Body mass is a fundamental indicator of animal health closely linked to survival and reproductive success. Systematic assessment of body mass for a large proportion of a population can allow early detection of changes likely to impact population growth, facilitating responsive management and a mechanistic understanding of ecological trends. One challenge with integrating body mass assessment into monitoring is sampling enough animals to detect trends and account for individual variation. Harbour seals (Phoca vitulina) are philopatric marine mammals responsive to regional environmental changes, resulting in their use as an indicator species. We present a novel method for the non‐invasive and semi‐automatic assessment of harbour seal body condition, using unoccupied aerial vehicles (UAVs/drones). Morphological parameters are automatically measured in georeferenced images and used to estimate volume, which is then translated to estimated mass. Remote observations of known individuals are utilized to calibrate the method. We achieve a high level of accuracy (mean absolute error of 4.5 kg or 10.5% for all seals and 3.2 kg or 12.7% for pups‐of‐the‐year). We systematically apply the method to wild seals during the Spring pupping season and Autumn over 2 years, achieving a near‐population‐level assessment for pups on land (82.5% measured). With reference to previous mark‐recapture work linking Autumn pup weights to survival, we estimate mean expected probability of over‐winter survival (mean = 0.89, standard deviation = 0.08). This work marks a significant step forward for the non‐invasive assessment of body condition in pinnipeds and could provide daily estimates of body mass for thousands of individuals. It can act as an early warning for deteriorating environmental conditions and be utilized as an integrative tool for wildlife monitoring. It also enables estimation of yearly variation in demographic rates which can be utilized in parameterizing models of population growth with relevance for conservation and evolutionary biology.

中文翻译：

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使用无人机对鳍足类动物的体型进行种群水平评估，这是环境退化的早期预警


体重是动物健康的基本指标，与生存和繁殖成功密切相关。对大部分人口的体重进行系统评估可以及早发现可能影响人口增长的变化，促进响应性管理和对生态趋势的机械理解。将体重评估纳入监测的一项挑战是对足够的动物进行采样以检测趋势并解释个体差异。斑海豹 (Phoca vitulina) 是亲亲海洋哺乳动物，对区域环境变化做出反应，因此被用作指示物种。我们提出了一种使用无人飞行器（无人机）对斑海豹身体状况进行非侵入性和半自动评估的新方法。在地理参考图像中自动测量形态参数并用于估计体积，然后将其转换为估计质量。利用对已知个体的远程观察来校准该方法。我们实现了很高的准确度（所有海豹的平均绝对误差为 4.5 公斤或 10.5%，年度幼崽的平均绝对误差为 3.2 公斤或 12.7%）。我们在两年多的时间里系统地将该方法应用于春季幼崽季节和秋季的野生海豹，对陆地上的幼崽进行了接近种群水平的评估（测量了 82.5%）。参考之前将秋季幼崽体重与生存联系起来的标记重新捕获工作，我们估计了越冬生存的平均预期概率（平均值 = 0.89，标准差 = 0.08）。这项工作标志着鳍足类身体状况的非侵入性评估向前迈出了重要一步，并且可以为数千人提供每日体重估计。 它可以作为环境条件恶化的早期预警，并用作野生动物监测的综合工具。它还可以估计人口变化率的年度变化，可用于参数化与保护和进化生物学相关的人口增长模型。