论昆虫空间生态学研究

空间特征是昆虫生态学研究的热点之一 ,具有重要的理论与应用意义。该文从理论、尺度、时空动态模型、技术手段及研究热点几个方面概述近期昆虫空间生态学研究进展。主要理论包括概率及统计模型、地学统计学、景观生态学、集合种群生态学 ;研究技术涉及地理信息系统、遥感、计算机辅助分析等。简要论述研究的空间尺度问题 ,介绍空间分子生态、进化生态等新研究热点在昆虫空间生态领域的发展 ,并分析昆虫空间生态学存在的问题和发展趋势。     

地质统计学理论与方法及其在昆虫生态学中的应用

空间相关是昆虫生态学中普遍存在的一种客观现象 ,但这种空间相关性在传统的统计学分析中被忽略了。据此 ,文章对常用的地质统计学的空间相关理论和方法、以及这些理论和方法在昆虫生态学中的应用途径和研究进展作了简述。此外 ,对GIS在昆虫空间相关分析中的应用途径和方法也作了探讨。通过综合分析和比较 ,作者认为 ,未来地质统计学的发展将更多地与GIS融为一体 ,并且二者将与传统的时间序列方法和生物统计学方法有机结合 ,共同应用于昆虫生态学的时空分析和预测之中     

生态学的时空特性(英文)

 众所周知,几乎所有的生态学特征和现象都受限于一定的时间和空间。因此,相应的科学假设和相关的生态学结论也只能基于这些特定的时空尺度范围。我们利用颇为熟知的事例,引用生态学文献中的具体实例,提纲挈领地论述了时空在生态学研究中的重要性。这些实例包括我们在长白山对云、冷杉(Picea jezoensis, Abies nephrolepis)林林冠结构的模拟、在北美应用遥感和气象方法对碳通量的估算,以及测定湿地生态系统对加温的反应等。文中所涉及的所有生态学现象,对时间和空间都有强烈的依赖性。因而, 从生态学问题的提出,到科学假设的演绎,以至试验设计和综合数据分析,都必须以时、空为前提,才不至于导致荒谬结论。     

森林害虫发生的空间模式研究进展

森林昆虫种群表现出多样的时空模式,空间同步性是其中最常见的。回顾了森林昆虫空间同步性的特点、形成机制及研究方法方面的进展。森林害虫发生的同步性是广泛存在的,但不同昆虫种类的同步性大小不同。空间同步性常随距离的增大而下降,还与时间尺度有关。Moran效应和扩散是解释空间同步性的两种主要机制,通常Moran效应的影响要比扩散大。从虫害发生数据的获取、同步性的度量及成因3个方面介绍了空间同步性的研究方法方面的进展。利用树轮生态学原理重建森林虫害发生历史的方法可在事后获取可靠的数据,很值得国内研究者借鉴和应用。在空间自相关度量上,空间统计学方法和地统计学方法都是非常有力的手段,但由于不能处理多时间点数据而限制了其在同步性研究中的应用。在同步性成因研究中,利用变异分解将基于距离的Moran特征向量图(dbMEM)作为空间变量研究害虫发生的驱动力是比较新颖的研究方法。     

《昆虫种群生态学——基础与前沿》

该书由科学出版社2005年出版，徐汝梅、成新跃编。介绍了昆虫生态学的基础与前沿，包括昆虫种群数量的时、空动态规律、调节机制及有关的研究方法。同时，还特别强调了空间生态学在昆虫种群生态学研究中的应用;并介绍了当前昆虫种群生态学的研究热点，如种群变动的遗传机制、昆虫与植物的协同进化等；结合重大的生态学问题，对昆虫暴发的一般理论、昆虫濒危与生物多样性保育、种群扩散与生物入侵、全球变化与昆虫种群动态等进行了论述。     

地理信息系统及其在昆虫生态学中的应用

以往昆虫种群生物学的研究只着重于时间的变化,处理多维数据的困难性和复杂性始终困扰着昆虫生态学研究者们,使其难以对复杂的空间现象进行有效的研究,尤其是涉及大范围、多因素的时空动态研究,更是缺乏合适的空间数据管理和分析工具。而近年来地理信息系统（ＧｅｏｇｒａｐｈｉｃＩｎｆｏｒｍａｔｉｏｎＳｙｓｔｅｍｓ,ＧＩＳ）的迅速发展为研究昆虫生态学的空间问题开辟了新的途径。地理信息系统的定义有很多,通常可以将其定义为在计算机软件和硬件的支持下,运用系统工程的方法和理论,科学管理和综合分析具有空间内涵的地理数据,…     

无人机遥感技术在景观生态学中的应用

野外数据的获取是生态学研究的挑战之一,而通过遥感技术能够实现对地球表面的多面立体观测,获取丰富多样的空间信息数据,开展从微观到宏观不同尺度上的景观单元(包括物种、种群、群落、生态系统等)的空间关系研究。传统卫星遥感影像受空间和时间分辨率的限制,难以满足局域尺度或者时间序列上的景观空间生态学研究需求。无人机遥感技术为生态学研究的野外数据获取提供了一种新方法,以其灵活、高效、简便等特点弥补了传统卫星遥感的空间分辨率低、重访周期长、云雾影响等方面的不足,在景观空间生态学研究中受到越来越多的关注。简要介绍无人机类型及其搭载常见的传感器类型,分别从不同尺度的景观单元,即物种、种群、群落以及生态系统水平上探讨其应用进展,并指出当前无人机技术在景观生态学研究中存在的挑战与困难,同时展望了未来可能的研究热点,以期对今后无人机遥感技术在景观生态学领域的应用研究有所启发。     

昆虫种群空间格局研究方法的最近进展

<正> 昆虫种群空间格局是由物种的行为内禀特征与栖境相互作用而形成的种群个体在空间的分布状况。它的研究无论在生态学理论,还是生产实践上都具有重要意义。空间格局的研究方法可归纳为3类:(1)频次分布拟合x~2检验法;(2)扩散型指数法;(3)回归模型分析法。随着对大量昆虫种群空间格局的实际研究,     

空间分析方法在微生物生态学研究中的应用

微生物生态正在受到越来越多的关注,对其研究也渐趋深入。然而由于微生物个体微小的特点及研究手段的限制,多数研究还停留在探索阶段,研究方法也在不断完善当中。近年来,较多的研究开始探讨空间因素在微生物多样性和分布中的影响,对空间分布的探讨有助于更好地认识生态过程,是一种有力的研究手段。微生物空间分析方法已经成为微生物生态学领域中重要的研究方向之一,我国空间方法在微生物生态研究中的应用还没有得到普遍的重视。从不同研究角度出发,结合空间统计的作用,对空间统计方法在微生物生态研究中的应用的必要性及现状做了评述。介绍了空间自相关性的检验,方差图,Mantel检验,Kriging插值等方法在微生物生态研究中的应用,并论述了微生物研究中的尺度问题。这一梳理,对丰富微生物生态学研究中的新方法、新手段具有一定价值。     

虫草蝠蛾幼虫空间分布型的研究

空间分布型的研究是现代理论生态学的重要基础工作之一,它在实际应用上亦具重要意义。它不仅可揭示出种群的空间结构特征,而且还是确定抽样技术、资料代换和正确估计种群数量的基础。 目前,国内外有关昆虫空间分布型的研究多限于农林业害虫,对其它昆虫的空间分布研究甚少。虫草蝠蛾是我国名贵中药材冬虫夏草的寄主昆虫,主要分布在青海、西藏、四川、云南四省境内的高山草甸。近年来,冬虫夏草产量逐年下降,远远不适应市场的需求,更因自然资源日趋减少,大有枯竭之势。为挽救这一珍贵资源昆虫,急待尽     

An expectation maximization algorithm for training hidden substitution models

We derive an expectation maximization algorithm for maximum-likelihood training of substitution rate matrices from multiple sequence alignments. The algorithm can be used to train hidden substitution models, where the structural context of a residue is treated as a hidden variable that can evolve over time. We used the algorithm to train hidden substitution matrices on protein alignments in the Pfam database. Measuring the accuracy of multiple alignment algorithms with reference to BAliBASE (a database of structural reference alignments) our substitution matrices consistently outperform the PAM series, with the improvement steadily increasing as up to four hidden site classes are added. We discuss several applications of this algorithm in bioinformatics.     

A substitution matrix for structural alphabet based on structural alignment of homologous proteins and its applications

Analysis of protein structures based on backbone structural patterns known as structural alphabets have been shown to be very useful. Among them, a set of 16 pentapeptide structural motifs known as protein blocks (PBs) has been identified and upon which backbone model of most protein structures can be built. PBs allows simplification of 3D space onto 1D space in the form of sequence of PBs. Here, for the first time, substitution probabilities of PBs in a large number of aligned homologous protein structures have been studied and are expressed as a simplified 16 x 16 substitution matrix. The matrix was validated by benchmarking how well it can align sequences of PBs rather like amino acid alignment to identify structurally equivalent regions in closely or distantly related proteins using dynamic programming approach. The alignment results obtained are very comparable to well established structure comparison methods like DALI and STAMP. Other interesting applications of the matrix have been investigated. We first show that, in variable regions between two superimposed homologous proteins, one can distinguish between local conformational differences and rigid-body displacement of a conserved motif by comparing the PBs and their substitution scores. Second, we demonstrate, with the example of aspartic proteinases, that PBs can be efficiently used to detect the lobe/domain flexibility in the multidomain proteins. Lastly, using protein kinase as an example, we identify regions of conformational variations and rigid body movements in the enzyme as it is changed to the active state from an inactive state.     

Generation time,life history and the substitution rate of neutral mutations

Our understanding of molecular evolution is hampered by a lack of quantitative predictions about how life-history (LH) traits should correlate with substitution rates. Comparative studies have shown that neutral substitution rates vary substantially between species, and evidence shows that much of this diversity is associated with variation in LH traits. However, while these studies often agree, some unexplained and contradictory results have emerged. Explaining these results is difficult without a clear theoretical understanding of the problem. In this study, we derive predictions for the relationships between LH traits and substitution rates in iteroparous species by using demographic theory to relate commonly measured life-history traits to genetic generation time, and by implication to neutral substitution rates. This provides some surprisingly simple explanations for otherwise confusing patterns, such as the association between fecundity and substitution rates. The same framework can be applied to more complex life histories if full life-tables are available.     

Connectivity of Neutral Networks,Overdispersion, and Structural Conservation in Protein Evolution

Abstract Protein structures are much more conserved than sequences during evolution. Based on this observation, we investigate the consequences of structural conservation on protein evolution. We study seven of the most studied protein folds, determining that an extended neutral network in sequence space is associated with each of them. Within our model, neutral evolution leads to a non-Poissonian substitution process, due to the broad distribution of connectivities in neutral networks. The observation that the substitution process has non-Poissonian statistics has been used to argue against the original Kimura neutral theory, while our model shows that this is a generic property of neutral evolution with structural conservation. Our model also predicts that the substitution rate can strongly fluctuate from one branch to another of the evolutionary tree. The average sequence similarity within a neutral network is close to the threshold of randomness, as observed for families of sequences sharing the same fold. Nevertheless, some positions are more difficult to mutate than others. We compare such structurally conserved positions to positions conserved in protein evolution, suggesting that our model can be a valuable tool to distinguish structural from functional conservation in databases of protein families. These results indicate that a synergy between database analysis and structurally based computational studies can increase our understanding of protein evolution.     

Similarity and difference among rainforest fruit-feeding butterfly communities in Central and South America

1. Documenting species abundance distributions in natural environments is critical to ecology and conservation biology. Tropical forest insect faunas vary in space and time, and these partitions can differ in their contribution to overall species diversity. 2. In the Neotropics, the Central American butterfly fauna is best known in terms of general natural history, but butterfly community diversity is best documented by studies on South American fruit-feeding butterflies. Here, we present the first long-term study of fruit-feeding nymphalid species diversity from Central America and provide a unique comparison between Central and South American butterfly communities. 3. This study used 60 months of sampling among multiple spatial and temporal partitions to assess species diversity in a Costa Rican rainforest butterfly community. Abundance distributions varied significantly at the species and higher taxonomic group levels, and canopy and understorey samples were found to be composed of distinct species assemblages. 4. Strong similarities in patterns of species diversity were found between this study and one from Ecuador; yet, there was an important difference in how species richness was distributed in vertical space. In contrast to the Ecuadorian site, Costa Rica had significantly higher canopy richness and lower understorey richness. 5. This study affirms that long-term sampling is vital to understanding tropical insect species abundance distributions and points to potential differences in vertical structure among Central and South American forest insect communities that need to be explored.     

pANT: a method for the pairwise assessment of nonfunctionalization times of processed pseudogenes

We present a method for pairwise Assessment of Nonfunctionalization Times (pANT) in processed pseudogenes. Contrary to existing methods for estimating nonfunctionalization times, pANT utilizes previously calculated probabilities of nucleotide substitution as explicit rate measurements, rather than assume that the substitution rates are the same for all nucleotides. Thus, the method allows a more accurate computation of the time that has elapsed since the nonfunctionalization of a pseudogene. Whereas existing methods require the sequence of an orthologous functional gene, which is not always at hand, pANT only uses the pairwise alignment of the gene/pseudogene pair, thus expanding the range of problems that can be tackled. To estimate evolutionary times in nonfunctional sequences, pANT measures the differences in the pairwise alignment of a gene and its paralogous processed pseudogene, using only the first and second codon positions. It assumes that, because of functional constraints, these positions in the sequence of the functional homolog have not changed since the time of nonfunctionalization of the pseudogene. Hence, the sequence of the gene may be used as the ancestor of the pseudogene. We show that the method's reliance on a detailed substitution matrix, which is derived separately for each species, makes it more accurate than existing methods. We applied pANT to the case of the unitary alpha-1,3-galactosyltransferase human pseudogene and found that our estimate of the nonfunctionalization time was in agreement with that obtained by taxonomic and paleontological considerations pertaining to the divergence between platyrrhines (New World monkeys) and cattarhines (Old World monkeys).     

The value of space‐for‐time substitution for studying fine‐scale microevolutionary processes

When the drivers of biological turnover in space are the same as those that drive turnover through time, space can be substituted for time to model how patterns of variation are predicted to change into the future. These space‐for‐time substitutions are widely used in ecological modeling but have only recently been applied to the study of microevolutionary processes, particularly over relatively fine spatial and temporal scales. Here, we review recent examples that have employed space‐for‐time substitution to study genetic patterns on stationary and non‐stationary landscapes and examine whether space can reliably substitute for time in studies of population divergence, genetic structure, and adaptive evolution. Although there are only a relatively few examples, several recent studies were excellently crafted to provide valuable insights into the conditions governing the validity of space‐for‐time substitutions applied to population genetic data. We found that, although caution should be taken, space‐for‐time substitutions appear valid for studying microevolutionary processes on both stationary and non‐stationary landscapes. Further studies can help to evaluate the conditions under which space‐for‐time substitutions are reliable. When these methods are reliable, they will play an important role in modeling genetic responses to environmental change, population viability on non‐stationary landscapes, and patterns of divergence and adaptation.