Algorithms applied for monitoring pelagic Sargassum

Massive arrivals of pelagic Sargassum to the coasts of several countries in the Atlantic Ocean began in 2011. Monitoring the abundance and distribution of Sargassum in the ocean and along the coasts is necessary to understand the phenomena better and develop forecasting products and management protocols. Most Sargassum monitoring has been conducted in the open ocean through traditional remote sensing techniques. However, since the most significant ecologic and socioeconomic impacts occur on the coasts, it is necessary to monitor these macroalgae on nearshore waters and beaches. This manuscript reviews the remote sensing algorithms used in Sargassum observation reported in the last 17 years in more than sixty high-impact scientific publications. The discussion regarding the evolution of the methodologies used for monitoring these macroalgae allowed us to conclude that the synergy generated by incorporating new disciplines like artificial intelligence and citizen science has positively impacted the development of this field. Additionally, the current state-of-the-art methods, the fundamental challenges, and the directions for future research are also discussed

Ground Truthing Sargassum in Satellite Imagery: Assessment of Its Effectiveness as an Early Warning System

Large aggregations of Sargassum, when at sea, provide important habitat for numerous marine species of vertebrates and invertebrates. It is especially important for the young of several species of sea turtles. However, when large aggregations of Sargassum come ashore on beaches frequented by tourist it is often viewed as a nuisance or even a health hazard. It then becomes a burden to beach management and has to be physically removed as quickly as possible. Many Gulf coast beaches suffer from Sargassum accumulation on a regular basis. Timely information on the size and location of the Sargassum habitat is important to developing coastal management plans. Yet, little is known about the spatial and temporal distribution of Sargassum in the Gulf of Mexico. There is no systematic program to assess the distribution of the macroalgae, therefore practical management plans are difficult to execute. In 2008, Gower and King of the Canadian Institute of Ocean Sciences along with Hu of the University of South Florida, using satellite imagery, identified extensive areas of Sargassum in the western Gulf of Mexico. These were not confirmed with ground truthing data. To date ground truthing observations have not been directly compared with the corresponding satellite images to confirm that it was in fact Sargassum, as the satellite images suggested. y building on the information and research methods of Gower and King, current ground truthing data taken from Texas Parks and Wildlife Gulf trawl sampling surveys was analyzed. In addition, shoreline information and imagery was used to substantiate the data derived from current Moderate-resolution Imaging Spectroradiometer (MODIS) Enhanced Floating Algae Index (EFAI) images. As part of the NASA sponsored research project Mapping and Forecasting of Pelagic Sargassum Drift Habitat in the Gulf of Mexico and South Atlantic Bight for Decision Support, NASA satellite MODIS EFAI images provided by Dr. Hu were used to identify and substantiate corresponding floating Sargassum patches in the Gulf of Mexico. Using the most recent advances in technology and NASA satellite remote sensing, knowledge can be obtained that will aid future decision making for addressing Sargassum in the Gulf of Mexico by substantiating the data provided by satellite imagery. Findings from this research may be useful in developing an early warning system that will allow beach managers to respond in a timely manner to Sargassum events

A Site profile of the Chesapeake Bay National Estuarine Research Reserve in Virginia

The purpose of this Site Profile is to review the existing state of knowledge for important geological, physical, chemical and biological components of the York River ecosystem within which the four individual reserve sites of Chesapeake Bay National Estuarine Research Reserve in Virginia (CBNERRVA) are located. It is developed from a combination of literature and field research studies that provide an overall picture of the Reserve in terms of its ecosystem, management, and research needs. It is not designed to be a complete review of all the ecosystem components, but rather it is designed to provide, through a series of reviews, an overview of the York system to students, researchers, resource managers and the general public, and to provide a system context for the individual reserve sites located within the York River estuary. It starts first with an Introduction to the Reserve including its mission and objectives. Next the geological, physical and water quality setting of the individual reserve sites and the overall York River ecosystem are described. Scientific overviews of three important primary producer components and habitats within the region (phytoplankton, wetlands and submerged aquatic vegetation) are presented next. Secondary and higher trophic components (zooplankton, benthos, and fishes) are then reviewed, and finally the principal reptiles, amphibians, birds and mammals that are associated with the local estuarine waters are described. This Site Profile concludes with a description of the Reserve’s ongoing research and monitoring programs, the Reserve goals and strategies, and an overview of research and monitoring needs for the future

A Geospatial Habitat Suitability Model to Determine the Spatial and Temporal Variability of \u3ci\u3eUlva\u3c/i\u3e Blooms in Jamaica Bay, New York

The main objective of this study involves the development of a habitat suitability model for the Ulva genus in Jamaica Bay, New York. This incorporates several steps that were initiated by the selection of the most suitable water quality parameters that facilitate the successful growth of Ulva. These water quality parameters include dissolved oxygen, pH, temperature, salinity, nitrate + nitrite, ammonium, phosphates, dissolved organic nitrogen, dissolved organic carbon, depth and Secchi depth. This water quality data was generated by the Department of Environmental Protection. The Secchi depth and Jamaica Bay bathymetry data were necessary for the calculation of the % light to bottom that has been vital to the development of this model. For model development, inverse distance weighted interpolation was used to generate water quality surfaces. Because Jamaica Bay possesses islands, a modelling challenge is presented. In order to take into account the presence of these islands, polyline data was included in the creation of the IDW surfaces so that hard lines can delineate the water column from the islands. This allowed better water quality analyses to be carried out. After the development of the IDW surfaces, scored ranges and weights were applied so that the more influential and important parameters for Ulva growth such as light, temperature and nutrients were highlighted and given higher weights than the other parameters. After the assignment of the scored ranges and weights using the reclassify and weighted sum tool in ArcGIS, these surfaces were summed to create habitat suitability models. These models were then validated using Ulva biomass data and subsequently, composite bands and iso cluster analysis using ArcGIS Pro. Ulva biomass data were collected in 2012, 2015 and 2017. The 2017 sampling sites that were used in both biomass and satellite imagery analyses were Marine Park, Plumb beach, Big Egg, Cross bay bridge and Norton basin. In the iso cluster and composite band analyses, several band combinations were applied to visualize the algal/phytoplankton content of the bay. The most effective visualizations were obtained from 12-8-3, 12-11-4 and 4-8-11 based on the combined comparisons for both random and non-random analyses for biomass, composite bands and iso clusters. Additionally, for the biomass-model prediction comparisons, there was a 40.6% match rate. However, when biomass data comparisons were combined with that of the iso clusters and the composite bands, the model assessment was increased to 73.4% for 12-8-3 and 70.3% for several other combinations that includes 11-8-2, 12-8-4, 8-3-2, 12-11-4 and 4-8-11. However, for the random point model assessment, there was a 62.4% overall model accuracy for band combination 12-11-4. Overall, the model assessment has shown acceptability based on Holmes et al. (2008): 67-84%, Renken and Mumby (2009): 55-100%, and Zavalas et al. (2014): \u3e70% acceptability scales

11th International Coral Reef Symposium Proceedings

A defining theme of the 11th International Coral Reef Symposium was that the news for coral reef ecosystems are far from encouraging. Climate change happens now much faster than in an ice-age transition, and coral reefs continue to suffer fever-high temperatures as well as sour ocean conditions. Corals may be falling behind, and there appears to be no special silver bullet remedy. Nevertheless, there are hopeful signs that we should not despair. Reef ecosystems respond vigorously to protective measures and alleviation of stress. For concerned scientists, managers, conservationists, stakeholders, students, and citizens, there is a great role to play in continuing to report on the extreme threat that climate change represents to earth’s natural systems. Urgent action is needed to reduce CO2 emissions. In the interim, we can and must buy time for coral reefs through increased protection from sewage, sediment, pollutants, overfishing, development, and other stressors, all of which we know can damage coral health. The time to act is now. The canary in the coral-coal mine is dead, but we still have time to save the miners. We need effective management rooted in solid interdisciplinary science and coupled with stakeholder buy in, working at local, regional, and international scales alongside global efforts to give reefs a chance.https://nsuworks.nova.edu/occ_icrs/1000/thumbnail.jp

Synthesis of new pyrazolium based tunable aryl alkyl ionic liquids and their use in removal of methylene blue from aqueous solution

In this study, two new pyrazolium based tunable aryl alkyl ionic liquids, 2-ethyl-1-(4-methylphenyl)-3,5- dimethylpyrazolium tetrafluoroborate (3a) and 1-(4-methylphenyl)-2-pentyl-3,5-dimethylpyrazolium tetrafluoroborate (3b), were synthesized via three-step reaction and characterized. The removal of methylene blue (MB) from aqueous solution has been investigated using the synthesized salts as an extractant and methylene chloride as a solvent. The obtained results show that MB was extracted from aqueous solution with high extraction efficiency up to 87 % at room temperature at the natural pH of MB solution. The influence of the alkyl chain length on the properties of the salts and their extraction efficiency of MB was investigated