基于MaxEnt模型模拟肯尼亚茜草科河骨木属植物的潜在分布及其在植物志中的应用初探(英文)

物种分布模型目前被广泛应用于生物学、生态学和保护生物学的各个领域。该文以肯尼亚茜草科河骨木属(Afrocanthium)为例,利用最大熵模型(MaxEnt)模拟植物在当前气候情景下的潜在分布,并将这些分布图利用于正在编写的《肯尼亚植物志》中。结果显示,基于足够的原始标本记录,模型能够很好地模拟出每种植物的潜在分布区域。相比传统和新一代植物志仅提供标本信息点或是粗略分布图,《肯尼亚植物志》预采用的潜在分布图,将为志书使用者提供更加全面、实用的信息。     

草问荆（木贼科）的地理分布

通过整合全球植物志文献资料,结合调查中国科学院植物研究所植物标本馆（PE）、北京林业大学森林植物标本馆（BJFC）和中国科学院沈阳应用生态研究所植物标本馆（IFP）馆藏腊叶标本,以及进行野外观测,获取了草问荆的地理分布数据。采用地理绘图软件MapInfo Professional 8．0,绘制草问荆在中国及世界的资源分布图,首次提供了其在中国的详细分布资料,为深入理解和开发草问荆资源提供了必要的生物学基本数据。     

安徽植物增补及地理新分布Ⅱ

本文第二次增补《安徽植物志》未记入的植物２２种５变种。其中２０种３变种为安徽地理新分布,３属（白屈菜属、离子芥属和石莲属）为安徽地理新分布属。本文所引用的植物标本,全部收藏于安微大学资源植物标本室。     

中国不产曲籽芋属植物

曲籽芋属在中国的分布源自对采自海南的一号标本———W.T.Tsang（曾怀德）553=L.U.16052（1927年8月27日采）的错误鉴定。这号标本被E.D.Merrill定名为曲籽芋Cyrtosperma lasioides Griffith,并分藏于国内外的标本馆。因此,《海南植物志》第四卷、《中国植物志》第十三卷第二分册、《中国种子植物科属词典》以及吴征镒的《中国种子植物属的分布区类型》一文等都记录了曲籽芋属。收藏在中国科学院华南植物研究所、英国邱皇家植物园和爱丁堡皇家植物园的W.T.Tsang（     

黑龙江省野生维管植物名录

黑龙江省位于中国的东北端, 省下辖区划分复杂而繁多, 植被可分为3大区域: 寒温带针叶林区域、温带针阔混交林区域、温带草原区域。本名录主要参考《中国生物物种名录(2021版)》《东北植物志》《东北植物检索表》《黑龙江省植物志》《黑龙江省树木志》《东北植物分布图集》《东北草本植物志》等著作、近年来发表的论文和来自国家标本资源共享平台（NSII）、全球生物多样性信息网络(GBIF)、东北林业大学植物标本室(NEFI)、东北农业大学生命科学学院植物标本室(NEAU)、中国科学院沈阳应用生态研究所东北生物标本馆(IFP)的标本资料以及最近发表的文献资料。由于“无分布”比“有分布”的信息相对较难确定, 我们在整理数据时, 轻易不删除重要著作中已经有收录的物种, 除非有较可信的证据, 这可能使得本数据集的物种数量稍偏多。本名录中物种分布精确到县级, 共收录黑龙江省野生维管植物132科651属2,276种(亚种、变种), 有凭证标本的本土植物2,122种(亚种、变种), 广泛入侵的44种, 无凭证标本但是有较可靠资料的154种。其中石松类2科6属17种, 蕨类植物16科34属81种, 裸子植物3科6属20种, 被子植物111科605属2,158种。收录国家级重点保护植物22科25属39种。黑龙江野生维管植物中, 菊科(67属258种)、禾本科(61属187种)、莎草科(14属174种)、毛茛科(18属124种)和蔷薇科(24属112种)所含种数较多。统计发现, 黑龙江省物种县域分布差异较大, 131个县级行政单位中, 物种数超过1,000的约占1/6, 且县级分布数据严重不均衡。本名录中, 省级名录的可信度相对较高, 县级分布数据质量还需要大大提升。     

值得注意的中国植物

近年为研究中国的大戟科、檀香科等科的植物,对中山大学生物系植物标本馆（ＳＹＳ）、华南植物研究所标本馆（ＩＢＳＣ）等的标本予以重新鉴定．现将中国植物区系中一些属或种作必要的修订,增加《中国植物志》未收载的２个新记录种,处理１个新异名．     

我国地方植物志出版情况简介(五)

本文继《广西植物》等１６卷第４期３３８页（１９９６）刊登我国地方植物志出版情况简介之后,根据最近收集的资料将我国地方植物志最近出版的信息简介如下：１－《黑龙江植物志》第４卷（１９９２）。该卷含双子叶植物胡桃目至中央种子目;第５卷（１９９３）,含木兰目至罂粟目;第１１卷（１９９３）,含单子叶植物佛焰苞目至微子目。该志划计出１１卷,前三卷分别的苔纲、藓组和蕨类植物、裸子植物,后八卷为被子植物,被子植物依据恩格勒系统（１９６４年版）。２－《云南植物志》第７卷（１９９７）。该卷含小檗科、星叶草科、粟米草…     

草问荆(木贼科)的地理分布

通过整合全球植物志文献资料, 结合调查中国科学院植物研究所植物标本馆(PE)、北京林业大学森林植物标本馆(BJFC)和中国科学院沈阳应用生态研究所植物标本馆(IFP)馆藏腊叶标本, 以及进行野外观测, 获取了草问荆的地理分布数据。采用地理绘图软件MapInfo Profes sional 8.0, 绘制草问荆在中国及世界的资源分布图, 首次提供了其在中国的详细分布资料, 为深入理解和开发草问荆资源提供了必要的生物学基本数据。     

安徽植物增补及地理新分布II

本文第二次增补《安徽植物志》未记入的植物22种5变种。其中20种3变种为安徽地理新分布, 3属(白屈菜属、离子芥属和石莲属)为安徽地理新分布属。本文所引用的植物标本,全部收藏于安微大学资源植物标本室。     

中国特有植物白玉山蔷薇分类学考证

白玉山蔷薇（Rosa baiyushanensis Q.L.Wang）为中国特有植物,仅分布于辽宁省大连市旅顺口区,被列为辽宁省二级保护植物。本种发表于1984年,模式标本是1957年6月由朱有昌采自大连旅顺白玉山。笔者通过近年来的野外调查发现,由于模式产地生境被破坏,未见到白玉山蔷薇的分布,但是在旅顺范围内距离白玉山不远的郭家沟、对庄沟一带均见到此植物。考虑到上述地方均是人为活动较频繁的区域,而且还发现此植物与原产欧洲的犬蔷薇（Rosa canina L.）同时出现,加之该地区的历史原因,笔者推断白玉山蔷薇与犬蔷薇类似,均是外来植物。通过野外观察、查阅中外植物志和比对模式标本,对其外部形态进行仔细对照研究发现,白玉山蔷薇与原产欧洲的锈红蔷薇（Rosa rubiginosa L.）没有本质区别,故将白玉山蔷薇处理为锈红蔷薇的异名。同时,考虑到白玉山蔷薇（锈红蔷薇）在某些国家被列为外来入侵种,笔者建议将白玉山蔷薇从保护名单上删除。此外,根据Rehder蔷薇属分类系统白玉山蔷薇（锈红蔷薇）和犬蔷薇在分类上均属于蔷薇属（Rosa L.）蔷薇亚属（Subgen.Eurosa）犬齿组（Sect.Caninae）,这一发现填补了《中国植物志》未收录犬齿组植物的空白。同时,笔者也纠正了Flora of China将白玉山蔷薇（锈红蔷薇）划分到桂味组（Sect.Cinnamomeae）的错误。     

A Landscape and Climate Data Logistic Model of Tsetse Distribution in Kenya

Background

Trypanosoma spp, biologically transmitted by the tsetse fly in Africa, are a major cause of illness resulting in both high morbidity and mortality among humans, cattle, wild ungulates, and other species. However, tsetse fly distributions change rapidly due to environmental changes, and fine-scale distribution maps are few. Due to data scarcity, most presence/absence estimates in Kenya prior to 2000 are a combination of local reports, entomological knowledge, and topographic information. The availability of tsetse fly abundance data are limited, or at least have not been collected into aggregate, publicly available national datasets. Despite this limitation, other avenues exist for estimating tsetse distributions including remotely sensed data, climate information, and statistical tools.

Methodology/Principal Findings

Here we present a logistic regression model of tsetse abundance. The goal of this model is to estimate the distribution of tsetse fly in Kenya in the year 2000, and to provide a method by which to anticipate their future distribution. Multiple predictor variables were tested for significance and for predictive power; ultimately, a parsimonious subset of variables was identified and used to construct the regression model with the 1973 tsetse map. These data were validated against year 2000 Food and Agriculture Organization (FAO) estimates. Mapcurves Goodness-Of-Fit scores were used to evaluate the modeled fly distribution against FAO estimates and against 1973 presence/absence data, each driven by appropriate climate data.

Conclusions/Significance

Logistic regression can be effectively used to produce a model that projects fly abundance under elevated greenhouse gas scenarios. This model identifies potential areas for tsetse abandonment and expansion.     

新一代植物志：iFlora

进入21世纪,随着分子生物学及计算机信息等技术的快速发展,人们认知自然的手段和方式发生了根本性的变化。在现有电子植物志（eFlora）的基础上,融入新一代测序技术、DNA条形码数据、地理信息数据和计算机信息技术等新元素的新一代植物志（iFlora）应运而生。iFlora是通过系列关键技术的集成和攻关,构建便捷、准确识别植物和掌握相关数字化信息的新一代植物志（或智能装备）,它将极大地促进植物分类学和系统发育、演化生物学、生态学、生物地理学和保护生物学等相关学科的发展,有效地服务于生物多样性保护和生物资源可持续利用、国家生态安全和社会公共教育等,并进一步提升公众对生物多样性的认识。iFlora的实施,将为培育和拓展物种识别圈（taxasphere）和生物文化圈（bioliterate world）做出应有的贡献,并可能成为引领国际植物学发展新的生长点。     

Distribution,degree of damage and risk of spread of Trioza erytreae (Hemiptera: Triozidae) in Kenya

The African citrus triozid (ACT), Trioza erytreae Del Guercio, is a destructive pest particularly on citrus, and vectors, “Candidatus” Liberibacter africanus (CLaf), which is the causal agent of the African citrus greening disease. Our study seeks to establish the distribution and host‐plant relationship of ACT across citrus production areas in Kenya. We also modelled the risk of spread using the maximum entropy modelling algorithm with known occurrence data. Our results infer that ACT is widely distributed and causes severe damage to four alternative host plants belonging to the family Rutaceae. The adults, immature stages (eggs and nymphs), galls and the percentage of infested leaves were significantly higher in shaded than unshaded trees. However, adult ACTs preferred Kenyan highlands to Victoria Lake and coastal regions. The average area under the curve of the model predictions was 0.97, indicating an optimal model performance. The environmental variables that most influenced the prediction were the precipitation of wettest quarter, precipitation of wettest month, mean diurnal range, temperature seasonality and mean temperature of the coldest quarter. The current prediction of ACT exceeded its existing range, especially in the Western, Nyanza, Central, Rift valley and Eastern regions of Kenya. The model predicted a contraction of suitable habitats for a potential spread in 2040 with an inland shift to higher altitudes in the cooler regions. The potential for further expansion to climatically suitable areas was more pronounced for the 2080 forecast. These findings provide relevant information to improve monitoring/surveillance and designing IPM strategies to limit its spread and damage.     

The Next-Generation Flora iFlora

The 21st century has witnessed a rapid development in technologies of molecular biology and computer informatics. Fundamental changes have taken place in means and methods in which humans take cognition of the world. Based on the currently available eFlora and combining this with elements of next generation sequencing techniques, DNA sequence data, geographical information system data and computer information technology, the next-generation Flora (iFlora) is bursting. Through a series of key technological innovations and integrations, the main objective of iFlora is to construct the next-generation Flora, which will fulfill the function of accurately and rapidly identifying species and acquiring species related digital information. iFlora will greatly advance the development of plant taxonomy, phylogenetics, evolutionary biology, ecology, biogeography, conservation biology and other related disciplines. Furthermore, iFlora will be a valuable tool for biodiversity conservation and sustainable utilization of biological resources, ecological security, public education and services, and will profoundly promote public understanding of biodiversity. The application of iFlora will tremendously nurture and boost the taxasphere and bioliterate world, and will be a new focal point that may reshape modern botany at the global and regional levels.     

Seaweeds of potential economic importance in Kenya: field survey and future prospects

Kenya is a net importer of agar and alginate based on recent government statistics, although it may have the potential to be self-sufficient or even an exporter of these phycocolloids. There is little information on carrageenan importation into Kenya since government statistics incorporate it as agar. Seaweeds are relatively unimportant in the Kenyan diet since they are consumed rarely by coastal people. A survey of 15 sites along of the Kenyan coast evaluated the potential for harvesting seaweeds and for establishing seaweed farms. Gracilaria appears to comprise the bulk of the low grade agar import, even though local species of this genus are widely distributed along the Kenyan coast. Major populations of Gelidium may be a potential source of high quality bacteriological grade agar. Eucheuma may be farmed locally to support the increasing local and regional demands for carrageenan. Recommendations for a national program of management and production for Kenya will be discussed.     

Use of Geospatial Modeling to Predict Schistosoma mansoni Prevalence in Nyanza Province,Kenya

Background

Schistosomiasis, a parasitic disease that affects over 200 million people, can lead to significant morbidity and mortality; distribution of single dose preventative chemotherapy significantly reduces disease burden. Implementation of control programs is dictated by disease prevalence rates, which are determined by costly and labor intensive screening of stool samples. Because ecological and human factors are known to contribute to the focal distribution of schistosomiasis, we sought to determine if specific environmental and geographic factors could be used to accurately predict Schistosoma mansoni prevalence in Nyanza Province, Kenya.

Methodology/Principal Findings

A spatial mixed model was fit to assess associations with S. mansoni prevalence in schools. Data on S. mansoni prevalence and GPS location of the school were obtained from 457 primary schools. Environmental and geographic data layers were obtained from publicly available sources. Spatial models were constructed using ArcGIS 10 and R 2.13.0. Lower S.mansoni prevalence was associated with further distance (km) to Lake Victoria, higher day land surface temperature (LST), and higher monthly rainfall totals. Altitude, night LST, human influence index, normalized difference vegetation index, soil pH, soil texture, soil bulk density, soil water capacity, population, and land use variables were not significantly associated with S. mansoni prevalence.

Conclusions

Our model suggests that there are specific environmental and geographic factors that influence S. mansoni prevalence rates in Nyanza Province, Kenya. Validation and use of schistosomiasis prevalence maps will allow control programs to plan and prioritize efficient control campaigns to decrease schistosomiasis burden.     

A Study of a population of Micronecta scutellaris Stal (Hemiptera : Corixidae) in Lake Naivasha,Kenya

Micronecta scutellaris is one of the most abundant macro-invertebrates found in Lake Naivasha, Kenya and forms an important component of the diet of juvenile large mouthed bass.Its distribution in the lake and breeding biology are described and considered in relation to the lake's food chains.     

Bayesian Spatial Semi-Parametric Modeling of HIV Variation in Kenya

Spatial statistics has seen rapid application in many fields, especially epidemiology and public health. Many studies, nonetheless, make limited use of the geographical location information and also usually assume that the covariates, which are related to the response variable, have linear effects. We develop a Bayesian semi-parametric regression model for HIV prevalence data. Model estimation and inference is based on fully Bayesian approach via Markov Chain Monte Carlo (McMC). The model is applied to HIV prevalence data among men in Kenya, derived from the Kenya AIDS indicator survey, with n = 3,662. Past studies have concluded that HIV infection has a nonlinear association with age. In this study a smooth function based on penalized regression splines is used to estimate this nonlinear effect. Other covariates were assumed to have a linear effect. Spatial references to the counties were modeled as both structured and unstructured spatial effects. We observe that circumcision reduces the risk of HIV infection. The results also indicate that men in the urban areas were more likely to be infected by HIV as compared to their rural counterpart. Men with higher education had the lowest risk of HIV infection. A nonlinear relationship between HIV infection and age was established. Risk of HIV infection increases with age up to the age of 40 then declines with increase in age. Men who had STI in the last 12 months were more likely to be infected with HIV. Also men who had ever used a condom were found to have higher likelihood to be infected by HIV. A significant spatial variation of HIV infection in Kenya was also established. The study shows the practicality and flexibility of Bayesian semi-parametric regression model in analyzing epidemiological data.     

构建基于磁珠微流控芯片的iFlora遗传信息高效获取系统

磁珠以其比表面积大、易与生物分子耦联、操控方便等优点,在生命科学中得到了广泛应用。随着微机电系统（MicroElectroMechanicalSystems,MEMS）技术的发展,将磁珠应用到微流控芯片中构建磁珠微流控分析系统,为生物样品分离、检测提供了一种全新方法。新一代植物志iFlora融入现代DNA测序技术．应用高速发展的信息、网络技术及云计算分析平台,收集、整合和管理植物物种相关信息,以实现物种智能鉴定和数据提取,而包括DNA条形码在内的遗传信息及其获取技术在iFlora中的作用至关重要。本文重点概述了基于纳米磁珠的微流控芯片技术及其在分子生物学领域中的应用,提出构建基于纳米磁珠微流控芯片的iFlora遗传信息采集系统,在微芯片上完成从DNA提取到测序全过程,实现物种遗传信息的快速、高效获取。     

Habitat suitability modelling and implications for management of roan antelopes in Kenya

The roan antelope is locally endangered in Kenya with <50 individuals remaining in Ruma National Park (RNP). An understanding of the habitat requirements is essential to formulate habitat management strategies for species recovery. This study identifies habitat and management features affecting roan distribution in different seasons using information‐theoretic and multimodel inference (MMI) techniques. MMI averaged models were coupled with GIS data to develop habitat suitability maps. Results showed that roan habitat suitability is determined by different factors in different seasons but overall habitat was more important than management. Best predictors of roan incidence were wooded grassland, open grassland and water points. Water was more significant in the dry season whilst vegetation burned status, slope, soil type, distances to snares, park fence and security gates were important predictors at other seasons. Receiver operating characteristic (ROC) plots confirmed that the models fitted well to the data (AUC>0.9). Sustainable conservation of roans in RNP can be achieved via long‐term habitat management including prescribed burning and construction of more water points and short‐term urgent solutions to key management issues, especially control of poaching.