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In this study, we use simulations from seven global vegetation models to provide the first multi‐model estimate of fire impacts on global tree cover and the carbon cycle under current climate and anthropogenic land use conditions, averaged for the years 2001–2012. Fire globally reduces the tree covered area and vegetation carbon storage by 10%. Regionally, the effects are much stronger, up to 20% for certain latitudinal bands, and 17% in savanna regions. Global fire effects on total carbon storage and carbon turnover times are lower with the effect on gross primary productivity (GPP) close to 0. We find the strongest impacts of fire in savanna regions. Climatic conditions in regions with the highest burned area differ from regions with highest absolute fire impact, which are characterized by higher precipitation. Our estimates of fire‐induced vegetation change are lower than previous studies. We attribute these differences to different definitions of vegetation change and effects of anthropogenic land use, which were not considered in previous studies and decreases the impact of fire on tree cover. Accounting for fires significantly improves the spatial patterns of simulated tree cover, which demonstrates the need to represent fire in dynamic vegetation models. Based upon comparisons between models and observations, process understanding and representation in models, we assess a higher confidence in the fire impact on tree cover and vegetation carbon compared to GPP, total carbon storage and turnover times. We have higher confidence in the spatial patterns compared to the global totals of the simulated fire impact. As we used an ensemble of state‐of‐the‐art fire models, including effects of land use and the ensemble median or mean compares better to observational datasets than any individual model, we consider the here presented results to be the current best estimate of global fire effects on ecosystems. [ABSTRACT FROM AUTHOR]

Fire is a key driver in savannah systems and widely used as a land management tool. Intensifying human land uses are leading to rapid changes in the fire regimes, with consequences for ecosystem functioning and composition. We undertake a novel analysis describing spatial patterns in the fire regime of the Serengeti‐Mara ecosystem, document multidecadal temporal changes and investigate the factors underlying these patterns. We used MODIS active fire and burned area products from 2001 to 2014 to identify individual fires; summarizing four characteristics for each detected fire: size, ignition date, time since last fire and radiative power. Using satellite imagery, we estimated the rate of change in the density of livestock bomas as a proxy for livestock density. We used these metrics to model drivers of variation in the four fire characteristics, as well as total number of fires and total area burned. Fires in the Serengeti‐Mara show high spatial variability—with number of fires and ignition date mirroring mean annual precipitation. The short‐term effect of rainfall decreases fire size and intensity but cumulative rainfall over several years leads to increased standing grass biomass and fuel loads, and, therefore, in larger and hotter fires. Our study reveals dramatic changes over time, with a reduction in total number of fires and total area burned, to the point where some areas now experience virtually no fire. We suggest that increasing livestock numbers are driving this decline, presumably by inhibiting fire spread. These temporal patterns are part of a global decline in total area burned, especially in savannahs, and we caution that ecosystem functioning may have been compromised. Land managers and policy formulators need to factor in rapid fire regime modifications to achieve management objectives and maintain the ecological function of savannah ecosystems. [ABSTRACT FROM AUTHOR]

The factors controlling the extent of fire in Africa south of the equator were investigated using moderate resolution (500 m) satellite-derived burned area maps and spatial data on the environmental factors thought to affect burnt area. A random forest regression tree procedure was used to determine the relative importance of each factor in explaining the burned area fraction and to address hypotheses concerned with human and climatic influences on the drivers of burnt area. The model explained 68% of the variance in burnt area. Tree cover, rainfall in the previous 2 years, and rainfall seasonality were the most important predictors. Human activities – represented by grazing, roads per unit area, population density, and cultivation fraction – were also shown to affect burnt area, but only in parts of the continent with specific climatic conditions, and often in ways counter to the prevailing wisdom that more human activity leads to more fire. The analysis found no indication that ignitions were limiting total burnt area on the continent, and most of the spatial variation was due to variation in fuel load and moisture. Split conditions from the regression tree identified (i) low rainfall regions, where fire is rare; (ii) regions where fire is under human control; and (iii) higher rainfall regions where burnt area is determined by rainfall seasonality. This study provides insights into the physical, climatic, and human drivers of fire and their relative importance across southern Africa, and represents the beginnings of a predictive framework for burnt area. [ABSTRACT FROM AUTHOR]