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1.
末次盛冰期以来红豆树在不同气候变化情景下的分布动态   总被引:1,自引:0,他引:1  
红豆树(Ormosia hosiei Hemsl. et Wils.)是中国的特有种,具有极高的经济价值、景观价值和药用价值。由于木材珍贵,人工盗伐严重,其种群数量和分布范围不断减少,被世界自然保护联盟(IUCN)濒危物种红色名录列为近危物种。气候变化会对物种的分布造成严重影响,理解该影响将有助于物种保护策略的制定,尤其是为濒危物种未来的保护提供重要参考。本研究基于红豆树在中国的地理分布数据,借助经相关性分析后筛选出的9个变量因子,利用最大熵模型(MaxEnt)模拟红豆树在末次盛冰期、全新世中期、当代和未来气候情景下的潜在分布区和影响其分布的主导环境因子,并且通过空间分析模拟其在不同气候变化情景下空间分布格局的变化。结果表明MaxEnt在各时期训练集和测试集的AUC(受试者工作特征曲线下的面积)均值均达到0.9以上,表明模型有很好的预测能力。刀切法(Jackknife)表明年均降水量、温度季节性变化标准差和昼夜温差月均值是主导其分布的三大因子,累计贡献率达到91.8%。将模拟结果导入到ArcGIS后,处理得到不同时期红豆树适生区空间分布格局变化。结果表明,自末次盛冰期以来,红豆树的适生...  相似文献   

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长苞铁杉(Tsuga longibracteata)是中国特有的珍贵树种,不仅对研究裸子植物的系统发育、古生态和古气候具有重要作用,而且该树种具有造林、用材和药用等方面的较高价值。研究长苞铁杉在气候变化下的分布格局变化是制定其保护和可持续利用的重要基础。采用最大熵模型(MaxEnt),结合不同时期(当前、2050年和2070年)和不同二氧化碳排放情境下(RCP2.6和RCP8.5)的气候因子变量,探讨气候变化与物种地理分布格局的关系,预测长苞铁杉的潜在分布区变迁。本研究考虑了空间约束对物种分布的限制作用,构建了气候因子预测模型(C)和气候+空间约束因子预测模型(C+S)分别进行潜在分布区预测,比较其结果差异。结果显示,最干月降水量和温度年较差是影响长苞铁杉地理分布的主导气候因子,空间约束因子对长苞铁杉未来的地理分布有重要影响。随时间年限增加,长苞铁杉总潜在适生区面积降低,特别是中高等级的适生区面积有不同程度地减少,分布范围总体向北移动,这些变化趋势在RCP8.5情境下更加突出。这一结果表明未来气候变化会导致长苞铁杉种群分布范围收缩和生境适宜度下降,加剧其受胁程度。加入空间约束因子后,C+S模型的预测精度更高,结果更符合长苞铁杉的迁移、扩散特性。长苞铁杉未来的核心分布区仍位于现存的湘、桂、黔结合部,表明其具有"原地避难"的特性,应进一步加强对现有野生资源的保护。渝、川、鄂结合部的大巴山等地区是未来气候变化下长苞铁杉的理论分布区域,可作为长苞铁杉应对未来气候变化的引种地区,应提早进行人工引种、栽培等前期研究。研究结果可为气候变化背景下长苞铁杉的保护、物种迁地保存和可持续管理提供科学依据,也可为准确预测濒危、珍稀植物的地理分布范围提供方法参考。  相似文献   

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气候变化对东北沼泽湿地潜在分布的影响   总被引:1,自引:0,他引:1  
贺伟  布仁仓  刘宏娟  熊在平  胡远满 《生态学报》2013,33(19):6314-6319
东北地区是我国沼泽湿地分布最广泛的地区。为研究沼泽湿地对气候变化的响应,选取了对沼泽湿地分布可能存在影响的26个环境因子,利用最大熵(Maximum Entropy, MaxEnt)模型模拟了沼泽湿地基准气候条件下的潜在分布,并预测了气候变化情景下2011-2040 年、2041-2070 年和2071-2100 年3个研究阶段东北沼泽湿地潜在分布。研究结果表明:最大熵模型预测精度较高(平均AUC(Aera Under Curve)为(0.826±0.005))。基准气候条件下东北沼泽潜在分布区主要为大小兴安岭和三江平原地区。随着时间的推进,东北地区沼泽湿地原有潜在分布面积明显减少,而新增潜在分布面积较少,总面积呈现急剧减少趋势。至2071-2100年,原有沼泽湿地潜在分布面积将减少99.80%,新增潜在分布面积仅2.48%,总潜在分布面积减少97.32%。空间分布上,东北沼泽湿地潜在分布呈现由东向西迁移,南北向中心收缩的趋势。研究结果可为东北地区沼泽湿地保护政策的制定提供参考。  相似文献   

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AimInvasive alien species (IAS) threaten ecosystems and humans worldwide, and future climate change may accelerate the expansion of IAS. Predicting the suitable areas of IAS can prevent their further expansion. Ageratina adenophora is an invasive weed over 30 countries in tropical and subtropical regions. However, the potential suitable areas of A. adenophora remain unclear along with its response to climate change. This study explored and mapped the current and future potential suitable areas of Ageratina adenophora.LocationGlobal.TaxaAsteraceae A. adenophora (Spreng.) R.M.King & H.Rob. Commonly known as Crofton weed.MethodsBased on A. adenophora occurrence data and climate data, we predicted its suitable areas of this weed under current and future (four RCPs in 2050 and 2070) by MaxEnt model. We used ArcGIS 10.4 to explore the potential suitable area distribution characteristics of this weed and the “ecospat” package in R to analyze its altitudinal distribution changes.ResultsThe area under the curve (AUC) value (>0.9) and true skill statistics (TSS) value (>0.8) indicated excelled model performance. Among environment factors, mean temperature of coldest quarter contributed most to the model. Globally, the suitable areas for A. adenophora invasion decreased under climate change scenarios, although regional increases were observed, including in six biodiversity hotspot regions. The potential suitable areas of A. adenophora under climate change would expand in regions with higher elevation (3,000–3,500 m).Main conclusionsMean temperature of coldest quarter was the most important variable influencing the potential suitable area of A. Adenophora. Under the background of a warming climate, the potential suitable area of A. adenophora will shrink globally but increase in six biodiversity hotspot regions. The potential suitable area of Aadenophora would expand at higher elevation (3,000–3,500 m) under climate change. Mountain ecosystems are of special concern as they are rich in biodiversity and sensitive to climate change, and increasing human activities provide more opportunities for IAS invasion.  相似文献   

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The Mediterranean basin is considered a hotspot of biological diversity with a long history of modification of natural ecosystems by human activities, and is one of the regions that will face extensive changes in climate. For 181 terrestrial mammals (68% of all Mediterranean mammals), we used an ensemble forecasting approach to model the future (approx. 2100) potential distribution under climate change considering five climate change model outputs for two climate scenarios. Overall, a substantial number of Mediterranean mammals will be severely threatened by future climate change, particularly endemic species. Moreover, we found important changes in potential species richness owing to climate change, with some areas (e.g. montane region in central Italy) gaining species, while most of the region will be losing species (mainly Spain and North Africa). Existing protected areas (PAs) will probably be strongly influenced by climate change, with most PAs in Africa, the Middle East and Spain losing a substantial number of species, and those PAs gaining species (e.g. central Italy and southern France) will experience a substantial shift in species composition.  相似文献   

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中国水稻潜在分布及其气候特征   总被引:12,自引:0,他引:12  
段居琦  周广胜 《生态学报》2011,31(22):6659-6668
基于全国层次和年尺度筛选的影响中国水稻分布的潜在气候指标,结合水稻地理分布信息,利用最大熵模型和ArcGIS软件的空间分析功能,分析了中国水稻潜在分布及其气候特征.结果表明:年降水量(P)、湿润指数(MI)、稳定通过18℃持续日数( N18)和≥10℃积温(∑T10)4个因子是影响水稻分布的主导气候因子,其累积贡献百分率达97.6%.采用主导气候因子作为环境变量重建气候水稻分布关系的最大熵模型,利用重建的最大熵模型给出的中国水稻存在概率,对中国水稻潜在分布区的气候适宜等级进行了划分,并分析了各适宜区的气候特征.研究结果可为中国水稻生产布局及制定应对气候变化政策提供参考.  相似文献   

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大花杓兰(Cypripedium macranthos)隶属兰科杓兰属,是国家二级重点保护野生植物,与大多数杓兰属植物分布在我国西南山区不同,主要分布于我国的华北、东北和台湾等地区。多年来,过渡采挖等导致了大花杓兰种群数量和个体数目急剧下降。鉴于大花杓兰特殊的分布格局和濒危现状,选择过去、当前和未来8个气候情景,利用MaxEnt物种分布模型结合38个环境变量及来源于数据库和最新实地调查的80个分布位点进行建模,分析了影响大花杓兰分布的关键环境变量,预测了其在当前、过去和未来气候情景下的适生区及其分布中心和迁移趋势。结果表明:当前情景下,大花杓兰适生区主要分布在我国东北和华北地区。影响其分布的5个关键环境变量分别是:UV-B最强月份均值(UV-B3,贡献率:54.0%)、森林覆盖率(FOR,贡献率:14.3%)、降水量季节性变化(BIO15,贡献率:7.4%)、温度季节性变动系数(BIO4,贡献率:6.8%)和草/灌木/林地(GRS,贡献率:4.6%)。其中,紫外辐射相关变量是首次被运用在杓兰属植物的适生区分布预测中,并被证实对大花杓兰的分布具有重要影响。过去3个气候情景下大花杓兰总适生...  相似文献   

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唐杨欣  皮杰  刘新华  向建国  曾聪  李德亮 《生态学报》2023,43(10):4250-4259
河蚬是一类在我国广泛分布的底栖贝类,具有重要的经济价值及生态价值。近年来,河蚬野生资源量锐减,了解河蚬在国内的潜在分布能为河蚬的保护和合理利用提供重要参考。基于河蚬在中国的136个分布点和8个环境因子,采用ENMeval包和biasfile优化后的最大熵模型(MaxEnt)预测分别河蚬现代和未来(2041—2060年和2081—2100年) 6个气候情景下的潜在分布。综合Jackknife检验、置换重要值和环境因子贡献率评估影响现代河蚬潜在分布的主要因子,比较未来气候情景下潜在适生区差异从而分析预测河蚬适宜分布的变化。结果表明:(1)优化后的MaxEnt模型预测准确度极高,平均AUC值为0.900±0.037,平均AUCDIFF值为0.019,现代河蚬潜在分布区域总面积为188.33×104 km2,主要集中在长江流域、海河流域、淮河流域、珠江流域、东南沿海区域以及黄河流域下游和渤海湾沿岸区域。(2)影响河蚬潜在分布的主要环境因子为海拔、温度(年均温和温度年较差)和降水(年降水量)。(3)在未来6种气候情景下,河蚬主要潜...  相似文献   

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Understanding how environmental and climate change can alter habitat overlap of marine predators has great value for the management and conservation of marine ecosystems. Here, we estimated spatiotemporal changes in habitat suitability and inter‐specific overlap among three marine predators: Baltic gray seals (Halichoerus grypus), harbor seals (Phoca vitulina), and harbor porpoises (Phocoena phocoena) under contemporary and future conditions. Location data (>200 tagged individuals) were collected in the southwestern region of the Baltic Sea; one of the fastest‐warming semi‐enclosed seas in the world. We used the maximum entropy (MaxEnt) algorithm to estimate changes in total area size and overlap of species‐specific habitat suitability between 1997–2020 and 2091–2100. Predictor variables included environmental and climate‐sensitive oceanographic conditions in the area. Sea‐level rise, sea surface temperature, and salinity data were taken from representative concentration pathways [RCPs] scenarios 6.0 and 8.5 to forecast potential climate change effects. Model output suggested that habitat suitability of Baltic gray seals will decline over space and time, driven by changes in sea surface salinity and a loss of currently available haulout sites following sea‐level rise in the future. A similar, although weaker, effect was observed for harbor seals, while suitability of habitat for harbor porpoises was predicted to increase slightly over space and time. Inter‐specific overlap in highly suitable habitats was also predicted to increase slightly under RCP scenario 6.0 when compared to contemporary conditions, but to disappear under RCP scenario 8.5. Our study suggests that marine predators in the southwestern Baltic Sea may respond differently to future climatic conditions, leading to divergent shifts in habitat suitability that are likely to decrease inter‐specific overlap over time and space. We conclude that climate change can lead to a marked redistribution of area use by marine predators in the region, which may influence local food‐web dynamics and ecosystem functioning.  相似文献   

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鲨鱼在气候变化和人类活动等因素的影响下面临着种群衰退的风险,开展鲨鱼保护优先区研究是鲨鱼保护行动的重要工作.将气候速度引入鲨鱼保护优先区的识别过程,旨在阐明中国周边海域鲨鱼现状保护成效和保护空缺,并预测气候速度影响下的鲨鱼保护优先区空间格局及其变化趋势.以集成物种分布模型模拟的146种鲨鱼栖息地作为保护对象,以2015年至2100年两种气候变化情景下的气候速度作为保护的机会成本,基于系统保护规划理论模拟现状和未来情景下的鲨鱼保护优先区选址方案.研究结果表明:(1)长江口以南至台湾海峡和北部湾近岸海域为鲨鱼多样性分布的主要区域,台湾海峡区域亦为珍稀濒危物种的重要分布区;(2)在两种气候情景下,南海中南部将面临较高的气候变化风险,而长江口以南至珠江口的近岸海域气候速度均相对较低,提示了这些区域或能成为气候变化影响下的生物避难所;(3)现有保护区仅保护了1.33%的海域和不到4%的鲨鱼物种,尚存在较大的保护空缺.当保护海域比例提升至10%时,可覆盖绝大多数鲨鱼物种.而当比例提升至30%时,珍稀濒危物种的栖息地将得到有效保护;(4)气候变化影响下保护优先区选址将发生不同程度的变化,尤其是在中国南海区域,如在保护规划时兼顾气候速度,可在满足相似保护目标的前提下减少保护优先区内25%以上的气候压力,以使其具有较强的应对气候变化潜力。  相似文献   

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气候变化情景下大沙鼠潜在地理分布   总被引:1,自引:1,他引:1  
大沙鼠(Rhombomys opimus)是中亚地区典型的荒漠啮齿动物,其采食和掘洞行为造成了荒漠林和荒漠草原退化加剧,生态环境恶化。基于大沙鼠分布数据、气候、土壤和地形因子数据,采用MaxEnt模型预测大沙鼠在当前气候和温室气体低、中、高3种浓度排放情景下2050年和2070年的潜在适生区,分析亚洲大陆未来气候条件下大沙鼠适生面积和分布格局的变化趋势,探讨影响大沙鼠分布的主要环境因子。结果表明:模型AUC(Area Under Curve)值达到0.9以上,预测的准确性达到"极好"。经刀切法分析(Jackknife)表明,影响大沙鼠在适生区分布最主要的环境变量为温度季节性变化的标准差、土壤基本饱和度、最干季度降水量、最暖季度降水量和土壤可交换钠盐。Rcp2.6、Rcp4.5和Rcp8.5三种气候场景下2050年高适生区面积较当前分别增长15.78%、15.10%和13.44%;Rcp2.6、Rcp4.5和Rcp8.5三种气候场景下2070年高适生区面积较当前增长8.32%、13.18%和18.18%。中国大沙鼠适生区范围内,新疆所分布的大沙鼠适生区分布范围变化较大,3种情景模式下大沙鼠的适生区位置向新疆北部扩张;甘肃适生区位置向西北部扩张;内蒙西北部和阿拉善地区大沙鼠的适生区位置向四周扩张。研究揭示了未来气候下大沙鼠高适生区范围和空间变化,并得到影响其分布的主要环境变量,对其防控具有重要意义。  相似文献   

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曹雪萍  王婧如  鲁松松  张晓玮 《生态学报》2019,39(14):5232-5240
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。  相似文献   

17.
Recent observations show that human‐induced climate change (CC) and land transformation (LT) are threatening wildlife globally. Thus, there is a need to assess the sensitivity of wildlife on large spatial scales and evaluate whether national parks (NPs), a key conservation tools used to protect species, will meet their mandate under future CC and LT conditions. Here, we assess the sensitivity of 277 mammals at African scale to CC at 10′ resolution, using static LT assumptions in a ‘first‐cut’ estimate, in the absence of credible future LT trends. We examine the relationship between species' current distribution and macroclimatic variables using generalized additive models, and include LT indirectly as a filter. Future projections are derived using two CC scenarios (for 2050 and 2080) to estimate the spatial patterns of loss and gain in species richness that might ultimately result. We then apply the IUCN Red List criteria A3(c) of potential range loss to evaluate species sensitivity. We finally estimate the sensitivity of 141 NPs in terms of both species richness and turnover. Assuming no spread of species, 10–15% of the species are projected to fall within the critically endangered or extinct categories by 2050 and between 25% and 40% by 2080. Assuming unlimited species spread, less extreme results show proportions dropping to approximately 10–20% by 2080. Spatial patterns of richness loss and gain show contrasting latitudinal patterns with a westward range shift of species around the species‐rich equatorial zone in central Africa, and an eastward shift in southern Africa, mainly because of latitudinal aridity gradients across these ecological transition zones. Xeric shrubland NPs may face significant richness losses not compensated by species influxes. Other NPs might expect substantial losses and influxes of species. On balance, the NPs might ultimately realize a substantial shift in the mammalian species composition of a magnitude unprecedented in recent geological time. To conclude, the effects of global CC and LT on wildlife communities may be most noticeable not as a loss of species from their current ranges, but instead as a fundamental change in community composition.  相似文献   

18.
There is increasing evidence that the distributions of a large number of species are shifting with global climate change as they track changing surface temperatures that define their thermal niche. Modelling efforts to predict species distributions under future climates have increased with concern about the overall impact of these distribution shifts on species ecology, and especially where barriers to dispersal exist. Here we apply a bio‐climatic envelope modelling technique to investigate the impacts of climate change on the geographic range of ten cetacean species in the eastern North Atlantic and to assess how such modelling can be used to inform conservation and management. The modelling process integrates elements of a species' habitat and thermal niche, and employs “hindcasting” of historical distribution changes in order to verify the accuracy of the modelled relationship between temperature and species range. If this ability is not verified, there is a risk that inappropriate or inaccurate models will be used to make future predictions of species distributions. Of the ten species investigated, we found that while the models for nine could successfully explain current spatial distribution, only four had a good ability to predict distribution changes over time in response to changes in water temperature. Applied to future climate scenarios, the four species‐specific models with good predictive abilities indicated range expansion in one species and range contraction in three others, including the potential loss of up to 80% of suitable white‐beaked dolphin habitat. Model predictions allow identification of affected areas and the likely time‐scales over which impacts will occur. Thus, this work provides important information on both our ability to predict how individual species will respond to future climate change and the applicability of predictive distribution models as a tool to help construct viable conservation and management strategies.  相似文献   

19.
绵刺(Potaninia mongolica Maxim.)为我国西北干旱、半干旱地区孑遗濒危荒漠植物,具有重要的生态作用。预测过去、当代及未来气候变化情景下绵刺植物在中国的潜在地理分布区和迁移路线,将为绵刺的保护利用及种群合理建立提供一定的科学依据。基于绵刺在中国的73个有效分布点和8个环境因子变量,利用MaxEnt模型和ArcGIS软件预测末次间冰期、末次盛冰期、当代及未来绵刺在中国的潜在地理分布变化,综合分析影响绵刺分布的主要环境因子及其适宜范围,并用检验受试者工作特征(ROC)曲线下面积(AUC)评估模型的精确度。结果表明:(1)MaxEnt模型预测精确度极高,受试者工作特征(ROC)曲线下面积(AUC)值为0.988,预测显示当代绵刺主要分布在内蒙古中西部地区(阿拉善地区)、宁夏东北部和西北部、甘肃中东部、新疆中部和西部少量狭长分布区,潜在地理分布的总适生区面积约是51.94×104 km~2;(2)影响绵刺潜在地理分布的重要环境因子变量是降雨(最干月降雨量、年均降雨量、最湿月降雨量、最冷季度平均降雨量)和温度(最热月的最高温);(3)从末次间冰期到末次...  相似文献   

20.
张华  赵浩翔  王浩 《生态学报》2020,40(18):6552-6563
胡杨(Populus euphratica)是全世界干旱和半干旱区急需优先保护的林木基因资源,预测未来气候变化情景下胡杨在中国的潜在地理分布将为胡杨种群资源的保护和管理提供科学依据,并为绿洲恢复过程中胡杨的合理种植和配置提供有价值的理论指导。本研究基于胡杨在中国地区的92条有效分布记录和10个环境因子变量,利用Maxent模型和ArcGIS软件预测了未来气候变化情景下胡杨在中国的潜在地理分布,综合环境因子变量贡献率及置换重要值、刀切法检验评估制约现代胡杨潜在地理分布的重要因子,采用响应曲线确定环境因子变量的适宜区间,定量确定胡杨未来受威胁的潜在地理分布区域和面积。结果表明:(1)Maxent模型的预测准确度极高,受试者工作曲线面积(AUC值)达0.932,现代胡杨潜在地理分布的总适生区面积为289.94×104km2,主要位于内蒙古中西部地区(额济纳旗和阿拉善地区)、新疆大部分地区、甘肃北部和西北部地区、青海中西部地区和宁夏北部地区;(2)影响胡杨的潜在地理分布的主要环境因子变量为气温因子变量(年均温和最冷月最低温)和降水因子变量(最湿月降水量和最干季降水量),最湿月降水量是影响胡杨潜在地理分布的关键因素;(3)在未来4种气候变化情景下,胡杨不同等级潜在地理分布区的面积较现代潜在地理分布区面积均有不同程度的缩小,且整体上看胡杨的潜在地理分布区有向高海拔区域迁移的趋势。  相似文献   

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