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Global human-made mass exceeds all living biomass

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  • 1.

    Ramankutty, N. & Foley, J. A. Estimating historical changes in global land cover: croplands from 1700 to 1992. Glob. Biogeochem. Cycles 13, 997–1027 (1999).

    ADS  CAS  Article  Google Scholar 

  • 2.

    Krausmann, F. et al. Growth in global materials use, GDP and population during the 20th century. Ecol. Econ. 68, 2696–2705 (2009).

    Article  Google Scholar 

  • 3.

    Matthews, E. The Weight of Nations: Material Outflows from Industrial Economies (World Resources Inst., 2000).

  • 4.

    Smil, V. Harvesting the Biosphere: What We Have Taken from Nature (MIT Press, 2013).

  • 5.

    Smil, V. Making the Modern World: Materials and Dematerialization (John Wiley & Sons, 2013).

  • 6.

    Haff, P. K. Technology as a geological phenomenon: implications for human well-being. Geol. Soc. Lond. Spec. Publ. 395, 301–309 (2014).

    ADS  Article  Google Scholar 

  • 7.

    Zalasiewicz, J. et al. Scale and diversity of the physical technosphere: a geological perspective. Anthropocene Rev. 4, 9–22 (2017).

    Article  Google Scholar 

  • 8.

    Zalasiewicz, J., Waters, C. N., Williams, M. & Summerhayes, C. The Anthropocene as a Geological Time Unit: A Guide to the Scientific Evidence and Current Debate (Cambridge Univ. Press, 2018).

  • 9.

    Stephens, L. et al. Archaeological assessment reveals Earth’s early transformation through land use. Science 365, 897–902 (2019).

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 10.

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

    ADS  CAS  PubMed  Article  Google Scholar 

  • 11.

    Bar-On, Y. M., Phillips, R. & Milo, R. The biomass distribution on Earth. Proc. Natl Acad. Sci. USA 115, 6506–6511 (2018).

    CAS  PubMed  Article  Google Scholar 

  • 12.

    Pan, Y. et al. A large and persistent carbon sink in the world’s forests. Science 333, 988–993 (2011).

    ADS  CAS  PubMed  Article  Google Scholar 

  • 13.

    Reddington, C. L. et al. Air quality and human health improvements from reductions in deforestation-related fire in Brazil. Nat. Geosci. 8, 768–771 (2015).

    ADS  CAS  Article  Google Scholar 

  • 14.

    Ceballos, G. & Ehrlich, P. R. Mammal population losses and the extinction crisis. Science 296, 904–907 (2002).

    ADS  CAS  PubMed  Article  Google Scholar 

  • 15.

    WWF. Living Planet Report–2018: Aiming Higher (WWF, 2018).

  • 16.

    Bar-On, Y. M. & Milo, R. Towards a quantitative view of the global ubiquity of biofilms. Nat. Rev. Microbiol. 17, 199–200 (2019).

    CAS  PubMed  Article  Google Scholar 

  • 17.

    Pauliuk, S. & Hertwich, E. G. Socioeconomic metabolism as paradigm for studying the biophysical basis of human societies. Ecol. Econ. 119, 83–93 (2015).

    Article  Google Scholar 

  • 18.

    Haberl, H. et al. Contributions of sociometabolic research to sustainability science. Nat. Sustainability 2, 173–184 (2019).

    Article  Google Scholar 

  • 19.

    Fischer-Kowalski, M. et al. Methodology and indicators of economy-wide material flow accounting. J. Ind. Ecol. 15, 855–876 (2011).

    Article  Google Scholar 

  • 20.

    Krausmann, F., Schandl, H., Eisenmenger, N., Giljum, S. & Jackson, T. Material flow accounting: measuring global material use for sustainable development. Annu. Rev. Environ. Resour. 42, 647–675 (2017).

    Article  Google Scholar 

  • 21.

    Krausmann, F. et al. Global socioeconomic material stocks rise 23-fold over the 20th century and require half of annual resource use. Proc. Natl Acad. Sci. USA 114, 1880–1885 (2017).

    CAS  PubMed  Article  Google Scholar 

  • 22.

    Krausmann, F., Lauk, C., Haas, W. & Wiedenhofer, D. From resource extraction to outflows of wastes and emissions: the socioeconomic metabolism of the global economy, 1900–2015. Glob. Environ. Change 52, 131–140 (2018).

    PubMed  PubMed Central  Article  Google Scholar 

  • 23.

    Steffen, W., Broadgate, W., Deutsch, L., Gaffney, O. & Ludwig, C. The trajectory of the Anthropocene: the great acceleration. Anthropocene Rev. 2, 81–98 (2015).

    Article  Google Scholar 

  • 24.

    Vitousek, P. M., Ehrlich, P. R., Ehrlich, A. H. & Matson, P. A. Human appropriation of the products of photosynthesis. Bioscience 36, 368–373 (1986).

    Article  Google Scholar 

  • 25.

    Haberl, H. et al. Quantifying and mapping the human appropriation of net primary production in Earth’s terrestrial ecosystems. Proc. Natl Acad. Sci. USA 104, 12942–12947 (2007).

    ADS  CAS  PubMed  Article  Google Scholar 

  • 26.

    Haberl, H., Erb, K.-H. & Krausmann, F. Human appropriation of net primary production: patterns, trends, and planetary boundaries. Annu. Rev. Environ. Resour. 39, 363–391 (2014).

    Article  Google Scholar 

  • 27.

    Vitousek, P. M. Human domination of Earth’s ecosystems. Science 277, 494–499 (1997).

    CAS  Article  Google Scholar 

  • 28.

    Dirzo, R. et al. Defaunation in the Anthropocene. Science 345, 401–406 (2014).

    ADS  CAS  PubMed  Article  Google Scholar 

  • 29.

    Crutzen, P. J. in Earth System Science in the Anthropocene (eds. Ehlers, E. & Kraft, T.) 13–18 (Springer, 2006).

  • 30.

    Steffen, W., Crutzen, J. & McNeill, J. R. The Anthropocene: are humans now overwhelming the great forces of Nature? Ambio 36, 614–621 (2007).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 31.

    Lewis, S. L. & Maslin, M. A. Defining the Anthropocene. Nature 519, 171–180 (2015).

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 32.

    Waters, C. N. et al. The Anthropocene is functionally and stratigraphically distinct from the Holocene. Science 351, aad2622 (2016).

    PubMed  Article  CAS  PubMed Central  Google Scholar 

  • 33.

    Krausmann, F. et al. Economy-wide Material Flow Accounting. Introduction and Guide Version 1, Social Ecology Working Paper 151 (Alpen-Adria Univ., 2015).

  • 34.

    Miatto, A., Schandl, H., Fishman, T. & Tanikawa, H. Global patterns and trends for non-metallic minerals used for construction. J. Ind. Ecol. 21, 924–937 (2017).

    Article  Google Scholar 

  • 35.

    Cooper, A. H., Brown, T. J., Price, S. J., Ford, J. R. & Waters, C. N. Humans are the most significant global geomorphological driving force of the 21st century. Anthropocene Rev. 5, 222–229 (2018).

    Article  Google Scholar 

  • 36.

    Food and Agriculture Organization of the United Nations. Global Forest Resources Assessment 2010: Main Report (FAO, 2010).

  • 37.

    Liu, Y. Y. et al. Recent reversal in loss of global terrestrial biomass. Nat. Clim. Chang. 5, 470–474 (2015).

    ADS  Article  Google Scholar 

  • 38.

    Sitch, S. et al. Recent trends and drivers of regional sources and sinks of carbon dioxide. Biogeosciences 12, 653–679 (2015).

    ADS  Article  Google Scholar 

  • 39.

    Friedlingstein, P. et al. Global carbon budget 2019. Earth Syst. Sci. Data 11, 1783–1838 (2019).

    ADS  Article  Google Scholar 

  • 40.

    Food and Agriculture Organization of the United Nations FAOSTAT http://faostat.fao.org.

  • 41.

    Magnabosco, C. et al. The biomass and biodiversity of the continental subsurface. Nat. Geosci. 11, 707–717 (2018).

    ADS  CAS  Article  Google Scholar 

  • 42.

    Haverd, V. et al. A new version of the CABLE land surface model (Subversion revision r4601) incorporating land use and land cover change, woody vegetation demography, and a novel optimisation-based approach to plant coordination of photosynthesis. Geosci. Model Dev. 11, 2995–3026 (2018).

    ADS  CAS  Article  Google Scholar 

  • 43.

    Melton, J. R. & Arora, V. K. Competition between plant functional types in the Canadian Terrestrial Ecosystem Model (CTEM) v. 2.0. Geosci. Model Dev. 9, 323–361 (2016).

    ADS  CAS  Article  Google Scholar 

  • 44.

    Lawrence, D. M. et al. The community land model version 5: description of new features, benchmarking, and impact of forcing uncertainty. J. Adv. Model. Earth Syst. 11, 4245–4287 (2019).

    ADS  Article  Google Scholar 

  • 45.

    Tian, H. et al. North American terrestrial CO2 uptake largely offset by CH4 and N2O emissions: toward a full accounting of the greenhouse gas budget. Clim. Change 129, 413–426 (2015).

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 46.

    Meiyappan, P., Jain, A. K. & House, J. I. Increased influence of nitrogen limitation on CO2 emissions from future land use and land use change. Glob. Biogeochem. Cycles 29, 1524–1548 (2015).

    ADS  CAS  Article  Google Scholar 

  • 47.

    Mauritsen, T. et al. Developments in the MPI-M Earth System Model version1.2 (MPI-ESM1.2) and its response to increasing CO2. J. Adv. Model. Earth Syst. 11, 998–1038 (2019).

    ADS  PubMed  PubMed Central  Article  Google Scholar 

  • 48.

    Clark, D. B. et al. The Joint UK Land Environment Simulator (JULES), model description – Part 2: Carbon fluxes and vegetation dynamics. Geosci. Model Dev. 4, 701–722 (2011).

    ADS  Article  Google Scholar 

  • 49.

    Poulter, B., Frank, D. C., Hodson, E. L. & Zimmermann, N. E. Impacts of land cover and climate data selection on understanding terrestrial carbon dynamics and the CO2 airborne fraction. Biogeosciences 8, 2027–2036 (2011).

    ADS  CAS  Article  Google Scholar 

  • 50.

    Smith, B. et al. Implications of incorporating N cycling and N limitations on primary production in an individual-based dynamic vegetation model. Biogeosciences 11, 2027–2054 (2014).

    ADS  Article  Google Scholar 

  • 51.

    Lienert, S. & Joos, F. A Bayesian ensemble data assimilation to constrain model parameters and land-use carbon emissions. Biogeosciences 15, 2909–2930 (2018).

    ADS  CAS  Article  Google Scholar 

  • 52.

    Zaehle, S. & Friend, A. D. Carbon and nitrogen cycle dynamics in the O-CN land surface model: 1. Model description, site-scale evaluation, and sensitivity to parameter estimates. Glob. Biogeochem. Cycles 24, GB1005 (2010).

    ADS  Google Scholar 

  • 53.

    Krinner, G. et al. A dynamic global vegetation model for studies of the coupled atmosphere–biosphere system. Glob. Biogeochem. Cycles 19, GB1015 (2005).

    ADS  Article  CAS  Google Scholar 

  • 54.

    Goll, D. S. et al. Carbon–nitrogen interactions in idealized simulations with JSBACH (version 3.10). Geosci. Model Dev. 10, 2009–2030 (2017).

    ADS  CAS  Article  Google Scholar 

  • 55.

    Walker, A. P. et al. The impact of alternative trait-scaling hypotheses for the maximum photosynthetic carboxylation rate (V cmax) on global gross primary production. New Phytol. 215, 1370–1386 (2017).

    CAS  PubMed  Article  Google Scholar 

  • 56.

    Kato, E., Kinoshita, T., Ito, A., Kawamiya, M. & Yamagata, Y. Evaluation of spatially explicit emission scenario of land-use change and biomass burning using a process-based biogeochemical model. J. Land Use Sci. 8, 104–122 (2013).

    Article  Google Scholar 

  • 57.

    Tang, Z. et al. Patterns of plant carbon, nitrogen, and phosphorus concentration in relation to productivity in China’s terrestrial ecosystems. Proc. Natl Acad. Sci. USA 115, 4033–4038 (2018).

    PubMed  Article  Google Scholar 

  • 58.

    Poorter, H. et al. Biomass allocation to leaves, stems and roots: meta-analyses of interspecific variation and environmental control. New Phytol. 193, 30–50 (2012).

    CAS  PubMed  Article  Google Scholar 

  • 59.

    Heldal, M., Norland, S. & Tumyr, O. X-ray microanalytic method for measurement of dry matter and elemental content of individual bacteria. Appl. Environ. Microbiol. 50, 1251–1257 (1985).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  • 60.

    von Stockar, U. & Liu, J. Does microbial life always feed on negative entropy? Thermodynamic analysis of microbial growth. Biochim. Biophys. Acta 1412, 191–211 (1999).

    Article  Google Scholar 

  • 61.

    Guo, L., Lin, H., Fan, B., Cui, X. & Chen, J. Impact of root water content on root biomass estimation using ground penetrating radar: evidence from forward simulations and field controlled experiments. Plant Soil 371, 503–520 (2013).

    CAS  Article  Google Scholar 

  • 62.

    Glass, S. V. & Zelinka, S. L. in Wood Handbook: Wood as an Engineering Material Vol. 190, 4.1–4.19 (US Department of Agriculture, 2010).

  • 63.

    Loveys, B. R. et al. Thermal acclimation of leaf and root respiration: an investigation comparing inherently fast- and slow-growing plant species. Glob. Change Biol. 9, 895–910 (2003).

    ADS  Article  Google Scholar 

  • 64.

    Sheremetev, S. N. Herbs on the Soil Moisture Gradient (Water Relations and the Structural-Functional Organization) (KMK, 2005).

  • 65.

    Michaletz, S. T. & Johnson, E. A. A heat transfer model of crown scorch in forest fires. Can. J. For. Res. 36, 2839–2851 (2006).

    Article  Google Scholar 

  • 66.

    Messier, J., McGill, B. J. & Lechowicz, M. J. How do traits vary across ecological scales? A case for trait-based ecology. Ecol. Lett. 13, 838–848 (2010).

    PubMed  Article  Google Scholar 

  • 67.

    Boucher, F. C., Thuiller, W., Arnoldi, C., Albert, C. H. & Lavergne, S. Unravelling the architecture of functional variability in wild populations of Polygonum viviparum L. Funct. Ecol. 27, 382–391 (2013).

    PubMed  PubMed Central  Article  Google Scholar 

  • 68.

    Dahlin, K. M., Asner, G. P. & Field, C. B. Environmental and community controls on plant canopy chemistry in a Mediterranean-type ecosystem. Proc. Natl Acad. Sci. USA 110, 6895–6900 (2013).

    ADS  CAS  PubMed  Article  Google Scholar 

  • 69.

    Kattge, J. et al. TRY–a global database of plant traits. Glob. Change Biol. 17, 2905–2935 (2011).

    ADS  Article  Google Scholar 

  • 70.

    Lebigot, E. O. Uncertainties: a Python package for calculations with uncertainties. https://pythonhosted.org/uncertainties/ (2010).

  • 71.

    Wiedenhofer, D., Fishman, T., Lauk, C., Haas, W. & Krausmann, F. Integrating material stock dynamics into economy-wide material flow accounting: concepts, modelling, and global application for 1900–2050. Ecol. Econ. 156, 121–133 (2019).

    Article  Google Scholar 


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