title: Persistence despite perturbations for interacting populations.
abstract: Two definitions of persistence despite perturbations in deterministic models are presented. The first definition, persistence despite frequent small perturbations, is shown to be equivalent to the existence of a positive attractor i.e. an attractor bounded away from extinction. The second definition, persistence despite rare large perturbations, is shown to be equivalent to permanence i.e. a positive attractor whose basin of attraction includes all positive states. Both definitions set up a natural dichotomy for classifying models of interacting populations. Namely, a model is either persistent despite perturbations or not. When it is not persistent, it follows that all initial conditions are prone to extinction due to perturbations of the appropriate type. For frequent small perturbations, this method of classification is shown to be generically robust: there is a dense set of models for which persistent (respectively, extinction prone) models lies within an open set of persistent (resp. extinction prone) models. For rare large perturbations, this method of classification is shown not to be generically robust. Namely, work of Josef Hofbauer and the author have shown there are open sets of ecological models containing a dense sets of permanent models and a dense set of extinction prone models. The merits and drawbacks of these different definitions are discussed.
authors.affiliation: Department of Mathematics, The College of William and Mary, Williamsburg, Virginia 23187-8795, USA. sjschr@wm.edu <sjschr@wm.edu>
authors.forename: Sebastian J
authors.initials: SJ
authors.lastname: Schreiber
mesh_terms: D000818:Animals; D017753:Ecosystem; D053476:Extinction, Biological; D020387:Food Chain; D008954:Models, Biological; D011157:Population Dynamics; D011235:Predatory Behavior