title: Integral projection models for finite populations in a stochastic environment.
abstract: Continuous types of population structure occur when continuous variables such as body size or habitat quality affect the vital parameters of individuals. These structures can give rise to complex population dynamics and interact with environmental conditions. Here we present a model for continuously structured populations with finite size, including both demographic and environmental stochasticity in the dynamics. Using recent methods developed for discrete age-structured models we derive the demographic and environmental variance of the population growth as functions of a continuous state variable. These two parameters, together with the expected population growth rate, are used to define a one-dimensional diffusion approximation of the population dynamics. Thus, a substantial reduction in complexity is achieved as the dynamics of the complex structured model can be described by only three population parameters. We provide methods for numerical calculation of the model parameters and demonstrate the accuracy of the diffusion approximation by computer simulation of specific examples. The general modeling framework makes it possible to analyze and predict future dynamics and extinction risk of populations with various types of structure, and to explore consequences of changes in demography caused by, e.g., climate change or different management decisions. Our results are especially relevant for small populations that are often of conservation concern.
authors.affiliation: Centre for Conservation Biology, Department of Biology, Norwegian University of Science and Technology, N-7491 Trondheim, Norway. vindenes@bio.ntnu.no
authors.forename: Yngvild
authors.initials: Y
authors.lastname: Vindenes
authors.forename: Steinar
authors.initials: S
authors.lastname: Engen
authors.forename: Bernt-Erik
authors.initials: BE
authors.lastname: Saether
mesh_terms: D000818:Animals; D003198:Computer Simulation; D017753:Ecosystem; D004784:Environmental Monitoring; D008954:Models, Biological; D011157:Population Dynamics; D013269:Stochastic Processes