Causal relationships versus emergent patterns in the global controls of fire frequency

Abstract

Abstract. Global controls on month-by-month fractional burnt area (2000)(2001)(2002)(2003)(2004)(2005) were investigated by fitting a generalised linear model (GLM) to Global Fire Emissions Database (GFED) data, with 11 predictor variables representing vegetation, climate, land use and potential ignition sources. Burnt area is shown to increase with annual net primary production (NPP), number of dry days, maximum temperature, grazing-land area, grass/shrub cover and diurnal temperature range, and to decrease with soil moisture, cropland area and population density. Lightning showed an apparent (weak) negative influence, but this disappeared when pure seasonal-cycle effects were taken into account. The model predicts observed geographic and seasonal patterns, as well as the emergent relationships seen when burnt area is plotted against each variable separately. Unimodal relationships with mean annual temperature and precipitation, population density and gross domestic product (GDP) are reproduced too, and are thus shown to be secondary consequences of correlations between different controls (e.g. high NPP with high precipitation; low NPP with low population density and GDP). These findings have major implications for the design of global fire models, as several assumptions in current models -most notably, the widely assumed dependence of fire frequency on ignition rates -are evidently incorrect.

The status and challenge of global fire modelling

“…However, in general, when climate and vegetation factors are accounted for, there is a monotonic negative relationship between burnt area and human population -i.e. burnt area decreases with increasing human presence (Bistinas et al, 2014;Knorr et al, 2014). The unimodal statistical relationship of burnt area with population density (and other socio-economic variables such as gross domestic product (GDP) that are linked to population density) results from the co-variance of population density with vegetation production and moisture (Bistinas et al, 2014).…”

“…Morton et al, 2008). Humans may also suppress fire directly or indirectly through land-use change (Bistinas et al, 2014;Knorr et al, 2014;Andela and van der Werf, 2014). Grazing herbivores (the densities of which are also often controlled by humans) can also decrease fire occurrence by reducing fuel loads (Pachzelt et al, 2015).…”

Fire Influences on Atmospheric Composition, Air Quality and Climate

“…There are several key linkages between fire, the atmosphere and the biosphere, with implications for climate change, ecosystems, human health and the economy. Forest fire activity is strongly affected by climate change, since temperature, humidity and precipitation can affect the flammability of vegetation [3,4] and since vegetation itself undergoes changes driven by climate change. Furthermore, fire activity depends on the ignition sources available in a region, which can be natural (lightning) or anthropogenic (accidental or deliberate) [4], with the natural sources potentially influenced by climate change as well.…”

“…CO 2 emissions can have important implications for CO 2 concentrations and understanding the carbon cycle but do not directly affect atmospheric chemistry or contribute to air quality degradation. Other carbonaceous emissions (BC, OC, CO, NMVOCs and methane (CH 4 ), for which biomass burning is only a minor source) and NO x can be important for both air pollution/chemistry and climate. NO x , NMVOCs, CO and methane are important precursors of tropospheric ozone, which is a secondary pollutant and is not directly emitted by fires [9•, 10].…”

A fire model with distinct crop, pasture, and non-agricultural burning: Use of new data and a model-fitting algorithm for FINALv1

“…Second, the functions elaborated by Li et al (2013) are somewhat ad-hoc, not 30 taking into account other variables that might be responsible for the observed relationships. Bistinas et al (2014), for example,…”