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Abstract Background The Oxford classification of IgA nephropathy (IgAN) defines histologic criteria (MEST-C) that provide prognostic information based on the kidney biopsy. There are few data on the predictive impact of this classification in randomized clinical trial settings. Methods We performed an exploratory analysis of MEST-C scores in 70 available renal biopsies from 162 randomized STOP-IgAN trial participants and correlated the results with clinical outcomes. Analyses were performed by researchers blinded to the clinical outcome of the patients. Biopsies had been obtained 6.5 to 95 (median 9.4) months prior to randomization. Results Mesangial hypercellularity (M1) associated with higher annual eGFR-loss during the 3-year trial (M1: − 5.06 ± 5.17 ml/min/1.73 m2, M0: − 0.79 ± 4.50 ml/min/1.73 m2, p = 0.002). An M0-score additionally showed a weak association with full clinical remission, whereas the percentage of patients losing ≥15 ml/min/1.73 m2 over the 3-year trial phase was higher among those scored as M1. Among patients with additional immunosuppression, ESRD occurred more frequently in patients when tubulointerstitial fibrosis (T1/2) was present (T1/2 = 33%, T0 = 0%, p = 0.008). In patients receiving supportive care only, ESRD frequencies were similar (T1/2 = 18%, T0 = 7%, p = 0.603). At randomization, eGFR was significantly lower when tubulointerstitial fibrosis was present (T1/2: 45.2 ± 15.7 ml/min/1.73 m2, T0: 74.6 ± 28.2 ml/min/1.73 m2, p

Abstract Organismal functional strategies form a continuum from slow- to fast-growing organisms, in response to common drivers such as resource availability and disturbance. However, whether there is synchronisation of these strategies at the entire community level is unclear. Here, we combine trait data for >2800 above- and belowground taxa from 14 trophic guilds spanning a disturbance and resource availability gradient in German grasslands. The results indicate that most guilds consistently respond to these drivers through both direct and trophically mediated effects, resulting in a ‘slow-fast’ axis at the level of the entire community. Using 15 indicators of carbon and nutrient fluxes, biomass production and decomposition, we also show that fast trait communities are associated with faster rates of ecosystem functioning. These findings demonstrate that ‘slow’ and ‘fast’ strategies can be manifested at the level of whole communities, opening new avenues of ecosystem-level functional classification.

Traditional orchards are distinctive features of cultural landscapes in Central Europe. Despite their high level of ecological importance, they are in decline, and comprehensive spatial data over broad extents, which could enable a trend analysis, are lacking. We analysed traditional orchard maps from 1952 to 1967 and a map from 2010, generated via aerial image interpretation, for the state of Hesse (ca. 21,115 km2), which has the second largest share of traditional orchards in Germany. We aimed to (1) quantify long-term orchard dynamics, (2) compare orchard characteristics in terms of topographical, ecological, and socioeconomic factors, and (3) identify key drivers of orchard loss. We found that the number and area of orchards have clearly decreased across Hesse, with varying local and regional patterns. Further, historically old orchards tended to have a larger area, higher shape complexity, and were located closer to settlements, highways, and neighbouring orchards. In contrast, newly established orchards were often found at higher elevations and on steeper slopes. Finally, the three historical orchard hotspots also experienced the most notable losses driven by different factors, namely the expansion of Artificial Surfaces, Residential Buildings, and Agricultural Land. We highlight the importance of such multitemporal spatial data for a wide range of ecological applications, and we encourage the use of novel technologies to support geospatial analyses in the future.

Terrestrial ecosystems such as coniferous forests in Central Europe are experiencing changes in health status following extreme droughts compounding with severe heat waves. The increasing temporal resolution and spatial coverage of earth observation data offer new opportunities to assess these dynamics. Dense time-series of optical satellite data allow for computing Dynamic Habitat Indices (DHIs), which have been predominantly used in biodiversity studies. However, DHIs cover three aspects of vegetation changes that could be affected by drought: annual productivity, minimum cover, and seasonality. Here, we evaluate the health status of coniferous forests in the federal state of Hesse in Germany over the period 2017–2020 including the severe drought year of 2018 using DHIs based on the Normalized Difference Vegetation Index (NDVI) for drought assessment. To identify the most important variables affecting coniferous forest die-off, a series of environmental variables together with the three DHIs components were used in a logistic regression (LR) model. Each DHI component changed significantly across non-damaged and damaged sites in all years (p-value 0.05). When comparing 2017 to 2019, DHI-based annual productivity decreased and seasonality increased. Most importantly, none of the DHI components had reached pre-drought conditions, which likely indicates a change in ecosystem functioning. We also identified spatially explicit areas highly affected by drought. The LR model revealed that in addition to common environmental parameters related to temperature, precipitation, and elevation, DHI components were the most important factors explaining the health status. Our analysis demonstrates the potential of DHIs to capture the effect of drought events on Central European coniferous forest ecosystems. Since the spaceborne data are available at the global level, this approach can be applied to track the dynamics of ecosystem conditions in other regions, at larger spatial scales, and for other Land Use/Land Cover types.

Abstract Photo observations are a highly valuable but rarely used source of citizen science (CS) data. Recently, the number of publicly available photo observations has increased strongly, for example, due to the use of smartphone applications for species identification. This has enabled the raising of ecological insights in poorly studied subjects. One of the fields with the highest potential to benefit from the use of photo observations is phenology. We propose a workflow for iPhenology, the use of publicly available photo observations to track phenological events at large scales. The workflow comprises data acquisition, cleaning of observations, phenological classification and modelling spatiotemporal patterns of phenology. We explore the suitability of iPhenology to observe key phenological stages in the plant reproductive cycle of a model species and discuss limitations and future prospects of the approach using the example of an invasive species in Europe. We show that iPhenology is suitable to track key phenological events of widespread species. However, the number and quality of available observations may differ among species and phenological stages. Overall, publicly available CS photo observations are suitable to track key phenological events and can thus significantly advance the knowledge on the timing and drivers of plant phenology. In future, integrating the workflow with automated image processing and analysis may enable real‐time tracking of plant phenology.

AbstractThis study evaluates the sensitivity of the Dynamic Habitat Index (DHI), utilizing multitemporal Normalized Difference Vegetation Index (NDVI) data, to changing environmental conditions across Land Use/Land Cover (LULC) types in a central European landscape (2017–2020). We observed distinct DHI characteristics for all LULC types, and the DHI responded to an extreme drought year in 2018 with no return to pre-drought conditions except for deciduous forests. The DHI also effectively captured spatio-temporal variability of pedo-climatic conditions. Thus, integrated with ancillary geodata, the DHI enhances traditional categorical LULC maps, offering applications in biodiversity and ecosystem research. Such integrated products could serve as valuable tools for decision makers to formulate sustainable land management strategies and contribute to Sustainable Develop Goal indicators related to land degradation, e.g. by identifying deviations from typical, context-specific DHI profiles as a response to disturbance and environmental stress.

In Central Europe, species-rich grasslands have strongly diminished over the last century. The transfer of seed-containing plant material from donor sites with a desired species composition to restoration sites is a well-established method to restore species-rich grasslands. Despite a plethora of available literature, restoration projects with plant material transfer often fail or do not reach the planned goals. Practitioners’ knowledge is a highly important but underexplored source of information on factors deciding about success of restoration projects. At the same time, it is unclear to which degree scientific findings on success factors are known and considered by practitioners, and if science actually investigates the most relevant aspects for practice. To bridge the gap between practitioners’ knowledge and restoration science, we conducted semi-structured interviews with 33 practitioners involved in plant material transfer projects. Using qualitative content analysis, we analysed the interviews for success factors, and compared them to success factors of plant material transfer as investigated in peer-reviewed European studies on the method. We found that science investigated a broad range of practical, technical, and ecological success factors, and that practitioners were generally well aware of this evidence, trying to make use of the knowledge. Failure of practitioners’ projects often resulted from organizational obstacles, which were founded in lacking trust and low experience levels among the involved people. We advise unexperienced practitioners to involve more experienced practitioners in their projects if possible. Furthermore, we emphasize the importance of identifying relevant local stakeholders and building trustful regional networks. Interdisciplinary scientific studies considering success factors beyond practical and ecological aspects are required to support widespread effective grassland restoration with plant material transfer.

Restoration of floodplain meadows remains a challenge, as many degraded sites suffer from seed limitation. The transfer of seed-containing plant material from species-rich donor sites is a widely used method to restore semi-natural grasslands. However, most studies on the success of such restoration projects comprise limited time frames. As factors determining restoration success may only become evident after many years, long-term observations are crucial. We re-investigated 20 restored grassland sites in the floodplain of the Northern Upper Rhine 13–16 years after plant material transfer with different soil preparation treatments. To this end, we carried out vegetation surveys on 254 permanent plots and studied the potential influence of soil preparation, soil nutrients, and hydrology on plant species composition, diversity, and transfer of target species. Since sustainable agricultural use is important to ensure the long-term stability of restored semi-natural grasslands, we further investigated biomass productivity and feeding value. While most target species increased in frequency or remained stable over time, we found no positive long-term effect of soil preparation on vegetation development and target species establishment. Instead, increased biomass yield and flooding frequency led to reduced restoration success, while higher soil C/N ratios had a positive effect. Overall, restoration measures did not affect the agricultural value of the restored grasslands, which had higher dry matter biomass yields compared with the donor sites. Our results indicate that the positive effect of soil preparation on the number and cover of target species, which is regularly reported in short-term studies, diminishes over time, and other factors such as site conditions become increasingly important. Furthermore, additional plant material transfer or manual seeding may be necessary to support target species establishment. Concerning agricultural usability, the integration of restored floodplain meadows in farming systems is possible and can ensure long-term management and thus stability of these ecosystems. Our study shows that long-term monitoring of restoration projects is necessary, as factors determining restoration success may only become evident in the long-term.

Relationships between biodiversity and phosphorus cycling and the underlying processes are complex. Here the authors analyse a biodiversity manipulation experiment and an agricultural management gradient to show how plant and mycorrhizal fungal diversity promote phosphorus exploitation.

Land use intensification is a major driver of biodiversity change. Here the authors measure diversity across multiple trophic levels in agricultural grassland landscapes of varying management, finding decoupled responses of above- and belowground taxa to local factors and a strong impact of landscape-level land use.

Acidobacteria occur in a large variety of ecosystems worldwide and are particularly abundant and highly diverse in soils. In spite of their diversity, only few species have been characterized to date which makes Acidobacteria one of the most poorly understood phyla among the domain Bacteria. We used a culture-independent niche modeling approach to elucidate ecological adaptations and their evolution for 4,154 operational taxonomic units (OTUs) of Acidobacteria across 150 different, comprehensively characterized grassland soils in Germany. Using the relative abundances of their 16S rRNA gene transcripts, the responses of active OTUs along gradients of 41 environmental variables were modeled using hierarchical logistic regression (HOF), which allowed to determine values for optimum activity for each variable (niche optima). By linking 16S rRNA transcripts to the phylogeny of full 16S rRNA gene sequences, we could trace the evolution of the different ecological adaptations during the diversification of Acidobacteria. This approach revealed a pronounced ecological diversification even among acidobacterial sister clades. Although the evolution of habitat adaptation was mainly cladogenic, it was disrupted by recurrent events of convergent evolution that resulted in frequent habitat switching within individual clades. Our findings indicate that the high diversity of soil acidobacterial communities is largely sustained by differential habitat adaptation even at the level of closely related species. A comparison of niche optima of individual OTUs with the phenotypic properties of their cultivated representatives showed that our niche modeling approach (1) correctly predicts those physiological properties that have been determined for cultivated species of Acidobacteria but (2) also provides ample information on ecological adaptations that cannot be inferred from standard taxonomic descriptions of bacterial isolates. These novel information on specific adaptations of not-yet-cultivated Acidobacteria can therefore guide future cultivation trials and likely will increase their cultivation success.

Litter decomposition is a key process for carbon and nutrient cycling in terrestrial ecosystems and is mainly controlled by environmental conditions, substrate quantity and quality as well as microbial community abundance and composition. In particular, the effects of climate and atmospheric nitrogen (N) deposition on litter decomposition and its temporal dynamics are of significant importance, since their effects might change over the course of the decomposition process. Within the TeaComposition initiative, we incubated Green and Rooibos teas at 524 sites across nine biomes. We assessed how macroclimate and atmospheric inorganic N deposition under current and predicted scenarios (RCP 2.6, RCP 8.5) might affect litter mass loss measured after 3 and 12 months. Our study shows that the early to mid-term mass loss at the global scale was affected predominantly by litter quality (explaining 73% and 62% of the total variance after 3 and 12 months, respectively) followed by climate and N deposition. The effects of climate were not litter-specific and became increasingly significant as decomposition progressed, with MAP explaining 2% and MAT 4% of the variation after 12 months of incubation. The effect of N deposition was litter-specific, and significant only for 12-month decomposition of Rooibos tea at the global scale. However, in the temperate biome where atmospheric N deposition rates are relatively high, the 12-month mass loss of Green and Rooibos teas decreased significantly with increasing N deposition, explaining 9.5% and 1.1% of the variance, respectively. The expected changes in macroclimate and N deposition at the global scale by the end of this century are estimated to increase the 12-month mass loss of easily decomposable litter by 1.1–3.5% and of the more stable substrates by 3.8–10.6%, relative to current mass loss. In contrast, expected changes in atmospheric N deposition will decrease the mid-term mass loss of high-quality litter by 1.4–2.2% and that of low-quality litter by 0.9–1.5% in the temperate biome. Our results suggest that projected increases in N deposition may have the capacity to dampen the climate-driven increases in litter decomposition depending on the biome and decomposition stage of substrate.

Abstract Plant functional traits reflect individual and community ecological strategies. They allow the detection of directional changes in community dynamics and ecosystemic processes, being an additional tool to assess biodiversity than species richness. Analysis of functional patterns in plant communities provides mechanistic insight into biodiversity alterations due to anthropogenic activity. Although studies have consi‐dered of either anthropogenic management or nutrient availability on functional traits in temperate grasslands, studies combining effects of both drivers are scarce. Here, we assessed the impacts of management intensity (fertilization, mowing, grazing), nutrient stoichiometry (C, N, P, K), and vegetation composition on community‐weighted means (CWMs) and functional diversity (Rao's Q) from seven plant traits in 150 grasslands in three regions in Germany, using data of 6 years. Land use and nutrient stoichiometry accounted for larger proportions of model variance of CWM and Rao's Q than species richness and productivity. Grazing affected all analyzed trait groups; fertilization and mowing only impacted generative traits. Grazing was clearly associated with nutrient retention strategies, that is, investing in durable structures and production of fewer, less variable seed. Phenological variability was increased. Fertilization and mowing decreased seed number/mass variability, indicating competition‐related effects. Impacts of nutrient stoichiometry on trait syndromes varied. Nutrient limitation (large N:P, C:N ratios) promoted species with conservative strategies, that is, investment in durable plant structures rather than fast growth, fewer seed, and delayed flowering onset. In contrast to seed mass, leaf‐economics variability was reduced under P shortage. Species diversity was positively associated with the variability of generative traits. Synthesis. Here, land use, nutrient availability, species richness, and plant functional strategies have been shown to interact complexly, driving community composition, and vegetation responses to management intensity. We suggest that deeper understanding of underlying mechanisms shaping community assembly and biodiversity will require analyzing all these parameters.

Climate change, increasing environmental pollution, continuous loss of biodiversity, and a growing human population with increasing food demand, threaten the functioning of agro-ecosystems and their contribution to people and society. Agroforestry systems promise a number of benefits to enhance nature’s contributions to people. There are a wide range of agroforestry systems implemented representing different levels of establishment across the globe. This range and the long time periods for the establishment of these systems make empirical assessments of impacts on ecosystem functions difficult. In this study we investigate how simulation models can help to assess and predict the role of agroforestry in nature’s contributions. The review of existing models to simulate agroforestry systems reveals that most models predict mainly biomass production and yield. Regulating ecosystem services are mostly considered as a means for the assessment of yield only. Generic agroecosystem models with agroforestry extensions provide a broader scope, but the interaction between trees and crops is often addressed in a simplistic way. The application of existing models for agroforestry systems is particularly hindered by issues related to code structure, licences or availability. Therefore, we call for a community effort to connect existing agroforestry models with ecosystem effect models towards an open-source, multi-effect agroforestry modelling framework.

The intensification of food production systems has resulted in landscape simplification, with trees and hedges disappearing from agricultural land, principally in industrialized countries. However, more recently, the potential of agroforestry systems and small woody landscape features (SWFs), e.g., hedgerows, woodlots, and scattered groups of trees, to sequester carbon was highlighted as one of the strategies to combat global climate change. Our study was aimed to assess the extent of SWFs embedded within agricultural landscapes in Germany, estimate their carbon stocks, and investigate the potential for increasing agroforestry cover to offset agricultural greenhouse gas (GHG) emissions. We analyzed open-source geospatial datasets and identified over 900,000 hectares of SWFs on agricultural land, equivalent to 4.6% of the total farmland. The carbon storage of SWFs was estimated at 111 ± 52 SD teragrams of carbon (Tg C), which was previously unaccounted for in GHG inventories and could play a role in mitigating the emissions. Furthermore, we found cropland to have the lowest SWF density and thus the highest potential to benefit from the implementation of agroforestry, which could sequester between 0.2 and 2 Tg of carbon per year. Our study highlights that country-specific data are urgently needed to refine C stock estimates, improve GHG inventories and inform the large-scale implementation of agroforestry in Germany.

Long-term stability of ecological communities is vital for maintaining ecosystem functioning. Here, Blüthgen et al. show that greater land-use intensity in grasslands and forests can have negative impacts on the stability of plant and animal communities, driven primarily by variation in asynchrony between species.

Adequate biogeochemical characterization and monitoring of aquatic ecosystems, both for scientific purposes and for water management, pose high demands on spatial and temporal replication of chemical analyses. Near-infrared reflectance spectroscopy (NIRS) may offer a rapid, low-cost and reproducible alternative to standard analytical sample processing (digestion or extraction) and measuring techniques used for the chemical characterization of aquatic sediments. We analyzed a total of 191 sediment samples for total and NaCl-extractable concentrations of Al, Ca, Fe, K, Mg, Mn, N, Na, P, S, Si, and Zn as well as oxalate- extractable concentrations of Al, Fe, Mn and P. Based on the NIR spectral data and the reference values, calibration models for the prediction of element concentrations in unknown samples were developed and tested with an external validation procedure. Except Mn, all prediction models of total element concentrations were found to be acceptable to excellent (ratio of performance deviation: RPD 1.8-3.1). For extractable element fractions, viable model precision could be achieved for NaCl-extractable Ca, K, Mg, NH4 (+)-N, S and Si (RPD 1.7-2.2) and oxalate-extractable Al, Fe and P (RPD 1.9-2.3). For those elements that showed maximum total values below 3 g kg(-1) prediction models were found to become increasingly critical (RPD

Distinguishing organic and conventional products is a major issue of food security and authenticity. Previous studies successfully used stable isotopes to separate organic and conventional products, but up to now, this approach was not tested for organic grassland hay and soil. Moreover, isotopic abundances could be a powerful tool to elucidate differences in ecosystem functioning and driving mechanisms of element cycling in organic and conventional management systems. Here, we studied the δ(15)N and δ(13)C isotopic composition of soil and hay samples of 21 organic and 34 conventional grasslands in two German regions. We also used Δδ(15)N (δ(15)N plant - δ(15)N soil) to characterize nitrogen dynamics. In order to detect temporal trends, isotopic abundances in organic grasslands were related to the time since certification. Furthermore, discriminant analysis was used to test whether the respective management type can be deduced from observed isotopic abundances. Isotopic analyses revealed no significant differences in δ(13)C in hay and δ(15)N in both soil and hay between management types, but showed that δ(13)C abundances were significantly lower in soil of organic compared to conventional grasslands. Δδ(15)N values implied that management types did not substantially differ in nitrogen cycling. Only δ(13)C in soil and hay showed significant negative relationships with the time since certification. Thus, our result suggest that organic grasslands suffered less from drought stress compared to conventional grasslands most likely due to a benefit of higher plant species richness, as previously shown by manipulative biodiversity experiments. Finally, it was possible to correctly classify about two third of the samples according to their management using isotopic abundances in soil and hay. However, as more than half of the organic samples were incorrectly classified, we infer that more research is needed to improve this approach before it can be efficiently used in practice.

While bryophytes greatly contribute to plant diversity of semi-natural grasslands, little is known about the relationships between land-use intensity, productivity, and bryophyte diversity in these habitats. We recorded vascular plant and bryophyte vegetation in 85 agricultural used grasslands in two regions in northern and central Germany and gathered information on land-use intensity. To assess grassland productivity, we harvested aboveground vascular plant biomass and analyzed nutrient concentrations of N, P, K, Ca and Mg. Further we calculated mean Ellenberg indicator values of vascular plant vegetation. We tested for effects of land-use intensity and productivity on total bryophyte species richness and on the species richness of acrocarpous (small & erect) and pleurocarpous (creeping, including liverworts) growth forms separately. Bryophyte species were found in almost all studied grasslands, but species richness differed considerably between study regions in northern Germany (2.8 species per 16 m(2)) and central Germany (6.4 species per 16 m(2)) due environmental differences as well as land-use history. Increased fertilizer application, coinciding with high mowing frequency, reduced bryophyte species richness significantly. Accordingly, productivity estimates such as plant biomass and nitrogen concentration were strongly negatively related to bryophyte species richness, although productivity decreased only pleurocarpous species. Ellenberg indicator values for nutrients proved to be useful indicators of species richness and productivity. In conclusion, bryophyte composition was strongly dependent on productivity, with smaller bryophytes that were likely negatively affected by greater competition for light. Intensive land-use, however, can also indirectly decrease bryophyte species richness by promoting grassland productivity. Thus, increasing productivity is likely to cause a loss of bryophyte species and a decrease in species diversity.