| Issue |
E3S Web Conf.
Volume 53, 2018
2018 3rd International Conference on Advances in Energy and Environment Research (ICAEER 2018)
|
|
|---|---|---|
| Article Number | 03036 | |
| Number of page(s) | 8 | |
| Section | Environment Engineering, Environmental Safety and Detection | |
| DOI | https://doi.org/10.1051/e3sconf/20185303036 | |
| Published online | 14 September 2018 | |
Study on the Driving Mechanism of Ecosystem Service Value on Ximen Island Based on STIRPAT Model
1
Second Institute of Oceanography, SOA, Hangzhou, 310012, China
2
Nanjing University, Nanjing, 210000, China
* Corresponding author: tanyonghua@sio.org.cn
The ecosystem service value on Ximen Island was calculated using the value table of ecosystem services proposed by Xie et al. according to the land use data from 2006–2017. The STIRPAT model was used to analyze the driving mechanisms of ecosystem services on Ximen Island. The results show that the ecosystem service value of Ximen Island has gradually decreased from 2006 to 2017, and the value of ecosystem services has decreased by 15.842 million Yuan over 10 years. Applying the principal component analysis method can effectively eliminate the collinearity problem in the process of regression analysis. The value of ecosystem services has a high correlation with socio-economic variables. The total population, GDP per capita, the increased rate of forestry output, the proportion of primary industry, and the Engel coefficient are all important driving factors that affect the change of valuable ecosystem services on Ximen Island. Among them, the proportion of primary industry is positive, and the other 4 indicators are negative. The rate of increase in forestry output has the greatest negative impact. A 1% increase in the total population, in the GDP per capita, in the rate of forestry output, in the proportion of primary industry, and in the Engel coefficient results in ecosystem service values varying by 0.199%, 0.165%, 0.289%, -0.144%, and 0.252%, respectively.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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