Harnessing big data to support the conservation and rehabilitation of mangrove forests globally

Mangrove forests are found on sheltered coastlines in tropical, subtropical, and some warm temperate regions. These forests support unique biodiversity and provide a range of benefits to coastal communities, but as a result of large-scale conversion for aquaculture, agriculture, and urbanization, mangroves are considered increasingly threatened ecosystems. Scientific advances have led to accurate and comprehensive global datasets on mangrove extent, structure, and condition, and these can support evaluation of ecosystem services and stimulate greater conservation and rehabilitation efforts. To increase the utility and uptake of these products, in this Perspective we provide an overview of these recent and forthcoming global datasets and explore the challenges of translating these new analyses into policy action and on-the-ground conservation. We describe a new platform for visualizing and disseminating these datasets to the global science community, non-governmental organizations, government officials, and rehabilitation practitioners and highlight future directions and collaborations to increase the uptake and impact of large-scale mangrove research. This Perspective reviews the role of global-scale research in stimulating policy action and on-the-ground conservation for mangrove ecosystems. We outline the current state of knowledge in terms of global analyses and examine the challenge of translating this research in action

Fishers who rely on mangroves: Modelling and mapping the global intensity of mangrove-associated fisheries

Mangroves are critical nursery habitats for fish and invertebrates, providing livelihoods for many coastal communities. Despite their importance, there is currently no estimate of the number of fishers engaged in mangrove associated fisheries, nor on the fishing intensity associated with mangroves at a global scale. We address these gaps by developing a global model of mangrove associated fisher numbers and mangrove fishing intensity. To develop the model, we undertook a three-round Delphi process with mangrove fisheries experts to identify the key drivers of mangrove fishing intensity. We then developed a conceptual model of intensity of mangrove fishing using those factors identified both as being important and for which appropriate global data could be found or developed. These factors were non-urban population, distance to market, distance to mangroves and other fishing grounds, and storm events. By projecting this conceptual model using geospatial datasets, we were able to estimate the number and distribution of mangrove associated fishers and the intensity of fishing in mangroves. We estimate there are 4.1 million mangrove associated fishers globally, with the highest number of mangrove fishers found in Indonesia, India, Bangladesh, Myanmar, and Brazil. Mangrove fishing intensity was greatest throughout Asia, and to a lesser extent West and Central Africa, and Central and South America

Fishers who rely on mangroves: Modelling and mapping the global intensity of mangrove-associated fisheries

Mangroves are critical nursery habitats for fish and invertebrates, providing livelihoods for many coastal communities. Despite their importance, there is currently no estimate of the number of fishers engaged in mangrove associated fisheries, nor on the fishing intensity associated with mangroves at a global scale. We address these gaps by developing a global model of mangrove associated fisher numbers and mangrove fishing intensity. To develop the model, we undertook a three-round Delphi process with mangrove fisheries experts to identify the key drivers of mangrove fishing intensity. We then developed a conceptual model of intensity of mangrove fishing using those factors identified both as being important and for which appropriate global data could be found or developed. These factors were non-urban population, distance to market, distance to mangroves and other fishing grounds, and storm events. By projecting this conceptual model using geospatial datasets, we were able to estimate the number and distribution of mangrove associated fishers and the intensity of fishing in mangroves. We estimate there are 4.1 million mangrove associated fishers globally, with the highest number of mangrove fishers found in Indonesia, India, Bangladesh, Myanmar, and Brazil. Mangrove fishing intensity was greatest throughout Asia, and to a lesser extent West and Central Africa, and Central and South America

Mangrove restoration potential: A global map highlighting a critical opportunity

Rapid losses of mangroves over the past 50 years have had negative consequences on the environment, climate, and humanity, through diminished benefits such as carbon storage, coastal protection and fish production. Restoration of mangrove forests is possible, and has already been undertaken in many settings, but such efforts have been piecemeal, and many have failed. The current work describes the findings from a new effort to locate and map, on a global scale, the places where mangroves can be restored, and to calculate the potential benefits from such restoration. As a framework for the study, a new global typology of mangroves has been developed with Mangrove areas classified into deltaic, estuarine, lagoonal and fringing systems, and subsequent analyses based on the resulting 6000 individual typological units. In total, some 8,120 km2, or 6%, of former mangrove area are considered restorable. An expert-derived model for restorability has been developed based on the key environmental components, tidal range; recent sea Level rise; projected future sea level rise; recent change in sediments; time since loss; average size of loss patches; and the proximity of loss areas to remaining mangroves, that influence the ease of restoration. Using this model, some 6,665 km2 are considered highly restorable. The work overlays current and potential mangroves areas with models of ecosystem services to assess potential benefits from restoration, including carbon sequestration in aboveground biomass amounting to 69 million tonnes of carbon, the saving of 296 million tonnes of soil carbon stocks through a combination of avoided emissions and sequestration and the addition of commercial fisheries species in mangrove waters totalling 23 trillion young-of year finfish and 40 trillion crabs, shrimp and molluscs. The output of the work the Mangrove Restoration Potential Map, provides a critical tool for encouraging restoration and enabling robust, data-driven policy changes and investments

Fishers who rely on mangroves : Modelling and mapping the global intensity of mangrove-associated fisheries

Mangroves are critical nursery habitats for fish and invertebrates, providing livelihoods for many coastal communities. Despite their importance, there is currently no estimate of the number of fishers engaged in mangrove associated fisheries, nor of the fishing intensity associated with mangroves at a global scale. We address these gaps by developing a global model of mangrove associated fisher numbers and mangrove fishing intensity. To develop the model, we undertook a three-round Delphi process with mangrove fisheries experts to identify the key drivers of mangrove fishing intensity. We then developed a conceptual model of intensity of mangrove fishing using those factors identified both as being important and for which appropriate global data could be found or developed. These factors were non-urban population, distance to market, distance to mangroves and other fishing grounds, and storm events. By projecting this conceptual model using geospatial datasets, we were able to estimate the number and distribution of mangrove associated fishers and the intensity of fishing in mangroves. We estimate there are 4.1 million mangrove associated fishers globally, with the highest number of mangrove fishers found in Indonesia, India, Bangladesh, Myanmar, and Brazil. Mangrove fishing intensity was greatest throughout Asia, and to a lesser extent West and Central Africa, and Central and South America