Projets

ETH Zürich Foundation

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BiodiviX

Biodiversity
In partnership with
Client
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The challenge

The sharp decline in global animal and plant biodiversity has put nearly one million species at risk of extinction with the staggering point that this means one in eight species are at risk of extinction. Loss of life from earth on this scale and its effect on all ecosystems and the services they provide to humans will push the planet across what we expect are tipping points for a safe operational state for humanity. Scientific and technological advances to monitor biodiversity and its functions to supply clean water, food security through our agricultural systems and a healthy biosphere (life on land and life in water) underpins all the Sustainable Development Goals of the United Nations. While we are waking up to these challenges and are trying to change the path ahead, we currently lack a viable and cost-effective way to examine the biodiversity change of our planet.

The$10M XPRIZE Rainforest is a five-year competition launched in November 2019 by the XPRIZE Foundation. The goal of the XPRIZE Rainforest is to accelerate the innovation of autonomous technologies needed for biodiversity assessment and enhance the understanding of rainforest ecosystems. For this purpose, rapid data integration will be used to provide new wisdom about the forest as well as inspire new investment and exploration to accelerate the development of new, just, and sustainable bioeconomies.

1 Million

Number of species at risk of extinction or one out of eight species on the planet

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The solution

At ETH, Professors Kristy Deiner (Environmental DNA) and Stefano Mintchev (Environmental Robotics), and PhD student David Dao are leading the team ETH BiodivX consisting of about 30 team members from various scientific disciplines, local and indigenous people, and NGOs to co-design the necessary technology.

To create a scalable biodiversity monitoring solution an inter- and transdisciplinary collaboration is needed. BiodivX therefore unites expertise from material science, robotics, computer science, ecology, and molecular biology to develop autonomous robots of manoeuvring and remotely sampling environmental DNA(eDNA), sound and images in complex environments such as forests. The data will then be transformed into measures of species richness and genetic diversity through use of bioinformatics matching sequences to species and machine learning algorithms to identify species from sound and images. These measures of species and genetic diversity will be used as the basis to generate insights. The insights will not only deliver critical and verifiable raw data but will be transformed into information shedding light on how to collect in remote locations critical data related to biodiversity monitoring and essential biodiversity variables set forth by the Group on Earth Observations Biodiversity Observation Network. They include how to capture critical scales and dimensions of biodiversity that are sensitive to change, how to make this insight generation ecosystem agnostic, and how to create a system that is technically feasible, economically viable and sustainable over time.

« To create a scalable biodiversity monitoring solution an inter- and transdisciplinary collaboration is needed. »

The insights will be digested into dashboards, videos and converted even into music to deliver a multi-media approach for education, sharing of knowledge and deliver the information in the hands of people who need them for making critical decisions to safeguard what nature provides to people and to bring us back in balance with a sustainable, yet interconnected global society. While applied to rainforest in this competition, the technology will be scalable to many ecosystems around the world.

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