蒙古栎地理分布的主导气候因子及其阈值

Drought characteristics and dominant factors across China: Insights from high-resolution daily SPEI dataset between 1979 and 2018

The climatic suitability for maize cultivation in China

Starting from the national scale and annual level, the potential climate factors are interpolated into 10 km×10 km grid data based on the daily data set of 1903 weather stations from 1961 to 2019 across the country, and a tea plant distribution dataset consisting 1115 records is established. Using the maximum entropy model and GIS technology, the dominant climatic factors affecting tea plant in mainland China are screened according to the contribution percentage and Jackknife method, and the climatic suitability zoning of tea plant is divided into 4 grades: Unsuitable, sub-suitable, suitable and optimum, using the natural break point classification method. The threshold values of dominant climate factors for different division levels are determined and the climate characteristics of tea suitable zones are analyzed. The result shows that the maximum entropy model constructed based on the dominant affecting climatic factors is suitable for climatic suitability zoning of tea plant. The dominant climatic factors affecting the distribution of tea plant are averaged extreme minimum temperature, the frequency of spring frost, annual mean temperature, annual precipitation, and averaged relative humidity from March to September. The zoning results by the model are in good agreement with the distribution of famous tea towns and the location of geographical symbol tea. The changes of areas suitable for tea plant in different periods are also studied, and it shows that the north boundary of the tea plant suitable area for the six decadal periods from 1961 to 2019 is roughly the same, and all regions show a decreasing distribution trend from high latitudes in the east to low latitudes in the west. The areas where the northern boundary moves obviously are mainly in the high-latitude provinces in the east. The decadal variation of the centroid of the overall tea plant suitable area is relatively slight: The suitable areas expand northwards gradually except for the 1960s-1970s and the 1980s-1990s. These results provide a scientific basis for rational planning of tea planting layout and scientific development of tea industry. The zoning method adequately considers climatic conditions of the study area under natural conditions. However, other factors such as land use types, soil conditions, and tea varieties are not fully considered, and the interpolation method does not consider the influence of altitude on meteorological elements, which makes the result of area optimum for tea planting larger than reality.

Climate variability and climate extremes are important climatic determinants of plant growth, species distribution and net primary productivity. A comprehensively quantitative analysis of the sensitivity and resilience of ecosystems to climate variability is vital to identify which regions and species are most in danger in response to future climate change. Here, we proposed an empirical approach to assess the relative sensitivity and resilience of ecosystems to short‐term climate variability in the Heihe River Basin (HRB) which is the second largest inland river basin in the northern China and contains ecosystems of semi‐arid, arid and hyper‐arid types. Based on the monthly time series of normalized difference vegetation index (NDVI), land surface temperatures (LST) and the ratio of actual evapotranspiration to potential evapotranspiration (AET/PET) derived from MODIS sensor from 2000 to 2013, we developed a multiple linear regressive and autoregressive model to determine the sensitivity of NDVI anomalies to climate variability indicated by monthly LST anomalies (temperature variability) and monthly AET/PET anomalies (water variability). We included 1 month time lag of NDVI anomalies in order to reflect ecosystem resilience. We found that the sensitivity and resilience to climate variability were different in the upper, middle and lower reaches of the HRB. Temperature variability dominantly controlled vegetation anomalies in the upper reach, but water variability was the dominant climatic factor in the middle and lower reaches. The different responses of semi‐arid to hyper‐arid ecosystems to climate variability depended much on the distinct climatic conditions and diverse vegetation types. Ecosystems in drier condition tended to show higher sensitivity to water variability, and ecosystems with colder climate were likely to be more sensitive to temperature variability. The most sensitive vegetation type to water variability and temperature variability in the HRB was crop and meadow, respectively. Grass had been proved to have the lowest resilience. Our research on the sensitivity and resilience of semi‐arid to hyper‐arid ecosystems is helpful for formulating and implementing adaptation and mitigation strategies in response to climate change.

Leonurus japonicus Houtt. is a traditional Chinese medicinal plant with high medicinal and edible value. Wild L. japonicus resources have reduced dramatically in recent years. This study predicted the response of distribution range of L. japonicus to climate change in China, which provided scientific basis for the conservation and utilization. In this study, 489 occurrence points of L. japonicus were selected based on GIS technology and spThin package. The default parameters of MaxEnt model were adjusted by using ENMeva1 package of R environment, and the optimized MaxEnt model was used to analyze the distribution of L. japonicus. When the feature combination in the model parameters is hing and the regularization multiplier is 1.5, the MaxEnt model has a higher degree of optimization. With the AUC of 0.830, our model showed a good predictive performance. The results showed that L. japonicus were widely distributed in the current period. The maximum temperature of warmest month, the min temperature of coldest month, the precipitation of wettest month, the precipitation of driest month, and altitude were the main environmental factors affecting the distribution of L. japonicus. Under the three climate change scenarios, the suitable distribution area of L. japonicus will range shift to high latitudes, indicating that the distribution of L. japonicus has a strong response to climate change. The regional change rate is the lowest under the SSP126-2090s scenario and the highest under the SSP585-2090s scenario.

Fructus Aurantii (FA) is a valuable medicinal material used in traditional China medicine. Predicting the suitable distribution areas of FA and identifying its potential distribution patterns driven by various environmental factors are crucial for the selection of planting sites and maintenance of medicinal quality. Here, the maximum entropy model was used to predict the potential distribution of FA in Jiangxi Province, China under current and future climate conditions. A total of 105 geographical distribution data of FA were collected through field investigation and 32 environmental variables were obtained from public databases. The maximum entropy model showed high prediction accuracy when 16 environmental variables were selected (AUC = 0.932). The habitat suitability of FA was prominently affected by climate, which surpassed topography and soil factors. Maximum temperature of the warmest month, annual temperature range, precipitation of the wettest month, precipitation coefficient of variation, elevation, aspect, and soil organic carbon were the key factors shaping the geographic distribution of FA. Among them, maximum temperature of the warmest month (16.9%), followed by annual temperature range (16.1%), made the greatest contribution to model predictions. In the current climate background, the total potential suitable area for FA covered 6.30 × 104 km2 of garden land. Under future climate warming scenarios (shared socioeconomic pathways 245, 585), the potential suitable area was predicted to move southward and expand twice in 2040-2080, with notable increase in moderately and poorly suitable areas. Low hilly areas at higher elevations with moist cool conditions and gentle undulations would become more suitable for future introduction and planting of FA. Regionalized strategies for different suitable planting areas were proposed taking into account future climate change. All data are available in Mendeley Data (DOI: 10.17632/s9wsnn2xcn.1). Code is available at https://github.com/mrmaxent/Maxent.

PDF HTML阅读 XML下载 导出引用 引用提醒 气候变化情景下基于最大熵模型的青海云杉潜在分布格局模拟 DOI: 10.5846/stxb201809151999 作者: 作者单位: 甘肃农业大学林学院,兰州大学生命科学学院,甘肃农业大学林学院,甘肃农业大学林学院 作者简介: 通讯作者: 中图分类号: 基金项目: 甘肃农业大学科技创新基金-公招博士科研启动基金项目（GSAU-RCZX01707）；学科建设专项基金项目（GAU-XKJS-2018-099）；国家自然基金项目（31860197） Simulation of the potential distribution patterns of Picea crassifolia in climate change scenarios based on the maximum entropy (Maxent) model Author: Affiliation: Gansu Agricultural University, Lanzhou 730070 Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:青海云杉（Picea crassifolia）是我国青藏高原东北缘特有树种，在维系我国西北地区生态平衡、水土保持、水源涵养和生物多样性等方面发挥着重要作用。基于其分布范围内的69个地理分布样点，利用最大熵（Maxent）模型对现实气候条件下青海云杉的潜在分布及其分布的主导气候因子进行分析，同时结合3种大气环流模型模拟青海云杉在3种气候变化情景（温室气候排放量不同）下未来2050s和2080s潜在分布区的变化。结果表明：Maxent模型对青海云杉潜在分布区的预测具有极高的准确度，所有模型的平均受试者工作特征曲线下面积（AUC测试值）均高于0.99；Jackknife检验和气候因子响应曲线表明年最低降雨量是限制青海云杉分布的主导因子；当前青海云杉的潜在分布区主要集中于青海东部、甘肃东南部、宁夏大部分地区、西藏东部、四川西部山区以及陕西、新疆和内蒙古部分地区。在未来3种增温情景下，青海云杉在2050s和2080s的潜在分布总面积与当前相比变化不明显，但不同适生等级的潜在分布面积变化较大，其中，中度适生区和低度适生区受气候增温影响显著，中度增温下这些区域在2080s的面积明显增大，而高度适生区（核心分布）则在所有增温情景下均呈缩小趋势。同时，在未来3种增温情景下，青海云杉在2050s和2080s的潜在分布区有向北移动趋势，但其心分布区域（高度适生区）仍然以青海东部、甘肃北部为主，无明显变迁趋势。从气候因素角度考虑，本研究表明未来气候变化情景下，青海云杉依然在西部高山地区，特别是作为我国重要生态屏障的祁连山、贺兰山等山区具有重要的经济价值并将持续其生态服务功能。 Abstract:Qinghai spruce (Picea crassifolia) is the endemic tree species in the northeastern margin of the Qinghai-Tibet Plateau (QTP) in China. It plays an important role in maintaining ecological balance, biodiversity, and soil and water conservation in northwestern China. In this study, the current potential distribution of Qinghai spruce and its dominant climatic factors were analyzed firstly based on 69 distributional records via the maximum entropy model (Maxent). Then the distribution patterns of Qinghai spruce under three climate change scenarios (i.e., the lowest, a moderate, and the highest greenhouse gas emission scenarios; RCP2.6, RCP4.5 and RCP8.5) with three general atmospheric circulation models were predicted by Maxent for two future decades:the 2050s and 2080s. The results showed that the accuracy of the Maxent model was pretty high for modeling potential distribution regions of Qinghai spruce, and the average values of the area under the receiver operator characteristic curve (AUC) were higher than 0.99. The results from the Jackknife test and climate factor response curves revealed that the annual lowest precipitation is the key factor that limited the distribution of Qinghai spruce; the current potential distribution regions of Qinghai spruce are mainly concentrated in eastern Qinghai, southeastern Gansu, most of Ningxia, eastern Tibet, mountainous areas of western Sichuan, and parts of Shaanxi, Xinjiang, and Inner Mongolia. The total potential distribution area of Qinghai spruce in the 2050s and 2080s was changed little compared to the current distribution in all three scenarios, but its potential distribution area at different levels of fitness was changed a lot. Among them, the regions with fitness of less than 0.1 and in the range of 0.1-0.3 were significantly affected by the climate changes, and their area was largely increased in the medium emission scenario. In contrast, the regions with fitness in the range of 0.5-0.8 were shrunk in all scenarios. At the same time, the distribution patterns of Qinghai spruce in the 2050s and 2080s had a tendency to move northward in all scenarios, whereas its central distributional regions (more suitable regions) were still kept in eastern Qinghai and northern Gansu, with no obvious trend to change. From the perspective of climatic factors, this study showed that Qinghai spruce would continue to have important economic values and ecological service functions in the western mountains, especially in the Qilian Mountains and Helan Mountains, which are the important ecological barriers in China. 参考文献 相似文献 引证文献

Seasonally and spatially varied controls of climatic factors on net primary productivity in alpine grasslands on the Tibetan Plateau

Spatial-temporal variability pattern of multi-depth soil moisture jointly driven by climatic and human factors in China

The past climate change impact on some natural objects is usually studied using available observations or re-analysis data. To assess future climate changes, the only source of information is simulations of global or regional climate models. A particular application depends on the problem to be studied - if the natural object needs to be considered in more detail, then a smaller spatiotemporal grid step in a model must be used. The present study focuses on the methodology for selecting representative simulations from the EURO-CORDEX ensemble by RCP8.5 scenario and assessing near-future temperature and precipitation trends in Odesa, Ukraine. The approach is to minimize bias in average monthly temperature and precipitation. The 1970–2005 average bias by 76 simulations of the EURO-CORDEX ensemble is about +0.5÷+1.0 °C for the monthly temperature and about –25÷+10 mm for the monthly precipitation sum. The preferably positive bias for precipitation is registered from October to March and a negative one – from April to September with a minimum in July-August. Some models can show almost dry summer, which is not in fact. The procedure for selecting representative simulations involves choosing the minimum bias in the reference period 1970-2005 and adjusting the results obtained for the scenario simulation period 2006-2020. Minimizing the mean bias allowed the selection of the eight simulations that satisfactorily describe changes in temperature and precipitation over the period 1970-2020. These simulations were then used to assess the near-future climate in Odesa. The mean temperature in Odesa has increased by ~1 °C over the past 30 years. A significant trend towards an increase in the average annual temperature will continue in 2021-2050, and the temperature will also increase for all months. There exists only little probability of a negative average monthly temperature and only in January. Although the average annual precipitation sum will increase slightly (~ 20 mm), it will decrease significantly in summer and increase in spring and at the end of the year. In general, it seems that the climate of Odesa is moving towards the Mediterranean climate – warm to hot, dry summers and mild, moderately wet winters.

Elevated CO2 moderates the impact of climate change on future bamboo distribution in Madagascar

BackgroundCryptosporidiosis is a zoonotic intestinal infectious disease caused by Cryptosporidium spp., and its transmission is highly influenced by climate factors. In the present study, the potential spatial distribution of Cryptosporidium in China was predicted based on ecological niche models for cryptosporidiosis epidemic risk warning and prevention and control.MethodsThe applicability of existing Cryptosporidium presence points in ENM analysis was investigated based on data from monitoring sites in 2011–2019. Cryptosporidium occurrence data for China and neighboring countries were extracted and used to construct the ENMs, namely Maxent, Bioclim, Domain, and Garp. Models were evaluated based on Receiver Operating Characteristic curve, Kappa, and True Skill Statistic coefficients. The best model was constructed using Cryptosporidium data and climate variables during 1986‒2010, and used to analyze the effects of climate factors on Cryptosporidium distribution. The climate variables for the period 2011‒2100 were projected to the simulation results to predict the ecological adaptability and potential distribution of Cryptosporidium in future in China.ResultsThe Maxent model (AUC = 0.95, maximum Kappa = 0.91, maximum TSS = 1.00) fit better than the other three models and was thus considered the best ENM for predicting Cryptosporidium habitat suitability. The major suitable habitats for human-derived Cryptosporidium in China were located in some high-population density areas, especially in the middle and lower reaches of the Yangtze River, the lower reaches of the Yellow River, and the Huai and the Pearl River Basins (cloglog value of habitat suitability > 0.9). Under future climate change, non-suitable habitats for Cryptosporidium will shrink, while highly suitable habitats will expand significantly (χ2 = 76.641, P < 0.01; χ2 = 86.836, P < 0.01), and the main changes will likely be concentrated in the northeastern, southwestern, and northwestern regions.ConclusionsThe Maxent model is applicable in prediction of Cryptosporidium habitat suitability and can achieve excellent simulation results. These results suggest a current high risk of transmission and significant pressure for cryptosporidiosis prevention and control in China. Against a future climate change background, Cryptosporidium may gain more suitable habitats within China. Constructing a national surveillance network could facilitate further elucidation of the epidemiological trends and transmission patterns of cryptosporidiosis, and mitigate the associated epidemic and outbreak risks.Graphical

Temperature was the dominant climatic factor that controlled Juniperus przewalskii growth before 1988. However, the limiting effect of temperature on trees gradually weakened after 1988. Treeline shifted upward since 1890, especially during the 1930–1949. The saplings of the species died due to the warming. Forest mortality triggered by drought and treeline dynamics due to the regional warming has been widely reported. In the eastern Qilian Mountains, northwestern China, sapling of Juniperus przewalskii was found dead in the high elevation at the fringe of its spatial distribution. Tree-ring widths were measured, and climatic records were related to the tree-ring width to understand the sapling’s death and the mechanism of the treeline dynamics in this region. Results showed that tree-ring widths were positively correlated with the temperatures of previous year’s September to current year’s February. However, this correlation weakened in the late twentieth century as the mean annual temperature increased. Treeline shifted upwards, and the regeneration of J. przewalskii trees peaked during 1930–1949, of which most grew at higher elevations. Sapling trees (less than 2 m tall) started to die after 1959 and the death rate peaked 2000–2004, which lagged the warming induced drought. Drought stress induced by rising temperatures explained the death of the sapling trees. This study sheds light on the impacts of climate changes for tree growth, forest dynamics, and tree mortality, and provides insights that will be useful to forest managers for managing vulnerable arid and semi-arid forests.

Subotica municipality is situated in the Subotica-Horgoš sands in the Bačka loess plateau, the two geomorphological units made of the early Quaternary sediments of intergranular porosity which form the water collecting environment for the phreatic aquifer. Owing to this, the phreatic aquifer is developed within the whole study area. Because of incomplete database, primarily the lack of contemporary data of the phreatic water table depth from various measuring points, the main aims of the paper are restricted to defining basic characteristics of water regime of the phreatic aquifer in Subotica municipality and their causal connection with the dominant climatic factor. Special emphasis in the paper is given to the issue of inade­quate monitoring of water table depth in the study area, which is the result of insufficient coverage of the area with active monitoring wells. Actually, there are only 10 active monitoring wells in Subotica municipality, which are unevenly distributed in the study area. Such situation disables the studious approach in studying the water regime of the phreatic aquifer and estimating the exact directions of its outputs, which creates a significant problem that needs to be solved in the near future. .

The self-thinning rule is fundamental in regulating maximum stocking and constructing stand density management diagrams. Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) is the most important tree species and widely distributed across subtropical China. Yet, our understanding of how the self-thinning line of Chinese fir relates to climate is limited. Longitudinal data from 48 plots distributed in Fujian, Jiangxi, Guangxi, and Sichuan provinces were used to describe self-thinning for Chinese fir in relation to climate through first-order autoregressive (AR(1)) and nonlinear mixed effects (NLME) models. Results showed that self-thinning lines had steeper slopes for Chinese fir growing in areas with larger annual precipitation and summer mean maximum temperature but flatter slopes with higher mean annual temperature, degree-days below 0 °C, and winter mean minimum temperature. Winter mean minimum temperature was the dominant climatic factor in shaping self-thinning lines, which suggests that temperature was the key climate driver that affects self-thinning of Chinese fir. In addition, differences of slopes for any two of the four sites were significant, except between the Guangxi and Sichuan sites. Our results will be useful for both the silvicultural practices and mitigation strategies of Chinese fir under climate change in south China.