Resumen

CABRERA ALVAREZ, Elia Natividad; DIAZ GISPERT, Lidia Inés  y  BARROS DIAZ, Otilia. The multidimensionally of the sustainable development in the mountain ecosystems of Cuba. Universidad y Sociedad [online]. 2019, vol.11, n.1, pp.25-33.  Epub 02-Mar-2019. ISSN 2218-3620.

The sustainable handling of the ecosystems of mountain requires of the application of multidisciplinary approaches, in order to evaluate the current stage of these mountainous space which constitutes fountains of biodiversity, like reference for their future stages. Cuba develops actions for the conservation and the sustainable administration of his protected areas, but these are not enough yet, against the threats of the environment. The purpose of this investigation is to contribute to the scientific results of the project developed in the University of Cienfuegos, System of actions for improve the administration of the local development in settlements of population and municipalities of the city of Cienfuegos. This project responds to the National Program of Local Development in Cuba. It is objective of this investigation to propose a methodological procedure for the evaluation of the current stage of the ecosystems of mountain, structured from the economical, social and environmental dimensions of the sustainable development. This procedure was applied in the Mountains of Guamuhaya (Cumanayagua) with possibilities of adequacies to the remaining mountainous ecosystems from Cuba. There are articulated several methods and procedures like, the DAFO analysis, Method of experts and the statistical modelling. It was identified 20 basic variables and 60 territorial indicators of reference for the mentioned ecosystem. A computerized system was also designed which facilitates the administration and the centralization of the information as well as the evaluation of the ecosystem through and index of sustainable development, favoring the objectives of the 2030 Calendar.

Palabras clave : Sustainable development; current scenery; mountainous ecosystems; statistical modelling.

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