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Throughfall is the largest source of water entering the soil in forests, and its spatial distribution depends on several biotic and abiotic factors. It is well documented that the distribution of throughfall results in reoccurring higher and lower water inputs at certain locations. However, the role of horizontal root water uptake patterns in understanding the effects of throughfall patterns on subsurface water dynamics remains unresolved. Therefore, here we investigate root water uptake patterns by considering spatial patterns of throughfall and soil water patterns in addition to soil and neighboring tree characteristics. We conducted weekly intensive throughfall sampling at locations paired with soil moisture sensors during the 2019 growing season. We employed a linear mixed effects model to understand controlling factors for root water uptake patterns. Our results show that soil water patterns and interactions among neighbouring trees are the most significant factors regulating root water uptake patterns. Temporally stable throughfall patterns did not influence root water uptake patterns. Similarly, soil properties were unimportant for spatial patterns of root water uptake. We found that wetter locations (rarely associated with throughfall hotspots) promoted greater root water uptake. Root water uptake in monitored soil layers also increased with neighbourhood species richness. Ultimately our findings suggest that complementarity mechanisms within the forest stand, in addition to soil water variability and availability, govern root water uptake patterns.

Environmental monitoring involves the quantification of microscopic cells and particles such as algae, plant cells, pollen, or fungal spores. Traditional methods using conventional microscopy require expert knowledge, are time-intensive and not well-suited for automated high throughput. Multispectral imaging flow cytometry (MIFC) allows measurement of up to 5000 particles per second from a fluid suspension and can simultaneously capture up to 12 images of every single particle for brightfield and different spectral ranges, with up to 60x magnification. The high throughput of MIFC has high potential for increasing the amount and accuracy of environmental monitoring, such as for plant-pollinator interactions, fossil samples, air, water or food quality that currently rely on manual microscopic methods. Automated recognition of particles and cells is also possible, when MIFC is combined with deep-learning computational techniques. Furthermore, various fluorescence dyes can be used to stain specific parts of the cell to highlight physiological and chemical features including: vitality of pollen or algae, allergen content of individual pollen, surface chemical composition (carbohydrate coating) of cells, DNA- or enzyme-activity staining. Here, we outline the great potential for MIFC in environmental research for a variety of research fields and focal organisms. In addition, we provide best practice recommendations.

Changes in phenology induced by climate change occur across the globe with important implications for ecosystem functioning and services, species performance and trophic interactions. Much of the work on phenology, especially leaf out and flowering, has been conducted on woody plant species. Less is known about the responses in phenology of herbaceous species induced by global change even though they represent a large and important part of biodiversity worldwide. A globally coordinated research effort is needed to understand the drivers and implications of such changes and to predict effects of global change on plant species phenology and related ecosystem processes. Here, we present the rationale of the PhenObs initiative-botanical gardens as a global phenological observation network. The initiative aims to collect data on plant phenology in botanical gardens which will be used alongside information on plant traits and site conditions to answer questions related to the consequences of global change: What is the variation in plant phenology in herbaceous species across the growing season and in response to changes in climate? How can plant phenology be predicted from species' trait composition, provenance, position and extent of the distribution range and species' phylogeny? What are the implications of this variation with respect to species performance and assembly, biotic interactions (e.g. plant-pollinator interactions) as well as ecosystem processes and services under changing land use and climate? Here, we lay out the development of a straightforward protocol that is appropriate for monitoring phenology across a vast diversity of growth forms of herbaceous species from various habitats and geographical regions. To focus on a key number of stages necessary to capture all aspects of plant species phenology, we analysed associations between 14 phenological stages. These data were derived from a 2-year study on 199 species in four German botanical gardens. Based on the relationships of the phenological stages, we propose to monitor three vegetative stages ('initial growth', 'leaves unfolding' and 'senescence') and two reproductive stages ('flowers open' and 'ripe fruits') to fully capture herbaceous species phenology. A free Plain Language Summary can be found within the Supporting Information of this article.

Trees store most of the nonstructural carbon (NSC, mainly sugars and starch) in the stem wood to support metabolism and growth. For many species, NSC concentration decreases radially with sapwood depth. Spatial distribution of NCS also varies with wood anatomical traits, as NSC is dispersed in the wood living-fibers or concentrated in parenchyma cells. These distributions may influence temporal changes in NSC and are related to mortality and growth. Observed relations between NSC storage and wood traits thus are associated with differences in the time scales of NSC cycling in trees and in the ability of trees to survive and recover from stressful conditions such as drought or mechanical damage. Here we focus on the following questions: i) what are the radial mobilization rates of NSC across the sapwood for tropical trees with different NSC spatial distributions? and ii) how old is the NSC stored in these trees and the NSC that they access for respiration and wood growth?To answer these questions we measured NSC content through a radial path in the sapwood (from bark to pith) in eight tropical tree species, four fiber and four parenchyma-storing species, in a seasonal dry forest in Brazil during 2019. We measured the 14C in the soluble carbon extracted from wood segments corresponding to two depth ranges of each radial path (0-2cm and 2-4cm) and in the respired CO2 from 6cm wood core segments. We estimated the age of the wood by counting tree rings and measuring the 14C in the cellulose. We found significant seasonal changes in the starch content at different sapwood depths in all trees evaluated, indicating that NSC is metabolically active across all depths where starch is stored. Radiocarbon data indicate that fiber-storing trees retained NSC in the wood for decades. In some cases NSC was even older than the wood that contained it, indicating the mixing of old NSC coming from deeper layers of wood. Irrespective of the stored NSC ages, trees always used younger NSC for respiration, indicating that our water extraction includes both reserves being used for metabolism and older C that may be less available at the moment of sampling. However, trees accessed older NSC when they faced stressful conditions, e.g. when in negative C balance, requiring a larger contribution of the old stored NSC to support respiration. Thus, tree species with low mortality and slow growth such as fiber-storing species may remobilize older NSC from deeper layers of wood to survive stressful conditions for longer time than parenchyma-storing species.These findings highlight the diversity of NSC storage and remobilization strategies in tropical trees. These strategies have important implications for our understanding not only of how trees will respond to future climatic changes but also about the mechanism of carbon cycling in tropical trees and ecosystems.

Nowadays, more and more biodiversity datasets containing observational and experimental data are collected and produced by different projects. In order to answer the fundamental questions of biodiversity research, these data need to be integrated for joint analyses. However, to date, too often, these data remain isolated in silos. Both in academia and industry, Knowledge Graphs (KGs) are widely regarded as a promising approach to overcome issues of data silos and lack of common understanding of data (Fensel and Şimşek 2020). KGs are graph-structured knowledge bases that store factual information in the form of structured relationships between entities, like “tree_species has_trait average_SLA” or “nutans is_observed_in SCH_Location" (Hogan et al. 2021). In our context, entities could be, e.g., abstract concepts like a kingdom, a species, or a trait, or a concrete specimen of a species. Example relationships could be "co-occurs" or, "possesses-trait". KGs for biodiversity have been proposed by Page 2019 and have also been the topic at prior TDWG conferences *1 (Page 2021). However, to date, uptake of this concept in the community has been rather slow (Sachs et al. 2019). We argue that this is at least partially due to the high effort and expertise required in developing and managing such KGs. Therefore, in our ongoing project, iKNOW (Babalou et al. 2021), we aim to provide a toolbox for reproducible KG creation. While iKNOW is still in an early stage, we aim to make this platform open-source and freely available to the biodiversity community. Thus, it can significantly contribute to making biodiversity data widely available, easily discoverable, and integratable. For now, we focus on tabular datasets resulting from biodiversity observation or sampling events or experiments. Given such a dataset, iKNOW will support its transformation into (subject, predicate, object) triples in the RDF standard (Resource Description Framework). Every uploaded dataset will be considered as a subgraph of the main KG in iKNOW. If required, data can be cleaned. After that, the entities and relationships among them should be extracted. For that, a user will be able select one of the existing semi-automatic tools available on our platform (e.g., JenTab (Abdelmageed and Schindler 2020)). The entities in this step can be linked to respective global identifiers in Wikidata, GBIF, the Global Biodiversity Information Facility, or any other user-selected knowledge resource. In the next step, (subject, predicate, object) triples based on the extracted information from the previous steps will be created. After these processes, the generated sub-KG can be used directly. However, one can take further steps such as: Triple Augmentation (generate new triples and extra relations to ease KG completion), Schema Refinement (refine the schema, e.g., via logical reasoning for the KG completion and correctness), Quality Checking (check the quality of the generated sub-KG), and Query Building (create customized SPARQL queries for the generated KG). iKNOW will include a wide range of functionalities for creating, accessing, querying, visualizing, updating, reproducing, and tracking the provenance of KGs. The reproducibility of such a creation is essential to strengthening the establishment of open science practices in the biodiversity domain. Thus, all information regarding the user-selected tools with parameters and settings, along with the initial dataset and intermediate results, will be saved in every step of our platform. With the help of this, users can redo the previous steps. Moreover, this enables us to track the provenance of the created KG. The iKNOW project is a joint effort by computer scientists and domain experts from the German Centre for Integrative Biodiversity Research (iDiv). As a showcase, we aim to create a KG of plant-related data sources at iDiv. These include, among others: TRY (the plant trait database) (Kattge and DÍaz 2011), sPlot (the database about global patterns of taxonomic, functional, and phylogenetic diversity) (Bruelheide and Dengler 2019), and PhenObs (the dataset of the global network of botanical gardens monitoring the impacts of climate change on the phenology of herbaceous plant species) (Nordt and Hensen 2021), LCVP, the Leipzig Catalogue of Vascular Plants, (Freiberg and Winter 2020), and many others. The resulting KG will serve as a discovery tool for biodiversity data and provide a robust infrastructure for managing biodiversity knowledge. From the biodiversity research perspective, iKNOW will contribute to creating a dataset following the Linked Open Data principles by interlinking to cross-domain and specific-domain KGs. From the computer science perspective, iKNOW will contribute to developing tools for dynamic, low-effort creation of reproducible knowledge graphs.

We tested the seasonal variability of frost resistance and photosynthesis characteristics, namely net photosynthetic rate at saturating irradiance and ambient atmospheric CO2 concentrations, maximum carboxylation rate, and measurements based on the JIP-test, namely maximum quantum yield of PSII and the performance index. Additionally, we measured leaf functional traits, namely specific leaf area, leaf dry matter content, stomatal pore area index, and chlorophyll content. We assessed all traits weekly on two evergreen species Berberis vulgaris and Quercus × hispanica as well as the two summer green species Betula pendula and Quercus pubescens. We found that there was a high seasonal variability in all traits except stomatal pore area index. In a multivariate analysis, we could show trade-offs between growth rates and leaf thickness on the first axis, as well as resistance and performance on the second axis. The findings help understand ecophysiological processes and fine-tune biosphere models.

Patterns of flowering phenology, i.e. first and last flowering day (FFD and LFD) and flowering duration (FD) govern plant pollination and reproduction. Most research has focused on FFD whereas LFD, FD and second flowering events were neglected although they are crucial events. To assess whether flowering patterns change species-specifically with changing abiotic conditions and whether these are related to leaf persistence, reproduction and pollination syndrome, we monitored flowering phenology (including also second flowering events) of 29 herbaceous species along two elevational gradients ranging from 700 to 1800 m a.s.l. in two consecutive years. FFD was delayed with increasing elevation. LFD followed two alternative strategies: species which ceased flowering early in the season delayed LFD with increasing elevation, species which ceased flowering late did not change LFD. FD decreased with increasing elevation in most species. The timing of flowering phenology had strong influences on the intensity of change along the elevational gradient and other stages of flowering phenology. Many species showed a second flowering event which occurred irrespective of elevation, suggesting a link to unsuccessful pollination rather than temperature. Life history strategies helped explain patterns of flowering phenology and a species’ ability to track changes in abiotic conditions, e.g. evergreen species started to flower earlier than summer green species and insect-pollinated species were able to expand FD most. These findings give insight into species-specific changes in phenological patterns and thus plant performance with changing environment. They should be considered when assessing the consequences of environmental change at both the community and ecosystem level.

Plant functional traits can predict community assembly and ecosystem functioning and are thus widely used in global models of vegetation dynamics and land–climate feedbacks. Still, we lack a global understanding of how land and climate affect plant traits. A previous global analysis of six traits observed two main axes of variation: (1) size variation at the organ and plant level and (2) leaf economics balancing leaf persistence against plant growth potential. The orthogonality of these two axes suggests they are differently influenced by environmental drivers. We find that these axes persist in a global dataset of 17 traits across more than 20,000 species. We find a dominant joint effect of climate and soil on trait variation. Additional independent climate effects are also observed across most traits, whereas independent soil effects are almost exclusively observed for economics traits. Variation in size traits correlates well with a latitudinal gradient related to water or energy limitation. In contrast, variation in economics traits is better explained by interactions of climate with soil fertility. These findings have the potential to improve our understanding of biodiversity patterns and our predictions of climate change impacts on biogeochemical cycles., Nature Ecology & Evolution, 6 (1), ISSN:2397-334X

1. Phenology has emerged as key indicator of the biological impacts of climate change, yet the role of functional traits constraining variation in herbaceous species’ phenology has received little attention. Botanical gardens are ideal places in which to investigate large numbers of species growing under common climate conditions. We ask whether interspecific variation in plant phenology is influenced by differences in functional traits. 2. We recorded onset, end, duration and intensity of initial growth, leafing out, leaf senescence, flowering and fruiting for 212 species across five botanical gardens in Germany. We measured functional traits, including plant height, absolute and specific leaf area, leaf dry matter content, leaf carbon and nitrogen content and seed mass and accounted for species’ relatedness. 3. Closely related species showed greater similarities in timing of phenological events than expected by chance, but species' traits had a high degree of explanatory power, pointing to paramount importance of species’ life-history strategies. Taller plants showed later timing of initial growth, and flowered, fruited and underwent leaf senescence later. Large-leaved species had shorter flowering and fruiting durations. 4. Taller, large-leaved species differ in their phenology and are more competitive than smaller, small-leaved species. We assume climate warming will change plant communities’ competitive hierarchies with consequences for biodiversity.

13 Pág. Departamento de Medio Ambiente y Agronomía​ (INIA), Remote sensing capabilities to monitor evergreen broadleaved vegetation are limited by the low temporal variability in the greenness signal. With canopy greenness computed from digital repeat photography (PhenoCam), we investigated how canopy greenness related to seasonal changes in leaf age and traits as well as variation of trees’ water fluxes (characterized by sap flow and canopy conductance). The results showed that sprouting leaves are mainly responsible for the rapid increase in canopy green chromatic coordinate (GCC) in spring. We found statistically significantly differences in leaf traits and spectral properties among leaves of different leaf ages. Specifically, mean GCC of young leaves was 0.385 ± 0.010 (mean ± SD), while for mature and old leaves was 0.369 ± 0.003, and 0.376 ± 0.004, respectively. Thus, the temporal dynamics of canopy GCC can be explained by changes in leaf spectral properties and leaf age. Sap flow and canopy conductance are both well explained by a combination of environmental drivers and greenness (96% and 87% of the variance explained, respectively). In particular, air temperature and vapor pressure deficit (VPD) explained most of sap flow and canopy conductance variance, respectively. Besides, GCC is an important explanatory variable for variation of canopy conductance may because GCC can represent the leaf ontogeny information. We conclude that PhenoCam GCC can be used to identify the leaf flushing for evergreen broadleaved trees, which carries important information about leaf ontogeny and traits. Thus, it can be helpful for better estimating canopy conductance which constraints water fluxes., The authors acknowledge the Alexander von Humboldt Foundation for supporting this research with the Max Planck Prize to Markus Reichstein. Yunpeng Luo and Mirco Migliavacca gratefully acknowledge the financial support from the China Scholarship Council. ADR acknowledges support for the PhenoCam network from the National Science Foundation ( DEB- 1702697 ). Javier Pacheco-Labrador and Mirco Migliavacca acknowledge the German Aerospace Center (DLR) project OBEF-Accross2 “The Potential of Earth Observations to Capture Patterns of Biodiversity” (Contract No. 50EE1912). The research also received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 721995 and Ministerio de Economíay Competitividad through FLUXPEC CGL2012-34383 and SynerTGE CGL2015-G9095-R (MINECO/FEDER, UE) projects.

Questions: Livestock management in rangelands depends on the production of plant biomass. Biomass production is driven by the temporal and spatial variability in precipitation, but our understanding of how precipitation variability mediates grazing effects on biomass production is still fragmented. Along a 600-km precipitation gradient we extracted biomass data to ask the questions: (a) what are the effects of grazing intensity on biomass production; (b) does grazing intensity interact with plant species richness to affect biomass production; and (c) how do plant functional groups respond to grazing and precipitation?. Location: Mongolia. Methods: Biomass was sampled along 15 grazing intensity transects within the precipitation gradient over two consecutive years. We modeled spatial variability in above-ground plant biomass using mixed-effects models. Normalized difference vegetation index (NDVI) data were combined with field-sampled biomass data to correct for inter-annual precipitation variation. The effects of species richness were modeled with respect to possible interactions with grazing intensity, and the composition of plant functional groups was modeled with respect to possible interactions between grazing intensity and precipitation. Results: Biomass was negatively correlated with grazing intensity and this effect increased as precipitation increased. Biomass was positively correlated with species richness in both years, but the strength of this effect and the interaction between species richness and grazing intensity differed between 2014 and 2015 in line with highly variable precipitation between both years. The plant functional groups grasses, sedges, legumes, wormwood and forbs had contrasting responses to grazing and precipitation. Conclusion: Biomass production in drylands is more vulnerable to changes in precipitation variability and grazing intensities in relatively moist and productive rangelands than in dry and unproductive ones. Future rangeland management needs to address potentially increasing precipitation variability in order to promote desired forage plants, and to preserve the positive effects of biodiversity for biomass production.

The intraspecific plant trait variability (ITV) is key for many ecological processes, but large-scale analysis of co-occurring species are rare. Here we studied ITV of 14 plant traits for five co-occurring species across 56 European dry grassland sites – large parts of the species distribution ranges. We evaluated variation in ITV relative to between species trait variability (BTV) with a particular emphasis on how within versus between population variability contributes to ITV. We performed this analysis trait by trait (univariate) and by considering hypervolumes in the multi-variate trait space. We also tested whether climatic variables can be used to predict between population variation in traits. For the trait by trait analysis, for 9 out of 14 traits ITV exceeded BTV, which suggests an extraordinary large role of ITV. However, when considering all traits jointly the hypervolume occupied by ITV was only 23% of overall trait variability. We found comparatively small effects of within population variability in the uni- as well as in the multivariate analysis decreasing rapidly with increasing number of considered traits. The dominance of between population variability suggests that ITV is mainly driven by environmental effects rather than local biotic interactions and microsite effects. ITV of leaf chemical traits was related to precipitation and growing degree days until sampling ITV can be substantial compared to BTV, in particular when considering single traits, such that ITV should be considered in trait-based research. Since the importance of ITV appears to decrease when considering multiple traits jointly, using species mean trait values is more appropriate for multi-variate trait analysis. Because ITV varied mainly between populations rather than within populations, and was related to climatic conditions, we suggest that ITV could be accounted for in future trait based research by including environmental covariates in hierarchical models of trait variation

Moisture availability is the main limiting factor of plant growth and biomass production in arid and semi-arid grasslands. The question whether plant responses to changing precipitation are species-specific, or change over entire plant communities is still controversial. Our study focussed on intraspecific changes in the plant traits canopy height, plant width, specific leaf area, chlorophyll fluorescence, performance index, and individual biomass of three congeneric species pairs with changing precipitation in Mongolian rangelands, covering a gradient from the desert to the forest steppes. Using this trait data set, we focussed on three questions: (i) Is the replacement of congeneric species along an environmental gradient also reflected in their trait values? (ii) Can intraspecific trait variation patterns be derived from patterns in species abundances, i.e., are trait values optimal where species are most abundant? (iii) Is the within-population trait variability lowest in populations growing under very dry conditions, i.e., under highest environmental stress, caused by stronger filtering? We tested the responses of the six traits to changing precipitation according to species’ identity and abundance. We found unimodal relationships between most of the species’ traits and precipitation, and strong associations between species abundances and trait values, but not for all investigated species. Trait variability did not significantly differ between populations from different positions along the precipitation gradient. Our results highlight that species show multiple or even opposite trait responses along the precipitation gradient. It thus remains challenging to predict how plant distributions will shift under changing environmental conditions based on their trait composition.

Frost resistance (FR) is a highly adaptive trait and important for plant performance, survival and distribution. While overall seasonal changes in the frost resistance of herbaceous species are well documented, knowledge of the variability during the growth period is scarce. Responses could be expected due to differences in temperature yet investment in frost resistance might be at the expense of plant performance. To analyse temporal and spatial (i.e. same date but differing temperatures) variability, FR of leaves of six herbaceous species on five sampling dates were assessed along an elevational gradient in the northern limestone Alps. We used chlorophyll fluorescence techniques to calculate the lethal temperature of 90% of the population (LT90) thereof. To test the association with plant performance, we measured eco-morphological leaf traits (specific leaf area (SLA), leaf dry matter content, leaf phosphorous and magnesium content as well as stomatal pore area index (SPI)) in parallel. We found that FR as well as leaf traits exhibit a strong temporal variation whereas spatial variability was low. When analysing the relationship of FR to leaf traits we found that SLA as a proxy of growth rate was negatively associated with FR indicating a trade-off between growth and resistance, whereas SPI showed a positive relationship to FR. This finding gives further insight into the variability of traits and will help to improve predictions concerning plant performance and distribution under changing climate regimes.

QUESTIONS: Are the vegetation structure and soil properties of fallows similar to adjacent species‐rich Mediterranean steppe communities 35 years after abandonment? Is there a spontaneous redevelopment towards the original steppe vegetation after reintroduction of the traditional grazing system? Can differences in functional trait composition be identified according to different land‐use types? Do traits of selected species affect the ability to recolonize fallow land? LOCATION: Mediterranean steppe of La Crau (Southeastern France). METHODS: We conducted 80 vegetation surveys and soil analyses in the steppe and adjacent fallow land in six locations in La Crau in 2015; for three locations, data from 2001 were included. To compare the functional composition of steppe vs fallow land, community‐weighted means (CMW) of specific leaf area (SLA), leaf dry matter content (LDMC) and canopy height were calculated. To test whether trait variability is associated with the recolonization success of 12 selected target species, we measured SLA, LDMC, canopy height, plant width and aboveground biomass on eight replicate individuals per site and species. RESULTS: Fallow land was characterized by lower species richness and elevated phosphorus and potassium content in the soil. Comparing vegetation releves between 2001 and 2015 revealed that the fallows were developing towards steppe vegetation. CWMs of SLA were significantly lower and CWM of LDMC higher in steppe than in fallow land. There was no similarity in trait composition between steppe species that successfully recolonized the fallow‐land community, and no evidence that intraspecific trait variability is associated with recolonization success of these species. CONCLUSIONS: Even after decades of abandonment and reintroduction of the grazing system, the vegetation structure, soil properties and plant functional trait composition of fallows differ from those of adjacent steppe communities. These results illustrate the need for active restoration to accelerate the recovery of former arable land to the target steppe communities.

We tested whether cheap and quick chlorophyll (Chl) fluorescence can be used in ecophysiological field studies as proxies for gas-exchange measurements. We measured net photosynthetic rate at saturating irradiance and ambient atmospheric CO2 concentrations (PNsat), maximum carboxylation rate (Vcmax), maximum quantum yield of PSII (Fv/Fm), the performance index (PIabs), leaf nitrogen (Narea), and carbon isotope discrimination (Δ13C) within four herbaceous species along two elevational gradients. We analysed the relationship between Chl fluorescence and gas-exchange parameters and their link to indirect assessment of plant performance via ecophysiological traits. Fv/Fm showed no relationship to PNsat and only weak relationships to Vcmax. PIabs was positively related to PNsat and Vcmax. PIabs, PNsat, and Vcmax were positively associated with Narea and negatively to Δ13C, whereas Fv/Fm showed no relationship to Narea and a positive to Δ13C. Thus, PIabs might be suitable to characterize the photosynthetic activity when aiming on large numbers of samples.

Data is central in almost all scientific disciplines nowadays. Furthermore, intelligent systems have developed rapidly in recent years, so that in many disciplines the expectation is emerging that with the help of intelligent systems, significant challenges can be overcome and science can be done in completely new ways. In order for this to succeed, however, first, fundamental research in computer science is still required, and, second, generic tools must be developed on which specialized solutions can be built. In this paper, we introduce a recently started collaborative project funded by the Carl Zeiss Foundation, a virtual manufactory for digitization in the sciences, the “Werkstatt”, which is being established at the Michael Stifel Center Jena (MSCJ) for data-driven and simulation science to address fundamental questions in computer science and applications. The Werkstatt focuses on three key areas, which include generic tools for machine learning, knowledge generation using machine learning processes, and semantic methods for the data life cycle, as well as the application of these topics in different disciplines. Core and pilot projects address the key aspects of the topics and form the basis for sustainable work in the Werkstatt.

Background and Aims Non-native plant species are not restricted to lowlands, but increasingly are invading high elevations. While for both native and non-native species we expected variability of plant functional traits due to the changing environmental conditions along elevational gradients, we additionally assumed that non-native species are characterized by a more acquisitive growth strategy, as traits reflecting such a strategy have been found to correlate with invasion success. Furthermore, the typical lowland introduction of non-native species coming from multiple origins should lead to higher trait variability within populations of non-native species specifically at low elevations, and they might therefore occupy a larger total trait space. Methods Along an elevational gradient ranging from 55 to 1925 m a.s.l. on Tenerife, we collected leaves from eight replicate individuals in eight evenly distributed populations of five native and six non-native forb species. In each population, we measured ten eco-morphological and leaf biochemical traits and calculated trait variability within each population and the total trait space occupied by native and non-native species. Key Results We found both positive (e.g. leaf dry matter content) and negative (e.g. leaf N) correlations with elevation for native species, but only few responses for non-native species. For non-native species, within-population variability of leaf dry matter content and specific leaf area decreased with elevation, but increased for native species. The total trait space occupied by all non-native species was smaller than and a subset of that of native species. Conclusions We found little evidence that intraspecific trait variability is associated with the success of non-native species to spread towards higher elevations. Instead, for non-native species, our results indicate that intermediate trait values that meet the requirements of various conditions are favourable across the changing environmental conditions along elevational gradients. As a consequence, this might prevent non-native species from overcoming abruptly changing environmental conditions, such as when crossing the treeline.

There are still major gaps in our understanding of rangeland degradation. Assessing the interactions between climate and grazing effects could help to explain what unifies and separates rangelands, and may therefore promote a more sustainable management of livestock. We studied 15 local land-use transects along a 600 km long climatic gradient in Central Asia to test the hypothesis that grazing effects differ between relatively moist equilibrium (EQ) and dry non-equilibrium (NEQ) rangeland systems. We analysed plant community composition, species diversity and indicator species for different grazing intensities. We found pronounced differences in community composition along our climate gradient, revealed climate-related grazing effects on richness, responses of Simpson's diversity, and also found different grazing indicator species along the larger transect. We conclude that in NEQ rangelands, grazing effects are limited to sacrifice zones and environmental filtering dominates vegetation composition. With increasing precipitation, resource availability gains in importance leading to more complex communities dominated by grazing-tolerant species under EQ dynamics. Hints for xerophytization in the transition zone between EQ and NEQ highlight the vulnerability of rangelands that temporally shift from one state to the other. This calls for extra care in the management of livestock numbers in these transition areas.

Based on fossil organism remains including plant macrofossils, charcoal, pollen, and invertebrates preserved in syngenetic deposits of the Batagay permafrost sequence in the Siberian Yana Highlands, we reconstructed the environmental history during marine isotope stages (MIS) 6 to 2. Two fossil assemblages, exceptionally rich in plant remains, allowed for a detailed description of the palaeo-vegetation during two climate extremes of the Late Pleistocene, the onset of the last glacial maximum (LGM) and the last interglacial. In addition, altogether 41 assemblages were used to outline the vegetation history since the penultimate cold stage of MIS 6. Accordingly, meadow steppes analogue to modern communities of the phytosociological order Festucetalia lenensis formed the primary vegetation during the Saalian and Weichselian cold stages. Cold-resistant tundra-steppe communities (Carici rupestris-Kobresietea bellardii) as they occur above the treeline today were, in contrast to more northern locations, mostly lacking. During the last interglacial, open coniferous woodland similar to modern larch taiga was the primary vegetation at the site. Abundant charcoal indicates wildfire events during the last interglacial. Zoogenic disturbances of the local vegetation were indicated by the presence of ruderal plants, especially by abundant Urtica dioica, suggesting that the area was an interglacial refugium for large herbivores. Meadow steppes, which formed the primary vegetation during cold stages and provided potentially suitable pastures for herbivores, were a significant constituent of the plant cover in the Yana Highlands also under the full warm stage conditions of the last interglacial. Consequently, meadow steppes occurred in the Yana Highlands during the entire investigated timespan from MIS 6 to MIS 2 documenting a remarkable environmental stability. Thus, the proportion of meadow steppe vegetation merely shifted in response to the respectively prevailing climatic conditions. Their persistence indicates low precipitation and a relatively warm growing season throughout and beyond the late Pleistocene. The studied fossil record also proves that modern steppe occurrences in the Yana Highlands did not establish as late as in the Holocene but instead are relicts of a formerly continuous steppe belt extending from Central Siberia to Northeast Yakutia during the Pleistocene. The persistence of plants and invertebrates characteristic of meadow steppe vegetation in interior Yakutia throughout the late Quaternary indicates climatic continuity and documents the suitability of this region as a refugium also for other organisms of the Pleistocene mammoth steppe including the iconic large herbivores. (C)2018 Elsevier Ltd. All rights reserved.

Anthropogenic nitrogen (N) deposition and resulting differences in ecosystem N and phosphorus (P) ratios are expected to impact photosynthetic capacity, that is, maximum gross primary productivity (GPP). However, the interplay between N and P availability with other critical resources on seasonal dynamics of ecosystem productivity remains largely unknown. In a Mediterranean tree–grass ecosystem, we established three landscape-level (24 ha) nutrient addition treatments: N addition (NT), N and P addition (NPT), and a control site (CT). We analyzed the response of ecosystem to altered nutrient stoichiometry using eddy covariance fluxes measurements, satellite observations, and digital repeat photography. A set of metrics, including phenological transition dates (PTDs; timing of green-up and dry-down), slopes during green-up and dry-down period, and seasonal amplitude, were extracted from time series of GPP and used to represent the seasonality of vegetation activity. The seasonal amplitude of GPP was higher for NT and NPT than CT, which was attributed to changes in structure and physiology induced by fertilization. PTDs were mainly driven by rainfall and exhibited no significant differences among treatments during the green-up period. Yet, both fertilized sites senesced earlier during the dry-down period (17–19 days), which was more pronounced in the NT due to larger evapotranspiration and water usage. Fertilization also resulted in a faster increase in GPP during the green-up period and a sharper decline in GPP during the dry-down period, with less prominent decline response in NPT. Overall, we demonstrated seasonality of vegetation activity was altered after fertilization and the importance of nutrient–water interaction in such water-limited ecosystems. With the projected warming-drying trend, the positive effects of N fertilization induced by N deposition on GPP may be counteracted by an earlier and faster dry-down in particular in areas where the N:P ratio increases, with potential impact on the carbon cycle of water-limited ecosystems., The authors acknowledge the Alexander von Humboldt Foundation for supporting this research with the Max-Planck Prize to Markus Reichstein. Yunpeng Luo and Mirco Migliavacca gratefully acknowledge financial support from the China Scholarship Council. Gerardo Moreno acknowledges financial support from the grant agreement IB16185 of the Regional Government of Extremadura.

●In trees, the use of nonstructural carbon (NSC) under limiting conditions impacts the age structure of the NSC pools. We compared model predictions of NSC ages and transit times for Pinus halepensis, Acer rubrum and Pinus taeda, to understand differences in carbon (C) storage dynamics in species with different leaf phenology and growth environments. ●We used two C allocation models from the literature to estimate the NSC age and transit time distributions, to simulate C limitation, and to evaluate the sensitivity of the mean ages to changes in allocation fluxes. ●Differences in allocation resulted in different NSC age and transit time distributions. The simulated starvation flattened the NSC age distribution and increased the mean NSC transit time, which can be used to estimate the age of the NSC available and the time it would take to exhaust the reserves. Mean NSC ages and transit times were sensitive to C fluxes in roots and allocation of C from wood storage. ●Our results demonstrate how trees with different storage traits are expected to react differently to starvation. They also provide a probabilistic explanation for the 'last-in, first-out' pattern of NSC mobilization from well-mixed C pools.