MacNeil MA et al. (2016), Joint estimation of crown of thorns (Acanthaste...

ECB-ART-44919

PeerJ 2016 Jan 01;4:e2310. doi: 10.7717/peerj.2310.

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Joint estimation of crown of thorns (Acanthaster planci) densities on the Great Barrier Reef.

MacNeil MA , Mellin C , Pratchett MS , Hoey J , Anthony KR , Cheal AJ , Miller I , Sweatman H , Cowan ZL , Taylor S , Moon S , Fonnesbeck CJ .

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Crown-of-thorns starfish (CoTS; Acanthaster spp.) are an outbreaking pest among many Indo-Pacific coral reefs that cause substantial ecological and economic damage. Despite ongoing CoTS research, there remain critical gaps in observing CoTS populations and accurately estimating their numbers, greatly limiting understanding of the causes and sources of CoTS outbreaks. Here we address two of these gaps by (1) estimating the detectability of adult CoTS on typical underwater visual count (UVC) surveys using covariates and (2) inter-calibrating multiple data sources to estimate CoTS densities within the Cairns sector of the Great Barrier Reef (GBR). We find that, on average, CoTS detectability is high at 0.82 [0.77, 0.87] (median highest posterior density (HPD) and [95% uncertainty intervals]), with CoTS disc width having the greatest influence on detection. Integrating this information with coincident surveys from alternative sampling programs, we estimate CoTS densities in the Cairns sector of the GBR averaged 44 [41, 48] adults per hectare in 2014.

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Species referenced: Echinodermata
Genes referenced: LOC100893907 LOC576414

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	Figure 1. Sampling scheme for crown-of-thorns starfish (CoTS) mark-recapture study.(A) Study reefs on the Great Barrier Reef; (B) multiple tagged CoTS #62 from the study; (C) parameter-expanded data augmentation (PXDA) matrix of observed (1 to n), unobserved (n + 1 to N), and not present (N + 1 to M) individuals within the study superpopulation (M); (D) reef schematic showing partitioning of reef (r) perimeter into manta-tow sections (s), delineated by radiating straight lines. yi denotes the number of capture occasions over which an individual was observed; zi indicates an individual was observed in any capture occasion.
	Figure 2. Factors affecting the detectability of crown-of-thorns starfish on the Great Barrier Reef.(A) Highest posterior density (HPD) effect sizes for alternative observation team (Team), tagging effects (Tagged), nighttime surveys (Night), animal size (disc with), and the percentage of hard coral present within the survey area. (B) Estimated median relationship between animal size and detectability (solid blue line), with 95% uncertainty intervals (dashed lines) and observed detection rates for k = 6 capture-occasions (dots). (C) Posterior probabilities of detection for CoTS, given presence for surveys conducted during the day and night. (D) Posterior probabilities of detection for CoTS among survey sites.
	Figure 3. Data calibration of alternative CoTS survey methods.(A) Estimated median catch-per-unit-effort (CPUE) calibration curve (solid blue line) and 95% uncertainty intervals (dotted lines) for AMPTO surveys; estimated relationship with CoTS density per hectare was DCoTS = [log(0.83) + 0.33∗log(CPUE)]∗40; (B) posterior median (dots), 50% (thick lines) and 95% (thin lines) density estimated CoTS densities for detection-corrected FMP surveys. Black diagonal is a 1:1 line in (B).
	Figure 4. Data-integrated estimated CoTS outbreak densities in the Cairns sector of the Great Barrier Reef, 2014.(A) Reef-wide average probability of a CoTS outbreak; (B) reef-wide average expected CoTS density; (C) estimated relationship between linear distance from Lizard Island and the probability of CoTS outbreak among Cairns-sector reefs.

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Aukema, Economic impacts of non-native forest insects in the continental United States. 2011, Pubmed