We can't monitor ecosystems at the scale or speed needed

Technologies that track and measure biodiversity at scale, including eDNA analysis, acoustic sensors, camera traps, and satellite observation of habitats.

Using satellites, drones, and aircraft to continuously watch forests, grasslands, wetlands, and other ecosystems from above. These systems can detect deforestation, track vegetation health, monitor water bodies, and spot environmental changes across vast areas in near real-time. The technology combines high-resolution imagery with AI to automatically identify threats and changes that would take human observers years to catalog on the ground.

Deploying networks of smart sensors that can detect and identify wildlife without human presence. Environmental DNA (eDNA) sensors find traces of genetic material in water and soil to identify what species are present. Acoustic sensors listen for bird calls, bat echolocation, and other animal sounds. Camera traps automatically photograph wildlife and use AI to identify species. These tools can monitor biodiversity continuously across huge areas with minimal human intervention.

Creating networks of underwater sensors, autonomous vehicles, and floating platforms that monitor ocean health in real-time. These systems track water temperature, acidity, oxygen levels, pollution, and marine life populations across the vast ocean areas that are impossible to monitor from ships alone. The data helps scientists understand how climate change and human activities are affecting marine ecosystems.

Developing sensors and testing methods that can quickly assess soil quality, carbon content, microbial diversity, and nutrient levels across large agricultural and natural areas. Healthy soil is the foundation of terrestrial ecosystems, but traditional soil testing is slow and expensive. New technologies can provide rapid, affordable soil health assessments to guide conservation and restoration efforts.

Using artificial intelligence to analyze massive datasets from satellites, sensors, and field observations to predict where species live, how ecosystems function, and how they might change under different scenarios. These models can identify biodiversity hotspots, predict which areas are most vulnerable to climate change, and help prioritize conservation efforts by showing where interventions will have the biggest impact.