How to improve the accuracy of height data from bird tracking devices? An assessment of high-frequency GPS tracking and barometric altimetry in field conditions

Author:

Schaub TonioORCID,Millon AlexandreORCID,De Zutter Caroline,Buij Ralph,Chadœuf Joël,Lee Simon,Mionnet Aymeric,Klaassen Raymond Hendrikus Gerardus

Abstract

Abstract Background In the context of rapid development of wind energy infrastructure, information on the flight height of birds is vital to assess their collision risk with wind turbines. GPS tags potentially represent a powerful tool to collect flight height data, yet GPS positions are associated with substantial vertical error. Here, we assessed to what extent high-frequency GPS tracking with fix intervals of 2–3 s (GPS remaining turned on between fixes), or barometric altimetry using air pressure loggers integrated in GPS tags, improved the accuracy of height data compared to standard low-frequency GPS tracking (fix interval ≥ 5 min; GPS turned off between fixes). Results Using data from 10 GPS tag models from three manufacturers in a field setting (194 tags deployed on free-living raptors), we estimated vertical accuracy based on periods when the birds were stationary on the ground (true height above ground was approximately zero), and the difference between GPS and barometric height in flight. In GPS height data, vertical accuracy was mainly driven by noise (little bias), while in barometric data, it was mostly affected by bias (little noise). In high-frequency GPS data, vertical accuracy was improved compared to low-frequency data in each tag model (mean absolute error (AE) reduced by 72% on average; range of mean AE 2–7 vs. 7–30 m). In barometric data, vertical accuracy did not differ between high- and low-frequency modes, with a bias of − 15 to − 5 m and mean AE of 7–15 m in stationary positions. However, the median difference between GPS and barometric data was smaller in flight positions than in stationary positions, suggesting that the bias in barometric height data was smaller in flight. Finally, simulations showed that the remaining vertical error in barometric and high-frequency GPS data had little effect on flight height distributions and the proportion of positions within the collision risk height range, as opposed to the extensive noise found in low-frequency GPS data in some tag models. Conclusions Barometric altimetry may provide more accurate height data than standard low-frequency GPS tracking, but it involves the risk of a systematic error. Currently, high-frequency GPS tracking provides highest vertical accuracy and may thus substantially advance the study of wind turbine collision risk in birds.

Funder

ANRT & ENGIE

Dutch Province of Flevoland and Dutch Ministry of Agriculture, Nature and Food Quality

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Instrumentation,Animal Science and Zoology,Signal Processing

Reference39 articles.

1. De Lucas M, Perrow MR. Birds: Collision. In: Perrow MR, editor. Wildlife and wind farms, conflicts and solutions. Volume 1: Onshore: Potential effects. Exeter: Pelagic Publishing; 2017. p. 155–90.

2. Thaxter CB, Buchanan GM, Carr J, Butchart SHM, Newbold T, Green RE, et al. Bird and bat species’ global vulnerability to collision mortality at wind farms revealed through a trait-based assessment. Proc R Soc B Biol Sci. 1862;2017(284):20170829.

3. Bellebaum J, Korner-Nievergelt F, Dürr T, Mammen U. Wind turbine fatalities approach a level of concern in a raptor population. J Nat Conserv. 2013;21(6):394–400.

4. Carrete M, Sánchez-Zapata JA, Benítez JR, Lobón M, Donázar JA. Large scale risk-assessment of wind-farms on population viability of a globally endangered long-lived raptor. Biol Conserv. 2009;142(12):2954–61.

5. Chamberlain DE, Rehfisch MR, Fox AD, Desholm M, Anthony SJ. The effect of avoidance rates on bird mortality predictions made by wind turbine collision risk models. Ibis. 2006;148:198–202.

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3