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Chaos in a long-term experiment with a plankton community

机译：在浮游生物社区的长期实验中出现的混乱

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摘要

Mathematical models predict that species interactions such as competition and predation can generate chaos. However, experimental demonstrations of chaos in ecology are scarce, and have been limited to simple laboratory systems with a short duration and artificial species combinations. Here, we present the first experimental demonstration of chaos in a long-term experiment with a complex food web. Our food web was isolated from the Baltic Sea, and consisted of bacteria, several phytoplankton species, herbivorous and predatory zooplankton species, and detritivores. The food web was cultured in a laboratory mesocosm, and sampled twice a week for more than 2,300 days. Despite constant external conditions, the species abundances showed striking fluctuations over several orders of magnitude. These fluctuations displayed a variety of different periodicities, which could be attributed to different species interactions in the food web. The population dynamics were characterized by positive Lyapunov exponents of similar magnitude for each species. Predictability was limited to a time horizon of 15-30 days, only slightly longer than the local weather forecast. Hence, our results demonstrate that species interactions in food webs can generate chaos. This implies that stability is not required for the persistence of complex food webs, and that the long-term prediction of species abundances can be fundamentally impossible.
机译：数学模型预测，诸如竞争和捕食等物种相互作用会产生混乱。但是，生态学中混沌的实验证明很少，并且仅限于持续时间短的简单实验室系统和人工物种的组合。在这里，我们展示了在复杂食物网的长期实验中对混沌的首次实验演示。我们的食物网是从波罗的海中分离出来的，由细菌，几种浮游植物，草食性和掠食性浮游动物以及有害生物组成。食物网在实验室中膜培养，每周取样两次，共2300天以上。尽管外部条件不断变化，但物种的丰度却出现了几个数量级的惊人波动。这些波动表现出各种不同的周期性，这可以归因于食物网中不同物种的相互作用。种群动态的特征是每个物种的Lyapunov正指数相似。可预测性仅限于15-30天的时间范围，仅比本地天气预报稍长。因此，我们的结果表明，食物网中的物种相互作用会产生混乱。这意味着复杂的食物网的持久性并不需要稳定性，而从根本上不可能长期预测物种的丰度。

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