Imaging techniques are increasingly used in ecology studies, producing vast quantities of data. Inferring functional traits from individual images can provide original insights on ecosystem processes. Morphological traits are, as other functional traits, individual characteristics influencing an organism's fitness. We measured them from in situ image data to study an Arctic zooplankton community during sea ice break‐up. Morphological descriptors (e.g., area, lightness, complexity) were automatically measured on ∼ 28,000 individual copepod images from a high‐resolution underwater camera deployed at more than 150 sampling sites across the ice‐edge. A statistically‐defined morphological space allowed synthesizing morphological information into interpretable and continuous traits (size, opacity, and appendages visibility). This novel approach provides theoretical and methodological advantages because it gives access to both inter‐ and intra‐specific variability by automatically analyzing a large dataset of individual images. The spatial distribution of morphological traits revealed that large copepods are associated with ice‐covered waters, while open waters host smaller individuals. In those ice‐free waters, copepods also seem to feed more actively, as suggested by the increased visibility of their appendages. These traits distributions are likely explained by bottom‐up control: high phytoplankton concentrations in the well‐lit open waters encourages individuals to actively feed and stimulates the development of small copepod stages. Furthermore, copepods located at the ice edge were opaquer, presumably because of full guts or an increase in red pigmentation. Our morphological trait‐based approach revealed ecological patterns that would have been inaccessible otherwise, including color and posture variations of copepods associated with ice‐edge environments in Arctic ecosystems.

中文翻译：

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基于性状co足类动物图像的基于性状的方法揭示了北极冰融带上不同的生态模式

影像技术越来越多地用于生态学研究中，产生大量数据。从单个图像推断功能性状可以提供有关生态系统过程的原始见解。像其他功能性特征一样，形态特征是影响有机体适应性的个体特征。我们通过实地图像数据对其进行了测量，以研究海冰破裂期间的北极浮游动物群落。形态描述符（例如，面积，亮度，复杂度）是从高分辨率的水下相机对大约28,000个单独的pe足类动物图像进行自动测量的，该高分辨率水下相机部署在整个冰缘的150多个采样点上。通过统计定义的形态空间，可以将形态信息合成为可解释和连续的特征（大小，不透明度和附件可见性）。这种新颖的方法具有理论和方法上的优势，因为它可以通过自动分析单个图像的大型数据集来访问种间和种内变异性。形态特征的空间分布表明，大型co足类动物与被冰覆盖的水有关，而开阔水域则容纳较小的个体。在那些无冰的水域中，seem足类动物似乎也更加活跃地进食，正如其附肢的可见度增加所暗示的那样。自下而上的控制可能解释了这些性状分布：光线充足的开阔水域中浮游植物的高浓度鼓励个体积极进食并刺激小型co足类的发育。此外，位于冰缘的co足类动物是不透明的，大概是由于胆量充沛或红色色素沉着增加所致。