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With the rise in population migration there has been an increased need for professional interpreters who can bridge language barriers and operate in a variety of fields such as business, legal, social and medical. Interpreters require specialized training to cope with the idiosyncrasies of each field and their potential clients need to be aware of professional parlance. We present ‘Project IVY’. In IVY, users can make a selection from over 30 interpreter training scenarios situated in the 3D virtual world. Users then interpret the oral interaction of two avatar actors. In addition to creating different 3D scenarios, we have developed an asset management system for the oral files and permit users (mentors of the training interpreters) to easily upload and customize the 3D environment and observe which scenario is being used by a student. In this article we present the design and development of the IVY Virtual Environment and the asset management system. Finally we make discussion over our plans for further development.

Commercial pressures to produce faster and more dependable software prompt management initiatives to improve software practices. Technical solutions such as CASE tools, 4GLs, Interactive Development Environments and more recent modeling notations and tools have made some contribution. This article concentrates on the introduction of new development methodologies that are shown to have a positive on software development practices.

The aim of the following application of canonical analysis is to clarify relationships between soils and vegetation in a 1 km2 area of rain forest in the Bartica Triangle region of Guyana, South America. The available field data consist of estimates of the composition of twenty-five 100 m × 100 m stands of forest vegetation together with determinations of selected soil characteristics of the sites. Stands were arranged on a square lattice at intervals of 200 m, and, in recording their vegetation, attention was confined to the predominant, woody component of the vegetation. One hundred and seventy species of woody plant were encountered in all, the representation of these being estimated in terms of basal area. Ten soil samples were collected in each site and pooled to form a single, composite sample on which determinations of twenty physical and chemical properties were later made in the laboratory. A comprehensive account of the field sampling procedures and of methods of soil analysis has been given by Ogden (1966).

Many ecological endeavors lead naturally to comparisons between plant communities with respect to their overall species’ composition. The object of comparative studies of this kind is to obtain through a description of community differences insight into the processes responsible for the differences and an indication of the avenues along which more intensive study might be rewarding. In this chapter the use of canonical analysis in a comparative study is illustrated. Previous work on the composition and structure of grassland vegetation overlying a small (5 ha) area of Carboniferous Limestone in Anglesey, North Wales, showed the vegetation to be composed of three comparatively distinct communities (Gittins, 1965). The communities recognized were described as limestone, neutral and fertile grassland. With the aim of obtaining further insight into the structure of the vegetation a clearer understanding of interrelationships among the communities was sought. Examination of the sample in a geometric space chosen to emphasize both the distinctiveness of the communities and their mutual relationships would be appropriate for this purpose. Such a mapping could be achieved by a canonical analysis in which one set of variables consisted of estimates of species’ representation in the stands surveyed while the variables of the second set consisted of dummy variables specifying the community affiliation of stands — that is, in other words, by a canonical variate analysis.

This experiment concerns relationships between the abundances of several plant species and associated soil characteristics in a limestone grassland community in Anglesey, North Wales. Previous work (Gittins, 1969) suggested that the factor-complexes of soil moisture and soil fertility are influential in determining the representation of many of the species present. Knowledge of the salient soil-species relationships provides a basis against which the ability of canonical analysis to recover such relationships can be assessed.

Identification of factors which control the occurrence and representation of plant species in the field is a prime objective of much ecological work. Preliminary indications of the identity of operative factors may be obtained either by direct observation in the field or by use of exploratory multivariate techniques in the analysis of survey data. The next step towards identification involves attempts to substantiate provisional insights of these kinds. The most direct and convincing means of substantiation is provided by examining the response of species to treatments of one or more of the indicated factors in a designed experiment. In this chapter the use of canonical analysis in the analysis of experimental data is described and illustrated. The study concerns the comparative response of eight grass species to five treatment levels of nitrate nitrogen. General field observation had indicated that the species in question differed in their response to variation in soil fertility. The experiment was designed to enable evidence for the differential response of the species to one component of the factor-complex of soil fertility, namely, nitrate nitrogen, to be assessed.

In studies of dependency it is often useful to distinguish between studies of relationship and studies of structure. The term structure is used here to refer to the way in which the sample is organized or constructed. In studies of relationship it is the connections between two sets of observed or measured variables which are of interest. In structural investigations, on the other hand, it is affinities among subsamples making up a sample with respect to p response variables considered simultaneously which are of interest. For this purpose a set of q artificial variables may be created to account for the design characteristics of the survey or experiment which gave rise to the data, or to embody hypotheses concerning structural relationships among subsamples. In this chapter we shall be concerned with the use of canonical analysis in structural investigations of these kinds. The topic is a large one and we cannot hope to do more than touch upon a few selected aspects. Many of the theoretical results presented are illustrated by worked, numerical examples in Chaps. 10 and 11.

The stability of vegetation over time is frequently of interest to plant ecologists. Stability, however, is a property of vegetation which is not readily investigated because its definitive study calls for sequential observation over time. This is especially true of forest vegetation where the time-scales involved are often too long to permit direct observation. One means of circumventing the difficulty in the case of forest communities is to regard size class measurements as if they constituted observations at different times. Differences in size correspond to differences in age which, cautiously interpreted, may be substituted for observations at particular points in time or of particular seral stages. In this way it may be possible to gain insight into the dynamic status of forest vegetation over the short term, at least. The present chapter concerns a study of this kind.

In this chapter we shall summarize the essential elements of the theory of canonical correlations and variates. We shall begin by formulating the problem. The derivation of canonical correlations and canonical variates will then be taken up. Canonical analysis can be derived in several ways. Two derivations will be described rather fully — those leading to eigenanalysis and singular value decomposition, respectively. Several other derivations are of interest for the light which they shed on canonical analysis and its relations with other methods, and these will be described more briefly. We shall then consider the properties of canonical correlations, weights and variates. Finally, computational aspects of canonical analysis will be taken up.

The Rwenzori National Park lies astride the equator in the Western Rift Valley of Uganda. The Park contains a variety of plant communities, including forests, swamps and several kinds of grassland. The grasslands are noteworthy in that they support the highest recorded large mammal biomass of any natural area of the world (Bourliere, 1965; Coe, Cumming & Phillipson, 1976). An estimate of 294.9 kg ha−1 for the average year-round standing-crop herbivore biomass is given by Field and Laws (1970). Interrelationships between the herbivore species, in particular, and their environment — vegetation, climate, soils and other animal species — have been studied by Field and Laws (1970). Herbivore distribution was found to show considerable heterogeneity in relation to the occurrence of different plant communities, the presence of standing water and the incidence of fire. Table 2 of Field and Laws’ (1970) paper gives estimates of the mean density km−2 of nine herbivore species in ten sites or study areas. These data provided the starting point for the present investigation. Proceeding along different lines from Field and Laws, the data were analyzed in an attempt to clarify relationships within and between herbivores and study areas. Two methods were employed for the purpose — dual scaling and the contingency table analysis of E.J. Williams (1952). At a more fundamental level, the aims of the study were to illustrate the use of canonical analysis in an ecological context involving two categorial variables and to verify connections between dual scaling and contingency table analysis described in Sect. 5.5.1.

The experiment concerns the joint pattern of spatial variation common to three plant species belonging to a limestone grassland community in Anglesey, North Wales. The species were Phleum bertolonii DC., Dactylis glomerata L. and Galium verum L. From previous work, the species were known to share the same relatively simple generalized distribution pattern, which was centered on the southwestern extremity of the study area. Furthermore, the direction and extent of the departure of the distribution of each species from the common trend was also known. P. bertolonii was the most circumscribed of the species, being strictly confined to the southwestern corner. G. verum, on the other hand, was the most widespread species, occurring throughout the study area although its maximum representation occurred in the southwest. D. glomerata was less extreme with a distribution intermediate between those of the other species, but resembling that of P. bertolonii more closely than that of G. verum.

In the preceding chapter we introduced the essential ingredients of the theory of canonical correlation. The theory stems from the work of Hotelling in the 1930s. Since Hotelling’s pioneering studies the theory has been added to in a number of ways. The present chapter deals with developments of this kind. We shall begin by considering several numerical indices which have been devised in order to further the interpretation of results in addition to the canonical correlations, weights and variates of the classical solution. Other developments are directed towards widening the applicability of the original theory and several generalizations of this kind will be mentioned. Tests of statistical hypotheses are sometimes of interest in canonical analysis and the chapter closes with an account of hypothesis testing.

We have endeavored in the preceding chapters to draw attention to the richness and flexibility of canonical analysis. The flexibility of the underlying model, in particular, is expressed in part by the number of apparently distinct methods which prove on examination to be special cases of canonical correlation analysis. Canonical variate analysis and dual scaling were both shown abstractly to be equivalent to canonical correlation analysis. The model’s flexibility is complemented by a correspondingly diverse range of application. While, in relation to the worked examples of Chaps. 6–12, it may be that the ability of canonical analysis to have parsimoniously summarized the dependence structures in question is to be attributed to the small scale of these investigations, within the class of small-scale investigations the applicability of canonical analysis was shown to be very wide. Altogether, it seems justifiable to conclude that canonical analysis offers an unusually versatile structure by means of which statistical theory, ecological theory and empirical data can be harnessed to provide insight into the organization of ecological systems.