the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 14 Aug 2024
Spatiotemporal variability of CO2, N2O and CH4 fluxes from a semi-deciduous tropical forest soil in the Congo basin
Abstract. Tropical forests play an important role in the greenhouse gas exchange between biosphere and atmosphere. Despite holding the second largest tropical forest globally, the Congo basin is generally understudied and ground based greenhouse gas flux data are lacking. In this study, high frequency measurements spanning of sixteen months from automated and manual soil chambers are combined, to characterize spatio-temporal variability in soil greenhouse gas fluxes from a lowland tropical forest in Yangambi, in the Congo Basin. Based on sub-daily continuous measurements, for CO2, a total emission of 15.3 ± 4.4 Mg C ha-1 yr-1 was calculated, with highest fluxes at the start of the wetter periods and a decline in emissions during drier periods. For CH4, the total uptake was -3.9 ± 5.2 kg C ha-1 yr-1. Over the whole period the soil acted as a sink however sporadic emission events were also observed. For N2O an emission of 3.6 ± 4.1 kg N ha-1 yr-1 was calculated, which is higher than most previously reported tropical forest estimates. N2O emissions decreased substantially during drier periods and emission pulses were detected after rain events. High spatial and temporal variability was observed for both CH4 and N2O, but less for CO2. Higher spatial variability was assessed by the manual compared to the automated measurements. Overall, the tropical forest soil acted as a major source for CO2 and N2O and a minor sink for CH4.
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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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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- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-2346', Dianming Wu, 13 Sep 2024
In this work, Daelman et al. offer a critical examination of greenhouse gas fluxes from a semideciduous tropical forest soil in the Congo Basin, an area underrepresented in the scientific literature. Utilizing a combination of automated and manual soil chamber measurements, the research provides a detailed analysis of the spatiotemporal variability of CO2, CH4, and N2O emissions, revealing the forest soil as a significant source of CO2 and N2O and a minor sink for CH4. The findings are pivotal in elucidating the nitrogen and carbon cycles within tropical forest soils, as well as in assessing the ecosystem's vulnerability to climate change. However, this study has the following issues:
- The Congo Basin is a vast and diverse region. How do you ensure that the data collected from the specific study site in Yangambi is representative of the broader Congo Basin's tropical forest soils?
- You mention the use of both automated and manual soil chambers. Could you elaborate on how the data from these two different methods were integrated, and whether any corrections or normalizations were applied to ensure consistency in the dataset?
- The manuscript notes sporadic CH4 emission events. What are the potential ecological or environmental triggers for these events, and how were they identified in your study?
- The study identifies water-filled pore space (WFPS) as a significant driver of N2O emissions. Have you investigated other potential drivers, such as soil pH, nutrient availability, or microbial community composition, which could also influence N2O emissions?
- The high temporal variability of N2O emissions is noted. Could the authors provide insights into the seasonal patterns and inter-annual variability observed in the study, and how this variability might be linked to climate drivers?
- What is the detection limit of the flux /GC? Are these real negative fluxes? please state detection limits - important when claiming negative fluxes.
- L120, give a reference for the equation used.
- 2.3.2: should provide detailed information about the experimental design for manual chamber measurements, which is crucial for understanding the methodology and interpreting the results. For example, clarify the time of day when measurements are taken and whether these times are consistent across all measurements or vary according to a specific schedule.
Citation: https://doi.org/10.5194/egusphere-2024-2346-RC1 - AC1: 'Reply on RC1', Roxanne Daelman, 22 Oct 2024
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RC2: 'Comment on egusphere-2024-2346', Anonymous Referee #2, 19 Sep 2024
Forests are highly relevant to global greenhouse gas (GHG) budgets. The Congo equatorial forest is one of the forests with little knowledge of GHG fluxes. Daelman et al. presents a study on fluxes in the Congo Basin using dynamic chamber techniques. The flux numbers are robust, with results close to those obtained in other tropical forests. However, some points require further clarification or discussion:
1) What are the intervals between samples for both types of chambers, the average number of measurements for the daytime and nighttime periods?
2) It is not clear in the text that the soil parameters shown in Table S2 were obtained only for the CongoFlux climate site and not for the other points of the experiment (CF1, CF2, Mi2 and Mi5). How representative are these measurements for the remaining points?
3) Regarding fast boxes, is there any reference to their use in an experiment like the one presented or were they designed by the authors?
4) Was there any place where the automatic chambers and fast box were placed close together in the same sampling location to evaluate the performances?
5) Considering the occurrence of precipitation almost every day (Fig. S3), what is the strategy for measurements with these events?
6) In tab. 1, inform that the data refers to fast boxes.
7) Check if the CH4 fluxes reported in lines 201 and 316 are correct, with the aforementioned tables.
8) Still in relation to the fast boxes, when evaluating the performance of the chambers, it should be taken into account that with their small area, an increase in the variability of the fluxes was expected due to edge effects, while a larger area of the automatic chamber would reduce this influence on the fluxes.
Citation: https://doi.org/10.5194/egusphere-2024-2346-RC2 - AC2: 'Reply on RC2', Roxanne Daelman, 22 Oct 2024
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RC3: 'Comment on egusphere-2024-2346', Anonymous Referee #3, 30 Sep 2024
This work presented GHG fluxes from tropical forest in Congo Basin where there are large gaps of knowledge. By combining automatic chamber and manual chamber methods, both temporal and spatial variability are examined. Soils of this study site was shown to be large sources of CO2 and N2O with high spatiotemporal variations, highlighting the importance of extensive research. Some more questions are listed below:
- Please provide more details in 2.3.1 if the automatic chamber is opaque or not, this determine the measured CO2 fluxes are NEE or respiration.
- Line 130 described the manual chamber was permanently installed into soil, when they are installed and do you take into account any effect caused by the installation? Did you do quality control of fast box fluxes measurement as for automatic chamber? What’s the percentage of bad quality measurements that are discarded?
- It’s not clear where the environmental variables are measured, is the “each chamber location” in Line 95 refers to which kind of chamber or both?
- Since automatic chambers are at plot CF1, could you compare their results with fast box result in same plot to have an idea of the performance of the two methods?
- N2O emissions are highly related to soil nutrient availability, do you have information about the spatial variation of soil N among chamber locations? Table S2 shows the soil properties data but where the soils are sampled and how they can represent the different chamber measurement locations?
- Since the observed CH4 emissions are not explained by moist soil or rain event, do you have more information can explain this? How about the ground vegetation in different plots, especially in the chamber location which show emissions throughout the period.
- Please check and clarify if the data comes from automatic chamber or fast box chamber in all table and figure captions.
Citation: https://doi.org/10.5194/egusphere-2024-2346-RC3 - AC3: 'Reply on RC3', Roxanne Daelman, 22 Oct 2024
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-2346', Dianming Wu, 13 Sep 2024
In this work, Daelman et al. offer a critical examination of greenhouse gas fluxes from a semideciduous tropical forest soil in the Congo Basin, an area underrepresented in the scientific literature. Utilizing a combination of automated and manual soil chamber measurements, the research provides a detailed analysis of the spatiotemporal variability of CO2, CH4, and N2O emissions, revealing the forest soil as a significant source of CO2 and N2O and a minor sink for CH4. The findings are pivotal in elucidating the nitrogen and carbon cycles within tropical forest soils, as well as in assessing the ecosystem's vulnerability to climate change. However, this study has the following issues:
- The Congo Basin is a vast and diverse region. How do you ensure that the data collected from the specific study site in Yangambi is representative of the broader Congo Basin's tropical forest soils?
- You mention the use of both automated and manual soil chambers. Could you elaborate on how the data from these two different methods were integrated, and whether any corrections or normalizations were applied to ensure consistency in the dataset?
- The manuscript notes sporadic CH4 emission events. What are the potential ecological or environmental triggers for these events, and how were they identified in your study?
- The study identifies water-filled pore space (WFPS) as a significant driver of N2O emissions. Have you investigated other potential drivers, such as soil pH, nutrient availability, or microbial community composition, which could also influence N2O emissions?
- The high temporal variability of N2O emissions is noted. Could the authors provide insights into the seasonal patterns and inter-annual variability observed in the study, and how this variability might be linked to climate drivers?
- What is the detection limit of the flux /GC? Are these real negative fluxes? please state detection limits - important when claiming negative fluxes.
- L120, give a reference for the equation used.
- 2.3.2: should provide detailed information about the experimental design for manual chamber measurements, which is crucial for understanding the methodology and interpreting the results. For example, clarify the time of day when measurements are taken and whether these times are consistent across all measurements or vary according to a specific schedule.
Citation: https://doi.org/10.5194/egusphere-2024-2346-RC1 - AC1: 'Reply on RC1', Roxanne Daelman, 22 Oct 2024
-
RC2: 'Comment on egusphere-2024-2346', Anonymous Referee #2, 19 Sep 2024
Forests are highly relevant to global greenhouse gas (GHG) budgets. The Congo equatorial forest is one of the forests with little knowledge of GHG fluxes. Daelman et al. presents a study on fluxes in the Congo Basin using dynamic chamber techniques. The flux numbers are robust, with results close to those obtained in other tropical forests. However, some points require further clarification or discussion:
1) What are the intervals between samples for both types of chambers, the average number of measurements for the daytime and nighttime periods?
2) It is not clear in the text that the soil parameters shown in Table S2 were obtained only for the CongoFlux climate site and not for the other points of the experiment (CF1, CF2, Mi2 and Mi5). How representative are these measurements for the remaining points?
3) Regarding fast boxes, is there any reference to their use in an experiment like the one presented or were they designed by the authors?
4) Was there any place where the automatic chambers and fast box were placed close together in the same sampling location to evaluate the performances?
5) Considering the occurrence of precipitation almost every day (Fig. S3), what is the strategy for measurements with these events?
6) In tab. 1, inform that the data refers to fast boxes.
7) Check if the CH4 fluxes reported in lines 201 and 316 are correct, with the aforementioned tables.
8) Still in relation to the fast boxes, when evaluating the performance of the chambers, it should be taken into account that with their small area, an increase in the variability of the fluxes was expected due to edge effects, while a larger area of the automatic chamber would reduce this influence on the fluxes.
Citation: https://doi.org/10.5194/egusphere-2024-2346-RC2 - AC2: 'Reply on RC2', Roxanne Daelman, 22 Oct 2024
-
RC3: 'Comment on egusphere-2024-2346', Anonymous Referee #3, 30 Sep 2024
This work presented GHG fluxes from tropical forest in Congo Basin where there are large gaps of knowledge. By combining automatic chamber and manual chamber methods, both temporal and spatial variability are examined. Soils of this study site was shown to be large sources of CO2 and N2O with high spatiotemporal variations, highlighting the importance of extensive research. Some more questions are listed below:
- Please provide more details in 2.3.1 if the automatic chamber is opaque or not, this determine the measured CO2 fluxes are NEE or respiration.
- Line 130 described the manual chamber was permanently installed into soil, when they are installed and do you take into account any effect caused by the installation? Did you do quality control of fast box fluxes measurement as for automatic chamber? What’s the percentage of bad quality measurements that are discarded?
- It’s not clear where the environmental variables are measured, is the “each chamber location” in Line 95 refers to which kind of chamber or both?
- Since automatic chambers are at plot CF1, could you compare their results with fast box result in same plot to have an idea of the performance of the two methods?
- N2O emissions are highly related to soil nutrient availability, do you have information about the spatial variation of soil N among chamber locations? Table S2 shows the soil properties data but where the soils are sampled and how they can represent the different chamber measurement locations?
- Since the observed CH4 emissions are not explained by moist soil or rain event, do you have more information can explain this? How about the ground vegetation in different plots, especially in the chamber location which show emissions throughout the period.
- Please check and clarify if the data comes from automatic chamber or fast box chamber in all table and figure captions.
Citation: https://doi.org/10.5194/egusphere-2024-2346-RC3 - AC3: 'Reply on RC3', Roxanne Daelman, 22 Oct 2024
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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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