While many ecology studies require estimations of species abundance, doing so for mobile animals in an accurate, non‐invasive manner remains a challenge. One popular stopgap method involves the use of remote video‐based surveys using several cameras, but abundance estimates derived from this method are computed with conservative metrics (e.g., maxN computed as the maximum number of individuals seen simultaneously on a single video). We propose a novel methodological framework based on a remote‐camera network characterized by known positions and non‐overlapping field‐of‐views. This approach involves a temporal synchronization of videos and a maximal speed estimate for studied species. Such a design allows computing a new abundance metric called Synchronized maxN (SmaxN). We provide a proof‐of‐concept of this approach with a network of nine remote underwater cameras that recorded fish for three periods of 1 h on a fringing reef in Mayotte (Western Indian Ocean). We found that abundance estimation with SmaxN yielded up to four times higher values than maxN among the six fish species studied. SmaxN performed better with an increasing number of cameras or longer recordings. We also found that using a network of synchronized cameras for a short time period performed better than using a few cameras for a long duration. The SmaxN algorithm can be applied to many video‐based approaches. We built an open‐sourced R package to encourage its use by ecologists and managers using video‐based censuses, as well as to allow for replicability with SmaxN metric.

中文翻译：

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使用摄像头网络估算动物数量的新框架

虽然许多生态学研究需要估计物种丰度，但以准确、非侵入性的方式对移动动物进行估计仍然是一个挑战。一种流行的权宜之计方法涉及使用多个摄像机进行基于远程视频的调查，但从该方法得出的丰度估计值是用保守的指标计算的（例如，最大N计算为在单个视频中同时看到的最大人数）。我们提出了一种基于远程摄像机网络的新颖方法框架，其特征是已知位置和不重叠的视场。这种方法涉及视频的时间同步和所研究物种的最大速度估计。这样的设计允许计算一个新的丰度度量，称为同步最大N（最大N）。我们通过由九个远程水下摄像机组成的网络提供了这种方法的概念验证，该网络在马约特岛（西印度洋）的岸礁上记录了三个时间段各一小时的鱼类。我们发现丰度估计最大N产生的值比最大N在所研究的六种鱼类中。最大N随着摄像机数量的增加或录制时间的延长，效果会更好。我们还发现，短时间使用同步摄像机网络比长时间使用几个摄像机的效果更好。这最大N算法可以应用于许多基于视频的方法。我们构建了一个开源 R 包，以鼓励生态学家和管理者使用基于视频的人口普查，并允许可复制性最大N公制。