基于MaxEnt的入侵植物刺轴含羞草的适生分布区预测

【背景】刺轴含羞草是世界危害最严重的100种入侵生物之一,因此明确刺轴含羞草在全球以及中国的潜在分布对有效预防和控制其蔓延具有重要意义。【方法】本研究利用MaxEnt生态位模型对刺轴含羞草在全球以及中国潜在分布区进行预测。【结果】结果表明,刺轴含羞草适生区分布在全球南北纬30度以内的热带和亚热带地区。其中,中南美洲、非洲中部、东南亚以及大洋洲北部为刺轴含羞草中、高度适生区的集中分布区。中国处于刺轴含羞草适生区的边缘。刺轴含羞草在中国的适生区主要分布在云南、海南、广东西南部以及台湾地区。在温室气体A1B排放模式下,到2050年,刺轴含羞草在全球适生区面积与当前相似,但在中国的适生区略有减少。【结论与意义】刺轴含羞草有入侵我国大陆的风险,检疫部门应对刺轴含羞草进行检疫,防止其入侵。     

外来入侵植物肿柄菊在云南的扩散风险研究

预测外来入侵植物的潜在入侵范围以及对不同环境的适应性,能够为外来植物入侵提供预警和预防。该文通过实地调查肿柄菊(Tithonia diversifolia)在云南的入侵范围,以及收集世界其他地区分布点,结合12个关键环境变量,利用MaxEnt模型对肿柄菊适生区范围和环境限制因子进行分析。结果表明:在世界范围适生区分布格局中,肿柄菊在云南无高适生区,次适生区总面积占全省总面积的3.58%,中适生区占32.90%,低适生区占42.80%,非适生区占20.72%;有扩散风险的区域主要为中适生区,普遍分布于云南省26°N以南地区;实地调查肿柄菊分布最高海拔2 200 m,在海拔1 000～1 500 m分布最为密集,而模型预测显示海拔2 000 m以下都适宜肿柄菊生长,且500～2 000 m为最适宜海拔范围;在12个环境变量中年降雨量、人类足迹、年均温、海拔等环境变量对肿柄菊的分布起到了最重要的作用。综上结果表明,目前在云南肿柄菊零星的分布点已到达其潜在分布区的边缘,但已入侵区域还远小于潜在可入侵区域。为了预防肿柄菊在我国南方地区大面积扩散带来危害,有必要对其入侵和扩散态势进行监测。     

外来入侵杂草假苍耳在新疆地区的适生性分析及风险评估

【目的】假苍耳是一种恶性入侵杂草,预测其在新疆地区的潜在适生区并进行风险评估,旨在为其科学防控提供参考。【方法】采用MaxEnt模型与Arc GIS 10.4软件进行分析,预测假苍耳在新疆的潜在分布区,并划分风险等级。运用多指标综合评估方法,对假苍耳的危害风险性进行综合分析评估。【结果】假苍耳在新疆的适生区主要在北疆地区,适生区范围较广。高适生区主要包括克拉玛依市、昌吉回族自治州北部及塔城地区中部。年平均温(bio1)、最干季平均温(bio9)、最冷季平均温(bio11)及最热季平均温(bio10)是影响假苍耳分布的主要环境因子。假苍耳的危险性综合评价值为2.238,属于高度危险的有害生物。【结论】假苍耳目前在新疆仅分布在塔城地区,预测结果表明其在北疆地区继续扩散的趋势较大,需要提前制定好相应的管理和控制措施。     

北美刺龙葵在中国的适生区预测

【背景】北美刺龙葵是一种全球广泛分布的恶性杂草,已被列入我国进境检疫性有害生物名单。近年来北美刺龙葵不断随进口货物传入我国,明确其传入途径和适生区对控制其入侵具有重要意义。【方法】采用GIS、空间统计学、Maxent生态位模型等方法分析了北美刺龙葵的传入途径与潜在分布区,并通过ROC分析法对模型进行检验。【结果】跨区域农产品贸易是北美刺龙葵全球扩散的驱动力与传入我国的主要途径。生态模型预测结果表明,北美刺龙葵在我国具有广阔的适生区,除黑龙江、吉林、内蒙古、青海、甘肃、西藏、四川西北部以外的区域都是其在我国的适生区,其中高风险区主要集中在东部和南部沿海、西南边境和新疆的部分地区。AUC值为0.789,表明本研究建立的Maxent模型的预测能力较强,能够很好地拟合物种已知分布的环境生态位。【结论与意义】北美刺龙葵在我国的传入风险极高。基于北美刺龙葵在我国的主要传入途径与潜在扩散媒介的时空分布,划定了重点监测的区域,建议对适生区内极易传入的高风险区如港口、机场、物流中转站、加工厂等开展早期监测预警,以预防其再次入侵与进一步扩散蔓延。     

稻水象甲在新疆的潜在分布及适生性研究

【目的】通过精准开展稻水象甲在新疆荒漠绿洲稻区的适生性研究,旨在为新疆地区该重大外来有害生物的科学防控提供指导。【方法】基于19个环境因子和64个稻水象甲在新疆及内地重要代表性发生地的最新地理分布点信息,采用MaxEnt模型与ArcGIS 10.2软件进行具体分析,预测稻水象甲在新疆的最新潜在分布区,并划分风险等级。【结果】稻水象甲在新疆荒漠绿洲稻区的适生区域主要集中在北疆天山北坡和伊犁河谷一带,以及南疆阿克苏地区和克州的部分区域,其非适生区占新疆总面积的79.97%,低适生区占7.34%,适生区占10.84%,高适生区则仅占1.85%。【结论】稻水象甲在新疆继续扩散的趋势与危害风险依然较大,其中,年平均温(bio1)、等温性(bio3)、最湿季平均温(bio8)、最暖季的降雨量(bio18)和最热月的高温(bio5)是影响稻水象甲在新疆潜在扩散的主要环境因子。     

气候变化对全球马缨丹分布影响的空间模拟

【目的】马缨丹是世界10种最有害的入侵杂草之一,预测其潜在适生区变化对入侵植物防控具有重要意义。【方法】以马缨丹为研究对象,采用有效分布点数据1744份和10个气候因子,使用MaxEnt模型和ArcGIS10.4软件,选用当前气候情景以及2050sSSP126、2050sSSP245、2050sRCP5.8、2090sSSP126、2090sSSP245、2090sSSP585 6个不同气候情景,对马缨丹全球潜在分布区进行预测。【结果】温度和降水因子是制约马缨丹入侵的主要因子,其中年降水量(bio12,48.6%)、最干季度的平均温度(bio9,36.4%)、温度季节性(bio4,4.6%)和最热季度的平均温度(bio10,4.2%)是制约马缨丹分布格局的主要环境因子。南美洲、非洲南部、亚洲南部以及澳大利亚北部和东部具有较高的入侵风险。从当前气候情景到2050年气候情景再到2090年气候情景的过渡中,其适生区面积呈增加趋势,其中高适生区面积持续增加。【结论】在水热条件以及生物因素3个层面上严格防控马缨丹入侵,以增加土著生态系统的完整性。     

外来入侵植物腺龙葵在我国的适生区预测

【目的】全球恶性杂草腺龙葵最早于20世纪80年代入侵我国辽宁,90年代以后在河南被发现,近年来在新疆和北京都有入侵记录。明确其潜在的适生区对制定防控措施具有重要意义。【方法】通过查找全球生物多样性信息数据库、标本记录、文献信息以及实地调查等途径获得了腺龙葵在全球的分布点,利用Maxent生态位模型模拟了其适应的气候生态位,并投影到中国预测了其潜在适生区。【结果】适生区预测结果显示,腺龙葵在我国存在广阔的适生区,除海南、广东、黑龙江、吉林外的27省区都存在其适生区。【结论】腺龙葵在我国进一步扩散蔓延的风险极高。建议对新入侵地采取早期监测预警和根除措施,并加大对适生区内进口货物接受区的监测力度,以预防其再次入侵。     

入侵植物薇甘菊在贵州的潜在适生区及其变化趋势

【目的】薇甘菊是一种危害性极大的外来入侵植物,2016—2022年间,多次在贵州省发现其入侵种群。预测薇甘菊在贵州的潜在适生区及其变化规律,可对贵州薇甘菊防控体系建设提供依据。【方法】在全球筛选薇甘菊分布点1001个,结合22个环境因子数据,采用最大熵模型(MaxEnt)预测当前及未来气候条件下薇甘菊在贵州的潜在分布情况,并进行主导因子分析。【结果】当前气候条件下,薇甘菊在贵州的高适生区面积为1.51万km²,占全省面积的8.60%,主要位于黔西南州和黔南州;在未来气候条件下,薇甘菊在贵州的适生区呈扩增状态,适生区分布中心坐标(26.43°N,107.00°E)由黔南州向贵阳市转移;影响薇甘菊适生范围的主导因子是年平均温度、昼夜温差平均值、温度季节性变化、最冷月份最低温、年降水量和最热季平均降水量。【结论】薇甘菊在贵州的适生区范围广,温度和降水是主要影响因素。在未来气候条件下,薇甘菊在贵州的适生区呈扩增状态,整体向北迁移扩散的趋势明显。     

栎方翅网蝽Corythucha arcuata(Say)在中国的潜在适生区预测

【目的】栎方翅网蝽是栎树上的一种重要害虫,自21世纪入侵意大利以来,迅速在欧洲地区暴发成灾。本文旨在探明栎方翅网蝽入侵中国的风险性。【方法】利用MaxEnt生态位模型预测栎方翅网蝽在中国的潜在适生区,分析栎方翅网蝽入侵、定殖和扩散的可能性。【结果】栎方翅网蝽入侵中国并在中国黄河长江中下游平原定殖和扩散的风险性极高,高度适生区包括重庆市、安徽省、湖北省、河南省、浙江省、湖南省、贵州省和四川省。通过分析环境因子重要性表明,最冷季度平均温度是影响栎方翅网蝽适应区的最关键环境变量;年平均温度、等温性和最干季度平均温度是影响栎方翅网蝽适应区分布的主要环境因素。【结论】栎方翅网蝽在我国定殖扩散风险高,建议植物检疫部门加强栎方翅网蝽的监控,并将栎方翅网蝽列入中华人民共和国进境植物检疫性有害生物名录。     

广西内陆水域外来鱼类入侵风险分析

【目的】对广西内陆水域的外来鱼类进行入侵风险评估和适生区预测,为广西外来鱼类入侵防治及水生态环境保护提供科学依据。【方法】采用鱼类入侵风险和水生生物入侵能力筛查系统2个体系筛选广西内陆水域具有入侵风险的鱼类,并用最大熵模型预测高入侵风险鱼类在广西内陆水域的潜在适生区。【结果】广西内陆水域共记录有外来鱼类18种,其中13种鱼类具有高入侵风险,分别为尖齿胡鲇、尼罗罗非鱼、莫桑比克罗非鱼、奥利亚罗非鱼、豹纹脂身鲇、齐氏罗非鱼、大口黑鲈、斑点叉尾鮰、短盖肥脂鲤、露斯塔野鲮、条纹鲮脂鲤、麦瑞加拉鲮和食蚊鱼,2种具有中入侵风险,为丁鱥和太湖新银鱼。适生区预测结果表明,极易发生鱼类入侵的水域为黔江、郁江和南流江。【结论】对中、高入侵风险的鱼类均需重点监控且在具有高入侵风险水域应对外来鱼类开展持续性监测,并进行早期筛查。     

大黄属(蓼科) 植物ｎｄｈＦ 基因的适应性进化

大黄属(Rheum L.)是蓼科(Polygonaceae)中一个高度分化的大属,广泛分布在亚洲和欧洲的高山和沙漠地区,全世界约60种,其中在青藏高原及其邻近地区发现了约40种。该属种的高度分化曾被推测是第三纪末青藏高原的快速隆升以及第四纪气候的反复变化所引发的适应性辐射导致。为进一步了解大黄属植物辐射式物种分化的分子适应机制,该研究选取34个形态上多样化的大黄属物种,利用系统发育分析软件,在时间框架下采用位点模型和分支模型对大黄属的叶绿体ndhF基因进行了适应性进化分析。结果表明：大黄属植物的分子进化系统树呈现短而平行的辐射式分支式样,显示出典型的物种快速辐射多样化特征;用位点模型检验ndhF基因是否存在经受正向选择(ω>1)时,在氨基酸水平上共鉴定出3个NDHF亚基的正选择位点(188H,465H,551L),对NDHF亚基的二级结构进行分析后发现编码的188H氨基酸位于α螺旋上。大黄属植物可能通过这些结构域的适应性进化,适应青藏高原的快速隆升以及第四纪气候的反复变化而引发的陆地生态系统改变。该研究结果可为今后对该属植物的实验分析提供首选位点。     

Critical evaluation of the VSC model for tip growth

The vesicle supply centre (VSC) model (Bartnicki-Garcia et al., 1989) for hyphal tip growth is powerful because it can model diverse developmental morphologies and predicts cellular organization based in current cell biology. It predicts that tip growth results from the random distribution of cell surface synthesizing vesicles from a point in the tip, the VSC, which determines their pattern of impact and fusion at the plasma membrane. We derive equations for tip-high gradients of vesicle fusions, generated by mechanisms not related to a supply centre, which create typical hyphal morphologies. These equations direct the conceptual basis for tip growth to vesicle fusion gradients, presumably mediated by a putative membrane skeleton associated with the plasma membrane. We also show that the organization and behaviour of motile organelles in growing hyphal tips of the oomycete,Saprolegnia ferax, argue against the presence of an apparatus capable of generating the distribution of vesicles postulated by the VSC model. We conclude that the VSC model is unlikely to describe the mechanistic basis of tip growth inS. ferax, and therefore, at best, it is not universally applicable.     

Individual-based modelling of Pinus sylvestris invasion after grazing abandonment in the French Massif Central

In the Chaîne des Puys, a mid-elevation volcanic mountain of the French Massif Central, Scots pine proves to be an invasive species colonizing abandoned lawns or heathlands, and forms in a few years monospecific natural forests. Most of the abandonment occurred 30 to 40 years ago and this process has now stopped. Thus, we lack data on the very first phase of tree colonization. We anticipate that a simulation tool could bring an appreciable help in (i) rebuilding the entire colonization process – including the initial phase – of pine settlement and (ii) answering questions about the origin of the narrow and unimodal distributions of age of pine stands we observed. In addition, such a simulator could help managers to forecast extension of Scots pine and to predict growth and evolution of present secondary forests. A spatially explicit individual-based model is presented. The model takes into account both space and time and includes growth of trees, seed production and seed dispersal, death and competition between individuals. The influence of the initial parameters are analyzed and elements of validation given. The model was then used to predict tree settlement and stand establishment using the initial conditions from a natural stand studied in the field whose characteristics before abandonment were known (number and age-distribution of trees, location of mother trees, time of abandonment). Three simulations were achieved by using the same initial conditions but following different scenarios for the recruitment process. The scenario of a fluctuating resistance of the resident vegetation (that controls the susceptibility of the environment to tree establishment) seemed as one of the most probable to explain the actual stand characteristics. We thus concluded that dynamic models could be improved by taking into account the resistance of the vegetation to colonization as a fluctuating parameter instead of a static and permanent attribute.     

The clam sipho as indicator for growth indices in the soft-shell clam <Emphasis Type="Italic">Mya arenaria</Emphasis>

Due to the species’ deep burrowing behaviour, growth parameters of the soft-shell clam Mya arenaria L. 1758 are difficult to estimate, especially in deeper habitats which are not directly accessible. In this study, we analysed 192 specimens of M. arenaria and found, contrary to results of most other studies that the sigmoid Gompertz growth model (GGM) is appropriate to describe the growth. Predictions from this model confirm the finding of a life span up to 8 years and as a consequence of this, a maximum shell-length of 60 mm. Individual growth rates calculated from the first deviation indicate a nearly exponential growth in young individuals. The relationship between the clam sipho-width and age, shell-length and biomass conform to the GGM. This is a new approach to assess growth of M. arenaria and to solve practical problems that arise in field studies.     

FLEXPART模式模拟褐飞虱回迁的适用性

褐飞虱是威胁我国水稻生产安全的主要害虫之一,已经严重地威胁到我国南方地区水稻的安全生产。褐飞虱作为一种风媒迁飞性昆虫,与大气气溶胶粒子的运动相似。采用褐飞虱迁飞相关参数,利用WRF-FLEXPART模式模拟分析两次褐飞虱秋季回迁过程。通过模拟2013年9月20—24日褐飞虱迁入兴安县的迁飞过程,发现褐飞虱虫量的模拟结果与实验观测到的褐飞虱高空灯诱数据相近、变化趋势一致,相关性达到0.49(P0.01)。褐飞虱迁飞峰的模拟值平均早于观测值1.5h,这可能与褐飞虱起飞迁飞的主动性及其生理特性等有关。模拟2008年10月5—7日一次冷锋无降水天气过程中的褐飞虱迁飞过程,发现此次冷锋南下和降温过程对褐飞虱的回迁影响显著,主要表现在:(1)在迁飞轨迹上,受热带气旋影响,广西、贵州、湖南和广东西部地区以东北风为主,有利于褐飞虱向西南方向的迁飞;(2)在虫量密度分布上,广东中部地区同时具备了较好的动力和温湿条件,促使大量褐飞虱向着该地区(较温暖)迁入,而湖北地区虽以西北—东北风为主,但地面气温较低(低于广东地区),不利于褐飞虱的大量迁入。综上所述,WRF-FLEXPART模式适用于褐飞虱的迁飞模拟且有较好的模拟能力,该研究对我国褐飞虱灾变的准确预警、病虫测报水平的提高具有重要的参考价值。     

基于光谱参数对小白菜叶片镉含量的高光谱估算

为实现利用高光谱技术快速、准确、无损地检测叶类蔬菜叶片重金属镉污染情况,通过采用室内盆栽试验,检测了小白菜在6个不同的镉浓度梯度0 mg/kg(CK)、0.5 mg/kg(T1)、1 mg/kg(T2)、5 mg/kg(T3)、10 mg/kg(T4)和20 mg/kg(T5)下的叶片高光谱反射率及其镉含量。利用相关分析和逐步回归的统计方法对叶片原光谱、一阶导数光谱和光谱参数与镉含量进行统计分析,确定了反演叶片镉含量的敏感光谱参数,并建立了估算叶片镉含量的参数模型。结果表明:(1)在540 nm附近和红外区域,叶片光谱反射率随着处理浓度的增加呈下降趋势。T1组叶片光谱与对照组的光谱没有明显的变化差异;(2)原光谱与镉含量的敏感波段主要在690—1300 nm,相关系数最高的波段是782 nm。一阶微分光谱与镉含量的敏感波段在黄边、红外、近红外和远红外范围均有分布;(3)反映植物色素、水含量和细胞结构的参数MCARI(叶绿素吸收反射修正指数Modified Chlorophyll Absorption Reflectance Index),SDy(黄边面积Yellow Edge Area),WI(水质指数Water Index),DCWI(病态水分胁迫指数Disease Water Stress Index),SDr(红边面积Red Edge Area)和Dr(红边幅值The Amplitude of the Red Edge)可分别作为反演镉含量的敏感光谱参数,其倒数回归模型能够较好地反演镉污染下小白菜叶片的镉含量;(4)镉胁迫处理15 d时,建立的SDr的倒数模型估算处理30 d时小白菜叶片镉含量的效果最优。研究表明红边面积参数可以用于估算小白菜叶片的镉含量,可为评价小白菜的食用安全提供科学方法。     

气候变化下青藏高原全缘叶绿绒蒿的潜在分布变迁

青藏高原物种丰富且属于气候变化敏感区,研究气候变化对青藏高原物种的潜在分布影响,对于该区域物种多样性保护具有重要意义。该研究以一级濒危藏药植物全缘叶绿绒蒿为研究对象,利用加权平均算法(weighted average algorithm, WAA)构建随机森林(RF)、灵活判别分析(FDA)及人工神经网络(ANN)的集成模型,同时对比分析了WAA模型和不同生态位模型的预测精度。最后利用WAA模型预测了全缘叶绿绒蒿在当前(1970~2000年平均)和未来(2041~2060年平均)气候情景下的潜在分布,其中未来气候考虑了2种“共享社会经济路径”(SSP2-45和SSP5-85)。结果显示:(1) WAA模型的预测表明,基于RF、FDA和ANN的集成模型的AUC值为0.926,在AUC值最高RF模型的基础上提高了3%,在FDA和ANN模型的AUC值的基础上均提高了5%。(2) WAA模型确定,全缘叶绿绒蒿的潜在分布对年降水量和最暖季降水量最为敏感,其次是最热月份最高气温,同时对最湿月份降水量以及等温性表现出较低的敏感性。(3)当前全缘叶绿绒蒿潜在分布区主要分布在甘肃西南部、青海东部至南部、四川西部和西北部、云南西北部和东北部、西藏东部。(4)未来气候变化下青藏高原全缘叶绿绒蒿潜在分布预测表明,在2050年SSP2-45情景下,全缘叶绿绒蒿的潜在分布区大小与当前潜在分布区大小基本相同,但整体向西北方向高海拔高纬度地区迁移;在SSP5-85情景下,全缘叶绿绒蒿的潜在分布区明显收缩,且向西北高纬度高海拔地区延伸的趋势更加明显。     

Current state and the future of the crested ibis (Nipponia nippon): A case study by population viability analysis

There is only one population of the crested ibis (Nipponia nippon) surviving in the wild, which has not exceeded 40 individuals since it was rediscovered in 1981. We used detailed data of the annual population size and natality collected by the Crested Ibis Conservation and Observation Station (CICOS) over the past 17years. We were able to obtain a more accurate census of age structure and mortality as all of the fledglings have been identified by leg bands in 1987. Consequently, we analyzed the current state of the crested ibis and predicted its future using Population Viability Analysis (PVA) with the help of the computer simulation model VORTEX (Version 7.2). The results indicated that the extinction probability of the crested ibis was 19.7% in 100years. Sensitivity analysis showed that the extinction probabilities were sensitive to catastrophes and environmental variation, and the long-term existence of the population was dependent on the carrying capacity of the habitat and inbreeding depression. Conservation efforts are critical for the survival of the crested ibis. The prior conservation project involves controlling hunting and predation, as well as improving the life level of these few remnant creatures.     

A Study on the Synthetic Characteristics of the Extracellular Polysaccharide (EPS) of Ganoderma lucidum Cultured in Batch Fermentation Using a Kinetic Model

The synthetic characteristics of the extracellular polysaccharide (EPS) of Ganoderma lucidum in batch fermentation were studied. The result showed that the production of EPS was partially growth-associated. The cell dry weight (CDW) and EPS reached 15.56 g·L⁻¹ and 3.02 g·L⁻¹, respectively. The yield of EPS to cell dry weight (Y_p/x) was 0.19. On the basis of the test results of batch fermentation, a kinetic model was proposed by using the Logistic equation for cell growth, the Luedeking–Piret equation for EPS production, and the Luedeking-piret-like equation for the consumption of glucose as substrate. The calculated results using these models were satisfactorily compared with the experimental data under various concentrations of glucose, and the average of relative errors was found to be not more than 5%. The kinetic model had practical guidance interesting in producing PES by Ganoderma lucidum.     

Bagging GLM: Improved generalized linear model for the analysis of zero-inflated data

Species-occurrence data sets tend to contain a large proportion of zero values, i.e., absence values (zero-inflated). Statistical inference using such data sets is likely to be inefficient or lead to incorrect conclusions unless the data are treated carefully. In this study, we propose a new modeling method to overcome the problems caused by zero-inflated data sets that involves a regression model and a machine-learning technique. We combined a generalized liner model (GLM), which is widely used in ecology, and bootstrap aggregation (bagging), a machine-learning technique. We established distribution models of Vincetoxicum pycnostelma (a vascular plant) and Ninox scutulata (an owl), both of which are endangered and have zero-inflated distribution patterns, using our new method and traditional GLM and compared model performances. At the same time we modeled four theoretical data sets that contained different ratios of presence/absence values using new and traditional methods and also compared model performances. For distribution models, our new method showed good performance compared to traditional GLMs. After bagging, area under the curve (AUC) values were almost the same as with traditional methods, but sensitivity values were higher. Additionally, our new method showed high sensitivity values compared to the traditional GLM when modeling a theoretical data set containing a large proportion of zero values. These results indicate that our new method has high predictive ability with presence data when analyzing zero-inflated data sets. Generally, predicting presence data is more difficult than predicting absence data. Our new modeling method has potential for advancing species distribution modeling.