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  • Thursday, April 4, 2019
  • 3:40 PM–4:30 PM
  • North Hall 276

Elise Zipkin, Michigan State University

Data integration is a statistical approach that simultaneously analyzes multiple data sources within a single, unified modeling framework. Ecological studies increasingly use data integration techniques to expand the spatiotemporal scope of research and inferences, increase precision of parameter estimates, account for multiple sources of uncertainty, and produce reliable predictions about future ecosystem states and processes. I will present the basic background and utility of data integration and also discuss some ongoing challenges in this emerging area of research.  I will also highlight a case study examining a barred owl invasion in the Pacific Northwest using a modeling framework for integrating presence-absence and count data to estimate population dynamics and abundance through time. The population model assumes that site-specific abundance changes over time according to survival of individuals and gains through reproduction and immigration. The case study combines long-term detection-nondetection data (1995-2014) with newly collected count data (2015-2016) from a growing population of barred owls (Strix varia) in the Pacific Northwest to examine the factors influencing population abundance over time. Model results show that the barred owl population grew substantially over the course of the survey period from approximately 0.13 (95% CI: [0.06, 0.48]) territorial owls per site in 1995 to 7.5 (95% CI: [4.26, 11.53]) in 2016, an increase that can be attributed to a positive density dependent effect of recruitment and immigration. This model provides a foundation for integrating a variety of unmarked data types and should be useful for survey design and to researchers interested in incorporating historical or citizen science data into analyses focused on understanding how demographic rates drive population abundance.

Refreshments precede the talk at 3:30 p.m. in North Hall 282.

April 2019
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