Repeatable Semantic Reef-Mapping through Photogrammetry and Label-Augmentation

Closing the gap between existing large-area imaging research and marine conservation needs

Emerging technology has immense potential to increase the scale and efficiency of marine conservation. One such technology is large-area imaging (LAI), which relies on structure-from-motion photogrammetry to create composite products, including 3-dimensional (3-D) environmental models, that are larger in spatial extent than the individual images used to create them. Use of LAI has become widespread in certain fields of marine science, primarily to measure the 3D structure of benthic ecosystems and track change over time. However, the use of LAI in the field of marine conservation appears limited. We conducted a review of the coral reef literature on the use of LAI to identify research themes and regional trends in applications of this technology. We also surveyed 135 coral reef scientists and conservation practitioners to determine community familiarity with LAI, evaluate barriers practitioners face in using LAI, and identify applications of LAI believed to be most exciting or relevant to coral conservation. Adoption of LAI was limited primarily to researchers at institutions based in advanced economies and was applied infrequently to conservation, although conservation practitioners and survey respondents from emerging economies indicated they expect to use LAI in the future. Our results revealed disconnect between current LAI research topics and conservation priorities identified by practitioners, highlighting the need for more diverse, conservation-relevant research using LAI. We provide recommendations for how early adopters of LAI (typically Global North scientists from well-resourced institutions) can facilitate access to this conservation technology. These recommendations include developing training resources, creating partnerships for data storage and analysis, publishing standard operating procedures for LAI workflows, standardizing methods, developing tools for efficient data extraction from LAI products, and conducting conservation-relevant research using LAI.

Emerging 3D technologies for future reformation of coral reefs: Enhancing biodiversity using biomimetic structures based on designs by nature

The rapid decline of vulnerable coral reefs has increased the necessity of exploring interdisciplinary methods for reef restoration. Examining how to upgrade these tools may uncover options to better support or increase biodiversity of coral reefs. As many of the issues facing reef restoration today deal with the scalability and effectiveness of restoration efforts, there is an urgency to invest in technology that can help reach ecosystem-scale. Here, we provide an overview on the evolution to current state of artificial reefs as a reef reformation tool and discuss a blueprint with which to guide the next generation of biomimetic artificial habitats for ecosystem support. Currently, existing artificial structures have difficulty replicating the 3D complexity of coral habitats and scaling them to larger areas can be problematic in terms of production and design. We introduce a novel customizable 3D interface for producing scalable, biomimetic artificial structures, utilizing real data collected from coral ecosystems. This interface employs 3D technologies, 3D imaging and 3D printing, to extract core reef characteristics, which can be translated and digitized into a 3D printed artificial reef. The advantages of 3D printing lie in providing customized tools by which to integrate the vital details of natural reefs, such as rugosity and complexity, into a sustainable manufacturing process. This methodology can offer economic solutions for developing both small and large-scale biomimetic structures for a variety of restoration situations, that closely resemble the coral reefs they intend to support.

Coral-bleaching responses to climate change across biological scales

The global impacts of climate change are evident in every marine ecosystem. On coral reefs, mass coral bleaching and mortality have emerged as ubiquitous responses to ocean warming, yet one of the greatest challenges of this epiphenomenon is linking information across scientific disciplines and spatial and temporal scales. Here we review some of the seminal and recent coral-bleaching discoveries from an ecological, physiological, and molecular perspective. We also evaluate which data and processes can improve predictive models and provide a conceptual framework that integrates measurements across biological scales. Taking an integrative approach across biological and spatial scales, using for example hierarchical models to estimate major coral-reef processes, will not only rapidly advance coral-reef science but will also provide necessary information to guide decision-making and conservation efforts. To conserve reefs, we encourage implementing mesoscale sanctuaries (thousands of km² ) that transcend national boundaries. Such networks of protected reefs will provide reef connectivity, through larval dispersal that transverse thermal environments, and genotypic repositories that may become essential units of selection for environmentally diverse locations. Together, multinational networks may be the best chance corals have to persist through climate change, while humanity struggles to reduce emissions of greenhouse gases to net zero.

Automated 2D, 2.5D, and 3D Segmentation of Coral Reef Pointclouds and Orthoprojections

Enabled by advancing technology, coral reef researchers increasingly prefer use of image-based surveys over approaches depending solely upon in situ observations, interpretations, and recordings of divers. The images collected, and derivative products such as orthographic projections and 3D models, allow researchers to study a comprehensive digital twin of their field sites. Spatio-temporally located twins can be compared and annotated, enabling researchers to virtually return to sites long after they have left them. While these new data expand the variety and specificity of biological investigation that can be pursued, they have introduced the much-discussed Big Data Problem: research labs lack the human and computational resources required to process and analyze imagery at the rate it can be collected. The rapid development of unmanned underwater vehicles suggests researchers will soon have access to an even greater volume of imagery and other sensor measurements than can be collected by diver-piloted platforms, further exacerbating data handling limitations. Thoroughly segmenting (tracing the extent of and taxonomically identifying) organisms enables researchers to extract the information image products contain, but is very time-consuming. Analytic techniques driven by neural networks offer the possibility that the segmentation process can be greatly accelerated through automation. In this study, we examine the efficacy of automated segmentation on three different image-derived data products: 3D models, and 2D and 2.5D orthographic projections thereof; we also contrast their relative accessibility and utility to different avenues of biological inquiry. The variety of network architectures and parameters tested performed similarly, ∼80% IoU for the genus Porites, suggesting that the primary limitations to an automated workflow are 1) the current capabilities of neural network technology, and 2) consistency and quality control in image product collection and human training/testing dataset generation.

Automatic Semantic Segmentation of Benthic Habitats Using Images from Towed Underwater Camera in a Complex Shallow Water Environment

Underwater image segmentation is useful for benthic habitat mapping and monitoring; however, manual annotation is time-consuming and tedious. We propose automated segmentation of benthic habitats using unsupervised semantic algorithms. Four such algorithms––Fast and Robust Fuzzy C-Means (FR), Superpixel-Based Fast Fuzzy C-Means (FF), Otsu clustering (OS), and K-means segmentation (KM)––were tested for accuracy for segmentation. Further, YCbCr and the Commission Internationale de l’Éclairage (CIE) LAB color spaces were evaluated to correct variations in image illumination and shadow effects. Benthic habitat field data from a geo-located high-resolution towed camera were used to evaluate proposed algorithms. The Shiraho study area, located off Ishigaki Island, Japan, was used, and six benthic habitats were classified. These categories were corals (Acropora and Porites), blue corals (Heliopora coerulea), brown algae, other algae, sediments, and seagrass (Thalassia hemprichii). Analysis showed that the K-means clustering algorithm yielded the highest overall accuracy. However, the differences between the KM and OS overall accuracies were statistically insignificant at the 5% level. Findings showed the importance of eliminating underwater illumination variations and outperformance of the red difference chrominance values (Cr) in the YCbCr color space for habitat segmentation. The proposed framework enhanced the automation of benthic habitat classification processes.

Different population trajectories of two reef-building corals with similar life-history traits

Increases in the frequency and intensity of acute and chronic disturbances are causing declines of coral reefs world‐wide. Although quantifying the responses of corals to acute disturbances is well documented, detecting subtle responses of coral populations to chronic disturbances is less common, but can also result in altered population and community structures.

We investigated the population dynamics of two key reef‐building Merulinid coral species, Dipsastraea favus and Platygyra lamellina, with similar life‐history traits, in the Gulf of Eilat and Aqaba, Red Sea from 2015 to 2018, to assess potential differences in their population trajectories.

Demographic processes, which included rates of survival, growth, reproduction and recruitment were used to parametrize integral projection models and estimate population growth rates and the likely population trajectories of both coral species.

The survival and reproduction rates of both D. favus and P. lamellina were positively related to coral colony size, and elasticity analyses showed that large colonies most influenced population dynamics. Although both species have similar life‐history traits and growth morphologies and are generally regarded as ‘stress‐tolerant’, the populations showed contrasting trajectories—D. favus appears to be increasing whereas P. lamellina appears to be decreasing.

As many corals have long‐life expectancies, the process of local and regional decline might be subtle and slow. Ecological assessments based on total living coral coverage, morphological groups or functional traits might overlook subtle, species‐specific trends. However, demographic approaches capable of detecting subtle species‐specific population changes can augment ecological studies and provide valuable early warning signs of decline before major coral loss becomes evident.