Fine‐scale spatial risk models to predict avian collisions with power lines

Abstract Avian fatalities caused by collisions with overhead power lines are an important conservation issue worldwide. Although mitigation strategies can help reduce mortalities, given their considerable cost and the vast scale of power line infrastructure, cost‐effective action requires that these efforts be prioritised to areas with the highest potential risk to birds. To date, this risk assessment has usually been guided by potentially biased information on the location of recorded fatalities. Here we use 6 years of GPS‐tracking data from endangered Tasmanian wedge‐tailed eagles to develop an alternative approach to risk assessment: fine‐scale spatial risk models based on behavioural analyses. We built and cross‐validated a model that generates spatially explicit predictions of the probability that eagles would cross power lines at hazardous altitudes throughout the entire Tasmanian electricity distribution network. In our model, the probability of power line crossings was most strongly associated with the proportion of open habitat, forest edges, rural residential developments, wet forest and freshwater sources in the area surrounding the power lines. Cross‐validation indicated that the model effectively predicted where Tasmanian wedge‐tailed eagles cross power lines at low altitude. Model validation suggested our approach was a powerful predictor of the locations of power line collisions involving eagles. The locations of almost all (94%) confirmed eagle fatalities were in the half of the total Tasmanian power line area assigned the higher risk by the model, and 50% of incidents occurred in the 20% of the power line area estimated to be highest risk. Synthesis and applications. Our study illustrates a framework for using bird movement data to provide insights into avian behaviour and the risk they encounter around power line infrastructure. Electricity delivery industries can use these models to identify the electrical infrastructure that poses the highest risk to avian survival and prioritise mitigation efforts, thereby optimising the benefit of investments to reduce detrimental effects on biodiversity. Our model can inform pre‐emptive mitigation across Tasmania's 20,310 km of distribution infrastructure to meet management targets aiming to reduce the negative effects of power lines on the Tasmanian wedge‐tailed eagle.

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Publication Details

Journal
Journal of Applied Ecology
Published
2025-06-18
DOI
https://doi.org/10.1111/1365-2664.70076
Citations
1
Primary Topic
Wildlife Ecology and Conservation
Type
article
Field-Weighted Citation Impact
1.72

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article

Fine‐scale spatial risk models to predict avian collisions with power lines

Amelia J. Koch, Jason M. Wiersma, Clare E. Hawkins, James M. Pay et al.
1 citations
Journal of Applied Ecology
Wildlife Ecology and Conservation
1.72
article

Fine‐scale spatial risk models to predict avian collisions with power lines

Amelia J. Koch, Jason M. Wiersma, Clare E. Hawkins, James M. Pay, Todd E. Katzner, Elissa Z. Cameron, Christopher N. Johnson
article en
1 citations

Abstract

Abstract Avian fatalities caused by collisions with overhead power lines are an important conservation issue worldwide. Although mitigation strategies can help reduce mortalities, given their considerable cost and the vast scale of power line infrastructure, cost‐effective action requires that these efforts be prioritised to areas with the highest potential risk to birds. To date, this risk assessment has usually been guided by potentially biased information on the location of recorded fatalities. Here we use 6 years of GPS‐tracking data from endangered Tasmanian wedge‐tailed eagles to develop an alternative approach to risk assessment: fine‐scale spatial risk models based on behavioural analyses. We built and cross‐validated a model that generates spatially explicit predictions of the probability that eagles would cross power lines at hazardous altitudes throughout the entire Tasmanian electricity distribution network. In our model, the probability of power line crossings was most strongly associated with the proportion of open habitat, forest edges, rural residential developments, wet forest and freshwater sources in the area surrounding the power lines. Cross‐validation indicated that the model effectively predicted where Tasmanian wedge‐tailed eagles cross power lines at low altitude. Model validation suggested our approach was a powerful predictor of the locations of power line collisions involving eagles. The locations of almost all (94%) confirmed eagle fatalities were in the half of the total Tasmanian power line area assigned the higher risk by the model, and 50% of incidents occurred in the 20% of the power line area estimated to be highest risk. Synthesis and applications. Our study illustrates a framework for using bird movement data to provide insights into avian behaviour and the risk they encounter around power line infrastructure. Electricity delivery industries can use these models to identify the electrical infrastructure that poses the highest risk to avian survival and prioritise mitigation efforts, thereby optimising the benefit of investments to reduce detrimental effects on biodiversity. Our model can inform pre‐emptive mitigation across Tasmania's 20,310 km of distribution infrastructure to meet management targets aiming to reduce the negative effects of power lines on the Tasmanian wedge‐tailed eagle.

Journal of Applied EcologyVol. 62(8)
United States Geological Survey (US), University of Tasmania (AU), University of Canterbury (NZ), Rocky Mountain Research Station (US), Forest and Rangeland Ecosystem Science Center, Forestry Tasmania (AU)
Holsworth Wildlife Research Endowment, Norske Skog, Australian Research Council
Openalex Percentile: Top 16%
Wildlife Ecology and Conservation
1.72
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