The engine of soil health: Food web functioning and its drivers

Dead organic matter enters the soil, undergoing transformation, decomposition, sequestration, or respiration. These biological processes, along with functions like herbivory, predation, and parasitism, are regulated by soil food webs. Consequently, variations in soil food web structure and function provide insights into the overall dynamics of the soil ecosystem, including various aspects of soil health. We are making initial strides in understanding how soil food webs vary across environmental gradients, which may help establish mechanistic and comprehensive links between soil communities and soil health.

This summary presents several recent projects employing an energy flux approach to explore the development of soil animal food webs and their structural and functional responses to climate and land use. Aligning with classical ecosystem development theory, we showed a progression in soil food webs from fast-turnover systems with high herbivory and predation (the ‘green’ state) to low-turnover systems reliant on detritus consumption (the ‘brown’ state). We observed a similar trend in energy distribution among micro-, meso-, and macrofauna in temperate (Germany, Russia) and tropical forest soil food webs (Vietnam, Indonesia). Our results indicated that tropical food webs have higher energy flux, predation rates, and herbivory, while temperate food webs have higher bacterivory and litter feeding. Additionally, a comparison between forest and agricultural systems in Indonesia and Argentina revealed that land use does not reduce energy flux in soil food webs but significantly restructures energy pathways based on land-use type. Intensively managed systems typically have decreased predation and increased basal consumption, mainly due to earthworm dominance. However, changes in individual trophic functions appear sensitive to specific land use and management practices.

These findings suggest promise for future development of soil food web diagnostic tools to enhance our understanding of functional consequences of ecosystem management on soil health. New technologies, such as AI-assisted image analysis, may enable over 95% automation of this diagnostic process.