impact assessment
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This record provides an overview of the NESP Marine and Coastal Hub Research Plan 2024 project "Potential impacts of offshore wind developments on eastern Indian Ocean pygmy blue whales (Balaenoptera musculus brevicauda)". For specific data outputs from this project, please see child records associated with this metadata. -------------------- Pygmy blue whales (Balaenoptera musculus brevicauda) are listed as Endangered under the Environment Protection and Biodiversity Conservation Act (EPBC 1999), and their distribution and Biologically Important Areas (BIAs) overlap with areas proposed for offshore renewable energy (ORE) development in Western Australia, South Australia, Victoria, and potentially NSW. This project will quantify the distribution and location of areas of residency (e.g., foraging) for eastern Indian Ocean pygmy blue whales, where these overlap with proposed ORE developments, and assess the potential impacts of these developments to the species in addition to existing impacts from other anthropogenic activities. The outputs from this project will assist government, regulators, proponents, and other stakeholders in the assessment and mitigation of ORE projects to this threatened species, and will identify future research and associated data collection needs. Outputs • Spatial layers quantifying the relative distribution including migratory corridors and foraging areas across the known eastern Indian Ocean pygmy blue whale range [dataset] • Spatial layers of habitat suitability distribution [dataset] • Spatial layers for human activities identified as key pressures in this study [dataset] • Spatial layers of cumulative impact score across the species' range including potential threats from ORE and existing threats from other industries [dataset] • Final project report [written]
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This record provides an overview of the NESP Marine and Coastal Hub scoping study - "Research needs for a national approach to socio-economic values of the marine environment". For specific data outputs from this project, please see child records associated with this metadata. -------------------- Effective management of natural resources and biodiversity requires an integrated understanding of the complex relationships between people and nature. This project reviewed a range of socio-ecological frameworks to identify which system components influence environmental outcomes, and which are most relevant for policy design and behaviour change. A key point of difference from previous NESP Marine Biodiversity Hub projects was an additional theme on implementation pathways, enabling research to inform the full progression from policy to on-ground action. Through a co-design process with stakeholders, the project identified priority social and economic research needs and assessed the availability of relevant datasets to meet them. A key outcome was the identification of three common decision contexts faced by managers—monitoring, trade-off analysis, and promoting behaviour change—and the matching of appropriate frameworks and data to each context. The findings highlight critical data gaps, while providing practical guidance on how existing information can be strategically used to inform management and policy decisions. Outputs • Inventory of compiled datasets relating to relevant economic values, threats, and socioeconomic values for Case Study locations [data inventory] • Four fact sheets, each based around common decision contexts encountered by the project [written] • Final Project Report [written]
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This project developed an interim Population Consequence of Disturbance (iPCoD) model for blue whales (Balaenoptera musculus) and southern right whales (Eubalaena australis) to document a methodology for assessing population-level impacts of one, or multiple, wind farm developments off the southern Australian coast. The iPCoD model was developed in Europe to quantify how disturbances of individuals caused by physiological injury or changes in behaviour can have population-level consequences in data poor marine mammal populations. This model was adapted to suit Australian marine mammal species, highlighting key data gaps for locally threatened populations that overlap in range with the declared offshore wind areas in Australia. Due to the lack of baseline data currently available, this study documented a framework that can be updated as more information becomes available. We outlined how to leverage simulation-based population modelling as a tool for policymakers, industry and management authorities, to aid in environmental impact assessments, with a specific focus on data poor marine mammal populations.