Data from: Distinguishing distribution dynamics from temporary emigration using dynamic occupancy models
Valente, Jonathon J., Oregon State University
Hutchinson, Rebecca A., Oregon State University
Betts, Matthew G., Oregon State University
Published Jun 12, 2018 on Dryad.
Cite this dataset
Valente, Jonathon J.; Hutchinson, Rebecca A.; Betts, Matthew G. (2018). Data from: Distinguishing distribution dynamics from temporary emigration using dynamic occupancy models [Dataset]. Dryad. https://doi.org/10.5061/dryad.5d8s7
1. Dynamic occupancy models are popular for estimating dynamic distribution rates (colonization and extinction) from repeated presence/absence surveys of unmarked animals. This approach assumes closure among repeated samples within primary periods, allowing estimation of dynamic rates between these periods. However, the impact of temporary emigration (reversible changes in sampling availability) on dynamic rate estimates, has not been tested.
2. Using simulated data, we investigated the degree to which temporary emigration could mislead researchers interested in quantifying dynamics. We then compared results from three avian point count datasets to evaluate the likelihood that temporary emigration confounds estimates of dynamics for 19 species under a popular sampling protocol.
3. Simulated experiments indicated that when secondary periods were open to temporary emigration, presence of dynamics was correctly identified ≥ 95.1% of the time, and dynamic rate estimates were accurate. However, dynamic rate estimates were biased when secondary periods were closed to temporary emigration. In empirical datasets, dynamic occupancy models had greater support than closed models for all species when secondary sampling periods occurred in immediate succession (i.e., 3 samples within 10 minutes); however, our results suggest that this is because these estimates were heavily influenced by temporary emigration. When counts within a primary period were separated by 24-48 hours, we found evidence of dynamics for less than half of these species. We recommend an alternative sampling approach that allows accurate estimation of dynamic rates when temporary emigration is of no interest, and introduce a novel model for estimating both processes simultaneously in rare cases where they are both of biological interest.
4. Concern for violating the occupancy modeling closure assumption has led to widespread recommendations that samples within primary periods be conducted extremely close in time. However, this may not be the best approach when interest is in quantifying dynamic rates. While dynamic occupancy models provide estimates of ‘colonization’ and ‘extinction,’ these values do not inherently represent dynamics unless temporary emigration has been explicitly modeled, or accounted for with sampling design. Naiveté to this fact can result in incorrect conclusions about biological processes.
Case Study Data
This file contains one row for each site visit (3) to each point count station (193) for each of the 19 species examined. Point count stations were 50 m radius circles, and we recorded a 1 in detection columns only when the species was detected inside that circle. As part of a separate project, point count stations were located on 12 different forest plots within 6 publicly-owned entities. We provide additional sampling details (e.g., Julian date, air temperature, wind speed) that were not used in the case study data analysis.
National Science Foundation, Award: CCF-1215950, DEB-1050954, DEB-1457837