烟青虫种群动态模型的研究

在对烟青虫Ｈｅｌｉｃｏｖｅｒｐａａｓｓｕｌｔａ实验种群研究的基础上,应用变维矩阵综合差分方程,建立了烟青虫种群动态模拟模型,模型采用分块矩阵的方式,以实际日龄为步长,通过适当增加矩阵维数,对虫期（态）向量实行按矩阵维数的变化而伸缩的形式,使模型不但适合于变温条件,而且能够表示烟青虫个体发育的差异,该理论模型有待于地方化。     

稻纵卷叶螟(Cnaphalocrocis medinalis Guene'e)种群生命系统模型的研究

经过五年来对稻纵卷叶螟自然种群生命表的研究,组建了预测种群动态的生命系统模拟模型。本模型为一变维矩阵组合模型。除能随环境温度而改变矩阵维数外,采用生理年龄为矩阵步长。每一虫期内各个体的发育不一致,矩阵中各元素均为某些环境因素的函数,共组建有18个子模式。在输入起始日期,预测期限,水稻生育期,环境温、湿度和初始种群各年龄向量后,即可自动打印出逐日种群年龄向量及总虫量。计算机模拟曲线与实测曲线基本吻合。本模型可用来预测南京地区稻纵卷叶螟二代迁入峰后种群的发展以至第三代种群各虫态的起始虫量和发生期。     

呼中林区森林景观的历史变域模拟及评价

在大兴安岭地区呼中区,将物种的年龄和分布信息进行随机化处理后,应用空间直观景观模型LANDIS对森林景观进行长时间(2500a)模拟,取物种演替稳定时间段作为模拟历史变域的数据来源.分别在景观水平和年龄类型水平上利用景观指数空间分析、主成分分析和核密度估计方法分析景观格局历史变域的模拟结果,并在二维空间坐标内,将研究区1990年、2000年森林景观特征与之比较.结果表明,各树种面积比例在模拟900a后都达到稳定状态,可作为无干扰条件下森林景观特征的历史变域;由于长期采伐,研究区1990年景观的斑块面积和破碎化程度都偏离了该历史变域,其中,过熟林偏离最明显,其斑块面积远小于历史变域,破碎化程度非常严重;虽然1990年后的采伐管理方案比之前的更为合理,但2000年的森林景观仍旧继续偏离历史变域.     

昆虫种群动态模拟模型

昆虫是动物界中最大的类群,与人类有着密切的利害关系。对昆虫的数量预测与符合经济和生态规律的管理,一直都被国内外列入重点研究课题。种群动态模拟是害虫管理中重要的基础工作。近十年来,关于昆虫种群动态模型的理论和实验研究进展迅速。现分别从单种种群和多种种群两个方面对国内外近些年来昆虫种群动态模拟模型的研究进展进行了概括和总结。单种种群从两个方面阐述:一是最基本的种群动态模拟模型Log istic方程的研究成果,包括方程的修正、参数的拟合与最优捕获策略等;另一个方面是对种群动态模拟常用的矩阵模型的概述,主要介绍不等期年龄组、矩阵维数的变化、矩阵维数与历期的关系、个体之间的发育差异以及发育速率差异等等对昆虫种群动态模型的影响。多种群主要从建模和模型应用两个部分对国内外研究成果进行综述。最后,对种群动态模拟模型研究的发展方向做了深入地讨论,即在原有的数据采集工作的基础上,使用面向对象程序设计语言,把各种要素包括各种物种及各种环境条件抽象成类,用消息传递来表示昆虫种群内个体与个体、昆虫种群与环境之间的相互作用,再结合先进的数学算法,建立一个直观的、操作简单的昆虫种群动态模型库,使模型结构与现实世界有最大的相似性。这样就可以实现昆虫种群动态的可视化、立体化、实时化和精确化的监测及预测。     

陕西不同地区栓皮栎种群年龄结构动态模型的研究

栓皮栎种群动态模型能阐明其自然种群动态的规律,揭示种群的内在机制和对种群行为进行预测。矩阵模型是一种i状态分布方法,依靠矩阵形式来处理种群的特征分布,可以模拟和预测种群中各个年龄组的数量动态和年龄结构的变化,它能够从目前已知的年龄结构及种群的生存率和生育率,来推测种群的未来年龄结构。在研究栓皮栎种群动态时,也借用该模型对栓皮栎种群各年龄组的结构和数量动态作出预测。Leslie矩阵模型就是该模型中的一种,利用该模型的理论和方法,对栓皮栎种群的自然变化过程进行了模拟和预测。结果发现,从分布中心到分布边缘,随着生境的差异,栓皮栎种群产生幼苗的年龄级、内禀增长率、生育力和幼苗的数量都发生变化,预测结果与实际反映的情况基本一致,表明Leslie矩阵模型是一种较为理想的反映种群动态的模型。模型表达形式简单,参数生态学意义确切,应用精度高,从而达到准确预测栓皮栎种群动态的目的。     

基于风险交流视角的水产品质量安全风险分级研究

风险分级是风险管理的重要组成部分。本文在传统二维风险矩阵的基础上,将消费者敏感性维度引入风险矩阵,并以水产品为例,构建了包括严重性、可能性、敏感性的水产品质量安全风险分级模型,并依据不同风险程度提出了优化风险交流策略的建议。     

食物链种群模型的格子Boltzmann方法模拟

用格子Boltzmann方法求解用反应一扩散方程组描述的食物链种群模型．我们用一维和二维方程组进行数值实验,模拟结果与现有的数值实验结果很好地吻合,反映了格子Boltzmann方法的高效性和稳定性,并就二维格子、Boltzmann格式,通过其等价的差分格式,由极值原理证明了该格式的稳定性．     

手术前后三维动脉瘤模型的血液动力学模拟对比

本研究目的在于从临床患者的医学影像出发,在手术前后分别对三维动脉瘤模型进行了定常模拟,观察动脉瘤模型内的流场形态以及各血液动力学参数的变化并进行讨论。由于三维的数值模拟比二维的跟接近实际,而且更加直观形象,所以研究结果对于分析动脉瘤的破裂机理具有重要的临床应用价值。     

构建和评估猪氨基酰化酶I的三维结构

运用同源模建的方法构建了pACY1三维结构模型,并在能量最小化后对模型进行分子动力学模拟和结构合理性评估。同源模建生成了50个原始模型,经过PROCHECK评测后,筛选出模型A、B进行能量最小化,并得到模型A1、B1。分子动力学模拟结果表明模型B1二聚体结构较稳定。PROCHECK、ProSa以及WHATIF检测结果验证了模型B1属于合理性结构。得到的猪氨基酰化酶Ⅰ(pACY1)的三维结构,为研究其结构与功能关系打下基础。     

山美水库流域水量水质模拟的SWAT与CE-QUAL-W2联合模型

为更好地模拟分析流域非点源污染对山美水库水质的影响,联合运用流域日尺度分布式水文模型SWAT和二维垂向水动力水质模型CE-QUAL-W2,将SWAT模型的时序输出作为CE-QUAL-W2模型的输入条件,构建了山美水库流域水量水质模拟联合模型,并对流域径流、输沙和污染物以及水库的水位、水温和无机氮等变量进行了率定.结果表明: 尽管受流域部分计算结果的影响,误差会累积到对下游水库水体的计算,但模型的模拟结果与实测数据的吻合程度仍较高,说明联合模型可以较好地反映山美水库流域及库区水体的水动力和污染过程.模型的使用可以为定位流域关键污染源区及控制水库富营养化提供科学依据.     

变维矩阵模型在温室白粉虱种群动态模拟中的应用

自七十年代以来,温室白粉虱(Trialeurodes vaporariorum Westw.)已成为我国北部温室中的主要害虫。为了最经济地将害虫控制在经济允许水平以下,必须进行数量预报和最优管理。为此,建立种群动态的模拟模型是必不可少的一步。 当然,影响昆虫种群动态的因子是很多的。但作为变温动物,温度因子是最基本的因子之一。尤其对那些象温室白粉虱的昆虫,温室系统相对地简单,天敌从种类到数量上都很     

A hyperspace model to decipher the genetic architecture of developmental processes: allometry meets ontogeny

To better utilize limited resources for their survival and reproduction, all organisms undergo developmental changes in both body size and shape during ontogeny. The genetic analysis of size change with increasing age, i.e., growth, has received considerable attention in quantitative developmental genetic studies, but the genetic architecture of ontogenetic changes in body shape and its associated allometry have been poorly understood partly due to the lack of analytical tools. In this article, we attempt to construct a multivariate statistical framework for studying the genetic regulation of ontogenetic growth and shape. We have integrated biologically meaningful mathematical functions of growth curves and developmental allometry into the estimation process of genetic mapping aimed at identifying individual quantitative trait loci (QTL) for phenotypic variation. This model defined with high dimensions can characterize the ontogenetic patterns of genetic effects of QTL over the lifetime of an organism and assess the interplay between genetic actions/interactions and phenotypic integration. The closed forms for the residual covariance matrix and its determinant and inverse were derived to overcome the computational complexity typical of our high-dimensional model. We used a worked example to validate the utility of this model. The implications of this model for genetic research of evo-devo are discussed.     

A model of developmental canalization,applied to human cranial form

Developmental mechanisms that canalize or compensate perturbations of organismal development (targeted or compensatory growth) are widely considered a prerequisite of individual health and the evolution of complex life, but little is known about the nature of these mechanisms. It is even unclear if and how a “target trajectory” of individual development is encoded in the organism’s genetic-developmental system or, instead, emerges as an epiphenomenon. Here we develop a statistical model of developmental canalization based on an extended autoregressive model. We show that under certain assumptions the strength of canalization and the amount of canalized variance in a population can be estimated, or at least approximated, from longitudinal phenotypic measurements, even if the target trajectories are unobserved. We extend this model to multivariate measures and discuss reifications of the ensuing parameter matrix. We apply these approaches to longitudinal geometric morphometric data on human postnatal craniofacial size and shape as well as to the size of the frontal sinuses. Craniofacial size showed strong developmental canalization during the first 5 years of life, leading to a 50% reduction of cross-sectional size variance, followed by a continual increase in variance during puberty. Frontal sinus size, by contrast, did not show any signs of canalization. Total variance of craniofacial shape decreased slightly until about 5 years of age and increased thereafter. However, different features of craniofacial shape showed very different developmental dynamics. Whereas the relative dimensions of the nasopharynx showed strong canalization and a reduction of variance throughout postnatal development, facial orientation continually increased in variance. Some of the signals of canalization may owe to independent variation in developmental timing of cranial components, but our results indicate evolved, partly mechanically induced mechanisms of canalization that ensure properly sized upper airways and facial dimensions.     

Rapid divergence of genetic variance-covariance matrix within a natural population

The matrix of genetic variances and covariances (G matrix) represents the genetic architecture of multiple traits sharing developmental and genetic processes and is central for predicting phenotypic evolution. These predictions require that the G matrix be stable. Yet the timescale and conditions promoting G matrix stability in natural populations remain unclear. We studied stability of the G matrix in a 20-year evolution field experiment, where a population of the cosmopolitan parthenogenetic soil nematode Acrobeloides nanus was subjected to drift and divergent selection (benign and stress environments). Selection regime did not influence the level of absolute genetic constraints: under both regimes, two genetic dimensions for three life-history traits were identified. A substantial response to selection in principal components structure and in general matrix pattern was indicated by three statistical methods. G structure was also influenced by drift, with higher divergence under benign conditions. These results show that the G matrix might evolve rapidly in natural populations. The observed high dynamics of G structure probably represents the general feature of asexual species and limits the predictive power of G in phenotypic evolution analyses.     

Analysing growth and development of plants jointly using developmental growth stages

Background and Aims Plant growth, the increase of organ dimensions over time, and development, the change in plant structure, are often studied as two separate processes. However, there is structural and functional evidence that these two processes are strongly related. The aim of this study was to investigate the co-ordination between growth and development using mango trees, which have well-defined developmental stages.Methods Developmental stages, determined in an expert way, and organ sizes, determined from objective measurements, were collected during the vegetative growth and flowering phases of two cultivars of mango, Mangifera indica. For a given cultivar and growth unit type (either vegetative or flowering), a multistage model based on absolute growth rate sequences deduced from the measurements was first built, and then growth stages deduced from the model were compared with developmental stages.Key Results Strong matches were obtained between growth stages and developmental stages, leading to a consistent definition of integrative developmental growth stages. The growth stages highlighted growth asynchronisms between two topologically connected organs, namely the vegetative axis and its leaves.Conclusions Integrative developmental growth stages emphasize that developmental stages are closely related to organ growth rates. The results are discussed in terms of the possible physiological processes underlying these stages, including plant hydraulics, biomechanics and carbohydrate partitioning.     

Exploring multicollinearity using a random matrix theory approach

Clustering of gene expression data is often done with the latent aim of dimension reduction, by finding groups of genes that have a common response to potentially unknown stimuli. However, what is poorly understood to date is the behaviour of a low dimensional signal embedded in high dimensions. This paper introduces a multicollinear model which is based on random matrix theory results, and shows potential for the characterisation of a gene cluster's correlation matrix. This model projects a one dimensional signal into many dimensions and is based on the spiked covariance model, but rather characterises the behaviour of the corresponding correlation matrix. The eigenspectrum of the correlation matrix is empirically examined by simulation, under the addition of noise to the original signal. The simulation results are then used to propose a dimension estimation procedure of clusters from data. Moreover, the simulation results warn against considering pairwise correlations in isolation, as the model provides a mechanism whereby a pair of genes with `low' correlation may simply be due to the interaction of high dimension and noise. Instead, collective information about all the variables is given by the eigenspectrum.     

Development and phenotypic correlations: the evolution of tooth shape in Sorex araneus

Summary Do morphogenetic processes cause common patterns of phenotypic covariation, and do those patterns evolve over microevolutionary timescales? Evolution of molar shape variance–covariance (P) matrixes was studied in five populations of the common shrew, Sorex araneus. P matrix evolution was assessed using matrix correlation, matrix disparity, and common principal component analysis (CPCA). Significant changes in covariance structure were found among the populations, but the differences were small. A computer model was used to estimate the theoretical covariance introduced into the phenotype by developmental interactions. Molar developmental processes explained some of the covariance in the shrew samples, especially as measured by matrix correlation, but the proportion was relatively small. Developmental principal components (PCs) were only infrequently associable with common principal components. The results suggest that molar shape P matrixes can evolve quickly in a manner only loosely constrained by development, and that their shared covariance is probably dominated by factors more proximate than development. Rarefaction showed that sample size severely affected P comparisons when n < 15 for matrix correlation and disparity, and when n < 30 for CPCA. Among CPCA evaluation criteria, Akaike Information Criterion performed better than jump‐up at n < 30, but worse at n > 30.