A novel process to infer the reliability of ecological information derived from passive acoustic telemetry track reconstruction

Author:

Bowers Mary E.12ORCID,Kajiura Stephen M.1

Affiliation:

1. Department of Biological Sciences Florida Atlantic University Boca Raton Florida USA

2. Smithsonian Environmental Research Center Edgewater Maryland USA

Abstract

Abstract Passive acoustic telemetry can be used within cooperative networks to track migratory species over great distances at a relatively low cost. However, the non‐uniform distribution of fixed receivers within networks often results in sporadic detection data. Here, we propose a novel combination of methods to measure the reliability of hot spot analysis results derived from track reconstructions of passive telemetry data. We use an iterative process to simulate tracks of animals, derive detection data from these tracks, and reconstruct tracks from these derived data using a movement model. We then compare quadrat count residuals from the simulated and reconstructed tracks for different grid resolutions. The methodological framework is outlined in detail and tested on the acoustic telemetry cooperative arrays off the US East Coast. Our methods are applied to a subset of blacktip shark, Carcharhinus limbatus, acoustic telemetry detection data collected off the US East Coast. We then apply the resultant quadrat count to a hot spot analysis to determine the distribution of animals derived from these track reconstruction methods. We integrate the results of our methods process with the hot spot analysis results to determine the reliability of this distribution information. The track reconstruction methods performed well in coastal regions, from Palm Beach County, FL to Long Island, NY, minimized the clustering effect of high densities of receivers, and closed the gaps in some regions that were lacking receiver coverage. This performance was primarily affected by the presence/absence of receivers, and to a lesser extent by receiver density and water depth, depending on the grid resolution. Our method combination demonstrates a means by which passive telemetry data can be regularized to determine the spatial distribution of animals across regions with non‐uniform sampling coverage. These methods also allow the user to determine the reliability of animal distribution products in a telemetry array and the factors that contribute to high accuracy and precision. Our iterative process enables managers to infer the reliability of ecological results in decision‐making processes and could be leveraged for use as a gap analysis to develop a national strategy for telemetry assets.

Publisher

Wiley

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