Sector-wide outbreak definitions and non-outbreak populations.

The purple line represents the COTS density at a given location. (A)–An example of a population that would be categorised as an Outbreak. This is due to the population breaching the 0.22 COTS/tow density (an established outbreak). The years categorised as an ‘outbreak’ are denoted by the transparent, red rectangle. The year prior to the outbreak threshold being breached is included to capture the pre-outbreak coral cover and the outbreak is ended with two consecutive years below the threshold. (B)–an example of a population that would not be categorised as an Outbreak. This is due to the density of COTS not crossing the 0.22 COTS/tow threshold (denoting a ‘severe’ outbreak). NB These sector-wide definitions of outbreak periods are distinct from the reef level outbreak which simply reflect the Outbreak Status of a reef at a singular point in time. (TIF)</p

COTS strategic management conceptual framework.

Diagrammatic representation of COTS outbreak and coral cover dynamics, and the management objectives at various stages of the outbreak cycle. The COTS Control Program capacity and the timing of culling commencement strongly influences when and how the objectives can be achieved. (TIF)</p

COTS Management on the GBR.

Resilience-based management is essential to protect ecosystems in the Anthropocene. Unlike large-scale climate threats to Great Barrier Reef (GBR) corals, outbreaks of coral-eating crown-of-thorns starfish (COTS; Acanthaster cf. solaris) can be directly managed through targeted culling. Here, we evaluate the outcomes of a decade of strategic COTS management in suppressing outbreaks and protecting corals during the 4th COTS outbreak wave at reef and regional scales (sectors). We compare COTS density and coral cover dynamics during the 3rd and 4th outbreak waves. During the 4th outbreak wave, sectors that received limited to no culling had sustained COTS outbreaks causing significant coral losses. In contrast, in sectors that received timely and sufficient cull effort, coral cover increased substantially, and outbreaks were suppressed with COTS densities up to six-fold lower than in the 3rd outbreak wave. In the Townsville sector for example, despite exposure to comparable disturbance regimes during the 4th outbreak wave, effective outbreak suppression coincided with relative increases in sector-wide coral cover (44%), versus significant coral cover declines (37%) during the 3rd outbreak wave. Importantly, these estimated increases span entire sectors, not just reefs with active COTS control. Outbreaking reefs with higher levels of culling had net increases in coral cover, while the rate of coral loss was more than halved on reefs with lower levels of cull effort. Our results also indicate that outbreak wave progression to adjoining sectors has been delayed, probably via suppression of COTS larval supply. Our findings provide compelling evidence that proactive, targeted, and sustained COTS management can effectively suppress COTS outbreaks and deliver coral growth and recovery benefits at reef and sector-wide scales. The clear coral protection outcomes demonstrate the value of targeted manual culling as both a scalable intervention to mitigate COTS outbreaks, and a potent resilience-based management tool to “buy time” for coral reefs, protecting reef ecosystem functions and biodiversity as the climate changes.</div

Relative coral cover change time series with outlier reefs.

Relative change in coral cover (%) by Sector, coloured according to the type of management action implemented ‘Limited Action’ (orange), ‘Reactive’ (yellow), and ‘Timely’ (green) Each line represents the relative change in coral cover at a given reef, up to 6 years following the start of the sector-specific 4th outbreak (see Table 1). Highlighted reefs are example outliers that are discussed in section 3.2. These individual trajectories underpin the modelled trajectory in Fig 4. NB Reefs surveyed less than 3 times were not included in this figure to increase the clarity of individual trajectories. Additionally, each facet is displayed on a variable y-axis to increase visual interpretation. Reefs from “Proactive action” (Cape Upstart sector) are not included in either time series analyses (see Fig 4) as the time series is not long enough from the predicted onset of the outbreak in 2020. (TIF)</p

Data and R code for analysis.

Detailed code for data wrangling (“Coral Protection Outcomes_Wrangle.Rmd”) as well as analysis and figure generation (“Coral Protection Outcomes_FinguresAnalysis.Rmd”). Outputs from the data wrangling step to be used in the analysis script are included in the “CoralProtection.Rdata” file. (ZIP)</p

COTS outbreaks, spatial extent and management action.

Maximum COTS density and the corresponding outbreak category at each reef during the 3rd outbreak wave (A) (1992–2009) and the 4th outbreak wave (B) (2011-Present) at LTMP reefs. Only reefs from sectors and outbreaks included in the following analysis are shown. Sector-scale colour coding depicts the management action taken during the 4th outbreak wave with the number of culling hours (total of all cull divers bottom time) listed below the sector labels. + Site-Scale Action refers to COTS culling conducted at high-value tourism sites during the 3rd outbreak wave, which had no discernible impact on sectoral level outbreak dynamics. * No Action refers to sectors where no control was implemented. ^ Insufficient Data reflects sectors where time series data was insufficient to determine Outbreak periods or no distinct outbreak wave was observed. These sectors have thus been excluded from these analyses. Sector outlines republished from AIMS: https://apps.aims.gov.au/reef-monitoring/sector/list under a CC BY license, with permission from Mike Emslie, AIMS under a CC BY license, original copyright 2023.</p

Spatial scales overview.

The spatial relationship between the Great Barrier Reef Marine Park (Marine Park), Sectors, Reefs, and Sites. (A) the entire Marine Park, (B) an individual Sector (Townsville), (C) an individual reef (John Brewer Reef), with an indicative reef-wide manta-tow path as conducted by the AIMS LTMP (D) culling sites. (TIF)</p

Annual coral cover change at varying intensities of COTS control.

Comparison of posterior probability distributions from Bayesian generalised linear mixed models of annual change in coral cover at increasing levels of culling effort observed during the 4th outbreak wave. Data points below probability distributions are the mean responses ±66% (thick bars) and 90% (thin bars) credible intervals. Culling effort is categorised based on the number of culling hours divided by the maximum COTS density observed during the 4th outbreak wave (see Table 1 for time period), as (1) reefs with no recorded COTS outbreak (blue); (2) reefs with recorded COTS outbreaks and above median culling effort relative to maximum COTS density (green); (3) reefs with recorded COTS outbreaks and below median culling effort relative to maximum COTS density (orange) and (4) reefs with recorded COTS outbreaks and no culling effort (red).</p

S1 File -

Resilience-based management is essential to protect ecosystems in the Anthropocene. Unlike large-scale climate threats to Great Barrier Reef (GBR) corals, outbreaks of coral-eating crown-of-thorns starfish (COTS; Acanthaster cf. solaris) can be directly managed through targeted culling. Here, we evaluate the outcomes of a decade of strategic COTS management in suppressing outbreaks and protecting corals during the 4th COTS outbreak wave at reef and regional scales (sectors). We compare COTS density and coral cover dynamics during the 3rd and 4th outbreak waves. During the 4th outbreak wave, sectors that received limited to no culling had sustained COTS outbreaks causing significant coral losses. In contrast, in sectors that received timely and sufficient cull effort, coral cover increased substantially, and outbreaks were suppressed with COTS densities up to six-fold lower than in the 3rd outbreak wave. In the Townsville sector for example, despite exposure to comparable disturbance regimes during the 4th outbreak wave, effective outbreak suppression coincided with relative increases in sector-wide coral cover (44%), versus significant coral cover declines (37%) during the 3rd outbreak wave. Importantly, these estimated increases span entire sectors, not just reefs with active COTS control. Outbreaking reefs with higher levels of culling had net increases in coral cover, while the rate of coral loss was more than halved on reefs with lower levels of cull effort. Our results also indicate that outbreak wave progression to adjoining sectors has been delayed, probably via suppression of COTS larval supply. Our findings provide compelling evidence that proactive, targeted, and sustained COTS management can effectively suppress COTS outbreaks and deliver coral growth and recovery benefits at reef and sector-wide scales. The clear coral protection outcomes demonstrate the value of targeted manual culling as both a scalable intervention to mitigate COTS outbreaks, and a potent resilience-based management tool to “buy time” for coral reefs, protecting reef ecosystem functions and biodiversity as the climate changes.</div

Supplemental text and tables.

Detailed explanations of the use of disturbance data, COTS control program methods, definition of sector-wide management action and the rationale for categorising the Cape Upstart sector as ‘Proactive action’. Also includes supplemental tables: Table S1. Glossary of key words and acronyms; Table S2. Model formulae and the description of the variables analysed; Table S3. Summary statistics for COTS densities and Coral Cover for each outbreak by sector. (DOCX)</p