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Dataset: Blue Food policy objectives: an analysis of opportunities and trade-offs

Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)

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Title Dataset: Blue Food policy objectives: an analysis of opportunities and trade-offs
 
Identifier https://doi.org/10.7910/DVN/ILA0XI
 
Creator Crona, Beatrice
Jonell, Malin
Koehn, Zachary
Short, Rebecca
Tigchelaar, Michelle
Daw, Tim
Wassénius, Emmy
Golden, Christopher D.
Gephart, Jessica A.
Allison, Edward H.
Bush, Simon R.
Cao, Ling
Cheung, William W.L.
DeClerk, Fabrice
Fanzo, Jessica
Gelcich, Stefan
Kishore, Avinash
Halpern, Benjamin S.
Hicks, Christina C.
Leape, James P.
Little, David C.
Micheli, Fiorenza
Naylor, Rosamond L.
Phillips, Michael
Selig, Elizabeth R.
Springmann, Marco
Sumaila, Rashid U.
Troell, Max
Thilsted, Shakuntala H.
Wabnitz, Colette
 
Publisher Harvard Dataverse
 
Description The paper "Blue Food policy objectives: an analysis of opportunities and trade-offs" integrates the findings of an initiative to assess the multiple roles of blue foods in food systems worldwide (https://www.bluefood.earth/) and translates them into four policy objectives aimed at realizing the contributions of aquatic foods to more nutritious, just, resilient and environmentally sustainable food systems. This dataset contains the variables used to assess conditions (at the level of nations) when blue food policy objectives are likely to be relevant. The R code used for Boolean analysis is available here: https://github.com/emmywas/BFA_Policy_analysis
 
Subject Earth and Environmental Sciences
Other
sustainability
food system
food policy
blue foods
 
Language English
 
Contributor Maniatakou, Sofia
Crona, Beatrice
Wassénius, Emmy
 
Type aggregate data; national statistics data
 
Source Data sources for each variable used in the analysis:
1. Golden, C. D. et al. Aquatic Foods for Nourishing Nations. Nature Accepted, (2021).
2. FAO. Fishery and Aquaculture Statistics. Global capture production 1950 - 2019 (FishstatJ). (2021).
3. Smith, M. R., Micha, R., Golden, C. D., Mozaffarian, D. & Myers, S. S. Global expanded nutrient supply (GENuS) model: A new method for estimating the global dietary supply of nutrients. PLoS One 11, (2016).
4. WHO. Global health estimates: Leading causes of DALYs. Available at: https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates/global-health-estimates-leading-causes-of-dalys. (Accessed: 3rd September 2021)
5. Funge-Smith, S. & Bennett, A. A fresh look at inland fisheries and their role in food security and livelihoods. Fish Fish. 20, 1176–1195 (2019).
6. Teh, L. C. L. & Sumaila, U. R. Contribution of marine fisheries to worldwide employment. Fish Fish. 14, 77–88 (2013).
7. FAO. FAO Yearbook. Fishery and Aquaculture Statistics 2018.
8. ILO. ILOSTAT labour statistics. (2020). Available at: https://ilostat.ilo.org/. (Accessed: 3rd September 2021)
9. World Bank. World Development Indicators | DataBank. (2012). Available at: https://databank.worldbank.org/reports.aspx?source=world-development-indicators. (Accessed: 3rd September 2021)
10. FAO. FAOSTAT Food Balances. Available at: http://www.fao.org/faostat/en/#data/FBS. (Accessed: 3rd September 2021)
11. Tigchelaar, M. et al. Compound climate risks threaten aquatic food benefits. Nat. Food Accepted, (2021).