Demographic Analysis of Forest Dynamics Using Stochastic Integral Projection Models

• Activity Number: 101
• Type: Invited
• Date/Time: Monday, July 30, 2012 : 8:30 AM to 10:20 AM
• Sponsor: ENAR
• Author(s): Alan Gelfand*+
• Companies: Duke University

Abstract

Demographic analysis for plant and animal populations is a prominent problem in studying ecological processes. Typical demography studies age, size, length, or mass distributions. Usual treatment employs matrix projection models, creating classi?cation bins, to model bin to bin transitions using individual level data. Integral projection models (IPMs) offer a continuous version of this approach, providing evolving mean surfaces over time to explain the dynamics in such trait distributions. These models are a class of integro-differential equations and, as such, may be driven by a partial differential equation. However, for demography, we specify the redistribution kernel mechanistically using demographic functions, i.e., parametric models for demographic processes such as survival, growth, and replenishment. With interest in scaling in space, we work with data in the form of point patterns yielding intensities (which are easy to scale). We show problems fitting with individual level data. As a result, we learn about the IPM through marginal (e.g., annual) patterns. We illustrate with an investigation of forest dynamics in Duke Forest. (Joint work with S. Ghosh and J. Clark)