Crossref] [Google Scholar]
  63. 63.
    Rodrigues ASL, Brooks TM. 2007.. Shortcuts for biodiversity conservation planning: the effectiveness of surrogates. . Annu. Rev. Ecol. Evol. Syst. 38::713–37
     [Crossref] [Google Scholar]
  64. 64.
    Larsen FW, Bladt J, Balmford A, Rahbek C. 2012.. Birds as biodiversity surrogates: Will supplementing birds with other taxa improve effectiveness?. J. Appl. Ecol. 49:(2):349–56
     [Crossref] [Google Scholar]
  65. 65.
    IUCN (Int. Union Conserv. Nat.). 2012.. IUCN Red List categories and criteria: version 3.1. Database, IUCN, Gland, Switz:.
     [Google Scholar]
  66. 66.
    IPBES (Intergov. Sci.-Policy Platf. Biodivers. Ecosyst. Serv.). 2018.. Summary for policymakers of the regional assessment report on biodiversity and ecosystem services for Europe and Central Asia of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. Rep. , IPBES, Bonn, Ger:.
     [Google Scholar]
  67. 67.
    Durán AP, Green JMH, West CD, Visconti P, Burgess ND, et al. 2020.. A practical approach to measuring the biodiversity impacts of land conversion. . Methods Ecol. Evol. 11:(8):910–21
     [Crossref] [Google Scholar]
  68. 68.
    Butchart SHM, Akçakaya HR, Chanson J, Baillie JEM, Collen B, et al. 2007.. Improvements to the Red List Index. . PLOS ONE. 2:(1):e140
     [Crossref] [Google Scholar]
  69. 69.
    Akçakaya HR, Bennett EL, Brooks TM, Grace MK, Heath A, et al. 2018.. Quantifying species recovery and conservation success to develop an IUCN Green List of Species. . Conserv. Biol. 32:(5):1128–38
     [Crossref] [Google Scholar]
  70. 70.
    Stephenson PJ, Workman C, Grace MK, Long B. 2020.. Testing the IUCN Green List of Species. . Oryx J. Fauna Preserv. Soc. 54:(1):10–11
     [Google Scholar]
  71. 71.
    Větrovský T, Kohout P, Kopecký M, Machac A, Man M, et al. 2019.. A meta-analysis of global fungal distribution reveals climate-driven patterns. . Nat. Commun. 10::5142
     [Crossref] [Google Scholar]
  72. 72.
    Phillips HRP, Guerra CA, Bartz MLC, Briones MJI, Brown G, et al. 2019.. Global distribution of earthworm diversity. . Science 366:(6464):480–85
     [Crossref] [Google Scholar]
  73. 73.
    van den Hoogen J, Geisen S, Routh D, Ferris H, Traunspurger W, et al. 2019.. Soil nematode abundance and functional group composition at a global scale. . Nature 572:(7768):194–98
     [Crossref] [Google Scholar]
  74. 74.
    Antonelli A, Fry C, Smith R, Simmonds M, Kersey P, et al. 2020.. State of the world's plants and fungi 2020. Rep. , R. Bot. Gard., London:
     [Google Scholar]
  75. 75.
    Tedersoo L, Mikryukov V, Zizka A, Bahram M, Hagh-Doust N, et al. 2022.. Global patterns in endemicity and vulnerability of soil fungi. . Glob. Change Biol. 28:(22):6696–710
     [Crossref] [Google Scholar]
  76. 76.
    Thakur MP, Phillips HRP, Brose U, Vries FTD, Lavelle P, et al. 2020.. Towards an integrative understanding of soil biodiversity. . Biol. Rev. 95:(2):350–64
     [Crossref] [Google Scholar]
  77. 77.
    Rondinini C, Wilson KA, Boitani L, Grantham H, Possingham HP. 2006.. Tradeoffs of different types of species occurrence data for use in systematic conservation planning. . Ecol. Lett. 9:(10):1136–45
     [Crossref] [Google Scholar]
  78. 78.
    Brooks TM, Pimm SL, Akçakaya HR, Buchanan GM, Butchart SHM, et al. 2019.. Measuring terrestrial area of habitat (AOH) and its utility for the IUCN Red List. . Trends Ecol. Evol. 34:(11):977–86
     [Crossref] [Google Scholar]
  79. 79.
    Jung M, Arnell A, de Lamo X, García-Rangel S, Lewis M, et al. 2021.. Areas of global importance for conserving terrestrial biodiversity, carbon and water. . Nat. Ecol. Evol. 5:(11):1499–509
     [Crossref] [Google Scholar]
  80. 80.
    Brennan A, Naidoo R, Greenstreet L, Mehrabi Z, Ramankutty N, Kremen C. 2022.. Functional connectivity of the world's protected areas. . Science 376:(6597):1101–4
     [Crossref] [Google Scholar]
  81. 81.
    Keith DA, Ferrer-Paris JR, Nicholson E, Kingsford RT, eds. 2020.. IUCN Global Ecosystem Typology 2.0: descriptive profiles for biomes and ecosystem functional groups. Database, IUCN (Int. Union Conserv. Nat.), Gland, Switz.:
     [Google Scholar]
  82. 82.
    Keith DA, Ferrer-Paris JR, Nicholson E, Bishop MJ, Polidoro BA, et al. 2022.. A function-based typology for Earth's ecosystems. . Nature 610:(7932):513–18
     [Crossref] [Google Scholar]
  83. 83.
    Hansen MC, Potapov PV, Moore R, Hancher M, Turubanova SA, et al. 2013.. High-resolution global maps of 21st-century forest cover change. . Science 342:(6160):850–53
     [Crossref] [Google Scholar]
  84. 84.
    Grantham HS, Duncan A, Evans TD, Jones KR, Beyer HL, et al. 2020.. Anthropogenic modification of forests means only 40% of remaining forests have high ecosystem integrity. . Nat. Commun. 11::5978
     [Crossref] [Google Scholar]
  85. 85.
    Potapov P, Hansen MC, Laestadius L, Turubanova S, Yaroshenko A, et al. 2017.. The last frontiers of wilderness: tracking loss of intact forest landscapes from 2000 to 2013. . Sci. Adv. 3:(1):e1600821
     [Crossref] [Google Scholar]
  86. 86.
    Bunting P, Rosenqvist A, Hilarides L, Lucas RM, Thomas N, et al. 2022.. Global mangrove extent change 1996–2020: Global Mangrove Watch version 3.0. . Remote Sens. 14:(15):3657
     [Crossref] [Google Scholar]
  87. 87.
    UNEP-WCMC (U. N. Environ. Progr. World Conserv. Monit. Cent.), Short FT. 2021.. Global Distribution of Seagrasses, version 7.1: seventh update to the data layer used in Green and Short (2003). Data Set, UNEP-WCMC, Cambridge, UK:
     [Google Scholar]
  88. 88.
    McOwen C, Weatherdon L, Bochove J-W, Sullivan E, Blyth S, et al. 2017.. A global map of saltmarshes. . Biodivers. Data J. 5::e11764
     [Crossref] [Google Scholar]
  89. 89.
    Lyons M, Larsen K, Skone M. 2022.. Imagery, maps and monitoring of the world's tropical coral reefs. Data Set, Zenodo:. https://doi.org/10.5281/zenodo.6622015
    [Google Scholar]
  90. 90.
    U. N. Environ. Progr. 2022.. Global peatlands assessment—the state of the world's peatlands. Evidence for action toward the conservation, restoration, and sustainable management of peatlands. Main Rep. , Glob. Peatl. Initiat., U. N. Environ. Progr., Nairobi:
     [Google Scholar]
  91. 91.
    Gumbricht T, Román-Cuesta RM, Verchot LV, Herold M, Wittmann F, et al. 2017.. Tropical and subtropical wetlands distribution. Data Set, CIFOR (Cent. Int. For. Res.), Jawa Barat, Indones:.
     [Google Scholar]
  92. 92.
    Fluet-Chouinard E, Stocker BD, Zhang Z, Malhotra A, Melton JR, et al. 2023.. Extensive global wetland loss over the past three centuries. . Nature 614:(7947):281–86
     [Crossref] [Google Scholar]
  93. 93.
    Tropek R, Sedláček O, Beck J, Keil P, Musilová Z, et al. 2014.. Comment on “High-resolution global maps of 21st-century forest cover change. .” Science 344:(6187):981
     [Crossref] [Google Scholar]
  94. 94.
    Skowno A, Monyeki M. 2021.. South Africa's Red List of Terrestrial Ecosystems (RLEs). . Land 10:(10):1048
     [Crossref] [Google Scholar]
  95. 95.
    Finch JM, Meadows ME. 2019.. South African biomes and their changes over time. . In The Geography of South Africa: Contemporary Changes and New Directions, ed. J Knight, CM Rogerson , pp. 57–69. Berlin:: Springer
     [Google Scholar]
  96. 96.
    World Resour. Inst. 2024.. Indicators of forest extent: forest loss. Glob. For. Rev., update 8 . World Resour. Inst., Washington, DC:. https://research.wri.org/gfr/forest-extent-indicators/forest-loss
    [Google Scholar]
  97. 97.
    Hansen MC, Potapov PV, Goetz SJ, Turubanova S, Tyukavina A, et al. 2016.. Mapping tree height distributions in sub-Saharan Africa using Landsat 7 and 8 data. . Remote Sens. Environ. 185::221–32
     [Crossref] [Google Scholar]
  98. 98.
    McNicol IM, Keane A, Burgess ND, Bowers SJ, Mitchard ETA, Ryan CM. 2023.. Protected areas reduce deforestation and degradation and enhance woody growth across African woodlands. . Commun. Earth Environ. 4::392
     [Crossref] [Google Scholar]
  99. 99.
    Watson JEM, Evans T, Venter O, Williams B, Tulloch A, et al. 2018.. The exceptional value of intact forest ecosystems. . Nat. Ecol. Evol. 2:(4):599–610
     [Crossref] [Google Scholar]
  100. 100.
    Phillips H, Palma AD, Gonzalez R, Contu S. 2021.. The Biodiversity Intactness Index—country, region and global-level summaries for the year 1970 to 2050 under various scenarios. Data Set, Natl. Hist. Mus., London:
     [Google Scholar]
  101. 101.
    Newbold T, Hudson LN, Arnell AP, Contu S, De Palma A, et al. 2016.. Has land use pushed terrestrial biodiversity beyond the planetary boundary? A global assessment. . Science 353:(6296):288–91
     [Crossref] [Google Scholar]
  102. 102.
    Alkemade R, van Oorschot M, Miles L, Nellemann C, Bakkenes M, ten Brink B. 2009.. GLOBIO3: a framework to investigate options for reducing global terrestrial biodiversity loss. . Ecosystems 12:(3):374–90
     [Crossref] [Google Scholar]
  103. 103.
    Schipper AM, Hilbers JP, Meijer JR, Antão LH, Benítez-López A, et al. 2020.. Projecting terrestrial biodiversity intactness with GLOBIO4. . Glob. Change Biol. 26:(2):760–71
     [Crossref] [Google Scholar]
  104. 104.
    Rodríguez JP, Rodríguez-Clark KM, Baillie JEM, Ash N, Benson J, et al. 2011.. Establishing IUCN Red List criteria for threatened ecosystems. . Conserv. Biol. 25:(1):21–29
     [Crossref] [Google Scholar]
  105. 105.
    Bland LM, Rowland JA, Regan TJ, Keith DA, Murray NJ, et al. 2018.. Developing a standardized definition of ecosystem collapse for risk assessment. . Front. Ecol. Environ. 16:(1):29–36
     [Crossref] [Google Scholar]
  106. 106.
    Bland LM, Keith DA, Miller RM, Murray NJ, Ródriguez JP, eds. 2017.. Guidelines for the application of IUCN Red List of Ecosystems categories and criteria, version 1.1. Guidel., IUCN (Int. Union Conserv. Nat.), Gland, Switz.:
     [Google Scholar]
  107. 107.
    Keith DA, Rodríguez JP, Rodríguez-Clark KM, Nicholson E, Aapala K, et al. 2013.. Scientific foundations for an IUCN Red List of Ecosystems. . PLOS ONE 8:(5):e62111
     [Crossref] [Google Scholar]
  108. 108.
    Rowland JA, Bland LM, Keith DA, Juffe-Bignoli D, Burgman MA, et al. 2020.. Ecosystem indices to support global biodiversity conservation. . Conserv. Lett. 13:(1):e12680
     [Crossref] [Google Scholar]
  109. 109.
    EEA (Eur. Environ. Agency). 2017.. Terrestrial mean species abundance, globally and for selected world regions. Figure, EEA, Copenhagen:. https://www.eea.europa.eu/data-and-maps/figures/terrestrial-mean-species-abundance-globally
    [Google Scholar]
  110. 110.
    Joppa LN, O'Connor B, Visconti P, Smith C, Geldmann J, et al. 2016.. Filling in biodiversity threat gaps: Only 5% of global threat data sets meet a “gold standard. .” Science 352:(6284):416–18
     [Crossref] [Google Scholar]
  111. 111.
    Maxwell SL, Fuller RA, Brooks TM, Watson JEM. 2016.. Biodiversity: the ravages of guns, nets and bulldozers. . Nature 536:(7615):143–45
     [Crossref] [Google Scholar]
  112. 112.
    Harfoot MBJ, Johnston A, Balmford A, Burgess ND, Butchart SHM, et al. 2021.. Using the IUCN Red List to map threats to terrestrial vertebrates at global scale. . Nat. Ecol. Evol. 5:(11):1510–19
     [Crossref] [Google Scholar]
  113. 113.
    Irwin A, Geschke A, Brooks TM, Siikamaki J, Mair L, Strassburg BBN. 2022.. Quantifying and categorising national extinction-risk footprints. . Sci. Rep. 12::5861
     [Crossref] [Google Scholar]
  114. 114.
    Salafsky N, Salzer D, Stattersfield AJ, Hilton-Taylor C, Neugarten R, et al. 2008.. A standard lexicon for biodiversity conservation: unified classifications of threats and actions. . Conserv. Biol. 22:(4):897–911
     [Crossref] [Google Scholar]
  115. 115.
    Eyres A, Ball T, Dales M, Swinfield T, Arnell A, et al. 2023.. LIFE: a metric for quantitively mapping the impact of land-cover change on global extinctions. Earth Environ. Sci. Work. Pap., Cambridge Open Engage. https://doi.org/10.33774/coe-2023-gpn4p-v5
    [Google Scholar]
  116. 116.
    Butchart SHM. 2008.. Red List indices to measure the sustainability of species use and impacts of invasive alien species. . Bird Conserv. Int. 18:(Suppl. 1):S245–62
     [Crossref] [Google Scholar]
  117. 117.
    Marsh SME, Hoffmann M, Burgess ND, Brooks TM, Challender DWS, et al. 2022.. Prevalence of sustainable and unsustainable use of wild species inferred from the IUCN Red List of Threatened Species. . Conserv. Biol. 36:(2):e13844
     [Crossref] [Google Scholar]
  118. 118.
    Soto-Navarro C, Ravilious C, Arnell A, de Lamo X, Harfoot M, et al. 2020.. Mapping co-benefits for carbon storage and biodiversity to inform conservation policy and action. . Philos. Trans. R. Soc. B 375:(1794):20190128
     [Crossref] [Google Scholar]
  119. 119.
    Sanderson EW, Jaiteh M, Levy MA, Redford KH, Wannebo AV, Woolmer G. 2002.. The human footprint and the last of the wild: The human footprint is a global map of human influence on the land surface, which suggests that human beings are stewards of nature, whether we like it or not. . BioScience 52:(10):891–904
     [Crossref] [Google Scholar]
  120. 120.
    Venter O, Sanderson EW, Magrach A, Allan JR, Beher J, et al. 2016.. Sixteen years of change in the global terrestrial human footprint and implications for biodiversity conservation. . Nat. Commun. 7::12558
     [Crossref] [Google Scholar]
  121. 121.
    Williams BA, Venter O, Allan JR, Atkinson SC, Rehbein JA, et al. 2020.. Change in terrestrial human footprint drives continued loss of intact ecosystems. . One Earth 3:(3):371–82
     [Crossref] [Google Scholar]
  122. 122.
    Bowler DE, Bjorkman AD, Dornelas M, Myers-Smith IH, Navarro LM, et al. 2020.. Mapping human pressures on biodiversity across the planet uncovers anthropogenic threat complexes. . People Nat. 2:(2):380–94
     [Crossref] [Google Scholar]
  123. 123.
    Kennedy CM, Oakleaf JR, Theobald DM, Baruch-Mordo S, Kiesecker J. 2019.. Managing the middle: a shift in conservation priorities based on the global human modification gradient. . Glob. Change Biol. 25:(3):811–26
     [Crossref] [Google Scholar]
  124. 124.
    Beyer HL, Venter O, Grantham HS, Watson JEM. 2020.. Substantial losses in ecoregion intactness highlight urgency of globally coordinated action. . Conserv. Lett. 13:(2):e12692
     [Crossref] [Google Scholar]
  125. 125.
    Jacobson AP, Riggio J, Tait AM, Baillie JEM. 2019.. Global areas of low human impact (‘low impact areas’) and fragmentation of the natural world. . Sci. Rep. 9::14179
     [Crossref] [Google Scholar]
  126. 126.
    Gosling J, Jones MI, Arnell A, Watson JEM, Venter O, et al. 2020.. A global mapping template for natural and modified habitat across terrestrial Earth. . Biol. Conserv. 250::108674
     [Crossref] [Google Scholar]
  127. 127.
    Ellis EC, Beusen A, Goldewijk KK. 2020.. Anthropogenic biomes: 10,000 bce to 2015 ce. . Land 9:(5):129
     [Crossref] [Google Scholar]
  128. 128.
    Ellis EC, Gauthier N, Goldewijk KK, Bird RB, Boivin N, et al. 2021.. People have shaped most of terrestrial nature for at least 12,000 years. . PNAS 118:(17):e2023483118
     [Crossref] [Google Scholar]
  129. 129.
    Hansen MC, Krylov A, Tyukavina A, Potapov PV, Turubanova S, et al. 2016.. Humid tropical forest disturbance alerts using Landsat data. . Environ. Res. Lett. 11::034008
     [Crossref] [Google Scholar]
  130. 130.
    Zubkova M, Boschetti L, Abatzoglou JT, Giglio L. 2019.. Changes in fire activity in Africa from 2002 to 2016 and their potential drivers. . Geophys. Res. Lett. 46:(13):7643–53
     [Crossref] [Google Scholar]
  131. 131.
    World Resour. Inst. 2023.. Indicators of forest extent: deforestation linked to agriculture. Glob. For. Rev., update 8. World Resour. Inst., Washington, DC:. https://research.wri.org/gfr/forest-extent-indicators/deforestation-agriculture
    [Google Scholar]
  132. 132.
    Bingham HC, Bignoli DJ, Lewis E, MacSharry B, Burgess ND, et al. 2019.. Sixty years of tracking conservation progress using the World Database on Protected Areas. . Nat. Ecol. Evol. 3:(5):737–43
     [Crossref] [Google Scholar]
  133. 133.
    Jonas H, Barbuto V, Jonas H, Kothari A, Nelson F. 2014.. New steps of change: looking beyond protected areas to consider other effective area-based conservation measures. . Parks J. 20:(2):111–28
     [Crossref] [Google Scholar]
  134. 134.
    UNEP-WCMC (U. N. Environ. Progr. World Conserv. Monit. Cent.), IUCN (Int. Union Conserv. Nat.). 2024.. Protected Planet: the World Database on Protected Areas (WDPA) and World Database on Other Effective Area-Based Conservation Measures (WD-OECM). Database, UNEP-WCMC, Cambridge, UK:
     [Google Scholar]
  135. 135.
    Geldmann J, Deguignet M, Balmford A, Burgess ND, Dudley N, et al. 2021.. Essential indicators for measuring site-based conservation effectiveness in the Post-2020 Global Biodiversity Framework. . Conserv. Lett. 14:(4):e12792
     [Crossref] [Google Scholar]
  136. 136.
    IPBES (Intergov. Sci.-Policy Platf. Biodivers. Ecosyst. Serv.). 2019.. Global assessment report on biodiversity and ecosystem services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. Rep. , IPBES, Bonn, Ger:.
     [Google Scholar]
  137. 137.
    Theobald DM, Keeley ATH, Laur A, Tabor G. 2022.. A simple and practical measure of the connectivity of protected area networks: the ProNet metric. . Conserv. Sci. Pract. 4:(11):e12823
     [Crossref] [Google Scholar]
  138. 138.
    KBA Partnersh. 2022.. KBA Programme annual report 2021. Rep. , KBA Partnersh., London:. https://www.keybiodiversityareas.org/working-with-kbas/publications/annual-reports
    [Google Scholar]
  139. 139.
    Strassburg BBN, Iribarrem A, Beyer HL, Cordeiro CL, Crouzeilles R, et al. 2020.. Global priority areas for ecosystem restoration. . Nature 586:(7831):724–29
     [Crossref] [Google Scholar]
  140. 140.
    UNDP (U. N. Dev. Progr.). 2023.. Ecosystem restoration. Country dossier—South Africa. Rep. , UNDP, Nairobi:. https://www.learningfornature.org/en/restoring-hope-optimizing-and-aligning-restoration-goals-using-spatial-data
    [Google Scholar]
  141. 141.
    Carpenter SR, Mooney HA, Agard J, Capistrano D, Defries RS, et al. 2009.. Science for managing ecosystem services: beyond the Millennium Ecosystem Assessment. . PNAS 106:(5):1305–12
     [Crossref] [Google Scholar]
  142. 142.
    Díaz S, Pascual U, Stenseke M, Martín-López B, Watson RT, et al. 2018.. Assessing nature's contributions to people: recognizing culture, and diverse sources of knowledge, can improve assessments. . Science 359:(6373):270–72
     [Crossref] [Google Scholar]
  143. 143.
    Leach K, Grigg A, O'Connor B, Brown C, Vause J, et al. 2019.. A common framework of natural capital assets for use in public and private sector decision making. . Ecosyst. Serv. 36::100899
     [Crossref] [Google Scholar]
  144. 144.
    Chaplin-Kramer R, Sharp RP, Weil C, Bennett EM, Pascual U, et al. 2019.. Global modeling of nature's contributions to people. . Science 366:(6462):255–58
     [Crossref] [Google Scholar]
  145. 145.
    Chaplin-Kramer R, Neugarten RA, Sharp RP, Collins PM, Polasky S, et al. 2023.. Mapping the planet's critical natural assets. . Nat. Ecol. Evol. 7:(1):51–61
     [Crossref] [Google Scholar]
  146. 146.
    Hooftman DAP, Bullock JM, Jones L, Eigenbrod F, Barredo JI, et al. 2022.. Reducing uncertainty in ecosystem service modelling through weighted ensembles. . Ecosyst. Serv. 53::101398
     [Crossref] [Google Scholar]
  147. 147.
    Dickson B, Blaney R, Miles L, Regan E, van Soesbergen A, et al. 2014.. Toward a global map of natural capital: key ecosystem assets. Rep. , U. N. Environ. Progr., Nairobi:
     [Google Scholar]
  148. 148.
    Willcock S, Hooftman DAP, Neugarten RA, Chaplin-Kramer R, Barredo JI, et al. 2023.. Model ensembles of ecosystem services fill global certainty and capacity gaps. . Sci. Adv. 9:(14):adf5492
     [Crossref] [Google Scholar]
  149. 149.
    Willcock S, Hooftman DAP, Balbi S, Blanchard R, Dawson TP, et al. 2019.. A continental-scale validation of ecosystem service models. . Ecosystems 22:(8):1902–17
     [Crossref] [Google Scholar]
  150. 150.
    Vysna V, Maes J, Petersen JE, La Notte A, Vallecillo S, et al. 2021.. Accounting for ecosystems and their services in the European Union (INCA). Final report from phase II of the INCA project aiming to develop a pilot for an integrated system of ecosystem accounts for the EU. Stat. Rep. , EU Publ. Off., Luxembourg:. https://ec.europa.eu/eurostat/en/web/products-statistical-reports/-/ks-ft-20-002
    [Google Scholar]
  151. 151.
    EPA (US Environ. Prot. Agency). 2023.. Ecosystem services—EnviroAtlas. Interact. Tool, EPA, Washington, DC:. https://www.epa.gov/enviroatlas/ecosystem-services-enviroatlas-1
    [Google Scholar]
  152. 152.
    Speziale L, Geneletti D. 2014.. Applying an ecosystem services approach to support land-use planning: a case study in Koboko district, Uganda. . Ecol. Process. 3::10
     [Crossref] [Google Scholar]
  153. 153.
    Niquisse S, Cabral P, Rodrigues Â, Augusto G. 2017.. Ecosystem services and biodiversity trends in Mozambique as a consequence of land cover change. . Int. J. Biodivers. Sci. Ecosyst. Serv. Manag. 13:(1):297–311
     [Crossref] [Google Scholar]
  154. 154.
    Capitani C, van Soesbergen A, Mukama K, Malugu I, Mbilinyi B, et al. 2019.. Scenarios of land use and land cover change and their multiple impacts on natural capital in Tanzania. . Environ. Conserv. 46:(1):17–24
     [Crossref] [Google Scholar]
  155. 155.
    Harris NL, Gibbs DA, Baccini A, Birdsey RA, de Bruin S, et al. 2021.. Global maps of twenty-first century forest carbon fluxes. . Nat. Clim. Change 11:(3):234–40
     [Crossref] [Google Scholar]
  156. 156.
    Spawn SA, Sullivan CC, Lark TJ, Gibbs HK. 2020.. Harmonized global maps of above and belowground biomass carbon density in the year 2010. . Sci. Data 7::112
     [Crossref] [Google Scholar]
  157. 157.
    Shin S, Park MS, Lee H, Baral H. 2022.. The structure and pattern of global partnerships in the REDD+ mechanism. . Foreign Policy Econ. 135::102640
     [Google Scholar]
  158. 158.
    Mulligan M. 2024.. WaterWorld, version 2. Model Doc. https://docs.google.com/document/d/1GKheQFp5_rsZyazwCJxCzeEStQF2jh04x-Dl_oG5yoY/edit
    [Google Scholar]
  159. 159.
    Watson SCL, Newton AC, Ridding LE, Evans PM, Brand S, et al. 2021.. Does agricultural intensification cause tipping points in ecosystem services?. Landsc. Ecol. 36:(12):3473–91
     [Crossref] [Google Scholar]
  160. 160.
    Hill SLL, Fajardo J, Maney C, Harfoot M, Harrison M, et al. 2022.. The Ecosystem Integrity Index: a novel measure of terrestrial ecosystem integrity with global coverage. . bioRxiv 2022.08.21.504707. https://doi.org/10.1101/2022.08.21.504707
  161. 161.
    Ferrier S, Harwood TD, Ware C, Hoskins AJ. 2020.. A globally applicable indicator of the capacity of terrestrial ecosystems to retain biological diversity under climate change: the Bioclimatic Ecosystem Resilience Index. . Ecol. Indic. 117::106554
     [Crossref] [Google Scholar]
  162. 162.
    Hoekstra JM, Boucher TM, Ricketts TH, Roberts C. 2005.. Confronting a biome crisis: global disparities of habitat loss and protection. . Ecol. Lett. 8:(1):23–29
     [Crossref] [Google Scholar]
  163. 163.
    Burgess ND, Hales JD, Ricketts TH, Dinerstein E. 2006.. Factoring species, non-species values and threats into biodiversity prioritisation across the ecoregions of Africa and its islands. . Biol. Conserv. 127:(4):383–401
     [Crossref] [Google Scholar]
  164. 164.
    Long PR, Benz D, Martin AC, Holland PWA, Macias-Fauria M, et al. 2018.. LEFT—a web-based tool for the remote measurement and estimation of ecological value across global landscapes. . Methods Ecol. Evol. 9:(3):571–79
     [Crossref] [Google Scholar]
  165. 165.
    Soto-Navarro CA, Harfoot M, Hill SLL, Campbell J, Mora F, et al. 2021.. Towards a multidimensional biodiversity index for national application. . Nat. Sustain. 4:(11):933–42
     [Crossref] [Google Scholar]
  166. 166.
    Jones J, Collen B, Atkinson G, Baxter P, Bubb P, et al. 2010.. The why, what, and how of global biodiversity indicators beyond the 2010 target. . Conserv. Biol. 25::450–57
     [Crossref] [Google Scholar]
  167. 167.
    Local Ecol. Footpr. Tool. 2016.. Puntarenas: Costa Rica site 3587. Rep. , Local Ecol. Footpr. Tool, Oxford, UK.: https://www.left.ox.ac.uk/samples/sample-report.pdf
    [Google Scholar]
  168. 168.
    Purvis A. 2020.. A single apex target for biodiversity would be bad news for both nature and people. . Nat. Ecol. Evol. 4:(6):768–69
     [Crossref] [Google Scholar]
  169. 169.
    Hill SLL, Harfoot M, Purvis A, Purves DW, Collen B, et al. 2016.. Reconciling biodiversity indicators to guide understanding and action. . Conserv. Lett. 9:(6):405–12
     [Crossref] [Google Scholar]
  170. 170.
    Rounsevell MDA, Harfoot M, Harrison PA, Newbold T, Gregory RD, Mace GM. 2020.. A biodiversity target based on species extinctions. . Science 368:(6496):1193–95
     [Crossref] [Google Scholar]
  171. 171.
    Jung M, Dahal PR, Butchart SHM, Donald PF, Lamo XD, et al. 2020.. A global map of terrestrial habitat types. . Sci. Data 7::256
     [Crossref] [Google Scholar]
  172. 172.
    Pereira HM, Ferrier S, Walters M, Geller GN, Jongman RHG, et al. 2013.. Essential biodiversity variables. . Science 339:(6117):277–78
     [Crossref] [Google Scholar]
  173. 173.
    Navarro LM, Fernández N, Guerra C, Guralnick R, Kissling WD, et al. 2017.. Monitoring biodiversity change through effective global coordination. . Curr. Opin. Environ. Sustain. 29::158–69
     [Crossref] [Google Scholar]
  174. 174.
    Asner GP, Martin RE. 2016.. Spectranomics: emerging science and conservation opportunities at the interface of biodiversity and remote sensing. . Glob. Ecol. Conserv. 8::212–19
     [Google Scholar]
  175. 175.
    Brown CF, Brumby SP, Guzder-Williams B, Birch T, Hyde SB, et al. 2022.. Dynamic World, near real-time global 10 m land use land cover mapping. . Sci. Data 9::251
     [Crossref] [Google Scholar]
  176. 176.
    Sato H, Ise T. 2022.. Predicting global terrestrial biomes with the LeNet convolutional neural network. . Geosci. Model Dev. 15:(7):3121–32
     [Crossref] [Google Scholar]
  177. 177.
    Ekim B, Stomberg TT, Roscher R, Schmitt M. 2022.. MapInWild: a remote sensing dataset to address the question what makes nature wild. . arXiv:2212.02265 [cs]
  178. 178.
    Danielsen F, Pirhofer-Walzl K, Adrian T, Kapijimpanga D, Burgess ND, et al. 2013.. Linking public participation in scientific research to the indicators and needs of international environmental agreements. . Conserv. Lett. 7:(1):12–24
     [Crossref] [Google Scholar]
  179. 179.
    Turrini T, Dörler D, Richter A, Heigl F, Bonn A. 2018.. The threefold potential of environmental citizen science—generating knowledge, creating learning opportunities and enabling civic participation. . Biol. Conserv. 225::176–86
     [Crossref] [Google Scholar]
  180. 180.
    King N, Rajvanshi A, Willoughby S, Roberts R, Mathur VB, et al. 2012.. Improving access to biodiversity data for, and from, EIAs—a data publishing framework built to global standards. . Impact Assess. Proj. Apprais. 30:(3):148–56
     [Crossref] [Google Scholar]
  181. 181.
    Johnston A, Hochachka WM, Strimas-Mackey ME, Gutierrez VR, Robinson OJ, et al. 2021.. Analytical guidelines to increase the value of community science data: an example using eBird data to estimate species distributions. . Divers. Distrib. 27:(7):1265–77
     [Crossref] [Google Scholar]
  182. 182.
    Krasny ME, Russ A, Tidball KG, Elmqvist T. 2014.. Civic ecology practices: participatory approaches to generating and measuring ecosystem services in cities. . Ecosyst. Serv. 7::177–86
     [Crossref] [Google Scholar]
  183. 183.
    IUCN (Int. Union Conserv. Nat.). 2022.. Application of Indigenous and local knowledge (ILK) in IUCN Red List assessments, version 1. White Pap. , IUCN, Gland, Switz.:
     [Google Scholar]
  184. 184.
    Juffe-Bignoli D, Brooks TM, Butchart SHM, Jenkins RB, Boe K, et al. 2016.. Assessing the cost of global biodiversity and conservation knowledge. . PLOS ONE 11:(8):e0160640
     [Crossref] [Google Scholar]
  185. 185.
    Deere Birkbeck C, Antoni E, Kettunen M, Wang J. 2021.. Biodiversity and international trade policy primer: How does nature fit in the sustainable trade agenda? Rep. , U. N. Environ. Progr., Nairobi:
     [Google Scholar]
  186. 186.
    Inst. Sustain. Leadersh. 2021.. Handbook for nature-related financial risks: key concepts and a framework for identification. Rep. , Inst. Sustain. Leadersh., Univ. Cambridge, Cambridge, UK:
     [Google Scholar]
  187. 187.
    CDP. 2023.. The forest transition: from risk to resilience. Glob. For. Rep., CDP, New York:. https://cdn.cdp.net/cdp-production/cms/reports/documents/000/007/182/original/CDP_Global_Forest_Report_2023.pdf?1688396252
    [Google Scholar]
  188. 188.
    Persson L, Carney Almroth BM, Collins CD, Cornell S, De Wit CA, et al. 2022.. Outside the safe operating space of the planetary boundary for novel entities. . Environ. Sci. Technol. 56:(3):1510–21
     [Crossref] [Google Scholar]
  189. 189.
    Taskf. Nat.-Relat. Financ. Discl. 2023.. Recommendations of the Taskforce on Nature-Related Financial Disclosures. Rep. , Taskf. Nat.-Relat. Financ. Discl., London:
     [Google Scholar]
  190. 190.
    Hillsdon M. 2022.. How business helped drive “historic” agreement for nature at COP15. . Reuters, Dec. 21
    [Google Scholar]
  191. 191.
    Bus. Nat., Capitals Coalit., CDP. 2022.. Make It Mandatory: the case for mandatory corporate assessment and disclosure on nature. Slides, Bus. Nat. Coalit. https://static1.squarespace.com/static/5d777de8109c315fd22faf3a/t/635930f22c677e36eefb6807/1666789622524/Make+it+Mandatory+Report_final.pdf
    [Google Scholar]
  192. 192.
    IPBES (Intergov. Sci.-Policy Platf. Biodivers. Ecosyst. Serv.). 2018.. The IPBES assessment report on land degradation and restoration. Rep. , IPBES, Bonn, Ger:.
     [Google Scholar]
  193. 193.
    Mueller C, West C, Bastos Lima MG, Doherty B. 2023.. Demand-side actors in agricultural supply chain sustainability: an assessment of motivations for action, implementation challenges, and research frontiers. . World 4:(3):569–88
     [Crossref] [Google Scholar]
  194. 194.
    IUCN (Int. Union Conserv. Nat.). 2012.. Guidelines for application of IUCN Red List criteria at regional and national levels: version 4.0. Guidel., IUCN, Gland, Switz:.
     [Google Scholar]
  195. 195.
    Bubb PJ, Butchart SHM, Collen B, Dublin H, Kapos V, et al. 2009.. IUCN Red List Index—Guidance for National and Regional Use. Gland, Switz:.: IUCN
     [Google Scholar]
  196. 196.
    Taskf. Nat.-Relat. Financ. Discl. 2023.. Findings of a high-level scoping study exploring the case for a gloal nature-related public data facility. Final Rep., Taskf. Nat.-Relat. Financ. Discl., London:. https://tnfd.global/wp-content/uploads/2023/08/23-24755-Global-Data-Facility-Paper_V14.pdf
    [Google Scholar]
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Global Metrics for Terrestrial Biodiversity
Annual Review of Environment and Resources 49, 673 (2024); https://doi.org/10.1146/annurev-environ-121522-045106
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