The goal of Forest-Web 3.0 is to develop new data-driven solutions focused on monitoring biodiversity in forest ecosystems. The project aims to initiate a paradigm shift within the academic community by advancing the management of existing forest biodiversity and environmental data through Web 3.0 technologies and demonstrating the use of such data in modelling changes in biodiversity. By creating nature-backed digital assets, the project demonstrates the economic potential of afforestation and aligns ecological goals with innovative digital solutions.
It has been previously expected that making scientific research more open and accessible would trigger a revolution in biodiversity science. However, this expectation has not materialized: primary ecological data often remain difficult to access. Studies examining attitudes towards open data in the fields of ecology and evolution have revealed several common concerns among researchers – data are often treated as private property, particularly when data collection has been resource-intensive. Furthermore, fears that competitors may monopolize hard-earned data, and a reluctance to relinquish control to centralized repositories, exacerbate the problem.
Distributed ledger technologies, such as blockchains, offer solutions to issues of trust, transparency, and control. Distributed ledgers, with blockchain technology being the most prominent example, form the core of Web 3.0 approaches. By decentralizing data in a cryptographically secured and chronologically ordered chain of blocks, blockchains enable a new level of data governance and help to remove the barriers that have thus far hindered the development of open science.
This will involve integrating ’bottom-up’ in-situ biodiversity and environmental data, collected through a remote sensor network, with other top-down data to model changes in biodiversity. This will involve harmonising and validating data from a diverse range of sources and assessing its validity to be the basis for advanced modelling into biodiversity change. The feasibility of such a model will be considered in terms of its robustness and generalisability, with the ultimate aim of developing a predictive tool for assessing the risk of biodiversity change in forests. In doing so, the model will seek to provide evidence and value for „nature-backed“ digital assets.
This activity is targeting at forest land-owners, facilitating education and knowledge exchange in proforestation and Web 3.0 regenerative finance (ReFi).
This is a Biodiversa+ project funded in the 2022 – 2023 call (BiodivMon).
Head of Unit, Senior Expert (Sustainable Cities and Resilient Communities Unit)
SEI Tallinn
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