the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 05 Oct 2023
Impacts of passive experimental warming on daytime and night-time respiration in a semi-natural grassland
Abstract. Soil respiration (SR) is the largest source of CO2 released from the terrestrial ecosystem. It is greatly influenced by soil carbon pool, climate warming and daily fluxes i.e., daytime (DT) and night-time (NT) temperatures. However, there are hardly any studies relating to the effects of passive experimental warming on Ecosystem respiration (ER) and SR during DT and NT. We conducted a simulated warming experiment using passive Open Top Chamber (OTC) in a semi-natural grassland of Doon Valley, in the state of Uttarakhand, India. OTCs showed an increase in DT and NT soil temperatures. SR and ER were measured within OTC as well as outside using LI-8100A Automated Soil CO2 Flux System. We found that SR and ER increased under passive experimental warming by 38.66 % and 20.35 % during DT, and 38.8 % and 12.41 % during NT respectively. SR/ER ratio increased under passive warming treatment during DT and NT, indicating SR as the major contributor to ER. Temperature-respiration showed a positive relationship under ambient and warming conditions. Q10 analyses revealed that respiration rates are sensitive to passive warming, especially during the NT. This study addresses the crucial gap of monitoring NT respiration in addition to DT respiration to estimate the CO2 efflux and its response to passive experimental warming.
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Status: closed
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RC1: 'Comment on bg-2023-168', Anonymous Referee #1, 04 Nov 2023
In this study, authors constructed regression models to describe relationships between respiration rates and environmental factors. For this purpose, authors employed CO2 concentrations observed on the soil surfaces outside and inside of open-top-chambers.
___ Critical Issues ___
(1) First, the data needs to be more expansive to bring out some general perspectives. The authors conducted observations on only one field site for three months.(2) For estimating respiration rates from observed CO2 concentration in open-air environments, air exchange rates between soil surface and ambient atmosphere are required. As the authors do not mention it, I cannot figure out how they estimated respiration rates.
(3) For estimating ecosystem respiration rate, authors utilized CO2 concentration on intact (control) plots. As the intact plots contain grass leaves, the influence of photosynthesis should be removed to estimate the respiration rate at the time. However, the authors do not mention it at all.
___ Minor issues ___
(1) Line 39
But, photosynthesis would show more fluctuation with daily changes in sunlight.(2) Lines 108-109 "depending upon the temperature peak and environmental feasibility."
That is a very ambiguous description explaining how you selected the observation time.(3) Line 132 "even after transformation"
What transformation?(4) Equations 1, 2, 3
Factrial terms would be presented in superscripts. All equations employ α and β for representing coefficients, but different symbols would represent different coefficients.(5) Equations 3
This equation is different from the definition of Q10 of general usage. More descriptions are needed.(6) Section 3.1
No description of soil temperature (Fig 2b).(7) Section 3.4
What is the single "grain" of data for conducting statistical analysis? According to the description in lines 107-110, two patterns exist in data observation timing. Did the authors mix data from different observation timings?Citation: https://doi.org/10.5194/bg-2023-168-RC1 -
AC1: 'Reply on RC1', Deepali Bansal, 09 Nov 2023
Comment: First, the data needs to be more expansive to bring out some general perspectives. The authors conducted observations on only one field site for three months.
Response: Studies focusing on daytime and night-time respiration rates are scarce in the existing literature. Only a few studies have studied nighttime soil respiration in control setups. This is the first study assessing the daytime as well as night-time respiration rates in natural and elevated temperature scenarios [line 259]. Though this is a short study, it provides valuable insights related to respiration rates response to experimental warming [line 252] which will be useful for studies relating to night-time respiration. We found that night-time respiration rates are more sensitive to warming than daytime [line 253-254].
Comment: For estimating respiration rates from observed CO2 concentration in open-air environments, air exchange rates between soil surface and ambient atmosphere are required. As the authors do not mention it, I cannot figure out how they estimated respiration rates.
Response: Respiration measurements have been monitored using LI-8100A Soil Flux CO2 System [Line 104]. This is an automated system for especially designed to automatically measure soil CO2 flux.
Comment: For estimating ecosystem respiration rate, authors utilized CO2 concentration on intact (control) plots. As the intact plots contain grass leaves, the influence of photosynthesis should be removed to estimate the respiration rate at the time. However, the authors do not mention it at all.
Response: Ecosystem respiration is the net CO2 emission resulting from both autotrophic and heterotrophic respiration. While the intact plots contained plant parts that could influence photosynthesis, our measurements accounted for the net CO2 exchange to measure respiration rates (CO2 flux).
Comment: Line 39: But, photosynthesis would show more fluctuation with daily changes in sunlight.
Response: Line 39 has been referred from the study by Valentini et al., 2000. The net carbon exchange of terrestrial ecosystems is the result of balance between uptake (photosynthesis) and loss (respiration), and shows a strong diurnal, seasonal, annual, and environmental variability. Especially during night-time, net ecosystem flux is dominated by respiration (Valentini et al., 2000).
Comment: Lines 108-109: "depending upon the temperature peak and environmental feasibility." That is a very ambiguous description explaining how you selected the observation time.
Response: We monitored the respiration rates twice between 0600-1800 hours, to capture the minimum and maximum temperature of the day. We will reframe the statement in the manuscript.
Comment: Line 132 "even after transformation". What transformation?
Response: The data was not normally distributed, therefore, transformations like natural logarithm, square root, and reciprocal were computed. We will mention this in the manuscript.
Comment: Equations 1,2,3: Factorial terms would be presented in superscripts. All equations employ α and β for representing coefficients, but different symbols would represent different coefficients.
Response: We agree with your suggestion and will revise Equations 1, 2, and 3 to ensure that factorial terms are presented in superscripts. The symbols used in these equations [line 137, 138, 142] are well-recognised and used in similar studies (Peng et al., 2009; Li et al., 2020).
Comment: Equations 3: This equation is different from the definition of Q10 of general usage. More descriptions are needed.
Response: Temperature sensitivity of soil respiration during daytime and nighttime was assessed by fitting an exponential equation R= αeβ t where R is the respiration rate (ecosystem or soil), t is the temperature, coefficient a is the intercept of the respiration rates at 0°C and β represents the temperature sensitivity of the respiration [line 137]. The respiration quotient (Q10), which is efflux over a 10°C in soil temperature was calculated based on the coefficient b by Q10= e10β [line 142].
Comment: Section 3.1: No description of soil temperature (Fig 2b).
Response: Results related to soil temperature (ST) and experimental warming are mentioned in Line 149-150. Same is represented in Figure 2b [line 155-157].
Comment: Section 3.4: What is the single "grain" of data for conducting statistical analysis? According to the description in lines 107-110, two patterns exist in data observation timing. Did the authors mix data from different observation timings?
Response: We used two different ‘grains’ of data depending on the analysis being conducted. For the comparisons of daytime and night-time parameters including respiration, we used hourly measurements. This allowed us to capture the diurnal variations effectively. On the other hand, to understand the temperature-respiration relationships, we used bi-weekly data (maximum and minimum temperature). We ensured that data from different observation timings (daytime and night-time) were appropriately segregated and not mixed.
Citation: https://doi.org/10.5194/bg-2023-168-AC1
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AC1: 'Reply on RC1', Deepali Bansal, 09 Nov 2023
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RC2: 'Comment on bg-2023-168', Anonymous Referee #2, 11 Nov 2023
General comments
This manuscript describes a passive experimental warming experiment in which soil respiration (SR) from an open-top chamber is compared to control measurements. Despite decades of such manipulations, the response of SR to climate warming remains poorly constrained, but (as the authors describe in the introduction) very important due to the large soil carbon stocks and large, sensitive SR flux. The experiment is generally well described and results clearly shown.
Unfortunately, there are many problems with this work; three are absolutely fatal in my opinion:
- It’s an unreplicated experiment—there’s only a single warming chamber and a single control. There are many measurement collars within that chamber, but they’re all measuring the same thing. In addition, measurements were only made for 2-3 months, which for an in situ study isn’t long enough to draw robust conclusions.
- The treatment chamber had large differences in temperature, soil moisture, soil water content, and CO2 from the control (Figure 2). As a result, it’s impossible to attribute changes in SR to temperature with any confidence, because of the confounding effects of these other factors.
- There’s no code or data availability; see #8 below.
In summary, I appreciate the large amount of work done here, but with no replication and no proper control, these results are opaque and anecdotal.
Specific comments
- Lines 16-17: statistical significance should be reported here as well as percentages
- 31: there really aren’t credible SR flux estimates of 50 PgC/yr that I’m aware of…almost all in the last 20 years cluster in the 80-95 range
- 34-36: this is very tendentious; an increase in SR does not necessarily exert a climate warming effect, and the references provided don’t prove that. I suggest rewording to reflect considerably scientific uncertainty on this topic
- 52-54: this is not true; Q10 is a temperature response only, and while the ‘apparent’ Q10 might include the effects of e.g. soil moisture, it’s not everything. For example, consider an ecosystem with no temperature variability at all but large soil moisture swings
- 65: a more recent citation would be useful here
- Figure 1: nice photo—this is very helpful
- 132-133: interesting and conservative choice! Thanks for documenting
- Code and data availability? In 2023 I generally expect these to be permanently deposited for reviewers and to support long-term scientific transparency and reproducibility; “available upon request” is not acceptable
- Figure 2: it would be helpful if the caption said exactly what statistical test is being used
- Table 1: Including the temperature and moisture ranges, and N of the models, would be useful
- 203: “passive experimental warming increased…” the problem is that many different things changed in the treatment chamber (Figure 2), so you don’t know what actually drove this
- Figure 5 is confusing. Why do the T-SR relationships look so linear, when the Q10 values get quite large? By definition this should mean an exponential increase
- 212-221: well written and informative
- 246-248: well, suggesting it, but you have to address the N=1 problem somewhere here in the discussion. Also, there were only three months of measurements
- 250-256: probably not needed?
- Out of curiosity, why is DB credited with respiration measurements in line 281 but Pooja Panthari credited in 294?
Citation: https://doi.org/10.5194/bg-2023-168-RC2 -
AC2: 'Reply on RC2', Deepali Bansal, 04 Dec 2023
Comment: It’s an unreplicated experiment—there’s only a single warming chamber and a single control. There are many measurement collars within that chamber, but they’re all measuring the same thing.
Response: This study employed a single experimental warming and single control plot [line 89], with six collars in each plot [line 94] serving as pseudo-replicates for all parameter measurements. While we acknowledge the limitation in replication [line 261], it's important to note that our research is pioneering, focusing on the significance of monitoring night-time respiration responses along with daytime to understand the respiratory dynamics. [line 255].
The duration of soil respiration studies varies based on specific goals and conditions. Some, like Dyukarev & Kurakov (2023), span only a few days, while others extend over several years. Even though this is a short study, it provides valuable insights related to respiration rates response to experimental warming [line 252] which will be useful for studies relating to night-time respiration.
Comment: The treatment chamber had large differences in temperature, soil moisture, soil water content, and CO2 from the control (Figure 2). As a result, it’s impossible to attribute changes in SR to temperature with any confidence, because of the confounding effects of these other factors.
Response: In our study, the initial driver was the simulation of air temperature changes, which subsequently led to alterations in various environmental parameters, including soil temperature and moisture [line 149-152]. The deliberate simulation of air temperature changes in our study was designed to reflect the complexities of real-world conditions, recognizing that in nature, warming would similarly exert indirect effects on various parameters. It's essential to recognize that confounding effects are an integral aspect of ecological studies conducted in natural environments. The intentional design of our study aligns with the unpredictable nature of ecosystems, where uncontrollable variables contribute to their inherent complexity.
Comment: There’s no code or data availability; see #8 below.
All the raw and processed data is readily available and will be deposited to the journal repository.
Comment: In summary, I appreciate the large amount of work done here, but with no replication and no proper control, these results are opaque and anecdotal.
Response: We appreciate your acknowledgment of our efforts in studying the potential impacts of passive experimental warming on daytime (DT) and night-time (NT) respiration rates. This study addresses a critical gap by monitoring NT respiration alongside DT under passive experimental warming in a natural setup—a novel approach in the field. Our findings provide valuable insights, suggesting increased sensitivity of NT respiration rates to warming [line 247], as indicated by the rise in Q10 values [line 203].
All the raw and processed data is available and will be deposited to the journal repository.
Specific comments
Comment: Lines 16-17: statistical significance should be reported here as well as percentages
Response: We will include information on both statistical significance and percentages to provide a more comprehensive presentation of the results.
Comment: 31: there really aren’t credible SR flux estimates of 50 PgC/yr that I’m aware of…almost all in the last 20 years cluster in the 80-95 range
Response: Please find references supporting the line 31:
Lu, H., Li, S., Ma, M., Bastrikov, V., Chen, X., Ciais, P., Dai, Y., Ito, A., Ju, W., Lienert, S., Lombardozzi, D., Lu, X., Maignan, F., Nakhavali, M., Quine, T., Schindlbacher, A., Wang, J., Wang, Y., Wårlind, D., Zhang, S., & Yuan, W. (2021). Comparing machine learning-derived global estimates of soil respiration and its components with those from terrestrial ecosystem models. Environmental Research Letters, 16. https://doi.org/10.1088/1748-9326/abf526.
Hashimoto, S., Carvalhais, N., Ito, A., Migliavacca, M., Nishina, K., & Reichstein, M. (2015). Global spatiotemporal distribution of soil respiration modeled using a global database. Biogeosciences, 12(13), 4121-4132.
Comment: 34-36: this is very tendentious; an increase in SR does not necessarily exert a climate warming effect, and the references provided don’t prove that. I suggest rewording to reflect considerably scientific uncertainty on this topic
Response: Line 34-36 reflects the findings published in the referenced literature, providing a comprehensive overview of the available information.
Lu et al. (2013) outlined that small changes in soil respiration flux can have a substantial impact on atmospheric CO2 concentrations, potentially constituting positive feedback to the climate system. On the other hand, Wang et al. (2014) provides insights into the biological causes of diel hysteresis between respiration rates and temperature, indicating that the response of respiration to soil moisture may result in negative feedback to climate warming.
Comment: 52-54: this is not true; Q10 is a temperature response only, and while the ‘apparent’ Q10 might include the effects of e.g. soil moisture, it’s not everything. For example, consider an ecosystem with no temperature variability at all but large soil moisture swings
Response: The temperature sensitivity of soil respiration is often expressed as the Q10 value; that is, the factor by which soil respiration increases by a 10°C increase in temperature. We will modify the line 52-54 further for clarity.
Comment: 65: a more recent citation would be useful here
Response: We will include a more recent reference for line 65.
Comment: Figure 1: nice photo—this is very helpful
Response: We're glad you find Figure 1 helpful.
Comment: 132-133: interesting and conservative choice! Thanks for documenting
Response: We appreciate your attention to this detail.
Comment: Code and data availability? In 2023 I generally expect these to be permanently deposited for reviewers and to support long-term scientific transparency and reproducibility; “available upon request” is not acceptable.
Response: We haven't submitted the data for public discussion, but we plan to deposit it to the journal repository upon acceptance. All the raw and processed data will be made available.
Comment: Figure 2: it would be helpful if the caption said exactly what statistical test is being used
Response: The statistical test information is common for Figures 2, 3, and 4 and is detailed in the respective sections of the manuscript [Line 133].
Comment: Table 1: Including the temperature and moisture ranges, and N of the models, would be useful
Response: We appreciate your suggestion. In the revision, we'll include the temperature and moisture ranges, along with the number (N).
Comment: 203: “passive experimental warming increased…” the problem is that many different things changed in the treatment chamber (Figure 2), so you don’t know what actually drove this
Response: The observed changes in the treatment chamber were primarily driven by the simulated air temperature, which, in turn, had indirect effects on other parameters. This mimics the natural process of warming, where alterations often originate from changes in air temperature. We will explicitly highlight this point in the manuscript for clarity.
Comment: Figure 5 is confusing. Why do the T-SR relationships look so linear, when the Q10 values get quite large? By definition this should mean an exponential increase
Response: T-SR relationships observed in Figure 5 is due to the use of an exponential equation (R= αeβ t), where R is the respiration rate, t is the temperature, α is the intercept at 0°C, and β represents the temperature sensitivity [line 137]. The resulting Q10 values, indicating the temperature sensitivity over a 10°C change, were calculated as Q10= e^(10β) [line 142]. These details are explicitly stated in the manuscript, and for further clarity, the exponential relationships between soil temperature (ST) and respiration rates are outlined in Table 1 [line 191] and Table 2 [line 195].
Comment: 212-221: well written and informative
Response: We appreciate your positive feedback.
Comment: 246-248: well, suggesting it, but you have to address the N=1 problem somewhere here in the discussion. Also, there were only three months of measurements
Response: We have taken a proactive approach by incorporating future works specifically aimed at addressing these limitations.
Comment: 250-256: probably not needed?
Response: The content in lines 250-256 is crucial as it constitutes the conclusion of the manuscript, summarizing key findings and implications. We want to ensure that the conclusion effectively reflects the significance of the study.
Comment: Out of curiosity, why is DB credited with respiration measurements in line 281 but Pooja Panthari credited in 294?
Response: The distinction between lines 281 and 294 lies in their purpose. Line 281 is dedicated to summarizing the authors' contributions to the respiration measurements, while line 294 serves as acknowledgments for those who provided support to the authors in their research work.
Citation: https://doi.org/10.5194/bg-2023-168-AC2
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RC3: 'Comment on bg-2023-168', Anonymous Referee #3, 12 Nov 2023
Comments bg-2023-168-1
This study conducted a simulated warming experiment in a semi-natural grassland. Soil respiration and ecosystem respiration were measured during daytime and night-time. This study highlights the importance of monitoring respiration during daytime and night-time for improving our understanding of grassland carbon cycle under climate warming. Although the warming facility, i.e., OTC, has some issues in mimicking climate warming, the major findings in this study are novel and interesting. There are some questions for this article to be further clarified, so I’d recommend some major revisions before this study is considered for publication. Please find my specific comments below:
The specific comments are as follows:
- In the abstract section, please consider deleting some descriptions about measuring instruments. It might be more appropriate for the abstract to highlight the results and significance of the study.
- The writing of the introduction can be further improved. For example, the research topic of day and night warming has been well reviewed in the scope of non-uniform warming or asymmetric climate warming. It would be helpful to let the readers know that day and night warming are important for understanding terrestrial carbon cycle in response to climate warming.
- In lines 17-18, SR/ER ratio increased under passive warming treatment might indicate that SR increased more than ER, why indicated SR as the major contributor to ER?
- In the introduction section, it is necessary to integrate the progress and different perspectives based on previous studies, thus leading to the research topic and content. In lines 41-42, perhaps there has been lots of research on respiration; however, it is only limited in some ways.
- Please consider combining the four objectives of this study (Line 69-72). There is some duplication in the current content.
- In the results section, please note the English grammar and expression. Meanwhile, please add the analysis of the results as appropriate.
- Please note some of the details, such as the corner markers.
- In the discussion section, the discussion in the current version does not seem to be sufficient and in-depth. The discussion is centred around the results of the experiment, but a broader range of content could be added. For example, about the difference between warming on night-time and daytime soil respiration, whether it is found in other ecosystems, etc.
- The method of using OTC to mimic climate warming may have some issues, which have been discussed in the literature. Please add some discussions on this issue.
- It is recommended that the article be revised in its entirety to meet publication requirements.
- 1: You may add an experimental design associated with the picture of a single plot.
- Lines 137-142; the format of equations needs to be corrected.
Citation: https://doi.org/10.5194/bg-2023-168-RC3 -
AC3: 'Reply on RC3', Deepali Bansal, 04 Dec 2023
Comment: In the abstract section, please consider deleting some descriptions about measuring instruments. It might be more appropriate for the abstract to highlight the results and significance of the study.
Response: We’ll make sure that essential information about the technique is maintained for clarity and description of the measuring instrument will be deleted.
Comment: The writing of the introduction can be further improved. For example, the research topic of day and night warming has been well reviewed in the scope of non-uniform warming or asymmetric climate warming. It would be helpful to let the readers know that day and night warming are important for understanding terrestrial carbon cycle in response to climate warming.
Response: Recognizing the significance of day and night warming in the context of non-uniform or asymmetric climate warming is crucial. We will incorporate additional information as suggested.
Comment: In lines 17-18, SR/ER ratio increased under passive warming treatment might indicate that SR increased more than ER, why indicated SR as the major contributor to ER?
warming.
Response: ER is composed of both aboveground and belowground respiration (SR). The observed increase in the SR/ER ratio implies a proportionally greater contribution from belowground respiration (SR) in the overall ER.
Comment: In the introduction section, it is necessary to integrate the progress and different perspectives based on previous studies, thus leading to the research topic and content. In lines 41-42, perhaps there has been lots of research on respiration; however, it is only limited in some ways.
warming.
Response: In the introduction, we incorporate diverse perspectives from previous studies. Notably, we emphasize that respiration rates respond differently to alterations in temperatures and environmental conditions (line 38, 45-52). While studies have mainly concentrated on DT respiration rates, especially during the growing season (line 42), the exploration of NT respiration rates is infrequently undertaken (line 43). Additionally, we highlight the unique characteristics of semi-natural grasslands, underlining their significance in the global soil carbon stock (line 55-63).
Comment: Please consider combining the four objectives of this study (Line 69-72). There is some duplication in the current content.
Response: We acknowledge the suggestion to streamline the language and combine the four study objectives outlined in lines 69-72. While maintaining the individual clarity of each objective, we will work on modifying the language to present them more concisely.
Comment: In the results section, please note the English grammar and expression. Meanwhile, please add the analysis of the results as appropriate.
Response: We will rectify the grammar in the result section if needed. The statistical test information is common for the results and is detailed in the respective sections of the manuscript [Line 133].
Comment: Please note some of the details, such as the corner markers.
Response: We'll ensure to include additional details for clarity.
Comment: In the discussion section, the discussion in the current version does not seem to be sufficient and in-depth. The discussion is centred around the results of the experiment, but a broader range of content could be added. For example, about the difference between warming on night-time and daytime soil respiration, whether it is found in other ecosystems, etc.
Response: We will revise the discussion based on the reliability and relevance of our findings within their specific context.
Comment: The method of using OTC to mimic climate warming may have some issues, which have been discussed in the literature. Please add some discussions on this issue.
Response: We'll discuss the limitations associated with using OTCs to simulate climate warming in the revised discussion section.
It is recommended that the article be revised in its entirety to meet publication requirements.
Comment: You may add an experimental design associated with the picture of a single plot.
Response: The experimental design, including the depiction of a single plot, is already presented in Figure 1. This figure provides a visual representation of our experimental setup.
Comment: Lines 137-142; the format of equations needs to be corrected.
Response: We agree with your suggestion and will revise Equations 1, 2, and 3 to ensure that factorial terms are presented in superscripts.
Citation: https://doi.org/10.5194/bg-2023-168-AC3
Status: closed
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RC1: 'Comment on bg-2023-168', Anonymous Referee #1, 04 Nov 2023
In this study, authors constructed regression models to describe relationships between respiration rates and environmental factors. For this purpose, authors employed CO2 concentrations observed on the soil surfaces outside and inside of open-top-chambers.
___ Critical Issues ___
(1) First, the data needs to be more expansive to bring out some general perspectives. The authors conducted observations on only one field site for three months.(2) For estimating respiration rates from observed CO2 concentration in open-air environments, air exchange rates between soil surface and ambient atmosphere are required. As the authors do not mention it, I cannot figure out how they estimated respiration rates.
(3) For estimating ecosystem respiration rate, authors utilized CO2 concentration on intact (control) plots. As the intact plots contain grass leaves, the influence of photosynthesis should be removed to estimate the respiration rate at the time. However, the authors do not mention it at all.
___ Minor issues ___
(1) Line 39
But, photosynthesis would show more fluctuation with daily changes in sunlight.(2) Lines 108-109 "depending upon the temperature peak and environmental feasibility."
That is a very ambiguous description explaining how you selected the observation time.(3) Line 132 "even after transformation"
What transformation?(4) Equations 1, 2, 3
Factrial terms would be presented in superscripts. All equations employ α and β for representing coefficients, but different symbols would represent different coefficients.(5) Equations 3
This equation is different from the definition of Q10 of general usage. More descriptions are needed.(6) Section 3.1
No description of soil temperature (Fig 2b).(7) Section 3.4
What is the single "grain" of data for conducting statistical analysis? According to the description in lines 107-110, two patterns exist in data observation timing. Did the authors mix data from different observation timings?Citation: https://doi.org/10.5194/bg-2023-168-RC1 -
AC1: 'Reply on RC1', Deepali Bansal, 09 Nov 2023
Comment: First, the data needs to be more expansive to bring out some general perspectives. The authors conducted observations on only one field site for three months.
Response: Studies focusing on daytime and night-time respiration rates are scarce in the existing literature. Only a few studies have studied nighttime soil respiration in control setups. This is the first study assessing the daytime as well as night-time respiration rates in natural and elevated temperature scenarios [line 259]. Though this is a short study, it provides valuable insights related to respiration rates response to experimental warming [line 252] which will be useful for studies relating to night-time respiration. We found that night-time respiration rates are more sensitive to warming than daytime [line 253-254].
Comment: For estimating respiration rates from observed CO2 concentration in open-air environments, air exchange rates between soil surface and ambient atmosphere are required. As the authors do not mention it, I cannot figure out how they estimated respiration rates.
Response: Respiration measurements have been monitored using LI-8100A Soil Flux CO2 System [Line 104]. This is an automated system for especially designed to automatically measure soil CO2 flux.
Comment: For estimating ecosystem respiration rate, authors utilized CO2 concentration on intact (control) plots. As the intact plots contain grass leaves, the influence of photosynthesis should be removed to estimate the respiration rate at the time. However, the authors do not mention it at all.
Response: Ecosystem respiration is the net CO2 emission resulting from both autotrophic and heterotrophic respiration. While the intact plots contained plant parts that could influence photosynthesis, our measurements accounted for the net CO2 exchange to measure respiration rates (CO2 flux).
Comment: Line 39: But, photosynthesis would show more fluctuation with daily changes in sunlight.
Response: Line 39 has been referred from the study by Valentini et al., 2000. The net carbon exchange of terrestrial ecosystems is the result of balance between uptake (photosynthesis) and loss (respiration), and shows a strong diurnal, seasonal, annual, and environmental variability. Especially during night-time, net ecosystem flux is dominated by respiration (Valentini et al., 2000).
Comment: Lines 108-109: "depending upon the temperature peak and environmental feasibility." That is a very ambiguous description explaining how you selected the observation time.
Response: We monitored the respiration rates twice between 0600-1800 hours, to capture the minimum and maximum temperature of the day. We will reframe the statement in the manuscript.
Comment: Line 132 "even after transformation". What transformation?
Response: The data was not normally distributed, therefore, transformations like natural logarithm, square root, and reciprocal were computed. We will mention this in the manuscript.
Comment: Equations 1,2,3: Factorial terms would be presented in superscripts. All equations employ α and β for representing coefficients, but different symbols would represent different coefficients.
Response: We agree with your suggestion and will revise Equations 1, 2, and 3 to ensure that factorial terms are presented in superscripts. The symbols used in these equations [line 137, 138, 142] are well-recognised and used in similar studies (Peng et al., 2009; Li et al., 2020).
Comment: Equations 3: This equation is different from the definition of Q10 of general usage. More descriptions are needed.
Response: Temperature sensitivity of soil respiration during daytime and nighttime was assessed by fitting an exponential equation R= αeβ t where R is the respiration rate (ecosystem or soil), t is the temperature, coefficient a is the intercept of the respiration rates at 0°C and β represents the temperature sensitivity of the respiration [line 137]. The respiration quotient (Q10), which is efflux over a 10°C in soil temperature was calculated based on the coefficient b by Q10= e10β [line 142].
Comment: Section 3.1: No description of soil temperature (Fig 2b).
Response: Results related to soil temperature (ST) and experimental warming are mentioned in Line 149-150. Same is represented in Figure 2b [line 155-157].
Comment: Section 3.4: What is the single "grain" of data for conducting statistical analysis? According to the description in lines 107-110, two patterns exist in data observation timing. Did the authors mix data from different observation timings?
Response: We used two different ‘grains’ of data depending on the analysis being conducted. For the comparisons of daytime and night-time parameters including respiration, we used hourly measurements. This allowed us to capture the diurnal variations effectively. On the other hand, to understand the temperature-respiration relationships, we used bi-weekly data (maximum and minimum temperature). We ensured that data from different observation timings (daytime and night-time) were appropriately segregated and not mixed.
Citation: https://doi.org/10.5194/bg-2023-168-AC1
-
AC1: 'Reply on RC1', Deepali Bansal, 09 Nov 2023
-
RC2: 'Comment on bg-2023-168', Anonymous Referee #2, 11 Nov 2023
General comments
This manuscript describes a passive experimental warming experiment in which soil respiration (SR) from an open-top chamber is compared to control measurements. Despite decades of such manipulations, the response of SR to climate warming remains poorly constrained, but (as the authors describe in the introduction) very important due to the large soil carbon stocks and large, sensitive SR flux. The experiment is generally well described and results clearly shown.
Unfortunately, there are many problems with this work; three are absolutely fatal in my opinion:
- It’s an unreplicated experiment—there’s only a single warming chamber and a single control. There are many measurement collars within that chamber, but they’re all measuring the same thing. In addition, measurements were only made for 2-3 months, which for an in situ study isn’t long enough to draw robust conclusions.
- The treatment chamber had large differences in temperature, soil moisture, soil water content, and CO2 from the control (Figure 2). As a result, it’s impossible to attribute changes in SR to temperature with any confidence, because of the confounding effects of these other factors.
- There’s no code or data availability; see #8 below.
In summary, I appreciate the large amount of work done here, but with no replication and no proper control, these results are opaque and anecdotal.
Specific comments
- Lines 16-17: statistical significance should be reported here as well as percentages
- 31: there really aren’t credible SR flux estimates of 50 PgC/yr that I’m aware of…almost all in the last 20 years cluster in the 80-95 range
- 34-36: this is very tendentious; an increase in SR does not necessarily exert a climate warming effect, and the references provided don’t prove that. I suggest rewording to reflect considerably scientific uncertainty on this topic
- 52-54: this is not true; Q10 is a temperature response only, and while the ‘apparent’ Q10 might include the effects of e.g. soil moisture, it’s not everything. For example, consider an ecosystem with no temperature variability at all but large soil moisture swings
- 65: a more recent citation would be useful here
- Figure 1: nice photo—this is very helpful
- 132-133: interesting and conservative choice! Thanks for documenting
- Code and data availability? In 2023 I generally expect these to be permanently deposited for reviewers and to support long-term scientific transparency and reproducibility; “available upon request” is not acceptable
- Figure 2: it would be helpful if the caption said exactly what statistical test is being used
- Table 1: Including the temperature and moisture ranges, and N of the models, would be useful
- 203: “passive experimental warming increased…” the problem is that many different things changed in the treatment chamber (Figure 2), so you don’t know what actually drove this
- Figure 5 is confusing. Why do the T-SR relationships look so linear, when the Q10 values get quite large? By definition this should mean an exponential increase
- 212-221: well written and informative
- 246-248: well, suggesting it, but you have to address the N=1 problem somewhere here in the discussion. Also, there were only three months of measurements
- 250-256: probably not needed?
- Out of curiosity, why is DB credited with respiration measurements in line 281 but Pooja Panthari credited in 294?
Citation: https://doi.org/10.5194/bg-2023-168-RC2 -
AC2: 'Reply on RC2', Deepali Bansal, 04 Dec 2023
Comment: It’s an unreplicated experiment—there’s only a single warming chamber and a single control. There are many measurement collars within that chamber, but they’re all measuring the same thing.
Response: This study employed a single experimental warming and single control plot [line 89], with six collars in each plot [line 94] serving as pseudo-replicates for all parameter measurements. While we acknowledge the limitation in replication [line 261], it's important to note that our research is pioneering, focusing on the significance of monitoring night-time respiration responses along with daytime to understand the respiratory dynamics. [line 255].
The duration of soil respiration studies varies based on specific goals and conditions. Some, like Dyukarev & Kurakov (2023), span only a few days, while others extend over several years. Even though this is a short study, it provides valuable insights related to respiration rates response to experimental warming [line 252] which will be useful for studies relating to night-time respiration.
Comment: The treatment chamber had large differences in temperature, soil moisture, soil water content, and CO2 from the control (Figure 2). As a result, it’s impossible to attribute changes in SR to temperature with any confidence, because of the confounding effects of these other factors.
Response: In our study, the initial driver was the simulation of air temperature changes, which subsequently led to alterations in various environmental parameters, including soil temperature and moisture [line 149-152]. The deliberate simulation of air temperature changes in our study was designed to reflect the complexities of real-world conditions, recognizing that in nature, warming would similarly exert indirect effects on various parameters. It's essential to recognize that confounding effects are an integral aspect of ecological studies conducted in natural environments. The intentional design of our study aligns with the unpredictable nature of ecosystems, where uncontrollable variables contribute to their inherent complexity.
Comment: There’s no code or data availability; see #8 below.
All the raw and processed data is readily available and will be deposited to the journal repository.
Comment: In summary, I appreciate the large amount of work done here, but with no replication and no proper control, these results are opaque and anecdotal.
Response: We appreciate your acknowledgment of our efforts in studying the potential impacts of passive experimental warming on daytime (DT) and night-time (NT) respiration rates. This study addresses a critical gap by monitoring NT respiration alongside DT under passive experimental warming in a natural setup—a novel approach in the field. Our findings provide valuable insights, suggesting increased sensitivity of NT respiration rates to warming [line 247], as indicated by the rise in Q10 values [line 203].
All the raw and processed data is available and will be deposited to the journal repository.
Specific comments
Comment: Lines 16-17: statistical significance should be reported here as well as percentages
Response: We will include information on both statistical significance and percentages to provide a more comprehensive presentation of the results.
Comment: 31: there really aren’t credible SR flux estimates of 50 PgC/yr that I’m aware of…almost all in the last 20 years cluster in the 80-95 range
Response: Please find references supporting the line 31:
Lu, H., Li, S., Ma, M., Bastrikov, V., Chen, X., Ciais, P., Dai, Y., Ito, A., Ju, W., Lienert, S., Lombardozzi, D., Lu, X., Maignan, F., Nakhavali, M., Quine, T., Schindlbacher, A., Wang, J., Wang, Y., Wårlind, D., Zhang, S., & Yuan, W. (2021). Comparing machine learning-derived global estimates of soil respiration and its components with those from terrestrial ecosystem models. Environmental Research Letters, 16. https://doi.org/10.1088/1748-9326/abf526.
Hashimoto, S., Carvalhais, N., Ito, A., Migliavacca, M., Nishina, K., & Reichstein, M. (2015). Global spatiotemporal distribution of soil respiration modeled using a global database. Biogeosciences, 12(13), 4121-4132.
Comment: 34-36: this is very tendentious; an increase in SR does not necessarily exert a climate warming effect, and the references provided don’t prove that. I suggest rewording to reflect considerably scientific uncertainty on this topic
Response: Line 34-36 reflects the findings published in the referenced literature, providing a comprehensive overview of the available information.
Lu et al. (2013) outlined that small changes in soil respiration flux can have a substantial impact on atmospheric CO2 concentrations, potentially constituting positive feedback to the climate system. On the other hand, Wang et al. (2014) provides insights into the biological causes of diel hysteresis between respiration rates and temperature, indicating that the response of respiration to soil moisture may result in negative feedback to climate warming.
Comment: 52-54: this is not true; Q10 is a temperature response only, and while the ‘apparent’ Q10 might include the effects of e.g. soil moisture, it’s not everything. For example, consider an ecosystem with no temperature variability at all but large soil moisture swings
Response: The temperature sensitivity of soil respiration is often expressed as the Q10 value; that is, the factor by which soil respiration increases by a 10°C increase in temperature. We will modify the line 52-54 further for clarity.
Comment: 65: a more recent citation would be useful here
Response: We will include a more recent reference for line 65.
Comment: Figure 1: nice photo—this is very helpful
Response: We're glad you find Figure 1 helpful.
Comment: 132-133: interesting and conservative choice! Thanks for documenting
Response: We appreciate your attention to this detail.
Comment: Code and data availability? In 2023 I generally expect these to be permanently deposited for reviewers and to support long-term scientific transparency and reproducibility; “available upon request” is not acceptable.
Response: We haven't submitted the data for public discussion, but we plan to deposit it to the journal repository upon acceptance. All the raw and processed data will be made available.
Comment: Figure 2: it would be helpful if the caption said exactly what statistical test is being used
Response: The statistical test information is common for Figures 2, 3, and 4 and is detailed in the respective sections of the manuscript [Line 133].
Comment: Table 1: Including the temperature and moisture ranges, and N of the models, would be useful
Response: We appreciate your suggestion. In the revision, we'll include the temperature and moisture ranges, along with the number (N).
Comment: 203: “passive experimental warming increased…” the problem is that many different things changed in the treatment chamber (Figure 2), so you don’t know what actually drove this
Response: The observed changes in the treatment chamber were primarily driven by the simulated air temperature, which, in turn, had indirect effects on other parameters. This mimics the natural process of warming, where alterations often originate from changes in air temperature. We will explicitly highlight this point in the manuscript for clarity.
Comment: Figure 5 is confusing. Why do the T-SR relationships look so linear, when the Q10 values get quite large? By definition this should mean an exponential increase
Response: T-SR relationships observed in Figure 5 is due to the use of an exponential equation (R= αeβ t), where R is the respiration rate, t is the temperature, α is the intercept at 0°C, and β represents the temperature sensitivity [line 137]. The resulting Q10 values, indicating the temperature sensitivity over a 10°C change, were calculated as Q10= e^(10β) [line 142]. These details are explicitly stated in the manuscript, and for further clarity, the exponential relationships between soil temperature (ST) and respiration rates are outlined in Table 1 [line 191] and Table 2 [line 195].
Comment: 212-221: well written and informative
Response: We appreciate your positive feedback.
Comment: 246-248: well, suggesting it, but you have to address the N=1 problem somewhere here in the discussion. Also, there were only three months of measurements
Response: We have taken a proactive approach by incorporating future works specifically aimed at addressing these limitations.
Comment: 250-256: probably not needed?
Response: The content in lines 250-256 is crucial as it constitutes the conclusion of the manuscript, summarizing key findings and implications. We want to ensure that the conclusion effectively reflects the significance of the study.
Comment: Out of curiosity, why is DB credited with respiration measurements in line 281 but Pooja Panthari credited in 294?
Response: The distinction between lines 281 and 294 lies in their purpose. Line 281 is dedicated to summarizing the authors' contributions to the respiration measurements, while line 294 serves as acknowledgments for those who provided support to the authors in their research work.
Citation: https://doi.org/10.5194/bg-2023-168-AC2
-
RC3: 'Comment on bg-2023-168', Anonymous Referee #3, 12 Nov 2023
Comments bg-2023-168-1
This study conducted a simulated warming experiment in a semi-natural grassland. Soil respiration and ecosystem respiration were measured during daytime and night-time. This study highlights the importance of monitoring respiration during daytime and night-time for improving our understanding of grassland carbon cycle under climate warming. Although the warming facility, i.e., OTC, has some issues in mimicking climate warming, the major findings in this study are novel and interesting. There are some questions for this article to be further clarified, so I’d recommend some major revisions before this study is considered for publication. Please find my specific comments below:
The specific comments are as follows:
- In the abstract section, please consider deleting some descriptions about measuring instruments. It might be more appropriate for the abstract to highlight the results and significance of the study.
- The writing of the introduction can be further improved. For example, the research topic of day and night warming has been well reviewed in the scope of non-uniform warming or asymmetric climate warming. It would be helpful to let the readers know that day and night warming are important for understanding terrestrial carbon cycle in response to climate warming.
- In lines 17-18, SR/ER ratio increased under passive warming treatment might indicate that SR increased more than ER, why indicated SR as the major contributor to ER?
- In the introduction section, it is necessary to integrate the progress and different perspectives based on previous studies, thus leading to the research topic and content. In lines 41-42, perhaps there has been lots of research on respiration; however, it is only limited in some ways.
- Please consider combining the four objectives of this study (Line 69-72). There is some duplication in the current content.
- In the results section, please note the English grammar and expression. Meanwhile, please add the analysis of the results as appropriate.
- Please note some of the details, such as the corner markers.
- In the discussion section, the discussion in the current version does not seem to be sufficient and in-depth. The discussion is centred around the results of the experiment, but a broader range of content could be added. For example, about the difference between warming on night-time and daytime soil respiration, whether it is found in other ecosystems, etc.
- The method of using OTC to mimic climate warming may have some issues, which have been discussed in the literature. Please add some discussions on this issue.
- It is recommended that the article be revised in its entirety to meet publication requirements.
- 1: You may add an experimental design associated with the picture of a single plot.
- Lines 137-142; the format of equations needs to be corrected.
Citation: https://doi.org/10.5194/bg-2023-168-RC3 -
AC3: 'Reply on RC3', Deepali Bansal, 04 Dec 2023
Comment: In the abstract section, please consider deleting some descriptions about measuring instruments. It might be more appropriate for the abstract to highlight the results and significance of the study.
Response: We’ll make sure that essential information about the technique is maintained for clarity and description of the measuring instrument will be deleted.
Comment: The writing of the introduction can be further improved. For example, the research topic of day and night warming has been well reviewed in the scope of non-uniform warming or asymmetric climate warming. It would be helpful to let the readers know that day and night warming are important for understanding terrestrial carbon cycle in response to climate warming.
Response: Recognizing the significance of day and night warming in the context of non-uniform or asymmetric climate warming is crucial. We will incorporate additional information as suggested.
Comment: In lines 17-18, SR/ER ratio increased under passive warming treatment might indicate that SR increased more than ER, why indicated SR as the major contributor to ER?
warming.
Response: ER is composed of both aboveground and belowground respiration (SR). The observed increase in the SR/ER ratio implies a proportionally greater contribution from belowground respiration (SR) in the overall ER.
Comment: In the introduction section, it is necessary to integrate the progress and different perspectives based on previous studies, thus leading to the research topic and content. In lines 41-42, perhaps there has been lots of research on respiration; however, it is only limited in some ways.
warming.
Response: In the introduction, we incorporate diverse perspectives from previous studies. Notably, we emphasize that respiration rates respond differently to alterations in temperatures and environmental conditions (line 38, 45-52). While studies have mainly concentrated on DT respiration rates, especially during the growing season (line 42), the exploration of NT respiration rates is infrequently undertaken (line 43). Additionally, we highlight the unique characteristics of semi-natural grasslands, underlining their significance in the global soil carbon stock (line 55-63).
Comment: Please consider combining the four objectives of this study (Line 69-72). There is some duplication in the current content.
Response: We acknowledge the suggestion to streamline the language and combine the four study objectives outlined in lines 69-72. While maintaining the individual clarity of each objective, we will work on modifying the language to present them more concisely.
Comment: In the results section, please note the English grammar and expression. Meanwhile, please add the analysis of the results as appropriate.
Response: We will rectify the grammar in the result section if needed. The statistical test information is common for the results and is detailed in the respective sections of the manuscript [Line 133].
Comment: Please note some of the details, such as the corner markers.
Response: We'll ensure to include additional details for clarity.
Comment: In the discussion section, the discussion in the current version does not seem to be sufficient and in-depth. The discussion is centred around the results of the experiment, but a broader range of content could be added. For example, about the difference between warming on night-time and daytime soil respiration, whether it is found in other ecosystems, etc.
Response: We will revise the discussion based on the reliability and relevance of our findings within their specific context.
Comment: The method of using OTC to mimic climate warming may have some issues, which have been discussed in the literature. Please add some discussions on this issue.
Response: We'll discuss the limitations associated with using OTCs to simulate climate warming in the revised discussion section.
It is recommended that the article be revised in its entirety to meet publication requirements.
Comment: You may add an experimental design associated with the picture of a single plot.
Response: The experimental design, including the depiction of a single plot, is already presented in Figure 1. This figure provides a visual representation of our experimental setup.
Comment: Lines 137-142; the format of equations needs to be corrected.
Response: We agree with your suggestion and will revise Equations 1, 2, and 3 to ensure that factorial terms are presented in superscripts.
Citation: https://doi.org/10.5194/bg-2023-168-AC3
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