the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 08 Sep 2021
Effect of vegetation distribution driven by hydrological fluctuation on sedimental stoichiometry regulating N2O emissions in freshwater wetland
Abstract. Hydrological conditions drive the distribution of plant communities in wetlands to form vegetation zones where the material cycling varies with plant species. This mediation effect caused by the distribution of vegetation under hydrological conditions will affect the emission of N2O during the nitrogen migration in wetlands. In this study, five vegetation zones in the second largest wetland of China were investigated in situ during high and low water levels to elucidate the effect mediated by vegetation. With the increase in the rate of change of water levels, the zones of the mud flat, nymphoides, phalaris, carex, and reeds were distributed in sequence in the wetland, and the densities of carbon and nitrogen sequestrated by plants also increased. The carbon and nitrogen densities in each zone during low water level was significantly higher than that during high water level, while the organic carbon and the total nitrogen of sediments during high water level was higher. Sediments converted between source and sink for both carbon and nitrogen, during the annual fluctuation in water level. The flux in N2O emissions showed significant differences between the vegetation zones during each water level period. The emission flux decreased with the increasing C : N ratio in sediments, approximating the threshold at 0.23 μg m−2 h−1 when the C : N ratio > 25. The phylum abundance of Firmicutes, Proteobacteria, and Chloroflexi in sediments increased with flooding. The denitrifying nirS and nirK genes and anammox hzsB gene were significantly affected by water level fluctuation, with the maximal variations of these genes occurring in the mud flat and nymphoides zone. The results indicate that the distribution of plants under hydrological conditions modified the stoichiometric ratio of sediments, resulting in the variations of N2O emission fluxes and microbial communities in vegetation zones. Therefore, hydraulic regulation rather than direct planting would be an effective strategy to reduce greenhouse gas emissions in freshwater wetlands.
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Interactive discussion
Status: closed
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RC1: 'Comment on bg-2021-208', Anonymous Referee #1, 30 Sep 2021
General comments:
Overall, the idea of the study is interestig, however the major limitation is that it is based on only few grab samples (both soil and gas). Samples were collected once during low water level event and once during high water level event. Making conclusing about the ecosystem based on few samples is not sufficient. For example, Figure 1 shows regression analyses that is based on only few points and same goes with other figures as well. To understand the dynamics at an ecosystem level, a much larger amount of samples should be collected. First to see the seasonal dynamics and secondly to have a realiable amount of data for statistical analyses.
Specific comments:
Figure 1 - Photos have low quality. Location of the region would be nice to show .
Lines 115-120 - You inserted pedestal into the soil and then started to collect gas samples. How long was the stabilisation period because this could create relatively large distrubance to the soil? How many gas samples were used to calculated flux? How did you access the site durign high flood to avoid soil distrubance? The size of the chambers?
Line 135 - Statistical analyses: was the data normally distributed? And whats tests were used to control that?
Figure 3 - caption is not refering to correct sub-plots. E.g. B is TOC not nitrogen density etc.
Figure 5 - text in the figure is so small that it is unreadable.
Line 350 - do you have data about N2O reducers: nosZ clade I and II genes? Currently the abundace of nirS, nirK and hzsB genes does not provide enough information about the entire N cycle.
Throughout the text: sometimes N2O has subscript (N2O) and sometimes not.
Citation: https://doi.org/10.5194/bg-2021-208-RC1 -
AC1: 'Reply on RC1', Wei Li, 05 Jan 2022
Reply on RC1
Huazu Liu et al.
RC1
Overall, the idea of the study is interesting, however the major limitation is that it is based on only few grab samples (both soil and gas). Samples were collected once during low water level event and once during high water level event. Making conclusing about the ecosystem based on few samples is not sufficient. For example, Figure 1 shows regression analyses that is based on only few points and same goes with other figures as well. To understand the dynamics at an ecosystem level, a much larger amount of samples should be collected. First to see the seasonal dynamics and secondly to have a realizable amount of data for statistical analyses.
Author’s response: We thank the anonymous referee#1 for the detailed reviews with relevant and constructive comments to improve the quality of the manuscript. The received recommendations were carefully considered and incorporated into the current version of the manuscript. We focused on the differences between nitrogen cycle during high and low water levels in ecosystem. Therefore, we monitored N2O emissions, vegetations and soil in the steady period after the change of water level. In addition, influenced by the Three Gorges Dam, the annual change of water level in the study area were very regular. As a result, the variations between years in the change of water level were very small. Although we set up three sampling sites at each vegetation zone in the study area, we collected as many samples as possible at each sampling site for statistical analysis. And we ensured that the distances between the sampling sites made less interference between the sites. We agreed the detailed review and comments which will be helpful in our future researches. A point-by-point response to comments was given below.
- Figure 1 - Photos have low quality. Location of the region would be nice to show.
Author’s response:
Thanks for the correction; we have replaced a photo with high quality.
- Lines 115-120 - You inserted pedestal into the soil and then started to collect gas samples. How long was the stabilisation period because this could create relatively large distrubance to the soil? How many gas samples were used to calculated flux? How did you access the site during high flood to avoid soil distrubance? The size of the chambers?
Author’s response:
For the first sampling, we inserted the pedestal about 10cm into the soil. And we didn’t take the pedestal to reduce the disturbance of subsequent samples. After the pedestal into the soil, we set a stabilization period of 30 minutes and a board to reduce soil disturbance from people (Wang, H. J., Wang, W. D., Yin, C. Q., Wang, Y. C., and Lu, J. W.: Littoral zones as the "hotspots" of nitrous oxide (N2O) emission in a hyper-eutrophic lake in China, Atmospheric Environment, 40, 5522-5527, 10.1016/j.atmosenv.2006.05.032, 2006.)(as shown in the figure below).
We shut down the ship's machinery in the study area and waited for an hour before sampling during high water level. Then, we let the chamber on the water for 30 minutes before collecting the gas. We used a 10m air pipe, which kept chamber as far away from the ship as possible to reduce disturbance (as shown in the figure below).
Seven gas samples were used to calculated flux in each sampling site. And three sampling sites were set in each vegetation zones.
We described the size of the chambers in the manuscript as following:
L116-117. “The volume of the upper chambers used during low water level was 0.028 m3 (h = 40cm, Φ = 30cm), and the volume of the pedestal was 0.011 m3 (h = 15cm, Φ = 30cm). And the volume of the chambers used during high water level was 0.018 m3 (l = 40cm, w = 30cm, h = 15cm).”
- Line 135 - Statistical analyses: was the data normally distributed? And what tests were used to control that?
Author’s response:
We used KS-test to confirm that the data was normally distributed (as shown in the figure below).
- Figure 3 - caption is not referring to correct sub-plots. E.g. B is TOC not nitrogen density etc.
Author’s response:
New caption was as following:
L171-172. “Figure 3. Content of carbon and nitrogen in vegetation and sediments during different water levels. Carbon (a) and nitrogen (c) densities of vegetation in different zones. Concentration of TOC (b) and TN (d) in sediments in different vegetation zones”
- Figure 5 - text in the figure is so small that it is unreadable.
Author’s response:
We have resized the text in the figure as suggest.
- Line 350 - do you have data about N2O reducers: nosZ clade I and II genes? Currently the abundance of nirS, nirK and hzsB genes does not provide enough information about the entire N cycle.
Author’s response:
In this study, we mainly focused on N2O emissions in the N cycle. Nitrite is converted to NO or N2O by nitrite reductase (NIR) in denitrification, the extensively used biomarkers for which are nirK (Cu-containing) and nirS (cytochrome cd 1) (Levy-Booth, D.J., Prescott, C.E., Grayston, S.J.: Microbial functional genes involved in nitrogen fixation, nitrification and denitrification in forest ecosystems, Soil Biol. Biochem., 75, 11–25, 10.1016/j.soilbio.2014.03.021, 2014.). And the N2O emission varied with the abundance of nirS and nirK genes (Zhang, L., Jiang, M.H., Ding, K.R., Zhou, S.G., Iron oxides affect denitrifying bacterial communities with the nirS and nirK genes and potential N2O emission rates from paddy soil, EUROPEAN JOURNAL OF SOIL BIOLOGY, 93, 103903, 10.1016/j.ejsobi.2019.103093, 2019). Thus, the abundance of nirS and nirK genes became the main object of discussion. Meanwhile, in order to further explore the N cycle in the anaerobic environment such as reservoirs and lakes, we analyzed the functional gene (hzsB gene) of anammox to compare with the denitrification.
- Throughout the text: sometimes N2O has subscript (N2O) and sometimes not.
Author’s response:
We double checked the subscripts and revised the incorrect subscripts.
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AC1: 'Reply on RC1', Wei Li, 05 Jan 2022
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RC2: 'Comment on bg-2021-208', Anonymous Referee #2, 10 Dec 2021
The manuscript submitted by Liu and colleagues investigates relationships between plant species, hydrology and N2O fluxes. In their work, they evaluate four (or five?) vegetation zones in a Chinese wetland and analysed C and N contents in the vegetation and sediments, N2O fluxes, microbial communities and selected genes involved in the N cycle during high and low water levels. They conclude that “the distribution of plants under hydrological conditions modified the stoichiometric ratio of sediments, resulting in the variations of N2O emission fluxes and microbial communities in the vegetation zones”.
While the topic is interesting and relevant for the journal, I have my serious doubts about the experimental design and the approach used. One of the main arguments of the manuscript is that the vegetation distribution is driven by hydrological changes; it is also argued that is the vegetation distribution the factor affecting the emission of N2O (Abstract, L3). Your first objective was indeed to examine the relationship between hydrology and species distribution. I was however not able to understand how your experimental set up was helpful to elucidate more about this matter, and which kind of data you use to support that this is indeed the case in your plots. You merely monitored the water level across the vegetation types and, actually, found that all vegetation types except reed were having exactly the same pattern (Figure 2a). And, even if you find a distinct pattern in the water dynamics across your vegetation zones, you won´t be able to conclude whether if it is the hydrology or the plant communities the ones driving the N2O fluxes.
Further, you focus on N2O emissions. We know that the temporal and spatial variability of N2O fluxes can be really high so I strongly suspect that measuring only twice a year over three (pseudo?) replicates is not enough to adequately catch the dynamics of the fluxes, especially with this highly contrasting environmental conditions. I also see that you measured on the soil surface (during low water level conditions) and on the water surface (high water level). This means your measurement conditions are totally different (different chamber setup, different diffusion coefficients, etc). I miss a clear explanation on how the different measurement conditions may have affected your results. For example, if I interpret Fig S2 correctly, I can see that the starting concentrations when setting the chamber (which should be the atmospheric N2O concentration) differ by a factor of three, which is hard for me to understand.
Further, I honestly think some results are misinterpreted, probably as a result of using flawed statistical methods. I found no mention to how the parameters measured were compared across vegetation zones, which in theory is your central point. For example, you highlight the role of the C:N ratio in the sediments and the N2O emissions (L190) but this is not supported by Figure 4b, probably because you ignored the effect of the different vegetation types in the approach. What I actually see in Figure 4b is how a change in the C:N ratio from 20-25 to 45-50 does not have any effect on the N2O fluxes. By the way, at least for the mud-flat, data from Fig 4a and 4b are different, so plese revise the consistence of your data.
I like to see that there is a part including microbial communities, but as it is now, this section is decoupled from the rest of the manuscript. How do these genes influence/are influenced by the rest of the parameters you are investigating? How do they fit into the big picture? As it is now, you provide a mere description of abundances (many times without any statistical analysis), but without a clear context. For example, why is annamox important here, if it doesn´t involve N2O turnover?
In summary, I strongly recommend to rethink the approach of the manuscript; you may merely compare different vegetation areas, considering that they are (or not) subjected to different hydrological regimes. Carefully think your hypotheses and reflect whether they can be tested with your experimental set up. Further, revise the methods, and provide a solid description of what was made in the statistical part. Then, you can explain the results which are relevant to these hypotheses, and discuss them accordingly.
Specific comments to the different sections (not exhaustive)
Abstract (L16-17): This is the closing sentence of your abstract, but it is actually coming out of the blue. I haven´t seen any reference to mitigation strategies at all in the rest of the manuscript. Please, be aware the abstract should reflect the most important aspects of the manuscript.
Objectives (L81-86): What are the “ecological factors” you refer to? As they are formulated now, the objectives are a mix between aims and hypotheses. For example, in 3) you are somehow assuming that C:N ratio of sediments will be the dominant factor for N2O fluxes. I suggest to clearly define your objectives and then, in order to achieve them, develop working hypotheses, that you will try to answer with your experimental design
Fig 1: The left-hand side part has no context at all. What are the photographs, why are there two sets? What is the lower panel?
I have a very practical question. According to Figure 2, the surface was covered by several meters of water when you sampled sediments and vegetation in June 2020. How did you sample? Did you differentiate between floating and submersed vegetation? When the water column is > 5 m, how can you differentiate between e.g. mud flat and nymphoides?
I miss the whole explanation on how the biomass was estimated. How is the 1 m x 1 m plot defined in the water? Was all the vegetation harvested and processed in the lab? There are huge changes in C and N densities (Figure 3). Are they coming only from changes in biomass, or did the concentrations in the plant change? Which sample did you take to determine C and N %? I can imagine this trait is not homogenous across the plant.
For the statistics, you mention one way ANOVA or t-test for comparind between high and low water levels, but I wonder how the vegetation factor was taken into account, and the interaction between water level and vegetation.
Results & Discussion:
L152: It seems that the main line of argumentation of the manuscript (and part of the title) originates from here “The correlation between water level variation and plant assimilation indicated that the long-term change of hydrological regime induced the stratification of vegetation”. As explained before, I don´t get it; in case this correlation is true, it would tell you, at most (ie, assuming causation), about plant productivity, but not about vegetation types. And, in any case, I see a point cloud (including one with no vegetation) and the reed, clearly out of the region and likely highly responsible for your fitting.
Figure 2: I had troubles understanding this figure. First, there is no information (not in the caption, neither in the methods) on how the data from panel a were obtained. Second, what are the photographs? Third, what is the x-axis of panels b and c?
In the discussion, I was confused quite often because I was not sure if the results of this study or of others were discussed. This is quite often not clear (e.g. L234-235), probably because of the past tense use. Please, revise this.
Some other comments:
L47, L83: You use the concept of “vegetation decline”. This refers to vegetation dynamics, so it intrinsically involves a temporal component, which you are not covering with your approach.
Concepts of assimilation/accumulation/decomposition (e.g. L150, 280) and sink/source (e.g. L9) are usually misused. Only “densities” (in g m-2) are investigated, you are not looking at changes in stocks, neither you are looking at all components of the C or N cycle. I strongly suggest to revise these parts accordingly.
L112-114: specify what is the “closed-chamber technique”. What is “a static chamber with an upper chamber”?
L123. Sediments were collected/sampled, I guess
L136: Which “traits of vegetation” do you mean?
L144: the maximum seems to be at about 6 meters, according to Fig 2. Please check your data.
L245: What does this sentence mean? “The discrepancies between the niches of plant species caused by hydrological conditions indicated the essence of stratification of vegetation zones”
L261: I think the mention to peat here is out of context here, unless you have evidence of peat being present in your study area
L292: You address interesting points here, but I don’t see a relation to your data. Do you have any information about these parameters? I am not sure either if you claim that these effets are having solely a physical effect ("affecting the diffusion of N2O from sediment to water"), or also biological effects on the production rates. As I mentioned before, this might be critical when comparing the two seasons you have conducted measurements.
Citation: https://doi.org/10.5194/bg-2021-208-RC2 -
AC2: 'Reply on RC2', Wei Li, 05 Jan 2022
Reply on RC2
Huazu Liu et al.
RC2
A:
The manuscript submitted by Liu and colleagues investigates relationships between plant species, hydrology and N2O fluxes. In their work, they evaluate four (or five?) vegetation zones in a Chinese wetland and analysed C and N contents in the vegetation and sediments, N2O fluxes, microbial communities and selected genes involved in the N cycle during high and low water levels. They conclude that the distribution of plants under hydrological conditions modified the stoichiometric ratio of sediments, resulting in the variations of N2O emission fluxes and microbial communities in the vegetation zones.
While the topic is interesting and relevant for the journal, I have my serious doubts about the experimental design and the approach used. One of the main arguments of the manuscript is that the vegetation distribution is driven by hydrological changes; it is also argued that is the vegetation distribution the factor affecting the emission of N2O (Abstract, L3). Your first objective was indeed to examine the relationship between hydrology and species distribution. I was however not able to understand how your experimental set up was helpful to elucidate more about this matter, and which kind of data you use to support that this is indeed the case in your plots. You merely monitored the water level across the vegetation types and, actually, found that all vegetation types except reed were having exactly the same pattern (Figure 2a). And, even if you find a distinct pattern in the water dynamics across your vegetation zones, you won’t be able to conclude whether if it is the hydrology or the plant communities the ones driving the N2O fluxes.
Author’s response:
We would like to thank anonymous referee#2 for the detailed reviews with relevant and constructive comments to improve the quality of the manuscript. The received recommendations were carefully considered and incorporated into the current version of the manuscript.
Hydrological conditions, such as flooding time, flooding depth, and flooding frequency, were the dominant factors driving vegetation distribution (Tan, Z. Q., Zhang, Q., Li, M. F., Li, Y. L., Xu, X. L., and Jiang, J. H.: A study of the relationship between wetland vegetation communities and water regimes using a combined remote sensing and hydraulic modeling approach, Hydrol. Res., 47, 278-292, 2016.; Toogood, S. E., Joyce, C. B., and Waite, S.: Response of floodplain grassland plant communities to altered water regimes, Plant Ecology, 197, 285-298, 2008.). Plant species had different amounts of carbon and nitrogen in their organisms (Elser, J. J., Fagan, W. F., Denno, R. F., Dobberfuhl, D. R., Folarin, A., Huberty, A., Interlandi, S., Kilham, S. S., McCauley, E., Schulz, K. L., Siemann, E. H., and Sterner, R. W.: Nutritional constraints in terrestrial and freshwater food webs, Nature, 408, 578-580, 2000.; Yu, Q., Chen, Q., Elser, J. J., He, N., Wu, H., Zhang, G., Wu, J., Bai, Y., and Han, X.: Linking stoichiometric homoeostasis with ecosystem structure, functioning and stability, Ecology Letters, 13, 1390-1399, 2010.). Therefore, we hypothesized that the biomass (carbon density and nitrogen density) of plants can be used as an index to distinguish plant species. And the change rate of water level (Figures 2a and 2b) can reflect the flooding time, frequency and depth. Thus, we explored the driving effect of hydrology on vegetation distribution by analyzing the relationship between the biomass (carbon density and nitrogen density) of plants and the change rate of water level. In fact, there were differences in the water level of all vegetation zones. Due to the large flooding depth, the difference in water level changes of these vegetation zones was not obvious in Figure 2a. In order to verify this, we scaled the image and showed part of the data during high water level (as shown in the figure below).
We thought that hydrology drove vegetation distribution, and the vegetation distribution effected the content of carbon and nitrogen in soil. The changes in the content of carbon and nitrogen (or stoichiometric proportion) varied the microbial processes and N2O emission. As anonymous referee#2 said, there were many factors affecting N2O emission, and we won’t be able to conclude whether if it is the hydrology or the plant communities the ones driving the N2O fluxes. However, our study attempted to reveal that the change of water level mediated by plant community drove the N2O emission in wetlands. Additionally, we also discussed the influence of hydrology, plant communities and other factors on N2O emission in the section of Discussion.
B:
Further, you focus on N2O emissions. We know that the temporal and spatial variability of N2O fluxes can be really high so I strongly suspect that measuring only twice a year over three (pseudo?) replicates is not enough to adequately catch the dynamics of the fluxes, especially with this highly contrasting environmental conditions. I also see that you measured on the soil surface (during low water level conditions) and on the water surface (high water level). This means your measurement conditions are totally different (different chamber setup, different diffusion coefficients, etc). I miss a clear explanation on how the different measurement conditions may have affected your results. For example, if I interpret Fig S2 correctly, I can see that the starting concentrations when setting the chamber (which should be the atmospheric N2O concentration) differ by a factor of three, which is hard for me to understand.
Author’s response:
We focused on the differences between nitrogen cycle during high and low water levels in ecosystem. Therefore, we monitored N2O emissions, vegetations and soil in the steady period after the change of water level. In addition, influenced by the Three Gorges Dam, the annual change of water level in the study area were very regular. As a result, the variations between years in the change of water level were very small. Although we set up three sampling sites at each vegetation zone in the study area, we ensured that the distances between the sampling sites made less interference between the sites. The approximate location of sampling sites was shown in the figure below, and the yellow box represents sampling sites.
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AC2: 'Reply on RC2', Wei Li, 05 Jan 2022