Veiko Lehsten

Wildfires are a wide spread global phenomenon. Their activity peaks in the tropical savannas, especially in the African continent, where fires are a key component of ecosystem dynamics. Fires affect the ecological balance between trees and grasses in savannas with concomitant effects on biodiversity, soil fertility and biogeochemical cycles. Large amounts of trace greenhouse gases and aerosols from wildfires are

Fire is the most important ecological and forest disturbance agent worldwide, is a major way by which carbon is transferred from the land to the atmosphere, and is globally a significant source of greenhouse gases and aerosols. Wildfires across all major biome types globally consume about 5% of net annual terrestrial primary production per annum, and release about 2-4 Pg C per annum, of which approximately 0.6 Pg C comes from tropical deforestation and below-ground peat fires. The global figure is equivalent to about 20-30% of global emissions from fossil fuels. Tropical savannas comprise the largest areas burned and greatest emissions sources from vegetation wildfires. Fires in Mediterranean forests and shrublands, tropical forests and boreal forests are also significant sources of emissions because they are generally characterised by much higher fuel loads per unit area compared with grasslands. Improved satellite data and sophisticated biogeochemical modeling enables emis-sions a...

ABSTRACT Aim: To reconstruct spatial and temporal patterns of European fire activity during the Holocene and to explore their potential drivers, by relating biomass burning to simulated biotic and abiotic parameters. Location: Europe. Methods: Holocene fire activity was investigated based on 156 sedimentary charcoal records from lakes and peat bogs across Europe. Charcoal data covering the last 9000 years were statistically compared with palaeoclimate data derived from the Max Planck Institute for Meteorology/University of Wisconsin-Madison Earth System Model, with vegetation and fire indices simulated with the dynamic vegetation model LPJ-GUESS and with two independent scenarios of past anthropogenic land-cover change. Results: The combined sedimentary charcoal records suggest that there was little fire activity during the early and the middle Holocene compared with recent millennia. A progressive increase in fire frequency began around 3500 cal. yr BP. and continues into the late Holocene. Biomass burning rose sharply from 250 cal. yr BP onwards, reaching a maximum during the early Industrial Era and then declining abruptly. When considering the whole Holocene, the long-term control of fire is best explained by anthropogenic land-cover change, litter availability and temperature-related parameters. Main conclusions: While the general patterns found across Europe suggest the primary role of vegetation, precipitation and temperature-related parameters in explaining fire dynamics during the early Holocene, the increase in fire activity observed in the mid–late Holocene is mainly related to anthropogenic land-cover changes, followed by vegetation and temperature-related parameters. The 20th-century decline in biomass burning seems to be due to increased landscape fragmentation and active fire suppression policies. Our hypothesis that human activities played a primary role in Holocene biomass burning across Europe could be tested by improved palaeoclimate reconstructions and more refined representations of anthropogenic fires in climate and vegetation models.

The analysis of co-occurrence matrices is a common practice to evaluate community structure. The observed data are compared with a ''null model'', a randomised co-occurrence matrix derived from the observation by using a statistic, e.g. the C-score, sensitive to the pattern investigated. The most frequently used algorithm, ''sequential swap'', has been criticised for not sampling with equal frequencies thereby calling

The simulation of current and projected wildfires is essential for predicting crucial aspects of vegetation patterns, biogeochemical cycling as well as pyrogenic emissions across the African continent. This study uses a data-driven approach to parameterize two burned area models applicable to dynamic vegetation models (DVMs) and Earth system models (ESMs). We restricted our analysis to variables for which either projections based on climate scenarios are available, or that are calculated by DVMs, and we consider a spatial scale of one degree as the scale typical for DVMs and ESMs. By using the African continent here as an example, an analogue approach could in principle be adopted for other regions, for global scale dynamic burned area modelling. We used 9 years of data (2000-2008) for the variables: precipitation over the last dry season, the last wet season and averaged over the last 2 years, a fire-danger index (the Nesterov index), population density, and annual proportion of area burned derived from the MODIS MCD45A1 product. Two further variables, tree and herb cover were only available for 2001 as a remote sensing product. Since the effect of fires on vegetation depends strongly on burning conditions, the timing of wildfires is of high interest too, and we were able to relate the seasonal occurrence of wildfires to the daily Nesterov index. We parameterized two generalized linear models (GLMs), one with the full variable set (model VC) and one considering only climate variables (model C). All introduced variables resulted in an increase in model performance. Model VC correctly predicts the spatial distribution and extent of fire prone areas though the total variability is underrepresented. Model VC has a much lower performance in both aspects (correlation coefficient of predicted and observed ratio of burned area: 0.71 for model VC and 0.58 for model C). We expect the remaining variability to be attributed to additional variables which are not available at a global scale and thus not incorporated in this study as well as its coarse resolution. An application of the models using climate hindcasts and projections ranging from 1980 to 2060 resulted in a strong decrease of burned area of ca. 20-25%. Since wildfires are an integral part of land use practices in Africa, their occurrence is an indicator of areas favourable for food production. In absence of other compensating land use changes, their projected decrease can hence be interpreted as a indicator for future loss of such areas.