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.     

The detection of spatial discontinuities: interactions between contrast and spatial contiguity

Thresholds were measured for the detection of spatial discontinuities (notches and bumps) along luminance boundaries. At high contrasts of the boundary, thresholds expressed in terms of the spatial notch/bump height fell well inside the hyperacuity range. Expressed as luminance increment thresholds between adjacent photoreceptors, the same thresholds were similar to those previously reported by Hartridge and by Hecht and Mintz for the detection of a single line. The ability of observers to detect differences in the height of a boundary on either side of a mean luminance gap was also investigated, and the effect of the gap was found to depend upon stimulus contrast. At high contrasts the introduction of a gap increased thresholds, but at the lowest contrasts, thresholds were unaffected by a gap. The role of different spatial frequency and orientational mechanisms in vernier acuity is discussed.     

Dispersal and spatial scale affect synchrony in spatial population dynamics

A large body of theoretical studies has shown that synchrony among populations is critical for the long-term persistence of species in fragmented habitats. Although the effects of dispersal and environmental factors on synchrony have been investigated theoretically, empirical studies of these relationships have been lacking. We explored the interplay between environmental and demographic factors (fecundity, survival, dispersal) on population synchrony for 53 species of birds. We show that the interspecific differences in mean synchrony were determined by global environmental factors whose action was probably mediated by the abundance of each species. After removing the effect of these global factors on synchrony, the residual synchrony was strongly correlated with dispersal distance. The relationship between dispersal and synchrony was stronger for the species nesting in wet habitats than for those nesting in dry habitats. Our results indicate that different factors synchronize bird populations at different spatial scales, thus highlighting the role of scale in understanding spatial population dynamics and extinction risks.     

An index of spatial distribution

The index , which takes the value of −1 for a perfectly regular distribution, +1 for a highly aggregated distribution and 0 for the distribution implied by the theoretical varianceσ², is proposed and a significance table provided.     

Tissue-specific spatial organization of genomes

Background

Genomes are organized in vivo in the form of chromosomes. Each chromosome occupies a distinct nuclear subvolume in the form of a chromosome territory. The spatial positioning of chromosomes within the interphase nucleus is often nonrandom. It is unclear whether the nonrandom spatial arrangement of chromosomes is conserved among tissues or whether spatial genome organization is tissue-specific.

Results

Using two-dimensional and three-dimensional fluorescence in situ hybridization we have carried out a systematic analysis of the spatial positioning of a subset of mouse chromosomes in several tissues. We show that chromosomes exhibit tissue-specific organization. Chromosomes are distributed tissue-specifically with respect to their position relative to the center of the nucleus and also relative to each other. Subsets of chromosomes form distinct types of spatial clusters in different tissues and the relative distance between chromosome pairs varies among tissues. Consistent with the notion that nonrandom spatial proximity is functionally relevant in determining the outcome of chromosome translocation events, we find a correlation between tissue-specific spatial proximity and tissue-specific translocation prevalence.

Conclusions

Our results demonstrate that the spatial organization of genomes is tissue-specific and point to a role for tissue-specific spatial genome organization in the formation of recurrent chromosome arrangements among tissues.

     

Detection of irregular spatial structures

Wilson et al.'s (1997) study on Glass patterns suggested that the integration of stimulus features into a linear shape occurs quite locally, whereas curved structures--such as circular--require global summation. Their conclusion was based on experiments in which they varied the size of the signal area containing a spatial structure. In the present study, we tested the integration of constant-sized linear and curved Glass patterns by varying their global irregularity. If the mechanisms underlying the detection of a Glass pattern pool features globally throughout the stimulus, the irregularity should have a strong effect on detection performance. The irregular Glass patterns were composed of a variable number of sub-areas, each of which contained its own linear or curved structure. The structural irregularity impaired the detection of the curved patterns, whereas the thresholds for the linear patterns were not affected. Thus, our results are in line with the notion that the integration of curved Glass patterns occurs more globally than the integration of linear patterns.     

The geography of spatial synchrony

Spatial synchrony, defined as correlated temporal fluctuations among populations, is a fundamental feature of population dynamics, but many aspects of synchrony remain poorly understood. Few studies have examined detailed geographical patterns of synchrony; instead most focus on how synchrony declines with increasing linear distance between locations, making the simplifying assumption that distance decay is isotropic. By synthesising and extending prior work, we show how geography of synchrony, a term which we use to refer to detailed spatial variation in patterns of synchrony, can be leveraged to understand ecological processes including identification of drivers of synchrony, a long‐standing challenge. We focus on three main objectives: (1) showing conceptually and theoretically four mechanisms that can generate geographies of synchrony; (2) documenting complex and pronounced geographies of synchrony in two important study systems; and (3) demonstrating a variety of methods capable of revealing the geography of synchrony and, through it, underlying organism ecology. For example, we introduce a new type of network, the synchrony network, the structure of which provides ecological insight. By documenting the importance of geographies of synchrony, advancing conceptual frameworks, and demonstrating powerful methods, we aim to help elevate the geography of synchrony into a mainstream area of study and application.     

The spatial structure of populations

1. Studies of the spatio-temporal dynamics and structure of populations have identified many categories of population type. However, recognized categories intergrade, making it difficult to assign empirical population systems to single categories.
2. We suggest that most population categories can be arranged along two axes that combine per capita birth (B), death (D), emigration (E) and immigration (I) rates. The 'Compensation Axis' describes the source-sink component of population structure, with source populations exporting individuals (B > D, E > I) and sinks and pseudosinks consuming individuals (B < D, E < I). The 'Mobility Axis' describes the involvement of a local population in regional (I + E) rather than local (B + D) processes, running from separate populations, through metapopulations, to patchy populations.
3. Each sample area within a spatially structured population system can potentially be assigned to a position along each of these axes, with individual sample areas weighted by local population size. The positions of these sample areas and their relative weightings allow the relative importance of different types of process to be judged. A worked exampled is provided, using the butterfly Hesperia comma . This approach shifts the emphasis from pattern (categories that real population systems do not fit) onto process.
4. In many systems, continuous variation in habitat quality and demographic parameters make clear distinctions between 'habitat' and 'non-habitat' difficult to sustain. In such cases, we advocate the use of a spatial grid system, with effects of patch size and isolation combined into a single, weighted distance function (neighbourhood).
5. The relative importance of different processes depends on the spatial scale at which the system is observed. This again emphasizes the value of a process-based approach.     

Modelling spatial dynamics of fish

Our ability to model spatial distributions of fish populations is reviewed by describing the available modelling tools. Ultimate models of the individual's motivation for behavioural decisions are derived from evolutionary ecology. Mechanistic models for how fish sense and may respond to their surroundings are presented for vision, olfaction, hearing, the lateral line and other sensory organs. Models for learning and memory are presented, based both upon evolutionary optimization premises and upon neurological information processing and decision making. Functional tools for modelling behaviour and life histories can be categorized as belonging to an optimization or an adaptation approach. Among optimization tools, optimal foraging theory, life history theory, ideal free distribution, game theory and stochastic dynamic programming are presented. Among adaptation tools, genetic algorithms and the combination with artificial neural networks are described. The review advocates the combination of evolutionary and neurological approaches to modelling spatial dynamics of fish.     

Nonhomogeneous spatial distributions of populations

Summary Spatial inhomogeneities such as nonconstant population densities usually will be attributed to random effects or to an inhomogeneous substrate. Such an explanation may be incorrect since from certain chemical reactions it is known that the interaction of species together with diffusion may generate nonhomogeneous spatial structures. However, the effect of boundary conditions has been so far neglected. In this paper nonlinear and linear interaction-diffusion models are investigated under various side-conditions by analytic methods and by computer simulations. A remarkable fact, as compared with earlier results in the field, is the example of an interaction-diffusion process which in the whole space has only the constant as a stable limit distribution, whereas the introduction of a side condition, e.g. a population reservoir or a barrier, leads to standing spatial population waves.     

Formation of RNA spatial structures

The review considers different experimental and theoretical approaches to the investigation of RNA folding and identification of nucleotides that critically affect the folding of molecules, such as tRNA, and several classes of ribozymes. For instance, it has been shown that nucleotides of the D- and T-loop regions are the last to be involved in the tRNA structure, or, rather, they are not included in the tRNA folding nucleus. A specially developed SHAPE method was used to show that the long-recognized hierarchical folding model does not hold true for tRNA folding. In the second part of the review, algorithms and programs used for the prediction of RNA secondary structures, as well as for modeling RNA folding, are considered.     

甘肃臭草型退化草地优势种群空间格局及其关联性

空间格局和空间关联性是研究种群扩散和群落演替的重要方法。在石羊河上游高寒退化草地,运用点格局分析法,对不同演替阶段甘肃臭草和阿尔泰针茅的格局及关联性进行了研究。结果表明:甘肃臭草在没有形成斑块(CK)和斑块形成阶段(A),所有尺度上为聚集分布,在斑块扩散(B)、稳定(C)和衰退阶段(D)分别在0-90 cm、0-70 cm和0-40 cm上为聚集分布,90-100 cm、70-150 cm和40-150 cm为随机分布;阿尔泰针茅在CK阶段所有尺度上为随机分布,在A、B、C阶段分别在0-47 cm、0-75 cm、0-130 cm上为聚集分布,在47-50 cm、75-100 cm和130-150 cm上为随机分布,D阶段在所有尺度上为聚集分布;从CK-D阶段,甘肃臭草和阿尔泰针茅之间的关联性由显著负关联向关联性不显著转变,负关联显著程度先增强,后减弱;甘肃臭草种群从CK到D样地,种群领地密度先增大后减小,阿尔泰针茅种群领地密度逐渐减小。优势种替代过程中,种内竞争和种间竞争的相互转化影响格局的分布类型,竞争的不对称性影响关联性程度的强弱。     

Hierarchical spatial modeling of additive and dominance genetic variance for large spatial trial datasets

Summary .  This article expands upon recent interest in Bayesian hierarchical models in quantitative genetics by developing spatial process models for inference on additive and dominance genetic variance within the context of large spatially referenced trial datasets. Direct application of such models to large spatial datasets are, however, computationally infeasible because of cubic-order matrix algorithms involved in estimation. The situation is even worse in Markov chain Monte Carlo (MCMC) contexts where such computations are performed for several iterations. Here, we discuss approaches that help obviate these hurdles without sacrificing the richness in modeling. For genetic effects, we demonstrate how an initial spectral decomposition of the relationship matrices negate the expensive matrix inversions required in previously proposed MCMC methods. For spatial effects, we outline two approaches for circumventing the prohibitively expensive matrix decompositions: the first leverages analytical results from Ornstein–Uhlenbeck processes that yield computationally efficient tridiagonal structures, whereas the second derives a modified predictive process model from the original model by projecting its realizations to a lower-dimensional subspace, thereby reducing the computational burden. We illustrate the proposed methods using a synthetic dataset with additive, dominance, genetic effects and anisotropic spatial residuals, and a large dataset from a Scots pine ( Pinus sylvestris L.) progeny study conducted in northern Sweden. Our approaches enable us to provide a comprehensive analysis of this large trial, which amply demonstrates that, in addition to violating basic assumptions of the linear model, ignoring spatial effects can result in downwardly biased measures of heritability.