我国单季稻种植区的气候适宜性

从国家层次和年尺度阐明影响我国单季稻种植区分布的主导气候因子, 揭示我国单季稻种植区的潜在分布及其气候适宜性,可为我国优化单季稻生产布局、改进种植制度和引种提供科学依据.本文从国家层次和年尺度选取影响我国单季稻分布的潜在气候因子, 利用其地理分布信息,结合最大熵模型和ArcGIS的空间分析功能, 阐明影响我国单季稻分布的主导气候因子并构建我国单季稻分布与气候的关系模型. 结果表明: 影响我国单季稻潜在种植区分布的主导气候因子是年降水量、湿润指数和稳定通过18 ℃日数, 它们对单季稻分布的累积贡献率达到了潜在气候因子的94.5%; 基于主导气候因子和单季稻种植点分布的地理信息, 结合最大熵模型构建的我国单季稻种植区分布与气候的关系模型能够很好地模拟我国单季稻种植区的潜在分布. 根据待预测区单季稻的存在概率, 明确了我国单季稻种植区潜在分布的气候低、中、高适宜区和气候不适宜区, 并分析了各气候适宜区的气候特征.     

我国单季稻种植区的气候适宜性

从国家层次和年尺度阐明影响我国单季稻种植区分布的主导气候因子, 揭示我国单季稻种植区的潜在分布及其气候适宜性,可为我国优化单季稻生产布局、改进种植制度和引种提供科学依据.本文从国家层次和年尺度选取影响我国单季稻分布的潜在气候因子, 利用其地理分布信息,结合最大熵模型和ArcGIS的空间分析功能, 阐明影响我国单季稻分布的主导气候因子并构建我国单季稻分布与气候的关系模型. 结果表明: 影响我国单季稻潜在种植区分布的主导气候因子是年降水量、湿润指数和稳定通过18 ℃日数, 它们对单季稻分布的累积贡献率达到了潜在气候因子的94.5%; 基于主导气候因子和单季稻种植点分布的地理信息, 结合最大熵模型构建的我国单季稻种植区分布与气候的关系模型能够很好地模拟我国单季稻种植区的潜在分布. 根据待预测区单季稻的存在概率, 明确了我国单季稻种植区潜在分布的气候低、中、高适宜区和气候不适宜区, 并分析了各气候适宜区的气候特征.     

我国春玉米潜在种植分布区的气候适宜性

根据中国气象局216个春玉米农业气象观测站资料与1971—2000年10 km×10 km空间分辨率的气候资料,基于全国区域和年尺度筛选出了影响我国玉米种植分布的潜在气候指标,利用最大熵(Maximum Entropy,MaxEnt)模型和ArcGIS空间分析技术,构建了春玉米潜在种植分布与气候因子关系模型,研究了影响我国春玉米潜在种植分布区的主导气候因子及其气候适宜性。结果表明,影响我国春玉米潜在种植分布的主导气候因子有:≥10℃积温、≥10℃的天数、最热月平均温度、年平均温度、年降水、湿润指数和气温年较差;结合春玉米存在概率,将我国春玉米潜在种植分布区划分成4个等级:气候不适宜区、次适宜区、适宜区和最适宜区,给出了各气候适宜区的气候特征。选取作物在待预测地区的存在概率这一综合反映各主导气候因子影响的指标来划分作物潜在种植分布区,有助于更加准确地进行气候区划,从而可为制定玉米应对气候变化措施提供科学依据。     

中国兴安落叶松天然林地理分布及其气候适宜性

准确评估兴安落叶松林潜在分布及其气候适宜性对科学指导森林经营和管理具有重要的现实意义。基于可能影响兴安落叶松林地理分布的8个气候变量:最冷月平均温度(Tc)、最暖月平均温度(Tw)、气温年较差(DTY)、≥5℃积温(GDD5)、年均降水量(P)、秋冬季平均降水量(Paw)、湿润指数(MI)和年辐射量(RAD),利用最大熵模型确定了影响中国兴安落叶松林地理分布的主导气候因子,并构建了兴安落叶松林地理分布与气候的关系模型。结果表明:影响中国兴安落叶松林地理分布的主导气候因子是Tc、DTY、RAD和GDD5,累积贡献率达87.8%,表明热量(温度与辐射)是兴安落叶松林存在与否的决定因素,而水分限制作用相当有限。中国兴安落叶松林主要分布在中、低气候适宜区域,其气候特征为:-28.8℃≤Tc≤-19.5℃;39.0℃≤DTY≤46.2℃;2871.7 MJ·m-2≤RAD≤3519.8 MJ·m-2;1000.0℃·d≤GDD5≤2100.0℃·d。     

中国欧亚种酿酒葡萄种植分布的主要气候影响因子与气候适宜性

开展酿酒葡萄气候适宜性研究对于优化酿酒葡萄布局、气候资源开发利用具有重要意义。基于欧亚种酿酒葡萄(Vitis vinifera L.)分布数据和影响其分布的气候因子,利用最大熵模型(MaxEnt)和地理信息系统(ArcGIS),研究影响欧亚种酿酒葡萄种植分布的主导气候因子及其气候适宜性。结果表明:MaxEnt模型能够很好地模拟我国欧亚种酿酒葡萄的潜在分布,模拟效果达到"非常好"(AUC平均值0.936)的水平。基于气候因子对欧亚种酿酒葡萄地理分布影响的贡献确定了主导气候因子,即无霜期、干燥度、极端最低气温、年降水量、生长季日照时数、≥10℃活动积温。当前,我国欧亚种酿酒葡萄种植分布的气候高适宜区、适宜区、次适宜区分别占次适宜及以上区域总面积的2.9%、20.4%和76.7%。欧亚种酿酒葡萄气候高适宜区主要分布在宁夏、山西、陕西、内蒙古、山东、河北、新疆、甘肃等省,只考虑气候因子,陕西、山西、内蒙古具有较大的发展空间。     

气候变化条件下苦参在我国潜在分布区的预测分析

为了解气候变化情景下苦参在中国的潜在分布区变化,探讨生物气候因子与苦参适宜分布格局的关系.该文通过收集苦参的地理分布点并结合19项生态因子,运用最大熵模型(MaxEnt)和地理信息系统(ArcGIS)对末次盛冰期、当前气候、未来气候三种气候情景下苦参在我国适生区的分布格局进行模拟,并分析影响苦参生长的主导生态因子.结果...     

基于MaxEnt模型的中国沙棘潜在适宜分布区分析

中国沙棘主要分布于我国华北、西北、西南等地森林—草原过渡地带，是我国北方地区退耕还林、生态修复等工程的重要造林树种，对维持干旱、半干旱地区的生态环境稳定具有重要意义。探讨限制中国沙棘分布的主导气候因子，模拟其潜在适宜分布区，以期为中国沙棘在林业生态工程和生态经济林建设中的合理种植和推广提供理论依据。基于中国沙棘自然分布的328个地理样点，利用最大熵(MaxEnt)模型对中国沙棘的潜在分布区的主导气候因子进行分析，并预测中国沙棘的潜在分布范围。结果表明，基于气候变量的MaxEnt模型训练集和测试集受试者工作特征曲线下面积(AUC值)分别为0.962±0.001和0.949±0.001,均大于0.9,表明MaxEnt模型对中国沙棘潜在分布区的预测具有极高的准确度，可信度好。基于环境变量贡献率和刀切法的结果表明年降雨情况、生长季的水热状况、最干季降雨和最冷月最低温等是限制中国沙棘分布的主要气候因素，其中年降雨是限制中国沙棘分布的主导气候因子。通过模拟得到现代中国沙棘潜在地理分布的总适生区面积为165.1万km~2;其中高适生区和中适生区面积共93.3万km~2,主要集中分布于河北西部、北部，...     

蒙古栎地理分布的主导气候因子及其阈值

基于影响植物功能型分布的6个气候变量:年均降水量、气温年较差、最冷月温度、最暖月温度、大于5℃积温和湿润指数,结合蒙古栎地理分布资料,根据最大熵模型和各气候变量对蒙古栎地理分布的贡献,确定了影响蒙古栎地理分布的主导气候因子,即年均降水量、气温年较差、大于5℃积温和最暖月温度;利用模拟的蒙古栎地理分布概率与主导气候因子的关系给出了各主导气候因子的阈值,即年均降水量330-910 mm、气温年较差大于29℃、大于5 ℃有效积温为1200-3500℃·d、最暖月温度为17-26℃.     

基于Maxent和ARCGIS的醉鱼草属植物适生区预测

为分析园林观赏植物醉鱼草属Buddleja在中国的潜在适生区, 和环境因子对其在地理分布上的影响, 基于世界气候数据网提供的19个气候因子数据, 以及中国地区内128份可查证的分布点, 运用最大熵模型及相关生物地理软件, 模拟醉鱼草属植物在中国的潜在分布区, 并通过刀切法得出影响其分布的主导气候因子。结果表明: 醉鱼草属植物潜在适生区为西南云贵地区和东南江浙一带; 暖季降雨量、冷季均温、温度季节变异系数、降雨季节变异系数是影响醉鱼草属植物分布的主导因子, 其适宜生长在暖季降水量为200—2500 mm, 冷季均温为-20—20 ℃的地区; 醉鱼草适生区与年降水量具有一定的相关性, 其分布边界与400 mm年等降水量线大致重合。     

基于最大熵模型的狸尾豆属植物在中国的潜在分布区模拟

基于19个气候因子和203条狸尾豆属(Uraria)植物地理分布记录,采用最大熵模型(Max Ent)对植物当前分布点的气候变量进行分析,推断其在末次盛冰期(LGM)、当前和未来气候(2070s)情景下的潜在分布;采用受试者工作曲线和刀切法对模型的准确性进行检验并探明影响该属在中国分布的气候因子。结果显示:最大熵模型模拟结果极准确,测试集和训练集假阳性值(AUC)分别达到0.934和0.936;影响该属植物分布的主要气候因子是最暖季节降水和最冷月份最低温度;广西、广东及台湾地区为该属在中国的起源中心。在全球气候变暖背景下,狸尾豆属植物的适生环境将向中国北部及东部沿海地区推移,且面积逐渐增加。     

Regional and global climate risks for reef corals: Incorporating species-specific vulnerability and exposure to climate hazards

Climate change is driving rapid and widespread erosion of the environmental conditions that formerly supported species persistence. Existing projections of climate change typically focus on forecasts of acute environmental anomalies and global extinction risks. The current projections also frequently consider all species within a broad taxonomic group together without differentiating species-specific patterns. Consequently, we still know little about the explicit dimensions of climate risk (i.e., species-specific vulnerability, exposure and hazard) that are vital for predicting future biodiversity responses (e.g., adaptation, migration) and developing management and conservation strategies. Here, we use reef corals as model organisms (n = 741 species) to project the extent of regional and global climate risks of marine organisms into the future. We characterise species-specific vulnerability based on the global geographic range and historical environmental conditions (1900–1994) of each coral species within their ranges, and quantify the projected exposure to climate hazard beyond the historical conditions as climate risk. We show that many coral species will experience a complete loss of pre-modern climate analogs at the regional scale and across their entire distributional ranges, and such exposure to hazardous conditions are predicted to pose substantial regional and global climate risks to reef corals. Although high-latitude regions may provide climate refugia for some tropical corals until the mid-21st century, they will not become a universal haven for all corals. Notably, high-latitude specialists and species with small geographic ranges remain particularly vulnerable as they tend to possess limited capacities to avoid climate risks (e.g., via adaptive and migratory responses). Predicted climate risks are amplified substantially under the SSP5-8.5 compared with the SSP1-2.6 scenario, highlighting the need for stringent emission controls. Our projections of both regional and global climate risks offer unique opportunities to facilitate climate action at spatial scales relevant to conservation and management.     

气候变化背景下中国农业气候资源变化Ⅴ.宁夏农业气候资源变化特征

基于1961—2009年宁夏21个气象站点的气象资料,分析了宁夏各区农业气候资源的时空变化趋势.结果表明：研究期间,宁夏各地气温逐渐升高,呈北高南低的空间分布特征,年均气温的气候倾向率为0.4 ℃·(10 a)^-1;大部分地区年降水量呈逐渐减少趋势,年降水量的气候倾向率为4.26 mm·(10 a)^-1;无霜期和作物生长季天数随着气候变暖逐渐延长;≥10 ℃积温在3200 ℃·d以上的区域向南扩展,宁夏适宜种植中晚熟水稻的区域有所扩大;2001—2009年,宁夏大部分地区适宜种植冬小麦,全区各地几乎都适宜种植春小麦;宁夏南部山区各地7月平均气温≤20 ℃的区域面积逐渐缩小,适宜种植马铃薯的地域也随之缩小.     

植物物候与气候研究进展

植物物候及其变化是多个环境因子综合影响的结果,其中气候是最重要、最活跃的环境因子。主要从气候环境角度分析了植物物候与气候以及气候变化间的相互关系,概述了国内外有关植物物候及物候模拟等方面的研究进展。表明,温度是影响物候变化最重要的因子;同时,水分成为胁迫因子时对物候的影响也十分重要。近50a左右,世界范围内的植物物候呈现出了春季物候提前,秋季物候推迟或略有推迟的特征,从而导致了多数植物生长季节的延长,并成为全球物候变化的趋势。全球气候变暖改变了植物开始和结束生长的日期,其中冬季、春季气温的升高使植物的春季物候提前是植物生长季延长的主要原因。目前对物候学的研究方向主要集中在探讨物候与气候变化之间的关系,而模型模拟是定量研究气候变化与植物物候之间关系的重要方式,国内外已经开发出多种物候模型来分析气候驱动与物候响应之间的因果关系。另外遥感资料的应用也为物候模型研究提供了新的方向。物候机理研究、物候与气候关系以及物候模型研究将是研究的重点。     

气候变化背景下中国农业气候资源变化V.宁夏农业气候资源变化特征

基于1961-2009年宁夏21个气象站点的气象资料,分析了宁夏各区农业气候资源的时空变化趋势.结果表明:研究期间,宁夏各地气温逐渐升高,呈北高南低的空间分布特征,年均气温的气候倾向率为0.4℃·(10 a)-1;大部分地区年降水量呈逐渐减少趋势,年降水量的气候倾向率为4.26 mm·(10 a)-1;无霜期和作物生长季天数随着气候变暖逐渐延长;≥10℃积温在3200℃·d以上的区域向南扩展,宁夏适宜种植中晚熟水稻的区域有所扩大;2001-2009年,宁夏大部分地区适宜种植冬小麦,全区各地几乎都适宜种植春小麦;宁夏南部山区各地7月平均气温≤20℃的区域面积逐渐缩小,适宜种植马铃薯的地域也随之缩小.     

Human land uses reduce climate connectivity across North America

Climate connectivity, the ability of a landscape to promote or hinder the movement of organisms in response to a changing climate, is contingent on multiple factors including the distance organisms need to move to track suitable climate over time (i.e. climate velocity) and the resistance they experience along such routes. An additional consideration which has received less attention is that human land uses increase resistance to movement or alter movement routes and thus influence climate connectivity. Here we evaluate the influence of human land uses on climate connectivity across North America by comparing two climate connectivity scenarios, one considering climate change in isolation and the other considering climate change and human land uses. In doing so, we introduce a novel metric of climate connectivity, ‘human exposure’, that quantifies the cumulative exposure to human activities that organisms may encounter as they shift their ranges in response to climate change. We also delineate potential movement routes and evaluate whether the protected area network supports movement corridors better than non‐protected lands. We found that when incorporating human land uses, climate connectivity decreased; climate velocity increased on average by 0.3 km/year and cumulative climatic resistance increased for ~83% of the continent. Moreover, ~96% of movement routes in North America must contend with human land uses to some degree. In the scenario that evaluated climate change in isolation, we found that protected areas do not support climate corridors at a higher rate than non‐protected lands across North America. However, variability is evident, as many ecoregions contain protected areas that exhibit both more and less representation of climate corridors compared to non‐protected lands. Overall, our study indicates that previous evaluations of climate connectivity underestimate climate change exposure because they do not account for human impacts.     

Designing ecological climate change impact assessments to reflect key climatic drivers

Identifying the climatic drivers of an ecological system is a key step in assessing its vulnerability to climate change. The climatic dimensions to which a species or system is most sensitive – such as means or extremes – can guide methodological decisions for projections of ecological impacts and vulnerabilities. However, scientific workflows for combining climate projections with ecological models have received little explicit attention. We review Global Climate Model (GCM) performance along different dimensions of change and compare frameworks for integrating GCM output into ecological models. In systems sensitive to climatological means, it is straightforward to base ecological impact assessments on mean projected changes from several GCMs. Ecological systems sensitive to climatic extremes may benefit from what we term the ‘model space’ approach: a comparison of ecological projections based on simulated climate from historical and future time periods. This approach leverages the experimental framework used in climate modeling, in which historical climate simulations serve as controls for future projections. Moreover, it can capture projected changes in the intensity and frequency of climatic extremes, rather than assuming that future means will determine future extremes. Given the recent emphasis on the ecological impacts of climatic extremes, the strategies we describe will be applicable across species and systems. We also highlight practical considerations for the selection of climate models and data products, emphasizing that the spatial resolution of the climate change signal is generally coarser than the grid cell size of downscaled climate model output. Our review illustrates how an understanding of how climate model outputs are derived and downscaled can improve the selection and application of climatic data used in ecological modeling.     

The climate velocity of the contiguous United States during the 20th century

Rapid climate change has the potential to affect economic, social, and biological systems. A concern for species conservation is whether or not the rate of on‐going climate change will exceed the rate at which species can adapt or move to suitable environments. Here we assess the climate velocity (both climate displacement rate and direction) for minimum temperature, actual evapotranspiration, and climatic water deficit (deficit) over the contiguous US during the 20th century (1916–2005). Vectors for these variables demonstrate a complex mosaic of patterns that vary spatially and temporally and are dependent on the spatial resolution of input climate data. Velocities for variables that characterize the climatic water balance were similar in magnitude to that derived from temperature, but frequently differed in direction resulting in the divergence of climate vectors through time. Our results strain expectations of poleward and upslope migration over the past century due to warming. Instead, they suggest that a more full understanding of changes in multiple climatic factors, in addition to temperature, may help explain unexpected or conflicting observational evidence of climate‐driven species range shifts during the 20th century.     

Solar history and human affairs

Historical research at different time scales from 10s to 1000s of years suggests that solar variation may have influences on global climate. Climate change has had significant impacts on cultures during these periods. Very high solar output during the Medieval Optimum would be expected to have particularly large impacts on peoples of that time as sunspot numbers are thought to have reached one third again any values observed in the current century. Certain other impacts can be inferred from modern populations. For example, the higher parts of the solar cycle are associated with greater incidence of skin melanoma.     

Range expansion during the Pleistocene drove morphological radiation of the fir genus (Abies,Pinaceae) in the Qinghai‐Tibet Plateau and Himalayas

Range expansion caused by climate oscillations in the past probably promoted morphological radiation in a few plant groups. In this study, we aim to test this hypothesis through phylogeographical analysis of the cold‐tolerant fir genus (Abies) in the Qinghai‐Tibet Plateau (QTP) and Himalayas, where it comprises 12 described species. We examined sequence variation in two maternally inherited mitochondrial (mt) DNA fragments (nad5‐4 and nad7‐1) and two paternally inherited plastid DNA fragments (trnS‐G and trnL‐F) for 733 individuals from 75 populations of the species in a monophyletic group. Only six mtDNA haplotypes were recovered, but five were shared between multiple species and one occurred at a high frequency, providing strong evidence of range expansion. Forty‐three plastid DNA haplotypes were detected, 19 of which were shared between species and three occurred at high frequency. Network, mismatch and Bayesian skyline plot analyses of all plastid DNA haplotypes from this clade clearly suggested range expansion. This expansion was dated as having occurred during the longest and most extensive glaciation in the Pleistocene. Our results therefore supported the range expansion hypothesis for this clade of Abies during the Pleistocene; expansion probably drove the morphological radiation of the clade in the QTP and Himalayas, although it remains unclear whether the different morphotypes should be acknowledged as independent, reproductively isolated species. © 2015 The Linnean Society of London, Botanical Journal of the Linnean Society, 2015, 179 , 444–453.