Derivation of the mesoscopic elasticity tensor of cortical bone from quantitative impedance images at the micron scale

This paper addresses the relationships between the microscopic properties of bone and its elasticity at the millimetre scale, or mesoscale. A method is proposed to estimate the mesoscale properties of cortical bone based on a spatial distribution of acoustic properties at the microscopic scale obtained with scanning acoustic microscopy. The procedure to compute the mesoscopic stiffness tensor involves (i) the segmentation of the pores to obtain a realistic model of the porosity; (ii) the construction of a field of anisotropic elastic coefficients at the microscopic scale which reflects the heterogeneity of the bone matrix; (iii) finite element computations of mesoscopic homogenized properties. The computed mesoscopic properties compare well with available experimental data. It appears that the tissue anisotropy at the microscopic level has a major effect on the mesoscopic anisotropy and that assuming the pores filled with an incompressible fluid or, alternatively, empty, leads to significantly different mesoscopic properties.     

Semiparametric estimation of the transformation model by leveraging external aggregate data in the presence of population heterogeneity

Leveraging information in aggregate data from external sources to improve estimation efficiency and prediction accuracy with smaller scale studies has drawn a great deal of attention in recent years. Yet, conventional methods often either ignore uncertainty in the external information or fail to account for the heterogeneity between internal and external studies. This article proposes an empirical likelihood-based framework to improve the estimation of the semiparametric transformation models by incorporating information about the t-year subgroup survival probability from external sources. The proposed estimation procedure incorporates an additional likelihood component to account for uncertainty in the external information and employs a density ratio model to characterize population heterogeneity. We establish the consistency and asymptotic normality of the proposed estimator and show that it is more efficient than the conventional pseudopartial likelihood estimator without combining information. Simulation studies show that the proposed estimator yields little bias and outperforms the conventional approach even in the presence of information uncertainty and heterogeneity. The proposed methodologies are illustrated with an analysis of a pancreatic cancer study.     

空间异质性对样地数据空间外推的影响

应用模型结合的方法模拟了3个空间异质性等级预案下反应变量(气候变化下景观水平的树种分布面积)的变化情况,并分析模拟结果在预案之间的差异性,探讨了环境空间异质性对样地观测到的树种对气候变化响应向更大空间尺度外推的影响.结果表明：空间异质性在一般情况下对样地数据向土地类型尺度外推没有影响,而对样地尺度外推到海拔带尺度的影响则有较复杂的情况.对于对气候变化不敏感的树种以及非地带性树种,空间异质性对样地数据向海拔带尺度外推没有影响;对于大多数对气候变化敏感的地带性树种而言,空间异质性对样地数据向海拔带尺度外推则有影响.     

A stochastic model for the spatial distribution of species based on an aggregation–repulsion rule

The heterogeneity associated with the spatial distribution of organisms is an awkward problem in ecology because this heterogeneity directly depends on the sampling scale. To specify the scope of the influence of sampling scale on the level of species aggregation, we need data sets that entail excessive sampling costs in situ. To find a solution for this problem, we can use models to simulate patterns of organisms. These models are often very complex models that take into account heterogeneity of habitats and displacement or longevity of studied species. In this article, we introduce a new stochastic model to simulate patterns for one taxon and we want this model to be parsimonious, i.e., with few parameters and able to simulate observed patterns. This model is based on an aggregation–repulsion rule. This aggregation–repulsion rule is defined by two parameters. On a large scale, the number of aggregates present on the pattern is the first parameter. On a smaller scale, the level of aggregation–repulsion among individuals is determined by a probability distribution. These two parameters are estimated from field data set in a robust way so that the simulated patterns reflect the observed heterogeneity. We apply this model to entomological data: four Diptera families, namely the Sciaridae, Phoridae, Cecidomyiidae, and Empididae. The field data for the Phoridae family are used to simulate sampling using different trap sizes. We record changes in the coefficient of variation (C) as a function of the sampling scale, and we can suggest to ecologists emergence traps of 0.6 m², in other words a square 77 × 77 cm trap, to obtain a C value under 20%. Received: February 28, 2000 / Accepted: October 14, 2000     

植被叶面积指数遥感反演的尺度效应及空间变异性

遥感作为宏观生态学研究中数据获取的一种便捷手段,有助于把握较大尺度内生态学现象的特征.应用遥感数据反演LAI时,由于像元的异质性,不同尺度遥感数据之间的转换是遥感发展的一个重要问题.以河北省黄骅市为研究区,在利用TM和MODIS遥感数据对芦苇LAI反演误差产生原因进行分析的基础上,利用半变异函数对像元空间异质性进行了定量描述.发现NDVI算法的非线性带给LAI尺度转换的误差很小,而LAI的空间异质性则是引起LAI尺度效应的根本原因.并且当像元内空间异质性很大时半变异函数的基台值比纯像元要大得多,空间自相关的程度是引起LAI尺度转换误差的主要原因;反之,像元内空间异质性不大时,随机误差是引起LAI尺度转换误差的主要原因.当像元为纯像元时,由像元异质性引起的反演误差基本可以忽略.此外,研究区芦苇的空间相关有效尺度约为360m,超过此距离空间相关性则不复存在.     

景观生态学——概念与理论

现代景观生态学是一门新兴的、正在深入开拓和迅速发展的学科。因此 ,不但欧洲和北美的景观生态学有显著不同 ,就是在北美景观生态学短暂的发展进程中也逐渐形成了不同的观点和论说。概括地说 ,景观生态学研究的重点主要集中在下列几个方面 ,即 :空间异质性或格局的形成及动态 ;空间异质性与生态学过程的相互作用 ;景观的等级结构特征 ;格局 -过程 -尺度之间的相互关系 ;人类活动与景观结构 ,功能的反馈关系以及景观异质性 (或多样性 )的维持和管理[1～ 6] 。反映这些研究重点的主要景观生态学概念和理论是什么呢 ?本文拟在总结该学科最近 2…     

Spatial scale mediates the influence of habitat fragmentation on dispersal success: Implications for conservation

Increasingly, conservationists are seeking insights from ecological theory to choose strategies of habitat management that will best maintain threatened species. Often, these questions revolve around ways of mitigating the dangers posed by habitat fragmentation. Problems involving the scale of both animal movement and spatial heterogeneity inexorably arise when assessing the effects of fragmentation. We present results from a simple spatial model that simulates the dispersal of animals in a landscape of stochastically clustered habitat fragments. Varying the number of clusters and the spatial scale at which clustering occurs illustrates that heterogeneity has different and conflicting effects on animal movement when it occurs at different scales. Indeed, the scale of clustering is the most important feature in determining disperser performance in our model. Seeking to compare our modeling results with actual data, we review empirical studies of fragmented populations and habitats. Surprisingly, we conclude that very few studies have addressed the mechanisms by which fragmentation will influence population dynamics or, in particular, the ways in which spatial scale mediate these effects. We conclude that the explicit consideration of scale is essential in discussions of habitat fragmentation and of optimal conservation strategies.     

Covariance analyses with heterogeneity of slopes in fixed models

Techniques that describe the use of covariance when heterogeneity of slopes exists are severely limited. Although a few procedures for model selection have been recommended, none, except the hierarchical approach, is straightforward and usable with present computer programs. The hierarchical subset selection procedure presented in this paper is based on the proposition that heterogeneity may be present only for certain terms in the model. After hierarchical selection, those terms which do not involve heterogeneity are interpreted as in the usual analysis for covariance. The interpretations of those terms which do involve heterogeneity are modified with respect to significance tests performed at various values of the covariate. The hierarchical subset selection method allows one to investigate heterogeneity of slopes in covariance models as functions of the classification variables present in the design.     

Incorporation of inter-individual heterogeneity into the multistage carcinogenesis model: approach to the analysis of cancer incidence data

We investigate a multistage carcinogenesis frailty model to incorporate inter-individual heterogeneity into carcinogenic response. Attention is focused on inference concerning the effects of different sources of population heterogeneity on cancer rates. The authors consider unobserved variability arising from either carcinogen exposure or background characteristics. Gamma and Inverse-Gaussian distributions are selected for frailty models, and the baseline hazard function is the generalized Armitage-Doll model (i.e. non-frailty model) in which exposure effects shift the age scale instead of acting multiplicatively on cancer rates. For illustration, we apply the method to solid cancer data from a cohort of atomic bomb survivors to examine some features of proposed models. The results show that the Gamma frailty model for the heterogeneity of baseline rates provides the best goodness-of-fit of the model and a non-zero frailty variance. Parameter estimates are, for the most part, comparable between the Gamma and Inverse-Gaussian frailty models. In a heterogeneous population the exposure effects on young adulthood cancer rates might be underestimated for the non-frailty model. Meaningful information regarding each source of heterogeneity has been provided by the proposed method. Therefore, the multistage carcinogenesis frailty model approach is useful for analyses of epidemiological cancer data to assess population heterogeneity and heterogeneity-influenced exposure effects.     

Effects of matrix heterogeneity on animal dispersal: from individual behavior to metapopulation-level parameters

Mounting theoretical and empirical evidence shows that matrix heterogeneity may have contrasting effects on metapopulation dynamics by contributing to patch isolation in nontrivial ways. We analyze the movement properties during interpatch dispersal in a metapopulation of Iberian lynx (Lynx pardinus). On a daily temporal scale, lynx habitat selection defines two types of matrix habitats where individuals may move: open and dispersal habitats (avoided and used as available, respectively). There was a strong and complex impact of matrix heterogeneity on movement properties at several temporal scales (hourly and daily radiolocations and the entire dispersal event). We use the movement properties on the hourly temporal scale to build a simulation model to reconstruct individual dispersal events. The two most important parameters affecting model predictions at both the individual (daily) and metapopulation scales were related to the movement capacity (number of movement steps per day and autocorrelation in dispersal habitat) followed by the parameters representing the habitat selection in the matrix. The model adequately reproduced field estimates of population-level parameters (e.g., interpatch connectivity, maximum and final dispersal distances), and its performance was clearly improved when including the effect of matrix heterogeneity on movement properties. To assume there is a homogeneous matrix results in large errors in the estimate of interpatch connectivity, especially for close patches separated by open habitat or corridors of dispersal habitat, showing how important it is to consider matrix heterogeneity when it is present. Movement properties affect the interaction of dispersing individuals with the landscape and can be used as a mechanistic representation of dispersal at the metapopulation level. This is so when the effect of matrix heterogeneity on movement properties is evaluated under biologically meaningful spatial and temporal scales.     

What kind of spatial and temporal details are required in models of heterogeneous systems?

Spatial and temporal heterogeneity can make ecological systems hard to understand and model. We propose a simple classification of the types of spatial and temporal complexity contained in ecological systems, and describe the kinds of data and models needed to account for each. We classify ecological systems by the presence of heterogeneity at the scale of study, the nature of their dynamics (linear vs non-linear), attributes of the patches that constitute the heterogeneous system, and the presence and directionality of interactions among patches. Heterogeneity in space and time are nearly equivalent in our framework. Advanced modeling skills are necessary to create appropriate mathematical representations of highly complex systems (with non-linear dynamics, patches with more than one kind of important attribute, or interactive patches). Simple models can work well when the scale of heterogeneity is much finer than the scale of observation, when low precision is sufficient, when patches interact only weakly, or when empirical approaches are used to fit functions and constants. Having a way to classify complexity in space and time in ecological systems should help ecologists to select modeling approaches consistent with their abilities and goals.     

长白山次生杨桦林种群空间点格局及密度制约效应

以长白山5.2 hm²次生杨桦林样地为研究对象,利用空间点格局分析的双相关函数g（r）以及随机标签零模型和案例-对照设计法,探讨了树木种群空间格局及其密度制约效应。研究结果表明：生境异质性对不同生活型以及不同树种的成熟个体在大尺度范围上具有强烈影响。剔除生境异质性带来的影响后,在14个常见树种中有12个树种在小尺度上呈显著的空间聚集分布格局;随着空间尺度的增加聚集性分布树种数量急剧下降,在18 m尺度上聚集率下降到0。全部14个常见树种均呈现出显著的密度制约效应,表明密度制约是调节温带森林树木种群空间结构的主要作用机制。此外,密度制约与物种多度呈负相关,与亚林层和灌木层树种的同种聚集强度呈正相关。并且随着空间尺度增大受密度制约影响的树种百分比逐渐减小,14个常见树种中有11个在0-1 m处达到最大的密度制约强度。     

生态学系统的空间异质性

空间异质性是生态学系统的一个普遍牧场生,生态学家对它在生态学中的重要性已取得了比以往更深刻的认识。试图从空间异质性的含义,空间异质性与尺度和等级的关系,空间异质性的定量描述,空间异质性对生物和非生物过程的影响,以及空间异质性的动态等5个方面综述了有关空间异质性的生态学研究的新进展。     

空间粒度变化对景观格局分析的影响

认识空间异质性的多尺度依赖性和景观格局特征对尺度效应关系的影响是进行空间尺度推绎的基础。以2种真实景观(中国广东粤北植被景观与美国凤凰城城市景观)和SIMMAP景观中性模型产生的27种模拟景观为对象。利用景观格局分析软件FRAGSTATS对18种常用景观指数的尺度效应进行了系统的分析。根据这些指数对空间粒度变化的响应曲线和尺度效应关系,18种景观指数可分为3类。第1类指数随空间粒度的增大单调减小。具有比较明确的尺度效应关系(幂函数下降),尺度效应关系受景观空间格局特征的影响较小;这类指数包括缀块数、缀块密度、边界总长、边界密度、景观形状指数、缀块面积变异系数、面积加权平均缀块形状指数、平均缀块分维数和面积加权平均缀块分维数。第2类指数随空间粒度的增大将最终下降。但不是单调下降的;尺度效应关系比较多样,可表现为幂函数下降、直线下降或阶梯形下降。主要受缀块空间分布方式和缀块类优势度的交互影响;这类指数有5种：平均缀块形状指数、双对数回归分维数、缀块丰度、缀块丰度密度和Shannon多样性指数。第3类指数随空间粒度的变粗而增加。随缀块类优势度均等性的增加。尺度效应关系由阶梯形增加、对数函数增加、直线增加向幂函数增加过渡。尺度效应关系主要受缀块类优势度的影响;此类指数包括平均缀块面积、缀块面积标准差、最大缀块指数与聚集度。景观指数随空间粒度变化是一种1临界现象,当粒度大于或小于1临界值时,景观指数对空间粒度变化非常敏感。变化速率非常大。绝大部分情况下。真实景观粒度效应关系和曲线形状与模拟景观所得分析结果相似。说明模拟景观具有很好的代表性。文中也讨论了本研究结果与前人研究的异同。分析了造成差异的原因。景观指数的粒度效应关系与指数本身所反映的景观格局信息有一定关系,总体上来说。随粒度增加。缀块数、边界长度、缀块形状的复杂性、多样性将减小,而平均缀块面积和聚集度将增加。一系列的尺度效应图和不同景观指数的尺度效应关系可作为景观格局分析时指数选择、分析结果的解释和进行空间尺度推绎的参考。     

森林更新与空间异质性

森林更换是一个重要的生态学过程,一直是森林生态系统动态研究中的主要领域之一。森林更新受物理环境、自然干扰、人为干扰、更新树种特性、树种对干扰的反应等因素及其相互作用的影响。这些生物和非生物的因素随空间和时间而不断变化,构成了森林的空间异质性和时间异质性,使森林更新具有空间和时间上的变化特点,表现在异质性的格局和过程中。探索森林更新与空间异质性的内在规律,可揭示空间格局对更新的生态学过程的潜在作用机制。本文主要综述了近年来有关森林更新与空间异质性研究的主要内容和一些观点,分析了更新中空间异质性的来源,着重评述了空间异质性的生境及更新树种的反应、小尺度的空间异质性与更新动态、林分中光有效性的空间异质性与更新格局以及土壤和更新的空间异质性尺度的关联性等方面的研究。     

Synthesis by high-efficiency liquid-phase (HELP) method of oligonucleotides conjugated with high-molecular weight polyethylene glycols (PEGs)

The chemical modification of synthetic oligonucleotides has recently been investigated to improve their pharmacological utilization. In addition to chemical alterations of the backbone and of the heterocyclic bases, their conjugation with amphiphylic moieties, such as the polyethylene glycol has been proposed. The large scale production of these molecules as demanded for commercial purposes is hampered by the heterogeneity of the solid-phase processes and by the low reactivity of high-molecular weight PEGs in solution. A new synthetic procedure based on the recently developed liquid-phase method (HELP), has been set up to overcome these limitations.     

The richness–heterogeneity relationship differs between heterogeneity measures within and among habitats

The positive monotonic relationship between habitat heterogeneity and species richness is a cornerstone of ecology. Recently, it was suggested that this relationship should be unimodal rather than monotonic due to a tradeoff between environmental heterogeneity and population sizes, which increases local species extinctions at high heterogeneity levels. Here, we studied the richness–heterogeneity relationship for an avian community using two different environmental variables, foliage‐height diversity and cover type diversity. We analyzed the richness–heterogeneity within different habitat types (grasslands, savannas, or woodlands) and at the landscape scale. We found strong evidence that both positive and unimodal relationships exist at the landscape scale. Within habitats we found positive relationships between richness and heterogeneity in grasslands and woodlands, and unimodal relationships in savannas. We suggest that the length of the environmental heterogeneity gradient (which is affected by both spatial scale and the environmental variable being analyzed) affects the type of the richness–heterogeneity relationship. We conclude that the type of the relationship between species richness and environmental heterogeneity is non‐ubiquitous, and varies both within and among habitats and environmental variables.     

Intrinsic and extrinsic causes of spatial variability across scales in a metacommunity

The relative importance of extrinsic and intrinsic causes of variability is among the oldest unresolved problems in ecology. However, the interaction between large-scale intrinsic variability in species abundance and environmental heterogeneity is still unknown. We use a metacommunity model with disturbance-recovery dynamics to resolve the interaction between scales of environmental heterogeneity, biotic processes and of intrinsic variability. We explain how population density increases with environmental variability only when its scale matches that of intrinsic patterns of abundance, through their ability to develop in heterogeneous environments. Succession dynamics reveals how the strength of local species interactions, through its control of intrinsic variability, can in turn control the scale of metapopulation response to environmental scales. Our results show that the environment and species density might fail to show any correlation despite their strong causal association. They more generally suggest that the spatial scale of ecological processes might not be sufficient to build a predictive framework for spatially heterogeneous habitats, including marine reserve networks.     

红松老龄林主要树种的空间异质性特征与比较的定量研究

 空间异质性研究对认识不同尺度上的生态系统结构、功能和过程具有重要的理论意义。采用地统计学理论和方法,通过空间异质性特征和比较研究了我国东北红松老龄林中主要树种,即红松(Pinus koraiensis)、云杉(Picea koraiensis)、冷杉(Abies nephrolepis)、枫桦(Betula costata)和紫椴(Tilia amurensis)的空间异质性程度、空间异质性组成、尺度和格局问题。结果表明：红松老龄林中主要树种虽然生长在同一林分中,但是它们的空间异质性与格局具有明显的差异。红松的空间异质性程度最高,分数维较低,其空间异质性主要由空间自相关部分组成,在450m的尺度内,具有明显的空间格局。枫桦的空间异质性程度最低,分数维最大,空间异质性主要由随机部分组成,在大于100m的尺度上不存在明显的空间格局。云杉和冷杉由于生长的立地相似,因此具有相似的空间异质性特征和格局。紫椴是红松最重要的伴生树种,其空间异质性程度、空间异质性组成、尺度和格局等方面与红松接近。红松老龄林中主要树种空间异质性与格局在一定尺度上的差异,反映这些树种在生态系统中具有不同的生态学功能和过程。