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Fit models to data from unmarked animals using Stan. Uses a similar interface to the R package 'unmarked', while providing the advantages of Bayesian inference and allowing estimation of random effects.
Rossman R., Yackulic C., Saunders S.P., Reid J., Davis R., and Zipkin E.F. 2016. Dynamic N-occupancy models: estimating demographic rates and local abundances from detection-nondetection data. Ecology. 97: 3300-3307.
Wright, A.D., Grant, E.H.C., & Zipkin, E.F. 2020. A hierarchical analysis of habitat area, connectivity, and quality on amphibian diversity across spatial scales.
This repository contains data and analysis from a 2022 regional survey conducted in coastal North Carolina and Virginia. The primary focus was modeling the abundance and occupancy of a threatened bird species in these areas using R.
Zipkin E.F., Rossman S., Yackulic C., Wiens J.D., Thorson J.T., Davis R.J., and Grant E.H.C. 2017. Integrating count and detection-nondetection data to model population dynamics. Ecology. 98: 1640-1650.
Hostetter NJ, D Ryan, D Grosshuesch, T Catton, S Malick-Wahls, TA Smith, and B Gardner. Quantifying spatiotemporal occupancy dynamics and multi-year core use areas at a species range boundary. Diversity and Distributions. Accepted.
Zylstra, E. R., D. E. Swann, B. R. Hossack, E. Muths, and R. J. Steidl. 2019. Drought-mediated extinction of an arid-land amphibian: insights from a spatially explicit dynamic occupancy model. Ecological Applications 29:e01859
Simulation models using metapopulation modeling framework to investigate relationship between species-traits (colonisation, extinction, dipsersal) and time lags (extinction debt and colonisation lag) in response to landscape degradation and restoration.