the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 28 May 2025
PHOREAU v1.0: a new process-based model to predict forest functioning, from tree ecophysiology to forest dynamics and biogeography
Abstract. Climate change impacts forest functioning and dynamics, but large uncertainties remain regarding the interactions between species composition, demographic processes and environmental drivers. While the effects of changing climates on individual plant processes are well studied, few tools dynamically integrate them, which precludes accurate projections and recommendations for long-term sustainable forest management. Forest gap models present a balance between complexity and generality and are widely used in predictive forest ecology, but their lack of explicit representation of some of the processes most sensitive to climate changes, like plant phenology and water use, puts into question the relevance of their predictions. Therefore, integrating trait- and process-based representations of climate-sensitive processes is key to improving predictions of forest dynamics under climate change.
In this study, we describe the PHOREAU model, a new semi-empirical forest dynamic model resulting from the coupling of a gap model (FORCEEPS), with two process-based models: a phenology-based species distribution model (PHENOFIT) and a plant hydraulics model (SurEAU), each parametrized for the main European species. The performance of the resulting PHOREAU model was then evaluated over many processes, metrics and time-scales, from the ecophysiology of individuals to the biogeography of species.
PHOREAU reliably predicted fine hydraulic processes at both the forest and stand scale for a variety of species and forest types. This, alongside an improved capacity to predict stand leaf areas from inventories, resulted in better annual growth compared to ForCEEPS, and a strong ability to predict potential community compositions.
By integrating recent advancements in plant hydraulic, phenology, and competition for light and water into a dynamic, individual-based framework, the PHOREAU model, developed on the Capsis platform, can be used to understand complex emergent properties and trade-offs linked to diversity-effects effects under extreme climatic events, with implications for sustainable forest management strategies.
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Status: open (until 23 Jul 2025)
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RC1: 'Comment on egusphere-2025-2110', Anonymous Referee #1, 15 Jun 2025
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Review of: PHOREAU v1.0
This paper introduces PHOREAU, a new individual-based, process-based forest dynamics model. The model is a significant development as it couples three existing models: a forest gap model (ForCEEPS), a plant hydraulics model (SurEau), and a phenology-based species distribution model (PHENOFIT). The primary goal of PHOREAU is to improve predictions of forest dynamics under climate change by integrating detailed, trait-based representations of climate-sensitive processes like water use, phenology, and competition for both light and water. The authors perform a comprehensive multi-scale validation, evaluating the model's performance on metrics ranging from daily tree-level hydraulic functioning (e.g., stem water potential) to long-term, landscape-level species composition (Potential Natural Vegetation). The results show that PHOREAU provides reliable predictions across these scales and generally outperforms its predecessor, ForCEEPS.
General Comments
First and foremost, I would like to congratulate the authors for this impressive and substantial piece of work! The manuscript, while long, is exceptionally thorough, providing a wealth of necessary detail for understanding and evaluating the model. It is well-structured and written with great clarity, making it a joy to read.
The presentation of the model is a particular strength. The authors guide the reader effectively from the foundational ForCEEPS model through the various layers of modification and integration. This, combined with high-quality figures (e.g., Figure 2), makes the complex structure of PHOREAU highly accessible. The integration of the sophisticated water modeling via its effects on growth and mortality is elegantly done and represents a significant conceptual advance. Furthermore, the authors should be commended for their transparency regarding model simplifications and the assumptions that underpin them.
The evaluation is very extensive, examining different processes across multiple scales. This approach is reminiscent of "pattern-oriented modelling," and the authors might consider framing it in this context and citing the relevant literature. I particularly appreciate the forward-looking perspective of establishing an evaluation framework that can be easily repeated, which will undoubtedly guide future model development.
The presentation of the evaluation results could, however, be improved. In several figures, font sizes are quite small, and some plots appear stretched. For long time series of daily data (e.g., Fig. 10), the fine temporal scale is lost, making them difficult to interpret. Presenting more of this data as scatter plots (as in Fig. 13) could enhance clarity. To improve readability and focus given the paper's length, the authors might also consider moving some detailed results to the supplementary materials, while retaining the key findings from each evaluation level in the main text.
A minor suggestion would be to more frequently remind the reader in the technical sections (e.g., 2.1.2) that additional details are available in the appendices. Given the manuscript's length, this would help reader navigation. Similarly, a clearer, earlier statement regarding the different time-steps (e.g., daily, hourly) and the multi-layered soil structure used in the water modeling would help orient the reader from the outset.
In summary, PHOREAU v1.0 represents a substantial and impressive advancement in forest modeling. The authors' forward-looking approach, designing the model and its evaluation for continuous improvement, signals a long-term commitment to advancing the field, which I highly appreciate!
Specific Comments
Introduction:
- The introduction provides a very detailed account of species mixture effects (e.g., lines 70-95), which could be shortened. On the other had, a broader context of other forest modeling approaches is a bit lacking.
- L105-110: The text mentions "identified two main shortcomings in forest models." It would be helpful to briefly elaborate on how these specific shortcomings were identified (e.g., through literature review, previous modeling experiments, etc.).
Model Description:
- L159: Typo: "plaform" should be "platform".
- L216 (Eq. 1): There appears to be a layout issue in the equation. It should likely read 2*H_max,s - b_s * e^(...) rather than having the allometric parameters in the denominator's exponent. Please verify the formula.
- L232: Suggest inserting the word "species": "shade intolerant species having...".
- L251-265: The concept of "crown ratio reversion" needs clarification. Does this mechanism allow the base of the living crown to move downwards again, effectively re-greening parts of the stem that were previously bare? This should be clarified here and in the appendix.
- L277: The symbol for the clumping factor appears to be missing from the parentheses: clumping factor ( ).
- L333ff: While "symplasm" is defined by contrast, a brief explanation of "apoplasm" (the continuum of cell walls and extracellular spaces) would be beneficial for non-specialists.
- L368: Typo: "depending on depends".
- L382: It would be useful to briefly explain what a "semi-implicit solver" is and give an indication of the runtime difference it makes compared to an explicit solver.
- L531 (Eq. 13): There may be a typo in the denominator. The text reads P_gSBB, which seems inconsistent with the parameter P_gs88 defined on L525. Please check.
- L545: The growth reduction factor GR_crown is used here but has not been fully explained. A brief definition is needed.
- L553: The citation Hammond et al., 2019 appears to be missing a closing parenthesis.
- L620: The rationale for weighting light availability by daily mean temperature needs more justification. This method heavily weights hot summer months when growth may be limited by other factors (like drought). A temperature response curve that is primarily limiting at the cool end of the spectrum might be more ecologically realistic.
- L651 (Eq. 19): Notation for leaf unfolding and coloration intervals is slightly inconsistent between the text (Uls, Cls) and the key below the equation (UI_s, CI_s).
- L695: A word appears to be missing in "the fine root area of a tree in a determines...".
- L749: There is an extraneous character (a hyphen) after the period at the end of the paragraph.
Results, Discussion & Figures:
- L765/Figure 4: This figure is difficult to interpret due to very small font sizes and hard-to-distinguish color-coding. Furthermore, the claim that it shows "acclimatization" over 1500 years seems more likely to reflect changes in stand structure and species composition rather than plastic adaptation within individual long-living trees. Please clarify.
- L880/Figure 6: There appears to be an inconsistency in the visualization. For instance, for the Puéchabon site, the caption states "3 patches of 100m²", but the grey grid lines on the ground seem to depict a different arrangement (e.g., 4x4 grid). This should be checked for all subplots.
- L914: The paper states that longer time-lapses "would have mechanically improved simulation results". This is counter-intuitive, as one might expect simulating longer periods to be more challenging and prone to error accumulation. Could the authors please clarify what is meant by "mechanically improved" results in this context?
- L1019: Typo: "crown Al ratio" should likely be "crown ratio" or similar.
- L1059: There is a minor date discrepancy for the Hesse site thinning. The main text mentions a cut in 2005, whereas Appendix Q lists thinnings in 2004 and 2009. This could be harmonized for clarity.
- L1250/Figure 17: This figure effectively illustrates the model's performance across ecological gradients. A very nice visualization.
- L1375 (and elsewhere): The citation 'Allen, Macalady, Chenchouni...' is very long. This format occurs multiple times (e.g., L54) and could be consistently shortened to 'Allen et al.' for readability.
References:
- L2231: The reference for Bréda, Soudan and Bergonzini is listed with "(no date)", which is unusual and could be clarified.
Citation: https://doi.org/10.5194/egusphere-2025-2110-RC1
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