Changes in climate, land use, and land management impact the occurrence and severity of wildland fires in many parts of the world. This is particularly evident in Europe, where ongoing changes in land use have strongly modified fire patterns over the last decades. Although satellite data by the European Forest Fire Information System provide large-scale wildland fire statistics across European countries, there is still a crucial need to collect and summarize in-depth local analysis and understanding of the wildland fire condition and associated challenges across Europe. This article aims to provide a general overview of the current wildland fire patterns and challenges as perceived by national representatives, supplemented by national fire statistics (2009–2018) across Europe. For each of the 31 countries included, we present a perspective authored by scientists or practitioners from each respective country, representing a wide range of disciplines and cultural backgrounds. The authors were selected from members of the COST Action “Fire and the Earth System: Science & Society” funded by the European Commission with the aim to share knowledge and improve communication about wildland fire. Where relevant, a brief overview of key studies, particular wildland fire challenges a country is facing, and an overview of notable recent fire events are also presented. Key perceived challenges included (1) the lack of consistent and detailed records for wildland fire events, within and across countries, (2) an increase in wildland fires that pose a risk to properties and human life due to high population densities and sprawl into forested regions, and (3) the view that, irrespective of changes in management, climate change is likely to increase the frequency and impact of wildland fires in the coming decades. Addressing challenge (1) will not only be valuable in advancing national and pan-European wildland fire management strategies, but also in evaluating perceptions (2) and (3) against more robust quantitative evidence.

This paper presents a quantitative assessment of adaptation options in the context of forest fires in Europe under projected climate change. A standalone fire model (SFM) based on a state-of-the-art large-scale forest fire modelling algorithm is used to explore fuel removal through prescribed burnings and improved fire suppression as adaptation options. The climate change projections are provided by three climate models reflecting the SRES A2 scenario. The SFM’s modelled burned areas for selected test countries in Europe show satisfying agreement with observed data coming from two different sources (European Forest Fire Information System and Global Fire Emissions Database). Our estimation of the potential increase in burned areas in Europe under “no adaptation” scenario is about 200 % by 2090 (compared with 2000–2008). The application of prescribed burnings has the potential to keep that increase below 50 %. Improvements in fire suppression might reduce this impact even further, e.g. boosting the probability of putting out a fire within a day by 10 % would result in about a 30 % decrease in annual burned areas. By taking more adaptation options into consideration, such as using agricultural fields as fire breaks, behavioural changes, and long-term options, burned areas can be potentially reduced further than projected in our analysis.

[1] In this study we present an assessment of the impact of future climate change on total fire probability, burned area, and carbon (C) emissions from fires in Europe. The analysis was performed with the Community Land Model (CLM) extended with a prognostic treatment of fires that was specifically refined and optimized for application over Europe. Simulations over the 21st century are forced by five different high‐resolution Regional Climate Models under the Special Report on Emissions Scenarios A1B. Both original and bias‐corrected meteorological forcings is used. Results show that the simulated C emissions over the present period are improved by using bias corrected meteorological forcing, with a reduction of the intermodel variability. In the course of the 21st century, burned area and C emissions from fires are shown to increase in Europe, in particular in the Mediterranean basins, in the Balkan regions and in Eastern Europe. However, the projected increase is lower than in other studies that did not fully account for the effect of climate on ecosystem functioning. We demonstrate that the lower sensitivity of burned area and C emissions to climate change is related to the predicted reduction of the net primary productivity, which is identified as the most important determinant of fire activity in the Mediterranean region after anthropogenic interaction. This behavior, consistent with the intermediate fire‐productivity hypothesis, limits the sensitivity of future burned area and C emissions from fires on climate change, providing more conservative estimates of future fire patterns, and demonstrates the importance of coupling fire simulation with a climate driven ecosystem productivity model.

In this study, we present simulations of a burned area at a European scale for the period 1990–2009 conducted with the Community Land Model (CLM). By using statistics on fire counts and mean fire suppression time from the European Fire Database, we refined the parameterization of the functions describing human ignition/suppression, and we modified the description of biomass availability for fires. The results obtained with the modified model show an improvement of the description of the spatial and interannual variability of the burned area: the model bias is reduced by 45%, and the explained variance is increased by about 9% compared to the original parameterization of the model. The observed relationships between burned area, climate (temperature and precipitation), and aboveground biomass are also reproduced more accurately by the modified model. This is particularly relevant for the applicability of the model to simulate future fire regimes under different climate conditions. However, results showed an overestimation of the burned area for some European countries (e.g., Spain and France) and an underestimation in years with an extreme fire season in Mediterranean countries. Our results highlight the need for refining the parameterization of human ignition/suppression and fuel availability for regional application of fire models implemented in land surface models.

Climate change-induced heat waves increase the global risk of forest fires, intensifying biomass burning and accelerating climate change in a vicious cycle. This presents a challenge to the response system in heavily forested South Korea, increasing the risk of more frequent and large-scale fire outbreaks. This study aims to optimize IIASA’s wildFire cLimate impacts and Adaptation Model (FLAM)—a processed-based model integrating biophysical and human impacts—to South Korea for projecting the pattern and scale of future forest fires. The developments performed in this study include: (1) the optimization of probability algorithms in FLAM based on the national GIS data downscaled to 1 km² with additional factors introduced for national specific modeling; (2) the improvement of soil moisture computation by adjusting the Fine Fuel Moisture Code (FFMC) to represent vegetation feedbacks by fitting soil moisture to daily remote sensing data; and (3) projection of future forest fire frequency and burned area. Our results show that optimization has considerably improved the modeling of seasonal patterns of forest fire frequency. Pearson’s correlation coefficient between monthly predictions and observations from national statistics over 2016–2022 was improved from 0.171 in the non-optimized to 0.893 in the optimized FLAM. These findings imply that FLAM’s main algorithms for interpreting biophysical and human impacts on forest fire at a global scale are only applicable to South Korea after the optimization of all modules, and climate change is the main driver of the recent increases in forest fires. Projections for forest fire were produced for four periods until 2100 based on the forest management plan, which included three management scenarios (current, ideal, and overprotection). Ideal management led to a reduction of 60–70% of both fire frequency and burned area compared to the overprotection scenario. This study should be followed by research for developing adaptation strategies corresponding to the projected risks of future forest fires.

Consideration was given to the optimal control of investments in the economic growth model. The basic construction of the model is the production function relating the growth of production with the dynamics of production factors, and the investments in the production factors are the control parameters. The integral indicator of the discounted consumption index is the optimization functional. The Pontryagin principle of maximum for problems on infinite horizon was used to construct the optimal investment control. For the corresponding Hamiltonian system, considered were its qualitative properties such as existence and uniqueness of the steady state, properties of the eigenvalues and eigenvectors of the linearized system, and characteristics of the saddle point. This analysis allows one to obtain an algorithm to construct the optimal growth trajectories. The model was calibrated for the USA macroeconomic indicators.