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NEXTGENDEM focuses on the protection and improvement of the conservation of natural spaces and terrestrial plant biodiversity in Macaronesia. For this, genetic, ecological and geographical indicators will be used in order to interpret the genetic and phylogenetic diversity of terrestrial flora in the island territories and apply resulting knowledge to the management and conservation of species and protected areas.

The project complements genetic, taxonomic, ecological, geographic and computational lines of work to help managers have decision-making based on verified and updated scientific data. In order to achieve these goals:

  1. molecular data will be crossed with data of other types;
  2. various analysis techniques and methodologies will be developed;
  3. the BIOTA and Jardín Canario databases will be updated,
  4. bioinformatics tools based on ICT and advanced computing will be created to manage and accelerate the processes for obtaining indicators and decision-making, and
  5. they will develop actions to improve the conservation status of 60 threatened endemic species.

The Canarian Botanical Garden 'Viera y Clavijo', associated unit to the CSIC, Cabildo de Gran Canaria, is the main beneficiary of the project that has as partners Canary Islands Institute of Technology, a public R&D&i center attached to the Ministry of Economy, Knowledge and Employment of the Government of the Canary Islands, and INIDA of Cape Verde.

Under the title "Evolutionary management of the endemic terrestrial plant diversity of Macaronesia through actions on threatened species and the creation of geographic bioinformatics tools with application to the conservation of species, spaces and genes", NEXTGENDEM will improve the conservation status of 60 endemisms threatened from the Canary Islands and Cape Verde through various actions in the field, and the transnational cooperation network on biodiversity will be consolidated.

The project (with code MAC2/4.6d/236) is co-financed by the 2014-2020 Interreg MAC Cooperation Program, within Axis 4 "Conserve and Protect the environment and promote resource efficiency".

Expected results of the actions carried out in this project are:

  • New tools for the management of biological diversity in the territory and plant forensics.
  • Identification of seed sources for reinforcements and reintroductions based on genetic data.
  • Public awareness of the added value of scientific-technical research for the conservation of species and spaces.
  • Boost of high-performance ICT resources for biodiversity management.
  • Field actions to improve the conservation status of threatened species
     

NEXTGENDEM is aligned with Sustainable Development Goals (SDGs), the following being of special interest:

  • Jardín Botánico Canario 'Viera y Clavijo'-Unidad Asociada al CSIC, Cabildo de Gran Canaria. Canarias. España
  • Instituto Tecnológico de Canarias, S.A. Canarias. España.
  • Instituto Nacional de Investigação e Desenvolvimento Agrário (INIDA). Cabo Verde.

Presupuesto final aprobado:   1.322.631,54 €

Financiación a través del Programa INTERREG MAC 2014-2020, Fondo Europeo de Desarrollo Regional-FEDER (85%): 1.124.236,81€

November 2019 – December 2022

Main Objective:

Interpret the genetic and phylogenetic diversity of the terrestrial flora in terms of ecological and geographic variables for each grid of target island territories, and apply resulting knowledge to the management and conservation of species and spaces.

Specific objectives:

  • Carry out necessary samplings, generate genetic and non-genetic knowledge and consolidate the Macaronesian network of sample banks and data for the conservation of floras.
  • Relate genetic parameters associated with the insular terrestrial flora with non-genetic variables (taxonomic, ecological, geological, climatic and geographic) using versatile biocomputing tools based on supercomputing.
  • Improve the conservation of terrestrial plant biodiversity and territory against global changes by integrating multidisciplinary spatial, genetic, taxonomic, and environmental data that includes interpretations of patterns and processes.
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