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Modelling and inference of maize pollen emission rate with a Lagrangian dispersal model using Monte Carlo method

Published online by Cambridge University Press:  01 October 2020

Otmane Souhar Open the ORCID record for Otmane Souhar [Opens in a new window] ,
Alexis Marceau  and
Benjamin Loubet Open the ORCID record for Benjamin Loubet [Opens in a new window]
Otmane Souhar*
Affiliation:
LIMA Laboratory, University of Chouaib Doukkali, BP. 20, 24000 El Jadida, Morocco
Alexis Marceau
Affiliation:
National Institute of Agronomic Research, UMR EcoSys INRAE-AgroParisTech, 78850, Thiverval-Grignon, France
Benjamin Loubet
Affiliation:
National Institute of Agronomic Research, UMR EcoSys INRAE-AgroParisTech, 78850, Thiverval-Grignon, France
*
Author for correspondence: Otmane Souhar, E-mail: souhar.o@ucd.ac.ma
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Abstract

This work explores the uncertainty of the inferred maize pollen emission rate using measurements and simulations of pollen dispersion at Grignon in France. Measurements were obtained via deposition of pollen on the ground in a canopy gap; simulations were conducted using the two-dimensional Lagrangian Stochastic Mechanistic mOdel for Pollen dispersion and deposition (SMOP). First, a quantitative evaluation of the model's performance was conducted using a global sensitivity analysis to analyse the convergence behaviour of the results and scatter diagrams. Then, a qualitative study was conducted to infer the pollen emission rate and calibrate the methodology against experimental data for several sets of variable values. The analysis showed that predicted and observed values were in good agreement and the calculated statistical indices were mostly within the range of acceptable model performance. Furthermore, it was revealed that the mean settling velocity and vertical leaf area index are the main variables affecting pollen deposition in the canopy gap. Finally, an estimated pollen emission rate was obtained according to a restricted setting, where the model studied includes no deposition on leaves, no resuspension and with horizontal pollen fluctuations either taken into account or not. The estimated pollen emission rate obtained was nearly identical to the measured quantity. In conclusion, the findings of the current study show that the described methodology could be an interesting approach for accurate prediction of maize pollen deposition and emission rates and may be appropriate for other pollen types.

Keywords

Lagrangian stochastic approachMonte Carlo methodpollen dispersion and depositionsensitivity analysis
Type
Crops and Soils Research Paper
Information
The Journal of Agricultural Science , Volume 158 , Issue 5 , July 2020 , pp. 383 - 395
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Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

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