PARENT SESSION
Contributed Oral Session 19: Modeling: Movement and Population Dynamics
Monday, August 8, 1:30 PM - 5:00 PM, Meeting Room 513 A, Level 5, Palais des congrès de Montréal
Cross-scale, integrated modeling and prediction using hierarchical modeling and MCMC.
Conroy, Michael*,1, Fonnesbeck, Christopher2, Cook, Kiersten 3, Howell, Jay3, Peterson, James1, Carroll, John4, 1 USGS, Georgia Cooperative Fish and Wildlife Research Unit, Athens, Georgia, USA2 Fish & Wildlife Research Institute, Athens, Georgia, USA3 Georgia Cooperative Fish and Wildlife Research Unit, Athens, Georgia, USA4 Warnell School of Forest Resources, Athens, Georgia, USA
ABSTRACT- Many ecological processes operate at multiple spatial and temporal scales. Likewise, empirical modeling of ecological systems frequently involves the connection of disparate pieces of information via predictive models, with data gathered at multiple spatial and temporal scales. Hierarchical modeling integrates data across different scales of resolution, and allows explicit separation of local-scale, faster processes from broad-scale, slower processes. A Bayesian approach allows for decomposition of complex, hierarchical models into individual, tractable components. Markov chain Monte Carlo (MCMC) methods allow for sampling from the joint posterior distribution of model parameters, otherwise these are mathematically intractable. We give examples where integrated, hierarchical modeling is used to model resource selection for American black bears (Ursus americanus) and to investigate the influence of large-scale perturbations on the occurrence of bull trout (Salvelinus confluentus). Black bears are confirmed to be habitat generalists, whose resource utilization is nevertheless constrained by broad-scale landscape features. Bull trout are sensitive to aspects of the local physical environment, such as stream elevation and aspect, but also shown to be influenced by attributes measured at the broad (e.g., watershed) scale, such as total amount of forest cover. We also show how integrated modeling can be used in conjunction with resource decision analysis to seek optimal management strategies, as in developing conservation plans for black bears and conservation of critical habitats for bull trout.
Key words: model, hierarchical, MCMC, cross-scale