Speaker
Description
1. Introduction
The synergy between different technologies such as field sensors and crop models is fundamental for crop monitoring growth and yield, while assessing climate change impacts at both field and broader scales. In the perspective of climate change mitigation, the implementation of biogeochemical cycles within crop models is essential to evaluate water and carbon (C) fluxes and C sequestration capacity of the agro-ecosystems. This requires an accurate monitoring of those cropping systems in which the atmospheric C can be stored and long-time sequestered in biomass compartments (i.e. vineyards and orchards). In this work, the first version of UNIFI.GrapeML model (Leolini et al., 2018), previously based on the radiation use efficiency approach for simulating biomass growth and development, was implemented with modules simulating water competition between tree and grass layers and soil carbon fluxes. Methodological approach (Fig. 1) and preliminary results are presented here.
2. Materials and Methods
The UNIFI.GrapeML model was initially coupled with the GRASSVISTOCK model (Leolini et al., submitted), which included the grass and soil carbon modules (RothC model, Coleman & Jenkison, 1996), to account grass growth dynamics, water competition and carbon fluxes in vineyards. The grass module was calibrated and validated under different climates in Italy (Torgnon: 45.84°N, 7.58°E and Borgo S. Lorenzo: 43.95°N, 11.35°E) to simulate daily fractional transpirable soil water (FTSW), net ecosystem exchange (NEE), gross primary production (GPP) and ecosystem respiration (Reco) in agro-pastoral systems. Currently, this module is integrated in UNIFI.GrapeML, and under testing, for evaluating its capability in vine biomass C-partitioning and inter-row grass growth in Mediterranean vineyards.
Figure 1 – UNIFI.GrapeML workflow
3. Results
The first results provided by the grass module showed satisfactory performances at simulating biomass (Torgnon: r = 0.68; RMSE = 72.79 g m-2 dry matter; Borgo S. Lorenzo: r = 0.78; RMSE = 67.46 g m-2 dry matter) and FTSW (Torgnon: r = 0.88; RMSE = 0.13; Borgo S. Lorenzo: r = 0.95; RMSE = 0.13) in pastures. Daily C-fluxes simulations, carried out only at Torgnon, confirmed the goodness of the simulations (NEE: r = 0.60; RMSE = 0.02 Mg C ha-1; GPP: r = 0.84; RMSE = 0.02 Mg C ha-1; Reco: r = 0.67; RMSE = 0.02 Mg C ha-1).
4. Discussion
The simulation of ecophysiological processes (i.e. biomass growth, water and C fluxes) of plant species is challenging in cropping systems composed of multiple vegetation layers such as vineyards and orchards. To our best knowledge, current grapevine growth models are not able to well represent ecosystem fluxes, since processes such as water competition between vegetation layers and soil organic carbon turnover from different residues are still not included (Moriondo et al., 2015). In this context, the implementation of UNIFI.GrapeML is a fundamental step to reduce uncertainties in the dynamics of biomass growth, soil water content and soil C fluxes estimates, thereby promoting optimization of agronomic practices with regards to productivity and climate mitigation.
Acknowledgements
The publication was made by researcher Luisa Leolini with a research contract co-funded by the European Union - PON Research and Innovation 2014-2020 in accordance with Article 24, paragraph 3a), of Law No. 240 of December 30, 2010, as amended and Ministerial Decree No. 1062 of August 10, 2021.
5. References
Coleman, K., et al. RothC-26.3-A Model for the turnover of carbon in soil. In Evaluation of soil organic matter models: using existing long-term datasets. Springer Berlin Heidelberg, 237-246, 1996.
Leolini, L., et al. A model library to simulate grapevine growth and development: Software implementation, sensitivity analysis and field level application. European Journal of Agronomy, 99, 92-105, 2018.
Leolini, L., et al. Modeling carbon and water fluxes in agro-pastoral systems under contrasting climates and different management practices. Agriculture and Forestry Meteorology, submitted.
Moriondo, M., et al. Modelling olive trees and grapevines in a changing climate. Environmental Modelling & Software, 72, 387-401, 2015.
| Keywords | biogeochemical cycles; crop modeling; inter-row grass cover; vineyard management |
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