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Tytuł artykułu

Is there a relationship between human development and dependence on fisheries?

Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
International food and raw material security issueshas gained much more importance than ever. This studyexamines that the following questions ‘Who depends onwhom?’ and ‘What is the level of dependency?’ consideringrelationships between “fisheries context” (catch andaquaculture production, total fisheries export and import,fisheries export and import value, fish consumption percapita, and processed fisheries product) and humandevelopment of countries (as Human DevelopmentIndex-HDI). The overall result of the study pointed thatthe countries located in the highest categories in terms ofHDI were both export and import-dependent. The mostimportance levels of dependency for the Low DevelopedCountries (HDI < 0.550) were fish consumption, and totalimports; for Medium Developed Countries (0.550 ≤ HDI <0.699) were export value, exports, and catch production;for High Developed Countries (0.699 ≤ HDI <0.80) wastotal exports; for Very High Developed Countries-I (0.80≤ HDI < 0.900) was exports; and for Very High DevelopedCountries-II ( HDI ≥ 0.90) was import value. To improve thehuman development of the countries and maintain thefood security around the world, the following points couldbe suggested: i) to increase the aquaculture productionboth in inland and marine environments where possible,ii) for low and medium developed countries, instead of rawmaterial exporting, to support increasing the productioncapacity of processed fisheries products that have higherglobal market prices.
Rocznik
Strony
245--257
Opis fizyczny
Bibliogr. 42 poz., rys., tab., wykr.
Twórcy
  • İskenderun Technical University, Marine Scienceand Technology Faculty, Türkiye
autor
  • İskenderun Technical University, Marine Scienceand Technology Faculty, Türkiye
autor
  • İskenderun Technical University, Business and Management Sciences Faculty, Türkiy
Bibliografia
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  • [18]. Hastie, T., Tibshirani, R., & Friedman, J. (2009). Unsupervised Learning. In: The Elements of Statistical Learning (pp. 485-585). Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-0-387-84858-7_14
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  • [24]. Lawrence, R. L., & Wright, A. (2001). Rule-based classification systems using classification and regression tree (CART) analysis. Photogrammetric Engineering and Remote Sensing, 67(10), 1137-1142.
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  • [27]. Mazlum, Y., & Can, M. F. (2021). Analysis of Aquaculture Production Trends in OECD and Key Partner Countries. In M. L. Emek (Ed.), Understanding New Cases in Microeconomics: Markets and Industries (pp. 177-204). IKSAD Publishing House.
  • [28]. Merino, G., Barange, M., Blanchard, J. L., Harle, J., Holmes, R., Allen, I., Allison, E. H., Badjeck, M. C., Dulvy, N. K., Holt, J., Jennings, S., Mullon, C., & Rodwell, L. D. (2012). Can marine fisheries and aquaculture meet fish demand from a growing human population in a changing climate? Global Environmental Change, 22(4), 795-806. https://doi.org/10.1016/j.gloenvcha.2012.03.003
  • [29]. Nkurunziza, J., Tsowou, K., & Cazzaniga, S. (2017). Commodity Dependence and Human Development. African Development Review, 29(S1), 27-41. https://doi.org/10.1111/1467-8268.12231
  • [30]. Noorbakhsh, F. (1998). A Modified Human Development Index. World Development, 26(3), 517-528. https://doi.org/10.1016/S0305-750X(97)10063-8
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  • [32]. Pata, U. K., Aydin, M., & Haouas, I. (2021). Are natural resources abundance and human development a solution for environmental pressure? Evidence from top ten countries with the largest ecological footprint. Resources Policy, 70, 101923. https://doi.org/10.1016/j.resourpol.2020.101923
  • [33]. Pathak, S., Mishra, I., & Swetapadma, A. (2018). An assessment of decision tree based classification and regression algorithms. In 2018 3rd International Conference on Inventive Computation Technologies (ICICT) (pp. 92-95). IEEE. https://doi.org/10.1109/ICICT43934.2018.9034296
  • [34]. Pauly, D., & Zeller, D. (2017). Comments on FAOs state of world fisheries and aquaculture (SOFIA 2016). Marine Policy, 77, 176-181. https://doi.org/10.1016/j.marpol.2017.01.006
  • [35]. Ramadona, T., Septya, F., Darwis, Rengi, P., Yanti, C:W. & Darfia, N:E (2021). IOP Conf. Series: Earth and Environmental Science 934 012046 IOP Publishing https://doi.org/10.1088/1755-1315/934/1/012046.
  • [36]. Ross, N. (2013). Exploring concepts of fisheries ‘dependency’and ‘community’in Scotland. Marine Policy, 37, 55-61. https://doi.org/10.1016/j.marpol.2012.04.003
  • [37]. Shrestha, N. (2020). Detecting multicollinearity in regression analysis. American Journal of Applied Mathematics and Statistics, 8(2), 39-42. https://doi.org/10.12691/ajams-8-2-1
  • [38]. Subasinghe, R. (2017). World aquaculture 2015: A brief overview. FAO Fisheries and Aquaculture Circular FIAA/C1140 (En) (1140), 35.
  • [39]. UNDP (United Nations Development Programme). (2022). Human Development Report 2021-22: Uncertain Times, Unsettled Lives: Shaping our Future in a Transforming World. New York.
  • [40]. Williams, G. (2011). Data mining with Rattle and R: The art of excavating data for knowledge discovery. Springer Science & Business Media. https://doi.org/10.1007/978-1-4419-9890-3
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  • [42]. Yarkina, N. N., & Logunova, N. N. (2022). Fisheries and Aquaculture: Implementing Sustainable Development Goals. In Arkhipov, A.G. (eds) Sustainable Fisheries and Aquaculture: Challenges and Prospects for the Blue Bioeconomy(pp. 149-160). Environmental Science and Engineering. Springer.https://doi.org/10.1007/978-3-031-08284-9_15
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-2270cecd-b922-4cad-b3db-6581144e0244
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