Tongan socio-environmental spatial layers for marine ecosystem management
Smallhorn-West, Patrick F., Sophie E. Gordon, Alexandra C. Dempsey, Sam J. Purkis, Siola’a Malimali, Tu’ikolongahau Halafihi, Paul C. Southgate, Tom C. L. Bridge, Robert L. Pressey, and Geoffrey P. Jones. Tongan socio-environmental spatial layers for marine. ecosystem management. Pacific Conservation Biology. 26, 1–7. (2020)
Environmental conditions and anthropogenic impacts are key influences on ecological processes and associated ecosystem services. Effective management of Tonga’s marine ecosystems therefore depends on accurate and up-to-date knowledge of environmental and anthropogenic variables. Although many types of environmental and anthropogenic data are now available in global layers, they are often inaccessible to end users, particularly in developing countries with limited accessibility and analytical training. Furthermore, the resolution of many global layers might not be sufficient to make informed local decisions. Although the near-shore marine ecosystem of Tonga is extensive, the resources available for its management are limited, and little is known about its current ecological state. Here we provide a marine socio-environmental dataset covering Tonga’s near-shore marine ecosystem as compiled from various global layers, remote sensing projects, local ministries, and the 2016 national census. The dataset consists of 11 environmental and 6 anthropogenic variables summarised in ecologically relevant ways, spatially overlaid across the near-shore marine ecosystem of Tonga. The environmental variables selected include bathymetry, coral reef density, distance from deep water, distance from land, distance from major terrestrial inputs, habitat, land area, net primary productivity, salinity, sea surface temperature and wave energy. The anthropogenic variables selected include fishing pressure, management status, distance to fish markets, distance from villages, population pressure and a socioeconomic development index based on population density, growth, mean age, mean education level and unemployment. We hope this extensive and accessible dataset will be a useful tool for future assessment and management of marine ecosystems in Tonga.