Prediction of Potential Geological Distribution of Asarum in China by Maxent Model

Genus Asarum contains several plant species that are mostly used as precious drug resources. In this study, 126 distribution records of 3 Asarum species and relevant 28 environmental factors data were collected, then a geographical distribution model of the genus medicinal plants in China was made by Maxent and the ArcGIS spatial analysis technique. The results showed that the 3 Asarum species have a wide potential distribution region. High suitable region and suitable region were 3125km2 and 276042km2 respectively. Among the environmental factors, 3 precipitation factors (annual precipitation, precipitations in the most dry season and the most warm season) are the main ones that can affect the distribution of the 3 Asarum medicinal plants. This study can provide a useful reference for the collection and cultivation of Asarum medicinal plants.     

山西翅果油树的适生区预测及其对气候变化的响应

研究濒危物种生境在气候变化下的响应对保护物种多样性和保持生态系统功能完整性具有重要意义.本文选取我国特有濒危植物翅果油树为研究对象,以该物种73个野外调查数据和35个环境因子为基础,应用最大熵模型对山西翅果油树当前的适生分布区进行预测;进而结合政府间气候变化专门委员会第五次评估报告发布的气候模式数据,探讨未来不同气候情景下山西翅果油树分布格局的变化趋势.结果表明:受试者工作特征曲线分析法的AUC值为0.987,表明模型的模拟精度很好且预测可靠性高;刀切法检验结果显示,降水量季节变化、温度年变化范围、年均温、等温线、表层土p H值和年降水量是影响翅果油树分布的主要环境因子,其累积贡献率达到了94.8%;当前,山西翅果油树的适生区主要集中在山西省吕梁山南部和中条山地带;未来不同气候情景下,到21世纪70年代翅果油树适生区面积均有不同幅度的缩减,低浓度情景(RCP 2.6)下呈先增后减趋势,中高浓度情景(RCP 4.5和RCP8.5)下响应较敏感且呈先减后增趋势.两个不同适生区的空间分布格局对气候变化也有不同的响应,吕梁山南部表现出纬度方向的轻微波动,而中条山地带则是海拔方向的迁移.     

基于MaxEnt模型的道路对朱鹮繁殖地的影响

道路对野生动物适宜繁殖地影响的定量研究是目前道路生态学领域有待深入的内容之一.本文以国家一级保护动物朱鹮为研究对象,利用物种分布模型(SDM)中MaxEnt模型,通过对影响朱鹮繁殖地的环境变量进行自相关分析,剔除自相关系数大于0.8的环境变量,最终选择了10个环境变量为朱鹮繁殖地的影响因子,分别为最冷季度平均气温、景观类型、归一化植被指数、坡度、坡向、距水体距离、距水田距离、距高等级公路(县级及以上道路)距离、距低等级公路(乡镇和林间道路)距离、距居住地距离.通过对环境变量的贡献率进行分析表明: 最冷季度平均气温、景观类型以及距水田距离、距高等级公路距离是影响朱鹮筑巢的主要因子.分别研究了含道路变量(情景Ⅰ)、不含高等级公路(情景Ⅱ)以及不含低等级公路(情景Ⅲ)3种情景下朱鹮繁殖地适宜区分布.结果表明:道路对朱鹮繁殖地干扰影响显著,高等级公路的影响比低等级公路大,高等级公路和低等级公路的存在分别使朱鹮繁殖地适宜区的面积减小了66.23和35.69 km².朱鹮筑巢对高等级公路有明显的回避效应,平均回避距离为1500 m.本研究对未来制定朱鹮的保护管理措施具有重要意义,同时可为工程建设项目对野生动物的环境影响定量评价提供应用示范.     

Using niche modelling and human influence index to indicate conservation priorities for Atlantic forest deer species

To prioritise conservation actions and management strategies for threatened forest deer species at the Atlantic forest, we aimed to identify and describe the most suitable habitat areas for forest deer species and to indicate conservation measures for state agents and local communities. We adopt an approach based on ecological niche modelling, key variable thresholds and spatial analyses. In addition, we associated our approach with a human influence index, an invasive species dataset of occurrences, protected area cover and IUCN category. We indicate 2 % (484 km²) of the Atlantic forest cover as conservation priority areas (CPAs). Of these, 56.8 % are outside protected areas, 20.7 % are inside IUCN categories i, ii and iii protected areas, 19.9 % are inside IUCN categories iv, v, and vi protected areas, and 2.6 % are inside indigenous areas. Also, we indicate the most relevant protected areas for deer conservation in the Atlantic forest. The CPAs were classified into more human-influenced areas (MHIA) and less human-influenced areas (LHIA), and we identified 21 significant (greater than120 km²) continuous CPAs outside protected areas. We highlight actions in several perspectives of human influence, governance levels and law protection that would rationalise the use of funds and human resources.     

Maxent modeling for predicting the potential distribution of Sanghuang,an important group of medicinal fungi in China

The ability to identify the spatial distribution of economically important fungal species is crucial for understanding the environmental factors that affect them and for conservation management. A potentially valuable approach for this is maximum entropy (Maxent) spatial distribution modeling, which was applied here to map the potential distribution of three “Sanghuang” mushrooms in China, which include Phellinus baumii, Phellinus igniarius and Phellinus vaninii. Nineteen WorldClim bioclimatic variables, with corresponding altitude data, and 89 spatially well-dispersed species occurrence records were used in the modeling. The relative importance of the environmental variables was evaluated by Jackknife tests in the modeling analysis. The maximum entropy models obtained have high Area Under Receiver Operating Characteristic Curve (AUC) values: 0.956, 0.967 and 0.960, for P. baumii, P. igniarius and P. vaninii, respectively. The bioclimatic variable that most strongly affected distributions of P. baumii and P. vaninii was precipitation in the warmest quarter, while the mean temperature in the warmest quarter affected the distribution of P. igniarius most strongly. Overall, these models could provide valuable help in searching for the target species in areas where it is hitherto unknown, and be the reference of conservation measures for these medicinal fungal species.     

Projected changes in climatic suitability for Kinosternon turtles by 2050 and 2070

Chelonians are expected to be negatively impacted by climate change due to limited vagility and temperature‐dependent sex determination. However, few studies have examined how freshwater turtle distributions may shift under different climate change scenarios. We used a maximum entropy approach to model the distribution of five widespread North American Kinosternon species (K. baurii, K. flavescens, K. hirtipes, K. sonoriense, and K. subrubrum) under four climate change scenarios. We found that areas with suitable climatic conditions for K. baurii and K. hirtipes are expected to decline substantially during the 21st century. In contrast, the area with suitable climate for K. sonoriense will remain essentially unchanged, while areas suitable for K. flavescens and K. subrubrum are expected to substantially increase. The centroid for the distribution of four of the five species shifted northward, while the centroid for K. sonoriense shifted slightly southward. Overall, centroids shifted at a median rate of 37.5 km per decade across all scenarios. Given the limited dispersal ability of turtles, it appears unlikely that range shifts will occur rapidly enough to keep pace with climate change during the 21st century. The ability of chelonians to modify behavioral and physiological responses in response to unfavorable conditions may allow turtles to persist for a time in areas that have become increasingly unsuitable, but this plasticity will likely only delay local extinctions.     

未来气候变化对广布种麻栎地理分布的影响和主导气候因子分析

为了解麻栎（Quercus acutissima）的潜在分布特征及其对未来气候的响应,运用最大熵模型（Maxent）模拟在当前气候条件下麻栎的潜在分布格局,预测未来不同温室气体排放情景下的格局变化,并分析影响其分布的主导因子。结果表明,Maxent模型有较好的预测能力,AUC值大于0.95。当前气候条件下,麻栎广泛分布于我国南方大部分地区和陕西、河南、山西、甘肃、北京、辽宁等北方省市。此外,在日本、朝鲜半岛、老挝、越南、缅甸、尼泊尔、不丹、印度、巴基斯坦等国家和地区亦存在不同程度和范围的麻栎适生区域,麻栎总适生区域面积达11.57×10⁵km²。在RCP2.6和RCP8.5情景下,麻栎适宜分布区域向北和西南方向扩展,新增适生区面积为（2.49~3.02）×10⁵km²;适生区域丧失主要集中在广西南部、广东南部和缅甸东部等地。影响其分布的主导气候因子为最暖季降水量、等温性、最干季均温、最冷月最低温,因子贡献率分别为54.2%、13.7%、8.8%和7.8%。这为麻栎的栽培和保育研究提供了参考依据。     

东方白鹳在山东省适宜栖息地的分布预测

东方白鹳(Ciconia boyciana)隶属鹳形目(Ciconiiformes)鹳科(Cioniidae)鹳属(Ciconia),被IUCN濒危物种红色名录列为濒危(EN),主要繁殖于俄罗斯远东地区与中国东北三江平原,在长江中下游鄱阳湖等沿海内陆湖泊越冬。山东省从2003年开始有东方白鹳繁殖记录,黄河三角洲为该物种在山东省的主要繁殖地。以在黄河三角洲自然保护区收集到的位点数据、物种分布数据库(GBIF)提取的位点数据和山东省环境气候因子为基础数据,基于最大熵(Maxent)模型和地理信息系统(ArcGIS)技术平台,预测东方白鹳在山东省的潜在适生区。结果表明在该物种在黄河三角洲及附近地区存在较集中的高适宜区,庙岛群岛和微山湖地区存在少量高适宜区,高适宜区总面积为1359.27km²;北至河北边界,南至微山县,沿黄河支流至西到达聊城市、菏泽市,存在1893.82km²较适宜区和3955.63km²低适宜区。潜在适宜生境总和为7208.72km²,占比为研究区域的0.89%。新出现的较为集中的较适宜...     

A comparison of methods for mapping species ranges and species richness

Aim  Maps of species richness are the basis for applied research and conservation planning as well as for theoretical research investigating patterns of richness and the processes shaping these patterns. The method used to create a richness map could influence the results of such studies, but differences between these methods have been insufficiently evaluated. We investigate how different methods of mapping species ranges can influence patterns of richness, at three spatial resolutions.
Location  California, USA.
Methods  We created richness maps by overlaying individual species range maps for terrestrial amphibians and reptiles. The methods we used to create ranges included: point-to-grid maps, obtained by overlaying point observations of species occurrences with a grid and determining presence or absence for each cell; expert-drawn maps; and maps obtained through species distribution modelling. We also used a hybrid method that incorporated data from all three methods. We assessed the correlation and similarity of the spatial patterns of richness maps created with each of these four methods at three different resolutions.
Results  Richness maps created with different methods were more correlated at lower spatial resolutions than at higher resolutions. At all resolutions, point-to-grid richness maps estimated the lowest species richness and those derived from species distribution models the highest. Expert-drawn maps and hybrid maps showed intermediate levels of richness but had different spatial patterns of species richness from those derived with the other methods.
Main conclusions  Even in relatively well-studied areas such as California, different data sources can lead to rather dissimilar maps of species richness. Evaluating the strengths and weaknesses of different methods for creating a richness map can provide guidance for selecting the approach that is most appropriate for a given application and region.