Coral reef ecosystems worldwide are under pressure from chronic and acute stressors that threaten their continued existence. Most obvious among changes to reefs is loss of hard coral cover, but a precise multi-scale estimate of coral cover dynamics for the Great Barrier Reef (GBR) is currently lacking. Monitoring data collected annually from fixed sites at 47 reefs across 1300 km of the GBR indicate that overall regional coral cover was stable (averaging 29% and ranging from 23% to 33% cover across years) with no net decline between 1995 and 2009. Subregional trends (10–100 km) in hard coral were diverse with some being very dynamic and others changing little. Coral cover increased in six subregions and decreased in seven subregions. Persistent decline of corals occurred in one subregion for hard coral and Acroporidae and in four subregions in non-Acroporidae families. Change in Acroporidae accounted for 68% of change in hard coral. Crown-of-thorns starfish (Acanthaster planci) outbreaks and storm damage were responsible for more coral loss during this period than either bleaching or disease despite two mass bleaching events and an increase in the incidence of coral disease. While the limited data for the GBR prior to the 1980's suggests that coral cover was higher than in our survey, we found no evidence of consistent, system-wide decline in coral cover since 1995. Instead, fluctuations in coral cover at subregional scales (10–100 km), driven mostly by changes in fast-growing Acroporidae, occurred as a result of localized disturbance events and subsequent recovery.

Networks of no-take marine reserves (NTMRs) are widely advocated for preserving exploited fish stocks and for conserving biodiversity. We used underwater visual surveys of coral reef fish and benthic communities to quantify the short- to medium-term (5 to 30 years) ecological effects of the establishment of NTMRs within the Great Barrier Reef Marine Park (GBRMP). The density, mean length, and biomass of principal fishery species, coral trout (Plectropomus spp., Variola spp.), were consistently greater in NTMRs than on fished reefs over both the short and medium term. However, there were no clear or consistent differences in the structure of fish or benthic assemblages, non-target fish density, fish species richness, or coral cover between NTMR and fished reefs. There was no indication that the displacement and concentration of fishing effort reduced coral trout populations on fished reefs. A severe tropical cyclone impacted many survey reefs during the study, causing similar declines in coral cover and fish density on both NTMR and fished reefs. However, coral trout biomass declined only on fished reefs after the cyclone. The GBRMP is performing as expected in terms of the protection of fished stocks and biodiversity for a developed country in which fishing is not excessive and targets a narrow range of species. NTMRs cannot protect coral reefs directly from acute regional-scale disturbance but, after a strong tropical cyclone, impacted NTMR reefs supported higher biomass of key fishery-targeted species and so should provide valuable sources of larvae to enhance population recovery and long-term persistence.

Changes in the relative abundances of coral taxa during recovery from disturbance may cause shifts in essential ecological processes on coral reefs. Coral cover can return to pre-disturbance levels (coral recovery) without the assemblage returning to its previous composition (i.e., without reassembly). The processes underlying such changes are not well understood due to a scarcity of longterm studies with sufficient taxonomic resolution. We assessed the trajectories and time frames for coral recovery and reassembly of coral communities following disturbances, using modeled trajectories based on data from a broad spatial and temporal monitoring program. We studied coral communities at six reefs that suffered substantial coral loss and subsequently regained at least 50 % of their pre-disturbance coral cover. Five of the six communities regained their coral cover and the rates were remarkably consistent, taking 7-10 years. Four of the six communities reassembled to their pre-disturbance composition in 8-13 years. The coral communities at three of the reefs both regained coral cover and reassembled ten years. The trajectories of two communities suggested that they were unlikely to reassemble and the remaining community did not regain pre-disturbance coral cover. The communities that regained coral cover and reassembled had high relative abundance of tabulate Acropora spp. Coral communities of this composition appear likely to persist in a regime of pulse disturbances at intervals of ten years or more. Communities that failed to either regain coral cover or reassemble were in near-shore locations and had high relative abundance of Porites spp. and soft corals. Under current disturbance regimes, these communities are unlikely to re-establish their pre-disturbance community composition.

In the face of increasing cumulative effects from human and natural disturbances, sustaining coral reefs will require a deeper understanding of the drivers of coral resilience in space and time. Here we develop a high‐resolution, spatially explicit model of coral dynamics on Australia's Great Barrier Reef (GBR). Our model accounts for biological, ecological and environmental processes, as well as spatial variation in water quality and the cumulative effects of coral diseases, bleaching, outbreaks of crown‐of‐thorns starfish (Acanthaster cf. solaris), and tropical cyclones. Our projections reconstruct coral cover trajectories between 1996 and 2017 over a total reef area of 14,780 km2, predicting a mean annual coral loss of −0.67%/year mostly due to the impact of cyclones, followed by starfish outbreaks and coral bleaching. Coral growth rate was the highest for outer shelf coral communities characterized by digitate and tabulate Acropora spp. and exposed to low seasonal variations in salinity and sea surface temperature, and the lowest for inner‐shelf communities exposed to reduced water quality. We show that coral resilience (defined as the net effect of resistance and recovery following disturbance) was negatively related to the frequency of river plume conditions, and to reef accessibility to a lesser extent. Surprisingly, reef resilience was substantially lower within no‐take marine protected areas, however this difference was mostly driven by the effect of water quality. Our model provides a new validated, spatially explicit platform for identifying the reefs that face the greatest risk of biodiversity loss, and those that have the highest chances to persist under increasing disturbance regimes.

Climate change threatens coral reefs across the world. Intense bleaching has caused dramatic coral mortality in many tropical regions in recent decades, but less obvious chronic effects of temperature and other stressors can be equally threatening to the long-term persistence of diverse coral-dominated reef systems. Coral reefs persist if coral recovery rates equal or exceed average rates of mortality. While mortality from acute destructive events is often obvious and easy to measure, estimating recovery rates and investigating the factors that influence them requires long-term commitment. Coastal development is increasing in many regions, and sea surface temperatures are also rising. The resulting chronic stresses have predictable, adverse effects on coral recovery, but the lack of consistent long-term data sets has prevented measurement of how much coral recovery rates are actually changing. Using long-term monitoring data from 47 reefs spread over 10 degrees of latitude on Australia's Great Barrier Reef (GBR), we used a modified Gompertz equation to estimate coral recovery rates following disturbance. We compared coral recovery rates in two periods: 7 years before and 7 years after an acute and widespread heat stress event on the GBR in 2002. From 2003 to 2009, there were few acute disturbances in the region, allowing us to attribute the observed shortfall in coral recovery rates to residual effects of acute heat stress plus other chronic stressors. Compared with the period before 2002, the recovery of fast-growing Acroporidae and of "Other" slower growing hard corals slowed after 2002, doubling the time taken for modest levels of recovery. If this persists, recovery times will be increasing at a time when acute disturbances are predicted to become more frequent and intense. Our study supports the need for management actions to protect reefs from locally generated stresses, as well as urgent global action to mitigate climate change.

Ecosystem monitoring is central to effective management, where rapid reporting is essential to provide timely advice. While digital imagery has greatly improved the speed of underwater data collection for monitoring benthic communities, image analysis remains a bottleneck in reporting observations. In recent years, a rapid evolution of artificial intelligence in image recognition has been evident in its broad applications in modern society, offering new opportunities for increasing the capabilities of coral reef monitoring. Here, we evaluated the performance of Deep Learning Convolutional Neural Networks for automated image analysis, using a global coral reef monitoring dataset. The study demonstrates the advantages of automated image analysis for coral reef monitoring in terms of error and repeatability of benthic abundance estimations, as well as cost and benefit. We found unbiased and high agreement between expert and automated observations (97%). Repeated surveys and comparisons against existing monitoring programs also show that automated estimation of benthic composition is equally robust in detecting change and ensuring the continuity of existing monitoring data. Using this automated approach, data analysis and reporting can be accelerated by at least 200x and at a fraction of the cost (1%). Combining commonly used underwater imagery in monitoring with automated image annotation can dramatically improve how we measure and monitor coral reefs worldwide, particularly in terms of allocating limited resources, rapid reporting and data integration within and across management areas.

Amounts of seed predation by grapsid crabs (Brachyura: Grapsidae) on two species of mangroves (Aegiceras corniculatum and Avicennia marina) were compared among different habitats in an Australian mangrove forest. For Avicennia, comparisons were between canopy gaps and the adjacent forest understory for six, mid intertidal, gaps of different sizes. For Aegiceras the comparisons were among canopy gaps in the high intertidal; open, accreting mud/sand banks where mangroves were colonizing in the low intertidal; and in the forest understory in both the high and low intertidal zones. These were repeated in the high salinity (35%0) downstream portion and the low salinity (0-5%0) upstream portion of a tidal river.Predation on A vicennia was significantly higher in the understory than in adjacent canopy gaps. Within a canopy opening, predation was greatest in the smallest gaps and lowest in the largest gaps. Predation on Aegiceras was greater in the high intertidal compared to the low intertidal, but no differences were found between river mouth and upstream locations. In the high intertidal zone of the forest, there were no differences in predation between canopy gap or forest understory sites for Aegiceras. In the low intertidal zone, however, significant differences in amount of predation were found between habitats. More Aegiceras propagules were consumed in the understory than on adjacent accreting sandbanks.Frequency of tidal inundation, which in turn affects the amount of time available to forage, is hypothesized to account for differences in predation between low and high intertidal forests and between small and large canopy gaps. Our results also suggest that 'shade intolerance' in these two species may actually reflect an escape from predators, successful when the seeds are dispersed into open areas such as canopy gaps or mud banks.

Using trained observers and video images of reef transects from many parts of the Great Barrier Reef, we investigated (1) accuracy of classification of benthos and (2) variability contributed by observers to the precision of estimates of benthic cover obtained from video tapes. In order to estimate accuracy of identification, benthic organisms were identified twice, first in the field and later from video images. These identifications were then compared. The effect of observer error on precision of benthic cover estimates was examined by having 2 observers sample the same video images on 3 separate occasions. These estimates were then compared at the level of different benthic groups (hard coral, soft coral and algae) and for different hierarchical levels of classification of hard corals (life form, family, genus and species). 'Benthic groups' (mean accuracy of 90 ± 8%) and 'families of hard coral' (91 ± 7%) were identified most accurately and least variably from video images, although many genera and some distinctive species were also identified reliably. Life forms of hard corals proved to be the least accurate and most variable level of classification, with a mean accuracy rating of 74 ± 16%. There was little additional variation in estimates of cover when 2 trained observers sampled images, compared with variation in estimates of cover from repeated samples of images by a single observer. At 10% cover, variability in estimates made by a single observer resulted in mean CIs of 7.9 to 12.1%. Inclusion of variation between observers expanded CIs by only ± 0.22%. Furthermore, total observer error was small relative to estimates of cover. For example, at 30% cover, the mean CI due to both between-and within-observer variability was 27.2 to 32.8%. KEY WORDS: Coral reef · Benthic cover · Underwater video · Observer error · Great Barrier Reef Resale or republication not permitted without written consent of the publisherMar Ecol Prog Ser 265: [107][108][109][110][111][112][113][114][115][116] 2003 along fixed survey lines, and also the relationship between sampling effort and the reliability of estimates of percent cover of corals. Many other potential sources of error remain unquantified. For example, an observer's ability to identify benthic organisms accurately may be affected by their familiarity with benthic communities in different regions, or by variation in the quality of video images from different environments. Long-term programs will have staff changes, so several observers will sample the video images over time. Training can reduce differences in the ability to identify benthic organisms from video images, but some will occur even among experienced observers: a single observer's perception will change through time with increasing experience and skills in identification. All inconsistencies in identification among observers and by the same observer over time contribute to 'observer error'.The magnitude of observer error may depend on the level of classification. Cover estimates of benthic orga...