A new approach to experimental charcoal analyses: lessons for the Cretaceous and other time periods

doi:10.21203/rs.3.rs-5188072/v1

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A new approach to experimental charcoal analyses: lessons for the Cretaceous and other time periods

https://doi.org/10.21203/rs.3.rs-5188072/v1

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Earth’s climate has historically oscillated between climate states, with greenhouse climate periods offering valuable analogs for future climate projections. The Cretaceous period, characterized by high atmospheric CO₂ levels and the absence of polar ice caps, provides insights into potential ecological responses to anthropogenic climate change. This study presents experimental data to inform the use of sedimentary charcoal as a paleofire and palaeoecological proxy during the Cretaceous, supplementing the limitations of traditional palynological and fossil perspectives. Our experimental analysis includes 23 broadly sampled plant taxa, focusing on charcoal morphological classifications and a novel set of the following morphometric parameters: aspect ratio (L:W), rectangularity, circularity, and feret diameter. Our results reveal significant differences in charcoal morphometrics at the tissue (e.g., leaf, petiole) and component (e.g., vein, blade) levels, challenging the assumption that larger plant tissues produce relatively uniform charcoal particles. This emphasizes the need for refined morphometric techniques that consider plant tissues as an assemblage of their respective components. Our findings provide a nuanced framework that will improve the accuracy of future charcoal-based paleofire and paleoecology studies, particularly in pre-Holocene contexts, aiding predictions of future ecological dynamics under changing climate conditions.

Earth and environmental sciences/Environmental sciences

Earth and environmental sciences/Ecology

Earth and environmental sciences/Ecology/Fire ecology

Earth and environmental sciences/Climate sciences/Palaeoclimate

paleofire

paleoecology

charcoal morphometry

fire ecology

paleontology

Earth’s climate has varied substantially, with several periods in the past experiencing greenhouse climates similar to future climate projections (Scotese et al., 2021). For example, during the Cretaceous period, the Earth was in a greenhouse climatic state (Berner, 2006), characterized by atmospheric CO₂ levels at 112% of modern levels (Huber et al., 2018). However, modern anthropogenic activities are causing unprecedented and accelerated climate changes (Anderegg et al., 2010), prompting significant responses from ecological systems, including more severe and frequent forest fires, as well as shifts in plant ecological communities (McCarthy, 2001; Carvalho et al., 2011; Flannigan et al., 2000). These changes have the potential to alter species compositions, nutrient cycling, and habitat structures, thereby impacting ecosystem services such as carbon sequestration, water filtration, and biodiversity (Carvalho et al., 2011; Malhi et al., 2020; Jolly et al., 2015). Furthermore, the increased frequency and severity of forest fires can lead to substantial economic losses due to property damage, firefighting costs, and healthcare expenses from degraded air quality (Lee et al., 2015). Fire regimes and plant communities of the Cretaceous can provide insights into future ecological dynamics under changing climatic conditions (Marlon, 2020; Hay, 2011). The Cretaceous is a reasonable analog to this potential climatic state because of its high atmospheric CO₂ and lack of permanent polar ice caps, among other factors (Scotese et al., 2021; Berner, 2006; Huber et al., 2018). But it should be noted that the Cretaceous is not a perfect analog because of stark differences in ocean circulation mechanisms (Hay, 2008), as well, the role of anthropogenic activities being exclusive to modern times. To better understand the mechanisms driving fire in greenhouse climate states and conditions, comprehensive examination of paleoecological records from analogous periods like the Cretaceous are needed.

Paleoecological reconstructions allow us to understand how ecological communities respond to climate changes, with each proxy having benefits and biases. Paleofire records provide a useful means of assessing fire-climate relationships as well as informing predictions of how fire will respond to changing climate scenarios (Marlon, 2020; Whitlock et al., 2010; Sayedi et al., 2024; Conedera et al., 2009). Palynological records and macrofossil records have been traditionally used to assess ecological shifts and plant community dynamics (Braman and Koppelhus, 2005; Webb III et al., 1981). Sedimentary charcoal can be used as a proxy for both paleofire reconstruction and ecological analysis (Brown et al., 2023). The proxy is independent from many biases that persist in the palynological and fossil records (Adrian and Westrop, 2003), such as an overrepresentation of angiosperm pollen and an underrepresentation of fern spores (Harris, 1981; Crane et al., 1995 Braman and Koppelhus, 2005)). These biases are preservational; each proxy provides limited perspectives on their respective ecosystems (Adrian and Westrop, 2003; Ferguson, 1985).

Although much research has developed paleofire methods (Conedera et al., 2009; Remy et al., 2018), the bulk of this work has focused on the Holocene (Power et al., 2010). The climate of the Holocene was relatively cold (as compared to a greenhouse climate) in the context of geologic time (Willis and MacDonald, 2011), meaning that the research methods developed within this field are predominantly applicable to climatically cool deciduous and boreal forests (Leys et al., 2018; Rehn et al., 2021; Vachula et al., 2024); not the tropical/subtropical forests as would have dominated climatically hot periods (Levin and King, 2016). Therefore, much of the interpretation-focused, charcoal-based paleofire research is not directly applicable to deeper geologic time scales (Crawford et al., 2018). To apply paleofire methodology to new ecosystems, it is necessary to undertake experimental proxy calibration (Leys et al., 2018; Rehn et al., 2021; Blarquez et al., 2013).

Charcoal morphology and morphometry are two common paleofire methods. Both techniques focus on the classification and quantification of macroscopic (> 125 µm charcoal)(Vachula, 2019) particles isolated from sediment samples (Crawford et al., 2018), sediment cores (Feurdean et al., 2022), or experimental charcoal samples (Vachula et al., 2024). Charcoal morphology refers to the practice of classifying individual particles based on qualitative shape and structure characteristics, whereas morphometry refers to the practice of measuring physical variables of particles (e.g., L:W, rectangularity, etc.) (Vachula et al., 2021). Morphology provides inferences on fuel type, fire extent, and combustion temperature (Enache and Cumming, 2006; 2009). Morphometry can provide perspective on fuel type, burn temperature, and taxonomic classification (Feurdean, 2021; Feurdean et al., 2023).

Previous studies have used experimental charcoal production of known plants to inform the interpretation of charcoal particles found in sediments samples. These studies have focused their experimental burns on individual plant tissues (leaf, needle, etc.) (Feurdean, 2021; Vachula et al., 2024). Previous morphometric studies have been primarily focused on one measured variable, aspect ratio (L:W)(Vachula et al., 2021; 2024; Crawford and Belcher, 2014; Ogura, 2007; Pereboom et al., 2020; Umbanhowar and McGrath, 1998; Zhang and Lu, 2005; Li et al, 2019; Feurdean 2021; Feurdean et al., 2023). This variable has shown reliable accuracy in fuel type delineation, specifically in identification of graminoid fuels (Feurdean, 2021). A guiding framework was developed by Vachula et al. (2021) that values over 3.5 L:W indicate graminoid/herbaceous material while values less than 2.5 correspond to woody fuels. In addition to L:W values, other morphometrics such as rectangularity, circularity, and particle size (feret diameter) have shown promise in paleoecological research (Frank-DePue et al., 2022; Vachula et al., 2024), but have not been examined in great detail.

This paper presents a modern case study and experimental proof-of-concept for the application of sedimentary charcoal morphometry analyses to Cretaceous sediments. We conducted an extensive experimental charcoal production analysis, focusing on sub-tropical trees, ferns, and aquatic plants that have all been historically underrepresented in Holocene focused studies and are more relevant to the Cretaceous period (and other greenhouse climates) than those traditionally tested. This experiment included 23 taxa and quantified several novel morphometrics (rectangularity, circularity, and feret diameter) to explore diverse ways of differentiating charcoal particulates by source fuel. We also conducted novel dissections of plant tissue components (e.g., leaf vein, leaf petiole, etc.) to a finer scale than previous studies. And the results of burning these dissections shed light on the cause of charcoal morphological and morphometric variations. Last, we contextualize our results for fuel type delineation in subtropical ecosystems relevant to the Cretaceous period and other deep time contexts.

2.1 Sample Collection and Preparation

We collected samples of 23 plant species ranging in mass from 25–50 g each. Samples were obtained from the John D. Freeman Herbarium at Auburn University (n = 13), the Donald E. Davis Arboretum at Auburn University (n = 4), and the Graham Creek Nature Preserve in Foley, Alabama (n = 6). Samples were air dried for a minimum of 7 days prior to analysis.

Classification of the collected plant taxa was facilitated using the USDA PLANTS database (https://plants.usda.gov/home), wherein each taxon was assigned to specific plant groups (e.g., angiosperm, gymnosperm) and growth habits (e.g., fern, shrub, tree). The PLANTS database separates trees from shrubs on the basis of single (trees) vs. multiple (shrubs) stems and heights greater than 4 to 5 m. Sub-shrubs are differentiated from shrubs on the basis of heights less than 1 m. These classifications, though not absolute, align with established conventions and provide an impartial framework for growth habit categorization (Vachula et al. 2021).

In total, the 23 plant taxa were divided into 42 tissue samples, as outlined in Table 1. Five taxa (Table 2), were chosen to fully represent the dataset (Table 1) and were dissected to examine the influence of specific plant component tissues on measured variables. The selected taxa represented eudicots (n = 3), ferns (n = 1), and gymnosperms (n = 1). Each of the 5 selected taxa were dried and then dissected using a razor blade. The tissues we isolated for each sample were leaf blade, leaf vein, leaf petiole (when available), stem pith, and stem phloem. Leaf veins were sourced by dissecting the central vein from a leaf sample leaving behind the blade component. When available, petiole components were sourced by cutting the component off the rest of the leaf sample at the point of contact with the blade/vein components. Stem pith components were retrieved by peeling the outer bark of the stem off. Stem phloem components were sourced from the remaining inner bark complex. We acknowledge the complexity of this structure but for simplicity’s sake we will henceforth refer to this component as “phloem”.

Table 1

Experimental charcoal results for plants and their tissues analyzed in this study.
Species Name	Common Name	Tissue	Plant Group	Growth Habit	AR Median ± σ	Median Rectangularity	Median Circularity	Median Feret Diameter
Trapa natans	Water Caltrop	Leaf	Eudicot	F/H	2.03 ± 1.33	1.14 ± 0.43	0.17 ± 0.16	498.43 ± 987.59
Trapa natans	Water Caltrop	Petiole	Eudicot	F/H	3.48 ± 3.53	1.19 ± 0.67	0.11 ± 0.13	608.61 ± 707.9
Vitis vinifera	Grapevine	Leaf	Eudicot	S/V	1.78 ± 2.36	0.97 ± 0.22	0.41 ± 0.16	339.32 ± 540.9
Vitis vinifera	Grapevine	Stem	Eudicot	S/V	2.63 ± 3.7	1.02 ± 0.29	0.23 ± 0.16	472.67 ± 713.02
Platanus occidentalis	American Sycamore	Leaf	Eudicot	T	1.63 ± 0.82	1.13 ± 0.3	0.30 ± 0.17	413.20 ± 359.71
Platanus occidentalis	American Sycamore	Petiole	Eudicot	T	3.16 ± 2.3	1.00 ± 0.23	0.23 ± 0.11	522.36 ± 564.45
Morella cerifera	Wax Myrtle	Stem	Eudicot	S/S/T	2.43 ± 3.37	1.03 ± 0.43	0.24 ± 0.17	331.15 ± 410.43
Morella cerifera	Wax Myrtle	Leaf	Eudicot	S/S/T	1.99 ± 1.24	1.18 ± 0.49	0.18 ± 0.15	818.53 ± 3373.08
Magnolia virginiana	Sweetbay Magnolia	Leaf	Eudicot	S/T	1.71 ± 1.09	0.94 ± 0.2	0.50 ± 0.15	131.95 ± 316.58
Magnolia virginiana	Sweetbay Magnolia	Petiole	Eudicot	S/T	1.74 ± 2.64	0.96 ± 0.26	0.45 ± 0.18	187.98 ± 502.94
Magnolia grandiflora	Southern Magnolia	Leaf	Eudicot	T	2.36 ± 2.14	1.36 ± 0.41	0.08 ± 0.09	1800.85 ± 2631
		Stem	Eudicot	T	2.59 ± 2.67	0.97 ± 0.36	0.27 ± 0.17	346.02 ± 359.39
		Petiole	Eudicot	T	2.11 ± 2.25	1.63 ± 0.82	0.08 ± 0.09	805.92 ± 904.83
Cyrilla racemiflora	Titi	Leaf	Eudicot	S/T	1.93 ± 2.27	1.27 ± 0.28	0.19 ± 0.12	393.192415.48
Cyrilla racemiflora	Titi	Petiole	Eudicot	S/T	2.10 ± 2.27	1.31 ± 0.33	0.18 ± 0.12	395.22 ± 1337.9
Pinckneya bracteta	Fever tree	Leaf	Eudicot	S/T	1.95 ± 0.67	0.86 ± 0.19	0.61 ± 0.17	47.22 ± 41.88
Cornus amomum	Silky Dogwood	Leaf	Eudicot	S	1.55 ± 0.82	0.90 ± 0.08	0.55 ± 0.14	84.19 ± 137.93
Dicranopteris	Uluhe Fern	Leaf	Fern	F/H/V	1.77 ± 1.7	1.10 ± 0.18	0.26 ± 0.16	301.20 ± 611.12
Dicranopteris	Uluhe Fern	Petiole	Fern	F/H/V	3.29 ± 3	1.04 ± 0.24	0.23 ± 0.14	432.79 ± 249.08
Cyathea corallifera	N/A	Leaf	Fern	F/H/T	2.23 ± 4.26	0.95 ± 0.21	0.36 ± 0.19	308.80 ± 377.45
Cyathea corallifera	N/A	Petiole	Fern	F/H/T	3.233.79	1.40 ± 0.62	0.10 ± 0.07	884.77 ± 983.84
Sceptridium biternatum	Grape Fern	Leaf	Fern	F/H	2.20 ± 1.39	0.94 ± 0.2	0.42 ± 0.14	258.57 ± 744.03
Polystichum acrostichoides	Christmas Fern	Leaf	Fern	F/H	2.24 ± 2.19	1.02 ± 0.15	0.30 ± 0.16	312.28 ± 935.15
Polystichum acrostichoides	Christmas Fern	Petiole	Fern	F/H	4.77 ± 3.37	0.98 ± 0.21	0.20 ± 0.15	509.91 ± 1217.6
Onoclea sensibilis	Sensitive Fern	Leaf	Fern	F/H	2.38 ± 2.06	1.01 ± 0.39	0.22 ± 0.17	436.75 ± 1188.12
Onoclea sensibilis	Sensitive Fern	Petiole	Fern	F/H	3.38 ± 2.53	1.18 ± 0.38	0.13 ± 0.13	591.33 ± 800.3
Anchistea virginica	Virginia chain fern	Leaf	Fern	F/H	1.81 ± 3.51	1.25 ± 0.53	0.18 ± 0.15	437.95 ± 966.87
Anchistea virginica	Virginia chain fern	Petiole	Fern	F/H	4.66 ± 3.81	1.12 ± 0.47	0.10 ± 0.08	702.90 ± 788.73
Osmundastrum cinnamomeum	Cinnamon Fern	Leaf	Fern	F/H	2.45 ± 3.11	1.13 ± 0.33	0.15 ± 0.2	636.55 ± 688.93
Osmundastrum cinnamomeum	Cinnamon Fern	Petiole	Fern	F/H	2.81 ± 1.56	1.16 ± 0.28	0.21 ± 0.1	561.75 ± 764.1
Angiopteris evecta	King Fern	Leaf	Fern	F/H	2.24 ± 2.83	1.22 ± 0.31	0.19 ± 0.13	756.13 ± 619.72
Juniperus virginiana	Eastern Red Cedar	Leaf	Gymnosperm	T	2.12 ± 1.27	1.05 ± 0.28	0.27 ± 0.17	570.78 ± 494.53
Juniperus virginiana	Eastern Red Cedar	Needle	Gymnosperm	T	4.55 ± 5.2	0.990.22	0.13 ± 0.15	693.75 ± 430.9
Metasequoia glyptostroboides	Dawn Redwood	Bark	Gymnosperm	T	3.08 ± 2.32	0.98 ± 0.26	0.26 ± 0.15	434.67 ± 642.02
		Stem	Gymnosperm	T	2.58 ± 3.16	1.00 ± 0.24	0.33 ± 0.16	610.41 ± 764.79
		Leaf	Gymnosperm	T	2.10 ± 1.3	0.94 ± 0.17	0.42 ± 0.18	137.59 ± 1318.36
Taxodium ascendens	Pond Cypress	Stem	Gymnosperm	T	2.50 ± 2.49	0.97 ± 0.11	0.39 ± 0.16	185.79 ± 239.38
Taxodium ascendens	Pond Cypress	Needle	Gymnosperm	T	2.20 ± 5.79	1.10 ± 0.31	0.15 ± 0.16	248.37 ± 511.45
Pistia stratiotes	Water Lettuce	Leaf	Monocot	F/H	1.99 ± 1.39	1.46 ± 0.44	0.13 ± 0.08	713.87 ± 1200.01
Pistia stratiotes	Water Lettuce	Root	Monocot	F/H	4.17 ± 3.8	0.96 ± 0.33	0.15 ± 0.19	601.10 ± 1110.4
Equisetum	Horsetail	Horsetail	Horsetail	F/H	2.27 ± 4.03	0.96 ± 0.21	0.31 ± 0.17	455.70 ± 517.86
Marchantiophyta	Liverwort	Liverwort	Liverwort	F/H	2.02 ± 3.8	1.09 ± 0.51	0.22 ± 0.17	376.09 ± 470.93
F/H = Forb/Herb; S/V = Shrub/vine; T = Tree; S/S/T = Shrub/Subshrub/tree; S/T = Shrub/tree; S = Shrub; F/H/V = Forb/Herb/Vine; F/H/T = Forb/herb/tree; F/H = Forb/Herb

Table 2

Tissue component comparison results for selected plant species.
Scientific Name	Common Name	Tissue Components	Median AR ± σ	Median Rectangularity ± σ	Median Circularity ± σ	Median Feret diameter ± σ
Morella cerifera	Wax Myrtle	Blade	1.995 ± 1.67	1.245 ± 0.44	0.1445 ± 0.12	485.1805 ± 427.28
		Vein	3.1105 ± 2.71	0.953 ± 0.27	0.2285 ± 0.17	244.817 ± 781.99
		Petiole	2.459 ± 1.82	0.9335 ± 0.18	0.378 ± 0.19	197.499 ± 830.54
		Pith	2.65 ± 1.95	0.927 ± 0.14	0.3645 ± 0.16	257.1195 ± 275.68
		Phloem	1.579 ± 2.45	0.955 ± 0.19	0.4105 ± 0.18	253.216 ± 366.36
Magnolia virginiana	Sweetbay Magnolia	Blade	1.5655 ± 0.56	0.991 ± 0.21	0.428 ± 0.16	253.5195 ± 285.25
		Vein	1.9075 ± 1.14	1.0935 ± 0.34	0.258 ± 0.17	408.1125 ± 515.94
		Petiole	2.9935 ± 2.76	1.0545 ± 0.26	0.2305 ± 0.15	316.724 ± 2180.85
		Pith	2.345 ± 2.12	0.9905 ± 0.23	0.269 ± 0.16	291.427 ± 385.48
		Phloem	2.1495 ± 1.87	1.0125 ± 0.26	0.3145 ± 0.13	331.0285 ± 452.32
Cyrilla racemiflora	Titi	Blade	1.9675 ± 2.8	1.4435 ± 0.5	0.133 ± 0.1	703.15 ± 572.05
		Vein	7.25 ± 3.89	0.9655 ± 0.38	0.141 ± 0.09	535.889 ± 347.73
		Petiole	2.467 ± 2.39	1.0145 ± 0.19	0.3365 ± 0.14	413.009 ± 326.29
		Pith	3.17 ± 2.28	0.979 ± 0.25	0.245 ± 0.13	382.6385 ± 313.13
		Phloem	4.3215 ± 4.38	0.974 ± 0.2	0.192 ± 0.19	372.4975 ± 373.99
Osmundastrum cinnamomeum	Cinnamon Fern	Blade	2.28 ± 4.76	1.06 ± 0.34	0.21 ± 0.18	369.24 ± 817.97
		Vein	4.03 ± 2.33	1.14 ± 0.26	0.14 ± 0.11	648.87 ± 761.51
		Pith	2.88 ± 1.97	1.32 ± 0.33	0.13 ± 0.09	769.45 ± 512.94
		Phloem	2.47 ± 1.43	1.11 ± 0.28	0.22 ± 0.12	547.26 ± 455.65
Metasequoia glyptostroboides	Dawn Redwood	Blade	1.96 ± 1.75	1.16 ± 0.23	0.25 ± 0.16	644.87 ± 564.08
		Vein	2.36 ± 1.83	0.96 ± 0.24	0.32 ± 0.16	346.23496.17
		Pith	2.63 ± 1.69	1.04 ± 0.22	0.31 ± 0.15	440.451267.3
		Phloem	2.52 ± 2.46	0.98 ± 0.21	0.27 ± 0.15	345.85281.57

2.2 Combustion and Sample Production

Following Vachula et al. (2024), we combusted samples in an apparatus with open air combustion that collected charcoal. Subsequently, deionized water was used to transfer the charcoal particulates into 15 mL centrifuge tubes for storage. The apparatus was thoroughly cleaned with water between successive samples. To mimic natural, at minimum sedimentological breakage, samples were gently shaken for approximately 10 seconds within the centrifuge tubes (Crawford and Belcher, 2014; Umbanhowar and McGrath, 1998).

While conventional methods such as muffle furnaces have been employed in previous studies, it is worth noting that charcoal produced in furnaces tends to yield higher length-to-width (L:W) ratios (Vachula et al., 2021). Given the potential for anaerobic combustion in furnaces to inflate L:W values (Vachula et al., 2021) and/or alter other morphometric characteristics, open burns were used in this study to ensure that observed morphometric variations reflect fuel characteristics rather than combustion parameters.

2.3 Microscopy and Data Analysis

Samples were examined and imaged using a Nikon SMZ745T stereo microscope equipped with a DSFi3 color camera. Image analysis, including measurement of morphometric variables, was conducted using the CharTool image processing program (Snitker, 2020). We quantified a minimum of 50 particles for each sample to ensure robust characterization of morphometric variance (Pereboom et al., 2020).

We measured the following parameters (sensu Snitker, 2020): particle aspect ratios (length: width; L:W); circularity (4π × area ÷ perimeter²; values approaching 1.0 will be increasingly circular while values approaching 0.0 will be increasingly elongated); regularity ( perimeter ÷ ((width + height) × 2); values approaching 1.0 will resemble a perfect rectangle; as values approach 0.0, the selected particle will be increasingly circular; as values exceed 1.0, the selected will be increasingly irregular in shape); and feret diameter (diameter of the selected particle, where feret is measured as is the longest distance between any two points along the boundary of the selected particle).

Recognizing the potential for sieving particles to influence morphometric measurements (Crawford and Belcher, 2014), samples were not sieved in this study. Instead, the feret diameter of each particle, representing the greatest distance between any two points on the particle's edge, was recorded to provide a metric analogous to sieved size range (Snitker, 2020).

Boxplots were employed to visually depict the range of our measured variables across different plant taxa and tissue types. Outliers were not plotted to improve clarity of plots. Two-sample t-tests assuming unequal variances were utilized to assess significant differences between L:W means of analyzed groups. Both boxplots and statistics were generated using R Studio. Our primary statistical methods for this paper were Welch’s 2-sample t-tests and Tukey Tests. Welch's 2-Sample t-Test compares the means of two independent groups. Tukey's HSD Test is used after an ANOVA to compare all possible pairs of group means, controlling for possibility of multiple comparisons inflating the chance of Type I errors.

3.1 Plants sampled in this study

All sampled plants were perennials, with the majority of taxa comprised of eudicots (n = 9) and ferns (n = 8). The remaining taxa consisted of gymnosperms (n = 3) and monocot, horsetail, and nonvascular plants (n = 1 each). Predominantly, the sampled plants exhibited forb/herb growth habits (n = 10), with a smaller proportion demonstrating mixed tree, shrub, vine, and/or sub-shrub growth habits (n = 10). Additionally, we sampled single plants of shrub, shrub/vine, and shrub/sub-shrub/tree growth habits.

3.2 Morphometric characteristics of the experimental charcoal in this study

Our morphometric measurements yielded an abundance of data. Though the data can be examined in their entirety in Table 1 and the figures, we herein highlight the broad differences of charcoal morphometrics between fuel types, plant tissues, and plant tissue components.

The L:W ratios of leaves (Fig. 1A) tended to measure significantly less than petioles of the same plant species (P < 0.05). Though L:W values of leaves from all taxa analyzed in this study (Table 1, Fig. 1A) measured comparatively low, eudicots had significantly lower L:W values than all other taxonomic groupings (P < 0.01). Forb growth habits were significantly different from shrub growth habits in L:W, rectangularity, and feret diameter (P < 0.01).

Circularity measurements were generally higher in leaves than petioles of the same species (Fig. 1B). Eudicots and gymnosperms measured significantly higher than ferns and our other class (P < 0.05; Figs. 2 & 5).

Rectangularity measurements averaged around 1.0 for gymnosperm fuels and a number of fern leaves (Fig. 1C). Generally, petiole components measured smaller than other components (Fig. 3C & 4C). Gymnosperms measured significantly less than all other classes (P < 0.05; Figs. 2 & 5).

Feret diameter measurements were relatively consistent with published values in the field, however some samples (sweetbay magnolia leaf, sweetbay magnolia petiole, fever tree leaf, silky dogwood leaf, and dawn redwood leaf) had values below the standard sieve size of 125 µm (Fig. 1). Gymnosperms measured significantly less than both the eudicot and fern classes (P < 0.05; Figs. 2 & 5).

Our dissections of plant tissue components also produced notable differences in charcoal morphometrics. Vein components had significantly greater L:W values than blade, petiole, or pith tissues (P < 0.05; Figs. 4 & 5). Petiole and Phloem components measured significantly higher than the blade and vein components (P < 0.05; Figs. 4 & 5). Blade components measured significantly higher than all other components (P < 0.05; Figs. 4 & 5). Petiole and phloem components measured significantly less than the vein and blade components (P < 0.05; Figs. 4 & 5).

4.1 Morphometric and morphological variations of our experimental charcoal

Our results demonstrate the value of undertaking multiple morphometric measurements to distinguish fuel type burned. For example, of all of the plant groups we analyzed, the L:W values differentiated only the eudicot plant lineage, which measured significantly smaller in L:W than all other classes (P < 0.05; Fig. 5). When we consider other morphometrics, additional differentiation is possible. Gymnosperms measured smaller in rectangularity than the other plant classes (P < 0.05; Fig. 5). Circularity of eudicots and gymnosperms measured significantly larger than ferns and other classes (P < 0.05; Fig. 5). However, gymnosperms measured significantly smaller in feret diameter than ferns and eudicots (P < 0.05). Altogether, differences in the morphometric characteristics of charcoal produced by different plant types demonstrate the value of these multiple morphometric measurements. Indeed, whereas the bulk of previous charcoal morphometric work has focused on L:W values alone (Pereboom et al., 2020; Vachula et al., 2021; Crawford and Belcher, 2014; Ogura, 2007; Feurdean 2021; Feurdean et al., 2023), our findings emphasize the value and potential of these other metrics for paleofire research.

Our tissue component burns further emphasize and underscore the utility of our diverse morphometric approach to distinguish fuel type burned. The vein components measured significantly larger (feret diameter) than blade, petiole, and pith components (P < 0.05; Fig. 5). Leaves measured significantly larger than all other components in rectangularity (P < 0.05; Fig. 5). Petiole and phloem components measured larger than blades and veins in circularity (P < 0.05; Fig. 5). An opposite trend to this is shown in feret diameter (P < 0.05; Fig. 5). Overall, these data demonstrate that a multi-morphometric approach enables us to see more nuanced and more richly resolved differences than would be provided by L:W values alone. In other words, we established 7 additional significant morphometric proxies to differentiate both plant classes and plant components, providing new avenues for paleofire research.

The potential of our diverse morphometric dataset for fuel type differentiation can be demonstrated by several examples. Although fern leaves showed a relatively constant signal when only measured by L:W (Fig. 1), circularity values between fern leaves are much more varied. Similarly, our data show that gymnosperms measured smaller and more rectangular than the other plant classes, in agreement with the assumption that gymnosperm charcoal would be more geometric/rectangular (Mustaphi and Pisaric, 2014).

4.2 Plant component analysis: insights into the controls of charcoal morphometric variations

Our results show significant differences of charcoal morphometrics produced in the burns of our dissected plant tissue components (Fig. 5). Across multiple morphometrics, there are significant differences between two or more tissue components. Yet in previous experimental charcoal research (e.g., Feurdean. 2021; Vachula et al., 2024), these dissected tissue components would be resolved at the singular tissue scale. For example, the L:W and rectangularity data show that the blade and vein tissue components have significantly different morphometrics, despite together composing leaf tissue. This finding challenges the previous methodology of the field, which has traditionally grouped plant tissues in charcoal experiments (Feurdean, 2021; Feurdean et al., 2023; Vachula et al., 2021). Though it has been speculated that large plant tissues (e.g., leaf) do not necessarily produce uniform or homogenous charcoal (Crawford et al., 2018), we provide the first data to support this theory. Therefore, our findings are more consistent with the theories of Umbanhowar and McGrath (1998), who suggested that the individual concentration and orientation of individual xylem bundles could control charcoal morphometrics (namely, L:W values). These findings are further emphasized by the significant differences between the morphometrics of plant tissue components which would not be resolved using the field traditional methodologies (Fig. 6). For example, there is a significant difference in the L:W values of two tissue components, which when synthetically combined, show no significant difference when compared to its traditional methodological counterpart (Table 1 & Fig. 1). Overall, our findings support the plant tissue component theory of Umbanhowar and McGrath (1998) and emphasize the need for further investigation into the mechanisms that control morphometric variations at the component level.

Furthermore, these significant charcoal morphometric differences in plant component tissues are seen in every measured value collected in this study (Fig. 5). Vein tissue components measured significantly larger in L:W than all other tissue components except phloem (Fig. 5). This finding supports the theory that vascular bundles control charcoal L:W values as vein tissue components typically have larger and more abundant vascular bundles than other plant components (Umbanhowar and McGrath, 1998; Taiz and Zeiger, 2010). As mentioned previously, blade tissue components had a higher rectangularity than every other component (Fig. 5). By definition, this means that blade tissues are far more irregular in shape than other components. In addition to this quantitative measurement, some plants (wax myrtle, titi, etc.) had branching morphology, as defined by Jensen et al. (2007). Therefore, combining morphometric and morphological approaches may be a reliable method to identify blade components within a sedimentary charcoal sample, potentially leading to more nuanced interpretations.

Our quantification of feret diameter provides important insights for paleofire research. For example, ferns and “other” plant types (e.g., aquatic and horsetail) produce charcoal particles which are significantly smaller than the other plant classes, potentially suggesting a difference between the plants and those of the other categories. Notably, these plant lineages (ferns, horsetails) are evolutionarily old, suggesting that the difference in charcoal size could reflect differences in taxonomy-related plant chemistry or structure, as has been suggested previously (Vachula et al., 2021, 2024). However, there are also significant differences in the feret diameter of plant tissue components; blade and vein components are significantly larger than both petiole and phloem components. Therefore, it is possible that taxonomic differences in the abundance of plant tissue components are the underlying control of charcoal size. Moreover, these findings emphasize the influence that sieving might have on paleofire interpretations of fuel type burned Last, they suggest that the exclusion or limitation of sieving might provide better means of distinguishing fuel types of charcoal in geologic contexts.

Differences between petiole, pith, and phloem were found to be insignificant across all measured variables in this study (Fig. 5). This suggests that in paleofire studies, these tissue components are not distinguishable. However, it is possible that in other plants (i.e., those not sampled in this study), these tissue components could be different.

Overall, our data show considerable variation of charcoal morphometrics produced from dissected plant tissue components, underscoring the need to revisit traditional approaches and interpretations of experimental charcoal research. These findings have important implications for the interpretation of paleofire data. For example, Crawford and Belcher (2014) noted that leaf tissues had higher L:W values than woody tissues. However, our tissue component data show that they could have been observing a combination of low L:W blade components and high L:W vein components. These more nuanced distinctions may allow for more precise interpretations of sedimentary charcoal, echoing points made by Feurdean et al. (2023) and Vachula et al. (2021) that more refined experimental charcoal work is needed for robust interpretations of past fuel and fire types.

4.3 Addressing sampling gaps and biases in experimental charcoal research

Our sampling scheme provides resolution of new plant taxa, plant groups, and novel plant tissue components for lesser studied ecosystems. Our analysis contributes 14 new plant taxa to the growing charcoal L:W dataset (Vachula et al. 2024). Of the 14 new taxa, 8 are ferns, a large increase in charcoal morphometric resolution when compared to the only 2 previously published fern taxa (Crawford et al., 2018; Ogura, 2007; Feurdean, 2021). Additionally, our study conducts novel analysis of dissected plant tissue components for 5 selected taxa. Further, our sampling approach provides resolution of three additional morphometrics that have shown promise but have not been extensively explored in the literature (Frank-DePue et al. 2022). These new morphometrics were explored both for the traditional and tissue component level experimental burns in this study.

Our feret diameter data echo previous research demonstrating the relationship between charcoal particle size and morphometrics and calling for caution when sieving sediment samples. For example, in our dataset feret diameter shares an inverse relationship with circularity (Fig. 1C & 1E). We did not use sieves, so our experimental morphometric data reflect the range of likely charcoal particulates produced naturally in the environment. Paleofire research commonly uses 125 µm sieves to separate “macroscopic charcoal” from aggregate sediments (Umbanhowar and McGrath, 1998; Vachula 2019). Notably, many plant taxa and tissues exhibited median feret diameters less than 150 µm (e.g., sweetbay magnolia leaf = 131.95 ± 316.58 µm, fever tree leaf = 47.22 ± 41.88 µm, dawn redwood leaf = 137.59 ± 1318.36 µm; Table 1), insinuating that sieving these samples in the traditional manner would exclude a sizeable proportion of the measured particles in the sample.

Our feret diameter data highlight distinct differences in the charcoal particle sizes produced by different plant groups. Interestingly, we found that gymnosperms measured significantly less than both the fern and eudicot classes (Fig. 5). Additionally, we find a significant difference between the feret diameter of eudicot samples (predominantly leafy fuel) and gymnosperm samples (predominantly woody fuels) (P < 0.05). This finding contrasts with previous work by Vachula et al. (2024), who observed no significant differences of feret diameter. However, it agrees with findings of Umbanhowar and McGrath (1998), who sieved their samples and noted a slight trend for leaf samples to be smaller than wood samples, though this was not a statistically significant difference (P > 0.05; Tukey HSD (the same test we used)). Our finding that there are significant differences of charcoal particle size between plant classes further emphasizes the need to use caution when sieving sedimentary charcoal samples to avoid affecting the environmental signals collected.

4.4. Recommendations for the application of charcoal morphometrics to pre-Holocene samples

Our results have shown nuanced differences in L:W values between both tissue and tissue components across species. In general, we find that leaves measured significantly lower than petioles of the same species. This difference broadly aligns with past findings that broad-scale plant tissues will have significant differences of L:W values (Vachula et al., 2021; 2024; Feurdean, 2021). Further, different L:W values could be indicative of fire intensity or behavior, due to differential burning of leaves and petioles (Enache and Cumming, 2006). Our observations of the differences of L:W also have implications for interpretations of fire regimes in the fossil record. For instance, an increased number of low L:W particles may suggest that predominantly blade tissues were burned. This finding supports Feurdean et al. (2023) and their emphasis of the need for refined morphometric techniques that consider different plant tissues separately as a means of more detailed charcoal morphometric studies. In general, the plants used in this study have low L:W values, demonstrating the possibility of misidentifying leaf charcoal as woody charcoal due to a low L:W, as pointed out by Umbanhowar and McGrath (1998). Eudicots measured significantly lower in L:W than all other classes, suggesting that lower L:W in a given charcoal sample may have a eudicot-dominated fuel source. Lastly, vein plant components measured higher in L:W than the other components. Additionally, this finding potentially suggests a source of bias in a given dataset; if a particular plant has a high number of vein components within it the corresponding measurements could be artificially inflated in L:W, not because of plant class differences but due to plant anatomy (i.e., more veins). Altogether, our findings align with those of Frank-DePue et al. (2023), who noted that trends in sedimentary charcoal shapes can correspond with broader-scale land-use changes and emphasized the importance of detailed morphometric analysis.

Our results show that circularity can be used as a viable metric for future charcoal morphometry work. Leaves measured higher than petioles of the same species (Fig. 1B), whereas ferns and other plants measured significantly lower than eudicots and gymnosperms (Fig. 5). Further, the petiole tissue component measures significantly higher in circularity than vein and blade components (Fig. 5), despite the three components making up the “leaf complex” that would have been measured in previous research (Feurdean, 2021; Taiz and Zeiger, 2010).

Our results show that rectangularity has promise as a charcoal morphometric proxy. In aggregate, gymnosperms had average rectangularity values centered ~ 1.0, which were significantly different (P < 0.05) from herbaceous fuels (eudicot and fern) that averaged ~ 1.5 (Fig. 1D). Gymnosperms had significantly lower rectangularity values than all other combined plant classes (Figs. 3 & 5), supporting rectangularity values as a metric for identifying gymnosperm charcoal (i.e. ~1.0). However, fern leaves also have rectangularity values ~ 1.0 (Fig. 1D). In contrast, Frank-DePue et al. (2023) found that higher rectangularity values corresponded with woody fuels. This disconnect highlights the potential need for additional variables to be considered when interpreting fuel types using charcoal rectangularity values.

Our results show that feret diameter can be used to differentiate fuel types. Herbaceous fuels had significantly higher (P < 0.05) feret diameters than gymnosperm (woody) fuels and somewhat higher, but not significantly different (P < 0.1) feret diameters than eudicots (Figs. 1 & 5). These findings are broadly in accordance with those discussed by Crawford and Belcher (2014). Further, blade and vein tissue components had larger feret diameters than petiole and phloem tissue components (Fig. 5). These findings further underscore the need to use caution when interpreting fuel sources of sieved material and use finer sieve sizes.

4.5 Guidance for future experimental charcoal research focusing on the Cretaceous and other pre-Holocene time periods

Our study demonstrates the utility of a multivariate approach to charcoal morphometry. Experimental charcoal morphometry, largely developed through Holocene-focused studies (Vachula et al., 2021), has not before sampled the plant taxa we focused on in this study, so we provide novel resolution of plants more relevant to pre-Holocene contexts. Further, by quantifying a diversity of morphometric parameters, we show that the multivariate approach can provide more nuanced paleofire insights.

Charcoal morphometry and our new experimental dataset provide a complementary perspective for paleoecological research of the Cretaceous and other pre-Holocene time periods. Though limited work has focused on Cretaceous charcoal, it has primarily focused on the relationship with vertebrate fossil assemblages (Brown et al., 2013) or the use as a proxy for the K-T extinction event (Belcher et al., 2003). The use of charcoal as a paleofire proxy is therefore a promising means of learning more about Cretaceous paleoecology as it can provide inferences that have not been examined before. Mendes et al. (2014) demonstrated the value of combining palynological and mesofossil data to reconstruct ancient vegetation, which can be complemented by our morphometric analyses to offer a more comprehensive picture of past fire regimes. Sedimentary charcoal should be viewed as another tool to resolve the paleoecology of ecosystems in the Cretaceous and other pre-Holocene time periods. For example, Tosolini et al. (2018) noted a lack of fern and angiosperm macrofossils, despite their prevalence in palynological records. Morphometric analyses of sedimentary charcoal alongside their macrofossil/palynological analysis may have provided additional perspective on the paleoecology of the system and the perceived lack of ferns and angiosperms. Additionally, Crawford et al. (2018) used morphological and morphometric techniques to characterize Jurassic charcoal particles. However, the authors could only speculate their fuel sources to be conifer xylems and tree ferns; our multivariate experimental dataset provides a more robust interpretative framework. Moreover, when working on geologic time scales at which evolutionary changes occurred (i.e. evolution of grasses, etc.), a multivariate morphometric approach ensures that despite changes in plant evolution which might nullify the utility of a single morphometric in earlier periods of time (e.g., L:W), additional morphometrics can still provide guidance for paleofire fuel type interpretations

Our study demonstrates the importance of a multivariate approach to charcoal morphometry. We highlight significant differences in charcoal morphometrics at the plant group, tissue, and tissue component levels. Both eudicot and gymnosperm classes measured significantly larger than fern and the “other” classes in circularity, whereas petiole and phloem components measured significantly larger than the other components in circularity. Gymnosperms exhibited distinct rectangularity values, which could serve as a framework for their identification in future studies. Additionally, feret diameter was effective in differentiating herbaceous and woody fuels, providing further identification mechanisms in charcoal analysis. We found that plant tissue components (veins, blades, petioles, etc.) produce distinct charcoal morphometrics, challenging the assumption that larger plant tissues generate relatively uniform charcoal particles. These findings emphasize the need for refined techniques that consider individual plant components to improve the accuracy of paleofire and paleoecological reconstructions. Vein components showed higher L:W values due to their vascular structure, suggesting a potential for sampling biases if these components are not adequately represented. Circularity and rectangularity metrics also varied significantly among plant classes and components, reinforcing the value of a multivariate approach. These results contribute to a novel framework for charcoal morphometry that is particularly relevant for studying pre-Holocene deposits, such as those from the Cretaceous period. By incorporating our refined methods, future studies can achieve more accurate and detailed reconstructions of past fire regimes and ecological dynamics, offering critical insights into how these systems may respond to ongoing climate change.

Author Contribution

The study was designed by all authors and implemented by RS Vachula, TM Cullen, and MR Galinger. MR Galinger produced and analyzed experimental samples. MR Galinger analyzed the data and created the figures. MR Galinger drafted the manuscript with extensive edits from RS Vachula and TM Cullen. Final edits were conducted by LR Goertzen and CJ Hansen. All authors have approved the final version of the manuscript.

Acknowledgements

These authors would like to extend a special thanks to The John D. Freeman Herbarium at Auburn University for providing plant samples from the Herbarium collection. This material is based upon work supported by the National Science Foundation under Grant Number (NSF Grant #1922687). MG was supported by NSF-NRT (Award #1922687). RSV and TMC were supported by start-up funds from Auburn University. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

Data Availability

Data used in this manuscript is provided in the supplementary information files

Adrain, J. M. & Westrop, S. R. Paleobiodiversity: we need new data. Paleobiology. 29 (1), 22–25 (2003).
Anderegg, W. R., Prall, J. W., Harold, J. & Schneider, S. H. Expert credibility in climate change. Proceedings of the National Academy of Sciences, 107(27), 12107–12109. (2010).
Berner, R. A. GEOCARBSULF: a combined model for Phanerozoic atmospheric O2 and CO2. Geochim. Cosmochim. Acta. 70 (23), 5653–5664 (2006).
Belcher, C. M., Collinson, M. E., Sweet, A. R., Hildebrand, A. R. & Scott, A. C. Fireball passes and nothing burns—The role of thermal radiation in the Cretaceous-Tertiary event: Evidence from the charcoal record of North America. Geology. 31 (12), 1061–1064 (2003).
Blarquez, O. et al. Paleofire reconstruction based on an ensemble-member strategy applied to sedimentary charcoal. Geophys. Res. Lett. 40 (11), 2667–2672 (2013).
Brown, K. J., Dietze, E., Walsh, M. K., Hennebelle, A. & Power, M. J. (2023). Charred particles and other paleofire proxies.
Brown, S. A., Collinson, M. E. & Scott, A. C. Did fire play a role in formation of dinosaur-rich deposits? An example from the Late Cretaceous of Canada. Palaeobiodiversity Palaeoenvironments. 93, 317–326 (2013).
Carvalho, A. et al. Forest fires in a changing climate and their impacts on air quality. Atmos. Environ. 45 (31), 5545–5553 (2011).
Crane, P. R., Friis, E. M. & Pedersen, K. R. The origin and early diversification of angiosperms. Nature. 374 (6517), 27–33 (1995).
Crawford, A. J. & Belcher, C. M. Charcoal morphometry for paleoecological analysis: the effects of fuel type and transportation on morphological parameters. Appl. plant. Sci. 2 (8), 1400004 (2014).
Crawford, A. J., Baker, S. J. & Belcher, C. M. Fossil charcoals from the Lower Jurassic challenge assumptions about charcoal morphology and identification. Palaeontology. 61 (1), 49–56 (2018).
Conedera, M. et al. Reconstructing past fire regimes: methods, applications, and relevance to fire management and conservation. Q. Sci. Rev. 28 (5–6), 555–576 (2009).
Enache, M. D. & Cumming, B. F. Tracking recorded fires using charcoal morphology from the sedimentary sequence of Prosser Lake, British Columbia (Canada). Quatern. Res. 65 (02), 282–292 (2006).
Enache, M. D. & Cumming, B. F. Extreme fires under warmer and drier conditions inferred from sedimentary charcoal morphotypes from Opatcho Lake, central British Columbia, Canada. Holocene. 19 (6), 835–846 (2009).
Ferguson, D. K. The origin of leaf-assemblages—new light on an old problem. Rev. Palaeobot. Palynol. 46 (1–2), 117–188 (1985).
Feurdean, A. Experimental production of charcoal morphologies to discriminate fuel source and fire type in the Siberian taiga. Biogeosciences discussions, 2021, 1–26. (2021).
Feurdean, A. et al. Holocene wildfire regimes in western Siberia: interaction between peatland moisture conditions and the composition of plant functional types. Clim. Past. 18 (6), 1255–1274 (2022).
Feurdean, A., Vachula, R. S., Hanganu, D., Stobbe, A. & Gumnior, M. Charcoal morphologies and morphometrics of a Eurasian grass-dominated system for robust interpretation of past fuel and fire type. Biogeosciences. 20 (24), 5069–5085 (2023).
Flannigan, M. D., Stocks, B. J. & Wotton, B. M. Climate change and forest fires. Sci. Total Environ. 262 (3), 221–229 (2000).
Frank-DePue, L., Vachula, R. S., Balascio, N. L., Cahoon, K. & Kaste, J. M. Trends in sedimentary charcoal shapes correspond with broad-scale land-use changes: insights gained from a 300-year lake sediment record from eastern Virginia. USA J. Paleolimnology. 69 (1), 21–36 (2023).
Harris, T. M. Burnt ferns from the English Wealden. Proceedings of the Geologists' Association, 92(1), 47–58. (1981).
Hay, W. W. Evolving ideas about the Cretaceous climate and ocean circulation. Cretac. Res. 29 (5–6), 725–753 (2008).
Hay, W. W. Can humans force a return to a ‘Cretaceous’ climate? Sed. Geol. 235 (1–2), 5–26 (2011).
Huber, B. T., MacLeod, K. G., Watkins, D. K. & Coffin, M. F. The rise and fall of the Cretaceous Hot Greenhouse climate. Glob. Planet Change. 167, 1–23 (2018).
Jensen, K., Lynch, E. A., Calcote, R. & Hotchkiss, S. C. Interpretation of charcoal morphotypes in sediments from Ferry Lake, Wisconsin, USA: do different plant fuel sources produce distinctive charcoal morphotypes? Holocene. 17 (7), 907–915 (2007).
Jolly, W. M. et al. Climate-induced variations in global wildfire danger from 1979 to 2013. Nat. Commun. 6 (1), 7537 (2015).
Koppelhus, E. Dennis R. Braman and101 (A Spectacular Ancient Ecosystem Revealed, 2005).
Lee, C., Schlemme, C., Murray, J. & Unsworth, R. The cost of climate change: Ecosystem services and wildland fires. Ecol. Econ. 116, 261–269 (2015).
Levin, H. L. & King, D. T. The Earth through time, 11th edition. Wiley. (2016).
Leys, B. A., Marlon, J. R., Umbanhowar, C. & Vannière, B. Global fire history of grassland biomes. Ecol. Evol. 8 (17), 8831–8852 (2018).
Li, C. et al. Study on the ratio of microcharcoal particles to phytoliths derived from plant combustion. Acta Micropalaeontologica Sinica. 36 (01), 83–90 (2019).
Malhi, Y. et al. Climate change and ecosystems: threats, opportunities and solutions. Philosophical Trans. Royal Soc. B. 375 (1794), 20190104 (2020).
McCarty, J. P. & Marlon, J. R. Ecological consequences of recent climate change. Conservation biology, (2020). What the past can say about the present and future of fire. Quaternary Research, 96, 66-87.15(2), 320–331. (2001).
Mendes, M. M., Dinis, J., Pais, J. & Friis, E. M. Vegetational composition of the Early Cretaceous Chicalhão flora (Lusitanian Basin, western Portugal) based on palynological and mesofossil assemblages. Rev. Palaeobot. Palynol. 200, 65–81 (2014).
Ogura, J. A study on the identification of original plants of minute charcoal fragments. Japanese J. Hist. Bot. 15 (2), 85–95 (2007).
Pereboom, E. M., Vachula, R. S., Huang, Y. & Russell, J. The morphology of experimentally produced charcoal distinguishes fuel types in the Arctic tundra. Holocene. 30 (7), 1091–1096 (2020).
Power, M. J., Marlon, J. R., Bartlein, P. J. & Harrison, S. P. Fire history and the Global Charcoal Database: A new tool for hypothesis testing and data exploration. Palaeogeogr., Palaeoclimatol. Palaeoecol. 291 (1–2), 52–59 (2010).
Rehn, E. et al. Multiproxy Holocene fire records from the tropical savannas of northern Cape York Peninsula, Queensland, Australia. Front. Ecol. Evol. 9, 771700 (2021).
Remy, C. C. et al. Guidelines for the use and interpretation of palaeofire reconstructions based on various archives and proxies. Q. Sci. Rev. 193, 312–322 (2018).
Sayedi, S. S. et al. Assessing changes in global fire regimes. Fire Ecol. 20 (1), 1–22 (2024).
Scotese, C. R., Song, H., Mills, B. J. & van der Meer, D. G. Phanerozoic paleotemperatures: The earth’s changing climate during the last 540 million years. Earth Sci. Rev. 215, 103503 (2021).
Taiz, L. & Zeiger, E. Plant Physiology (Sinauer Associates, Inc., 2010).
Tosolini, A. M. P. et al. Palaeoenvironments and palaeocommunities from Lower Cretaceous high-latitude sites, Otway Basin, southeastern Australia49662–84 (Palaeogeography, Palaeoclimatology, 2018).
Umbanhowar, C. E. Jr & McGrath, M. J. Experimental production and analysis of microscopic charcoal from wood, leaves and grasses. Holocene. 8 (3), 341–346 (1998).
Vachula, R. S. A usage-based size classification scheme for sedimentary charcoal. Holocene. 29 (3), 523–527 (2019).
Vachula, R. S., Sae-Lim, J. & Li, R. A critical appraisal of charcoal morphometry as a paleofire fuel type proxy. Q. Sci. Rev. 262, 106979 (2021).
Vachula, R. S. et al. (in press) Morphometric characteristics of charcoal produced from plants endemic to the southeastern United States of America (USA). The Holocene.
Webb, I. I. I., Howe, T., Bradshaw, S. E., Heide, K. M. & R. H. W., & Estimating plant abundances from pollen percentages: the use of regression analysis. Rev. Palaeobot. Palynol. 34 (3–4), 269–300 (1981).
Whitlock, C., Higuera, P. E., McWethy, D. B. & Briles, C. E. Paleoecological perspectives on fire ecology: revisiting the fire-regime concept. Open. Ecol. J. 3, 6–23 (2010).
Willis, K. J. & MacDonald, G. M. Long-term ecological records and their relevance to climate change predictions for a warmer world. Annu. Rev. Ecol. Evol. Syst. 42, 267–287 (2011).
Zhang, J. & Lü, H. Preliminary study of charcoal morphology and its environmental significance. Quaternary Sci. 26 (5), 857–863 (2006).

No competing interests reported.

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A new approach to experimental charcoal analyses: lessons for the Cretaceous and other time periods

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Abstract

Figures

1. Introduction

2. Materials and Methods

2.1 Sample Collection and Preparation

2.2 Combustion and Sample Production

2.3 Microscopy and Data Analysis

3. Results

3.1 Plants sampled in this study

3.2 Morphometric characteristics of the experimental charcoal in this study

4. Discussion

4.1 Morphometric and morphological variations of our experimental charcoal

4.2 Plant component analysis: insights into the controls of charcoal morphometric variations

4.3 Addressing sampling gaps and biases in experimental charcoal research

4.4. Recommendations for the application of charcoal morphometrics to pre-Holocene samples

4.5 Guidance for future experimental charcoal research focusing on the Cretaceous and other pre-Holocene time periods

5. Conclusion

Declarations

Author Contribution

Acknowledgements

Data Availability

References

Additional Declarations

Supplementary Files

Status:

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