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Estimation and Correction of Visibility Bias in Aerial Surveys of Wintering Ducks
Authors:AARON T PEARSE  PATRICK D GERARD  STEPHEN J DINSMORE  RICHARD M KAMINSKI  KENNETH J REINECKE
Institution:1. Experimental Statistics Unit, Box 9653, Mississippi State University, Mississippi State, MS 39762, USA

Department of Applied Economics and Statistics, 291 Barre Hall, Clemson University, Clemson, SC 29634, USA;2. Department of Natural Resource Ecology and Management, 339 Science II, Iowa State University, Ames, IA 50011, USA;3. Department of Wildlife and Fisheries, Box 9690, Mississippi State University, Mississippi State, MS 39762, USA;4. United States Geological Survey, Patuxent Wildlife Research Center, 2524 S Frontage Road, Suite C, Vicksburg, MS 39180, USA

Abstract:Abstract: Incomplete detection of all individuals leading to negative bias in abundance estimates is a pervasive source of error in aerial surveys of wildlife, and correcting that bias is a critical step in improving surveys. We conducted experiments using duck decoys as surrogates for live ducks to estimate bias associated with surveys of wintering ducks in Mississippi, USA. We found detection of decoy groups was related to wetland cover type (open vs. forested), group size (1–100 decoys), and interaction of these variables. Observers who detected decoy groups reported counts that averaged 78% of the decoys actually present, and this counting bias was not influenced by either covariate cited above. We integrated this sightability model into estimation procedures for our sample surveys with weight adjustments derived from probabilities of group detection (estimated by logistic regression) and count bias. To estimate variances of abundance estimates, we used bootstrap resampling of transects included in aerial surveys and data from the bias-correction experiment. When we implemented bias correction procedures on data from a field survey conducted in January 2004, we found bias-corrected estimates of abundance increased 36–42%, and associated standard errors increased 38–55%, depending on species or group estimated. We deemed our method successful for integrating correction of visibility bias in an existing sample survey design for wintering ducks in Mississippi, and we believe this procedure could be implemented in a variety of sampling problems for other locations and species. (JOURNAL OF WILDLIFE MANAGEMENT 72(3):808–813; 2008)
Keywords:abundance estimation  aerial survey  bootstrapping  Mississippi  sightability model  variance estimation  visibility bias  waterfowl  winter
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