the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 06 Sep 2024
Including the Phosphorus cycle into the LPJ-GUESS Dynamic Global Vegetation Model (v4.1, r10994) – Global patterns and temporal trends of N and P primary production limitation
Abstract. Phosphorus (P) is a critical macronutrient for plant growth, often limiting plant production in areas where plant demand is higher than soil supply. In contrast to nitrogen (N), P cannot be sourced from the atmosphere, therefore where it is rare, it becomes a strong constraint of primary production. Due to this, most DGVMs are incorporating a prognostic P cycle in addition to N, improving their ability to correctly predict stocks and fluxes of carbon, and how climate change may impact N and/or P limitations to soil processes and plant productivity.
We included the P-cycle into an individual-based DGVM, LPJ-GUESS (v4.1, r10994), in order to improve the model performance with regard to observations of vegetation and soil N and P stocks and fluxes in comparison to the N-only (LPJ-GUESS-CN) model version. The new model version (LPJ-GUESS-CNP) includes soil organic P dynamics, P limitation of organic matter decomposition, P deposition, temperature and humidity-dependent P weathering, plant P demand and uptake, and P limitations to photosynthesis. Using the CNP version of LPJ-GUESS we also estimated global spatial patterns of nutrient limitation to plant growth, as well the temporal change in plant N and P limitation during the 20th and early 21st centuries, evaluating the causes for these temporal shifts.
We show that including the P-cycle significantly reduces simulated global vegetation and soil C and N stocks and fluxes, in particular in tropical regions. The CNP model simulation improved the fit to global biomass observations in relation to the CN simulation. The CNP model predicted predominant P limitation of plant growth in the tropics, and N limitation in the temperate, boreal, and high altitude tropical regions. The CNP model also correctly predicted the global magnitude (~ 50 PgP) and the spatial pattern of total organic P stocks. P limited regions cover less land surface area (46 %) than N limited, but are responsible for 57 % of global GPP and 68 % of vegetation biomass, while N limited regions store a larger portion of total carbons stocks (55.9 %). Finally, the model showed that globally primary production limitation to N availability decreased and limitation to P increased from 1901 to 2018, with N being more responsive to temperature, and P to CO2 changes. We conclude that including the P-cycle in models like LPJ-GUESS is crucial for understanding global-scale spatial and temporal patterns in nutrient limitation and improving the simulated carbon stocks and fluxes.
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Status: open (until 22 Dec 2024)
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RC1: 'Comment on egusphere-2024-2592', Anonymous Referee #1, 16 Oct 2024
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This manuscript clearly explains the method and performance of integrating the phosphorus cycle into the LPJ-GUESS Dynamic Global Vegetation Model. The writing is logically structured, and the model development process is well-reasoned. The authors also provide a thorough discussion of the results. I have only a few detailed comments, which are outlined below.
Introduction:
The introduction does a good job in establishing the need for incorporating the phosphorus cycle into dynamic vegetation models, highlighting its importance as a plant growth constraint. However, it would benefit from a more thorough discussion of past challenges in phosphorus modeling and recent advancements, especially regarding prior efforts in Earth system models, where phosphorus cycling, though less common than nitrogen, has been integrated in models like ORCHIDEE-CNP and CASA-CNP. Clarifying research gaps and this study’s unique contributions compared to these models would enhance its impact. Additionally, providing context for the four scientific questions would help readers understand their relevance, as they currently appear somewhat abruptly.
Methodology:
In Figure 1, consider adding some equations (or other elements) to illustrate the principles behind phosphorus limitation, such as how soil phosphorus cycling regulates available phosphorus levels and how soil phosphorus uptake limits plant photosynthesis. This would help readers better understand the model's configuration, especially as this is a central focus of the study. Additionally, is the leaching path missing from the figure?
I recommend moving the content related to P soil processes from the appendix into the main text, particularly sections on P sorption and P weathering. For readers less familiar with these processes, equations can facilitate understanding.
Integrating phosphorus limitation into the model is indeed a significant advancement. However, we know that plant growth may also be limited by other elements, such as potassium or calcium. Therefore, there is still the potential to overestimate plant growth in this model (at least from a nutrient supply perspective). I suggest adding a few sentences in the discussion to address this limitation.
Results:
The results are well-documented.
Discussion:
The discussion section provides a thorough evaluation of the model's performance and areas for improvement. I suggest more discussion of potential limitations. For example, the model lacks certain processes in the phosphorus cycle, such as the impact of plants and microbes on weathering, and there is uncertainty in data sources, as phosphorus content in rock is typically based on sample averages that may not fully represent the mineral composition across all regions. Highlighting these limitations would inspire future research to address these aspects.
Citation: https://doi.org/10.5194/egusphere-2024-2592-RC1 -
AC1: 'Reply on RC1', Mateus Dantas de Paula, 25 Oct 2024
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Many thanks for your comment to the manuscript, the suggestions have been duly appreciated:
Introduction
The paragraph starting in line 62 was extended to include additional arguments in favor of including the phosphorus cycle in DGVMs, as well as a larger list of existing models such as ORCHIDEE and CASA-CNP which include this cycle. In addition, the research gaps in these previous studies were included, namely a global spatial and temporal analysis of N and P limitation, also through a factorial analysis, which in addition provide more context for the four scientific questions which were presented.
Methodology
References to the equations illustrated by Figure 1 were added, as well as further details on how P in soil may affect decomposition rates. Hopefully this increases the understanding of the model´s configuration. The leaching path that was absent was included.
Due to text size constraints, the equations were kept in the appendix. It is believed this would not hinder access to this information, since in the journal´s format the Appendix are embedded into the main document, and not a separate one.
Model limitations in relation to absent processes were added in the manuscript´s final paragraph.
Discussion
A few lines on the uncertainty of P release estimations based on the Chemical Weathering Model and due to the limited amount of sampling was added to the last paragraph of section 4.2.
Citation: https://doi.org/10.5194/egusphere-2024-2592-AC1
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AC1: 'Reply on RC1', Mateus Dantas de Paula, 25 Oct 2024
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