基于生态位模型预测野生油茶的潜在分布

油茶(Camellia oleifera)是我国第一大木本油料作物, 野生油茶是油茶育种的宝贵遗传资源。本研究从中国数字植物标本馆(CVH, http://www.cvh.org.cn/)获得可靠的野生油茶分布点数据, 结合气象和土壤数据, 分别应用最大熵(MaxEnt)模型和规则集遗传算法(GARP)模型构建了野生油茶的生态位模型, 预测了野生油茶的潜在分布区, 并分析了影响野生油茶分布的主要环境变量。根据生态位模型预测的分布概率值, 对野生油茶的潜在分布区划分适生等级, 并与主要油茶产地的实际分布数据进行比较, 以验证适生等级划分的可靠性。结果表明, 两种模型的预测结果均能较好地反映油茶的分布情况。GARP模型预测的潜在分布区更广, 而MaxEnt模型的预测结果更精确。两种模型的预测结果均显示, 野生油茶的潜在分布区大部分位于中国, 但在中南半岛也有部分分布。MaxEnt模型预测的野生油茶在中国的潜在分布区与我国亚热带常绿阔叶林的分布区基本吻合, 高适生区主要可以分为3大区域: (1)东北-西南走向的武夷山脉及附近的群山区域; (2)东西走向的南岭山脉及附近的群山区域; (3)东北-西南走向的武陵山脉及附近的群山区域。MaxEnt模型分析显示, 影响野生油茶分布的主要环境变量是昼夜温差月均值、最干季降水量与最暖季降水量。油茶生长面积较大的地区绝大部分都位于MaxEnt模型预测的中、高适生区, 说明适生等级的划分较可靠。实地考察显示, 生态位模型的预测结果对于寻找野生油茶资源具有较高的参考价值。此外, 本研究也充分显示, 利用中国数字植物标本馆的植物分布数据, 结合相应的环境数据构建生态位模型, 有助于了解作物野生近缘种的地理分布。     

Predicting the Distribution Pattern of Small Carnivores in Response to Environmental Factors in the Western Ghats

Due to their secretive habits, predicting the pattern of spatial distribution of small carnivores has been typically challenging, yet for conservation management it is essential to understand the association between this group of animals and environmental factors. We applied maximum entropy modeling (MaxEnt) to build distribution models and identify environmental predictors including bioclimatic variables, forest and land cover type, topography, vegetation index and anthropogenic variables for six small carnivore species in Mudumalai Tiger Reserve. Species occurrence records were collated from camera-traps and vehicle transects during the years 2010 and 2011. We used the average training gain from forty model runs for each species to select the best set of predictors. The area under the curve (AUC) of the receiver operating characteristic plot (ROC) ranged from 0.81 to 0.93 for the training data and 0.72 to 0.87 for the test data. In habitat models for F. chaus, P. hermaphroditus, and H. smithii “distance to village” and precipitation of the warmest quarter emerged as some of the most important variables. “Distance to village” and aspect were important for V. indica while “distance to village” and precipitation of the coldest quarter were significant for H. vitticollis. “Distance to village”, precipitation of the warmest quarter and land cover were influential variables in the distribution of H. edwardsii. The map of predicted probabilities of occurrence showed potentially suitable habitats accounting for 46 km² of the reserve for F. chaus, 62 km² for V. indica, 30 km² for P. hermaphroditus, 63 km² for H. vitticollis, 45 km² for H. smithii and 28 km² for H. edwardsii. Habitat heterogeneity driven by the east-west climatic gradient was correlated with the spatial distribution of small carnivores. This study exemplifies the usefulness of modeling small carnivore distribution to prioritize and direct conservation planning for habitat specialists in southern India.     

落叶松枯梢病在中国的适生性

落叶松枯梢病(Neofusicoccum laricinum)是威胁落叶松人工林的检疫性林木病害。明确当前该病在中国的潜在适生区及其在未来对气候变化的响应,揭示影响该病害发生流行的主导环境变量,对落叶松枯梢病的早期预警及防治具有重要意义。基于落叶松枯梢病分布数据和环境数据,利用ENMTools、R和刀切法(Jack knife test)筛选分布点数据和环境因子,通过MaxEnt、ArcGIS、SDMTools等技术预测当前和未来气候条件下落叶松枯梢病在中国的潜在适生区,划分病害适生等级并计算各适生等级面积占比,绘制质心转移轨迹。结果表明:(1)建立的落叶松枯梢病在中国的潜在适生区预测模型具有高精确性和可信度(不同年份和不同气候模式下的AUC值均大于0.9);(2)影响落叶松枯梢病分布的主要环境变量为年平均气温、最暖季度降水量、年降水量和最暖季度平均温度;(3)当前气候模式下落叶松枯梢病在中国的潜在适生区面积占中国国土总面积的18.02%,中高适生区集中分布在中国辽宁东南部、吉林东部、黑龙江大部分地区、内蒙古东北部;(4)在三种不同气候条件下(ssp126、ssp245、ssp585),未来落叶松枯梢病在中国的潜在适生区面积与现代气候条件相比均有所减少,其质心由东北向华北、西南地区转移。落叶松枯梢病一旦发生将会造成不可逆的生态灾难和经济损失,因此本研究对落叶松枯梢病在中国的潜在适生区进行预测和分析,研究结果对合理区划落叶松枯梢病潜在入侵风险地、加强重点地区的检疫监测、及时制定有效的防治手段,以及对于发生区的监测和防治与未发生区的早期预警和监管具有重要意义。     

Modeling Potential Distribution of Oligoryzomys longicaudatus, the Andes Virus (Genus: Hantavirus) Reservoir, in Argentina

We constructed a model to predict the potential distribution of Oligoryzomys longicaudatus, the reservoir of Andes virus (Genus: Hantavirus), in Argentina. We developed an extensive database of occurrence records from published studies and our own surveys and compared two methods to model the probability of O. longicaudatus presence; logistic regression and MaxEnt algorithm. The environmental variables used were tree, grass and bare soil cover from MODIS imagery and, altitude and 19 bioclimatic variables from WorldClim database. The models performances were evaluated and compared both by threshold dependent and independent measures. The best models included tree and grass cover, mean diurnal temperature range, and precipitation of the warmest and coldest seasons. The potential distribution maps for O. longicaudatus predicted the highest occurrence probabilities along the Andes range, from 32°S and narrowing southwards. They also predicted high probabilities for the south-central area of Argentina, reaching the Atlantic coast. The Hantavirus Pulmonary Syndrome cases coincided with mean occurrence probabilities of 95 and 77% for logistic and MaxEnt models, respectively. HPS transmission zones in Argentine Patagonia matched the areas with the highest probability of presence. Therefore, colilargos presence probability may provide an approximate risk of transmission and act as an early tool to guide control and prevention plans.     

珍稀濒危植物野生莲的适生分布区预测

基于野生莲（Nelumbo nucifera Gaertn.）136个分布点的数据和14个环境因子参数,运用规则集遗传算法（GARP）和最大熵（MaxEnt）两个生态位模型对他们在我国的适生分布区进行预测。结果显示：根据GARP和MaxEnt模型计算得到的ROC曲线下面积的AUC均值分别为0.861和0.964,其中MaxEnt模型的AUC值更大,预测结果更精准。MaxEnt模型预测结果表明,莲的最适分布区主要集中在四川、湖北、湖南等地的大部分地区,江西北部,以及黑龙江、辽宁、浙江、广东等地的小部分地区。刀切法（Jackknife）检测结果表明,影响莲适生分布区的主要环境因子包括：水汽压、海拔、年平均气温、多年平均降水量、最热季节平均温度、最冷季节平均温度、最干月降水量、最冷月最低温和最热月最高温等。适生区环境因子的统计分析结果显示,野生莲最适宜生长在海拔1~2216 m、年降水量丰富（1202.50 mm）、年均温约为16.19℃、最热月温度范围在24.60℃~35.10℃、最冷月均温不低于-0.53℃的地区。研究结果可为有效保护中国野生莲资源提供有利依据。     

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.     

石山苣苔属的潜在适生区特征及其环境驱动变量

石山苣苔属(Petrocodon Hance)是著名的观赏花卉之一，但气候动荡和人类活动的强烈干扰，使其绝大部分被评估为极危(CR),至少也是易危(VU)以上。为重建末次间冰期以来石山苣苔属潜在适生区的时空变化，探讨适生区对环境变化的响应关系，为石山苣苔属的起源、地理分化研究和中国特有种质资源保护、园林开发利用提供理论指导，该研究结合120个分布记录和17个环境变量，应用优化的MaxEnt模型和地理信息技术(ArcGIS)对石山苣苔属在中国及中南半岛的适生区及其分布格局进行模拟，并基于逐步多元线性回归分析、冗余分析和蒙特卡洛检验评估影响石山苣苔属当前地理分布的主导变量。结果表明：(1)优化的MaxEnt模型的预测精度高，AUC值大于0.96;石山苣苔属当前适生区从中国西南部连续分布至越南北部，零散分布于中国中部和南部、块状分布于缅甸北部，其中以中国云贵高原南部为最佳适生区。(2)制约石山苣苔属当前地理分布的主导环境变量为最干月降雨量(bio14)、最热季度平均降雨量(bio18)、最湿季降雨量(bio16)、温度变化方差(bio4)、最冷月最低温度(bio6)、海拔(alt)。(3)在...     

Environmental factors contributing to the spread of H5N1 avian influenza in mainland China

Background

Since late 2003, highly pathogenic avian influenza (HPAI) outbreaks caused by infection with H5N1 virus has led to the deaths of millions of poultry and more than 10 thousands of wild birds, and as of 18-March 2008, at least 373 laboratory-confirmed human infections with 236 fatalities, have occurred. The unrestrained worldwide spread of this disease has caused great anxiety about the potential of another global pandemic. However, the effect of environmental factors influencing the spread of HPAI H5N1 virus is unclear.

Methodology/Principal Findings

A database including incident dates and locations was developed for 128 confirmed HPAI H5N1 outbreaks in poultry and wild birds, as well as 21 human cases in mainland China during 2004–2006. These data, together with information on wild bird migration, poultry densities, and environmental variables (water bodies, wetlands, transportation routes, main cities, precipitation and elevation), were integrated into a Geographical Information System (GIS). A case-control design was used to identify the environmental factors associated with the incidence of the disease. Multivariate logistic regression analysis indicated that minimal distance to the nearest national highway, annual precipitation and the interaction between minimal distance to the nearest lake and wetland, were important predictive environmental variables for the risk of HPAI. A risk map was constructed based on these factors.

Conclusions/Significance

Our study indicates that environmental factors contribute to the spread of the disease. The risk map can be used to target countermeasures to stop further spread of the HPAI H5N1 at its source.     

野生食用菌“苇菇”的物种多样性及中华美味蘑菇适生区预测

“苇菇”是主产于新疆的野生食用菌,主要分布于我国西北内陆湖泊周边的芦苇或多枝柽柳林内,埋生或半埋生在土壤中。本研究共采集和收集相关标本91份,开展了形态学和分子系统学研究,结果表明这些宏观形态特征相似的“苇菇”标本并非一个物种,而是分属于蘑菇属Bivelares组的大肥蘑菇Agaricus bitorquis、中华美味蘑菇A. sinodeliciosus和亚托柄蘑菇A. subperonatus;及Nigrobrunnescentes组的帕达纳蘑菇A. padanus。本文对“苇菇”形态进行了描述,并提供了它们的分种检索表。其中大肥蘑菇、亚托柄蘑菇和帕达纳蘑菇在我国和欧洲等地均有分布,而中华美味蘑菇仅在我国有报道。据此,依据1950-2000年生物气候数据结合中华美味蘑菇的分布实地调查结果,利用最大熵模型(maximum entropy model,MaxEnt)开展了对中华美味蘑菇分布区的分析和预测,结果表明中华美味蘑菇适生区在我国主要为新疆天山山脉南北两侧、西藏西南部、青海海西州、甘肃西北部以及内蒙古西部地区;预测国外适生区域在中亚的哈萨克斯坦和蒙古国。物种分布模型涉及的环境变量对模型的贡献率显示,最湿月降水量、最暖季度降水量、最冷季度平均温度和最暖月最高温是影响中华美味蘑菇分布的主要环境因子。研究结果表明中华美味蘑菇适生区域狭窄,为狭域种,建议应加强相关资源的保护,并积极拓展其可持续利用途径以降低对野生中华美味蘑菇子实体的过度消耗。     

基于MaxEnt与ArcGIS对白水江国家级自然保护区缺苞箭竹适生区分析

缺苞箭竹是甘肃白水江国家级自然保护区大熊猫的主要食用竹种之一,是该区天然分布最广的一种箭竹,掌握其地理分布对于野生大熊猫的保护具有重要意义。通过野外实地调查和数据整理,获取缺苞箭竹有效分布记录共73条,同时对保护区气候、土壤、地形和蒸散4类45个环境变量进行多重共线性分析,筛选出7个气候变量、3个土壤变量、2个地形变量和2个蒸散变量作为模型输入;进而采用最大熵模型MaxEnt与地理信息系统ArcGIS模拟缺苞箭竹的地理分布,分析环境变量对缺苞箭竹分布的影响,并划分适生区等级,分析适生区环境特征。结果表明,基于最大熵模型的缺苞箭竹受试者工作特征曲线AUC值为0.932,模型结果很好,可信度高。刀切法检验结果表明,最冷月份的最低温度、海拔、温度季节性变化的标准差、最潮湿月份的降雨量、年温度范围对缺苞箭竹分布影响较大。适生区分析显示,缺苞箭竹集中分布在保护区西部,适生面积为584.76 km²,占保护区总面积的31.13%,其中最适生区面积103.15 km²,其特征是最冷月份的最低温度-15～-9℃,海拔2148～3468 m。研究认为,最大熵模...     

基于MaxEnt模型的大豆蚜全球潜在地理分布分析

【目的】为预测和分析大豆蚜Aphis glycines的全球潜在地理分布,研究大豆蚜分布与环境变量之间的联系。【方法】利用最大熵法生态位模型(maximum entropy niche-based modeling, MaxEnt)和地理信息系统软件ArcGIS,根据收集的大豆蚜已知分布点和环境变量,预测大豆蚜的全球潜在地理分布区,推测环境变量对大豆蚜分布的影响。【结果】结果表明,大豆蚜适生区主要分布在低海拔地区,高 度适生区集中在25°~50°N的中国、日本、韩国、朝鲜、加拿大、美国、意大利和格鲁吉亚。决定大豆蚜分布地点的关键环境变量为最暖季度降水量、最暖季度平均温度、最湿季度平均温度、最干月降水量、月平均昼夜温差和温度季节性变化标准差。【结论】大豆蚜潜在地理分布区域广泛,应在各国大豆农产品贸易时做好检验检疫工作,以防止大豆蚜的扩散。     

基于生态位模型的外来入侵种克氏原螯虾在中国的适生区预测

克氏原螯虾在20世纪初作为重要的水产品引入中国,但因其繁殖能力强、生长迅速、适应性强、喜掘洞穴,对农作物、池埂及农田水利有一定破坏作用,降低入侵地区当地物种多样性,对当地生态系统造成严重危害。因此,研究未来气候情景下克氏原螯虾适生区的变化,可为其监控和管理措施提供关键信息,有效预防和控制其蔓延。本研究基于克氏原螯虾的分布点,应用最大熵(MaxEnt)模型和规则集遗传算法(GARP)模型模拟了当前气候条件下克氏原螯虾在中国的潜在适生区,并预测了2041—2060年和2061—2080年克氏原螯虾在4种气候变化情景下(RCP 2.6、RCP 4.5、RCP 6.0、RCP 8.5)的分布,采用ROC曲线对预测结果进行检验和评价。结果表明: 在当前气候条件下克氏原螯虾集中分布在上海、江苏、浙江、安徽等长江沿岸地区;最冷季平均温度、最冷月最低温度对克氏原螯虾分布影响最大,其次是温度季节性变化、最暖月最高温度和最干月降水量。在未来气候情景下,2061—2080年克氏原螯虾的适生区面积有不同程度的变化,在RCP 2.6和RCP 4.5情景下总适生面积增加,但在RCP 8.5情景下呈先增后减趋势,而在RCP 6.0情景下无明显变化;克氏原螯虾适生区在空间分布上不仅有纬度方向上的扩散,也有向海拔较高地区迁移的趋势。     

Ecological analysis and environmental niche modelling of Dactylorhiza hatagirea (D. Don) Soo: A conservation approach for critically endangered medicinal orchid

The natural populations of Dactylorhiza hatagirea have been greatly affected due to incessant exploitation. As such, studies on its population attributes together with habitat suitability and environmental factors affecting its distribution are needed to be undertaken for its conservation in nature. Present study aimed at accessing an impact of anthropogenic pressure on population structure and locate suitable habitats for the conservation of this critically endangered orchid. Considerable changes in the phytosociological attributes were observed on account of the changing magnitude and extent of anthropogenic threat in their natural abode. The distribution pattern of species indicated that more than 90% of the populations exhibit substantially aggregated spatial distribution. Maximum Entropy (MaxEnt) distribution modelling algorithm was used to predict suitable habitat and potential area for its cultivation and reintroduction. Twenty-seven occurrence records, nineteen bioclimatic variables, altitude, and slope were used. MaxEnt map output gave the habitat suitability for this species and predicted its distribution in the North-Western Himalayas of India for approximately 616 km². Jackknifing indicated that maximum temperature of warmest month, annual mean temperature, mean temperature of the driest quarter, and mean temperature of the wettest quarter were the governing factors for its distribution and hence, presented a higher gain with respect to other variables. According to permutation importance, precipitation seasonality and mean temperature of wettest quarter shows the prominent impact on the habitat distribution. Results of AUC (area under curve) were statistically significant (0.940) and the line of predicted omission falls very close to an omission on training samples, validating a better run of the model. Response curves revealed a probable increase in the occurrence of D. hatagirea with an increase in mean temperature of the wettest quarter and maximum temperature of the warmest month contributed more than 50% to predicted habitat suitability. Direct field observations concurrent with predicted habitat suitability and google-earth images represent greater model thresholds for successful inception of the species. Together, the study proposes that the species can be conserved in or near its present-day natural habitats and is equally effective in determining the possible habitats for its cultivation and reintroduction.     

Ecological niche modelling as a technique for assessing threats and setting conservation priorities for Asian slow lorises (Primates: Nycticebus)

Aim Data on geographical ranges are essential when defining the conservation status of a species, and in evaluating levels of human disturbance. Where locality data are deficient, presence‐only ecological niche modelling (ENM) can provide insights into a species’ potential distribution, and can aid in conservation planning. Presence‐only ENM is especially important for rare, cryptic and nocturnal species, where absence is difficult to define. Here we applied ENM to carry out an anthropogenic risk assessment and set conservation priorities for three threatened species of Asian slow loris (Primates: Nycticebus). Location Borneo, Java and Sumatra, Southeast Asia. Methods Distribution models were built using maximum entropy (MaxEnt) ENM. We input 20 environmental variables comprising temperature, precipitation and altitude, along with species locality data. We clipped predicted distributions to forest cover and altitudinal data to generate remnant distributions. These were then applied to protected area (PA) and human land‐use data, using specific criteria to define low‐, medium‐ or high‐risk areas. These data were analysed to pinpoint priority study sites, suitable reintroduction zones and protected area extensions. Results A jackknife validation method indicated highly significant models for all three species with small sample sizes (n = 10 to 23 occurrences). The distribution models represented high habitat suitability within each species’ geographical range. High‐risk areas were most prevalent for the Javan slow loris (Nycticebus javanicus) on Java, with the highest proportion of low‐risk areas for the Bornean slow loris (N. menagensis) on Borneo. Eighteen PA extensions and 23 priority survey sites were identified across the study region. Main conclusions Discriminating areas of high habitat suitability lays the foundations for planning field studies and conservation initiatives. This study highlights potential reintroduction zones that will minimize anthropogenic threats to animals that are released. These data reiterate the conclusion of previous research, showing MaxEnt is a viable technique for modelling species distributions with small sample sizes.     

广东中山市薇甘菊地理分布及适生区预测

通过实地踏查，收集薇甘菊(Mikania micrantha)在广东中山市的分布情况，绘制薇甘菊在中山市的分布图，并利用MaxEnt模型，对薇甘菊实际分布点的环境变量进行定量分析，预测出当前气候下薇甘菊在中山市的适生区。结果表明，中山市所辖25个镇(街道)和市自然保护地管护中心均有薇甘菊分布，总体呈南多北少的态势；ROC曲线的AUC值均在0.8以上，预测结果具有较高的可信度；降水量变化方差、海拔、最冷月份最低温度和最暖季降水量为限制薇甘菊在中山市分布的4个最大环境变量，累积贡献率达75.5%；中山市95.40%的地区对薇甘菊的生长具有不同程度的适宜性，其中高、中、低适生区面积分别占中山市面积的5.33%、33.56%、56.51%。综上所述，薇甘菊对中山市的入侵较为严重，扩散趋势未被遏制；MaxEnt模型能较好地预测薇甘菊在中山市的潜在分布区，但是存在一定偏差。     

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.     

基于MaxEnt模型的白缘象甲潜在地理分布区识别

【目的】白缘象甲Naupactus leucoloma是中国进境植物检疫性有害生物，对农作物和栽培植物的潜在危害风险较高。自20世纪在美国被首次发现以来，在全球多个国家内发生扩散，造成严重的经济损失。本研究旨在对白缘象甲的潜在地理分布区进行识别并进一步分析其定殖和扩散风险。【方法】基于白缘象甲的752个有效分布记录和10个环境变量，利用MaxEnt模型和ArcGIS软件对白缘象甲的潜在地理分布区进行识别，同时综合环境变量贡献率和刀切法(jackknife)检验评估制约其潜在地理分布的重要环境变量。【结果】白缘象甲在全球的潜在适宜生境主要分布在美国东南部、法国西南部地区、西班牙北部地区、土耳其西北部地区等地，在我国暂时没有其高适宜生境的分布。在我国适宜生境的分布集中在中部和东部沿海地区10余个省份。在影响白缘象甲潜在地理分布的环境变量中，以最干月降水量、年平均气温和最冷月最低温为重要影响变量，其中气温起主导作用。【结论】白缘象甲有一定的入侵、定殖和扩散风险。建议农林行业部门、海关口岸加强调查、检疫和监控工作，严防白缘象甲传入对我国农作物造成危害。     

四川省猕猴桃溃疡病潜在分布预测及适生区域划分

为探明猕猴桃溃疡病在四川的适生性,选用MaxEnt模型,基于分布信息和环境变量,对该病在四川潜在分布区进行预测,分析主要环境变量对其分布的影响,并利用受试者工作特征曲线对模拟准确度进行评价.结果表明: 10次重复模拟的曲线下面积平均值为0.914,预测结果准确.猕猴桃溃疡病在四川的高适生区主要位于成都市、德阳市、绵阳市、广元市、巴中市、达州市和雅安市,中适生区在四川21地市州均有分布.刀切法筛选出影响猕猴桃溃疡病潜在分布的主要环境变量及其指标为:最冷月最低气温(-6.8～7.5 ℃)、最暖季度平均气温(15.6～32.3 ℃)、最干季度平均气温(-0.8～21 ℃)、年降水量(709～950.9 mm)和气温季节性变化标准差(4.7～9.6 ℃).本研究对制定猕猴桃溃疡病早期监测、预警及控制措施意义重大.     

基于MaxEnt模型的菜豆象全球潜在适生区预测

[目的]菜豆象是重要的检疫性害虫,预测其在全球范围内的潜在适生区可为农业部门开展菜豆象防控工作和检验检疫部门制定检疫策略提供科学依据.[方法]在收集菜豆象已有分布点和全球气象数据的基础上,采用MaxEnt模型对其在全球范围内的潜在适生区进行预测分析.[结果]MaxEnt模型的AUC平均值为0.926,预测结果准确可靠....