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  • Review Article
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Insights into terrestrial carbon and water cycling from the global eddy covariance network

Nature Reviews Earth & Environment volume 7, pages 60–79 (2026)Cite this article

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Abstract

Ecosystem–atmosphere exchanges of carbon dioxide (CO2) and water vapour respond to global environmental changes, such as climate change, elevated atmospheric CO2, disturbances, and land use change and management. Understanding these exchanges requires globally distributed and continuous, long-term ecosystem-scale measurements spanning diverse climates and ecosystems, as supported by the development of the eddy covariance (EC) technique. In this Review, we discuss how the global network of EC sites, led by FLUXNET, has advanced understanding of terrestrial carbon and water cycling. Since the early 1990s, EC measurements have provided insights into variations in carbon and water fluxes across different timescales (half-hourly to decadal), vegetation types and environmental gradients, and their responses to global change. Upscaling EC measurements and the resulting datasets have also enhanced understanding of the magnitude, spatial patterns, seasonal changes, interannual variability, and trends in carbon sinks and sources, evapotranspiration, and water-use efficiency in response to global change at regional to global scales. EC measurements and upscaled data also help interpret and evaluate satellite-derived products, as well as benchmark and improve terrestrial biosphere models and Earth system models. Future efforts should improve network representativeness, foster open data sharing, provide near real-time measurements, enhance accuracy of upscaled products and better support climate mitigation efforts.

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Fig. 1: Evolution of the global network of EC flux sites.
Fig. 2: Variations in ecosystem-level carbon fluxes across time and space.
Fig. 3: Procedures for upscaling EC flux measurements.
Fig. 4: Spatiotemporal variations in annual GPP and ET across global vegetated land.
Fig. 5: Uncertainty of annual carbon fluxes measured by the eddy covariance technique.
Fig. 6: Evaluating the annual GPP of satellite-based products and process-based models.

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Acknowledgements

J.X. thanks the National Science Foundation (Macrosystem Biology and NEON-Enabled Science program: DEB-2017870), Google and the Iola Hubbard Climate Change Endowment for support. D.B. thanks the US DOE AmeriFlux Management Project and its support of core sites for support. F.L. thanks the National Natural Science Foundation of China (grant no. 42471426) for support. K.I. thanks JSPS Core-to-Core Program (grant no. JPJSCCA20220008), JSPS Kakenhi (grant no. JP22H05004) and Environment Research and Technology Development Fund (grant no. JPMEERF24S12207) of the Environmental Restoration and Conservation Agency provided by Ministry of the Environment of Japan for support. D.P. thanks the EU Next Generation EU Mission 4 ‘Education and Research’, project IR0000032; ITINERIS, Italian Integrated Environmental Research Infrastructures System CUP B53C22002150006 for support. K.I. thanks M. Hase and A. Kosugo for graphic support. D.P. thanks the ICOS Ecosystem Thematic Centre and the OEMC HEurope project (GA 101059548) for support.

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Authors and Affiliations

  1. Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH, USA

    Jingfeng Xiao

  2. Department of Environmental Science, Policy and Management, University of California, Berkeley, CA, USA

    Dennis Baldocchi

  3. Center for Environmental Remote Sensing, Chiba University, Chiba, Japan

    Kazuhito Ichii

  4. Institute of Grassland Research, Chinese Academy of Agricultural Sciences, Hohhot, China

    Fei Li

  5. Institute of Research on Terrestrial Ecosystems (IRET), National Research Council (CNR), Monterotondo Scalo, Italy

    Dario Papale

  6. Fondazione CMCC - Centro Euro-Mediterraneo sui Cambiamenti Climatici, Viterbo, Italy

    Dario Papale

Authors
  1. Jingfeng Xiao
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  2. Dennis Baldocchi
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  3. Kazuhito Ichii
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  4. Fei Li
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  5. Dario Papale
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Contributions

J.X. conceptualized and led the study, with substantial contributions to the outline and design from D.B., K.I., F.L. and D.P. All authors substantially contributed to data research and analysis, discussion, drafting and revision of the manuscript.

Corresponding author

Correspondence to Jingfeng Xiao.

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Nature Reviews Earth & Environment thanks Ning Ma and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Related links

La Thuile 2007: https://fluxnet.org/data/la-thuile-dataset/

Marconi 2000: https://doi.org/10.3334/ornldaac/811

Supplementary information

Glossary

Disturbance

Events that alter ecosystem carbon and water fluxes, such as fire, logging, hurricanes and insect outbreaks.

Earth system models

Comprehensive, computer-based models that simulate coupled interactions among the atmosphere, oceans, land and biosphere, including carbon, water and energy cycles.

Ecosystem assimilation

The amount of atmospheric CO2 absorbed by plants through photosynthesis; equivalent to gross primary production.

Ecosystem respiration

The total release of CO2 from an ecosystem to the atmosphere through autotrophic and heterotrophic respiration.

Eddy covariance

(EC) A micrometeorological technique that directly and continuously measures the exchange of gases, energy, and momentum between ecosystems and the atmosphere at high frequency.

Enhanced vegetation index

A remote-sensing vegetation index indicative of canopy greenness and photosynthetic activity, designed to minimize atmospheric and soil background effects.

Evaporative fraction

The ratio of latent heat flux to the sum of latent and sensible heat fluxes, which indicates surface energy partitioning and plant water status.

Evapotranspiration

(ET) The sum of evaporation from canopy, soil and water surfaces plus transpiration from plants, which can be calculated from latent heat flux measurements.

Explanatory variables

Independent variables or predictors used in statistical or machine learning analyses.

Fraction of photosynthetically active radiation

The proportion of photosynthetically active radiation absorbed by vegetation canopies.

Friction velocity

(u*) A key parameter quantifying the intensity of atmospheric turbulence, used to filter out low-turbulence flux data, particularly at night.

Gap filled

The process of estimating missing eddy covariance measurements due to instrument failures or data quality issues.

Gross primary production

(GPP) The total amount of atmospheric CO2 fixed by an ecosystem through photosynthesis.

Hysteresis

Dependence of a system’s response on its prior states or history, leading to lagged or looped input–output relationships.

Latent heat flux

The energy flux associated with evapotranspiration, representing water loss from the surface and a major component of the surface energy budget.

Leaf area index

(LAI) The total one-sided green leaf area per unit ground surface area.

Leaf senescence

The ageing and programmed degradation of leaves, involving nutrient remobilization and eventual leaf death.

Light-use efficiency

(LUE) The efficiency with which plants convert absorbed light into carbon gain through photosynthesis.

Machine learning

Algorithms that identify patterns in data and make predictions or decisions, as part of artificial intelligence.

Near-infrared reflectance of terrestrial vegetation

A remote sensing vegetation index calculated as the product of near-infrared reflectance and the normalized difference vegetation index, used as a proxy for canopy photosynthetic activity.

Net ecosystem exchange

(NEE) The net flux of CO2 between an ecosystem and the atmosphere, where negative values indicate ecosystem carbon uptake and positive values indicate carbon release into the atmosphere.

Normalized difference vegetation index

A remote sensing vegetation index calculated from the contrast in reflectance between red and near-infrared bands, indicative of canopy greenness and photosynthetic activity.

Photochemical reflectance index

A remote-sensing vegetation index indicating changes in photosynthetic light-use efficiency.

Photosynthetically active radiation

(PAR) Incoming solar radiation in the wavelength range of 400–700 nm used for photosynthesis.

Sensible heat flux

Energy flux that warms or cools the air without a phase change.

Solar-induced chlorophyll fluorescence

The faint energy flux re-emitted by chlorophyll during photosynthesis, providing a direct proxy for photosynthetic activity and gross primary production.

Stomatal conductance

The rate at which CO2 enters and water vapour exits a leaf through stomata, reflecting plant water–carbon exchange regulation.

Terrestrial biosphere models

Mechanistic, computer-based models that represent the processes of carbon, water and energy exchanges between the terrestrial biosphere and the atmosphere.

Tower footprint

The upwind surface area contributing to the fluxes measured by an eddy covariance tower.

Upscaling

The process of extending site-level measurements, such as eddy covariance fluxes, to regional or global scales using machine learning or modelling combined with satellite and climate data.

Vapour pressure deficit

(VPD) The difference between the saturation and actual vapour pressure of water in the air; a key driver of transpiration.

Water-use efficiency

(WUE) The ratio of carbon gain through photosynthesis to water loss via transpiration, representing how efficiently plants or ecosystems use water.

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Xiao, J., Baldocchi, D., Ichii, K. et al. Insights into terrestrial carbon and water cycling from the global eddy covariance network. Nat Rev Earth Environ 7, 60–79 (2026). https://doi.org/10.1038/s43017-025-00743-1

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