As the global climate has changed, studies on the relationship between vegetation and climate have become crucial. We analyzed the long-term vegetation dynamics and diverse responses to extreme climate changes in Inner Mongolia, based on long-term Global Inventory Monitoring and Modelling Studies (GIMMS) NDVI3g datasets, as well as the eight extreme precipitation indices and six extreme temperature indices that are highly correlated with the occurrence of droughts or floods, heat or cold temperature disasters, and vegetation growth in Inner Mongolia. These datasets were analyzed using linear regression analysis, the Hurst exponent index, residual analysis, and the Pearson correlation analysis. The results showed the following: (1) The vegetation dynamical changes exhibited trends of improvement during 1982 to 2015, and 68% of the vegetation growth changes in Inner Mongolia can be explained by climate changes. (2) The extreme precipitation indices exhibited a slight change, except for the annual total wet–day precipitation (PRCPTOT). The occurrence of extreme cold temperatures showed a significant decline, while the occurrence of extreme warm temperatures showed an upward trend in Inner Mongolia. (3) The typical steppe, desert steppe, and forest steppe regions are more sensitive to extreme large precipitation, and the forest regions are more sensitive to extreme warm temperatures. (4) Extreme precipitation exhibits a one-month lagged effect on vegetation that is larger than the same-month effects on the grassland system. Extreme temperature exhibits same-month effects on vegetation, which are larger than the one-month lagged effects on the forest system. Therefore, studies of the relationship between extreme climate indices and vegetation are important for performing risk assessments of droughts, floods, and other related natural disasters.

Vegetation greenness dynamics in arid and semi-arid regions are sensitive to climate change, which is an important phenomenon in global climate change research. However, the driving mechanism, particularly for the longitudinal and latitudinal changes in vegetation greenness related to climate change, has been less studied and remains poorly understood in arid and semi-arid areas. In this study, we investigated changes in vegetation greenness and the vegetation greenness line (the mean growing season normalized difference vegetation index (NDVI) = 0.1 contour line) and its response to climate change based on AVHRR-GIMMS NDVI3g and the fifth and latest global climate reanalysis dataset from 1982 to 2015 in the arid and semi-arid transition zone of the Mongolian Plateau (ASTZMP). The results showed that the mean growing season NDVI increased from the central west to east, northeast, and southeast in ASTZMP. The vegetation greenness line migrated to the desert during 1982–1994, to the grassland during 1994–2005, and then to the desert during 2005–2015. Vegetation greenness was positively correlated with precipitation and negatively correlated with temperature. The latitudinal variation of the vegetation greenness line was mainly affected by the combination of precipitation and temperature, while the longitudinal variation was mainly affected by precipitation. In summary, precipitation was a key climatic factor driving rapid changes in vegetation greenness during the growing season of the transition zone. These results can provide meaningful information for research on vegetation coverage changes in arid and semi-arid regions.

Erannis jacobsoni Djak (Lepidoptera, Geometridae) is a leaf-feeding pest unique to Mongolia. Outbreaks of this pest can cause larch needles to shed slowly from the top until they die, leading to a serious imbalance in the forest ecosystem. In this work, to address the need for the low-cost, fast, and effective identification of this pest, we used field survey indicators and UAV images of larch forests in Binder, Khentii, Mongolia, a typical site of Erannis jacobsoni Djak pest outbreaks, as the base data, calculated relevant multispectral and red–green–blue (RGB) features, used a successive projections algorithm (SPA) to extract features that are sensitive to the level of pest damage, and constructed a recognition model of Erannis jacobsoni Djak pest damage by combining patterns in the RGB vegetation indices and texture features (RGB_VI&TF) with the help of random forest (RF) and convolutional neural network (CNN) algorithms. The results were compared and evaluated with multispectral vegetation indices (MS_VI) to explore the potential of UAV RGB images in identifying needle pests. The results show that the sensitive features extracted based on SPA can adequately capture the changes in the forest appearance parameters such as the leaf loss rate and the colour of the larch canopy under pest damage conditions and can be used as effective input variables for the model. The RGB_VI&TF-RF₄₄₀ and RGB_VI&TF-CNN₇₄₀ models have the best performance, with their overall accuracy reaching more than 85%, which is a significant improvement compared with that of the RGB_VI model, and their accuracy is similar to that of the MS_VI model. This low-cost and high-efficiency method can excel in the identification of Erannis jacobsoni Djak-infested regions in small areas and can provide an important experimental theoretical basis for subsequent large-scale forest pest monitoring with a high spatiotemporal resolution.

To improve how extreme events and climate variations are managed, there is a need to foster a deeper understanding of their interconnections. Consistent with this objective, this paper describes how precipitation extremes change both temporally and spatially in the Inner Mongolian Plateau (IMP), China and explains their causal factors. The paper refers to data collected from 43 meteorological stations in IMP and describes how precipitation extremes formed and how they influence agriculture. Data gathered and presented in this paper may be useful in understanding the extent to which the IMP is being influenced by global environmental change. This study reveals that the eleven precipitation extremes indices, except the number of precipitation days with over 0.5 mm (R0.5), number of heavy precipitation days (R10), and total precipitation in wet days (PRCPTOT), decreased in the IMP between 1959 and 2014, and most of them were non-significant in temporal. But the dry index has a larger magnitude decreasing trend than that of the wet indices, which can indicate that the dry situation was alleviated in IMP during the study interval. This study also indicated that precipitation extremes have strong relationships with elevation, latitude, and longitude. Atmospheric circulation and topography may be further primary reasons which result in the spatial variation characteristics in precipitation extremes over the IMP. Decreases in precipitation extremes, together with human activities such as livestock improvement and ecological restoration programs, has a positive effect in gross output value of agriculture and animal husbandry in the IMP. The results contribute to a deeper insight on the possible impacts of precipitation extremes and support the development of appropriate adaptation and mitigation strategies to cope with climate extremes. This paper further proposes science-based policies for grassland protection, agriculture, and animal husbandry on the national or regional and herdsman scales.

Water use efficiency (WUE) reflects the balance between carbon assimilation and water consumption in terrestrial ecosystems. Considering the fragile conditions of global water resources, the evaluation of regional WUE variation characteristics and response mechanisms is critical for promoting sustainable ecological development and water resource utilization. Based on gross primary productivity (GPP) and evapotranspiration (ET) datasets, combined with vegetation and meteorological data, this study examined the spatiotemporal variations, annual variation contribution rate, and driving mechanism of WUE in Inner Mongolia from 2001 to 2020. The main results are as follows: (1) The interannual and spatial variations of GPP, ET, and WUE all exhibited increasing trends, with WUE increasing in approximately 70% of the region and significantly increasing in 22.35% of pixels exhibiting a significant increase. Areas with the most significant increases were located in the Horqin sandy land and Mu Us sandy land. (2) The highest WUE values were observed in the summer season, followed by autumn and winter, and the lowest in spring. (3) Among all vegetation types, the typical steppe ecosystems contributed most to the interannual variability (IAV) of GPP, ET, and WUE, with values of 169.89%, 141.09%, and 193.42%, respectively. While the coniferous forest contributed least or negatively to GPP, ET, and WUE IAV, with values of −36.28%, 28.20%, and −32.86%, respectively. (4) The primary driver of WUE variation was found to be GPP, which contributed 59.36%, mainly in the central and western regions. The remaining 40.64% was attributable to ET, concentrated in the northeast region. (5) Human activities significantly affected WUE, with a contribution (about 53.52%) larger than that of climate change (nearly 46.48%). Increased precipitation improves vegetation WUE and is the most important climate factor influencing WUE variations. These findings will aid the formulation of vegetation protection and water resource management strategies in water-stressed areas.

Water is a crucial resource for agricultural development in the Yellow River Basin. However, the effects of water shortages on the region’s agricultural development are becoming increasingly evident, creating a need to examine the relationship between agricultural water use (AWU) and the agricultural economy. This study uses panel vector autoregression to analyze the relationship between AWU and the agricultural economy in the Inner Mongolia section of the Yellow River Basin from 1998 to 2018. The results indicate the following: (1) AWU in the Inner Mongolia section of the Yellow River Basin significantly declined during the study period, showing clear differences in the AWU’s effectiveness among regions; (2) agriculture in the region stabilized after significant growth, and the share of primary-sector industries in the national economy also stabilized after significant decline; (3) in the long run, AWU and the agricultural economy become cointegrated with the AWU Granger-causing agricultural economy. By deepening our understanding of agricultural water demand in the Yellow River Basin, these findings provide theoretical justification for establishing water-conserving irrigation systems and making sustainable use of water resources.