A Generalized Machine Learning Model for Long-Term Coral Reef Monitoring in the Red Sea

Coral reefs, despite covering less than 0.2 % of the ocean floor, harbor approximately 35 % of all known marine species, making their conservation critical. However, coral bleaching, exacerbated by climate change and phenomena such as El Niño, poses a significant threat to these ecosystems. This study focuses on the Red Sea, proposing a generalized machine learning approach to detect and monitor changes in coral reef cover over an 18-year period (2000–2018). Using Landsat 7 and 8 data, a Support Vector Machine (SVM) classifier was trained on depth-invariant indices (DII) derived from the Gulf of Aqaba and validated against ground truth data from Umluj. The classifier was then applied to Al Wajh, demonstrating its robustness across different sites and times. Results indicated a significant decline in coral cover: 11.4 % in the Gulf of Aqaba, 3.4 % in Umluj, and 13.6 % in Al Wajh. This study highlights the importance of continuous monitoring using generalized classifiers to mitigate the impacts of environmental changes on coral reefs

Synergistic Use of Remote Sensing and Modeling for Estimating Net Primary Productivity in the Red Sea With VGPM, Eppley-VGPM, and CbPM Models Intercomparison

Primary productivity (PP) has been recently investigated using remote sensing-based models over quite limited geographical areas of the Red Sea. This work sheds light on how phytoplankton and primary production would react to the effects of global warming in the extreme environment of the Red Sea and, hence, illuminates how similar regions may behave in the context of climate variability. study focuses on using satellite observations to conduct an intercomparison of three net primary production (NPP) models--the vertically generalized production model (VGPM), the Eppley-VGPM, and the carbon-based production model (CbPM)--produced over the Red Sea domain for the 1998-2018 time period. A detailed investigation is conducted using multilinear regression analysis, multivariate visualization, and moving averages correlative analysis to uncover the models\u27 responses to various climate factors. Here, we use the models\u27 eight-day composite and monthly averages compared with satellite-based variables, including chlorophyll-a (Chla), mixed layer depth (MLD), and sea-surface temperature (SST). Seasonal anomalies of NPP are analyzed against different climate indices, namely, the North Pacific Gyre Oscillation (NPGO), the multivariate ENSO Index (MEI), the Pacific Decadal Oscillation (PDO), the North Atlantic Oscillation (NAO), and the Dipole Mode Index (DMI). In our study, only the CbPM showed significant correlations with NPGO, MEI, and PDO, with disagreements relative to the other two NPP models. This can be attributed to the models\u27 connection to oceanographic and atmospheric parameters, as well as the trends in the southern Red Sea, thus calling for further validation efforts

An Assessment of Atmospheric and Meteorological Factors Regulating Red Sea Phytoplankton Growth

This study considers the various factors that regulate nutrients supply in the Red Sea. Multi-sensor observation and reanalysis datasets are used to examine the relationships among dust deposition, sea surface temperature (SST), and wind speed, as they may contribute to anomalous phytoplankton blooms, through time-series and correlation analyses. A positive correlation was found at 0–3 months lag between chlorophyll-a (Chl-a) anomalies and dust anomalies over the Red Sea regions. Dust deposition process was further examined with dust aerosols’ vertical distribution using satellite lidar data. Conversely, a negative correlation was found at 0–3 months lag between SST anomalies and Chl-a that was particularly strong in the southern Red Sea during summertime. The negative relationship between SST and phytoplankton is also evident in the continuously low levels of Chl-a during 2015 to 2016, which were the warmest years in the region on record. The overall positive correlation between wind speed and Chl-a relate to the nutritious water supply from the Gulf of Aden to the southern Red Sea and the vertical mixing encountered in the northern part. Ocean Color Climate Change Initiative (OC-CCI) dataset experience some temporal inconsistencies due to the inclusion of different datasets. We addressed those issues in our analysis with a valid interpretation of these complex relationships

Long-Term NDVI and Recent Vegetation Cover Profiles of Major Offshore Island Nesting Sites of Sea Turtles in Saudi Waters of the Northern Arabian Gulf

Vegetation is an important ecological component of offshore islands in the Arabian Gulf (AG), which maintains long-term resilience of these islands. This is achieved by influencing sediment retention and moisture acquisition via condensation during periods of high humidity and by providing a variety of microhabitats for island fauna. The resilience of offshore islands’ ecosystems in the Saudi waters is important because they host the largest number of nesting hawksbill and green turtles in the AG. This study defines the characteristics and the long-term trends in vegetation cover of the offshore islands used by sea turtles as nesting grounds in the northern AG. To establish a ground-validated baseline for vegetation profiles, a 50 m × 50 m grid system is developed on Karan and Jana islands (Is.) with photo-quadrats taken at each grid intersection. The 1,317 and 444 photo-quadrats, for Karan and Jana Is., respectively, were analyzed for maximum plant height and percent cover of living (green) plants, dead plants, and bare sand. Landsat 7 and 8 satellite top-of-atmosphere reflectance images were used to calculate the Normalized Difference Vegetation Index (NDVI) from 1999 through 2018 to analyze the long-term vegetation profiles of the islands. Monthly rainfall data from five meteorological stations along the Eastern Province of Saudi Arabia and Oceanic Niño Index (ONI) are presented to provide a context of the long-term NDVI time series variability. The ground-validated vegetation profiles provided baseline data during the onset of summer in 2017 and revealed differences in maximum plant height and the extent of living, dead vegetation and sand cover on Jana Is. (28.3 cm, 19.9%, 63.3%, and 16.8%) and Karan Is. (21.7 cm, 20.6%, 48.7%, and 30.7%), respectively. The NDVI data for both islands are grouped into three periods, namely: 2001–2007 - high winter, low summer; 2008–2013 – low winter, low summer; 2014–2018 – irregular high/low winter, low summer. The long-term trend showed a slightly decreasing NDVI when compared in the context of the high NDVI measured for the two islands during the early 2000 s, particularly during the winter time. An extended reduction in winter NDVI was recorded for six years from 2008 to 2013, which coincided with reduced rainfall in the region and prolonged La Niña. Five extreme dips in winter NDVI values coincided with strong (2000, 2008, and 2011) and moderate (2012 and 2018) La Niña events. Long-term vegetation profiles of the offshore islands seemed to be tightly coupled with long-term rainfall patterns

Transcriptomes and expression profiling of deep-sea corals from the Red Sea provide insight into the biology of azooxanthellate corals

Despite the importance of deep-sea corals, our current understanding of their ecology and evolutionis limited due to difficulties in sampling and studying deep-sea environments. Moreover, a recent reevaluation of habitat limitations has been suggested after characterization of deep-sea corals in the Red Sea, where they live at temperatures of above 20 °C at low oxygen concentrations. To gain further insight into the biology of deep-sea corals, we produced reference transcriptomes and studied gene expression of three deep-sea coral species from the Red Sea, i.e. Dendrophyllia sp., Eguchipsammia fistula, and Rhizotrochus typus. Our analyses suggest that deep-sea coral employ mitochondrial hypometabolism and anaerobic glycolysis to manage low oxygen conditions present in the Red Sea. Notably, we found expression of genes related to surface cilia motion that presumably enhance small particle transport rates in the oligotrophic deep-sea environment. This is the first study to characterize transcriptomes and in situ gene expression for deep-sea corals. Our work offers several mechanisms by which deep-sea corals might cope with the distinct environmental conditions present in the Red Sea. As such, our data provides direction for future research and further insight to organismal response of deep sea coral to environmental change and ocean warming.Tis work was supported by King Abdullah University of Science and Technology (KAUST), baseline funds to CRV and Center Competitive Funding (CCF) Program FCC/1/1973-18-01

Cost-Effective Digital Transformation of SMEs through Low-cost Digital Solutions

2023 Low-Cost Digital Solutions for Industrial Automation, LoDiSA 2023 -- 25 September 2023 through 26 September 2023 -- 194731Digital transformation is the process of using digital technologies to enhance business processes. Although digital transformation has become significant for the sustainability of Small and Medium-sized Enterprises (SMEs), they are challenged by the barriers to digitalisation due to their limited resources, and the complexity of equivalent commercial solutions. Low-cost digital solutions are often tailored to meet the requirements of SMEs to initiate their digital transformation. However, there is a lack of studies about the cost-effectiveness of acquiring low-cost digital solutions compared to off-the-shelf commercial tools, particularly for SMEs. This study demonstrates the cost-effectiveness of low-cost digital solutions for SMEs through a real-world case study performed in a sustainable building components manufacturer and off-site construction SME. We developed a low-cost inventory tracking solution using a so-called'Digital Shoestring' approach, which provides a template for designing digital solutions based on low-cost readily available hardware and software components. The time/effort and cost spent on designing and developing the digital solution were compared with potential off-the-shelf commercial inventory tracking solutions. The results showed that the low-cost inventory tracking solution facilitated the digital transformation of the construction SME in a cost-effective manner. Moreover, the inventory tracking solution was tailored based on the user requirements of the SME, thereby making it more suitable for their day-to-day operations. © 2023 IET Conference Proceedings. All rights reserved.UK Research and Innovation, UKRI; University of Cambridge: RG9663

Ocular Surface Symptoms in Veterans Returning From Operation Iraqi Freedom and Operation Enduring Freedom

PURPOSE. To correlate situational exposures and psychiatric disease with self-reported ocular surface symptoms in a younger veteran population involved in Operation Iraqi Freedom and Operation Enduring Freedom (OIF/OEF). METHODS. Cross-sectional study of all veterans evaluated in the OIF/OEF clinic between December 2012 and April 2013 who completed the dry eye questionnaire and screening evaluations for environmental exposures, posttraumatic stress disorder (PTSD), and depression. The main outcome measures were the influence of environmental exposure and psychiatric disease on ocular surface symptoms. RESULTS. Of 115 participants, the average age was 33 years. While overseas, exposure to incinerated waste (odds ratio [OR] 2.67, 95% confidence interval [CI] 1.23–5.81, P = 0.02) and PTSD (OR 2.68, 95% CI 1.23–5.85, P = 0.02) were associated with self-reported ocular surface symptoms. On return to the United States, older age (OR per decade 2.66, 95% CI 1.65–4.31, P = 0.04) was associated with persistent symptoms and incinerated waste was associated with resolution of symptoms (OR 0.25, 95% CI 0.07–0.90, P = 0.04). When evaluating symptom severity, 26% of the responders complained of severe ocular surface symptoms, with PTSD (OR 3.10, 95% CI 1.22–7.88, P = 0.02) and depression (OR 4.28, 95% CI 1.71–10.68, P = 0.002) being significant risk factors for their presence. CONCLUSIONS. PTSD was significantly associated with ocular surface symptoms both abroad and on return to the United States, whereas air pollution in the form of incinerated waste, was correlated with reversible symptoms

Synergistic Use of Remote Sensing and Modeling to Assess an Anomalously High Chlorophyll-a Event during Summer 2015 in the South Central Red Sea

An anomalously high chlorophyll-a (Chl-a) event (\u3e2 mg/m3) during June 2015 in the South Central Red Sea (17.5° to 22°N, 37° to 42°E) was observed using Moderate Resolution Imaging Spectroradiometer (MODIS) data from the Terra and Aqua satellite platforms. This differs from the low Chl-a values (\u3c0.5 mg/m3) usually encountered over the same region during summertime. To assess this anomaly and possible causes, we used a wide range of oceanographical and meteorological datasets, including Chl-a concentrations, sea surface temperature (SST), sea surface height (SSH), mixed layer depth (MLD), ocean current velocity and aerosol optical depth (AOD) obtained from different sensors and models. Findings confirmed this anomalous behavior in the spatial domain using Hovmöller data analysis techniques, while a time series analysis addressed monthly and daily variability. Our analysis suggests that a combination of factors controlling nutrient supply contributed to the anomalous phytoplankton growth. These factors include horizontal transfer of upwelling water through eddy circulation and possible mineral fertilization from atmospheric dust deposition. Coral reefs might have provided extra nutrient supply, yet this is out of the scope of our analysis. We thought that dust deposition from a coastal dust jet event in late June, coinciding with the phytoplankton blooms in the area under investigation, might have also contributed as shown by our AOD findings. However, a lag cross correlation showed a two- month lag between strong dust outbreak and the high Chl-a anomaly. The high Chl-a concentration at the edge of the eddy emphasizes the importance of horizontal advection in fertilizing oligotrophic (nutrient poor) Red Sea waters

DNA barcoding of marine fishes from Saudi Arabian waters of the Gulf

We used the cytochrome oxidase subunit I (coI) gene DNA to barcode 117 endemic Gulf and cosmopolitan Indo–West Pacific fish species belonging to 54 families and 13 orders. Novel DNA barcodes were provided for 18 fish species (Trachinocephalus sp., Nematalosa sp., Herklotsichthys lossei, Upeneus doriae, Trachurus indicus, Apogonichthyoides taeniatus, Verulux cypselurus, Favonigobius sp., Suezichthus gracilis, Sillago sp., Brachirus orientalis, Pegusa sp., Lepidotrigla bispinosa, Lepidotrigla sp., Grammoplites suppositus, Hippichthys sp., Paramonacanthus sp. and Triacanthus sp.). The species delimitation analysis, conducted with Poisson tree processes– Bayesian PTP (PTP–bPTP) and nucleotide-divergence-threshold (NDT) models), found 137 and 119 entities respectively. Overall, NDT method, neighbour-joining species tree and the prior taxonomic assessment provided similar results. Among the 54 families considered, only 10 (Ariommatidae, Ephippidae, Leiognathidae, Nemipteridae, Plotosidae, Pomacanthidae, Pomacentridae, Priacanthidae and Rachycentridae) showed the occurrence of molecular diagnostic pure characters. The DNA barcoding database developed during this study will help ichthyologists to identify and resolve the taxonomic ambiguities they may encounter with the fishes occurring in The Gulf and throughout the region