New thousand-seed weight dataset for plant species of Central Europe.

One of the most important and most easily measurable physical characteristics of plant seeds is their weight, which influences and indicates crucial ecological processes. Seed weight affects spatial and temporal dispersibility, and can also influence seed predation and the germination, growth and survival of seedlings. Providing trait data for species missing from international databases is key to promote studies that advance our understanding of the functioning of plant communities and ecosystems, which is an essential issue in the face of the global climate change and biodiversity loss. Compared to species from Western and Northwestern Europe, those with an Eastern or Central European centre of distribution are underrepresented in most international trait databases. Therefore, the creation of specific trait databases is key to help regional studies. In this respect, it is important not only to collect fresh seeds for weight measurements, but also to measure and process data of seeds preserved in collections and make them available to the broader scientific community. In this data paper we provide seed weight data to fill in missing trait data of plant species of Central and Eastern Europe. Our dataset includes weight measurement for 281 taxa of the Central European flora including also some cultivated and exotic species. The seeds were collected between 1971 and 2021 mostly in Central Europe. One part of the measured seeds was collected in the last decade, the other part is from an older seed collection, but all seeds were measured recently. For each species, we collected a minimum of 3 × 100 intact seeds, if possible. The seeds were air-dried at room temperature (approximately 21 °C and 50% relative humidity) for at least two weeks and measured with an accuracy of 0.001 g using an analytical balance. The thousand-seed weights reported here were calculated based on the measured values. Our goal for the future is to incorporate the seed weight data reported here in a regional database (Pannonian Database of Plant Traits - PADAPT) that gathers plant traits and other plant characteristics for the Pannonian flora. The data presented here will facilitate trait-based analyses of the flora and vegetation of Central Europe.

PADAPT 1.0 - the Pannonian Dataset of Plant Traits.

The existing plant trait databases' applicability is limited for studies dealing with the flora and vegetation of the eastern and central part of Europe and for large-scale comparisons across regions, mostly because their geographical data coverage is limited and they incorporate records from several different sources, often from regions with markedly different climatic conditions. These problems motivated the compilation of a regional dataset for the flora of the Pannonian region (Eastern Central Europe). PADAPT, the Pannonian Dataset of Plant Traits relies on regional data sources and collates data on 54 traits and attributes of the plant species of the Pannonian region. The current version covers approximately 90% of the species of the region and consists of 126,337 records on 2745 taxa. By including species of the eastern part of Europe not covered by other databases, PADAPT can facilitate studying the flora and vegetation of the eastern part of the continent. Although data coverage is far from complete, PADAPT meets the longstanding need for a regional database of the Pannonian flora.

New data of plant leaf traits from Central Europe.

Trait-based ecology is gaining ground nowadays on species-based ecology: the number of research and publication focusing on the ecological role of taxa instead of the species themselves increased significantly in the last two decades. One great advantage of this approach is that communities with different species composition due to great geographical distances (e.g., different continents) or different environmental conditions (e.g., loess, sand, and alkaline grasslands) become comparable. Obtaining trait values is, however, labour and time consuming even in the case of so-called soft traits. It is therefore reasonable and desirable for scientists to share their data as widely as possible. Demand for such data induced the publication of data papers and the establishment of databases, which support both theoretical ecological research and practical restoration ecological projects. Although several international databases (e.g., TRY, LEDA, CLO-PLA, BiolFLOR) are available nowadays, Central and Eastern European species are either missing or underrepresented in them. Consequently, measurement and publication of the traits of species typical in the above region is necessary. This paper presents leaf trait (leaf fresh and dry weight, leaf area, specific leaf area and leaf dry matter content) data for more than 1100 species of the Central European flora.

Vegetation type and grazing intensity jointly shape grazing effects on grassland biodiversity.

In the Palaearctic steppe zone, overgrazing was identified as one of the key drivers of declining grassland biodiversity, which underlines the necessity of the functional evaluation of increased grazing pressure on grassland vegetation. We tested the following hypotheses: (a) The effect of grazing intensity on species and functional diversity is strongly dependent on grassland type. (b) The magnitude of diet selectivity of grazers decreases with increasing grazing intensity. (c) Increasing grazing intensity increases evenness and functional evenness of the subjected grasslands. We analyzed vegetation patterns in four types of grasslands (Dry alkali short-grass steppes, Dry loess steppes, Non-alkali wet and Alkali wet grasslands) along an intensity gradient of beef cattle grazing at 73 sites in Hungary. Species richness, Shannon diversity, evenness, and four leaf traits were analyzed. We calculated community-weighted means for each single trait, and multi-trait functional richness, functional evenness, and divergence for all leaf traits. All species and functional diversity metrics were significantly affected by the grassland type, except leaf dry matter content. The effect of interaction between grazing intensity and grassland type was also significant for functional richness, functional evenness, community-weighted means of leaf area, and for species richness and evenness. An upward trend of specific leaf area was detected in all grasslands with the highest scores for the overgrazed sites, but the change was also grassland type dependent. The detected trend suggests that with increased intensity the overall selectivity of grazing decreased. We found that evenness was affected but functional evenness was not affected by grazing intensity. Functional evenness scores were more related to the grassland type than to changes in grazing intensity, and displayed a high variability. We stress that one-size-fits-all strategies cannot be recommended and actions should be fine-tuned at least at the level of grassland type.

Analysis of sub µg/kg lincomycin in honey, muscle, milk, and eggs using fast liquid chromatography-tandem mass spectrometry.

A fast liquid chromatography-tandem mass spectrometry (LC-MS-MS) method is developed to determine lincomycin (LM) in honey, muscle, milk, and egg. Samples are cleaned-up at pH 4.7 using Strata-X-C mixed-mode polymeric strong cation exchange solid-phase extraction (SPE) cartridges, which could selectively adsorb the lincomycin from matrices under the acidic condition. LM is separated on the recently introduced Kinetex XB core-shell type HPLC column using isocratic elution mode with a mobile phase containing 0.1% formic acid in water/acetonitrile (93/7, v/v, pH 2.6) at a flow rate of 0.7 mL/min. The subsequent MS/MS detection has decreased ion effect, which allows the limit of detection (LOD) of LM for honey to be 0.05 µg/kg for honey and 0.5 µg/kg for muscle, milk, and egg. These LODs are much lower than those reported previously. The other main advantage of the developed method is the analysis time of only 3.5 min, which is about three times shorter than other reported LC-MS-MS methods. Recoveries varies between 94.2% and 125.2% and in-house reproducibility ranges from 3.7% to 28.7%. The developed method is validated according to European Union (EU) Commission Decision 2002/657/EC using a matrix-comprehensive validation strategy. All studied analytical parameters fulfills the EU guidelines.