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Few studies have undertaken rigorous comparative analyses of levels of ethnic residential segregation across two or more countries. Using data for the latest available censuses (2000-2001) and a bespoke methodology for such comparative work, this article analyses levels of segregation across the urban systems of five major immigrant-receiving, English-speaking countries: Australia, Canada, New Zealand, the United Kingdom and the United States of America. After describing the levels of segregation in each, the paper tests a model based on generic factors which should influence segregation levels in all five countries and then evaluates-for the urban population as a whole, for the "charter group" in each society, and for various ethnic minority groups-whether there are also significant country-specific variations in segregation levels. The findings show common factors influencing segregation levels in all five countries-notably the size of the group being considered as a percentage of the urban total, but also urban size and urban ethnic diversity-plus country-specific variations that cannot be attributed to these generic factors. In general there is less segregation in Australia and New Zealand than in the other three countries.

Bioclimatic models are the primary tools for simulating the impact of climate change on species distributions. Part of the uncertainty in the output of these models results from uncertainty in projections of future climates. To account for this, studies often simulate species responses to climates predicted by more than one climate model and/or emission scenario. One area of uncertainty, however, has remained unexplored: internal climate model variability. By running a single climate model multiple times, but each time perturbing the initial state of the model slightly, different but equally valid realizations of climate will be produced. In this paper, we identify how ongoing improvements in climate models can be used to provide guidance for impacts studies. In doing so we provide the first assessment of the extent to which this internal climate model variability generates uncertainty in projections of future species distributions, compared with variability between climate models. We obtained data on 13 realizations from three climate models (three from CSIRO Mark2 v3.0, four from GISS AOM, and six from MIROC v3.2) for two time periods: current (1985)(1986)(1987)(1988)(1989)(1990)(1991)(1992)(1993)(1994)(1995) and future (2025)(2026)(2027)(2028)(2029)(2030)(2031)(2032)(2033)(2034)(2035). Initially, we compared the simulated values for each climate variable (P, T max , T min , and T mean ) for the current period to observed climate data. This showed that climates simulated by realizations from the same climate model were more similar to each other than to realizations from other models. However, when projected into the future, these realizations followed different trajectories and the values of climate variables differed considerably within and among climate models. These had pronounced effects on the projected distributions of nine Australian butterfly species when modelled using the BIOCLIM component of DIVA-GIS. Our results show that internal climate model variability can lead to substantial differences in the extent to which the future distributions of species are projected to change. These can be greater than differences resulting from between-climate model variability. Further, different conclusions regarding the vulnerability of species to climate change can be reached due to internal model variability. Clearly, several climate models, each represented by multiple realizations, are required if we are to adequately capture the range of uncertainty associated with projecting species distributions in the future.

The residential segregation of ethnic groups in urban areas remains an issue of importance for policy-making in multicultural societies, such as England's, with levels of segregation frequently linked to questions of social exclusion and equal treatment. But how segregated are ethnic groups in England? Most studies answer this question using single indices which address one aspect only of a multidimensional concept. In this paper, an alternative approach is used which identifies residential area types according to the degree of ethnic mixing; we evaluate their relative importance in 18 English cities in the light of Boal and Peach's arguments regarding the processes and patterns involved in segregation. We find little evidence of significant segregation of Black ethnic groups, but more with regard to Asian groups-especially outside London.

Studies of ethnic residential segregation in cities have traditionally used relative measures of groups' areal concentrationösuch as the indices of dissimilarity and segregation pioneered by Duncan and Duncan (1955)öto identify the level of spatial separateness between groups. Although such methods have been modified in a variety of ways over the last fifty years [see James and Taeuber (1985), Massey and Denton (1988;1989), Voas and Williamson (2000), and also Wong's (1998) introduction of an explicit spatial element to such indices], they have not formally addressed major issues raised by the theories of residential concentration and segregation that such measures were designed to test. The indices of dissimilarity and segregation look at only one aspect of the geography of ethnic groups within citiesödifference, or unevennessöand ignore other aspects of the relevant maps, such as isolation, clustering, concentration, and centralisation (Denton, 1994;Massey and Denton, 1988;1989;1993). In this paper we develop a procedure which incorporates all but the last of these concepts, and is particularly suited to comparative study.Alongside the indices of map pattern, other studies have sought to define ethnic residential areas. Most of these use one of two methods. The simplest just maps the percentage of an area's population who are members of a particular ethnic group, thereby giving some impression of the degree of concentration and its localisation but, unless the group is highly concentrated in certain areas, gives little indication of the amount and nature of ethnic mixing in many parts of a city. Linked to these are studiesösuch as those by Philpott (1978) and Jargowsky (1997)öwhich define a threshold which leads to an area being categorised as either within or outwith a particular type of ethnic enclave (a ghetto, say, or a barrio, to use Jargowsky's terminology). A further method, based on the well-established factorial ecology procedures, maps a