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Estimating the Encounter Rate Variance in Distance Sampling
Author(s) -
Fewster Rachel M.,
Buckland Stephen T.,
Burnham Kenneth P.,
Borchers David L.,
Jupp Peter E.,
Laake Jeffrey L.,
Thomas Len
Publication year - 2009
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.1541-0420.2008.01018.x
Subject(s) - statistics , distance sampling , variance (accounting) , sampling (signal processing) , mathematics , econometrics , computer science , biology , economics , habitat , ecology , accounting , filter (signal processing) , computer vision
Summary 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.