Forecasting intensifying disturbance effects on coral reefs

Anticipating future changes of an ecosystem's dynamics requires knowledge of how its key communities respond to current environmental regimes. The Great Barrier Reef (GBR) is under threat, with rapid changes of its reef‐building hard coral (HC) community structure already evident across broad spatial scales. While several underlying relationships between HC and multiple disturbances have been documented, responses of other benthic communities to disturbances are not well understood. Here we used statistical modelling to explore the effects of broad‐scale climate‐related disturbances on benthic communities to predict their structure under scenarios of increasing disturbance frequency. We parameterized a multivariate model using the composition of benthic communities estimated by 145,000 observations from the northern GBR between 2012 and 2017. During this time, surveyed reefs were variously impacted by two tropical cyclones and two heat stress events that resulted in extensive HC mortality. This unprecedented sequence of disturbances was used to estimate the effects of discrete versus interacting disturbances on the compositional structure of HC, soft corals (SC) and algae. Discrete disturbances increased the prevalence of algae relative to HC while the interaction between cyclones and heat stress was the main driver of the increase in SC relative to algae and HC. Predictions from disturbance scenarios included relative increases in algae versus SC that varied by the frequency and types of disturbance interactions. However, high uncertainty of compositional changes in the presence of several disturbances shows that responses of algae and SC to the decline in HC needs further research. Better understanding of the effects of multiple disturbances on benthic communities as a whole is essential for predicting the future status of coral reefs and managing them in the light of new environmental regimes. The approach we develop here opens new opportunities for reaching this goal.     

Fine-scale time series surveys reveal new insights into spatio-temporal trends in coral cover (2002–2018), of a coral reef on the Southern Great Barrier Reef

Reef monitoring programmes often focus on limited sites, predominantly on reef slope areas, which do not capture compositional variability across zones. This study assessed spatial and temporal changes in hard coral cover at four hierarchical spatial scales. ~ 55,000, geo-referenced photoquadrats were collected annually from 2002 to 2018 and analysed using artificial intelligence for 31 sites across reef flat and reef slope zones on Heron Reef, Southern Great Barrier Reef, Australia. Trends in hard coral cover were examined at three spatial scales: (1) “reef scale”, all data; (2) “geomorphic zone scale”—north/south reef slope, inner/outer reef flat; and (3) “site scale”—31 sites. Coral cover trajectories were also examined at: (4) “sub-site scale”—sub-division of sites into 567 sub-sites, to estimate variability in coral cover trajectories via spatial statistical modelling. At reef scale coral cover increased over time to 25.6 ± 0.4 SE % in 2018 but did not recover following disturbances caused by disease (2004–2008), cyclonic conditions (2009) or severe storms (2015) to the observed pre-disturbance level (44.0 ± 0.7 SE %) seen in 2004. At geomorphic zone scale, the reef slope had significantly higher coral cover than the reef flat. Trends of decline and increase were visible in the slope zones, and the southern slope recovered to pre-decline levels. Variable coral cover trends were visible at site scale. Furthermore, sub-site spatial modelling captured eight years of coral recovery that occurred at different times and magnitudes across the four geomorphic zones, effectively estimating variability in the trajectory of the reef’s coral community. Derived spatial predictions for the entire reef show patchy coral recovery, particularly on the southern slope, and that recovery hotspots are distributed across the reef. These findings suggest that to fully understand and interpret coral decline or recovery on a reef, more accurate assessment can be achieved by examining sites distributed within different geomorphic zones to capture variation in exposure, depth and consolidation.

     

Predator Crown-of-Thorns Starfish (Acanthaster planci) Outbreak,Mass Mortality of Corals,and Cascading Effects on Reef Fish and Benthic Communities

Outbreaks of the coral-killing seastar Acanthaster planci are intense disturbances that can decimate coral reefs. These events consist of the emergence of large swarms of the predatory seastar that feed on reef-building corals, often leading to widespread devastation of coral populations. While cyclic occurrences of such outbreaks are reported from many tropical reefs throughout the Indo-Pacific, their causes are hotly debated, and the spatio-temporal dynamics of the outbreaks and impacts to reef communities remain unclear. Based on observations of a recent event around the island of Moorea, French Polynesia, we show that Acanthaster outbreaks are methodic, slow-paced, and diffusive biological disturbances. Acanthaster outbreaks on insular reef systems like Moorea''s appear to originate from restricted areas confined to the ocean-exposed base of reefs. Elevated Acanthaster densities then progressively spread to adjacent and shallower locations by migrations of seastars in aggregative waves that eventually affect the entire reef system. The directional migration across reefs appears to be a search for prey as reef portions affected by dense seastar aggregations are rapidly depleted of living corals and subsequently left behind. Coral decline on impacted reefs occurs by the sequential consumption of species in the order of Acanthaster feeding preferences. Acanthaster outbreaks thus result in predictable alteration of the coral community structure. The outbreak we report here is among the most intense and devastating ever reported. Using a hierarchical, multi-scale approach, we also show how sessile benthic communities and resident coral-feeding fish assemblages were subsequently affected by the decline of corals. By elucidating the processes involved in an Acanthaster outbreak, our study contributes to comprehending this widespread disturbance and should thus benefit targeted management actions for coral reef ecosystems.     

Improved Coral Population Estimation Reveals Trends at Multiple Scales on Australia’s Great Barrier Reef

The global erosion of biodiversity presents unique challenges for identifying major changes in population dynamics, establishing their causes, and managing and conserving affected ecosystems at broad spatial scales. Adaptive learning approaches connecting different spatial scales through the transfer of hierarchical information are powerful tools to address such challenges. Here, we use a Semi-Parametric Bayesian Hierarchical (SPa-BaH) model to estimate coral cover trajectories using 16 years of a broad-scale survey on Australia’s Great Barrier Reef (GBR). The spatiotemporal variability of coral populations has been considered by separating three-tiered spatial scales and allowing for alternating phases of increasing and decreasing in the estimation of their trajectories. Model estimates revealed coral cover trajectories that were highly variable according to location but that fairly consistently declined at a regional spatial scale. Notwithstanding this general trend, individual reefs within subregions in the central part of the GBR often displayed different trajectory types between sites separated by only a few hundred meters. These coral dynamics were also associated with reduced recovery rates in the Cairns and Swain subregions. Our study highlights the importance of accounting for local variation in coral cover when estimating the spatiotemporal trends in coral cover trajectories, in this case, at the GBR scale. By retaining information at different hierarchical spatial scales, our SPa-BaH model supports better estimation of large-scale coral cover trajectories. The quantitative approaches developed here can also be applied to other species with complex dynamics thereby enhancing estimations of their trajectories at local- and larger-scales and options for their management.