scholarly journals High-resolution modeling of thermal thresholds and multiple environmental influences on coral bleaching for regional and local reef managements

2017 ◽  
Author(s):  
Naoki H. Kumagai ◽  
Hiroya Yamano ◽  
Keyword(s):  
High Resolution ◽  
Uv Radiation ◽  
Coral Bleaching ◽  
Environmental Influences ◽  
Thermal Indices ◽  
Water Turbidity ◽  
Thermal Index ◽  
Thermal Thresholds ◽  
Cooling Effects ◽  
Global And Local

AbstractCorals are one of the communities most threatened by global and local stressors. Excessive summer sea temperatures can cause coral bleaching, resulting in decreases in living coral coverage. Coral bleaching may begin with rising sea temperatures, although the widely used threshold of 1 °C over the local climatological maximum sea temperature has been reconsidered. In this study, we refine thermal indices predicting coral bleaching at high resolution (1 km) by statistically optimizing the thermal threshold and multiple environmental influences on bleaching, such as ultraviolet (UV) radiation, water turbidity, and cooling effects on corals. We use a dataset of coral bleaching events observed during 2004–2016 in Japan derived from the Web-based monitoring system, the Sango (Coral) Map Project, aiming at regional to local conservation of Japanese corals. We show how the ability to predict coral bleaching is improved by the choice of thermal index, statistical optimization of thermal thresholds, usage of multiple environmental influences, and modeling methods (generalized linear model and random forest). After optimization, the differences among the thermal indices in the ability to predict coral bleaching were slight. Among environmental influences, cooling effects, UV radiation, and water turbidity, in addition to a thermal index, well explain the occurrence of coral bleaching. Prediction based on the best explanatory model reveals that recent Japanese coral reefs are experiencing bleaching in many areas, although we show a practical way to reduce bleaching frequency significantly by screening UV radiation. Thus, our high-resolution models may provide a quantitative basis for the management of local reefs under current global and local stressors. The results of this study may be useful to other researchers for selecting a predictive method according to their needs or skills.

scholarly journals High-resolution modeling of thermal thresholds and environmental influences on coral bleaching for local and regional reef management

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e4382 ◽  
Author(s):  
Naoki H. Kumagai ◽  
Hiroya Yamano ◽  
Keyword(s):  
Coral Reefs ◽  
Uv Radiation ◽  
Coral Bleaching ◽  
Coral Cover ◽  
Environmental Influences ◽  
Thermal Indices ◽  
Reef Management ◽  
Water Turbidity ◽  
Thermal Thresholds ◽  
Cooling Effects

Coral reefs are one of the world’s most threatened ecosystems, with global and local stressors contributing to their decline. Excessive sea-surface temperatures (SSTs) can cause coral bleaching, resulting in coral death and decreases in coral cover. A SST threshold of 1 °C over the climatological maximum is widely used to predict coral bleaching. In this study, we refined thermal indices predicting coral bleaching at high-spatial resolution (1 km) by statistically optimizing thermal thresholds, as well as considering other environmental influences on bleaching such as ultraviolet (UV) radiation, water turbidity, and cooling effects. We used a coral bleaching dataset derived from the web-based monitoring system Sango Map Project, at scales appropriate for the local and regional conservation of Japanese coral reefs. We recorded coral bleaching events in the years 2004–2016 in Japan. We revealed the influence of multiple factors on the ability to predict coral bleaching, including selection of thermal indices, statistical optimization of thermal thresholds, quantification of multiple environmental influences, and use of multiple modeling methods (generalized linear models and random forests). After optimization, differences in predictive ability among thermal indices were negligible. Thermal index, UV radiation, water turbidity, and cooling effects were important predictors of the occurrence of coral bleaching. Predictions based on the best model revealed that coral reefs in Japan have experienced recent and widespread bleaching. A practical method to reduce bleaching frequency by screening UV radiation was also demonstrated in this paper.

scholarly journals Marine Heatwaves Exceed Cardiac Thermal Limits of Adult Sparid Fish (Diplodus capensis, Smith 1884)

2021 ◽  
Vol 8 ◽  
Author(s):  
Kerry-Ann van der Walt ◽  
Warren M. Potts ◽  
Francesca Porri ◽  
Alexander C. Winkler ◽  
Murray I. Duncan ◽  
...  
Keyword(s):  
Heart Rate ◽  
East Coast ◽  
Reaction Rates ◽  
Range Limit ◽  
Thermal Indices ◽  
Thermal Thresholds ◽  
Thermal Limits ◽  
Relative Change ◽  
Warm Temperate ◽  
Established Technique

Climate change not only drives increases in global mean ocean temperatures, but also in the intensity and duration of marine heatwaves (MHWs), with potentially deleterious effects on local fishes. A first step to assess the vulnerability of fishes to MHWs is to quantify their upper thermal thresholds and contrast these limits against current and future ocean temperatures during such heating events. Heart failure is considered a primary mechanism governing the upper thermal limits of fishes and begins to occur at temperatures where heart rate fails to keep pace with thermal dependency of reaction rates. This point is identified by estimating the Arrhenius breakpoint temperature (TAB), which is the temperature where maximum heart rate (fHmax) first deviates from its exponential increase with temperature and the incremental Q10 breakpoint temperature (TQB), which is where the Q10 temperature coefficient (relative change in heart rate for a 10°C increase in temperature) for fHmax abruptly decreases during acute warming. Here we determined TAB, TQB and the temperature that causes cardiac arrhythmia (TARR) in adults of the marine sparid, Diplodus capensis, using an established technique. Using these thermal indices results, we further estimated adult D. capensis vulnerability to contemporary MHWs and increases in ocean temperatures along the warm-temperate south-east coast of South Africa. For the established technique, we stimulated fHmax with atropine and isoproterenol and used internal heart rate loggers to measure fHmax under conditions of acute warming in the laboratory. We estimated average TAB, TQB, and TARR values of 20.8°C, 21.0°C, and 28.3°C. These findings indicate that the physiology of D. capensis will be progressively compromised when temperatures exceed 21.0°C up to a thermal end-point of 28.3°C. Recent MHWs along the warm-temperate south-east coast, furthermore, are already occurring within the TARR threshold (26.6–30.0°C) for cardiac function in adult D. capensis, suggesting that this species may already be physiologically compromised by MHWs. Predicted increases in mean ocean temperatures of a conservative 2.0°C, may further result in adult D. capensis experiencing more frequent MHWs as well as a contraction of the northern range limit of this species as mean summer temperatures exceed the average TARR of 28.3°C.

scholarly journals ReefTemp: An interactive monitoring system for coral bleaching using high-resolution SST and improved stress predictors

2008 ◽  
Vol 35 (5) ◽  
Author(s):  
Jeffrey A. Maynard ◽  
Peter J. Turner ◽  
Kenneth R. N. Anthony ◽  
Andrew H. Baird ◽  
Ray Berkelmans ◽  
...  
Keyword(s):  
High Resolution ◽  
Monitoring System ◽  
Coral Bleaching

scholarly journals Fusion High-Resolution Network for Diagnosing ChestX-ray Images

Electronics ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 190 ◽  
Author(s):  
Zhiwei Huang ◽  
Jinzhao Lin ◽  
Liming Xu ◽  
Huiqian Wang ◽  
Tong Bai ◽  
...  
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
High Resolution ◽  
Convolutional Neural Networks ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Disease Classification ◽  
Deep Convolutional Neural Networks ◽  
Learning Methods ◽  
Global And Local

The application of deep convolutional neural networks (CNN) in the field of medical image processing has attracted extensive attention and demonstrated remarkable progress. An increasing number of deep learning methods have been devoted to classifying ChestX-ray (CXR) images, and most of the existing deep learning methods are based on classic pretrained models, trained by global ChestX-ray images. In this paper, we are interested in diagnosing ChestX-ray images using our proposed Fusion High-Resolution Network (FHRNet). The FHRNet concatenates the global average pooling layers of the global and local feature extractors—it consists of three branch convolutional neural networks and is fine-tuned for thorax disease classification. Compared with the results of other available methods, our experimental results showed that the proposed model yields a better disease classification performance for the ChestX-ray 14 dataset, according to the receiver operating characteristic curve and area-under-the-curve score. An ablation study further confirmed the effectiveness of the global and local branch networks in improving the classification accuracy of thorax diseases.

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