Ward's Hierarchical Clustering Method: Clustering Criterion and Agglomerative Algorithm

The Ward error sum of squares hierarchical clustering method has been very widely used since its first description by Ward in a 1963 publication. It has also been generalized in various ways. However there are different interpretations in the literature and there are different implementations of the Ward agglomerative algorithm in commonly used software systems, including differing expressions of the agglomerative criterion. Our survey work and case studies will be useful for all those involved in developing software for data analysis using Ward's hierarchical clustering method.Comment: 20 pages, 21 citations, 4 figure

Analysis of a recovery process: Dwingelose Heide revisited

The recovery process of a Dutch heathland after fire is investigated. The study area, 12 m x 20 m, has been surveyed yearly between 1963 and 1993. Previous work has shown that a stationary Markov chain models the observed recovery process well. However, the Markov model fails to capture an important observation, the existence of a phase structure. The process begins deterministically, but small random (non-Markov) effects accumulate through time and at some point the process suddenly becomes noisy. Here we make use of the spatial information contained in vegetation maps to examine dynamics at a fine spatial scale. We find that the phases observed at a large spatial scale separate themselves out distinctly at finer spatial scales. This spatial information allows us to investigate hypotheses about the mechanisms governing deterministic versus noisy vegetation dynamics

Vegetation dynamics and plant constraints: separating generalities and specifics

Vegetation dynamics is a stochastic process of species replacement after disturbance. It occurs because individual species are limited by general constraints and trade-offs. As these constraints and trade-offs are becoming better known, we understand more about the relationships between disturbance dynamics, species pools, and vegetation dynamics. This paper provides a summary of recent work on plant scaling and ecological trade-offs, and explores its implications for vegetation dynamics. Those aspects of succession that are predictable . given the local species complement . can be understood as consequences of these general patterns and constraints. Several are explored in this paper. The inherently stochastic nature of the process derives from the disturbance dynamics that forces it, from the sampling processes that are responsible for selecting potential invaders, and from the chance processes involved in species interactions. The dynamics of species that invade established communities is the least understood but potentially the most crucial aspect of vegetation dynamics. The relation of community invasion to gap creation and to scaling constraints is briefly discussed

Multilocus Bayesian Estimates of Intra-Oceanic Genetic Differentiation, Connectivity, and Admixture in Atlantic Swordfish (Xiphias gladius L.)

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