Estimating the Encounter Rate Variance in Distance Sampling

• Published in: Biometrics Vol. 65; no. 1; pp. 225 - 236
• Main Authors: Fewster, Rachel M., Buckland, Stephen T., Burnham, Kenneth P., Borchers, David L., Jupp, Peter E., Laake, Jeffrey L., Thomas, Len
• Format: Journal Article
• Language: English
• Published: Malden, USA Blackwell Publishing Inc 01.03.2009; Blackwell Publishing; Blackwell Publishing Ltd
• Subjects: Bias; Biometric Methodology; Biometrics; Biometry - methods; Confidence interval; Density estimation; Distance sampling; Encounter rate; Estimating techniques; Estimation bias; Estimation methods; Estimators; Line transect sampling; Models, Statistical; Point transect sampling; Population estimates; Population trends; Research Design; Sampling; Statistical variance; Stratified variance estimators; Survey design; Systematic sampling; Variance estimation
• ISSN: 0006-341X; 1541-0420
• DOI: 10.1111/j.1541-0420.2008.01018.x

The dominant source of variance in line transect sampling is usually the encounter rate variance. Systematic survey designs are often used to reduce the true variability among different realizations of the design, but estimating the variance is difficult and estimators typically approximate the variance by treating the design as a simple random sample of lines. We explore the properties of different encounter rate variance estimators under random and systematic designs. We show that a design-based variance estimator improves upon the model-based estimator of Buckland et al. (2001, Introduction to Distance Sampling. Oxford: Oxford University Press, p. 79) when transects are positioned at random. However, if populations exhibit strong spatial trends, both estimators can have substantial positive bias under systematic designs. We show that poststratification is effective in reducing this bias.