Regional estimates of gross primary production applying the Process-Based Model 3D-CMCC-FEM vs. Remote-Sensing multiple datasets

ABSTRACT

Process-based Forest Models (PBFMs) offer the possibility to capture important spatial and temporal patterns of carbon fluxes and stocks in forests. Yet, their predictive capacity should be demonstrated not only at the stand-level but also in the context of broad spatial and temporal heterogeneity. We apply a stand scale PBFM (3D-CMCC-FEM) in a spatially explicit manner at 1 km resolution in southern Italy. We developed a methodology to initialize the model that includes information derived from the integration of Remote Sensing (RS) and the National Forest Inventory (NFI) data and regional forest maps to characterize structural features of the main forest species. Gross primary production (GPP) is simulated over 2005–2019 period and the model predictive capability of the model in simulating GPP is evaluated both aggregated as at species-level through multiple independent data sources based on different nature RS-based products. We show that the model is able to reproduce most of the spatial (~2800 km²) and temporal (32 years in total) patterns of the observed GPP at both seasonal, annual and interannual time scales, even at the species-level. These promising results open the possibility of confindently applying the 3D-CMCC-FEM to investigate the forests’ behaviour under climate and environmental variability over large areas across highly variable ecological and bio-geographical heterogeneity of the Mediterranean region.

KEYWORDS:

• Process-based forest model
• wall-to-wall map
• gross primary production
• national forest inventory
• Mediterranean region

Acknowledgments

The work was carried out in the framework of the project ‘Advanced EO Technologies for studying Climate Change impacts on the environment – OT4CLIMA’ (D.D. 2261 - 6.9.2018, PON R&I 2014–2020 and FSC). This work has been partially supported by MIUR Project (PRIN 2020) “Unraveling interactions between WATER and carbon cycles during drought and their impact on water resources and forest and grassland ecosySTEMs in the Mediterranean climate (WATERSTEM)” (Project number: 20202WF53Z), “WAFER” at CNR (Consiglio Nazionale delle Ricerche) and D.D., E.V., A.C. were supported by PRIN 2020 (cod 2020E52THS) - Research Projects of National Relevance funded by the Italian Ministry of University and Research entitled: “Multi-scale observations to predict Forest response to pollution and climate change” (MULTIFOR, project number 2020E52THS). D.D., E.V., A.C. acknowledge also funding by the project OptForEU H2020 research and innovation programme under grant agreement No. 101060554. We also acknowledge the project funded under the National Recovery and Resilience Plan (NRRP), Mission 4 Component 2 Investment 1.4 - Call for tender No. 3138 of 16 December 2021, rectified by Decree n.3175 of 18 December 2021 of Italian Ministry of University and Research funded by the European Union – NextGenerationEU under award Number: Project code CN_00000033, Concession Decree No. 1034 of 17 June 2022 adopted by the Italian Ministry of University and Research, CUP B83C22002930006, Project title “National Biodiversity Future Centre - NBFC”. We acknowledge the E-OBS dataset from the EU-FP6 project UERRA (https://www.uerra.eu) and the Copernicus Climate Change Service, and the data providers in the ECA&D project (https://www.ecad.eu)”. The FLUXCOM products were obtained from the Data Portal at https://www.fluxcom.org/. D.D. thanks C. Trotta for valuable discussions about tree allometric relationships and thanks M. Willeit and E. Grieco for providing comments on a previous draft of the manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/22797254.2023.2301657.

Author contribution

Daniela Dalmonech: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Resources, Software, Validation, Visualization, Writing – original draft. Elia Vangi, Gherardo Chirici, and Francesca Giannetti: Resources, Writing – review & editing. Jingfend Xiao: Resources, Writing – review & editing; Marta Chiesi and Luca Fibbi: Resources, Writing – review & editing. Gina Marano: Software, Writing – review & editing Christian Massari: Writing – review & editing. Angelo Nole: Resources, Writing – review & editing. Alessio Collalti: Conceptualization, Formal analysis, Investigation, Methodology, Resources, Software, Validation, Visualization, Writing – review & editing, Funding aquisition.

Data availability statement

The 3D-CMCC-FEM model code version 5.6 is publicly available under the GNU General Public Licence v3.0 (GPL) and can be found on the GitHub platform at: https://github.com/Forest-Modelling-Lab/3D-CMCC-FEM). All data and model executable, and scripts to perform analyses and figures presented in this work are provided open access in the Zenodo server (https://doi.org/10.5281/zenodo.8060401). Correspondence and requests for additional materials should be addressed to the corresponding author.

Additional information

Funding

This work was supported by the Consiglio Nazionale delle Ricerche ['WAFER' @ CNR]; Horizon 2020 Framework Programme [OptForEU H2020 No. 101060554]; Ministero dell’Istruzione, dell’Università e della Ricerca ['WATERSTEM ' Project number: 20202WF53Z].