title: Detecting the order of population dynamics from time series: nonlinearity causes spurious diagnosis.
abstract: Partial autocorrelation and partial rate correlation functions are frequently used to detect the order of the endogenous process generating an observed population time series. Here we uncover a problem with this approach: the diagnosis of spurious second order autocorrelation due to strong nonlinearity in a first order endogenous process, as exemplified by time series data from a population of Soay sheep. Causes and a possible solution are discussed.
authors.affiliation: Emeritus Professor, Departments of Entomology and Natural Resource Sciences, Washington State University, Pullman, Washington 99164, USA.
authors.forename: Alan
authors.initials: A
authors.lastname: Berryman
authors.forename: Mauricio
authors.initials: M
authors.lastname: Lima
mesh_terms: D000818:Animals; D008433:Mathematics; D008954:Models, Biological; D017711:Nonlinear Dynamics; D011156:Population Density; D011157:Population Dynamics; D012756:Sheep / Q000502:physiology*; D013997:Time Factors