Trait means, trait plasticity and trait differences to other species jointly explain species performances in grasslands of varying diversity

Functional traits may help to explain the great variety of species performances in plant communities, but it is not clear whether the magnitude of trait values of a focal species or trait differences to co‐occurring species are key for trait‐based predictions. In addition, trait expression within species is often plastic, but this variation has been widely neglected in trait‐based analyses. We studied functional traits and plant biomass of 59 species in 66 experimental grassland mixtures of varying species richness (Jena Experiment). We related mean species performances (species biomass and relative yield RY) and their plasticities along the diversity gradient to trait‐based pedictors involving mean species traits (Tmean), trait plasticities along the diversity gradient (Tslope), extents of trait variation across communities (TCV; coefficient of variation) and hierarchical differences (Tdiff) and trait distances (absolute values of trait differences Tdist) between focal and co‐occurring species. Tmean (30–55%) and Tdiff (30–33%) explained most variation in mean species performances and their plasticities, but Tslope (20–25%) was also important in explaining mean species performances. The mean species traits and the trait differences between focal species and neighbors with the greatest explanatory power were related to plant size and stature (shoot length, mass:height ratios) and leaf photosynthetic capacity (specific leaf area, stable carbon isotopes and leaf nitrogen concentration). The contribution of trait plasticities in explaining species performances varied in direction (positive or negative) and involved traits related to photosynthetic capacity, nitrogen acquisition (nitrogen concentrations and stable isotopes) as well as structural stability (shoot carbon concentrations). Our results suggest that incorporating plasticity in trait expression as well as trait differences to co‐occurring species is critical for extending trait‐based analyses to understand the assembly of plant communities and the contribution of individual species in structuring plant communities

Origin context of trait data matters for predictions of community performance in a grassland biodiversity experiment

Plant functional traits may explain the positive relationship between species richness and ecosystem functioning, but species‐level trait variation in response to growth conditions is often ignored in trait‐based predictions of community performance. In a large grassland biodiversity experiment (Jena Experiment), we measured traits on plants grown as solitary individuals, in monocultures or in mixtures. We calculated two measures of community‐level trait composition, i.e., community‐weighted mean traits (CWM) and trait diversity (Rao's quadratic entropy; FD) based on different contexts in which traits were measured (trait origins). CWM and FD values of the different measurement origins were then compared regarding their power to predict community biomass production and biodiversity effects quantified with the additive partitioning method. Irrespective of trait origin, models combining CWM and FD values as predictors best explained community biomass and biodiversity effects. CWM values based on monoculture, mixture‐mean or community‐specific trait data were similarly powerful predictors, but predictions became worse when trait values originated from solitary‐grown individuals. FD values based on monoculture traits were the best predictors of community biomass and net biodiversity effects, while FD values based on community‐specific traits were the best predictors for complementarity and selection effects. Traits chosen as best CWM predictors were not strongly affected by trait origin but traits chosen as best FD predictors varied strongly dependent on trait origin and altered the predictability of community performance. We conclude that by adjusting their functional traits to species richness and even specific community compositions, plants can change community‐level trait compositions, thereby also changing community biomass production and biodiversity effects. Incorporation of these plastic trait adjustments of plants in trait‐based ecology can improve its predictive power in explaining biodiversity–ecosystem functioning relationships

Long-read sequencing identifies a common transposition haplotype predisposing for CLCNKB deletions

BACKGROUND: Long-read sequencing is increasingly used to uncover structural variants in the human genome, both functionally neutral and deleterious. Structural variants occur more frequently in regions with a high homology or repetitive segments, and one rearrangement may predispose to additional events. Bartter syndrome type 3 (BS 3) is a monogenic tubulopathy caused by deleterious variants in the chloride channel gene CLCNKB, a high proportion of these being large gene deletions. Multiplex ligation-dependent probe amplification, the current diagnostic gold standard for this type of mutation, will indicate a simple homozygous gene deletion in biallelic deletion carriers. However, since the phenotypic spectrum of BS 3 is broad even among biallelic deletion carriers, we undertook a more detailed analysis of precise breakpoint regions and genomic structure. METHODS: Structural variants in 32 BS 3 patients from 29 families and one BS4b patient with CLCNKB deletions were investigated using long-read and synthetic long-read sequencing, as well as targeted long-read sequencing approaches. RESULTS: We report a ~3 kb duplication of 3'-UTR CLCNKB material transposed to the corresponding locus of the neighbouring CLCNKA gene, also found on ~50 % of alleles in healthy control individuals. This previously unknown common haplotype is significantly enriched in our cohort of patients with CLCNKB deletions (45 of 51 alleles with haplotype information, 2.2 kb and 3.0 kb transposition taken together, p=9.16×10-9). Breakpoint coordinates for the CLCNKB deletion were identifiable in 28 patients, with three being compound heterozygous. In total, eight different alleles were found, one of them a complex rearrangement with three breakpoint regions. Two patients had different CLCNKA/CLCNKB hybrid genes encoding a predicted CLCNKA/CLCNKB hybrid protein with likely residual function. CONCLUSIONS: The presence of multiple different deletion alleles in our cohort suggests that large CLCNKB gene deletions originated from many independently recurring genomic events clustered in a few hot spots. The uncovered associated sequence transposition haplotype apparently predisposes to these additional events. The spectrum of CLCNKB deletion alleles is broader than expected and likely still incomplete, but represents an obvious candidate for future genotype/phenotype association studies. We suggest a sensitive and cost-efficient approach, consisting of indirect sequence capture and long-read sequencing, to analyse disease-relevant structural variant hotspots in general

Measurement of the cosmic ray spectrum above 4×10184{\times}10^{18} eV using inclined events detected with the Pierre Auger Observatory

A measurement of the cosmic-ray spectrum for energies exceeding $4{\times}10^{18}$ eV is presented, which is based on the analysis of showers with zenith angles greater than $60^{\circ}$ detected with the Pierre Auger Observatory between 1 January 2004 and 31 December 2013. The measured spectrum confirms a flux suppression at the highest energies. Above $5.3{\times}10^{18}$ eV, the "ankle", the flux can be described by a power law $E^{-\gamma}$ with index $\gamma=2.70 \pm 0.02 \,\text{(stat)} \pm 0.1\,\text{(sys)}$ followed by a smooth suppression region. For the energy ($E_\text{s}$) at which the spectral flux has fallen to one-half of its extrapolated value in the absence of suppression, we find $E_\text{s}=(5.12\pm0.25\,\text{(stat)}^{+1.0}_{-1.2}\,\text{(sys)}){\times}10^{19}$ eV.Comment: Replaced with published version. Added journal reference and DO

Using Plant Functional Traits to Explain Diversity–Productivity Relationships

Background: The different hypotheses proposed to explain positive species richness–productivity relationships, i.e. selection effect and complementarity effect, imply that plant functional characteristics are at the core of a mechanistic understanding of biodiversity effects. Methodology/Principal Findings: We used two community-wide measures of plant functional composition, (1) community- weighted means of trait values (CWM) and (2) functional trait diversity based on Rao’s quadratic diversity (FDQ) to predict biomass production and measures of biodiversity effects in experimental grasslands (Jena Experiment) with different species richness (2, 4, 8, 16 and 60) and different functional group number and composition (1 to 4; legumes, grasses, small herbs, tall herbs) four years after establishment. Functional trait composition had a larger predictive power for community biomass and measures of biodiversitity effects (40–82% of explained variation) than species richness per se (,1–13% of explained variation). CWM explained a larger amount of variation in community biomass (80%) and net biodiversity effects (70%) than FDQ (36 and 38% of explained variation respectively). FDQ explained similar proportions of variation in complementarity effects (24%, positive relationship) and selection effects (28%, negative relationship) as CWM (27% of explained variation for both complementarity and selection effects), but for all response variables the combination of CWM and FDQ led to significant model improvement compared to a separate consideration of different components of functional trait composition. Effects of FDQ were mainly attributable to diversity in nutrient acquisition and life-history strategies. The large spectrum of traits contributing to positive effects of CWM on biomass production and net biodiversity effects indicated that effects of dominant species were associated with different trait combinations. Conclusions/Significance: Our results suggest that the identification of relevant traits and the relative impacts of functional identity of dominant species and functional diversity are essential for a mechanistic understanding of the role of plant diversity for ecosystem processes such as aboveground biomass production

Bottom-up effects of plant diversity on multitrophic interactions in a biodiversity experiment

Biodiversity is rapidly declining1, and this may negatively affect ecosystem processes, including economically important ecosystem services. Previous studies have shown that biodiversity has positive effects on organisms and processes4 across trophic levels. However, only a few studies have so far incorporated an explicit food-web perspective. In an eight-year biodiversity experiment, we studied an unprecedented range of above- and below-ground organisms and multitrophic interactions. A multitrophic data set originating from a single long-term experiment allows mechanistic insights that would not be gained from meta-analysis of different experiments. Here we show that plant diversity effects dampen with increasing trophic level and degree of omnivory. This was true both for abundance and species richness of organisms. Furthermore, we present comprehensive above-ground/below-ground biodiversity food webs. Both above ground and below ground, herbivores responded more strongly to changes in plant diversity than did carnivores or omnivores. Density and richness of carnivorous taxa was independent of vegetation structure. Below-ground responses to plant diversity were consistently weaker than above-ground responses. Responses to increasing plant diversity were generally positive, but were negative for biological invasion, pathogen infestation and hyperparasitism. Our results suggest that plant diversity has strong bottom-up effects on multitrophic interaction networks, with particularly strong effects on lower trophic levels. Effects on higher trophic levels are indirectly mediated through bottom-up trophic cascades

Diversity Promotes Temporal Stability across Levels of Ecosystem Organization in Experimental Grasslands

The diversity–stability hypothesis states that current losses of biodiversity can impair the ability of an ecosystem to dampen the effect of environmental perturbations on its functioning. Using data from a long-term and comprehensive biodiversity experiment, we quantified the temporal stability of 42 variables characterizing twelve ecological functions in managed grassland plots varying in plant species richness. We demonstrate that diversity increases stability i) across trophic levels (producer, consumer), ii) at both the system (community, ecosystem) and the component levels (population, functional group, phylogenetic clade), and iii) primarily for aboveground rather than belowground processes. Temporal synchronization across studied variables was mostly unaffected with increasing species richness. This study provides the strongest empirical support so far that diversity promotes stability across different ecological functions and levels of ecosystem organization in grasslands

Ten new insights in climate science 2022

Non-technical summary We summarize what we assess as the past year's most important findings within climate change research: limits to adaptation, vulnerability hotspots, new threats coming from the climate–health nexus, climate (im)mobility and security, sustainable practices for land use and finance, losses and damages, inclusive societal climate decisions and ways to overcome structural barriers to accelerate mitigation and limit global warming to below 2°C. Technical summary We synthesize 10 topics within climate research where there have been significant advances or emerging scientific consensus since January 2021. The selection of these insights was based on input from an international open call with broad disciplinary scope. Findings concern: (1) new aspects of soft and hard limits to adaptation; (2) the emergence of regional vulnerability hotspots from climate impacts and human vulnerability; (3) new threats on the climate–health horizon – some involving plants and animals; (4) climate (im)mobility and the need for anticipatory action; (5) security and climate; (6) sustainable land management as a prerequisite to land-based solutions; (7) sustainable finance practices in the private sector and the need for political guidance; (8) the urgent planetary imperative for addressing losses and damages; (9) inclusive societal choices for climate-resilient development and (10) how to overcome barriers to accelerate mitigation and limit global warming to below 2°C. Social media summary Science has evidence on barriers to mitigation and how to overcome them to avoid limits to adaptation across multiple fields

Comprehensive Molecular Characterization of Pheochromocytoma and Paraganglioma

SummaryWe report a comprehensive molecular characterization of pheochromocytomas and paragangliomas (PCCs/PGLs), a rare tumor type. Multi-platform integration revealed that PCCs/PGLs are driven by diverse alterations affecting multiple genes and pathways. Pathogenic germline mutations occurred in eight PCC/PGL susceptibility genes. We identified CSDE1 as a somatically mutated driver gene, complementing four known drivers (HRAS, RET, EPAS1, and NF1). We also discovered fusion genes in PCCs/PGLs, involving MAML3, BRAF, NGFR, and NF1. Integrated analysis classified PCCs/PGLs into four molecularly defined groups: a kinase signaling subtype, a pseudohypoxia subtype, a Wnt-altered subtype, driven by MAML3 and CSDE1, and a cortical admixture subtype. Correlates of metastatic PCCs/PGLs included the MAML3 fusion gene. This integrated molecular characterization provides a comprehensive foundation for developing PCC/PGL precision medicine