Featured Publication: A guide to state-space modeling of ecological time series
A guide to state-space modeling of ecological time series
Co-authored by Ken Newman, Principal Researcher in Statistical Methodology
Long-term ecological monitoring programs supply the raw data necessary to quantify the effects of climate change on biological populations, to allow calculation of biodiversity measures, and to assess the effectiveness of management actions. State-space models (SSMs) are a powerful conceptual framework and practical means for making sense of the resulting time series data, data such as annual counts of sea birds and locations over time of electronically monitored animals. This review paper on SSMs was written to help ecologists formulate, fit, evaluate, and use SSMs. A lengthy (130 page) appendix to the paper can serve as a tutorial, providing cut-and-paste computer code for fitting SSMs to both a population dynamics model and a movement model using a variety of R packages including JAGS, nimble, Stan, TMB, and pomp. The breadth and depth of the paper and appendices are sufficient for a several day short-course or a semester long reading group.