The enduring mystery of differences between eddy covariance and biometric measurements for ecosystem respiration and net carbon storage in forests

Ryan, Michael G.

doi:10.1111/nph.19105

Cited by 3 publications

(1 citation statement)

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“…Nevertheless, there are slight inconsistencies, particularly during peak photosynthesis periods (around the 200 th day of the year) in both deciduous and evergreen forests, which have been acknowledged in existing literature. Studies indicate that estimates of ecosystem respiration derived from eddy covariance often underestimate actual values for forest ecosystems ( Lavigne et al, 1997;Campioli et al, 2016;Speckman et al, 2015;Ryan, 2023).…”

Section: Model Validationmentioning

confidence: 99%

Predicted Future Changes in the Mean Seasonal Carbon Cycle Due to Climate Change

Morichetti,

Vangi,

Collalti

2024

Preprint

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Through photosynthesis, forests absorb annually massive amounts of atmospheric CO2. However, they also release CO2 back through respiration. The net ecosystem exchange (NEE) determines how much carbon forests store or release. The mean seasonal cycle (MSC) is an interesting metric that associate phenology and carbon (C) partitioning-allocation within forest stands. Here we applied the 3D-CMCC-FEM model and analyzed its capability to represent the main C-fluxes, by validating the model against observed data, questioning if the sink/source mean seasonality is influenced under two scenarios of climate change, in five European forest sites. We found the model showing under current climate conditions robust predictive abilities in estimating NEE. The analysis also reveals a consistent reduction of the forest's capabilities to act as a C-sink under climate change and stand-ageing at all sites. Such a reduction is modelled despite the number of annual days of C-sink in evergreen increasing over the years, indicating a consistent downward trend. Similarly, deciduous forests, despite maintaining a relatively stable number of C-sink days throughout the year and over the century, show a reduction in the overall annual C-sink capacity. Overall both types of forests at all sites show a consistent reduction in their future mitigating potential.

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Section: Model Validationmentioning

confidence: 99%

Predicted Future Changes in the Mean Seasonal Carbon Cycle Due to Climate Change

Morichetti,

Vangi,

Collalti

2024

Preprint

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Disaggregation of canopy photosynthesis among tree species in a mixed broadleaf forest

Stojanović,

Jocher,

Kowalska

et al. 2024

Tree Physiology

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Carbon dioxide sequestration from the atmosphere is commonly assessed using the eddy covariance (EC) method. Its net flux signal can be decomposed into gross primary production (GPP) and ecosystem respiration components, but these have seldom been tested against independent methods. In addition, EC lacks the ability to partition carbon sequestration among individual trees or species within mixed forests. Therefore, we compared GPP from EC to an independent method based on sap flow and water-use efficiency, as measured by the tissue heat balance method and δ13C of phloem contents, respectively. The latter measurements were conducted on individual trees throughout a growing season in a mixed broadleaf forest dominated by three tree species, namely English oak, narrow-leaved ash, and common hornbeam. In this context, we applied an alternative ecophysiological method aimed at verifying the accuracy of a state-of-the-art EC system while also offering a solution to the partitioning problem. We observed strong agreement in the ecosystem GPP estimates (R2 = 0.56; p < 0.0001), with correlation being especially high and nearly on the 1:1 line in the period before end of July (i.e., DOY 212; R2 = 0.85; p < 0.0001). After this period, the estimates of GPP began to diverge. Possible reasons for the divergence are discussed, focusing especially on phenology and the limitation of the isotopic data. English oak showed the highest per-tree daily photosynthetic rates among tree species, but the smaller, more abundant common hornbeam contributed most to the stand-level summation, especially early in the spring. These findings provide a rigorous test of the methods and the species-level photosynthesis offers avenues for enhancing forest management aimed at carbon sequestration.

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Predicted Future Changes in the Mean Seasonal Carbon Cycle Due to Climate Change

Morichetti,

Vangi,

Collalti

2024

Forests

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Through photosynthesis, forests absorb annually large amounts of atmospheric CO2. However, they also release CO2 back through respiration. These two, opposite in sign, large fluxes determine how much of the carbon is stored or released back into the atmosphere. The mean seasonal cycle (MSC) is an interesting metric that associates phenology and carbon (C) partitioning/allocation analysis within forest stands. Here, we applied the 3D-CMCC-FEM model and analyzed its capability to represent the main C-fluxes, by validating the model against observed data, questioning if the sink/source mean seasonality is influenced under two scenarios of climate change, in five contrasting European forest sites. We found the model has, under current climate conditions, robust predictive abilities in estimating NEE. Model results also predict a consistent reduction in the forest’s capabilities to act as a C-sink under climate change and stand-aging at all sites. Such a reduction is predicted despite the number of annual days as a C-sink in evergreen forests increasing over the years, indicating a consistent downward trend. Similarly, deciduous forests, despite maintaining a relatively stable number of C-sink days throughout the year and over the century, show a reduction in their overall annual C-sink capacity. Overall, both types of forests at all sites show a consistent reduction in their future mitigating potential.

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The enduring mystery of differences between eddy covariance and biometric measurements for ecosystem respiration and net carbon storage in forests

Abstract: This article is a Commentary on Marshall et al. (2023), 239: 2166–2179.

Cited by 3 publications

References 13 publications

Predicted Future Changes in the Mean Seasonal Carbon Cycle Due to Climate Change

Predicted Future Changes in the Mean Seasonal Carbon Cycle Due to Climate Change

Disaggregation of canopy photosynthesis among tree species in a mixed broadleaf forest

Predicted Future Changes in the Mean Seasonal Carbon Cycle Due to Climate Change

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