Pivotal is the British startup building a reliable and scalable platform to track biodiversity and enable farmers and beyond to be compensated for the ecosystem services they provide.

Tracking biodiversity

While up until now it has only been possible to be compensated for the CO2 removed from the atmosphere, Pivotal is committed to figuring out how to measure and pay for the biodiversity produced. Whereas the current status quo involves sending a team of ecologists to conduct field surveys and listen and observe plants, insects, and birds as indicators of biodiversity and then compile a report – a very expensive system that only mining companies can afford, partly because they are obligated to do so – Pivotal relies on technology. It uses drones, acoustic and image sensors to monitor plant and animal life on the lands in detail.
By applying technology, expert knowledge, and machine learning, the company measures biodiversity economically, efficiently, and at scale. The increase in biodiversity is quantified by considering several key factors such as the number of different species present, the abundance of each species, the prevalence of threatened species, and the size and cohesion of the habitat.

The Nature Uplifts credits

The increase in biodiversity is then translated into tradable goods, credits, called Nature Uplifts, designed as a way for companies to invest in nature restoration around the world. This asset can be traded between suppliers and buyers on the Pivotal Nature Exchange, the exchange platform for biodiversity regeneration.
Under this system, biodiversity providers are paid to increase biodiversity on their land, companies have an immediate impact on their sustainability commitments, investors in regeneration benefit from financial returns, and nature is regenerated.

Website
www.pivotal.earth

Sector
Biodiversity measurement

Plus
Drones, acoustic and image sensors to monitor plant and animal life on the ground in detail

Features
Technology and machine learning systems to measure biodiversity efficiently, accurately, and at scale

Image: Sagar Kulkarni (Unsplash)