Coral Monitoring Research Articles

Why keep monitoring coral reefs?

Abstract The high demand for information on how coral reefs are changing often exceeds the capacity of the scientific community to deliver the data necessary to meet this need. However, given the degraded state of coral reefs and the poor prognosis for their recovery, it is reasonable to ask whether coral reef monitoring should continue. Using my experiences from a 37-year study in the US Virgin Islands, I highlight the information that monitoring conveys on the changing state of coral reefs, and underscore how the interpretation of ecological trends matures with increasing longevity of records. Because the past is an imperfect predictor of the future, monitoring coral reefs remains an important endeavor. It offers the only opportunity to understand how reefs will continue to change, to connect patterns of change to the processes causing them to occur, and to create opportunities for management to best ensure their future.

Local conditions modulated the effects of marine heatwaves on coral bleaching in subtropical Hong Kong waters

A mass coral bleaching event occurred in the summer of 2022 in subtropical Hong Kong, driven by two marine heatwaves (MHWs) with high intensities of 1.56 and 0.86 °C above a mean climate condition, both MHWs 7 days with a short gap of 4 days during the strong La Niña year. A transect survey was conducted at nine study sites in three regions, which revealed widespread coral bleaching with bleached coral cover ranging from 2.4 to 70.3%. In situ environmental data revealed the presence of a thermocline and halocline. Local conditions, including depth and wave exposure, significantly influenced the bleaching response. Shallow-water (2–4 m) corals were primarily affected, particularly in sheltered and moderately sheltered sites that exhibited higher levels of bleached coral cover (42.97 ± 15.4% and 44.93 ± 29.4%, respectively) compared to the exposed sites (31.8 ± 5.2%). Bleaching in deep waters (4–6 m) was minimal, with only a few colonies of Goniopora at two of the three sheltered sites exhibiting bleaching (1.7 ± 1.5%). Heat stress resistance differed between coral genera. Recovery rate for four common coral genera is low for Acropora tumida. Additionally, a minor hypoxia event was found to cause mortality of non-coral benthos at a sheltered site (Sharp Island). These findings highlight the alarming impact of extreme heatwaves on subtropical coral communities and underscore the importance of monitoring coral bleaching.

Coral Health and Benthic Composition of Reefs in an MPA and Open-access Site in Western Calatagan, Batangas

Monitoring hard coral health and diversity is essential in assessing their resilience to disturbances such as coral bleaching. This study gathered baseline data on the health and benthic composition of coral reefs in western Calatagan, Batangas, the Philippines. Coral health in two sites – Buntong Gasang and the Quilitisan Marine Protected Area (MPA) – was assessed using the CoralWatch citizen science Coral Health Chart method. The average color score of more than 200 coral colonies was compared between sites and coral growth forms (i.e. branching, boulder, and plate). In addition, benthic composition in both sites was determined using photoquadrats. Buntong Gasang Point and Quilitisan MPA had mean coral scores that are 4.4 (± 1.0 SD) and 3.6 (± 1.0 SD), respectively, thus indicating normal symbiont densities. The analysis also showed little differences in mean color scores among coral growth forms ranging from 3.8–4.3. Both sites had relatively high coral cover (mean = 52.3% ± 4.3% SD in Buntong Gasang, mean = 49.7% ± 8.7% SD in Quilitisan MPA) despite having different benthic compositions [PERMANOVA, F(1,8) = 8.87, p = 0.006]. Branching coral cover was about six times higher in Buntong Gasang Point (17%), whereas encrusting corals dominated at Quilitisan MPA (~ 39%). In addition, algal cover was higher in Quilitisan (45.0%) than in Buntong Gasang (35.5%). Although other studies show that branching corals are less resistant than massive or encrusting forms to coral bleaching, examining coral color suggests that reefs in both Buntong Gasang and Quilitisan MPA appeared to have comparably recovered from the mass bleaching events in 2020–2021. However, regular monitoring is needed to assess the responses of these reefs to future thermal stress. This study shows the potential of monitoring coral color in assessing coral reef health in the Philippines.

Measuring multi-year changes in the Symbiodiniaceae algae in Caribbean corals on coral-depleted reefs.

Monitoring coral cover can describe the ecology of reef degradation, but rarely can it reveal the proximal mechanisms of change, or achieve its full potential in informing conservation actions. Describing temporal variation in Symbiodiniaceae within corals can help address these limitations, but this is rarely a research priority. Here, we augmented an ecological time series of the coral reefs of St. John, US Virgin Islands, by describing the genetic complement of symbiotic algae in common corals. Seventy-five corals from nine species were marked and sampled in 2017. Of these colonies, 41% were sampled in 2018, and 72% in 2019; 28% could not be found and were assumed to have died. Symbiodiniaceae ITS2 sequencing identified 525 distinct sequences (comprising 42 ITS2 type profiles), and symbiont diversity differed among host species and individuals, but was in most cases preserved within hosts over 3 yrs that were marked by physical disturbances from major hurricanes (2017) and the regional onset of stony coral tissue loss disease (2019). While changes in symbiont communities were slight and stochastic over time within colonies, variation in the dominant symbionts among colonies was observed for all host species. Together, these results indicate that declining host abundances could lead to the loss of rare algal lineages that are found in a low proportion of few coral colonies left on many reefs, especially if coral declines are symbiont-specific. These findings highlight the importance of identifying Symbiodiniaceae as part of a time series of coral communities to support holistic conservation planning. Repeated sampling of tagged corals is unlikely to be viable for this purpose, because many Caribbean corals are dying before they can be sampled multiple times. Instead, random sampling of large numbers of corals may be more effective in capturing the diversity and temporal dynamics of Symbiodiniaceae metacommunities in reef corals.

Host density and anthropogenic stress are drivers of variability in dark spot disease in Siderastrea siderea across the Florida Reef Tract

Dark spot disease (DSD) was first reported within Florida's coral reefs in the 1990s but factors affecting its spatial distribution have not been well studied. We used a 14-yr (2005–2019) coral monitoring data set, utilizing 2242 surveys collected along Florida's coral reefs (about 530 linear km) to explore the spatial and temporal patterns of DSD occurrence. We built predictive statistical models to test for correlations between a suite of environmental and human impact factors and the occurrence of DSD in the reef coral, Siderastrea siderea. DSD in S. siderea is a chronic disease which occurred in all 14 yrs of the study. Annual DSD prevalence ranged from 0.45% to 4.4% and the proportion of survey sites that had DSD ranged from 4.8% to 30.9%. During the study period, DSD became more widespread across Florida's coral reefs and affected a higher proportion of S. siderea populations. Spatial variations in DSD correlated with environmental and human factors which together explained 64.4% of the underlying variability. The most influential factors were concentration of silica in the surface waters (a proxy for freshwater input), the total number of coral hosts, and distance to septic areas. DSD occurred in all regions, but the highest cumulative prevalence occurred in the upper Keys on reefs around major urban centers with links to coastal water discharges. Our results support the hypothesis that coastal water quality is a key component of DSD disease dynamics in Florida and provides motivation for addressing land–sea connections to ameliorate disease occurrence in the region.

Improving coral monitoring by reducing variability and bias in cover estimates from seabed images

Seabed cover of organisms is an established metric for assessing the status of many vulnerable marine ecosystems. When deriving cover estimates from seafloor imagery, a source of uncertainty in capturing the true distribution of organisms is introduced by the inherent variability and bias of the annotation method used to extract ecological data. We investigated variability and bias in two common annotation methods for estimating organism cover, and the role of size selectivity in this variability. Eleven annotators estimated sparse cold-water coral cover in the same 96 images with both grid-based and manual segmentation annotation methods. The standard deviation between annotators was three times greater in the grid-based method compared to segmentation, and grid-based estimates from annotators tended to overestimate coral cover. Size selectivity biased the manual segmentation; the minimum size of colonies segmented varied between annotators fivefold. Two modelling techniques (based on Richard’s selection curves and Gaussian processes) were used to impute areas where annotators identified colonies too small for segmentation. By imputing small coral sizes in segmentation estimates, the coefficient of variation between annotators was reduced by approximately 10%, and method bias (compared to a reference dataset) was reduced by up to 23%. Therefore, for sparse, low cover organisms, manual segmentation of images is recommended to minimise annotator variability and bias. Uncertainty in cover estimates may be further reduced by addressing size selectivity bias when annotating small organisms in images using a data-driven modelling technique.

Monitoring climate change effects on coral reefs using edge-based image segmentation

Coral reefs are valuable ecosystems that face vulnerability to climate change impacts. Underwater images often encounter noise from various factors, such as water turbidity, lighting conditions, attenuation, and scattering, which can complicate edge detection and segmentation processes, leading to inaccuracies. However, image processing techniques offer a viable solution to this issue. In this study, an edge-based segmentation approach is proposed that uses multiple contrast techniques to detect and quantify changes in coral reef imagery. The proposed approach effectively identifies changes in coral reef imagery, making it a valuable tool for monitoring climate change's effects on these ecosystems. Furthermore, high-resolution images at different time points and locations were collected, and then an edge-based segmentation approach was utilized to enhance the accuracy of edge detection and segmentation. Comparing the proposed method with traditional segmentation techniques showed a significant improvement in terms of segmentation precision. Subsequently, alterations in the structure and composition of coral reefs are observed, indicating the influence of climate change on these ecosystems. This research highlights the capabilities of image processing techniques using edge-based segmentation in monitoring coral reefs. It offers an effective and precise approach to detecting changes in coral reef images, thereby contributing to conservation endeavors.

#DeOlhoNosCorais: a polygonal annotated dataset to optimize coral monitoring.

Corals are colonial animals within the Phylum Cnidaria that form coral reefs, playing a significant role in marine environments by providing habitat for fish, mollusks, crustaceans, sponges, algae, and other organisms. Global climate changes are causing more intense and frequent thermal stress events, leading to corals losing their color due to the disruption of a symbiotic relationship with photosynthetic endosymbionts. Given the importance of corals to the marine environment, monitoring coral reefs is critical to understanding their response to anthropogenic impacts. Most coral monitoring activities involve underwater photographs, which can be costly to generate on large spatial scales and require processing and analysis that may be time-consuming. The Marine Ecology Laboratory (LECOM) at the Federal University of Rio Grande do Norte (UFRN) developed the project "#DeOlhoNosCorais" which encourages users to post photos of coral reefs on their social media (Instagram) using this hashtag, enabling people without previous scientific training to contribute to coral monitoring. The laboratory team identifies the species and gathers information on coral health along the Brazilian coast by analyzing each picture posted on social media. To optimize this process, we conducted baseline experiments for image classification and semantic segmentation. We analyzed the classification results of three different machine learning models using the Local Interpretable Model-agnostic Explanations (LIME) algorithm. The best results were achieved by combining EfficientNet for feature extraction and Logistic Regression for classification. Regarding semantic segmentation, the U-Net Pix2Pix model produced a pixel-level accuracy of 86%. Our results indicate that this tool can enhance image selection for coral monitoring purposes and open several perspectives for improving classification performance. Furthermore, our findings can be expanded by incorporating other datasets to create a tool that streamlines the time and cost associated with analyzing coral reef images across various regions.

Coral Detection, Ranging, and Assessment (CDRA) algorithm-based automatic estimation of coral reef coverage

Climate change poses significant threats to the health of coral reefs. The detection of coral coverage is a quantitative method for assessing the health of coral reefs. Valuable insights into the effects of climate change on coral reef ecosystems and the trends in coral reef development can be gained through the monitoring of coral coverage. However, traditional manual methods for estimating coral coverage are time-consuming and labor-intensive, limiting the scalability and efficiency of coral surveys. The field of automated processing for coral video imagery is currently limited, impeding the development of effective techniques for comprehensive coral monitoring and further hindering progress in coral ecosystem monitoring. To cope with these challenges, there is a crucial need for automated systems to efficiently handle large volumes of video data, thereby transforming imaging devices, such as underwater robots, into autonomous sensors capable of conducting reliable and comprehensive surveys. In response to this pressing issue, this study presents a novel video analysis approach, termed the Coral Detection, Ranging, and Assessment (CDRA) algorithm, which combines cutting-edge computer vision techniques including You Only Look Once version 5 (YOLOv5) object detection, binocular stereo vision, and tracking algorithms. The CDRA algorithm aims to analyze continuous video segments of coral reefs, enabling the identification, counting, and estimation of size and location of individual coral colonies. Experimental evaluations conducted in controlled pool environments demonstrated the high accuracy of the proposed method, with an average accuracy of 90.7% in estimating coral coverage at different locations. Moreover, field trials conducted in Xidao Island of China verified the effectiveness and robustness of the CDRA algorithm under varying water quality and lighting conditions. The findings of this study represent a significant step towards the development of reliable and automated techniques for coral reef detection, contributing to the advancement of coral reef conservation efforts.

NEW STANDARDS FOR MITIGATING DREDGING IMPACTS IN SENSITIVE HABITATS IN SAUDI ARABIA

We propose a systematic approach to monitoring and managing dredge operations based on industry best practice advice, tailored to the specific conditions in the Red Sea, including the following key elements: 1) Relocation of corals from the direct dredging footprint, 2) Development of a site and project-specific dredging environmental management plan, 3) Undertaking turbidity and coral monitoring, 4) Turbidity plume hindcast and forecast, 5) Adaptive management involving all key project stakeholders. The paper lists the above key elements and presents a case study from Sindalah Island where the system was successfully applied – the first time such an approach has been implemented in the Middle East region.

Combining Drones and Deep Learning to Automate Coral Reef Assessment with RGB Imagery

Coral reefs and their associated marine communities are increasingly threatened by anthropogenic climate change. A key step in the management of climate threats is an efficient and accurate end-to-end system of coral monitoring that can be generally applied to shallow water reefs. Here, we used RGB drone-based imagery and a deep learning algorithm to develop a system of classifying bleached and unbleached corals. Imagery was collected five times across one year, between November 2018 and November 2019, to assess coral bleaching and potential recovery around Lord Howe Island, Australia, using object-based image analysis. This training mask was used to develop a large training dataset, and an mRES-uNet architecture was chosen for automated segmentation. Unbleached coral classifications achieved a precision of 0.96, a recall of 0.92, and a Jaccard index of 0.89, while bleached corals achieved 0.28 precision, 0.58 recall, and a 0.23 Jaccard index score. Subsequently, methods were further refined by creating bleached coral objects (>16 pixels total) using the neural network classifications of bleached coral pixels, to minimize pixel error and count bleached coral colonies. This method achieved a prediction precision of 0.76 in imagery regions with >2000 bleached corals present, and 0.58 when run on an entire orthomosaic image. Bleached corals accounted for the largest percentage of the study area in September 2019 (6.98%), and were also significantly present in March (2.21%). Unbleached corals were the least dominant in March (28.24%), but generally accounted for ~50% of imagery across other months. Overall, we demonstrate that drone-based RGB imagery, combined with artificial intelligence, is an effective method of coral reef monitoring, providing accurate and high-resolution information on shallow reef environments in a cost-effective manner.

The Use of Unoccupied Aerial Systems (UASs) for Quantifying Shallow Coral Reef Restoration Success in Belize

There is a growing need for improved techniques to monitor coral reef restoration as these ecosystems and the goods and services they provide continue to decline under threats of anthropogenic activity and climate change. Given the difficulty of fine-scale requirements to monitor the survival and spread of outplanted branching coral fragments, Unoccupied Aerial Systems (UASs) provide an ideal platform to spatially document and quantitatively track growth patterns on shallow reef systems. We present findings from monitoring coral reef restoration combining UAS data with object-oriented segmentation techniques and open-source GIS analysis to quantify the areal extent of species-specific coverage across ~one hectare of shallow fringing reef over a one-year period (2019–2020) in Laughing Bird Caye National Park, southern Belize. The results demonstrate the detection of coral cover changes for three species (Acropora cervicornis, Acropora palmata, and Acropora prolifera) outplanted around the caye since 2006, with overall target coral species cover changing from 2142.58 to 2400.64 square meters from 2019 to 2020. Local ecological knowledge gathered from restoration practitioners was used to validate classified taxa of interest within the imagery collected. Our methods offer a monitoring approach that provides insight into coral growth patterns at a fine scale to better inform adaptive management practices for future restoration actions both within the park and at other reef replenishment target sites.

Interactions between hard corals and reef fish communities in the Komodo National Park, East Nusa Tenggara Timur

The Komodo National Park is one of the largest National Parks in Indonesia that conserves not only terrestrial to protect the habitat of Komodo dragons but also marine areas. The marine ecosystems play important roles in protecting the shoreline from abrasion and supporting sustainability of seafood supplies for local communities. This study presents observed interactions between hard corals (number of species and coverage) and reef fish communities (number of species, abundance, and biomass). Coral monitoring was conducted at 12 stations in 2019. The study found 211 species of hard corals with an average hard coral cover of 30.84%. There is no significant correlation between the number of coral species with the fish communities. However, the branching coral cover shows a significant correlation with herbivorous fish communities (the number of species, abundance, and biomass. Such correlation may be attributed to the structural complexity of branching corals which provides shelters that prevent herbivorous fish from predation. Although branching corals are physically vulnerable to destruction and bleaching, their existence can promote herbivorous fish population sustainability and reef resilience.

Point Label Aware Superpixels for Multi-Species Segmentation of Underwater Imagery

Monitoring coral reefs using underwater vehicles increases the range of marine surveys and availability of historical ecological data by collecting significant quantities of images. Analysis of this imagery can be automated using a model trained to perform semantic segmentation, however it is too costly and time-consuming to densely label images for training supervised models. In this letter, we leverage photo-quadrat imagery labeled by ecologists with sparse point labels. We propose a point label aware method for propagating labels within superpixel regions to obtain augmented ground truth for training a semantic segmentation model. Our point label aware superpixel method utilizes the sparse point labels, and clusters pixels using learned features to accurately generate single-species segments in cluttered, complex coral images. Our method outperforms prior methods on the UCSD Mosaics dataset by 3.62% for pixel accuracy and 8.35% for mean IoU for the label propagation task, while reducing computation time reported by previous approaches by 76%. We train a DeepLabv3+ architecture and outperform state-of-the-art for semantic segmentation by 2.91% for pixel accuracy and 9.65% for mean IoU on the UCSD Mosaics dataset and by 4.19% for pixel accuracy and 14.32% mean IoU for the Eilat dataset.

A health survey of the reef forming scleractinian cold-water corals Lophelia pertusa and Madrepora oculata in a remote submarine canyon on the European continental margin, NE Atlantic

Monitoring of cold-water corals (CWCs) for pathogens and diseases is limited due to the environment, protected nature of the corals and their habitat and as well as the challenging and sampling effort required. It is recognised that environmental factors such as temperature and pH can expedite the ability of pathogens to cause diseases in cold-water corals therefore the characterisation of pathogen diversity, prevalence and associated pathologies is essential. The present study combined histology and polymerase chain reaction (PCR) diagnostic techniques to screen for two significant pathogen groups (bacteria of the genus Vibrio and the protozoan Haplosporidia) in the dominant NE Atlantic deep-water framework corals Lophelia pertusa (13 colonies) and Madrepora oculata (2 colonies) at three sampling locations (canyon head, south branch and the flank) in the Porcupine Bank Canyon (PBC), NE Atlantic. One M. oculata colony and four L. pertusa colonies were collected from both the canyon flank and the south branch whilst five L. pertusa colonies were collected from the canyon head. No pathogens were detected in the M. oculata samples. Neither histology nor PCR detected Vibrio spp. in L. pertusa, although Illumina technology used in this study to profile the CWCs microbiome, detected V. shilonii (0.03%) in a single L. pertusa individual, from the canyon head, that had also been screened in this study. A macroborer was observed at a prevalence of 0.07% at the canyon head only. Rickettsiales-like organisms (RLOs) were visualised with an overall prevalence of 40% and with a low intensity of 1 to 4 (RLO) colonies per individual polyp by histology. L. pertusa from the PBC canyon head had an RLO prevalence of 13.3% with the highest detection of 26.7% recorded in the south branch corals. Similarly, unidentified cells observed in L. pertusa from the south branch (20%) were more common than those observed in L. pertusa from the canyon head (6.7%). No RLOs or unidentified cells were observed in corals from the flank. Mean particulate organic matter concentration is highest in the south branch (2,612 μg l−1) followed by the canyon head (1,065 μg l−1) and lowest at the canyon flank (494 μg l−1). Although the route of pathogen entry and the impact of RLO infection on L. pertusa is unclear, particulate availability and the feeding strategies employed by the scleractinian corals may be influencing their exposure to pathogens. The absence of a pathogen in M. oculata may be attributed to the smaller number of colonies screened or the narrower diet in M. oculata compared to the unrestricted diet exhibited in L. pertusa, if ingestion is a route of entry for pathogen groups. The findings of this study also shed some light on how environmental conditions experienced by deep sea organisms and their life strategies may be limiting pathogen diversity and prevalence.

Machine-Learning for Mapping and Monitoring Shallow Coral Reef Habitats

Mapping and monitoring coral reef benthic composition using remotely sensed imagery provides a large-scale inference of spatial and temporal dynamics. These maps have become essential components in marine science and management, with their utility being dependent upon accuracy, scale, and repeatability. One of the primary factors that affects the utility of a coral reef benthic composition map is the choice of the machine-learning algorithm used to classify the coral reef benthic classes. Current machine-learning algorithms used to map coral reef benthic composition and detect changes over time achieve moderate to high overall accuracies yet have not demonstrated spatio-temporal generalisation. The inability to generalise limits their scalability to only those reefs where in situ reference data samples are present. This limitation is becoming more pronounced given the rapid increase in the availability of high temporal (daily) and high spatial resolution (<5 m) multispectral satellite imagery. Therefore, there is presently a need to identify algorithms capable of spatio-temporal generalisation in order to increase the scalability of coral reef benthic composition mapping and change detection. This review focuses on the most commonly used machine-learning algorithms applied to map coral reef benthic composition and detect benthic changes over time using multispectral satellite imagery. The review then introduces convolutional neural networks that have recently demonstrated an ability to spatially and temporally generalise in relation to coral reef benthic mapping; and recurrent neural networks that have demonstrated spatio-temporal generalisation in the field of land cover change detection. A clear conclusion of this review is that existing convolutional neural network and recurrent neural network frameworks hold the most potential in relation to increasing the spatio-temporal scalability of coral reef benthic composition mapping and change detection due to their ability to spatially and temporally generalise.

A Review of Current and New Optical Techniques for Coral Monitoring

Monitoring the health of coral reefs is essential to understanding the damaging impacts of anthropogenic climate change as such non-invasive methods to survey coral reefs are the most desirable. Optics-based surveys, ranging from simple photography to multispectral satellite imaging are well established. Herein, we review these techniques, focusing on their value for coral monitoring and health diagnosis. The techniques are broadly separated by the primary method in which data are collected: by divers and/or robots directly within the environment or by remote sensing where data are captured above the water’s surface by planes, drones, or satellites. The review outlines a new emerging technology, low-cost hyperspectral imagery, which is capable of simultaneously producing hyperspectral and photogrammetric outputs, thereby providing integrated information of the reef structure and physiology in a single data capture.

Conservation of the coral community and local stakeholders’ perceptions of climate change impacts: Examples and gap analysis in three Japanese national parks

Coastal ecosystems consisting of coral communities have high ecosystem services and are important for tourism, fisheries, and the maintenance of biodiversity. Corals are often considered a major tourist resource in national parks located in the southern part of Japan. However, due to global-scale stresses such as climate change and local-scale stresses such as mass outbreaks of coral predators, there is a need to consider appropriate management and countermeasures. Two national parks in the subtropical zone (Keramashoto and Amamigunto national parks) and one national park in the temperate zone (Ashizuri-Uwakai National Park) in Japan were selected as a case study. The objectives of this study were to determine the status of coral conservation/management from websites and reports, and to clarify perceptions/concerns about climate change impacts through interviews with local stakeholders. The overall aim was to identify challenges in achieving sustainable use of coral ecosystems in national parks under climate change. In all of the national parks, the use of the sea area for tourism, such as diving, was very active. At the same time, coral monitoring and culling of predators were being carried out. However, the results of the interviews revealed that each park had different issues in implementing conservation activities, and Ashizuri-Uwakai showed a lack of manpower compared to the other two parks due to the scattered distribution of diving operators. From the interviews on the impacts of climate change, the increases in air and water temperatures were recognized in all parks and were consistent with the actual observed data. In terms of future concerns, increased coral bleaching frequency was common. Text mining showed that perceptions of coastal resources differed among parks and between occupations (tourism, fisheries, and government). Since concerns about climate change varied among regions and conservation activity systems also differed, it is important to consider and implement adaptation measures based on an appropriate understanding of local conditions.

Novel Mitochondrial DNA Markers for Scleractinian Corals and Generic-Level Environmental DNA Metabarcoding

Coral reefs, the most biodiverse habitats in the ocean, are formed by anthozoan cnidarians, the scleractinian corals. Recently, however, ongoing climate change has imperiled scleractinian corals and coral reef environments are changing drastically. Thus, convenient, high-density monitoring of scleractinian corals is essential to understand changes in coral reef communities. Environmental DNA (eDNA) metabarcoding is potentially one of the most effective means of achieving it. Using publicly available scleractinian mitochondrial genomes, we developed high-specificity primers to amplify mitochondrial 12S ribosomal RNA (12S) and cytochrome oxidase-1 (CO1) genes of diverse scleractinian corals, which could be used for genus-level metabarcoding analyses, using next-generation sequencing technologies. To confirm the effectiveness of these primers, PCR amplicon sequencing was performed using eDNA isolated along the seashore of Okinawa, Japan. We successfully amplified all eDNA samples using PCR. Approximately 93 and 72% of PCR amplicon sequences of 12S and CO1 primers originated from scleractinian 12S and CO1 genes, respectively, confirming higher specificities for coral mitochondrial genes than primers previously used for coral eDNA metabarcoding. We also found that hierarchical clustering, based on the percentage of mapped reads to each scleractinian genus, discriminates between sampling locations, suggesting that eDNA surveys are sufficiently powerful to reveal differences between coral communities separated by <1 km. We conclude that the method reported here is a powerful tool for conducting efficient eDNA surveys targeting scleractinian corals.

Optimizing coral reef recovery with context-specific management actions at prioritized reefs

Assisting the natural recovery of coral reefs through local management actions is needed in response to increasing ecosystem disturbances in the Anthropocene. There is growing evidence that commonly used resilience-based passive management approaches may not be sufficient to maintain coral reef key functions. We synthesize and discuss advances in coral reef recovery research, and its application to coral reef conservation and restoration practices. We then present a framework to guide the decision-making of reef managers, scientists and other stakeholders, to best support reef recovery after a disturbance. The overall aim of this management framework is to catalyse reef recovery, to minimize recovery times, and to limit the need for ongoing management interventions into the future. Our framework includes two main stages: first, a prioritization method for assessment following a large-scale disturbance, which is based on a reef's social-ecological values, and on a classification of the likelihood of recovery or succession resulting in degraded, novel, hybrid or historical states. Second, a flow chart to assist with determining management actions for highly valued reefs. Potential actions are chosen based on the ecological attributes of the disturbed reef, defined during ecological assessments. Depending on the context, management actions may include (1) substrata rehabilitation actions to facilitate natural coral recruitment, (2) repopulating actions using active restoration techniques, (3) resilience-based management actions and (4) monitoring coral recruitment and growth to assess the effectiveness of management interventions. We illustrate the proposed decision framework with a case study of typhoon-damaged eastern outer reefs in Palau, Micronesia. The decisions made following this framework lead to the conclusion that some reefs may not return to their historical state for many decades. However, if motivation and funds are available, new management approaches can be explored to assist coral reefs at valued locations to return to a functional state providing key ecosystem services.