Urban fauna communities may be strongly influenced by environmental and socio-economic factors, but the relative importance of these factors is poorly known. Most research on urban fauna has been conducted in large cities and it is unclear if the patterns found in these locations coincide with those from smaller human settlements. We examined the relative importance of environmental and socio-economic factors in explaining variation in urban bird communities across 72 neighbourhoods in 18 regional towns in south-eastern Australia. Native bird species richness varied from 6 to 32 across neighbourhoods and was higher in neighbourhoods with more nectar-rich plants. Variation in bird species diversity across neighbourhoods was also strongly positively related to the density of nectar-rich plants, but was higher also in neighbourhoods with higher socio-economic status (reflecting higher levels of disposal income, education and home ownership). The density of native birds across neighbourhoods per season varied from 1 to 15 birds per hectare and was lower in neighbourhoods with a greater cover of impervious surfaces. The density of exotic birds (introduced to Australia) per season also varied across neighbourhoods (0-13 birds per hectare) and was lower in neighbourhoods with more nectar-rich plants and higher in neighbourhoods with greater impervious surface cover. Our results demonstrated that the vegetation characteristics of household gardens, along streetscapes and in urban parklands had a strong influence on the richness and diversity of urban bird communities.The density of native and exotic birds varied primarily in response to changes in the built environment (measured through impervious surface cover). Socio-economic factors had relatively little direct influence on urban birds, but neighbourhood socio-economics may influence bird communities indirectly through the positive relationship between socio-economic status and vegetation cover recorded in our study area.

No abstract

No abstract

There is a demand for regularly updated, broad-scale, accurate land cover information in Victoria from multiple stakeholders. This paper documents the methods used to generate an annual dominant land cover (DLC) map for Victoria, Australia from 2009 to 2013. Vegetation phenology parameters derived from an annual time series of the Moderate Resolution Imaging Spectroradiometer Vegetation Indices 16-day 250 m (MOD13Q1) product were used to generate annual DLC maps, using a three-tiered hierarchical classification scheme. Classification accuracy at the broadest (primary) class level was over 91% for all years, while it ranged from 72 to 81% at the secondary class level. The most detailed class level (tertiary) had accuracy levels ranging from 61 to 68%. The approach used was able to accommodate variable climatic conditions, which had substantial impacts on vegetation growth patterns and agricultural production across the state between both regions and years. The production of an annual dataset with complete spatial coverage for Victoria provides a reliable base data set with an accuracy that is fit-for-purpose for many applications.

No abstract