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

作者：Maik Billing, Werner von Bloh, Matthew Forrest, Luke Oberhagemann, Christoph Müller, Susanne Rolinski, Jessica Hetzer, Simon Bowring, Alex Neidermeier, Thomas Hickler, Kirsten Thonicke · 发表于：Zenodo (CERN European Organization for Nuclear Research) · 年份：2026 · DOI：10.5281/zenodo.21701500 · 研究领域：Environmental science、Environmental resource management、Geography、Meteorology、Climatology、Physical geography

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...