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Limitation of potential yield by phosphorus at the global scale
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Phosphorus (P) is one of the key limitations to crop yields. However, the relationship between soil P and yield is far to be understood at the global scale, given some difficulties in global soil P mapping [Helfenstein et al., 2024], complexities to model soil P dynamics and spatially variable interactions between P and other sources of yield gap (nitrogen, water, pest and diseases).To better understand the P limitation of crop yield at the global scale, we developed here a simple but mechanistic approach (called GPCROP) to simulate the interaction between plant and soil P at daily time-step for one year. The model assumes no other limitation (water, N), and thus allows quantifying the P limitation of potential yield by the current soil P. Simulations are performed for maize at half-degree latitude x longitude spatial resolution.GPCROP combines and builds on four previously developed models that we here combined: a model of potential growth for maize (SIM, [Ringeval et al., 2021]), a model describing the soil P dynamics (GPASOIL, [Ringeval et al., 2024]), a parametrization for the P supply by root (following [Kvakic et al., 2018]), and a model describing the allocation of C and P among plant organs, inspired of [Kvakic et al., 2020]. In particular, the soil P dynamics model allows us to represent the resplenishment of the soil P solution by more stable soil P pools, the parametrization for the P supply by root allows us to represent the diffusion of P in soil and the allocation model, based on an optimization procedure, allows us to represent plant adjustments to P limitation such as change in root:shoot ratio and change in leaf P concentration.Thanks to GPCROP, we quantified the limitation of potential yield by P at the global scale. An uncertainty related to key model parameters and model input was also provided. Simulations underlined the importance of the begin of the growing season when roots are poorly developped in the magnitude of the limitation on final yield. Plant adjustements do particularly matter at that moment of the growing season as they allow (at least partly) to alleviate the P limitation, and we estimated their contribution in the reduction of the global P limitation.References:Helfenstein et al., 2024 : Understanding soil phosphorus cycling for sustainable development: A review. One Earth, S2590332224003737.Kvakic et al., 2018 : Quantifying the Limitation to World Cereal Production Due To Soil Phosphorus Status. Global Biogeochemical Cycles, https://doi.org/10.1002/2017GB005754.Kvakic et al., 2020 : Carbon and Phosphorus Allocation in Annual Plants: An Optimal Functioning Approach. Frontiers in Plant Science, 11:149, https://doi.org/10.3389/fpls.2020.00149.Ringeval et al., 2021 : Potential yield simulated by global gridded crop models: using a process-based emulator to explain their differences. Geoscientific Model Development, 14(3):1639–1656, https://doi.org/10.5194/gmd-14-1639-2021, 2021.Ringeval et al., 2024 : A global dataset on phosphorus in agricultural soils. Scientific Data, 11(1):17, https://doi.org/10.1038/s41597-023-02751-6.
Title: Limitation of potential yield by phosphorus at the global scale
Description:
Phosphorus (P) is one of the key limitations to crop yields.
However, the relationship between soil P and yield is far to be understood at the global scale, given some difficulties in global soil P mapping [Helfenstein et al.
, 2024], complexities to model soil P dynamics and spatially variable interactions between P and other sources of yield gap (nitrogen, water, pest and diseases).
To better understand the P limitation of crop yield at the global scale, we developed here a simple but mechanistic approach (called GPCROP) to simulate the interaction between plant and soil P at daily time-step for one year.
The model assumes no other limitation (water, N), and thus allows quantifying the P limitation of potential yield by the current soil P.
Simulations are performed for maize at half-degree latitude x longitude spatial resolution.
GPCROP combines and builds on four previously developed models that we here combined: a model of potential growth for maize (SIM, [Ringeval et al.
, 2021]), a model describing the soil P dynamics (GPASOIL, [Ringeval et al.
, 2024]), a parametrization for the P supply by root (following [Kvakic et al.
, 2018]), and a model describing the allocation of C and P among plant organs, inspired of [Kvakic et al.
, 2020].
In particular, the soil P dynamics model allows us to represent the resplenishment of the soil P solution by more stable soil P pools, the parametrization for the P supply by root allows us to represent the diffusion of P in soil and the allocation model, based on an optimization procedure, allows us to represent plant adjustments to P limitation such as change in root:shoot ratio and change in leaf P concentration.
Thanks to GPCROP, we quantified the limitation of potential yield by P at the global scale.
An uncertainty related to key model parameters and model input was also provided.
Simulations underlined the importance of the begin of the growing season when roots are poorly developped in the magnitude of the limitation on final yield.
Plant adjustements do particularly matter at that moment of the growing season as they allow (at least partly) to alleviate the P limitation, and we estimated their contribution in the reduction of the global P limitation.
References:Helfenstein et al.
, 2024 : Understanding soil phosphorus cycling for sustainable development: A review.
One Earth, S2590332224003737.
Kvakic et al.
, 2018 : Quantifying the Limitation to World Cereal Production Due To Soil Phosphorus Status.
Global Biogeochemical Cycles, https://doi.
org/10.
1002/2017GB005754.
Kvakic et al.
, 2020 : Carbon and Phosphorus Allocation in Annual Plants: An Optimal Functioning Approach.
Frontiers in Plant Science, 11:149, https://doi.
org/10.
3389/fpls.
2020.
00149.
Ringeval et al.
, 2021 : Potential yield simulated by global gridded crop models: using a process-based emulator to explain their differences.
Geoscientific Model Development, 14(3):1639–1656, https://doi.
org/10.
5194/gmd-14-1639-2021, 2021.
Ringeval et al.
, 2024 : A global dataset on phosphorus in agricultural soils.
Scientific Data, 11(1):17, https://doi.
org/10.
1038/s41597-023-02751-6.
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