Jeanne Poughon

Increasing temperature and drought conditions can result in leaf dehydration and summer defoliation even in drought-adapted tree species such as the Mediterranean evergreen oak Quercus ilex. This phenomenon was widespread in forests of Southern France in 2022-2023 when record-breaking temperatures of 2022 were associated with two consecutive years of low precipitation, severe drought episodes and recurrent heatwaves.Using the 20-year data series (2001-2021) of eddy-covariance carbon and water fluxes measured at the ICOS Mediterranean forest site FR-Pue (Puéchabon) prior to this event, we assess the impacts of these two exceptional years on the carbon budget of the forest. While the Puéchabon forest always behaved as a net carbon sink between 2001 and 2021, with an annual net ecosystem exchange (NEE) ranging between -450 and -137 gC m-2 y-1, the carbon balance was reversed to a net annual carbon source of +14 and +65 gC m-2 y-1 in 2022 and 2023, respectively. This anomaly is caused by a deficit of photosynthetic carbon uptake, as leaf physiology was severely impacted by both water stress and heat stress. Significantly lower photosynthetic rates than in the previous years were, however, not restricted to the most stressful conditions of heat or soil water deficit but manifested under most meteorological conditions even outside the summer period. This observation suggests that neither heat nor drought alone can explain the photosynthesis limitation in 2022 and 2023 but that the two acted in synergy. It also demonstrates that such extreme meteorological events have long lasting effects on tree physiology, mediated by cell physiological damage, leaf hydraulic failure and canopy dieback that limit photosynthetic recovery when favorable temperature and soil moisture conditions return.Interestingly, these negative effects on photosynthesis were not observed during the following year 2024 when a complete recovery of photosynthetic rates was achieved with the production of new leaves, highlighting a strong resilience of Quercus ilex to drought and heat. Nevertheless, the annual carbon budget in 2024 was also particularly low because of an excess of total ecosystem respiration compared to the long-term mean. The higher respiration rates in 2024 could be caused by the decomposition of dead trees and organs after the extreme years 2022-2023, and by the reallocation of trees carbon reserves to the production of short-lived organs such as new leaves and seeds.This study is, yet, a rare example of an inversion of a forest carbon balance driven merely by meteorological conditions and it highlights the value of long-term observations to better understand and interpret the consequences of extreme events on ecosystem functioning.

Predicting the future carbon balance of forests, and their carbon sequestration capacity, requires a precise understanding of how gross primary productivity (GPP) is partitioned among autotrophic respiration and the different compartments of the net primary productivity (NPP). Studies show an important variability of the NPP:GPP ratio across forest, and a partial decoupling between GPP and wood production in forest ecosystems. This suggests an interannual variation of carbon allocation among tree functions and organs, which is generally not accounted for in most dynamic vegetation models. Using GPP estimated from eddy-covariance measurements and independent above-ground NPP measured over 6 to 20 years on six forest sites (5 sites in France belonging to the ICOS network and one site in Brazil), we explored the interannual variations in GPP partitioning to aboveground growth and its distribution among years and aboveground organs (wood, leaves, fruits, flowers).The partitioning of GPP to aboveground biomass varied considerably across sites, with Mediterranean evergreen forests showing the lowest values (15% and 18%), temperate forests intermediate values (21-37%), and the tropical eucalypt site showing the highest fraction (48%). At four of the sites, biomass production exhibited a larger inter-annual variability than did GPP, suggesting a greater sensitivity to environmental controls of the carbon sinks than the carbon source. All sites but one exhibited a significant correlation between annual aboveground NPP and annual GPP, but with small R² values between 0.2 and 0.6, thus showing a rather weak coupling between the two productivities. The coupling was generally even weaker for wood production alone (generally considered as the main carbon sequestration in forests) than for total aboveground NPP (which also includes short-lived organs such as leaves that will rapidly decompose). Finally, we observed that the inter-annual correlations between GPP and biomass production varied depending on the onset of the GPP integration time-window, indicating different temporal lags between assimilation and growth according to species and organs.This works highlights the necessity to take into account inter-annual variations of carbon allocation in forest carbon balances, and to better understand of the climatic drivers of sink activity including potential lags between assimilation, storage and growth.

Forestry industry requires high-quantity and quality seeds for afforestation and assisted migration programs. Finding reliable non-destructive methods to characterize seeds would significantly enhance efforts to identify climate-adapted populations. This study presents near-infrared (NIR) spectroscopy models to classify seed origin and predict germination characteristics at different temperatures non-destructively. We focus on Abies alba Mill., a key European forest tree with genetic variation along climatic gradients and seeds with shallow physiological dormancy. Seeds from six populations were analyzed using NIR spectroscopy, and germination was tested at 15°C, 20°C, and 25°C after stratification treatments at 4°C (0 or 3 weeks). Population classification accuracy using Partial Least Squares Discriminant Analysis was 69%, with significant NIR peaks at 1712, 1929, and 2111 nm, linked to moisture content and storage compounds. NIR spectra explained 51% and 65% of the variation in germination probability and timing using Partial Least Squares Regression, with significant peaks at 1712, 1929, 2111, 1632, and 2073 nm. General Linear Mixed-Effects Models showed that a NIR predictor contributed to 39% of the germination probability variance explained by fixed-effects, and the stratification treatment was the most important driver explaining germination time. Our results proved the utility of NIR-based tools to effectively classify bulked seeds and predict germination, opening new perspectives to nursery and forestry sectors and populations’ adaptation and adjustments to warming climate. This study will facilitate further investigations on the physiological processes that occur during dormancy, a critical process for forest regeneration given the expected impact of shorter and warmer winters on seed behavior.