TerraTwin

OBJECTIVES

The TerraTwin project aims to develop a holistic DTE (Digital Twin of Ecosystem) tool to better understand the complex interplay between climate change and marine and terrestrial biodiversity. This will be accomplished by leveraging existing multiparametric data from various sources, for marine, land, soil and atmospheric biodiversity, which will be used to feed and train the DTE, which in turn will offer innovative features, such as data analytics, anomaly detection, predictive capabilities, feedback loops, policy recommendations and connection with other tools and databases. he following advanced solutions will be integrated to the DTE, to meet its goals: a) Advanced data harmonisation to unify and standardise different types of collected biological and environmental data, b) Big data to handle diverse types of datasets, c) Blockchain technology to enhance the functionality, security, traceability and trustworthiness, d) Gathering and harmonising of Historical and near real time data from existing databases and on-field activities for climate and biodiversity, d) AI and machine learning, an “in-silico” approach will be enforced to recompile all available physiological information as maps for different key or iconic species, in order to match the different physiological scenarios with changing environmental conditions as a mechanism to predict biodiversity changes, as predicted for the different areas by the International Panel for Climate Change (IPCC), e) DTE integration GUI, f) Simulation for various climatic scenarios based on the selection of areas and environmental data, g) Socio-economic modelling integrating environmental data with human activity patterns, providing a holistic view of how climate and biodiversity changes impact communities and economies and h) Environment-species mapping modelling links species distribution with environmental conditions, enabling the identification of potential habitats and the assessment of biodiversity resilience.

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