Shanxi Province holds an important strategic position in the overall ecological pattern of the Yellow River Basin. To investigate the changes of the ecological environment in the Shanxi section of the Yellow River Basin from 2000 to 2020, we selected MODIS remote sensing image data to determine the remote sensing ecological index (RSEI) based on the principal component analysis of greenness, humidity, dryness, and heat. Then, we analyzed the spatial and temporal variations of ecological quality in this region to explore the influencing factors. We further used the CA-Markov model to simulate and predict the ecological environment under different development scenarios in the Shanxi section of the Yellow River Basin in 2030. The results showed that RSEI had good applicability in the Shanxi section of the Yellow River Basin which could be used to monitor and evaluate the spatiotemporal variations in its ecological environment. From 2000 to 2020, the Shanxi section of the Yellow River Basin was dominated by low quality habitat areas, in which the ecological environment quality continued to improve from 2000 to 2010 and decreased from 2010 to 2020. The high quality habitat areas mainly located on the mountainous areas with superior natural conditions and rich biodiversity, while the low ecological quality areas were mainly in the Taiyuan Basin and the northern part of the study area, where the mining industry developed well. Climate factors were negatively correlated with ecological environment quality in the northern and central parts of the study area, and positively correlated with that in the mountainous area. Under all three development scenarios, the area of cultivated land, forest, water and construction land increased in 2030 compared to that in 2020. Compared to the natural development scenario and the cultivated land protection scenario, the ecological constraint scenario with RSEI as the limiting factor had the highest area of new forest and the lowest expansion rate of cultivated land and construction land. The results would provide a reference for land space planning and ecological environment protection in the Shanxi section of the Yellow River Basin.
山西省在黄河流域总体生态格局中具有重要的战略地位。为深入研究2000—2020年黄河流域山西段生态环境的变化,选用MODIS遥感影像数据,基于绿度、湿度、干度和热度的主成分分析确定遥感生态指数(RSEI),对该区域生态环境质量的时空变化进行分析并探讨影响因素;同时,利用CA-Markov模型对2030年黄河流域山西段不同发展情景下生态环境进行模拟和预测。结果表明: RSEI在黄河流域山西段具有较好的适用性,可用于监测和评估其生态环境的时空变化特征。2000—2020年,黄河流域山西段以低生境质量区为主,其中,2000—2010年生态环境质量持续改善,而2010—2020年则有所退化;高生境质量区集中于山区,其自然条件优越、生物多样性丰富,低生态质量区主要分布在城市群集中的太原盆地及研究区北部采矿业发达的地区;在研究区的北部和中部,气候因子与生态环境质量呈负相关关系,而在高山区域二者呈正相关关系。3种发展情景下,2030年研究区的耕地、林地、水体和建设用地面积均较2020年有所增加;相较于自然发展情景和耕地保护情景,在以RSEI为限制因子的生态约束情景中,新增林地面积最多,而耕地和建设用地的扩张速率最低。研究结果可为黄河流域山西段的国土空间规划及生态环境保护提供参考。.

The radial growth of trees plays a crucial role in determining forest carbon sequestration capacity. Understanding the growth dynamics of trees and their response to environmental factors is essential for predicting forest\'s carbon sink potential under future climate change. Coniferous forest trees are particularly sensitive to climate change, with growth dynamics responding rapidly to environmental shifts. We collected and analyzed data from 99 papers published between 1975 and 2023, and examined the effects of exogenous factors (such as temperature, water, and photoperiod) and endogenous factors (including tree age and species) on cambial activity and radial growth in conifers. We further explored the mechanisms underlying these effects. The results showed that climate warming had the potential to advance the onset while delayed the end of xylem differentiation stages in conifers in temperate and boreal regions. Water availability played a crucial role in regulating the timing of cambial phenology and wood formation by influencing water potential and cell turgor. Additionally, the photoperiod not only participated in regulating the start and end times of growth, but also influenced the timing of maximum growth rate occurrence. Future climate warming was expected to extend the growing season, leading to increase in growth of conifers in boreal regions and expanding forests to higher altitudes or latitudes. However, changes in precipitation patterns and increased evapotranspiration resulting from temperature increases might advance the end of growing season and reduce growth rate in arid areas. To gain a more comprehensive understanding of the relationship between radial growth and climatic factors, it is necessary to develop process-based models to elucidate the physiological mechanisms underlying wood formation and the response of trees to climatic factors.
树木径向生长是森林固碳的主要方式,明确树木生长动态及其与环境要素的响应关系对于预测气候变化背景下森林固碳能力具有重要意义。针叶树生长对气候变化非常敏感,其生长动态能够快速响应气候变化。本文收集了1975—2023年的99篇文献,评述了外源因素(温度、水分和光周期)和内在因素(树龄、树种)对针叶树形成层活动和径向生长的影响及其机制。结果表明:气候变暖可能会导致温带和北方针叶树木质部分化的各阶段开始时间提前,生长停止时间推迟;水分条件参与调控形成层活动的开始并通过影响水势和细胞膨压进而调节树木生长;光周期除了可以参与调节生长开始、结束时间外,也对最大生长速率发生时间产生重要影响。未来气候变暖可能会使北方针叶树生长季延长、生长量增加,并使森林向更高海拔或高纬度地区迁移。同时,未来降水格局改变以及温度升高导致的蒸散发加剧可能会使干旱区树木生长季提前结束,生长速率下降。在未来研究中,还需进一步开发树木生长过程模型,量化径向生长与气候要素的关系,以便进一步明确树木生长对气候要素响应的生理机制。.

The natural abundance of stable carbon and nitrogen isotopes (δ13C and δ15N) in leaves can provide comprehensive information on the physiological and ecological processes of plants and has been widely used in ecological research. However, recent studies on leaf δ13C and δ15N have focused mainly on woody species, few studies have been conducted on herbs in different vegetation types, and their differences and driving factors are still unclear. In this study, we focused on the herbs in subalpine coniferous forests, alpine shrublands, and alpine mea-dows on the eastern Qinghai-Tibet Plateau, and investigated the differences in leaf δ13C and δ15N of herbs and the driving factors. The results showed that there were significant differences in leaf δ13C and δ15N values of herbs among different vegetation types, with the highest δ13C and δ15N values in alpine meadows, followed by alpine shrublands, and the lowest in subalpine coniferous forests. Using variation partitioning analysis, we revealed that differences in leaf δ13C and δ15N of herbs among various vegetation types were driven by both leaf functional traits and climate factors, with the contribution of leaf functional traits being relatively higher than that of climate factors. Hierarchical partitioning results indicated that mean annual temperature (MAT), chlorophyll content index, leaf nitrogen content per unit area (Narea), and leaf mass per area were the main drivers of leaf δ13C variations of herbs across different vegetation types, while the relative importance of Narea and MAT for variation in leaf δ15N of herbs was much higher than those other variables. There was a strong coupling relationship between leaf δ13C and δ15N as indicated by the result of the ordinary least squares regression. Our findings could provide new insights into understanding the key drivers of leaf δ13C and δ15N variations in herbs across different vegetation types.
植物叶片碳氮稳定同位素自然丰度(δ13C和δ15N)可以提供植物生理生态过程的综合信息,已广泛应用于生态学研究。然而,目前对叶片δ13C和δ15N的研究主要集中于木本植物,对不同植被类型下草本植物叶片δ13C和δ15N的研究相对较少,其碳氮稳定同位素差异和驱动因素尚不明确。本研究以青藏高原东缘亚高山针叶林、高山灌丛和高山草甸中草本植物叶片为对象,研究了不同植被类型下草本植物叶片δ13C和δ15N的差异及其驱动因素。结果表明: 不同植被类型下草本植物叶片δ13C和δ15N值存在显著差异,高山草甸中草本植物叶片δ13C和δ15N值最高,高山灌丛次之,亚高山针叶林最低。方差分解发现,不同植被类型下草本植物叶片δ13C和δ15N的差异是由叶片功能性状和气候因子共同驱动的,其中叶片功能性状的相对贡献超过了气候因子。层次分割法分解广义混合效应模型发现,年均温度(MAT)、叶绿素指数、单位面积叶片氮含量(Narea)和比叶重是不同植被类型下草本植物叶片δ13C差异的主要驱动因素,而Narea和MAT对不同植被类型下草本植物叶片δ15N变异的相对重要性远高于其他变量。此外,使用最小二乘回归分析发现,不同植被类型下草本植物叶片δ13C与δ15N之间存在强烈耦合关系。本研究结果为理解不同植被类型下草本植物叶片δ13C和δ15N差异的关键驱动因素提供了新的见解。.

Forest fires are sudden, destructive, hazardous, and challenging to manage and rescue, earning them a place on UNESCO\'s list of the world\'s eight major natural disasters. Currently, amid global warming, all countries worldwide have entered a period of high forest fire incidence. Due to global warming, the frequency of forest fires has accelerated, the likelihood of large fires has increased, and the spatial and temporal dynamics of forest fires have shown different trends. Therefore, the impact of climate change on the spatiotemporal dynamics of forest fires has become a hot issue in the field of forest fire research in recent years. Therefore, it is of great significance and necessity to conduct a review of the research in this area. This review delves into the interactions and impacts between climate change and the spatiotemporal dynamics of forest fires. To address this issue, scholars have mainly adopted the following research methods: first, statistical analysis methods, second, the establishment of spatiotemporal prediction models for meteorology and forest fires, and third, the coupling of climate models with forest fire risk forecasting models. The statistical analysis method relies on the analysis of historical meteorological and fire-related data to study the effects of climate change and meteorological factors on fire occurrence. Meanwhile, forest fire prediction models utilize technical tools such as remote sensing. These models synthesize historical meteorological and fire-related data, incorporating key meteorological factors such as temperature, rainfall, relative humidity, and wind. The models revealed the spatial and temporal distribution patterns of fires, identified key drivers, and explored the interactions between climate change and forest fire dynamics, culminating in the construction of predictive models. With the deepening of the study, the coupling of climate models and fire risk ranking systems became a trend in the prediction of forest fire risk trends. Moreover, as the climate warms, the increased frequency of extreme weather events like heatwaves, droughts, snow and ice storms, and El Niño-Southern Oscillation (ENSO) has accelerated forest fire occurrences and raised the risk of major fires. This review offers valuable technical insights by comprehensively analyzing the spatial and temporal characteristics of forest fires, elucidating key meteorological drivers, and exploring potential mechanisms. These insights serve as a scientific foundation for preventive measures and effective forest fire management. In the face of a changing climate, this synthesis contributes to the development of informed strategies to mitigate the escalating threat of forest fires.

The Huangshui River, a vital tributary in the upper reaches of the Yellow River within the eastern Qinghai-Tibet Plateau, is home to the endemic black fly species S. qinghaiense. In this study, we conducted a systematic survey of the distribution of the species in the Huangshui River basin, revealing its predominant presence along the river\'s main stem. Based on four ecological niche models-MaxEnt with parameter optimization; GARP; BIOCLIM; and DOMAIN-we conduct a comparative analysis; evaluating the accuracy of AUC and Kappa values. Our findings indicate that optimizing parameters significantly improves the MaxEnt model\'s predictive accuracy by reducing complexity and overfitting. Furthermore, all four models exhibit higher accuracy compared to a random model, with MaxEnt demonstrating the highest AUC and Kappa values (0.9756 and 0.8118, respectively), showcasing significant superiority over the other models (p < 0.05). Evaluation of predictions from the four models elucidates that potential areas of S. qinghaiense in the Huangshui River basin are primarily concentrated in the central and southern areas, with precipitation exerting a predominant influence. Building upon these results, we utilized the MaxEnt model to forecast changes in suitable areas and distribution centers during the Last Interglacial (LIG), Mid-Holocene (MH), and future periods under three climate scenarios. The results indicate significantly smaller suitable areas during LIG and MH compared to the present, with the center of distribution shifting southeastward from the Qilian Mountains to the central part of the basin. In the future, suitable areas under different climate scenarios are expected to contract, with the center of distribution shifting southeastward. These findings provide important theoretical references for monitoring, early warning, and control measures for S. qinghaiense in the region, contributing to ecological health assessment.

The big-headed ant, Pheidole megacephala (Fabricius), has a widespread distribution across numerous regions globally. The International Union for Conservation of Nature (IUCN) has identified it as one of the 100 worst invasive alien species worldwide, given the severe ecological and economic harm it causes in invaded areas. In this study, we predicted the present and future global distribution of P. megacephala, taking into account known distribution points and bioclimatic factors. Our results indicated that temperature is the primary factor affecting the distribution of P. megacephala, with potential suitable areas currently found mainly in South America, Southern North America, Western Europe, Coastal areas of the Mediterranean and Red Seas, Southern Africa, Southern Asia, Islands in Southeast Asia, and coastal regions of Australia. The total suitable area spans 3,352.48 × 104 km2. In China, the potential suitable area for P. megacephala is 109.02 × 104 km2, representing 11.36% of China\'s land area. In the future, based on different climatic conditions, the suitable area of P. megacephala generally showed a declining trend, but some newly added suitable areas showed that it had a tendency to expand to higher latitudes. Relevant agencies should implement effective measures to control P. megacephala populations to mitigate damage in invaded areas and slow down or prevent the spread of big-headed ants into noninvaded regions.

We analyzed the variation patterns of growth and wood properties of 24 different provenances of 18-year-old Schima superba in Jian\'ou, Fujian Province. A total of 11 growth and wood indices were measured, including tree height, diameter at breast height, wood basic density and anatomical structure. We analyzed the geographical variation patterns of growth and wood properties, and the provenance areas were divided. Further, the excellent timber provenances were selected according to different uses. The results showed that the variation of growth traits, which was 17.6%-27.3% with mean value of 22.4%, was larger than that of wood properties (7.0%-21.0%, mean 12.7%). Growth properties and some wood properties (fiber length, fiber lumen diameter and fiber cell wall thickness) had significant differences among provenances. Growth traits were not correlated with fiber traits, and they could be selected independently without emphasis on other traits. There was significant correlation between the longitudinal and radial growth indicators of wood properties, but they were not correlated with the wood basic density, which could be selected independently. In addition, the growth and wood properties were significantly influenced by temperature and precipitation, which showed a latitudinal variation pattern. According to Q-type clustering analysis, 24 provenances could be divided into four categories, of which southern provenances from distribution area of S. superba had vigorous growth and supper wood properties. They had smaller microfibril angle, higher maturity, longer fiber length, and thicker fiber cell wall. Finally, five excellent provenances were selected according to pulpwood and building use.
本研究以福建建瓯18年生24个木荷种源为材料,分析树高、胸径、木材基本密度以及木纤维解剖结构等11个生长和材性性状的种源变异规律及与地理气候因子间的相关性,通过聚类分析进行种源区划分,揭示木荷生长和材性的地理变异模式,根据不同用途,筛选优良用材种源。结果表明: 木荷生长性状变异较大(17.6%～27.3%,平均22.4%),材性性状变异相对较小(7.0%～21.0%,平均12.7%),生长性状和部分材性性状(纤维长、腔径和双壁厚等)在种源间具有显著差异。相关分析表明,生长性状与材性性状不相关,两者相对独立,可单独对某一性状进行选择与改良。木纤维纵向生长指标以及径向生长指标之间呈显著相关,但其与木材基本密度均不相关,两者可独立选择;木荷生长与材性性状受温度影响显著,同时亦受降水影响,呈纬向变异模式。根据Q型聚类分析,将24个种源分为4类,其中,木荷分布区南部种源的木纤维微纤丝角较小,成熟度较高,纤维较长,细胞壁较厚,材性相对较好。根据造纸和建筑家居等不同用材用途,选出5个优良种源。.

Climate and human activities are the basic driving forces that control and influence the spatial distribution and change of vegetation. Using trend analysis, the Hurst index, correlation analysis, the Moran index, path analysis, residual analysis, and other methods, the effects of human activities and climate factors on vegetation change were analyzed. The results show that: (1) The research area\'s normalized difference vegetation index (NDVI) exhibited a substantial upward trend from 2001 to 2020, increasing at a rate of 0.003/a, and the vegetation cover was generally healthy. The generally constant NDVI region made up 78.45% of the entire area, and the grassland, cultivated land, and forest land showed the most visible NDVI aggregation features. (2) The Vegetation is mainly promoted by water and heat, particularly precipitation, have a major impact on plants, with the direct influence of precipitation on vegetation growth being much greater than the indirect effect through the temperature. (3) The trend of NDVI residuals showed obvious spatial variability, presenting a distribution characteristic of high in the south and low in the north. The results of this study can provide a basis for the scientific layout of ecological protection and restoration projects in the Yinshanbeilu area.

BACKGROUND: Environmental factors difference is the key factor for the difference in the production, transformation and accumulation of effective components in plants. UPLC-MS/MS and multivariate statistical methods were applied to describe the region difference of amides compounds in Chinese prickly ash peels from different regions and their correlation with climatic factors and soil factors.
RESULTS: Amides compounds contents were significantly higher in high altitude areas, with obvious altitude change trend. Two ecotypes were classified based on the amides compounds contents, one was the high altitude-cool type from Qinghai, Gansu, Sichuan and western Shaanxi province, and the other one was low altitude-warm type from eastern Shaanxi, Shanxi, Henan, Hebei and Shandong province. Amides compounds content were negatively correlated with annual mean temperature, max temperature of warmest month, mean temperature of wettest quarter and mean temperature of warmest quarter (P < 0.01). Except for hydroxy-γ-sanshool and ZP-amide A, the residual amides contents were significantly positively correlated with organic carbon, available nitrogen, phosphorus and potassium in soil and negatively correlated with soil bulk density. Low temperature, low precipitation and high organic carbon in soil were conducive to amides accumulation.
CONCLUSIONS: This study aided in site specific exploration of high amides contents yielding samples, enriched the environment factors effects on amides compounds, and provided scientific foundation for the improvement of Chinese prickly ash peels quality and the location of high-quality production areas.

The near-surface lapse rate reflects the atmospheric stability above the surface. Lapse rates calculated from land surface temperature (γTs) and near-surface air temperature (γTa) have been widely used. However, γTs and γTa have different sensitivity to local surface energy balance and large-scale energy transport and therefore they may have diverse spatial and temporal variability, which has not been clearly illustrated in existing studies. In this study, we calculated and compared γTa and γTs at ~ 2200 stations over China from 1961 to 2014. This study finds that γTa and γTs have a similar multiyear national average (0.53 °C/100 m) and seasonal cycle. Nevertheless, γTs shows steeper multiyear average than γTa at high latitudes, and γTs in summer is steeper than γTa, especially in Northwest China. The North China shows the shallowest γTa and γTs, then inhibiting the vertical diffusion of air pollutants and further reducing the lapse rates due to accumulation of pollutants. Moreover, the long-term trend signs for γTa and γTs are opposite in northern China. However, the trends in γTa and γTs are both negative in Southwest China and positive in Southeast China. Surface incident solar radiation, surface downward longwave radiation and precipitant frequency jointly can account for 80% and 75% of the long-term trends in γTa and γTs in China, respectively, which provides an explanation of trends of γTa and γTs from perspective of surface energy balance.