Using Artificial Intelligence to Study Natural Environments
In rainforests many animals are nearly invisible, but not all are silent. Rainforests click, whirr, and hum with the sound of life. Like heartbeats offer clues to doctors, these sounds convey endless information about the life of forests, capturing the coming and going of animals, the start and end of seasons, and even the sound of wind and rain. Until recently, making sense of these sounds was slow and laborious. At the Center for Conservation Bioacoustics, we are developing ways to automate and accelerate the process.
The need for rainforest conservation has never been more urgent. In recent times, we have witnessed drastic changes in rainforest ecosystems that are experiencing local and global threats. Preserving these environments means protecting not just the large iconic species, such as jaguars, but also understanding the smaller species that form a vital link in the ecosystem’s food chain.
Insects are a ubiquitous element of rainforests. Many tropical insects have not yet been named or described. For most, we know very little about where they occur or how many there are. Recent studies suggest that global insect populations may have declined by half or more. Perhaps even more staggering than the purported magnitude of the decline is the simple fact that we do not know to what extent this is accurate and have very few ways to support or refute these claims.
Technological advances are providing new ways of monitoring ecosystems. Advances in machine learning technology have made it possible for cell phones to transcribe human speech. Now, we are applying these same machine learning approaches to transcribe the sounds of the rainforest. In particular, we are focusing on the sounds of katydids — a diverse family of large grasshopper-like insects that are a central element of tropical food webs. Katydids feed on a wide variety of plants and are eaten by many diverse predators.
Tracking the populations of insects like katydids is vital in part because populations can change so quickly. Events in a single season or year can drive massive population declines given that the lifespan of these insects only last weeks or months. At the same time, many insect species have a remarkable potential for population growth, meaning that, if given the opportunity to recover, insect populations may rebound quickly, providing critical support for the species that depend on them.
Our initial efforts have focused on Barro Colorado Island, a Smithsonian-run research station located on an island in the Panama Canal. This site is an excellent starting location because we have a multi-year dataset on katydid abundance and acoustic recordings of many species. The goal, however, is to create tools that translate across sites, allowing researchers to apply these techniques to many different species and habitats. We are now using these approaches in forests of Costa Rica to compare the insect communities in sites subject to different restoration approaches.
Top row L to R: Hannah ter Hofstede, Rachel Page, Christine Palmer, Laurel Symes, Shyam Madhusudhana, Jen Hamel, Sharon MartinsonBottom row L to R: Tony Robillard, Alvaro Vega, Ciara Kernan, Estefania Velilla, Rick Buesink, Inga Geipel
Developing and applying analytical approaches is an ongoing endeavor of the Center for Conservation Bioacoustics. The work described here is made possible by support from an AI for Earth grant from National Geographic and Microsoft and a grant from the Arthur Vining Davis Foundations.
In addition to collaborations within Cornell, we are working with researchers at many other organizations, including: Castleton University, Dartmouth College, Elon University, Muséum national d’Histoire naturelle (Paris), Osa Conservation, Smithsonian Tropical Research Institute, Universidad de San Jose, and University of Antwerp.
Students and technicians including: Aboubacar Cherif, Robin Costello, Abenezer Dara, Nate Gallagher, Angela Golding, McKenna Grey, Lars Hoeger, Alina Iwan, Autumn Jensen, Nicole Kleinas, Sara McElheny, Colleen Miller, Rebecca Novello, Kingsley Osei-Karikari, Caitlyn Lee, Jessica, Ralston Jones, Jean Ross, Matt Sears, Nicole Wershoven, Cassidy Yrsha