| Issue |
E3S Web Conf.
Volume 158, 2020
2019 7th International Conference on Environment Pollution and Prevention (ICEPP 2019)
|
|
|---|---|---|
| Article Number | 06003 | |
| Number of page(s) | 7 | |
| Section | Environmental Economy and Management | |
| DOI | https://doi.org/10.1051/e3sconf/202015806003 | |
| Published online | 23 March 2020 | |
Influence of meteorological factors on ecosystem services value: a case study of Beijing-Tianjin-Hebei region, China
1 College of Soil and Water Conservation, Beijing Forestry University, 100083, Beijing China
2 Changjiang Water Resources Protection Institute, 430051 Wuhan, China
3 School of Nature Conservation, Beijing Forestry University, 10083 Beijing, China
∗ Corresponding author: zhenya_zhu@126.com
Meteorological factors are one of the natural factors, which affect ecosystem services value (ESV). Influence of meteorological factors was studied in Beijing-Tianjin-Hebei region using ordinary least square (OLS) with geographical weighted regression (GWR). The main aim of this study was to reveal the differences in the influence mechanism at the global and local levels. The main meteorological factors influencing ESV were temperature and precipitation, followed by humidity. Days with annual daily precipitation≥0.1mm, annual minimum precipitation and annual average relative humidity were three important meteorological factors. Annual temperature range, annual minimum precipitation, days with annual daily precipitation≥0.1mm, in particular, the last one had an obvious positive effect. The positive and negative effects of annual average relative humidity were coexisting, and the negative effect was the main. It was obvious that the spatial distribution characteristics of the local influence mechanism. The local model of GWR can better solve the spatial non-stationarity of the dependent and independent variables, thus it was better than the global model of OLS. The results also provide detailed field information on the different effects of meteorological factors at different locations.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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