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Fine-scale landscape features such as scattered trees are increasingly thought to be critical for dispersal, and need to be considered in connectivity modelling and planning. Yet existing modelling approaches struggle to adequately take fine-scale features and threshold dynamics of dispersal behaviour into account, in part because of computational limitations. We present a framework for modelling connectivity at fine spatial resolutions over large spatial extents. Our framework involves a novel approach to characterising fine-scale dispersal behaviour within the context of existing modelling methods, and uses key parameters of dispersal behaviour to link models and their interpretation at multiple scales. We address computational limitations by creating a gap-crossing threshold layer, which identifies areas where dispersal is possible because of the presence and spacing of fine-scale connectivity elements. This layer is combined with a dispersal-cost layer within a graph-network analysis to identify the optimal least-cost path between patches. Graph metrics are used to assess the importance of specific patches at the regional-scale and to describe connectivity for the whole landscape. A local-scale connectivity model using the Circuitscape software complements the regional analysis outputs by considering all possible pathways across a landscape simultaneously rather than a single least-cost path. The framework was designed specifically to be applied by land use planners who need to quantify the impacts of property development on fine-scale connectivity, yet need to assess implications at the regional scale. We demonstrate the framework by applying it in the Lower Hunter region, Australia. ; This project was funded by the Australian Government Sustainable Regional Development Program in conjunction with the National Environmental Research Program's Landscapes and Policy research Hub.

Despite the proliferation of connectivity modelling approaches, static models have limited usefulness for decision-making by policy-makers and land managers, particularly where significant changes in land uses might be expected into the future. This study presents a flexible, scenario-based approach for modelling fine-scaled connectivity using graph-theory with least-cost paths for modelling connectivity at the regional scale and circuit theory at the local scale. The method allows for the assessment of a range of scenarios based on varying land use practices. Using the Lower Hunter region, Australia as a case study we tested five scenarios that describe the impact of different development choices on connectivity, ranging from high rates of urbanisation to revegetation of a designated green corridor. The changes in connectivity from the current state were assessed by visualising component boundaries and link locations and calculating patch- and landscape-scale graph metrics. In the Lower Hunter we found the green corridor scenario increased connectivity both visually and quantitatively, as shown by a 105% increase in the integral index of connectivity (IIC) which measures habitat availability (reachability) at the landscape scale. In contrast the urbanisation scenario resulted in a decrease in connectivity, with a 39% decrease in the IIC. The approach outlined in this paper is flexible, enabling a range of interests to be included, depending on the datasets available and the issues that need to be addressed. Such methods can be readily and rapidly applied by consultants or government agencies, in this region and elsewhere, to incorporate connectivity modelling into development plans.

Despite the proliferation of connectivity modelling approaches, static models have limited usefulness for decision-making by policy-makers and land managers, particularly where significant changes in land uses might be expected into the future. This study presents a flexible, scenario-based approach for modelling fine-scaled connectivity using graph-theory with least-cost paths for modelling connectivity at the regional scale and circuit theory at the local scale. The method allows for the assessment of a range of scenarios based on varying land use practices. Using the Lower Hunter region, Australia as a case study we tested five scenarios that describe the impact of different development choices on connectivity, ranging from high rates of urbanisation to revegetation of a designated green corridor. The changes in connectivity from the current state were assessed by visualising component boundaries and link locations and calculating patch- and landscape-scale graph metrics. In the Lower Hunter we found the green corridor scenario increased connectivity both visually and quantitatively, as shown by a 105% increase in the integral index of connectivity (IIC) which measures habitat availability (reachability) at the landscape scale. In contrast the urbanisation scenario resulted in a decrease in connectivity, with a 39% decrease in the IIC. The approach outlined in this paper is flexible, enabling a range of interests to be included, depending on the datasets available and the issues that need to be addressed. Such methods can be readily and rapidly applied by consultants or government agencies, in this region and elsewhere, to incorporate connectivity modelling into development plans.

Deer are among the world's most successful invasive mammals and can have substantial deleterious impacts on natural and agricultural ecosystems. Six species have established wild populations in Australia, and the distributions and abundances of some species are increasing. Approaches to managing wild deer in Australia are diverse and complex, with some populations managed as 'game' and others as 'pests'. Implementation of cost-effective management strategies that account for this complexity is hindered by a lack of knowledge of the nature, extent and severity of deer impacts. To clarify the knowledge base and identify research needs, we conducted a systematic review of the impacts and management of wild deer in Australia. Most wild deer are in south-eastern Australia, but bioclimatic analysis suggested that four species are well suited to the tropical and subtropical climates of northern Australia. Deer could potentially occupy most of the continent, including parts of the arid interior. The most significant impacts are likely to occur through direct effects of herbivory, with potentially cascading indirect effects on fauna and ecosystem processes. However, evidence of impacts in Australia is largely observational, and few studies have experimentally partitioned the impacts of deer from those of sympatric native and other introduced herbivores. Furthermore, there has been little rigorous testing of the efficacy of deer management in Australia, and our understanding of the deer ecology required to guide deer management is limited. We identified the following six priority research areas: (i) identifying long-term changes in plant communities caused by deer; (ii) understanding interactions with other fauna; (iii) measuring impacts on water quality; (iv) assessing economic impacts on agriculture (including as disease vectors); (v) evaluating efficacy of management for mitigating deer impacts; and (vi) quantifying changes in distribution and abundance. Addressing these knowledge gaps will assist the development and prioritisation of cost-effective management strategies and help increase stakeholder support for managing the impacts of deer on Australian ecosystems.