• Energy Research

French forests are at the crossroads of multiple dynamics and expectations: while they are supposed to be managed to ensure multifunctionality, national policies mostly focus on their role of carbon sink as a remedy for climate change mitigation. Simultaneously, French forests are increasingly impacted by on-going climate change (droughts, heat waves, bio-aggressors, fires), which alters their functioning and survival – and raises adaptation issues. As a result, forest management is currently facing a key challenge: how can we promote forests’ ability to maintain wood production and carbon sequestration, without impacting their other contributions (such as providing biodiversity habitats, air and water filtering, soil protection, leisures…), while also considering their sensitivity to climate change? This is the question addressed by the FISSA project (ForecastIng forest Socio-ecosystems’ Sensitivity and Adaptation to climate change) – whose ultimate aim is to test complex forest management scenarios at national and local levels within three regional natural parks (Pyrénées Ariégeoises, Luberon and Morvan) – in a context of climate change. FISSA has been designed to enlighten ongoing controversy, in this context of tensions between mitigation and adaptation strategies, between our multiple expectations regarding forests’ roles, and regarding the practices to promote to respond to such a challenge. To do so, it relies on an interdisciplinary approach: while social sciences inform dynamics of discourses and practices through social surveys at both national and local levels, natural sciences assess the effects of different forest management and climate scenarios on forests’ contributions through process-based models of forest dynamics and functioning. At the interface, transdisciplinary approaches are implemented to collectively define the management scenarios to be implemented both at local and national levels. In this presentation, we highlight how inter- and transdisciplinarity are promoted in the project, and how they can shape the original assumptions of modelers. First, we discuss how this project ensures the inter- and transdisciplinary dialogue through diverse boundary objects, both conceptual (social-ecological system), methodological (participatory modelling) and practical (common field work and promotion of dialogue among the participants). Second, we illustrate the changes in the modelling process brought by inter- and transdisciplinary contributions. Qualitative surveys, focus groups and dialogue have shown that expectations towards modelling are multiple depending on the territories, the stakeholders involved and the considered scale: (i) nourish a scientific and societal debate and controversy around adaptation and mitigation, but also (ii) respond to an extreme and unknown event such as major forest diebacks; or (iii) anticipate a shift from traditional sylvicultural practices and inherited forests towards more desirable practices in the face of environmental and climate urges. We conclude on the interests and limits of participatory social-ecological modelling approaches to promote collective action in a context where uncertainties and tensions are unavoidable.

Studying the forest subsurface is a challenge because of its heterogeneous nature and difficult access. Traditional approaches used by ecologists to characterize the subsurface have a low spatial representativity. This review article illustrates how geophysical techniques can and have been used to get new insights into forest ecology. Near-surface geophysics offers a wide range of methods to characterize the spatial and temporal variability of subsurface properties in a non-destructive and integrative way, each with its own advantages and disadvantages. These techniques can be used alone or combined to take advantage of their complementarity. Our review led us to define three topics how near-surface geophysics can support forest ecology studies: 1) detection of root systems, 2) monitoring of water quantity and dynamics, and 3) characterisation of spatial heterogeneity in subsurface properties at the stand level. The number of forest ecology studies using near-surface geophysics is increasing and this multidisciplinary approach opens new opportunities and perspectives for improving quantitative assessment of biophysical properties and exploring forest response to the environment and adaptation to climate change.

Anticipating future fire activity at global and regional scales is critical in a changing climate. Indeed, fire seasons are expected to lengthen and fire prone areas are expected to extend, but the magnitude, location and timing of such increases remain uncertain. Moreover, an intensification is expected during the core of the fire season of already fire-prone regions. However, quantifying seasonal and spatial impacts of climate change on fire activity is challenging. Here, we projected future fire activities in Southern France using the Firelihood model. This Bayesian probabilistic model operates on a daily basis in 8-km pixels, allowing to analyze both seasonal and spatial distributions of fire activities in a framework integrating stochasticity. Projections were computed for 13 GCM-RCM couples under two RCP scenarios (4.5 and 8.5), assuming that the only factor of change in future fire activity was the daily fire weather. The fire season was defined as the period with fire-activity level higher than the level of the 15th of July of the present period. The fire prone region corresponded to locations with fire-activity levels higher than the 2nd level of a 5-level fire-activity scale derived from numbers of fires larger than 1ha, 100ha (N1ha and N100ha) and burnt areas (BA). Simulations under RCP8.5 show that large increases in fire activity should be expected from the mid-century and that the rate of increase should then accelerate, leading to up to three-fold increases for number of fires larger than 100ha by the end of the century. In particular, all metrics except N1ha increased faster than the mean FWI and even the mean DSR. Such increases were partly caused by a massive seasonal lengthening from 45-50 days to up to 125 days, equally distributed between spring and autumn. However, the intensification during the present fire season was found to contribute slightly more to the overall increase than the lengthening itself. For example, for N100ha, the intensification would represent a 280 % increase in fire activity with respect to the present seasonal reference, whereas the lengthening outside of the present season would represent +230%. The fire prone area would increase by 168%, shifting from 22 to 56% of region total area. However, the intensification inside the already fire-prone region was found to contribute more to the increase than the spatial extension. For example, for N100ha, the intensification would represent a 190% increase with respect to the present fire-prone regional reference, whereas the extension outside of this area would represent +110%. These drastic increases provide a good indication of the potential lengthening of the fire season, spatial extension and intensification of future fire activities under RCP 8.5, all three being importantly concerned, but dominated by intensification. Extending and lengthening suppression policies may allow to mitigate projected increases, but the intensification of fire activity during the core of the fire season overwhelm current fire suppression capacities.

Le changement climatique devrait, en Europe, conduire à une aggravation des risques naturels encourus par les forêts. Pour les régions méditerranéennes, les risques connus les plus importants sont la sécheresse, les incendies de forêt et les attaques d'insectes. Les projections du danger d'incendie de forêt indiquent que les feux seront plus fréquents et plus intenses en région méditerranéenne et que l'aire géographique soumise à ce risque s'étendra vers le nord de l'Europe. Ces projections à grande échelle reposent sur des relations empiriques établies entre le climat et un indicateur du danger d'incendie. Pour affiner ces projections et les appliquer aux échelles de la gestion forestière, dans un contexte de changement climatique, les processus biophysiques du fonctionnement des couverts forestiers qui déterminent l'état du combustible sont à considérer. Ces processus sont impactés par la sécheresse, et les pullulations d'insectes peuvent aussi modifier brutalement et fortement le combustible. Une fois le combustible connu, la prédiction de l'intensité et de l'impact des feux est possible grâce aux modèles physiques de propagation, y compris dans des conditions nouvelles de végétation. Dans cet article, nous rapportons les projections du danger d'incendie en Europe et discutons leurs limites, nous illustrons les interactions possibles entre pullulations d'insectes et incendies, et nous présentons nos travaux de modélisation du feu et du combustible forestier basée sur les processus qui relient le climat, la végétation et le feu. In Europe, climate change is expected to exacerbate natural risks in forests. For the Mediterranean regions, the most important known risks are drought, wildfires and insect attacks. The projections of forest fire danger indicate that fires will be more frequent and more intense in Mediterranean region and that the geographical area subjected to this risk will extend towards the north of Europe. These largescale projections rest on empirical relations linking climate variables and fire danger indices. To refine these projections and apply them to forest management scales, in a context of climate change, the biophysical processes of forest functioning that determine fuel moisture and fuel amount are to be considered. Drought impacts these processes, but insect outbreaks may also change fuels fast and strongly. Once fuel is known, fire intensity and impacts may be predicted thanks to physics-based models for fire behaviour, including in new fuel conditions. In this article, we report the projections of forest fire danger for Europe and discuss their limits, we illustrate the possible interactions between insect outbreaks and wildfires, and we describe our fuel and fire modelling approaches, which are based on processes linking climate, vegetation and fire.

Abstract High-resolution meteorological data are necessary to understand and predict climate-driven impacts on the structure and function of terrestrial ecosystems. However, the spatial resolution of climate reanalysis data and climate model outputs is often too coarse for studies at local/landscape scales. Additionally, climate model projections usually contain important biases, requiring the application of statistical corrections. Here we present ‘meteoland’, an R package that integrates several tools to facilitate the estimation of daily weather over landscapes, both under current and future conditions. The package contains functions: (1) to interpolate daily weather including topographic effects; and (2) to correct the biases of a given weather series (e.g., climate model outputs). We illustrate and validate the functions of the package using weather station data from Catalonia (NE Spain), re-analysis data and climate model outputs for a specific county. We conclude with a discussion of current limitations and potential improvements of the package.

Climate change is often expected to lead to an increase in wildfire danger. The Forest Fire Weather Index (FWI) and its subcomponents, like the Drought Code (DC), are widely used to forecast and project climatic fire danger. However, applications of such wildfire danger indices are subjected to different uncertainties. A first one is related to the ability of these indices to accurately predict empirical data of observed wildfires (“empirical uncertainty”); whereas a second lies in the projection of these indices, which is inherently affected by the spread among climatic input data available from different general and regional circulation models (“projection uncertainty”). It is crucial to take this aspect into account as uncertainties pile up in the modelling chains, what has seldom been done in the context of wildfires. Our study aims at exploring both types of uncertainties, and comparing their respective contributions to the global prediction. First, we analyse uncertainties related to the predictions of an empirical record of past fire observations (number of fire) over French Mediterranean area (Prométhée) using the FWI computed at an 8km resolution (using SAFRAN climatic input) for the historical period 1995-2015. We then investigate the uncertainty linked to climatic projections by projecting FWI and fire occurrence (based on the empirical relation calibrated under historical conditions) under two IPCC scenarios and using two GCM/RCM model combinations for the period 2005-2100. Predictions of fire occurrence under historical conditions reveal important bias both spatially and temporally, highlighting potential uncertainties in the global use of FWI to predict wildfire. FWI and fire occurrence projected under different RCP scenario also reveal an important spread. Ongoing work includes computation with additional models and the assessment of the relative weight of different uncertainty sources in the projection of wildfire risk.

AbstractIncreasing tree diversity is considered a key management option to adapt forests to climate change. However, the effect of species diversity on a forest's ability to cope with extreme drought remains elusive. In this study, we assessed drought tolerance (xylem vulnerability to cavitation) and water stress (water potential), and combined them into a metric of drought–mortality risk (hydraulic safety margin) during extreme 2021 or 2022 summer droughts in five European tree diversity experiments encompassing different biomes. Overall, we found that drought–mortality risk was primarily driven by species identity (56.7% of the total variability), while tree diversity had a much lower effect (8% of the total variability). This result remained valid at the local scale (i.e within experiment) and across the studied European biomes. Tree diversity effect on drought–mortality risk was mediated by changes in water stress intensity, not by changes in xylem vulnerability to cavitation. Significant diversity effects were observed in all experiments, but those effects often varied from positive to negative across mixtures for a given species. Indeed, we found that the composition of the mixtures (i.e., the identities of the species mixed), but not the species richness of the mixture per se, is a driver of tree drought–mortality risk. This calls for a better understanding of the underlying mechanisms before tree diversity can be considered an operational adaption tool to extreme drought. Forest diversification should be considered jointly with management strategies focussed on favouring drought‐tolerant species.