Methods and measurement variance for field estimations of coral colony planar area using underwater photographs and semi-automated image segmentation.

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.

A contemporary baseline record of the world's coral reefs.

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.

Caribbean massive corals not recovering from repeated thermal stress events during 2005-2013.

Massive coral bleaching events associated with high sea surface temperatures are forecast to become more frequent and severe in the future due to climate change. Monitoring colony recovery from bleaching disturbances over multiyear time frames is important for improving predictions of future coral community changes. However, there are currently few multiyear studies describing long-term outcomes for coral colonies following acute bleaching events. We recorded colony pigmentation and size for bleached and unbleached groups of co-located conspecifics of three major reef-building scleractinian corals (Orbicella franksi, Siderastrea siderea, and Stephanocoenia michelini; n = 198 total) in Bocas del Toro, Panama, during the major 2005 bleaching event and then monitored pigmentation status and changes live tissue colony size for 8 years (2005-2013). Corals that were bleached in 2005 demonstrated markedly different response trajectories compared to unbleached colony groups, with extensive live tissue loss for bleached corals of all species following bleaching, with mean live tissue losses per colony 9 months postbleaching of 26.2% (±5.4 SE) for O. franksi, 35.7% (±4.7 SE) for S. michelini, and 11.2% (±3.9 SE) for S. siderea. Two species, O. franksi and S. michelini, later recovered to net positive growth, which continued until a second thermal stress event in 2010. Following this event, all species again lost tissue, with previously unbleached colony species groups experiencing greater declines than conspecific sample groups, which were previously bleached, indicating a possible positive acclimative response. However, despite this beneficial effect for previously bleached corals, all groups experienced substantial net tissue loss between 2005 and 2013, indicating that many important Caribbean reef-building corals will likely suffer continued tissue loss and may be unable to maintain current benthic coverage when faced with future thermal stress forecast for the region, even with potential benefits from bleaching-related acclimation.

Improving Automated Annotation of Benthic Survey Images Using Wide-band Fluorescence.

Large-scale imaging techniques are used increasingly for ecological surveys. However, manual analysis can be prohibitively expensive, creating a bottleneck between collected images and desired data-products. This bottleneck is particularly severe for benthic surveys, where millions of images are obtained each year. Recent automated annotation methods may provide a solution, but reflectance images do not always contain sufficient information for adequate classification accuracy. In this work, the FluorIS, a low-cost modified consumer camera, was used to capture wide-band wide-field-of-view fluorescence images during a field deployment in Eilat, Israel. The fluorescence images were registered with standard reflectance images, and an automated annotation method based on convolutional neural networks was developed. Our results demonstrate a 22% reduction of classification error-rate when using both images types compared to only using reflectance images. The improvements were large, in particular, for coral reef genera Platygyra, Acropora and Millepora, where classification recall improved by 38%, 33%, and 41%, respectively. We conclude that convolutional neural networks can be used to combine reflectance and fluorescence imagery in order to significantly improve automated annotation accuracy and reduce the manual annotation bottleneck.

Wide field-of-view fluorescence imaging of coral reefs.

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.

Towards Automated Annotation of Benthic Survey Images: Variability of Human Experts and Operational Modes of Automation.

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.