Search

It is commonly expected that informal settlements in developing countries have a smaller ecological footprint than more economically advantaged areas because they consume fewer resources and use less energy. In this paper we examine this idea by comparing material consumption of two informal settlements to one moderate socio-economic status (SES) neighbourhood in Suva, Fiji. We use the concept of the Ecological Footprint (EF) as a metric of comparison. Using a component-based EF approach we administered a questionnaire to 150 respondents from two informal settlements and one adjacent planned neighbourhood. Total EF and separate EF components (water, food, transport, energy, clothing, and material assets) were analysed through graphs, by examination of descriptive statistics, and through the use of non-parametric inferential statistics. We found differences between the adjacent planned neighbourhood and the informal settlements for several EF components, but found no difference for other EF components (e.g. water consumption). Through questionnaires and interviews we also examined perceived level of concern for environmental threats of informal settlement dwellers and residents of an adjacent moderate SES neighbourhood who share the same geographic space, but have very different living conditions. We found that concerns about sewage, deforestation, clean water and poor sanitation were of particularly high concern in one informal settlement, but not the other, suggesting that perceptions of threat can be very different even among informal settlements. We conclude that a better understanding of the social characteristics of informal settlements is valuable for informal settlement urban planning decisions in developing countries. [ABSTRACT FROM AUTHOR]

Highlights: [•] Compares eighteen urban form metrics for 542 neighborhoods in Salt Lake County, Utah. [•] Linear regression and correlation analysis across time periods to assess each metric’s ability to characterize urban form. [•] We make recommendations about thirteen spatial metrics for planners and policy analysts. [•] This case study shows despite policy efforts to encourage smart growth, urban sprawl occurred. [ABSTRACT FROM AUTHOR]

Abstract: We present an innovative approach to estimating residential irrigation water demand for a large metropolitan area using GIS data, weather station data, and a water budget modeling approach commonly used by plant scientists and landscape management professionals. An important question addressed by our study is how a growing urban forest affects the overall irrigation water demand of a semiarid metropolitan area. To estimate the amount of water required by residential landscaping, we consider water demand to be a function of the areal extent of residential landscaping (i.e. tree/shrub or turf grass), the water-loss rate for different landscaping types, the efficiency with which the landscape is irrigated, and local climatic factors (i.e. reference evapotranspiration and precipitation). We estimated irrigation water demand for 542 residential neighborhoods in Salt Lake County, UT, USA for 2005. To investigate the effects of a maturing urban forest on water demand, we used simultaneous autoregression (SAR) models to predict the spatial extent of future forest canopy and future exposed turf grass in residential neighborhoods. For both the forest canopy model and the turf grass model we used the median age of housing stock as the dependent variable. Psuedo R 2 were 0.70 and 0.82 for the tree/shrub canopy and turf grass models, respectively. Based on projected areal extents of tree/shrub canopy, exposed turf grass, and turf grass under canopy, we estimated future water demands for the 542 residential neighborhoods. Our predictive model suggests that as urban tree canopy increases in residential urban areas, exposed turf grass decreases, with a net effect of a slight decrease in residential landscape water demand. This can be explained by the relative differences in water lost through evapotranspiration by different landscape types, namely; trees/shrub (i.e. woody plants), exposed turf grass, and turf grass under tree canopy. [Copyright &y& Elsevier]

• 14 problematic invasive woody plants can be classified into 4 spatial patterns • Presence and abundance on urban-rural gradient type differs by plant species • Abundance of IWP is explained more by urban-rural gradient type than road type • IWP species may be common in urban sector type but not necessarily abundant • Overall abundance of target species in urban sector lower than other sectors Tropical Pacific island countries, many of which are less-developed, are experiencing invasions of alien plant species at rates faster than areas of comparable size elsewhere. In this paper we examine the relationship between the presence, abundance, and richness of 14 invasive woody plant (IWP) species and level of urbanization and road type in the Greater Suva Urban Area (GSUA), Fiji. One hundred and fifty-four sample locations within a 29 km transect traversing urban, peri-urban and rural land sectors on local, collector and arterial roads were surveyed. We analyzed the 14 species for frequency of occurrence across the urban-rural gradient and found spatial patterns of IWP presence differed by species. We analyzed the abundance of seven species using multivariable regression and found abundance was more often influenced by urban-rural sector than road type, though road type had a significant effect for some species. We conclude by offering plausible explanations for differences attributed to modes of dispersal, introduction history and human activities. We include supplementary material providing detailed characterization of biology, ecology, and history of the 14 target species. These findings are expected to help inform risk assessments and management of IWP in other tropical urban-rural gradients, and especially small island developing states. [ABSTRACT FROM AUTHOR]

Regression models are the standard approaches used in infectious disease epidemiology, but have limited ability to represent causality or complexity. We explore Bayesian networks (BNs) as an alternative approach for modelling infectious disease transmission, using leptospirosis as an example. Data were obtained from a leptospirosis study in Fiji in 2013. We compared the performance of naïve versus expert-structured BNs for modelling the relative importance of animal species in disease transmission in different ethnic groups and residential settings. For BNs of animal exposures at the individual/household level, R 2 for predicted versus observed infection rates were 0.59 for naïve and 0.75–0.93 for structured models of ethnic groups; and 0.54 for naïve and 0.93–1.00 for structured models of residential settings. BNs provide a promising approach for modelling infectious disease transmission under complex scenarios. The relative importance of animal species varied between subgroups, with important implications for more targeted public health control strategies. [ABSTRACT FROM AUTHOR]