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By 2050, 70% of the Earth’s human population will live in urban areas. Urbanization can have a devastating impact on local ecosystems, but these impacts vary across time and space. Identifying links between spatiotemporal change in urban ecosystems and neighborhood socio-economics is crucial to management aimed at maintaining flora and fauna in urban areas. Here, we tracked 20 years of socio-economic change and 15 years of vegetation change in 32 residential neighborhoods in south-eastern Australia. Regression models that explicitly accounted for a time lag between neighborhood socio-economic characteristics and vegetation response explained more variation in vegetation cover than models that ignored the effects of time. Also, relationships between vegetation and socio-economic factors were stronger in later years for the same neighborhoods suggesting the influence of socio-economics is more readily identified in established neighborhoods. Socio-economic variables alone, or in combination with biophysical variables, were better predictors of vegetation cover than only biophysical variables. Across space, vegetation cover had a negative quadratic relationship with neighborhood housing density, peaking at mid-density values, and a positive relationship with education level and immigration status (the percentage of residents with a non-Australian background). Over time, housing density had a positive relationship with vegetation cover, reflecting an increase in vegetation as neighborhoods develop. Our results highlight the need to understand temporal context when attempting to explain contemporary patterns in vegetation cover and the increasing importance of socio-economic factors in influencing cover as neighborhoods become established. [ABSTRACT FROM AUTHOR]

Natural disturbances are key processes in the vast majority of ecosystems and a range of ecological theories have been developed in an attempt to predict biotic responses to them. However, empirical support for these theories has been inconsistent and considerable additional work remains to be done to better understand the response of biodiversity to natural disturbance. We tested predictions from the intermediate disturbance hypothesis and the habitat accommodation model of succession for reptile responses to fire history and a single major fire event. We focused our work on a broad range of vegetation types spanning sedgeland to temperate rainforest located within a national park in south-eastern Australia. We found no significant relationships between reptile species richness and the number of fires over the past 35 years, the time since the last fire, or the severity of a major fire in 2003. Thus, we found no strong evidence to support the intermediate disturbance hypothesis. A correspondence analysis of reptile assemblages revealed a gradient in species responses to fire history. However, we found limited evidence for an ordered succession of reptiles. Nor could the responses of individual species be readily predicted from life history attributes. Thus, our findings were generally not consistent with predictions from the habitat accommodation model of succession. A possible explanation for the absence of a predictable sequence of recovery following disturbance might be the rapidity of post-fire recovery of many components of native vegetation cover that were found to be important for reptiles (e.g. the extent of grass cover). This would have limited the time for early successional conditions to prevail and limited opportunities for species associated with such conditions. We found that most reptile species responses were much more strongly linked to vegetation type than fire variables, emphasizing a need to understand relationships with vegetation before being able to understand possible fire effects (if and where they exist). We found the disturbance concepts we examined were limited in their ability to accurately predict reptile responses to past fire history or the impacts of a single major fire in 2003. Practical management might be best guided not by disturbance theory, but by carefully setting objectives to meet conservation goals for particular individual species of reptiles. [ABSTRACT FROM AUTHOR]

The article discusses the classification and mapping of ecological communities in Australia. Researchers in the country use the non-agglomerative, flexible unweighted pair group arithmetic averaging (UPGMA) approach to classify vegetation within a landscape context. The author explains that vegetation maps are spatial expressions of vegetation type and structural patterns. He also points out about the variation in the quality of vegetation maps. He states that the variation is caused by the quality of remote sensing images across different regions.