Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/28322
Title: Modelling burned area in Africa
Authors: Lehsten, V.
Harmand, P.
Palumbo, Iiaria
Arneth, A.
First Published: 2010
Publisher: Copernicus GmbH (Copernicus Publications) on behalf of the European Geosciences Union (EGU)
Citation: Biogeosciences, 2010, 10 (7), pp. 3199-3214
Abstract: 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.
DOI Link: 10.5194/bg-7-3199-2010
ISSN: 1726-4170
eISSN: 1726-4189
Links: http://www.biogeosciences.net/7/3199/2010/bg-7-3199-2010.html
http://hdl.handle.net/2381/28322
Version: Publisher Version
Status: Peer-reviewed
Type: Journal Article
Rights: © Author(s) 2010. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Appears in Collections:Published Articles, Dept. of Geography

Files in This Item:
File Description SizeFormat 
10.5194_BG-7-3199-2010.pdf6.26 MBAdobe PDFView/Open


Items in LRA are protected by copyright, with all rights reserved, unless otherwise indicated.