Measuring range-wide species population changes to support global conservation monitoring and decision-making

Global conservation organizations invest heavily in protected areas and management actions to support biodiversity outcomes, often with a particular focus on target species. However, they require more flexible, efficient means to monitor the impact of these interventions at scale. Lack of responsive tools that can regularly track progress and impact of conservation actions can limit effective resourcing and planning for future work. While sufficient in situ data may exist for specific regions, and species, conservation organizations require standardized measurements and aggregate metrics to support decision-making across their global portfolio and countries of activity. 

This presented work addresses these challenges by leveraging the advanced and proven species-level models and metrics of Map of Life (MOL). This effort utilizes NASA-supported remote sensing workflows and the digital infrastructure that enables calculations of Species Habitat Scores and Species Habitat Indices – formally adopted indicators of Goal A of the UN Global Biodiversity Framework. 

These indicators rely on species-habitat association calculations, historically developed from expert-informed range maps validated against a single independent source of species presence data. To enhance the accuracy and reliability of these measures, we will implement emerging modelling techniques that integrate diverse data streams, including citizen science records as well as visual, acoustic, and GPS tracking data. Combining species occurrence information from multiple data sources substantially improves model predictions and resulting conservation insights, but these approaches have yet to be widely adopted by conservation practitioners for large-scale decision-making.

We show results for implementing these models for mammal species based on camera trap data and citizen science data, with all routines designed to be easily extended to additional taxa. By integrating multi-source datasets with NASA and other Earth Observation products that capture fine-scale climatic and environmental conditions, we can provide annual, range-wide estimates of suitable habitat, habitat connectivity, protection adequacy, and estimate total population size trends for target species. Our advanced species distribution and occupancy modeling approaches enables us to offer both high-resolution maps and species-level trends alongside method-associated uncertainty that will directly support tracking progress towards 30x30 goals and guide adaptive management interventions.