Detection of spatial change points in the mean and covariances of multivariate simultaneous autoregressive models

In this paper, we propose a test procedure to detect change points of multidimensional autoregressive processes. The considered process differs from typical applied spatial autoregressive processes in that it is assumed to evolve from a predefined center into every dimension. Additionally, structural breaks in the process can occur at a certain distance from the predefined center. The main aim of this paper is to detect such spatial changes. In particular, we focus on shifts in the mean and the autoregressive parameter. The proposed test procedure is based on the likelihood‐ratio approach. Eventually, the goodness‐of‐fit values of the estimators are compared for different shifts. Moreover, the empirical distribution of the test statistic of the likelihood‐ratio test is obtained via Monte Carlo simulations. We show that the generalized Gumbel distribution seems to be a suitable limiting distribution of the proposed test statistic. Finally, we discuss the detection of lung cancer in computed tomography scans and illustrate the proposed test procedure.     

Estimating the environmental Kuznets curve for ecological footprint at the global level: A spatial econometric approach

The national ecological footprint of both consumption and production are significantly spatially autocorrelated at global level. This violates the assumption of independently distributed errors of most conventional estimation techniques. Using a spatial econometric approach, this paper re-examine the relationship between economic growth and environmental impact for indicator of ecological footprint. The results do not show evidence of inverted U-shape Environmental Kuznets Curve. The domestic ecological footprint of consumption (or production) was obviously influenced by the ecological footprint of consumption (or production), income and biocapacity in neighborhood countries. We also found that the consumption footprint is more sensitive to domestic income, while production footprint is more sensitive to domestic biocapacity, which is often unnoticed in EKC hypothesis analyses that focus exclusively on the consumption-based or production-based indictors.     

Neighborhood Dependence in Bayesian Spatial Models

The conditional autoregressive model and the intrinsic autoregressive model are widely used as prior distribution for random spatial effects in Bayesian models. Several authors have pointed out impractical or counterintuitive consequences on the prior covariance matrix or the posterior covariance matrix of the spatial random effects. This article clarifies many of these puzzling results. We show that the neighborhood graph structure, synthesized in eigenvalues and eigenvectors structure of a matrix associated with the adjacency matrix, determines most of the apparently anomalous behavior. We illustrate our conclusions with regular and irregular lattices including lines, grids, and lattices based on real maps.     

Spatially correlated disturbances in a locally dispersing population model

The basic contact process in continuous time is studied, where instead of single occupied sites becoming empty independently, larger-scale disturbance events simultaneously remove the population from contiguous blocks of sites. Stochastic spatial simulations and pair approximations were used to investigate the model. Increasing the spatial scale of disturbance events increases spatial clustering of the population and variability in growth rates within localized regions, reduces the effective overall population density, and increases the critical reproductive rate necessary for the population to persist. Pair approximations yield a closed-form analytic expression for equilibrium population density and the critical value necessary for persistence.     

Analysing yield stability of maize genotypes using a spatial model

Summary The yield stability of some CIMMYT tropical maize (Zea mays L.) populations of early and intermediate maturity, measured by the performance of varieties derived from them, was determined. Results of the stability analyses, conducted over international environments from 1980 to 1983, indicated that selections from Mezcla Amarilla exhibited good stability in high yielding sites. Varieties derived from Antigua-Republica Dominicana tended to be more stable in unfavourable environments, whereas selections from Blanco Cristalino-1 and Blanco Dentado-2 were stable in both low and high production sites. The combination of enviromental factors in the specific test locations, namely Poza Rica (Mexico), Tocumen (Panama), Islamabad (Pakistan), and Ferkessedougou (Ivory Coast), allowed selection of varieties that are very stable in other regions of the world. The varieties formed on the basis of multilocational data do not seem to be any more stable than those formed using data from a single location.     

The effect of landscape pattern on Mediterranean vegetation dynamics: A modelling approach using functional types

Abstract. In the framework of land use changes in the Mediterranean area, I asked to what extent different landscape structures might determine long‐term dynamics in Mediterranean ecosystems. To answer this question, a spatially explicit model was developed (the Melca model), incorporating two functional types of woody species dominant in Mediterranean ecosystems: a resprouter (R) and a non‐resprouter fire‐recruiter (seeders, S). The model was used as a tool for generating hypotheses on the possible consequences of different landscape scenarios. Thus, five different hierarchically structured random landscapes were generated, all having the same cover for the two functional types but different landscape structure (ranging from highly heterogeneous to homogeneous landscapes). After a 100‐yr simulation, plant cover and spatial pattern had changed and the changes were different for the different initial spatial configurations, suggesting that long‐term vegetation dynamics is spatially dependent (the resultant dynamics are sensitive to the initial spatial structure). In the landscapes where R‐type species had a low number of large patches and S‐species had a large number of small patches, the number of R‐patches increased and their size decreased, while the number of S‐patches decreased. In these cases, the final cover of the two types changed little from the initial cover. Landscapes with a large number of small R‐patches interspersed with S‐patches had a decrease in the number of R‐patches, an increase in the number of S‐patches and a decrease in the size of S‐patches. In these landscapes, final cover was significantly changed, increasing in R‐type and decreasing in S‐type species. These results suggest that low spatial autocorrelation (low aggregation) favours R‐type species. Implications for land management are also discussed.     

稻鸭共作系统中主要捕食性天敌的结构及多样性

为了探明稻鸭共作模式对稻田天敌群落的影响,设置稻鸭共作区、常规稻作区和空白区3个处理的田间小区试验,对早稻生长期间稻田主要捕食性天敌群落的结构及多样性特征进行了研究.结果表明:3个处理区主要捕食性天敌的优势种类均为园蛛科、微蛛科、狼蛛科和肖蛸科蜘蛛;稻鸭共作区中园蛛科、微蛛科和狼蛛科的优势度指数高于其他两个处理;在整个调查期间,常规稻作区、稻鸭共作区主要捕食性天敌的总数分别比空白区低1.7%和14.9%;除个别观测时段外,稻鸭共作区主要捕食性天敌的多样性指数均低于其他两个处理,但并不显著;多样性指数的减少以放鸭下田初期较为明显,随水稻的生长,多样性指数呈现持续上升的趋势.     

Are potential natural vegetation maps a meaningful alternative to neutral landscape models?

Abstract. In this paper, we present a short overview of neutral landscape models traditionally adopted in the landscape ecological literature to differentiate landscape patterns that are the result of simple random processes from patterns that are generated from more complex ecological processes. Then, we present another family of models based on Tuxen’ s definition of potential natural vegetation that play an important role, especially in Europe, for landscape planning and management. While neutral landscape models by their very nature do not take into account vegetation dynamics, nor abiotic constraints to vegetation distribution, the concept of potential natural vegetation includes the effects of vegetation dynamics in a spatially explicit manner. Therefore, we believe that distribution maps of potential natural vegetation may represent an ecological meaningful alternative to neutral landscape models for evaluating the effects of landscape structure on ecological processes.     

新型降水分布数学模型研究及其应用

在分布式水文模型中,单元栅格内的降水输入是准确模拟各种水文过程的关键因素,寻求产生分布式降水数据的方法是水文模型研究的热点之一.在对国内外降水模型分析基础上,认为流域面上实际降水分布是天气系统降水与下垫面地形影响共同作用的结果,如果不受地形影响,天气系统降水的降水量等值线在平面上的分布近似为一组同心椭圆.根据这一原理,建立了一种能够模拟天气系统降水分布,并利用牛顿插值法对模拟结果进行地形影响修正的新型降水分布数学模型,提出了对降水中心位置及其中心降水量的模型模拟.利用黄土高原西川河流域实测资料对模型进行了检验,结果表明,该模型具有较高精度.由于模型概念简单明晰,且能指明降水中心位置及其中心降水量,因此在流域暴雨分析和洪水预报中具有一定价值.     

Prediction of plant species distribution in lowland river valleys in Belgium: modelling species response to site conditions

In ecological modelling, limitations in data and their applicability for predictive modelling are more rule than exception. Often modelling has to be performed on sub-optimal data, as explicit and controlled collection of (more) appropriate data would not be feasible. An example of predictive ecological modelling is given with application of generalized additive and generalized linear models fitted to presence–absence records of plant species and site condition data from four nutrient-poor Flemish lowland valleys. Standard regression procedures are used for modelling, although explanatory and response data do not meet all the assumptions implicit in these procedures. Data were non-randomly collected and are spatially autocorrelated; model residuals retain part of that correlation. The scale of most site-condition records does not match the scale of the response variable (species distribution). Hence, interpolated and up-scaled explanatory variables are used. Data are aggregated from distinct phytogeographical regions to allow for generalized models, applicable to a wider population of river valleys in the same region. Nevertheless, ecologically sound models are obtained, which predict well the distribution of most plant species for the Flemish river valleys considered.     

Linking small desert mammal distribution to habitat structure in a protected and grazed landscape of the Monte, Argentina

Interpretation of landscape patterns from the perspective of different species allows knowing the way in which they perceive landscape, and how their perception varies with scale. We examined distribution of four small mammal species at different scales over a landscape including protected and grazed areas, and associated species distribution with landscape structure. The study was conducted in the central Monte Desert (Reserve of Ñacuñán). Trap grids were set in both areas at two scales, varying their grain and extent. To determine whether spatial patterns are random, clumped or regular, we used a point pattern analysis. Logistic regressions were performed to relate the presence-absence of small mammals to environmental variables. Intensity of the point pattern was not constant, either in the Reserve or the grazed area. Small mammal abundance exhibited a heterogeneous distribution, and the existence of a first-order effect was detected for all species. No second-order effects were detected, the point pattern was random for all species in both areas. Both areas were differently perceived by rodent species. Habitat structure in both conditions and its variations with scale appear to be important factors affecting distribution patterns.     

昆虫种群密度的二项抽样估计模型研究进展

昆虫种群密度的二项抽样估计模型主要有两类,一类是根据空间分布型理论演绎而来,另一类是根据样方中有虫样方比例或不大于某一阈值密度T头的样方比例与平均密度的经验关系拟合的．本文综述了这两类模型、模型的变异分析、模型的理论抽样数估计等方面的研究进展．     

Using network models to approximate spatial point-process models

Spatial effects are fundamental to ecological and epidemiological systems, yet the incorporation of space into models is potentially complex. Fixed-edge network models (i.e. networks where each edge has the same fixed strength of interaction) are widely used to study spatial processes but they make simplistic assumptions about spatial scale and structure. Furthermore, it can be difficult to parameterize such models with empirical data. By comparison, spatial point-process models are often more realistic than fixed-edge network models, but are also more difficult to analyze. Here we develop a moment closure technique that allows us to define a fixed-edge network model which predicts the prevalence and rate of epidemic spread of a continuous spatial point-process epidemic model. This approach provides a systematic method for accurate parameterization of network models using data from continuously distributed populations (such as data on dispersal kernels). Insofar as point-process models are accurate representations of real spatial biological systems, our example also supports the view that network models are realistic representations of space.     

Colonization rules and spatial distributions in ecology

Because they are intuitive and mathematically straight-forward, colonization rules are often used to model spatial patterns in ecology. Colonization rules assign individuals to categories according to the locations of previous colonists. In this note, a compact introduction to colonization rules in ecology is presented with implications for autocorrelation and spatial distributions. I use the colonization rule approach to unify a diverse set of spatial and species diversity analyses, exploring future extensions to incorporate greater realism.     

基于时间机理与部位机理整合的鲁棒性语音信号表达

传统语音信号谱特征的提取是基于ＦＦＴ 的能谱分析方法,在噪音环境情况下,对噪音的频谱成分与语音信号的频谱成分的处理采用“平均主义”的原则。也就是说噪音的频谱成分与语音信号的频谱成分占同等重要的地位。显然在噪音环境中这种处理方法会使噪音掩蔽掉语音信号的成分。在听觉系统中这种处理编码方式如同耳蜗滤波器的频率分析功能那样,也就是部位机理。实际上听觉系统对噪音和周期信号的处理不是“平均主义”原则,而是对周期信号敏感, 对噪音不敏感,听觉神经纤维通过神经脉冲发放的周期间隔来编码刺激信号, 这对应听觉处理机制中的时间编码方式。基于这两种处理机制,文中提出整合部位机理和时间机理的方法,这正是听觉的处理刺激的方式。这样处理的方法很好地结合了两种处理机制的优点,能有效地探测噪音环境中的语音信号     

一种感知视觉运动信息的简化脑模型

视觉运动信息的感知过程,包括从局域运动检测到对模式整体运动的感知过程.我们以蝇视觉系统的图形-背景相对运动分辨的神经回路网络为基本框架,采用初级运动检测器的六角形阵列作为输入层,构造了一种感知视觉运动信息的简化脑模型,模拟了运动信息应该神经计算模型各个层次上的处理.该模型对差分行为实验结果作出了正确预测.本文并对空间生理整合的神经机制作了讨论.