Coastal areas are among the most thermally dynamic environments on Earth. It is now clear that global warming is impacting these ecosystems not only through the unabated rise of average temperature, but also through an increase in variability and stochasticity (e.g. marine heatwaves).

Recent studies by us and others have also highlighted the pivotal role played by spatial and temporal variability in shaping local temperatures, and how this variability can provide (or deprive) organisms with important climate change refugia. However, the extent to which these concepts matter for biodiversity at continental and decadal scales remains largely unaddressed because of a lack of simultaneously detailed and wide coastal temperature and biodiversity datasets. This is in no small part because previous attempts at collecting such coupled datasets over large scales have been hampered by soaring costs and unmanageable complexity. The adoption of technology-aided biodiversity surveying procedures and the employment of a novel, state-of-the-art temperature logging system designed by our group will allow us to bypass most issues encountered by other networks and, crucially, will allow us to rely on the collective efforts of researchers external to this proposal who are already actively engaged in fieldwork throughout the Atlantic, resulting in the largest sustained temperature and biodiversity observation network of its kind in the entire globe. Having just been fully funded for the North Atlantic by the Luso-American Development Foundation (FLAD), the present proposal requests support for its implementation in the South Atlantic. OceanLog will collect high resolution data on coastal temperatures and the abundance of conspicuous key coastal macro-species. Field sites encompass virtually all coastal climates present in the Atlantic, from Svalbard to the Antarctic, along the E and W coasts, and include most oceanic islands. By keeping the number of collaborating teams to a minimum, providing innovative tools and training, ensuring their expertise in the field, and keeping the target dataset simple, collected data will be fully consistent and of high quality. This means that all sites will be directly comparable, allowing for the analysis of even subtle patterns with an unprecedented level of confidence and across multiple scales. We will use in-situ data collected by our temperature loggers to characterize the thermal envelopes occurring in each location and interpret their thermal heterogeneity in light of their specific climatic and oceanographic context. Given its large geographical span, temperature data collected by the network will be ideal to validate satellite-derived estimates of temperature across a series of providers of remote sensed data. Most importantly, we will expand on how temperature shapes species’ distributions, and investigate how thermal refugia contribute to the presence of biodiversity hotspots across a variety of spatial scales and in the context of a changing climate. Understanding the mechanistic links between climate change, thermal refugia, and macro-ecological processes is not a trivial task but has the potential to inform us on the degree to which environmental variability exacerbates or ameliorates the long-term effects of global warming. These data and findings will be invaluable for the forecasting of climate change impacts and the improvement of conservation strategies, not only in the Atlantic basin, but also across the global ocean. Critically, by implementing a simple, robust and low-cost surveying strategy, we are confident most of the sites will be maintained beyond the timeframe of this project, becoming, in essence, climate change sentinels, thus greatly increasing the value-for-money of this proposal. All data outputs will be made fully available to the public, and citizen science opportunities will be explored. As this project will yield a suite of maps depicting areas of thermal sensitivity and redistribution of biological communities across the Atlantic Ocean, assisting environmental managers and policy makers to identify areas/communities that can be used as early warning systems for climate change, it will contribute to the goal 13.3 of the United Nations 2030 Agenda for Sustainable Development.