基于地理加权随机森林的青藏地区放牧强度时空格局模拟

doi:10.13249/j.cnki.sgs.2023.03.003

Abstract

Abstract:

Accurately quantifying the spatiotemporal pattern of grazing intensity on the Qinghai-Tibet Plateau (QTP) is crucial to improving our understanding of the driving mechanism of alpine grassland change, and is of great significance for maintaining regional ecological security and promoting sustainable development policies. Based on the data of livestock inventory at the end of the year and environmental covariates (e.g. population density in pastoral areas, growing season NDVI, annual precipitation, annual mean temperature, and settlements), the gridded grazing intensities on the QTP in 2000, 2010, and 2020 were simulated by geographically weighted random forest (GRF), and the regional differences in the interpretability of environmental variables were then analyzed. The results showed that grazing intensity maps predicted by the GRF could mirror the spatial distribution of grazing intensity on the QTP, compared with the classic random forest model, the R² was higher, and both the mean absolute value error (MAE) and root mean square error (RMSE) were lower. The grazing intensity was generally higher in the southeast and lower in the northwest of the QTP. The areas with grazing intensity of less than 25 sheep units/km² in the northwest part accounted for about half of the QTP. Compared with 2000 and 2010, the grazing intensity of the QTP in 2020 showed a trend of overall decrease but local increase. For example, compared with 2010, the areas of grazing intensity decreased by higher than 1 sheep unit/km² in 2020 accounting for 61.69% of the pastoral area. The population density in pastoral areas was the most important factor explaining the spatial heterogeneity of grazing intensity, and its relative importance was higher in the western QTP and lower in the eastern QTP. On the contrary, the relative importance of both precipitation and growing season NDVI was higher in the northwest part and lower in the southeast part of QTP. Our results provide scientific references for sustainable grassland management and ecological safety barrier construction on the QTP.

Key words: grazing intensity, geographically weighted random forest, population density in pastoral areas, the Qinghai-Tibetan Plateau

CLC Number:

Li Lanhui, Huang Congcong, Zhang Yili, Liu Linshan, Wang Zhaofeng, Zhang Haiyan, Ding Mingjun, Zhang Huamin. Mapping the multi-temporal grazing intensity on the Qinghai-Tibet Plateau using geographically weighted random forest[J].SCIENTIA GEOGRAPHICA SINICA, 2023, 43(3): 398-410.

Figures/Tables 12

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数据名称	时间粒度（年份）	数据类型/分辨率	来源/参考文献
注：区县、地级市和自治州牲畜年末存栏统计数据来源于《西藏统计年鉴》和《青海统计年鉴》（ https://data.cnki.net/Yearbook/）及当地政府的统计数据；资源环境科学与数据中心网址 https://www.resdc.cn/；“–”为无此项。
县级牲畜年末存栏量	2000，2010，2020	Excel	统计数据
乡镇牲畜年末存栏量（部分）	2010	Excel	统计数据
地表覆盖类型	2000，2010，2020	1 000 m	Liu等^[31]、Zhang等^[32]
夜间灯光指数	2000，2010，2020	15 arcsec （～500 m）	Chen等^[33]
人口密度	2000，2010，2020	1 000 m	Li等^[34]
到居民点距离	2000，2012，2016	1 000 m	Li等^[34]
居民点密度	2000，2012，2016	1 000 m	Li等^[34]
到道路的距离	2000，2012，2016	1 000 m	Li等^[34]
河流	–	矢量	资源环境科学与数据中心
保护区	–	矢量	资源环境科学与数据中心
行政区划	–	矢量	资源环境科学与数据中心
DEM	–	1 000 m	资源环境科学与数据中心
生长季NDVI均值	2000—2016	1 000 m	资源环境科学与数据中心
年平均气温均值	2000—2016	0.1°	He等^[35]
年降水量均值	2000—2016	0.1°	He等^[35]
GLW2牲畜密度	2001	~1 000 m	Robinson等^[12]
GLW3牲畜密度	2001	~10 000 m	Gilbert等^[11]

Mapping the multi-temporal grazing intensity on the Qinghai-Tibet Plateau using geographically weighted random forest

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