Accounting for uncertainty in duplicate identification and group size judgements in mark–recapture distance sampling. Issue 2 (6th November 2017)

• Record Type: Journal Article
• Authors: Hamilton, Olivia N. P.; Kincaid, Sophie E.; Constantine, Rochelle; Kozmian‐Ledward, Lily; Walker, Cameron G.; Fewster, Rachel M.
• Editors: Yoccoz, Nigel
• Is Part Of: Methods in ecology and evolution. Volume 9:Issue 2(2018)
• Page Start: 354
• Page End: 362
• Publication Date: 2017-11-06
• Subjects: abundance -- coefficient of variation -- common dolphins -- double‐observer aerial surveys -- group size -- mark–recapture distance sampling; Ecology -- Periodicals; Evolution -- Periodicals; 577
• DOI: 10.1111/2041-210X.12895
• Languages: English
• ISSNs: 2041-210X

Abstract

Abstract: Mark–recapture distance sampling (MRDS) surveys with two independent observers are widely used to estimate wildlife population abundance. The analysis relies on accurate identification of duplicate sightings common to both observers, and correct judgements of group size, both of which are hard to achieve for species that exhibit complex grouping patterns. In this paper, we examine the impact of these sources of uncertainty on bias and precision of abundance estimates, using a case study of 22 aerial surveys of common dolphins ( Delphinus delphis ) in the Hauraki Gulf, New Zealand. We develop a novel probabilistic method to identify duplicate observations, and account for various sources of uncertainty using a simulation‐intensive approach. For our case study, identifying duplicates using reasonable but arbitrary thresholds of time and angle discrepancies created a range of abundance estimates differing by up to 20%, whereas our novel threshold‐free probabilistic analysis returned an estimate roughly central to this range. Uncertainty in group size made a smaller impact of up to 5% on abundance estimates. All analysis choices returned similar values for the coefficient of variation, from 20 to 23%. Generating robust estimates of abundance, and accounting for all associated sources of uncertainty, is critical for informing conservation management. Our novel approach provides a way to eliminate arbitrary decisions associated with MRDS, and account for a wider range of uncertainties. Our method allows for the reliable application of MRDS to a wider range of terrestrial and marine species, and will be a useful tool for producing robust abundance estimates for species that exhibit complex grouping patterns.