Abrupt Change in Ecological Systems: Inference and Diagnosis. (July 2018)

• Record Type: Journal Article
• Authors: Ratajczak, Zak; Carpenter, Stephen R.; Ives, Anthony R.; Kucharik, Christopher J.; Ramiadantsoa, Tanjona; Stegner, M. Allison; Williams, John W.; Zhang, Jien; Turner, Monica G.
• Is Part Of: Trends in ecology & evolution. Volume 33:Number 7(2018)
• Page Start: 513
• Page End: 526
• Publication Date: 2018-07
• Subjects: collapse -- disturbance -- regime shifts -- resilience -- tipping points -- stochasticity; Ecology -- Periodicals; Evolution (Biology) -- Periodicals; 576.8
• DOI: 10.1016/j.tree.2018.04.013
• Languages: English
• ISSNs: 0169-5347

Abstract

Abstract : Abrupt ecological changes are, by definition, those that occur over short periods of time relative to typical rates of change for a given ecosystem. The potential for such changes is growing due to anthropogenic pressures, which challenges the resilience of societies and ecosystems. Abrupt ecological changes are difficult to diagnose because they can arise from a variety of circumstances, including rapid changes in external drivers (e.g., climate, or resource extraction), nonlinear responses to gradual changes in drivers, and interactions among multiple drivers and disturbances. We synthesize strategies for identifying causes of abrupt ecological change and highlight instances where abrupt changes are likely. Diagnosing abrupt changes and inferring causation are increasingly important as society seek to adapt to rapid, multifaceted environmental changes. Highlights: Abrupt ecological changes occur rapidly relative to typical rates of ecosystem change and are increasingly observed in ecosystems worldwide, thereby challenging adaptive capacities. Abrupt ecological changes can arise from many processes, only some of which are transitions between alternative states. Focusing solely on the mean values for drivers and states is insufficient for diagnosing abrupt changes, because abrupt changes can be produced by changes in the variability of drivers and disturbance regimes. Diagnosing the likely causes of abrupt state changes in real-world systems remains difficult. Long-term data and experimental manipulations of drivers remains essential. Multiple changing drivers can interact to increase the likelihood of abrupt changes. Identifying interventions that decrease the risk of undesirable abrupt changes is an urgent priority.