USING NETWORK ANALYSIS TO CHARACTERIZE FOREST STRUCTURE

Abstract Network analysis quantifies different structural properties of systems of interrelated parts using a single analytical framework. Many ecological phenomena have network‐like properties, such as the trophic relationships of food webs, geographic structure of metapopulations, and species interactions in communities. Therefore, our ability to understand and manage such systems may benefit from the use of network‐analysis techniques. But network analysis has not been applied extensively to ecological problems, and its suitability for ecological studies is uncertain. Here, we investigate the ability of network analysis to detect spatial patterns of species association in a tropical forest. We use three common graph‐theoretic measures of network structure to quantify the effect of understory tree size on the spatial association of understory species with trees in the canopy: the node degree distribution (NDD), characteristic path length (CPL), and clustering coefficient (CC). We compute the NDD, CPL, and CC for each of seven size classes of understory trees. For significance testing, we compare the observed values to frequency distributions of each statistic computed from randomized data. We find that the ability of network analysis to distinguish observed patterns from those representing randomized data strongly depends on which aspects of structure are investigated. Analysis of NDD finds no significant difference between random and observed networks. However, analysis of CPL and CC detected nonrandom patterns in three and one of the seven size classes, respectively. Network analysis is a very flexible approach that holds promise for ecological studies, but more research is needed to better understand its advantages and limitations.     

A STRUCTURALLY BASED ANALYTIC MODEL FOR ESTIMATION OF BIOMASS AND FUEL LOADS OF WOODLAND TREES

Abstract Allometric/structural relationships in tree crowns are a consequence of the physical, physiological, and fluid conduction processes of trees, which control the distribution, efficient support, and growth of foliage in the crown. The structural consequences of these processes are used to develop an analytic model based on the concept of branch orders. A set of interrelated equations describe the relationships between structural characteristics, including the distribution of a tree's foliage and the partitioning of the structural components within the crown for the efficient support of that foliage. The foliage biomass distribution in a tree crown and the geometric relationships between the branch orders supporting that distribution are used to define a functional depth that is used to compute an associated functional crown volume. These are computed first for the foliage and then for each of the tree's branch orders. Each functional crown volume is linearly related to its respective biomass component. These consistent linear relationships are demonstrated first with data from pinyon pine and then with data from Utah juniper and Valencia orange trees. The structural changes and associated biomass distribution changes suggest that crown growth is controlled from the outside in, with the resulting structural changes an emergent property of crown adjustment to the annual addition of new foliage. The relationships derived are potentially applicable across a range of additional tree species, in other woody species and applicable over a wide range of locations and conditions.     

Exit times for an increasing Lévy tree-valued process

We give an explicit construction of the increasing tree-valued process introduced by Abraham and Delmas using a random point process of trees and a grafting procedure. This random point process will be used in companion papers to study record processes on Lévy trees. We use the Poissonian structure of the jumps of the increasing tree-valued process to describe its behavior at the first time the tree grows higher than a given height, using a spinal decomposition of the tree, similar to the classical Bismut and Williams decompositions. We also give the joint distribution of this exit time and the ascension time which corresponds to the first infinite jump of the tree-valued process.     

Visualizing Marked Spatial and Origin-Destination Point Patterns With Dynamically Linked Windows

We present dynamic linked graphs for exploratory analysis of spatial marked point processes data and give an introduction to our exploratory graphical analysis tool, called Marked Point Processes Exploratory Analysis (MaPPEA). In particular, we consider point processes with events marked with another spatial event representing origin-destination data types. Using linked windows brushing, MaPPEA provides an illustration of the structure and relationships between marks and locations of point patterns. The main feature is the dynamically changing, spatially localized graphical summary of the mark distribution. Many different graphical summaries are available, and they are updated dynamically as the user moves the mouse on the map showing the events. The methods are illustrated with data on car theft location and the eventual car retrieval location and on trees’ locations and their associated marks. This article has supplementary material online.     

Residual Diagnostics for Covariate Effects in Spatial Point Process Models

For a spatial point process model in which the intensity depends on spatial covariates, we develop graphical diagnostics for validating the covariate effect term in the model, and for assessing whether another covariate should be added to the model. The diagnostics are point-process counterparts of the well-known partial residual plots (component-plus-residual plots) and added variable plots for generalized linear models. The new diagnostics can be derived as limits of these classical techniques under increasingly fine discretization, which leads to efficient numerical approximations. The diagnostics can also be recognized as integrals of the point process residuals, enabling us to prove asymptotic results. The diagnostics perform correctly in a simulation experiment. We demonstrate their utility in an application to geological exploration, in which a point pattern of gold deposits is modeled as a point process with intensity depending on the distance to the nearest geological fault. Online supplementary materials include technical proofs, computer code, and results of a simulation study.     

Instability analysis of saddle points by a local minimax method

The objective of this work is to develop some tools for local instability analysis of multiple critical points, which can be computationally carried out. The Morse index can be used to measure local instability of a nondegenerate saddle point. However, it is very expensive to compute numerically and is ineffective for degenerate critical points. A local (weak) linking index can also be defined to measure local instability of a (degenerate) saddle point. But it is still too difficult to compute. In this paper, a local instability index, called a local minimax index, is defined by using a local minimax method. This new instability index is known beforehand and can help in finding a saddle point numerically. Relations between the local minimax index and other local instability indices are established. Those relations also provide ways to numerically compute the Morse, local linking indices. In particular, the local minimax index can be used to define a local instability index of a saddle point relative to a reference (trivial) critical point even in a Banach space while others failed to do so.

     

Subtree Transfer Operations and Their Induced Metrics on Evolutionary Trees

. Leaf-labelled trees are widely used to describe evolutionary relationships, particularly in biology. In this setting, extant species label the leaves of the tree, while the internal vertices correspond to ancestral species. Various techniques exist for reconstructing these evolutionary trees from data, and an important problem is to determine how "far apart" two such reconstructed trees are from each other, or indeed from the true historical tree. To investigate this question requires tree metrics, and these can be induced by operations that rearrange trees locally. Here we investigate three such operations: nearest neighbour interchange (NNI), subtree prune and regraft (SPR), and tree bisection and reconnection (TBR). The SPR operation is of particular interest as it can be used to model biological processes such as horizontal gene transfer and recombination. We count the number of unrooted binary trees one SPR from any given unrooted binary tree, as well as providing new upper and lower bounds for the diameter of the adjacency graph of trees under SPR and TBR. We also show that the problem of computing the minimum number of TBR operations required to transform one tree to another can be reduced to a problem whose size is a function just of the distance between the trees (and not of the size of the two trees), and thereby establish that the problem is fixed-parameter tractable.     

INCORPORATION AND INFLUENCE OF VARIABILITY IN AN AGGREGATED FOREST MODEL

ABSTRACT. Variability influences ecological processes at various scales and is incorporated in different ways in forest models. The forest model Dis CFor M scales an individual based, stochastic forest patch model up to a height structured tree population model. To describe the variability arising from stochastic processes in the patch model, Dis CFor M uses theoretical random dispersions of trees in each height class over all patches. This yields a spatial distribution of light and consequently of light dependent process rates. Three major influences of variability on simulations are examined: site condition, patch to patch, and temporal environmental variability. Simulation studies and comparison with forest compositions from the Swiss National Forest Inventory reveal that these influences affect simulated forest dynamics, species composition, and biodiversity, depending on climatic boundary conditions and hence have to be taken into account in modeling.     

A spatial scan statistic for case event data based on connected components

We propose a new spatial scan statistic based on graph theory as a method for detecting irregularly-shaped clusters of events over space. A graph-based method is proposed for identifying potential clusters in spatial point processes. It relies on linking the events closest than a given distance and thus defining a graph associated to the point process. The set of possible clusters is then restricted to windows including the connected components of the graph. The concentration in each of these possible clusters is measured through classical concentration indices based on likelihood ratio and also through a new concentration index which does not depend on any alternative hypothesis. These graph-based spatial scan tests seem to be very powerful against any arbitrarily-shaped cluster alternative, whatever the dimension of the data. These results have applications in various fields, such as the epidemiological study of rare diseases or the analysis of astrophysical data.     

An economic model of short-rotation forestry

This paper presents an economic model of short-rotation forestry and shows that Lemke's linear complementarity algorithm can be used to compute optimal sustainable harvesting strategies. As an example, we apply our method, using existing data, to calculate optimal harvesting strategies for a plantation consisting of two interdependent species of trees.     

Representations of the Brownian snake with drift

We consider a path-valued process which is a generalization of the classical Brownian snake introduced by Le Gall. More precisely we add a drift term b to the lifetime process, which may depends on the spatial process. Consequently, this introduces a coupling between the lifetime process and the spatial motion. This process can be obtained from the standard Brownian snake by Girsanov's theorem or by killing of the spatial motion. It can also be viewed as the limit of discrete snakes or, in some special cases, as conditioned Brownian snakes. We also use this process to describe the solutions of the non-linear partial differential equation j u =4 u 2 +4 bu .     

Bias expansion of spatial statistics and approximation of differenced lattice point counts

Investigations of spatial statistics, computed from lattice data in the plane, can lead to a special lattice point counting problem. The statistical goal is to expand the asymptotic expectation or large-sample bias of certain spatial covariance estimators, where this bias typically depends on the shape of a spatial sampling region. In particular, such bias expansions often require approximating a difference between two lattice point counts, where the counts correspond to a set of increasing domain (i.e., the sampling region) and an intersection of this set with a vector translate of itself. Non-trivially, the approximation error needs to be of smaller order than the spatial region’s perimeter length. For all convex regions in 2-dimensional Euclidean space and certain unions of convex sets, we show that a difference in areas can approximate a difference in lattice point counts to this required accuracy, even though area can poorly measure the lattice point count of any single set involved in the difference. When investigating large-sample properties of spatial estimators, this approximation result facilitates direct calculation of limiting bias, because, unlike counts, differences in areas are often tractable to compute even with non-rectangular regions. We illustrate the counting approximations with two statistical examples.     

Computation of Spatial Covariance Matrices

In an earlier article, Ghosh derived the density for the distance between two points uniformly and independently distributed in a rectangle. This article extends that work to include the case where the two points lie in two different rectangles in a lattice. This density allows one to find the expected value of certain functions of this distance between rectangles analytically or by one-dimensional numerical integration.

In the case of isotropic spatial models or spatial models with geometric anisotropy terms for agricultural experiments one can use these theoretical results to compute the covariance between the yields in different rectangular plots. As the numerical integration is one-dimensional these results are computed quickly and accurately. The types of covariance functions used come from the Matérn and power families of processes. Analytic results are derived for the de Wijs process, a member of both families and for the power models also.

Software in R is available. Examples of the code are given for fitting spatial models to the Fairfield Smith data. Other methods for the estimation of the covariance matrices are discussed and their pros and cons are outlined.     

Balanced vertices in trees and a simpler algorithm to compute the genomic distance

This paper provides a short and transparent solution for the covering cost of white–grey trees which play a crucial role in the algorithm of Bergeron et al. to compute the rearrangement distance between two multichromosomal genomes in linear time (A. Bergeron, J. Mixtacki, J. Stoye, A new linear time algorithm to compute the genomic distance via the double cut and join distance, Theor. Comput. Sci. 410 (2009) 5300–5316). In the process it introduces a new center notion for trees, which seems to be interesting on its own.     

Interactive Visualization of Hierarchically Structured Data

We introduce methods for visualization of data structured along trees, especially hierarchically structured collections of time series. To this end, we identify questions that often emerge when working with hierarchical data and provide an R package to simplify their investigation. Our key contribution is the adaptation of the visualization principles of focus-plus-context and linking to the study of tree-structured data. Our motivating application is to the analysis of bacterial time series, where an evolutionary tree relating bacteria is available a priori. However, we have identified common problem types where, if a tree is not directly available, it can be constructed from data and then studied using our techniques. We perform detailed case studies to describe the alternative use cases, interpretations, and utility of the proposed visualization methods.     

具有生态位构建作用的种群进化动力学模型及其应用研究

依据进化动力学的理论与方法,系统探讨了生态位构建的机理与模式．通过建立生态位构建的空间模式及其适合度计算公式和具有生态位构建作用的单种群与两种群的进化动力学模型,并对其种群进化动态、种间竞争共存机制进行的理论与数值模拟分析,揭示了生物与环境资源的协同进化关系．结果表明:种群动态受其主要生态因子及资源含量的正反馈作用．生态位构建作用通过对种群适宜度的影响而产生进化响应．单种群动力系统存在种群大小的阈值效应;在两竞争种群动力系统中,生态位构建可以导致进化动力系统的多个竞争结果,从而为解释种间竞争与稳定共存提供了一种新的理论机制．     

A Point Process Approach to Filtered Processes

We consider some models of filtered point processes such as those developped in Yue and Hashino (2001), and rephrase them in terms of point processes. We derive from this formulation some estimates for the probability of overflow in a rainfall process. This method allows us by considering a non deterministic model of filtering to compute some characteristics of the compound models of Cowpertwait (1994), Phelan (1991), and Rodriguez-Iturbe et al. (1987, 1988). A spatial version of this point process is also studied, using an analogy with the boolean model of stochastic geometry we compute bounds for the probability of dryness in a compound rainfall process.     

Symbolic Computation of Local Symmetries of Nonlinear and Linear Partial and Ordinary Differential Equations

The paper illustrates the use of a symbolic software package GeM for Maple to compute local symmetries of nonlinear and linear differential equations (DEs). In the cases when a given DE system contains arbitrary functions or parameters, symbolic symmetry classification is performed. Special attention is devoted to the computation of point symmetries of linear PDE systems. Routines are available that effectively eliminate infinite obvious symmetries of linear DEs.     

Achieving sharp deliveries in supply chains through variance pool allocation

Variability reduction and business process synchronization are acknowledged as key to achieving sharp and timely deliveries in supply chain networks. In this paper, we develop an approach that facilitates variability reduction and business process synchronization for supply chains in a cost effective way. The approach developed is founded on an analogy between mechanical design tolerancing and supply chain lead time compression. We first present a motivating example to describe this analogy. Next, we define, using process capability indices, a new index of delivery performance called delivery sharpness which, when used with the classical performance index delivery probability, measures the accuracy as well as the precision with which products are delivered to the customers. Following this, we solve the following specific problem: how do we compute the allowable variability in lead time for individual stages of the supply chain so that specified levels of delivery sharpness and delivery probability are achieved in a cost-effective way? We call this the variance pool allocation (VPA) problem. We suggest an efficient heuristic approach for solving the VPA problem and also show that a variety of important supply chain design problems can be posed as instances of the VPA problem. One such problem, which is addressed in this paper, is the supply chain partner selection problem. We formulate and solve the VPA problem for a plastics industry supply chain and demonstrate how the solution can be used to choose the best mix of supply chain partners.     

Computation by computer of Lie superalgebra homology and cohomology

In this paper, we introduce a package to compute homology and cohomology spaces of Lie superalgebras. We describe most of its features and the implementation in REDUCE.