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.
Online course on statistical modeling in population ecology. Includes instructional videos with associated code and data.
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.
Using eBird data to estimate species distributions. Code to reproduce the analyses and figures in published paper.
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.
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.
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
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.
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.
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