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Despite a decrease in industrial nitrogen and sulfur deposition over recent decades, soil acidification remains a persistent challenge to European forest health, especially in regions of intense agriculture and urbanisation. Using topsoil eDNA metabarcoding and functional annotations from a sample of 49 plots (each 30 × 30 m) located in The Netherlands and Germany, we investigated the effect of severe acidification on bacterial taxonomic diversity under different forest types and explored potential functional implications for nutrient cycling. Furthermore, we assessed which soil parameters known to influence soil bacterial communities affect these acidophilic communities. Here, we are the first to demonstrate under natural conditions that soil bacterial diversity in extremely acidic soils (pH <4.5) continues to decline similarly across forest types as pH further decreases under intensifying human activity. Our results confirmed pH as the key driver of soil bacterial communities, even in extremely acidic soils. Ongoing severe acidification continues to reduce bacterial communities, favouring taxa adapted to extreme acidity and primarily involved in recalcitrant carbon-degradation compounds (e.g. cellulolysis potential = 0.78%–9.99%) while simultaneously diminishing taxa associated with nitrogen cycling (e.g. fixation potential = 6.72%–0.00%). Altogether, our findings indicate a further decline in bacterial diversity in already extremely acidic soils, likely disrupting nutrient cycling through changes in immobilisation and mineralisation processes. Our study highlights the continuous acidification of European temperate forests to extremely low pH levels, further disrupting forest ecosystem functioning. The significant reduction in bacterial diversity under such a severe acidification gradient, as demonstrated here, underscores the necessity to include severely acidified forests in conservation programmes and monitoring to prevent further degradation of European soils

Background: The phyllosphere microbiome is crucial for plant health and ecosystem functioning. While host species play a determining role in shaping the phyllosphere microbiome, host trees of the same species that are subjected to different environmental conditions can still exhibit large degrees of variation in their microbiome diversity and composition. Whether these intra-specific variations in phyllosphere microbiome diversity and composition can be observed over the broader expanse of forest landscapes remains unclear. In this study, we aim to assess the variation in the top canopy phyllosphere bacterial communities between and within host tree species in the temperate European forests, focusing on Fagus sylvatica (European beech) and Picea abies (Norway spruce). Results: We profiled the bacterial diversity, composition, driving factors, and discriminant taxa in the top canopy phyllosphere of 211 trees in two temperate forests, Veluwe National Parks, the Netherlands and Bavarian Forest National Park, Germany. We found the bacterial communities were primarily shaped by host species, and large variation existed within beech and spruce. While we showed that there was a core microbiome in all tree species examined, community composition varied with elevation, tree diameter at breast height, and leaf-specific traits (e.g., chlorophyll and P content). These driving factors of bacterial community composition also correlated with the relative abundance of specific bacterial families. Conclusions: While our results underscored the importance of host species, we demonstrated a substantial range of variation in phyllosphere bacterial diversity and composition within a host species. Drivers of these variations have implications at both the individual host tree level, where the bacterial communities differed based on tree traits, and at the broader forest landscape level, where drivers like certain highly plastic leaf traits can potentially link forest canopy bacterial comm

Aims: The phyllosphere and soil are crucial and distinct microbial spheres in forests, connected through trees that interact with both. As part of the tree's holobiont, these communities are vital to the fitness and evolution of the host. Differences between the spheres may be particularly evident at the two extreme ends of tall and long-lived trees of natural temperate forest; the top-canopy and the soil. Here, we evaluated the connectivity between the top-canopy and soil microbial communities of European beech and Norway spruce trees to determine the significance of tree-sphere and host-species identity, and to assess the contribution of taxa inhabiting both spheres. Methods: Bacterial and fungal community composition was determined through metabarcoding analysis of linked top-canopy leaf and bulk soil samples collected from tall (old) trees in the natural forest of Bavarian Forest National Park. Results: This study shows sphere-specific communities in European temperate forests, characterized by low connectivity. Results highlight that spheres exert stronger influence than host identity. Only a few taxa inhabited both spheres, yet they accounted for the bulk of the (relative) abundance in each sphere. Conclusion: Analysing the divergence and shared characteristics of these interlinked communities redefines the tree holobiont concept and enhances our understanding of the evolution of plant-associated microbial communities in a sphere-specific manner. This study emphasizes the importance of examining multiple microbiome components for a thorough understanding of temperate forest ecology, while also highlighting the existence of a small group of overlapping taxa that may play a bigger role than previously anticipated.

Although an enormous number of plant and animal species have been directly observed and recorded in online databases, the spatial variation in the composition of the microbiome remains relatively largely unknown. In this study, for the first time, we demonstrate mapping of the relative abundance of the soil microbiome for three terrestrial ecosystems across North America (savanna, boreal and tundra) using airborne image spectroscopy and environmental DNA (eDNA) data. We identified field plots of publicly available eDNA data co-occurring with AVIRIS-NG hyperspectral imagery. An eDNA processing pipeline was developed to generate a consistent profile of the relative abundance for thousands of microbiome operational taxonomic units (OTU) and 225 microbiome families. Using Linear Discriminate Analysis (LDA) scores for the eDNA data, we identified 81 families with the greatest explanatory power based on the community composition between the three ecosystems. A case study example demonstrates our conceptual approach by selecting a dominant and functionally important bacterial family for each ecosystem, with each family representing a specific biomarker. A partial least squares regression (PLSR) was applied to spatially predict the relative abundance of each bacteria family (in the boreal, tundra, and savanna ecosystems) from the hyperspectral imagery. For the boreal, Pseudomonadaceae is shown to be a dominant family taxon, as it is a saprophytic family specialized in decomposing the dense organic matter of boreal forest soils. Members of an understudied family of Acidobacteria, so far indicated as AKIW659, are abundant in acidic Arctic soils and peat bogs. Finally, the Micromonosporaceae are dominant and functionally important in drier regions with grass-tree dominated woodlands, being a member of Actinobacteria with a high relative abundance in soils with high carbon content and nitrate leaching. We demonstrate for the first time how the spatial prediction of relative abu

Models and approaches have been developed to predict radiation exposure of wildlife under field conditions. However, there have been few attempts to directly measure radiation exposure of wildlife in the field and confirm the doses predicted by models. This is a potential issue for stakeholder acceptance of modelling-based assessments. Here is presented a comprehensive study comparing the results of different dosimeters fitted to free-ranging reindeer inhabiting an area that received comparatively high radiocaesium deposition from the 1986 Chernobyl accident. The external dose of reindeer was measured using the four dosimeter types in aluminium box mounted on the GPS collar. The measurements were compared with two model predictions: (i) external dose to reindeer across the entire range area of the herd; and (ii) external doses of individual reindeer predicted using GPS tracking data to determine locations. It was found that although significant differences between the estimates of the various dosimeters were found these were small with no practical implication. Also, the mean predicted external doses using the GPS tracking data were not significantly different to estimates from two of the four passive dosimeter results. The average external dose predicted across the herd area was significantly lower than doses recorded by the dosimeters and also estimates using GPS data to determine reindeer location (and hence exposure). For 137Cs the average external dose from the GPS tracking data was about twice that predicted across the herd area, because collared animals favoured the more contaminated area of the study site. This suggests that in some circumstances the assumption of averaging contamination over an assumed home range within assessments may be inadequate though this would need to be balanced against other uncertainties. Natural radiation was the greatest contribution to reindeer exposure and a function of the high altitude.

Models and approaches have been developed to predict radiation exposure of wildlife under field conditions. However, there have been few attempts to directly measure radiation exposure of wildlife in the field and confirm the doses predicted by models. This is a potential issue for stakeholder acceptance of modelling-based assessments. Here is presented a comprehensive study comparing the results of different dosimeters fitted to free-ranging reindeer inhabiting an area that received comparatively high radiocaesium deposition from the 1986 Chernobyl accident. The external dose of reindeer was measured using the four dosimeter types in aluminium box mounted on the GPS collar. The measurements were compared with two model predictions: (i) external dose to reindeer across the entire range area of the herd; and (ii) external doses of individual reindeer predicted using GPS tracking data to determine locations. It was found that although significant differences between the estimates of the various dosimeters were found these were small with no practical implication. Also, the mean predicted external doses using the GPS tracking data were not significantly different to estimates from two of the four passive dosimeter results. The average external dose predicted across the herd area was significantly lower than doses recorded by the dosimeters and also estimates using GPS data to determine reindeer location (and hence exposure). For 137Cs the average external dose from the GPS tracking data was about twice that predicted across the herd area, because collared animals favoured the more contaminated area of the study site. This suggests that in some circumstances the assumption of averaging contamination over an assumed home range within assessments may be inadequate though this would need to be balanced against other uncertainties. Natural radiation was the greatest contribution to reindeer exposure and a function of the high altitude.