| Literature DB >> 28834087 |
David L Strayer1,2, Carla M D'Antonio3, Franz Essl4, Mike S Fowler5, Juergen Geist6, Sabine Hilt7, Ivan Jarić7,8, Klaus Jöhnk9, Clive G Jones1, Xavier Lambin10, Alexander W Latzka11, Jan Pergl12, Petr Pyšek13,14,15, Peter Robertson16, Menja von Schmalensee17,18, Robert A Stefansson17, Justin Wright19, Jonathan M Jeschke2,7,20.
Abstract
Boom-bust dynamics - the rise of a population to outbreak levels, followed by a dramatic decline - have been associated with biological invasions and offered as a reason not to manage troublesome invaders. However, boom-bust dynamics rarely have been critically defined, analyzed, or interpreted. Here, we define boom-bust dynamics and provide specific suggestions for improving the application of the boom-bust concept. Boom-bust dynamics can arise from many causes, some closely associated with invasions, but others occurring across a wide range of ecological settings, especially when environmental conditions are changing rapidly. As a result, it is difficult to infer cause or predict future trajectories merely by observing the dynamic. We use tests with simulated data to show that a common metric for detecting and describing boom-bust dynamics, decline from an observed peak to a subsequent trough, tends to severely overestimate the frequency and severity of busts, and should be used cautiously if at all. We review and test other metrics that are better suited to describe boom-bust dynamics. Understanding the frequency and importance of boom-bust dynamics requires empirical studies of large, representative, long-term data sets that use clear definitions of boom-bust, appropriate analytical methods, and careful interpretations.Keywords: alien species; biological invasions; concepts; exotic species; invasive species; long-term; management; non-native species; population collapse; population crash; population dynamics; reckless invaders; systematic review
Mesh:
Year: 2017 PMID: 28834087 DOI: 10.1111/ele.12822
Source DB: PubMed Journal: Ecol Lett ISSN: 1461-023X Impact factor: 9.492