The study presents an easy to use ecosystem model, which is a step to open up ecosystem modelling for a wider community.

With a background in ecosystem modelling, I find this really appealing. Although I can not fully understand/buy into what you are talking about in the introduction regarding the use of R by ecologists. Sure, we in the ecosystem modelling community are using lower level computer language, but we are also using R, Matlab or Python for our analysis. I suggest that you re-write that section.

Generally, I like your model description, but there are two things that I beleive needs a bit more attention. First of all, PFT:s (Plant Functional Types), are you really simulating PFT:s? From what I have read, it is more like you are simulating different land tiles with monocultures of PFT:s planted on them. There is a mix, in the text, between talking about a PFT as plant and PFT as a land-cover/vegetation type. For instance in section 2.2.1. For instance, bare ground can not be a PFT.

Depending on your answer to the question above, if you are truly simulating different PFT:s in a tile, then competition needs to be presented. If not, then clearly state that you are not simulating competition between different strategies, and that the spatial extent of these strategies is fixed. Something that I was missing from the discussion as well. How is that affecting your results, that you have a fixed fraction of strategies?

I would claim that for instance having different sensitiveness to ozone would affect the composition if [O3] will change in the future.

Some specific corrections:

line 10, page 2; there is a missing "is" on that line.

Eq. 14 is missing something

Review comments for egusphere-2023-1287

Title: Terrestrial Ecosystem Model in R (TEMIR) version 1.0: Simulating ecophysiological responses of vegetation to atmospheric chemical and meteorological changes

This study developed a terrestrial ecosystem model using the R programming language, which is beneficial for more ecologists to use ecosystem model. I like the idea of developing an open and free ecosystem model using the user-friendly programming language R, it will help expand the ecosystem modeling community. The TEMIR is capable of modeling plant ecophysiological responses to varying meteorological conditions and CO₂ concentrations and ground-level ozone (O₃) based on prescribed meteorological and atmospheric chemical inputs. The authors validated the model performance at both site and global scales.  In general, this manuscript is well organized, but still has several drawbacks. The reviewer has the following concerns and suggestions for the authors to consider:

(1) Is the spatial distribution and fractional coverage of PFTs fixed during the simulation period? Does it mean that the model doesn’t consider land use change effect? If so, it is necessary to discuss the effect of lacking LULCC change on GPP estimation.

(2) Please elaborate what MODIS product did you use to derive PFTs distribution maps. And how did you sperate C3 and C4 crops, since MODIS products don’t have such information.

(3) MERRA-2 has a native resolution of 0.5° x 0.625°, why didn’t you conduct simulations at this relative high resolution?

(4) Please elaborate how is the dark respiration (Rd) rate calculated in the model.

(5) The TEMIR contains a two-layer soil model. Does this soil model have carbon cycling and water transport processes?

(6) The canopy decay coefficient for nitrogen Kn is 0.30 in the model. How was this number determined? Shouldn’t it vary with leaf nitrogen content or nitrogen availability? It seems that the current version of TEMIR doesn’t have an explicit nitrogen cycle. If so, it is necessary to discuss how does lack of considering nitrogen cycle affect GPP estimation.

(7) The model doesn’t perform well at several crop sites. Could you add one paragraph discussing the potential measures to improve model performance for crops?

(8) For the site-level simulation, why did you fix CO₂ concentration at the level of 390 ppmv, rather than using the actual CO₂ concentration during the study period?

(9) For the site CH-Cha, can you explain why the model performance is good using reanalysis meteorological input data?

(10) You explained that the underestimation of GPP at the FR-Fon site is most likely due to inaccurate parameterization overcompensating for the uncertainties of satellite derived LAI. Have you tried to quantify how uncertainties in LAI affect GPP estimation. Maybe you can compare the difference using tow simulations: one use MODIS LAI as input, one use observed LAI as input.

(11) I suggest the author add a paragraph describing what meteorological variables are needed to drive the TEMIR.

(12) Please add one table listing the key parameters for different PFTs.