the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 17 Dec 2024
Reduced microbial respiration sensitivity to soil moisture following long-term N fertilization enhances soil C retention in a boreal Scots pine forest
Abstract. Nutrient availability effects microbial respiration kinetics and their sensitivities to environmental conditions, thus the soil organic C (SOC) stocks. We examined long-term nitrogen (N) addition effects on soil heterotrophic respiration (Rh), methane (CH4) oxidation, and nitrous oxide (N2O) emissions in an N-limited boreal Scots pine (Pinus sylvestris) forest. Measurements included long term 1960–2020 tree biomass monitoring, 2023 SOC, 2021–2023 monthly aboveground litterfall, 2021–2023 growing seasons biweekly CO₂, CH₄, and N₂O fluxes, and quarter-hourly soil temperature (T), and soil water content (SWC) in both control and N-fertilized plots. We assessed mean greenhouse gas (GHG) flux differences and Rh dependence on T and SWC using polynomial and parametric non-linear regression models.
Tree biomass, litterfall and SOC increased with long-term N fertilization. However, N fertilization significantly increased mean Rh, reduced CH₄ oxidation slightly, and modestly raised N₂O emissions. SOC-normalized Rh (Rh/SOC) did not significantly differ between treatments, yet relationships between Rh/SOC and T and SWC diverged with fertilization. In control plots, Rh/SOC peaked at 15 °C but increased monotonically with T in N-fertilized plots. Under N fertilization, Rh/SOC was weakly SWC-dependent, contrasting with a distinct humped SWC response in control plots, enhancing annual Rh/SOC. Annually, N-fertilized plots respired 11.2 % of SOC, compared to 12.6 % in controls, suggesting N fertilization promoted SOC retention. Consequently, N fertilization reduced net CO₂ emissions by 262.5 g CO₂ m⁻² year⁻¹, while combined effects on CH₄ and N₂O fluxes and the production energy of N fertilizer contributed a minor CO₂-equivalent increase of 15.8 g CO₂-eq m⁻² year⁻¹.
In conclusion, long-term N fertilization in boreal forests could mitigate climate warming by reducing soil GHG emissions, slowing Rh/SOC, and altering its responses to T and SWC, thereby enhancing SOC sequestration in addition to the increased tree biomass carbon sink.
- Preprint
(1751 KB) - Metadata XML
-
Supplement
(399 KB) - BibTeX
- EndNote
Status: open (until 18 Feb 2025)
-
RC1: 'Comment on egusphere-2024-3813', Anonymous Referee #1, 02 Jan 2025
reply
The manuscript raises important questions about the effects of N fertilization on soil GHG emissions and moisture dynamics. The authors have collected unique and valuable data. The paper is mainly very clear and well written. I have read the manuscript with great interest, but I am concerned about several issues in the methodology, results, and conclusions. The data presented do not adequately support the conclusions, and there are inconsistencies between the observations and the model outputs. Below, I outline the main issues with the study followed by few detailed comments.
Conflicting patterns in observations
In Supplementary Figure S2, the highest mean momentary soil moisture values appear to be in the N+ treatment during 2021–2022. However, in Figures 3F and 4B, the highest soil moisture values are in the CTR treatment. While these observations may not be strictly contradictory, they are at least unusual and require further explanation. Additionally, in 2022, the soil moisture appears lowest in N+ (S2), while in 2021 and 2023, it is approximately equal with CTR. Despite this, Figure 4B suggests there are notably more low soil moisture values (<0.2) in CTR than in N+. These discrepancies between the observations and figures need clarification.
It also seems very strange that the soil moisture has such a different dynamic in the different treatments in late July 2023, with N+ zigzagging (Fig S2). I recommend checking the dates for N+.
Conflicting results by the observations and the model
The authors themselves state based on the observations that 'Rh showed sensitivity to T and SWC, rising with warmer conditions and declining in dry periods, then recovering after rewetting events (Fig. S2).’
Then, in the results and discussion they state that ‘Soil moisture effects on Rh/SOC were only observed in control (CTR) plots’ and ‘In our N-fertilized plots, Rh/SOC was largely independent of soil moisture.’
These latter ones arise from the model that is fitted to the growing season (Apr-Oct) data and then applied for the whole year. These estimates are presented without any estimates of uncertainty, which undermines its reliability.
I see that the main issue behind this is that the models presented in the study do not perform well, especially during the dry year of 2021 (Figure 5). In the figure, for example, the observed soil moisture data for N+ in 2021 show a significant mid-season drop, which is as substantial, if not even larger than the drop in CTR. However, the model fails to capture this, and based on the model, the authors conclude that there is no soil moisture effect. In other words, the main conclusion of the whole paper appears to be unsupported by the observational data and raises questions about the validity of the model. The poor performance might arise from the model structure but also that there are significantly fewer data points for the N+ treatment under very wet conditions (>0.45 SWC, just two observations). Similarly, under dry conditions (<0.2) , there are notably more measurements for the CTR treatment than for the N+ treatment. This limited dataset could easily skew the soil moisture response curve.
Misleading conclusions about GHG emissions
The authors conclude: ‘Our results also suggest a net reduction in soil GHG emissions with long-term N fertilization.’
However, this is only supported by the poor model and not by the observational data, which show increased Rh (with no difference in Rh/SOC), reduced CH4 sink and increased N2O emissions in the fertilised treatment compared to the control. These observations indicate that the net impact of N fertilization on soil GHG emissions may be neutral or even negative. To see the relative importantce of CH4 and N2O, it would be useful for the reader to see all fluxes as CO2 equivalents.
Issues with MethodsThe methods section contains critical gaps that limit the reproducibility and reliability of the study:
- The manuscript does not describe the equations or models used for tree biomass in the methods but refer to Lehtonen et al. in the Fig 2 caption. The methods section should be improved here.
- The manuscript does not include any estimates of uncertainty for their main result that is the decreased (modelled) Rh/SOC after fertilization.
- Fluxes were measured over only 3 minutes using a large (21 L) chamber. Considering the low flux rates of CH4 and N2O, it is doubtful whether this short measurement duration is sufficient for reliable estimates. It might be though but makes me worry if the equipment used is sensitive enough to detect such low fluxes. Of course, it is not the volume that is important here, but the area, but this is not given. Based on the chamber description in the manuscript, no one could repeat it.
Other
The authors state in the introduction: ‘Moreover, full accounting of GHG emissions should include emissions associated with N fertilizer production.’ However, they do not include these emissions in their own analysis and conclusions.
Although CH4 and N2O fluxes are a central part of one of the hypotheses, those are not well motivated and the discussion does not address these at all.
The title and main findings revolve around soil moisture dependency, yet this was not one of the original hypotheses or a focus in the introduction. This shift in focus feels post-hoc, as if it were added after analyzing the data and models, rather than being a central research question from the start. For that reason, the story does not seem to hold together.
Detailed comments, by line number
15: Carbon (C) is usually written out in full the first time it is mentioned, as was done for nitrogen (N) even though we all know it.
30-32: The conclusion seems overly broad, given that just one upland forest was studied. Your site was originally a very poor Scots pine forest, but you generalize your conclusions to all forest types. What about peatland forests? Do you know, even for your own site, what, for example, the N2O fluxes were just after the fertilisation events or in earlier phases of the rotation?
73-74: These seem like very nice references, but I’m not sure that they are both conducted in the actual boreal zone and represent the entire boreal zone?
L81: The introduction lacks any reasoning/motivation for such a hypothesis.
L89: Even if you follow the silvicultural practices in principle, there can be a lot of variation in practice. So for the sake of repeatability I would add some details on the harvests, like how much basal area was reduced or something like that.
111: Please be more specific and use dates instead of growing seasons.
112: I don't understand. Did you take measurements from two individual points within each of three or six plots, which you refer to as a group? If you had two points, is that a group or a pair? How close were the groups to each other? Are they independent? How do you take into account in the statistical analyses that the two points are close and probably not independent? Please clarify the description of the overall setup including what was the distance between the points and groups and treatments.
114: Why do you use both Rh and Rh for heterotrophic respiration here and elsewhere? It gives a slightly unfinished impression.
116-119: This paragraph seems to be the earlier or at least less complete version of the following one, please combine these sections to avoid redundancy.
116&122: Don't you need to write down the manufacturer's details anymore?
131 Depth should be given
132 end date is missing
142 You have not yet introduced CTR and N+
Citation: https://doi.org/10.5194/egusphere-2024-3813-RC1
Viewed
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 102 | 20 | 6 | 128 | 17 | 2 | 0 |
- HTML: 102
- PDF: 20
- XML: 6
- Total: 128
- Supplement: 17
- BibTeX: 2
- EndNote: 0
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1