the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 06 Jan 2025
Eco-evolutionary Modelling of Global Vegetation Dynamics and the Impact of CO2 during the late Quaternary: Insights from Contrasting Periods
Abstract. Changes in climate have had major impacts on global vegetation during the Quaternary. However, variations in CO2 levels also play a role in shaping vegetation dynamics by influencing plant productivity and water-use efficiency, and consequently the relative competitive success of the C3 and C4 photosynthetic pathways. We use an eco-evolutionary optimality (EEO) based modelling approach to examine the impacts of climate fluctuations and CO2-induced alterations on gross primary production (GPP). We considered two contrasting periods, the Last Glacial Maximum (LGM, 21,000 years before present) and the mid-Holocene (MH, 6,000 years before present) and compared both to pre-industrial conditions (PI). The LGM, characterised by generally colder and drier climate, had a CO2 level close to the minimum for effective C3 plant operation. In contrast, the MH had warmer summers and increased monsoonal rainfall in the northern hemisphere, although with a CO2 level still below PI. We simulated vegetation primary production at the LGM and the MH compared to the PI baseline using a light-use efficiency model that simulates GPP coupled to an EEO model that simulates leaf area index (LAI) and C3/C4 competition. We found that low CO2 at the LGM was nearly as important as climate in reducing tree cover, increasing the abundance of C4 plants and lowering GPP. Global GPP in the MH was similar to the PI (although greater than the LGM), also reflecting CO2 constraints on plant growth despite the positive impacts of warmer and/or wetter climates experienced in the northern hemisphere and tropical regions. These results emphasise the importance of taking account of impacts of changing CO2 levels on plant growth to model ecosystem changes.
-
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.
-
Preprint
(7659 KB)
-
Supplement
(8507 KB)
-
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(7659 KB) - Metadata XML
-
Supplement
(8507 KB) - BibTeX
- EndNote
- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-3897', Anonymous Referee #1, 10 Mar 2025
-
AC1: 'Reply on RC1', Sandy Harrison, 04 Apr 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2024-3897/egusphere-2024-3897-AC1-supplement.pdf
-
AC1: 'Reply on RC1', Sandy Harrison, 04 Apr 2025
-
RC2: 'Comment on egusphere-2024-3897', Anonymous Referee #2, 20 Apr 2025
Zhao et al. investigated the impacts of climate fluctuations and CO2-induced alterations on gross primary production (GPP) using an eco-evolutionary optimality (EEO) based modelling approach. Two contrasting periods are focused, including the Last Glacial Maximum (LGM) and the mid-Holocene (MH), and compared to pre-industrial conditions (PI). This study assessed the importance of CO2, climate change, and light on the GPP at the global scale and pixel level. I have a few concerns about the robustness and implications of this study.
There is a large model range of GPP at the LGM (61-109 PgC yr-1 or 40-110 PgC yr-1), which could be primarily attributed to uncertainties in the effects of tree cover, distribution of C4 plants, and/or effects of climate change and changing CO2. Thus, the uncertainties associated with climate change and CO2 may be much larger than or at least comparable to their effects on the GPP differences between LGM and PI estimated by this study (Figure 5). This substantial uncertainty could raise questions about the robustness and reliability of the results presented in this study.
This study emphasizes the impacts of CO2 on the GPP and vegetation dynamics during both LGM and MH. Different levels of CO2 during LGM, MH, and PI, cause various light-use efficiency and distribution of C4 plants, thereby inducing different GPP. Figure 5 shows the magnitudes of effects of CO2 on the GPP during LGM and MH, thus could be used to estimate the sensitivity of GPP to CO2 changes. Although it is CO2 sensitivity based on the long-term changes, it would be meaningful and interesting to compared it with that based on the recent observations and simulations.
The description of units is confusing. For example, the unit of global GPP is PgC yr-1 rather than PgC. In Table 3, the unit of the contribution of C3/C4 to GPP is gC m2 yr. It should be checked because gC m-2 yr-1 is more commonly used.
Citation: https://doi.org/10.5194/egusphere-2024-3897-RC2 - AC2: 'Reply on RC2', Sandy Harrison, 20 Apr 2025
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-3897', Anonymous Referee #1, 10 Mar 2025
This paper presents an eco-evolutionary optimality (EEO)-based modeling approach to examine the effects of climate fluctuations and CO₂ levels on GPP during the Last Glacial Maximum (LGM, 21,000 years before present) and the mid-Holocene (MH, 6,000 years before present), relative to pre-industrial conditions (PI). The study effectively integrates climate and vegetation models to assess the influence of CO₂ constraints, climate variability, and solar radiation on plant productivity and C3/C4 competition. However, I have concerns regarding the novelty and broader implications of this work, particularly how it advances beyond previous factorial simulations.
The impacts of changing CO₂ levels on plant growth have already been incorporated into many land surface models (LSMs) and Earth System Models (ESMs), though the magnitude of physiological effects differs between models. The authors should clarify how this study advances prior work and explicitly discuss its implications for ecosystem modeling.
A direct comparison with existing models (e.g., DGVMs, LSMs, and ESMs) would strengthen the study’s contribution. How does the EEO-based approach improve upon these models in simulating GPP and C3/C4 competition?
The study reports an LGM GPP estimate of 84 PgC, within the CMIP6/PMIP4 range of 61–109 PgC. There is large inter-model variability (spanning tens of PgC). The authors conclude that CO₂ effects led to a 3 PgC reduction in GPP during MH, while climate changes contributed to a 2 PgC increase, yielding a net difference of only 1 PgC. Given the large uncertainty in model estimates, is this difference statistically significant? Could this conclusion be influenced by model structural biases or sensitivity to parameter choices?
Citation: https://doi.org/10.5194/egusphere-2024-3897-RC1 -
AC1: 'Reply on RC1', Sandy Harrison, 04 Apr 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2024-3897/egusphere-2024-3897-AC1-supplement.pdf
-
AC1: 'Reply on RC1', Sandy Harrison, 04 Apr 2025
-
RC2: 'Comment on egusphere-2024-3897', Anonymous Referee #2, 20 Apr 2025
Zhao et al. investigated the impacts of climate fluctuations and CO2-induced alterations on gross primary production (GPP) using an eco-evolutionary optimality (EEO) based modelling approach. Two contrasting periods are focused, including the Last Glacial Maximum (LGM) and the mid-Holocene (MH), and compared to pre-industrial conditions (PI). This study assessed the importance of CO2, climate change, and light on the GPP at the global scale and pixel level. I have a few concerns about the robustness and implications of this study.
There is a large model range of GPP at the LGM (61-109 PgC yr-1 or 40-110 PgC yr-1), which could be primarily attributed to uncertainties in the effects of tree cover, distribution of C4 plants, and/or effects of climate change and changing CO2. Thus, the uncertainties associated with climate change and CO2 may be much larger than or at least comparable to their effects on the GPP differences between LGM and PI estimated by this study (Figure 5). This substantial uncertainty could raise questions about the robustness and reliability of the results presented in this study.
This study emphasizes the impacts of CO2 on the GPP and vegetation dynamics during both LGM and MH. Different levels of CO2 during LGM, MH, and PI, cause various light-use efficiency and distribution of C4 plants, thereby inducing different GPP. Figure 5 shows the magnitudes of effects of CO2 on the GPP during LGM and MH, thus could be used to estimate the sensitivity of GPP to CO2 changes. Although it is CO2 sensitivity based on the long-term changes, it would be meaningful and interesting to compared it with that based on the recent observations and simulations.
The description of units is confusing. For example, the unit of global GPP is PgC yr-1 rather than PgC. In Table 3, the unit of the contribution of C3/C4 to GPP is gC m2 yr. It should be checked because gC m-2 yr-1 is more commonly used.
Citation: https://doi.org/10.5194/egusphere-2024-3897-RC2 - AC2: 'Reply on RC2', Sandy Harrison, 20 Apr 2025
Peer review completion
Journal article(s) based on this preprint
Model code and software
CMIP6 MPI-ESM1-2-LR outputs Earth System Federation Grid http://esgf-node.llnl.gov/search/cmip6/
Viewed
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 743 | 104 | 27 | 874 | 82 | 28 | 53 |
- HTML: 743
- PDF: 104
- XML: 27
- Total: 874
- Supplement: 82
- BibTeX: 28
- EndNote: 53
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
Jierong Zhao
Boya Zhou
Sandy P. Harrison
I. Colin Prentice
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(7659 KB) - Metadata XML
-
Supplement
(8507 KB) - BibTeX
- EndNote
- Final revised paper
This paper presents an eco-evolutionary optimality (EEO)-based modeling approach to examine the effects of climate fluctuations and CO₂ levels on GPP during the Last Glacial Maximum (LGM, 21,000 years before present) and the mid-Holocene (MH, 6,000 years before present), relative to pre-industrial conditions (PI). The study effectively integrates climate and vegetation models to assess the influence of CO₂ constraints, climate variability, and solar radiation on plant productivity and C3/C4 competition. However, I have concerns regarding the novelty and broader implications of this work, particularly how it advances beyond previous factorial simulations.
The impacts of changing CO₂ levels on plant growth have already been incorporated into many land surface models (LSMs) and Earth System Models (ESMs), though the magnitude of physiological effects differs between models. The authors should clarify how this study advances prior work and explicitly discuss its implications for ecosystem modeling.
A direct comparison with existing models (e.g., DGVMs, LSMs, and ESMs) would strengthen the study’s contribution. How does the EEO-based approach improve upon these models in simulating GPP and C3/C4 competition?
The study reports an LGM GPP estimate of 84 PgC, within the CMIP6/PMIP4 range of 61–109 PgC. There is large inter-model variability (spanning tens of PgC). The authors conclude that CO₂ effects led to a 3 PgC reduction in GPP during MH, while climate changes contributed to a 2 PgC increase, yielding a net difference of only 1 PgC. Given the large uncertainty in model estimates, is this difference statistically significant? Could this conclusion be influenced by model structural biases or sensitivity to parameter choices?