New from DSE: data science tools to scale state and global conservation efforts

GLEN: an open source, local AI model for conservation decisionmaking

The Geospatial LLM-Enabled Navigator (GLEN) is an open source AI assistant that allows decisionmakers to interrogate global data on threatened lands and waters in order to inform conservation policy and action. Users can ask the interactive model more complex analytical questions than current LLMs can answer, and will receive reproducible answers in minutes.

Importantly, GLEN runs locally on a your desktop server or laptop, which minimizes cost, privacy concerns, and energy demands. It achieves similar (or better) performance to commercial LLMs like ChatGPT or Gemini, while avoiding the need for incredibly resource-intensive data centers. DSE is increasingly pivoting to developing local AI models for stakeholders in an effort to demonstrate that we can think beyond data centers when it comes to AI. This also includes our previously released and co-developed tools to reduce global greenhouse gas pollution and improve vegetation recovery after a wildfire. 

There are over a dozen active use cases. For example, policymakers are currently using GLEN to inform proposals for the United Nations High Seas Treaty to establish new global marine protected areas. In California, scientists and land managers are employing the tool to improve gray wolf recovery. Dive into GLEN: view the tool and read more about this project.

Soundhub: responsibly scaling bioacoustic data collection for California

Soundhub is a remarkable web tool that identifies species using bioacoustic sound data (i.e. animal calls). Bioacoustic data is critical for understanding wildlife abundance and distribution, can signal changes in environmental health over time, and informs conservation decisionmaking. The tool can passively collect, sort, and classify terabytes of audio to detect species. This provides an exciting and time-saving approach to data collection at scale rather than relying on field observations. 

We are partnering with the UC Berkeley Geospatial Innovation Facility (GIF) and California Department of Fish and Wildlife to expand Soundhub so that it becomes the official home for all bioacoustic data across California, including the California Sentinel Site Network. Within Soundhub, we are developing targeted AI models to identify vocalizations from frogs, birds, coyotes, and other species of interest, as well as anthropogenic sounds (i.e. vehicle noise) and natural environmental sounds (i.e. wind and rain). Simultaneously, we are helping to integrate Indigenous Data Sovereignty parameters to ensure the tool protects the privacy of and data from Indigenous users. Explore Soundhub: check out the dev website and see the key species we're training our models to detect.