Widespread breakdown in masting in European beech due to rising summer temperatures.

Climate change effects on tree reproduction are poorly understood, even though the resilience of populations relies on sufficient regeneration to balance increasing rates of mortality. Forest-forming tree species often mast, i.e. reproduce through synchronised year-to-year variation in seed production, which improves pollination and reduces seed predation. Recent observations in European beech show, however, that current climate change can dampen interannual variation and synchrony of seed production and that this masting breakdown drastically reduces the viability of seed crops. Importantly, it is unclear under which conditions masting breakdown occurs and how widespread breakdown is in this pan-European species. Here, we analysed 50 long-term datasets of population-level seed production, sampled across the distribution of European beech, and identified increasing summer temperatures as the general driver of masting breakdown. Specifically, increases in site-specific mean maximum temperatures during June and July were observed across most of the species range, while the interannual variability of population-level seed production (CVp) decreased. The declines in CVp were greatest, where temperatures increased most rapidly. Additionally, the occurrence of crop failures and low seed years has decreased during the last four decades, signalling altered starvation effects of masting on seed predators. Notably, CVp did not vary among sites according to site mean summer temperature. Instead, masting breakdown occurs in response to warming local temperatures (i.e. increasing relative temperatures), such that the risk is not restricted to populations growing in warm average conditions. As lowered CVp can reduce viable seed production despite the overall increase in seed count, our results warn that a covert mechanism is underway that may hinder the regeneration potential of European beech under climate change, with great potential to alter forest functioning and community dynamics.

Author Correction: Environment and host as large-scale controls of ectomycorrhizal fungi.

Change history: In the HTML version of this Article, author 'Filipa Cox' had no affiliation in the author list, although she was correctly associated with affiliation 3 in the PDF. In addition, the blue circles for 'oak' were missing from Extended Data Fig. 1. These errors have been corrected online.

Environment and host as large-scale controls of ectomycorrhizal fungi.

Explaining the large-scale diversity of soil organisms that drive biogeochemical processes-and their responses to environmental change-is critical. However, identifying consistent drivers of belowground diversity and abundance for some soil organisms at large spatial scales remains problematic. Here we investigate a major guild, the ectomycorrhizal fungi, across European forests at a spatial scale and resolution that is-to our knowledge-unprecedented, to explore key biotic and abiotic predictors of ectomycorrhizal diversity and to identify dominant responses and thresholds for change across complex environmental gradients. We show the effect of 38 host, environment, climate and geographical variables on ectomycorrhizal diversity, and define thresholds of community change for key variables. We quantify host specificity and reveal plasticity in functional traits involved in soil foraging across gradients. We conclude that environmental and host factors explain most of the variation in ectomycorrhizal diversity, that the environmental thresholds used as major ecosystem assessment tools need adjustment and that the importance of belowground specificity and plasticity has previously been underappreciated.

Accuracy, realism and general applicability of European forest models.

Forest models are instrumental for understanding and projecting the impact of climate change on forests. A considerable number of forest models have been developed in the last decades. However, few systematic and comprehensive model comparisons have been performed in Europe that combine an evaluation of modelled carbon and water fluxes and forest structure. We evaluate 13 widely used, state-of-the-art, stand-scale forest models against field measurements of forest structure and eddy-covariance data of carbon and water fluxes over multiple decades across an environmental gradient at nine typical European forest stands. We test the models' performance in three dimensions: accuracy of local predictions (agreement of modelled and observed annual data), realism of environmental responses (agreement of modelled and observed responses of daily gross primary productivity to temperature, radiation and vapour pressure deficit) and general applicability (proportion of European tree species covered). We find that multiple models are available that excel according to our three dimensions of model performance. For the accuracy of local predictions, variables related to forest structure have lower random and systematic errors than annual carbon and water flux variables. Moreover, the multi-model ensemble mean provided overall more realistic daily productivity responses to environmental drivers across all sites than any single individual model. The general applicability of the models is high, as almost all models are currently able to cover Europe's common tree species. We show that forest models complement each other in their response to environmental drivers and that there are several cases in which individual models outperform the model ensemble. Our framework provides a first step to capturing essential differences between forest models that go beyond the most commonly used accuracy of predictions. Overall, this study provides a point of reference for future model work aimed at predicting climate impacts and supporting climate mitigation and adaptation measures in forests.

Research questions to facilitate the future development of European long-term ecosystem research infrastructures: A horizon scanning exercise.

Distributed environmental research infrastructures are important to support assessments of the effects of global change on landscapes, ecosystems and society. These infrastructures need to provide continuity to address long-term change, yet be flexible enough to respond to rapid societal and technological developments that modify research priorities. We used a horizon scanning exercise to identify and prioritize emerging research questions for the future development of ecosystem and socio-ecological research infrastructures in Europe. Twenty research questions covered topics related to (i) ecosystem structures and processes, (ii) the impacts of anthropogenic drivers on ecosystems, (iii) ecosystem services and socio-ecological systems and (iv), methods and research infrastructures. Several key priorities for the development of research infrastructures emerged. Addressing complex environmental issues requires the adoption of a whole-system approach, achieved through integration of biotic, abiotic and socio-economic measurements. Interoperability among different research infrastructures needs to be improved by developing standard measurements, harmonizing methods, and establishing capacities and tools for data integration, processing, storage and analysis. Future research infrastructures should support a range of methodological approaches including observation, experiments and modelling. They should also have flexibility to respond to new requirements, for example by adjusting the spatio-temporal design of measurements. When new methods are introduced, compatibility with important long-term data series must be ensured. Finally, indicators, tools, and transdisciplinary approaches to identify, quantify and value ecosystem services across spatial scales and domains need to be advanced.

The response of soil solution chemistry in European forests to decreasing acid deposition.

Acid deposition arising from sulphur (S) and nitrogen (N) emissions from fossil fuel combustion and agriculture has contributed to the acidification of terrestrial ecosystems in many regions globally. However, in Europe and North America, S deposition has greatly decreased in recent decades due to emissions controls. In this study, we assessed the response of soil solution chemistry in mineral horizons of European forests to these changes. Trends in pH, acid neutralizing capacity (ANC), major ions, total aluminium (Altot ) and dissolved organic carbon were determined for the period 1995-2012. Plots with at least 10 years of observations from the ICP Forests monitoring network were used. Trends were assessed for the upper mineral soil (10-20 cm, 104 plots) and subsoil (40-80 cm, 162 plots). There was a large decrease in the concentration of sulphate (SO42-) in soil solution; over a 10-year period (2000-2010), SO42- decreased by 52% at 10-20 cm and 40% at 40-80 cm. Nitrate was unchanged at 10-20 cm but decreased at 40-80 cm. The decrease in acid anions was accompanied by a large and significant decrease in the concentration of the nutrient base cations: calcium, magnesium and potassium (Bc = Ca2+  + Mg2+  + K+ ) and Altot over the entire dataset. The response of soil solution acidity was nonuniform. At 10-20 cm, ANC increased in acid-sensitive soils (base saturation ≤10%) indicating a recovery, but ANC decreased in soils with base saturation >10%. At 40-80 cm, ANC remained unchanged in acid-sensitive soils (base saturation ≤20%, pHCaCl2 ≤ 4.5) and decreased in better-buffered soils (base saturation >20%, pHCaCl2 > 4.5). In addition, the molar ratio of Bc to Altot either did not change or decreased. The results suggest a long-time lag between emission abatement and changes in soil solution acidity and underline the importance of long-term monitoring in evaluating ecosystem response to decreases in deposition.

Fungal community composition predicts forest carbon storage at a continental scale.

Forest soils harbor hyper-diverse microbial communities which fundamentally regulate carbon and nutrient cycling across the globe. Directly testing hypotheses on how microbiome diversity is linked to forest carbon storage has been difficult, due to a lack of paired data on microbiome diversity and in situ observations of forest carbon accumulation and storage. Here, we investigated the relationship between soil microbiomes and forest carbon across 238 forest inventory plots spanning 15 European countries. We show that the composition and diversity of fungal, but not bacterial, species is tightly coupled to both forest biotic conditions and a seven-fold variation in tree growth rates and biomass carbon stocks when controlling for the effects of dominant tree type, climate, and other environmental factors. This linkage is particularly strong for symbiotic endophytic and ectomycorrhizal fungi known to directly facilitate tree growth. Since tree growth rates in this system are closely and positively correlated with belowground soil carbon stocks, we conclude that fungal composition is a strong predictor of overall forest carbon storage across the European continent.

Networking the forest infrastructure towards near real-time monitoring - A white paper.

Forests account for nearly 90 % of the world's terrestrial biomass in the form of carbon and they support 80 % of the global biodiversity. To understand the underlying forest dynamics, we need a long-term but also relatively high-frequency, networked monitoring system, as traditionally used in meteorology or hydrology. While there are numerous existing forest monitoring sites, particularly in temperate regions, the resulting data streams are rarely connected and do not provide information promptly, which hampers real-time assessments of forest responses to extreme climate events. The technology to build a better global forest monitoring network now exists. This white paper addresses the key structural components needed to achieve a novel meta-network. We propose to complement - rather than replace or unify - the existing heterogeneous infrastructure with standardized, quality-assured linking methods and interacting data processing centers to create an integrated forest monitoring network. These automated (research topic-dependent) linking methods in atmosphere, biosphere, and pedosphere play a key role in scaling site-specific results and processing them in a timely manner. To ensure broad participation from existing monitoring sites and to establish new sites, these linking methods must be as informative, reliable, affordable, and maintainable as possible, and should be supplemented by near real-time remote sensing data. The proposed novel meta-network will enable the detection of emergent patterns that would not be visible from isolated analyses of individual sites. In addition, the near real-time availability of data will facilitate predictions of current forest conditions (nowcasts), which are urgently needed for research and decision making in the face of rapid climate change. We call for international and interdisciplinary efforts in this direction.

Forest tree growth is linked to mycorrhizal fungal composition and function across Europe.

Most trees form symbioses with ectomycorrhizal fungi (EMF) which influence access to growth-limiting soil resources. Mesocosm experiments repeatedly show that EMF species differentially affect plant development, yet whether these effects ripple up to influence the growth of entire forests remains unknown. Here we tested the effects of EMF composition and functional genes relative to variation in well-known drivers of tree growth by combining paired molecular EMF surveys with high-resolution forest inventory data across 15 European countries. We show that EMF composition was linked to a three-fold difference in tree growth rate even when controlling for the primary abiotic drivers of tree growth. Fast tree growth was associated with EMF communities harboring high inorganic but low organic nitrogen acquisition gene proportions and EMF which form contact versus medium-distance fringe exploration types. These findings suggest that EMF composition is a strong bio-indicator of underlying drivers of tree growth and/or that variation of forest EMF communities causes differences in tree growth. While it may be too early to assign causality or directionality, our study is one of the first to link fine-scale variation within a key component of the forest microbiome to ecosystem functioning at a continental scale.

Meta-analysis of multidecadal biodiversity trends in Europe.

Local biodiversity trends over time are likely to be decoupled from global trends, as local processes may compensate or counteract global change. We analyze 161 long-term biological time series (15-91 years) collected across Europe, using a comprehensive dataset comprising ~6,200 marine, freshwater and terrestrial taxa. We test whether (i) local long-term biodiversity trends are consistent among biogeoregions, realms and taxonomic groups, and (ii) changes in biodiversity correlate with regional climate and local conditions. Our results reveal that local trends of abundance, richness and diversity differ among biogeoregions, realms and taxonomic groups, demonstrating that biodiversity changes at local scale are often complex and cannot be easily generalized. However, we find increases in richness and abundance with increasing temperature and naturalness as well as a clear spatial pattern in changes in community composition (i.e. temporal taxonomic turnover) in most biogeoregions of Northern and Eastern Europe.

Root turnover and root necromass accumulation of Norway spruce (Picea abies) are affected by soil acidity.

Fine root distribution and turnover were investigated in ca. 40-year-old pure Norway spruce (Picea abies Karst.) stands in Germany, growing on four sites that differed in soil acidity (Ebergötzen < Barbis < Fichtelgebirge = Harz). The density of fine root biomass and necromass in different soil horizons differed among the sites. At one of the most acidic sites (Harz), fine root density in the humus layer was more than twice that at the least acidic site (Ebergötzen). At the two most acidic sites, Fichtelgebirge and Harz, the ratio of biomass to necromass was significantly lower than at Ebergötzen and Barbis, particularly in the subsoil layer. In each stand, clear vertical gradients in fine root length density and root tip density were observed. Most of the roots and the root tips were in the humus layer and in the first mineral soil horizon (0-10 cm). There was a significantly different decrease in specific root length (cm gDM (-1)) and specific root tip density (root tips gDM (-1)) in the more acidified stands Fichtelgebirge and Harz compared with Ebergötzen and Barbis. Fine root production estimated by ingrowth cores and a net method was approximately twice as high in the more acidic stands Fichtelgebirge and Harz compared with Ebergötzen and Barbis. Rates of living fine root biomass turnover were higher at the Fichtelgebirge and Harz sites than at the Ebergötzen site. Rates of necromass turnover were similar at all sites. The results suggest that the accumulation of necromass was not due to a slower disappearance at the more acid sites, but to earlier root death. Roots contributed 46% to root + needle litter and 32% to root + total aboveground litter at the Harz site in 1997.

Using advanced surface complexation models for modelling soil chemistry under forests: Solling forest, Germany.

Various dynamic soil chemistry models have been developed to gain insight into impacts of atmospheric deposition of sulphur, nitrogen and other elements on soil and soil solution chemistry. Sorption parameters for anions and cations are generally calibrated for each site, which hampers extrapolation in space and time. On the other hand, recently developed surface complexation models (SCMs) have been successful in predicting ion sorption for static systems using generic parameter sets. This study reports the inclusion of an assemblage of these SCMs in the dynamic soil chemistry model SMARTml and applies this model to a spruce forest site in Solling Germany. Parameters for SCMs were taken from generic datasets and not calibrated. Nevertheless, modelling results for major elements matched observations well. Further, trace metals were included in the model, also using the existing framework of SCMs. The model predicted sorption for most trace elements well.