title: Adaptive line transect sampling.
abstract: Adaptive line transect sampling offers the potential of improved population density estimation efficiency over conventional line transect sampling when populations are spatially clustered. In adaptive sampling, survey effort is increased when areas of high animal density are located, thereby increasing the number of observations. Its disadvantage is that the survey effort required is not known in advance. We develop an adaptive line transect methodology that, by varying the degree of adaptation, allows total effort to be fixed at the design stage. Relative to conventional line transect surveys, it also provides better survey coverage in the event of disruption in survey effort, e.g., due to poor weather. In analysis, sightings from the adaptive sections are downweighted in proportion to the increase in effort. We evaluate the methodology by simulation and report on surveys of harbor porpoise in the Gulf of Maine, in which the approach was compared with conventional line transect sampling.
authors.affiliation: School of Mathematics and Statistics, University of St. Andrews, North Haugh, St. Andrews, Fife KY16 9SS, UK. john.pollard@gb.unisys.com
authors.forename: J H
authors.initials: JH
authors.lastname: Pollard
authors.forename: D
authors.initials: D
authors.lastname: Palka
authors.forename: S T
authors.initials: ST
authors.lastname: Buckland
mesh_terms: D000818:Animals; D016000:Cluster Analysis; D003625:Data Collection / Q000379:methods*; D008281:Maine; D008954:Models, Biological; D019370:Observation / Q000379:methods; D011156:Population Density; D011157:Population Dynamics; D019576:Porpoises / Q000254:growth & development*; D012107:Research Design