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| 1 | 基于新型最大熵模型预测刺槐叶瘿蚊(双翅目:瘿蚊科)在中国的适生区显示文摘【目的】基于对刺槐叶瘿蚊在全国的普查情况,利用最大熵模型MaxEnt软件的互补双对数输出方式对刺槐叶瘿蚊在中国当前和未来(2050年)的适生区进行预测,为林业和海关检疫部门对刺槐叶瘿蚊当前与未来的防控与检疫工作提供重要参考依据。【方法】使用MaxEnt、ArcGIS、R软件对刺槐叶瘿蚊危害点,气候图层,模型参数这3方面进行科学的优化选择,确保模型的科学性、有效性。当前气候适生区的预测使用WorldClim网站全球气候数据Version 1.4,未来数据则采用通用气候系统模型CCSM4下3种外排情景(RCP26、RCP45、RCP85)。【结果】最终确定52个危害点,7个主导气候图层,运用互补双对数输出方式对适生区进行预测。模拟结果的测试遗漏率与理论遗漏率基本吻合,ROC曲线即AUC值为0.919,标准差为0.023,表明所使用的数据无空间自相关,构建的模型达到'极好'的标准。通过刀切图分析,对刺槐叶瘿蚊分布影响最大的3个气候图层分别为Bio1(年平均气温)、Bio12(年降水量)、Bio5(最热月的最高温度)。对当前气候刺槐叶瘿蚊适生区进行划分,刺槐叶瘿蚊在中国的适生范围为22.08°—48.42°N,39.39°—135.06°E,达国土面积的31.90%。除西藏、青海、海南、台湾4省区外,其余省份均包含其适生区,其高度适生区以西南(四川、重庆)和华北(北京、天津、河北、山东、陕西)为主。对未来(2050年)适生区的预测,3种外排情景RCP26、RCP45、RCP85的总适生区均比当前气候的总适生范围大,以高度、中度适生区面积的增大为主,新疆和我国北部区域面积显著扩增。RCP85情景下的刺槐叶瘿蚊适生区面积最大,达国土面积的39.71%,比当前预测的多出75万km^2。【结论】结合实际调查情况,新型MaxEnt模型预测结果可信度高,阐明影响刺槐叶瘿蚊分布的主导气候因子,预测出刺槐叶瘿蚊当前与未来的分布范围及适生程度情况,对刺槐叶瘿蚊的防控具有重要意义。 | 赵佳强 石娟 | 2019 | 林业科学2019，55，2： | 23 |
| 2 | 孑遗植物长苞铁杉(Tsuga longibracteata)分布格局对未来气候变化的响应显示文摘长苞铁杉(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。 | 谭雪 张林 张爱平 王毅 黄丹 伍小刚 孙晓铭 熊勤犁 潘开文 | 2018 | 生态学报2018，38，24： | 16 |
| 3 | 滇黄精的潜在分布与气候适宜性分析显示文摘为了解滇黄精(Polygonatum kingianum)的适宜生长区,运用Maxent模型模拟其潜在分布区,探讨其引种栽培的适宜气候条件。结果表明,预测模型的AUC值为0.974~0.980,表明模型具有良好的预测能力。滇黄精主要适生区位于我国西南地区,适生面积约81.34×10~4 km^2,占全国适生区面积的88.24%。云南的高度适生区面积最大(19.96×10~4 km^2);四川次之(5.49×10~4 km^2)。75%的高度适生区分布于海拔2 492 m以下的地区,3 400 m以上的地区不适宜于滇黄精生长。最冷月最低温度、7月最低温度、5-8月太阳辐射、最干月降水量、4月和9-11月平均降水量是限制滇黄精分布的主要气候变量。因此,海拔1 400~2 100 m的亚热带地区是滇黄精最适宜的生长区。 | 姚馨 张金渝 万清清 李云蓉 沈涛 | 2018 | 热带亚热带植物学报2018，26，5： | 12 |
| 4 | Geoclimatic factors influence the population genetic connectivity of Incarvillea arguta(Bignoniaceae)in the Himalaya-Hengduan Mountains biodiversity hotspot显示文摘Geoclimatic factors related to the uplift of the Himalaya and the Quaternary climatic oscillations in fluence the population genetic connectivity in the Himalaya-Hengduan Mountains(HHM)biodiversity hotspot.Therefore,to explore the relative roles played by these two factors,we examined the population dynamics and dispersal corridors of Incarvillea arguta(Royle)Royle incorporating ensemble species distribution modelling(SDM).Thirty-seven populations were genotyped using plastid chloroplast DNA and low copy nuclear gene(ncpCS)sequences.Phylogeographic analysis was carried out to reveal the genetic structure and lineage differentiation.Ensemble SDMs were carried out for distributional change in the last glacial maximum,present,and future.Finally,the least cost path method was used to trace out possible dispersal corridors.The haplotypes were divided into four clades with strong geographical structure.The late Miocene origin of I.arguta in the western Himalaya ca.7.92 Ma indicates lineage diversification related to the uplift of the HHM.The variability in habitat connectivity revealed by SDM is due to change in suitability since the Pleistocene.A putative dispersal corridor was detected along the drainage systems and river valleys,with strong support in the eastern Hengduan Mountains group.Our results support the signature of geoclimatic influence on population genetic connectivity of I.arguta in the HHM.We proposed that the major drainage systems might have assisted the rapid dispersal of isolated riverine plant species I.arguta in the HHM.The population genetic connectivity,using the fine-tuned ensemble SDMs,enables scientists and policymakers to develop conservation strategies for the species gene pool in the HHM biodiversity hotspots. | Santosh Kumar Rana Dong Luo Hum Kala Rana Alexander Robert O'Neill Hang Sun | 2021 | Journal of Systematics and Evolution2021，59，1： | 3 |
| 5 | Determining bioclimatic space of Himalayan alder for agroforestry systems in Nepal显示文摘Himalayan alder species are proven to be very useful in traditional as well as contemporary agroforestry practice. These nitrogen-fixing trees are also useful in the land restoration. Therefore, understanding the distribution of Himalayan alder and the potential zone for plantation is meaningful in the agroforestry sector. Suitable climatic zones of Alnus spp. were modelled in Max Ent software using a subset of least correlated bioclimatic variables for current conditions(1950 -2000), topographic variables(DEM derived) and Landuse Landcover(LULC) data. We generated several models and selected the best model against random models using ANOVA and t-test. The environmental variables that best explained the current distribution of the species were identified and used to project into the future. For future projections, ensemble scenarios of climate change projection derived from the results of 19 Earth System Models(ESM) were used. Our model revealed that the most favorable conditions for Alnus nepalensis are in central Nepal in the moist north-west facing slope, whereas for Alnus nitida they are in western Nepal.The major climatic factor that contributes to Alnus species distribution in Nepal appears to be precipitation during the warmest quarter for A. nepalensis and precipitation during the driest quarter for A. nitida. Future projections revealed changes in the probability distribution of these species, as well as where they need conservation and where they can be planted. Also, our model predicts that the distribution of Alnus spp. in hilly regions will remain unchanged, and therefore may represent sites that can be used to revitalize traditional agroforestry systems and extract source material for land restoration. | Santosh Kumar Rana Hum Kala Rana Krishna Kumar Shrestha Suresh Sujakhu Sailesh Ranjitkar | 2018 | Plant Diversity2018，40，1： | 1 |
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