How contemporary bioclimatic and human controls change global fire regimes


Anthropogenically driven declines in tropical savannah burnt area1,2 have recently received attention due to their effect on trends in global burnt area3,4. Large-scale trends in ecosystems where vegetation has adapted to infrequent fire, especially in cooler and wetter forested areas, are less well understood. Here, small changes in fire regimes can have a substantial impact on local biogeochemistry5. To investigate trends in fire across a wide range of ecosystems, we used Bayesian inference6 to quantify four primary controls on burnt area: fuel continuity, fuel moisture, ignitions and anthropogenic suppression. We found that fuel continuity and moisture are the dominant limiting factors of burnt area globally. Suppression is most important in cropland areas, whereas savannahs and boreal forests are most sensitive to ignitions. We quantify fire regime shifts in areas with more than one, and often counteracting, trends in these controls. Forests are of particular concern, where we show average shifts in controls of 2.3–2.6% of their potential maximum per year, mainly driven by trends in fuel continuity and moisture. This study gives added importance to understanding long-term future changes in the controls on fire and the effect of fire trends on ecosystem function.

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Fig. 1: Limitation on burnt area by each control.
Fig. 2: The relative limits and sensitivity imposed on burnt area by each control.
Fig. 3: Drivers of trends in burnt area.
Fig. 4: Normalized trends in controls on burnt area for the period 2000–2014.
Fig. 5: Annual average effects of trends in controls on burnt area.

Data availability

The data that support the findings in this study are available from the corresponding author on request.

Code availability

We were able to find control relationships using a Bayesian Inference framework that could be extended to other areas of high uncertainty in land surface modelling and that we have made available for use. See for more information.


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The contribution by D.K. was supported by the UK Natural Environment Research Council through The UK Earth System Modelling Project (UKESM, grant no. NE/N017951/1). N.D. was funded by the European Research Council through Reading University (GC2.0 grant no. 694481). C.B. was supported by the Newton Fund through the Met Office Climate Science for Service Partnership Brazil.

Author information

D.K. and I.B. devised the modelling framework. R.W. designed the Bayesian inference framework. D.K., I.B. and C.B. identified drivers for use in the framework. D.K., I.B., C.B. and T.M. designed the limitation and sensitivity assessments and fire regime shift index. D.K., C.B. and N.D. collated and regridded input data. D.K. performed trend analysis. D.K. wrote the first draft of the paper with input from I.B., C.B. and R.W. All authors contributed to the final manuscript.

Correspondence to Douglas I. Kelley.

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The authors declare no competing interests.

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Peer review information: Nature Climate Change thanks Niels Andela, Sam Rabin and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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