High-resolution livestock seasonal distribution data on the Qinghai-Tibet Plateau in 2020

被引:13
|
作者
Zhan, Ning [1 ,2 ,3 ,4 ,5 ]
Liu, Weihang [1 ,2 ,3 ,4 ,5 ]
Ye, Tao [1 ,2 ,3 ,4 ,5 ]
Li, Hongda [6 ]
Chen, Shuo [1 ,2 ,3 ,4 ,5 ,7 ]
Ma, Heng [1 ,2 ,3 ,4 ,5 ]
机构
[1] Beijing Normal Univ, State Key Lab Earth Surface Proc & Resource Ecol E, Beijing 100875, Peoples R China
[2] Beijing Normal Univ, Key Lab Environm Change & Nat Disasters, Minist Educ, Beijing 100875, Peoples R China
[3] Minist Emergency Management, Acad Disaster Reduct & Emergency Management, Beijing 100875, Peoples R China
[4] Minist Educ, Beijing 100875, Peoples R China
[5] Beijing Normal Univ, Fac Geog Sci, Beijing 100875, Peoples R China
[6] Qinghai Gen Stn Grassland, Xining 810008, Qinghai, Peoples R China
[7] Purdue Univ, Dept Agr & Biol Engn, W Lafayette, IN 47907 USA
关键词
SYSTEMS; CHINA; DEGRADATION; POPULATION; RESPONSES; WILDLIFE; CLIMATE; CARBON;
D O I
10.1038/s41597-023-02050-0
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Incorporating seasonality into livestock spatial distribution is of great significance for studying the complex system interaction between climate, vegetation, water, and herder activities, associated with livestock. The Qinghai-Tibet Plateau (QTP) has the world's most elevated pastoral area and is a hot spot for global environmental change. This study provides the spatial distribution of cattle, sheep, and livestock grazing on the warm-season and cold-season pastures at a 15 arc-second spatial resolution on the QTP. Warm/cold-season pastures were delineated by identifying the key elements that affect the seasonal distribution of grazing and combining the random forest classification model, and the average area under the receiver operating characteristic curve of the model is 0.98. Spatial disaggregation weights were derived using the prediction from a random forest model that linked county-level census livestock numbers to topography, climate, vegetation, and socioeconomic predictors. The coefficients of determination of external cross-scale validations between dasymetric mapping results and township census data range from 0.52 to 0.70. The data could provide important information for further modeling of human-environment interaction under climate change for this region.
引用
收藏
页数:15
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