Boom‐bust dynamics in biological invasions: towards an improved application of the concept. (17th August 2017)

• Record Type: Journal Article
• Authors: Strayer, David L.; D'Antonio, Carla M.; Essl, Franz; Fowler, Mike S.; Geist, Juergen; Hilt, Sabine; Jarić, Ivan; Jöhnk, Klaus; Jones, Clive G.; Lambin, Xavier; Latzka, Alexander W.; Pergl, Jan; Pyšek, Petr; Robertson, Peter; von Schmalensee, Menja; Stefansson, Robert A.; Wright, Justin; Jeschke, Jonathan M.
• Editors: Early, Regan
• Is Part Of: Ecology letters. Volume 20:Number 10(2017)
• Page Start: 1337
• Page End: 1350
• Publication Date: 2017-08-17
• Subjects: 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; Ecology -- Periodicals; 577
• DOI: 10.1111/ele.12822
• Languages: English
• ISSNs: 1461-023X

Abstract

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.