Changing conditions may lead to sudden shifts in the state of ecosystems when critical thresholds are passed. Some well-studied drivers of such transitions lead to predictable outcomes such as a turbid lake or a degraded landscape. Many ecosystems are, however, complex systems of many interacting species. While detecting upcoming transitions in such systems is challenging, predicting what comes after a critical transition is terra incognita altogether. The problem is that complex ecosystems may shift to many different, alternative states. Whether an impending transition has minor, positive or catastrophic effects is thus unclear. Some systems may, however, behave more predictably than others. The dynamics of mutualistic communities can be expected to be relatively simple, because delayed negative feedbacks leading to oscillatory or other complex dynamics are weak. Here, we address the question of whether this relative simplicity allows us to foresee a community's future state. As a case study, we use a model of a bipartite mutualistic network and show that a network's post-transition state is indicated by the way in which a system recovers from minor disturbances. Similar results obtained with a unipartite model of facilitation suggest that our results are of relevance to a wide range of mutualistic systems.

中文翻译：

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预见互惠社区的未来，超越崩溃。


当超过关键阈值时，不断变化的条件可能会导致生态系统状态突然发生变化。一些经过充分研究的此类转变的驱动因素会导致可预测的结果，例如湖泊浑浊或景观退化。然而，许多生态系统是由许多相互作用的物种组成的复杂系统。虽然检测此类系统中即将发生的转变具有挑战性，但预测关键转变后会发生什么却完全是未知领域。问题在于复杂的生态系统可能会转变为许多不同的替代状态。因此，尚不清楚即将到来的转变是否会产生轻微、积极或灾难性的影响。然而，某些系统的行为可能比其他系统更可预测。互惠社区的动态预计会相对简单，因为导致振荡或其他复杂动态的延迟负反馈较弱。在这里，我们解决这样的问题：这种相对简单性是否使我们能够预见社区的未来状态。作为案例研究，我们使用二分互惠网络模型，并表明网络的过渡后状态是通过系统从微小干扰中恢复的方式来指示的。通过单方促进模型获得的类似结果表明，我们的结果与广泛的互利系统相关。