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Representatives of the genus Stentor (Stentoridae, Heterotrichea) are striking ciliates in environmental water samples because of their size (up to 4 mm) and their trumpet-like shape. Important for species identification are the following main characteristics: (1) the presence or absence of endosymbiotic algae (zoochlorellae); (2) the colour of the pigmented cortical granules, and (3) the shape of the macronucleus. The complete small subunit rDNA (SSU rDNA) of 19 further representatives of the genus Stentor was sequenced to examine the phylogenetic relationships within this genus and to determine the taxonomic value of these main characteristics. The detailed phylogenetic analyses yielded a separation of all species possessing a single compact macronucleus from those species with an "elongated" macronucleus (moniliform or vermiform). The data also indicate that the uptake of algae as well as the loss of pigmentation happened independently in different lineages. Furthermore, a high level of intraspecific variation within several species was found. Thus, S. muelleri and S. (sp.) cf. katashimai appear to represent distinct species and S. multiformis is composed of a species complex.
The AlpArray seismic network
(2018)
The AlpArray programme is a multinational, European consortium to advance our understanding of orogenesis and its relationship to mantle dynamics, plate reorganizations, surface processes and seismic hazard in the Alps-Apennines-Carpathians-Dinarides orogenic system. The AlpArray Seismic Network has been deployed with contributions from 36 institutions from 11 countries to map physical properties of the lithosphere and asthenosphere in 3D and thus to obtain new, high-resolution geophysical images of structures from the surface down to the base of the mantle transition zone. With over 600 broadband stations operated for 2 years, this seismic experiment is one of the largest simultaneously operated seismological networks in the academic domain, employing hexagonal coverage with station spacing at less than 52 km. This dense and regularly spaced experiment is made possible by the coordinated coeval deployment of temporary stations from numerous national pools, including ocean-bottom seismometers, which were funded by different national agencies. They combine with permanent networks, which also required the cooperation of many different operators. Together these stations ultimately fill coverage gaps. Following a short overview of previous large-scale seismological experiments in the Alpine region, we here present the goals, construction, deployment, characteristics and data management of the AlpArray Seismic Network, which will provide data that is expected to be unprecedented in quality to image the complex Alpine mountains at depth.
Biodiversity-multifunctionality relationships depend on identity and number of measured functions
(2017)
Biodiversity ensures ecosystem functioning and provisioning of ecosystem services, but it remains unclear how biodiversity-ecosystem multifunctionality relationships depend on the identity and number of functions considered. Here, we demonstrate that ecosystem multifunctionality, based on 82 indicator variables of ecosystem functions in a grassland biodiversity experiment, increases strongly with increasing biodiversity. Analysing subsets of functions showed that the effects of biodiversity on multifunctionality were stronger when more functions were included and that the strength of the biodiversity effects depended on the identity of the functions included. Limits to multifunctionality arose from negative correlations among functions and functions that were not correlated with biodiversity. Our findings underline that the management of ecosystems for the protection of biodiversity cannot be replaced by managing for particular ecosystem functions or services and emphasize the need for specific management to protect biodiversity. More plant species from the experimental pool of 60 species contributed to functioning when more functions were considered. An individual contribution to multifunctionality could be demonstrated for only a fraction of the species.
Very few principles have been unraveled that explain the relationship between soil properties and soil biota across large spatial scales and different land-use types. Here, we seek these general relationships using data from 52 differently managed grassland and forest soils in three study regions spanning a latitudinal gradient in Germany. We hypothesize that, after extraction of variation that is explained by location and land-use type, soil properties still explain significant proportions of variation in the abundance and diversity of soil biota. If the relationships between predictors and soil organisms were analyzed individually for each predictor group, soil properties explained the highest amount of variation in soil biota abundance and diversity, followed by land-use type and sampling location. After extraction of variation that originated from location or land-use, abiotic soil properties explained significant amounts of variation in fungal, meso-and macrofauna, but not in yeast or bacterial biomass or diversity. Nitrate or nitrogen concentration and fungal biomass were positively related, but nitrate concentration was negatively related to the abundances of Collembola and mites and to the myriapod species richness across a range of forest and grassland soils. The species richness of earthworms was positively correlated with clay content of soils independent of sample location and land-use type. Our study indicates that after accounting for heterogeneity resulting from large scale differences among sampling locations and land-use types, soil properties still explain significant proportions of variation in fungal and soil fauna abundance or diversity. However, soil biota was also related to processes that act at larger spatial scales and bacteria or soil yeasts only showed weak relationships to soil properties. We therefore argue that more general relationships between soil properties and soil biota can only be derived from future studies that consider larger spatial scales and different land-use types.
The St. Nicolas House Algorithm (SNHA) finds association chains of direct dependent variables in a data set. The dependency is based on the correlation coefficient, which is visualized as an undirected graph. The network prediction is improved by a bootstrap routine. It enables the computation of the empirical p-value, which is used to evaluate the significance of the predicted edges. Synthetic data generated with the Monte Carlo method were used to firstly compare the Python package with the original R package, and secondly to evaluate the predicted network using the sensitivity, specificity, balanced classification rate and the Matthew's correlation coefficient (MCC). The Python implementation yields the same results as the R package. Hence, the algorithm was correctly ported into Python. The SNHA scores high specificity values for all tested graphs. For graphs with high edge densities, the other evaluation metrics decrease due to lower sensitivity, which could be partially improved by using bootstrap,while for graphs with low edge densities the algorithm achieves high evaluation scores. The empirical p-values indicated that the predicted edges indeed are significant.
In order to predict which ecosystem functions are most at risk from biodiversity loss, meta-analyses have generalised results from biodiversity experiments over different sites and ecosystem types. In contrast, comparing the strength of biodiversity effects across a large number of ecosystem processes measured in a single experiment permits more direct comparisons. Here, we present an analysis of 418 separate measures of 38 ecosystem processes. Overall, 45 % of processes were significantly affected by plant species richness, suggesting that, while diversity affects a large number of processes not all respond to biodiversity. We therefore compared the strength of plant diversity effects between different categories of ecosystem processes, grouping processes according to the year of measurement, their biogeochemical cycle, trophic level and compartment (above- or belowground) and according to whether they were measures of biodiversity or other ecosystem processes, biotic or abiotic and static or dynamic. Overall, and for several individual processes, we found that biodiversity effects became stronger over time. Measures of the carbon cycle were also affected more strongly by plant species richness than were the measures associated with the nitrogen cycle. Further, we found greater plant species richness effects on measures of biodiversity than on other processes. The differential effects of plant diversity on the various types of ecosystem processes indicate that future research and political effort should shift from a general debate about whether biodiversity loss impairs ecosystem functions to focussing on the specific functions of interest and ways to preserve them individually or in combination.