Foreseeing the future of mutualistic communities beyond collapse. (10th November 2019)

• Record Type: Journal Article
• Authors: Lever, J. Jelle; van de Leemput, Ingrid A.; Weinans, Els; Quax, Rick; Dakos, Vasilis; van Nes, Egbert H.; Bascompte, Jordi; Scheffer, Marten
• Editors: Drake, John
• Is Part Of: Ecology letters. Volume 23:Number 1(2020)
• Page Start: 2
• Page End: 15
• Publication Date: 2019-11-10
• Subjects: Critical transitions -- ecological networks -- mutualistic communities -- critical slowing down -- predictive ecology -- forecasting -- global environmental change; Ecology -- Periodicals; 577
• DOI: 10.1111/ele.13401
• Languages: English
• ISSNs: 1461-023X

Abstract

Abstract: 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. Abstract : While detecting upcoming critical transitions in complex ecosystems is challenging, predicting what comes after a critical transition is terra incognita altogether. Here, we address the question of whether the relative simplicity of the dynamics of complex mutualistic communities allows us to foresee a community's future state.