A process-based model of nitrogen cycling in forest plantations: Part I. Structure,calibration and analysis of the decomposition model |
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| Institution: | 1. CSIRO Forestry and Forest Products, Private Bag 5, Wembley, WA 6913, Australia;2. CIRAD, EMBRAPA-Cerrados, Km 18, BR 020, CP 08223, 73301-970 Planaltina, DF, Brazil;3. School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, NSW 2052, Australia;1. Departamento de Estadística y Métodos de Gestión en Agricultura, Universidad Politécnica de Madrid, Madrid, Spain;2. Estación Experimental de Zonas Áridas, Consejo Superior de Investigaciones Científicas (EEZA-CSIC), Almería, Spain;3. Departamento de Ingeniería Rural, Universidad de Córdoba, Córdoba, Spain;4. Instituto de Agricultura Sostenible, Consejo Superior de Investigaciones Científicas (IAS-CSIC), Córdoba, Spain;1. Real-Time Systems Lab, Merckstr. 25, 64283 Darmstadt, Germany;2. Telecooperation Group, Hochschulstr. 10, 64289 Darmstadt, Germany;3. Secure Mobile Networking Lab, Mornewegstr. 32, 64293 Darmstadt, Germany;1. Institut D’Economie Rurale (IER), Programme Coton, SRA N’Tarla Bp: 28 Koutiala, Mali;2. International Crops Research Institute for the Semi-Arid Tropics (ICRISAT-Mali), BP 320 Bamako, Mali;3. Plant Production Systems, Wageningen University, P.O. Box 430, 6700 AK Wageningen, The Netherlands;4. Livestock Systems and the Environment, International Livestock Research Institute (ILRI), P.O. Box 30709, 00100 Nairobi, Kenya;5. Agro-ecology and Sustainable Intensification of Annual Crops, Centre de Coopération Internationale en Recherche Agronomique pour le Développement (CIRAD)-Av. Agropolis, 34060 Montpellier, France;6. Sustainable Intensification Program, International Maize and Wheat Improvement Center (CIMMYT), P.O. Box 1041-00621, Gigiri, Nairobi, Kenya;7. Earth System Science and Climate Adaptive Land Management, Wageningen University and Research, P.O. Box 47, 6700 AK Wageningen, The Netherlands;1. Department of Earth System Science and Center on Food Security and the Environment, Stanford University, Stanford, CA 94305, USA;2. Department of Natural Resources and Environmental Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA;3. Sorbonne Universités (UPMC, Univ Paris 06)-CNRS-IRD-MNHN, LOCEAN/IPSL, 4 place Jussieu, F-75005 Paris, France;4. Lamont-Doherty Earth Observatory, Earth Institute at Columbia University, Palisades, NY, USA;5. CIRAD UMR TETIS, Maison de la Télédétection, 500 rue Jean François Breton, Montpellier 34093, France;1. Department of Physical Geography, Stockholm University, Svante Arrhenius väg 8C, Frescati, SE-106 91 Stockholm, Sweden;2. Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden;3. Department of Bioclimatology, Georg-August-Universität, Göttingen, Niedersachsen, Germany;4. Department of Ecology, Swedish University of Agricultural Sciences, Uppsala, Sweden;5. Department of Ecology, Evolution and Marine Biology, University of California Santa Barbara, Santa Barbara, CA, USA |
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| Abstract: | We present a new decomposition model of C and N cycling in forest ecosystems that simulates N mineralisation from decomposing tree litter. It incorporates a mechanistic representation of the role of soil organisms in the N mineralisation-immobilisation turnover process during decomposition. We first calibrate the model using data from decomposition of 14C-labelled cellulose and lignin and 14C-labelled legume material and then calibrate and test it using mass loss and N loss data from decomposing Eucalyptus globulus residues. The model has been linked to the plant production submodel of the G’DAY ecosystem model, which previously used the CENTURY decomposition submodel for simulating C and N cycling. The key differences between this new decomposition model and the previous one, based on the CENTURY model, are: (1) growth of microbial biomass is the process that drives N mineralisation-immobilisation, and microbial succession is simulated; (2) decomposition of litter can be N-limited, depending on soil inorganic N availability relative to N requirements for microbial growth; (3) ‘quality’ of leaf and fine root litter is expressed in terms of biochemically measurable fractions; (4) the N:C ratio of microbial biomass active in decomposing litter is a function of litter quality and N availability; and (5) the N:C ratios of soil organic matter (SOM) pools are not prescribed but are instead simulated output variables defined by litter characteristics and soil inorganic N availability. With these modifications the model is able to provide reasonable estimates of both mass loss and N loss by decomposing E. globulus leaf and branch harvest residues in litterbag experiments. A sensitivity analysis of the decomposition model to selected parameters indicates that parameters regulating the stabilisation of organic C and N, as well as those describing incorporation of soil inorganic N in Young-SOM (biochemical immobilisation of N) are particularly critical for long-term applications of the model. A parameter identifiability analysis demonstrates that simulated short-term C and N loss from decomposing litter is highly sensitive to three model parameters that are identifiable from the E. globulus litterbag data. |
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