Dear Authors,

I have been asked to review the paper but unfortunately, I don't have time to perform an in-depth peer-review now. I also feel this is not so usefull as the paper is already in minor revision. I still took the time to read the paper on demand on the editor. While I found the overall idea of great interest of coupling forest dynamic models with plant hydraulic, I have a few concerns :

REPLY: We thank the reviewer for nonetheless taking the time to read our manuscript and appreciate the feedback given by the reviewer.

1. Part of the traits database used to parametrize plant hydraulic model is wrong, in particular for cavitation resistance (P50) more than half of the species have wrong data. This is probably because author used data that have not been filtered for different artefacts that affect P50  measurements (Cochard et al 2013). I encourage the author to have a look to this database which is dedicated for plant hydraulic models and acknowledge uncertainties in parametrizaiton : https://zenodo.org/records/854700.

   

   This database is from this papers : Martin-StPaul, N., Delzon, S., & Cochard, H. (2017). Plant resistance to drought depends on timely stomatal closure. Ecology Letters, 20(11), 1437–1447. https://doi.org/10.1111/ele.12851. This paper explains how the data should be filter to avoid artifacts

 

2. I know it is hardly acceptable to rerun simulations at this stage. So I would at least encourage the author to be cautious and add some "warnings" in their discussion in regard to the parametrization of plant hydraulic models from traits database to avoid dubious data to spread in the other model parametrization. There are some discussion in this point in this paper :

   

Ruffault, J., Pimont, F., Cochard, H., Dupuy, J.-L., & Martin-StPaul, N. (2022). SurEau-Ecos v2.0: A trait-based plant hydraulics model for simulations of plant water status and drought-induced mortality at the ecosystem level. Geoscientific Model Development, 15(14), 5593–5626. https://doi.org/10.5194/gmd-15-5593-2022

REPLY: We thank the reviewer for bringing this to our attention. In the revised manuscript we will clarify that using data directly from trait databases to parameterize mechanistic plant hydraulic models is not without pitfalls. Both the methods section and the discussion section will be revised to mention the need to consider the effect of different measurement methods on the data used to parameterize models. Additionally, we will rerun a subset of our simulations with the data from the database suggested by the reviewer and reproduce Figure 4 to highlight the potential impact such discrepancies can have on model output. 

   

3. Regarding the sensitivity analysis, I think the author should compare their results to recent modelling papers in the field of plant hydraulic :

   

   Ruffault, J., Pimont, F., Cochard, H., Dupuy, J.-L., & Martin-StPaul, N. (2022). SurEau-Ecos v2.0: A trait-based plant hydraulics model for simulations of plant water status and drought-induced mortality at the ecosystem level. Geoscientific Model Development, 15(14), 5593–5626. https://doi.org/10.5194/gmd-15-5593-2022

   

   Cochard, H., Pimont, F., Ruffault, J., & Martin-StPaul, N. (2021). SurEau: A mechanistic model of plant water relations under extreme drought. Annals of Forest Science, 78(2), 55. https://doi.org/10.1007/s13595-021-01067-y

REPLY: We thank the reviewer for bringing these studies to our attention. In the revised manuscript Section 4.1 “Relevance of the hydraulic parameters” which discusses the results of the sensitivity analysis, and at present compares our results to available results from experiments and observations, will include a discussion of the results from the papers recommended by the reviewer. This will set our results in the context of results from other modeling studies. 

   

 4. There is no real validation that the new model allows to predict drought stress/drought vulnerability of multiple species. This is not really a problem because the paper intends to present a new model but it should be stated and called for evaluation.

REPLY: We thank the reviewer for bringing up this important point. Unfortunately, the dataset we use for validation contains primarily sites with two or more species present making it impossible to attribute the measured evapotranspiration to any single species. However, for a subset of four species we have identified sites which contain only a single species. The revised manuscript will include a plot showing the evapotranspiration response to VPD for those four species. This will allow for a comparison between the simulated response curves from LPJ-GUESS-HYD and observed response curves from the eddy-covariance flux sites.

   

  5. Also note there are some typos/strange things in Figure 5 :

      - the unit for ETR is strange (mm/m) in general mm is used.

      - the unit for GPP is wrong : I have never seen GPP in mm/m.

   REPLY: Thank you for bringing these typos to our attention. They will be fixed in the revised manuscript.

Please see the reply to RC2

For clarity, we have formatted our reply as follows:



The reviewer's comments are in plain text and numbered. Our replies are formatted in italics and in instances where we highlight specific additions to the text that will be made in the revised manuscript the new (or altered) text is highlighted in bold.



This paper focuses on improving plant hydraulic architecture within the LPJ-GUESS model, validated using flux tower data during drought periods. Overall, the content aligns well with the scope of the journal, as the integration of more complicated plant hydraulic modules with better performance is increasingly common in these state-of-the-art land surface models. However, I have several concerns regarding the clarity, methodology, and results in this study.

Major comments:

1. The description of the model needs to be more organized, with a clear distinction between the old and new model versions. There are typo errors, especially in the equations, and some symbols are not explained immediately after their introduction. These issues reduce the clarity of this section.

REPLY: We thank the reviewer for pointing out a number of typos and have also addressed instances where symbols were not explained in close proximity to the equations they appear in as best as possible without interrupting the text flow (see the replies to the specific minor comments below for concrete changes to the text). 

A clearly organized manuscript is important, particularly, in a manuscript such as this where two separate model versions are described. As such we agree with the reviewer that a well organized model description benefits the manuscript. That being said, we are unsure what the reviewer’s concern with the organization of our model description is. Section 2.1 “Description of the standard version of LPJ-GUESS” deals only with the old version of the model while all newly implemented processes are described separately in section 2.2 “Description of the hydraulic architecture as implemented in LPJ-GUESS-HYD”. Additionally, we provide a flowchart (Fig. 1) clearly highlighting which model processes are newly implemented in LPJ-GUESS-HYD and how they integrate with existing processes from the standard version of LPJ-GUESS. We are happy to implement more specific changes if the reviewer can clearly outline which sections yet lack the desired structure.

2. The reasons behind the less improved performance of GPP should be discussed in depth. For instance, the biochemical processes related to Vcmax​ could be explored as a contributing factor.

REPLY: We thank the reviewer for this suggestion. While the focus of this manuscript is on plant hydraulic architecture and not photosynthesis we will expand upon brief discussion in section 4.2 to further include the possible effects of water limitation on photosynthesis. Additionally, we will expand the explanation of the link between plant hydraulic processes and photosynthesis in the methods section preceding Eq. 4 as described in comment 22 below. To further clarify the link between plant hydraulic processes and photosynthesis we will add an additional equation to section 2.2.3 which explains how the canopy conductance for plant hydraulic processes determines whether trees in LPJ-GUESS-HYD experience water limitation. In brief, when the canopy conductance constrained by plant hydraulic processes (Eq. 23) is less than the non-stressed canopy conductance (estimated from the non-stressed photosynthesis; see the equation in response to comment 22) trees are assumed to be limited by water supply and consequently photosynthesis is limited by canopy conductance. This is in contrast to the formulation of water limitation in standard LPJ-GUESS (see section 2.1.3 and our response to comment 23). 

3. The overestimation and underestimation of ET for certain data points during drought and non-drought years require further analysis. The author should investigate and explain these discrepancies more thoroughly.

REPLY: In conjunction with the additional species-specific plots (see comment 11) that will be included in the revised manuscript, we will add a more thorough discussion of the over- or underestimation of some data points in Figure 5 and tie these to specific species and their respective behavior on the isohydric spectrum. In general, the pattern we see is that species which are parameterized to be towards the edge of either end of the spectrum tend to over- or underestimate the observed fluxes. Given the results of our sensitivity analysis that ΔѰmax, which controls the degree of stomatal regulation by limiting the difference between leaf and soil water potential in the model, contributes significantly to variance in the model output the discussion will highlight that better constraining this parameter should be a priority. 

4. Validation of species-specific ET rates is crucial for evaluating model performance effectively. While field measurements may be limited, some partial validation is necessary to support the results.

REPLY: Unfortunately, most of the eddy-covariance flux sites which we obtained evapotranspiration data from have multiple species present which means the observed evapotranspiration response to VPD cannot be attributed to a single species. However, we agree with the reviewer that a plot validating the species-specific evapotranspiration response would benefit the study. Consequently, the revised manuscript will include a plot showing the evapotranspiration response to VPD for four species for which eddy-covariance flux sites exist which only have a single species present.

5. Figure 2, Figure 3: The use of annual-scale evaluation may be too coarse and could dilute the significance of certain patterns. The author should consider whether a finer temporal scale would better capture the model's performance

REPLY: In principle, we agree with the reviewer that a finer temporal scale could offer additional insights to the sensitivity of the model to variations in the hydraulic parameters. In practice, we believe that the the tradeoff between complexity and additional knowledge gained from conducting the sensitivity analysis at a finer temporal resolution is only marginal and would detract from the main objective of this study which is to a) describe the model implementation of LPJ-GUESS-HYD for European tree species, b) determine the importance of the newly added parameters for long-term carbon and water cycle dynamics, and c) highlight the improved representation of species-specific water-use compared to the old model. 

However, we do believe that future studies aiming to further improve LPJ-GUESS-HYD could make use of sensitivity analyses at a finer temporal scale to identify avenues for development in specific, individual processes related to the plant hydraulics implementation. Consequently, in the revised manuscript we will highlight this potential for future research in the discussion section 4.3 “Limitations of the modeling approach and ways forward”.

6. λ and Ψ50 - Both parameters represent aspects of isohydricity. The author should clarify whether their variance decomposition results could be affected by potential redundancy or collinearity.

REPLY: We thank the reviewer for bringing this to our attention. To test the influence of individual parameters on the model outputs we sampled the parameters independently from one another to construct our 6000 parameter sets. Therefore, there is no collinearity between individual parameters in parameter sets used for the sensitivity analysis. 

Regarding the potential redundancy between parameters associated with the same processes in LPJ-GUESS-HYD the use of total-, first-, and second-order Sobol’ indices helps to account for such interactions. For example, the first-order indices account for the influence of a single parameter on the model output even if it interacts with another parameter in the model. Please see our reply to comment 8 for more details.  

 

7. Table 1 - Clarify whether the parameter ranges in Table 1 correspond to all 12 species used in the study.

REPLY: The parameter ranges in Table 1 do not correspond to the 12 species used in this study. Rather they represent the potential range of these parameters across all tree species available in the datasets described in Table 1. We use these extensive ranges in the sensitivity analysis to explore the model’s reaction to as wide a parameter space as is plausible. We mention this in the methods in the sentence starting on line 276. For additional clarity we will also expand the description in the caption of Table 1 with this information. 

8. second-order interactions - Specify what the second-order interactions account for in the model and their ecological relevance.

REPLY: To ensure the relevance of second-order interactions is more thoroughly explained in the revised manuscript we will discuss the ecological relevance of second-order interactions and provide some examples in the method section. The part of the method section from line 287 to line 295 will be reworked to incorporate the aforementioned explanation and examples.

“First order indices measure the contribution of a single parameter to the variance in the model output excluding any interactions with other parameters. Similarly, second

order indices measure the contribution of the interaction between two parameters to the variation in model output. Lastly, total order indices measure the contribution of a single parameter, including all its interactions with other parameters, to variation in the model output (Saltelli, 2008). In practical terms, these interactions refer to instances where separate parameters jointly affect a given model process or a given model output. For example, leaf water potential regulation in LPJ-GUESS-HYD (Eq. 11) is driven in part by both λ and ΔΨmax. In this case, the first order index for each parameter quantifies that parameter's individual contribution to Equation 11. The second-order index then quantifies the joint effect of the two parameters on Equation 11. This concept also extends beyond single, self-contained processes. That is, since, for example, both the water potential gradient between leaf and soil (governed by λ and ΔΨmax, Eq. 8, Eq. 10, Eq. 11) and the total plant resistance (governed by kr,max, ks,max, and kl,max, Eq. 16-18)” affect canopy conductance the joint effect of any combination of these five parameters on canopy conductance can be quantified using either the second-order or total-order indices. The sensitivity indices range between 0 (least influential)...”

9. Section 3.2- Is there any validation for the results presented in this section? If not, the author should address this gap. Check the typo please. ‘-day’ should not be the superscript.

REPLY: As pointed out in our replies to comments 4 and 10, most of the eddy-covariance flux sites which we obtained evapotranspiration data from have multiple species present which means the observed evapotranspiration response to VPD cannot be attributed to a single species. However, we agree with the reviewer that a plot validating the species-specific evapotranspiration response would benefit the study. Consequently, the revised manuscript will include a plot showing the evapotranspiration response to VPD for four species for which eddy-covariance flux sites exist which only have a single species present.

10. For the validation - the author only presents Figure 5, which appears to aggregate data from all flux towers and tree species. To provide a more detailed evaluation, the author should clarify how the model performs across different tree species. Are there notable differences in model accuracy between species, and if so, what might explain these variations? Including species-specific validation results would strengthen the analysis.

REPLY: As mentioned in the reply to comment 4 only a limited number of the eddy-covariance flux sites have only single species present. Usually, two or more species grow at each site making it impossible to attribute the measured evapotranspiration to any single species. However, for four species used in our study eddy-covariance flux sites exist which are monospecific. To include a partial validation as suggested by the reviewer in comment 4, the revised manuscript will include species-specific versions of Figure 4 and Figure 5 (see also the response to comment 4).

  Minor comments:

11. Figure 1: The light blue color in the flowchart appears unnecessary and could be removed.

REPLY: Done. In the revised manuscript they will be the same dark blue color as the other additions in LPJ-GUESS-HYD.

12. The labeling should be consistent. For example, both "standard mortality mechanisms" and "mortality" are used, which could confuse readers.

REPLY: Done. “Mortality” will be changed to “Total Mortality” indicating that the cavitation-induced mortality in LPJ-GUESS-HYD does not replace the standard mortality mechanism but rather both contribute to overall mortality in the model

13. L33: check please

REPLY: We assume the reviewer is referring to the phrase “two distinct” erroneously being used twice. This will be fixed in the revised manuscript.

14. L37: check please

REPLY: We are unsure what the reviewer is referring to here but would be glad to have another look upon further clarification.

15. L75: does the author mean that, in the old model version, ET and canopy conductance are not coupled?

REPLY: We thank the reviewer for pointing this out. What we meant is that LPJ-GUESS-HYD more tightly couples the model representation of evapotranspiration to canopy conductance. In the standard (i.e. “old”) model version canopy conductance is only based on plant hydraulic processes during periods of water limitation, that is, when the calculated evapotranspiration would be greater than the water available in the soil to be transpired. In such cases, canopy conductance is downregulated in order to ensure that evapotranspiration does not outweigh water availability. During non-stressed periods canopy conductance for evapotranspiration is simply based on the non water-stressed canopy conductance estimated by the photosynthesis routine as outlined in Sitch et al. (2003). This will be reflected in the revised manuscript:

“and explicitly coupling the model representation of evapotranspiration to canopy conductance governed by plant hydraulic processes (Papastefanou

et al., 2024) in contrast to the standard version of LPJ-GUESS which only does so during periods of limited water availability.”

16. L121-125: check the unit please

REPLY: Thank you for pointing out the oversight. The correct units will be used in the revised manuscript.

    

18. L128: explain the source of awl?

 

REPLY: The sentence "The dimensionless ratio of awc_l to the actual available liquid water (aw_l; mm) is defined as the water content (wcont ∈ [0, 1])" will be changed to "The dimensionless ratio of awc_l to the actual available liquid water in the soil (aw_l ; mm) is defined as the water content (wcont ∈ [0, 1])"

19. L126: which processes?

REPLY: We assume the reviewer is referring to the soil texture properties used as input to the model. In the revised manuscript the relevant section will be changed to give more information on these properties:

“... physical soil texture properties (e.g. clay-, sand-, and, silt-fraction, soil carbon content, bulk density, etc.) provided as input to the model …”

20. L140-141: unclear

    

REPLY: In the revised manuscript we will clarify that the drought tolerance level (from 0 to 1) for establishment refers to the water content (as a fraction of available water holding capacity) necessary for a given species to establish in the model:

"Each species is assigned a drought tolerance level from 0 (extremely drought tolerant) to 1 (extremely drought intolerant) based on the water content as a fraction of the available water holding capacity required for that species to establish."

22. L143: Confirm if photosynthesis is computed using the FVCB model. How is stomatal conductance expressed? Are any empirical stomatal models used?

REPLY: We initially chose not to include detailed information on the photosynthesis routine since the advancements in LPJ-GUESS-HYD do not alter the photosynthesis routine itself. However, for the clarity of the manuscript we are happy to include more information on the photosynthesis routine in the revised manuscript. Starting at line 144, the following text will be added:

“Photosynthesis is modeled based on the Collatz simplification of the Farquhar model (Collatz et al. 1991) described in detail in Haxeltine and Prentice (1996) and Sitch et al., (2003). When water supply is ample, the optimal canopy conductance for photosynthesis is calculated as:

g_c= g_min+((1.6 * A_dt)/ (c_a * (1-λ_max)))

Where gmin is the species-specific minimum canopy conductance (a parameter), Adt is the daytime net assimilation, and 𝜆max is a species-specific parameter. Conversely, when water supply is limited, photosynthesis is calculated using actual rather than maximum potential gc and χCO2 where gc is calculated…”

23. Eq. 4 Provide justification or references for using this equation.

REPLY: We thank the reviewer for pointing out the erroneous equation given to calculate canopy conductance under water limited conditions. This was an error and is not the correct equation. The revised manuscript will instead include the correct equation originally described in Haxeltine and Prentice (1996; Eq. 25):

g_c = -g_min  * ln[(1- E_su)/(E_q * α_m)]

24. L150-151: unclear - clarify the source of Emax and Wr.

REPLY: The revised manuscript will reflect that E_max is a species-specific parameter and W_r is the soil moisture availability in the rooting zone, that is the fraction of water content accessible by each individual based on the species-specific root distribution across all soil layers:

“… maximum transpiration rate (E_max, a parameter; mm s^-1) and the soil moisture availability in the rooting zone (W_r, mm s^-1), that is, the fraction of soil water content accessible to an individual based on the parameterized species-specific root distribution across all soil layers (Haxeltine and Prentice, 1996)

25. Ede - are there any iterative optimization used in the computation of Ede and gc?

REPLY: Water demand, E_de, is used to constrain g_c in the context of plant hydraulic processes. No iterative optimization occurs here. Rather, iterative optimization happens in the photosynthesis routine to find an optimal stomatal sensitivity for photosynthesis to match g_c. This is described in detail in Sitch et al., (2003) and Haxeltine and Prentice (1996) and has been an integral part of LPJ-GUESS since its inception.

26. L162: typo

REPLY: We have checked the sentence on line 162 and could not identify any typo. If the reviewer could point out the specific typo we would be glad to take another look.

27. L181: unclear

REPLY: We assume the reviewer is referring to the description of wcont_tot, and subsequently will rephrase the sentence to indicate that we are referring to the total water content of the soil:

“... sum of plant available soil water and the soil water content at wilting point.”

28. Eq. 11: letter r?

REPLY: r is a rate parameter describing the adjustment speed of Ѱ_L to changes in Ѱ_s (see Equation 2, Papastefanou et al., 2024). Since LPJ-GUESS-HYD runs daily this parameter is equal to 1. This means that plants can quickly adjust to changes in soil moisture, a reasonable assumption when running the model on a daily timestep. For clarity, the revised manuscript will use the formulation from Papastefanou et al. 2024.

29. Eq. 17: cs?

    

REPLY: Thank you for bringing this typo to our attention. It should of course be a_s, the stem cross-sectional area, and will be fixed in the revised manuscript.

30. L331: vegetation carbon? GPP or biomass?

REPLY: We thank the reviewer for bringing this ambiguous statement to our attention. In the revised manuscript we will use “carbon in vegetation biomass” instead.

31. Section 3.3: check the unit of ET

REPLY: Done, the revised manuscript will feature the correct unit. Thank you for pointing out this oversight.

33. L387-388: unclear

REPLY: For clarity, we will reformulate this sentence in the revised manuscript.

Perhaps unsurprisingly, this pattern suggests that model processes which are more closely related to the

newly implemented plant hydraulic architecture (e.g., canopy conductance; see Figure 1) are more sensitive to the same factors affecting those processes. That is, while processes like carbon allocation to biomass which are further downstream from the new implementations are primarily affected by a single parameter (Ѱ₅₀), processes like canopy conductance which are directly affected by the new implementations are more sensitive to a greater number of the newly implemented parameters because the influence of these parameters is less diluted by other contributing model processes (e.g. plant demography) as is the case with the carbon allocation. 

34. L403-404: Discuss potential redundancy among variables related to isohydricity (e.g., ΔΨmax​) and its impact on the reliability of variance decomposition results.

REPLY: See our reply to comment No. 6

35. Section 4.1 - the author should discuss more on the different behaviors of ‘mean annual canopy conductance’ and its implications.

REPLY: We thank the reviewer for this suggestion. The discussion in the revised manuscript will dedicate more space to the results of the sensitivity analysis for mean annual canopy conductance.

36. L410-413: I understand that when the actual hydraulic conductance approaches zero, the maximum hydraulic conductance of root, stem, and leaf does not necessarily impose a limit on the actual hydraulic conductance. But what about non-stressed conditions? Would the sensitivity test show different results under stressed and non-stressed conditions?

REPLY: We thank the reviewer for this interesting question. It is quite possible that doing separate sensitivity analyses for stressed and non-stressed conditions would paint a different picture. While this was not in the scope of our current study which instead had the objective of quantifying the overall sensitivity of the model to the new plant hydraulic architecture, we believe this is an important point that should be addressed in subsequent studies. Consequently, we will add a call for future, more detailed sensitivity analyses to the discussion of the sensitivity analysis results in section 4.1.

37. Section 4.2 - check the logic flow please. L420-424: the author confirmed the performance of LPJ-GUESS-HYD, but in the next paragraph, the author stated how they validate the model performance.

REPLY: We thank the reviewer for pointing this out. The intention here was to say that since the sensitivity analysis suggests the same factors relevant to the model are widely discussed as relevant to drought response in observations and experiments LPJ-GUESS-HYD should be able to correctly simulate drought response across different species and hydraulic strategies. In the next paragraph we then go on to discuss how we are able to show that it indeed does. In the revised version of the manuscript we will clarify this:

“ … suggests that LPJ-GUESS-HYD should be able to correctly simulate drought and its associated impacts across a range of different species

and hydraulic strategies.”

38. L427-429: Explain the differences in ET across species, given that VPD should theoretically be consistent.

REPLY: As mentioned in comment 9, above, and comment 40, below, the revised manuscript will include a plot validating the ET response to VPD based on the limited observations available for single-species sites from the eddy-covariance flux data. The results of that plot will, of course, be included in the discussion here and add on to the already existing discussion (Line 434-440) placing our results in the context of the theoretical framework of the isohydric-anisohydric continuum whereby plants with different stomatal regulation strategies respond differently to the same levels of VPD. 

39. L437: There are many studies discussing the relative importance of VPD and soil moisture. The author should consider comparing the contributions of increased VPD and decreased soil moisture in explaining ET variations, if possible. This comparison would provide valuable insights into the dominant drivers of ET dynamics in the model and their alignment with observed patterns.

REPLY: We thank the reviewer for this suggestion. However, this is out of the scope of this study which is primarily a model description paper. We agree that further research should focus on exploring the ability of models to capture such relative contributions and will mention this in the discussion.

40. L438-440: Include a plot validating the species-specific ET response, as this is a key result of the study.

REPLY: Done. See response to comment 9.

41. L451-455: unclear. The author should provide a more detailed discussion of potential reasons for the undesirable performance of the modeled GPP.

REPLY: We do not necessarily consider the performance of modeled GPP to be undesirable. Rather, we here explain why LPJ-GUESS-HYD and LPJ-GUESS perform similarly at simulating observed GPP. To add context to this we will include a discussion on how future modle versions may be able to strengthen the link between plant hydraulic processes and photosynthesis.

42. L481-482: does leaf area decrease during drought in the LPJ-GUESS-HYD model? This process should ideally be included. If it is not, the author should clarify how leaf area dynamics are represented in the current model version and discuss whether the absence of such a mechanism could impact the model's performance during drought conditions.

REPLY: Currently, drought does not induce early leaf senescence to reduce leaf area in LPJ-GUESS-HYD. As the reviewer states this should ideally be included. Consequently, we discuss this in Section 4.3 “Limitations of the modeling approach and ways forward” and mention that:

 “...crown dieback reduces the leaf area, altering canopy water demand and growth even once the drought has subsided (Arend et al., 2022; Guada et al., 2016). While the exact mechanisms may be too detailed for a model such as LPJ-GUESS-HYD, some relationship between hydraulic failure and reduced leaf area should be a part of future developments to ensure that the actual leaf area matches that which is able to be supported by the diminished sapwood area due to xylem cavitation.”

To more clearly highlight the challenges associated with modeling this behavior the revised version of the manuscript will include the additional lines: 

“...crown dieback reduces the leaf area, altering canopy water demand and growth even once the drought has subsided (Arend et al., 2022; Guada et al., 2016). While early leaf senescence in response to drought has been widely observed in beech and other temperate broad-leaved species (Schuldt et al., 2020 and references therein), evidence suggests that coniferous species, such as spruce, may die from hydraulic failure before such protective measures can occur (Arend et al. 2021). Additionally, the relationship between drought intensity, hydraulic failure and early leaf senescence is difficult to quantify and studies establishing concrete thresholds for leaf senescence are scarce and focused on single species (e.g. Walthert et al., 2021). Nevertheless, early leaf senescence plays an important role in governing tree drought response (Nadal-Sala et al., 2024). While the exact mechanisms may be too detailed for a model such as LPJ-GUESS-HYD, some relationship between hydraulic failure and reduced leaf area should be a part of future developments to ensure that the actual leaf area matches that which is able to be supported by the diminished sapwood area due to xylem cavitation.”