Advertisement

Regional Environmental Change

, Volume 18, Issue 1, pp 129–142 | Cite as

Future land use and land cover in Southern Amazonia and resulting greenhouse gas emissions from agricultural soils

  • Jan Göpel
  • Jan Schüngel
  • Rüdiger Schaldach
  • Katharina H. E. Meurer
  • Hermann F. Jungkunst
  • Uwe Franko
  • Jens Boy
  • Robert Strey
  • Simone Strey
  • Georg Guggenberger
  • Anna Hampf
  • Phillip Parker
Original Article

Abstract

The calculation of robust estimates of future greenhouse gas emissions due to agriculture is essential to support the framing of the Brazilian climate change mitigation policy. Information on the future development of land use and land cover change (LULCC) under the combination of various driving factors operating at different spatial scale levels, e.g., local land use policy and global demands for agricultural commodities, is required. The spatially explicit land use model, LandSHIFT, was applied to calculate a set of high-resolution land use scenarios for Southern Amazonia. The time frame of the analysis was 2010–2030. Based on the generated maps, emission coefficients were applied to calculate annual N2O, CH4, and CO2 emissions from agricultural soils (croplands and pastures). The results indicate that future land use pattern and the resultant greenhouse gas emissions in Southern Amazonia will be strongly determined by global and regional demands for agricultural commodities, as well as by the level of intensification of agriculture and the implementation of conservation policies.

Keywords

Land use and land cover change Southern Amazonia Scenarios Agriculture Greenhouse gas emissions 

Notes

Acknowledgements

This study has been conducted as part of the Carbiocial project (funding reference number 01LL0902A-01LL0902N) commissioned by the German Federal Ministry of Education and Research. We would like to thank the entire project team for their contribution to this research.

Supplementary material

10113_2017_1235_MOESM1_ESM.docx (611 kb)
ESM 1 (DOCX 610 kb)

References

  1. Aguiar APD, Câmara G, Escada MIS (2007) Spatial statistical analysis of land use determinants in the Brazilian Amazonia: exploring intra-regional heterogeneity. Ecol Model 209(2):169–188.  https://doi.org/10.1016/j.ecolmodel.2007.06.019 CrossRefGoogle Scholar
  2. Amine E, Baba N, Belhadj M, Deurenbery-Yap M, Djazayery A, Forrester T, Galuska D, Herman S, James W, M’Buyamba J, Katan M, Key T, Kumanyika S, Mann J, Moynihan P, Musaiger A, Prentice A, Reddy K, Schatzkin A, Seidell J, Simpopoulos A, Srinujata S, Steyn N, Swinburn B, Uauy R, Wahlqvist M, Zhao-su W, Yoshiike N (2002) Diet, nutrition and the prevention of chronic diseases: report of a joint WHO/FAO expert consultation. World Health Organization, Geneva ISBN: 924120916XGoogle Scholar
  3. Arima EY, Barreto P, Araújo E, Soares-Filho B (2014) Public policies can reduce tropical deforestation: lessons and challenges from Brazil. Land Use Policy 41:465–473.  https://doi.org/10.1016/j.landusepol.2014.06.026 CrossRefGoogle Scholar
  4. Arvor D, Meirelles M, Dubreuil V, Begue A, Shimabukuro YE (2012) Analyzing the agricultural transition in Mato Grosso, Brazil, using satellite-derived indices. Appl Geogr 32(2):702–713.  https://doi.org/10.1016/j.apgeog.2011.08.007 CrossRefGoogle Scholar
  5. Arvor D, Dubreuil V, Simões M, Bégué A (2013) Mapping and spatial analysis of the soybean agricultural frontier in Mato Grosso, Brazil, using remote sensing data. GeoJournal 78(5):833–850.  https://doi.org/10.1007/s10708-012-9469-3 CrossRefGoogle Scholar
  6. Assunção J, Gandour CC, Rocha R (2012) Deforestation slowdown in the legal Amazon: prices or policies. Clim Pol Initiat 1:03–37.  https://doi.org/10.1017/S1355770X15000078 Google Scholar
  7. Banco de Nomes Geográficos do Brasil (IBGE), 2012. http://www.ngb.ibge.gov.br/. Accessed Apr 2012
  8. Barona E, Ramankutty N, Hyman G, Coomes OT (2010) The role of pasture and soybean in deforestation of the Brazilian Amazon. Environ Res Lett 5(2):024002.  https://doi.org/10.1088/1748-9326/5/2/024002 CrossRefGoogle Scholar
  9. Bondeau A, Smith PC, Zaehle S, Schaphoff S, Lucht W, Cramer W, Smith B (2007) Modelling the role of agriculture for the 20th century global terrestrial carbon balance. Glob Chang Biol 13(3):679–706.  https://doi.org/10.1111/j.1365-2486.2006.01305.x CrossRefGoogle Scholar
  10. Bringezu S, O’Brien M, Schütz H (2012) Beyond biofuels: assessing global land use for domestic consumption of biomass: a conceptual and empirical contribution to sustainable management of global resources. Land Use Policy 29(1):224–232.  https://doi.org/10.1016/j.landusepol.2011.06.010 CrossRefGoogle Scholar
  11. Cardoso AS, Berndt A, Leytem A, Alves BJ, de Carvalho IDN, de Barros Soares LH, Boddey RM (2016) Impact of the intensification of beef production in Brazil on greenhouse gas emissions and land use. Agric Syst 143:86–96.  https://doi.org/10.1016/j.agsy.2015.12.007 CrossRefGoogle Scholar
  12. Chaplin-Kramer R, Sharp RP, Mandle L, Sim S, Johnson J, Butnar I, Kareiva PM (2015) Spatial patterns of agricultural expansion determine impacts on biodiversity and carbon storage. Proc Natl Acad Sci 112(24):7402–7407.  https://doi.org/10.1073/pnas.1406485112 CrossRefGoogle Scholar
  13. Cohn AS, Mosnier A, Havlík P, Valin H, Herrero M, Schmid E, Obersteiner M (2014) Cattle ranching intensification in Brazil can reduce global greenhouse gas emissions by sparing land from deforestation. Proc Natl Acad Sci 111(20):7236–7241.  https://doi.org/10.1073/pnas.1307163111 CrossRefGoogle Scholar
  14. Coy M (2001) Globalisierung in Brasilien: Raumwirksamkeit und Reaktionen. Beispiele aus städtischen und ländlichen Regionen. In: Krömer G, Borsdorf A, Parnreiter C (eds.) Lateinamerika im Umbruch. Geistige Strömungen im Globalisierungsstress. Innsbrucker Geographische Studien Band 32. Geographie Innsbruck, Innsbruck. ISBN: 978-3-901182-32-7120916XGoogle Scholar
  15. Coy M, Klingler M (2008 ) Pionierfronten im brasilianischen Amazonien zwischen alten Problemen und neuen Dynamiken. Das Beispiel des „Entwicklungskorridors “Cuiabá (Mato Grosso)–Santarém (Pará). Innsbrucker Geographische Gesellschaft (Hg.) Jahresbericht 2008-2010:109-129. Geographie Innsbruck, Innsbruck ISBN: 3901182837Google Scholar
  16. Dalla-Nora EL, de Aguiar APD, Lapola DM, Woltjer G (2014) Why have land use change models for the Amazon failed to capture the amount of deforestation over the last decade? Land Use Policy 39:403–411.  https://doi.org/10.1016/j.landusepol.2014.02.004 CrossRefGoogle Scholar
  17. Embrapa Amazônia Oriental: Agência de Desenvolvimento da Amazônia (2008) ZONAMENTO ecológico-econômico da área de influência da Rodovia BR-163 (Cuiabá-Santarém). Belem, PA. https://www.infoteca.cnptia.embrapa.br/bitstream/doc/409035/1/Fd422.pdf. Accessed June 2013
  18. FAO (2014) FAOSTAT Emissions Database. http://cait.wri.org. Accessed 11 Dec 2014
  19. Farr TG, Kobrick M (2000) Shuttle radar topography mission produces a wealth of data. Eos, Trans Am Geophys Union 81(48):583–585.  https://doi.org/10.1029/EO081i048p00583 CrossRefGoogle Scholar
  20. Fearnside PM, Righi CA, de Alencastro Graça PML, Keizer EW, Cerri CC, Nogueira EM, Barbosa RI (2009) Biomass and greenhouse-gas emissions from land use change in Brazil’s Amazonian “arc of deforestation”: the states of Mato Grosso and Rondônia. For Ecol Manag 258(9):1968–1978.  https://doi.org/10.1016/j.foreco.2009.07.042 CrossRefGoogle Scholar
  21. Friedl MA, Sulla-Menashe D, Tan B, Schneider A, Ramankutty N, Sibley A, Huang X (2010) MODIS collection 5 global land cover: algorithms and characterization of new datasets. Remote Sens Environ 115:168–182.  https://doi.org/10.1016/j.rse.2009.08.016 CrossRefGoogle Scholar
  22. Galford GL, Melillo JM, Kicklighter DW, Cronin TW, Cerri CE, Mustard JF, Cerri CC (2010) Greenhouse gas emissions from alternative futures of deforestation and agricultural management in the southern Amazon. Proc Natl Acad Sci 107(46):19649–19654.  https://doi.org/10.1073/pnas.1000780107 CrossRefGoogle Scholar
  23. Galford GL, Soares-Filho B, Cerri CE (2013) Prospects for land use sustainability on the agricultural frontier of the Brazilian Amazon. Philos Trans Royal Soc Lond B: Biol Sci 368(1619). doi:  https://doi.org/10.1098/rstb.2012.0171
  24. Gibbs HK, Rausch L, Munger J, Schelly I, Morton DC, Noojipady P, Walker NF (2015b) Brazil’s Soy Moratorium. Science 347(6220):377–378.  https://doi.org/10.1126/science.aaa0181 CrossRefGoogle Scholar
  25. Gibbs HK, Munger J, L’Roe J, Barreto P, Pereira R, Christie M, Amaral T, Walker NF (2015a) Did ranchers and slaughterhouses respond to zero-deforestation agreements in the Brazilian Amazon? Conserv Lett 9(1):32–42.  https://doi.org/10.1111/conl.12175 CrossRefGoogle Scholar
  26. Godfray HCJ, Beddington JR, Crute IR, Haddad L, Lawrence D, Muir JF, Toulmin C (2010a) Food security: the challenge of feeding 9 billion people. Science 327(5967):812–818.  https://doi.org/10.1126/science.1185383 CrossRefGoogle Scholar
  27. Godfray HCJ, Crute IR, Haddad L, Lawrence D, Muir JF, Nisbett N, Whiteley R (2010b) The future of the global food system. Philos Trans Royal Soc B: Biol Scis 365(1554):2769–2777.  https://doi.org/10.1098/rstb.2010.0180 CrossRefGoogle Scholar
  28. Gollnow F, Lakes T (2014) Policy change, land use, and agriculture: the case of soy production and cattle ranching in Brazil, 2001–2012. Appl Geogr 55:203–211.  https://doi.org/10.1016/j.apgeog.2014.09.003 CrossRefGoogle Scholar
  29. Greenpeace-Brazil (2009) Amazon cattle footprint. Mato Grosso: state of destruction. www.greenpeace.org/international/press/reports/amazon-cattle-footprint-mato. Accessed June 2015
  30. Hecht SB (2011) From eco-catastrophe to zero deforestation? Interdisciplinarities, politics, environmentalism and reduced clearing in Amazonia. Environ Conserv 39(1):4–19.  https://doi.org/10.1017/S0376892911000452 CrossRefGoogle Scholar
  31. Instituto Brasileiro de Geografia e Estatística (IBGE) (2013) Indicadores IBGE. IBGE http://wwwibgegovbr/estadosat/indexphp. Accessed August 2013
  32. Instituto Brasileiro de Geografia e Estatística (IBGE) (2014) Amazonia Legal 2014. IBGE. ftp://geoftp.ibge.gov.br/organizacao_territorial/amazonia_legal/amazonia_legal_2014.pdf. Accessed June 2015
  33. Instituto Brasileiro de Geografia e Estatística (IBGE) (2015) Indicadores IBGE Estatística da Produção Agrícola. ftp://ftp.ibge.gov.br/Producao_Agricola/Fasciculo_Indicadores_IBGE/estProdAgr_201508.pdf. Accessed Aug 2015
  34. INPE (2013) PRODES. http://www.obt.inpe.br/prodes/index.php. Accessed May 2013
  35. Jasinski E, Morton D, DeFries R, Shimabukuro Y, Anderson L, Hansen M (2005) Physical landscape correlates of the expansion of mechanized agriculture in Mato Grosso, Brazil. Earth Interact 9(16):1–18.  https://doi.org/10.1175/EI143.1 CrossRefGoogle Scholar
  36. Klingler M, Richards PD, Ossner R (2017) Cattle vaccination records question the impact of recent zero-deforestation agreements in the Amazon. Regional Environmental Change, this issueGoogle Scholar
  37. Kohlhepp G (2002) Regionalentwicklung im Amazonasgebiet Brasiliens. In: Donato H, Kutschat RSG, Tiemann J (eds.): Institut Martius-Staden. Jahrbuch 2001–2002 (49). Nova Bandeira, São Paulo. ISSN 1677-051XGoogle Scholar
  38. Krogh L, Noergaard A, Hermansen M, Greve M, Balstroem T, Breuning-Madsen H (2003) Preliminary estimates of contemporary soil organic carbon stocks in Denmark using multiple datasets and four scaling-up methods. AGEE 96:19–28.  https://doi.org/10.1016/S0167-8809(03)00016-1 Google Scholar
  39. Lambin EF, Rounsevell MDA, Geist HJ (2000) Are agricultural land use models able to predict changes in land use intensity? Agric Ecosyst Environ 82(1):321–331.  https://doi.org/10.1016/S0167-8809(00)00235-8 CrossRefGoogle Scholar
  40. Lambin EF, Meyfroidt P (2011) Global land use change, economic globalization, and the looming land scarcity. Proc Natl Acad Sci 108(9):3465–3472.  https://doi.org/10.1073/pnas.1100480108 CrossRefGoogle Scholar
  41. Lambin EF, Gibbs HK, Ferreira L, Grau R, Mayaux P, Meyfroidt P, Munger J (2013) Estimating the world's potentially available cropland using a bottom-up approach. Glob Environ Chang 23(5):892–901.  https://doi.org/10.1016/j.gloenvcha.2013.05.005 CrossRefGoogle Scholar
  42. Lapola DM, Priess JA, Bondeau A (2009) Modeling the land requirements and potential productivity of sugarcane and jatropha in Brazil and India using the LPJmL dynamic global vegetation model. Biomass Bioenergy 33(8):1087–1095.  https://doi.org/10.1016/j.biombioe.2009.04.005 CrossRefGoogle Scholar
  43. Lapola DM, Schaldach R, Alcamo J, Bondeau A, Koch J, Koelking C, Priess JA (2010) Indirect land use changes can overcome carbon savings from biofuels in Brazil. Proc Natl Acad Sci 107(8):3388–3393.  https://doi.org/10.1073/pnas.0907318107 CrossRefGoogle Scholar
  44. Lapola DM, Schaldach R, Alcamo J, Bondeau A, Msangi S, Priess JA, Silvestrini R, Soares-Filho BS (2011) Impacts of climate change and the end of deforestation on land use in the Brazilian Amazon. Earth Interact 15:1–29.  https://doi.org/10.1175/2010EI333.1 CrossRefGoogle Scholar
  45. Lapola DM, Martinelli LA, Peres CA, Ometto JP, Ferreira ME, Nobre CA, Vieira IC (2014) Pervasive transition of the Brazilian land use system. Nat Clim Chang 4(1):27–35.  https://doi.org/10.1038/nclimate2056 CrossRefGoogle Scholar
  46. Lawson S, Blundell A, Cabarle B, Basik N, Jenkins M, Canby K (2014) Consumer goods and deforestation: an analysis of the extent and nature of illegality in Forest conversion for agriculture and timber plantations. Forest Trend Report Series, Washington DC. http://www.forest-trends.org/illegal-deforestation.php. Accessed May 2014
  47. Macedo MN, DeFries RS, Morton DC, Stickler CM, Galford GL, Shimabukuro YE (2012) Decoupling of deforestation and soy production in the southern Amazon during the late 2000s. Proc Natl Acad Sci 109(4):1341–1346.  https://doi.org/10.1073/pnas.1111374109 CrossRefGoogle Scholar
  48. Malingreau JP, Eva HD, De Miranda EE (2012) Brazilian Amazon: a significant five year drop in deforestation rates but figures are on the rise again. Ambio 41(3):309–314.  https://doi.org/10.1007/s13280-011-0196-7 CrossRefGoogle Scholar
  49. Marengo JA, Chou SC, Kay G, Alves LM, Pesquero JF, Soares WR, Tavares P (2012) Development of regional future climate change scenarios in South America using the eta CPTEC/HadCM3 climate change projections: climatology and regional analyses for the Amazon, São Francisco and the Paraná River basins. Clim Dyn 38(9–10):1829–1848.  https://doi.org/10.1007/s00382-011-1155-5 CrossRefGoogle Scholar
  50. Martinelli LA, Naylor R, Vitousek PM, Moutinho P (2010) Agriculture in Brazil: impacts, costs, and opportunities for a sustainable future. Curr Opin Environ Sustain 2(5):431–438.  https://doi.org/10.1016/j.cosust.2010.09.008 CrossRefGoogle Scholar
  51. Meurer KHE, Franko U, Stange CF, Dalla Rosa J, Madari BE, Jungkunst HF (2016) Direct nitrous oxide (N2O) fluxes from soils under different land use in Brazil—a critical review. Environ Res Lett 11:023001.  https://doi.org/10.1088/1748-9326/11/2/023001 CrossRefGoogle Scholar
  52. Mietzner D, Reger G (2005) Advantages and disadvantages of scenario approaches for strategic foresight. Int J Technol Intell Plan 1(2):220–239.  https://doi.org/10.1504/IJTIP.2005.006516 Google Scholar
  53. Ministério da Agricultura, Pecuária e Abastecimento (MAPA) (2012) Plano Setorial de Mitigação e de Adaptação às Mudanças Climáticas para a Consolidação de uma Economia de baixa Emissão de Carbono na Agricultura. Plano ABC (Agricultura de Baixa Emissão de Carbono). Coordenado por Casa Civil da Presidência da República, Ministério da Agricultura, Pecuária e Abastecimento (MAPA) e Ministério do Desenvolvimento Agrário (MDA). Versão final-13/01. ISBN 978-85-7991-062-0Google Scholar
  54. Ministério do Meio Ambiente (MMA) (2001) Causas e dinamica do desmatamento na Amazonia. MMA, Brasilia DF. ISBN: 8587166271Google Scholar
  55. Ministério do Meio Ambiente (MMA) (2013) Indigenous Areas Mato Grosso and Pará. Available at: http://mapas.mma.gov.br/i3geo/datadownload.htm. Accessed Mar 2013
  56. Mitchell TD, Jones PD (2005) An improved method of constructing a database of monthly climate observations and associated high-resolution grids. Int J Climatol 25(6):693–712.  https://doi.org/10.1504/IJTIP.2005.006516 CrossRefGoogle Scholar
  57. Myhre G, Shindell D, Bréon FM, Collins W, Fuglestvedt J, Huang J, Koch D, Lamarque J-F, Lee D, Mendoza B, Nakajima T (2013) Anthropogenic and natural radiative forcing. In: Stocker TF, Qin D, Plattner GK, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds) Climate change 2013: the physical science basis. Contribution of Working Group I to the Fifth Assessment Report of hte Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge.  https://doi.org/10.1017/CBO9781107415324 Google Scholar
  58. Nendel C, Berg M, Kersebaum KC, Mirschel W, Specka X, Wegehenkel M, Wieland R (2011) The MONICA model: testing predictability for crop growth, soil moisture and nitrogen dynamics. Ecol Model 222(9):1614–1625.  https://doi.org/10.1016/j.ecolmodel.2011.02.018 CrossRefGoogle Scholar
  59. Nepstad D, Soares-Filho BS, Merry F, Lima A, Moutinho P, Carter J, Stella O (2009) The end of deforestation in the Brazilian Amazon. Science 326(5958):1350–1351.  https://doi.org/10.1126/science.1182108 CrossRefGoogle Scholar
  60. Nepstad D, McGrath D, Stickler C, Alencar A, Azevedo A, Swette B, Hess L (2014) Slowing Amazon deforestation through public policy and interventions in beef and soy supply chains. Science 344(6188):1118–1123.  https://doi.org/10.1126/science.1248525 CrossRefGoogle Scholar
  61. Pacheco P (2012) Actor and frontier types in the Brazilian Amazon: assessing interactions and outcomes associated with frontier expansion. Geoforum 43(4):864–874.  https://doi.org/10.1016/j.geoforum.2012.02.003 CrossRefGoogle Scholar
  62. Quesada CA, Lloyd J, Anderson LO, Fyllas NM, Schwarz M, Czimczik CI (2011) Soils of Amazonia with particular reference to the RAINFOR sites. Biogeosciences 8(6):1415–1440.  https://doi.org/10.5194/bg-8-1415-2011
  63. Rosenzweig C, Elliott J, Deryng D, Ruane AC, Müller C, Arneth A, Jones JW (2014) Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison. Proc Natl Acad Sci 111(9):3268–3273.  https://doi.org/10.1073/pnas.1222463110 CrossRefGoogle Scholar
  64. Salvatore M, Pozzi F, Ataman E, Huddleston B, Bloise M, Balk D, Yetman G (2005) Mapping global urban and rural population distributions. FAO, Rome. ftp://ftp.fao.org/docrep/fao/009/a0310e/a0310e00.pdf. Accessed Apr 2013
  65. Schaldach R, Alcamo J, Koch J, Kölking C, Lapola DM, Schüngel J, Priess JA (2011) An integrated approach to modelling land use change on continental and global scales. Environ Model Softw 26(8):1041–1051.  https://doi.org/10.1016/j.envsoft.2011.02.013 CrossRefGoogle Scholar
  66. Schmidt MWI, Torn MS, Abiven S, Dittmar T, Guggenberger G, Janssens IA, Kleber M, Kögel-Knabner I, Lehmann J, Manning DAC, Nannupieri P, Rasse DP, Weiner S, Trumbore SE (2011) Persistence of soil organic matter as an ecosystem property. Nature 478:49–56.  https://doi.org/10.1038/nature10386 CrossRefGoogle Scholar
  67. Schönenberg R, Schaldach R, Lakes T, Göpel J, Gollnow F (2017) Inter- and transdisciplinary scenario construction to explore future land-use options in Southern Amazonia. Ecol Soc 22(3).  https://doi.org/10.5751/ES-09032-220313
  68. Sitch S, Smith B, Prentice IC, Arneth A, Bondeau A, Cramer W, Thonicke K (2003) Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model. Glob Chang Biol 9(2):161–185.  https://doi.org/10.1046/j.1365-2486.2003.00569.x CrossRefGoogle Scholar
  69. Soares-Filho B, Alencar A, Nepstad D, Cerqueira G, Diaz V, del Carmen M, Voll E (2004) Simulating the response of land-cover changes to road paving and governance along a major Amazon highway: the Santarém–Cuiabá corridor. Glob Chang Biol 10(5):745–764.  https://doi.org/10.1111/j.1529-8817.2003.00769.x CrossRefGoogle Scholar
  70. Soares-Filho B, Nepstad DC, Curran LM, Cerqueira GC, Garcia RA, Ramos CA, Schlesinger P (2006) Modelling conservation in the Amazon basin. Nature 440(7083):520–523.  https://doi.org/10.1038/nature04389 CrossRefGoogle Scholar
  71. Soares-Filho B, Moutinho P, Nepstad D, Anderson A, Rodrigues H, Garcia R, Silvestrini R (2010) Role of Brazilian Amazon protected areas in climate change mitigation. Proc Natl Acad Sci 107(24):10821–10826.  https://doi.org/10.1073/pnas.0913048107 CrossRefGoogle Scholar
  72. Soares-Filho B, Rajão R, Macedo M, Carneiro A, Costa W, Coe M, Alencar A (2014) Cracking Brazil’s forest code. Science 344(6182):363–364.  https://doi.org/10.1126/science.1246663 CrossRefGoogle Scholar
  73. Srinivasan CS, Irz X, Shankar B (2006) An assessment of the potential consumption impacts of WHO dietary norms in OECD countries. Food Policy 31(1):53–77.  https://doi.org/10.1016/j.foodpol.2005.08.002 CrossRefGoogle Scholar
  74. Stehfest E, Bouwman L, van Vuuren DP, den Elzen MG, Eickhout B, Kabat P (2009) Climate benefits of changing diet. Clim Chang 95(1–2):83–102.  https://doi.org/10.1007/s10584-008-9534-6 CrossRefGoogle Scholar
  75. Turner BL, Lambin EF, Reenberg A (2007) The emergence of land change science for global environmental change and sustainability. Proc Natl Acad Sci 104(52):20666–20671.  https://doi.org/10.1073/pnas.0704119104 CrossRefGoogle Scholar
  76. Veldkamp A, Lambin EF (2001) Predicting land use change. Agric Ecosyst Environ 85:1):1–1):6.  https://doi.org/10.1016/S0167-8809(01)00199-2 CrossRefGoogle Scholar
  77. Vieira ICG, Toledo PM, Silva JMC, Higuchi H (2008) Deforestation and threats to the biodiversity of Amazonia. Braz J Biol 68(4, Suppl):949–956.  https://doi.org/10.1590/S1519-69842008000500004 CrossRefGoogle Scholar
  78. Walker R, Drzyzga SA, Li Y, Qi J, Caldas M, Arima E, Vergara D (2004) A behavioral model of landscape change in the Amazon basin: the colonist case. Ecol Appl 14(sp4):299–312.  https://doi.org/10.1890/01-6004 CrossRefGoogle Scholar
  79. Wint W, Robinson T (2007) Gridded livestock of the world 2007. FAO, Rome ISBN 978-92-5-106791-9Google Scholar
  80. Wright HL, Lake IR, Dolman PM (2012) Agriculture—a key element for conservation in the developing world. Conserv Lett 5(1):11–19.  https://doi.org/10.1111/j.1755-263X.2011.00208.x CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Jan Göpel
    • 1
  • Jan Schüngel
    • 1
  • Rüdiger Schaldach
    • 1
  • Katharina H. E. Meurer
    • 2
  • Hermann F. Jungkunst
    • 3
  • Uwe Franko
    • 4
  • Jens Boy
    • 5
  • Robert Strey
    • 5
  • Simone Strey
    • 5
  • Georg Guggenberger
    • 5
  • Anna Hampf
    • 6
  • Phillip Parker
    • 6
  1. 1.Center for Environmental Systems Research (CESR)University of KasselKasselGermany
  2. 2.Department of EcologySwedish University of Agricultural Sciences - SLUUppsalaSweden
  3. 3.Institute for Environmental SciencesUniversity of Koblenz-LandauLandauGermany
  4. 4.Department of Soil Physics, Helmholtz Centre for Environmental Research—UFZHalle (Saale)Germany
  5. 5.Institute of Soil ScienceLeibniz Universität HannoverHannoverGermany
  6. 6.Leibniz-Zentrum für Agrarlandschaftsforschung (ZALF) e. VMünchebergGermany

Personalised recommendations