8 resultados para Urban quality

em University of Queensland eSpace - Australia


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Cities have a major impact on Australian landscapes, especially in coastal regions, to the detriment of native biodiversity. Areas suitable for urban development often coincide with those areas that support high levels of species diversity and endemism. However, there is a paucity of reliable information available to guide urban conservation planning and management, especially regarding the trade-off between investing in protecting and restoring habitat at the landscape level, and investing in programmes to maintain the condition of remnant vegetation at the local (site) level. We review the literature on Australian urban ecology, focusing on urban terrestrial and aquatic vertebrate and invertebrate fauna. We identify four main factors limiting our knowledge of urban fauna: (i) a lack of studies focusing at multiple ecological levels; (ii) a lack of multispecies studies; (iii) an almost total absence of long-term (temporal) studies; and (iv) a need for stronger integration of research outcomes into urban conservation planning and management. We present a set of key principles for the development of a spatially explicit, long-term approach to urban fauna research. This requires an understanding of the importance of local-level habitat quality and condition relative to the composition, configuration and connectivity of habitats within the larger urban landscape. These principles will ultimately strengthen urban fauna management and conservation planning by enabling us to prioritize and allocate limited financial resources to maximize the conservation return.

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Predicting the various responses of different species to changes in landscape structure is a formidable challenge to landscape ecology. Based on expert knowledge and landscape ecological theory, we develop five competing a priori models for predicting the presence/absence of the Koala (Phascolarctos cinereus) in Noosa Shire, south-east Queensland (Australia). A priori predictions were nested within three levels of ecological organization: in situ (site level) habitat (< 1 ha), patch level (100 ha) and landscape level (100-1000 ha). To test the models, Koala surveys and habitat surveys (n = 245) were conducted across the habitat mosaic. After taking into account tree species preferences, the patch and landscape context, and the neighbourhood effect of adjacent present sites, we applied logistic regression and hierarchical partitioning analyses to rank the alternative models and the explanatory variables. The strongest support was for a multilevel model, with Koala presence best predicted by the proportion of the landscape occupied by high quality habitat, the neighbourhood effect, the mean nearest neighbour distance between forest patches, the density of forest patches and the density of sealed roads. When tested against independent data (n = 105) using a receiver operator characteristic curve, the multilevel model performed moderately well. The study is consistent with recent assertions that habitat loss is the major driver of population decline, however, landscape configuration and roads have an important effect that needs to be incorporated into Koala conservation strategies.