Email this article 
Hide
Show all
[test by reto]
| Authors: | John R. Fieberg | ||||
| Title: | Estimating Population Abundance Using Sightability Models: R SightabilityModel Package | ||||
| Abstract: | Sightability models are binary logistic-regression models used to estimate and adjust for visibility bias in wildlife-population surveys (Steinhorst and Samuel 1989). Estimation proceeds in 2 stages: (1) Sightability trials are conducted with marked individuals, and logistic regression is used to estimate the probability of detection as a function of available covariates (e.g., visual obstruction, group size). (2) The fitted model is used to adjust counts (from future surveys) for animals that were not observed. A modified Horvitz-Thompson estimator is used to estimate abundance: counts of observed animal groups are divided by their inclusion probabilites (determined by plot-level sampling probabilities and the detection probabilities estimated from stage 1). We provide a brief historical account of the approach, clarifying and documenting suggested modifications to the variance estimators originally proposed by Steinhorst and Samuel (1989). We then introduce a new R package, SightabilityModel, for estimating abundance using this technique. Lastly, we illustrate the software with a series of examples using data collected from moose (Alces alces) in northeastern Minnesota and mountain goats (Oreamnos americanus) in Washington State. | ||||
|
Page views:: 2669. Submitted: 2011-10-17. Published: 2012-11-13. |
|||||
| Paper: |
Estimating Population Abundance Using Sightability Models: R SightabilityModel Package
Download PDF
(Downloads: 2417)
|
||||
| Supplements: |
| ||||
| DOI: |
10.18637/jss.v051.i09
|
This work is licensed under the licenses Paper: Creative Commons Attribution 3.0 Unported License Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license. |