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Plant diversity effects on community productivity often increase over time. Whether the strengthening of diversity effects is caused by temporal shifts in species-level overyielding (i.e., higher species-level productivity in diverse communities compared with monocultures) remains unclear. Here, using data from 65 grassland and forest biodiversity experiments, we show that the temporal strength of diversity effects at the community scale is underpinned by temporal changes in the species that yield. These temporal trends of species-level overyielding are shaped by plant ecological strategies, which can be quantitatively delimited by functional traits. In grasslands, the temporal strengthening of biodiversity effects on community productivity was associated with increasing biomass overyielding of resource-conservative species increasing over time, and with overyielding of species characterized by fast resource acquisition either decreasing or increasing. In forests, temporal trends in species overyielding differ when considering above- versus belowground resource acquisition strategies. Overyielding in stem growth decreased for species with high light capture capacity but increased for those with high soil resource acquisition capacity. Our results imply that a diversity of species with different, and potentially complementary, ecological strategies is beneficial for maintaining community productivity over time in both grassland and forest ecosystems.

Aims We introduce ReSurveyEurope — a new data source of resurveyed vegetation plots in Europe, compiled by a collaborative network of vegetation scientists. We describe the scope of this initiative, provide an overview of currently available data, governance, data contribution rules, and accessibility. In addition, we outline further steps, including potential research questions. Results ReSurveyEurope includes resurveyed vegetation plots from all habitats. Version 1.0 of ReSurveyEurope contains 283,135 observations (i.e., individual surveys of each plot) from 79,190 plots sampled in 449 independent resurvey projects. Of these, 62,139 (78%) are permanent plots, that is, marked in situ, or located with GPS, which allow for high spatial accuracy in resurvey. The remaining 17,051 (22%) plots are from studies in which plots from the initial survey could not be exactly relocated. Four data sets, which together account for 28,470 (36%) plots, provide only presence/absence information on plant species, while the remaining 50,720 (64%) plots contain abundance information (e.g., percentage cover or cover–abundance classes such as variants of the Braun-Blanquet scale). The oldest plots were sampled in 1911 in the Swiss Alps, while most plots were sampled between 1950 and 2020. Conclusions ReSurveyEurope is a new resource to address a wide range of research questions on fine-scale changes in European vegetation. The initiative is devoted to an inclusive and transparent governance and data usage approach, based on slightly adapted rules of the well-established European Vegetation Archive (EVA). ReSurveyEurope data are ready for use, and proposals for analyses of the data set can be submitted at any time to the coordinators. Still, further data contributions are highly welcome.

Enhancing tree diversity may be important to fostering resilience to drought-related climate extremes. So far, little attention has been given to whether tree diversity can increase the survival of trees and reduce its variability in young forest plantations.We conducted an analysis of seedling and sapling survival from 34 globally distributed tree diversity experiments (363,167 trees, 168 species, 3744 plots, 7 biomes) to answer two questions: (1) Do drought and tree diversity alter the mean and variability in plot-level tree survival, with higher and less variable survival as diversity increases? and (2) Do species that survive poorly in monocultures survive better in mixtures and do specific functional traits explain monoculture survival?Tree species richness reduced variability in plot-level survival, while functional diversity (Rao's Q entropy) increased survival and also reduced its variability. Importantly, the reduction in survival variability became stronger as drought severity increased. We found that species with low survival in monocultures survived comparatively better in mixtures when under drought. Species survival in monoculture was positively associated with drought resistance (indicated by hydraulic traits such as turgor loss point), plant height and conservative resource-acquisition traits (e.g. low leaf nitrogen concentration and small leaf size).Synthesis. The findings highlight: (1) The effectiveness of tree diversity for decreasing the variability in seedling and sapling survival under drought; and (2) the importance of drought resistance and associated traits to explain altered tree species survival in response to tree diversity and drought. From an ecological perspective, we recommend mixing be considered to stabilize tree survival, particularly when functionally diverse forests with drought-resistant species also promote high survival of drought-sensitive species.

The study of tree species coexistence is crucial to understand the assembly of forest communities. In this context, trees adjust their traits in response to the interactions with other trees and, specifically, as a result of the competition for resources. Further, mycorrhizal fungal diversity and associations are important drivers of ecosystem functioning in forests, but their role as drivers of intraspecific trait variation has been disregarded. Here, we studied intraspecific trait variation of trees in response to tree and mycorrhizal fungal diversity.We sampled 3200 leaves from 640 trees belonging to 10 native, deciduous species in a tree diversity experiment in Central Germany. This experiment relies on the combination of gradients of tree richness and mycorrhizal associations. To handle large amounts of leaf samples, we acquired leaf-level spectral data and used deep learning to predict values for five leaf traits from the leaf economics spectrum (LES): specific leaf area, leaf dry matter content, carbon to nitrogen ratio, carbon content and phosphorus content. For every tree, we calculated the mean value for every trait and two multi-trait functional indices (functional richness and functional dispersion) based on values for individual leaves. Finally, we used sequencing-based data to assess the richness of mycorrhizal fungi associated with the trees.We found that tree and mycorrhizal fungi richness had an effect on different leaf functional traits. Specifically, tree richness positively affected specific leaf area and, additionally, had a negative effect on the functional indicies, which revealed that the phenotypic diversity within the tree crown decreased with tree species richness. In addition, leaf carbon to nitrogen ratio decreased with increasing arbuscular mycorrhizal fungal richness in both arbuscular and ectomycorrhizal tree species. Finally, we did not find differences between arbuscular and ectomycorrhizal trees regarding their location within the

Understanding the complex interactions between trees and fungi is crucial for forest ecosystem management, yet the influence of tree mycorrhizal types, species identity, and diversity on tree-tree interactions and their root-associated fungal communities remains poorly understood.Our study addresses this gap by investigating root-associated fungal communities of different arbuscular mycorrhizal (AM) and ectomycorrhizal (EcM) tree species pairs (TSPs) in a subtropical tree diversity experiment, spanning monospecific, two-species, and multi-species mixtures, utilizing Illumina sequencing of the ITS2 region.The study reveals that tree mycorrhizal type significantly impacts the alpha diversity of root-associated fungi in monospecific stands. Meanwhile, tree species identity's influence is modulated by overall tree diversity. Tree-related variables and spatial distance emerged as major drivers of variations in fungal community composition. Notably, in multi-species mixtures, compositional differences between root fungal communities of AM and EcM trees diminish, indicating a convergence of fungal communities irrespective of mycorrhizal type. Interestingly, dual mycorrhizal fungal communities were observed in these multi-species mixtures.This research underscores the pivotal role of mycorrhizal partnerships and the interplay of biotic and abiotic factors in shaping root fungal communities, particularly in varied tree diversity settings, and its implications for effective forest management and biodiversity conservation.

The emergence of alternative stable states in forest systems has significant implications for the functioning and structure of the terrestrial biosphere, yet empirical evidence remains scarce. Here, we combine global forest biodiversity observations and simulations to test for alternative stable states in the presence of evergreen and deciduous forest types. We reveal a bimodal distribution of forest leaf types across temperate regions of the Northern Hemisphere that cannot be explained by the environment alone, suggesting signatures of alternative forest states. Moreover, we empirically demonstrate the existence of positive feedbacks in tree growth, recruitment and mortality, with trees having 4–43% higher growth rates, 14–17% higher survival rates and 4–7 times higher recruitment rates when they are surrounded by trees of their own leaf type. Simulations show that the observed positive feedbacks are necessary and sufficient to generate alternative forest states, which also lead to dependency on history (hysteresis) during ecosystem transition from evergreen to deciduous forests and vice versa. We identify hotspots of bistable forest types in evergreen-deciduous ecotones, which are likely driven by soil-related positive feedbacks. These findings are integral to predicting the distribution of forest biomes, and aid to our understanding of biodiversity, carbon turnover, and terrestrial climate feedbacks.

Carbon-focused climate mitigation strategies are becoming increasingly important in forests. However, with ongoing biodiversity declines we require better knowledge of how much such strategies account for biodiversity. We particularly lack information across multiple trophic levels and on established forests, where the interplay between carbon stocks, stand age, and tree diversity might influence carbon–biodiversity relationships. Using a large dataset (>4600 heterotrophic species of 23 taxonomic groups) from secondary, subtropical forests, we tested how multitrophic diversity and diversity within trophic groups relate to aboveground, belowground, and total carbon stocks at different levels of tree species richness and stand age. Our study revealed that aboveground carbon, the key component of climate-based management, was largely unrelated to multitrophic diversity. By contrast, total carbon stocks—that is, including belowground carbon—emerged as a significant predictor of multitrophic diversity. Relationships were nonlinear and strongest for lower trophic levels, but nonsignificant for higher trophic level diversity. Tree species richness and stand age moderated these relationships, suggesting long-term regeneration of forests may be particularly effective in reconciling carbon and biodiversity targets. Our findings highlight that biodiversity benefits of climate-oriented management need to be evaluated carefully, and only maximizing aboveground carbon may fail to account for biodiversity conservation requirements.

In this report, we present the analysis of the different available biodiversity data streams at the EU and national level, both baseline biodiversity data and monitoring data. We assess how these biodiversity data inform and trigger policy action and identify the related challenges the different European countries and relevant EU agencies face and the solutions to overcome them. To do this, we consulted with more than 350 expert stakeholders from policy, research and practice. The assessment identified a fragmented biodiversity data landscape that cannot currently easily answer all relevant policy questions. Quantity and quality of biodiversity baseline datasets differ for the different countries, ranging from non-existent biodiversity monitoring due to capacity issues, to regular monitoring of ecosystem processes and state. By engaging stakeholders and experts in both member states and non-member states and from several EU bodies, we identified key challenges and ways to address these with targeted solutions towards building a joint European Biodiversity Monitoring Network. Solutions include focussing on cooperation and coordination, enhanced data standardisation and sharing, as well as the use of models and new technologies. These solutions can however only be realised with dedicated funding and capacity building, in coordination with all stakeholders in partnership.

Leaf functional traits provide important insights into plants’ responses to different environments. Leaf traits have been increasingly studied within-species in the last decade, following the growing realisation that neglecting the intra-specific scale can result in misreading plants’ response to environmental change. However, while likely to lead to similar pitfalls, within-individual leaf traits are under-researched despite being the scale at which elementary interactions shape ecosystem processes.To address this critical lack of understanding at the local scale, we assessed leaf trait variation in a large biodiversity-ecosystem functioning experiment in subtropical China. We used optical spectroscopy to determine nine morphological and biochemical traits of >5800 leaves from 414 trees representing 14 species. We evaluated the relative importance of the intra-individual level for total leaf trait variation, and the interacting effect of two trait variation’s drivers, soil nutrient availability, and a local species richness gradient.Comparing the amount of trait variation at the between-species, between-individuals and intra-individual levels, we found that intra-individual variation accounted on average for >25% of total trait variation. Additionally, intra-individual variation was the most prominent component of intra-specific variation. We found partial support for positive effects of soil nutrient availability and species diversity on intra-individual trait variation, and a strong interdependence of both effects. Contrary to the amplifying effects we expected, trait variation increased with soil nutrient availability at intermediate diversity, but decreased at low and high diversity.Our findings quantify the relevance of intra-individual level for leaf trait variation, and expose a complex interaction between its drivers. In particular, interactive effects of soil nutrient availability and local species diversity on trait variation suggest respons

Forest ecosystems are critical for their carbon sequestration potential. Increasing tree diversity has been shown to enhance both forest productivity and litter decomposition. Litter diversity increases litter decomposability by increasing the diversity of substrates offered to decomposers. However, the relative importance of litter decomposability and decomposer community in mediating tree diversity effects on decomposition remains unknown. Moreover, tree diversity modulation of litterfall spatial distribution, and consequently litter decomposition, has rarely been tested. We studied tree diversity effects on leaf litter decomposition and its mediation by the amount of litterfall, litter species richness and decomposability, and soil microorganisms in a large-scale tree diversity experiment in subtropical China. Furthermore, we examined how litter functional identity and diversity affect leaf litter decomposability. Finally, we tested how leaf functional traits, tree biomass, and forest spatial structure drive the litterfall spatial distribution. We found evidence that tree species richness increased litter decomposition by increasing litter species richness and the amount of litterfall. We showed that soil microorganisms in this subtropical forest perform 84–87% of litter decomposition. Moreover, changes in the amount of litterfall and microbial decomposition explained 19–37% of the decomposition variance. Additionally, up to 20% of the microbial decomposition variance was explained by litter decomposability, while litter decomposability itself was determined by litter functional identity, diversity, and species richness. Tree species richness increased litter species richness and the amount of litterfall (+200% from monoculture to eight-species neighborhood). We further demonstrated that the amount of species-specific litterfall increased with increasing tree proximity and biomass, and was modulated by leaf functional traits. These litterfall drivers increased th

Aim Theoretical, experimental and observational studies have shown that biodiversity–ecosystem functioning (BEF) relationships are influenced by functional community structure through two mutually non-exclusive mechanisms: (1) the dominance effect (which relates to the traits of the dominant species); and (2) the niche partitioning effect [which relates to functional diversity (FD)]. Although both mechanisms have been studied in plant communities and experiments at small spatial extents, it remains unclear whether evidence from small-extent case studies translates into a generalizable macroecological pattern. Here, we evaluate dominance and niche partitioning effects simultaneously in grassland systems world-wide. Location Two thousand nine hundred and forty-one grassland plots globally. Time period 2000–2014. Major taxa studied Vascular plants. Methods We obtained plot-based data on functional community structure from the global vegetation plot database “sPlot”, which combines species composition with plant trait data from the “TRY” database. We used data on the community-weighted mean (CWM) and FD for 18 ecologically relevant plant traits. As an indicator of primary productivity, we extracted the satellite-derived normalized difference vegetation index (NDVI) from MODIS. Using generalized additive models and deviation partitioning, we estimated the contributions of trait CWM and FD to the variation in annual maximum NDVI, while controlling for climatic variables and spatial structure. Results Grassland communities dominated by relatively tall species with acquisitive traits had higher NDVI values, suggesting the prevalence of dominance effects for BEF relationships. We found no support for niche partitioning for the functional traits analysed, because NDVI remained unaffected by FD. Most of the predictive power of traits was shared by climatic predictors and spatial coordinates. This highlights the importance of community assembly processes for BEF relationships i

Addressing global biodiversity loss requires an expanded focus on multiple dimensions of biodiversity. While most studies have focused on the consequences of plant interspecific diversity, our mechanistic understanding of how genetic diversity within plant species affects plant productivity remains limited. Here, we use a tree species × genetic diversity experiment to disentangle the effects of species diversity and genetic diversity, and how they are related to tree functional diversity and trophic feedbacks. We found that tree species diversity increased tree productivity via increased tree functional diversity, reduced soil fungal diversity and marginally reduced herbivory. The effects of tree genetic diversity on productivity via functional diversity and soil fungal diversity were negative in monocultures but positive in the mixture of the four tree species tested. Given the complexity of interactions between species and genetic diversity, tree functional diversity and trophic feedbacks on productivity, we suggest that both tree species and genetic diversity should be considered in afforestation.   &nbsp

Addressing global biodiversity loss requires an expanded focus on multiple dimensions of biodiversity. While most studies have focused on the consequences of plant interspecific diversity, our mechanistic understanding of how genetic diversity within plant species affects plant productivity remains limited. Here, we use a tree species × genetic diversity experiment to disentangle the effects of species diversity and genetic diversity, and how they are related to tree functional diversity and trophic feedbacks. We found that tree species diversity increased tree productivity via increased tree functional diversity, reduced soil fungal diversity and marginally reduced herbivory. The effects of tree genetic diversity on productivity via functional diversity and soil fungal diversity were negative in monocultures but positive in the mixture of the four tree species tested. Given the complexity of interactions between species and genetic diversity, tree functional diversity and trophic feedbacks on productivity, we suggest that both tree species and genetic diversity should be considered in afforestation.   &nbsp

Understanding what controls global leaf type variation in trees is crucial for comprehending their role in terrestrial ecosystems, including carbon, water and nutrient dynamics. Yet our understanding of the factors influencing forest leaf types remains incomplete, leaving us uncertain about the global proportions of needle-leaved, broadleaved, evergreen and deciduous trees. To address these gaps, we conducted a global, ground-sourced assessment of forest leaf-type variation by integrating forest inventory data with comprehensive leaf form (broadleaf vs needle-leaf) and habit (evergreen vs deciduous) records. We found that global variation in leaf habit is primarily driven by isothermality and soil characteristics, while leaf form is predominantly driven by temperature. Given these relationships, we estimate that 38% of global tree individuals are needle-leaved evergreen, 29% are broadleaved evergreen, 27% are broadleaved deciduous and 5% are needle-leaved deciduous. The aboveground biomass distribution among these tree types is approximately 21% (126.4 Gt), 54% (335.7 Gt), 22% (136.2 Gt) and 3% (18.7 Gt), respectively. We further project that, depending on future emissions pathways, 17-34% of forested areas will experience climate conditions by the end of the century that currently support a different forest type, highlighting the intensification of climatic stress on existing forests. By quantifying the distribution of tree leaf types and their corresponding biomass, and identifying regions where climate change will exert greatest pressure on current leaf types, our results can help improve predictions of future terrestrial ecosystem functioning and carbon cycling.

Forests are a substantial terrestrial carbon sink, but anthropogenic changes in land use and climate have considerably reduced the scale of this system1. Remote-sensing estimates to quantify carbon losses from global forests2–5 are characterized by considerable uncertainty and we lack a comprehensive ground-sourced evaluation to benchmark these estimates. Here we combine several ground-sourced6 and satellite-derived approaches2,7,8 to evaluate the scale of the global forest carbon potential outside agricultural and urban lands. Despite regional variation, the predictions demonstrated remarkable consistency at a global scale, with only a 12% difference between the ground-sourced and satellite-derived estimates. At present, global forest carbon storage is markedly under the natural potential, with a total deficit of 226 Gt (model range = 151–363 Gt) in areas with low human footprint. Most (61%, 139 Gt C) of this potential is in areas with existing forests, in which ecosystem protection can allow forests to recover to maturity. The remaining 39% (87 Gt C) of potential lies in regions in which forests have been removed or fragmented. Although forests cannot be a substitute for emissions reductions, our results support the idea2,3,9 that the conservation, restoration and sustainable management of diverse forests offer valuable contributions to meeting global climate and biodiversity targets.

In forest ecosystems, many ecosystem functions such as tree growth are affected by tree species richness. This biodiversity–productivity relationship (BPR) is mediated by leaf traits, which themselves are known to be influenced by tree species richness; at the same time, as the primary organs of light capture, they are an important factor for tree growth. However, how tree growth is influenced by a tree's ability to phenotypically adjust its leaf traits to the within-individual light gradient has largely been unexplored. Furthermore, it is not known how such impacts of within-tree leaf trait variation on individual tree growth sums up to productivity at the community scale. In this study we tested how tree species richness, a tree's mean leaf traits, within-tree leaf trait variation and the light extinction coefficient within a tree crown influence tree growth. We measured these variables in the temperate forest plantation of the Kreinitz biodiversity experiment. We found that the relationship between tree species richness and tree growth is mediated via the leaf trait variation of the individual trees, which in turn was modified by light availability. In particular, trees in monocultures show a higher within-individual leaf trait variation, which partly compensates for the lack in among-species leaf trait variation, and thus affects the BPR. It seems that tree richness operates both through increased acquisitive trait values and within-individual leaf trait variation, two processes that cancelled out each other and resulted in the absence of a significant effect of tree richness on productivity in our study. In conclusion, to understand the BPR, it is important to study the underlying processes and to know which ones reinforce or oppose each other. In particular, our study highlights the importance of including within-individual leaf trait variation in ecological research as one important moderator in the BPR.

In forest ecosystems, many ecosystem functions such as tree growth are affected by tree species richness. This biodiversity–productivity relationship (BPR) is mediated by leaf traits, which themselves are known to be influenced by tree species richness; at the same time, as the primary organs of light capture, they are an important factor for tree growth. However, how tree growth is influenced by a tree's ability to phenotypically adjust its leaf traits to the within-individual light gradient has largely been unexplored. Furthermore, it is not known how such impacts of within-tree leaf trait variation on individual tree growth sums up to productivity at the community scale. In this study we tested how tree species richness, a tree's mean leaf traits, within-tree leaf trait variation and the light extinction coefficient within a tree crown influence tree growth. We measured these variables in the temperate forest plantation of the Kreinitz biodiversity experiment. We found that the relationship between tree species richness and tree growth is mediated via the leaf trait variation of the individual trees, which in turn was modified by light availability. In particular, trees in monocultures show a higher within-individual leaf trait variation, which partly compensates for the lack in among-species leaf trait variation, and thus affects the BPR. It seems that tree richness operates both through increased acquisitive trait values and within-individual leaf trait variation, two processes that cancelled out each other and resulted in the absence of a significant effect of tree richness on productivity in our study. In conclusion, to understand the BPR, it is important to study the underlying processes and to know which ones reinforce or oppose each other. In particular, our study highlights the importance of including within-individual leaf trait variation in ecological research as one important moderator in the BPR.

Soil microbial communities play crucial roles in the earth’s biogeochemical cycles. Yet, their genomic potential for nutrient cycling in association with tree mycorrhizal type and tree-tree interactions remained unclear, especially in diverse tree communities. Here, we studied the genomic potential of soil fungi and bacteria with arbuscular (AM) and ectomycorrhizal (EcM) conspecific tree species pairs (TSPs) at three tree diversity levels in a subtropical tree diversity experiment (BEF-China). The soil fungi and bacteria of the TSPs’ interaction zone were characterized by amplicon sequencing, and their subcommunities were determined using a microbial interkingdom co-occurrence network approach. Their potential genomic functions were predicted with regard to the three major nutrients carbon (C), nitrogen (N), and phosphorus (P) and their combinations. We found the microbial subcommunities that were significantly responding to different soil characteristics. The tree mycorrhizal type significantly influenced the functional composition of these co-occurring subcommunities in monospecific stands mixtures and two-tree-species mixtures but not in mixtures with more than three tree species (here multi-tree-species mixtures). Differentiation of subcommunities was driven by differentially abundant taxa producing different sets of nutrient cycling enzymes across the tree diversity levels, predominantly enzymes of the P (n = 11 and 16) cycles, followed by the N (n = 9) and C (n = 9) cycles, in monospecific stands and two-tree-species mixtures, respectively. Fungi of the Agaricomycetes, Sordariomycetes, Eurotiomycetes, and Leotiomycetes and bacteria of the Verrucomicrobia, Acidobacteria, Alphaproteobacteria, and Actinobacteria were the major differential contributors (48% to 62%) to the nutrient cycling functional abundances of soil microbial communities across tree diversity levels. Our study demonstrated the versatility and significance of microbial subcommunities in differen

Carbon-focused climate mitigation strategies are becoming increasingly important in forests. However, with ongoing biodiversity declines we require better knowledge of how much such strategies account for biodiversity. We particularly lack information across multiple trophic levels and on established forests, where the interplay between carbon stocks, stand age, and tree diversity might influence carbon–biodiversity relationships. Using a large dataset (>4600 heterotrophic species of 23 taxonomic groups) from secondary, subtropical forests, we tested how multitrophic diversity and diversity within trophic groups relate to aboveground, belowground, and total carbon stocks at different levels of tree species richness and stand age. Our study revealed that aboveground carbon, the key component of climate-based management, was largely unrelated to multitrophic diversity. By contrast, total carbon stocks—that is, including belowground carbon—emerged as a significant predictor of multitrophic diversity. Relationships were nonlinear and strongest for lower trophic levels, but nonsignificant for higher trophic level diversity. Tree species richness and stand age moderated these relationships, suggesting long-term regeneration of forests may be particularly effective in reconciling carbon and biodiversity targets. Our findings highlight that biodiversity benefits of climate-oriented management need to be evaluated carefully, and only maximizing aboveground carbon may fail to account for biodiversity conservation requirements.

Determining the drivers of non-native plant invasions is critical for managing native ecosystems and limiting the spread of invasive species1,2. Tree invasions in particular have been relatively overlooked, even though they have the potential to transform ecosystems and economies3,4. Here, leveraging global tree databases5-7, we explore how the phylogenetic and functional diversity of native tree communities, human pressure and the environment influence the establishment of non-native tree species and the subsequent invasion severity. We find that anthropogenic factors are key to predicting whether a location is invaded, but that invasion severity is underpinned by native diversity, with higher diversity predicting lower invasion severity. Temperature and precipitation emerge as strong predictors of invasion strategy, with non-native species invading successfully when they are similar to the native community in cold or dry extremes. Yet, despite the influence of these ecological forces in determining invasion strategy, we find evidence that these patterns can be obscured by human activity, with lower ecological signal in areas with higher proximity to shipping ports. Our global perspective of non-native tree invasion highlights that human drivers influence non-native tree presence, and that native phylogenetic and functional diversity have a critical role in the establishment and spread of subsequent invasions.

Aim Theoretical, experimental and observational studies have shown that biodiversity–ecosystem functioning (BEF) relationships are influenced by functional community structure through two mutually non-exclusive mechanisms: (1) the dominance effect (which relates to the traits of the dominant species); and (2) the niche partitioning effect [which relates to functional diversity (FD)]. Although both mechanisms have been studied in plant communities and experiments at small spatial extents, it remains unclear whether evidence from small-extent case studies translates into a generalizable macroecological pattern. Here, we evaluate dominance and niche partitioning effects simultaneously in grassland systems world-wide. Location Two thousand nine hundred and forty-one grassland plots globally. Time period 2000–2014. Major taxa studied Vascular plants. Methods We obtained plot-based data on functional community structure from the global vegetation plot database “sPlot”, which combines species composition with plant trait data from the “TRY” database. We used data on the community-weighted mean (CWM) and FD for 18 ecologically relevant plant traits. As an indicator of primary productivity, we extracted the satellite-derived normalized difference vegetation index (NDVI) from MODIS. Using generalized additive models and deviation partitioning, we estimated the contributions of trait CWM and FD to the variation in annual maximum NDVI, while controlling for climatic variables and spatial structure. Results Grassland communities dominated by relatively tall species with acquisitive traits had higher NDVI values, suggesting the prevalence of dominance effects for BEF relationships. We found no support for niche partitioning for the functional traits analysed, because NDVI remained unaffected by FD. Most of the predictive power of traits was shared by climatic predictors and spatial coordinates. This highlights the importance of community assembly processes for BEF relationships i

1. Biodiversity is an important component of natural ecosystems, with higher species richness often correlating with an increase in ecosystem productivity. Yet, this relationship varies substantially across environments, typically becoming less pronounced at high levels of species richness. However, species richness alone cannot reflect all important properties of a community, including community evenness, which may mediate the relationship between biodiversity and productivity. If the evenness of a community correlates negatively with richness across forests globally, then a greater number of species may not always increase overall diversity and productivity of the system. Theoretical work and local empirical studies have shown that the effect of evenness on ecosystem functioning may be especially strong at high richness levels, yet the consistency of this remains untested at a global scale. 2. Here, we used a dataset of forests from across the globe, which includes composition, biomass accumulation and net primary productivity, to explore whether productivity correlates with community evenness and richness in a way that evenness appears to buffer the effect of richness. Specifically, we evaluated whether low levels of evenness in speciose communities correlate with the attenuation of the richness–productivity relationship. 3. We found that tree species richness and evenness are negatively correlated across forests globally, with highly speciose forests typically comprising a few dominant and many rare species. Furthermore, we found that the correlation between diversity and productivity changes with evenness: at low richness, uneven communities are more productive, while at high richness, even communities are more productive. 4. Synthesis. Collectively, these results demonstrate that evenness is an integral component of the relationship between biodiversity and productivity, and that the attenuating effect of richness on forest productivity might be partly explain

Current biodiversity monitoring in Europe is fragmented and often inconsistent across countries. Monitoring efforts face multiple challenges including insufficient technical and human capacity, limited funding, data unavailability, and lack of long-term policy support. To address these challenges, the Europa Biodiversity Observation Network (EuropaBON) proposes five clusters of solutions to improve the collection and uptake of policy-relevant biodiversity data: - Enhance coordination and collaboration of monitoring efforts by identifying priorities, using standardized protocols, and aligning reporting requirements with specific indicators. - Increase data standardization through the combination of Essential Biodiversity and Essential Ecosystem Services Variables (EBVs and EESVs) with dedicated data sharing and exchange mechanisms that adhere to open and FAIR (findable, accessible, interoperable, and reusable) principles. - Leverage modeling efforts and new technologies to integrate with traditional monitoring methods. - Enable additional, consistent, and long-term financial resources for monitoring efforts, including more and better coordination across countries, institutions, and sectors, along with privatesector investments. - Expand, adapt, and deliver capacity building, such as expert training, creating new exchange knowledge platforms, and embracing citizen science initiatives. We propose the creation of a European Biodiversity Monitoring Coordination Centre in the near future to implement lasting improvements in the collection, analysis, reporting, and political uptake of biodiversity data in all European countries.

Observations are key to understand the drivers of biodiversity loss, and the impacts on ecosystem services and ultimately on people. Many EU policies and initiatives demand unbiased, integrated and regularly updated biodiversity and ecosystem service data. However, efforts to monitor biodiversity are spatially and temporally fragmented, taxonomically biased, and lack integration in Europe. EuropaBON aims to bridge this gap by designing an EU-wide framework for monitoring biodiversity and ecosystem services. EuropaBON harnesses the power of modelling essential variables to integrate different reporting streams, data sources, and monitoring schemes. These essential variables provide consistent knowledge about multiple dimensions of biodiversity change across space and time. They can then be analyzed and synthesized to support decision-making at different spatial scales, from the sub-national to the European scale, through the production of indicators and scenarios. To develop essential biodiversity and ecosystem variables workflows that are policy relevant, EuropaBON is built around stakeholder engagement and knowledge exchange (WP2). EuropaBON will work with stakeholders to identify user and policy needs for biodiversity monitoring and investigate the feasibility of setting up a center to coordinate monitoring activities across Europe (WP2). Together with stakeholders, EuropaBON will assess current monitoring efforts to identify gaps, data and workflow bottlenecks, and analyse cost-effectiveness of different schemes (WP3). This will be used to co-design improved monitoring schemes using novel technologies to become more representative temporally, spatially and taxonomically, delivering multiple benefits to users and society (WP4). Finally, EuropaBON will demonstrate in a set of showcases how workflows tailored to the Birds Directive, Habitats Directive, Water Framework Directive, Climate and Restoration Policy, and the Bioeconomy Strategy, can be implemented (WP5).

Large-scale biodiversity databases have great potential for quantifying long-term trends of species, but they also bring many methodological challenges. Spatial bias of species occurrence records is well recognized. Yet, the dynamic nature of this spatial bias – how spatial bias has changed over time – has been largely overlooked. We examined the spatial bias of species occurrence records within multiple biodiversity databases in Germany and tested whether spatial bias in relation to land cover or land use (urban and protected areas) has changed over time. We focused our analyses on urban and protected areas as these represent two well-known correlates of sampling bias in biodiversity datasets. We found that the proportion of annual records from urban areas has increased over time while the proportion of annual records within protected areas has not consistently changed. Using simulations, we examined the implications of this changing sampling bias for estimation of long-term trends of species' distributions. When assessing biodiversity change, our findings suggest that the effects of spatial bias depend on how it affects sampling of the underlying land-use change drivers affecting species. Oversampling of regions undergoing the greatest degree of change, for instance near human settlements, might lead to overestimation of the trends of specialist species. For robust estimation of the long-term trends in species' distributions, analyses using species occurrence records may need to consider not only spatial bias, but also changes in the spatial bias through time.

Forests are critical ecosystems to understand the global carbon budget, due to their carbon sequestration potential in both above- and belowground compartments, especially in species-rich forests. Soil carbon sequestration is strongly linked to soil microbial communities, and this link is mediated by the tree community, likely due to modifications of micro-environmental conditions (i.e., biotic conditions, soil properties, and microclimate). We studied soil carbon concentration and the soil microbial biomass of 180 local neighborhoods along a gradient of tree species richness ranging from 1 to 16 tree species per plot in a Chinese subtropical forest experiment (BEF-China). Tree productivity and different tree functional traits were measured at the neighborhood level. We tested the effects of tree productivity, functional trait identity and dissimilarity on soil carbon concentrations, and their mediation by the soil microbial biomass and micro-environmental conditions. Our analyses showed a strong positive correlation between soil microbial biomass and soil carbon concentrations. Besides, soil carbon concentration increased with tree productivity and tree root diameter while it decreased with litterfall C:N content. Moreover, tree productivity and tree functional traits (e.g. root fungal association and litterfall C:N ratio) modulated micro-environmental conditions with substantial consequences for soil microbial biomass. We also showed that soil history and topography should be considered in future experiments and tree plantations, as soil carbon concentrations were higher where historical (i.e., at the beginning of the experiment) carbon concentrations were high, themselves being strongly affected by the topography. Altogether, these results imply that the quantification of the different soil carbon pools is critical for understanding microbial community–soil carbon stock relationships and their dependence on tree diversity and micro-environmental conditions.

In this report, we present the analysis of the different available biodiversity data streams at the EU and national level, both baseline biodiversity data and monitoring data. We assess how these biodiversity data inform and trigger policy action and identify the related challenges the different European countries and relevant EU agencies face and the solutions to overcome them. To do this, we consulted with more than 350 expert stakeholders from policy, research and practice. The assessment identified a fragmented biodiversity data landscape that cannot currently easily answer all relevant policy questions. Quantity and quality of biodiversity baseline datasets differ for the different countries, ranging from non-existent biodiversity monitoring due to capacity issues, to regular monitoring of ecosystem processes and state. By engaging stakeholders and experts in both member states and non-member states and from several EU bodies, we identified key challenges and ways to address these with targeted solutions towards building a joint European Biodiversity Monitoring Network. Solutions include focussing on cooperation and coordination, enhanced data standardisation and sharing, as well as the use of models and new technologies. These solutions can however only be realised with dedicated funding and capacity building, in coordination with all stakeholders in partnership.

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Addressing global biodiversity loss requires an expanded focus on multiple dimensions of biodiversity. While most studies have focused on the consequences of plant interspecific diversity, our mechanistic understanding of how genetic diversity within plant species affects plant productivity remains limited. Here, we use a tree species × genetic diversity experiment to disentangle the effects of species diversity and genetic diversity, and how they are related to tree functional diversity and trophic feedbacks. We found that tree species diversity increased tree productivity via increased tree functional diversity, reduced soil fungal diversity and marginally reduced herbivory. The effects of tree genetic diversity on productivity via functional diversity and soil fungal diversity were negative in monocultures but positive in the mixture of the four tree species tested. Given the complexity of interactions between species and genetic diversity, tree functional diversity and trophic feedbacks on productivity, we suggest that both tree species and genetic diversity should be considered in afforestation.   &nbsp

Vegetation-plot resurvey data are a main source of information on terrestrial biodiversity change, with records reaching back more than one century. Although more and more data from re-sampled plots have been published, there is not yet a comprehensive open-access dataset available for analysis. Here, we compiled and harmonised vegetation-plot resurvey data from Germany covering almost 100 years. We show the distribution of the plot data in space, time and across habitat types of the European Nature Information System (EUNIS). In addition, we include metadata on geographic location, plot size and vegetation structure. The data allow temporal biodiversity change to be assessed at the community scale, reaching back further into the past than most comparable data yet available. They also enable tracking changes in the incidence and distribution of individual species across Germany. In summary, the data come at a level of detail that holds promise for broadening our understanding of the mechanisms and drivers behind plant diversity change over the last century.

Der globale Biodiversitätsverlust schreitet trotz vielfältiger internationaler, europäischer und nationaler Bemühungen voran und ist eine zentrale globale und nationale Herausforderung (IPBES 2019b). Ein prägnantes Beispiel für den Biodiversitätsverlust ist der starke Rückgang der Brutvogelvorkommen Europas in den letzten Jahrzehnten (Inger et al. 2015). Besonders die Agrarvögel sind von dieser rückläufigen Entwicklung betroffen, welche vornehmlich der landwirtschaftlichen Intensivierung geschuldet ist (Gerlach et al. 2019; Nationale Akademie der Wissenschaften Leopoldina et al. 2020). Insgesamt ließ sich in Deutschland über die letzten 150-200 Jahre ein Rückgang der Artenvielfalt an Schmetterlingen um 30-40 % verzeichnen (Habel et al. 2016). Seit den 1960er Jahren hat die Vorkommenswahrscheinlichkeit von Gefäßpflanzen um 30% abgenommen (Eichenberg et al. 2021). Aber erst der alarmierende Insektenrückgang in Deutschland, mit 50-75 % Verlust an Biomasse (Hallmann et al. 2017; Seibold et al. 2019) hat die Brisanz der Biodiversitätskrise und ihre Verzahnung mit dem Klimawandel in den politischen Fokus gerückt (Settele 2020; WBGU 2020).

Citizen scientists play an increasingly important role in biodiversity monitoring. Most of the data, however, are unstructured—collected by diverse methods that are not documented with the data. Insufficient understanding of the data collection processes presents a major barrier to the use of citizen science data in biodiversity research. We developed a questionnaire to ask citizen scientists about their decision-making before, during and after collecting and reporting species observations, using Germany as a case study. We quantified the greatest sources of variability among respondents and assessed whether motivations and experience related to any aspect of data collection. Our questionnaire was answered by almost 900 people, with varying taxonomic foci and expertise. Respondents were most often motivated by improving species knowledge and supporting conservation, but there were no linkages between motivations and data collection methods. By contrast, variables related to experience and knowledge, such as membership of a natural history society, were linked with a greater propensity to conduct planned searches, during which typically all species were reported. Our findings have implications for how citizen science data are analysed in statistical models; highlight the importance of natural history societies and provide pointers to where citizen science projects might be further developed.

Litter decomposition is a key ecosystem function in forests and varies in response to a range of climatic, edaphic, and local stand characteristics. Disentangling the relative contribution of these factors is challenging, especially along large environmental gradients. In particular, knowledge of the effect of management options, such as tree planting density and species composition, on litter decomposition would be highly valuable in forestry. In this study, we made use of 15 tree diversity experiments spread over eight countries and three continents within the global TreeDivNet network. We evaluated the effects of overstory composition (tree identity, species/mixture composition and species richness), plantation conditions (density and age), and climate (temperature and precipitation) on mass loss (after 3 months and 1 year) of two standardized litters: high-quality green tea and low-quality rooibos tea. Across continents, we found that early-stage decomposition of the low-quality rooibos tea was influenced locally by overstory tree identity. Mass loss of rooibos litter was higher under young gymnosperm overstories compared to angiosperm overstories, but this trend reversed with age of the experiment. Tree species richness did not influence decomposition and explained almost no variation in our multi-continent dataset. Hence, in the young plantations of our study, overstory composition effects on decomposition were mainly driven by tree species identity on decomposer communities and forest microclimates. After 12 months of incubation, mass loss of the high-quality green tea litter was mainly influenced by temperature whereas the low-quality rooibos tea litter decomposition showed stronger relationships with overstory composition and stand age. Our findings highlight that decomposition dynamics are not only affected by climate but also by management options, via litter quality of the identity of planted trees but also by overstory composition and structure.

Global maps of plant functional traits are essential for studying the dynamics of the terrestrial biosphere, yet the spatial distribution of trait measurements remains sparse. With the increasing popularity of species identification apps, citizen scientists contribute to growing vegetation data collections. The question emerges whether such opportunistic citizen science data can help map plant functional traits globally. Here we show that we can map global trait patterns by complementing vascular plant observations from the global citizen science project iNaturalist with measurements from the plant trait database TRY. We evaluate these maps using sPlotOpen, a global collection of vegetation plot data. Our results show high correlations between the iNaturalist- and sPlotOpen-based maps of up to 0.69 (r) and higher correlations than to previously published trait maps. As citizen science data collections continue to grow, we can expect them to play a significant role in further improving maps of plant functional traits.

Winners and losers over 35 years of dragonfly and damselfly distributional change in Germany – Recent studies suggest insect declines in parts of Europe; however, the gen­erality of these trends across different taxa and regions remains unclear. Standardized data are not available to assess large-scale, long-term changes for most insect groups but opportunistic citizen science data is widespread for some. Here, we took advantage of ‘citizen science’ data to investigate distributional changes of Odonata. We compiled over 1 million occurrence records from different regional databases. We used occupancy-detection models to account for imperfect detection and estimate annual distributions for each species during 1980–2016 within 5 x 5 km quadrants. We also compiled data on species attributes that were hypothesized to affect species’ sensitivity to different drivers and related them to the changes in species’ distributions. We further developed a novel approach to cluster groups of species with similar patterns of distributional change to represent multi-species indicators. More species increased (45%) than decreased (29%) or remained stable (26%) in their distribution (i.e., number of occupied quadrants). Spe­cies showing increases were generally warm-adapted species and/or running water spe­cies, while species showing decreases were cold-adapted species using standing water habitats such as bogs. Time-series clustering defined five main patterns of change – each associated with a specific combination of species attributes, and confirming the key roles of species’ temperature and habitat preferences. Trends in Odonata provide mixed news – improved water quality, coupled with positive impacts of climate change, could explain the positive trends of many species. At the same time, declining species point to conser­vation challenges associated with habitat loss and degradation. Our study demonstrates the great value of ‘citizen science’ and the work of natural history socie

Current climate change aggravates human health hazards posed by heat stress. Forests can locally mitigate this by acting as strong thermal buffers, yet potential mediation by forest ecological characteristics remains underexplored. We report over 14 months of hourly microclimate data from 131 forest plots across four European countries and compare these to open-field controls using physiologically equivalent temperature (PET) to reflect human thermal perception. Forests slightly tempered cold extremes, but the strongest buffering occurred under very hot conditions (PET > 35°C), where forests reduced strong to extreme heat stress day occurrence by 84.1%. Mature forests cooled the microclimate by 12.1 to 14.5°C PET under, respectively, strong and extreme heat stress conditions. Even young plantations reduced those conditions by 10°C PET. Forest structure strongly modulated the buffering capacity, which was enhanced by increasing stand density, canopy height and canopy closure. Tree species composition had a more modest yet significant influence: i.e., strongly shade-casting, small-leaved evergreen species amplified cooling. Tree diversity had little direct influences, though indirect effects through stand structure remain possible. Forests in general, both young and mature, are thus strong thermal stress reducers, but their cooling potential can be even further amplified given targeted (urban) forest management that considers these new insights.

Der vorliegende Beitrag stellt grundsätzliche Anforderungen an ein künftiges Monitoringprogramm für Gefäßpflanzenarten in Deutschland auf den existierenden 1 km² großen bundesweit repräsentativen Stichprobenflächen (BRS-Flächen) zusammen. Konsequenzen der ursprünglich angewendeten Stratifizierung für das Erhebungsdesign werden evaluiert und Optionen für eine Beprobung mit permanenten oder nicht-permanenten Teilflächen oder Transekten dargestellt. Darauf aufbauend ergeben sich als Kernempfehlungen, die Beprobung auf Teilflächen durchzuführen und auf eine erneute Stratifizierung innerhalb der Stichprobenflächen zu verzichten. Die Teilflächen sollten permanent angelegt und nicht zu jedem Monitoringtermin erneut zufällig gewählt werden. Wir empfehlen, die Teilflächen als Quadrate und nicht als Transekte anzulegen. Zusätzlich sollten Vegetationsdauerflächen beprobt und Fernerkundungsdaten miteinbezogen werden. Mit einem so angelegten Monitoring wird es möglich sein, für ganz Deutschland repräsentative Aussagen zur Häufigkeit von Gefäßpflanzenarten und zur Veränderung dieser Häufigkeiten über die Zeit zu machen und daraus faktenbasierte Entscheidungsvorschläge für politisches Handeln und für die Naturschutzpraxis abzuleiten.          The article summarises basic requirements for a future monitoring programme for vascular plant species in Germany using the existing nationwide representative network of 1km² sample areas (BRS areas). We evaluate the consequences of the originally applied stratification for the survey design and present options for subsampling with permanent or non-permanent subplots or transects. Based on this, the core recommendations are to carry out sampling on subplots and to dispense with renewed stratification within the sample areas. The subplots should be established permanently and should not be newly selected at random at each monitoring date. We recommend using square

Aim Soil microorganisms are essential for the functioning of terrestrial ecosystems. Although soil microbial communities and functions are linked to tree species composition and diversity, there has been no comprehensive study of the generality or context dependence of these relationships. Here, we examine tree diversity–soil microbial biomass and respiration relationships across environmental gradients using a global network of tree diversity experiments. Location Boreal, temperate, subtropical and tropical forests. Time period 2013. Major taxa studied Soil microorganisms. Methods Soil samples collected from 11 tree diversity experiments were used to measure microbial respiration, biomass and respiratory quotient using the substrate-induced respiration method. All samples were measured using the same analytical device, method and procedure to reduce measurement bias. We used linear mixed-effects models and principal components analysis (PCA) to examine the effects of tree diversity (taxonomic and phylogenetic), environmental conditions and interactions on soil microbial properties. Results Abiotic drivers, mainly soil water content, but also soil carbon and soil pH, significantly increased soil microbial biomass and respiration. High soil water content reduced the importance of other abiotic drivers. Tree diversity had no effect on the soil microbial properties, but interactions with phylogenetic diversity indicated that the effects of diversity were context dependent and stronger in drier soils. Similar results were found for soil carbon and soil pH. Main conclusions Our results indicate the importance of abiotic variables, especially soil water content, for maintaining high levels of soil microbial functions and modulating the effects of other environmental drivers. Planting tree species with diverse water-use strategies and structurally complex canopies and high leaf area might be crucial for maintaining high soil microbial biomass and respiration. Give

Forests are critical ecosystems to understand the global carbon budget, due to their carbon sequestration potential in both above- and belowground compartments, especially in species-rich forests. Soil carbon sequestration is strongly linked to soil microbial communities, and this link is mediated by the tree community, likely due to modifications of micro-environmental conditions (i.e., biotic conditions, soil properties, and microclimate). We studied soil carbon concentration and the soil microbial biomass of 180 local neighborhoods along a gradient of tree species richness ranging from 1 to 16 tree species per plot in a Chinese subtropical forest experiment (BEF-China). Tree productivity and different tree functional traits were measured at the neighborhood level. We tested the effects of tree productivity, functional trait identity and dissimilarity on soil carbon concentrations, and their mediation by the soil microbial biomass and micro-environmental conditions. Our analyses showed a strong positive correlation between soil microbial biomass and soil carbon concentrations. Besides, soil carbon concentration increased with tree productivity and tree root diameter while it decreased with litterfall C:N content. Moreover, tree productivity and tree functional traits (e.g. root fungal association and litterfall C:N ratio) modulated micro-environmental conditions with substantial consequences for soil microbial biomass. We also showed that soil history and topography should be considered in future experiments and tree plantations, as soil carbon concentrations were higher where historical (i.e., at the beginning of the experiment) carbon concentrations were high, themselves being strongly affected by the topography. Altogether, these results imply that the quantification of the different soil carbon pools is critical for understanding microbial community–soil carbon stock relationships and their dependence on tree diversity and micro-environmental conditions.

Large-scale biodiversity databases have great potential for quantifying long-term trends of species, but they also bring many methodological challenges. Spatial bias of species occurrence records is well recognized. Yet, the dynamic nature of this spatial bias – how spatial bias has changed over time – has been largely overlooked. We examined the spatial bias of species occurrence records within multiple biodiversity databases in Germany and tested whether spatial bias in relation to land cover or land use (urban and protected areas) has changed over time. We focused our analyses on urban and protected areas as these represent two well-known correlates of sampling bias in biodiversity datasets. We found that the proportion of annual records from urban areas has increased over time while the proportion of annual records within protected areas has not consistently changed. Using simulations, we examined the implications of this changing sampling bias for estimation of long-term trends of species' distributions. When assessing biodiversity change, our findings suggest that the effects of spatial bias depend on how it affects sampling of the underlying land-use change drivers affecting species. Oversampling of regions undergoing the greatest degree of change, for instance near human settlements, might lead to overestimation of the trends of specialist species. For robust estimation of the long-term trends in species' distributions, analyses using species occurrence records may need to consider not only spatial bias, but also changes in the spatial bias through time.

In this report, we present the analysis of the different available biodiversity data streams at the EU and national level, both baseline biodiversity data and monitoring data. We assess how these biodiversity data inform and trigger policy action and identify the related challenges the different European countries and relevant EU agencies face and the solutions to overcome them. To do this, we consulted with more than 350 expert stakeholders from policy, research and practice. The assessment identified a fragmented biodiversity data landscape that cannot currently easily answer all relevant policy questions. Quantity and quality of biodiversity baseline datasets differ for the different countries, ranging from non-existent biodiversity monitoring due to capacity issues, to regular monitoring of ecosystem processes and state. By engaging stakeholders and experts in both member states and non-member states and from several EU bodies, we identified key challenges and ways to address these with targeted solutions towards building a joint European Biodiversity Monitoring Network. Solutions include focussing on cooperation and coordination, enhanced data standardisation and sharing, as well as the use of models and new technologies. These solutions can however only be realised with dedicated funding and capacity building, in coordination with all stakeholders in partnership.