Skip to Main Content
Dynamic N -occupancy models: estimating demographic rates and local abundance from detection-nondetection dataAuthor(s): Sam Rossman; Charles B. Yackulic; Sarah P. Saunders; Janice Reid; Ray Davis; Elise F. Zipkin
Source: Ecology. 97(12): 3300-3307.
Publication Series: Scientific Journal (JRNL)
Station: Pacific Northwest Research Station
View PDF (706.0 KB)
DescriptionOccupancy modeling is a widely used analytical technique for assessing species distributions and range dynamics. However, occupancy analyses frequently ignore variation in abundance of occupied sites, even though site abundances affect many of the parameters being estimated (e.g., extinction, colonization, detection probability). We introduce a new model (“dynamic N-occupancy”) capable of providing accurate estimates of local abundance, population gains (reproduction/immigration), and apparent survival probabilities while accounting for imperfect detection using only detection/nondetection data. Our model utilizes heterogeneity in detection based on variations in site abundances to estimate latent demographic rates via a dynamic N-mixture modeling framework. We validate our model using simulations across a wide range of values and examine the data requirements, including the number of years and survey sites needed, for unbiased and precise estimation of parameters. We apply our model to estimate spatiotemporal heterogeneity in abundances of barred owls (Strix varia) within a recently invaded region in Oregon (USA). Estimates of apparent survival and population gains are consistent with those from a nearby radio-tracking study and elucidate how barred owl abundances have increased dramatically over time. The dynamic N-occupancy model greatly improves inferences on individual-level population processes from occupancy data by explicitly modeling the latent population structure.
- You may send email to email@example.com to request a hard copy of this publication.
- (Please specify exactly which publication you are requesting and your mailing address.)
- We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
- This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
CitationRossman, Sam; Yackulic, Charles B.; Saunders, Sarah P.; Reid, Janice; Davis, Ray; Zipkin, Elise F. 2016. Dynamic N -occupancy models: estimating demographic rates and local abundance from detection-nondetection data . Ecology. 97(12): 3300-3307.
KeywordsBarred owl, demographic rates, dynamic, heterogeneity, latent, N-mixture model, occupancy, species distribution models.
- The effects of habitat, climate, and Barred Owls on long-term demography of Northern Spotted Owls
- Neighborhood and habitat effects on vital rates: expansion of the Barred Owl in the Oregon Coast Ranges
- Modeling co-occurrence of northern spotted and barred owls: accounting for detection probability differences
XML: View XML