结构稳定性: 概念、方法和应用

群落内物种间相互作用的结构是高度组织化的。群落结构对多物种共存的影响机制是群落生态学的核心科学问题之一。目前生态学界在这一问题上存在多种不同的观点。一个可能的原因是, 由于环境因子的复杂性, 大部分研究忽略了环境因子对群落结构和物种共存的重要影响。在这一背景下, 近期发展起来的结构稳定性理论系统地联系了群落结构、环境因子和物种共存, 并在此基础上建立了一个和经验数据紧密结合的理论框架。本文首先简要回顾了当前关于群落结构研究的争鸣, 然后介绍了结构稳定性的理论框架和计算方法, 最后详细介绍了结构稳定性理论在不同生态群落和不同生态学问题中的应用。在全球气候变化的背景下, 结构稳定性理论提供了一种新的视角来理解群落层面的生物多样性维持机制。     

杜鹃属植物与杜鹃灌丛群落的研究进展

对杜鹃属(Rhododendron L.)植物起源、中国分布、适应性、灌丛群落结构特征和演替特征等问题进行了综述,并对杜鹃属植物的深入研究和合理利用进行展望。中国西南地区以及喜马拉雅至缅甸北部地区为杜鹃属植物的起源中心,贵州百里杜鹃林是全球最大野生杜鹃资源库。杜鹃属植物的适应性与所在区系的同质性、海拔相似度、进化程度、关键功能性状等密切相关,基于进化-形态功能特征的比较为选育适应性优良的杜鹃品种提供了参考。杜鹃灌丛群落具有特殊性,表现出复杂的多层次垂直结构、镶嵌式水平结构和明显的年龄结构特征。依据群落具备优势种生态位宽度大且种群间的生态位相似性比例较小来判定杜鹃灌丛群落已演替至顶级的观点仍有待考证。     

兴隆山国家级自然保护区不同生境的蝴蝶群落结构与种-多度分布

为明确甘肃兴隆山国家级自然保护区内的蝴蝶种类, 以及不同生境的蝴蝶群落结构与种-多度分布的变化情况, 在全部5个林场选取6条样线, 于2015-2018年连续4年采用样线法对保护区的蝴蝶进行调查和采集, 并分析了其多样性指数及种-多度分布。4年共采集蝴蝶标本5,719号, 经鉴定隶属8科69属120种。眼蝶科(3,093号)是保护区的优势类群, 喙蝶科仅采集到1号标本(朴喙蝶, Libythea lepita), 为保护区的稀有种类。其中, 各样线的种数、个体数、多样性指数以及物种丰富度表现为: 样线I最高, 样线IV次之, 说明其生境结构稳定, 环境良好, 适合蝶类生存; 样线III蜜源植物丰富, 各项指数较高; 样线V海拔较高, 各项指数较低; 样线II植物群落结构单一, 各项指数最低。相似性系数分析结果表明: 样线I和VI、III和IV、III和VI均为中等相似; 其余各样线间为中等不相似。区系分析结果表明: 古北种有63种, 占总种数的52.5%; 东洋种2种, 占总种数的1.7%; 广布种55种, 占总种数的45.8%。说明古北种占绝对优势, 且明显高于东洋种, 具有很强的地区代表性。种-多度分布分析结果表明: 样线I和IV呈现出对数正态分布, 模型拟合效果较好; 样线II和VI为非典型的对数级数模型, 符合生态位优先占领假说。说明不同生境以及人为干扰因素与蝶类多样性关系密切, 表现出单一生态系统蝴蝶群落的多样性指数较低, 复杂生态系统其多样性指数较高的特点。     

湖南高望界国家级自然保护区及其周边蝶类多样性与影响因素

为了解湖南高望界国家级自然保护区蝶类多样性本底及其影响因素, 2016年5月至2018年10月, 我们采用样线法对保护区内外的6种生境(保护区内4种, 区外2种)开展了20次蝶类多样性调查。共记录蝴蝶个体13,956只, 依照五科分类系统, 隶属5科113属239种, 其中湖南省蝶类新记录17种。区系成分以东洋种为主(139种, 占58.1%), 广布种次之(97种, 占40.6%), 古北种最少(3种, 占1.3%)。对不同生境的蝶类群落多样性指数进行分析后发现, 人为干扰程度和生境异质性共同影响蝶类多样性。不同生境相似性分析结果表明, 蝶类群落的相似度与人为干扰程度和植被类型差异密切相关。3年间, 蝶类多样性指数月度变化基本一致, 蝶类物种数、多样性指数与月均温间呈显著正相关, 与月降水量无相关性。综上, 蝶类多样性受到人为干扰程度和气象因子的影响。为保护蝶类资源, 建议保护好蝶类栖息地, 减少人为干扰。     

Confidently identifying the correct K value using the ΔK method: When does K = 2?

Populations delineated based on genetic data are commonly used for wildlife conservation and management. Many studies use the program structure combined with the ΔK method to identify the most probable number of populations (K). We recently found K = 2 was identified more often when studies used ΔK compared to studies that did not. We suggested two reasons for this: hierarchical population structure leads to underestimation, or the ΔK method does not evaluate K = 1 causing an overestimation. The present contribution aims to develop a better understanding of the limits of the method using one, two and three population simulations across migration scenarios. From these simulations we identified the “best K” using model likelihood and ΔK. Our findings show that mean probability plots and ΔK are unable to resolve the correct number of populations once migration rate exceeds 0.005. We also found a strong bias towards selecting K = 2 using the ΔK method. We used these data to identify the range of values where the ΔK statistic identifies a value of K that is not well supported. Finally, using the simulations and a review of empirical data, we found that the magnitude of ΔK corresponds to the level of divergence between populations. Based on our findings, we suggest researchers should use the ΔK method cautiously; they need to report all relevant data, including the magnitude of ΔK, and an estimate of connectivity for the research community to assess whether meaningful genetic structure exists within the context of management and conservation.     

Regional differences in the abiotic environment contribute to genomic divergence within a wild tomato species

The wild currant tomato Solanum pimpinellifolium inhabits a wide range of abiotic habitats across its native range of Ecuador and Peru. Although it has served as a key genetic resource for the improvement of domestic cultivars, little is known about the genetic basis of traits underlying local adaptation in this species, nor what abiotic variables are most important for driving differentiation. Here we use redundancy analysis (RDA) and other multivariate statistical methods (structural equation modelling [SEM] and generalized dissimilarity modelling [GDM]) to quantify the relationship of genomic variation (6,830 single nucleotide polymorphisms [SNPs]) with climate and geography, among 140 wild accessions. RDA, SEM and GDM each identified environment as explaining more genomic variation than geography, suggesting that local adaptation to heterogeneous abiotic habitats may be an important source of genetic diversity in this species. Environmental factors describing temporal variation in precipitation and evaporative demand explained the most SNP variation among accessions, indicating that these forces may represent key selective agents. Lastly, by studying how SNP–environment associations vary throughout the genome (44,064 SNPs), we mapped the location and investigated the functions of loci putatively contributing to climatic adaptations. Together, our findings indicate an important role for selection imposed by the abiotic environment in driving genomic differentiation between populations.     

Sunshine versus gold: The effect of population age on genetic structure of an invasive mosquito

The genetic diversity and structure of invasive species are affected by the time since invasion, but it is not well understood how. We compare likely the oldest populations of Aedes aegypti in continental North America with some of the newest to illuminate the range of genetic diversity and structure that can be found within the invasive range of this important disease vector. Aedes aegypti populations in Florida have probably persisted since the 1600‐1700s, while populations in southern California derive from new invasions that occurred in the last 10 years. For this comparison, we genotyped 1,193 individuals from 28 sites at 12 highly variable microsatellites and a subset of these individuals at 23,961 single nucleotide polymorphisms (SNPs). This is the largest sample analyzed for genetic structure for either region, and it doubles the number of southern California populations previously analyzed. As predicted, the older populations (Florida) showed fewer indicators of recent founder effect and bottlenecks; in particular, these populations have dramatically higher genetic diversity and lower genetic structure. Geographic distance and driving distance were not good predictors of genetic distance in either region, especially southern California. Additionally, southern California had higher levels of genetic differentiation than any comparably sized documented region throughout the worldwide distribution of the species. Although population age and demographic history are likely driving these differences, differences in climate and transportation practices could also play a role.     

The complete chloroplast genome of Myriophyllum spicatum reveals a 4‐kb inversion and new insights regarding plastome evolution in Haloragaceae

Myriophyllum, among the most species‐rich genera of aquatic angiosperms with ca. 68 species, is an extensively distributed hydrophyte lineage in the cosmopolitan family Haloragaceae. The chloroplast (cp) genome is useful in the study of genetic evolution, phylogenetic analysis, and molecular dating of controversial taxa. Here, we sequenced and assembled the whole chloroplast genome of Myriophyllum spicatum L. and compared it to other species in the order Saxifragales. The complete chloroplast genome sequence of M. spicatum is 158,858 bp long and displays a quadripartite structure with two inverted repeats (IR) separating the large single copy (LSC) region from the small single copy (SSC) region. Based on sequence identification and the phylogenetic analysis, a 4‐kb phylogenetically informative inversion between trnE‐trnC in Myriophyllum was determined, and we have placed this inversion on a lineage specific to Myriophyllum and its close relatives. The divergence time estimation suggested that the trnE‐trnC inversion possibly occurred between the upper Cretaceous (72.54 MYA) and middle Eocene (47.28 MYA) before the divergence of Myriophyllum from its most recent common ancestor. The unique 4‐kb inversion might be caused by an occurrence of nonrandom recombination associated with climate changes around the K‐Pg boundary, making it interesting for future evolutionary investigations.