Overall, I think that the revisions the author's have carried out considerably improve the readability and framing for the reader, so I thank them for making those efforts. I think the addition of the CN and CNP is a nice contribution even if ultimately it does not change the interpretation; that message in itself is a useful one.
I have a few minor responses to their responses to my comments.
- In their revision the authors note: "𝛽 values at ecosystem levels are more variable with nutrient effects, LAI responses are still linearly correlated well with 𝛽GPP, 𝛽NPP and 𝛽𝑐𝑝𝑜𝑜𝑙 across different C3 PFTs in nutrient-coupled simulations as in C-only simulation, confirming the dominant role of LAI in regulating carbon cycle response under CO2 fertilization"
Here, I think a valuable link with this conclusion would be to discuss current models simulate allocation to leaves (discussion perhaps?). For example, the EucFACE CO2 experiment shows no increased LAI in response to CO2 (Duursma et al. 2016), despite the roughly expected theoretical increase in leaf-level photosynthesis in response to CO2 (Ellsworth et al. 2017). This would question a linear correlation between 𝛽GPP and LAI, I think? It is very likely that we have more to learn as we now begin to think further about mature ecosystems.
Duursma, R. A., Gimeno, T. E., Boer, M. M., Crous, K. Y., Tjoelker, M. G. and Ellsworth, D. S. (2016), Canopy leaf area of a mature evergreen Eucalyptus woodland does not respond to elevated atmospheric [CO2] but tracks water availability. Glob Change Biol, 22: 1666-1676. doi:10.1111/gcb.13151
Ellsworth, D. S., Anderson, I. C., Crous, K. Y., Cooke, J., Drake, J. E., Gher-
lenda, A. N., & Tjoelker, M. G. (2017). Elevated CO2 does not increase eucalypt forest productivity on a low-phosphorus soil. Nature Climate Change, 7, 279–282. https://doi.org/10.1038/nclimate3235
- To my question about the CABLE simulations almost always being limited by RuBP-regeneration rate ... I agree that at elevated CO2 concentrations this would be true, but I disagree this should be true when the CO2 concentration is "391 ppm" as they stated. If one assumed a Ci/Ca of 0.7, then the Ci concentration would be ~270, which should make the model Rubisco limited (excluding the contribution of LAI). I do suggest they should check this point again. I guess my point is fundamentally about interpretation. A fraction of the readership will read their statement and begin to question whether there is an underlying issue with the model simulations. However, as the authors argue (citing Luo and Mooney), it probably does not matter, but I feel it would be useful to remove any doubt from the reader's mind.
- To the author's response about me asking how different levels of water-stress across models would affect their conclusions, they now state: "Our results show modelled ratio of 𝐶𝑖 to atmospheric CO2 concentration (𝐶𝑎) is relatively constant for each PFT with eCO2 and varies little among PFTs (Table 1)". Here I refer them to my original point ... this may very well be true for CABLE, but what about if a model had twice as much water stress as CABLE? Whilst it may not be true that water stress has a bit impact on CABLE's results, it may not be true to conclude this factor does not impact a broader CMIP5 model ensemble which was their original comparison point. It is simply not true to asset that: "Wong et al. (1979) showed plant stomata could maintain a constant 𝐶𝑖/𝐶𝑎 across wide range of environmental conditions, including water stress condition. Therefore different vegetation types might have similar 𝐶𝑖 for a given 𝐶𝑎 in other models". The Wong study is not a model result, it may very well be theoretically true but models are known to disagree markedly on the impact on water stress, so they cannot have the a "similar Ci for given Ca" across models. In Fig 7, in De Kauwe et al. 2017, Global Change Biology (2017), doi: 10.1111/gcb.13643, I showed the average water stress for a range of models during the growing season. In these simulations Ca was increased in exactly the same way across models, so these differences must have equated to differences in Ci. Finally, they argue that Luo and Mooney showed insensitivity to a change in Ci/Ca from 0.8 to 0.6. But that is essentially without water stress, some of the models in the figure I referred to must have been considerably lower than 0.6. Frankly, a better argument to make to me here - is that water stress comes and goes and that it can be ignored as a factor when looking across years!
- To their response on leaf temperature. I can't recall the details of the Luo and Mooney study, which they seem to know well. Whilst I do not take issue with their point on the impact of leaf temp on gamma star, I was actually thinking about the impact of the different resolved leaf temperatures on Ci, which is solved via the energy balance. However, this is most likely speculative (on my part) anyway, so can be ignored.
- In their reframing of the text in reference to the Hajima et al. paper, I wonder if the author's could go further in their explanations. This strikes me as a very important and interesting point, but as written is a little too superficial. The author's are arguing that one gets a different interpretation of 𝛽 if one calculates it at the leaf-level vs. as canopy/stand-level, GPP/LAI. They appear to attribute this to the fact that the authors have ignored differences in the scaling in how the canopy is treated. If I follow, these are the only factors, or were there more? If these are the only factors, if the calculation is formulated on a big-leaf vs a two-leaf vs a multi-layer, which one best matches the GPP/LAI formulation that Hajima used? Or which PFTs does this issue matter most for? These strike me as points worth making, or perhaps I've oversimplified? |