AIMC Topic: Coral Reefs

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A low-cost, long-term underwater camera trap network coupled with deep residual learning image analysis.

PloS one
Understanding long-term trends in marine ecosystems requires accurate and repeatable counts of fishes and other aquatic organisms on spatial and temporal scales that are difficult or impossible to achieve with diver-based surveys. Long-term, spatiall...

Automated classification of three-dimensional reconstructions of coral reefs using convolutional neural networks.

PloS one
Coral reefs are biologically diverse and structurally complex ecosystems, which have been severally affected by human actions. Consequently, there is a need for rapid ecological assessment of coral reefs, but current approaches require time consuming...

A Dexterous, Glove-Based Teleoperable Low-Power Soft Robotic Arm for Delicate Deep-Sea Biological Exploration.

Scientific reports
Modern marine biologists seeking to study or interact with deep-sea organisms are confronted with few options beyond industrial robotic arms, claws, and suction samplers. This limits biological interactions to a subset of "rugged" and mostly immotile...

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

Sensors (Basel, Switzerland)
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 pap...

Mapping of the corals around Hendorabi Island (Persian Gulf), using WorldView-2 standard imagery coupled with field observations.

Marine pollution bulletin
High spatial resolution WorldView-2 (WV2) satellite imagery coupled with field observations have been utilized for mapping the coral reefs around Hendorabi Island in the northern Persian Gulf. In doing so, three standard multispectral bands (red, gre...

Using tropical reef, bird and unrelated sounds for superior transfer learning in marine bioacoustics.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences
Machine learning has the potential to revolutionize passive acoustic monitoring (PAM) for ecological assessments. However, high annotation and computing costs limit the field's adoption. Generalizable pretrained networks can overcome these costs, but...

Quantifying the impact of future climate change on the risk of coral rubble instability across the Great Barrier Reef by 2100.

Journal of environmental management
Coral reef systems are facing unprecedented pressures due to climate change, and stable coral rubble substrates are crucial for facilitating large-scale coral regeneration. This study integrates the Sixth Phase of the Coupled Model Intercomparison Pr...

Rapid detection of fish calls within diverse coral reef soundscapes using a convolutional neural networka).

The Journal of the Acoustical Society of America
The quantity of passive acoustic data collected in marine environments is rapidly expanding; however, the software developments required to meaningfully process large volumes of soundscape data have lagged behind. A significant bottleneck in the anal...

Identification of putative coral pathogens in endangered Caribbean staghorn coral using machine learning.

Environmental microbiology
Coral diseases contribute to the rapid decline in coral reefs worldwide, and yet coral bacterial pathogens have proved difficult to identify because 16S rRNA gene surveys typically identify tens to hundreds of disease-associate bacteria as putative p...

Parsing human and biophysical drivers of coral reef regimes.

Proceedings. Biological sciences
Coral reefs worldwide face unprecedented cumulative anthropogenic effects of interacting local human pressures, global climate change and distal social processes. Reefs are also bound by the natural biophysical environment within which they exist. In...