Learning from Nature: Manipulation of plant functional trait-driven plant-soil feedback to agriculture optimization.

Currently, agricultural development in China and globally is confronted with highly significant problems and challenges. One of the critical issues is the rise in the frequency and severity of ecological catastrophes, which recently resulted in replant problems and soil quality degradation. In some places, intensive agricultural production can damage the natural ecological environment, and problem-solving attempts are often designed singularly or linearly. As such, a theoretical basis for the development of systemic solutions is lacking. To fundamentally solve these problems, we need Agricultural Green Development (AGD), which aims at high productivity, high resource efficiency and low environmental impact. Ecological concepts, such Plant-Soil Feedback (PSF), has great potential to build healthy agroecosystems. PSF means that plants alter the soil community, which in turn affects subsequent plant growth. PSFs are often negative in intensive agriculture due to low crop diversity, but if we can steer towards positive PSFs, this may contribute to sustainable agriculture by reducing the need to use crop protection chemicals. From natural ecosystems we know that positive PSF exists and that plant functional traits influence the direction and magnitude of PSF. Moreover, plant traits may be connected to ecosystem functions and hence can help to link PSF to soil multifunctionality. However, how to optimize PSF effects through combining plant traits and manipulating cropping patterns for plant growth and multifunctionality in agroecosystems is not well understood. This research tests how plant functional traits drive the direction and the strength of plant-soil feedback and disentangle suitable plant functional trait combinations that shape positive plant-soil feedback in agroecosystems. This knowledge could be a theoretical base for formulating green solutions to address the new challenges facing agriculture.