Large-scale species monitoring remains a significant conservation challenge. Given the ongoing biodiversity crisis, the need for reliable and efficient methods has never been greater. Drone-based techniques have much to offer in this regard: they allow access to otherwise unreachable areas and enable the rapid collection of non-invasive field data. Herein, we describe the development of a drone-based method for the estimation of population size in Galápagos marine iguanas, Amblyrhynchus cristatus. As a large-bodied lizard that occurs in open coastal terrain, this endemic species is an ideal candidate for drone surveys. Almost all Amblyrhynchus subspecies are Endangered or Critically Endangered according to the IUCN yet since several colonies are inaccessible by foot, ground- based methods are unable to address the critical need for better census data. In order to establish a drone-based approach to estimate population size of marine iguanas, we surveyed in January 2021 four colonies on three focal islands (San Cristobal, Santa Fe and Espanola) using three techniques: simple counts (the standard method currently used by conservation managers), capture mark-resight (CMR), and drone-based counts. The surveys were performed within a 4-day window under similar ambient conditions. We then compared the approaches in terms of feasibility, outcome and effort. The highest population-size estimates were obtained using CMR, and drone-based counts were on average 14% closer to CMR estimates—and 17–35% higher—than those obtained by simple counts. In terms of field-time, drone-surveys can be faster than simple counts, but image analyses were highly time consuming. Though CMR likely produces superior estimates, it cannot be performed in most cases due to lack of access and knowledge regarding colonies. Drone-based surveys outperformed ground-based simple counts in terms of outcome and this approach is therefore suitable for use across the range of the species. Moreover, the aerial approach is currently the only credible solution for accessing and surveying marine iguanas at highly remote colonies. The application of citizen science and other aids such as machine learning will alleviate the issue regarding time needed to analyze the images.

中文翻译：

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使用无人机估计濒临灭绝的加拉帕戈斯海鬣蜥种群规模的初步研究

大规模物种监测仍然是一项重大的保护挑战。鉴于持续的生物多样性危机，对可靠和有效方法的需求从未如此强烈。基于无人机的技术在这方面大有可为：它们允许进入其他无法到达的区域，并能够快速收集非侵入性现场数据。在此，我们描述了一种基于无人机的方法的发展，用于估计加拉帕戈斯海鬣蜥 (Amblyrhynchus cristatus) 的种群规模。作为一种生活在开阔沿海地带的大型蜥蜴，这种特有物种是无人机调查的理想候选者。根据世界自然保护联盟，几乎所有的钝吻龙亚种都处于濒危或极度濒危状态，但由于步行无法到达几个殖民地，实地方法无法满足对更好的人口普查数据的迫切需求。为了建立一种基于无人机的方法来估计海鬣蜥的种群规模，我们在 2021 年 1 月使用三种技术调查了三个焦点岛屿（圣克里斯托瓦尔岛、圣达菲岛和埃斯帕诺拉岛）上的四个群落：简单计数（目前使用的标准方法养护管理人员）、捕获标记重视 (CMR) 和基于无人机的计数。这些调查是在类似环境条件下的 4 天窗口内进行的。然后，我们在可行性、结果和努力方面比较了这些方法。最高的人口规模估计是使用 CMR 获得的，基于无人机的计数比通过简单计数获得的计数平均更接近 CMR 估计值 14%，并且高出 17-35%。就现场时间而言，无人机调查比简单计数更快，但是图像分析非常耗时。尽管 CMR 可能产生更好的估计，但由于缺乏关于菌落的访问和知识，在大多数情况下无法执行。基于无人机的调查在结果方面优于基于地面的简单计数，因此这种方法适用于整个物种范围。此外，空中方法是目前在高度偏远的栖息地接触和调查海鬣蜥的唯一可靠解决方案。公民科学和机器学习等其他辅助工具的应用将缓解有关分析图像所需时间的问题。基于无人机的调查在结果方面优于基于地面的简单计数，因此这种方法适用于整个物种范围。此外，空中方法是目前在高度偏远的栖息地接触和调查海鬣蜥的唯一可靠解决方案。公民科学和机器学习等其他辅助工具的应用将缓解有关分析图像所需时间的问题。基于无人机的调查在结果方面优于基于地面的简单计数，因此这种方法适用于整个物种范围。此外，空中方法是目前在高度偏远的栖息地接触和调查海鬣蜥的唯一可靠解决方案。公民科学和机器学习等其他辅助工具的应用将缓解有关分析图像所需时间的问题。