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Description
Introduction
Weeds compete with crops for light, minerals and water, and weed-related yield losses will probably increase with climate change (drought, heat waves), under the influence of competitive weeds, in particular for increasingly scarcer water resources (Storkey et al., 2021). Thus, cropping systems must be redesigned to make weed management low-input and climate-resilient. FLORSYS is a 3D mechanistic model (Colbach et al., 2021) that can be used to investigate such issues. It simulates the multi-annual dynamics of weeds and their harmfulness (e.g. yield losses) and benefits (e.g. trophic supply for crop auxiliaries) from cropping system (rotation, cultivars, cropping techniques) and pedoclimate. However, FLORSYS does not include all mechanisms relevant to climate change, in particular plant-plant competition for water. To better forecast future weed dynamics in arable cropping systems, this work aimed at developing a water competition submodel for FLORSYS.
Material and methods
The submodel was customised for FLORSYS and connected to other submodels (e.g. growth and phenology, light and nitrogen competition). When possible, it reused existing formalisms. The submodel was designed to be generic across crop and weed species, with few parameters.
Results
As in Aschehoug et al. (2016), the submodel modelled: (1) water availability, demand, competition and uptake at the voxel (3D pixel) scale, as for light and nitrogen competitions (Munier-Jolain et al., 2013; Moreau et al., 2021) and (2) the consequences of water stress on photosynthesis and morphology at the plant scale (Figure 1).
The potential water uptake of a plant in each voxel occupied by its roots is the minimum of (1) its water demand in the voxel, downscaled from total plant demand according to soil water distribution (formalisms from ‘Virtual Grassland’, Louarn and Faverjon (2018)), (2) the amount of water available to plants in the voxel (linked with the STICS soil submodel, Brisson et al. (2008)) and (3) the maximum amount of water roots can take up (experiment of Cournault et al. (2024)). Competition among plants with roots in the voxel only occurs if the available water is insufficient to meet their potential uptakes. After completing the loop across soil voxels, it is possible that some plants did not take up enough water to fulfil their demands in some voxels, while water remains in other occupied voxels. Thus, a second uptake loop is run across voxels to compensate for the initial insufficient uptake.
The plant's total water uptake is the sum of water uptakes over all occupied voxels. For each plant, a daily water stress index is computed as “1 - the ratio of water uptake to water demand”. To account for past stresses, the daily indexes are combined into a relative linear combination over the plant life (since emergence), with a greater weight for recent stresses. Together with shading and nitrogen stress indexes, the water stress index can affect photosynthesis (according to DSSAT/APSIM formalisms, Ritchie (1998)), and plant morphology (new formalisms from Cournault et al. (2024), first presentation in this congress).
Discussion
FLORSYS becomes the first crop-weed model to account for light, water and nitrogen competitions, with new formalisms accounting for maximum root water uptake and water-stress effects on plant morphology. The new submodel includes only 7 new parameters, in line with FLORSYS’ spirit. It disregards daily lateral soil water flows, but this is consistent with FLORSYS' focus on multiannual cropping system evaluation (Colbach et al., 2021).
Conclusion
The new FLORSYS version is expected to improve the credibility of flora projections in the context of climate change. Once the model has been evaluated with field observations, it will be used in simulation studies and participatory workshops with farmers and crop advisors, to design sustainable low-input and climate-resilient cropping systems.
References
Aschehoug, E.T. et al., 2016. https://doi.org/10.1146/annurev-ecolsys-121415-032123
Brisson, N. et al., 2008. ISBN: 2759202909, 9782759202904
Colbach, N. et al., 2021. https://doi.org/10.1016/j.fcr.2020.108006
Cournault, Q. et al., 2024. Submitted to Environ. Exp. Bot.
Louarn, G., Faverjon, L., 2018. https://doi.org/10.1093/aob/mcx154
Moreau, D. et al., 2021. https://doi.org/10.1016/j.fcr.2021.108166
Munier-Jolain, N.M. et al., 2013. https://doi.org/10.1016/j.ecolmodel.2012.10.023
Queyrel, W. et al., 2023. https://doi.org/10.1016/j.agsy.2023.103645
Ritchie, J.T., 1998. https://doi.org/10.1007/978-94-017-3624-4_3
Storkey, J. et al., 2021. https://doi.org/10.1111/gcb.15585
| Keywords | Model; Weed/crop water competition ; Climate change; Arable cropping systems; Sustainable crop production |
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