Background and aims Decline in tree species is a complex phenomenon involving multiple factors, among edaphic conditions are assumed to play an important role as factor of predisposition of forests to this process. In this regard, scarce information exists on the effects of the internal variability of the soil with depth on the predisposition to decline, an aspect that requires further evaluation. Methods Characterization of the internal variability of soil was carried out at 20 sites (10 with evidence of decline and 10 with no signs of decline) and the results analyzed to determine their role in modulating the effect of drought, which is the main cause of the observed decline in Aleppo pine stands in the Comunidad Valenciana (Spain). Results The soil properties found to be the most explanatory were those associated with soil quality in terms of available space for root exploration, which is vital for nutrition and, above all, water uptake. Episodes of decline are associated with stands where soils have a shallow effective depth due to a low degree of profile development or through marked textural anisotropy because of particularly clayey horizons that cause abrupt changes in permeability and aeration. Conclusion The internal variability of the soil, closely linked to the degree of pedogenetic development, is identified as a factor that plays an important role in predisposing the vegetation to the effects of drought.

In recent decades, increases in severe drought, heat extremes, and pest burden have contributed to increased global tree mortality. These risks are expected to be exacerbated under projected climate change. So far, observations of tree mortality are mainly based on manual field surveys with limited spatial coverage. The lack of accurate tree mortality data over large areas has limited the development and applications of tree mortality models. However, a combination of high-resolution remote sensing data, such as aerial imagery and automated imagery analysis, may provide a solution to this problem. In this study, we analysed the dynamics and drivers of forest canopy mortality in 117 366 ha of boreal forest in Southeast Finland, between 2017 and 2023. For this purpose, we first developed a fully convolutional semantic segmentation model to automatically segment forest canopy mortality from aerial imagery in 2017, 2020, and 2023 with a spatial resolution of 0.5 m. Secondly, we trained the model using a dataset consisting of 32555 canopy mortality segments manually delineated from aerial imagery from various geographic regions in Finland. The trained model showed high accuracy in detecting forest canopy mortality (with an F1 score of 0.86-0.93) when tested using an independent test set. To estimate standing deadwood volume, we combined the observed yearly forest canopy mortality with open forest resource information based on extensive field campaigns and airborne laser scanning. In our study area, forest canopy mortality increased from 23.4 ha (0.02 % of the study area) to 207.8 ha (0.18 %) between 2017 and 2023. Consequently, standing deadwood volume was estimated to increase from 5192 m3 (0.04 m3/ha) to 52800 m3 (0.45 m3/ha) during the study period. Both the volume of standing deadwood and the extent of forest canopy mortality increased exponentially. The majority of the forest canopy mortality occurred in Norway sprucedominated forests (64.1-77.3 %) on relatively fertile soils (81.6-84.7 %) while 20-25 % of the forest canopy mortality occurred in Scots pine-dominated forests. The average age of stands where mortality was observed was between 60 and 70 years old (2017 = 69.7 years and 2023 = 62.6 years), indicating that mature forests were more susceptible to mortality than younger stands. Our findings highlight an exponential increase in forest canopy mortality over a relatively short time span (6 years). The increasing risk of tree mortality in boreal forests underlines the urgent need for large-scale and spatially accurate monitoring to keep up to date with fast-paced changes in boreal forest mortality. As climate change increases drought, extreme heat and bark beetle outbreaks, consistent canopy mortality mapping is essential for implementing timely risk management measures in forestry.

The record-breaking drought in 2018 caused premature leaf discoloration and shedding (early browning) in many beech (Fagus sylvatica L.) dominated forests in Central Europe. However, a high degree of variability in drought response among individual beech trees was observed. While some trees were severely impacted by the prolonged water deficits and high temperatures, others remained vital with no or only minor signs of crown vitality loss. Why some beech trees were more susceptible to drought-induced crown damage than others and whether growth recovery is possible are poorly understood. Here, we aimed to identify growth characteristics associated with the variability in drought response between individual beech trees based on a sample of 470 trees in northern Switzerland. By combining tree growth measurements and crown condition assessments, we also investigated the possible link between crown dieback and growth recovery after drought. Beech trees with early browning exhibited an overall lower growth vigor before the 2018 drought than co-occurring vital beech trees. This lower vigor is mainly indicated by lower overall growth rates, stronger growth declines in the past decades, and higher growth-climate sensitivity. Particularly, warm previous year summer conditions negatively affected current growth of the early-browning trees. These findings suggest that the affected trees had less access to critical resources and were physiologically limited in their growth predisposing them to early browning. Following the 2018 drought, observed growth recovery potential corresponded to the amount of crown dieback and the local climatic water balance. Overall, our findings emphasize that beech-dominated forests in Central Europe are under increasing pressure from severe droughts, ultimately reducing the competitive ability of this species, especially on lowland sites with shallow soils and low water holding capacity.

The present study analyzes for the first time the usefulness of the synergy between UAV-multispectral data and biomass-chlorophyll indices to discriminate and map carob trees dieback and damages. To achieve so, the UAV flight was performed over a carob forest located in a valley of a watershed in the Moroccan Middle-Atlas Mountain. The UAV data were rigorously pre-processed and twelve biomass-chlorophyll indices were implemented, analysed (spectrally and radiometrically), and validated using the ground truth. Then, a histogram thresholding classification was applied to the index offering the best performance. The results obtained pointed out that the TDVI and CIG indices have similar and good dynamic range values, and better performance than the other indices tested. They are well correlated, completely independent of soil background artefacts, and relatively avoid linearity and saturation problems. They showed a curvilinear relationship between their computed values and the considered classes (i.e., bare soil, healthy, dieback, and dead trees). The validation shows that TDVI and CIG are sensitive to the carob spatial variations, thus allowing an excellent land-use separating power, predicting early warning signals of dieback, and providing useful bio-physiological information about carob tree conditions. Furthermore, the results highlighted the radiometric and spectral performance of the DJI Phantom-4 camera for powerful sensitivities in discriminating carob forest classes. This simple and quick method can be a useful tool for decision support for monitoring and protecting carob forests on a large scale to promote sustainable development.