General Comments

The authours present an interesting test of the intermediate productivity aridity hypothesis. I quite like the combined use of clay / phytoclasts / charcoal as multiple lines of evidence to address their objectives. Overall, I enjoyed the reading manuscript and was interested in the authours’ findings. Thank you to the authours for sharing!

Their link with grasses is interesting though potentially not hugely important for the conclusions. It is evident from your results that sufficient fuels existed to support fire, and I assume that some analogous fuel existed that served a similar role then that grass does today. I was a bit disappointed not to see a stronger link with grasses as a specific pyrophylic biome component and fuel, as it is one of the pieces in the abstract that made me interested to read more. I may be missing an important point, and if I am I encourage you to add more information in your introduction to set readers like me up to understand your point about grasses. Perhaps it is that biomes that contain grass serve as the basis for the intermediate productivity hypothesis and without them the hypothesis should fall apart. Currently it reads that grasses are important for current global fire patterns, and then there is not much direct follow-up. Please clarify this argument.

You discuss charcoal largely in terms of overall abundance. Given that you consider fine and coarse charcoal, would it be possible to do any sort of discussion on fire intensity? E.g., greater coarse charcoal has been linked to larger more intense fire activity that generated sufficient convective energy to distribute larger particles. My experience is more with lakes and this may not translate to your system. But if it is possible it might be an interesting addition to discussion or future work. Perhaps you will see more or less intensity along the productivity-aridity gradient?

Specific Comments

The methods are generally intuitive as written. I had one major point of confusion: the number of samples taken and used for each analysis in each period was unclear. I suggest that you make a table showing these numbers explicitly. It would support the methods and support the reader in interpreting your results from SBP and LPE, which had different resolutions.

The results are fair as written. I have three suggestions: 1) I find it difficult to follow and be confident in your conclusions about terrestrial phytoclasts and charcoal particles given visual analysis alone. I see the importance for your conclusions that charcoal not be related to terrestrial inputs. I suggest that you demonstrate this relationship (or non relationship as you suggest) by some formal statistical test, perhaps a Mann-Kendall test. 2) I suspect that Fig 4 is unnecessary, and I suggest that you remove it given that you do not refer to it in text (I checked with a search) and one could reasonably be expected to understand these distributions from Fig 2/3. If you want to keep Fig 4 I suggest you expand your discussion of micro- vs macro-charcoal partitioning and how that may be associated with fire intensity (which I think would be very interesting but may not be within your intended scope). 3) Fig 1 is difficult to read given its current size. I suggest that you either stack panel d below the other panels to allow all to be larger, or rotate the table to allow it to be larger. 4) Figure 1 and 5 do not work well with black/white printing or for folks who struggle to differentiate colours. Consider differentiating with shape or texture rather than colour.

Technical Corrections

1. Please include the methods you used to generate SI Fig 3 in methods.
2. The caption on SI Fig 3 is confusing, please edit for clarity.
3. Please see attached highlights/comments

General comments:

This is a nice demonstration of the utility of the geological record for testing a hypothesis about fire occurrence that is relevant for explaining both the present-day distribution of fire as well as the response of fire to future climate changes.  Overall, the manuscript is in good shape, but there are a few concepts or ideas that could be amplified or discussed more.

First, what attributes of fire are being recorded here? It’s long been a goal of what we might call “Quaternary paleofire” studies to separate the effects of fire frequency and fire magnitude, including severity and area burned, but there seems to be little consensus there, any many studies simply fall back to using “fire activity” as a not totally ambiguous descriptor. In high (cm-scale) resolution lake records, peaks in charcoal are generally thought of as individual fires within the catchment of a lake, distinct from background levels related to extra-local fires and the general level of biomass burning in a region, with the magnitude of the peaks providing some kind of index of fire severity. The record here probably represents more of a regional index, which in Quaternary studies are often shown as smooth composite curves constructed using multiple records in a region, with the composite curve usually interpreted as a measure of area burned. It would be good to discuss a little what particular attributes of fire the charcoal represents (i.e. not individual fires, more likely regional biomass-burning levels), and to explicitly state what is meant by the term “fire activity”. (More discussion can be found in Marlon, 2020, Quaternary Research doi:10.1017/qua.2020.48.)

Second, the “intermediate-productivity gradient hypothesis” of Pausas abd Bradstock (2007) was orignially proposed and tested in an environment where vegetation productivity was clearly and solely linked to the moisture gradient. Pausas and Ribeiro’s (2013) extension of the idea to the globe, while still focused on productivity as represented by NPP, relates NPP to temperature, and Daniau et al. (2012) show that fire activity, in both charcoal records from the LGM to present, and in satellite remote-sensing data, depends not only on effective moisture, but also temperature. Temperature is often invoked in the discussion to explain features in the sedimentary record and paleoclimate in general, so it would be good to do two things: 1) discuss the idea that the productivity gradient isn’t strictly related to effective moisture, and also 2) discuss the paleoclimatic setting of the record (and why temperature is also a useful variable for explaining the record).

Third, throughout the manuscript the term “seasonal climate” is used in a casual way. Not until line 328 is it clear that it’s a seasonal contrast in effective moisture that is being emphasized, but orbitally related changes in the annual cycle of temperature are also important particularly in mid-latitude, mid-continental regions. So it would be good to be more explicit, and avoid terms like “seasonal climate”.

Specific/Technical Comments:

Throughout:  Hyphenate compound words, e.g. “Present-day” (line 19), “fuel-moisture status (line 27).

Line 21: Replace “whereas” with “where”.

Line 31: Replace “heightened” with “greater”.

Line 31:  Seasonality of what?  Moisture? Temperature?

Line 34-35: “… more pronounced seasonality during eccentricity maxima, explained by the overall cooler climate …” This implies to me that indeed there is some dependence upon temperature.

Line 47: “Shifts” implies to me a change in distribution or pattern.  Change to “… explain changes in biomass abundance, moisture availability, and fire frequency or magnitude.”?

Line 53: “productivity limited (minima) and the optimum fire-window (maxima)”  Reverse the order.  The modes are minima or maxima, the explanations are productivity limitation or not.

Line 67: Replace “ingredients” with “determinants”.

Line 67-68: This might be a good point to add an in-line definition of “fire regime”.

Line 68-69: “high moisture and biomass production, for example in tropical rainforests.”  It’s likely that temperature as well as moisture is responsible for high productivity in tropical climates.  But how does high biomass productivity limit fire?

Line 76: Replace “lowers” with “decreases”.

Line 84: I’m not sure “biases” is the right word because it implies that the optimum would occur somewhere else along a moisture gradient owing to the influence of grassland fires. That it doesn’t is basically the take-home message of the paper. So maybe grassland fires “reinforce” the generalizations?

Line 109 (Fig. 1): Explcitly label the SPB and LPE intervals in the figure, so it can stand alone without its legend.

Line 110: Define “mbs” here (as well as on Line 130).

Line 116: “Orbital filters of the 100 kyr and 405 kyr cycle based on the Ca and Ti elemental records in

the depth domain from Ruhl et al. (2016).” I see bandpass filtered time series for the Ca record in Rohl et al. (2016), but not for Ti. Also, you’re confusing the bandpass filter with the filtered time series. “Orbital filters” is jargon in this context.

Lines 155-156: I’m not sure I understand the sample counts here.  Should one of the “macrocharcoal”s be replaced by “microcharcoal”?

Line 193: “a syringe following Stokes [sic] law…” Replace with “a syringe (following Stokes’ law).

Lines 207-211: This paragraph confused me at first. I think it should be reorganized to describe the stratigraphy of the whole core first, then that of the two intervals analyzed in detail here.

Lines 212-213: “we compare the charcoal and clay records visually with the 100 kyr and 405 kyr filters based on Cabe and Ti…” Do you mean you compared the charcoal and clay records with the filtered Ca and Ti records?

Line 230: “… with bundling of peaks ever ~4-5 m.” I’m not sure I see that, but ok.

Line 233: “… in the context of the orbital filters” See earlier comment—“orbital filters” is jargon.  Also, which time series is being filtered?

Lines 235-236: “The macrocharcoal abundance shows ~5 peaks throughout the studied interval.” It would be helpful to label these. I see one peak at about 1239 m.

Line 242: “The peaks in the macrocharcoal record occur on a 100 kyr time scale.” How is this demonstrated?

Lines 244-254:  Same comments and questions as for Fig. 2.

Lines 268-272: The boxplots suggest that the charcoal data have long-tailed distributions, and that the variances of the groups differ from one another. Does this have any impact on the comparison.

Lines 314-315:  “Smectite preferentially forms under a hot and seasonally arid climate, similar to a monsoonal climate system or the winter-wet climate of the Mediterranean zone.” Because these climates differ substantially in the seasonality of moisture (hot monsoon/summer wet, Mediterranean/summer dry), it might be good emphasize just what aspect of those climates smectite reflects. (Presumably a pronounced dry season.) Also, which of the two climates are you imagining applies here?

Line 315:  What is an “accelerated hydrological cycle”?

Line 324: Again, what exactly is varying seasonally? Temperature? Moisture?

Lines 328-330: Ok, it sounds like it’s seasonality of effective moisture.

Lines 344-345: Replace “orbital filter representing the ~100 kyr cycle” with “the ~100 kyr bandpass filtered time series of [macrocharcoal?]”

Lines 374+: “… where fire activity is plotted along an aridity and productivity gradient” Although Pausas and Ribeiro (2013), for example, discuss the variations of fire activity along a productivity (NPP) gradient, Daniau et al. (2012) show that fire activity, in both charcoal records from the LGM to present and in satellite remote-sensing data, depends on both temperature and effective moisture (see also Bistinas et al., 2014, Biogeosci. doi:10.5194/bg-11-5087-2014). Because NPP or productivity is not easily reconstructable, it may be advantageous to discuss the separate and joint influence on fire of temperature and effective moisture, which can be inferred from the evidence in the paper. In fact, temperature is invoked frequently in the discussion; it’s not just moisture that explains the data.

Line 392: “hyperbola”.

Fig. 5: The tiny pictures are nice, but way too tiny.

P.J. Bartlein

General comments

The manuscript aims to test the intermediate fire productivity hypothesis based on analyses of charcoal particles, total organic matter, d13C, CaCO3 and clay mineralogy on sediments from two periods of the early Jurassic. Charcoal particles are used as a proxy of fire.

Based on my expertise (paleofire, paleoecology), I will discuss only the fire issue.

Two categories of charcoal measurements have been carried out, “macrocharcoal” based on sieving approach, and microcharcoal based on palynological slides. Technically, this reminds the methodological study by Carcaillet et al. (2001), but on different type of sediments and geological period.

I strongly recommend completing such study with SEM images of these “charcoal” extracted from these Jurassic sediments. This would be of great interest for people specialist of plant anatomy to prove that the measured charcoal was, indeed, burned plant material and not coal or any other type of artefacts. Nobody is protected from lab error. Indeed, I personally had a bad experience with one of my assistants that measured coal particles in lake sediments within a catchment area with coal. My assistant produced nice sedimentary “charcoal” series; fortunately, a second assistant worked in parallel on these sediments on other proxies and indicated me that he never observed charcoal in these sediments, but he found abundant coal fragments. After cross-verification, the second assistant was right. In such old material, I absolutely need images (and why not cross-verification with another lab, abroad, with no conflict of interest), to verify and validate the charcoal report.

If charcoal identification is validated with an independent lab, this study of sedimentary charcoal during the Jurassic, would be a great finding showing that fire is a global process since millions of years, maybe since the settlements of plant fuel on terrestrial habitats as already evidenced by Glasspool and co-workers (2004).

The first problem is less the quantification method than the use of data. Indeed, to reconstruct fire history, whatever the fire intervals/frequency or the fire severity, a solid chronology is absolutely needed to transform charcoal concentration in terms of accumulation rate (or influx). Same charcoal concentration can result different charcoal influx according to differences in sedimentation time inferred from measured chronology, and vice versa, different charcoal concentration can correspond to the same charcoal influx. Second, in international high-profile paleo-fire paper, no one uses today charcoal series without decomposing the time series to detect charcoal peaks to determine the fire intervals and thus the fire frequency, and to eventually assess changes in fire severity thanks to magnitude of charcoal peaks (see for instance Higuera 2006 or Blarquez et al. 2013 or also Higuera 2009).

Additionally, this study does not contain any statistics. It is not acceptable to read such a manuscript whose interpretation is completely intuitive. For example, a Wilcoxon test is a prerequisite for analysing the boxplots in Figure 4. Such a boxplot could be complemented by a kernel density which could be useful for detecting data distribution patterns. It is astonishing that this text is so intuitive (cf. L 270 or LL 301-304). Also, LL 304-307 mentions comparisons of means, even though no statistics have been carried out and the data are not illustrated.

Generally, the authors speculate on the interactions between bio- and geo-proxies, sometimes indicating correlations (r-values) associated with p-values, when a simple principal component analysis (PCA) would have been very efficient if carried out as a preliminary analysis. to make a solid descriptive statistic of the environmental data (all proxies) to clearly distinguish those that exhibit the same behaviour (correlated or anti-correlated) from those that have no links. With such a PCA, the authors would have interpreted their data based on a good methodology allowing a rational sedimentological interpretation (e.g., Clark-Wolf et al. 2023). Such a basic strategy should avoid “visual comparison” of data (L. 212) and speculation (the entire manuscript). I am not sure r (linear correlation coefficient) is appropriate. I would have used the coefficient of determination (r2) (LL261-264).

LL 81-83: I partly disagree with the assertion that “high fire activity in ecosystems (…) is strongly driven by grass biomes”. Archibald et al. 2018 is cited. This a very good paper, but many papers demonstrated that it is not grass component of the ecosystem that drive high biomass burning or fire risk but an intermediate tree-cover (Archibald et al. 2009; Frejaville et al. 2016; Aleman et al. 2017), which increases the ETP, then dryness, and finally the development of grass cover in the understorey. Grass cover is a secondary process, but the main process is the intermediate tree-cover, which can be sustained by wildfires resulting a feedback-loop.

If charcoals are well reported, this study is interesting evidencing the occurrence of wildfires during early times of the Earth. However, with these strong criticisms, I cannot be positive about this obsolete study. The discussion of fire and ecosystem functioning is pure speculation based on irrelevant findings on fire due to a methodological flaw. Biogeoscience is a top international journal that should not publish such a manuscript.

References

Aleman, J. C. et al. Tree cover in Central Africa: determinants and sensitivity under contrasted scenarios of global change. Sci. Rep. 7, 41393; doi: 10.1038/srep41393 (2017).

Archibald, S., Roy, D.P., Van Wilgen, B.W. & Scholes, R.J. (2009) What limits fire? An examination of drivers of burnt area in southern Africa. Global Change Biology, 15, 613–630.

Blarquez O., Girardin M.P., Leys B., Ali A.A., Aleman J.C., Bergeron Y., Carcaillet C. (2013) Paleofire reconstruction based on an ensemble-member strategy applied to sedimentary charcoal. Geophysical Research Letters 40, 2667-2672   doi:10.1002/grl.50504

Carcaillet C., Bouvier M., Fréchette B., Larouche A.C. & Richard P.J.H. (2001) Comparison of pollen-slide and sieving methods in lacustrine charcoal analyses for local and regional fire history. The Holocene 11, 467-476.

Clark-Wolf KD, Higuera PE, McLauchlan KK, Shuman BN, Parish MC (2023) Fire-regime variability and ecosystem resilience over four millennia in a Rocky Mountain subalpine watershed. Journal of Ecology, https://doi.org/10.1111/1365-2745.14201

Frejaville, T., Curt, T., & Carcaillet, C. (2016). Tree cover and seasonal precipitation drive understorey flammability in alpine mountain forests. Journal of Biogeography, 43, 1869–1880. https://doi.org/10.1111/jbi.12745

Glasspool, I.J., D. Edwards, and L. Axe. 2004. Charcoal in the silurian as evidence 785 for the earliest wildfire. Geology 32 (5): 381. https://doi.org/10.1130/G20363.1

Higuera, P. (2006). Detecting changes in fire-frequency regimes: Sample size & statistical power. In Late Glacial and Holocene Fire History in the Southcentral Brooks Range, Alaska: Direct and Indirect Impacts of Climatic Change on Fire Regimes (pp. 154–171). University of Washington

Higuera, P. (2009). CharAnalysis 0.9: Diagnostic and analytical tools for sedimentcharcoal analysis. User’s Guide, Montana State University, Bozeman, MT. www.montana.edu/phiguera