Issue addressed: Growing evidence shows that higher-density, mixed-use, pedestrian-friendly neighbourhoods encourage active transport, including transport-related walking. Despite widespread recognition of the benefits of creating more walkable neighbourhoods, there remains a gap between the rhetoric of the need for walkability and the creation of walkable neighbourhoods. Moreover, there is little objective data to benchmark the walkability of neighbourhoods within and between Australian cities in order to monitor planning and design intervention progress and to assess built environment and urban policy interventions required to achieve increased walkability. This paper describes a demonstration project that aimed to develop, trial and validate a 'Walkability Index Tool' that could be used by policy makers and practitioners to assess the walkability of local areas; or by researchers to access geospatial data assessing walkability. The overall aim of the project was to develop an automated geospatial tool capable of creating walkability indices for neighbourhoods at user-specified scales. Methods: The tool is based on open-source software architecture, within the Australian Urban Research Infrastructure Network (AURIN) framework, and incorporates key sub-component spatial measures of walkability (street connectivity, density and land use mix). Results: Using state-based data, we demonstrated it was possible to create an automated walkability index. However, due to the lack of availability of consistent of national data measuring land use mix, at this stage it has not been possible to create a national walkability measure. The next stage of the project is to increase useability of the tool within the AURIN portal and to explore options for alternative spatial data sources that will enable the development of a valid national walkability index. Conclusion: AURIN's open-source Walkability Index Tool is a first step in demonstrating the potential benefit of a tool that could measure walkability across Australia. It also demonstrates the value of making accurate spatial data available for research purposes. So what?There remains a gap between urban policy and practice, in terms of creating walkable neighbourhoods. When fully implemented, AURIN's walkability tool could be used to benchmark Australian cities against which planning and urban design decisions could be assessed to monitor progress towards achieving policy goals. Making cleaned data readily available for research purposes through a common portal could also save time and financial resources.
A variety of tagging techniques are now available to monitor fish behaviour, physiology and their environmental experience. Tagging is frequently used in aquaculture research to monitor free-swimming individuals within farmed populations. However, for information gathered from tagged fish to be representative of farmed populations, tagging must not fundamentally affect fish behaviour, physiology or survival. Here, we systematically review studies that used tags to monitor farmed fish behaviour and test factors that affect tag retrieval and tag-related mortality. Most studies using tags assessed movement and swimming behaviour in salmonids, predominantly in Europe and North America. Mortality of tagged fish was 10 times higher in sea-cages (mean = 25%, range = 0-61.5%, n = 22 studies) than in tanks (mean = 2.5%, range = 0-17%, n = 23 studies), while mortality of tagged fish in sea-cages was markedly higher in longer trials (from 4% in single day trials to 36% after 100 days). Higher-than-usual mortality rates among tagged fish, together with largely unknown sublethal effects on behaviour, should caution against using tagging studies to make decisions related to farm management. Moreover, key metrics such as mortality rates of tagged and untagged fish or evidence of sublethal effects are often unreported. We make several recommendations to improve future tagging studies and increase transparency in reporting. A greater insight into the causes of tagged fish mortality in sea-cages is required to secure animal welfare and data validity in studies that use tags to assess fish behaviour in aquaculture.
BackgroundPedestrian-friendly neighborhoods with proximal destinations and services encourage walking and decrease car dependence, thereby contributing to more active and healthier communities. Proximity to key destinations and services is an important aspect of the urban design decision making process, particularly in areas adopting a transit-oriented development (TOD) approach to urban planning, whereby densification occurs within walking distance of transit nodes. Modeling destination access within neighborhoods has been limited to circular catchment buffers or more sophisticated network-buffers generated using geoprocessing routines within geographical information systems (GIS). Both circular and network-buffer catchment methods are problematic. Circular catchment models do not account for street networks, thus do not allow exploratory ‘what-if’ scenario modeling; and network-buffering functionality typically exists within proprietary GIS software, which can be costly and requires a high level of expertise to operate.MethodsThis study sought to overcome these limitations by developing an open-source simple agent-based walkable catchment tool that can be used by researchers, urban designers, planners, and policy makers to test scenarios for improving neighborhood walkable catchments. A simplified version of an agent-based model was ported to a vector-based open source GIS web tool using data derived from the Australian Urban Research Infrastructure Network (AURIN). The tool was developed and tested with end-user stakeholder working group input.ResultsThe resulting model has proven to be effective and flexible, allowing stakeholders to assess and optimize the walkability of neighborhood catchments around actual or potential nodes of interest (e.g., schools, public transport stops). Users can derive a range of metrics to compare different scenarios modeled. These include: catchment area versus circular buffer ratios; mean number of streets crossed; and modeling of different walking speeds and wait time at intersections.ConclusionsThe tool has the capacity to influence planning and public health advocacy and practice, and by using open-access source software, it is available for use locally and internationally. There is also scope to extend this version of the tool from a simple to a complex model, which includes agents (i.e., simulated pedestrians) ‘learning’ and incorporating other environmental attributes that enhance walkability (e.g., residential density, mixed land use, traffic volume).
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