These data represent avian point count surveys conducted at 453 point sample survey locations on the 24,000 (approx) live-fire region of Fort Hood in central Texas. Surveys were conducted by independent double observers (2 per survey occasion) and as such we had a maximum of 3 paired survey histories, giving a maximum of 6 sample occasions (see MacKenzie et al. 2006, MacKenzie and Royle 2005, and Laake et al. 2011 for various sample survey design details). At each point, we surveyed for 5 minutes (technically broken into 3 time intervals of 2, 2, and 1 minutes; not used here) and we noted detections by each observer and collected distance to each observation within a set of distance bins (0-25, 25-50, 50-75, 75-100m) of the target species (Black-capped vireo's in this case) for each surveyor. Our primary focus was to use mark-recapture distance sampling methods to estimate density of Black-capped vireo's, and to estimate detection rates for the mark-recapture, distance, and composite model.
Format
The format is a data frame with the following covariate metrics.
- VisitNumber
Visit number to the point
- Species
Species designation, either Golden-cheeked warbler (GW) or Black-capped Vireo (BV)
- Distance
Distance measure, which is either NA (representing no detection), or the median of the binned detection distances
- PairNumber
ID value indicating which observers were paired for that sampling occasion
- Observer
Observer ID, either primary(1), or secondary (2)
- Detected
Detection of a bird, either 1 = detected, or 0 = not detected
- Date
Date of survey since 15 march 2011
- Pred
Predicted occupancy value for that survey hexagon based on Farrell et al. (2013)
- Category
Region.Label categorization, see
mrds
help file for details on data structure- Effort
Amount of survey effort at the point
- Day
Number of days since 15 March 2011
- ObjectID
Unique ID for each paired observations
Details
In addition to detailing the analysis used by Collier et al. (2013, In
Review), this example documents the use of mrds
for avian point count
surveys and shows how density models can be incorporated with occupancy
models to develop spatially explicit density surface maps. For those that
are interested, for the distance sampling portion of our analysis, we used
both conventional distance sampling (cds
) and multiple covariate
distance sampling (mcds
) with uniform and half-normal key functions.
For the mark-recapture portion of our analysis, we tended to use covariates
for distance (median bin width), observer, and date of survey (days since 15
March 2011).
We combined our mrds
density estimates via a Horvitz-Thompson styled
estimator with the resource selection function gradient developed in Farrell
et al. (2013) and estimated density on an ~3.14ha hexagonal grid across our
study area, which provided a density gradient for the Fort Hood military
installation. Because there was considerable data manipulation needed for
each analysis to structure the data appropriately for use in mrds
,
rather than wrap each analysis in a single function, we have provided both
the Golden-cheeked warbler and Black-capped vireo analyses in their full
detail. The primary differences you will see will be changes to model
structures and model outputs between the two species.
References
Farrell, S.F., B.A. Collier, K.L. Skow, A.M. Long, A.J. Campomizzi, M.L. Morrison, B. Hays, and R.N. Wilkins. 2013. Using LiDAR-derived structural vegetation characteristics to develop high-resolution, small-scale, species distribution models for conservation planning. Ecosphere 43(3): 42. http://dx.doi.org/10.1890/ES12-000352.1
Laake, J.L., B.A. Collier, M.L. Morrison, and R.N. Wilkins. 2011. Point-based mark recapture distance sampling. Journal of Agricultural, Biological and Environmental Statistics 16: 389-408.
Collier, B.A., S.L. Farrell, K.L. Skow, A. M. Long, A.J. Campomizzi, K.B. Hays, J.L. Laake, M.L. Morrison, and R.N. Wilkins. 2013. Spatially explicit density of endangered avian species in a disturbed landscape. Auk, In Review.