Various field studies on plankton dynamics have broadened our understanding of seasonal succession patterns. Additionally, laboratory experiments have described consumers ranging from generalists to selective grazers. While both approaches can give us a good understanding of the ecosystem and its dynamics, drawbacks in identification and a limited coverage of the ecosystem have left open questions on the generality of previous results. Using an integrative approach, we investigated water samples taken at Helgoland Roads by metabarcoding to describe seasonal succession patterns of the whole plankton community. By use of network analysis, we also tried to identify predator–prey dynamics. Our data set depicted the strong seasonality typically found for temperate waters. Despite a stable background community surviving strong fluctuations, small and abrupt changes, such as pronounced blooms and random appearance of autotrophs, cause seasons to be quite different in an inter-year comparison. Main consumers were copepods, ciliates, and dinoflagellates, of which the latter were most abundant. Furthermore, our results suggest that zooplankton predators might favour specific prey during certain time periods but seem to be quite opportunistic otherwise throughout the year. The variability and potential for many different relationships in the plankton community might be an indicator of resilience in the system.

中文翻译：

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元条形码分析表明，真核浮游生物群落中灵活的食物网相互作用比北海黑尔戈兰路的特定捕食者 - 猎物关系更常见

关于浮游生物动力学的各种实地研究拓宽了我们对季节性演替模式的理解。此外，实验室实验描述了从多面手到选择性食草动物的消费者。虽然这两种方法都可以让我们很好地了解生态系统及其动态，但识别方面的缺陷和对生态系统的有限覆盖使我们对先前结果的普遍性产生了悬而未决的问题。我们使用综合方法，通过元条形码研究了在 Helgoland Roads 采集的水样，以描述整个浮游生物群落的季节性演替模式。通过使用网络分析，我们还尝试识别捕食者 - 猎物动态。我们的数据集描述了温带水域通常发现的强烈季节性。尽管稳定的背景社区在剧烈波动中幸存下来，小的和突然的变化，例如明显的花朵和自养生物的随机出现，导致季节在年际比较中完全不同。主要消费者是桡足类、纤毛虫和甲藻，其中后者数量最多。此外，我们的研究结果表明，浮游动物捕食者可能会在特定时间段内偏爱特定的猎物，但全年似乎都非常投机取巧。浮游生物群落中许多不同关系的可变性和潜力可能是系统恢复能力的一个指标。我们的研究结果表明，浮游动物捕食者可能会在特定时间段内偏爱特定的猎物，但全年似乎都非常投机取巧。浮游生物群落中许多不同关系的可变性和潜力可能是系统恢复能力的一个指标。我们的研究结果表明，浮游动物捕食者可能会在特定时间段内偏爱特定的猎物，但全年似乎都非常投机取巧。浮游生物群落中许多不同关系的可变性和潜力可能是系统恢复能力的一个指标。