Modelling the habitat preference of two key <i>Sphagnum</i> species in a poor fen as controlled by capitulum water content

Gong, Jinnan; Roulet, Nigel; Frolking, Steve; Peltola, Heli; Laine, Anna M.; Kokkonen, Nicola; Tuittila, Eeva-Stiina

doi:https://doi.org/10.5194/bg-17-5693-2020

Articles | Volume 17, issue 22

https://doi.org/10.5194/bg-17-5693-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/bg-17-5693-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 17, issue 22

Research article

|

23 Nov 2020

Research article |

| 23 Nov 2020

Modelling the habitat preference of two key Sphagnum species in a poor fen as controlled by capitulum water content

Jinnan Gong, Nigel Roulet, Steve Frolking, Heli Peltola, Anna M. Laine, Nicola Kokkonen, and Eeva-Stiina Tuittila

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Final revised paper (published on 23 Nov 2020)
Supplement to the final revised paper
Preprint (discussion started on 18 Nov 2019)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'Review Gong et al Sphagnum model', Anonymous Referee #1, 08 Dec 2019
- AC1: 'Responce to Refree 1', Jinnan Gong, 30 Mar 2020
RC2: 'Comments on Manuscript', Anonymous Referee #3, 06 Feb 2020
- AC2: 'Responce to Refree 3', Jinnan Gong, 30 Mar 2020

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

ED: Reconsider after major revisions (06 Apr 2020) by Michael Bahn

AR by Jinnan Gong on behalf of the Authors (15 Apr 2020) Author's response

ED: Referee Nomination & Report Request started (02 May 2020) by Michael Bahn

RR by Anonymous Referee #1 (22 May 2020)

Suggestions for revision or reasons for rejection

1. Does the paper address relevant scientific questions within the scope of BG? YES
2. Does the paper present novel concepts, ideas, tools, or data? YES
3. Are substantial conclusions reached? YES
4. Are the scientific methods and assumptions valid and clearly outlined? YES
5. Are the results sufficient to support the interpretations and conclusions? ALMOST; it would be more interesting if the conclusion would critically evaluate the limitations of the current model version rather than emphasising that the model was a success.
6. Is the description of experiments and calculations sufficiently complete and precise to allow their reproduction by fellow scientists (traceability of results)? YES
7. Do the authors give proper credit to related work and clearly indicate their own new/original contribution? YES
8. Does the title clearly reflect the contents of the paper? YES
9. Does the abstract provide a concise and complete summary? YES
10. Is the overall presentation well structured and clear? YES
11. Is the language fluent and precise? YES
12. Are mathematical formulae, symbols, abbreviations, and units correctly defined and used? YES
13. Should any parts of the paper (text, formulae, figures, tables) be clarified, reduced, combined, or eliminated? YES
14. Are the number and quality of references appropriate? YES
15. Is the amount and quality of supplementary material appropriate? YES

Dear authors,

Thank you for addressing the concerns raised by me and the other reviewer. Several points have now been clarified in the text (please do check the grammar, which is not flawless in the added sections). There are a few remarks that you have responded to only in your reply to us but not in the main text (e.g. my previous points 3b (horizontal water exchange), point C and D of reviewer 3 (autogenic processes leading to hummock formation and differences in moss hydraulic conductivity)). I think those are missed chances of improving the outlook section for your model. In general, I would appreciate a more explicit acknowledgment of the limitations of your model. After all, even if you managed to recreate some ´realistic´ patterns, several potentially important processes are still missing from the model, so you cannot be sure whether you produced these patterns for the right reasons. It is absolutely fine to start with a simple model (even if your main purpose is to `illustrate the reality´ L188 in your response) and to ´leave perfection for later´ (L70 in your response), but thereby it is helpful to line out the path to perfection (well, at least to a model in which the importance of additional processes has been tested) for the readers.

Also, I think there are two points (6 and 7) that I think you may have misunderstood, so that I will try to formulate them better here. I pasted my old remark and your reply in here to keep track of the context.

My previous point 6 and your reply:

As an important difference between your and previous models lies in the coupling to environmental fluctuations and stochasticity (L97-98), it would make sense to present a test of the importance of these processes to the model output. Would a simpler model provide similarly good results?

R: We believe that the main purpose of modelling is to illustrate the reality and
188 serve as a tool for systematic assessment of the processes. Simple community
189 models without individual-based processes implicitly weigh on generality and
190 forgive outliers. However, environmental fluctuation and extremes are becoming
191 more frequent and intensive with climate change, and this is likely to give
192 advantage to an otherwise unlikely change in peatland community. To help with
193 this situation, our modelling is able to populate outputs along a probability
194 distribution and allows assessing individuals with different trait combinations as a
195 part of the probabilities. As these models are fundamentally different in focuses
196 and underlying mechanisms, simply comparing the goodness of results seems
197 pointless.
198

My new comment: In this case I was not suggesting that you compare your model to previous, unrelated, models, but that you do tests with your own model, simplifying some processes and seeing if that degrades the results. E.g. instead of using realistic parameter distributions just use a random number generator to e.g. modify the length growth of individual shoots (grid cells). Instead of using realistic environmental fluctuations just use the smoothed mean monthly climate. These are just some examples, I am sure you can think of better ones.

Continuation of my previous comment: I would also be interested in seeing the effects of the water retention and photosynthetic water-response parameters separately. Especially since the parameters for the latter may suffer from some measurement artefacts.

R: This is a very appreciated comment. Our future goal is also to make the picture
204 clearer and understanding the factorial effects is a very important aspect. At the 205 moment, our data and techniques are insufficient to separate the different effects. 206 Therefore, model testing based on the parameters quantified by the “mixed”
207 information could be less informative, unless we have had improved measurement
208 data.
209
210 In addition, S. fallax and S. magellanicum are largely different in both water
211 retention and photosynthetic response to water stress. Further testing on species 212 either with similar water retention, or with similar photosynthetic response would 213 be more informative to this question.

My new comment: In my mind, a model is the perfect opportunity to pretend that your species are not different in both but just in one or the other aspect and to test the individual effects of these parameters. You would not have real data to validate the result, but that is not the point here. The point is to understand what these parameters do and what would happen with hypothetical species with these parameter combinations. For me, this type of test is what would constitute a `systematic assessment of the processes´ (L189 in your response).

My new comment regarding my previous point 7: I did not mean to say that module III is unimportant, but it is not evaluated in this paper (just used to create input data for the presented model modules), so it seems too much (therefore unbalanced) to spend several pages on explaining the details of module III. I would recommend moving this information to the supplement.

Additionally: Table 4, the sensitivity analysis: how do these 10% changes relate to the actual uncertainty in the parameter values?

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RR by Anonymous Referee #3 (28 May 2020)

Suggestions for revision or reasons for rejection

This is my second review of this manuscript for Biogeosciences and I am pleased that the authors incorporated many of the suggestions made by me and the other reviewer. In brief, the strength of the study emerges from their combining an individual-based, two species competition model of Sphagnum community interactions with underlying functional models of water and carbon dynamics and linking it to a hydrology simulation model. Historically, most modeling efforts have focused on understanding and modeling the mechanisms of competition and function in Sphagnum. One of the highlights of this study is the connection to an existing hydrology and surface exchange model that was used to generate local environmental conditions that served as forcing variables for the simulation. Overall, I believe that this manuscript represents a valuable step in developing predictive models of peatland function.

I still have a couple of issues that I think the authors ought to address and then provide a list of minor edits.

A. There are still many places where “water retention” and “water content” are used synonymously. In my mind, retention is when existing water is not released via evaporation or drainage. I don’t think this is the meaning the authors intend. Most of the times, I think the authors mean capitulum “water content”. This incorporates fluxes in and out, but also the capacity for storage. I think the language needs to be clarified and it begins with its usage in the title. Here is a list of places that I found places where this should be clarified: L2, L28, L35, L75, and L522; there may be others.
B. I remain surprised that the authors still did not show sample light response curves in the Appendix, which were the source of many of their photosynthetic parameters; both reviewers questioned their measurements, especially with regards to the long time for samples to desiccate within the chamber. In the appendix, data for the photosynthetic—water content relationships are shown (Fig B2). I think light response curves should be added. They may be very useful if this study is used for comparative purposes in the future.

Minor edits
C. L15: what do you mean by “dynamic community structure”? There should be a better way to state this.
D. L25. The description of what PMS does should be more clear. Perhaps it would be better worded by placing competition up front. “PMS employs a, stochastic, individual-based approach to simulating competition based on species’ differences in functional traits.”
E. L35: replace “retention” with “relations”
F. L53: unclear what “dynamic community structure” relates to. “lack mechanisms that underlie and cause dynamic community processes”?
G. L55: delete “in order”
H. L55: delete after “and the research community”
I. L73: replace “the peers” with “its peers”.
J. L75: and water storage
K. L87: I think the ability to carry out such a quantitative study is not new and don’t believe this has been a great hindrance.
L. L93: occur to occurs
M. L98: rely to relies
N. L114: replace “locates” to “is located”
O. L118: to “10% of the surface is occupied….”
P. L128: to “flow with…”
Q. L143: “race for space” to competition
R. L414: change PCS to PMS
S. L491: lawnss to lawns
T. L535: delete the
U. L573 and 577: replace dynamical with dynamic

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ED: Publish subject to minor revisions (review by editor) (04 Jun 2020) by Michael Bahn

AR by Eeva-Stiina Tuittila on behalf of the Authors (26 Jun 2020) Author's response Manuscript

ED: Publish as is (10 Jul 2020) by Michael Bahn

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Short summary

In this study, which combined a field and lab experiment with modelling, we developed a process-based model for simulating dynamics within peatland moss communities. The model is useful because Sphagnum mosses are key engineers in peatlands; their response to changes in climate via altered hydrology controls the feedback of peatland biogeochemistry to climate. Our work showed that moss capitulum traits related to water retention are the mechanism controlling moss layer dynamics in peatlands.