the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 28 Jun 2023
A global function of climatic aridity accounts for soil moisture stress on carbon assimilation
Abstract. The coupling between carbon uptake and water loss through stomata implies that gross primary production (GPP) can be limited by soil water availability through reduced leaf area and/or reduced stomatal conductance. Vegetation and land-surface models typically assume that GPP is highest under well-watered conditions and apply a stress function to reduce GPP with declining soil moisture below a critical threshold, which may be universal or prescribed by vegetation type. It is unclear how well current schemes represent the water conservation strategies of plants in different climates. Here eddy-covariance flux data are used to investigate empirically how soil moisture influences the light-use efficiency (LUE) of GPP. Well-watered GPP is estimated using the P model, a first-principles LUE model driven by atmospheric data and remotely sensed green vegetation cover. Breakpoint regression is used to relate the daily value of the ratio β(θ) (flux-derived GPP/modelled well-watered GPP) to soil moisture, which is estimated using a generic water-balance model. Maximum LUE, even during wetter periods, is shown to decline with increasing climatic aridity index (AI). The critical soil-moisture threshold also declines with AI. Moreover, for any AI, there is a value of soil moisture at which β(θ) is maximized, and this value declines with increasing AI. Thus, ecosystems adapted to seasonally dry conditions use water more conservatively (relative to well-watered ecosystems) when soil moisture is high, but maintain higher GPP when soil moisture is low. An empirical non-linear function of AI expressing these relationships is derived by non-linear regression, and used to generate a β(θ) function that provides a multiplier for well-watered GPP as simulated by the P model. Substantially improved GPP simulation is shown during both unstressed and water-stressed conditions, compared to the reference model version that ignores soil-moisture stress, and to an earlier formulation in which maximum LUE was not reduced. This scheme may provide a step towards better-founded representations of carbon-water cycle coupling in vegetation and land-surface models.
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RC1: 'Comment on egusphere-2023-1261', Anonymous Referee #1, 24 Jul 2023
Simulations of carbon flux is of high importance but also very difficult. In this study, the authors applied the LUE model to simulate GPP and made modifications on the response of GPP to soil water. This should be interesting to broad readers within Earth science community. But the current depiction in this manuscript did not convince me as their manuscript seems too easy and incomplete. I would suggest a thorough major revision before I can be considered for the target journal.
Major points:
- There is no measure of statistical significance,and the description of the results lacks clarity. Currently, there are statistical numbers (PBIAS, Correlation coefficient), which are very useful.
- In the methods part, the description of the P model is incomplete. In addition, the authos should add the calculation of GPP in the model and describe the design of expriment and model setting in detail.
- The organization of the manuscript and presentation of the results need some improvement, current manuscript seems too easy, and the authos can add another part of results about regional comparison between the original model, the revised model and remote sensing GPP products.
- In the abstract, the authors didn’t fully explain the performances of the revised model, and the abstract looks unat
- Introduction: Line 71-88: Poorly literature citation, relevant literature on critical drought thresholds that affect GPP should be added. (Li et al., 2023. Global variations in critical drought thresholds that impact vegetation)
- Figure1: Although the authors use breakpoint regression analysis, I hardly find the relationship between scatters and fitting lines.
- Line 265-278: The description in this paragraph makes it difficult to see the improvement of the revised model compared to the original model, and the presentation must be revised. Currently, there are statistical numbers(PBIAS, Correlation coefficient), which are very useful. In addition, the average percentage reduction in RMSE in arid, semi-arid, and humid regions should be calculated separately for further clarification.
- I admit the revised model reduced the overestimation of GPP compared to the original model, however, the revised model can’t capture the peaks of GPP, and at some sites (US-SRG, US-Var), the revised model overestimated GPP in the non-growing season. The authors should be further analyzedthese results.
- The conclusion part shouldbe added to the manuscript.
Citation: https://doi.org/10.5194/egusphere-2023-1261-RC1 -
AC1: 'Reply on RC1', Giulia Mengoli, 17 Oct 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-1261/egusphere-2023-1261-AC1-supplement.pdf
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RC2: 'Comment on egusphere-2023-1261', Anonymous Referee #2, 01 Aug 2023
This development and technical paper concerna the development of a new model to simulate GPP which does not directly use soil moisture as limit to carbon assimilation, but rather uses aridity to account for soil moisture stress on carbon assimilation. It seeks to improve the performance of the ‘P model’. Overall, it has shown significant improvements from existing schemes. But the content of the paper needs to be expanded and improved.
Major comments:
- Following GMD paper conventions, a development and technical paper should be clear on which model/code it is improving. I assume in this case it is the “P model”? That should be emphasized in the title. It also lacks details on the “technical aspects of running models and the reproducibility of results”, or “a significant amount of evaluation against standard benchmarks, observations, and/or other model output”, see https://www.geoscientific-model-development.net/about/manuscript_types.html#item2. Discussing how the code can be used is a feature distinct to GMD papers, which is not provided in this preprint.
- Code availability: it is not entirely clear whether the provided code is an improved version of the “P model” or a standalone module that can be attached to the “P model”.
- An impression from reading this manuscript is that it reads like an report, rather than an academic paper. It only discusses work that are immediately related to the approach taken, but hasn't provided a survey of the full suite of other work that has contributed to the field.
- The sensitivity of the model parameters should be investigated, especially since the new model basically relies on a single scaling parameter beta. Also, a potential issue with using aridity index is that it is an long-term average, which may not capture changing aridity under changing climate.
Specific comments:
- L71: while you have given some empirical evidence of photosynthesis levels under drought stress, it should be properly introduced in the introduction section.
- L103: I think an expanded introduction of the P model is necessary somewhere in the paper.
- L120: so what is the version number of this new model?
- L360: this concluding paragraph seems quite short and incomplete.
- Figure 1: perhaps a hexbin plot can show the density of points better than a scatter plot
- Figure 5,6: much of them are presenting the same information and can be combined.
Citation: https://doi.org/10.5194/egusphere-2023-1261-RC2 -
AC2: 'Reply on RC2', Giulia Mengoli, 17 Oct 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-1261/egusphere-2023-1261-AC2-supplement.pdf
Status: closed
-
RC1: 'Comment on egusphere-2023-1261', Anonymous Referee #1, 24 Jul 2023
Simulations of carbon flux is of high importance but also very difficult. In this study, the authors applied the LUE model to simulate GPP and made modifications on the response of GPP to soil water. This should be interesting to broad readers within Earth science community. But the current depiction in this manuscript did not convince me as their manuscript seems too easy and incomplete. I would suggest a thorough major revision before I can be considered for the target journal.
Major points:
- There is no measure of statistical significance,and the description of the results lacks clarity. Currently, there are statistical numbers (PBIAS, Correlation coefficient), which are very useful.
- In the methods part, the description of the P model is incomplete. In addition, the authos should add the calculation of GPP in the model and describe the design of expriment and model setting in detail.
- The organization of the manuscript and presentation of the results need some improvement, current manuscript seems too easy, and the authos can add another part of results about regional comparison between the original model, the revised model and remote sensing GPP products.
- In the abstract, the authors didn’t fully explain the performances of the revised model, and the abstract looks unat
- Introduction: Line 71-88: Poorly literature citation, relevant literature on critical drought thresholds that affect GPP should be added. (Li et al., 2023. Global variations in critical drought thresholds that impact vegetation)
- Figure1: Although the authors use breakpoint regression analysis, I hardly find the relationship between scatters and fitting lines.
- Line 265-278: The description in this paragraph makes it difficult to see the improvement of the revised model compared to the original model, and the presentation must be revised. Currently, there are statistical numbers(PBIAS, Correlation coefficient), which are very useful. In addition, the average percentage reduction in RMSE in arid, semi-arid, and humid regions should be calculated separately for further clarification.
- I admit the revised model reduced the overestimation of GPP compared to the original model, however, the revised model can’t capture the peaks of GPP, and at some sites (US-SRG, US-Var), the revised model overestimated GPP in the non-growing season. The authors should be further analyzedthese results.
- The conclusion part shouldbe added to the manuscript.
Citation: https://doi.org/10.5194/egusphere-2023-1261-RC1 -
AC1: 'Reply on RC1', Giulia Mengoli, 17 Oct 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-1261/egusphere-2023-1261-AC1-supplement.pdf
-
RC2: 'Comment on egusphere-2023-1261', Anonymous Referee #2, 01 Aug 2023
This development and technical paper concerna the development of a new model to simulate GPP which does not directly use soil moisture as limit to carbon assimilation, but rather uses aridity to account for soil moisture stress on carbon assimilation. It seeks to improve the performance of the ‘P model’. Overall, it has shown significant improvements from existing schemes. But the content of the paper needs to be expanded and improved.
Major comments:
- Following GMD paper conventions, a development and technical paper should be clear on which model/code it is improving. I assume in this case it is the “P model”? That should be emphasized in the title. It also lacks details on the “technical aspects of running models and the reproducibility of results”, or “a significant amount of evaluation against standard benchmarks, observations, and/or other model output”, see https://www.geoscientific-model-development.net/about/manuscript_types.html#item2. Discussing how the code can be used is a feature distinct to GMD papers, which is not provided in this preprint.
- Code availability: it is not entirely clear whether the provided code is an improved version of the “P model” or a standalone module that can be attached to the “P model”.
- An impression from reading this manuscript is that it reads like an report, rather than an academic paper. It only discusses work that are immediately related to the approach taken, but hasn't provided a survey of the full suite of other work that has contributed to the field.
- The sensitivity of the model parameters should be investigated, especially since the new model basically relies on a single scaling parameter beta. Also, a potential issue with using aridity index is that it is an long-term average, which may not capture changing aridity under changing climate.
Specific comments:
- L71: while you have given some empirical evidence of photosynthesis levels under drought stress, it should be properly introduced in the introduction section.
- L103: I think an expanded introduction of the P model is necessary somewhere in the paper.
- L120: so what is the version number of this new model?
- L360: this concluding paragraph seems quite short and incomplete.
- Figure 1: perhaps a hexbin plot can show the density of points better than a scatter plot
- Figure 5,6: much of them are presenting the same information and can be combined.
Citation: https://doi.org/10.5194/egusphere-2023-1261-RC2 -
AC2: 'Reply on RC2', Giulia Mengoli, 17 Oct 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-1261/egusphere-2023-1261-AC2-supplement.pdf
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