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Construction and evaluation of ALOMYSYS modelling the effects of cropping systems on the blackgrass life-cycle: From seedling to seed production

Author

Listed:
  • Colbach, N.
  • Chauvel, B.
  • Gauvrit, C.
  • Munier-Jolain, N.M.

Abstract

Blackgrass (Alopecurus myosuroides Huds.) is an annual weed frequently found in winter crops and increasingly tolerant to herbicides. To manage this weed with less or no herbicides, the model ALOMYSYS was developed to quantify the effects of cropping systems on the demography of blackgrass. The sub-model for seed survival, dormancy, germination and pre-emergent growth was described in a previous paper. This paper presents the sub-model quantifying seedling survival, tillering, heading, flowering and seed production, as a function of the weed emergence date and density (predicted by the seed bank sub-model), the crops grown in the field, the cultivation techniques used to manage the crop (tillage, sowing, herbicides, nitrogen, harvest) and the climate (temperature, rainfall). The sub-model is based on the annual life-cycle of blackgrass; the relationship between the various life-stages depends on the model input variables and on the characteristics of the weed population (e.g. tillering decreases with weed density, herbicide efficacy decreases with plant stage and density, etc.). The equations describing the life-stages and processes were deduced from previous greenhouse experiments and field trials. The resulting model was evaluated by comparing the simulations to independent field observations. This validation showed the model to accurately predict weed stages for a given year as well as the dynamics over the years, in contrasted cropping systems. The model can thus be used to evaluate and design new cropping systems for integrated crop protection.

Suggested Citation

  • Colbach, N. & Chauvel, B. & Gauvrit, C. & Munier-Jolain, N.M., 2007. "Construction and evaluation of ALOMYSYS modelling the effects of cropping systems on the blackgrass life-cycle: From seedling to seed production," Ecological Modelling, Elsevier, vol. 201(3), pages 283-300.
    • Handle: RePEc:eee:ecomod:v:201:y:2007:i:3:p:283-300
    DOI: 10.1016/j.ecolmodel.2006.09.018
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    References listed on IDEAS

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    1. Wiles, L. J. & King, R. P. & Schweizer, E. E. & Lybecker, D. W. & Swinton, S. M., 1996. "GWM: General weed management model," Agricultural Systems, Elsevier, vol. 50(4), pages 355-376.
    2. Pekrun, C. & Lane, P.W. & Lutman, P.J.W., 2005. "Modelling seedbank dynamics of volunteer oilseed rape (Brassica napus)," Agricultural Systems, Elsevier, vol. 84(1), pages 1-20, April.
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    Cited by:

    1. Gardarin, Antoine & Dürr, Carolyne & Colbach, Nathalie, 2012. "Modeling the dynamics and emergence of a multispecies weed seed bank with species traits," Ecological Modelling, Elsevier, vol. 240(C), pages 123-138.
    2. Metcalfe, H. & Milne, A.E. & Coleman, K. & Murdoch, A.J. & Storkey, J., 2019. "Modelling the effect of spatially variable soil properties on the distribution of weeds," Ecological Modelling, Elsevier, vol. 396(C), pages 1-11.
    3. Lodovichi, Mariela V. & Blanco, Aníbal M. & Chantre, Guillermo R. & Bandoni, J. Alberto & Sabbatini, Mario R. & Vigna, Mario & López, Ricardo & Gigón, Ramón, 2013. "Operational planning of herbicide-based weed management," Agricultural Systems, Elsevier, vol. 121(C), pages 117-129.

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