Earth Observation for Genetic Indicators: Bridging Ground-Based and Satellite Data for Genetic Diversity Monitoring in the GBF Framework

Effective implementation of the GBF monitoring framework requires bridging the gap between research methods and the information that parties must report at a national scale. Genetic diversity is an important aspect of the GBF monitoring framework but remains the least developed for large-scale monitoring.

Genetic diversity indicators depend on knowledge of population stability and change, which is difficult to obtain repeatedly across many species and large areas. Although the parties to the CBD have recently adopted genetic diversity indicators that do not rely on DNA sequencing, established alternative workflows still rely on periodic ground-based assessments that can be costly, especially at national scales. Continuous, openly accessible data from satellites can be used to estimate habitat properties relevant for population status, thereby reducing dependence on sparse field observations and providing assessments that support national reporting. The project Earth Observation (EO) for Genetic Indicators demonstrates how EO can be integrated practically into workflows for monitoring genetic diversity indicators aligned with policy requirements.

An interdisciplinary team of experts in Earth observation, conservation genetics, and indicator development created a workflow that incorporates EO data-derived habitat extent and thus supports genetic diversity indicator calculation. An online tool, which was co-designed with end users, integrates public EO data to standardize and support indicator calculations for national-scale reporting. The workflow uses population locations and EO-based land cover data as core inputs from which it determines changes in population-specific habitat. We evaluate the presented workflow through a set of multi-country use cases across multiple continents. Using existing ground-based data from multiple partner projects, we assess how EO-derived habitat information can complement or update population-level information where ground data are limited. We demonstrate the workflow's feasibility, its alignment with existing ground-based approaches, and the ability to support repeated indicator calculations for various plant and animal species.

The presented approach provides a practical means to supply consistent, repeatable inputs for national genetic diversity reporting. Our project aims to strengthen the connection between EO and conservation genetics communities and move genetic diversity monitoring closer to large-scale operational use within the GBF monitoring framework.