- Monitor the biodiversity of rainforests globally
- Generate value for communities hosting biodiverse forests
- Increase the awareness about biodiversity among the general public
The data gap
Tropical forests, hosting at least two-thirds of the world’s flora and fauna diversity and storing 25% of the terrestrial carbon, are under growing pressure. In spite of their biodiversity and uniqueness, they are grossly understudied and underrepresented in wildlife monitoring platforms due to their relative inaccessibility.
We want to contribute towards closing this gap by intertwining and encouraging the participation of the scientific community, local communities and everyone else by developing a unique platform where scientific biodiversity monitoring systems are complemented with citizen science.
We have identified two cases that we will use as a test bed for our concept:
Biodiversity aware ecotourism: Locals can map their surroundings in terms of biodiversity, as well as its cultural and economic value (i.e., edible fruits), and travelers are challenged to document these species, and others they may encounter, by capturing images and audio in targeted gamified campaigns. Selvascope will engage with locals that are eager to share their knowledge and travelers who are willing to capture and share images and audio of wildlife. We will use the infrastructure from existing platforms such as iNaturalist. Partnerships are already being developed to record data and the narrative of locals, and gather visitors’ data of rainforest wildlife. With the aim to engage the general public in these communities we will develop a gamified version of the platform that fosters their participation.
Biodiversity respecting honey: Beekeepers can increase the visibility of the diversity of flowering plant and pollinator species that are found in their honey by linking to a report on the species detected in it and their description and use it as a differentiation from monospecific honey. Consumers will be encouraged to explore the biodiversity contained in a drop of this honey by organizing palynology workshops with accessible microscopy equipment in educational institutions.
Towards the XPRIZE Rainforest competition
The species observation data generated by our approach will be used in in two ways in order to help us identify species during the competition:
Better Species Distribution Models: The observation data generated through our approach will be added to current repositories of species observations in order to create more fine grained and precise Species Distribution Models (SDM). These models will serve as a basis, providing us with a list of species that are to be expected on the competition site a priori.
Better AI models for species identification: The observation data that is coupled with images, audio or video will be used to train AI models for species identification specifically for rainforest species. We will put special emphasis on AI model interpretability in order to improve user engagement and to assist in identifying data deficient species.