基于最大熵模型的中国兜兰属植物潜在分布模拟

基于已知分布点和20个环境因子,该研究利用MaxEnt模型模拟在现在(1970—2000年)气候条件和2种不同共享经济路径情景下(SSP1-2.6、SSP5-8.5)未来(2081—2100年)兜兰属(Paphiopedilum)植物的潜在分布格局,找出影响物种分布的环境因子。结果表明,兜兰属植物的最适宜分布区位于滇东南地区、贵州西南、广西西部、广东南部、海南北部。影响该属植物分布的主要环境因子是年降水量、年温度变化和最干旱季降水量。随着全球变暖,适生区有向北和西北方向扩张的趋势,逐渐往西北亚热带方向延伸。在SSP5-8.5的情景下,高适生区出现大幅度收缩。在未来气候情景下,不同种群的分布区变化规律并不一致,其分布格局响应气候变化的趋势也有所不同,因此该文针对分布区变化趋势不同的物种提出了不同的保护策略。     

气候变化下阔叶山麦冬的潜在适生区预测

基于MaxEnt最大熵模型和ArcGIS10.2软件,利用阔叶山麦冬(Liriope muscari (Decne.) L.H.Bailey)205条有效分布记录和10个生物气候变量,对现代和未来4个时期ssp245和ssp585气候情景下阔叶山麦冬潜在适生区进行预测,评估了制约阔叶山麦冬现代潜在分布区的主导气候因子。结果表明,训练及测试的AUC值范围分别为0.9861—0.9877和0.9849—0.9869,阔叶山麦冬现代潜在适生区的预测结果可信度较高。现代气候条件下阔叶山麦冬的潜在适生区主要分布于中国江西、安徽、广西、浙江、重庆及四川东部等地;总适生区面积占比为0.73%,其中高度、中度、一般适和低度适生区分别为0.08%、0.12%、0.17%和0.36%。影响其现代潜在适生区分布的主导气候因子为温度(bio11、bio10和bio4)和降水量(bio18和bio16)。未来4个时期2种气候情景下阔叶山麦冬适生区总面积较现代呈下降趋势,特别是在ssp585情景下,2090s时期适生区面积减少达到了0.68%。以上结果都为阔叶山麦冬的栽培、引种以及进一步探究单个气候因子对阔叶山麦...     

气候变化对祁连山蒙古扁桃潜在适生区的影响

气候变化将改变物种的生存环境,影响其分布范围,甚至威胁到某些物种的生存。本文通过ArcGIS软件和最大熵(MaxEnt)模型模拟蒙古扁桃(Amygdalus mongolica)在祁连山当前(1970—2000年)和未来(2081—2100年)2个气候时期背景下的地理分布格局,并分析其主要的环境影响因素。结果表明：(1)在当前气候条件下,蒙古扁桃在祁连山的东南部有较好的适生性;(2)未来4种气候情景下(SSP126,SSP245,SSP245和SSP585),蒙古扁桃在祁连山南部及东南部的适生区有消失的风险,扩张区主要集中在祁连山中北部的国家公园附近;(3)蒙古扁桃的分布格局主要向祁连山北部和高纬度地区迁移;(4)最湿月降水量(Bio13)、坡度(Slope)、最冷季度均温(Bio11)和最热月最高温(Bio5)的累计贡献率达到了80%以上,是影响蒙古扁桃适生分布的主要因子。本研究模拟、分析、预测了当前和未来不同情景下蒙古扁桃在祁连山的潜在分布及其变化,为祁连山生态及物种多样性的保护提供科学依据。     

闽楠(Phoebe bournei, Lauraceae)地理分布及随气候变化的分布格局模拟

掌握气候变化对珍稀濒危物种的分布和适应性变化趋势的影响,是开展保护生物学研究的基础。闽楠（Phoebe bournei）是我国东部亚热带森林的优势树种,也是金丝楠木的主要来源树种。它具有重要的经济、园林与生态价值,目前已被列为国家II级保护植物。预测不同气候背景下该物种的地理分布格局可为这一珍贵树种的资源保护、合理利用与开发提供指导依据,同时也为闽楠的起源与地理分化研究奠定基础。本研究基于闽楠的123个分布点信息与19个气候因子,采用最大熵模型（MaxEnt）与ArcGIS空间分析,构建闽楠于末次冰期（距今22000年）、当前（1950-2000年）以及未来（2050年与2070年）相应地潜在分布区格局,并确定未来受威胁的适生区、面积与影响分布的气候因子。结果表明：闽楠的适生区覆盖浙江、福建、江西、广东、广西、湖南、湖北、贵州及重庆,制约闽楠地理分布的气候因子主要是温度季节性变化标准差（Bio4）、最暖月最高温（Bio5）与最干季降水量（Bio17）;在末次盛冰期闽楠退缩到我国东部的许多山区,诸如武夷山、浙闽丘陵、武陵山、雪峰山、湘黔桂毗邻的山区;随着全球气候变暖,到2050年与2070年闽楠的适生区有着破碎化甚至丧失的风险。     

气候变化情景下大花杓兰在中国的适生区预测

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...     

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

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。     

中国东北地区12个建群树种对气候变化响应的MaxEnt模型分析

气候变化是当前全球生物多样性面临的最大威胁之一,对物种地理分布格局具有较大影响。东北森林物种丰富度较高,目前尚缺乏基于主要树种、未来不同气候模式的综合研究。基于12种建群树种的分布数据及23个环境变量（19个生物气候因子、土地利用类型、海拔、坡度、坡向）数据,应用MaxEnt模型首次对东北地区乔木树种在3种气候变化情景下（SSP126可持续路径、SSP245中间路径、SSP585化石燃料为主发展路径）的潜在丰富度分布格局、主导环境变量以及树种损失、获得和周转情况进行了预测。结果表明：不同未来气候情景下东北地区各树种的潜在分布变化存在差异,适生区面积减小的树种有：兴安落叶松、山杨、春榆、白桦、水曲柳、胡桃楸、蒙古栎、辽东桤木,减小幅度达到10%-30%;适生区面积变化不大的树种有：红皮云杉、樟子松、黄檗,多数情况下低、中和高适生区面积变化发生了抵消,导致总适生区面积变化不大;适生区增加的树种有：红松,增加幅度达20%左右。环境因素将影响东北地区乔木树种潜在适宜性分布,其中,降水因素对东北地区树种分布格局起关键作用,尤其是降水量季节性变化,是影响东北地区50%左右树种分布格局的主导环境因子。东北地区乔木树种在无迁移和SSP585气候情景下受威胁程度相对较高,而在SSP126气候情景下大多处于低风险状态;物种迁移假设的对物种受威胁程度的影响先于气候变化情景的影响,树种发生适度迁移能够缓解树种受威胁的状况。网格单元中物种损失和周转的预测表明,东北地区树种高周转率主要由树种高损失率造成,损失率较高的地区往往树种周转率也相对较高。预测气候变化对东北地区树木分布格局的影响,有助于制定更有效的气候变化适应策略,以促进东北地区树木的可持续发展。     

四川省岷江冷杉对气候变化的响应及其潜在分布格局

四川省是我国气候变化的敏感区之一,区域气候的暖干化趋势严重影响植物物种组成与分布。岷江冷杉(Abies faxoniana)作为我国特有种,其分布的动态变化对气候变化具有十分重要的指示作用。基于现有岷江冷杉分布数据、气候、土壤、地形等环境因子,运用最大熵模型(MaxEnt)预测当代气候条件下岷江冷杉潜在分布区,并分析未来时期(2050s和2070s)不同气候变化情景下(RCP2.6、RCP4.5和RCP8.5)岷江冷杉潜在适生分布区,筛选影响岷江冷杉分布的主导环境因子及阈值,探讨岷江冷杉分布对气候变化的响应机制。结果表明：(1)当前岷江冷杉的高适生区集中分布于岷江流域上游地区,在未来两个时期岷江冷杉潜在中、高适生区的面积较当代气候条件下适生区面积均有所增加,且适生区总体向四川南部扩张,北部适宜生境丧失。(2)岷江冷杉潜在中适生区在低排放浓度下(RCP2.6)面积占比最高,而潜在高适生区在高排放浓度下(RCP8.5)的面积占比最高。(3)影响岷江冷杉分布的主要环境因子分别是：降水季节性变异系数、气温年变化幅度、年降水量和海拔(累计贡献>70%)。适宜岷江冷杉潜在分布的环境条件是气温...     

气候变化下毛榛在中国的潜在适生区预测

气候变化影响着植物物种的地理分布,研究气候变化对物种地理分布格局的影响对物种的保护和合理利用具有重要意义。本研究通过ENMeval数据包调整特征组合和调控倍率参数来优化MaxEnt模型,利用221条毛榛有效分布点数据和16个环境因子,模拟预测毛榛在当前气候和未来(2050s、2070s)气候条件下的潜在分布区,并分析影响毛榛地理分布的主导环境因子。结果表明:当特征组合为LQPH、调控倍率为1.5时,模型复杂度和过拟合程度较低,预测结果准确性较高。当前气候条件下,毛榛高度适生区主要集中于长白山、太行山、秦巴山区及甘肃南部等地区;未来不同气候情景下,陕西中北部、中国西南地区、甘肃南部等地区毛榛的适生区逐渐减少,内蒙古东部与黑龙江等地区开始出现较多的毛榛高度适生区,毛榛适生区的质心有向东北方向迁移的趋势;影响毛榛地理分布的主导环境因子为年降水量、最干季均温、海拔和年均温,累计贡献率达78.8%,其适宜范围分别为430～970 mm、-21～3℃、40～2800 m和0.8～13℃。     

北重楼潜在适生区对气候变化的响应及其主导气候因子

基于现有物种数据结合气候变量来预测物种的潜在地理分布,对于了解物种进化以及合理保护具有重要意义。本研究基于中国境内220个北重楼分布点和12个相关系数较低的气候因子,利用MaxEnt模型和ArcGIS软件预测了北重楼在当前时期和未来时期(2050s、2070s)的潜在适生区,并分析了影响其地理分布的主导气候因子。结果表明: MaxEnt模型AUC值为0.940,预测结果准确性较高;当前时期,北重楼的总适生区面积占整个研究区域面积的18.1%,其中,高适生区和低适生区分别占7.0%和11.1%,主要位于大兴安岭、小兴安岭、长白山山脉、秦岭-大巴山区、河北、山西以及山东北部等地区;未来时期在RCP 2.6、RCP 4.5、RCP 6.0、RCP 8.5气候情景下,2050s和2070s中国境内北重楼的总适生区面积均呈现缩减趋势,其中,高适生区面积均减少,而低适生区面积则全部有所增加,且北重楼适生区的范围和几何中心逐渐向东北方向的高海拔地区扩散;影响北重楼地理分布的主导气候因子分别为最湿月降水量、年平均温度、等温性和1月降水量,累积贡献率高达89.2%,其适宜范围分别为100～275 mm、-0.1～16 ℃、21～35和3～14 mm。     

Effect of climate change in lizards of the genus Xenosaurus (Xenosauridae) based on projected changes in climatic suitability and climatic niche conservatism

Accelerated climate change represents a major threat to the health of the planet's biodiversity. Particularly, lizards of the genus Xenosaurus might be negatively affected by this phenomenon because several of its species have restricted distributions, low vagility, and preference for low temperatures. No study, however, has examined the climatic niche of the species of this genus and how their distribution might be influenced by different climate change scenarios. In this project, we used a maximum entropy approach to model the climatic niche of 10 species of the genus Xenosaurus under present and future suitable habitat, considering a climatic niche conservatism context. Therefore, we performed a similarity analysis of the climatic niche between each species of the genus Xenosaurus. Our results suggest that a substantial decrease in suitable habitat for all species will occur by 2070. Among the most affected species, X. tzacualtipantecus will not have suitable conditions according to its climatic niche requirements and X. phalaroanthereon will lose 85.75% of its current suitable area. On the other hand, we found low values of conservatism of the climatic niche among species. Given the limited capacity of dispersion and the habitat specificity of these lizards, it seems unlikely that fast changes would occur in the distribution of these species facing climate change. The low conservatism in climatic niche we found in Xenosaurus suggests that these species might have the capacity to adapt to the new environmental conditions originated by climate change.     

Habitat distribution modeling of endangered medicinal plant Picrorhiza kurroa (Royle ex Benth) under climate change scenarios in Uttarakhand Himalaya,India

Climate change has been the key factor in changing the alpine vegetation's habitat and causing it to migrate to higher latitudes. The present study aims to model the current and future potential habitat distribution of endangered medicinal plant Picrorhiza kurroa Royle ex Benth in Uttarakhand Himalaya using the maximum entropy (MaxEnt) modeling. We initially select twenty-two environmental variables (bioclimatic + topographic) got from the Fifty-four (54) species occurrence points, which were further reduced to nine variables to prevent multicollinearity. Shared Socioeconomic Pathways (SSP1–2.6 and SSP2–4.5) from the CMIP6 (BCC-CSM2-MR) climate model for the periods 2041–60 and 2061–80 were used to predict the current and future habitat distribution of P. kurroa. Results showed that the precipitation of the driest month (Bio 14; 33.8%), isothermality (Bio 3; 20.2%), mean temperature of warmest quarter (Bio 10; 12.7%), and temperature annual range (Bio 7; 12.2%) were the important bioclimatic variables influencing the habitat of P. kurroa. Overall, there is a decrease in the habitat of P. kurroa under climate change scenarios. The present results may prove insightful for the decision-makers to identify suitable sites in the wild for the further propagation of P. kurroa.     

Shifts in potential geographical distribution of Pterocarya stenoptera under climate change scenarios in China

Climate change poses a serious threat to biodiversity. Predicting the effects of climate change on the distribution of a species' habitat can help humans address the potential threats which may change the scope and distribution of species. Pterocarya stenoptera is a common fast‐growing tree species often used in the ecological restoration of riverbanks and alpine forests in central and eastern China. Until now, the characteristics of the distribution of this species' habitat are poorly known as are the environmental factors that influence its preferred habitat. In the present study, the Maximum Entropy Modeling (Maxent) algorithm and the Genetic Algorithm for Ruleset Production (GARP) were used to establish the models for the potential distribution of this species by selecting 236 sites with known occurrences and 14 environmental variables. The results indicate that both models have good predictive power. Minimum temperature of coldest month (Bio6), mean temperature of warmest quarter (Bio10), annual precipitation (Bio12), and precipitation of driest month (Bio14) were important environmental variables influencing the prediction of the Maxent model. According to the models, the temperate and subtropical regions of eastern China had high environmental suitability for this species, where the species had been recorded. Under each climate change scenario, climatic suitability of the existing range of this species increased, and its climatic niche expanded geographically to the north and higher elevation. GARP predicted a more conservative expansion. The projected spatial and temporal patterns of P. stenoptera can provide reference for the development of forest management and protection strategies.     

Ensemble modeling approach to predict the past and future climate suitability for two mangrove species along the coastal wetlands of peninsular India

Mangroves support numerous ecosystem services and help in reducing coastal ecological risks, yet they are declining rapidly due to climate change, sea level fluctuations and human activities. It is important to understand their responses to climate and sea level changes and identify conservation target areas at spatio-temporal scales, specifically in regions of rich mangrove biodiversity. In this study, we predicted the potential impact of past (Middle Holocene, ∼6000 years), current and future (2050s, 2070s; RCP 2.6 and RCP 8.5) climate change scenarios on the two dominant species in the coastal mangrove forest wetlands of India, i.e., Rhizophora mucronata and Avicennia officinalis through an ensemble species distribution modeling approach. The ensemble modeling has been carried out by integrating eight single algorithm methods. Based on the receiver operating characteristics of area under the curve (AUC) and true skill statistics (TSS) values the ensemble modeling has yielded the highest predictive performance for SVM for both the species and lowest by CART for R. mucronata and BIOCLIM for A. officinalis. The internal evaluation metrics of the resulting Species distribution models (SDMs) tested its robustness with AUC-0.97 and TSS-0.89 for A. officinalis and AUC-0.99 and TSS-0.90 for R. mucronata. Precipitation of Wettest Month (Bio 13) and Mean Temperature of Warmest Quarter (Bio 10) was the most important variable (54–67%) for the distribution of A. officinalis and Precipitation Seasonality (Bio 15) and Precipitation of Warmest Quarter (Bio 18) for R. mucronata. High precipitation and sea-level highstand during middle Holocene led to the maximum range expansion of suitable habitat for the mangrove species which is also validated in the present study by the fossil pollen datasets. Total mangrove habitat in current and future climatic scenarios decreased in 2.6 and 8.5 Representative Concentration Pathways (RCPs) for 2050 and 2070 which indicates the vulnerability of the species to climate change impacts. Mangrove species are projected to shift their ranges more towards land in future experiencing a decrease in the amount of suitable coastal area available to them throughout the Indian coastline. The plausible cause for this range shift may be due to higher precipitation that is usually associated with longer period of soil inundation and because of the rise in sea level. Our findings will assist in formulating species-specific restoration plans for these keystone species in context of climate change in the Indian Subcontinent.     

气候变化情景下外来入侵植物刺苍耳在新疆的潜在分布格局模拟

明确区域尺度上外来入侵种的潜在分布格局及其对气候变化的响应对入侵种的预防和控制具有重要意义。以外来入侵植物刺苍耳(Xanthium spinosum L.)为研究对象,以其扩散蔓延的新疆地区为研究区域,结合中国国家气候中心开发的BCC—CSM1—1模式下的将来气候条件,应用MaxEnt模型和ArcGIS空间分析技术构建了未来不同气候变化情景(RCP4.5,8.5)下2050s和2070s的刺苍耳适宜生境预测模型,定量的展示了气候变化情景下刺苍耳在新疆的扩散趋势及其适宜生境的面积空间变化和分布区中心移动轨迹。结果表明:年降雨量、下层土壤有机碳含量、上层土壤pH值、年温度变化范围、降雨量的季节性变化和年平均温度是影响刺苍耳地理分布的主导环境因子;博州、塔城、阿勒泰西北部、哈密中部、巴州北部、克州中部、阿克苏北部、奎屯市、克拉玛依市、五家渠市、喀什市等地为高危入侵风险区;两种气候模式下刺苍耳的各级适生区面积和总适生面积均呈持续增加的变化趋势,且在RCP8.5情景(最高温室气体排放情景)下响应更为敏感;总体上看,刺苍耳在新疆的分布未达到饱和,呈现以塔城中部为中心,向天山北麓和塔克拉玛干北缘方向辐射状扩散,且两种气候变化情景下至2070s分布区中心均向伊犁州奎屯方向移动。     

A MaxEnt modelling approach to understand the climate change effects on the distributional range of White-bellied Sholakili Sholicola albiventris (Blanford, 1868) in the Western Ghats,India

Each species is uniquely influenced by anthropogenic climate change. Change in temperature and precipitation due to climate change may lead to species adaptation or extinction, or in some cases, a range shift. To know the influence of climate change on a restricted and endemic bird species of the Western Ghats (WG), White-bellied Sholakili (WBS) Sholicola albiventris (Blanford, 1868), we conducted a study by using species distribution modelling. We considered 73 spatial bias-corrected occurrence points of WBS along with environmental variables like the mean temperature of coldest quarter (Bio 11), precipitation of driest month (Bio 14) and mean precipitation of warmest quarter (Bio 18). We used the MaxEnt application with ENM evaluate tool in R statistical package for developing a climate model for WBS. Bio 11 was observed to be the most crucial climate variable shaping the habitat of WBS. The current study predicts that only 2823km² in WG is suitable for WBS. One-third of this area falls under the protected area network, of which 52% is becoming unsuitable to this narrow endemic due to climate warming. The model also predicts 26% to 45% habitat loss under different climate change scenarios by the 2050s.     

气候变化下耐旱藓类连轴藓属在新疆的分布模拟

该研究基于耐旱藓类连轴藓属5种53条在新疆的地理分布信息和7个气候变量,利用最大熵模型和ArcGIS 10.2软件,分别模拟现代气候和未来气候情景下连轴藓属在新疆的适生分布区,为探讨气候变化对干旱、半干旱区苔藓植物物种分布的影响提供参考。结果表明:(1)Maxent模型预测连轴藓属在新疆适生区的准确性非常高(AUC=0.957)。(2)年降雨量、最干季度降雨量和最暖季度平均气温是影响连轴藓属分布的主要气候因子。(3)连轴藓属在新疆的适生区主要集中在阿尔泰山和天山沿线,在未来(2061~2080年)气候情景下,连轴藓属分布面积将比现代气候下减少10.39%,其绝大部分现有南部适生区将丧失。     

Predicting the distributions of Pouteria adolfi-friederici and Prunus africana tree species under current and future climate change scenarios in Ethiopia

Distributions of potential ranges of plant species are not yet fully known in Ethiopia where high climatic variability and vegetation types are found. This study was undertaken to predict distributions of suitable habitats of Pouteria adolfi-friederici and Prunus africana under current and two future climate scenarios (RCP 4.5 and RCP 8.5 in 2050 and 2070) in Ethiopia. Eleven environmental variables with less correlation coefficients (r < 0.7) were used to make the prediction. Shifting in extents of habitat suitability and effects of elevation, solar radiation and topographic position in relation to the current and future climatic scenarios were statistically analysed using independent t-test and linear model. We found decreasing area of highly suitable habitat from 0.51% to 0.46%, 0.36% and 0.33%, 0.24% for Prunus africana and 1.13% to 1.02%, 0.77% and 0.76%, 0.60% for Pouteria adolfi-friederici, under RCP 4.5 and RCP 8.5 by 2050 and 2070 respectively. Moist and dry afromontane forests are identified as the most suitable habitat for both species. Overall, our results suggest that climate change can promote dynamic suitable habitat niches under different future climate scenarios. Therefore, biodiversity conservation strategies should take into account habitat suitability dynamics issues and identify where to conserve species before implementing conservation practices.