Image Credit: Jayden Skelly ©

Map of Life

Rapid Assessments

Map of Life is a Yale University-based initiative that supports effective conservation outcomes by delivering biodiversity insights for locations anywhere. By integrating standardized global metrics, innovative survey technologies, and cutting-edge informatics tools, we provide comprehensive biodiversity measurement and decision-support solutions.

Our Rapid Assessments solution combines the power of Map of Life with a fleet of autonomous UAVs to collect audio, visual, and eDNA data, on-site eDNA processing methods, and AI technologies to deliver actionable insights. Powered by an authoritative biodiversity information engine, we enable deeper insights and practical solutions for biodiversity assessment, reporting, monitoring, and management—marking an exciting step in expanding the accessibility and effectiveness of biodiversity monitoring across diverse applications.

XPRIZE Rainforest 2nd Place Prize Winners

MOLRA was awarded the $2,000,000 2nd prize in the 5-year $10M XPRIZE Rainforest competition.

The MOLRA team analyzing collected data samples in the field during the XPRIZE finals competition.
© Cat Kutz

MOLRA was one of six teams out of an initial 300 who joined the competition that made it to the finals competition, which was held in July 2024 near Manaus, Brazil.

Over the 24 hours survey period, the MOLRA approach allowed us to record 225 species across 5,500 geolocated identifications all without stepping foot inside the study site. Our solution was the only one that covered the full area comprehensively and was unique in its largely autonomous execution. Our link to the Map of Life database and indicators allowed us to deliver key insights about the global significance and recommended management for the location.

XPRIZE Rainforest is a global 5-year, $10 million competition that convenes innovators and experts across disciplines and challenges them to use novel technologies to expedite the monitoring of tropical biodiversity.

MOLRA XPRIZE Rainforest Team

Professor of Ecology and Evolutionary Biology, Yale University Team Lead
Professor of Ecology, Evolution, and Natural Resources at Rutgers University EDNA Team Lead
Senior Conservation Ecologist at the Field Museum of Natural History EXPERT ENGAGEMENT AND IPLC LEAD
Associate Professor of Genetics at the Federal University of Amazonas EDNA Team Lead
FULL TEAM GUIDE (ENGLISH) Guia Completo da Equipe (Português)

Our Impact

Map of Life (MOL) global biodiversity indicators have been formally adopted by the CBD Global Biodiversity Framework, and MOL's online reporting tools are used by >100,000 visitors annually.
At rainforest sites in Peru, Guyana, and Brazil, nearly 2,000 species have been genetically sequenced, with new unique marker sequences for hundreds.
A MOLRA spin-off facilitated by Yale Ventures to support survey projects with a wide range of partners has received the 2024 Yale Faculty Innovation Award.
MOLRA's field tech has now been used with local partners to survey over a dozen separate rainforest locations, resulting in >10,000 records of >1000 species identified and mapped over >1,000ha from acoustic, visual, and eDNA.
MOLRA continent-wide 1km resolution, model-based biodiversity expectations are being used by the Guyanese government and regional NGOs as technical support for Indigenous land title extension requests and for conservation management

Our Approach

Our approach employs a fleet of semi-autonomous UAVs to collect audio, visual, and eDNA samples from a study site without ever needing to step foot in the site itself. Our surveys are supported by the global Map of Life biodiversity data and modeling engine, a suite of machine learning and AI models and innovative eDNA processing methods, and the combined knowledge and experience of a team that has been studying rainforests and biodiversity for decades.

Our Approach

Initial Biodiversity Prediction

For any site in the entire world, our robust Map of Life modeling engine predicts what terrestrial vertebrate and tree species are expected to be found there. For the Americas and Southeast Asia, these predictions are based on tens of thousands of high-resolution species distribution models developed by our team, which will soon be available for Africa and, finally, the entire world.

Our Approach

Vegetation Surveys

Our autonomous vegetation mapping missions deliver true-color maps at 5cm resolution along with a set of indices. These maps are fed through a set of AI models that automatically detect tree crowns, flowering canopies, and other important vegetation characteristics, estimate tree crown diameters and heights, and support habitat classifications of the entire area. This data all serves to inform our subsequent sampling missions and provide important insights.

Our Approach

Environmental DNA

We customize our UAVs to collect eDNA samples from the air, water, and leaf surfaces throughout the study site. These customized rigs, developed by our team, are extremely cost efficient. Our team has developed novel methods to process samples in the field and go from sample collection to species lists in as little as 24h with a minimal local setup. eDNA allows us to detect species that might otherwise be missed in our other sample collection modalities, particularly freshwater fish. Most of our eDNA sampling missions are fully autonomous.

Our Approach

Audiovisual

A combination of autonomous and remotely-controlled UAVs collect audiovisual samples in the study area guided by our vegetation and habitat mapping results. We collect visual samples from the canopy and the understory, targeting trees, epiphytes, and herbaceous plants, and we collect audio samples at dawn, dusk, and night to target birds, amphibians, and bats. These samples are fed into our AI models to produce preliminary species identifications.

Our Approach

The MOLRA Dashboard

All raw audiovisual samples along with AI-based identifications and processed eDNA samples with identifications are uploaded onto the MOLRA Dashboard where taxonomic experts can review, confirm, or edit species IDs. Taxonomic experts from anywhere in the world can log on to review samples and collaborate with other experts, greatly speeding up the ID process compared to traditional survey methods. The MOLRA Dashboard also provides a suite of insights for users to explore.

The MOLRA Dashboard

Linking all our technologies and data with collaborators and end users is the MOLRA Dashboard, a dedicated online platform for sharing survey results and insights and engaging with identification experts and the local community. The MOLRA dashboard facilitates rapid and collaborative review of our samples and their predicted IDs, culminating in a robust, quality-controlled final species list. Accompanying this species list is a suite of additional biodiversity insights drawn from the Map of Life global databases, including species conservation status and the broader regional and global significance of the study site.

Collaborate

We currently offer three levels of project partnership:

MAP OF LIFE ENGINE ONLY
  • Fully remote, no local data collection required
  • Delivers a local biodiversity expectation across terrestrial vertebrates, trees, and soon select invertebrate groups
  • Provides insights including standardized metrics and indicators on conservation status, trends, and global significance of locally occurring species
MOLRA
"IN A BOX"
  • All of the previous, plus:
  • Delivers the audiovisual UAV solution “in-a-box” complete with access to our AI models, expert validation, and the MOLRA Dashboard
  • Requires local on-the-ground technicians for minimal operation
FULL MOLRA INVENTORY
  • All of the previous, plus:
  • We send a small team to assist or lead survey efforts
  • Optional inclusion of the eDNA survey and analysis component

Interested in partnering or collaborating with us? Reach out to our team manager, Alex Killion, at [email protected]