Differentiating anthropogenic modification and precipitation-driven change on vegetation productivity on the Mongolian Plateau
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The Mongolian Plateau, comprising Inner Mongolia, China (IM) and Mongolia (MG) is undergoing consistent warming and accelerated land cover/land use change. Extensive modifications of water-limited regions can alter ecosystem function and processes; hence, it is important to differentiate the impacts of human activities and precipitation dynamics on vegetation productivity.
This study distinguished between human-induced and precipitation-driven changes in vegetation cover on the plateau across biome, vegetation type and administrative divisions.
Non-parametric trend tests were applied to the time series of vegetation indices (VI) derived from MODIS and AVHRR and precipitation from TRMM and MERRA reanalysis data. VI residuals adjusted for rainfall were obtained from the regression between growing season maximum VI and monthly accumulated rainfall (June–August) and were used to detect human-induced trends in vegetation productivity during 1981–2010. The total livestock and population density trends were identified and then used to explain the VI residual trends.
The slope of precipitation-adjusted EVI and EVI2 residuals were negatively correlated to total livestock density (R2 = 0.59 and 0.16, p < 0.05) in MG and positively correlated with total population density (R2 = 0.31, p < 0.05) in IM. The slope of precipitation-adjusted EVI and EVI2 residuals were also negatively correlated with goat density (R2 = 0.59 and 0.19, p < 0.05) and sheep density in MG (R2 = 0.59 and 0.13, p < 0.05) but not in IM.
Some administrative subdivisions in IM and MG showed decreasing trends in VI residuals. These trends could be attributed to increasing livestock or population density and changes in livestock herd composition. Other subdivisions showed increasing trends residuals, suggesting that the vegetation cover increase could be attributed to conservation efforts.
KeywordsMongolian Plateau Semi-arid Vegetation indices Precipitation RESTREND MODIS EVI EVI2 GIMMS3 g NDVI Livestock density Population density
This study was supported by the “Dynamics of Coupled Natural and Human Systems (CNH)” Program of the NSF (#1313761), the LCLUC program of NASA (NNX14AD85G), and the Natural Science Foundation of China (31229001). J. Xiao was supported by the National Science Foundation (NSF) through Macro Systems Biology (Award Number 1065777) and NASA through the Carbon Cycle Science Program (Award Number NNX14AJ18G). We would like to thank Gabriela Shirkey for editing the manuscript. We thank the anonymous reviewers and the editor for their constructive comments on the manuscript.
- Akram M, Qian Z, Wenjun L (2008) Policy analysis in grassland management of Xilingol Prefecture, Inner Mongolia in. In: Lee C, Schaaf T (eds) The future of drylands. Springer, Dordrecht, pp 493–505Google Scholar
- Barreto-Munoz A (2013) Multi-sensor vegetation index and land surface phenology earth science data records in support of global change studies: data quality challenges and data explorer system. The University of Arizona, TucsonGoogle Scholar
- Chen J, Wan S, Henebry G, Qi J, Gutman G, Sun G, Kappas M (eds) (2013) Dryland East Asia (DEA): land dynamics amid social and climate change. HEP and De Gruyter, Berlin, 470 pp. Retrieved 22 Aug 2015, from http://www.degruyter.com/view/product/183249
- Didan K (2010) Multi-satellite earth science data record for studying global vegetation trends and changes. In: International geoscience and remote sensing symposium, Honolulu, pp 25–30Google Scholar
- Groisman PY, Clark EA, Lettenmaier DP, Kattsov VM, Sokolik IN, Aizen VB, Cartus O, Chen J, Schmullius CC, Conard S, Katzenberger J, Krankina O, Kukkonen J, Sofiev MA, Machida T, Maksyutov S, Ojima D, Qi J, Romanovsky VE, Walker D, Santoro M, Shiklomanov AI, Vörösmarty C, Shimoyama K, Shugart HH, Shuman JK, Sukhinin AI, Wood EF (2009) The Northern Eurasia Earth Science Partnership: an example of science applied to societal needs. Bull Am Meteorol Soc 90(5):671–688CrossRefGoogle Scholar
- Liu Y, Zhuang Q, Miralles D, Pan Z, Kicklighter D, Zhu Q, He Y, Chen J, Tchebakova N, Sirin A, Niyogi D, Melillo J (2015) Evapotranspiration in Northern Eurasia: impact of forcing uncertainties on terrestrial ecosystem model estimates. J Geophys Res 120(7):2014JD022531Google Scholar
- Olson DM, Dinerstein E, Wikramanayake ED, Burgess ND, Powell GVN, Underwood EC, D'Amico JA, Itoua I, Strand HE, Morrison JC, Loucks CJ, Allnutt TF, Ricketts TH, Kura Y, Lamoreux JF, Wettengel WW, Hedao P, Kassem KR (2001) Terrestrial ecoregions of the world: a new map of life on earth. Bioscience 51(11):933–938CrossRefGoogle Scholar
- Reynolds JF, Smith DMS, Lambin EF, Turner BL, Mortimore M, Batterbury SPJ, Downing TE, Dowlatabadi H, Fernández RJ, Herrick JE, Huber-Sannwald E, Jiang H, Leemans R, Lynam T, Maestre FT, Ayarza M, Walker B (2007) Global desertification: building a science for dryland development. Science 316(5826):847–851PubMedCrossRefGoogle Scholar
- Rienecker MM, Suarez MJ, Gelaro R, Todling R, Bacmeister J, Liu E, Bosilovich MG, Schubert SD, Takacs L, Kim G-K, Bloom S, Chen J, Collins D, Conaty A, da Silva A, Gu W, Joiner J, Koster RD, Lucchesi R, Molod A, Owens T, Pawson S, Pegion P, Redder CR, Reichle R, Robertson FR, Ruddick AG, Sienkiewicz M, Woollen J (2011) MERRA: NASA’s modern-era retrospective analysis for research and applications. J Clim 24(14):3624–3648CrossRefGoogle Scholar