畜牧业是蒙古国国民经济的支柱产业，草地生态系统的稳定对其可持续发展至关重 要。但作为典型的干旱内陆国家，蒙古国草地生态系统十分脆弱，极易受到气候变化和 人类活动的影响，加之草畜矛盾突出等问题存在，使得畜牧业的可持续发展面临严峻挑 战。因此，有必要基于蒙古国草畜系统的时空变化特征开展畜牧承载力的预测研究。基 于上述背景，本研究首先分析了 2000—2020 年蒙古国畜牧业变化规律；并利用世界网 格化牲畜数据集（Gridded Livestock of the World，GLW）和随机森林回归模型模拟了2000、2006、2010、2015 和 2020 年蒙古国牲畜放牧密度空间分布格局。随后，采用一 元线性回归模型分析 2000—2020 年蒙古国植被净初级生产力（Net Primary Productivity，NPP）时空演变规律；并使用地理探测器定量探究 9 项自然和人类活动因素对蒙古国NPP 变化的影响规律。基于上述研究结果，模拟了 2030—2050 年 SSP1-2.6（低排放路 径）和 SSP5-8.5（高排放路径）情下蒙古国 NPP 空间分布格局，并结合灰色预测模型 模拟未来各类牲畜存栏量，对气候情景下蒙古国草地承载力和草畜平衡指数时空演变规 律进行预测分析。研究主要结论如下：

（1）2000—2020 年，蒙古国畜牧业生产指标和牲畜存栏量总体呈增加趋势，各类 省域牲畜存栏量增长趋势具有空间异质性。放牧密度在空间上整体呈现北高南低的空间 分布。研究期间蒙古国放牧密度总体呈增长趋势，其中变化率在0~10%的区域面积占比 最高，占蒙古国国土面积的 83.6%，集中分布于蒙古国东部地区、中部地区和杭爱地区 的北部。检验结果表明，2000—2020 年模拟数据与蒙古国省域牲畜存栏量拟合 R 2 均大 于 0.734，MAE 均小于 5.648，RMSE 均小于 9.514，均通过显著性检验。

（2）2000—2020 年，蒙古国 NPP 呈东增西减、北增南减的空间变化特征；整体上 呈增加趋势，并以非显著增加为主，非显著增加区域占蒙古国国土面积的 62.539%。单 因子分析显示，气候因素是蒙古国 NPP 变化的主要原因，其中下行短波辐射和年均降 水量的解释力最高，其 q 值分别为 0.615、0.602；但人类足迹指数、NO2 排放量与气候 因子间的交互作用大于单因子分析结果。省域尺度分析表明，气候和地形等自然因素仍 是蒙古国东部和西部地区 NPP 变化的主要驱动力，而蒙古国中部和杭爱地区 NPP 变化 更易受到放牧密度、NO2 排放量等人类活动与自然因素的交互作用，这些区域是今后开展草地退化风险防控的重点关注区域。

（3）2030—2050 年，蒙古国草地承载力整体呈东高西低、北高南低的空间分布格 局。截止 2050 年，高排放 SSP5-8.5 气候情景下，蒙古国中北部（如乌兰巴托、中央省 等）承载力表现出显著增加；而低排放SSP1-2.6气候情景下，承载力显著增加地区则主 要位于蒙古国东部（如东方省、苏赫巴托省），以及西北部（如库苏古尔、布尔干省）。

（4）蒙古国草畜平衡指数受牲畜压力与草地生态系统调节能力的共同作用影响。 在 SSP5-8.5 和 SSP1-2.6 情景下，草畜平衡指数整体以无显著变化为主，东部、杭爱和 西部地区均呈不显著增加趋势，但蒙古国中部、杭爱地区的中部以及西部地区的乌布苏 省将是未来草地管理的重点区域。

综上，尽管 2000—2020 年蒙古国 NPP 总体呈改善趋势，但其中部和杭爱地区易受 到人类活动与气候因素的交互影响，是未来草地退化风险防控的重点关注区域。为促进 畜牧业的可持续发展，需根据各区域放牧潜力的差异，合理规划放牧强度，实现草地资 源的科学利用。

Livestock husbandry is the mainstay of Mongolia's national economy, and the stabilization of grassland ecosystems is crucial to its sustainable development. However, as a typical arid and landlocked country, Mongolia's grassland ecosystems are very fragile and vulnerable to the impacts of climate change and human activities, which, coupled with the existence of problems such as prominent conflicts between grasses and livestock, have made the sustainable development of the livestock industry a serious challenge. Therefore, it is necessary to carry out research on the prediction of livestock carrying capacity based on the spatial and temporal characteristics of grass and livestock systems in Mongolia. Based on the above background, this study first analyzed the changing law of livestock husbandry in Mongolia from 2000 to 2020; and simulated the spatial distribution pattern of livestock grazing density in 2000, 2006, 2010, 2015, and 2020 using the Gridded Livestock of the World (GLW) dataset and random forest regression model. Subsequently, a univariate linear regression model was used to analyze the spatiotemporal variations in net primary productivity (NPP) of vegetation in Mongolia from 2000 to 2020; and the geographic detector method was used to quantitatively explore the influence of nine natural and anthropogenic factors on the changes of NPP in Mongolia. Based on the above results, the spatiotemporal distribution patterns of NPP in Mongolia were simulated under the SSP1-2.6 (low emission pathway) and SSP5-8.5 (high emission pathway) scenarios for 2030-2050, and the gray prediction model was used to simulate the future stocking levels of various types of livestock, and to analyze the spatiotemporal evolution patterns of the grassland carrying capacity and the grass-animal balance index in Mongolia under the climate scenarios. The study also analyzed the spatiotemporal evolution of grassland carrying capacity and grasslivestock balance index under climate scenario. The main conclusions of the study are as follows: (1) From 2000 to 2020, Mongolia's livestock production indicators and livestock stock have shown an overall increasing trend, with spatial heterogeneity in the growth trend of livestock stock in all types of provinces and regions. The overall spatial distribution of grazing density in space showed a high north and low south spatial distribution. The overall trend of grazing density in Mongolia has been increasing, with the highest percentage of the area with the rate of change of 0~10%, accounting for 83.6% of the country's land area, and concentrated in the Eastern region, Central region and the northern part of the Khangai region of Mongolia. The test results showed that the data better realized the simulation of spatialization of grazing density in Mongolia, and the R 2 of the simulated data fitted to the livestock stock in Mongolian provinces from 2000 to 2020 were all greater than 0.734, and they all passed the significance test, and the MAE were all less than 5.648, and the RMSE were all less than 9.514. (2) From 2000 to 2020, NPP in Mongolia was characterized by spatial changes of increasing in the east and decreasing in the west, increasing in the north and decreasing in the south; the overall trend was increasing and dominated by non-significant increase, with the nonsignificantly increasing area accounting for 62.539% of the country's land area. The single-factor analysis showed that climatic factors were the main cause of NPP changes in Mongolia, with downward shortwave radiation and average annual precipitation having the highest explanatory power, with q-values of 0.615 and 0.602, respectively; however, the interaction between the human footprint index, NO2 emissions and climate factors was greater than the results of the oneway analysis.. The provincial scale analysis showed that natural factors such as climate and topography are still the main drivers of NPP changes in the Eastern and Western regions of Mongolia, while NPP changes in the Central and Khangai regions of Mongolia are more susceptible to interactions between human activities and natural factors such as grazing density and NO2 emissions, and these regions are the key areas of concern for the prevention and control of grassland degradation risks in the future. (3) In 2030-2050, the overall spatial distribution pattern of grassland carrying capacity in Mongolia is high in the east and low in the west, high in the north and low in the south. As of 2050, under the high-emission SSP5-8.5 climate scenario, the north-central part of Mongolia (such as Ulaanbaatar, Central Province, etc.) shows a significant increase in carrying capacity, while under the low-emission SSP1-2.6 climate scenario, the areas with significant increase in carrying capacity are located mainly in the eastern part of Mongolia (such as Dornod Province, Sukhbaatar Province), and the northwestern part of the country (sunch as Kusughur, Burgan Province).

(4) The grass-animal balance index in Mongolia is influenced by the combined effects of livestock pressure and the regulatory capacity of grassland ecosystems. Under the SSP5-8.5 and SSP1-2.6 scenarios, the overall grass balance index is dominated by no significant change, with a non-significant increasing trend in the Eastern, Khangai and Western regions, but the Central

region, the central part of the Khangai region, and the Uvs Province in the Western region will be the key areas for grassland management in the future. In summary, although the overall trend of NPP in Mongolia is improving from 2000 to 2020, its Central and Khangai regions are susceptible to the interaction of human activities and climatic factors, and are the key areas of concern for the prevention and control of the risk of grassland degradation in the future. In order to promote the sustainable development of animal husbandry, it is necessary to rationally plan the grazing intensity according to the differences in grazing potential of each region and realize the scientific utilization of grassland resources.

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