Using remote cameras to measure seasonal molts
Using remote cameras to measure seasonal molts
复制标题
使用远程摄像机测量季节性蜕皮
DOI：
10.1002/ecs2.3084
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发表时间：
2020
期刊：
影响因子：
2.7
通讯作者：
Mills, L. Scott
中科院分区：
文献类型：
--
作者：
Zimova, Marketa;Barnard, Lindsey S.;Davis, Brandon M.;Kumar, Alexander V.;Lafferty, Diana J.;Mills, L. Scott
获得野外生命周期事件季节性时间的准确数据对于生态研究的许多方面都至关重要。然而，表征这样的物候过程是困难的，昂贵的，耗时的。远程相机陷阱越来越多地用于生态学，但其研究动物种群关键物候特征的潜力在很大程度上尚未开发。在这里，我们研究的潜力，远程相机陷阱来衡量哺乳动物的季节性蜕皮的进展。我们评估了受过训练的观察者从相机陷阱图像中分类蜕皮阶段的准确性，并确定了在常见的彩色蜕皮哺乳动物雪鞋兔（Lepus americanus）中提高该方法准确性的因素。我们的研究结果表明，由远程相机陷阱拍摄的图像可以用于以相对高的准确度对颜色蜕皮阶段进行分类（即，84%）。观察员实现了最高的准确性时，使用的分类协议与更少的蜕皮类别，并从白天获得的图像。我们还发现，野兔的身体位置在图像中，无论野兔是移动或静止的观察者分类精度的影响很小。相机型号对精度的影响可以忽略不计。总的来说，我们的研究结果表明，相机陷阱可用于分类蜕皮进展，以衡量蜕皮物候在野外。由于世界各地正在进行许多相机陷阱研究，因此可以将不同研究中经历可区分的季节性换羽的物种图像汇总起来，以描述局部和全球范围内的换羽物候。就像远程相机彻底改变了对一些动物种群的分布、丰度和行为的研究一样，远程相机图像也可以改变我们对空间、时间和分类群中关键物候过程的理解。
Obtaining accurate data on seasonal timing of lifecycle events in the wild is critical for many aspects of ecological research. However, characterizing such phenological processes is difficult, expensive, and time consuming. Remote camera traps are increasingly used in ecology, yet their potential to study key phenological traits in animal populations has been largely unexplored. Here, we examine the potential of remote camera traps to measure the progression of seasonal molts in mammals. We evaluated the accuracy of trained observers to classify the stage of molt from camera‐trap images and identified factors that increase the accuracy of this method in a common, color molting mammal, the snowshoe hare (Lepus americanus). Our results showed that images taken by remote camera traps can be used to classify the stage of color molt with relatively high accuracy (i.e., 84%). Observers achieved the highest accuracy when using a classification protocol with fewer molt categories, and from images acquired during the day. We also found that hare body position in the image, and whether the hare was moving or still had small influences on observer classification accuracy. Camera model had negligible effect on accuracy. Overall, our results suggest that camera traps can be used to classify molt progression to measure molt phenology in the wild. Because many camera‐trap studies are ongoing around the world, images of species that undergo distinguishable seasonal molts could be pooled across studies to characterize molt phenology on local and global scales. In much the same way that remote cameras have revolutionized the study of distribution, abundance, and behavior of some animal populations, so too can remote camera images transform our understanding of key phenological processes across space, time, and taxa.
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