Computational learning of the conditional phase-type (C-Ph) distribution: Learning C-Ph distributions

This paper presents a new algorithm for learning the structure of a special type of Bayesian network. The conditional phase-type (C-Ph) distribution is a Bayesian network that models the probabilistic causal relationships between a skewed continuous variable, modelled by the Coxian phase-type distribution, a special type of Markov model, and a set of interacting discrete variables. The algorithm takes a dataset as input and produces the structure, parameters and graphical representations of the fit of the C-Ph distribution as output.The algorithm, which uses a greedy-search technique and has been implemented in MATLAB, is evaluated using a simulated data set consisting of 20,000 cases. The results show that the original C-Ph distribution is recaptured and the fit of the network to the data is discussed.

The Conditional Phase-type distribution: Graphical Models for Continuous Non-Normal Data:The Conditional Phase-type (C-Ph) distribution:

Conditional Gaussian (CG) distributions allow the inclusion of both discrete and continuous variables in a model assuming that the continuous variable is normally distributed. However, the CG distributions have proved to be unsuitable for survival data which tends to be highly skewed. A new method of analysis is required to take into account continuous variables which are not normally distributed. The aim of this paper is to introduce the more appropriate conditional phase-type (C-Ph) distribution for representing a continuous non-normal variable while also incorporating the causal information in the form of a Bayesian network.

Studies of Microthrix parvicella in situ and in laboratory culture: production and use of specific antibodies

Physiological studies on M. parvicella have been conducted to determine the rate of growth of this organism in pure culture. The organism displayed a doubling time of 128 days despite its profuse abundance in a local Wastewater Treatment Plant (WWTW). An extensive survey has been ongoing since February 2000 into the extent of M. parvicella in the WWTW. A suite of monoclonal and polyclonal antibodies has been developed to detect and quantify M. parvicella.

Temporal changes in the distribution of native and introduced freshwater amphipods in Lough Neagh, Northern Ireland

Studies of invasion scenarios over long time periods are important to refine explanations and predictions of invasion success and impact. We used data from surveys in 1958 and 1999 of the macroinvertebrates of Lough Neagh, Northern Ireland, to assess changes in the distribution of native and introduced amphipods in relation to the wider assemblage. In 1958, the invader G. tigrinus dominated the shoreline fauna, with the native G. d. celticus present in very low numbers, whereas in 1999 the reverse was evident. In both surveys, G. tigrinus was the only amphipod present in the mid-Lough. G. tigrinus thus seems to have become established within L. Neagh, perhaps overshot and then senesced, with the native species re-establishing on the shoreline, with the invader mostly restricted to the deep mid-Lough. The non-amphipod macroinvertebrate assemblage was similar between the two surveys, in terms of Bray-Curtis community similarity, assemblage diversity, dominance and the taxa based ASPT water quality index. However, the mean density of macroinvertebrates (all taxa combined) was lower in 1999 compared to 1958, largely accounted for by a decline in oligochaete numbers. Since Gammarus species may be predators of other macroinvertebrates and influence their distribution and abundance, we investigated this trophic link in staged laboratory encounters. Both G. tigrinus and G. d. celticus preyed on isopods, alderflies, mayflies, chironomids and mysids, however, the native G. d. celticus had a significantly greater predatory impact on isopods and chironomids than did the invader G. tigrinus. While we cannot definitively ascribe cause and effect in the present scenario, we discuss how replacement of one amphipod species by another may have impacts on the wider macroinvertebrate assemblage.

Large-scale spatial patterns in the distribution of Collembola (Hexapoda) species in Antarctic terrestrial ecosystems

We tested whether the distribution of three common springtail species (Gressittacantha terranova, Gomphiocephalus hodgsoni and Friesea grisea) in Victoria Land (Antarctica) could be modelled as a function of latitude, longitude, altitude and distance from the sea.

Victoria Land, Ross Dependency, Antarctica.

Generalized linear models were constructed using species presence/absence data relative to geographical features (latitude, longitude, altitude, distance from sea) across the species' entire ranges. Model results were then integrated with the known phylogeography of each species and hypotheses were generated on the role of climate as a major driver of Antarctic springtail distribution.

Based on model selection using Akaike's information criterion, the species' distributions were: hump-shaped relative to longitude and monotonic with altitude for Gressittacantha terranova; hump-shaped relative to latitude and monotonic with altitude for Gomphiocephalus hodgsoni; and hump-shaped relative to longitude and monotonic with latitude, altitude and distance from the sea for Friesea grisea.

No single distributional pattern was shared by the three species. While distributions were partially a response to climatic spatial clines, the patterns observed strongly suggest that past geological events have influenced the observed distributions. Accordingly, present-day spatial patterns are likely to have arisen from the interaction of historical and environmental drivers. Future studies will need to integrate a range of spatial and temporal scales to further quantify their respective roles.