Double-observer line transect methods : levels of independence

• Published in: Biometrics
• Main Authors: Buckland, Stephen Terrence, Laake, Jeffrey L., Borchers, David Louis
• Other Authors: University of St Andrews.School of Mathematics and Statistics, University of St Andrews.Marine Alliance for Science & Technology Scotland, University of St Andrews.Scottish Oceans Institute, University of St Andrews.St Andrews Sustainability Institute, University of St Andrews.Centre for Research into Ecological & Environmental Modelling
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2011
• Subjects: Distance sampling; Double-observer methods; Full independence; Limiting independence; Line transect sampling; Point independence; QA Mathematics; SDG 14 - Life Below Water; QA; Petersen; minke whale
• Online Access: https://hdl.handle.net/10023/1928; https://doi.org/10.1111/j.1541-0420.2009.01239.x; http://www.scopus.com/inward/record.url?scp=77949660683&partnerID=8YFLogxK

Double-observer line transect methods are becoming increasingly widespread, especially for the estimation of marine mammal abundance from aerial and shipboard surveys when detection of animals on the line is uncertain. The resulting data supplement conventional distance sampling data with two-sample mark–recapture data. Like conventional mark–recapture data, these have inherent problems for estimating abundance in the presence of heterogeneity. Unlike conventional mark–recapture methods, line transect methods use knowledge of the distribution of a covariate, which affects detection probability (namely, distance from the transect line) in inference. This knowledge can be used to diagnose unmodeled heterogeneity in the mark–recapture component of the data. By modeling the covariance in detection probabilities with distance, we show how the estimation problem can be formulated in terms of different levels of independence. At one extreme, full independence is assumed, as in the Petersen estimator (which does not use distance data); at the other extreme, independence only occurs in the limit as detection probability tends to one. Between the two extremes, there is a range of models, including those currently in common use, which have intermediate levels of independence. We show how this framework can be used to provide more reliable analysis of double-observer line transect data. We test the methods by simulation, and by analysis of a dataset for which true abundance is known. We illustrate the approach through analysis of minke whale sightings data from the North Sea and adjacent waters. Peer reviewed