High mortality and enhanced recovery: modelling the countervailing effects of disturbance on population dynamics
Abstract
Disturbances cause high mortality in populations while simultaneously enhancing population growth by improving habitats. These countervailing effects make it difficult to predict population dynamics following disturbance events. To address this challenge, we derived a novel form of the logistic growth equation that permits time‐varying carrying capacity and growth rate. We combined this equation with concepts drawn from disturbance ecology to create a general model for population dynamics in disturbance‐prone systems. A river flooding example using three insect species (a fast life‐cycle mayfly, a slow life‐cycle dragonfly and an ostracod) found optimal tradeoffs between disturbance frequency vs. magnitude and a close fit to empirical data in 62% of cases. A savanna fire analysis identified fire frequencies of 3–4 years that maximised population size of a perennial grass. The model shows promise for predicting population dynamics after multiple disturbance events and for management of river flows and fire regimes.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Oct 24, 2017
- Source ID
- 10.1111/ele.12866
Entities
People
- David A. Lytle
- Jonathan D. Tonkin
- Laura E. Mcmullen
- Patrick De Leenheer
Organizations
- National Science Foundation
- Oregon State University
- United States Department of Defense
- United States Fish and Wildlife Service