Attila Lengyel

Can management intensity be more important than environmental factors? A case study along an extreme elevation gradient from central Italian cereal fields

This paper aims to assess the importance of environmental and management factors determining the weed species composition along a strong elevation gradient. A total of 76 cereal fields (39 low input and 37 intensively managed) were sampled along an elevation gradient in central Italy. Explanatory variables were recorded for each field to elucidate the role of large-scale spatial trends, of site-specific abiotic environmental conditions and of field management characters. Redundancy analysis was used to assess the relative importance of each environmental variable in explaining the variation in species composition. Our results indicate that variation in weed species composition is strongly determined by altitude, mean annual precipitation, mean annual temperature and also by soil characteristics. However, the level of intensification proved to be the most influential variable. There was a significant difference in species richness and composition between low-input and intensively managed fields. Intensification leads to considerable species loss at both lower and higher elevations. Low-input fields had 296 species in total, while intensively managed fields had only 196.

Classification of mesic grasslands and their transitions of South Transdanubia (Hungary)

Classification of mesic grasslands and their transitions of South Transdanubia (Hungary) Relevés from meadows and pastures of South Transdanubia (Hungary) are evaluated by clustering and ordination methods. The relevé selection focused on the Arrhenatheretalia order but its transitions towards other types were also included. The groups of relevés are delimited and described according to differential, dominant and constant species. Ecological conditions of the groups were compared using indicator values. Nine groups were distinguished, four of them belonging strictly to the order Arrhenatheretalia. Each alliance of Arrhenatheretalia presented in the study area (Cynosurion, Arrhenatherion) was represented by two groups. Groups from these two alliances are separated along a light gradient, while groups of the same alliance differ in nutrient values. Within Cynosurion, the nutrient-poor group cannot be identified unambiguously as any syntaxa previously known from Hungary. The nutrient-rich Cynosurion meadows are similar to Lolio-Cynosuretum, however, they show a stronger relationship with wet meadows. Within Arrhenatherion, Pastinaco-Arrhenatheretum is recognised as a hay meadow of nutrient-rich soils. The other meadow type is similar to Filipendulo-Arrhenatheretum, thus raising syntaxonomical problems. There are transitional groups towards semi-dry andwet meadows, one dynamic phase and one outlier group among the other five clusters.

On the lack of capillary Mössbauer spectroscopic effect for SnII-containing aqueous solutions trapped in corning Vycor ‘thirsty’ glass

Liquids trapped in the pores of certain silicate glasses (such as Corning Vycor ‘thirsty’ glass) were found to display frozen solutions like behavior at temperatures much higher than their actual freezing point. For example, recoilless γ-resonance absorption was observed for Mössbauer active solutes such as 119Sn and 57Fe salts at room temperature (i.e., without the need of quenching). Thus capillary Mössbauer spectroscopy (CMS) proved to be a new and useful experimental tool with great potential in solution chemistry. As part of a research project concerned with the hydrolysis of SnII salts, we attempted to perform 119Sn CMS measurements for solutions containing stannous ion in a range of aqueous environments. Somewhat surprisingly, we found that under ambient conditions, SnII aqueous liquid solutions, both the acidic and the basic systems, are essentially CMS-silent. This can be attributed to the strong temperature dependence of Lamb–Mössbauer factor of SnII species, which may result in the complete disappearance of Mössbauer pattern well below room temperature. These observations can also explain why previous publications concerned with the use of CMS dealt exclusively with SnIV and not with SnII containing liquids.

Visible-light activated photocatalytic effect of glass and glass ceramic prepared by recycling waste slag with hematite

Abstract A relationship between the local structure and the visible-light activated photocatalytic effect was investigated in the glass and glass ceramics prepared by recycling waste slag, which was discharged from a Tokyo Household Garbage Combustion Plant. For the preparation of a homogeneous sample of waste slag recycled glass, (WSRG), 10 wt% of Na2CO3 and 10–50 wt% of Fe2O3 were added. 57Fe-Mössbauer spectra of WSRG recorded at liquid nitrogen temperature showed three types of magnetic hfs; one due to FeII(Oh) with δ of 1.21 mm s−1 and Hint of 46.7 T, one due to FeIII(Oh) with δ of 0.46 mm s−1 and Hint of 44.1 T, and the other due to FeIII(Td) with δ of 0.38 mm s−1 and Hint of 47.8 T. They were superimposed on a relaxation spectrum due to superparamagnetic hematite. Methylene blue (MB) degradation test with 40 mg of the heat treated WSRG (50 wt% Fe2O3), under the visible-light irradiation for 6 h showed a marked decrease in the concentration of MB from 20 to 7.7 μmol L−1 with a rate constant (k) of 2.7×10−3 min−1 which was close to the k, 9.26×10−3 min− 1, recently obtained in 15Na2O⋅15CaO⋅40Fe2O3⋅ 11Al2O3⋅19SiO2 glass.

Synergistic effects of the components of global change: Increased vegetation dynamics in open, forest-steppe grasslands driven by wildfires and year-to-year precipitation differences

Climate change and land use change are two major elements of human-induced global environmental change. In temperate grasslands and woodlands, increasing frequency of extreme weather events like droughts and increasing severity of wildfires has altered the structure and dynamics of vegetation. In this paper, we studied the impact of wildfires and the year-to-year differences in precipitation on species composition changes in semi-arid grasslands of a forest-steppe complex ecosystem which has been partially disturbed by wildfires. Particularly, we investigated both how long-term compositional dissimilarity changes and species richness are affected by year-to-year precipitation differences on burnt and unburnt areas. Study sites were located in central Hungary, in protected areas characterized by partially-burnt, juniper-poplar forest-steppe complexes of high biodiversity. Data were used from two long-term monitoring sites in the Kiskunság National Park, both characterized by the same habitat complex. We investigated the variation in species composition as a function of time using distance decay methodology. In each sampling area, compositional dissimilarity increased with the time elapsed between the sampling events, and species richness differences increased with increasing precipitation differences between consecutive years. We found that both the long-term compositional dissimilarity, and the year-to-year changes in species richness were higher in the burnt areas than in the unburnt ones. The long-term compositional dissimilarities were mostly caused by perennial species, while the year-to-year changes of species richness were driven by annual and biennial species. As the effect of the year-to-year variation in precipitation was more pronounced in the burnt areas, we conclude that canopy removal by wildfires and extreme inter-annual variability of precipitation, two components of global environmental change, act in a synergistic way. They enhance the effect of one another, resulting in greater long-term and year-to-year changes in the composition of grasslands.

Silhouette width using generalized mean - a flexible method for assessing clustering efficiency

Cluster analysis plays vital role in pattern recognition in several fields of science. Silhouette width is a widely used measure for assessing the fit of individual objects in the classification, as well as the quality of clusters and the entire classification. This index uses two clustering criteria, compactness (average within-cluster distances) and separation (average between-cluster distances), which implies that spherical cluster shapes are preferred over others – a property that can be seen as a disadvantage in the presence 22 of clusters with high internal heterogeneity, which is common in real situations. We suggest a generalization of the silhouette width using the generalized mean. By changing the p parameter of the generalized mean between −∞ and +∞, several specific summary statistics, including the minimum, maximum, the arithmetic, harmonic, and geometric means, can be reproduced. Implementing the generalized mean in the calculation of silhouette width allows for changing the sensitivity of the index to compactness vs. connectedness. With higher sensitivity to connectedness instead of compactness the preference of silhouette width towards spherical clusters is expected to reduce. We test the performance of the generalized silhouette width on artificial data sets and on the Iris data set. We examine how classifications with different numbers of clusters prepared by single linkage, group average, and complete linkage algorithms are evaluated, if p is set to different values. When p was negative, well separated clusters achieved high silhouette widths despite their elongated or circular shapes. Positive values of p increased the importance of compactness, hence the preference towards spherical clusters became even more detectable. With low p, single linkage clustering was deemed the most efficient clustering method, while with higher parameter values the performance of group average and complete linkage seemed better. The generalized silhouette width is a promising tool for assessing clustering quality. It allows for adjusting the contribution of compactness and connectedness criteria to the index value, thus avoiding underestimation of clustering efficiency in the presence of clusters with high internal heterogeneity.

Joint optimization of cluster number and abundance transformation for obtaining effective vegetation classifications

Question: Is it possible to determine which combination of cluster number and taxon abundance transformation would produce the most effective classification of vegetation data? What is the effect of changing cluster number and taxon abundance weighting (applied simultaneously) on the stability and biological interpretation of vegetation classifications? Locality: Europe, Western Australia, simulated data. Methods: Real data sets representing Hungarian sub-montane grasslands, European wetlands, and Western Australian kwongan vegetation, as well as simulated data sets were used. The data sets were classified using the partitioning around medoids method. We generated classification solutions by gradually changing the transformation exponent applied to the species projected covers and the number of clusters. The effectiveness of each classification was assessed with a stability index. This index is based on bootstrap resampling of the original data set with subsequent elimination of duplicates. The vegetation types delimited by the most stable classification were compared with other classifications obtained at local maxima of the stability values. The effect of changing the transformation power exponent on the number of clusters, indexed according to their stability, was evaluated. Results: The optimal number of clusters varied with the power exponent in all cases, both with real and simulated data sets. With the real data sets, optimal cluster numbers obtained with different data transformations recovered interpretable biological patterns. Using the simulated data, the optima of stability values identified the simulated number of clusters correctly in most cases. Conclusions: With changing the settings of data transformation and the number of clusters, classifications of different stability can be produced. Highly stable classifications can be obtained from different settings for cluster number and data transformation. Despite similarly high stability, such classifications may reveal contrasting biological patterns, thus suggesting different interpretations. We suggest testing a wide range of available combinations to find the parameters resulting in the most effective classifications.

The effect of carboxylic acids on the oxidation of coated iron oxide nanoparticles

Abstract57Fe Mössbauer spectroscopy, XRD, and TEM were used to investigate the effect of mandelic- and salicylic acid coatings on the iron oxide nanoparticles. These two carboxylic acids have similar molecules size and stoichiometry, but different structure and acidity. Significant differences were observed between the Mössbauer spectra of samples coated with mandelic acid and salicylic acid. These results indicate that the occurrence of iron microenvironments in the mandelic- and salicylic acid-coated iron oxide nanoparticles is different. The results can be interpreted in terms of the influence of the acidity of carboxylic acids on the formation, core/shell structure, and oxidation of coated iron oxide nanocomposites.