I reviewed the manuscript ‘Limited impact of microtopography on alpine plant distribution’ submitted for publication in Ecography. The study explores how various microtopographic variables at different resolutions impact species distributions and community attributes. The study is interesting and thorough. I think the manuscript has great potential to be interesting for many readers, but needs some more work with the text and presentation. Some general comments are described here, followed by more specific comments below.

1. The Methods section is missing many details (more specifically described below), and in many cases it’s unclear at first which response and explanatory variables are included. These should be more clearly explained. Also, consider adding a table summarising all the explanatory variables (or add to Table 1).
2. The discussion needs further work to link the results to previous findings and to highlight the novelty. Are the results similar to previous studies?
3. The manuscript is generally clearly written, but could benefit some further polishing of English language.

Introduction:
Line 29 – perhaps remove the part ‘drawn from this fact’ (it’s clear without it) to make the sentence easier to read
Line 31 – maybe better to start a new paragraph with ‘While some authors…’, and combine with the following paragraph on line 42
Line 48 – remove ‘above’ or use ‘above-described’
Line 50 – do you mean higher than 20m? And why is 20 m the cutoff?
Line 93 – use ‘Austrian’

Material and methods:
Line 106 – maybe mention Austrian Alps here again for clarity
Line 110 – use ‘should cover’ or ‘covers’ (without ‘should’)
Lines 115-117 – explain more in the text how the different scales were considered, is it around each 1m x 1m plot, using the plot center?
Line 120 – give an approximate area these plots cover to get an idea of the regional scale
Line 122 – maybe remove the word ‘area’ (summit implies to a highest point)
Line 124 – I think this cannot be ‘exact’ assignment if plot and cell sizes are equal, even if plot location only has small accuracy error
Line 129 – the scale is understandable, but it’s not written accurately (e.g. cover <50% is also <0.1%), use ranges for the middle classes, and also clarify if cover=75% is class 4 or 5
Line 143 – I think the EIVs need some further explanation - where the data is from, what are the data values/ranges and what they represent. If there’s no space in the main text, it could be included in the supplementary materials
Lines 153-154 – difficult to understand here what the ‘frequent’ refers to (species or plots), rephrase to ‘We measured 56 most frequent species out of 253 recorded in the 900 plots.’
Line 156 – specify if the five individuals were from different plots?
Line 166 – maybe explain here also how elevation was estimated, and what was the resolution
Line 172 – here it would be useful to have a summary of the studied variables, or maybe include them in a table, and also include a reference to the supplementary material where they are already described in detail
Line 174 – maybe instead of ‘window sizes’ here it’s better to use ‘spatial scales’ (more understandable out of context)
Line 195 – clarify what was the response variable for species distribution, cover or presence/absence
Line 210 – use ‘aimed to assess’
Line 211 – add an explanation for fine scale as well
Line 217 – were the models all unique?
Line 227 – the Methods part is missing references to programs/packages that were used for the models and variation partitioning

Results:
Lines 233-239 – the acronyms ‘TWI’, ‘TP5’, etc. are not defined anywhere, maybe best to mention and define the variables in the Methods (or add a table)
Line 242 – use either ‘However’ or ‘of course’ in this sentence (they give opposite impressions – was the result a surprise or expected)
Line 251 – here it’s difficult to understand if you’re talking about species or communities, rephrase
Line 278 – are these results shown somewhere?
Line 279 – better to give exactly out of how many species instead of ‘approximately half of all species’
Line 280 – there seems to be something missing in this sentence or the parentheses are in the wrong spot? Also the values inside the parentheses imply that morphometric predictors explained more, but the start of the paragraph implies that it’s about the opposite result?
Line 294 – remove ‘coarseand’
Line 296 – use ‘and are relatively weakly correlated’
Line 297 – not clear from this sentence what the percentages mean

Discussion:
Lines 315-316 – rephrase to make it easier to understand, e.g. ‘Fine-scale topography, especially soil properties (EIV Moisture,…) predicted community attributes better than species distributions’
Line 325 – maybe mention the scale in meters here again, since ‘macro-topographic’ can be used for very large scales as well
Lines 328-334 – unclear if this reasoning is based on the current study or previous findings? could the results be linked to previous findings here (currently reads a lot like results)
Line 344 – could this be related to climate change impacts as well, which is a focus in the Introduction
Lines 370-382 – perhaps this could be linked to previous results as well, are similar results found for same indices?
Line 399 – from Methods I got the impression that elevation and topography were included in the same models and then variation partitioning was used? If that was not the case then this needs to be clearly mentioned in the Methods that elevation had a separate model
Line 417 – is this true for the fine-scale or coarse-scale topography?

Supplementary materials S3 and S4 are not referenced in the text.

Table 1:
Explain also ‘CM’ acronym in the table header.
CM values should have units added.
I understand from this table, that CM values were taken from previous study? Clarify this in the Methods section.

Figure 1:
Define TPI, VRM and TRI or write them out in the figure description.
Line 679 – maybe use ‘indicate the resolution in meters’

Figure 1:
I’m not sure, but would it make sense to add the explained variation of elevation on the figure as well? I guess it would be a straight line (if there as a single resolution for elevation), but maybe it would be nice to compare the elevation and topography results. If this is not possible or accurate to include in the single figure, please ignore my comment.
Use ‘Hill Shadeness’.
I count here 14 parameters, but in the text it’s mentioned 13. Is slope separate? Add info in the Methods how slope was estimated, and when it was included in the models.

Figure 3:
Fix typos in the figure – use ‘Succulency’, ‘Leaf Nitrogen’
Explain acronyms ‘EIV’ and ‘CM’ in the figure description.

Figure 4:
Line 698 – which five variables? or was it different combinations?

I reviewed the manuscript ‘Limited impact of microtopography on alpine plant distribution’ submitted to publication in Ecography. The authors explore if topography (and if fine- or coarse-scale) or elevation determine alpine species distribution and community attributes using extensive data from Austrian Alps. They find that coarse-scale topography and even more elevation determines species distribution in these regions that has important implications for climate warming and local species extinctions. This is an interesting study and very well executed. I have a few general comments and some minor suggestions to further improve the manuscript. The manuscript file had no line numbers, but hopefully the authors are able to link my comments and suggestions to the text.

1. It’s a bit unclear why the second hypothesis (comparison of community attributes and individual species) is stated in this study if the current study cannot test it (because it’s not possible to accurately compare logistic and Gaussian models as stated in the results and discussion). Or maybe it’s worth to compare the results without directly comparing the R2 values – e.g. elevation explained community attributes ~4 times better than morphometric variables, whereas elevation and morphometry had similar explanatory power for individual species; which factors were similar or different for explaining species distributions or community metrics?
2. Perhaps mention somewhere in the Methods or Results section if the quadratic term was in fact useful (was it included in the best models)?

Introduction:
Page 3 – the dark diversity idea is highlighted here, but not mentioned again later. Could this be linked to some results in the Discussion?

Material and methods:
Page 4 – add information about the size of the cells earlier in the text (when first mentioning it ‘computed from 3x3 and 99x99-cell neighbourhoods…’)
Page 4 – was the Potential Incoming Solar Radiation also for year 2020 and from the same source as NDVI (currently unclear)?
Page 4 – use ‘approx. 3 m for the remaining ones’
Page 6 (last line) – maybe clarify that ‘resulting in total of 19,669 models…’

Results:
Page 8 (first paragraph) – missing ‘%’ sign when describing fine-scale results for TR3
Pages 8-9 – when describing the results shown on Fig. 1, it’s difficult to follow since the text uses acronyms, but the figure has the factor name fully written out. Maybe add acronyms also to the figure (in parentheses after the full term), or use full terms in the text as well.
Page 9 (first paragraph of the section ‘Models using combinations…’) – it’s mentioned that 56 out of 79 species were better explained by coarse-scale variables, but according to Fig. 2 there are 53 (vs. 26 where it’s opposite). However, in Appendix S2A there are a total of 80 species (not 79), please revise the species numbers.

Discussion:
Page 13 (last paragraph) – better to use ‘reduce both the area and the connectivity…’
Page 14 (paragraph before the Significance statement) – I wander if the results could be explained a bit clearer here without using the ‘EIV’ which is a methodological detail; currently unclear what the ‘Its’ refers to in the second sentence (rephrase)

Table 1:
Use same formatting for units throughout (i.e. ‘-2’ as superscript or not, space around ‘x’ or not).
For SLA, max value is smaller than min value, revise.

Figure 2:
Consider adding labels a) and b) to the panels (and when explaining the figure) to make it easier to follow.

Figure 4:
Maybe use just ‘Community attributes’ in the lower row figures label, since the x and y axis titles already mention ‘variation’.