Environmental control of land-atmosphere CO₂ fluxes from temperate ecosystems: a statistical approach based on homogenized time series from five land-use types

Abstract

We assembled homogenized long-term time series, up to 19 years, of measurements of net ecosystem exchange of CO₂ (NEE) and its partitioning between gross primary production (GPP) and respiration (R_eco) for five different ecosystems representing the main plant functional types (PFTs) in France. Part of these data was analyzed to determine the influence of the main environmental variables on carbon fluxes between temperate ecosystems and the atmosphere, and to investigate the temporal patterns of their variations. A multi-temporal statistical analysis of the time series was conducted using random forest (RF) and wavelet coherence approaches. The RF analysis showed that, in all ecosystems, the incident solar radiation was highly correlated with GPP and that GPP was better correlated with the temporal variations of NEE than R_eco. The air temperature was the second most important driver in ecosystems with seasonal foliage, i.e., deciduous forest, cropland and grassland; whereas variables related to air or soil drought were prominent in evergreen forest sites. The environmental control on CO₂ fluxes was tighter at high frequency suggesting an increased resilience to environmental variations at longer time spans. The spectral analysis performed on three of the five sites selected revealed contrasting temporal patterns of the cross-coherence between CO₂ fluxes and climate variables among ecosystems; these were related to the respective PFT, management and soil conditions. In all PFTs, the power spectrum of GPP was well correlated with NEE and clearly different from R_eco. The spectral correlation analysis showed that the canopy phenology and disturbance regime condition the spectral correlation patterns of GPP and R_eco with the soil moisture and atmospheric vapour deficit.

Keywords:

• Net CO2 ecosystem exchange
• Ecosystem respiration
• Gross primary production
• spectral analysis
• random forest analysis

Acknowledgements

This work used meteorological and eddy covariance raw data obtained within the framework of European projects: Euroflux, Carboeuroflux, CarboEuropeIP, CarboAge, GHG Europe, IMECC. VM acknowledges the financial support from the national agency ADEME for the eddy covariance data processing and harmonization within the CESEC project (PI: B. Longdoz), as well as the financial support from the European Union’s Horizon 2020 research for the RINGO project (grant agreement No 730944). The authors would like to thank all the PIs and technicians (e.g. Karim Piquemal, Franck Granouillac, Bartosz Zawilski and Nicole Ferroni) of the eddy covariance sites, and site collaborators involved in ICOS-France who are not included as co-authors of this paper and finally the support of the ‘Nouvelle Aquitaine’ region, the Regional Spatial Observatory (OSR), the CNRS (Centre National de la Recherche Scientifique) and the CNES (Centre National d’ Etudes Spatiales). The authors also thank John Gash for editing the article for style and grammar that improved the readability of the article.

Disclosure statement

No potential conflict of interest was reported by the authors.