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Direct human influence on atmospheric CO2 seasonality from increased cropland productivity

Nature volume 515, pages 398–401 (2014)Cite this article

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Abstract

Ground- and aircraft-based measurements show that the seasonal amplitude of Northern Hemisphere atmospheric carbon dioxide (CO2) concentrations has increased by as much as 50 per cent over the past 50 years1,2,3. This increase has been linked to changes in temperate, boreal and arctic ecosystem properties and processes such as enhanced photosynthesis, increased heterotrophic respiration, and expansion of woody vegetation4,5,6. However, the precise causal mechanisms behind the observed changes in atmospheric CO2 seasonality remain unclear2,3,4. Here we use production statistics and a carbon accounting model to show that increases in agricultural productivity, which have been largely overlooked in previous investigations, explain as much as a quarter of the observed changes in atmospheric CO2 seasonality. Specifically, Northern Hemisphere extratropical maize, wheat, rice, and soybean production grew by 240 per cent between 1961 and 2008, thereby increasing the amount of net carbon uptake by croplands during the Northern Hemisphere growing season by 0.33 petagrams. Maize alone accounts for two-thirds of this change, owing mostly to agricultural intensification within concentrated production zones in the midwestern United States and northern China. Maize, wheat, rice, and soybeans account for about 68 per cent of extratropical dry biomass production, so it is likely that the total impact of increased agricultural production exceeds the amount quantified here.

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Figure 1: Latitudinal patterns of increased crop production.
Figure 2: Attributing the enhanced seasonality.
Figure 3: Increased production and seasonality.

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References

  1. Keeling, C., Chin, J. & Whorf, T. Increased activity of northern vegetation inferred from atmospheric CO2 measurements. Nature 382, 146–149 (1996)

    ADS  CAS  Google Scholar 

  2. Randerson, J., Thompson, M., Conway, T., Fung, I. & Field, C. The contribution of terrestrial sources and sinks to trends in the seasonal cycle of atmospheric carbon dioxide. Glob. Biogeochem. Cycles 11, 535–560 (1997)

    ADS  CAS  Google Scholar 

  3. Graven, H. D. et al. Enhanced seasonal exchange of CO2 by northern ecosystems since 1960. Science 341, 1085–1089 (2013)

    ADS  CAS  Google Scholar 

  4. Piao, S. et al. Net carbon dioxide losses of northern ecosystems in response to autumn warming. Nature 451, 49–52 (2008)

    ADS  CAS  PubMed  Google Scholar 

  5. Elmendorf, S. C. et al. Plot-scale evidence of tundra vegetation change and links to recent summer warming. Nature Clim. Change 2, 453–457 (2012)

    ADS  Google Scholar 

  6. Barichivich, J. et al. Large-scale variations in the vegetation growing season and annual cycle of atmospheric CO2 at high northern latitudes from 1950 to 2011. Glob. Change Biol. 19, 3167–3183 (2013)

    ADS  Google Scholar 

  7. Bacastow, R., Keeling, C. & Whorf, T. Seasonal amplitude increase in atmospheric CO2 concentration at Mauna Loa, Hawaii, 1959–1982. J. Geophys. Res. D 90, 10529–10540 (1985)

    ADS  Google Scholar 

  8. Pearman, G. & Hyson, P. The annual variation of atmospheric CO2 concentration observed in the Northern Hemisphere. J. Geophys. Res. Oceans 86, 9839–9843 (1981)

    ADS  CAS  Google Scholar 

  9. Xu, L. et al. Temperature and vegetation seasonality diminishment over northern lands. Nature Clim. Change 3, 581–586 (2013)

    ADS  Google Scholar 

  10. Falge, E. et al. Seasonality of ecosystem respiration and gross primary production as derived from FluxNET measurements. Agric. For. Meteorol. 113, 53–74 (2002)

    ADS  Google Scholar 

  11. FAO. FAOSTAT Databasehttp://faostat.fao.org/ (Food and Agriculture Organization of the United Nations, 2013)

  12. Tilman, D., Balzer, C., Hill, J. & Befort, B. L. Global food demand and the sustainable intensification of agriculture. Proc. Natl Acad. Sci. USA 108, 20260–20264 (2011)

    ADS  CAS  PubMed  Google Scholar 

  13. Ray, D. K., Ramankutty, N., Mueller, N. D., West, P. C. & Foley, J. A. Recent patterns of crop yield growth and stagnation. Nature Commun. 3, 1293 (2012)

    ADS  Google Scholar 

  14. Kucharik, C. J. Contribution of planting date trends to increased maize yields in the central United States. Agron. J. 100, 328–336 (2008)

    Google Scholar 

  15. Mueller, N. D. et al. Closing yield gaps through nutrient and water management. Nature 490, 254–257 (2012)

    ADS  CAS  Google Scholar 

  16. Vermeulen, S. J., Campbell, B. M. & Ingram, J. S. I. Climate change and food systems. Annu. Rev. Environ. Resour. 37, 195–222 (2012)

    Google Scholar 

  17. West, T. & Marland, G. Net carbon flux from agriculture: carbon emissions, carbon sequestration, crop yield, and land-use change. Biogeochemistry 63, 73–83 (2003)

    CAS  Google Scholar 

  18. West, T. & Marland, G. A synthesis of carbon sequestration, carbon emissions, and net carbon flux in agriculture: comparing tillage practices in the United States. Agric. Ecosyst. Environ. 91, 217–232 (2002)

    Google Scholar 

  19. Keppel-Aleks, G. et al. Atmospheric carbon dioxide variability in the community earth system model: evaluation and transient dynamics during the twentieth and twenty-first centuries. J. Clim. 26, 4447–4475 (2013)

    ADS  Google Scholar 

  20. Guanter, L. et al. Global and time-resolved monitoring of crop photosynthesis with chlorophyll fluorescence. Proc. Natl Acad. Sci. 111, E1327–E1333 (2014)

    CAS  PubMed  Google Scholar 

  21. Nemani, R. R. et al. Climate-driven increases in global terrestrial net primary production from 1982 to 1999. Science 300, 1560–1563 (2003)

    ADS  CAS  Google Scholar 

  22. Chapin, F. et al. Role of land-surface changes in Arctic summer warming. Science 310, 657–660 (2005)

    ADS  CAS  PubMed  Google Scholar 

  23. Goetz, S., Bunn, A., Fiske, G. & Houghton, R. Satellite-observed photosynthetic trends across boreal North America associated with climate and fire disturbance. Proc. Natl Acad. Sci. USA 102, 13521–13525 (2005)

    ADS  CAS  PubMed  Google Scholar 

  24. McGuire, A. D. et al. Carbon balance of the terrestrial biosphere in the twentieth century: analyses of CO2, climate and land use effects with four process-based ecosystem models. Glob. Biogeochem. Cycles 15, 183–206 (2001)

    ADS  CAS  Google Scholar 

  25. Buermann, W. et al. The changing carbon cycle at Mauna Loa observatory. Proc. Natl Acad. Sci. USA 104, 4249–4254 (2007)

    ADS  CAS  PubMed  Google Scholar 

  26. Angert, A. et al. Drier summers cancel out the CO2 uptake enhancement induced by warmer springs. Proc. Natl Acad. Sci. USA 102, 10823–10827 (2005)

    ADS  CAS  PubMed  Google Scholar 

  27. Stephens, B. B. et al. Weak northern and strong tropical land carbon uptake from vertical profiles of atmospheric CO2 . Science 316, 1732–1735 (2007)

    ADS  CAS  PubMed  Google Scholar 

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

    ADS  CAS  Google Scholar 

  29. Le Quéré, C. et al. The global carbon budget 1959–2011. Earth Syst. Sci. Data Discuss. 5, 1107–1157 (2012)

    ADS  Google Scholar 

  30. Foley, J. A. et al. Solutions for a cultivated planet. Nature 478, 337–342 (2011)

    ADS  CAS  Google Scholar 

  31. West, T. O., Bandaru, V., Brandt, C. C., Schuh, A. E. & Ogle, S. M. Regional uptake and release of crop carbon in the United States. Biogeosciences 8, 2037–2046 (2011)

    ADS  CAS  Google Scholar 

  32. Prince, S., Haskett, J., Steininger, M., Strand, H. & Wright, R. Net primary production of US midwest croplands from agricultural harvest yield data. Ecol. Appl. 11, 1194–1205 (2001)

    Google Scholar 

  33. Lobell, D. et al. Satellite estimates of productivity and light use efficiency in united states agriculture, 1982-98. Glob. Change Biol. 8, 722–735 (2002)

    ADS  Google Scholar 

  34. Hay, R. Harvest index—a review of its use in plant-breeding and crop physiology. Ann. Appl. Biol. 126, 197–216 (1995)

    Google Scholar 

  35. Sinclair, T. Historical changes in harvest index and crop nitrogen accumulation. Crop Sci. 38, 638–643 (1998)

    Google Scholar 

  36. Kumudini, S., Hume, D. & Chu, G. Genetic improvement in short season soybeans: I. dry matter accumulation, partitioning, and leaf area duration. Crop Sci. 41, 391–398 (2001)

    Google Scholar 

  37. Wirsenius, S. Efficiencies and biomass appropriation of food commodities on global and regional levels. Agric. Syst. 77, 219–255 (2003)

    Google Scholar 

  38. Shearman, V., Sylvester-Bradley, R., Scott, R. & Foulkes, M. Physiological processes associated with wheat yield progress in the UK. Crop Sci. 45, 175–185 (2005)

    Google Scholar 

  39. Johnson, J. M. F., Allmaras, R. R. & Reicosky, D. C. Estimating source carbon from crop residues, roots and rhizodeposits using the national grain-yield database. Agron. J. 98, 622–636 (2006)

    CAS  Google Scholar 

  40. 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  Google Scholar 

  41. Lorenz, A. J., Gustafson, T. J., Coors, J. G. & de Leon, N. Breeding maize for a bioeconomy: a literature survey examining harvest index and stover yield and their relationship to grain yield. Crop Sci. 50, 1–12 (2010)

    Google Scholar 

  42. Ma, S.-C., Li, F.-M., Xu, B.-C. & Huang, Z.-B. Effect of lowering the root/shoot ratio by pruning roots on water use efficiency and grain yield of winter wheat. Field Crops Res. 115, 158–164 (2010)

    Google Scholar 

  43. Yang, J. & Zhang, J. Crop management techniques to enhance harvest index in rice. J. Exp. Bot. 61, 3177–3189 (2010)

    CAS  PubMed  Google Scholar 

  44. Gower, S. T., Kucharik, C. J. & Norman, J. M. Direct and indirect estimation of leaf area index, fAPAR, and net primary production of terrestrial ecosystems. Remote Sens. Environ. 70, 29–51 (1999)

    ADS  Google Scholar 

  45. Bonifas, K., Walters, D., Cassman, K. & Lindquist, J. Nitrogen supply affects root: shoot ratio in corn and velvetleaf (Abutilon theophrasti). Weed Sci. 53, 670–675 (2005)

    CAS  Google Scholar 

  46. Insalud, N., Bell, R. W., Colmer, T. D. & Rerkasem, B. Morphological and physiological responses of rice (Oryza sativa) to limited phosphorus supply in aerated and stagnant solution culture. Ann. Bot. 98, 995–1004 (2006)

    CAS  PubMed  PubMed Central  Google Scholar 

  47. Jing, L., Shi-Qing, L., Yi, L. & Xiao-Li, C. Effects of increased ammonia on root/shoot ratio, grain yield and nitrogen use efficiency of two wheat varieties with various N supply. Plant Soil Environ. 55, 273–280 (2009)

    Google Scholar 

  48. Arai-Sanoh, Y., Ishimaru, T., Ohsumi, A. & Kondo, M. Effects of soil temperature on growth and root function in rice. Plant Prod. Sci. 13, 235–242 (2010)

    CAS  Google Scholar 

  49. Gehring, C. et al. Ecological intensification of rice production in the lowlands of Amazonia—options for smallholder rice producers. Eur. J. Agron. 46, 25–33 (2013)

    Google Scholar 

  50. Williams, J. D. et al. Root:shoot ratios and belowground biomass distribution for pacific northwest dryland crops. J. Soil Water Conserv. 68, 349–360 (2013)

    Google Scholar 

  51. FluxNET. http://www.fluxdata.org (2014)

  52. Aubinet, M. et al. Carbon sequestration by a crop over a 4-year sugar beet/winter wheat/seed potato/winter wheat rotation cycle. Agric. For. Meteorol. 149, 407–418 (2009)

    ADS  Google Scholar 

  53. Dawe, D., Frolking, S. & Li, C. Trends in rice-wheat area in China. Field Crops Res. 87, 89–95 (2004)

    Google Scholar 

  54. Sacks, W. J., Deryng, D., Foley, J. A. & Ramankutty, N. Crop planting dates: an analysis of global patterns. Glob. Ecol. Biogeogr. 19, 607–620 (2010)

    Google Scholar 

  55. Schnyder, H. The role of carbohydrate storage and redistribution in the source-sink relations of wheat and barley during grain filling—a review. New Phytol. 123, 233–245 (1993)

    Google Scholar 

  56. Frolking, S. et al. Combining remote sensing and ground census data to develop new maps of the distribution of rice agriculture in China. Glob. Biogeochem. Cycles 16, 1091 (2002)

    ADS  Google Scholar 

  57. Qiu, J. et al. Mapping single-, double-, and triple-crop agriculture in China at 0.5x0.5 by combining county-scale census data with remote sensing-derived land cover map. Geocarto Int. 18, 3–13 (2003)

    Google Scholar 

  58. Baker, J. M., Ochsner, T. E., Venterea, R. T. & Griffis, T. J. Tillage and soil carbon sequestration—what do we really know? Agric. Ecosyst. Environ. 118, 1–5 (2007)

    CAS  Google Scholar 

  59. DeFries, R., Field, C., Fung, I., Collatz, G. & Bounoua, L. Combining satellite data and biogeochemical models to estimate global effects of human-induced land cover change on carbon emissions and primary productivity. Glob. Biogeochem. Cycles 13, 803–815 (1999)

    ADS  CAS  Google Scholar 

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Acknowledgements

This work used eddy covariance data acquired by the FLUXNET community and in particular by the following networks: AmeriFlux (US Department of Energy, Biological and Environmental Research, Terrestrial Carbon Program (DE-FG02-04ER63917 and DE-FG02-04ER63911)), AfriFlux, AsiaFlux, CarboAfrica, CarboEuropeIP, CarboItaly, CarboMont, ChinaFlux, Fluxnet-Canada (supported by CFCAS, NSERC, BIOCAP, Environment Canada, and NRCan), GreenGrass, KoFlux, LBA, NECC, OzFlux, TCOS-Siberia, USCCC. We acknowledge the financial support to the eddy covariance data harmonization provided by CarboEuropeIP, FAO-GTOS-TCO, iLEAPS, Max Planck Institute for Biogeochemistry, National Science Foundation, University of Tuscia, Université Laval and Environment Canada and US Department of Energy and the database development and technical support from Berkeley Water Center, Lawrence Berkeley National Laboratory, Microsoft Research eScience, Oak Ridge National Laboratory, University of California - Berkeley, University of Virginia. This work was supported by NASA grant number NNX11AE75G and NSF grant numbers EF-1064614 and NSF EAR-1038818. Research support to D.K.R. was primarily provided by the Gordon and Betty Moore Foundation and the Institute on Environment at the University of Minnesota. We also acknowledge input and data provided by H. Graven and P. Patra.

Author information

Author notes

  1. Navin Ramankutty

    Present address: Present address: Liu Institute for Global Issues and Institute for Resources, Environment, and Sustainability, University of British Columbia, Vancouver, British Columbia V6T 1Z2, Canada.,

Authors and Affiliations

  1. Department of Earth and Environment, Boston University, Boston, 02215, Massachussetts, USA

    Josh M. Gray & Mark A. Friedl

  2. Earth Systems Research Center, University of New Hampshire, Durham, 03824, New Hampshire, USA

    Steve Frolking

  3. Department of Atmospheric, Oceanic and Space Sciences, University of Michigan, Ann Arbor, 48109, Michigan, USA

    Eric A. Kort

  4. Institute on the Environment, University of Minnesota, Saint Paul, 55108, Minnesota, USA

    Deepak K. Ray

  5. Department of Agronomy and Nelson Institute Center for Sustainability and the Global Environment, University of Wisconsin-Madison, Madison, 53706, Wisconsin, USA

    Christopher J. Kucharik

  6. Department of Geography, McGill University, Montreal, Quebec H3A 0B9, Canada,

    Navin Ramankutty

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Contributions

J.M.G. led the design, analysis, and writing of the paper. J.M.G., S.F., N.R. and M.A.F. designed the analysis. E.A.K. provided the initial inspiration for the paper and guidance on interpreting atmospheric CO2 dynamics. C.J.K. contributed guidance on agronomic elements of the paper. D.K.R. provided the gridded MWRS data set. All authors edited and contributed to writing the paper.

Corresponding author

Correspondence to Josh M. Gray.

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Competing interests

The authors declare no competing financial interests.

Additional information

MWRS yield and harvested area data will be archived at http://www.earthstat.org and are available on request.

Extended data figures and tables

Extended Data Figure 1 Calculating ΔS.

Schematic diagram showing the CO2 seasonality difference (ΔS) for two time periods representing a baseline condition (t1) with CO2 seasonality St1 and a scenario where NEE is enhanced 35% (t2) with correspondingly higher seasonality, St2. Flux-derived daily NEE (a), cumulative NEE (b), and NEPCUP and NEPCRP (c). Note the assumption that annual NEP = 0 (b).

Extended Data Figure 2 Harvest index and root:shoot ratio.

Crop-specific and MWRS aggregate distributions of literature-reported values of harvest index (a) and R:S (b).

Extended Data Figure 3 Agricultural fluxes from FluxNET.

NEE and GPP for agricultural FluxNET sites used in this study to determine the θ and φ parameters. Shading corresponds to May, June, July, and August, the CUP at the latitudes of most agricultural production, and the CUP definition used throughout this study.

Extended Data Figure 4 Parameter distributions.

PERT distributions for all Monte-Carlo-varied parameters in this study. Shown are moisture fraction (a), harvest efficiency (b), R:S ratio (c), harvest index (d), CUP proportion of NPP (e), and CUP proportion of Rh (f).

Extended Data Figure 5 Aggregation zones.

Eco-climatic (top; from ref. 3) and aggregated production regions (bottom) used in this study.

Extended Data Figure 6 Increased production and seasonality.

Change in MWRS production (top) and SCO2,MWRS (bottom) over the period 1965–2005.

Extended Data Figure 7 Remotely sensed growing season length.

Mean ‘greenup’ and dormancy values from MODIS Land Cover Dynamics product (MCD12Q2) for pixels identified as agriculture (AG) and deciduous broadleaf forest (DBF) in the MODIS Land Cover product (MCD12Q1; classes 12 and 4, respectively) for 1° latitudinal bands in North America (a) (MODIS tiles are h11v03, h12v03, h13v03, h10v04, h11v04, h12v04, h09v05, h10v05, and h11v05), and for China (b) (MODIS tiles are h23v03, h24v03, h25v03, h26v04, h27v04, h26v05, and h27v05.)

Extended Data Table 1 Global dry biomass production
Full size table
Extended Data Table 2 2009–2011 mean MWRS dry biomass production
Full size table
Extended Data Table 3 Proportion of NPP in CUP
Full size table

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Gray, J., Frolking, S., Kort, E. et al. Direct human influence on atmospheric CO2 seasonality from increased cropland productivity. Nature 515, 398–401 (2014). https://doi.org/10.1038/nature13957

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