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Por Sandra Rodrigues (Bioinsight e CEAUL).

This presentation demonstrates how a PhD applied in the field of industry can address concrete problems, highlighting the importance of bridging scientific research and practical applications in the job market. A methodology was developed to quantitatively assess the risk of bats colliding with wind turbine blades. The approach integrates spatial and temporal models to predict bat activity based on acoustic data and employs data fusion techniques to combine two different sources: ground-level data and data at the risk height (i.e., at the blade rotation height).

The proposed approach has a hierarchical structure with three levels, comprising three components: the first component uses spatial point process models combined with distance sampling techniques to determine bat activity at ground level; the second component determines the temporal variation of activity; and the third component interconnects the spatial and temporal components to feed a collision model and estimate the number of collisions with turbines over a year.

The risk of bat collisions in wind farms remains a problem that is not adequately addressed in environmental impact assessments (EIAs). This gap is critical since EIAs and monitoring programs are the first steps in implementing preventing and mitigation strategies. Thus, a correct impact analysis in these instruments is crucial for wildlife conservation.
The methodology was applied to a real-world case for an EIA South Africa, demonstrating its practical utility in minimizing impacts on bat populations.