Tongan socio-environmental spatial layers for marine ecosystem management
Patrick F. Smallhorn-West A B C J , Sophie E. Gordon D , Alexandra C. Dempsey E , Sam J. Purkis E F , Siola’a Malimali G , Tu’ikolongahau Halafihi G , Paul C. Southgate D H , Tom C. L. Bridge B I , Robert L. Pressey B and Geoffrey P. Jones A BA Marine Biology and Aquaculture, College of Science and Engineering, James Cook University, Townsville, Qld 4811, Australia.
B Australian Research Council Centre of Excellence for Coral Reef Studies, James Cook University, Townsville, Qld 4811, Australia.
C WorldFish, Jalan Batu Maung, 11960, Bayan Lepas, Penang, Malaysia.
D School of Science and Engineering, University of the Sunshine Coast, 90 Sippy Downs Drive, Sippy Downs, Qld 4556, Australia.
E Khaled bin Sultan Living Oceans Foundation, Annapolis, MD 21403, USA.
F CSL – Center for Carbonate Research, Department of Marine Geosciences, Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, FL 33149, USA.
G Ministry of Fisheries, Nuku’alofa, Tongatapu, Tonga.
H Australian Centre for Pacific Islands Research and School of Science and Engineering, University of the Sunshine Coast, 90 Sippy Downs Drive, Sippy Downs, Qld 4556, Australia.
I Biodiversity and Geosciences Program, Museum of Tropical Queensland, Queensland Museum Network, Townsville, Qld, 4810, Australia.
J Corresponding author. Email: patricksmallhornwest@jcu.edu.au
Pacific Conservation Biology - https://doi.org/10.1071/PC19032
Submitted: 15 August 2019 Accepted: 7 July 2020 Published online: 12 August 2020
Abstract
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.
Additional keywords: coral reefs, human impacts, marine spatial ecology, remote sensing, South Pacific.
References
Allen Coral Atlas (2019). Coral reefs revealed. Available at www.allencoralatlas.org [Verified 9 July 2020].Andrefouet, S., Muller-Karger, F. E., Robinson, J. A., Kranenburg, C. J., Torres-Pulliza, D., Spraggins, S. A., and Murch, B. (2006). Global assessment of modern coral reef extent and diversity for regional science and management applications: a view from space. In ‘Proceedings of the 10th International Coral Reef Symposium. Vol. 2’. pp. 1732–1745. (Japanese Coral Reef Society: Okinawa, Japan.)
Bradbury, R. H., and Young, P. C. (1981). The effects of a major forcing function, wave energy, on a coral reef ecosystem. Marine Ecology Progress Series 5, 229–241.
| The effects of a major forcing function, wave energy, on a coral reef ecosystem.Crossref | GoogleScholarGoogle Scholar |
Cinner, J. E., Graham, N. A., Huchery, C., and MacNeil, M. A. (2013). Global effects of local human population density and distance to markets on the condition of coral reef fisheries. Conservation Biology 27, 453–458.
| Global effects of local human population density and distance to markets on the condition of coral reef fisheries.Crossref | GoogleScholarGoogle Scholar | 23025334PubMed |
Cinner, J. E., Maire, E., Huchery, C., MacNeil, M. A., Graham, N. A., Mora, C., McClanahan, T. R., Barnes, M. L., Kittinger, J. N., Hicks, C. C., and D’agata, S. (2018). Gravity of human impacts mediates coral reef conservation gains. Proceedings of the National Academy of Sciences of the United States of America 115, E6116–E6125.
| Gravity of human impacts mediates coral reef conservation gains.Crossref | GoogleScholarGoogle Scholar | 29915066PubMed |
Dapueto, G., Massa, F., Costa, S., Cimoli, L., Olivari, E., Chiantore, M., Federici, B., and Povero, P. (2015). A spatial multi-criteria evaluation for site selection of offshore marine fish farm in the Ligurian Sea, Italy. Ocean and Coastal Management 116, 64–77.
| A spatial multi-criteria evaluation for site selection of offshore marine fish farm in the Ligurian Sea, Italy.Crossref | GoogleScholarGoogle Scholar |
de Novaes Vianna, L. F., and Bonetti Filho, J. (2018). Spatial analysis for site selection in marine aquaculture: an ecosystem approach applied to Baía Sul, Santa Catarina, Brazil. Aquaculture 489, 162–174.
| Spatial analysis for site selection in marine aquaculture: an ecosystem approach applied to Baía Sul, Santa Catarina, Brazil.Crossref | GoogleScholarGoogle Scholar |
Gassner, P., Westerveld, L., Fonua, E., Takau, L., Matoto, A. L., Kula, T., Macmillan-Lawler, M., Davey, K., Baker, E., Clark, M., Kaitu’u, J., Wendt, H., and Fernandes, L. (2019). ‘Marine atlas. Maximizing benefits for Tonga.’ (Marine and Coastal Biodiversity Management in Pacific Island Countries (MACBIO): Suva, Fiji.)
Gillett, R. (2017). A review of special management areas in Tonga. (FAO Fisheries and Aquaculture Circular No. 1137: Apia, Samoa).
Govan, H. (2015). ‘Area-based management tools for coastal resources in Fiji, Kiribati, Solomon Islands, Tonga And Vanuatu.’ (Marine and Coastal Biodiversity Management in Pacific Island Countries (MACBIO) project, Suva, Fiji.)
Gordon, S. E, Wingfield, M., Kurtböke, D. I., and Southgate, P. C. (2019). Effects of nucleus position, profile and arrangement on the quality of mabé pearls produced by the winged pearl oyster, Pteria penguin. Aquaculture 498, 109–115.
Gordon, S. E., Ngaluafe, P., Wingfield, M., and Southgate, P. C. (2017). Morphometric relationships and shell form of cultured winged pearl oysters (Pteria penguin) in Tonga. Journal of Shellfish Research 36, 677–682.
Government of Tonga and the Secretariat of the Pacific Community (2009). Joint Country Strategy 2009-2013: in support of Tonga’s strategic development plan 9. (Secretariat of the Pacific Community: Noumea, New Caledonia)
Graus, R. R., and Macintyre, I. G. (1989). The zonation patterns of Caribbean coral reefs as controlled by wave and light energy input, bathymetric setting and reef morphology: computer simulation experiments. Coral Reefs 8, 9–18.
| The zonation patterns of Caribbean coral reefs as controlled by wave and light energy input, bathymetric setting and reef morphology: computer simulation experiments.Crossref | GoogleScholarGoogle Scholar |
Hartmann, K., Wettle, M., Bindel, M., and Field, D. (2018). Satellite derived bathymetry survey report. Project number: HYD-2017-18-01 (HS60). (Land Information New Zealand, Wellington, New Zealand.
Hughes, T. P., Kerry, J. T., Álvarez-Noriega, M., Álvarez-Romero, J. G., Anderson, K. D., Baird, A. H., Babcock, R. C., Beger, M., Bellwood, D. R., Berkelmans, R., and Bridge, T. C. (2017a). Global warming and recurrent mass bleaching of corals. Nature 543, 373–377.
| Global warming and recurrent mass bleaching of corals.Crossref | GoogleScholarGoogle Scholar | 28300113PubMed |
Hughes, T. P., Barnes, M. L., Bellwood, D. R., Cinner, J. E., Cumming, G. S., Jackson, J. B., Kleypas, J., Van De Leemput, I. A., Lough, J. M., Morrison, T. H., Palumbi, S. R., van Nesm, E. H., and Scheffer, M. (2017b). Coral reefs in the Anthropocene. Nature 546, 82–90.
| Coral reefs in the Anthropocene.Crossref | GoogleScholarGoogle Scholar | 28569801PubMed |
Jenness, J., and Houk, P. (2014). UOGML Wave Energy ArcGIS Extension. (University of Guam Marine Laboratory: Mangilao).
Moore, B., and Malimali, S. (2016). Joint country strategy 2009–2013: in support of Tonga’s strategic development plan 9, 2009–2013. Prepared by the Government of Tonga and the Secretariat of the Pacific Community. Demographic assessment of exploited coastal finfish species of Tongatapu, Tonga. SPC.
Purkis, S. J. (2018). Remote sensing tropical coral reefs: the view from above. Annual Review of Marine Science 10, 149–168.
| Remote sensing tropical coral reefs: the view from above.Crossref | GoogleScholarGoogle Scholar | 28793810PubMed |
Purkis, S. J., Gleason, A. C., Purkis, C. R., Dempsey, A. C., Renaud, P. G., Faisal, M., Saul, S., and Kerr, J. M. (2019). High-resolution habitat and bathymetry maps for 65,000 sq. km of Earth’s remotest coral reefs. Coral Reefs 38, 467–488.
| High-resolution habitat and bathymetry maps for 65,000 sq. km of Earth’s remotest coral reefs.Crossref | GoogleScholarGoogle Scholar |
Radiarta, I. N., Saitoh, S. I., and Miyazono, A. (2008). GIS-based multi-criteria evaluation models for identifying suitable sites for Japanese scallop (Mizuhopecten yessoensis) aquaculture in Funka Bay, southwestern Hokkaido, Japan. Aquaculture 284, 127–135.
| GIS-based multi-criteria evaluation models for identifying suitable sites for Japanese scallop (Mizuhopecten yessoensis) aquaculture in Funka Bay, southwestern Hokkaido, Japan.Crossref | GoogleScholarGoogle Scholar |
Sbrocco, E. J., and Barber, P. H. (2013). MARSPEC: ocean climate layers for marine spatial ecology: ecological archives E094‐086. Ecology 94, 979.
| MARSPEC: ocean climate layers for marine spatial ecology: ecological archives E094‐086.Crossref | GoogleScholarGoogle Scholar |
Smallhorn‐West, P. F., Bridge, T. C., Malimali, S. A., Pressey, R. L., and Jones, G. P. (2019). Predicting impact to assess the efficacy of community‐based marine reserve design. Conservation Letters 12, e12602.
| Predicting impact to assess the efficacy of community‐based marine reserve design.Crossref | GoogleScholarGoogle Scholar |
Smallhorn‐West, P. F., Sheehan, J., Malimali, S. A., Halafihi, T., Bridge, T. C., Pressey, R. L., and Jones, G. P. (2020). Incentivizing co‐management for impact: mechanisms driving the successful national expansion of Tonga’s special management area program. Conservation Letters 13, e12742.
| Incentivizing co‐management for impact: mechanisms driving the successful national expansion of Tonga’s special management area program.Crossref | GoogleScholarGoogle Scholar |
Statistics Department of Tonga (2016). ‘Tonga national population and housing census.’ (Tongan Bureau of Statistics: Nuku’alofa, Tonga)
Stone, K., Fenner, D., LeBlanc, D., Vaisey, B., Purcell, I., and Eliason, B. (2019). Tonga. In ‘World seas: an environmental evaluation’. pp. 661–678. (Academic Press: New York, NY, USA.)
The Kingdom of Tonga (2017) Tonga Fisheries Sector Plan. (Tonga Ministry of Fisheries: Nuku’alofa).
Kingdom of Tonga’s Fifth National Report to the Convention on Biological Diversity (2014) (The Kingdom of Tonga: Nuku’alofa).
Yeager, L. A., Marchand, P., Gill, D. A., Baum, J. K., and McPherson, J. M. (2017). Marine socio‐environmental covariates: queryable global layers of environmental and anthropogenic variables for marine ecosystem studies. Ecology 98, 1976.
| Marine socio‐environmental covariates: queryable global layers of environmental and anthropogenic variables for marine ecosystem studies.Crossref | GoogleScholarGoogle Scholar | 28466482PubMed |