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Research May Also Help Determine Effects of Global Warming in the Region.

A new project focussing on Sustainable Oceans, Livelihoods and food Security Through Increased Capacity in Ecosystem research (SOLSTICE), aims to strengthen the ability of the nine Western Indian Ocean nations to address the challenges of sustainable management of marine resources.

From large- to small-scale, the country's already-struggling fishing industry has been derailed by a sudden lockdown, jeopardizing lives, livelihoods, and food security.

The food and nutrient security of billions of people worldwide depend on fish being treated as a domestic public health asset instead of a commodity.

Coastal upwelling is an oceanographic process that brings cold, nutrient-rich waters to the ocean surface from depth. These nutrient-rich waters help drive primary productivity which forms the foundation of ecological systems and the fisheries dependent on them. Although coastal upwelling systems of the Western Indian Ocean (WIO) are seasonal (i.e., only present for part of the year) with large variability driving strong fluctuations in fish catch, they sustain food security and livelihoods for millions of people via small-scale (subsistence and artisanal) fisheries. Due to the socio-economic importance of these systems, an "Upwelling Watch" analysis is proposed, for producing updates/alerts on upwelling presence and extremes. We propose a methodology for the detection of coastal upwelling using remotely-sensed daily chlorophyll-a and Sea Surface Temperature (SST) data. An unsupervised machine learning approach, K-means clustering, is used to detect upwelling areas off the Somali coast (WIO), where the Somali upwelling - regarded as the largest in the WIO and the fifth most important upwelling system globally - takes place. This automatic detection approach successfully delineates the upwelling core and surrounds, as well as non-upwelling ocean regions. The technique is shown to be robust with accurate classification of out-of-sample data (i.e., data not used for training the detection model). Once upwelling regions have been identified, the classification of extreme upwelling events was performed using confidence intervals derived from the full remote sensing record. This work has shown promise within the Somali upwelling system with aims to expand it to the rest of the WIO upwellings. This upwelling detection and classification method can aid fisheries management and also provide broader scientific insights into the functioning of these important oceanographic features.

A new study indicates that severe monsoon failure in the Indian subcontinent is more likely under the current global warming scenario.

Deep reefs below 30 m provide essential ecosystem services for ocean health and human well-being such as food security and climate change resilience. Yet, deep reefs remain poorly researched and largely unprotected, including in the Western Indian Ocean (WIO). Here, we assessed current conservation approaches in the WIO focusing on deep reefs, using a combination of online surveys and semi-structured interviews. Results indicated that deep-reef data are sparse and commonly stemming from non-peer-reviewed or non-publicly available sources, and are often not used to inform conservation of WIO marine protected areas. Based on those findings, we co-developed a framework with WIO stakeholders comprising recommendations linked to specific actions to be undertaken by regional actors to improve the capacity of the region to collect and share deep-reef information. We hope this framework will enhance deep-reef stewardship and management throughout the WIO and thus aid sustainable blue economic growth in the region.