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Dynamics of the Bering Sea is a valuable resource for scientists, students, and managers working in the Bering Sea and similar ecosystems worldwide. The international scientific organization PICES has successfully brought together the findings of scientists, of many disciplines and countries, to provide a perspective on physical, chemical, and biological research on the Bering Sea, one of the world's most productive ecosystems.
Oceans account for 50% of the anthropogenic CO2 released into the atmosphere. During the past 15 years an international programme, the Joint Global Ocean Flux Study (JGOFS), has been studying the ocean carbon cycle to quantify and model the biological and physical processes whereby CO2 is pumped from the ocean's surface to the depths of the ocean, where it can remain for hundreds of years. This project is one of the largest multi-disciplinary studies of the oceans ever carried out and this book synthesises the results. It covers all aspects of the topic ranging from air-sea exchange with CO2, the role of physical mixing, the uptake of CO2 by marine algae, the fluxes of carbon and nitrogen through the marine food chain to the subsequent export of carbon to the depths of the ocean. Special emphasis is laid on predicting future climatic change.
This Research Topic is the second volume of this collection. You can find the original collection via https://www.frontiersin.org/research-topics/45485/deep-learning-for-marine-science Deep learning (DL) is a critical research branch in the fields of artificial intelligence and machine learning, encompassing various technologies such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), Transformer networks and Diffusion models, as well as self-supervised learning (SSL) and reinforcement learning (RL). These technologies have been successfully applied to scientific research and numerous aspects of daily life. With the continuous advancements in oceanographic observation equipment and technology, there has been an explosive growth of ocean data, propelling marine science into the era of big data. As effective tools for processing and analyzing large-scale ocean data, DL techniques have great potential and broad application prospects in marine science. Applying DL to intelligent analysis and exploration of research data in marine science can provide crucial support for various domains, including meteorology and climate, environment and ecology, biology, energy, as well as physical and chemical interactions. Despite the significant progress in DL, its application to the aforementioned marine science domains is still in its early stages, necessitating the full utilization and continuous exploration of representative applications and best practices.
Fire-derived organic matter, also known as pyrogenic carbon (PyC), is ubiquitous on Earth. It can be found in soils, sediments, water and air. In this wide range of environments, fire-derived organic matter, represents a key component of the organic matter pool, and, in many cases, the largest identifiable group of organic compounds. PyC is also one of the most persistent organic matter fractions in the ecosystems, and its study is, therefore, particularly relevant for the global carbon cycle. From its production during vegetation fires to its transfer into soils, sediments and waters, PyC goes through different transformations, both abiotic and biotic. Contrary to early assumptions, PyC is not inert and interacts strongly with the environment: evidence of microbial decomposition, oxidation patterns and interactions with minerals have been described in different matrices. PyC travels across these different environments and it is modified chemically and physically, but remains persistent. This Research Topic explores important questions in our understanding of fire-derived organic matter, from the characterization and quantification of PyC components, to the transformation and mobilization processes taking place on terrestrial and aquatic ecosystems. The studies compiled here provide novel and, often, unexpected results. They all answer some of the questions posed and, more importantly, provide scope for many more.
The Pacific Arctic region is experiencing rapid sea ice retreat, seawater warming, ocean acidification and biological response. Physical and biogeochemical modeling indicates the potential for step-function changes to the overall marine ecosystem. This synthesis book was coordinated within the Pacific Arctic Group, a network of international partners working in the Pacific Arctic. Chapter topics range from atmospheric and physical sciences to chemical processing and biological response to changing environmental conditions. Physical and biogeochemical modeling results highlight the need for data collection and interdisciplinary modeling activities to track and forecast the changing ecosystem of the Pacific Arctic with climate change.