Environmental impacts of abrasive blasting of transmission towers in protected areas.

In Australia, and other parts of the world, tower infrastructure in electricity transmission networks are nearing the end of their asset life. In changing economic, political and regulatory environments Transmission Network Service Providers are implementing new approaches to asset management and reinvestment, such as refurbishment to extend the life of existing assets, instead of replacement. As part of these refurbishment efforts, abrasive blasting and recoating is being employed to remove corrosion and extend the life of steel electricity transmission towers. New controls and procedures have been developed to manage the most likely impacts associated with the abrasive blasting of transmission towers. However, little or no data have been available on the environmental impacts of abrasive blasting or the effectiveness of management procedures currently being used to mitigate potential adverse environmental impacts.We conducted an integrated study on the impacts of abrasive blasting, which brought together on-site research; modelling; and controlled laboratory trials. The study was undertaken during a transmission tower refurbishment project within the World Heritage listed Wet Tropics Region in Queensland, Australia. Measured metal deposition around towers due to blasting, was primarily as large particles (>PM10) at 12-30 m from the tower. Soil concentrations of metals were highest under towers, with a small number of samples showing elevated zinc at 12-30 m. The presence of spent abrasive media and dust on the geofabric material used under the towers and up to 15 m from the tower base, as part of control measures used to contain the abrasive products, indicates that deposition also occurs between 0 and 12 m from the tower.The potential impacts of the abrasive blasting technique on plants and invertebrates appear to be low. Five species of tropical rainforest tree seedlings exposed to abrasive blasting dust at worst-case levels had no negative impact on physiological performance or plant health. This research will assist Transmission Network Service Providers and other operators of corroded linear infrastructure to plan and implement mitigating management actions and procedures during abrasive blasting projects and assist regulators and the community to better understand the impacts of the practice.

Beyond the model: expert knowledge improves predictions of species' fates under climate change.

The need to proactively manage landscapes and species to aid their adaptation to climate change is widely acknowledged. Current approaches to prioritizing investment in species conservation generally rely on correlative models, which predict the likely fate of species under different climate change scenarios. Yet, while model statistics can be improved by refining modeling techniques, gaps remain in understanding the relationship between model performance and ecological reality. To investigate this, we compared standard correlative species distribution models to highly accurate, fine-scale, distribution models. We critically assessed the ecological realism of each species' model, using expert knowledge of the geography and habitat in the study area and the biology of the study species. Using interactive software and an iterative vetting with experts, we identified seven general principles that explain why the distribution modeling under- or overestimated habitat suitability, under both current and predicted future climates. Importantly, we found that, while temperature estimates can be dramatically improved through better climate downscaling, many models still inaccurately reflected moisture availability. Furthermore, the correlative models did not account for biotic factors, such as disease or competitor species, and were unable to account for the likely presence of micro refugia. Under-performing current models resulted in widely divergent future projections of species' distributions. Expert vetting identified regions that were likely to contain micro refugia, even where the fine-scale future projections of species distributions predicted population losses. Based on the results, we identify four priority conservation actions required for more effective climate change adaptation responses. This approach to improving the ecological realism of correlative models to understand climate change impacts on species can be applied broadly to improve the evidence base underpinning management responses.