There is a need for assessing past forest cover change from pollen regionally and the REVEALS model requiring knowledge on pollen productivity may not be the method of choice where that information is lacking or incomplete. Thus it is useful to explore other avenues and the manuscript by Sweeney et al. does that. It also adds interesting comparisons between the European estimates produced applying the REVEALS model and the modern analogue technique. While I welcome the attempt of applying a regression, I have my doubts on the choice of predictor variables. The authors should demonstrate how % needle leave and the Shannon index improve a regression model for overall tree cover. I can see how elevation improves the model in the current situation but have my doubt that this variable will improve past reconstructions. Instead using information on over and underrepresented pollen could perhaps make this a real winner. It is also not clear to me in which way this regression model improves upon the modern analogue technique requiring the same input information and seemingly yielding a similar performance. The manuscript is not explaining how the proposed regression model reduces the bias of simply using arboreal percentage, which may be dominated by pine and birch versus elm and lime. 

My second concern with the manuscript is the lack of appropriate recognition and citation of databases and initiatives that collected and curated the pollen data used here. Most of the modern and downcore pollen data used here was initially made available by the EPD/Neotoma or PANGAEA with a cc by 4 license requiring attribution and citation of this initial data release. Please see the recent discussion of the manuscript by Schild et al. (https://essd.copernicus.org/preprints/essd-2023-486/#discussion). 

Specific comments

L. 57: The LRA includes local reconstructions (LOVE) which has not been applied on the European scale. Only the REVEALS model was used.

L. 58: You should cite Zanon et al. (2018) already here.

L. 63: The main focus was on reconstructing the proportion of open versus forest land cover. 

L. 65: As an introductory overview this is almost too detailed while it is lacking studies to work as a good review of all that has come before: e.g. Pirzamanbein et al. (2014, Ecological Complexity), Roberts et al. (2018) Scientific Reports 8:716. Some of these appear in the discussion, but it would be good to mention them here already.

L. 80: Fall speeds are not the major issue as they can be estimated based on pollen size. 

L. 86: Since you mention PFTs you may want to include Davis et al. (2015) here already not only in the discussion. 

L. 115: The SPECIAL Modern Pollen Dataset (Villegas-Diaz and Harrison, 2022) compiles samples from other data sources including Neotoma and PANGAEA which also have a CC-BY-4.0 license, hence you need to cite or acknowledge the original data source not just the data compilation.

L. 116: SMPDS needs to be introduced. It is not clear from the above that this refers to the surface sample data.

L. 119: Particularly where core tops were used thus assumption is daring. 

L. 122: Give a brief motivation not just a reference. 

L. 122-124: Here you are referring to surface samples, core tops or Holocene records?

L. 126: So you include small bogs but exclude large bogs? I cannot find this constraint discussed in Githumbi et al. (2022).

L. 135: It would be useful to mention what is included in shrub pollen: Are you including dwarf shrubs like Calluna or rather taller perennial woody plants like Corylus and Juniperus?

L. 139: How did you deal with situations where alien tree plantations make up most forest cover: e.g. Eucalyptus. Also plantations of Pseudotsuga (0.83 million ha in Europe) may be a potential problem. 

L. 140: Large proportions of Cyperaceae and Polypodiales are limited to bogs, excluding them would reduce the biases from including bog samples. 

L. 145: It would be good if you mentioned here the range of resulting source areas considered. 

L. 153: What do you mean by “non-natural vegetation” here?

L. 154: How many from bogs?

L. 156: The same problem of attribution applies to the SPECIAL-EPD. Please cite and acknowledge the EPD. See https://www.neotomadb.org/data/data-use-and-embargo-policy 

L. 167ff: I like the idea, but am skeptical about the predictors used. Rather than using % needleleaf, it would have been better to classify the pollen types according to high mid and low pollen producing plants. Needleleaf trees include the high pollen producing Pines and low producing Larix (or Pseudotsuga). I am not sure elevation is a good predictor when thinking about the past as vegetation belts moved up and down the mountains during the Holocene. I would perhaps rather limit the inclusion of modern and fossil sites to below 500 m. I don’t understand the need of including the Shannon Index, particularly I don’t understand the provided motivation. 

L. 233ff: We know that % tree pollen is a strong predictor of forest cover without any transformation so it would be useful to compare the model performance to the performance of a simple regression model of % tree and shrub pollen (depending on what is in the shrubs) versus forest cover.

L. 233: The negative correlation between %needleleaf and tree cover is interesting and unexpected. Could that be due to frequent Pine pollen in generally open areas. Picea pollen should however correlate with high tree cover. 

L. 258: The overestimation of tree cover in northern Scandinavia is interesting and expected as pollen productivity is lower. This is also the case for higher elevations, which is why elevation is a good covariable for the present, but this relationship may not hold true in the past where temperature changes resulted in changing pollen productivities in the mountains. 

L. 330: The difference in tree cover between the reconstructions for the last 1000 years and the early Holocene is intriguing. As Zanon et al (2018) and Serge et al (2023) use completely different methodologies, but show the same trend, my initial response would be to trust them more, even if the absolute modern cover is off for both. Here it would be interesting to explore the reasons for the deviations of the current study. Could one reason be the separation of shrub pollen from tree pollen? 

L. 341: Please see the recent manuscript by Schild et al. (https://essd.copernicus.org/preprints/essd-2023-486/#discussion ) who argue that the REVEALS method underestimates the forest cover. If that would be true then your new method would perform worse as it scores below the REVEALS estimates. If you argue that forest cover was generally lower then it would be useful to find supporting evidence and make that a point of discussion.

L. 421: The main deforestation of Northwestern Europe took place during the Bronze Age and Medieval period leading to an all-time low around 1800 (see e.g. Bradshaw and Sykes 2014 Ecosystem Dynamics, Wiley). 

Sweeney et al. present a new, simplified approach for deriving tree cover estimates from fossil pollen compositional data. The authors apply this approach to selected pollen records in Europe to reconstruct tree cover changes throughout the Holocene. They compare their results to similar previous studies that used different approaches, and discuss the new approach, recommending it for application in future studies in other regions or on a global scale. The manuscript is well written, and, especially important for a study focused on presenting such a new modeling approach, outlines the methods very clearly and understandably. With its interesting approach to understanding tree cover changes through time and a discussion-based nature, it fits within the scope of Biogeosciences. I would suggest the acceptance of this study after minor revisions, related mostly to the structure of the manuscript.

Specific comments

“Forest cover” and “tree cover” from my point of view may not always refer to the same aspect. In the title, forest cover is mentioned, but throughout the manuscript the focus lies rather on tree cover. I suggest sticking to only one of these terms and including a brief definition in the introduction or methods section.

While reading the results section, I was sometimes wondering if I had unknowingly entered the discussion (e.g., in L345 onwards) – I think in this case it may be acceptable to have some level of discussion within the results section in this style of manuscript, since it relies heavily on comparisons to previous, similar studies. However, maybe the writing style could be adapted to better differentiate the two sections.

The supplement to this manuscript provides very relevant information, especially if a reproduction of the approach is wished, and seems well-organized. However, I would suggest the inclusion of some of the spatially plotted model results also in the main manuscript. Some patterns across Europe are described in the results and discussion sections, and having some of the time-slice plots close by would be very helpful (e.g., one each from the early, mid, and late Holocene, referring to the full range of plots in the supplement, or what may fit best to your discussion).

Technical comments

• L16: Not sure if “Earth System” needs to be written in capitals
• L29: Re-phrase this section as it is a bit repetitive (“[…] our approach […] provides a better approach […]”)
• L45: This may be purely subjective, but I’d suggest to use long-dashes when writing ranges
• L50: When saying that something is commonly done, I expected to find some references at the end of the statement
• L70: Re-phrase to make clear that n=46 is the total amount of taxa and not the additional amount of taxa
• L91: Suggest to standardize across the manuscript the way such lists are written using comma and only a single final “and” (e.g., “[…] data on tree cover, harmonized age models, and improved information […]”; similar cases e.g. in L181, L223)
• L126: Standardize the use of spaces before writing units across the manuscript (e.g., different way can be found in L219 – personally, I prefer the use of spaces)
• Figure 2A: Suggest to add either “%” next to the legend, or otherwise state in the caption that it depicts relative data
• L198: I was not sure who “they indicate” was – is that information from the cited study, or personal communication with the authors?
• L266: Dot missing in reference
• L288: Comma or other separator missing in the R package citation
• L324: Suggest to change “somewhat” to “slightly” and maybe separate this into two sentences
• L437: I think there’s an “as” missing in “such how”