Abstract

The BioDT project, funded by the European Union Horizon Europe Programme, seeks to investigate and push the boundaries of methodological, intellectual, data, technical and relevance aspects of the digital twin (DT) approach for understanding and predicting biodiversity patterns and processes. In this special issue, we present the reasoning and goals of the project and the overall advancements made towards the development of ten prototype Digital Twins (pDTs). Based on models of ecosystems, species and biological processes, digital twins integrate diverse data sources with advanced modelling and simulation techniques to provide a comprehensive, dynamic and data-driven understanding of biodiversity. Leveraging the EuroHPC LUMI infrastructure and data and expertise from GBIF, eLTER, DiSSCo and LifeWatch ERIC research infrastructures, the project aims to develop hybrid models combining the strengths of statistical and process-based models for improved predictive capabilities. While there are specific challenges and limitations to biodiversity DTs, the pDTs of BioDT lay the foundation for model-data fusions that will offer potential benefits to a wide range of end-users, from researchers and conservation organisations to policy-makers, land managers, educators and private sector companies. By fostering global interoperability in biodiversity data and research, BioDT paves the way for future collaborative efforts in biodiversity conservation and management.

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