Increasing impacts of land use on biodiversity and carbon sequestration driven by population and economic growth (original) (raw)

References

1. Venter, O. et al. Sixteen years of change in the global terrestrial human footprint and implications for biodiversity conservation. Nat. Commun. 7, 12558 (2016).
   CAS PubMed PubMed Central Google Scholar
2. Newbold, T. et al. Global effects of land use on local terrestrial biodiversity. Nature 520, 45–50 (2015).
   CAS PubMed Google Scholar
3. MA Board. Millenium Ecosystem Assesment—Ecosystems and Human Well-Being (Island Press, Washington, DC, 2005).
4. West, P. C. et al. Leverage points for improving global food security and the environment. Science 345, 325–328 (2014).
   CAS PubMed Google Scholar
5. Cardinale, B. J. et al. Biodiversity loss and its impact on humanity. Nature 486, 59–67 (2012).
   CAS PubMed Google Scholar
6. Transforming our World: The 2030 Agenda for Sustainable Development (United Nations, 2015).
7. Lenzen, M. et al. International trade drives biodiversity threats in developing nations. Nature 486, 109–112 (2012).
   CAS PubMed Google Scholar
8. Wilting, H. C., Schipper, A. M., Bakkenes, M., Meijer, J. R. & Huijbregts, M. A. J. Quantifying biodiversity losses due to human consumption: a global-scale footprint analysis. Environ. Sci. Technol. 51, 3298–3306 (2017).
   CAS PubMed Google Scholar
9. Verones, F., Moran, D., Stadler, K., Kanemoto, K. & Wood, R. Resource footprints and their ecosystem consequences. Sci. Rep. 7, 40743 (2017).
   CAS PubMed PubMed Central Google Scholar
10. Laurance, W. F., Sayer, J. & Cassman, K. G. Agricultural expansion and its impacts on tropical nature. Trends. Ecol. Evol. 29, 107–116 (2014).
    PubMed Google Scholar
11. 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 PubMed Google Scholar
12. Erb, K.-H., Krausmann, F., Lucht, W. & Haberl, H. Embodied HANPP: mapping the spatial disconnect between global biomass production and consumption. Ecol. Econ. 69, 328–334 (2009).
    Google Scholar
13. Pereira, H. M. et al. Essential biodiversity variables. Science 339, 277–278 (2013).
    CAS PubMed Google Scholar
14. Reyers, B., Stafford-Smith, M., Erb, K.-H., Scholes, R. J. & Selomane, O. Essential variables help to focus sustainable development goals monitoring. Curr. Opin. Environ. Sustain. 26–27, 97–105 (2017).
    Google Scholar
15. Pan, Y. et al. A large and persistent carbon sink in the world’s forests. Science 333, 988–993 (2011).
    CAS PubMed Google Scholar
16. Ehrlich, P. R. & Holdren, J. P. Impact of population growth. Science 171, 1212–1217 (1971).
    CAS PubMed Google Scholar
17. Stadler, K. et al. EXIOBASE 3: Developing a time series of detailed environmentally extended multi-regional input-output tables. J. Ind. Ecol. 22, 502–515 (2018).
    Google Scholar
18. Ceballos, G. et al. Accelerated modern human–induced species losses: entering the sixth mass extinction. Sci. Adv. 1, e1400253 (2015).
    PubMed PubMed Central Google Scholar
19. Blanco, G. et al. in Climate Change 2014: Mitigation of Climate Change (eds Edenhofer, O. et al.) (IPCC, Cambridge Univ. Press, 2014).
20. Vijay, V., Pimm, S. L., Jenkins, C. N. & Smith, S. J. The impacts of oil palm on recent deforestation and biodiversity loss. PLoS ONE 11, e0159668 (2016).
    PubMed PubMed Central Google Scholar
21. Ward, J. D. et al. Is decoupling GDP growth from environmental impact possible? PLoS ONE 11, e0164733 (2016).
    PubMed PubMed Central Google Scholar
22. Archive: Household Consumption Expenditure—National Accounts—Statistics Explained; http://ec.europa.eu/eurostat/statistics-explained/index.php/Archive:Household_consumption_expenditure_-_national_accounts (Eurostat, 2013).
23. Shao, Q., Schaffartzik, A., Mayer, A. & Krausmann, F. The high ‘price’ of dematerialization: a dynamic panel data analysis of material use and economic recession. J. Clean. Prod. 167, 120–132 (2017).
    Google Scholar
24. EU-27 Construction Activity falls by 16% From its Precrisis High by the Second Quarter of 2011 (Eurostat, 2011).
25. U.S. Forest Resource Facts and Historical Trends (United States Department of Agriculture, 2014).
26. Seppelt, R., Manceur, A., Liu, J., Fenichel, E. & Klotz, S. Synchronized peak-rate years of global resources use. Ecol. Soc. 19, 50 (2014).
27. Gerstner, K. et al. Editor’s choice: review: effects of land use on plant diversity—a global meta-analysis. J. Appl. Ecol. 51, 1690–1700 (2014).
    Google Scholar
28. Alcott, B. Impact caps: why population, affluence and technology strategies should be abandoned. J. Clean. Prod. 18, 552–560 (2010).
    Google Scholar
29. Decoupling Natural Resource Use and Environmental Impacts from Economic Growth, A Report of the Working Group on Decoupling to the International Resource Panel (UNEP, 2011).
30. Abel, G. J., Barakat, B., Kc, S. & Lutz, W. Meeting the sustainable development goals leads to lower world population growth. Proc. Natl Acad. Sci. USA 113, 14294–14299 (2016).
    CAS PubMed PubMed Central Google Scholar
31. Godfray, H. C. J. et al. Meat consumption, health, and the environment. Science 361, eaam5324 (2018).
    PubMed Google Scholar
32. Poore, J. & Nemecek, T. Reducing food’s environmental impacts through producers and consumers. Science 360, 987–992 (2018).
    CAS PubMed Google Scholar
33. United Nations Regional Groups of Member States (United Nations, 2014).
34. Erb, K.-H. et al. A comprehensive global 5 min resolution land-use data set for the year 2000 consistent with national census data. J. Land Use Sci. 2, 191–224 (2007).
    Google Scholar
35. Ramankutty, N., Evan, A. T., Monfreda, C. & Foley, J. A. Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000. Glob. Biogeochem. Cycles 22, GB1003 (2008).
    Google Scholar
36. Statistical Databases; http://faostat.fao.org/ (FAO, 2014).
37. Monfreda, C., Ramankutty, N. & Foley, J. A. Farming the planet: 2. Geographic distribution of crop areas, yields, physiological types, and net primary production in the year 2000. Glob. Biogeochem. Cycles 22, GB1022 (2008).
    Google Scholar
38. Schepaschenko, D. et al. Development of a global hybrid forest mask through the synergy of remote sensing, crowdsourcing and FAO statistics. Remote Sens. Environ. 162, 208–220 (2015).
    Google Scholar
39. Potapov, P. et al. The last frontiers of wilderness: tracking loss of intact forest landscapes from 2000 to 2013. Sci. Adv. 3, e1600821 (2017).
    PubMed PubMed Central Google Scholar
40. Müller, M., Pérez Dominguez, I. & Gay, S. H. Construction of Social Accounting Matrices for EU27 with Disaggregated Agricultural Sectors (agroSAM) (European Commission, 2009).
41. Erb, K. H. et al. Biomass turnover time in terrestrial ecosystems halved by land use. Nat. Geosci. 9, 674–678 (2016).
    CAS Google Scholar
42. Erb, K.-H. et al. Unexpectedly large impact of forest management and grazing on global vegetation biomass. Nature 553, 73–76 (2018).
    CAS PubMed Google Scholar
43. Evans, J. Planted Forests: Uses, Impacts and Sustainability (CABI Publishing, Wallingford, 2009).
44. Penna, I. Understanding the FAO’s ‘Wood Supply from Planted Forests’ Projections (Centre for Environmental Management, Univ. Ballarat, 2010).
45. Pereira, H. M. & Daily, G. C. Modeling biodiversity dynamics in countryside landscapes. Ecology 87, 1877–1885 (2006).
    PubMed Google Scholar
46. Pereira, H. M., Ziv, G. & Miranda, M. Countryside species–area relationship as a valid alternative to the matrix-calibrated species–area model. Conserv. Biol. 28, 874–876 (2014).
    PubMed PubMed Central Google Scholar
47. Martins, I. S. & Pereira, H. M. Improving extinction projections across scales and habitats using the countryside species–area relationship. Sci. Rep. 7, 12899 (2017).
    PubMed PubMed Central Google Scholar
48. Hanski, I., Zurita, G. A., Bellocq, M. I. & Rybicki, J. Species–fragmented area relationship. Proc. Natl Acad. Sci. USA 110, 12715–12720 (2013).
    CAS PubMed PubMed Central Google Scholar
49. Rybicki, J. & Hanski, I. Species–area relationships and extinctions caused by habitat loss and fragmentation. Ecol. Lett. 16, 27–38 (2013).
    PubMed Google Scholar
50. Rosenzweig, M. L. Species Diversity in Space and Tme (Cambridge Univ. Press, Cambridge, 1995).
51. Storch, D., Keil, P. & Jetz, W. Universal species–area and endemics–area relationships at continental scales. Nature 488, 78–81 (2012).
    CAS PubMed Google Scholar
52. Chaudhary, A., Verones, F., de Baan, L. & Hellweg, S. Quantifying land use impacts on biodiversity: combining species–area models and vulnerability indicators. Environ. Sci. Technol. 49, 9987–9995 (2015).
    CAS PubMed Google Scholar
53. Sodhi, N. S., Lee, T. M., Koh, L. P. & Brook, B. W. A meta-analysis of the impact of anthropogenic forest disturbance on Southeast Asia’s biotas. Biotropica 41, 103–109 (2009).
    Google Scholar
54. Hudson, L. N., Newbold, T., Contu, S. & Hill, S. L. L. The 2016 Release of the PREDICTS Database (Natural History Museum Data Portal, 2016).
55. ArcGIS (Environmental Systems Resource Institute, 2009).
56. Holt, B. G. et al. An update of Wallace’s Zoogeographic Regions of the World. Science 339, 74–78 (2013).
    CAS PubMed Google Scholar
57. Bird Species Distribution Maps of the World (BirdLife International and NatureServe, 2014).
58. Python Language Reference, v.2.7 (Python Software Foundation, 2010).
59. de Baan, L., Mutel, C. L., Curran, M., Hellweg, S. & Koellner, T. Land use in life cycle assessment: global characterization factors based on regional and global potential species extinction. Environ. Sci. Technol. 47, 9281–9290 (2013).
    PubMed Google Scholar
60. Holtsmark, B. Harvesting in boreal forests and the biofuel carbon debt. Clim. Change 112, 415–428 (2011).
    Google Scholar
61. Houghton, R. A. Revised estimates of the annual net flux of carbon to the atmosphere from changes in land use and land management 1850-2000. Tellus B 55, 378–390 (2003).
    Google Scholar
62. Kastner, T., Erb, K.-H. & Nonhebel, S. International wood trade and forest change: a global analysis. Glob. Environ. Change 21, 947–956 (2011).
    Google Scholar
63. Global Ecological Zoning for the Global Forest Resources Assessment, 2000 (Food and Agriculture Organization of the United Nations, 2001).
64. Ramankutty, N. & Foley, J. Estimating historical changes in global land cover: croplands from 1700 to 1992. Glob. Biogeochem. Cycles 13, 997–1027 (1999).
    CAS Google Scholar
65. Olson, D. M. et al. Terrestrial ecoregions of the world: a new map of life on Earth. A new global map of terrestrial ecoregions provides an innovative tool for conserving biodiversity. Bioscience 51, 933–938 (2001).
    Google Scholar
66. Krausmann, F., Erb, K.-H., Gingrich, S., Lauk, C. & Haberl, H. Global patterns of socioeconomic biomass flows in the year 2000: a comprehensive assessment of supply, consumption and constraints. Ecol. Econ. 65, 471–487 (2008).
    Google Scholar
67. Lauk, C., Haberl, H., Erb, K.-H., Gingrich, S. & Krausmann, F. Global socioeconomic carbon stocks in long-lived products 1900–2008. Environ. Res. Lett. 7, 034023 (2012).
    Google Scholar
68. Schlesinger, W. H. Are wood pellets a green fuel? Science 359, 1328–1329 (2018).
    CAS PubMed Google Scholar
69. Pingoud, K., Ekholm, T., Sievänen, R., Huuskonen, S. & Hynynen, J. Trade-offs between forest carbon stocks and harvests in a steady state—a multi-criteria analysis. J. Environ. Manage. 210, 96–103 (2018).
    PubMed Google Scholar
70. Davis, S. J. & Caldeira, K. Consumption-based accounting of CO2 emissions. Proc. Natl Acad. Sci. USA 107, 5687–5692 (2010).
    CAS PubMed PubMed Central Google Scholar
71. Wiedmann, T. O. et al. The material footprint of nations. Proc. Natl Acad. Sci. USA 112, 6271–6276 (2015).
    CAS PubMed Google Scholar
72. Marques, A., Verones, F., Kok, M. T., Huijbregts, M. A. & Pereira, H. M. How to quantify biodiversity footprints of consumption? A review of multi-regional input–output analysis and life cycle assessment. Curr. Opin. Environ. Sustain. 29, 75–81 (2017).
    Google Scholar
73. Kitzes, J. An introduction to environmentally-extended input-output analysis. Resources 2, 489–503 (2013).
    Google Scholar
74. Kanemoto, K., Lenzen, M., Peters, G. P., Moran, D. D. & Geschke, A. Frameworks for comparing emissions associated with production, consumption, and international trade. Environ. Sci. Technol. 46, 172–179 (2012).
    CAS PubMed Google Scholar
75. Miller, R. & Bair, P. Input-Ouput Analysis. Foundations and Extensions (Cambridge Univ. Press, Cambridge, 2009).
76. Lenzen, M., Wood, R. & Wiedmann, T. Uncertainty analysis for multi-region input–output models—a case study of the UK’s carbon footprint. Econ. Syst. Res. 22, 43–63 (2010).
    Google Scholar
77. Moran, D. & Wood, R. Convergence between the Eora, Wiod, Exiobase, and Open EU’s consumption-based carbon accounts. Econ. Syst. Res. 26, 245–261 (2014).
    Google Scholar
78. de Koning, A. et al. Effect of aggregation and disaggregation on embodied material use of products in input–output analysis. Ecol. Econ. 116, 289–299 (2015).
    Google Scholar
79. Lenzen, M. Aggregation versus disaggregation in input–output analysis of the environment. Econ. Syst. Res. 23, 73–89 (2011).
    Google Scholar
80. Wood, R., Hawkins, T. R., Hertwich, E. G. & Tukker, A. Harmonising national input–output tables for consumption-based accounting—experiences from Exiopol. Econ. Syst. Res. 26, 387–409 (2014).
    Google Scholar
81. Stadler, K., Steen-Olsen, K. & Wood, R. The ‘Rest of the World’—estimating the economic structure of missing regions in global multi-regional input–output tables. Econ. Syst. Res. 26, 303–326 (2014).
    Google Scholar
82. Owen, A., Wood, R., Barrett, J. & Evans, A. Explaining value chain differences in MRIO databases through structural path decomposition. Econ. Syst. Res. 28, 243–272 (2016).
    Google Scholar
83. Steen-Olsen, K., Owen, A., Hertwich, E. G. & Lenzen, M. Effects of sector aggregation on CO2 multipliers in multiregional input–output analyses. Econ. Syst. Res. 26, 284–302 (2014).
    Google Scholar
84. World Development Indicators, SP.POP.TOTL Population, Total (World Bank, 2015).
85. World Development Indicators, NY.GDP.MKTP.PP.KD, GDP, PPP (Constant 2011 International $) (World Bank, 2015).

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