Species divergence and trait convergence in experimental plant community assembly

Despite decades of research, it remains controversial whether ecological communities converge towards a common structure determined by environmental conditions irrespective of assembly history. Here, we show experimentally that the answer depends on the level of community organization considered. In a 9-year grassland experiment, we manipulated initial plant composition on abandoned arable land and subsequently allowed natural colonization. Initial compositional variation caused plant communities to remain divergent in species identities, even though these same communities converged strongly in species traits. This contrast between species divergence and trait convergence could not be explained by dispersal limitation or community neutrality alone. Our results show that the simultaneous operation of trait-based assembly rules and species-level priority effects drives community assembly, making it both deterministic and historically contingent, but at different levels of community organization.

The development of convergence and accommodation

Aim: To review current literature on the development of convergence and accommodation. The accommodation and vergence systems provide the foundation upon which bifoveal binocular single vision develops. Deviations from their normal development not only are implicated in the aetiology of convergence anomalies, accommodative anomalies and strabismus, but may also be implicated in failure of the emmetropisation process. Method: This review considers the problems of researching the development of accommodation and vergence in infants and how infant research has had to differ from adult methods. It then reviews and discusses the implications of current research into the development of both systems and their linkages. Results: Vergence and accommodation develop rapidly in the first months of life, with accommodation changing from relatively fixed myopic focus in the neonatal period to adult-like responses by 4 months of age. Vergence develops gradually and becomes more accurate after 4 months of age, but has been demonstrated in infants well before the age that binocular disparity detection mechanisms are thought to develop. Hypotheses for this early vergence mechanism are discussed. The relationship between accommodation and vergence shows much more variability in infants than adult literature has found, but this apparent adult/infant difference may be partly attributed to methodological differences rather than maturational change alone. Conclusions: Variability and flexibility characterise infant responses. This variability may enable infants to develop a flexible and robust binocular system for later life. Studies of infant visual cue use may give clues to the aetiology of strabismus and refractive error.

Visuospatial cognition in Williams syndrome: reviewing and accounting for the strengths and weaknesses in performance

Individuals with Williams syndrome typically show relatively poor visuospatial abilities in comparison to stronger verbal skills. However, individuals' level of performance is not consistent across all visuospatial tasks. The studies assessing visuospatial functioning in Williams syndrome are critically reviewed, to provide a clear pattern of the relative difficulty of these tasks. This prompts a possible explanation of the variability in performance seen, which focuses on the processing demands of some of these tasks. Individuals with Williams syndrome show an atypical processing style on tests of construction, which does not affect tests of perception.

Minimum stable convergence criteria for stochastic diffusion search

An analysis of Stochastic Diffusion Search (SDS), a novel and efficient optimisation and search algorithm, is presented, resulting in a derivation of the minimum acceptable match resulting in a stable convergence within a noisy search space. The applicability of SDS can therefore be assessed for a given problem.

Convergence analysis of stochastic diffusion search

In this paper we present a connectionist searching technique - the Stochastic Diffusion Search (SDS), capable of rapidly locating a specified pattern in a noisy search space. In operation SDS finds the position of the pre-specified pattern or if it does not exist - its best instantiation in the search space. This is achieved via parallel exploration of the whole search space by an ensemble of agents searching in a competitive cooperative manner. We prove mathematically the convergence of stochastic diffusion search. SDS converges to a statistical equilibrium when it locates the best instantiation of the object in the search space. Experiments presented in this paper indicate the high robustness of SDS and show good scalability with problem size. The convergence characteristic of SDS makes it a fully adaptive algorithm and suggests applications in dynamically changing environments.