Farm networks

Understanding why insect pests, weeds, and diseases (collectively called pests here) vary between fields and years is an important challenge in agriculture. Why do some fields consistently experience higher pest pressure than others? Why are certain years particularly severe? And do specific combinations of pests, weeds, and diseases tend to occur together—and if so, what drives these assemblages?

​

To address these questions, we are building large, integrated datasets that combine ecological, agronomic, and environmental information across networks of 50 commercial farms in Denmark and England. Rather than relying solely on traditional, controlled field experiments (which we also conduct - see our field experiments section), we focus on capturing the complexity of real-world farming systems. This allows us to study pest dynamics under the full range of conditions that farmers experience.

​

Each year, across autumn, spring, and summer, we monitor the presence, abundance, and spatial distribution of pests and beneficial organisms. Most of this work is carried out ‘on-the ground’ in the field by teams of agroecologists, generating detailed, high-resolution observations of agroecosystem biodiversity.

​

But data on the pesence of pests and beneficials alone are not enough. We also compile extensive environmental and management metadata, including weather patterns, soil characteristics, land use, and landscape structure. Crucially, we collaborate closely with farmers to access detailed field management histories. This combination of biological, environmental, and management data, collected consistently over multiple years, provides a powerful foundation for analysis.

​

Using these data, we will develop models to identify the key drivers of variation in pest, weed, and disease dynamics across space and time. Which environmental conditions promote or suppress outbreaks? Which management practices reduce pest pressure? And how do different components of the agroecosystem and crop management interact?

​

We treat each of the ~200 fields in our network as part of a large, distributed experiment. By leveraging this real-world variability, we aim to generate robust, generalisable insights into crop health and agroecosystems function. Ultimately, our goal is to identify the environmental and management factors that naturally regulate pest populations and to support the development of more sustainable, One Crop Health approaches that reduce reliance on pesticides.