title: Anatomy of a chaotic attractor: subtle model-predicted patterns revealed in population data.
abstract: Mathematically, chaotic dynamics are not devoid of order but display episodes of near-cyclic temporal patterns. This is illustrated, in interesting ways, in the case of chaotic biological populations. Despite the individual nature of organisms and the noisy nature of biological time series, subtle temporal patterns have been detected. By using data drawn from chaotic insect populations, we show quantitatively that chaos manifests itself as a tapestry of identifiable and predictable patterns woven together by stochasticity. We show too that the mixture of patterns an experimentalist can expect to see depends on the scale of the system under study.
authors.affiliation: Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, TN 37996, USA. king@tiem.utk.edu
authors.forename: Aaron A
authors.initials: AA
authors.lastname: King
authors.forename: R F
authors.initials: RF
authors.lastname: Costantino
authors.forename: J M
authors.initials: JM
authors.lastname: Cushing
authors.forename: Shandelle M
authors.initials: SM
authors.lastname: Henson
authors.forename: Robert A
authors.initials: RA
authors.lastname: Desharnais
authors.forename: Brian
authors.initials: B
authors.lastname: Dennis
mesh_terms: D000818:Animals; D007313:Insecta; D015233:Models, Statistical; D017711:Nonlinear Dynamics; D011157:Population Dynamics; D013269:Stochastic Processes