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European ash (Fraxinus excelsior) and narrow-leafed ash (F. angustifolia) are keystone forest tree species with a broad ecological amplitude and significant economic importance. Besides global warming both species are currently under significant threat by an invasive fungal pathogen that has been spreading progressively throughout the continent for almost three decades. Ash dieback caused by the ascomycete Hymenoscyphus fraxineus is capable of damaging ash trees of all age classes and often ultimately leads to the death of a tree after years of progressively developing crown defoliation. While studies at national and regional level already suggested rapid decline of ash populations as a result of ash dieback, a comprehensive survey at European level with harmonized crown assessment data across countries could shed more light into the population decline from a pan-European perspective and could also pave the way for a new conservation strategy beyond national boarders. Here we present data from the ICP Forests Level I crown condition monitoring from 27 countries resulting in > 36,000 observations. We found a substantial increase in defoliation and mortality over time indicating that crown defoliation has almost doubled during the last three decades. Hotspots of mortality are currently situated in southern Scandinavia and north-eastern Europe. Overall survival probability after nearly 30 years of infection has already reached a critical value of 0.51, but with large differences among regions (0.20–0.86). Both a Cox proportional hazard model as well as an Aalen additive regression model strongly suggest that survival of ash is significantly lower in locations with excessive water regime and which experienced more extreme precipitation events during the last two decades. Our results underpin the necessity for fast governmental action and joint rescue efforts beyond national borders since overall mean defoliation will likely reach 50% as early as 2030 as suggested by time series forecasting. [ABSTRACT FROM AUTHOR]

Key message: In a comparison of six methods of estimating foliage clumping, logarithmic methods were found to be the most suitable for validating remote sensing-based clumping maps. Abstract: The clumping index is a measure describing the spatial aggregation of foliage elements and has an important effect on radiation transfer in canopies. Quantifying the clumping index from field-based measurements has shown to be complicated, as values presented in literature vary substantially between methods. The goal of this work was to improve on previous comparison of beyond-shoot clumping quantification methods over Järvselja RAMI test sites by including additional methods as well as emphasizing the temporal variability of the clumping index by including two phenologically contrasting moments in the growing season. We show that while apparent clumping, digital cover photography-based methods and clumping from gap size distribution coincide well, they result in the maximum clumping value that should be considered in any case, whereas logarithmically based methods might provide more accurate estimates of clumping. The results are of great importance for the correct assessment of foliage clumping from space, as well as for current attempts to assess clumping using airborne and terrestrial laser scanning. [ABSTRACT FROM AUTHOR]

Forest reflectance models are able to contribute to the interpretation of satellite images over forested areas. A multipurpose forest reflectance model, its basic ideas, model input and output options are briefly described. The possibility to apply the model in forest remote sensing is demonstrated through the following simulation examples: the age dependence of forest reflectance, the seasonal course of forest reflectance, defoliation effects on forest reflectance, sensitivity of chlorophyll and water indices with respect to leaf chlorophyll and water content, respectively, and uncertainties in these indices introduced by the variation in stand parameters. When used together with the atmospheric radiative transfer and sensor calibration models, the forest reflectance model is applicable in satelliteimagery-aided forest ecology and health assessment, forest inventory and management. [ABSTRACT FROM AUTHOR]

The density of wood is a key indicator of the carbon investment strategies of trees, impacting productivity and carbon storage. Despite its importance, the global variation in wood density and its environmental controls remain poorly understood, preventing accurate predictions of global forest carbon stocks. Here we analyse information from 1.1 million forest inventory plots alongside wood density data from 10,703 tree species to create a spatially explicit understanding of the global wood density distribution and its drivers. Our findings reveal a pronounced latitudinal gradient, with wood in tropical forests being up to 30% denser than that in boreal forests. In both angiosperms and gymnosperms, hydrothermal conditions represented by annual mean temperature and soil moisture emerged as the primary factors influencing the variation in wood density globally. This indicates similar environmental filters and evolutionary adaptations among distinct plant groups, underscoring the essential role of abiotic factors in determining wood density in forest ecosystems. Additionally, our study highlights the prominent role of disturbance, such as human modification and fire risk, in influencing wood density at more local scales. Factoring in the spatial variation of wood density notably changes the estimates of forest carbon stocks, leading to differences of up to 21% within biomes. Therefore, our research contributes to a deeper understanding of terrestrial biomass distribution and how environmental changes and disturbances impact forest ecosystems., (© 2024. The Author(s).)

The latitudinal diversity gradient (LDG) is one of the most recognized global patterns of species richness exhibited across a wide range of taxa. Numerous hypotheses have been proposed in the past two centuries to explain LDG, but rigorous tests of the drivers of LDGs have been limited by a lack of high-quality global species richness data. Here we produce a high-resolution (0.025° × 0.025°) map of local tree species richness using a global forest inventory database with individual tree information and local biophysical characteristics from ~1.3 million sample plots. We then quantify drivers of local tree species richness patterns across latitudes. Generally, annual mean temperature was a dominant predictor of tree species richness, which is most consistent with the metabolic theory of biodiversity (MTB). However, MTB underestimated LDG in the tropics, where high species richness was also moderated by topographic, soil and anthropogenic factors operating at local scales. Given that local landscape variables operate synergistically with bioclimatic factors in shaping the global LDG pattern, we suggest that MTB be extended to account for co-limitation by subordinate drivers., (© 2022. The Author(s), under exclusive licence to Springer Nature Limited.)