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Using water-landing, fixed-wing UAVs and computer vision to assess seabird nutrient subsidy effects on sharks and rays
Remote Sensing in Ecology and Conservation ( IF 3.9 ) Pub Date : 2023-12-28 , DOI: 10.1002/rse2.378
Melissa Schiele 1, 2 , J. Marcus Rowcliffe 1 , Ben Clark 2 , Paul Lepper 2 , Tom B. Letessier 1
Affiliation  

Bird colonies on islands sustain elevated productivity and biomass on adjacent reefs, through nutrient subsidies. However, the implications of this localized enhancement on higher and often more mobile trophic levels (such as sharks and rays) are unclear, as spatial trends in mobile fauna are often poorly captured by traditional underwater visual surveys. Here, we explore whether the presence of seabird colonies is associated with enhanced abundances of sharks and rays on adjacent coral reefs. We used a novel long-range water-landing fixed-wing unoccupied aerial vehicle (UAV) to survey the distribution and density of sharks, rays and any additional megafauna, on and around tropical coral islands (n = 14) in the Chagos Archipelago Marine Protected Area. We developed a computer-vision algorithm to distinguish greenery (trees and shrubs), sand and sea glitter from visible ocean to yield accurate marine megafauna density estimation. We detected elevated seabird densities over rat-free islands, with the commonest species, sooty tern, reaching densities of 932 ± 199 per km−2 while none were observed over former coconut plantation islands. Elasmobranch density around rat-free islands with seabird colonies was 6.7 times higher than around islands without seabird colonies (1.3 ± 0.63 vs. 0.2 ± SE 0.1 per km2). Our results are evidence that shark and ray distribution is sensitive to natural and localized nutrient subsidies. Correcting for non-sampled regions of images increased estimated elasmobranch density by 14%, and our openly accessible computer vision algorithm makes this correction easy to implement to generate shark and ray and other wildlife densities from any aerial imagery. The water-landing fixed-wing long-range UAV technology used in this study may provide cost effective monitoring opportunities in remote ocean locations.

中文翻译:

使用水陆,固定翼无人机和计算机视觉评估鲨鱼和射线的海鸟养分补贴效果

通过营养补贴,岛上岛上的鸟类菌落在相邻珊瑚礁上维持生产率升高和生物量。但是,这种局部增强对更高和更多的移动营养水平(例如鲨鱼和射线)的含义尚不清楚,因为传统的水下视觉调查通常会捕获移动动物的空间趋势。在这里,我们探讨了海鸟菌落的存在是否与相邻珊瑚礁上的鲨鱼和射线的增强有关。我们使用了一种新型的远程水陆固定翼无人驾驶飞机(UAV)来调查鲨鱼群岛群岛和周围周围的鲨鱼,射线和任何其他Megafauna的分布和密度(n = 14)保护区。我们开发了一种计算机视觉算法,以区分绿色植物(树木和灌木),沙子和海洋闪光与可见海洋,以产生准确的海洋Megafauna密度估计。我们检测到无鼠的岛屿上的海鸟密度升高,最常见的物种,烟熏燕鸥,达到每公里-2的密度为932±199 ,而在以前的椰子种植群岛上没有观察到。海鸟菌落周围无鼠岛周围的弹性分支密度比没有海鸟菌落的岛屿周围高出6.7倍(1.3±0.63 vs. 0.2±SE 0.1每公里2)。我们的结果证明了鲨鱼和射线分布对天然和局部营养补贴敏感。校正图像的非采样区域的校正估计的弹性分支密度增加了14%,而我们公开访问的计算机视觉算法使得这种校正易于实现,从而从任何空中图像中产生鲨鱼,雷和其他野生动植物密度。这项研究中使用的水陆固定翼远程无人机技术可以在偏远的海洋位置提供成本效益的监视机会。
更新日期:2023-12-28
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