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

Abstract

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.

Mapping livestock density distribution in the Selenge River Basin of Mongolia using random forest

“…Precipitation and land surface temperature can reflect climatic differences in different regions. These environmental variables directly affect vegetation growth and indirectly influence livestock distribution by determining the availability of fodder and water in a given area 41 , 42 . Settlement density also reflects the aggregation of livestock density.…”

Gridded livestock density database and spatial trends for Kazakhstan

“…Environmental variables, such as precipitation, temperature, solar radiation, and vapor pressure deficit, were included to reflect climatological differences across regions. These environmental variables directly affect vegetation growth and indirectly impact livestock distribution by determining feed and water availability in a given area 36 , 37 , 48 . Additionally, the distance to settlements and water bodies was included as high-productive forage close to residential areas, and water bodies are more convenient for herders to allow livestock to graze 21 , 37 .…”

Climate warming creates an unequal burden on global cattle meat yields

“…The lack of management practices determines the greater sensitivity to warming in grassland-based system because some indoor alleviations, like shed shade, shower and house heating control (Hristov et al, 2018;Toghiani et al, 2020), cannot be applied. In addition, compared with the cropland-feed system, the rangeland vegetation productivity is also more sensitive to climate change (Lehnert et al, 2016;Sloat et al, 2018;Weindl et al, 2015;Zhan et al, 2023) Moreover, the unequal burdens of warming are found across the countries with different income levels (defined by World Bank) and economic production. Specifically, the low-income countries are more vulnerable to the effect of warming.…”