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Global climate change and other anthropogenic stressors have heightened the need to rapidly characterize ecological changes in marine benthic communities across large scales. Digital photography enables rapid collection of survey images to meet this need, but the subsequent image annotation is typically a time consuming, manual task. We investigated the feasibility of using automated point-annotation to expedite cover estimation of the 17 dominant benthic categories from survey-images captured at four Pacific coral reefs. Inter- and intra- annotator variability among six human experts was quantified and compared to semi- and fully- automated annotation methods, which are made available at coralnet.ucsd.edu. Our results indicate high expert agreement for identification of coral genera, but lower agreement for algal functional groups, in particular between turf algae and crustose coralline algae. This indicates the need for unequivocal definitions of algal groups, careful training of multiple annotators, and enhanced imaging technology. Semi-automated annotation, where 50% of the annotation decisions were performed automatically, yielded cover estimate errors comparable to those of the human experts. Furthermore, fully-automated annotation yielded rapid, unbiased cover estimates but with increased variance. These results show that automated annotation can increase spatial coverage and decrease time and financial outlay for image-based reef surveys.

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.

Karimunjawa National Park is one of Indonesia’s oldest established marine parks. Coral reefs across the park are being impacted by fishing, tourism and declining water quality (local stressors), as well as climate change (global pressures). In this study, we apply a multivariate statistical model to detailed benthic ecological datasets collected across Karimunjawa’s coral reefs, to explore drivers of community change at the park level. Eighteen sites were surveyed in 2014 and 2018, before and after the 2016 global mass coral bleaching event. Analyses revealed that average coral cover declined slightly from 29.2 ± 0.12% (Standard Deviation, SD) to 26.3 ± 0.10% SD, with bleaching driving declines in most corals. Management zone was unrelated to coral decline, but shifts from massive morphologies toward more complex foliose and branching corals were apparent across all zones, reflecting a park-wide reduction in damaging fishing practises. A doubling of sponges and associated declines in massive corals could not be related to bleaching, suggesting another driver, likely declining water quality associated with tourism and mariculture. Further investigation of this potentially emerging threat is needed. Monitoring and management of water quality across Karimunjawa may be critical to improving resilience of reef communities to future coral bleaching.

In 2007, a phase shift from corals to corallimorpharians (CM) centered around a shipwreck was documented at Palmyra Atoll, Line Islands. Subsequent surveys revealed CM to be overgrowing the reef benthos, including corals and coralline algae, potentially placing coral ecosystems in the atoll at risk. This prompted the U.S. Fish and Wildlife Service, the lead management agency of the atoll, to remove the shipwreck. Subsequent surveys showed reductions in CM around the ship impact site. We explain patterns of spread of the CM in terms of both life history and local currents and show with a pilot study that pulverized bleach may be an effective tool to eradicate CM on a local scale. If applied strategically, particularly in heavily infested (> 66% cover) areas, active intervention such as this could be an effective management tool to reduce CM impact on localized areas and decrease colonization rate of remaining reefs. This is the first documentation of the response of an invasive cnidarian to shipwreck removal. While this was a singular event in Palmyra, the spatial and temporal patterns of this invasion and the eradications lessons described herein, are useful for anticipating and controlling similar situations elsewhere.

Coral reefs globally are declining rapidly because of both local and global stressors. Improved monitoring tools are urgently needed to understand the changes that are occurring at appropriate temporal and spatial scales. Coral fluorescence imaging tools have the potential to improve both ecological and physiological assessments. Although fluorescence imaging is regularly used for laboratory studies of corals, it has not yet been used for large-scale in situ assessments. Current obstacles to effective underwater fluorescence surveying include limited field-of-view due to low camera sensitivity, the need for nighttime deployment because of ambient light contamination and the need for custom multispectral narrow band imaging systems to separate the signal into meaningful fluorescence bands. Here we describe the Fluorescence Imaging System (FluorIS), based on a consumer camera modified for greatly increased sensitivity to chlorophyll-a fluorescence and we show high spectral correlation between acquired images and in situ spectrometer measurements. This system greatly facilitates underwater wide field-of-view fluorophore surveying during both night and day and potentially enables improvements in semi-automated segmentation of live corals in coral reef photographs and juvenile coral surveys.

Addressing the global decline of coral reefs requires effective actions from managers, policymakers and society as a whole. Coral reef scientists are therefore challenged with the task of providing prompt and relevant inputs for science-based decision-making. Here, we provide a baseline dataset, covering 1300 km of tropical coral reef habitats globally, and comprised of over one million geo-referenced, high-resolution photo-quadrats analysed using artificial intelligence to automatically estimate the proportional cover of benthic components. The dataset contains information on five major reef regions, and spans 2012–2018, including surveys before and after the 2016 global bleaching event. The taxonomic resolution attained by image analysis, as well as the spatially explicit nature of the images, allow for multi-scale spatial analyses, temporal assessments (decline and recovery), and serve for supporting image recognition developments. This standardised dataset across broad geographies offers a significant contribution towards a sound baseline for advancing our understanding of coral reef ecology and thereby taking collective and informed actions to mitigate catastrophic losses in coral reefs worldwide.Measurement(s)ecosystem • coral reef • compositionTechnology Type(s)automated image annotation • machine learningFactor Type(s)year of data collection • geographic locationSample Characteristic - OrganismAnthozoa • Algae • PoriferaSample Characteristic - Environmentmarine coral reef biome • marine coral reef fore reefSample Characteristic - LocationAtlantic Ocean • Eastern Australia • Indian Ocean • Southeast Asia • Pacific Ocean • Great Barrier ReefMachine-accessible metadata file describing the reported data: 10.6084/m9.figshare.13007516

Size and growth rates for individual colonies are some of the most essential descriptive parameters for understanding coral communities, which are currently experiencing worldwide declines in health and extent. Accurately measuring coral colony size and changes over multiple years can reveal demographic, growth, or mortality patterns often not apparent from short-term observations and can expose environmental stress responses that may take years to manifest. Describing community size structure can reveal population dynamics patterns, such as periods of failed recruitment or patterns of colony fission, which have implications for the future sustainability of these ecosystems. However, rapidly and non-invasively measuring coral colony sizes in situ remains a difficult task, as three-dimensional underwater digital reconstruction methods are currently not practical for large numbers of colonies. Two-dimensional (2D) planar area measurements from projection of underwater photographs are a practical size proxy, although this method presents operational difficulties in obtaining well-controlled photographs in the highly rugose environment of the coral reef, and requires extensive time for image processing. Here, we present and test the measurement variance for a method of making rapid planar area estimates of small to medium-sized coral colonies using a lightweight monopod image-framing system and a custom semi-automated image segmentation analysis program. This method demonstrated a coefficient of variation of 2.26 % for repeated measurements in realistic ocean conditions, a level of error appropriate for rapid, inexpensive field studies of coral size structure, inferring change in colony size over time, or measuring bleaching or disease extent of large numbers of individual colonies.

Global climate change and other anthropogenic stressors have heightened the need to rapidly characterize ecological changes in marine benthic communities across large scales. Digital photography enables rapid collection of survey images to meet this need, but the subsequent image annotation is typically a time consuming, manual task. We investigated the feasibility of using automated point-annotation to expedite cover estimation of the 17 dominant benthic categories from survey-images captured at four Pacific coral reefs. Inter- and intra- annotator variability among six human experts was quantified and compared to semi- and fully- automated annotation methods, which are made available at coralnet.ucsd.edu. Our results indicate high expert agreement for identification of coral genera, but lower agreement for algal functional groups, in particular between turf algae and crustose coralline algae. This indicates the need for unequivocal definitions of algal groups, careful training of multiple annotators, and enhanced imaging technology. Semi-automated annotation, where 50% of the annotation decisions were performed automatically, yielded cover estimate errors comparable to those of the human experts. Furthermore, fully-automated annotation yielded rapid, unbiased cover estimates but with increased variance. These results show that automated annotation can increase spatial coverage and decrease time and financial outlay for image-based reef surveys.

Many inflammatory diseases may be linked to pathologically elevated signaling via the receptor for lipopolysaccharide (LPS), toll-like receptor 4 (TLR4). There has thus been great interest in the discovery of TLR4 inhibitors as potential anti-inflammatory agents. Recently, the structure of TLR4 bound to the inhibitor E5564 was solved, raising the possibility that novel TLR4 inhibitors that target the E5564-binding domain could be designed. We utilized a similarity search algorithm in conjunction with a limited screening approach of small molecule libraries to identify compounds that bind to the E5564 site and inhibit TLR4. Our lead compound, C34, is a 2-acetamidopyranoside (MW 389) with the formula C17H27NO9, which inhibited TLR4 in enterocytes and macrophages in vitro, and reduced systemic inflammation in mouse models of endotoxemia and necrotizing enterocolitis. Molecular docking of C34 to the hydrophobic internal pocket of the TLR4 co-receptor MD-2 demonstrated a tight fit, embedding the pyran ring deep inside the pocket. Strikingly, C34 inhibited LPS signaling ex-vivo in human ileum that was resected from infants with necrotizing enterocolitis. These findings identify C34 and the β-anomeric cyclohexyl analog C35 as novel leads for small molecule TLR4 inhibitors that have potential therapeutic benefit for TLR4-mediated inflammatory diseases.

Although pembrolizumab has appeared to be more effective than chemotherapy in patients with lung cancer whose tumors had at least 50% PD-L1–positive cells, nivolumab was not as effective as chemotherapy in patients with lung cancer whose tumors had PD-L1 expression of at least 5%. For the past two decades, platinum-based combination chemotherapy has been the standard-of-care, first-line treatment for patients with advanced non–small-cell lung cancer (NSCLC) without mutations that were sensitive to targeted therapy. 1 , 2 However, chemotherapy has provided only a moderate benefit, with a limited safety profile. In phase 3 clinical trials, the median progression-free survival with platinum-based chemotherapy was 4 to 6 months, and the median overall survival was 10 to 13 months. 3 – 8 In two phase 3 trials, nivolumab, a programmed death 1 (PD-1) immune-checkpoint–inhibitor antibody, resulted in significantly longer overall survival than docetaxel among patients with metastatic NSCLC who had . . .