Pinus densiflora is an important evergreen coniferous species with both economic and ecological value. It is an endemic species in East Asia. Global climate warming greatly interferes with species survival. This study explored the impact of climate change on the distribution of this species and the relationship between its geographical distribution and climate demand, so as to provide a theoretical basis for the protection of P. densiflora under the background of global warming. This research used 565 valid data points and 19 typical climatic environmental factors distributed in China, Japan, and South Korea. The potential distribution area of P. densiflora in East Asia under the last glacial maximum (LGM), mid-Holocene, the current situation and two scenarios (RCP 2.6 and RCP 8.5) in the future (2050s and 2070s) was simulated by the MaxEnt model. The species distribution model toolbox in ArcGIS software was used to analyze the potential distribution range and change of P. densiflora. The contribution rates, jackknife test and environmental variable response curves were used to assess the importance of key climate factors. The area under the receiver-operating characteristic curve (AUC) was used to evaluate model accuracy. The MaxEnt model had an excellent simulation effect (AUC = 0.982). The forecast showed that the Korean Peninsula and Japan were highly suitable areas for P. densiflora, and the area had little change. Moreover, during the LGM, there was no large-scale retreat to the south, and it was likely to survive in situ in mountain shelters. The results suggested that Japan may be the origin of P. densiflora rather than the Shandong Peninsula of China. The distribution area of P. densiflora in the mid-Holocene and future scenarios was reduced compared with the current distribution, and the reduction of future distribution was greater, indicating that climate warming will have certain negative impacts on the distribution of P. densiflora in the future. The precipitation of the warmest quarter (Bio18), temperature seasonality (Bio4), mean annual temperature (Bio1) and mean temperature of the wettest quarter (Bio8) had the greatest impact on the distribution area of P. densiflora.

Inappropriate grazing management is one of the most common causes of grassland degradation, and thus, an assessment of soil properties under different grazing intensities is critical for understanding its effects on ecosystem nutrient cycling and for formulating appropriate management strategies. However, the responses of certain main elements, including soil carbon, nitrogen, and phosphorus, to grazing in alpine meadow ecosystems remain insufficiently clarified. Here, we measured carbon, nitrogen, and phosphorus contents in the topmost 30 cm of soil in an alpine meadow under three grazing intensities (light, moderate, and heavy) and found clear differences in soil physical and chemical properties among different grazing intensities and soil layers. As grazing intensity increased, soil water content, carbon and nitrogen contents and stocks, and carbon to phosphorus and nitrogen to phosphorus ratios decreased, whereas soil bulk density increased. However, soil phosphorus and carbon to nitrogen ratio remained stable. Our findings highlight the negative impacts of heavy grazing intensity, in terms of soil carbon and nitrogen loss and phosphorus mineralization. Moreover, we emphasize that further related studies are necessary to gain a more comprehensive understanding of the effects of grazing on grassland ecosystems, and thereby provide information for sustainable management practices and eco-compensation policies.

The eco-system in the Qinghai-Tibet Plateau (QTP) is extremely fragile, and highly vulnerable to climate change. Knowledge of the changes in the ecological conditions is vital to mitigate the impact of climate change. In this study, we investigated the trend of ecological conditions of the QTP using the remotely sensed ecological index (RSEI), which is the first PCA (principal component analysis) axis of the four indexes derived from the MODIS (Moderate resolution Imaging Spectroradiometer) images captured in the growing season of 2000–2020. The four indexes, i.e., NDVI (normalized difference vegetation index), heat (land surface temperature, LST), wetness (tasseled cap wetness index, WET) and dryness (normalized difference impervious surface index, NDBSI), were calculated on the Google Earth Engine platform. Using land use cover change (LUCC) data, long-term meteorological records and the supplementary annual livestock production, we explored the drivers of spatiotemporal changes in the RSEI. The results show the following points: (1) the ecological conditions of the QTP have remarkable spatiotemporal variations. There were two ecological degradation periods, one of them occurred in the central region during 2005–2010, mainly attributed to the rising temperatures and decreasing precipitation. The other occurred during 2015–2020, driven primarily by overgrazing in the southwest. From 2000 to 2005, it was a period of rapid ecological restoration in the ecologically fragile northeast region. (2) The contribution rate of pc1 was stable at 60%, while the contribution rate of pc2 remained below 40%, indicating that pc1 demonstrated most of the characteristics of the four indexes. The correlation coefficients between NDVI and WET with pc1 are both positive, while LST and NDBSI have negative correlation coefficients, i.e., negative effects. This is consistent with the actual situation. (3) Overgrazing caused grass degradation in the southwest area of the QTP, which might be the main reason for the poor ecological conditions (i.e., low RSEI value) during 2015–2020. (4) Temperature and precipitation showed an increasing trend during the study period. A warmer and wetter climate is expected to have profound impacts on the ecosystems in QTP and practices should be concentrated on identifying climate-sensitive ecosystem components and designating adaptative options.

Grassland afforestation dramatically affects the abiotic, biotic, and ecological function properties of the original ecosystems. Interference from afforestation might disrupt the stasis of soil physicochemical properties and the dynamic balance of microbiota. Some studies have suggested low sensitivity of soil properties and bacterial community to afforestation, but the apparent lack of a significant relationship is probably due to the confounding effects of the generalist habitat and rare bacterial communities. In this study, soil chemical and prokaryotic properties in a 30-year-old Mongolia pine (Pinus sylvestris var. mongolica Litv.) afforested region and adjacent grassland in Inner Mongolia were classified and quantified. Our results indicate that the high richness of rare microbes accounts for the alpha-diversity of the soil microbiome. Few OTUs of generalist (core bacteria) and habitat-specialist bacteria are present. However, the high abundance of this small number of OTUs governs the beta-diversity of the grassland and afforested land bacterial communities. Afforestation has changed the soil chemical properties, thus indirectly affecting the soil bacterial composition rather than richness. The contents of soil P, Ca²⁺, and Fe³⁺ account for differentially abundant OTUs such as Planctomycetes and subsequent changes in the ecologically functional potential of soil bacterial communities due to grassland afforestation. We conclude that grassland afforestation has changed the chemical properties and composition of the soil and ecological functions of the soil bacterial community and that these effects of afforestation on the microbiome have been modulated by changes in soil chemical properties.

Understanding the intricate relationships among ecosystem services (ESs) and clarifying their driving factors are essential prerequisites for establishing effective ecosystem management strategies. Therefore, we plotted the spatial-temporal distribution of five ESs in the Beijing-Tianjin-Hebei (BTH) urban agglomeration and analyzed their interactions in terms of trade-offs, synergies, and bundles. We identified the primary drivers impacting ESs and proposed recommendations for urban spatial management and planning. The result revealed that (1) between 2000 and 2020, the supply of soil conservation increased the most, by 52.56%, and habitat quality decreased the most, by 6.92%; (2) four ES pairs were synergies and six ES pairs exhibited trade-offs, with three ES pairs showing decreased synergies and two ES pairs showing increased trade-offs; (3) the main factors influencing the driving forces of ESs were precipitation, cropland area ratio, and forest area ratio; and (4) the spatial-temporal analysis of ES interactions determined that ESs exhibiting decreasing synergies should be prioritized in ecosystem management, suggesting that the spatial planning of ecosystems should be based on ES bundles. Thus, this study provides guidance for regional ecosystem spatial planning and management.

It is of great significance to accurately assess the carbon sink capacity and trend of forest ecosystems on a regional scale, which is a key step to realizing sustainable forest management and carbon sink. Based on several remote sensing datasets, this study analyzes the dynamic characteristics of forest carbon stock in the Yangtze River Basin and its response to environmental factors using the Mann–Kendall nonparametric test, correlation analysis, and BP neural network during 2005–2020. The results show that forest carbon stock in the Yangtze River Basin shows a fluctuating upward trend, with an average annual growth rate of 0.91%. Forest carbon stock in western high-altitude areas and areas with high human activity in the east showed a downward trend, while the central plains showed a stable growth trend. In the vast plains of the Yangtze River Basin, a suitable drought degree (−0.5 < SPEI < 0.5) is helpful to the accumulation of forest carbon reserves. In the future, rich forest resources should be fully developed to promote synergy between environmental protection and economic development from the perspective of developing green carbon trading, such as the carbon-sink forestry projects of CCER.