Wind Farms and Biodiversity: Improving Environmental Risk Assessments

Book Chapter

Title: Wind Farms and Biodiversity: Improving Environmental Risk Assessments
Publication Date:
January 01, 2015
Volume: 1
Pages: 41-58
Publisher: Springer
Receptor:

Document Access

Website: External Link

Citation

Boothroyd, I.; Barea, L. (2015). Wind Farms and Biodiversity: Improving Environmental Risk Assessments. (pp. 41-58). Springer.
Abstract: 

Greenhouse gasses are widely acknowledged as the primary cause of anthropogenically driven climate change. As part of its response to climate change, the New Zealand Government has adopted a target for renewable electricity generation of 90% by 2025. Currently New Zealand has 16 wind farms in operation with a combined capacity of 622 MW. Wind-generated power, combined with a projected six-fold increase in wind generated electricity by 2030 has the potential to contribute significantly to New Zealand's renewable targets. In New Zealand, wind energy developments require resource consent under the Resource Management Act 1991 involving the preparation of an Assessment of Environmental Effects to identify and address the risks of a proposal to the environment, including biodiversity. Quantitative methods require empirical data while more qualitative approaches can be based more on knowledge of the topography and sensitivity of the ecosystems. Adopting quantitative approaches can provide a structured approach to study design, data needs and analysis that objectively inform a risk assessment, decisions about the appropriateness of a development, the mitigation hierarchy and, when required, the development of biodiversity offsets. Stratified qualitative approaches that use ranked data of significant habitats and/or species of regional or national significance can also inform decision making. We illustrate these principles with case studies involving modelling of collision risk for the threatened New Zealand falcon based on radio tracking data, and the use of a risk envelope for a wind farm based on habitat and species assessments.

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