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量化近岸海龟密度:无人航空系统在种群评估中的应用。

Quantifying Nearshore Sea Turtle Densities: Applications of Unmanned Aerial Systems for Population Assessments.

机构信息

Duke University Marine Laboratory, Nicholas School of the Environment, 135 Duke Marine Lab Road, Beaufort, North Carolina, 28516, USA.

Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, 27599, USA.

出版信息

Sci Rep. 2017 Dec 18;7(1):17690. doi: 10.1038/s41598-017-17719-x.

Abstract

Although sea turtles face significant pressure from human activities, some populations are recovering due to conservation programs, bans on the trade of turtle products, and reductions in bycatch. While these trends are encouraging, the status of many populations remains unknown and scientific monitoring is needed to inform conservation and management decisions. To address these gaps, this study presents methods for using unmanned aerial systems (UAS) to conduct population assessments. Using a fixed-wing UAS and a modified strip-transect method, we conducted aerial surveys along a three-kilometer track line at Ostional, Costa Rica during a mass-nesting event of olive ridley turtles (Lepidochelys olivacea). We visually assessed images collected during six transects for sea turtle presence, resulting in 682 certain detections. A cumulative total of 1091 certain and probable turtles were detected in the collected imagery. Using these data, we calculate estimates of sea turtle density (km) in nearshore waters. After adjusting for both availability and perception biases, we developed a low-end estimate of 1299 ± 458 and a high-end estimate of 2086 ± 803 turtles per km. This pilot study illustrates how UAS can be used to conduct robust, safe, and cost-effective population assessments of sea turtle populations in coastal marine ecosystems.

摘要

尽管海龟面临着人类活动的巨大压力,但由于保护计划、对海龟产品贸易的禁令以及减少副渔获物,一些种群正在恢复。虽然这些趋势令人鼓舞,但许多种群的状况仍不清楚,需要进行科学监测,以为保护和管理决策提供信息。为了解决这些差距,本研究提出了使用无人机系统(UAS)进行种群评估的方法。在哥斯达黎加 Ostional 进行大规模橄榄绿海龟(Lepidochelys olivacea)筑巢活动期间,我们使用固定翼 UAS 和改良的条带样带法,在三公里长的航迹线上进行了航空调查。我们对六次样带的图像进行了目视评估,以确定海龟的存在情况,结果得到了 682 个确定的海龟。在收集的图像中总共检测到 1091 个确定和可能的海龟。利用这些数据,我们计算了近岸水域中海龟密度(km)的估计值。在调整了可得性和感知偏差之后,我们得出了一个低值估计值为 1299 ± 458 只,一个高值估计值为 2086 ± 803 只/km。这项试点研究说明了如何使用无人机系统(UAS)在沿海海洋生态系统中对海龟种群进行稳健、安全和具有成本效益的种群评估。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26e9/5735099/e589a326160e/41598_2017_17719_Fig1_HTML.jpg

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