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SPACSYS: Integration of a 3D root architecture component to carbon, nitrogen and water cycling—Model description

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  • Wu, L.
  • McGechan, M.B.
  • McRoberts, N.
  • Baddeley, J.A.
  • Watson, C.A.

Abstract

It is an ongoing challenge to develop and demonstrate management practices that increase the sustainability of agricultural systems. Soil carbon and nitrogen dynamics directly affect soil quality, crop productivity and environmental impacts. Root systems are central to the acquisition of water and nutrients by plants, but are also a major pathway for the inputs of carbon and nutrients to soil. The complexity of both biotic and abiotic interactions, combined with stochastic changes in root architecture, makes it difficult to understand below-ground dynamics on the basis of experimentation alone. The integration of dynamic models of above-ground growth, three-dimensional root system demography, and interactions between plants and the environment, into one single model is a major challenge because of the complexity of the systems.

Suggested Citation

  • Wu, L. & McGechan, M.B. & McRoberts, N. & Baddeley, J.A. & Watson, C.A., 2007. "SPACSYS: Integration of a 3D root architecture component to carbon, nitrogen and water cycling—Model description," Ecological Modelling, Elsevier, vol. 200(3), pages 343-359.
  • Handle: RePEc:eee:ecomod:v:200:y:2007:i:3:p:343-359
    DOI: 10.1016/j.ecolmodel.2006.08.010
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    References listed on IDEAS

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    1. David Tilman & Kenneth G. Cassman & Pamela A. Matson & Rosamond Naylor & Stephen Polasky, 2002. "Agricultural sustainability and intensive production practices," Nature, Nature, vol. 418(6898), pages 671-677, August.
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    Cited by:

    1. Yan Shan & Mingbin Huang & Paul Harris & Lianhai Wu, 2021. "A Sensitivity Analysis of the SPACSYS Model," Agriculture, MDPI, vol. 11(7), pages 1-30, July.
    2. Höglind, Mats & Cameron, David & Persson, Tomas & Huang, Xiao & van Oijen, Marcel, 2020. "BASGRA_N: A model for grassland productivity, quality and greenhouse gas balance," Ecological Modelling, Elsevier, vol. 417(C).
    3. Quan, Hao & Ding, Dianyuan & Wu, Lihong & Qiao, Ruonan & Dong, Qin'ge & Zhang, Tibin & Feng, Hao & Wu, Lianhai & Siddique, Kadambot H.M., 2022. "Future climate change impacts on mulched maize production in an arid irrigation area," Agricultural Water Management, Elsevier, vol. 266(C).
    4. Wu, L. & Harris, P. & Misselbrook, T.H. & Lee, M.R.F., 2022. "Simulating grazing beef and sheep systems," Agricultural Systems, Elsevier, vol. 195(C).
    5. Wang, Yuehua & Wang, Zhongwu & Wu, Lianhai & Li, Haigang & Li, Jiangwen & Zhu, Aimin & Jin, Yuxi & Han, Guodong, 2024. "Effects of grazing and climate change on aboveground standing biomass and sheep live weight changes in the desert steppe in Inner Mongolia, China," Agricultural Systems, Elsevier, vol. 217(C).
    6. Yin, Xiaogang & Kersebaum, Kurt Christian & Kollas, Chris & Manevski, Kiril & Baby, Sanmohan & Beaudoin, Nicolas & Öztürk, Isik & Gaiser, Thomas & Wu, Lianhai & Hoffmann, Munir & Charfeddine, Monia & , 2017. "Performance of process-based models for simulation of grain N in crop rotations across Europe," Agricultural Systems, Elsevier, vol. 154(C), pages 63-77.
    7. Tyre, Andrew & Kerr, Gregory D. & Tenhumberg, Brigitte & Bull, C. Michael, 2007. "Identifying mechanistic models of spatial behaviour using pattern-based modelling: An example from lizard home ranges," Ecological Modelling, Elsevier, vol. 208(2), pages 307-316.
    8. Bown, James L. & Pachepsky, Elizaveta & Eberst, Alistair & Bausenwein, Ursula & Millard, Peter & Squire, Geoff R. & Crawford, John W., 2007. "Consequences of intraspecific variation for the structure and function of ecological communities," Ecological Modelling, Elsevier, vol. 207(2), pages 264-276.
    9. Gaiser, Thomas & Perkons, Ute & Küpper, Paul Martin & Kautz, Timo & Uteau-Puschmann, Daniel & Ewert, Frank & Enders, Andreas & Krauss, Gunther, 2013. "Modeling biopore effects on root growth and biomass production on soils with pronounced sub-soil clay accumulation," Ecological Modelling, Elsevier, vol. 256(C), pages 6-15.
    10. Li, Songyang & Gao, Jixun & Zhu, Qingsheng & Zeng, Lingqiu & Liu, Ji, 2015. "A dynamic root simulation model in response to soil moisture heterogeneity," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 113(C), pages 40-50.
    11. Richard Morris & Shannon Davis & Gwen-Aëlle Grelet & Crile Doscher & Pablo Gregorini, 2024. "A Model for Spatially Explicit Landscape Configuration and Ecosystem Service Performance, ESMAX: Model Description and Explanation," Sustainability, MDPI, vol. 16(2), pages 1-23, January.
    12. Wu, Lianhai & Curceac, Stelian & Atkinson, Peter M. & Milne, Alice & Harris, Paul, 2021. "A case study on the effects of data temporal resolution on the simulation of water flux extremes using a process-based model at the grassland field scale," Agricultural Water Management, Elsevier, vol. 255(C).
    13. Wu, Lianhai & Wu, Lu & Bingham, Ian J. & Misselbrook, Thomas H., 2022. "Projected climate effects on soil workability and trafficability determine the feasibility of converting permanent grassland to arable land," Agricultural Systems, Elsevier, vol. 203(C).
    14. Chuang Liu & Huiyi Yang & Kate Gongadze & Paul Harris & Mingbin Huang & Lianhai Wu, 2022. "Climate Change Impacts on Crop Yield of Winter Wheat ( Triticum aestivum ) and Maize ( Zea mays ) and Soil Organic Carbon Stocks in Northern China," Agriculture, MDPI, vol. 12(5), pages 1-12, April.
    15. Lu Wu & Thomas H. Misselbrook & Liping Feng & Lianhai Wu, 2020. "Assessment of Nitrogen Uptake and Biological Nitrogen Fixation Responses of Soybean to Nitrogen Fertiliser with SPACSYS," Sustainability, MDPI, vol. 12(15), pages 1-17, July.
    16. Kipling, Richard P. & Bannink, André & Bellocchi, Gianni & Dalgaard, Tommy & Fox, Naomi J. & Hutchings, Nicholas J. & Kjeldsen, Chris & Lacetera, Nicola & Sinabell, Franz & Topp, Cairistiona F.E. & va, 2016. "Modeling European ruminant production systems: Facing the challenges of climate change," Agricultural Systems, Elsevier, vol. 147(C), pages 24-37.

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