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Cited by 845Fire effects on ecosystemsRangeland and Wildlife ManagementFire dynamics and safety research

Defining pyromes and global syndromes of fire regimes

Open access
Archibald, Sally, Lehmann, Caroline E. R., Gómez-Dans, Jose L., Bradstock, Ross A.·2013·Proceedings of the National Academy of Sciences
DOI 10.1073/pnas.1211466110PMC PMC3631631
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Abstract

Fire is a ubiquitous component of the Earth system that is poorly understood. To date, a global-scale understanding of fire is largely limited to the annual extent of burning as detected by satellites. This is problematic because fire is multidimensional, and focus on a single metric belies its complexity and importance within the Earth system. To address this, we identified five key characteristics of fire regimes—size, frequency, intensity, season, and extent—and combined new and existing global datasets to represent each. We assessed how these global fire regime characteristics are related to patterns of climate, vegetation (biomes), and human activity. Cross-correlations demonstrate that only certain combinations of fire characteristics are possible, reflecting fundamental constraints in the types of fire regimes that can exist. A Bayesian clustering algorithm identified five global syndromes of fire regimes, or pyromes. Four pyromes represent distinctions between crown, litter, and grass-fueled fires, and the relationship of these to biomes and climate are not deterministic. Pyromes were partially discriminated on the basis of available moisture and rainfall seasonality. Human impacts also affected pyromes and are globally apparent as the driver of a fifth and unique pyrome that represents human-engineered modifications to fire characteristics. Differing biomes and climates may be represented within the same pyrome, implying that pathways of change in future fire regimes in response to changes in climate and human activity may be difficult to predict.

AI snapshot

Written from the paper’s full text.

TL;DR

The paper identifies five global syndromes of fire regimes, or pyromes, by clustering five remotely sensed fire characteristics independently of vegetation and climate. It shows that only certain combinations of fire characteristics are possible and that human activity, alongside climate and fuel type, strongly shapes modern fire regimes.

Key findings

  • Five pyromes were identified: frequent–intense–large (FIL), frequent–cool–small (FCS), rare–intense–large (RIL), rare–cool–small (RCS), and intermediate–cool–small (ICS). Four reflect crown, litter, and grass-fueled fire distinctions; ICS is interpreted as a human-derived pyrome.
  • The largest fires occur in FIL (mean 414 km²), the most intense in RIL (476 MW), FCS fires occur annually (estimated FRI 1 y), and RCS has an estimated FRI >50 y in Table 1 (text reports average FRI more than 100 y).
  • Fire characteristics show tradeoffs: frequent fires constrain intensity, very long fire seasons are only associated with small fires, and short fire return intervals always show high area burned.
  • Human impact scores clearly distinguish ICS from other pyromes, and large-fire pyromes FIL and RIL correlate with low human impact; the difference between FIL and FCS is most clearly explained by human impact rather than climate.

Methods

  • Global remotely sensed fire data at 0.5° resolution from MODIS MCD45A1, MCD14ML, and GFED3.1, covering a 14-y record (1997–2010), with 26,455 grid cells containing fire information.
  • Five fire characteristics were quantified: fire return interval, maximum fire intensity (95th quantile FRP), length of fire season, maximum fire size, and mean annual area burned; climate variables included effective rainfall, rainfall seasonality, and coefficient of variation in annual rainfall, plus a human impact index and WWF biomes.
  • Analysis used PCA, piecewise quantile linear regression, and Mclust Bayesian expectation–maximization clustering with a variable shape, volume, and orientation model; five clusters were chosen because BIC increases were negligible beyond five, with a training sample of 10,900 points and discriminant analysis for the remaining approximately 15,000 points.

Limitations

  • Stated: pyromes depend on the fire characteristics included, the number of clusters chosen, and data limitations, and are unlikely to be definitive; the 14-y record is only a snapshot, the FRI metric is most reliable for return intervals less than 50 y, and the analysis did not distinguish North American from Russian boreal fire regimes.
  • Evident: choosing five clusters was difficult because BIC continued to increase to 15 clusters, and the training/prediction split was made because of processor constraints.
  • Evident: the WWF biome map uses climate qualifiers to classify biomes, which the authors note they were aiming to avoid in their pyrome classification.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1073/pnas.1211466110

Cites

9 of 9 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 50 cited sources checked · 0 supported · 0 flagged

  • Findingown data
    § Results and Discussion

    Very long fire seasons are only associated with small fires.

    “Very long fire seasons are only associated with small fires (Fig. 1B).”
    Quote in the paperNot a substantial claim
  • Findingown data
    § Results and Discussion

    Constraints between maximum fire size and area burned are not as tight as would be expected from studies that have found the majority of area to be burned in a few large fires.

    “Constraints between maximum fire size and area burned are not as tight as would be expected from studies that have found the majority of area to be burned in a few large fires (33).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [33] Strauss D, Bednar L, Mees R. Do one percent of forest fires cause ninety-nine percent of the damage? For Sci. 1989;35:319–328. [Google Scholar]

      Not checked in the free run.

  • Findingown data
    § Abstract

    Pyromes were partially discriminated on the basis of available moisture and rainfall seasonality.

    “Pyromes were partially discriminated on the basis of available moisture and rainfall seasonality.”
    Quote in the paperSubstantial claim
  • Findingown data
    § Abstract

    Cross-correlations demonstrate that only certain combinations of fire characteristics are possible, reflecting fundamental constraints in the types of fire regimes that can exist.

    “Cross-correlations demonstrate that only certain combinations of fire characteristics are possible, reflecting fundamental constraints in the types of fire regimes that can exist.”
    Quote in the paperSubstantial claim
  • Findingown data
    § Results and Discussion

    The five pyromes overlap substantially when plotted on axes of mean annual precipitation and mean annual temperature.

    “The five pyromes overlap substantially when plotted on axes of MAP and MAT (Fig. 4A)”
    Quote in the paperSubstantial claim
  • May combine two claims. 32
  • Classified as probably not a substantial claim. 22
  • The quote only partly states this claim. 1

  • May combine two claims.

    Findingown data
    § Abstract

    A Bayesian clustering algorithm identified five global syndromes of fire regimes (pyromes), each associated with particular combinations of fire characteristics.

    “A Bayesian clustering algorithm identified five global syndromes of fire regimes, or pyromes.”
    • Also stated in: § Results and Discussion · plain
      “We identified five distinct pyromes (SI Materials and Methods), each associated with particular combinations of fire characteristics (Fig. 2).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingreasoning
    § Results and Discussion

    Fire intensity is strongly constrained where fires are frequent, but infrequent fires show a wide range of fire intensities.

    “Fire intensity is strongly constrained where fires are frequent, but infrequent fires show a wide range of fire intensities (Fig. 1A).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data
    § Results and Discussion

    91% and 68% of the FIL and FCS pyromes, respectively, are classified as grassland vegetation of some sort.

    “Respectively, 91% and 68% of these two pyromes are classified as grassland vegetation of some sort.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data
    § Results and Discussion

    A final pyrome (ICS) has intermediate fire return times but fairly small fires.

    “A final pyrome was identified with intermediate fire return times but fairly small fires (Table 1 and Fig. 3).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data
    § Results and Discussion

    Fire intensity data showed North American boreal fires to be generally more intense than Russian boreal fires.

    “although the fire intensity data showed the North American fires to be generally more intense (Fig. S1C).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingnone given
    § Results and Discussion

    In FCS regions fires occur annually, whereas the RCS pyrome has an average fire return interval of more than 100 y.

    “In FCS regions fires occur annually, whereas the RCS pyrome has an average FRI of more than 100 y.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data
    § Results and Discussion

    Our data were unable to distinguish the reported range of fire return intervals for crown fire regimes (approximately 15 y in fynbos to approximately 150 y in conifer forests) and identified only one crown fire pyrome.

    “Our data were unable to distinguish these and only identified one crown fire pyrome.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data
    § Results and Discussion

    The two frequently burning pyromes (FIL and FCS) cover warmer, wetter climate space than the other pyromes when plotted on axes of mean annual precipitation and mean annual temperature.

    “although it does appear that the two frequently burning pyromes (FIL and FCS) cover warmer, wetter climate space than the other pyromes.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data
    § Results and Discussion

    The two frequent pyromes differ in their fire size and fire intensity, as well as their spatial distribution: Australia has larger, more intense fires (FIL), whereas in Africa, smaller, less intense fires dominate (FCS).

    “These pyromes differ in their fire size and fire intensity, as well as their spatial distribution: Australia has larger, more intense fires [frequent–intense–large (FIL)], whereas in Africa, smaller, less intense fires dominate [frequent–cool–small (FCS)] (Fig. 2).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data
    § Results and Discussion

    The ICS pyrome occurs throughout the globe, particularly in regions of deforestation and agriculture.

    “This intermediate–cool–small (ICS) pyrome occurs throughout the globe, particularly in regions of deforestation and agriculture (Fig. 2).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data
    § Results and Discussion

    Systems with short fire return intervals always show high area burned, but at longer fire return intervals, the area burned ranges more widely.

    “Finally, systems with short FRIs always show high area burned, but, at longer FRIs, the area burned ranges more widely (Fig. 1D).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data
    § Results and Discussion

    The RIL and RCS pyromes dominate in temperate and boreal regions but occur elsewhere as well.

    “These pyromes dominate in temperate and boreal regions but occur elsewhere as well (Fig. 2).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data
    § Results and Discussion

    The RIL pyrome prevails in broadleaf and needleleaf forests, is found wherever there is Mediterranean vegetation, and also in the spinifex grasslands of Australia.

    “This pyrome prevails in broadleaf and needleleaf forests, is found wherever there is Mediterranean vegetation (Iberian peninsula, west coast of the United States, southwestern Australia), and also in the spinifex grasslands of Australia (Fig. 2).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data
    § Results and Discussion

    One infrequent pyrome has high-intensity, larger fires (RIL), and the other has lower fire intensity and smaller fires (RCS).

    “One has high-intensity, larger fires [rare–intense–large (RIL)], and the other has lower fire intensity and smaller fires [rare–cool–small (RCS)].”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data
    § Results and Discussion

    Fires in tropical moist broadleaf forests are predominantly of the ICS type, but this biome can also sustain RCS and FCS fires.

    “Fires in tropical moist broadleaf forests are predominantly of the ICS (blue) type but this biome can also sustain RCS (purple) and FCS (orange) fires (Table 1).”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Findingown data
    § Materials and Methods

    An initial analysis indicated that a VVV model gave the best results (highest BIC).

    “An initial analysis using all possible parameterizations of the covariance matrix and cluster sizes from two to 15 indicated that a VVV model gave the best results (i.e., highest BIC).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data
    § Materials and Methods

    All five fire characteristics contributed significantly to the principal components and were largely orthogonal to each other.

    “All five fire characteristics contributed significantly to the principal components and were largely orthogonal to each other (Fig. S4).”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data
    § Materials and Methods

    Uncertainties were fairly constant across pyromes, with most points having uncertainty values less than 0.2 and no clear spatial pattern emerging.

    “Uncertainties were fairly constant across pyromes, with most points having uncertainty values less than 0.2 and no clear spatial pattern emerging (Fig. S6).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data
    § Materials and Methods

    Beyond five clusters, the increase in BIC was negligible and did not justify further splitting of the data.

    “Beyond five clusters, the increase in BIC was negligible (Fig. S5) and did not justify further splitting of the data.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Findingown data
    § Materials and Methods

    All points were classified into one of five pyromes with an associated uncertainty value.

    “All points were classified into one of five pyromes with an associated uncertainty value.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data
    § Abstract

    Human impacts affected pyromes and are globally apparent as the driver of a fifth and unique pyrome that represents human-engineered modifications to fire characteristics.

    “Human impacts also affected pyromes and are globally apparent as the driver of a fifth and unique pyrome that represents human-engineered modifications to fire characteristics.”
    Quote in the paperSubstantial claim

  • The quote only partly states this claim.

    Study design and conductnone given
    § Abstract

    Five key characteristics of fire regimes-size, frequency, intensity, season, and extent-can be consistently quantified at global scales using remotely sensed imagery.

    “we identify five key fire regime characteristics that can consistently be quantified at global scales by using remotely sensed imagery”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning
    § Abstract

    Differing biomes and climates may be represented within the same pyrome, implying that pathways of change in future fire regimes in response to changes in climate and human activity may be difficult to predict.

    “Differing biomes and climates may be represented within the same pyrome, implying that pathways of change in future fire regimes in response to changes in climate and human activity may be difficult to predict.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation
    § Abstract

    Fuel and weather show opposite trends along a productivity gradient: low-productivity environments usually do not produce enough fuel, whereas in high-biomass environments the fuel is usually too wet to burn.

    “Fuel and weather show opposite trends along a productivity gradient: low-productivity environments usually do not produce enough fuel, whereas in high-biomass environments the fuel is usually too wet to burn.”
    Quote in the paperSubstantial claim0 of 4 sources checked
    • cites [10] Meyn A, White P, Buhk C, Jentsch A. Environmental drivers of large, infrequent wildfires: The emerging conceptual model. Prog Phys Geogr. 2007;31:287–312. [Google Scholar] source

      Not checked in the free run.

    • cites [11] Bradstock RA. A biogeographic model of fire regimes in Australia: Contemporary and future implications. Glob Ecol Biogeogr. 2010;19:145–158. [Google Scholar] source

      Not checked in the free run.

    • cites [12] Krawchuk MA, Moritz MA. Constraints on global fire activity vary across a resource gradient. Ecology. 2011;92(1):121–132. doi: 10.1890/09-1843.1. [DOI] [PubMed] [Google Scholar] source

      Not checked in the free run.

    • cites [13] McKenzie D, Miller C, Falk D, editors. The Landscape Ecology of Fire. New York: Springer; 2011. [Google Scholar] source

      Not checked in the free run.

  • May combine two claims.

    Interpretationreasoning
    § Results and Discussion

    Infrequent fire is associated with intense crown fire events and with low-intensity surface fires in tropical forests.

    “Ecologically, infrequent fire is associated with intense crown fire events and with low-intensity surface fires in tropical forests.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given
    § Results and Discussion

    The analysis did not distinguish between North American and Russian boreal fire regimes.

    “Our analysis did not distinguish between North American and Russian boreal fire regimes”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data
    § Results and Discussion

    Human activities are a major force disrupting the fire system, and human activities play an equal role to climate in determining current pyromes.

    “These data suggest that human activities are a major force disrupting the fire system, and that human activities play an equal role to climate in determining current pyromes.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning
    § Results and Discussion

    When fire is frequent, there is insufficient time to accumulate the fuel needed for very high-intensity fires, and these systems are climatically too flammable to produce creeping, low-intensity fires.

    “When fire is frequent, there is insufficient time to accumulate the fuel needed for very high-intensity fires, and these systems are climatically too flammable to produce creeping, low-intensity fires.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation
    § Abstract

    Mean burned area is a widely used global measure of fire; it has been linked to the paleorecord and is used to calculate fluxes of carbon from the biosphere to the atmosphere.

    “Mean burned area is a widely used global measure of fire. It has been linked to the paleorecord (30), and is used to calculate fluxes of carbon from the biosphere to the atmosphere (3).”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [30] Bowman DMJS, et al. Fire in the Earth system. Science. 2009;324(5926):481–484. doi: 10.1126/science.1163886. [DOI] [PubMed] [Google Scholar] source

      Not checked in the free run.

    • cites [3] van der Werf G, et al. Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997–2009) Atmos Chem Phys Discuss. 2010;10:16153–16230. [Google Scholar]

      Not checked in the free run.

  • May combine two claims.

    Premisecitation
    § Abstract

    The size of individual fires and the length of the year over which fires occur reflect the continuity of the fuel bed and the propensity of the vegetation to be flammable.

    “The size of individual fires and the length of the year over which fires occur reflect the continuity of the fuel bed and the propensity of the vegetation to be flammable (28, 29).”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [28] Le Page Y, Oom D, Silva J, Jönsson P, Pereira J. Seasonality of vegetation fires as modified by human action: observing the deviation from eco-climatic fire regimes. Glob Ecol Biogeogr. 2010;19:575–588. [Google Scholar] source

      Not checked in the free run.

    • cites [29] Miller C, Urban D. Connectivity of forest fuels and surface fire regimes. Landscape Ecol. 2000;15:145–154. [Google Scholar]

      Not checked in the free run.

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductreasoning
    § Abstract

    This approach ensures that we do not confound our response variable because we classify pyromes independently of vegetation and climate, allowing them to emerge from the multidimensional space occupied by the fire characteristics.

    “This approach ensures that we do not confound our response variable because we classify pyromes independently of vegetation and climate, allowing them to emerge from the multidimensional space occupied by the fire characteristics.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation
    § Abstract

    The circumpolar boreal forest biome extends through North America and Russia, but fire regimes on the two continents differ: one is characterized by crown fires, and the other by surface fires.

    “The circumpolar boreal forest biome extends through North America and Russia, but fire regimes on the two continents differ: one is characterized by crown fires, and the other by surface fires (23).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [23] Wooster M, Zhang Y. Boreal forest fires burn less intensely in Russia than in North America. Geophys Res Lett. 2004;31:L20505. [Google Scholar] source

      Not checked in the free run.

  • Classified as probably not a substantial claim. May combine two claims.

    Premisecitation
    § Abstract

    Global vegetation units (biomes) are characterized solely by the traits of vegetation, and the environmental correlates emerge post hoc and help to explain the boundaries between biomes.

    “Conceptually, global vegetation units (i.e., biomes) are characterized solely by the traits of vegetation (18), and the environmental correlates emerge post hoc and help to explain the boundaries between biomes.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [18] Whittaker R. Communities and Ecosystems. 2nd Ed. New York: MacMillan; 1975. [Google Scholar]

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Premisecitation
    § Abstract

    Changes in frequency or intensity of fires can alter vegetation community composition by promoting or excluding different types of plants.

    “Changes in frequency or intensity of fires can alter vegetation community composition by promoting or excluding different types of plants (1, 2)”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [1] Gill AM. Fire and the Australian flora: A review. Aust For. 1975;38:4–25. [Google Scholar] source

      Not checked in the free run.

    • cites [2] Bond WJ, Keeley JE. Fire as a global ‘herbivore’: The ecology and evolution of flammable ecosystems. Trends Ecol Evol. 2005;20(7):387–394. doi: 10.1016/j.tree.2005.04.025. [DOI] [PubMed] [Google Scholar] source

      Not checked in the free run.

  • May combine two claims.

    Interpretationreasoning
    § Results and Discussion

    FIL and FCS probably represent a 'sparsely habited grassy pyrome' and a 'densely habited grassy pyrome,' respectively.

    “and they probably represent a “sparsely habited grassy pyrome” and a “densely habited grassy pyrome,” respectively.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation
    § Results and Discussion

    Axes of mean annual temperature and mean annual precipitation have traditionally been used to describe the climatic determinants of biomes.

    “Axes of mean annual temperature (MAT) and mean annual precipitation (MAP) have traditionally been used to describe the climatic determinants of biomes (18)”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [18] Whittaker R. Communities and Ecosystems. 2nd Ed. New York: MacMillan; 1975. [Google Scholar]

      Not checked in the free run.

  • May combine two claims.

    Premisecitation
    § Results and Discussion

    Chuvieco et al., using three active fire data metrics, successfully distinguished boreal forest but found no clear patterns with other vegetation classes.

    “Chuvieco et al. (9), by using three active fire data metrics, successfully distinguished boreal forest but found no clear patterns with other vegetation classes.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [9] Chuvieco E, Giglio L, Justice C. Global characterization of fire activity: Toward defining fire regimes from earth observation data. Glob Change Biol. 2008;14:1488–1502. [Google Scholar] source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Interpretationnone given
    § Results and Discussion

    The RIL pyrome is often interspersed geographically with the RCS pyrome, presumably surface fires burning through litter fuels in the same vegetation.

    “It is often interspersed geographically with the RCS pyrome—presumably, surface fires burning through litter fuels in the same vegetation.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation
    § Materials and Methods

    Individual fires can be identified from burned area data by using a flood-fill algorithm.

    “Individual fires can be identified from burned area data by using a flood-fill algorithm (31).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [31] Archibald S, Roy D. Identifying individual fires from satellite-derived burned area data. Proc IGARSS. 2009;3:160–163. [Google Scholar]

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Study design and conductown data
    § Results and Discussion

    The 14-y data record effectively sets the time period over which the authors are describing global fire regimes.

    “Moreover, the 14-y data record effectively sets the time period over which we are describing global fire regimes”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given
    § Materials and Methods

    The short observational time period is an obvious constraint to characterizing fire regimes in systems which burn infrequently.

    “The short observational time period is an obvious constraint to characterizing fire regimes in systems which burn infrequently”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductreasoning
    § Results and Discussion

    The pyromes described here are unlikely to be definitive.

    “and are unlikely to be definitive.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductcitation
    § Results and Discussion

    The spatially explicit nature of the data and the range of fire metrics used complements longer-term, less data-rich studies.

    “However, the spatially explicit nature of our data and the range of fire metrics used complements longer-term, less data-rich studies (see ref. 45 for justification).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [45] Daniau AL, Bartlein PJ, Harrison SP, et al. Predictability of biomass burning in response to climate changes. Glob Biogeochem Cycles. 2012;26:GB4007. [Google Scholar] source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data
    § Materials and Methods

    Choosing the correct number of clusters was difficult because the BIC continued to increase to 15 clusters.

    “Choosing the correct number of clusters (i.e., pyromes) was difficult because the BIC continued to increase to 15 clusters.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation
    § Materials and Methods

    FRI is usually estimated by fitting a Weibull distribution to fire return time data.

    “FRI is usually estimated by fitting a Weibull distribution to fire return time data (50).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [50] Johnson E, Gutsell S. Fire frequency models, methods and interpretations. Adv Ecol Res. 1994;25:239–287. [Google Scholar] source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductcitation
    § Results and Discussion

    The pyromes described here depend on the fire characteristics included, on the number of clusters chosen, and on the limitations of data used to represent each fire characteristic.

    “The pyromes described here depend on the fire characteristics included, on the number of clusters chosen, and on the limitations of data used to represent each fire characteristic (SI Materials and Methods)”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites SI Materials and Methods

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Study design and conductcitation
    § Materials and Methods

    The authors chose indices that maximized the information that could be gained from the global datasets.

    “but we chose indices that maximized the information that could be gained from these global datasets (SI Materials and Methods).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites SI Materials and Methods

      Not checked in the free run.

  • May combine two claims.

    Interpretationreasoning
    § Results and Discussion

    The characteristics of the ICS pyrome are expected of a fire regime consisting of fires lit by people for specific purposes, and therefore less closely connected to vegetation and climate drivers.

    “This would be expected of a fire regime consisting of fires lit by people for specific purposes, and therefore less closely connected to vegetation and climate drivers.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationcitation
    § Results and Discussion

    Human impacts have acted to decouple the fire-climate signal in recent years, as corroborated by this spatial analysis and meta-analyses of charcoal records.

    “This spatial analysis corroborates meta-analyses of charcoal records, which suggest that HIs have acted to decouple the fire–climate signal in recent years (44).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [44] Marlon J, et al. Climate and human influences on global biomass burning over the past two millennia. Nat Geosci. 2008;1:697–702. [Google Scholar] source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given
    § Results and Discussion

    The 14-y data record is only a snapshot of a continuously changing system.

    “and is only a snapshot of a continuously changing system.”
    Quote in the paperNot a substantial claim
50 of 50

  • The paper relies on this without support.

    A definition of global-scale units of fire is lacking.

    “In contrast to vegetation, a definition of global-scale units of fire is lacking.”

  • The paper relies on this without support.

    At global scales, fire regimes can be treated as analogous to biomes.

    “At global scales, fire regimes could be seen as analogous to biomes.”

  • The paper relies on this without support.

    Fire at a point in space is controlled by environmental characteristics and should change in a predictable manner along environmental gradients.

    “Like vegetation, the fire that occurs at a point in space is controlled by environmental characteristics, and should change in a predictable manner along environmental gradients.”

  • The paper relies on this without support.

    Fire is multidimensional, and focus on a single metric belies its complexity and importance within the Earth system.

    “This is problematic because fire is multidimensional, and focus on a single metric belies its complexity and importance within the Earth system.”

  • The paper relies on this without support.

    Interannual variability in area burned is higher when fires occur infrequently.

    “because interannual variability in area burned is higher when fires occur infrequently.”

  • The paper relies on this without support.

    The WWF terrestrial ecoregions map is the only global product derived from ground-truthed vegetation maps.

    “which is the only global product derived from ground-truthed vegetation maps”
6 of 6

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • The geographic distribution of fire has been mapped based on current global fire activity and classified into geographically distinct fire regimes called pyromes.

    “The geographic distribution of fire has been mapped based on current global fire activity (Andela et al., 2019;Krawchuk et al., 2009) and classified into geographically distinct fire regimes called pyromes (Archibald, Lehmann, Gomez-Dans, & Bradstock, 2013).”

    From Fire as a fundamental ecological process: Research advances and frontiers (2020) · cites this paper as Archibald, Lehmann, Gomez-Dans, & Bradstock, 2013

  • HFP scores are scaled per biome and encompass different socio-environmental configurations, which have different effects on fire activity across the globe.

    “However, scores are scaled per biome and, thus, encompass different socio-environmental configurations, which, in turn, have different effects on fire activity across the globe [35].”

    From A Global Index for Mapping the Exposure of Water Resources to Wildfire (2016) · cites this paper as [35]

  • The anthropogenic influence on fire activity is well known but still a matter of debate, as the nature of this influence is complicated.

    “The anthropogenic influence (AI) on fire activity is well known, but is still a matter of debate, as the nature of this influence is complicated [33-35].”

    From A Global Index for Mapping the Exposure of Water Resources to Wildfire (2016) · cites this paper as [35]

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Fig. S1C is cited for two different fire characteristics

    Minor

    The discussion cites Fig. S1C as fire-intensity data, whereas the methods identify Fig. S1C as the coefficient of variation in annual burned area.

1 of 1

Cites

Flagged first, then by citations

Research works printed but not linked: 43

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Cited by

Sorted by citations

Authors
Archibald, S., Lehmann, C. E. R., Gómez-Dans, J. L., & Bradstock, R. A.
Affiliations
  • University of the Witwatersrand (ZA)
  • Macquarie University (AU)
  • National Centre for Earth Observation and Department of Geography, University College London, London WC1E 6BT, United Kingdom; and
  • University of Wollongong (AU)
ORCID
Venue
Proceedings of the National Academy of Sciences
Publisher
National Academy of Sciences
Published
2013-04-04
Volume
110
Issue
16
Pages
6442-6447
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
DOI
10.1073/pnas.1211466110
PMC
PMC3631631
OpenAlex
W2037321678
Semantic Scholar
04cb7e174dc27fe9d0e5f9569027f694b2fb83b7
Cited by
845
References
9
Citations by year
2026: 111 · 2025: 93 · 2024: 64 · 2023: 116 · 2022: 82 · 2021: 65 · 2020: 60 · 2019: 53 · 2018: 51 · 2017: 40 · 2016: 45 · 2015: 38 · 2014: 23 · 2013: 3
FWCI
27.60
Type
journal article
Language
en
Open access
Locations
  • Proceedings of the National Academy of Sciences (publishedVersion)
  • Europe PMC (PubMed Central) (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • Research Online (University of Wollongong) (submittedVersion)
  • UCL Discovery (University College London) (submittedVersion)
Funders
Natural Environment Research Council (earth010003)
Topics
  • Physical Sciences › Environmental Science › Global and Planetary Change › Fire effects on ecosystems
  • Physical Sciences › Environmental Science › Ecology › Rangeland and Wildlife Management
  • Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Fire dynamics and safety research
Keywords
fire regimes, fire size, fire frequency, fire intensity, fire seasonality, fire extent, fire-climate relationships, biomes, precipitation seasonality, moisture availability, crown fire, grassland fires, fire regime change
MeSH terms
Bayes Theorem, Climate, Fires, Humans, Human Activities, Humidity, Models, Theoretical, Rain, Biota, Geographic Mapping

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-06.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-06.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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