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Abstract Tree stems exchange CO2, CH4and N2O with the atmosphere but the magnitudes, patterns and drivers of these greenhouse gas (GHG) fluxes remain poorly understood. Our understanding mainly comes from static-manual measurements, which provide limited information on the temporal variability and magnitude of these fluxes. We measured hourly CO2, CH4and N2O fluxes at two stem heights and adjacent soils within an upland temperate forest. We analyzed diurnal and seasonal variability of fluxes and biophysical drivers (i.e., temperature, soil moisture, sap flux). Tree stems were a net source of CO2(3.80 ± 0.18 µmol m−2s−1; mean ± 95% CI) and CH4(0.37 ± 0.18 nmol m−2s−1), but a sink for N2O (−0.016 ± 0.008 nmol m−2s−1). Time series analysis showed diurnal temporal correlations between these gases with temperature or sap flux for certain days. CO2and CH4showed a clear seasonal pattern explained by temperature, soil water content and sap flux. Relationships between stem, soil fluxes and their drivers suggest that CH4for stem emissions could be partially produced belowground. High-frequency measurements demonstrate that: a) tree stems exchange GHGs with the atmosphere at multiple time scales; and b) are needed to better estimate fluxes magnitudes and understand underlying mechanisms of GHG stem emissions.
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The paradox of assessing greenhouse gases from soils for nature-based solutions
Abstract. Quantifying the role of soils in nature-based solutions requires accurate estimates of soil greenhouse gas (GHG) fluxes. Technological advancesallow us to measure multiple GHGs simultaneously, and now it is possible to provide complete GHG budgets from soils (i.e., CO2, CH4,and N2O fluxes). We propose that there is a conflict between the convenience of simultaneously measuring multiple soil GHG fluxes at fixedtime intervals (e.g., once or twice per month) and the intrinsic temporal variability in and patterns of different GHG fluxes. Information derived fromfixed time intervals – commonly done during manual field campaigns – had limitations to reproducing statistical properties, temporal dependence,annual budgets, and associated uncertainty when compared with information derived from continuous measurements (i.e., automated hourly measurements)for all soil GHG fluxes. We present a novel approach (i.e., temporal univariate Latin hypercube sampling) that can be applied to provide insightsand optimize monitoring efforts of GHG fluxes across time. We suggest that multiple GHG fluxes should not be simultaneously measured at a few fixedtime intervals (mainly when measurements are limited to once per month), but an optimized sampling approach can be used to reduce bias anduncertainty. These results have implications for assessing GHG fluxes from soils and consequently reduce uncertainty in the role of soils innature-based solutions.
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- Award ID(s):
- 1652594
- PAR ID:
- 10395721
- Date Published:
- Journal Name:
- Biogeosciences
- Volume:
- 20
- Issue:
- 1
- ISSN:
- 1726-4189
- Page Range / eLocation ID:
- 15 to 26
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.5194/bg-20-15-2023
