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Short Abstract

We co-designed a moth monitoring activity with farmers using portable LED light traps and an AI-based identification app. The project contributed to biodiversity monitoring and supported farmer engagement, highlighting the value of farmer-led citizen science initiatives.

Abstract

Farmland is an underrepresented landscape in biodiversity monitoring, despite its crucial role in agri-food systems. In this project, we explored how co-designed citizen science can support biodiversity data collection and nature engagement. We co-designed a moth recording activity with farmers, informed by interviews on their needs and perspectives. In 2024, farmers recorded moths weekly using portable LED light traps and an AI (artificial intelligence)-based identification app. Following expert verification, 5209 moths were confirmed from images, representing 279 species/aggregates. AI identifications were correct for 82% of photos of macro moths; the remainder either incorrect (2% of identifications), unidentified (11%) or correct to higher taxonomic levels (4%). The project revealed that farmers were interested and curious about moths, a taxonomic group often overlooked, however, time availability was a key barrier to participation. This project demonstrates how co-designed, tech-enabled citizen science can empower farmers to monitor biodiversity and highlights the potential for farmer-led initiatives to build bridges between land stewardship, digital innovation, and ecological knowledge, supporting more sustainable and connected food systems.