CliCFor

CliCFor — Unravelling seasonal to decadal CLImate influence on the Carbon cycle in FORest

CliCFor investigates how climate variability, extremes, and long‑term trends affect forest carbon cycling across contrasting environments. This repository hosts materials related to the PRIN 2022 project 2022ETAB7T (24 months), combining eddy covariance fluxes, tree‑ring quantitative wood anatomy, stable isotopes, and process‑based modelling to understand when flux‑based and biomass‑based signals converge or diverge.

• Status
• Project rationale
• Approach
• Study sites
• Research units and roles
• Project participants
• Work packages
• Model used in the project
• Dissemination and communication
• Data policy and availability
• Repository scope
• Repository structure
• How to cite
• License
• Acknowledgment
• Contact
• Contributing

🚧 Active cleanup / progressive update.
This repository is being reorganized to improve documentation, data provenance, and reproducible analysis workflows.

• Documentation and initial processed datasets are available.
• Analysis scripts and reusable functions are being added incrementally.
• Some raw datasets (e.g., full eddy covariance exports) may not be redistributed here (see Data policy).

Forest carbon sinks are central to climate-change mitigation, but the relationship between ecosystem carbon uptake and woody biomass accumulation is still only partially understood. CliCFor was designed to investigate the causal relationships between climate, primary productivity, and wood biomass, and to explain why flux-based and biomass-based estimates of forest carbon sequestration may diverge.

The project combines approaches that are often used separately:

• long eddy covariance time series
• tree-ring anatomy and biomass proxies
• stable carbon isotope analyses
• statistical and process-based modeling

High‑level components:

• Eddy covariance flux processing and analysis (quality control, partitioning, gap filling; daily to multi‑decadal variability)
• Tree‑ring analyses including quantitative wood anatomy to reconstruct wood formation/biomass proxies at finer temporal resolution than ring width alone
• Stable carbon isotopes (e.g., δ¹³C in earlywood vs latewood) to support physiological interpretations (e.g., intrinsic water‑use efficiency)
• Integrated modelling to test causal hypotheses and improve process understanding

The original PRIN proposal described three pure conifer stands under contrasting climates (OBS in Canada, Renon in Italy, Yatir in Israel). During the project, site selection was reassessed based on data availability, harmonization, and analysis scope. The table below reports the study sites actually considered in the current repository content.

• UNIPD — University of Padova (PI unit)
  • Principal Investigator: Daniele Castagneri (ORCID)
  • Main role: tree‑ring analysis, quantitative wood anatomy, project coordination
• UNINA — University of Naples Federico II
  • Unit lead: Angelo Rita (ORCID)
  • Main role: integrated data analysis, statistical modelling, process‑based modelling
• UNIBZ — Free University of Bozen‑Bolzano
  • Unit lead: Massimo Tagliavini (ORCID) / Leonardo Montagnani (ORCID)
  • Main role: eddy covariance flux analysis and site‑level flux data coordination

In addition to the unit leaders, the project involves the following participants and collaborators:

• UNIBZ — Free University of Bozen‑Bolzano, Bolzano, Italy: Enrico Tomelleri
• CNR-ISAFOM — Forest Modelling Lab., Institute for Agriculture and Forestry Systems in the Mediterranean, National Research Council of Italy, Perugia, Italy: Alessio Collalti; Paulina F. Puchi; Daniela Dalmonech
• UNINA — Department of Agricultural Sciences, University of Naples Federico II, Portici, Italy: Antonio Saracino; Enrica Pinelli; Greta Liuzzi
• UNIPD — Department of Land, Environment, Agriculture and Forestry (TESAF), University of Padua, Legnaro, Italy: Giancarlo Genovese

• WP1 — C fluxes: acquisition, validation, and analysis of long‑term eddy covariance and climate time series
• WP2 — Tree rings: sampling, quantitative wood anatomy, stable carbon isotopes, and climate‑growth relationships
• WP3 — Modelling: integration of flux, climate, and tree‑ring information; hypothesis testing; refinement of 3D-CMCC-FEM
• WP4 — Dissemination & communication: publications, outreach, metadata, and open science outputs
• WP5 — Project & data management: coordination, reproducibility, and data organization

CliCFor used the process‑based forest model 3D-CMCC-FEM within the modelling component of the project.

• Project repository used for this work: angelrita/3D-CMCC-FEM
• Original model repository: Forest-Modelling-Lab/3D-CMCC-FEM

• Project documentation (docs/)
• Processed/derived products prepared for analysis (see data/processed/)
• Dataset metadata and notes (see data/metadata/)
• Scripts and reusable code (as they become available; scripts/ and src/)

• Full raw eddy covariance exports, large model outputs, and/or third‑party data that cannot be redistributed.
• Credentials, private keys, or any sensitive material.

When data are not redistributed, this repository aims to provide:

• clear provenance and access notes in data/metadata/
• scripts that can rebuild derived products when access is granted

CliCFor/
|- docs/                              project notes and documentation
|- data/
|  |- raw/                            original data files kept unchanged (if redistributed)
|  |- processed/                      derived datasets ready for analysis
|  |  `- xylem_anatomy_chronologies/  chronology files currently versioned here
|  `- metadata/                       codebooks, notes, dataset descriptions
|- scripts/                           analysis scripts and workflow steps
|- src/                               reusable R functions
|- outputs/
|  |- figures/                        generated plots
|  `- tables/                         generated tables
|- CliCFor.Rproj
`- README.md

If you use this repository, please cite it using the metadata provided in CITATION.cff.

For software, documentation, or data products reused separately, also cite the specific component and any related publication when available.

• Code: MIT (see LICENSE)
• Documentation: CC BY 4.0 (see LICENSE-DOCS.md)
• Data products: CC BY 4.0 unless otherwise stated (see LICENSE-DATA.md and data/metadata/)

This project was supported by the National Recovery and Resilience Plan (PNRR), Mission 4, Component 2, Investment 1.1, Call for tender No. 104 published on 2.2.2022 by the Italian Ministry of University and Research (MUR), funded by the European Union - NextGenerationEU - Project Title "CliCFor" - CUP C53D23005270001 - Grant Assignment Decree No. 2022ETAB7T adopted on 14/07/2023 by the Italian Ministry of University and Research (MUR).

For repository issues, documentation corrections, or suggestions, please use the GitHub issue tracker. For scientific aspects of the project, refer to the unit leaders listed above.

Contributions that improve documentation, metadata quality, and reproducibility are welcome.

Before proposing major structural changes, please open an issue so that repository organization and data-policy constraints can be discussed first.