1932
0
  1. Home
  2. A-Z Publications
  3. Annual Review of Environment and Resources
  4. Volume 48, 2023
  5. Article

Annual Review of Environment and Resources

Volume 48, 2023

Mapping Industrial Influences on Earth's Ecology

Abstract

As anthropogenic transformation of Earth's ecology accelerates, and its impacts on the sustainability of humanity and the rest of nature become more obvious, geographers and other researchers are leveraging an abundance of spatial data to map how industrialization is transforming the biosphere. This review examines the methodologies used to create such maps and how they have enhanced our understanding of how societies can abate biodiversity loss, mitigate climate change, and achieve global sustainability goals. Although there have been great advances over the past two decades in mapping industrial transformations of ecology across the planet, the field is still in its infancy. We outline future research directions to better understand anthropogenic transformation of the biosphere and the utility of integrating global maps of socioeconomic, ecological, biodiversity, and climate data to explore and inform potential pathways of human-driven social-ecological change.

Keyword(s): Anthropocene, biodiversity conservation, conservation planning, Earth system science, land-use change, social-ecological systems
Loading

Article metrics loading...

/content/journals/10.1146/annurev-environ-112420-013640
2023-11-13
2024-05-02
Loading full text...

Full text loading...

/deliver/fulltext/energy/48/1/annurev-environ-112420-013640.html?itemId=/content/journals/10.1146/annurev-environ-112420-013640&mimeType=html&fmt=ahah

Literature Cited

  1. 1.
    Ellis EC. 2021. Land use and ecological change: a 12,000-year history. Annu. Rev. Environ. Res. 46:1–33
     [Google Scholar]
  2. 2.
    Lambin EF, Meyfroidt P. 2011. Global land use change, economic globalization, and the looming land scarcity. PNAS 108:93465–72
     [Google Scholar]
  3. 3.
    Ellis EC. 2021. People have shaped most of terrestrial nature for at least 12,000 years. PNAS 118:17e2023483118
     [Google Scholar]
  4. 4.
    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 3:3371–82
     [Google Scholar]
  5. 5.
    Daru BH. 2021. Migratory birds aid the redistribution of plants to new climates. Nature 595:786534–36
     [Google Scholar]
  6. 6.
    Hughes TP, Kerry JT, Baird AH, Connolly SR, Dietzel A et al. 2018. Global warming transforms coral reef assemblages. Nature 556:7702492–96
     [Google Scholar]
  7. 7.
    Ellis EC. 2011. Anthropogenic transformation of the terrestrial biosphere. Philos. Trans. R. Soc. 3691938:1010–35
     [Google Scholar]
  8. 8.
    Williams BA, Watson JEM, Beyer HL, Klein CJ, Montgomery J et al. 2022. Global rarity of intact coastal regions. Cons. Biol. 36:4e13874
     [Google Scholar]
  9. 9.
    Zalasiewicz J. 2017. The Working Group on the Anthropocene: summary of evidence and interim recommendations. Anthropocene 19:55–60
     [Google Scholar]
  10. 10.
    Brondízio ES, Settele J, Díaz S, Ngo HT, eds. 2019. Global Assessment Report on Biodiversity and Ecosystem Services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services Bonn, Ger.: IPBES Secr.
  11. 11.
    Wake DB, Vredenburg VT. 2008. Are we in the midst of the sixth mass extinction? A view from the world of amphibians. PNAS 105:11466–73
     [Google Scholar]
  12. 12.
    Crutzen PJ. 2002. Geology of mankind. Nature 415:686723
     [Google Scholar]
  13. 13.
    Lewis SL, Maslin MA. 2015. Defining the Anthropocene. Nature 519:7542171–80
     [Google Scholar]
  14. 14.
    Watson JEM, Venter O. 2019. Mapping the continuum of humanity's footprint on land. One Earth 1:2175–80
     [Google Scholar]
  15. 15.
    Díaz S, Settele J, Brondízio ES, Ngo HT, Guèze M et al. 2019. Summary for Policymakers of the Global Assessment Report on Biodiversity and Ecosystem Services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. Bonn, Ger.: Intergov. Sci.-Policy Platf. Biodivers. Ecosyst. Serv.
  16. 16.
    Lyver POB, Timoti P, Davis T, Tylianakis JM. Biocultural hysteresis inhibits adaptation to environmental change. Trends Ecol. Evol. 34:771–80
     [Google Scholar]
  17. 17.
    Fletcher M-S, Hamilton R, Dressler W, Palmer L. 2021. Indigenous knowledge and the shackles of wilderness. PNAS 118:40e2022218118
     [Google Scholar]
  18. 18.
    Ellis EC, Pascual U, Mertz O. 2019. Ecosystem services and nature's contribution to people: negotiating diverse values and trade-offs in land systems. Curr. Opin. Environ. Sustain. 38:86–94
     [Google Scholar]
  19. 19.
    Morrison KD, Hammer E, Boles O, Madella M, Whitehouse N et al. 2021. Mapping past human land use using archaeological data: a new classification for global land use synthesis and data harmonization. PLOS ONE 16:4e0246662
     [Google Scholar]
  20. 20.
    Stephens L, Fuller D, Boivin N, Rick T, Gauthier N et al. 2019. Archaeological assessment reveals Earth's early transformation through land use. Science 365:6456897–902
     [Google Scholar]
  21. 21.
    Runting RK, Phinn S, Xie Z, Venter O, Watson JEM. 2020. Opportunities for big data in conservation and sustainability. Nat. Commun. 11:11–4
     [Google Scholar]
  22. 22.
    Whittaker RJ, Araújo MB, Jepson P, Ladle RJ, Watson JEM, Willis KJ. 2005. Conservation biogeography: assessment and prospect. Divers. Distrib. 11:13–23
     [Google Scholar]
  23. 23.
    Soulé ME. 1991. Conservation: tactics for a constant crisis. Science 253:5021744–50
     [Google Scholar]
  24. 24.
    Noss RF. 1983. A regional landscape approach to maintain diversity. Bioscience 33:11700–6
     [Google Scholar]
  25. 25.
    Noss RF. 1990. Indicators for monitoring biodiversity: a hierarchical approach. Conserv. Biol. 4:4355–64
     [Google Scholar]
  26. 26.
    Melesse AM, Weng Q, Thenkabail PS, Senay GB. 2007. Remote sensing sensors and applications in environmental resources mapping and modelling. Sensors 7:123209–41
     [Google Scholar]
  27. 27.
    Olson JS, Watts JA, Allison LJ. 1985. Major world ecosystem complexes ranked by carbon in live vegetation: a database (NDP-017) Carbon Dioxide Inf. Anal. Cent. Oak Ridge Natl. Lab. Oak Ridge, TN.: https://cdiac.ess-dive.lbl.gov/epubs/ndp/ndp017/ndp017_1985.html
  28. 28.
    Matthews E. 1983. Global vegetation and land use: new high-resolution data bases for climate studies. J. Appl. Meteorol. Climatol. 22:3474–87
     [Google Scholar]
  29. 29.
    Defries RS, Townshend JRG. 1994. NDVI-derived land cover classifications at a global scale. Int. J. Remote Sens. 15:173567–86
     [Google Scholar]
  30. 30.
    Hansen MC, Sohlberg R, Defries RS, Townshend JRG. 2000. Global land cover classification at 1 km spatial resolution using a classification tree approach. Int. J. Remote Sens. 21:6–71331–64
     [Google Scholar]
  31. 31.
    Bartholomé E, Belward AS. 2005. GLC2000: a new approach to global land cover mapping from earth observation data. Int. J. Remote Sens. 26:91959–77
     [Google Scholar]
  32. 32.
    DeFries R, Hansen M, Townshend J. 1995. Global discrimination of land cover types from metrics derived from AVHRR pathfinder data. Remote Sens. Environ. 54:3209–22
     [Google Scholar]
  33. 33.
    Ramankutty N, Foley JA. 1999. Estimating historical changes in global land cover: croplands from 1700 to 1992. Glob. Biogeochem. Cycles. 13:4997–1027
     [Google Scholar]
  34. 34.
    Foley JA, DeFries R, Asner GP, Barford C, Bonan G et al. 2005. Global consequences of land use. Science 309:5734570–74
     [Google Scholar]
  35. 35.
    Turner W, Spector S, Gardiner N, Fladeland M, Sterling E, Steininger M. 2003. Remote sensing for biodiversity science and conservation. Trends Ecol. Evol. 18:6306–14
     [Google Scholar]
  36. 36.
    Sulla-Menashe D, Gray JM, Abercrombie SP, Friedl MA. 2019. Hierarchical mapping of annual global land cover 2001 to present: the MODIS Collection 6 Land Cover product. Remote Sens. Environ. 222:183–94
     [Google Scholar]
  37. 37.
    Buchhorn M, Smets B, Bertels L, De Roo B, Lesiv M et al. 2020. Copernicus Global Land Service: Land Cover 100 m: collection 3: epoch 2019: Globe (V3.0.1) [Data set]. Zenodo https://doi.org/10.5281/zenodo.3939050
    [Google Scholar]
  38. 38.
    Brown CF, Brumby SP, Guzder-Williams B, Birch T, Hyde SB et al. 2022. Dynamic World, Near real-time global 10m land use land cover mapping. Sci. Data 9:251
     [Google Scholar]
  39. 39.
    Sterling SM, Ducharne A, Polcher J. 2012. The impact of global land-cover change on the terrestrial water cycle. Nat. Clim. Change 3:4385–90
     [Google Scholar]
  40. 40.
    Feddema JJ, Oleson KW, Bonan GB, Mearns LO, Buja LE et al. 2005. Atmospheric science: the importance of land-cover change in simulating future climates. . Science 310:57541674–78
     [Google Scholar]
  41. 41.
    Newbold T, Hudson LN, Hill SLL, Contu S, Lysenko I et al. 2015. Global effects of land use on local terrestrial biodiversity. Nature 520:754545–50
     [Google Scholar]
  42. 42.
    Hansen MC, DeFries RS, Townshend JRG, Carroll M, Dimiceli C, Sohlberg RA. 2003. Global percent tree cover at a spatial resolution of 500 meters: first results of the MODIS vegetation continuous fields algorithm. Earth Interact 7:101–15
     [Google Scholar]
  43. 43.
    Hansen MC, Egorov A, Roy DP, Potapov P, Ju J et al. 2011. Continuous fields of land cover for the conterminous United States using Landsat data: first results from the Web-Enabled Landsat Data (WELD) project. Remote Sens. Lett. 2:4279–88
     [Google Scholar]
  44. 44.
    Hansen MC, Potapov PV, Moore R, Hancher M, Turubanova SA et al. 2013. High-resolution global maps of 21st-century forest cover change. Science 342:6160850–53
     [Google Scholar]
  45. 45.
    Tyukavina A, Potapov P, Hansen MC, Pickens AH, Stehman SV et al. 2022. Global trends of forest loss due to fire from 2001 to 2019. Front. Remote Sens. 3:825190
     [Google Scholar]
  46. 46.
    Song XP, Hansen MC, Stehman SV, Potapov PV, Tyukavina A et al. 2018. Global land change from 1982 to 2016. Nature 560:7720639–43
     [Google Scholar]
  47. 47.
    Ying Q, Hansen MC, Potapov PV, Tyukavina A, Wang L et al. 2017. Global bare ground gain from 2000 to 2012 using Landsat imagery. Remote Sens. Environ. 194:161–76
     [Google Scholar]
  48. 48.
    Pickens AH, Hansen MC, Hancher M, Stehman SV, Tyukavina A et al. 2020. Mapping and sampling to characterize global inland water dynamics from 1999 to 2018 with full Landsat time-series. Remote Sens. Environ. 243:111792
     [Google Scholar]
  49. 49.
    Hansen MC, Stehman SV, Potapov PV, Loveland TR, Townshend JRG et al. 2008. Humid tropical forest clearing from 2000 to 2005 quantified by using multitemporal and multiresolution remotely sensed data. PNAS 105:279439–44
     [Google Scholar]
  50. 50.
    Potapov P, Hansen MC, Pickens A, Hernandez-Serna A, Tyukavina A et al. 2022. The Global 2000–2020 Land Cover and Land Use Change Dataset derived from the Landsat archive: first results. Front. Remote Sens. 3:856903
     [Google Scholar]
  51. 51.
    Ellis EC, Ramankutty N. 2008. Putting people in the map: anthropogenic biomes of the world. Front. Ecol. Environ. 6:8439–47
     [Google Scholar]
  52. 52.
    Hoskins AJ, Bush A, Gilmore J, Harwood T, Hudson LN et al. 2016. Downscaling land-use data to provide global 30" estimates of five land-use classes. Ecol. Evol. 6:93040–55
     [Google Scholar]
  53. 53.
    Zhang Z, Liu Q, Wang Y. 2018. Road extraction by deep residual U-Net. IEEE Geosci. Remote Sens. Lett. 15:5749–53
     [Google Scholar]
  54. 54.
    Reinermann S, Asam S, Kuenzer C. 2020. Remote sensing of grassland production and management—a review. Remote Sens 12:121949
     [Google Scholar]
  55. 55.
    Corbane C, Syrris V, Sabo F, Politis P, Melchiorri M et al. 2021. Convolutional neural networks for global human settlements mapping from Sentinel-2 satellite imagery. Neural Comput. Appl. 33:126697–720
     [Google Scholar]
  56. 56.
    Sharma RC, Tateishi R, Hara K, Gharechelou S, Iizuka K. 2016. Global mapping of urban built-up areas of year 2014 by combining MODIS multispectral data with VIIRS nighttime light data. Int. J. Digit. Earth 9:101004–20
     [Google Scholar]
  57. 57.
    Hinton JC. 2007. GIS and remote sensing integration for environmental applications. Int. J. GIS 10:7877–90
     [Google Scholar]
  58. 58.
    Goldewijk KK. 2001. Estimating global land use change over the past 300 years: the HYDE database. Glob. Biogeochem. Cycles 15:2417–33
     [Google Scholar]
  59. 59.
    Cent. Int. Earth Sci. Inf. Netw., Columbia Univ 2016. Gridded Population of the World, Version 4 (GPWv4): population count NASA Socioecon. Data Appl. Cent. Palisades, NY.: http://dx.doi.org/10.7927/H4X63JVC. Accessed July 1, 2023
  60. 60.
    Dobson JE, Bright EA, Coleman PR, Durfee RC, Worley BA. 2000. LandScan: a global population database for estimating populations at risk. Photogramm. Eng. Remote Sens. 66:7849–57
     [Google Scholar]
  61. 61.
    Tiecke TG, Liu X, Zhang A, Gros A, Li N et al. 2017. Mapping the world population one building at a time. World Bank https://doi.org/10.1596/33700
    [Google Scholar]
  62. 62.
    Ramankutty N, Evan AT, Monfreda C, Foley JA. 2008. Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000. Glob. Biogeochem. Cycles 22:1 https://doi.org/10.1029/2007GB002952
    [Google Scholar]
  63. 63.
    Kuemmerle T, Erb K, Meyfroidt P, Müller D, Verburg PH et al. 2013. Challenges and opportunities in mapping land use intensity globally. Curr. Opin. Environ. Sustain. 5:5484–93
     [Google Scholar]
  64. 64.
    Muñoz L, Hausner VH, Runge C, Brown G, Daigle R. 2020. Using crowdsourced spatial data from Flickr versus PPGIS for understanding nature's contribution to people in Southern Norway. People Nat 2:2437–49
     [Google Scholar]
  65. 65.
    Lingua F, Coops NC, Lafond V, Gaston C, Griess VC. 2022. Characterizing, mapping and valuing the demand for forest recreation using crowdsourced social media data. PLOS ONE 17:8e0272406
     [Google Scholar]
  66. 66.
    Sanderson EW, Jaiteh M, Levy MA, Redford KH, Wannebo AV, Woolmer G. 2002. The human footprint and the last of the wild. BioScience 52:10891–904
     [Google Scholar]
  67. 67.
    McCloskey JM, Spalding H. 1989. A reconnaissance-level inventory of the amount of wilderness remaining in the world. Ambio 18:4221–27
     [Google Scholar]
  68. 68.
    Verma M, Symes WS, Watson JEM, Jones KR, Allan JR et al. 2020. Severe human pressures in the Sundaland biodiversity hotspot. Conserv. Sci. Pract. 2:3e169
     [Google Scholar]
  69. 69.
    Watson J. 2016. Persistent disparities between recent rates of habitat conversion and protection and implications for future global conservation targets. Conserv. Lett. 9:6413–21
     [Google Scholar]
  70. 70.
    Macdonald DW, Chiaverini L, Bothwell HM, Kaszta Ż, Ash E et al. 2020. Predicting biodiversity richness in rapidly changing landscapes: climate, low human pressure or protection as salvation?. Biodivers. Conserv. 29:144035–57
     [Google Scholar]
  71. 71.
    Yackulic CB, Sanderson EW, Uriarte M. 2011. Anthropogenic and environmental drivers of modern range loss in large mammals. PNAS 108:104024–29
     [Google Scholar]
  72. 72.
    Di Marco M, Venter O, Possingham HP, Watson JEM. 2018. Changes in human footprint drive changes in species extinction risk. Nat. Commun. 9:14621
     [Google Scholar]
  73. 73.
    Falcão JCF, Carvalheiro LG, Guevara R, Lira-Noriega A. 2022. The risk of invasion by angiosperms peaks at intermediate levels of human influence. Basic Appl. Ecol. 59:33–43
     [Google Scholar]
  74. 74.
    Skinner EB, Glidden CK, MacDonald AJ, Mordecai EA. 2023. Human footprint is associated with shifts in the assemblages of major vector-borne diseases. Nat. Sustain. 6:652–61
     [Google Scholar]
  75. 75.
    Keys PW, Barnes EA, Carter NH. 2021. A machine-learning approach to human footprint index estimation with applications to sustainable development. Environ. Res. Lett. 16:4044061
     [Google Scholar]
  76. 76.
    Venter O, Sanderson EW, Magrach A, Allan JR, Beher J et al. 2016. Global terrestrial Human Footprint maps for 1993 and 2009. Sci. Data. 3:160067
     [Google Scholar]
  77. 77.
    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. 25:3811–26
     [Google Scholar]
  78. 78.
    Venter O, Possingham HP, Watson JEM. 2020. The human footprint represents observable human pressures: reply to Kennedy et al. Glob. Change Biol. 26:2330–32
     [Google Scholar]
  79. 79.
    Hill NK, Woodworth BK, Phinn SR, Murray NJ, Fuller RA. 2021. Global protected-area coverage and human pressure on tidal flats. Conserv. Biol. 35:3933–43
     [Google Scholar]
  80. 80.
    Belote RT, Barnett K, Zeller K, Brennan A, Gage J. 2022. Examining local and regional ecological connectivity throughout North America. Landsc. Ecol. 37:2977–90
     [Google Scholar]
  81. 81.
    Harris NC, Murphy A, Green AR, Gámez S, Mwamidi DM, Nunez-Mir GC. 2022. Socio-ecological gap analysis to forecast species range contractions for conservation. PNAS 120:7e2201942119
     [Google Scholar]
  82. 82.
    Halpern BS, Walbridge S, Selkoe KA, Kappel CV, Micheli F et al. 2008. A global map of human impact on marine ecosystems. Science 319:5865948–52
     [Google Scholar]
  83. 83.
    Vörösmarty CJ, McIntyre PB, Gessner MO, Dudgeon D, Prusevich A et al. 2010. Global threats to human water security and river biodiversity. Nature 467:7315555–61
     [Google Scholar]
  84. 84.
    Ellis EC. 2015. Ecology in an anthropogenic biosphere. Ecol. Monogr. 85:3287–331
     [Google Scholar]
  85. 85.
    Ellis EC, Goldewijk KK, Siebert S, Lightman D, Ramankutty N. 2010. Anthropogenic transformation of the biomes, 1700 to 2000. Glob. Ecol. Biog. 19:5589–606
     [Google Scholar]
  86. 86.
    Waters CN, Zalasiewicz J, Summerhayes C, Barnosky AD, Poirier C et al. 2016. The Anthropocene is functionally and stratigraphically distinct from the Holocene. Science 351:6269 https://www.science.org/doi/10.1126/science.aad2622
    [Google Scholar]
  87. 87.
    Sanderson EW, Walston J, Robinson JG. 2018. From bottleneck to breakthrough: urbanization and the future of biodiversity conservation. BioScience 68:412–26
     [Google Scholar]
  88. 88.
    Ellis EC. 2019. Sharing the land between nature and people. Science 364:64471226–28
     [Google Scholar]
  89. 89.
    Garnett ST, Burgess ND, Fa JE, Fernández-Llamazares Á, Molnár Z et al. 2018. A spatial overview of the global importance of Indigenous lands for conservation. Nat. Sustain. 1:7369–74
     [Google Scholar]
  90. 90.
    Ellis E. 2012. All is not loss: plant biodiversity in the Anthropocene. PLOS ONE 7:e30535
     [Google Scholar]
  91. 91.
    Pekin BK, Pijanowski BC. 2012. Global land use intensity and the endangerment status of mammal species. Divers. Distrib. 18:9909–18
     [Google Scholar]
  92. 92.
    Brum FT, Gonçalves LO, Cappelatti L, Carlucci MB, Debastiani VJ et al. 2013. Land use explains the distribution of threatened New World amphibians better than climate. . PLOS ONE 8:4e60742
     [Google Scholar]
  93. 93.
    Rowan J, Beaudrot L, Franklin J, Reed KE, Smail IE et al. 2020. Geographically divergent evolutionary and ecological legacies shape mammal biodiversity in the global tropics and subtropics. PNAS 117:31559–65
     [Google Scholar]
  94. 94.
    Miraldo A, Li S, Borregaard MK, Flórez-Rodríguez A, Gopalakrishnan S et al. 2016. An Anthropocene map of genetic diversity. Science 353:63071532–35
     [Google Scholar]
  95. 95.
    Quinn JE, Awada T, Trindade F, Fulginiti L, Perrin R. 2017. Combining habitat loss and agricultural intensification improves our understanding of drivers of change in avian abundance in a North American cropland anthrome. Ecol. Evol. 7:3803–14
     [Google Scholar]
  96. 96.
    Van Dyke F, Lamb RL. 2020. Conservation Biology—The Anthropocene: Conservation in a Human-Dominated Nature Cham, Switz.: Springer
  97. 97.
    Dinerstein E. 2017. An ecoregion-based approach to protecting half the terrestrial realm. Bioscience 67:534–45
     [Google Scholar]
  98. 98.
    Obura DO, Katerere Y, Mayet M, Kaelo D, Msweli S et al. 2021. Integrate biodiversity targets from local to global levels. Science 373:6556746–48
     [Google Scholar]
  99. 99.
    Lawrence PJ, Chase TN. 2010. Investigating the climate impacts of global land cover change in the community climate system model. Int. J. Clim. 30:132066–87
     [Google Scholar]
  100. 100.
    Tucker MA, Böhning-Gaese K, Fagan WF, Fryxell JM, Van Moorter B et al. 2018. Moving in the Anthropocene: global reductions in terrestrial mammalian movements. Science 26:6374466–69
     [Google Scholar]
  101. 101.
    Pillay R, Watson JEM, Hansen AJ, Jantz PA, Aragon-Osejo J et al. 2022. Humid tropical vertebrates are at lower risk of extinction and population decline in forests with higher structural integrity. Nat. Ecol. Evol. 6:1840–49
     [Google Scholar]
  102. 102.
    Jagadesh S, Combe M, Gozlan RE. 2022. Human-altered landscapes and climate to predict human infectious disease hotspots. Trop. Med. Infect. Dis. 7:7124
     [Google Scholar]
  103. 103.
    Maxwell SL, Evans T, Watson JEM, Morel A, Grantham H et al. 2019. Degradation and forgone removals increase the carbon impact of intact forest loss by 626%. Sci. Adv. 5:10eaax2546
     [Google Scholar]
  104. 104.
    Purvis A, Molnar Z, Obura D, Ichii K, Willis K et al. 2019. Status and trends—nature. Global Assessment Report on Biodiversity and Ecosystem Services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services ES Brondízio, J Settele, S Díaz, HT Ngo 201–308. Bonn, Ger.: Int. Sci. Policy Biodivers. Ecosyst. Serv.
     [Google Scholar]
  105. 105.
    Masson-Delmotte V, Zhai P, Pörtner H-O, Roberts D, Skea J et al. 2018. Global Warming of 1.5°C. An IPCC Special Report on the Impacts of Global Warming of 1.5°C above Pre-Industrial Levels and Related Global Greenhouse Gas Emission Pathways, in the Context of Strengthening the Global Response to the Threat of Climate Change, Sustainable Development, and Efforts to Eradicate Poverty—Summary for Policymakers. Cambridge, UK: Cambridge Univ. Press
  106. 106.
    Secr. Conv. Biol. Divers 2020. Global Biodiversity Outlook 5 Montreal: Conv. Biol. Divers.
  107. 107.
    Biodivers. Indic. Partnersh 2023. The Biodiversity Indicators Partnership https://www.bipindicators.net
  108. 108.
    Watson JEM, Keith DA, Strassburg BBN, Venter O, Williams B, Nicholson E. 2020. Set a global target for ecosystems. Nature 578:7795360–62
     [Google Scholar]
  109. 109.
    Nicholson E, Watermeyer KE, Rowland JA, Sato CF, Stevenson SL et al. 2021. Scientific foundations for an ecosystem goal, milestones and indicators for the post-2020 global biodiversity framework. Nat. Ecol. Evol. 5:101338–49
     [Google Scholar]
  110. 110.
    Martin TG, Watson JEM. 2016. Intact ecosystems provide best defence against climate change. Nat. Clim. Change. 6:122–24
     [Google Scholar]
  111. 111.
    Watson JEM, Evans T, Venter O, Williams B, Tulloch A et al. 2018. The exceptional value of intact forest ecosystems. Nat. Ecol. Evol. 2:599–610
     [Google Scholar]
  112. 112.
    Secr. Conv. Biol. Divers 2022. Kunming-Montreal Global Biodiversity Framework Montreal: Conv. Biol. Divers.
  113. 113.
    Hobbs RJ. 2016. Degraded or just different? Perceptions and value judgements in restoration decisions. Restor. Ecol. 24:2153–58
     [Google Scholar]
  114. 114.
    Rowland JA, Bland LM, Keith DA, Juffe-Bignoli D, Burgman MA et al. 2019. Ecosystem indices to support global biodiversity conservation. Cons. Lett. 13:e12680
     [Google Scholar]
  115. 115.
    Hansen AJ, Noble BP, Veneros J, East A, Goetz SJ et al. 2021. Toward monitoring forest ecosystem integrity within the post-2020 Global Biodiversity Framework. Cons. Lett. 14:4e12822
     [Google Scholar]
  116. 116.
    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. 11:15978
     [Google Scholar]
  117. 117.
    Hansen AJ, Burns P, Ervin J, Goetz SJ, Hansen M et al. 2020. A policy-driven framework for conserving the best of Earth's remaining moist tropical forests. Nat. Ecol. Evol. 4:101377–84
     [Google Scholar]
  118. 118.
    Hansen A, Barnett K, Jantz P, Phillips L, Goetz SJ et al. 2019. Global humid tropics forest structural condition and forest structural integrity maps. Sci. Data. 6:1232
     [Google Scholar]
  119. 119.
    Beyer HL, Venter O, Grantham HS, Watson JEM. 2020. Substantial losses in ecoregion intactness highlight urgency of globally coordinated action. Conserv. Lett. 13:2e12692
     [Google Scholar]
  120. 120.
    Halpern BS, Frazier M, Potapenko J, Casey KS, Koenig K et al. 2015. Spatial and temporal changes in cumulative human impacts on the world's ocean. Nat. Commun. 6:7615
     [Google Scholar]
  121. 121.
    Jones KR, Klein CJ, Halpern BS, Venter O, Grantham H et al. 2018. The location and protection status of Earth's diminishing marine wilderness. Curr. Biol. 28:152506–12.e3
     [Google Scholar]
  122. 122.
    Jumani S, Deitch MJ, Valle D, Machado S, Lecours V et al. 2022. A new index to quantify longitudinal river fragmentation: conservation and management implications. Ecol. Indic. 136:108680
     [Google Scholar]
  123. 123.
    Grill G, Lehner B, Thieme M, Geenen B, Tickner D et al. 2019. Mapping the world's free-flowing rivers. Nature 569:7755215–21
     [Google Scholar]
  124. 124.
    Butt N, Halpern BS, O'Hara CC, Allcock AL, Polidoro B et al. 2022. A trait-based framework for assessing the vulnerability of marine species to human impacts. Ecosphere 13:2e3919
     [Google Scholar]
  125. 125.
    Allan JR, Watson JEM, Di Marco M, O'Bryan CJ, Possingham HP et al. 2019. Hotspots of human impact on threatened terrestrial vertebrates. PLOS Biol 17:12e3000598
     [Google Scholar]
  126. 126.
    O'Bryan CJ, Allan JR, Holden M, Sanderson C, Venter O et al. 2020. Intense human pressure is widespread across terrestrial vertebrate ranges. Glob. Ecol. Conserv. 21:e00882
     [Google Scholar]
  127. 127.
    Di Marco M, Santini L. 2015. Human pressures predict species’ geographic range size better than biological traits. Glob. Change Biol. 21:62169–78
     [Google Scholar]
  128. 128.
    Kühl HS, Boesch C, Kulik L, Haas F, Arandjelovic M et al. 2019. Human impact erodes chimpanzee behavioral diversity. Science 363:64341453–55
     [Google Scholar]
  129. 129.
    O'Hara CC, Frazier M, Halpern BS. 2021. At-risk marine biodiversity faces extensive, expanding, and intensifying human impacts. Science 372:653784–87
     [Google Scholar]
  130. 130.
    Miteva DA, Pattanayak SK, Ferraro PJ. 2012. Evaluation of biodiversity policy instruments: What works and what doesn't?. Oxf. Rev. Econ. Policy 28:169–92
     [Google Scholar]
  131. 131.
    Maxwell SL, Cazalis V, Dudley N, Hoffmann M, Rodrigues ASL et al. 2020. Area-based conservation in the twenty-first century. Nature 586:217–27
     [Google Scholar]
  132. 132.
    Jones KR, Venter O, Fuller RF, Allan JA, Maxwell SL et al. 2018. One-third of global protected land is under intense human pressure. Science 360:6390788–91
     [Google Scholar]
  133. 133.
    Maxwell SL, Fuller RA, Brooks TM, Watson JEM. 2016. Biodiversity: the ravages of guns, nets and bulldozers. Nature 536:143–45
     [Google Scholar]
  134. 134.
    Wolf C, Levi T, Ripple WJ, Zárrate-Charry DA, Betts MG. 2021. A forest loss report card for the world's protected areas. Nat. Ecol. Evol. 5:4520–29
     [Google Scholar]
  135. 135.
    Fritz S, Laso Bayas JC, See L, Schepaschenko D, Hofhansl F et al. 2022. A continental assessment of the drivers of tropical deforestation with a focus on protected areas. Front. Conserv. Sci. 3:830248
     [Google Scholar]
  136. 136.
    Buřivalová Z, Hart SJ, Radeloff VC, Srinivasan U. 2021. Early warning sign of forest loss in protected areas. Curr. Biol. 31:204620–26.e3
     [Google Scholar]
  137. 137.
    Asamoah EF, Beaumont LJ, Maina JM. 2021. Climate and land-use changes reduce the benefits of terrestrial protected areas. Nat. Clim. Change 11:121105–10
     [Google Scholar]
  138. 138.
    Cazalis V, Barnes MD, Johnston A, Watson JEM, Şekercioğlu CH, Rodrigues ASL. 2021. Mismatch between bird species sensitivity and the protection of intact habitats across the Americas. Ecol. Lett. 24:112394–405
     [Google Scholar]
  139. 139.
    Brennan A, Naidoo R, Greenstreet L, Mehrabi Z, Ramankutty N, Kremen C. 2022. Functional connectivity of the world's protected areas. Science 376:65971101–4
     [Google Scholar]
  140. 140.
    Ramírez-Delgado JP, Di Marco M, Watson JEM, Johnson CJ, Rondinini C et al. 2022. Matrix condition mediates the effects of habitat fragmentation on species extinction risk. Nat. Commun. 13:595
     [Google Scholar]
  141. 141.
    Garibaldi LA, Oddi FJ, Miguez FE, Bartomeus I, Orr MC et al. 2021. Working landscapes need at least 20% native habitat. Conserv. Lett. 14:2e12773
     [Google Scholar]
  142. 142.
    Kremen C, Merenlender AM. 2018. Landscapes that work for biodiversity and people. Science 362:6412eaau6020
     [Google Scholar]
  143. 143.
    Tscharntke T, Grass I, Wanger TC, Westphal C, Batáry P. 2021. Beyond organic farming—harnessing biodiversity-friendly landscapes. Trends Ecol. Evol. 36:10919–30
     [Google Scholar]
  144. 144.
    Locke H, Ellis EC, Venter O, Schuster R, Ma K et al. 2019. Three global conditions for biodiversity conservation and sustainable use: an implementation framework. Natl. Sci. Rev. 6:61080–82
     [Google Scholar]
  145. 145.
    Martin LJ, Quinn JE, Ellis EC, Shaw MR, Dorning MA et al. 2014. Conservation opportunities across the world's anthromes. Divers. Distrib. 20:7745–55
     [Google Scholar]
  146. 146.
    Mehrabi Z, Ellis EC, Ramankutty N. 2018. The challenge of feeding the world while conserving half the planet. . Nat. Sustain. 2018 1:8409–12
     [Google Scholar]
  147. 147.
    Wintle BA, Kujala H, Whitehead A, Cameron A, Veloz S et al. 2019. Global synthesis of conservation studies reveals the importance of small habitat patches for biodiversity. PNAS 116:3909–14
     [Google Scholar]
  148. 148.
    Quinn JE, Cook EK, Gauthier N. 2021. Patterns of vertebrate richness across global anthromes: prioritizing conservation beyond biomes and ecoregions. Glob. Ecol. Conserv. 27:e01591
     [Google Scholar]
  149. 149.
    Blois JL, Williams JW, Fitzpatrick MC, Jackson ST, Ferrier S. 2013. Space can substitute for time in predicting climate-change effects on biodiversity. PNAS 110:239374–79
     [Google Scholar]
  150. 150.
    Pillay R. 2022. Humans pressure wetland multifunctionality. Nat. Ecol. Evol. 6:91250–51
     [Google Scholar]
  151. 151.
    Surovell T, Waguespack N, Brantingham PJ. 2005. Global archaeological evidence for proboscidean overkill. PNAS 102:176231–36
     [Google Scholar]
  152. 152.
    Johnson C. 2006. Australia's Mammal Extinctions: A 50,000 Year History Port Melbourne, Vic., Aus.: Cambridge Univ. Press
  153. 153.
    Sandom C, Faurby S, Sandel B, Svenning JC. 2014. Global late Quaternary megafauna extinctions linked to humans, not climate change. Proc. R. Soc. B 281:2013325
     [Google Scholar]
  154. 154.
    Malhi Y, Doughty CE, Galetti M, Smith FA, Svenning JC, Terborgh JW. 2016. Megafauna and ecosystem function from the Pleistocene to the Anthropocene. PNAS 113:4838–46
     [Google Scholar]
  155. 155.
    Watson JEM, Venter O. 2021. Wilderness. Curr. Biol. 31:19R1169–72
     [Google Scholar]
  156. 156.
    Díaz S. 2019. Pervasive human-driven decline of life on Earth points to the need for transformative change. Science 366:eaax3100
     [Google Scholar]
  157. 157.
    Bird RB, Nimmo D. Restore the lost ecological functions of people. Nat. Ecol. Evol. 2:1050–52
     [Google Scholar]
  158. 158.
    Powers RP, Jetz W. 2019. Global habitat loss and extinction risk of terrestrial vertebrates under future land-use-change scenarios. Nat. Clim. Change 9:4323–29
     [Google Scholar]
  159. 159.
    Molotoks A, Henry R, Stehfest E, Doelman J, Havlik P et al. 2020. Comparing the impact of future cropland expansion on global biodiversity and carbon storage across models and scenarios. Philos. Trans. R. Soc. B 375:20190189
     [Google Scholar]
  160. 160.
    Laurance WF, Clements GR, Sloan S, O'Connell CS, Mueller ND et al. 2014. A global strategy for road building. Nature 513:7517229–32
     [Google Scholar]
  161. 161.
    Dinerstein E, Vynne C, Sala E, Joshi AR, Fernando S et al. 2019. A global deal for nature: guiding principles, milestones, and targets. Sci. Adv. 5:4
     [Google Scholar]
  162. 162.
    Zahn LM. 2016. Can modern technology prevent extinction?. Science 352:6287784–85
     [Google Scholar]
  163. 163.
    Berger-Tal O, Lahoz-Monfort JJ. 2018. Conservation technology: the next generation. Conserv. Lett. 11:6e12458
     [Google Scholar]
  164. 164.
    Lahoz-Monfort JJ, Chadès I, Davies A, Fegraus E, Game E et al. 2019. A call for international leadership and coordination to realize the potential of conservation technology. Bioscience 69:10823–32
     [Google Scholar]
  165. 165.
    Iacona G, Ramachandra A, McGowan J, Davies A, Joppa L et al. 2019. Identifying technology solutions to bring conservation into the innovation era. Front. Ecol. Environ. 17:10591–98
     [Google Scholar]
  166. 166.
    Lesiv M, Schepaschenko D, Buchhorn M, See L, Dürauer M et al. 2022. Global forest management data for 2015 at a 100m resolution. Sci. Data 9:199
     [Google Scholar]
  167. 167.
    Kroodsma DA, Mayorga J, Hochberg T, Miller NA, Boerder K et al. 2018. Tracking the global footprint of fisheries. Science 359:6378904–8
     [Google Scholar]
  168. 168.
    Ford JH, Peel D, Kroodsma D, Hardesty BD, Rosebrock U, Wilcox C. 2018. Detecting suspicious activities at sea based on anomalies in automatic identification systems transmissions. PLOS ONE 13:8e0201640
     [Google Scholar]
  169. 169.
    Yang J, Gong P, Fu R, Zhang M, Chen J et al. 2013. The role of satellite remote sensing in climate change studies. Nat. Clim. Change 3:10875–83
     [Google Scholar]
  170. 170.
    Shugar DH, Jacquemart M, Shean D, Bhushan S, Upadhyay K et al. 2021. A massive rock and ice avalanche caused the 2021 disaster at Chamoli, Indian Himalaya. Science 373:6552300–6
     [Google Scholar]
  171. 171.
    Shepherd A, Fricker HA, Farrell SL. 2018. Mass balance of the Antarctic Ice Sheet from 1992 to 2017. Nature 558:7709219–22
     [Google Scholar]
  172. 172.
    Bindschadler RA, Nowicki S, Abe-Ouchi A, Aschwanden A, Choi H et al. 2013. Ice-sheet model sensitivities to environmental forcing and their use in projecting future sea level (the SeaRISE project). J. Glaciol. 59:214195–224
     [Google Scholar]
  173. 173.
    Gandikota DM, Gladkova T, Tran K-A, Bapat S, Richkus J, Arnold Dr J. 2022. AI augmentation to remote sensing imagery in forestry conservation. 2022 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)1–16. Washington, DC: IEEE
     [Google Scholar]
  174. 174.
    Botelho J, Costa SCP, Ribeiro JG, Souza CM. 2022. Mapping roads in the Brazilian Amazon with artificial intelligence and Sentinel-2. Remote Sens. 14:153625
     [Google Scholar]
  175. 175.
    Rapinel S, Panhelleux L, Gayet G, Vanacker R, Lemercier B et al. 2023. National wetland mapping using remote-sensing-derived environmental variables, archive field data, and artificial intelligence. Helyon 9:2e13482
     [Google Scholar]
  176. 176.
    Abid SK, Sulaiman N, Chan SW, Nazir U, Abid M et al. 2021. Toward an integrated disaster management approach: how artificial intelligence can boost disaster management. Sustainability 13:2212560
     [Google Scholar]
  177. 177.
    Singh H, Dwivedi RK, Kumar A, Mishra VK. 2022. A review on AI techniques applied on tree detection in UAV and remotely sensed imagery. Proceedings of the 2022 11th International Conference on System Modeling and Advancement in Research Trends (16th–17th December, 2022): SMART–20221446–50. Washington, DC: IEEE
     [Google Scholar]
/content/journals/10.1146/annurev-environ-112420-013640
Loading
Mapping Industrial Influences on Earth's Ecology
Annual Review of Environment and Resources 48, 289 (2023); https://doi.org/10.1146/annurev-environ-112420-013640
/content/journals/10.1146/annurev-environ-112420-013640
/content/journals/10.1146/annurev-environ-112420-013640
Loading

Data & Media loading...

  • Article Type: Review Article

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error