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Collateral damage of the energy transition? Investigating the avoidance of powerlines by the Eurasian Skylark Alauda arvensis in a German agricultural landscape

Published online by Cambridge University Press:  18 February 2025

Sebastian Klaus*
Affiliation:
Faculty of Biological Sciences, J.W. Goethe Universität, Frankfurt am Main, Germany
Jia Huan Liew
Affiliation:
School of Natural Sciences, University of Tasmania, Australia
Christian Müller
Affiliation:
ERM GmbH, Neu-Isenburg, Germany
Boris Jechow
Affiliation:
ERM GmbH, Neu-Isenburg, Germany
*
Corresponding author: Sebastian Klaus; Email: klaus@bio.uni-frankfurt.de
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Summary

We investigated Eurasian Skylark Alauda arvensis avoidance of powerlines and their pylons by assessing the spatial distribution of Skylark territories. We mapped territory centres in a central German agricultural landscape during 2020 and used Bayesian logistic regression models to test if distances from powerlines and pylons are predictive of the presence of territories. We also tested other possible predictors, namely, nearest distances from roads, vertical structures, wind energy plants, settlements, as well as the nearest pylon type and vegetation. Distances from the nearest road and settlement were positively correlated with the probability of territory occurrence. However, distance from powerlines and pylons were not significant predictors. Skylarks were also more likely to establish territories in areas where winter grain is present. We conclude that powerlines are unlikely to lead to significant habitat reduction for the Skylark that would impact local populations. We can, however, confirm avoidance behaviour towards roads and settlements, as well as a preference for areas with winter grain because the crop’s growth period coincides with the start of the breeding season, initially providing vegetation of a suitable height and coverage.

Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - SA
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike licence (http://creativecommons.org/licenses/by-nc-sa/4.0), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the same Creative Commons licence is used to distribute the re-used or adapted article and the original article is properly cited. The written permission of Cambridge University Press must be obtained prior to any commercial use.
Copyright
© The Author(s), 2025. Published by Cambridge University Press on behalf of BirdLife International
Figure 0

Figure 1. The five survey plots in the agricultural landscapes of Wetterau and Vogelsberg in central Germany. A: Hungen; B: Wölfersheim; C: Dorheim; D: Weckesheim; E: Waldensberg. (Basemap: Open Street Map 2024)

Figure 1

Figure 2. Examples of pylon configurations. From left to right: 110 kV pylon (survey plot Hungen; Figures 1A and 4A), pylons of parallel running 110 kV and 380 kV powerlines (survey plot Dorheim, distance between pylons not to scale; Figures 1C and 5C); 380 kV pylon (survey plot Waldensberg; Figures 1E and 4E), and 20 kV concrete pylon (survey plot Weckesheim; Figures 1D and 4D). Pylon height only approximately drawn to scale, as heights can vary along the same powerline.

Figure 2

Table 1. Survey dates in 2020 for the five surveyed plots. Additionally, land cover was mapped on the second date (in bold)

Figure 3

Figure 3. An example of territory centre inference from consecutive observed activities. Note that we did not infer territory boundaries.

Figure 4

Figure 4. Territory centres and modelled territory density within the five surveyed plots. A: Hungen; B: Wölfersheim; C: Dorheim; D: Weckesheim; E: Waldensberg.

Figure 5

Figure 5. A, B, and D: logistic regression models describing the relationship between probability of Skylark territory centre occurrence and distances from the nearest road (A), settlement (B), and pylon (D), respectively, while keeping spatial coordinates constant. Solid blue lines (in A and B) are indicative of the upper and lower boundaries of 95% credible intervals in statistically significant outcomes (i.e. 95% credible intervals of slope parameters do not overlap with zero), while dashed blue lines (in D) represent 95% credible intervals of non-statistically significant outcomes. Solid black lines represent the models’ median slope. C: posterior distributions of the probability of territory centre occurrence in areas where winter grain is absent and present, respectively.

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