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ZENODO
Dataset . 2026
Data sources: ZENODO
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
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Model Code and Data for "Future projections of burned area in Europe highlight the importance of human action"

Authors: Billing, Maik; von Bloh, Werner; Forrest, Matthew; Oberhagemann, Luke; Müller, Christoph; Rolinski, Susanne; Hetzer, Jessica; +4 Authors

Model Code and Data for "Future projections of burned area in Europe highlight the importance of human action"

Abstract

This repository contains the LPJmL-SPITFIRE and LPJmL-BASE model code; R-code and data used to generate figures in the manuscript "Future projections of burned area in Europe highlight the importance of human action" The datasets are licensed under CC-BY. The LPJmL model code is licensed under AGPLv3. The R scripts are released under the BSD-2-Clause license. Manuscript abstract Wildfires are often a natural part of many European ecosystems, but human activities through land-use, other socio-economic factors and climate change have significantly changed how fires behave. Anthropogenic climate change is already intensifying fire prone weather and increasing wildfire risk across Europe with risk expected to grow sharply in coming decades. Past experience suggests that human action, such as fuel management and improved fire suppression capacity, can reduce wildfire spread and intensity. However, whether current or future efforts can counter rising risks under continued climate change remains uncertain. In this study, we assess the role of socio-economic factors and biophysical factors in shaping future fire regimes across Europe. Using two fire models (SPITFIRE and BASE) coupled with the fire-enabled Dynamic Global Vegetation Model LPJmL, we simulate future burned area under two socio-economic and greenhouse gas concentration pathways (SSP1-2.6 and SSP3-7.0). We also run experiments where socio-economic factors are held constant to isolate their influence. Our findings show that both biophysical and socio-economic factors strongly affect future wildfire activity. Fire weather and fire management capacity are important drivers, while population density, vegetation shifts and land use matter more at regional scales. By the end of the century, intensified fire weather alone could increase annual burned area by approximately +39% under a low emission scenario (SSP1-2.6) and by nearly +192% under a high emission scenario (SSP3-7.0). Continued improvements in fire management capacity could substantially moderate these increases, reducing burned area by 72–92% compared to scenarios without these improvements. However, under strong climate change, fire activity still rises in about 55% of Europe’s fire prone regions, even if investments in fire management capacity continue at current levels. Overall, improved wildfire management capacity has the potential to greatly limit impacts of worsening fire weather, but may not fully offset strong climate change impacts.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average