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PUBLIC INSTITUTION NATURE PARK VRANSKO JEZERO

JAVNA USTANOVA PARK PRIRODE VRANSKO JEZERO
Country: Croatia

PUBLIC INSTITUTION NATURE PARK VRANSKO JEZERO

1 Projects, page 1 of 1
  • Funder: European Commission Project Code: 101157886
    Overall Budget: 4,207,310 EURFunder Contribution: 3,968,230 EUR

    ProCleanLakes targets to combat the combined impact of various disruptive factors that generate continuous pressure on the lake's ecosystem status and facilitate the accumulation of emerging, non-regulated, chemical contaminants and nutrient enrichment. The project will design and demonstrate the feasibility of integrated nature-based emerging approaches for joint protection and restoration of European Natural Lakes (ENL) and their biodiversity, considering scenarios which imply the presence of various pressures that affect the aquatic ecosystems' status. The holistic transdisciplinary approaches that are to be used in the project, based on the synergic effect of the economic-environment-social nexus, targets to support the improvement of ENL ecological and chemical status in association with major EU instruments, sustainable development goals and policies related to freshwater ecosystems. The project engages multiple sites affected by the presence of various pressures and stressors, that will be the subjects for the demonstration of integrated protection and restoration solutions efficiency. A replication roadmap powered by the necessity of assuring upscaling and universality of the optimal integrated solutions (IS) will be developed to prove the replicability. An IS support platform which merges a business accelerator with an adaptive artificial intelligence (AI) solution for empowering citizen science related to lakes protection and restoration will assure the collaboration between the municipalities and citizens and will offer capacity-building and encourage co-development and co-design towards natural lakes protection and restoration. Tools such as mobile decision support platforms, serious games for digital readiness, e-learning and augmented-based modules for reinforce-learning and multiple AI machine learning analytical frameworks will be developed to assure the synergic approach toward the maximization of integrated solutions impact and replicability.

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