4.3 Article

Spatiotemporal Characteristics of Ecological Conditions and Its Response to Natural Conditions and Human Activities during 1990-2010 in the Yangtze River Delta, China

Publisher

MDPI
DOI: 10.3390/ijerph15122910

Keywords

ecological conditions; natural conditions; human activities; Lindeman-Merenda-Gold; Yangtze River Delta

Funding

  1. National Key Research and Development Program [2016YFC0500204, 2017YFC0505800]
  2. Shanghai Technology innovation action plan of Yangtze River Delta joint research projects [17295810603]
  3. Natural Science Foundation of Shanghai [17ZR1408700]
  4. Key Laboratory of Spatial Data Mining & Information Sharing of Ministry of Education, Fuzhou University [2017LSDMIS07]

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The Yangtze River Delta (YRD) region, including Shanghai City and the Jiangsu and Zhejiang Provinces, is the largest metropolitan region in China. In the past three decades, the region has experienced an unprecedented process of rapid and massive urbanization, which has dramatically altered the landscape and detrimentally affected the ecological environments in the region. In this paper, we analyzed the spatiotemporal variations of ecological conditions (Eco_C) via a synthetic index with analytic hierarchy processes in the YRD during 1990-2010. The relative contributions of influencing factors, including two natural conditions (i.e., elevation (Elev) and land-sea gradient (Dis_coa)), three indicators of human activities (i.e., urbanization rate (Urb_rate), per capita GDP (Per_gdp), the percentage of secondary and tertiary industry employment (Per_ind)), to the total variance of regional Eco_C were also investigated. The results showed that: (1) The Eco_C over YRD region was Moderately High, which was better than the national average and demonstrated obvious spatial variations between south and north. There existed fluctuations and an overall increasing trend for Eco_C during the study period, with 20% of the area being deteriorated and 40% being improved. (2) The areas with elevation below 10 m was relatively poor in Eco_C, while the regions above 1000 m showed the best Eco_C and had the most obvious changes (9.33%) during the study period. (3) The selected five influencing factors could explain 91.0-94.4% of the Eco_C spatial variability. Elevation was the dominant factor for about 42.4-52.9%, while urbanization rate and per capita GDP were about 32.5% and 9.3%.

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