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Leptocybe invasa is a globally invasive pest of eucalyptus plantations, and is steadily spread throughout China. Predicting the growth area of L. invasa in China is beneficial to the establishment of early monitoring, forecasting, and prevention of this pest. Based on 194 valid data points and 21 environmental factors of L. invasa in China, this study simulated the potential distribution area of L. invasa in China under three current and future climate scenarios (SSPs1–2.5, SSPs2–3.5, and SSPs5–8.5) via the MaxEnt model. The study used the species distribution model (SDM) toolbox in ArcGIS software to analyze the potential distribution range and change of L. invasa. The importance of crucial climate factors was evaluated by total contribution rate, knife-cut method, and environmental variable response curve, and the area under the receiver operating characteristic (ROC) curve was used to test and evaluate the accuracy of the model. The results showed that the simulation effect of the MaxEnt model is excellent (area under the ROC curve (AUC) = 0.982). The prediction showed that L. invasa is mainly distributed in Guangxi, Guangdong, Hainan, and surrounding provinces, which is consistent with the current actual distribution range. The distribution area of the potential high fitness zone of L. invasa in the next three scenarios increases by between 37.37% and 95.20% compared with the current distribution. Climate change affects the distribution of L. invasa, with the annual average temperature, the lowest temperature of the coldest month, the average temperature of the driest season, the average temperature of the coldest month, and the precipitation in the wettest season the most important. In the future, the core areas of the potential distribution of L. invasa in China will be located in Yunnan, Guangxi, Guangdong, and Hainan. They tend to spread to high latitudes (Hubei, Anhui, Zhejiang, Jiangsu, and other regions).

Understanding the historical dynamics of animal species is critical for accurate prediction of their response to climate changes. During the late Quaternary period, Southeast Asia had a larger land area than today due to lower sea levels, and its terrestrial landscape was covered by extensive forests and savanna. To date, however, the distribution fluctuation of vegetation and its impacts on genetic structure and demographic history of local animals during the Last Glacial Maximum (LGM) are still disputed. In addition, the responses of animal species on Hainan Island, located in northern Southeast Asia, to climate changes during the LGM are poorly understood. Here, we combined phylogeographic analysis, paleoclimatic evidence, and species distribution models to examine the response of the flightless Hainan Partridge (Arborophila ardens) to climate change. We concluded that A. ardens survived through LGM climate changes, and its current distribution on Hainan Island was its in situ refuge. Range model results indicated that A. ardens once covered a much larger area than its current distribution. Demographic history described a relatively stable pattern during and following the LGM. In addition, weak population genetic structure suggests a role in promoting gene flow between populations with climate-induced elevation shifts. Human activities must be considered in conservation planning due to their impact on fragmented habitats. These first combined data for Hainan Partridge demonstrate the value of paired genetic and SDMs study. More related works that might deepen our understanding of the responses of the species in Southeast Asia to late Quaternary Climate are needed.

Water shortages have always been the primary bottleneck for the healthy and sustainable development of the ecological environment on the Loess Plateau (LP). Proper water resource management requires knowledge of the spatiotemporal characteristics of precipitation frequency. This paper employed the gridded precipitation dataset obtained from the China Meteorological Data Service Centre to present a spatially explicit characterization of precipitation frequencies in tandem with their return periods on the LP based on the L-moment method. The 60% and 80% of the mean annual precipitation from 1981 to 2010 were synonymous with severe and moderate droughts, respectively. Droughts occurred more frequently in the northwest than in the southeast of the LP. Moreover, the frequencies of moderate drought showed a slight difference throughout the area, while those of severe droughts demonstrated considerable differences between the northwestern arid zone and the southeastern semi-humid zone. The maps associated with various return periods of precipitation deficits can be used to produce drought risk maps together with drought vulnerability maps. These findings could also provide useful information for drought management, water resource management and the development of food security policies.

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It is of great interest to elucidate the biogeographic patterns of soil microorganisms and their driving forces, which are fundamental to predicting alterations in microbial‐mediated functions arising from environmental changes. Although the vertical movement of dissolved organic matter (DOM) drives the cycle of nutrients such as soil carbon, in the restored ecosystem, the relationship between DOM and soil microbial nutrient utilization remains to be determined. Here, we investigated the changes of soil microbial community at 0–40 cm depth profile in three stages (10, 30, 50 years) of succession in Larix olgensis plantations and the fluorescence spectrum composition of DOM. With the increase of soil depth, the signal source of microorganisms increases. In a coniferous forest soil environment, the possible main source of DOM in deep soil is the production of microbial metabolism. Difficulty in the decomposition of organic matter determines the distribution and composition of microorganisms. Increasing forest age makes bacteria and fungi more specific and bacterial‐fungal associations greater. Overall, our work contributes to the understanding of factors underlying microbial community distribution in plantation forests and the importance of DOM quality in the building microbial community.

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