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 regimessize, 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 grassfueled 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.fire-climate-vegetation feedbacks | energetic constraints | fire intensity | fire return period | fire size F ires occur with varying regularity and severity across almost every biome on Earth. 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. In contrast to vegetation, a definition of global-scale units of fire is lacking.Fire is often described in terms of a fire regime, which represents a particular combination of fire characteristics, such as frequency, intensity, size, season, type, and extent (1, 2). It describes the repeated pattern of fire at a location in space. Fire regimes were originally used to explain plant responses to fire (such as resprouting or seroteny) (1). However, characterizing fire regimes is also necessary when quantifying emissions from fires (3) and planning fire suppression and control (4), and is particularly important if we hope to predict how patterns of fire might change in response to environmental and human drivers (5, 6). At global scales, fire regimes could be seen as analogous to biomes.To date, global analyses have used satellite-derived active fire and burned area data to describe the extent, interannual variability, and seasonality of burning (3,(7)(8)(9). This has contributed to an emerging global theory of fire that highlights two major energetic controls of burned area: fuel and weather (10-13)...

Non-native, invasive grasses have been linked to altered grass-fire cycles worldwide. Although a few studies have quantified resulting changes in fire activity at local scales, and many have speculated about larger scales, regional alterations to fire regimes remain poorly documented. We assessed the influence of large-scale Bromus tectorum (hereafter cheatgrass) invasion on fire size, duration, spread rate, and interannual variability in comparison to other prominent land cover classes across the Great Basin, USA. We compared regional land cover maps to burned area measured using the Moderate Resolution Imaging Spectroradiometer (MODIS) for 2000-2009 and to fire extents recorded by the USGS registry of fires from 1980 to 2009. Cheatgrass dominates at least 6% of the central Great Basin (650 000 km(2) ). MODIS records show that 13% of these cheatgrass-dominated lands burned, resulting in a fire return interval of 78 years for any given location within cheatgrass. This proportion was more than double the amount burned across all other vegetation types (range: 0.5-6% burned). During the 1990s, this difference was even more extreme, with cheatgrass burning nearly four times more frequently than any native vegetation type (16% of cheatgrass burned compared to 1-5% of native vegetation). Cheatgrass was also disproportionately represented in the largest fires, comprising 24% of the land area of the 50 largest fires recorded by MODIS during the 2000s. Furthermore, multi-date fires that burned across multiple vegetation types were significantly more likely to have started in cheatgrass. Finally, cheatgrass fires showed a strong interannual response to wet years, a trend only weakly observed in native vegetation types. These results demonstrate that cheatgrass invasion has substantially altered the regional fire regime. Although this result has been suspected by managers for decades, this study is the first to document recent cheatgrass-driven fire regimes at a regional scale.

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