Harnessing multi-source time-series biodiversity data to predict and mitigate the impacts of harmful algae blooms.

Our primary objective is to utilize comprehensive population dynamics and environmental data to anticipate harmful algae blooms, thereby aiding in timely interventions.

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The problem

Harmful Algae Blooms (HABs) have a significant impact on marine ecosystems, human health, and coastal economies. They produce toxins which can poison marine life, cause respiratory irritations in humans, and lead to economic losses in fisheries and tourism. Predicting these blooms is crucial to manage their threats efficiently.

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Our solution

At the heart of our platform is our specialty: the ability to assimilate time-series biodiversity data from diverse sources, such as eDNA, remote sensing, and more. This data, combined with environmental parameters like water currents and temperatures, positions us uniquely to model harmful algae bloom patterns.

While forecasting algae blooms is challenging, akin to predicting the weather, our data-centric approach offers a promising avenue. As an early-stage endeavor, we’re eager to harness this data-driven potential further.

We’re on the lookout for collaborative opportunities with researchers and experts in the field to refine and improve our forecasting capabilities. Together, we aim to mitigate the adverse effects of HABs on marine ecosystems and communities.

If you’re interested in joining forces or supporting our mission, we’d love to hear from you.