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Beyond BACI: Offsetting carcass numbers with flight intensity to improve risk assessments of bird collisions with power lines
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Beyond BACI: Offsetting carcass numbers with flight intensity to improve risk assessments of bird collisions with power lines
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Journal Article
Beyond BACI: Offsetting carcass numbers with flight intensity to improve risk assessments of bird collisions with power lines
2021
Overview
The continuing global expansion of electricity networks increases the risk of bird collisions with power lines. Several field studies have demonstrated that this risk can be reduced by marking lines with flight diverters. A before‐after control‐impact (BACI) design is currently the suggested approach for evaluating the effectiveness of these diverters and is generally assumed to give unbiased results. Using systematic flight survey data, we demonstrate that the assumptions underlying the BACI approach are frequently violated, leading to biased effectiveness estimates. We present an alternative field and statistical design in which the number of bird strike victims is directly related to bird flight intensity (“fusion design”), instead of estimating it indirectly using a control site. The presented design is validated based on simulations. We demonstrate that the presented method is unbiased and shows an approximately 3‐fold higher statistical power compared with BACI, even under ideal/unbiased data conditions, with similar field‐experimental effort. Moreover, this approach can provide a direct analysis of bird reactions/collisions, estimation of collision rates, and the possibility of conducting the required fieldwork within a single season. Our presented method can be used to standardize and improve future studies on diverter effectiveness, for example, by supporting the acquisition of a more detailed picture of species‐, diverter type‐, and habitat‐specific estimates. We compare and extend methods to analyze bird collision frequency at power lines. We present a new field and statistical approach (“fusion approach”) and demonstrate that this new method is unbiased and shows an approximately 3‐fold higher statistical power compared with previous methods.
