Carbon and nitrogen allocation in montane vegetation: Understanding the impact of environmental change on ecosystem processes

Dasgupta, Bibhasvata; Sanyal, Prasanta

doi:https://doi.org/10.5194/egusphere-2025-3687

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https://doi.org/10.5194/egusphere-2025-3687

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11 Aug 2025

| 11 Aug 2025

Status: this preprint is open for discussion and under review for Biogeosciences (BG).

Carbon and nitrogen allocation in montane vegetation: Understanding the impact of environmental change on ecosystem processes

Bibhasvata Dasgupta and Prasanta Sanyal

Abstract. Mountain forests, comprising nearly 20 % of the world’s forest cover, are among the most ecologically fragile ecosystems due to their strong topographic and climate sensitivity. Understanding how climate influences these ecosystems requires examining the allocation of key nutrients like carbon (C) and nitrogen (N). We investigated foliar C and N allocation in the Himalayan vegetation by sampling 141 leaf samples from 14 species across three climatically different transects spanning 1,900–5,200 m. The mean total nitrogen (TN) was 6.6 ± 4.5 %, with Juniperus and Abies exhibiting the highest TN (8.3 %) and grasses the lowest (1.6 %). Foliar δ¹⁵N ranged from +2.1 ‰ in Juniperus to +8.9 ‰ in grasses, varying inversely with TN. Total organic carbon (TOC) averaged 37.5 ± 6.2 %, peaking in Juniperus (40.6 %) and lowest in Abies (34.2 %). Foliar δ¹³C in C₃ species clustered near –27 ‰, while C₄ grasses reached –13.4 ‰. In the Central Himalaya, Juniperus maintained high TN and TOC at altitude, whereas in the West, Rhododendron had elevated TN and TOC relative to other genera. Statistical analyses showed that warmer growing seasons strongly reduced TN in Abies and Rhododendron, and wetter conditions increased δ¹³C in Abies and TN in Pinus. Clustering of δ¹³C and TN effectively distinguished mycorrhizal types, with arbuscular‐associated grasses displaying higher δ¹³C and lower TN than ectomycorrhizal and ericoid‐associated taxa. Geostatistical modelling produced a dual‐isotope map revealing “arid hotspots” (high δ¹⁵N and δ¹³C, low TN) in dry western valleys and “humid cold spots” (low δ¹⁵N and δ¹³C, high TN and TOC) in moist eastern slopes. These findings demonstrate that steep precipitation and temperature gradients drive N much more than C in Himalayan plants, underscore the tight coupling of C and N, and identify areas most sensitive to climate‐induced shifts in nutrient allocation.

Received: 29 Jul 2025 – Discussion started: 11 Aug 2025

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Bibhasvata Dasgupta and Prasanta Sanyal

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'Comment on egusphere-2025-3687', Anonymous Referee #1, 25 Sep 2025 reply
Review of the manuscript “Carbon and nitrogen allocation in mountain vegetation: Understanding the impact of environmental change on ecosystem processes“ by Dasgupta and Sanyal submitted to Biogeosciences
September 2025
In this manuscript, total C and N concentrations and C and N stable isotope ratios of leaves from 144 plant individuals across three climatically different elevational transects in the Himalayas are reported and discussed with respect to potential plant responses to changing climate. Moreover, the data was extrapolated to produce countrywide maps of C and N isotope ratios for Nepal with a geostatistical approach.
While I think that the presented results are novel and could finally be a valuable contribution to our knowledge, I have two major concerns regarding the current presentation and discussion of the results.
The authors sampled 14 plant species which are not all listed at the species level in the supplemental information and several names are cut and cannot be fully read. In the main text, they grouped these 14 plant species into the five genera to which they belong and only discussed results at the genus level. This is problematic because there can be a considerable variation in genetic properties among species belonging to the same genus resulting in varying C and N concentrations and isotope ratios. It would be better to differentiate the presentation of the results and the discussion to the species level.

To produce Nepal-wide stable isotope ratio maps of C and N, the authors use multiple regression models of the observed 144 results on growing season precipitation and temperature, soil microbial N concentrations and soil moisture contents (for d¹⁵N) or elevation and C₃/C₄ plant ratio (for d¹³C). In my view, 144 data points are not enough for geostatistical modelling, particularly because several of these samples likely originate from (almost) the same site. It is unclear from where the data of the explanatory variables come and particularly, at what time the microbial N concentrations and soil water contents, which vary strongly in time, were measured. Are these data really available in a representative form for all grid areas shown in Fig. 3g? Moreover, the model validation is based on the data shown in Figs. 3a and b where I see two dislocated data clouds without internal structure that a linearly linked which appears like a regression through two points. To me, this looks as if the model does not fit the data well. Finally, I am missing an external validation of the model by comparing predicted with measured independent data.

Beyond these two major concerns calling for a complete overhaul of the manuscript, I offer a number of line-by-line comments below.
12: I would skip “most ecologically fragile ecosystems”, because this applies to many more near-natural ecosystems. It is sufficient to point at the strong topographic and climate sensitivity.

15: …the mean total N concentration…

16: “%” is not an SI unit. Change to g/kg.

16: Genus (and species) names are usually shown in italics.

17: The foliar d¹⁵N values…

28-29: This is contradictory. Why should anything drive N much more than C if both are tightly coupled?

33: “sequestration” in the vegetation, the soils, the ecosystems? Specify.

33: “Nitrogen is likewise essential” sounds strange. Nitrogen is frequently the most growth-limiting nutrient. It would be good to know if this is also case in your study area. Moreover, C is not a nutrient.

40: I don’t understand “while respiration drives root allocation”? Plants respire all the time.

47: It is unclear what you mean by “nutrient-poor” soils. Soils of mountain ecosystems frequently show high nutrient stocks in partly thick organic layers. Probably, you refer to nutrient availability? Please add a reference.

49: I don’t think that it is possible to “disrupt” C-N linkages, which would be the end of life.

53: What do you mean by “enhance or suppress TN”? Please try to use more precise wording.

65: There are no specific objectives and/or testable hypotheses. It would increase the value of your manuscript and also improve the structure if you included objectives/hypotheses.

75: Are all sampled plants native to the study region? Please add a list of the species names to the supplemental information.

80: “in the … laboratory”

87: And which standards were used for C?

88: Where the calibration lines really (nonlinear) “curves”? The later listed equations are linear functions. Perhaps, “calibration functions”?

5: There can be a considerable differentiation in N demands and d¹³C and d¹⁵N values of leaves/needles of different species of the same genus, which needs to be discussed. Furthermore, you obviously didn’t sample Pinus trees in the Eastern Himalayas, which should be mentioned. What was the reason for this?

103: Explain abbreviations, when you first use them.

117-119: Why did you use different correlation approaches (Kendall vs. Pearson)?

131-135 belong to the Methods section.

138: Does the “I” in “Supplementary I” stand for Information? I would spell this word out.

140-142: This sentence is unclear. I don’t understand the part concerning C and doubt that the part concerning N is true. The d¹⁵N value of plant tissue is the result of complex processes, not only N₂ fixation, which results in a d¹⁵N value of 0‰. That TN concentrations reflect the overall N content is trivial. Moreover, I would avoid using the ill-defined “content” (sometimes meaning stock and sometimes concentrations) and replace it by “concentration” throughout the manuscript.

8: I suggest to use different symbol types instead or in addition to the different colors. Moreover, you just infer the mycorrhizal association from a statistical approach but did not determine them. How sure can you be that your inference is true?

145: “modelling of”

170: What is the number of data to which you fit the regression model? 144? Are all of these data really statistically independent of each other? Don’t the four and for C even five explanatory variables plus constants result in an overfit? What do you mean with “accuracy”? Is this just the R² value of your fit? This would rather be the explained variance of your data. You should try to predict the isotope ratios of independently measured values at other sites with your model and then report the quality of the prediction.

174: What does “highest data density” mean? Just the highest number of plant samples of your three transects or of the explanatory variables?

199-206: I would omit this paragraph which includes textbook stuff and an announcement.

209-218: This is pure repetition of results, no discussion although it would be interesting to read your interpretation of these results.

215: You don’t present analyses on the species level.

233-234: There seems to be a general misunderstanding. The C concentration cannot vary freely, because it is the main component of the organic matter that builds up the plant tissue. The C concentration can only decrease (to a small extent) if the concentrations of mineral components including e.g., nutrients, Si or not needed metals increase. For grasses the Si uptake plays a particular role.

234: I don’t think that you can infer the carbon allocation to specific plant metabolites just from an increasing C concentration. The C/N ratio reflects the nutrient-use efficiency, which is generally higher in conifers than deciduous trees. With increasing elevation, trees are adapted to decreasing nutrient availability and become more efficient (see e.g., Vitousek 1982, Am. Naturalist 119, 553-572).

238: A low C concentration of 34% can in my view only be explained by a high Si concentration in grasses. Thus, the increasing contribution of grasses with increasing elevation seems to explain the change in C concentrations.

241: The reason for the decreasing N availability with increasing elevation is mainly increasing waterlogging of the soils which hampers organic matter degradation. This is indeed partly related with climate, but also with drainage conditions and there is a negative feedback of increasingly less decomposable litter.

244-245: Why should dry zones lose more N than wet zones in spite of less N leaching and less denitrification in dry than wet soils? This explanation is not convincing. There are many other drivers of the N isotope ratios, including e.g., deposition from the atmosphere, possible supply from sedimentary parent rocks containing fossil organic matter, or degree of N₂ fixation from the atmosphere which need to be considered here. Moreover, there can be a strong species-specific variation in d¹⁵N values among different plant species – even at the same site -, which is genetically determined. If the species at your transects are different in spite of belonging to the same genus, your interpretation gets complicated. Therefore, it is very important to mention the species and to consider possibly different species of the same genus in your discussion. It would seem plausible to me that the species are different among the three transects given the climatic differences.

255: Why should nitrification be higher in cold and wet soils at higher elevation? I would even expect the reverse. Nitrification usually only occurs if more ammonium is released than is taken up by the microorganisms and plants, which is highly unlikely at higher elevation because of the slower organic matter mineralization and usually stronger N limitation of the vegetation.

257-258: This is an interesting aspect but to me it is not clear what you mean, to which transect this applies, and which consequences for the d¹⁵N value you infer. I could imagine that the monsoonal rains wash N out of the ecosystems shifting the d¹⁵N to higher values – but again likely in a more pronounced way at the more humid transects, while you observe the reverse distribution of d¹⁵N values.

261: As mentioned above, increased rainfall can also decrease soil organic matter decomposition if it results in waterlogging.

266-267: This is highly speculative. Please add evidence.

270: Where does this number and all the other response sizes to climate change in the later discussion come from? Is this an output of your model? But see my criticism of the model.

274: I think that the abbreviation PNL is not necessary.

278: Are drought-tolerant grasses not N-limited? The role of grasses for C and N concentrations and stable isotope ratios is not sufficiently explored in your work.

280: By which process will the stored C be released? Erosion? But then it possibly ends up in a long-term sedimentary C storage, e.g., as lake sediment and does not really present a C loss.

282: Consider deposition earlier, particularly with respect to the interpretation of the N isotope ratios.

284: CO₂ fertilization is only possible if enough nutrients, particularly N and P are available.

294: Add a reference.

294-296: This sentence belongs to the introduction.

297: Plants can take up nutrients with all their surfaces, e.g., also directly from deposition.

298: “other” nutrients, because N is also a nutrient

301: It would improve the structure of your discussion if you started each paragraph by mentioning a result with reference to a table or figure and then directly discussed this result.

308-309: Again, the role of deposition for the N isotope ratios needs to be discussed earlier.

309-310: N-limited plants take up all mineral N that they can get. A preference for ammonium or nitrate is not plausible.

310-311: This does not seem likely to me. Usually, deposited ammonium results from the volatilization of ammonia e.g., from animal production, and is therefore N-isotopically light. The same is true for nitrate, which frequently results from NO_x emission.

313: As far as I know, there is hardly any N isotope fractionation by plants during N uptake. What do you mean by “N assimilation”?

316: “show” instead of “measure”

319: This statement seems trivial and has already been mentioned earlier.

321-323: Plants do not only compete with each other for nutrients but particularly with microorganisms. If there is a high N availability, competition decreases and N limitation is reduced (or even replaced by another nutrient such as P). I don’t understand what you mean by “the allocation of N determines the N concentrations”. This seems trivial.

331-337 belong to the introduction.

344-345: Lower d¹⁵N values than what? I am not aware that plants can take up organic matter or microbial biomass for its nutrient supply without previous mineralization.

348: Higher C/N than what? Why should the C/N ratio be higher if the mycorrhiza provides more N than is available to non-mycorrhizal plants?

349: From what do you infer this preference?

350-351: But mycorrhiza also respond to climate change.

361: To me, the only explanation for low C concentrations (and simultaneously low N concentrations) is the contribution of grasses containing Si.

365-366: Already said.

372: Does this mean that there is less monsoonal rainfall at mid- than high-elevation sites? Can you support this with data? But again, rainfall is not the only driver of the complex N cycle.

376-379: Again, the concentration of C cannot vary independently of the mineral concentration (i.e., nutrients and Si).

380: I doubt that these gradients are unique to the Himalayas. They are common for all high-elevation mountains.

391: Again, why do wet conditions lower d¹⁵N values? Wet conditions would rather result in more N losses and thus increase d¹⁵N values.

395-396: This is a repetition. You should shorten your discussion and render your text more concise.

397-407: I don’t understand where these change estimates come from and suspect that they are highly speculative. Do you just vary temperature and precipitation in your regression function according to the climate change scenarios? This would be a rather simplified approach. Perhaps, you indicate that you roughly estimate these values assuming that only temperature and precipitation change, assuming that your regression equations can be generalized and ignoring the error of your models.

408-409: You cannot infer “drastic” changes just from a correlation. The size of the change depends on the slope of the regression line (or the first deviation of a non-linear relationship).

422: Low microbial N stocks usually indicate N scarcity and result in closed N cycling and thus low d¹⁵N values, i.e., the reverse of your interpretation.

436-438: I cannot follow.

441: Again, increased N availability increases losses driving N to higher not lower d¹⁵N values and higher soil moisture will increase the opening times of the stomata and thus decrease the d¹³C value.

446: You cannot infer C assimilation from C concentrations. Instead, you need to consider the biomass production.

454-455: I don’t think that your dual isotope map reflects C and N allocation. It perhaps reflects soil moisture conditions and N availability although this would still be a simplification of the complex C and N cycles. But see my second major concern.

457-459: Your findings concerning the d¹⁵N values contradict current knowledge and for d¹³C values is well known.

460: What do you mean by “decades of pointwise foliar chemistry”?

464-467: This is well known.

468-469: It could be promising to evaluate the monsoonal influence on the C and N concentrations and isotope ratios more in depth by specifically showing relationships between monsoon-influenced climate characteristics and your measured leaf properties, which I currently don’t see in your paper.

471-472: Shifting phenology and productivity is expected for all mountain areas. To me, it did not become clear, why increasing dryness should result in C losses.

473: You did not sufficiently address the complexity of the N cycle. As already said, you need to consider e.g., N deposition, N₂ fixation, and possible rock-derived N supply. Your explanations of the d¹⁵N values are not plausible.

483: The explanation of the variations in C concentrations need to be rethought, because C concentrations cannot vary independently of mineral concentrations.

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Citation: https://doi.org/10.5194/egusphere-2025-3687-RC1

Bibhasvata Dasgupta and Prasanta Sanyal

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Bibhasvata Dasgupta and Prasanta Sanyal

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Short summary

Mountain forests cover a fifth of Earth’s woodlands but are fragile because of topography and climate sensitivity. To understand how temperature and rainfall affect plant nutrition, we studied 141 plant samples from 14 species along 3 Himalayan elevation gradients. We measured leaf carbon and nitrogen amounts and their natural markers tied to water use and soil. We found nitrogen varies more with heat and moisture than carbon, highlighting areas most at risk from shifting climate.


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