the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 11 Aug 2025
Peat-DBase v.1: A Compiled Database of Global Peat Depth Measurements
Abstract. Peatlands are globally important carbon stores that face increasing threats from human activities and climate change impacts. Comprehensive peatland data are essential for understanding ecosystem responses to these stressors and mapping their past and current characteristics. Current peatland datasets remain limited due to poor representation in global soil mapping initiatives and the absence of a recognized, coordinated central repository for peat depth data. Existing compilations often contain errors, duplicates, and outdated observations, requiring researchers to repeatedly gather and harmonize data on a study-by-study basis. To address these challenges, we present Peat-DBase version 1.0—a harmonized, quality-controlled global compilation of basal peat depth measurements.
Version 1.0 of Peat-DBase comprises 204,902 peat depth measurements from 29 sources spanning 54.933° S to 82.217° N, with a significant proportion of measurements in Atlantic Canada and Scotland due to the inclusion of two particularly large datasets focused on those regions. We supplement the peat study measurements with 94,615 non-peat soil measurements to ensure comprehensive coverage consistent with the relatively low spatial coverage of peatlands globally. Despite the uneven distribution of peat depth measurements, Peat-DBase contains reasonable coverage of the major global peatland complexes in temperate and boreal North America and Europe, portions of Russia, the Amazon and Congo basins, and the Malay Archipelago, though gaps remain in the lower Amazon Basin, Eastern Indonesia, and Eastern Russia. From the current data, peat depths average 144 cm, although this is influenced by a predominance of measurements in the North Atlantic regions. Peat-DBase's deepest measurement is 3,527 cm.
While sampling biases and measurement uncertainties exist, Peat-DBase provides an essential foundation for global peatland research. Peat-DBase is under active development and future versions will incorporate additional datasets, information on current peatland status, and improved positional uncertainty quantification. Peat-DBase eliminates the need for overlapping data compilation efforts while identifying critical observational gaps for future research. Peat-DBase is available at https://doi.org/10.5281/zenodo.15530645.
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Status: open (until 11 Nov 2025)
- CC1: 'Comment on essd-2025-432', Julie Loisel, 13 Oct 2025 reply
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RC1: 'Comment on essd-2025-432', Steve Frolking, 23 Oct 2025
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This manuscript presents a new public data set of global peatland depths, compiled from published literature, national or regional datasets, and some unpublished data. This is an important new data set for global carbon cycle assessments and earth system modeling activities. ESSD is an appropriate journal outlet. The paper is very well written.
I have no major questions/issues with the manuscript. All of my comments and questions below are minor ones.
Line 60: ‘often contain errors’ seems a bit harsh for a ubiquitous problem. maybe just ‘can contain errors’?
Line 61: ‘outdated measurements’: I don’t know what this means.
Line 68: Not sure if this is necessary, but it might be worth noting that most land-surface models need peat depth data for initiation as they do not simulate the multiple millennia needed to accumulate the peat, and the peat stocks are not necessarily in equilibrium. They cannot be ‘spun up’ to an equilibrium state.
In Fig. 1, step 1 is to ‘confirm basal depths’. To me this implies confirm that the values are correct (how?) but maybe it means ‘confirm reported peat depths are basal’? Also, step 3 includes ‘remove unnecessary information’, which makes sense. In the best of all possible data worlds, it would be easy to align Peat-DBase data with other data sets (e.g., one of basal ages, or one of age-depth profiles). The burden of creating this best-of-all-possible-worlds shouldn’t fall on you, but it seems to me that it must be something you have thought about. Would any of this ‘unnecessary data’ be useful in this regard? Would that introduce uncertainties that you don’t want to (and shouldn’t be expected to) have to manage? Could this be discussed in the ‘future work’ section, perhaps identified as ‘future work for the community to move the field forward', not specifically as future work for Peat-DBase and this manuscript’s authors.
Line 125: are some of the peat depth data in the ocean from Treat et al. 2019, which included coastal shelf peatland data from the last glacial? If so, these are not in error, just not relevant for Peat-Dbase. Also, there is not universal agreement on where the land ocean boundary is, and it certainly depends on spatial resolution.
Table 2. ‘depth_cm’: is that reported to any particular significant figure? nearest integer cm?
Table 2 and elsewhere: for the sample duplication flag, one data sample is the ‘first instance’. How is this selected/determined: earliest published, first that you acquired, first that you entered, ...? It likely doesn’t matter in terms of the database, but it would be good to explain what you mean by ‘first instance’ as priority in time is an important currency in academic publication.
Fig. 3 caption: Bin sizes are 3° in longitude; how many in latitude?
Line 213: ‘enhanced growth, stagnation, or erosion’ -- I think that ‘loss’ (i.e., from ‘excess’ decomposition, not erosion) should be added to this list.
Fig. 4 caption: it would be useful to add binning sizes (50 cm?, 1° latitude?)
Fig. 5: The color scale is not too helpful here, at least for me, as the x-axis is number of measurements. I think it would be helpful to label the bar at the top ‘zero depth’, since it doesn’t really work on the vertical log scale (I initially mis-interpreted this as the sum of all other data, but, of course, it didn’t add up). In the caption: I don’t understand why a focus on depth distributions leads you to remove data points labeled as drained or modified. Particularly since you cannot make this assessment for all data. Nonetheless, if you maintain this, I suggest adding an ‘n = NN’ in parentheses for number excluded.
More generally on the drainage/disturbance question: you say in the captions to Figs. 4 & 5 that drainage information is only available for the NatureScot dataset. How is that noted in the Peat-Dbase (it is not mentioned in Table 2)? Others may also want to make the exclusion that you did.
-Steve Frolking
Citation: https://doi.org/10.5194/essd-2025-432-RC1 -
RC2: 'Comment on essd-2025-432', Anonymous Referee #2, 27 Oct 2025
reply
Skye et al., present a timely examination of global peat depths, based on the synthesis of 25 regional/global prior syntheses. The paper presents the motivation, analysis, results, and discussion well and I have no major issues with the current manuscript. I have several minor comments, mostly focused on how to deal with the definition of “peat” and the measurement of peat depth in a “meta-synthesis” such as this paper.
In definitions of peat that include lower OM%, it is often more difficult to characterize when “basal peat” is reached as opposed to mineral soils. I agree with the author’s decision to include everything described as peat by the primary source, but I think that should be explicitly stated early on in Sec. 3.1.
Additionally, while I appreciate the inclusion of non-peat mineral soils into the database to highlight regions where peat is not found, I think one of the recent maps of peat area should be included in the main text figures. This helps to visually highlight peat-rich regions that are currently under-sampled better than simply listing a few examples in the text.
Other Minor Comments:
Line 85 – “Peat study data…” This sentence is somewhat awkwardly phrased.
Line 91 – While you discuss limitations of the dataset elsewhere, I would rephrase this sentence “until they meet a non-peat layer and cannot go any further” as probes can still penetrate non-peat sediments without meeting refusal. This is especially true of very humified, lower organic % peats which often grade into organic-rich mineral soils (i.e. humic silt sediments) found in more temperate regions.
Line 100 – Where there any systematic methods used for searching the literature for peat depths?
Figure 2a – I’m not sure why the mineral soils are plotted for the Congo region but not elsewhere? Are those wetland soils that have a mineral substrate? i.e. hydric soils?
Figure 3 – You discuss comparisons with PEATMAP in the main text (line 183). Could you add the peat map as a background to your figure on Peat-DBase data density? This would be the most “major” revision I would recommend.
Line 200 – While I agree that the source data is biased to the northern hemisphere, the overall total land area coverage of tropical peatlands is also lower than boreal peatland coverage.
Figure 5 – The color bar scale should be reduced, as currently there is not much variation in the color for each bin.
251 – This is a minor comment, but I might put this paragraph first as I think it’s the most pressing issue to resolve in future versions of the dataset.
285 – If one of the major goals was to highlight under sampled regions, then I would definitely add one of the recent peat-map areas to the map in Figure 3 as there is currently not a great way for the reader to judge visually which peat-rich areas are under sampled.
Citation: https://doi.org/10.5194/essd-2025-432-RC2
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Peat-DBase: A Compiled Database of Global Peat Depth Measurements J. Skye et al. https://zenodo.org/records/15530645
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We are a group of graduate students who have read your study with interest. For context, we discuss 1-3 scientific papers that relate to peatland dynamics weekly.
The study reads very well and is adequately referenced. We understood the context, objectives, and the flow of information was always relevant to addressing the study’s goals.
One issue that was raised regards the definition of ‘peat’. Depending on the threshold used, the peatland extent could be more than 3%. Also, we appreciate that all peat depth data are included, making the ‘peat / no-peat cutoff’ at the discretion of the user, but it could be good to explicitly state this fact in the document. In other words, maybe add a sentence to the effect that all peat depths have been included.
Based on Figure 2, it looks like the vast majority of the shallowest peats (less than 30 cm; in red on panel A) are in the Congo Basin. Are we sure that these individual points referred to ‘peat depths’ in the original paper (Crezee et al. 2022), or did the original authors include lots of points aimed at showing areas without peat? (we believe the latter is correct). We also noticed a few of those red points in the Colombian lowlands. Lastly, the reds vs. greens may not be colorblind friendly.
Data availability: we like the ease of downloading a single CSV file that contains the database and the opportunity to share new data points via the Google form.
Discussion: we appreciate the focus on peat depth alone, without trying to correlate with other predictive factors. We anticipate that future work will be based on such types of analysis, given the inclusion of the (non-peat) WoSIS data.