Renatura

The digital map of regeneration.

A platform for encouraging transparent, digital ecosystem regeneration.

Challenge.

Faced with the difficulty to decarbonise the business models and value chains of large carbon-intensive industries, companies are turning to the regeneration of terrestrial ecosystems as a means of offsetting and absorbing their emissions. These projects, however, face significant challenges in the private sector:

Difficulty in bringing together businesses and regeneration agents in the territories.
Confusing procedures and technical difficulties in project management.
Difficulties in measuring and monitoring the impact of projects.

Solution.

Creating a digital platform in the form of a map that connects companies interested in carrying out regeneration projects with organisations in the territories where these projects are to be implemented. This platform facilitates the management and reporting process in each project and promotes transparent, accurate measurement of its impact in the country.

A platform model for simplifying the link-up among agents.

Platform models act as integrators of the supply of and demand for any good or service in one place. In this case, we connect companies interested in backing regeneration projects with different types of organisations in the territories where these projects are executed.

Thanks to this platform-mediated connection, we can meet the major challenges faced by companies and their sustainability areas when it comes to managing these projects. The difficulty in identifying regeneration sites, organisations, necessary information and budget is overcome thanks to a digital management that makes the process more efficient.

With this model, we seek to increase both the demand for regeneration projects by companies and the supply of regeneration projects carried out by both organisations and citizens themselves.

Collective intelligence to accelerate learning in terms of regeneration

As with all major systemic sustainability challenges, accelerated learning and knowledge gaining are essential in pursuing the most transformational solutions. Leading scientific research in regeneration keeps making progress with the aim of increasing this knowledge.

In this sense, Renatura aims to be a platform that aggregates the impact indicators of all regeneration projects being promoted in a country.

By combining the lessons learned in the different projects, techniques and ecosystems, we seek to generate collective intelligence to move scientific knowledge about regeneration forward.

In the long term, data analytics and machine learning will become digital technologies for boosting this intelligence and detecting best practices in CO2 absorption and care for terrestrial ecosystems.

Much more than CO2 absorption

Due to the climatic circumstances and the ecosystems in Spain, the country’s CO2 absorption capacity is low compared to other countries with tropical ecosystems, whose potential is much greater. This is why we think it is essential that regeneration projects in Spain take into account more variables than just CO2 absorption.

Renatura was conceived with the ambition to bring other indicators to companies and to help regeneration projects to maximise the generation of a positive environmental impact, as well as having a positive social impact.

The criteria Renatura aims to promote are as follows:

Regenerative capacity: to enhance the areas and ecosystems with the highest regenerative capacity based on their features.
CO2 absorption: to enhance the areas and ecosystems with the greatest CO2 absorption potential.
Impact on biodiversity: to increase the impact of the projects on the protection of biodiversity and species in the area.
Socio-economic impact and demographic challenge: to have a positive social impact in areas at risk of disappearing that leads to the promotion of economic activity therein.

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The digital map of regeneration.

Challenge.

Solution.

A platform model for simplifying the link-up among agents.

Collective intelligence to accelerate learning in terms of regeneration

Much more than CO2 absorption

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