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To tackle ecological problems, many ecological restoration projects have been implemented in northern China. Identifying the drivers of vegetation change is critical for continued ecological engineering. In this study, three typical ecological reserves in the Three-North Shelter Forest Program Region (TNSFR) were selected to identify their vegetation development characteristics and driving mechanisms using the normalized difference vegetation index (NDVI), climate factors, and land use data. The results show that (1) NDVIs increased in the range of human activities of all of the three ecological reserves, indicating an obvious effect of the vegetation restoration projects. (2) In the planting period, vegetation restoration was mainly correlated with human activities. After entering the tending period, the impact of climate changes on vegetation dynamics was enhanced. (3) Temperature and precipitation provided approximate driving effects on vegetation dynamics in Region I, while vegetation dynamics in Regions II and III were more strongly correlated with precipitation. (4) The proportion of areas with ecological measures exceeded 50% in all three regions. In short, ecological projects in the three ecological reserves dominated the quantity of vegetation restoration, while climate changes influenced the quality of vegetation restoration.

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Droughts have significantly damaged the environment of the Inner Mongolia Autonomous Region, China. In this study, the region was divided into two subregions. Soil moisture was used as the basic parameter to analyze the characteristics of agricultural droughts. Based on a geographical detector, the spatial stratified heterogeneity in different seasons was discussed. Moreover, the copula joint functions of characteristics and dominant factors of agricultural droughts were constructed. Based on the Soil Moisture Anomaly Percentage Index (SMAPI), the results demonstrate that the climate tendency rate of droughts in the summer and in spring in Subregion I shows an increasing trend, while it decreases in the autumn and winter. In Subregion II, the climate tendency rate of droughts in different seasons has no significant change. Through geographical detection, the single factor detection illustrates that temperature and Precipitation Conversion Efficiency (PCE) show the highest explanatory power in different subregions. The interactive detection also demonstrates the explanatory powers of the combination of the PCE and temperature, respectively. The t-copula function describes the correlation coefficients of the SMAPI with the PCE and temperature, with the optimal tail dependence. In short, agricultural droughts are most significantly affected by temperature and the PCE, and their balance has a significant impact on agricultural droughts.

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