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Seasonal dynamics and depth distribution of belowground biomass carbon and nitrogen of extensive grassland and a Miscanthus plantation

GND
1025492234
Affiliation
Thünen Institute of Climate-Smart AgricultureBraunschweigGermany
Poeplau, Christopher;
Affiliation
Institute of Geoecology, Department of Soil Science and Soil PhysicsTechnical University of BraunschweigBraunschweigGermany
Germer, Kai;
GND
1058991647
Affiliation
Julius Kühn-Institut (JKI), Federal Research Centre of Cultivated Plants, Institute for Crop and Soil Science, Braunschweig, Germany ; Institute of Landscape and Plant Ecology, University of Hohenheim, Stuttgart, Germany
Schwarz, Kai-Uwe

Background and aims Belowground carbon (C) inputs are a major source of soil organic carbon (SOC) in terrestrial ecosystems, and substrate C:N ratios drive SOC stabilisation. In perennial systems, quantitative information on seasonal dynamics of belowground biomass is scarce, but necessary, e.g. to improve SOC modelling and representative sampling. Methods Seasonal dynamics and depth distribution of belowground biomass C and N of extensive grassland and Miscanthus on sandy soil were estimated. Core samples (1 m depth) were taken six times in 1 year. Miscanthus-derived SOC was quantified using 13C natural abundance. Results Grassland and Miscanthus differed strongly in belowground biomass C (2.5 ± 0.3 vs. 7.3 ± 1.1 Mg ha−1) and C:N ratios (28.6 ± 0.5 vs. 60 ± 3.3). Peak grassland belowground biomass C and N stocks occurred in summer, while those of rhizomatous Miscanthus were in winter due to different strategies of resource allocation. Grassland roots showed a strong seasonal pattern of C:N ratios, indicating N remobilisation. Miscanthus-derived topsoil SOC was low relative to the high belowground biomass, indicating a slow transfer of rhizome carbon to bulk SOC. Conclusions Representative belowground biomass sampling of perennials should take seasonal dynamics into account, especially in system comparisons. Furthermore, C inputs from rhizome and roots should be estimated separately owing to likely differences in turnover times. Keywords

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