the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 02 Mar 2023
Quantification of hydraulic trait control on plant hydrodynamics and risk of hydraulic failure within a demographic structured vegetation model in a tropical forest (FATES-HYDRO V1.0)
Abstract. Vegetation plays a key role in the global carbon cycle and thus is an important component within Earth system models (ESMs) that project future climate. Many ESMs are adopting methods to trace the size and succession-stage-structure of plants within demographic models. These models make it feasible to conduct more realistic simulation of processes that control vegetation dynamics. Separately, increasing understanding of the ecophysiological processes governing plant water use, and the need to understand ecosystem responses to drought in particular, has led to the adoption of physical plant hydrodynamic schemes within ESMs. In this study, we report on a new hydrodynamics (HYDRO) model incorporated in the Functionally Assembled Terrestrial Ecosystem simulator (FATES). The size and canopy structured representation within FATES is able to simulate how plant size and hydraulic traits affect vegetation dynamics and carbon/water fluxes. To better understand this new model system and its functionality in tropical forest systems in particular, we conducted a global parameter sensitivity analysis at Barro Colorado Island, Panama. We assembled observations of plant hydraulic traits for stomata, leaves, stems, and roots, and determined the best-fit statistical distribution for each trait. Our model analysis showed that the taper component determining hydraulic conductivity tapering from trunk to branch, the water potential leading to 50 % loss (P50) of stomatal conductance, the maximum hydraulic conductivity for the stem, and the fraction of total hydraulic resistance in the above ground section are the top 5 traits determining the simulated water potential and loss of conductivity for different plant organs. For the risk of hydraulic failure and potential tree mortality, we found that ensemble members with high risk of mortality generally have a higher taper exponent and a higher xylem conductivity, less negative P50 for stomata conductance, and more negative P50 for stem and transporting roots. We expect that our results will provide guidance on future modeling studies using plant hydrodynamic models to predict the forest responses to droughts, and future field campaigns that aim to better parameterize the plant hydrodynamic model.
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Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(2688 KB) - Metadata XML
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Supplement
(344 KB) - BibTeX
- EndNote
- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2023-278', Anonymous Referee #1, 02 Apr 2023
This study tested the sensitivity of the parameters of a plant hydraulics model coupled in a demographic vegetation model (FATES-Hydro). This is an important step for model development and also helpful for understanding model behavior. The simulation experiments and analysis are solid, and the paper is generally well written. However, some places are not clear to me. I expect the authors can improve the description of the design of simulation experiments and the analysis of the results.
Major questions/suggestions:
1. For the key parameters in Table 1, is it possible to list the key equations of this model that are related to these parameters? An analytical analysis to these equations would help to understand the sensitivity of these parameters.
2. If I understand it correctly, the plant traits data of different species in the tropical forest of BCI are used to define the parameter ranges and distribution, from which the ensembles are sampled. This means a mean PFT is defined in each parameter combination. However, there are trade-offs in these parameters. How is this considered in the design of ensembles?
3. The authors set the vegetation static (no growth, no reproduction and mortality). Please list the details of vegetation. Such as how many cohorts? what are the sizes of these cohorts?, etc.
If there was only one cohort in these tests, what the size is? Does the parameter sensitivity change with tree size? For example, the most important parameter according to this test, taper factor, may relate to the tree sizes.
4. In the discussion, some claims and opinions can be evidenced by recent research. Please add those references.
Details comments:
- Lines 36~38: about the statistical distribution of plant traits, please also clarify that they are used in parameter sampling (if they are).
- Line 101: “we describe the implementation of a hydrodynamic scheme within FATES,”: to me, this paper only tested parameter sensitivity, did not “describe the implementation of a hydrodynamic scheme”. Am I wrong? If yest, please provide a detailed description of the hydro model.
- Line 102: “assess the importance of different hydraulic traits”. I think it is about the sensitivity. if it is “importance”, then an index should be defined.
- Lines 115~116: “FATES simulates growth by integrating photosynthesis across different leaf layers for each cohort.” From somewhere else, I learned that FATES does not have multiple leaf layers in a crown. Otherwise PPA principles cannot be applied. Please clarify.
- Line 151: “we used the static stand structure mode of FATES”: Please provide a detailed description of the static cohorts and tree sizes.
- Lines 166~167: “here we focused on hydrodynamic behaviors for trees of diameter more than 60 cm.”. Detailed cohorts and tree sizes please.
- Line 169: “We identified 36 parameters for the FATES-HYDRO model (Table 1).”. Please also provide the relevant equations.
- Lines 181~194: I am not quite clear about this section. do authors use the multiple trees’ traits to define a “mean state” tree?
- Lines 195~208, Section 2.3. I think an “important index” should be defined here. Or, make it clear that the most sensitive parameter is most important. (Though I don’t think it is always true.)
- Line 230 “during August compared to February”. Please also note “wet’ and “dry” season.
- Line 244: “1000 ensembles” should be defined in the method section. In the total 36 parameters, how many samples for each of them and how they combined?
- Lines 261~263: I guess p_taper is related to tree size. A test with different tree sizes can show if I am wrong.
Also p_taper comes with strong assumptions on plant development. Please cite some papers about that. There are some research on the changes in xylem structure with tree age.
- Lines 270~271. Citation?
- Line 278 “interaction between root, fungi and bacteria.”: citations are required here. I know there are some good review papers published in this area.
Citation: https://doi.org/10.5194/egusphere-2023-278-RC1 - AC1: 'Reply on RC1', Chonggang Xu, 26 May 2023
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RC2: 'Comment on egusphere-2023-278', Anonymous Referee #2, 05 Apr 2023
The work by Xu et al. implemented a more trait-based model into FATES, and explored how the variation in traits may impact model simulations hence to test the models' sensitivity to those hydraulic traits. The manuscript is well written and well delivered. However, there are some major concerns over the manuscript given its positioning.
1. It is not clear whether the manuscript is a model paper or validation paper. If the former, there were basically no details about the formulations; if the latter, the manuscript still lacks a fair amount of details for readers to understand how the traits are related to the modeling of vegetations processes. It seems that Lambert et al. (2022) GMD doi:10.5194/gmd-15-8809-2022 has more details on FATES-Hydro, but is not referenced in this study. I can see that the two studies have the different aims, but this study should contain adequate details as Lambert et al. (2022).
2. Following comment 1, these should be explictly described in the manuscript:
- How canopy RT is done
- How canopy energy balance is done
- How the key parameters like taper component, Kmax, P50, Gs50, and etc are related to stomatal control
- How soil water balance is done, it is impacted by root distribution?
- What is the hydraulic architecture, number of roots, branches, and leaves, is there a trunk?
- How is sap area computed
Without these details, it is impossible to tell what is going on.
Minor comments:
Line 2: (FATES-HYDRO V1.0) or using FATE-HYDRO v1.0?
Line 39: P50 for xylem or stomata? Need to be consistent, say P50x, P50gs
Line 41: top 5 traits? I can only found 4 from the text...
Line 86: such water limitation functions (based on soil moisture? to be more explicit)
Lines 138-139: a function of the tissue water content? Why water content? Shouldn't it be xylem pressure?
Line 203: Sensitivyt or Sensitivity?
Line 245: branches are most vulnerable... How about leaves? Does this branch mean stem and leaf?
Line 280: How is p50_gs used? Does it mean gs is aways a function of Pleaf? Regardless of variations in PAR, CO2, VPD, and Psoil?
Line 311: epsil_node, you need to be consistent with ths symbols (you provided two for the same parameter in Table 1)
Fig. 1 is too crowded, consider use fewer curves
Fig. 2 Xylem cavitation can fully recover?
Citation: https://doi.org/10.5194/egusphere-2023-278-RC2 - AC2: 'Reply on RC2', Chonggang Xu, 26 May 2023
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-278', Anonymous Referee #1, 02 Apr 2023
This study tested the sensitivity of the parameters of a plant hydraulics model coupled in a demographic vegetation model (FATES-Hydro). This is an important step for model development and also helpful for understanding model behavior. The simulation experiments and analysis are solid, and the paper is generally well written. However, some places are not clear to me. I expect the authors can improve the description of the design of simulation experiments and the analysis of the results.
Major questions/suggestions:
1. For the key parameters in Table 1, is it possible to list the key equations of this model that are related to these parameters? An analytical analysis to these equations would help to understand the sensitivity of these parameters.
2. If I understand it correctly, the plant traits data of different species in the tropical forest of BCI are used to define the parameter ranges and distribution, from which the ensembles are sampled. This means a mean PFT is defined in each parameter combination. However, there are trade-offs in these parameters. How is this considered in the design of ensembles?
3. The authors set the vegetation static (no growth, no reproduction and mortality). Please list the details of vegetation. Such as how many cohorts? what are the sizes of these cohorts?, etc.
If there was only one cohort in these tests, what the size is? Does the parameter sensitivity change with tree size? For example, the most important parameter according to this test, taper factor, may relate to the tree sizes.
4. In the discussion, some claims and opinions can be evidenced by recent research. Please add those references.
Details comments:
- Lines 36~38: about the statistical distribution of plant traits, please also clarify that they are used in parameter sampling (if they are).
- Line 101: “we describe the implementation of a hydrodynamic scheme within FATES,”: to me, this paper only tested parameter sensitivity, did not “describe the implementation of a hydrodynamic scheme”. Am I wrong? If yest, please provide a detailed description of the hydro model.
- Line 102: “assess the importance of different hydraulic traits”. I think it is about the sensitivity. if it is “importance”, then an index should be defined.
- Lines 115~116: “FATES simulates growth by integrating photosynthesis across different leaf layers for each cohort.” From somewhere else, I learned that FATES does not have multiple leaf layers in a crown. Otherwise PPA principles cannot be applied. Please clarify.
- Line 151: “we used the static stand structure mode of FATES”: Please provide a detailed description of the static cohorts and tree sizes.
- Lines 166~167: “here we focused on hydrodynamic behaviors for trees of diameter more than 60 cm.”. Detailed cohorts and tree sizes please.
- Line 169: “We identified 36 parameters for the FATES-HYDRO model (Table 1).”. Please also provide the relevant equations.
- Lines 181~194: I am not quite clear about this section. do authors use the multiple trees’ traits to define a “mean state” tree?
- Lines 195~208, Section 2.3. I think an “important index” should be defined here. Or, make it clear that the most sensitive parameter is most important. (Though I don’t think it is always true.)
- Line 230 “during August compared to February”. Please also note “wet’ and “dry” season.
- Line 244: “1000 ensembles” should be defined in the method section. In the total 36 parameters, how many samples for each of them and how they combined?
- Lines 261~263: I guess p_taper is related to tree size. A test with different tree sizes can show if I am wrong.
Also p_taper comes with strong assumptions on plant development. Please cite some papers about that. There are some research on the changes in xylem structure with tree age.
- Lines 270~271. Citation?
- Line 278 “interaction between root, fungi and bacteria.”: citations are required here. I know there are some good review papers published in this area.
Citation: https://doi.org/10.5194/egusphere-2023-278-RC1 - AC1: 'Reply on RC1', Chonggang Xu, 26 May 2023
-
RC2: 'Comment on egusphere-2023-278', Anonymous Referee #2, 05 Apr 2023
The work by Xu et al. implemented a more trait-based model into FATES, and explored how the variation in traits may impact model simulations hence to test the models' sensitivity to those hydraulic traits. The manuscript is well written and well delivered. However, there are some major concerns over the manuscript given its positioning.
1. It is not clear whether the manuscript is a model paper or validation paper. If the former, there were basically no details about the formulations; if the latter, the manuscript still lacks a fair amount of details for readers to understand how the traits are related to the modeling of vegetations processes. It seems that Lambert et al. (2022) GMD doi:10.5194/gmd-15-8809-2022 has more details on FATES-Hydro, but is not referenced in this study. I can see that the two studies have the different aims, but this study should contain adequate details as Lambert et al. (2022).
2. Following comment 1, these should be explictly described in the manuscript:
- How canopy RT is done
- How canopy energy balance is done
- How the key parameters like taper component, Kmax, P50, Gs50, and etc are related to stomatal control
- How soil water balance is done, it is impacted by root distribution?
- What is the hydraulic architecture, number of roots, branches, and leaves, is there a trunk?
- How is sap area computed
Without these details, it is impossible to tell what is going on.
Minor comments:
Line 2: (FATES-HYDRO V1.0) or using FATE-HYDRO v1.0?
Line 39: P50 for xylem or stomata? Need to be consistent, say P50x, P50gs
Line 41: top 5 traits? I can only found 4 from the text...
Line 86: such water limitation functions (based on soil moisture? to be more explicit)
Lines 138-139: a function of the tissue water content? Why water content? Shouldn't it be xylem pressure?
Line 203: Sensitivyt or Sensitivity?
Line 245: branches are most vulnerable... How about leaves? Does this branch mean stem and leaf?
Line 280: How is p50_gs used? Does it mean gs is aways a function of Pleaf? Regardless of variations in PAR, CO2, VPD, and Psoil?
Line 311: epsil_node, you need to be consistent with ths symbols (you provided two for the same parameter in Table 1)
Fig. 1 is too crowded, consider use fewer curves
Fig. 2 Xylem cavitation can fully recover?
Citation: https://doi.org/10.5194/egusphere-2023-278-RC2 - AC2: 'Reply on RC2', Chonggang Xu, 26 May 2023
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Chonggang Xu
Bradley Christoffersen
Zachary Robbins
Ryan Knox
Rosie A. Fisher
Rutuja Chitra-Tarak
Martijn Slot
Kurt Solander
Lara Kueppers
Charles Koven
Nate McDowell
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(2688 KB) - Metadata XML
-
Supplement
(344 KB) - BibTeX
- EndNote
- Final revised paper