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一种用于识别底栖觅食鳍足类动物中精细尺度底部利用情况的新方法。

A novel method for identifying fine-scale bottom-use in a benthic-foraging pinniped.

作者信息

Angelakis Nathan, Goldsworthy Simon D, Connell Sean D, Durante Leonardo M

机构信息

University of Adelaide, North Terrace, Adelaide, SA, 5000, Australia.

South Australian Research and Development Institute (SARDI) (Aquatic Sciences), 2 Hamra Avenue, West Beach, SA, 5024, Australia.

出版信息

Mov Ecol. 2023 Jun 9;11(1):34. doi: 10.1186/s40462-023-00386-1.

DOI:10.1186/s40462-023-00386-1
PMID:37296462
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10257308/
Abstract

BACKGROUND

For diving, marine predators, accelerometer and magnetometer data provides critical information on sub-surface foraging behaviours that cannot be identified from location or time-depth data. By measuring head movement and body orientation, accelerometers and magnetometers can help identify broad shifts in foraging movements, fine-scale habitat use and energy expenditure of terrestrial and marine species. Here, we use accelerometer and magnetometer data from tagged Australian sea lions and provide a new method to identify key benthic foraging areas. As Australian sea lions are listed as endangered by the IUCN and Australian legislation, identifying key areas for the species is vital to support targeted management of populations.

METHODS

Firstly, tri-axial magnetometer and accelerometer data from adult female Australian sea lions is used in conjunction with GPS and dive data to dead-reckon their three-dimensional foraging paths. We then isolate all benthic phases from their foraging trips and calculate a range of dive metrics to characterise their bottom usage. Finally, k-means cluster analysis is used to identify core benthic areas utilised by sea lions. Backwards stepwise regressions are then iteratively performed to identify the most parsimonious model for describing bottom usage and its included predictor variables.

RESULTS

Our results show distinct spatial partitioning in benthic habitat-use by Australian sea lions. This method has also identified individual differences in benthic habitat-use. Here, the application of high-resolution magnetometer/accelerometer data has helped reveal the tortuous foraging movements Australian sea lions use to exploit key benthic marine habitats and features.

CONCLUSIONS

This study has illustrated how magnetometer and accelerometer data can provide a fine-scale description of the underwater movement of diving species, beyond GPS and depth data alone, For endangered species like Australian sea lions, management of populations must be spatially targeted. Here, this method demonstrates a fine-scale analysis of benthic habitat-use which can help identify key areas for both marine and terrestrial species. Future integration of this method with concurrent habitat and prey data would further augment its power as a tool for understanding the foraging behaviours of species.

摘要

背景

对于潜水海洋捕食者而言,加速度计和磁力计数据能提供关于其水下觅食行为的关键信息,而这些信息无法从位置或时间深度数据中获取。通过测量头部运动和身体方位,加速度计和磁力计有助于识别陆地和海洋物种觅食活动、精细尺度栖息地利用及能量消耗的广泛变化。在此,我们利用来自佩戴标签的澳大利亚海狮的加速度计和磁力计数据,提供一种识别关键底栖觅食区域的新方法。由于澳大利亚海狮被国际自然保护联盟(IUCN)和澳大利亚法律列为濒危物种,识别该物种的关键区域对于支持针对性的种群管理至关重要。

方法

首先,将成年雌性澳大利亚海狮的三轴磁力计和加速度计数据与GPS及潜水数据结合使用,推算出它们的三维觅食路径。然后,我们从它们的觅食行程中分离出所有底栖阶段,并计算一系列潜水指标以表征它们在海底的活动情况。最后,使用k均值聚类分析来识别海狮利用的核心底栖区域。接着迭代进行向后逐步回归,以确定描述海底活动情况及其包含的预测变量的最简约模型。

结果

我们的结果显示澳大利亚海狮在底栖栖息地利用上存在明显的空间划分。该方法还识别出了底栖栖息地利用方面的个体差异。在此,高分辨率磁力计/加速度计数据的应用有助于揭示澳大利亚海狮用于利用关键底栖海洋栖息地和特征的曲折觅食活动。

结论

本研究说明了磁力计和加速度计数据如何能够提供对潜水物种水下运动的精细尺度描述,这超越了仅靠GPS和深度数据所能提供的信息。对于像澳大利亚海狮这样的濒危物种,种群管理必须在空间上具有针对性。在此,该方法展示了对底栖栖息地利用的精细尺度分析,这有助于识别海洋和陆地物种的关键区域。未来将此方法与同步的栖息地和猎物数据相结合,将进一步增强其作为理解物种觅食行为工具的能力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2dfc/10257308/c699ca8db816/40462_2023_386_Figg_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2dfc/10257308/f826a949da8b/40462_2023_386_Figd_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2dfc/10257308/966ba1ac9228/40462_2023_386_Fige_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2dfc/10257308/6aedecfb39fd/40462_2023_386_Figf_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2dfc/10257308/edb77dfde2bd/40462_2023_386_Figh_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2dfc/10257308/c699ca8db816/40462_2023_386_Figg_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2dfc/10257308/f826a949da8b/40462_2023_386_Figd_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2dfc/10257308/966ba1ac9228/40462_2023_386_Fige_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2dfc/10257308/6aedecfb39fd/40462_2023_386_Figf_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2dfc/10257308/edb77dfde2bd/40462_2023_386_Figh_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2dfc/10257308/c699ca8db816/40462_2023_386_Figg_HTML.jpg

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How often should dead-reckoned animal movement paths be corrected for drift?推算动物移动路径时,应多久对漂移进行一次校正?
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Hidden Markov models identify major movement modes in accelerometer and magnetometer data from four albatross species.隐马尔可夫模型识别了来自四种信天翁物种的加速度计和磁力计数据中的主要运动模式。
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