August 2, 2008
The Landscape Ecology Team uses state-space, or hidden process models, to make inference from our data. State-space models offer a convenient framework for analyzing data where observations are not independent, such as time series of abudance or animal tracks. State-space models consist of a process model (such as a stage-structured population model) and an observation model. These models are particularly useful for analyzing multi-strata capture-recapture models (such as arise in our fish tagging studies) and before-after-control-impact studies, such as arise from experiments where replication is sacrificed to maximize spatial scale.
Contact: SWFSC Fisheries Ecology Division, Landscape Ecology Team