An integrated data model to estimate spatiotemporal occupancy, abundance, and colonization dynamics

• Published in: Ecology
• Main Authors: Williams, Perry J., Hooten, Mevin B., Womble, Jamie N., Esslinger, George G., Bower, Michael R., Hefley, Trevor J.
• Other Authors: National Park Service, National Science Foundation
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2017
• Subjects: glacier; Alaska
• Online Access: http://dx.doi.org/10.1002/ecy.1643; https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fecy.1643; https://onlinelibrary.wiley.com/doi/pdf/10.1002/ecy.1643; https://onlinelibrary.wiley.com/doi/full-xml/10.1002/ecy.1643; https://esajournals.onlinelibrary.wiley.com/doi/am-pdf/10.1002/ecy.1643; https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.1002/ecy.1643

Abstract Ecological invasions and colonizations occur dynamically through space and time. Estimating the distribution and abundance of colonizing species is critical for efficient management or conservation. We describe a statistical framework for simultaneously estimating spatiotemporal occupancy and abundance dynamics of a colonizing species. Our method accounts for several issues that are common when modeling spatiotemporal ecological data including multiple levels of detection probability, multiple data sources, and computational limitations that occur when making fine‐scale inference over a large spatiotemporal domain. We apply the model to estimate the colonization dynamics of sea otters ( Enhydra lutris ) in Glacier Bay, in southeastern Alaska.