Yield response to soil test phosphorus in Switzerland: Pedoclimatic drivers of critical concentrations for optimal crop yields using multilevel modelling.

Phosphorus (P) management in agroecosystems is driven by opposing requirements in agronomy, ecology, and environmental protection. The widely used maintenance P fertilization strategy relies on critical concentrations of soil test P (STP), which should cause the lowest possible impact on the environment while still ensuring optimal yield. While both soil P availability and crop yields are fundamentally related to pedoclimatic conditions, little is known about the extent to which soil and climate variables control critical STP. The official P fertilization guidelines for arable crops in Switzerland are based on empirically derived critical concentrations for two soil test methods (H2O-CO2 and AAE10). To validate those values and evaluate their relation to pedoclimatic conditions, we established nonlinear multivariate multilevel yield response models fitted to long-term data from six sites. The Mitscherlich function proved most suitable out of three functions and model fit was significantly enhanced by taking the multilevel data structure into account. Yield response to STP was strongest for potato, intermediate for barley, and lowest for wheat and maize. Mean critical STP at 95% maximum yield ranged among crops from 0.15-0.58 mg kg-1 (H2O-CO2) and 0-36 mg kg-1 (AAE10). However, pedoclimatic conditions such as annual temperature or soil clay content had a large impact on critical STP, entailing changes of up to 0.9 mg kg-1 (H2O-CO2) and 80 mg kg-1 (AAE10). Critical STP for the AAE10 method was also affected by soil pH. Our findings suggest that the current Swiss fertilization guidelines overestimate actual crop P demand on average and that site conditions account for large parts of the variation in critical STP. We propose that site-specific fertilization recommendations could be improved on the basis of agro-climate classes in addition to soil information, which can help to counteract the accumulation of unutilized soil P by long-term P application.

Enhanced root carbon allocation through organic farming is restricted to topsoils.

Soils store significant amounts of carbon (C) and thus can play a critical role for mitigating climate change. Crop roots represent the main C source in agricultural soils and are particularly important for long-term C storage in agroecosystems. To evaluate the potential of different farming systems to contribute to soil C sequestration and thus climate change mitigation, it is of great importance to gain a better understanding of the factors influencing root C allocation and distribution. So far, it is still unclear how root C allocation varies among farming systems and whether the choice of management practices can help to enhance root C inputs. In this study, we compared root C allocation in three main arable farming systems, namely organic, no-till, and conventional farming. We assessed root biomass, vertical root distribution to 0.75 m soil depth, and root-shoot ratios in 24 winter wheat fields. We further evaluated the relative importance of the farming system compared to site conditions and quantified the contribution of individual management practices and pedoclimatic drivers. Farming system explained one third of the variation in topsoil root biomass and root-shoot ratios, both being strongly positively related to weed biomass and soil organic C content and negatively to mineral nitrogen fertilization intensity. Root C allocation was significantly higher in organic farming as illustrated by an increase in root biomass (+40%) and root-shoot ratios (+60%) compared to conventional farming. By contrast, the overall impact of no-till was low. The importance of pedoclimatic conditions increased substantially with soil depth and deep root biomass was largely controlled by precipitation and soil texture, while the impact of management was close to zero. Our findings highlight the potential of organic farming in promoting root C inputs to topsoils and thereby contributing to soil organic matter build-up and improved soil quality in agroecosystems.

Overestimation of Crop Root Biomass in Field Experiments Due to Extraneous Organic Matter.

Root biomass is one of the most relevant root parameters for studies of plant response to environmental change, soil carbon modeling or estimations of soil carbon sequestration. A major source of error in root biomass quantification of agricultural crops in the field is the presence of extraneous organic matter in soil: dead roots from previous crops, weed roots, incorporated above ground plant residues and organic soil amendments, or remnants of soil fauna. Using the isotopic difference between recent maize root biomass and predominantly C3-derived extraneous organic matter, we determined the proportions of maize root biomass carbon of total carbon in root samples from the Swiss long-term field trial "DOK." We additionally evaluated the effects of agricultural management (bio-organic and conventional), sampling depth (0-0.25, 0.25-0.5, 0.5-0.75 m) and position (within and between maize rows), and root size class (coarse and fine roots) as defined by sieve mesh size (2 and 0.5 mm) on those proportions, and quantified the success rate of manual exclusion of extraneous organic matter from root samples. Only 60% of the root mass that we retrieved from field soil cores was actual maize root biomass from the current season. While the proportions of maize root biomass carbon were not affected by agricultural management, they increased consistently with soil depth, were higher within than between maize rows, and were higher in coarse (>2 mm) than in fine (≤2 and >0.5) root samples. The success rate of manual exclusion of extraneous organic matter from root samples was related to agricultural management and, at best, about 60%. We assume that the composition of extraneous organic matter is strongly influenced by agricultural management and soil depth and governs the effect size of the investigated factors. Extraneous organic matter may result in severe overestimation of recovered root biomass and has, therefore, large implications for soil carbon modeling and estimations of the climate change mitigation potential of soils.