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Estimating Animal Abundance in Heterogeneous Environments: An Application to Aerial Surveys for Dugongs
Author(s) -
POLLOCK KENNETH H.,
MARSH HELENE D.,
LAWLER IVAN R.,
ALLDREDGE MATHEW W.
Publication year - 2006
Publication title -
the journal of wildlife management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.94
H-Index - 111
eISSN - 1937-2817
pISSN - 0022-541X
DOI - 10.2193/0022-541x(2006)70[255:eaaihe]2.0.co;2
Subject(s) - range (aeronautics) , abundance (ecology) , estimator , aerial survey , environmental science , population , distance sampling , statistics , fishery , geography , mathematics , cartography , biology , materials science , demography , sociology , composite material
The probability of detecting an animal in a sampled area during a survey consists of 2 components: 1) the probability of an animal being available for detection (availability), which can be highly variable in heterogeneous environments; and 2) the probability of an animal being detected, conditional on its being available for detection (perception). Many surveys only estimate the latter probability because modeling the availability process requires information collected external to the survey. We illustrate estimation of both probabilities in an application to aerial surveys of dugongs (Dugong dugon) in Northern Australian coastal waters where water clarity varies greatly over relatively small spatial scales. Using artificial dugong models and timed depth recorders deployed on 15 wild dugongs to obtain dive profiles, we carried out experiments to determine zones of detectability for dugongs at the range of depths, turbidities, and sea states that spanned the environmental heterogeneity encountered on dugong surveys. Resulting probability estimates were heterogeneous and dependent on the measured conditions. To estimate perception probability, we used a tandem team of 2 observers on either side of the aircraft. This permitted fitting generalized Lincoln–Petersen models with Program MARK. We then used the generalized Horvitz–Thompson estimator, based on the overall detection probability for each individual dugong, to generate population estimates. We also developed a new simulation‐based method for estimating standard errors and confidence intervals. We contrast absolute abundance estimates of dugongs in the Torres Strait and Northern Great Barrier Reef regions using both the new and original approaches (Marsh and Sinclair 1989a). For Torres Strait, the new method produced a substantially smaller estimate (11,956 vs. 14,106 dugongs) and a very much smaller standard error (1,189 vs. 2,314 dugongs), whereas the new method produced slightly larger estimates (mean 9,855 vs. 9,193 dugongs, standard error 1,184 vs. 917 dugongs) for the Northern Great Barrier Reef survey.