Skip to main content

Advertisement

Log in

Human-induced climate change: the impact of land-use change

Theoretical and Applied Climatology Aims and scope Submit manuscript

Abstract

For hundreds of years, human activity has modified the planet’s surface through land-use practices. Policies and decisions on how land is managed and land-use changes due to replacement of forests by agricultural cropping and grazing lands affect greenhouse gas emissions. Agricultural management and agroforestry and the resulting changes to the land surface alter the global carbon cycle as well as the Earth’s surface albedo, both of which in turn change the Earth’s radiation balance. This makes land-use change the second anthropogenic source of climate change after fossil fuel burning. However, the scientific research community has so far not been able to identify the direction and magnitude of the global impact of land-use change. This paper examines the effects of net carbon flux from land-use change on temperature by applying Granger causality and error correction models. The results reveal a significant positive long-run equilibrium relationship between land-use change and the temperature series as well as an opposing short-term effect such that land-use change tends to lead to global warming; however, a rise in temperature causes a decline in land-use change.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Notes

  1. Based on the global carbon model EFF + ELUC = GATM + SOCEAN + SLAND + BIM, where EFF is carbon dioxide emissions from fossil fuel and industry, ELUC represents emissions from land-use change, GATM is the growth rate of global atmospheric carbon dioxide concentration, SOCEAN and SLAND represent the ocean and terrestrial carbon dioxide sinks and BIM is a mismatch measure, the Global Carbon Project (2017) reports emission estimates of 9.4 ± 0.5 GtC yr.−1 for EFF, 1.3 ± 0.7 GtC yr.−1for ELUC, 4.7 ± 0.1 GtC yr.−1 for GATM, 2.4 ± 0.5 GtC yr.−1 for SOCEAN and 3.0 ± 0.8 GtC yr.−1 for SLAND between 2007 and 2016.

  2. For each temperature type (with the exception of sea surface temperature) datasets were additionally derived from different sources and serve as sort of sensitivity analysis and a safeguard against inaccuracies in the data and biased results.

  3. According to Alexander (1999) the Engle-Granger test is best suited for testing longer time series in a bivariate setting (Alexander 1999) and in such cases should be favored over the cointegration test developed by Johansen (1988).

  4. Including a deterministic trend would violate the idea of cointegration since errors would increase over time.

  5. Note that model selection criteria, such as the Bayesian Information Criterion (BIC) or the Akaike Information Criterion (AIC), can be used to determine the appropriate model order p.

  6. Although we can identify a long run relationship for the CDIAC temperature series and net carbon flux from land-use change, the results differ for the temperature series from the NASA GISS and the NCDC NOAA. These differences may be due to the different examination periods. While the CDIAC data are available from 1850, the remaining temperature series start in 1880.

  7. While our findings are data driven econometric estimates, the findings of Werth and Avissar (2005), Zhao et al. (2001), Chase et al. (2000) and Findell et al. (2007) are climate model based simulations of a change between naturel to present land cover or simulations of complete deforestation. Further, it should also be noted that although these studies can identify little or no global effect, they find local effects and statistically significant changes in regional temperature.

References

  • Alexander C (1999) Optimal hedging using cointegration. Philos Trans R Soc, Lond, A 357:2039–2058

    Article  Google Scholar 

  • Attanasio A (2012) Testing for linear Granger causality from natural/anthropogenic forcings to global temperature anomalies. Theor Appl Climatol 110:281–289

    Article  Google Scholar 

  • Attanasio A, Triacca U (2011) Detecting human influence on climate using neural networks based Granger causality. Theor Appl Climatol 103:103–107

    Article  Google Scholar 

  • Attanasio A, Antonello P, Triacca U (2012) A contribution to attribution of recent global warming by out-of-sample Granger causality analysis. Atmos Sci Lett 13:67–72

    Article  Google Scholar 

  • Attanasio A, Pasini A, Triacca U (2013) Granger causality analyses for climatic attribution. Atmos Climate Sci 3:515–522

    Google Scholar 

  • Bala G, Caldeira K, Wickett M, Phillips TJ, Lobell DB, Delire C, Mirin A (2007) Combined climate and carbon-cycle effects of large-sale deforestation. Proc Natl Acad Sci 104:6550–6555

    Article  Google Scholar 

  • Barnes CA, Roy DP, Loveland TR (2013) Projected surface radiative forcing due to 2000–2050 land-cover land-use albedo changes over the eastern United States. J Land Use Sci 8:369–382

    Article  Google Scholar 

  • Betts RA (2000) Offset of the potential carbon sink from boreal forestation by decreases in surface albedo. Nature 408:187–189

    Article  Google Scholar 

  • Betts RA (2001) Biogeophysical impacts of land use on present-day climate: near-surface temperature changes and radiative forcing. Atmos Sci Lett 1:1530–1543

    Google Scholar 

  • Betts RA, Falloon PD, Klein Goldewijk K, Ramankutty N (2007) Biogeophysical effects of land use on climate: model simulations of radiative forcing and large-scale temperature change. Agric For Meteorol 142:216–233

    Article  Google Scholar 

  • Bilancia M, Vitale D (2012) Anthropogenic CO2 emissions and global warming: evidence from Granger causality analysis. Adv Stat Methods Anal Large Data-Sets Stud Theoretical and Appl Stat:229–239

  • Bonan GB (1997) Effects of land use on the climate of the United States. Climate Change 37:449–486

    Article  Google Scholar 

  • Bonan GB (2008) Forests and climate change: forcings, feedbacks, and the climate benefits of forests. Science 320:1444–1449

    Article  Google Scholar 

  • Bonan GB, Pollard D, Thompson SL (1992) Effects of boreal forests vegetation on global climate. Nature 359:716–718

    Article  Google Scholar 

  • Bounoua L, DeFries R, Collatz GJ, Sellers P, Khan H (2002) Effects of land cover conversion on surface climate. Climate Change 52:29–64

    Article  Google Scholar 

  • Brovkin V, Ganopolski A, Claussen M, Kubatzki C, Petoukhov V (1999) Modelling climate response to historical land cover change. Glob Ecol Biogeogr 8:509–517

    Article  Google Scholar 

  • Brovkin V, Boysen L, Arora VK, Boisier JP, Cadule P, Chini L, Claussen M, Friedlingstein P, Gayler V, Van den Hurk BJJM, Hurtt GC, Jones CD, Kato E, De Noblet-Ducoudré N, Pacifico F, Pongratz J, Weiss M (2013) Effect of anthropogenic land-use and land-cover changes on climate and land carbon storage in CMIP5 projections for the twenty-first century. J Clim 26:6859–6881

    Article  Google Scholar 

  • Chase TN, Pielke RA, Kittel TGF, Nemani RR, Running SW (2000) Simulated impacts of historical land cover changes on global climate in northern winter. Clim Dyn 16:93–105

    Article  Google Scholar 

  • Claussen M, Brovkin V, Ganopolski A (2001) Biogeophysical versus biogeochemical feedbacks or large-scale land cover change. Geophys Res Lett 28:1011–1014

    Article  Google Scholar 

  • Costa MH, Foley JA (2000) Combined effects of deforestation and doubled atmospheric CO2 concentrations on the climate of Amazonia. J Clim 13:18–34

    Article  Google Scholar 

  • Davin EL, De Noblet-Ducoudré N, Friedlingstein P (2007) Impact of land cover change on surface climate: relevance of the radiative forcing concept. Geophys Res Lett 34:1–5

    Article  Google Scholar 

  • Dickey DA, Fuller WA (1979) Distribution of the estimators for autoregressive time series with a unit root. J Am Stat Assoc 74:427–431

    Google Scholar 

  • Donohue RJ, Roderick ML, McVicar TR, Farquhar GD (2013) Impact of CO2 fertilization on maximum foliage cover across the globe’s warm, arid environments. Geophys Res Lett 40(12):3031–3035

    Article  Google Scholar 

  • Engle RF, Granger CWJ (1987) Co-integration and error correction: representation, estimation and testing. Econometrica 55:251–276

    Article  Google Scholar 

  • Findell KL, Shevliakova E, Milly PCD, Stouffer RJ (2007) Modeled impact of anthropogenic land cover change on climate. J Clim 20:3621–3634

    Article  Google Scholar 

  • Gedney N, Valdes PJ (2000) The effect of Amazonian deforestation on the northern hemisphere circulation and climate. Geophys Res Lett 27:3053–3056

    Article  Google Scholar 

  • Ghommem M, Hajj MR, Puri IK (2012) Influence of natural and anthropogenic carbon dioxide sequestration on global warming. Ecol Model 235-236:1–7

    Article  Google Scholar 

  • Gibbard S, Caldeira K, Bala G, Phillips TJ, Wickett M (2005) Climate effects of global land cover change. Geophys Res Lett 32:1–4

    Article  Google Scholar 

  • Global Carbon Project (2017) Global carbon budget 2017. Earth System Science Data Discussions. https://doi.org/10.5194/essd-2017-123. pp. 1–79, by Le Quéré C, Andrew RM, Friedlingstein P, et al.

  • Granger CWJ (1969) Investigating causal relations by econometric models and cross-spectral methods. Econometrica 37:424–438

    Article  Google Scholar 

  • Hansen JE, Ruedy R, Glascoe J, Sato M (1999) GISS analysis of surface temperature change. J Geophys Res 104:997–1022

    Google Scholar 

  • Houghton RA (1999) The annual net flux of carbon to the atmosphere from changes in land use 1850–1990. Tellus 51(2):298–313

    Article  Google Scholar 

  • Houghton RA (2003) Revised estimates of the annual net flux of carbon to the atmosphere from changes in land use and land management 1850–2000. Tellus 55:378–390

    Google Scholar 

  • Houghton RA, Hackler JL (1995) Continental scale estimates of the biotic carbon flux from land cover change: 1850-1980. ORNL/CDIAC-79, NDP-050, carbon dioxide information analysis center, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee

  • Houghton RA, Nassikas AA (2017) Global and regional fluxes of carbon from land use and land cover change 1850–2015. Glob Biogeochem Cycles 31(3):456–472

    Article  Google Scholar 

  • Houghton RA, Hobbie JE, Melillo JM, Moore B, Peterson BJ, Shaver GR, Woodwell GM (1983) Changes in the carbon content of terrestrial biota and soils between 1860 and 1980: a net release of CO2 to the atmosphere. Ecol Monogr 53:235–262

    Article  Google Scholar 

  • Houghton RA, House JI, Pongratz J, van der Werf GR, DeFries RS, Hansen MC, Le Quéré C, Ramankutty N (2012) Carbon emissions from land use and land-cover change. Biogeosciences 9:5125–5142

    Article  Google Scholar 

  • IPCC (2000) Land use, land-use change, and forestry—summary for policymakers. IPCC special reports, [Watson, R.T.; Noble, I.R.; Bolin, B.; Ravindranath, N.H.; Verardo, D.J.; Dokken, D.J. (eds.)], Cambridge University Press, UK 6-22

  • IPCC (2007) Synthesis Report. Climate Change 2007: synthesis report. Contribution of Working Groups I, II and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, IPCC, Geneva, Switzerland 30–41

  • IPCC (2013) Summary for policymakers. Climate change 2013: the physical science basis. Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change, [Stocker TF, Qin D, Plattner G-K, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex, V and Midgley PM (eds)], Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA 11-26

  • Johansen S (1988) Statistical analysis of cointegration vectors. J Econ Dyn Control 12:231–254

    Article  Google Scholar 

  • Jones PD, Raper SCB, Cherry BSG, Goodess CM, Wigley TML (1986) Grid point surface air temperature data set for the southern hemisphere. U.S. Department of Energy, Carbon Dioxide Research Division, technical report TR027:73

  • Kang J, Larsson R (2014) What is the link between temperature and carbon dioxide levels? A Granger causality analysis based on ice core data. Theor Appl Climatol 116:537–548

    Article  Google Scholar 

  • Kaufmann RK, Stern DI (1997) Evidence for human influence on climate from hemispheric temperature relations. Nature 338:39–44

    Article  Google Scholar 

  • Kaufmann RK, Stern DI (2002) Cointegration analysis of hemispheric temperature relations. J Geophys Res 107:1–10

    Google Scholar 

  • Keenan TF, Prentice IC, Canadell JG, Williams CA, Wang H, Raupach M, Collatz GJ (2016) Recent pause in the growth rate of atmospheric CO2 due to enhanced terrestrial carbon uptake. Nat Commun 7. https://doi.org/10.1038/ncomms13428

  • Kirschbaum MUF, Saggar S, Tate KR, Thakur KP, Giltrap DL (2013) Quantifying the climate-change consequences of shifting land use between forest and agriculture. Sci Total Environ:1–11

  • Kodra E, Chatterjee S, Ganguly AR (2011) Exploring Granger causality between global average observed time series of carbon dioxide and temperature. Theor Appl Climatol 104:325–335

    Article  Google Scholar 

  • Kuo C, Lindberg C, Thomson DJ (1990) Coherence established between atmospheric carbon dioxide and global temperature. Nature 343:709–714

    Article  Google Scholar 

  • Lenton TM (2000) Land and ocean carbon cycle feedback effects on global warming in a simple Earth system model. Tellus 52(5):1159–1188

    Article  Google Scholar 

  • Liew VK-S (2004) Which lag length selection criteria should we employ? Econ Bull 3:1–9

    Google Scholar 

  • Liu H, Rodriguez G (2005) Human activities and global warming: a co-integration analysis. Environ Model Softw 20:761–773

    Article  Google Scholar 

  • Lütkepohl H, Krätzig M (2004) Applied time series econometrics. Cambridge University Press, Cambridge 148:11–64

    Google Scholar 

  • Mann EM, Bradley RS, Hughes MK (1998) Global-scale temperature patterns and climate forcing over the past six centuries. Nature 392:779–787

    Article  Google Scholar 

  • Myhre G, Myhre A (2003) Uncertainties in radiative forcing due to surface albedo changes caused by land-use changes. J Clim 16:1511–1524

    Article  Google Scholar 

  • NOAA–National Oceanic and Atmospheric Administration (2017) Global surface temperature anomalies. National Climatic Data Center, accessed 22 Dec 2017 <https://www.ncdc.noaa.gov/monitoring-references/faq/anomalies.php>

  • Pasini A, Lorè M, Ameli F (2006) Neural network modelling for the analysis of forcings/temperatures relationships at different scales in the climate system. Ecol Model 191:58–67

    Article  Google Scholar 

  • Phillips PCB, Perron P (1988) Testing for a unit root in time series regression. Biometrika 75:335–346

    Article  Google Scholar 

  • Pielke RA, Marland G, Betts RA, Chase TN, Eastman JL, Niles JO, Niyogi DDS, Running SW (2002) The influence of land-use change and landscape dynamics on the climate system: relevance to climate-change policy beyond the radiative effect of greenhouse gases. Philos Trans R Soc Lond 360:1705–1719

    Article  Google Scholar 

  • Pitman A, Pielke R, Avissar R, Claussen M, Gash J, Dolman H (2001) The role of the land surface in weather and climate: does the land surface matter? Glob Change Newsl 39:4–11

    Google Scholar 

  • Polcher J, Laval K (1994) A statistical study of the regional impact of deforestation on climate in the LMD GCM. Clim Dyn 10:205–219

    Article  Google Scholar 

  • Pongratz J, Caldeira K (2012) Attribution of atmospheric CO2 and temperature increases to regions: importance of preindustrial land use change. Environ Res Lett 7:1–8

    Article  Google Scholar 

  • Schönwiese CD (1994) Analysis and predictions of global climate temperature change based on multiforced observational statistics. Environ Pollut 83:149–154

    Article  Google Scholar 

  • Schwaiger HP, Bird DN (2010) Integration of albedo effects caused by land use change into the climate balance: should we still account in greenhouse gas units? For Ecol Manag 260:278–286

    Article  Google Scholar 

  • Sitch S, Brovkin V, von Bloh W, van Vuuren D, Eickhout B, Ganopolski A (2005) Impacts of future land cover changes on atmospheric CO2 and climate. Glob Biogeochem Cycles 19:1–15

    Article  Google Scholar 

  • Sitch S, Friedlingstein P, Gruber N, Jones SD, Murray-Tortarolo G, Ahlström A, Doney SC, Graven H, Heinze C, Huntingford C, Levis S, Levy PE, Lomas M, Poulter B, Viovy N, Zaehle S, Zeng N, Arneth A, Bonan G, Bopp L, Vanadell JG, Chevallier F, Ciais P, Ellis R, Gloor M, Peylin P, Piao SL, Le Quéré C, Smith B, Zhu Z, Myneni R (2015) Recent trends and drivers of regional sources and sinks of carbon dioxide. Biogeosciences 12(3):653–679

    Article  Google Scholar 

  • Smirnov DA, Mokhov IL (2009) From Granger causality to long-term causality: application to climate data. Phys Rev E 80:1–17

    Google Scholar 

  • Smith RL, Wigley TML, Santer BD (2003) A bivariate time series approach to anthropogenic trend detection in hemispheric time series. J Clim 16:1228–1240

    Article  Google Scholar 

  • Smith TM, Reynolds RW, Peterson TC, Lawrimore J (2008) Improvements to NOAA’s historical merged Land-Ocean surface temperature analysis (1880–2006). J Clim 21:2283–2296

    Article  Google Scholar 

  • Snyder PK, Foley JA, Hitchman MH, Delire C (2004) Analyzing the effects of complete tropical forest removal of the regional climate using a detailed three-dimensional energy budget: an application to Africa. J Geophys Res 109:1–19

    Article  Google Scholar 

  • Stern DI, Kaufmann RK (1997) Time series properties of global climate variables: detection and attribution of climate change. Working Papers in Ecological Economics, Center for Energy and Environmental Studies, Boston University, Boston 9702:1–37

  • Stern DI, Kaufmann RK (1999) Econometric analysis of global climate change. Environ Model Softw 14:597–605

    Article  Google Scholar 

  • Sun L, Wang M (1996) Global warming and global dioxide emission: an empirical study. J Environ Manag 46:327–343

    Article  Google Scholar 

  • Thomson DJ (1997) Dependence of global temperatures on atmospheric CO2 and solar irradiance. Proc Natl Acad Sci 94:8370–8377

    Article  Google Scholar 

  • Toda HY, Yamamoto T (1995) Statistical inference in vector autoregressions with possibly integrated processes. J Econ 66:225–250

    Article  Google Scholar 

  • Tol RSJ (1994) Greenhouse statistics—time series analysis: part II. Theor Appl Climatol 49:91–102

    Article  Google Scholar 

  • Tol RSJ, de Vos AF (1993) Greenhouse statistics—time series analysis. Theor Appl Climatol 48:63–74

    Article  Google Scholar 

  • Tol RSJ, de Vos AF (1998) A Bayesian statistical analysis of the enhanced greenhouse effect. Climate Change 38:87–112

    Article  Google Scholar 

  • Triacca U (2005) Is Granger causality analysis appropriate to investigate the relationship between atmospheric concentration of carbon dioxide and global surface air temperature? Theor Appl Climatol 81:133–135

    Article  Google Scholar 

  • Triacca U, Attanasio A, Pasini A (2013) Anthropogenic global warming hypothesis: testing its robustness by Granger causality analysis. Environmetrics 24:260–268

    Article  Google Scholar 

  • Voldoire A, Royer JF (2004) Tropical deforestation and climate variability. Clim Dyn 22:857–874

    Article  Google Scholar 

  • van der Werf GR, Morton DC, DeFries RS, Olivier JGJ, Kasibhatla PS, Jackson RB, Collatz GJ, Randerson JT (2009) CO2 emissions from forest loss. Nat Geosci 2:737–738

    Article  Google Scholar 

  • Werth D, Avissar R (2004) The local and global effects of African deforestation. Geophys Res Lett 32:1–4

    Google Scholar 

  • Zhao M, Pitman AJ, Chase T (2001) The impact of land cover change on the atmospheric circulation. Clim Dyn 17:467–477

    Article  Google Scholar 

  • Zhu Z, Piao S, Myneni RB, Huang M, Zeng Z, Canadell JG, Ciais P, Sitch S, Friedlingstein P, Arneth A, Cao C, Vheng L, Kato E, Koven C, Li Y, Lian X, Liu Y, Liu R, Mao J, Pan Y, Peng S, Peñuelas J, Poulter B, Pugh TAM, Stocker BD, Viovy N, Wang X, Wang Y, Xiao Z, Yang H, Zaehle S, Zeng N (2016) Greening of the Earth and its drivers. Nat Clim Chang 6(8):791–795

    Article  Google Scholar 

Download references

Acknowledgments

We would like to thank the editor and an anonymous reviewer for good comments that improved the quality of this paper.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Thomas Gries.

Electronic Supplementary Materials

ESM 1

(DOCX 42 kb)

ESM 2

(DTA 29 kb)

ESM 3

(DO 6 kb)

ESM 4

(DO 2 kb)

ESM 5

(DO 2 kb)

ESM 6

(DO 1 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gries, T., Redlin, M. & Ugarte, J.E. Human-induced climate change: the impact of land-use change. Theor Appl Climatol 135, 1031–1044 (2019). https://doi.org/10.1007/s00704-018-2422-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00704-018-2422-8

Navigation