Coral Reef Monitoring Research Articles

Combined passive acoustic and video monitoring of coral reefs to better understand reef soundscapes and multi-species interactions

A detailed understanding of ecological soundscapes provides a window into ecosystem state that might otherwise go undetected. Rather than consider acoustic emissions of a particular species, a top down ecosystem acoustics point of view gives potentially valuable insights to reef ecosystem function. Simultaneous passive acoustic and video data were collected from coral reefs off the Kona Coast of Hawaii in January 2019 during a soundscape experiment. Frequent interactions between fish species as well as collective behaviors are identified and tracked by applying computer vision to video data. Comparison relating video data to acoustic data allows assessment of the same behaviors as simultaneously reflected in directional passive acoustic data. Collective consideration of acoustics and video offers insight into acoustic signatures of particular soniferous communities and behaviors amongst and between reef species. Machine learning applications match patterns between fish trajectories in videos and the sound field as received by a directional antenna. The relative level of biological activity and presence or absence of particular behaviors provides key data in the effort to understand coral reef ecosystem state.

Modelo Batimétrico derivado de imágenes Landsat ETM+ en zonas de arrecifes tropicales

Para la cartografía y monitoreo de los arrecifes de coral, un mapa batimétrico es útil como un mapa base. Diferentes métodos han sido desarrollados para cartografiar la batimetría usando sensores remotos. Dos grandes grupos se pueden distinguir. El primero utiliza datos de teledetección de sensores activos y el segundo se basa en el empleo de sensores pasivos para generar información multiespectral. Este artículo se centra en el método de datos provenientes de sensores pasivos. Una modificación al método DOP “Profundidad de penetración” mediante espectrometría que se llevó a cabo en imágenes Landsat ETM+ sobre Archipiélago de San Andrés y Providen- cia (Colombia). Las mediciones de profundidad utilizadas en la validación del mo- delo fueron derivadas de lecturas de ecosonda en campo e interpolación de mapas batimétricos. La exactitud de la prueba reveló que el modelo batimétrico resultante es útil para el mapeo en zonas de arrecifes de coral del mar Caribe hasta 25m de profundidad aproximadamente. Los datos no conformes a la realidad fueron gene- rados por suposiciones inherentes a la teoría utilizada, la interpolación de datos, las características de la imagen de satélite y los errores durante la ejecución del método.

Coral Reef Monitoring, Reef Assessment Technologies, and Ecosystem-Based Management

Coral reefs are exceptionally biodiverse and human dependence on their ecosystem services is high. Reefs experience significant direct and indirect anthropogenic pressures, and provide a sensitive indicator of coastal ocean health, climate change, and ocean acidification, with associated implications for society. Monitoring coral reef status and trends is essential to better inform science, management and policy, but the projected collapse of reef systems within a few decades makes the provision of accurate and actionable monitoring data urgent. The Global Coral Reef Monitoring Network has been the foundation for global reporting on coral reefs for two decades, and is entering into a new phase with improved operational and data standards incorporating the Essential Ocean Variables (EOVs) (www.goosocean.org/eov) and Framework for Ocean Observing developed by the Global Ocean Observing System. Three EOVs provide a robust description of reef health: hard coral cover and composition, macro-algal canopy cover, and fish diversity and abundance. A data quality model based on comprehensive metadata has been designed to facilitate maximum global coverage of coral reef data, and tangible steps to track capacity building. Improved monitoring of events such as mass bleaching and disease outbreaks, citizen science, and socio-economic monitoring have the potential to greatly improve the relevance of monitoring to managers and stakeholders, and to address the complex and multi-dimensional interactions between reefs and people. A new generation of autonomous vehicles (underwater, surface, and aerial) and satellites are set to revolutionize and vastly expand our understanding of coral reefs. Promising approaches include Structure from Motion image processing, and acoustic techniques. Across all systems, curation of data in linked and open online databases, with an open data culture to maximize benefits from data integration, and empowering users to take action, are priorities. Action in the next decade will be essential to mitigate the impacts on coral reefs from warming temperatures, through local management and informing national and international obligations, particularly in the context of the Sustainable Development Goals, climate action, and the role of coral reefs as a global indicator. Mobilizing data to help drive the needed behavior change is a top priority for coral reef observing systems.

Rapid estimation of bathymetry from multispectral imagery without in situ bathymetry data.

Optimization-based semi-analytical methods (OSMs) and empirical methods (EMs) have been developed to derive bathymetry maps from satellite-based multispectral data of coral reefs, allowing for the management, monitoring, and protection of coral reefs. However, OSMs are often criticized due to the time-consuming requirements of iterative computations, yet they are praised for working without the need for in situ bathymetry data. EMs are praised for their time-saving characteristics and criticized for their need for in situ measurements. To estimate the water depth from multispectral data quickly without in situ bathymetry data, we provide a new EM that combines our previously developed OSM called the unmixing-based multispectral optimization process exemplar method (UMOPE) and an EM called Stumpf's ratio method (SRM). In the new method, reflectance values from a small number of sampled pixels and the corresponding water depths estimated by UMOPE are used to determine the regression parameters for SRM. Thus, SRM determines the upper limit of accuracy for the new method, and UMOPE determines the possibility of reaching the upper limit. The new method was evaluated using three types of imagery of Xisha Islands, namely, WorldView-2 imagery with three traditional visible bands (WV-2a), Landsat 8 imagery with four visible bands, and WV-2 imagery with six visible bands (WV-2b). The results show that the new method can perform as well as SRM for Landsat 8 data and WV-2b data with similar root mean square error values at different depths. The lack of a coastal band in WV-2a imagery may cause large errors for the new method in deep water regions, especially when the water-leaving reflectance is noise perturbed. We found that even though the depths estimated by UMOPE are not error free at different ranges of water depth, if the regression line between the depths estimated by UMOPE and the measured depths is near the 1:1 line, the new method can perform as well as SRM. The new method may facilitate the rapid estimation of bathymetry from free Landsat 8 data of optically shallow waters around the world without in situ bathymetry data.

Oxidative stress biomarkers as potential tools in reef degradation monitoring: A study case in a South Atlantic reef under influence of the 2015–2016 El Niño/Southern Oscillation (ENSO)

Abstract The third global-scale coral bleaching event, triggered by the 2015–2016 El Nino, presented unprecedented levels of thermal stress and bleaching occurrence. Identification of potential cellular biomarkers in key reef species can greatly improve coral reef resource manager’s ability to make ecological forecasts and develop efficient mitigation strategies. In this context, the present study evaluated ecologically relevant biochemical parameters involved in thermal-stress response in two important reef building species of southwestern Atlantic Reefs – the scleractinian coral Mussismilia harttii and the hydrocoral Millepora alcicornis – aiming to assess their potential to forecast bleaching occurrence in corals/hydrocorals. Bleaching frequency, lipid peroxidation (LPO) and total antioxidant capacity (TAC), as well as thermal stress parameters (Degree Heating Weeks, DHW), were monitored during a six-month period in a reef area under influence of the 2015–2016 El Nino event. LPO is suggested as an informative, cost-effective and logical complement to reef monitoring programs; and TAC basal level as a potential measurement for predicting corals/hydrocorals susceptibility to bleaching. Further, results indicate M. alcicornis as a promising bioindicator in South Atlantic reefs. Findings presented here are expected to improve South Atlantic coral reef monitoring programs, as well as to contribute with potential biomarker-monitoring techniques to be used as additional tools in traditional reef monitoring programs worldwide. Further, observations on oxidative stress responses of a hydrocoral undergoing thermal stress conditions in the field are reported here for the first time.

Microbial indicators of environmental perturbations in coral reef ecosystems

BackgroundCoral reefs are facing unprecedented pressure on local and global scales. Sensitive and rapid markers for ecosystem stress are urgently needed to underpin effective management and restoration strategies. Although the fundamental contribution of microbes to the stability and functioning of coral reefs is widely recognised, it remains unclear how different reef microbiomes respond to environmental perturbations and whether microbiomes are sensitive enough to predict environmental anomalies that can lead to ecosystem stress. However, the lack of coral reef microbial baselines hinders our ability to study the link between shifts in microbiomes and ecosystem stress. In this study, we established a comprehensive microbial reference database for selected Great Barrier Reef sites to assess the diagnostic value of multiple free-living and host-associated reef microbiomes to infer the environmental state of coral reef ecosystems.ResultsA comprehensive microbial reference database, originating from multiple coral reef microbiomes (i.e. seawater, sediment, corals, sponges and macroalgae), was generated by 16S rRNA gene sequencing for 381 samples collected over the course of 16 months. By coupling this database to environmental parameters, we showed that the seawater microbiome has the greatest diagnostic value to infer shifts in the surrounding reef environment. In fact, 56% of the observed compositional variation in the microbiome was explained by environmental parameters, and temporal successions in the seawater microbiome were characterised by uniform community assembly patterns. Host-associated microbiomes, in contrast, were five-times less responsive to the environment and their community assembly patterns were generally less uniform. By applying a suite of indicator value and machine learning approaches, we further showed that seawater microbial community data provide an accurate prediction of temperature and eutrophication state (i.e. chlorophyll concentration and turbidity).ConclusionOur results reveal that free-living microbial communities have a high potential to infer environmental parameters due to their environmental sensitivity and predictability. This highlights the diagnostic value of microorganisms and illustrates how long-term coral reef monitoring initiatives could be enhanced by incorporating assessments of microbial communities in seawater. We therefore recommend timely integration of microbial sampling into current coral reef monitoring initiatives.

Leveraging Automated Image Analysis Tools to Transform Our Capacity to Assess Status and Trends of Coral Reefs

Digital photography is widely used by coral reef monitoring programs to assess benthic status and trends. In addition to creating a permanent archive, photographic surveys can be rapidly conducted, which is important in environments where bottom-time is frequently limiting. However, substantial effort is required to manually analyze benthic images; which is expensive and leads to lags before data are available. Using previously analyzed imagery from NOAA’s Pacific Reef Assessment and Monitoring Program, we assessed the capacity of a trained and widely used machine-learning image analysis tool – CoralNet (coralnet.ucsd.edu) - to generate fully-automated benthic cover estimates for the main Hawaiian Islands (MHI) and American Samoa. CoralNet was able to generate estimates of site-level coral cover for both regions that were highly comparable to those generated by human analysts (Pearson’s r > 0.97, and with bias of 1% or less). CoralNet was generally effective at estimating cover of common coral genera (Pearson’s r > 0.92 and with bias of 2% or less in 6 of 7 cases), but performance was mixed for other groups including algal categories, although generally better for American Samoa than MHI. CoralNet performance was improved by simplifying the classification scheme from genus to functional group and by training within habitat types, i.e., separately for coral-rich, pavement, boulder, or ‘other’ habitats. The close match between human-generated and CoralNet-generated estimates of coral cover pooled to the scale of island and year demonstrates that CoralNet is capable of generating data suitable for assessing spatial and temporal patterns. The imagery we used was gathered from sites randomly located in <30 m hard-bottom at multiple islands and habitat-types per region, suggesting our results are likely to be widely applicable. As image acquisition is relatively straightforward, the capacity of fully-automated image analysis tools to minimize the need for resource intensive human analysts opens possibilities for enormous increases in the quantity and consistency of coral reef benthic data that could become available to researchers and managers.

Reef Rover: A Low-Cost Small Autonomous Unmanned Surface Vehicle (USV) for Mapping and Monitoring Coral Reefs

In the effort to design a more repeatable and consistent platform to collect data for Structure from Motion (SfM) monitoring of coral reefs and other benthic habitats, we explore the use of recent advances in open source Global Positioning System (GPS)-guided drone technology to design and test a low-cost and transportable small unmanned surface vehicle (sUSV). The vehicle operates using Ardupilot open source software and can be used by local scientists and marine managers to map and monitor marine environments in shallow areas (&lt;20 m) with commensurate visibility. The imaging system uses two Sony a6300 mirrorless cameras to collect stereo photos that can be later processed using photogrammetry software to create underwater high-resolution orthophoto mosaics and digital surface models. The propulsion system consists of two small brushless motors powered by lithium batteries that follow pre-programmed survey transects and are operated by a GPS-guided autopilot control board. Results from our project suggest the sUSV provides a repeatable, viable, and low-cost (&lt;$3000 USD) solution for acquiring images of benthic environments on a frequent basis from directly below the water surface. These images can be used to create SfM models that provide very detailed images and measurements that can be used to monitor changes in biodiversity, reef erosion/accretion, and assessing health conditions.

Detection of gaps in the spatial coverage of coral reef monitoring projects in the US Caribbean and Gulf of Mexico.

As part of the US Coral Reef Task Force's National Program to Map, Assess, Inventory, and Monitor US Coral Reef Ecosystems, a comprehensive survey of projects/programs monitoring coral reef ecosystems and related habitats (i.e., seagrass beds and mangroves) in the US Caribbean and Pacific was undertaken. Information was gathered on a total of 296 monitoring and assessment projects conducted since 1990 in the US Caribbean and the Gulf of Mexico. Substantial gaps in monitoring coverage of US coral reef ecosystems were revealed through geographic information system (GIS) analysis of survey metadata. Although southern Florida contains approximately two-thirds of all marine monitoring projects found in the US Caribbean and Gulf of Mexico, we were unable to identify any ongoing projects that monitor coral reefs along Florida's western coast and off of the Florida Middle Grounds. Additionally, Florida is covered by approximately 1 900 km2 of mangroves, yet there were only four ongoing projects that monitor this ecosystem, leaving gaps in coverage in the Lower and Middle Keys and along the eastern and western coasts. The Flower Garden Banks National Marine Sanctuary, located offshore of the Texas/Louisiana border, has an integral long-term monitoring program, but lacks a monitoring project that gathers long-term, quantitative data on reef lish abundance and certain water quality parameters. Numerous coral reef monitoring projects in Puerto Rico are concentrated on the island's southwestern coast surrounding La Parguera, while far fewer monitoring projects are conducted along the northern and southeastern coasts and around Vieques Island. In the US Virgin Islands, the paucity of monitoring projects in large areas of St. Croix and St. Thomas contrasts with monitoring activity in three marine protected areas (MPAs), where 66% of the US Virgin Islands' coral reef monitoring sites were found. Only a series of assessments have been conducted at Navassa, a small, uninhabited island located 55 km west of Haiti and 137 km northeast of Jamaica. In order to better understand changes in coral reef communities and to produce a series of biennial reports on the status of US coral reef ecosystems, the National Oceanic and Atmospheric Administration (NOAA) is developing a national coral reef monitoring network. This network has already begun to fill some of these gaps in monitoring coverage through issuing cooperative grants to states and territories to build long-term monitoring capacity.

A rapid in situ fluorescence census for coral reef monitoring

Since the discovery of Green fluorescent protein (GFP) from jellyfish, many GFP-like marine fluorescent proteins have been unveiled and implicated in myriad of biomedical and toxicological research applications. However, fluorescence trait has not been implemented in the field applications so far. In this study, using a UV-blue light, we induced fluorescence of corals to identify the diseased and damaged corals as well as newly recruiting and encrusting corals buried in sedimentation and algal covers. Healthy corals have displayed complete body fluorescence, whereas the dead, damaged and diseased corals are failed to display complete fluorescence. The development of pink line disease on Porites sp. was obvious under UV illumination than in visible light, revealing the hidden disease level propagation in Porites. Coral recruitment is well appreciated in both the study locations Burmanallah and Hare Island. Results of this study infer that this method is a highly reliable and rapid in field to study recruitment, disease propagation and health status of coral reefs.

Integrating Three-Dimensional Benthic Habitat Characterization Techniques into Ecological Monitoring of Coral Reefs

Long-term ecological monitoring of reef fish populations often requires the simultaneous collection of data on benthic habitats in order to account for the effects of these variables on fish assemblage structure. Here, we described an approach to benthic surveys that uses photogrammetric techniques to facilitate the extraction of quantitative metrics for characterization of benthic habitats from the resulting three-dimensional (3D) reconstruction of coral reefs. Out of 92 sites surveyed in the Northwestern Hawaiian Islands, photographs from 85 sites achieved complete alignment and successfully produced 3D reconstructions and digital elevation models (DEMs). Habitat metrics extracted from the DEMs were generally correlated with one another, with the exception of curvature measures, indicating that complexity and curvature measures should be treated separately when quantifying the habitat structure. Fractal dimension D64, calculated by changing resolutions of the DEMs from 1 cm to 64 cm, had the best correlations with other habitat metrics. Fractal dimension was also less affected by changes in orientations of the models compared to surface complexity or slope. These results showed that fractal dimension can be used as a single measure of complexity for the characterization of coral reef habitats. Further investigations into metrics for 3D characterization of habitats should consider relevant spatial scales and focus on obtaining variables that can complement fractal dimension in the characterization of reef habitats.

Practical Resilience Index for Coral Reef Assessment

Assessing coral reef resilience is an increasingly important component of coral reef management. Existing coral reef resilience assessments are not practical, especially for developing countries. South-east Asian countries have been using line-intercept-transect (LIT) in coral reef monitoring for a long time. The present study proposes an index for assessing coral reef resilience based on data collected from the LIT method. The resilience index formula was modified from an existing resilience index for soil communities developed by Orwin and Wardle. We used an ideal resilient coral reef community as a reference point for the index. The ideal coral reef was defined from data collected from 1992 to 2009. Six variables were statistically selected for the resilience indicators: coral functional group (CFG), coral habitat quality (CHQ), sand-silt cover (SSC), coral cover (COC), coral small-size number (CSN), and algae-other-fauna (AOF) cover. Maximum values of five variables were determined as the best state, while the maximum value of CSN was determined from 1240 data-sets of Indonesian reefs. The resilience index performed well in relation to changes in COC, AOF, and SSC variables. Managers can use this tool to compare coral reef resilience levels among locations and times. This index would be applicable for global coral reef resilience assessment.

Analysis on the outbreak period and cause of &amp;lt;italic&amp;gt;Acanthaster planci&amp;lt;/italic&amp;gt; in Xisha Islands in recent 15 years

Outbreaks of the crown-of-thorns starfish Acanthaster planci have received increasing attention due to their negative impacts on coral reefs. However, outbreaks of A. planci in Chinese seas are still poorly understood. Coral reefs in the Xisha Islands (Paracel Islands), South China Sea, have been monitored during 2005 and 2019, including hard coral coverage, larval recruitment rates, density of coral reef fish and the populations of A. planci . This study aims to analyse the regular pattern regarding outbreaks of A. planci in the main islands of Xisha Islands, the causes of outbreaks of the crown-of-thorns starfish Acanthaster planci , and the solutions for controlling the outbreaks of the crown-of-thorns starfish Acanthaster planci . Monitoring coral reef ecosystems on the main islands of Xisha Islands from 2005 to 2019 showed that the cycle of Acanthaster planci outbreaks in Xisha Islands is about 15 years. These 15 years can be divided into two phases, in which the period of A. planci outbreak is about 5 years, and the recovery period of coral reefs is about 10 years. When A. planci outbreak from 2006 to 2010, the coral reef cover rate decreased from more than 60% to less than 5%. During the recovery period from 2011 to 2019, the coverage of coral reefs gradually increased to around 15%, at the same time the coral recruitment and coral reef fish increased. Further analysis showed that the occurrence of A. planci in Xisha Islands is mainly related to typhoon weather, reduction of coral reef fish, global warming and human activities. The passage of the typhoon brought a large number of nutrients, which led to the increase of plankton, leading to the survival rate of larvae of A. planci . Global warming and a decline in coral reef fish could lead to a greater percentage of the eggs of A. planci hatching and surviving. Based on 15-years monitoring data, it is highly possible that Xisha Islands are entering the next outbreak cycle of A. planci , and therefore measures should be taken to prevent the coral reef ecosystem from being destroyed again. Outbreaks of the crown-of-thorns starfish A. planci should be controlled in several ways. Direct control methods including physical removal of individual starfish and cutting individuals into multiple pieces were most often used methods to kill starfish. The most effective methods to control A. planci require injecting individual starfish with lethal chemicals, including sodium bisulfate, powdered citric acid, vinegar and thiosulfate-citrate-bile-sucrose agar (TCBS). Releasing the predator of A. planci of their different life cycle was also an effective way to control A. planci . The Giant Triton Shells ( Charonia tritonis ), the Napoleon Maori Wrasse ( Cheilinus undulatus ), Starry Puffer ( Arathron stellatus ) and Titan Trigger Fish ( Ballistoides viridescens ) were the main predator of the crown-of-thorns starfish A. planci . Moreover, regular monitoring of the starfish A. planci should be conducted in the Xisha Islands for early warning of outbreaks.

Outbreak densities of the coral predator Drupella in relation to in situ Acropora growth rates on Ningaloo Reef, Western Australia

Outbreaks of coral predators are defined as increases (often rapid) in their abundance above threshold densities that can be sustained by local coral assemblages, which in turn depends on the abundance and turnover of coral prey. To investigate the outbreak densities of the corallivorous gastropod Drupella cornus, we conducted both in situ feeding and coral growth experiments at Mandu reef within the Ningaloo Marine Park, Western Australia. Over two 10-day periods, we tagged and photographed feeding scars on colonies of the tabulate coral Acropora spicifera that harboured Drupella feeding aggregations. We calculated a mean in situ Drupella consumption rate of 1.16 ± 1.1 cm2 coral area individual−1 d−1. We also determined coral growth rates by tagging and photographing 24 colonies of Acropora spicifera at time zero and then again 1 year later. We calculated a mean linear extension rate of 7.9 ± 3.7 cm yr−1 for actively growing Acropora spicifera, which we then used to estimate A. spicifera growth rates over a range of coral cover values. This combination allowed us to determine the maximum number of Drupella that could be sustained across a range of coral cover. Our data suggest that the outbreak density of Drupella at the average level of coral cover for back reef sites at Mandu reef (17.6 ± 13.7%) is approximately 0.95 individuals m−2 reef area. At the maximum coral cover observed at Mandu reef (60%), the outbreak density of Drupella is estimated to be approximately 2.83 individuals m−2 reef area. Establishing Drupella outbreak densities assists managers in predicting possible outbreak abundances and in monitoring coral reef health.

Detection of changes in shallow coral reefs status: Towards a spatial approach using hyperspectral and multispectral data

Coral reef degradation due to environmental change, including anthropogenic disturbances, is a major concern worldwide. Detecting and assessing both temporal and spatial changes in benthic cover is a crucial requirement to inform policy makers and guide conservation measures. Here, we introduce a spatial approach based on high resolution multispectral and hyperspectral image analysis, developed in order to detect and quantify changes in benthic cover in a highly heterogeneous shallow coral reef flat in Reunion Island in the South-West Indian Ocean. We propose a new index called HCAI (Hyperspectral Coral to Algae Index), defined as the ratio of living coral cover to the sum of living coral and algal covers. Benthic cover estimates were derived from airborne hyperspectral image processing using water column correction and unmixing models implemented with the four main coral reef benthic components: corals, algae, seagrass and sand. Ground truth and LIDAR data acquired simultaneously were used to validate processing accuracy. A significant positive correlation (adjusted R2 = 0.72, p-value < 0.001) was obtained between coral cover recorded in situ and estimated from image analysis. Moreover, 13 habitat classes based on the four main benthic component covers were mapped at a scale of an entire reef. Diachronic analyses of hyperspectral images between 2009 and 2015 revealed an overall decrease of the HCAI index and a decrease in the area of all the dominant coral classes along the reef (−28.24% for the coral class for example), while the area of habitat classes dominated by algae strongly increased during the same period. Moreover, we detected and documented the spatial and temporal evolutions of coral geomorphological features composed with coral rubble deposits called rubble tongues (RTs) using different available sensors (i.e. hyperspectral, satellite, and orthophotography). Since 2003, four detected (RTs) have spread shoreward at a mean rate of 8.4 m.y−1 including significant loss of reef structural complexity and heterogeneity, a spreading pattern which was confirmed by 2009 and 2015 hyperspectral data. Remote sensing and more specifically airborne hyperspectral approaches open new perspectives for coral reef monitoring, at high temporal and spatial resolutions.

UAVs, Hyperspectral Remote Sensing, and Machine Learning Revolutionizing Reef Monitoring.

Recent advances in unmanned aerial system (UAS) sensed imagery, sensor quality/size, and geospatial image processing can enable UASs to rapidly and continually monitor coral reefs, to determine the type of coral and signs of coral bleaching. This paper describes an unmanned aerial vehicle (UAV) remote sensing methodology to increase the efficiency and accuracy of existing surveillance practices. The methodology uses a UAV integrated with advanced digital hyperspectral, ultra HD colour (RGB) sensors, and machine learning algorithms. This paper describes the combination of airborne RGB and hyperspectral imagery with in-water survey data of several types in-water survey of coral under diverse levels of bleaching. The paper also describes the technology used, the sensors, the UAS, the flight operations, the processing workflow of the datasets, the methods for combining multiple airborne and in-water datasets, and finally presents relevant results of material classification. The development of the methodology for the collection and analysis of airborne hyperspectral and RGB imagery would provide coral reef researchers, other scientists, and UAV practitioners with reliable data collection protocols and faster processing techniques to achieve remote sensing objectives.

MONITORING CORAL GROWTH – THE DICHOTOMY BETWEEN UNDERWATER PHOTOGRAMMETRY AND GEODETIC CONTROL NETWORK

Abstract. Creating 3-dimensional (3D) models of underwater scenes has become a common approach for monitoring coral reef changes and its structural complexity. Also in underwater archeology, 3D models are often created using underwater optical imagery. In this paper, we focus on the aspect of detecting small changes in the coral reef using a multi-temporal photogrammetric modelling approach, which requires a high quality control network. We show that the quality of a good geodetic network limits the direct change detection, i.e., without any further registration process. As the photogrammetric accuracy is expected to exceed the geodetic network accuracy by at least one order of magnitude, we suggest to do a fine registration based on a number of signalized points. This work is part of the Moorea Island Digital Ecosystem Avatar (IDEA) project that has been initiated in 2013 by a group of international researchers (https://mooreaidea.ethz.ch/).

Design of a Low-Cost Modem for Short-Range Underwater Acoustic Communications

An underwater acoustic modem (UAM) is an essential component of an underwater wireless sensor network (UWSN). The applications of UWSNs include, but are not limited to, monitoring of aquatic environments and coral reefs, coastal surveillance, etc. The design of UAMs is a challenging research problem due to the varying water environment. Moreover, the cost of UAM is an impediment to use it in a large UWSN. Hence, an economical UAM is required to encourage research in this area. In this paper, a low-cost modem prototype for short-range underwater acoustic communications is presented. As compared to the available solutions, cost-effectiveness is novelty of the modem. Furthermore, design parameters are available that could be modified or replicated for further research. Each module is tested individually and the overall performance of the modem is evaluated by experiments in an aquatic environment. The outcomes of the research are useful for the scientific community and provide guidelines to design a low-cost underwater acoustic modem.

Predicting Heat Stress to Inform Reef Management: NOAA Coral Reef Watch's 4-Month Coral Bleaching Outlook

The U.S. National Oceanic and Atmospheric Administration’s (NOAA) Coral Reef Watch (CRW) operates a global Four-Month Coral Bleaching Outlook system for shallow-water coral reefs in collaboration with NOAA’s National Centers for Environmental Prediction (NCEP). The Outlooks are generated by applying the algorithm used in CRW’s operational satellite coral bleaching heat stress monitoring, with slight modifications, to the sea surface temperature (SST) predictions from NCEP’s operational Climate Forecast System Version 2 (CFSv2). Once a week, the probability of heat stress capable of causing mass coral bleaching is predicted for four months in advance. Each day, CFSv2 generates an ensemble of 16 forecasts, with nine runs out to 45 days, three runs out to three months, and four runs out to nine months. This results in 28-112 ensemble members produced each week. A composite for each predicted week is derived from daily predictions within each ensemble member. The probability of each of four heat stress ranges (Watch and higher, Warning and higher, Alert Level 1 and higher, and Alert Level 2) is determined from all the available ensemble members for the week to form the weekly probabilistic Outlook. The probabilistic Four-Month Outlook is the highest weekly probability predicted among all the weekly Outlooks during a four-month period for each of the stress ranges. An initial qualitative skill analysis of the Outlooks for 2011-2015, compared with CRW’s satellite-based coral bleaching heat stress products, indicated the Outlook has performed well with high hit rates and low miss rates for most coral reef areas. Regions identified with high false alarm rates will guide future improvements. This Outlook system, as the first and only freely available global coral bleaching prediction system, has been providing critical early warning to marine resource managers, scientists, and decision makers around the world to guide management, protection, and monitoring of coral reefs since 2012. This has been especially valuable during the third global coral bleaching event that started in mid-2014 and extended into mid-2017. The Outlook system is an integrated component of CRW’s global decision support system for coral bleaching. Recent management actions taken in light of this system are discussed.

Using Seawater to Document Coral-Zoothanthella Diversity: A New Approach to Coral Reef Monitoring Using Environmental DNA

Frequent, high-density coral monitoring is essential to understand coral reef ecosystems. For this purpose, we developed a novel method for simultaneous monitoring of Acropora corals and their symbiont, Symbiodinium, from environmental DNA (eDNA) in seawater using next generation sequencing technology (NGS). We performed a tank experiment with running seawater using 19 Acropora species. Complete mitochondrial genomes of all the Acropora species were assembled to create a database and major types of their Symbiodinium symbionts were identified. Then eDNA was isolated by filtering inlet and outlet seawater from the tanks. Acropora and Symbiodinium DNA were amplified by PCR and sequenced. We detected all of the tested Acropora types from eDNA samples. Proportions of the DNA sequences and the weights of corals, and the number of DNA sequences and the masses of corals were positively correlated in the tanks, respectively. In this trial, we detected DNA sequences from as little as 0.04 kg of Acropora colony, suggesting that existence of at least one adult Acropora colony (approx. 30 cm diameter = 1kg) per m2 at depths <10m could be detected using eDNA in the field. In addition, we detected major types of Symbiodinium within host corals from seawater, suggesting that it should be possible to detect major coral symbiont types if Acropora corals exist nearby, and possible free-living state Symbiodinium cells from eDNA in sea water. eDNA abundance of Symbiodinium types did not correlate well with frequencies of major Symbiodinium types in the corals, suggesting that quantification of Symbiodinium is difficult at this stage. Although this is the initial attempt to detect coral and Symbiodinium simultaneously from eDNA in seawater, this method may allow us to perform high-frequency, high-density coral reef monitoring of both corals and their symbionts in the near future.