Functional traits are increasingly used to assess changes in phytoplankton community structure and to link individual characteristics to ecosystem functioning. However, they are usually inferred from taxonomic identification or manually measured for each organism, both time consuming approaches. Instead, we focus on high throughput imaging to describe the main temporal variations of morphological changes of phytoplankton in Narragansett Bay, a coastal time-series station. We analyzed a 2-yr dataset of morphological features automatically extracted from continuous imaging of individual phytoplankton images (~ 105 million images collected by an Imaging FlowCytobot). We identified synthetic morphological traits using multivariate analysis and revealed that morphological variations were mainly due to changes in length, width, shape regularity, and chain structure. Morphological changes were especially important in winter with successive peaks of larger cells with increasing complexity and chains more clearly connected. Small nanophytoplankton were present year-round and constituted the base of the community, especially apparent during the transitions between diatom blooms. High inter-annual variability was also observed. On a weekly timescale, increases in light were associated with more clearly connected chains while more complex shapes occurred at lower nitrogen concentrations. On an hourly timescale, temperature was the determinant variable constraining cell morphology, with a general negative influence on length and a positive one on width, shape regularity, and chain structure. These first insights into the phytoplankton morphology of Narragansett Bay highlight the possible morphological traits driving the phytoplankton succession in response to light, temperature, and nutrient changes.

中文翻译：

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长度、宽度、形状规律和链结构：图像浮游植物形态的时间序列分析

功能性状越来越多地用于评估浮游植物群落结构的变化，并将个体特征与生态系统功能联系起来。然而，它们通常是从分类鉴定中推断出来的，或者是针对每个生物体手动测量的，这两种方法都很耗时。相反，我们专注于高通量成像来描述沿海时间序列站纳拉甘西特湾浮游植物形态变化的主要时间变化。我们分析了从单个浮游植物图像的连续成像中自动提取的 2 年形态特征数据集（约 1.05 亿张由 Imaging FlowCytobot 收集的图像）。我们使用多变量分析确定了合成的形态特征，并揭示形态变异主要是由于长度、宽度、形状规律性的变化，和链式结构。形态变化在冬季尤为重要，较大细胞的连续高峰随着复杂性的增加和链的连接更加清晰。小型纳米浮游植物全年都存在并构成群落的基础，在硅藻开花之间的过渡期间尤其明显。还观察到高的年际变化。在每周的时间尺度上，光的增加与更清晰的连接链有关，而在较低的氮浓度下会出现更复杂的形状。在每小时的时间尺度上，温度是限制细胞形态的决定性变量，对长度有负面影响，对宽度、形状规则和链结构有正面影响。