Brewing biodiversity: AI-powered acoustic monitoring of birds in coffee landscapes

Moonshot Award

Proposal Development

Abstract

Using AI-powered research, we aim to uncover novel insights into how regenerative agricultural practices affect bird communities. Globally, large-scale habitat modification from intensive agriculture has driven declines in more than half of all bird species. In contrast, regenerative agricultural systems, such as those that employ agroforestry, have high potential to support both biodiversity and sustainable livelihoods. For example, shade-grown coffee grown alongside native tree species can provide a crucial refuge for birds. However, studies of birds in agroforests remain limited as traditional approaches for impact assessment are resource-intensive, time-consuming, and lack the ability to simultaneously monitor large geographies. 

Emerging conservation technologies such as passive acoustic monitoring can help overcome these existing barriers to monitoring. By pairing large-scale audio sampling with deep-learning algorithms, it is now possible to cost-effectively detect and identify species across multiple landscapes simultaneously. As part of the CALS Moonshot Seed Grant Program, we are integrating AI and conservation technologies to study the impacts of regenerative agricultural practices on birds across smallholder coffee farms in India. By linking ecological data (derived from AI-based analyses) with on-the-ground farming practices, we aim to generate insights that directly inform biodiversity-friendly land management guidelines.