The practice of home in old Cairo: Towards socio-spatial models of sustainable living

The article investigates the practice of home as an everyday system for sustainable living in Old Cairo. The idea of home in this historic urban space has long involved fluid socio-spatial associations and made efficient use of space-activity-time dynamics. As in the past, a individual’s sense of home may here extend beyond or shrink within the physical boundaries of a particular house, as spatial settings are produced and consumed according to time of day, gender association, or special events. The article argues that architects working in this context must understand the dynamics of this complex traditional system if they are to develop locally informed, genuine designs that build on everyday spatial practices. Work by the architect Salah Zaki Said and by the Historic Cities Program of the Aga Khan Trust for Culture is described to illustrate the potential of such engagement, especially as it contrasts to more abstract architectural proposals.

Spatial patterns and autocorrelation in the response of microarthropods to soil pollutants: The example of oribatid mites in an abandoned mining and smelting area

Although exogenous factors such as pollutants can act on endogenous drivers (e.g. dispersion) of populations and create spatially autocorrelated distributions, most statistical techniques assume independence of error terms. As there are no studies on metal soil pollutants and microarthropods that explicitly analyse this key issue, we completed a field study of the correlation between Oribatida and metal concentrations in litter, organic matter and soil in an attempt to account for spatial patterns of both metals and mites. The 50-m wide study area had homogenous macroscopic features, steep Pb and Cu gradients and high levels of Zn and Cd. Spatial models failed to detect metal-oribatid relationships because the observed latitudinal and longitudinal gradients in oribatid assemblages were independent of the collinear gradients in the concentration of metals. It is therefore hypothesised that other spatially variable factors (e.g. fungi, reduced macrofauna) affect oribatid assemblages, which may be influenced by metals only indirectly. (C) 2009 Elsevier Ltd. All rights reserved.

Is Mortality Spatial or Social?

Mortality modelling for the purposes of demographic forecasting and actuarial pricing is generally done at an aggregate level using national data. Modelling at this level fails to capture the variation in mortality within country and potentially leads to a mis-specification of mortality forecasts for a subset of the population. This can have detrimental effects for pricing and reserving in the actuarial context. In this paper we consider mortality rates at a regional level and analyse the variation in those rates. We consider whether variation in mortality rates within a country can be explained using local economic and social variables. Using Northern Ireland data on mortality and measures of deprivation we identify the variables explaining mortality variation. We create a population polarisation variable and find that this variable is significant in explaining some of the variation in mortality rates. Further, we consider whether spatial and non-spatial models have a part to play in explaining mortality differentials.

Molecular modeling of N-terminal domains of NMDA-receptor. Study of ligand binding with N-terminal domains

Using the molecular-graphic complex Sybyl6.7.2, computational construction of spatial models for N-terminal domains (of NR1- and NR2B-subunits) of NMDA-receptor was conducted. On the basis of the constructed models and also CoMFA method the conclusion is made about presence of the binding site for the compounds similar to iphenprodyl in two N-terminal domains of NR1- and NR2B-subunits. The obtained data can be used for constructing new ligands.

A necessarily complex model to explain the biogeography of the amphibians and reptiles of Madagascar

Pattern and process are inextricably linked in biogeographic analyses, though we can observe pattern, we must infer process. Inferences of process are often based on ad hoc comparisons using a single spatial predictor. Here, we present an alternative approach that uses mixed-spatial models to measure the predictive potential of combinations of hypotheses. Biodiversity patterns are estimated from 8,362 occurrence records from 745 species of Malagasy amphibians and reptiles. By incorporating 18 spatially explicit predictions of 12 major biogeographic hypotheses, we show that mixed models greatly improve our ability to explain the observed biodiversity patterns. We conclude that patterns are influenced by a combination of diversification processes rather than by a single predominant mechanism. A ‘one-size-fits-all’ model does not exist. By developing a novel method for examining and synthesizing spatial parameters such as species richness, endemism and community similarity, we demonstrate the potential of these analyses for understanding the diversification history of Madagascar’s biota.

Outlier SNP markers reveal fine-scale genetic structuring across European hake populations (Merluccius merluccius)

Shallow population structure is generally reported for most marine fish and explained as a consequence of high dispersal, connectivity and large population size. Targeted gene analyses and more recently genome-wide studies have challenged such view, suggesting that adaptive divergence might occur even when neutral markers provide genetic homogeneity across populations. Here, 381 SNPs located in transcribed regions were used to assess large- and fine-scale population structure in the European hake (Merluccius merluccius), a widely distributed demersal species of high priority for the European fishery. Analysis of 850 individuals from 19 locations across the entire distribution range showed evidence for several outlier loci, with significantly higher resolving power. While 299 putatively neutral SNPs confirmed the genetic break between basins (F(CT) = 0.016) and weak differentiation within basins, outlier loci revealed a dramatic divergence between Atlantic and Mediterranean populations (F(CT) range 0.275-0.705) and fine-scale significant population structure. Outlier loci separated North Sea and Northern Portugal populations from all other Atlantic samples and revealed a strong differentiation among Western, Central and Eastern Mediterranean geographical samples. Significant correlation of allele frequencies at outlier loci with seawater surface temperature and salinity supported the hypothesis that populations might be adapted to local conditions. Such evidence highlights the importance of integrating information from neutral and adaptive evolutionary patterns towards a better assessment of genetic diversity. Accordingly, the generated outlier SNP data could be used for tackling illegal practices in hake fishing and commercialization as well as to develop explicit spatial models for defining management units and stock boundaries.

Modelling the influence of biotic factors on species distribution patterns

Biotic interactions can have large effects on species distributions yet their role in shaping species ranges is seldom explored due to historical difficulties in incorporating biotic factors into models without a priori knowledge on interspecific interactions. Improved SDMs, which account for biotic factors and do not require a priori knowledge on species interactions, are needed to fully understand species distributions. Here, we model the influence of abiotic and biotic factors on species distribution patterns and explore the robustness of distributions under future climate change. We fit hierarchical spatial models using Integrated Nested Laplace Approximation (INLA) for lagomorph species throughout Europe and test the predictive ability of models containing only abiotic factors against models containing abiotic and biotic factors. We account for residual spatial autocorrelation using a conditional autoregressive (CAR) model. Model outputs are used to estimate areas in which abiotic and biotic factors determine species’ ranges. INLA models containing both abiotic and biotic factors had substantially better predictive ability than models containing abiotic factors only, for all but one of the four species. In models containing abiotic and biotic factors, both appeared equally important as determinants of lagomorph ranges, but the influences were spatially heterogeneous. Parts of widespread lagomorph ranges highly influenced by biotic factors will be less robust to future changes in climate, whereas parts of more localised species ranges highly influenced by the environment may be less robust to future climate. SDMs that do not explicitly include biotic factors are potentially misleading and omit a very important source of variation. For the field of species distribution modelling to advance, biotic factors must be taken into account in order to improve the reliability of predicting species distribution patterns both presently and under future climate change.

What motion distributions yield global transparency and spatial segmentation?

We have examined the ability of observers to parse bimodal local-motion distributions into two global motion surfaces, either overlapping (yielding transparent motion) or spatially segregated (yielding a motion boundary). The stimuli were random dot kinematograms in which the direction of motion of each dot was drawn from one of two rectangular probability distributions. A wide range of direction distribution widths and separations was tested. The ability to discriminate the direction of motion of one of the two motion surfaces from the direction of a comparison stimulus was used as an objective test of the perception of two discrete surfaces. Performance for both transparent and spatially segregated motion was remarkably good, being only slightly inferior to that achieved with a single global motion surface. Performance was consistently better for segregated motion than for transparency. Whereas transparent motion was only perceived with direction distributions which were separated by a significant gap, segregated motion could be seen with abutting or even partially overlapping direction distributions. For transparency, the critical gap increased with the range of directions in the distribution. This result does not support models in which transparency depends on detection of a minimum size of gap defining a bimodal direction distribution. We suggest, instead, that the operations which detect bimodality are scaled (in the direction domain) with the overall range of distributions. This yields a flexible, adaptive system that determines whether a gap in the direction distribution serves as a segmentation cue or is smoothed as part of a unitary computation of global motion.

Neurobiological model of visuo-spatial cognition in young Williams Syndrome children: measures of dorsal-stream and frontal function

We examine hypotheses for the neural basis of the profile of visual cognition in young children with Williams syndrome (WS). These are: (a) that it is a consequence of anomalies in sensory visual processing; (b) that it is a deficit of the dorsal relative to the ventral cortical stream; (c) that it reflects deficit of frontal function, in particular of fronto-parietal interaction; (d) that it is related to impaired function in the right hemisphere relative to the left. The tests reported here are particularly relevant to (b) and (c). They form part of a more extensive programme of investigating visual, visuospatial, and cognitive function in large group of children with WS children, aged 8 months to 15 years. To compare performance across tests, avoiding floor and ceiling effects, we have measured performance in children with WS in terms of the ‘age equivalence’ for typically developing children. In this paper the relation between dorsal and ventral function was tested by motion and form coherence thresholds respectively. We confirm the presence of a subgroup of children with WS who perform particularly poorly on the motion (dorsal) task. However, such performance is also characteristic of normally developingchildren up to 5 years: thus the WS performance may reflect an overall persisting immaturity of visuospatial processing which is particularly evident in the dorsal stream. Looking at the performance on the global coherence tasks of the entire WS group, we find that there is also a subgroup who have both high form and motion coherence thresholds, relative to the performance of children of the same chronological age and verbal age on the BPVS, suggesting a more general global processing deficit. Frontal function was tested by a counterpointing task, ability to retrieve a ball from a ‘detour box’, and the Stroop-like ‘day-night’ task, all of which require inhibition of a familiar response. When considered in relation to overall development as indexed by vocabulary, the day-night task shows little specific impairment, the detour box shows a significant delay relative to controls, and the counterpointing task shows a marked and persistent deficit in many children. We conclude that frontal control processes show most impairment in WS when they are associated with spatially directed responses, reflecting a deficit of fronto-parietal processing. However, children with WS may successfully reduce the effect of this impairment by verbally mediated strategies. On all these tasks we find a range of difficulties across individual children and a small subset of WS who show very good performance, equivalent to chronological age norms of typically developing children. Neurobiological models of visuo-spatial cognition in children with WS p.4 Overall, we conclude that children with WS have specific processing difficulties with tasks involving frontoparietal circuits within the spatial domain. However, some children with WS can achieve similar performance to typically developing children on some tasks involving the dorsal stream, although the strategies and processing may be different in the two groups.

Non-stationary variogram models for geostatistical sampling optimisation: An empirical investigation using elevation data

A problem with use of the geostatistical Kriging error for optimal sampling design is that the design does not adapt locally to the character of spatial variation. This is because a stationary variogram or covariance function is a parameter of the geostatistical model. The objective of this paper was to investigate the utility of non-stationary geostatistics for optimal sampling design. First, a contour data set of Wiltshire was split into 25 equal sub-regions and a local variogram was predicted for each. These variograms were fitted with models and the coefficients used in Kriging to select optimal sample spacings for each sub-region. Large differences existed between the designs for the whole region (based on the global variogram) and for the sub-regions (based on the local variograms). Second, a segmentation approach was used to divide a digital terrain model into separate segments. Segment-based variograms were predicted and fitted with models. Optimal sample spacings were then determined for the whole region and for the sub-regions. It was demonstrated that the global design was inadequate, grossly over-sampling some segments while under-sampling others.