the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 27 Nov 2024
Aquatic and Soil CO2 Emissions from forested wetlands of Congo's Cuvette Centrale
Abstract. Within tropical forest ecosystems, wetlands such as swamp forests are an important interface between the terrestrial and aquatic landscape. Despite this assumed importance, there is a paucity of carbon flux data from wetlands in tropical Africa. Therefore, the magnitude and source of CO2 fluxes, carbon isotopic ratios, and environmental conditions were measured for three years between 2019 to 2022 in a seasonally flooded forest and a perennially flooded forest in the Cuvette Centrale of the Congo Basin. The mean surface fluxes for the seasonally flooded site and the perennially flooded site were 2.36 ± 0.51 µmol m-2 s-1 and 4.38 ± 0.64 µmol m-2 s-1 respectively. The time series data revealed no discernible seasonal pattern in CO2 fluxes. As for the environmental drivers, the fluxes at the seasonally flooded site exhibited a positive correlation with soil temperature and soil moisture. Additionally, the water table depth appeared to be a significant factor, demonstrating a quadratic relationship with the soil fluxes at the seasonally flooded site. δ13C values showed a progressive increase across the carbon pools, from above-ground biomass, then leaf litter, to soil organic carbon (SOC). However, there was no significant difference in δ13C enrichment between SOC and soil respired CO2.
An in-situ derived gas transfer velocity (k600 = 2.95 cm h-1) was used to calculate the aquatic CO2 fluxes at the perennially flooded site. Despite the low k600, relatively high CO2 surface fluxes were found due to very high dissolved pCO2 values measured in the flooding waters. Overall, these results offer a quantification of the CO2 fluxes from forested wetlands and provide an insight of the temporal variability of these fluxes as well as their sensitivity to environmental drivers.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Biogeosciences. The peer-review process was guided by an independent editor, and the authors also have no other competing interests to declare.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.-
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2024-3313', Anonymous Referee #1, 11 Jan 2025
The manuscript presents valuable data on forested wetlands in the Congo, addressing a significant gap in current knowledge and demonstrating how different flooding regimes impact surface CO2 fluxes. I particularly appreciate the detailed descriptions in the Methods section. However, I believe the Results section would benefit from a more thorough discussion, and the Discussion section could be further strengthened. Additionally, there are several formatting issues, such as mismatches between in-text figure numbers and the actual figures, as well as inconsistent use of subscripts. Below are my detailed comments.
Line 30: I’d suggest using the full term for pCO2 before using the acronym.
Line 55-57: The authors mention that 'probably only one study' has looked into GHG emissions from Congo's forested wetlands, specifically methane (Tathy et al. 1992). However, it seems there is another study that also investigates GHG emissions, including both methane (CH4) and nitrous oxide (N2O), from forested wetland soils in the Congo Basin (Barthel et al., 2022, Nature Communications).
Line 71-73: I suggest moving the description of measurement variables to the methods section. This would help streamline the Introduction and ensure methodological details are presented in the appropriate context.
Line 94: The sentence suggests that the forest is flooded because of its proximity to the river, which may not fully capture the cause of the seasonal flooding. It would be more accurate to say that the forest is flooded due to increased river flow during the rainy season or similar hydrological events. I recommend rephrasing the sentence to reflect the influence of the rainy season on the river's water levels, which causes the flooding.
Line 99: It seems that the sentence doesn't correspond to the content of Figure 2.
Line 116-118: I'd suggest clarifying whether the reference to Drake et al. (2023) is meant to support the statement about the previous analyses showing TDN consistently comprising 90% of DON, or if it only pertains to the specific methods and calculations. It might be helpful to provide a reference for the previous analyses as well to avoid confusion.
Line 126: Please clarify the abbreviations “h” and “ø” for better readability. It would be helpful to define these terms for readers who may not be familiar with them.
Line 135: Please use the full term for “h” here.
Line 144-145: Could you please clarify why data with such a low r² threshold were retained, despite the strong regression fit observed in most of the data?
Line 166: Remove the space before the colon.
Line 172: Please add a space between “50” and “µL” for consistency with units.
Line 179: The abbreviation “GC” should be defined earlier as “gas chromatograph” in line 177.
Line 184: Remove the space after the dash.
Line 189: Please use the full term “V-PDB” when first mentioned.
Line 206-212: Water table already implies the level of water beneath the ground so “level” is redundant. Since you seem to be referring to the river, “water level” may be a more appropriate term.
Line 208: Could you clarify the distance between the Congo River and the study site, or explain how it is hydrologically connected to the Ruki River?
Line 210: DRC is not defined earlier in the text.
Line 215: I'd suggest changing the heading from “Statistics” to “Statistical Analyses” for better clarity and accuracy.
Line 218: “Added” might be a better word than “tested” as the quadratic term was included in the model to account for the non-linear effect.
Line 232: Remove the space after 'tydr v1.3.0' and before the comma.
Line 236-248: For this section, I’d suggest first describing the general climate characteristics at the study site, such as the timing of the dry and wet seasons, to better contextualize the variables. Additionally, I recommend incorporating the water level into this section, potentially alongside Figure 3. Although you mentioned that in-situ measurements were not available and the Congo River water level was used as a proxy, you also noted in Section 2.6 that riverine water levels are more influenced by river hydrological dynamics than rainfall. Therefore, you might consider using a more general heading, like “Environmental Conditions”. For line 238, should it refer to Figure 3A instead of 2A? Lastly, in lines 247-248, please combine the sentences for better continuity instead of starting a new line.
Line 249-256: This section presents CO2 flux data from two sites (PFF and SFF), showing variations over time. However, it doesn't explicitly explain the drivers behind these fluctuations. It would be useful to explore how these CO2 flux variations correlate with specific environmental variables (e.g., temperature, precipitation, soil moisture, water level) or if they follow consistent seasonal patterns.
Line 250, 254 and 256: Same comment as Line 238—should it be Figure 3C instead of 2C?
Line 260: Figure 3 presents important data, but the current color scheme and legend structure could be improved for better clarity:
- Subplot A: The colours for the three lines (precipitation and two soil moisture sensors) are too similar, making it difficult to distinguish between them.
- Subplot B: The two lines representing soil temperature from different sensors (ECH2O 5TM and TMS-4 dataloggers) also have very similar colours, which may confuse readers.
- To enhance readability, it would be beneficial to include legends for each subplot.
Line 279: Are the fixed effect estimates presented in Table 1 standardized or are they unstandardized? Clarifying this would help in interpreting the relative importance of the predictors and their effects on soil CO2 fluxes.
Line 287-290: The text appears to be the caption for Figure 4, please remove it from the text.
Line 294-295: There appears to be a mismatch between the subplot labels (A and B) in the Figure 4 caption and the content. Also, please use the correct subscript for “CO2”.
Line 309: Figure 3 doesn't appear to show δ13C values.
Line 325-334: The authors compare CO2 fluxes from both seasonal and perennial flooded forest sites with those from other reported sites. However, the reasons for the higher emissions at the PFF compared to the SFF are unclear. It would be beneficial to discuss this, as it could provide further insight into the differences between the two forest types.
Line 340-341: It would be helpful to provide references for these factors influencing pCO2 concentrations.
Line 346: I did not see the plot of water level and pCO2 in Figure 5. Could you please clarify if this plot is included or if it is shown in a different figure?
Line 350: Please use a subscript for “CO2” in the table caption.
Line 379: Supp. Fig. 6 does not show seasonal CO2 fluxes.
Line 379-380: The authors suggest that factors like aboveground inputs, deposition, and rain-induced events may influence soil CO2 fluxes. While a linear relationship between the Congo and Ruki river levels is noted, and previous research indicates that water levels in the Cuvette Centrale correlate more with river dynamics than rainfall, there are still uncertainties to consider:
- The study site is approximately 1 km from the Ruki River, and local topography and soil characteristics could affect how well river levels represent the actual water table at the forest site.
- Short-term variations in soil CO2 fluxes may not be fully captured by this proxy, as local hydrological dynamics might differ from those of the broader river system.
- The lack of correlation between water table changes and CO2 fluxes may reflect limitations of the proxy measurement rather than a true absence of a relationship.
While you made a reasonable methodological choice using available data, it might be possible to acknowledge that the study site's water level could differ from the river proxy. This limitation should be considered when interpreting the results, especially regarding the influence of water table dynamics on soil CO2 fluxes.
Citation: https://doi.org/10.5194/egusphere-2024-3313-RC1 - AC1: 'Reply on RC1', Antoine De Clippele, 16 Feb 2025
-
RC2: 'Comment on egusphere-2024-3313', Anonymous Referee #2, 23 Jan 2025
Dear Editor and Authors,
Please find attached the review report.
Best regards
- AC2: 'Reply on RC2', Antoine De Clippele, 16 Feb 2025
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-3313', Anonymous Referee #1, 11 Jan 2025
The manuscript presents valuable data on forested wetlands in the Congo, addressing a significant gap in current knowledge and demonstrating how different flooding regimes impact surface CO2 fluxes. I particularly appreciate the detailed descriptions in the Methods section. However, I believe the Results section would benefit from a more thorough discussion, and the Discussion section could be further strengthened. Additionally, there are several formatting issues, such as mismatches between in-text figure numbers and the actual figures, as well as inconsistent use of subscripts. Below are my detailed comments.
Line 30: I’d suggest using the full term for pCO2 before using the acronym.
Line 55-57: The authors mention that 'probably only one study' has looked into GHG emissions from Congo's forested wetlands, specifically methane (Tathy et al. 1992). However, it seems there is another study that also investigates GHG emissions, including both methane (CH4) and nitrous oxide (N2O), from forested wetland soils in the Congo Basin (Barthel et al., 2022, Nature Communications).
Line 71-73: I suggest moving the description of measurement variables to the methods section. This would help streamline the Introduction and ensure methodological details are presented in the appropriate context.
Line 94: The sentence suggests that the forest is flooded because of its proximity to the river, which may not fully capture the cause of the seasonal flooding. It would be more accurate to say that the forest is flooded due to increased river flow during the rainy season or similar hydrological events. I recommend rephrasing the sentence to reflect the influence of the rainy season on the river's water levels, which causes the flooding.
Line 99: It seems that the sentence doesn't correspond to the content of Figure 2.
Line 116-118: I'd suggest clarifying whether the reference to Drake et al. (2023) is meant to support the statement about the previous analyses showing TDN consistently comprising 90% of DON, or if it only pertains to the specific methods and calculations. It might be helpful to provide a reference for the previous analyses as well to avoid confusion.
Line 126: Please clarify the abbreviations “h” and “ø” for better readability. It would be helpful to define these terms for readers who may not be familiar with them.
Line 135: Please use the full term for “h” here.
Line 144-145: Could you please clarify why data with such a low r² threshold were retained, despite the strong regression fit observed in most of the data?
Line 166: Remove the space before the colon.
Line 172: Please add a space between “50” and “µL” for consistency with units.
Line 179: The abbreviation “GC” should be defined earlier as “gas chromatograph” in line 177.
Line 184: Remove the space after the dash.
Line 189: Please use the full term “V-PDB” when first mentioned.
Line 206-212: Water table already implies the level of water beneath the ground so “level” is redundant. Since you seem to be referring to the river, “water level” may be a more appropriate term.
Line 208: Could you clarify the distance between the Congo River and the study site, or explain how it is hydrologically connected to the Ruki River?
Line 210: DRC is not defined earlier in the text.
Line 215: I'd suggest changing the heading from “Statistics” to “Statistical Analyses” for better clarity and accuracy.
Line 218: “Added” might be a better word than “tested” as the quadratic term was included in the model to account for the non-linear effect.
Line 232: Remove the space after 'tydr v1.3.0' and before the comma.
Line 236-248: For this section, I’d suggest first describing the general climate characteristics at the study site, such as the timing of the dry and wet seasons, to better contextualize the variables. Additionally, I recommend incorporating the water level into this section, potentially alongside Figure 3. Although you mentioned that in-situ measurements were not available and the Congo River water level was used as a proxy, you also noted in Section 2.6 that riverine water levels are more influenced by river hydrological dynamics than rainfall. Therefore, you might consider using a more general heading, like “Environmental Conditions”. For line 238, should it refer to Figure 3A instead of 2A? Lastly, in lines 247-248, please combine the sentences for better continuity instead of starting a new line.
Line 249-256: This section presents CO2 flux data from two sites (PFF and SFF), showing variations over time. However, it doesn't explicitly explain the drivers behind these fluctuations. It would be useful to explore how these CO2 flux variations correlate with specific environmental variables (e.g., temperature, precipitation, soil moisture, water level) or if they follow consistent seasonal patterns.
Line 250, 254 and 256: Same comment as Line 238—should it be Figure 3C instead of 2C?
Line 260: Figure 3 presents important data, but the current color scheme and legend structure could be improved for better clarity:
- Subplot A: The colours for the three lines (precipitation and two soil moisture sensors) are too similar, making it difficult to distinguish between them.
- Subplot B: The two lines representing soil temperature from different sensors (ECH2O 5TM and TMS-4 dataloggers) also have very similar colours, which may confuse readers.
- To enhance readability, it would be beneficial to include legends for each subplot.
Line 279: Are the fixed effect estimates presented in Table 1 standardized or are they unstandardized? Clarifying this would help in interpreting the relative importance of the predictors and their effects on soil CO2 fluxes.
Line 287-290: The text appears to be the caption for Figure 4, please remove it from the text.
Line 294-295: There appears to be a mismatch between the subplot labels (A and B) in the Figure 4 caption and the content. Also, please use the correct subscript for “CO2”.
Line 309: Figure 3 doesn't appear to show δ13C values.
Line 325-334: The authors compare CO2 fluxes from both seasonal and perennial flooded forest sites with those from other reported sites. However, the reasons for the higher emissions at the PFF compared to the SFF are unclear. It would be beneficial to discuss this, as it could provide further insight into the differences between the two forest types.
Line 340-341: It would be helpful to provide references for these factors influencing pCO2 concentrations.
Line 346: I did not see the plot of water level and pCO2 in Figure 5. Could you please clarify if this plot is included or if it is shown in a different figure?
Line 350: Please use a subscript for “CO2” in the table caption.
Line 379: Supp. Fig. 6 does not show seasonal CO2 fluxes.
Line 379-380: The authors suggest that factors like aboveground inputs, deposition, and rain-induced events may influence soil CO2 fluxes. While a linear relationship between the Congo and Ruki river levels is noted, and previous research indicates that water levels in the Cuvette Centrale correlate more with river dynamics than rainfall, there are still uncertainties to consider:
- The study site is approximately 1 km from the Ruki River, and local topography and soil characteristics could affect how well river levels represent the actual water table at the forest site.
- Short-term variations in soil CO2 fluxes may not be fully captured by this proxy, as local hydrological dynamics might differ from those of the broader river system.
- The lack of correlation between water table changes and CO2 fluxes may reflect limitations of the proxy measurement rather than a true absence of a relationship.
While you made a reasonable methodological choice using available data, it might be possible to acknowledge that the study site's water level could differ from the river proxy. This limitation should be considered when interpreting the results, especially regarding the influence of water table dynamics on soil CO2 fluxes.
Citation: https://doi.org/10.5194/egusphere-2024-3313-RC1 - AC1: 'Reply on RC1', Antoine De Clippele, 16 Feb 2025
-
RC2: 'Comment on egusphere-2024-3313', Anonymous Referee #2, 23 Jan 2025
Dear Editor and Authors,
Please find attached the review report.
Best regards
- AC2: 'Reply on RC2', Antoine De Clippele, 16 Feb 2025
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Antoine de Clippele
Astrid C. H. Jaeger
Simon Baumgartner
Marijn Bauters
Pascal Boeckx
Clement Botefa
Glenn Bush
Jessica Carilli
Travis W. Drake
Christian Ekamba
Gode Lompoko
Nivens Bey Mukwiele
Kristof Van Oost
Roland A. Werner
Joseph Zambo
Johan Six
Matti Barthel
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(1217 KB) - Metadata XML
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Supplement
(673 KB) - BibTeX
- EndNote
- Final revised paper