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In order to understand the variation of Estonian calcareous thin-soil grasslands on Ordovician or Silurian limestone (alvars), 58 stands,distributed over the whole alvar region of Estonia, were described and clustered numerically using TABORD. Alvars are characterized by a high species richness. These mainly semi-natural communities have mostly developed after clear-cutting of forests. Grazing by domestic animals and removal of woody plants is needed for their maintenance. Primary (natural) alvar grasslands are found in a few places in coastal regions or in areas with thin-soil on monolithic bedrock. In data processing a whole stand, described by several small releves, was used in the classification as one description, including species frequencies as a quantitative measure. Seven clusters were separated and their configuration checked in a PCA-ordination. The resulting classification agreed with the previous `rough' classification. Both geographicaland ecological factors were related with the clustering and the ordination. The broad classification units, suggested for Estonian alvar grasslands, were quite similar to the ones described earlier for alvar vegetation on Oland, Sweden. Clusters differed in their species richness, environmental conditions and life-form spectra. Differences inspecies richness were defined by regional species pools. Compared toearlier surveys, only a small fraction of alvars still remains in Estonia. Active conservation, i.e. suitable management is needed to protect the still surviving valuable plant communities. The present study can provide guidelines on how to protect and manage different typesof alvars in Estonia. [ABSTRACT FROM AUTHOR]

Currently, model-informed precision dosing uses one population pharmacokinetic model that best fits the target population. We aimed to develop a subgroup identification-based model selection approach to improve the predictive performance of individualized dosing, using vancomycin in neonates/infants as a test case. Data from neonates/infants with at least one vancomycin concentration was randomly divided into training and test dataset. Population predictions from published vancomycin population pharmacokinetic models were calculated. The single best-performing model based on various performance metrics, including median absolute percentage error (APE) and percentage of predictions within 20% (P20) or 60% (P60) of measurement, were determined. Clustering based on median APEs or clinical and demographic characteristics and model selection by genetic algorithm was used to group neonates/infants according to their best-performing model. Subsequently, classification trees to predict the best-performing model using clinical and demographic characteristics were developed. A total of 208 vancomycin treatment episodes in training and 88 in test dataset was included. Of 30 identified models from the literature, the single best-performing model for training dataset had P20 26.2-42.6% in test dataset. The best-performing clustering approach based on median APEs or clinical and demographic characteristics and model selection by genetic algorithm had P20 44.1-45.5% in test dataset, whereas P60 was comparable. Our proof-of-concept study shows that the prediction of the best-performing model for each patient according to the proposed model selection approaches has the potential to improve the predictive performance of model-informed precision dosing compared with the single best-performing model approach., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

We recruited 48 neonates (50 vancomycin treatment episodes) in a prospective study to validate a model-informed precision dosing (MIPD) software. The initial vancomycin dose was based on a population pharmacokinetic model and adjusted every 36-48 h. Compared with a historical control group of 53 neonates (65 episodes), the achievement of a target trough concentration of 10-15 mg/L improved from 37% in the study to 62% in the MIPD group ( P = 0.01), with no difference in side effects., Competing Interests: The authors declare no conflict of interest.

Island biogeography theory is one of the most influential paradigms in ecology. That island characteristics, including remoteness, can profoundly modulate biological diversity has been borne out by studies of animals and plants. By contrast, the processes influencing microbial diversity in island systems remain largely undetermined. We sequenced arbuscular mycorrhizal (AM) fungal DNA from plant roots collected on 13 islands worldwide and compared AM fungal diversity on islands with existing data from mainland sites. AM fungal communities on islands (even those >6000 km from the closest mainland) comprised few endemic taxa and were as diverse as mainland communities. Thus, in contrast to patterns recorded among macro-organisms, efficient dispersal appears to outweigh the effects of taxogenesis and extinction in regulating AM fungal diversity on islands. Nonetheless, AM fungal communities on more distant islands comprised a higher proportion of previously cultured and large-spored taxa, indicating that dispersal may be human-mediated or require tolerance of significant environmental stress, such as exposure to sunlight or high salinity. The processes driving large-scale patterns of microbial diversity are a key consideration for attempts to conserve and restore functioning ecosystems in this era of rapid global change.

Background: Our main aim has been to design a framework to improve vancomycin dosing in neonates. This required the development and verification of a computerized dose adjustment application, DosOpt, to guide the selection., Methods: Model fitting in DosOpt uses Bayesian methods for deriving individual pharmacokinetic (PK) estimates from population priors and patient therapeutic drug monitoring measurements. These are used to simulate concentration-time curves and target-constrained dose optimization. DosOpt was verified by assessing bias and precision through several error metrics and normalized prediction distribution errors on samples simulated from the Anderson et al PK model. The performance of DosOpt was also evaluated using retrospective clinical data. Achieved probabilities of target concentration attainment were benchmarked against corresponding attainments in our clinical retrospective data set., Results: Simulations showed no systemic forecast biases. Normalized prediction distribution error values of the base model were distributed by standardized Gaussian (P = 0.1), showing good model suitability. A retrospective test data set included 149 treatment episodes with 1-10 vancomycin concentration measurements per patient (median 2). Individual concentrations in PK estimation improved probability of target attainment and decreased the variance of the estimation. Including 3 individual concentrations in the kinetics estimation increased the probability of Ctrough attainment within 10-15 mg/L from 16% obtained with no individual data (95% confidence interval, 11%-24%) to 43% (21%-47%)., Conclusions: DosOpt uses individual concentration data to estimate kinetics and find optimal doses that increase the probability of achieving desired trough concentrations. Its performance started to exceed target levels attained in retrospective clinical data sets with the inclusion of a single individual input concentration. This tool is freely available at http://www.biit.cs.ut.ee/DosOpt.

Increased importance of genetic drift and selection for stress resistance have been predicted to lead to a reduction in the degree of phenotypic plasticity in populations at margins of a species' geographical range, relative to those in the centre. We examined the effect of population positioning within the species range on degree of active morphological plasticity to vegetation shade. Importantly, we discriminated between active, size-independent morphological adjustments in response to shade and passive changes in morphology caused by the dependence of morphological traits on plant size, as only the former are considered to be adaptive. Two closely related and ecologically similar Agrimonia species were examined in the same geographical location, where one species reaches the edge of its distribution (Agrimonia pilosa) and the other does not (A. eupatoria). Plasticity to light availability is likely to be advantageous for both species as they occupy habitats with variable light conditions. However, we hypothesised that high levels of environmental stress should lead to reduced active plasticity in marginal compared with more central populations. Agrimonia eupatoria exhibited active adjustments in leaf morphology in response to tree shade, and in elongation of stems and inflorescences in response to herbaceous shade. In contrast, A. pilosa exhibited very limited active plasticity. High active plasticity allowed A. eupatoria to retain constant shoot growth in a wide range of light conditions, while the lack of active plasticity in A. pilosa resulted in a strong dependence of shoot growth on light availability. We propose that high levels of environmental stress in marginal areas of a species' range may lead to a significant reduction in the degree of active plasticity. Our results clearly indicate that discrimination between active and passive plasticity is crucial for reaching valid conclusions about differences in adaptive plasticity between marginal and non-marginal populations., (© 2010 German Botanical Society and The Royal Botanical Society of the Netherlands.)

The Global Strategy of Plant Conservation states that at least 60% of threatened plant species should be within protected areas. This goal has been met in some regions with long traditions of plant protection. We used gap analysis to explore how particular groups of species of conservation interest, representing different types of natural or anthropogenic rarity, have been covered by protected areas on a national scale in Estonia during the last 100 years. Species-accumulation curves indicated that plant species that are naturally rare (restricted global or local distribution, always small populations, or very rare habitat requirements) needed almost twice as many protected areas to reach the 60% target as plant species that are rare owing to lack of suitable management (species depending on grassland management, moderate forest disturbances, extensive traditional agriculture, or species potentially threatened by collecting). Temporal analysis of the establishment of protected areas suggested that grouping plant species according to the predominant cause of rarity accurately reflected the history of conservation decision making. Species found in very rare habitats have previously received special conservation attention; species dependent on traditional extensive agriculture have been largely ignored until recently. Legislative initiative and new nature-protection schemes (e.g., Natura 2000, network of protected areas in the European Union) have had a positive influence on all species groups. Consequently, the species groups needing similar action for their conservation are sensitive indicators of the effectiveness of protected-area networks. Different species groups, however, may not be uniformly conserved within protected areas, and all species groups should fulfill the target of 60% coverage within protected areas., (©2008 Society for Conservation Biology.)