10.5061/DRYAD.88KS4G5
Chambert, Thierry
United States Geological Survey
Pennsylvania State University
Grant, Evan H. Campbell
United States Geological Survey
Miller, David A. W.
Pennsylvania State University
Nichols, James D.
United States Geological Survey
Mulder, Kevin P.
Smithsonian Conservation Biology Institute
Brand, Adrianne B.
United States Geological Survey
Data from: Two-species occupancy modeling accounting for species
misidentification and nondetection
Dryad
dataset
2019
2019-02-06T00:00:00Z
2019-02-06T00:00:00Z
en
https://doi.org/10.1111/2041-210x.12985
22704 bytes
1
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
1.In occupancy studies, species misidentification can lead to false
positive detections, which can cause severe estimator biases. Currently,
all models that account for false positive errors only consider omnibus
sources of false detections and are limited to single species occupancy.
2.However, false detections for a given species often occur because of the
misidentification with another, closely-related species. To exploit this
explicit source of false positive detection error, we develop a
two-species occupancy model that accounts for misidentifications between
two species of interest. As with other false positive models,
identifiability is greatly improved by the availability of unambiguous
detections at a subset of site-occasions. Here, we consider the case where
some of the field observations can be confirmed using laboratory or other
independent identification methods (“confirmatory data”). 3.We performed
three simulation studies to (1) assess the model's performance under
various realistic scenarios, (2) investigate the influence of the
proportion of confirmatory data on estimator accuracy, and (3) compare the
performance of this two-species model with that of the single-species
false positive model. The model shows good performance under all
scenarios, even when only small proportions of detections are confirmed
(e.g., 5%). It also clearly outperforms the single-species model. 4.We
illustrate application of this model using a four-year data set on two
sympatric species of lungless salamanders: the US federally endangered
Shenandoah salamander (Plethodon shenandoah), and its presumed competitor,
the red-backed salamander (Plethodon cinereus). Occupancy of red-backed
salamanders appeared very stable across the four years of study, whereas
the Shenandoah salamander displayed substantial turn-over in occupancy of
forest habitats among years. 5.Given the extent of species
misidentification issues in occupancy studies, this modelling approach
should help improve the reliability of estimates of species distribution,
which is the goal of many studies and monitoring programs. Further
developments, to account for different forms of state uncertainty, can be
readily undertaken under our general approach.
Salamander DatasetSalamander Dataset used for the real data analysis. It
includes the field detection data, as well as the confirmatory data (from
DNA analyses), for both species: P. cinereus and P. Shenandoah.Data
Salamanders.xlsx