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Response of Vegetation Productivity to Climate Change and Human Activities in the Shaanxi–Gansu–Ningxia Region, China

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Abstract

Based on the MODIS vegetation net primary productivity (NPP) product data (MOD17A3-NPP) and evapotranspiration (ET) product data (MOD16A3-ET) of 2000–2014, this study adopted linear trend analysis, correlation coefficient, partial correlation coefficient and other mathematical analysis methods to analyse both the temporal-spatial evolution of vegetation NPP in the Shaanxi–Gansu–Ningxia Region (SGNR) in the 15 years, and the influence of meteorological factors (temperature, precipitation and ET) and human activities on its vegetation NPP. The results indicated that (1) from 2000 to 2014 the vegetation annual net primary productivity (ANPP) of the study region significantly increased from 169.06 g C/(m2 a) to 262.49 g C/(m2 a), having an annual rate of increase of 4.57 g C/(m2 a); (2) the increase of ANPP was significant for more than 84% of the study region, and extremely significant for more than 70%; (3) no obvious correlation was detected between ANPP and annual average temperature (AAT), Areas which had a significant positive correlation between ANPP and annual precipitation (AP) were mainly concentrated in arid and semi-arid areas with an AP of less than 400 mm; (4) a significant positive correlation was detected between ANPP and AET in more than 90% of the study region; (5) a gradual improvement in ANPP and a continuous improvement in the ecological environment were identified in SGNR. These improvements were inseparable from the decisive role played by human activities.

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Acknowledgements

This paper is partially funded by National Hightech R&D Program of China (863 Program) (2015AA123901), Natural Science Foundation of Hebei Province of China (D2015402134; 15967663D; D2017402159), and the Education Department of Hebei Province (QN2015105; YQ2013012; QN2014184).

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Correspondence to Anbing Zhang.

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Liu, H., Zhang, A., Jiang, T. et al. Response of Vegetation Productivity to Climate Change and Human Activities in the Shaanxi–Gansu–Ningxia Region, China. J Indian Soc Remote Sens 46, 1081–1092 (2018). https://doi.org/10.1007/s12524-018-0769-z

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  • DOI: https://doi.org/10.1007/s12524-018-0769-z

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