Enabling conditions for an equitable and sustainable blue economy Cisneros-Montemayor, Andrés M.; Moreno-Baez, Marcia; Reygondeau, Gabriel; Cheung, William W.L.; Crosman, Katherine M.; Gonzalez-Espinosa, Pedro C.; Lam, Vicky W.Y.; Oyinlola, Muhammed A.; Singh, Gerald G.; Swartz, Wilf; Ota, Yoshitaka; Zheng, Chong-Wei
The future of the global ocean economy is currently envisioned as an advancement towards a ‘Blue Economy’—socially equitable, environmentally sustainable, and economically viable ocean industries. However, there are current tensions between development discourses from perspectives of natural capital versus social equity and environmental justice. Here we show there are stark differences in Blue Economy outlooks when social conditions and governance capacity beyond resource availability are considered, and highlight limits to establishing multiple overlapping industries. The key differences in regional capacities to achieve a Blue Economy are not due to available natural resources, but include factors such as national stability, corruption, and infrastructure, that can be improved through targeted investments and cross-scale cooperation. Knowledge gaps can be addressed by integrating historical natural and social science information on the drivers and outcomes of resource use and management, thus identifying equitable pathways to establishing or transforming ocean sectors. Policy-makers must engage researchers and stakeholders to promote evidence-based, collaborative planning that ensures that sectors are chosen carefully, local benefits are prioritized, and the Blue Economy delivers on its social, environmental, and economic goals.; Methods
This dataset presents all results necessary to reproduce the figures and analysis in the corresponding peer-reviewed article. All input data are also included, but any use must give credit to their original authors and sources; we strongly urge users to personally contact corresponding authors. These are specifically noted in the Supplementary Information 3 file of our peer-reviewed article, and include:
Hutchison J, Manica A, Swetnam R, Balmford A, Spalding M (2014) Predicting global patterns in mangrove forest biomass. Conservation Letters 7(3): 233–240. http://data.unep-wcmc.org/datasets/39
McOwen C, Weatherdon LV, Bochove J, Sullivan E, Blyth S, Zockler C, Stanwell- Smith D, Kingston N, Martin CS, Spalding M, Fletcher S (2017). A global map of saltmarshes. Biodiversity Data Journal 5: e11764. http://data.unep-wcmc.org/datasets/43
UNEP-WCMC, Short FT (2016). Global distribution of seagrasses (version 4.0). Fourth update to the data layer used in Green and Short (2003). Cambridge (UK): UNEP World Conservation Monitoring Centre. http://data.unep-wcmc.org/datasets/7
Zheng, C.-W., and Pan, J. 2014. Assessment of the global ocean wind energy resource. Renewable and Sustainable Energy Reviews 33: 382–391. doi:10.1016/j.rser.2014.01.065.
Bonjean F. and G.S.E. Lagerloef, 2002 , Diagnostic model and analysis of the surface currents in the tropical Pacific ocean, J. Phys. Oceanogr., 32, 2,938-2,954 https://podaac.jpl.nasa.gov/dataset/OSCAR_L4_OC_third-deg
General Bathymetric Chart of the Oceans (GEBCO). https://www.bodc.ac.uk/data/documents/nodb/301801/
Wessel, P., and W. H. F. Smith. 1996. A global, self-consistent, hierarchical, high-resolution shoreline database, J. Geophys. Res., 101(B4), 8741–8743, doi:10.1029/96JB00104.
World Tourism Organization (UNWTO). 2018. Yearbook of tourism statistics. Data 2012-2016. UNWTO, Madrid. DOI: https://doi.org/10.18111/9789284419531
Gagné, T. O., Reygondeau, G., Jenkins, C. N., Sexton, J. O., Bograd, S. J., Hazen, E. L., & Van Houtan, K. S. 2020. Towards a global understanding of the drivers of marine and terrestrial biodiversity. PloS one, 15(2), e0228065.
Reygondeau, G. 2019. Current and future biogeography of exploited marine exploited groups under climate change. In: Predicting Future Oceans (pp. 87-101). Elsevier.
Cheung, William W. L., Vicky W. Y. Lam, Jorge L. Sarmiento, Kelly Kearney, Reg Watson, Dirk Zeller, and Daniel Pauly. 2010. “Large-Scale Redistribution of Maximum Fisheries Catch Potential in the Global Ocean under Climate Change.” Global Change Biology 16 (1): 24–35. doi:10.1111/j.1365-2486.2009.01995.x
Oyinlola, M.A., Reygondeau, G., Wabnitz, C.C., Troell, M., and Cheung, W.W. 2018. Global estimation of areas with suitable environmental conditions for mariculture species. PLoS One 13(1): e0191086.
The Fund For Peace (FFP). 2018. Fragile States Index. https://fragilestatesindex.org/2018/04/24/fragile-states-index-2018-annual-report/
United Nations Development Programme (UNDP). 2017. Gender Inequality Index. http://hdr.undp.org/en/content/gender-inequality-index-gii
Daniel Kaufmann, Aart Kraay and Massimo Mastruzzi. 2010. The Worldwide Governance Indicators: A Summary of Methodology, Data and Analytical Issues. World Bank Policy Research Working Paper No. 5430. www.govindicators.org
World Bank. 2018. DataBank. https://databank.worldbank.org/data/home
Halpern et al. 2012. An index to assess the health and benefits of the global ocean. Nature 488(7413): 615–620. doi:10.1038/nature11397.; Usage notes
These data are results of an analysis at the global and regional level for an academic paper, and should not be used for other geographic scales or purposes. Assumptions, indicators, data sources, and weighting of indicators must be specifically discussed and selected in context for results to be meaningful. Please contact the corresponding author (email@example.com) if you have any questions.