Species and ecomorphological differentiation of genus Arvicola (Mammalia) in Eastern Europe

The genus Arvicola is represented in the fauna of Eastern Europe by several taxa and ecological races of semi-species and subspecies rank. Morphological data indicate the taxonomic homogeneity of lowland amphibious forms and a high level of differentiation of some mountain fossorial forms. Analysis of variation of morphometric characters shows a substantial hiatus for the Carpathian form of Arvicola, considered as A. scherman, as well as the absence of sufficient differentiation among other forms such as in lowland water voles from different parts of Ukraine or in mountain forms from the Northern Caucasus. Morphological features of the Carpathian taxon (A. scherman gutsulius) are stable compared to other mountain water vole populations from Europe and its substantial differences from the Caucasian form, which is very close to the lowland A. amphibius, do not support the idea of the ‘effect of mountains’ in the formation of small fossorial forms of Arvicola. The Carpathian Arvicola differs from all of the studied lowland forms in both morphometric and craniometric characters, which are important in the taxonomy and diagnostics of water voles (coefficient of divergence in body and skull dimensions reach CD = 4...5 ϭ. The mountain water vole (A. scherman) is characterized by a number of paedomorphic features that should be recognized as an ancestral state (plesiomorpy), whereas the European water vole (A. amphibius) is considered as an evolutionary advanced and gerontomorphic form. These two species are allopatric and the border between their distribution ranges coincide with the geographic limits of lowland and mountain faunal assemblages. Evidence for the recognition of the mountain fossorial form as either a separate species or an ecological race of the lowland species is considered. The fossorial A. scherman can be included to the group chosaricus–mosbachensis, but it remains unclear whether it should be considered an ancestral form in the evolution of the lowland A. amphibius or as an example of recapitulation of characters due to secondary transition to fossorial lifestyle. A comparison of different geographic forms of Arvicola suggests that the formation of the group took place in piedmont–mountainous areas of Europe, whereas the forms distributed further east are probably derived from the European ones.

Spatiotemporal variability patterns of PM2.5 in severe pollution events based on a large dataset from air quality monitoring stations over South Korea

<p>East Asia has suffered from severe air pollution, particularly concerning particulate matter less than 2.5 µm in diameter (PM<sub>2.5</sub>). Although air quality in Korea has been gradually improved with respect to annual mean PM<sub>2.5</sub> and PM<sub>10</sub> concentrations, high PM pollution events have been worse in their peak concentrations and durations.</p><p>In this study, we attempted to find statistically how the characteristics of PM<sub>2.5</sub> pollution over Korea have changed with a focus on temporal and spatial variations. Hourly PM<sub>2.5</sub> concentration data were obtained from 374 air quality monitoring stations (AQMS) throughout the country from January 2015 to June 2019. With obtained air quality data, we selected high PM pollution periods based on the national air pollution standard, and examined how the magnitudes and durations of high PM pollution events, as well as the background concentrations, have changed since 2015 over Korea. Additionally, we applied the time-lag correlation method to see how the onsets of PM<sub>2.5</sub> pollution events differ in space and how high PM<sub>2.5</sub> spread out in time. We also applied the coefficient of divergence (COD) to countrywide datasets of PM<sub>2.5</sub> as a measure of spatial heterogeneity of PM<sub>2.5</sub> distributions.</p><p>Although annual mean concentrations of PM<sub>2.5</sub> tend to decline from 2015 to 2018, the peak concentrations and durations for severe PM<sub>2.5</sub> pollution events tend to increase in most regions of Korea for the periods of January to April. We also categorized the characteristic distribution patterns in severe PM events combining the time-lag correlation and COD results. In most pollution events, the time-lag distributions showed clear delay patterns of pollution events from the reference area (Seoul). Additionally, COD results showed a clear heterogeneity of PM<sub>2.5</sub> distributions as the distance from the reference area increases along the time-lag. Although spatial correlations and COD results of PM<sub>2.5</sub> concentrations between the reference area and other regions indicated heterogeneous distributions, time-lag corrected COD values imply that PM<sub>2.5</sub> over much wider regions of Korea are homogeneously distributed in both magnitudes and temporal variations. The R<sup>2</sup> values were significantly improved after time-lag correction. These results imply that high PM<sub>2.5</sub> events are significantly affected by synoptic weather conditions over most regions of Korea; thus, potential modification of synoptic weather patterns in East Asia caused by climate change can be an important factor for variations in high PM<sub>2.5</sub> pollution events.</p><p>Keywords: coefficient of divergence (COD), PM<sub>2.5</sub> pollution events, spatial heterogeneity of PM distributions, pattern analysis.</p>

Measuring Spatial and Temporal PM2.5 Variations in Sacramento, California, Communities Using a Network of Low-Cost Sensors

Low-cost sensors can provide insight on the spatio-temporal variability of air pollution, provided that sufficient efforts are made to ensure data quality. Here, 19 AirBeam particulate matter (PM) sensors were deployed from December 2016 to January 2017 to determine the spatial variability of PM2.5 in Sacramento, California. Prior to, and after, the study, the 19 sensors were deployed and collocated at a regulatory air monitoring site. The sensors demonstrated a high degree of precision during all collocated measurement periods (Pearson R2 = 0.98 − 0.99 across all sensors), with little drift. A sensor-specific correction factor was developed such that each sensor reported a comparable value. Sensors had a moderate degree of correlation with regulatory monitors during the study (R2 = 0.60 − 0.68 at two sites). In a multi-linear regression model, the deviation between sensor and reference measurements of PM2.5 had the highest correlation with dew point and relative humidity. Sensor measurements were used to estimate the PM2.5 spatial variability, finding an average pairwise coefficient of divergence of 0.22 and a range of 0.14 to 0.33, indicating mostly homogeneous distributions. No significant difference in the average sensor PM concentrations between environmental justice (EJ) and non-EJ communities (p value = 0.24) was observed.

Demonstration of a Low-Cost Multi-Pollutant Network to Quantify Intra-Urban Spatial Variations in Air Pollutant Source Impacts and to Evaluate Environmental Justice

Air quality monitoring has traditionally been conducted using sparsely distributed, expensive reference monitors. To understand variations in PM2.5 on a finely resolved spatiotemporal scale a dense network of over 40 low-cost monitors was deployed throughout and around Pittsburgh, Pennsylvania, USA. Monitor locations covered a wide range of site types with varying traffic and restaurant density, varying influences from local sources, and varying socioeconomic (environmental justice, EJ) characteristics. Variability between and within site groupings was observed. Concentrations were higher near the source-influenced sites than the Urban or Suburban Residential sites. Gaseous pollutants (NO2 and SO2) were used to differentiate between traffic (higher NO2 concentrations) and industrial (higher SO2 concentrations) sources of PM2.5. Statistical analysis proved these differences to be significant (coefficient of divergence > 0.2). The highest mean PM2.5 concentrations were measured downwind (east) of the two industrial facilities while background level PM2.5 concentrations were measured at similar distances upwind (west) of the point sources. Socioeconomic factors, including the fraction of non-white population and fraction of population living under the poverty line, were not correlated with increases in PM2.5 or NO2 concentration. The analysis conducted here highlights differences in PM2.5 concentration within site groupings that have similar land use thus demonstrating the utility of a dense sensor network. Our network captures temporospatial pollutant patterns that sparse regulatory networks cannot.

On the Relationship between Economic Integration, Business Environment and Real Convergence: The Experience of the CEE Countries

The aim of the article is to verify the convergence process of the Central and Eastern Europe (CEE) (CEE10) countries towards Western European countries (EU15) in years 1995–2016. Additionally, the paper aims to show the interaction between economic integration and convergence as well as business environment and growth. The study methods applied in in the article are analysis of the literature and wide range of quantitative methods (descriptive statistics. regression models (OLS and panel), the elements of taxonomic analysis (cluster analysis and Clark’s coefficient of divergence). In the study years, CEE10 and EU15 countries were developing in accordance with the convergence hypothesis. The impact of economic integration on convergence was confirmed as well as the dependence of growth from the business environment in EU10. The added value of the study is the combination of three important research problems: convergence, economic integration and business environment. In addition, the research area concerns the CEE countries, which is very desirable. Many prior studies suggested to elaborate development and business processes in emerging countries like CEE. Thus, the article tries to fulfill this research needs. It has not only cognitive but also utilitarian values. The research results can be taken into consideration by policy makers to create an appropriate development policy and a conducive business environment.

The colour phases of the European red squirrel in Ukraine: Similarities and differences by craniometric characters

The different colour phases of the European red squirrel occuring in Ukraine were analysed in a morphological context. They are indicated in the literature as different subspecies of Sciurus vulgaris L. and described only based on their coat colouration. In Ukraine, at least three colour phases occur: dark (black and brown), red, and light red, which in natural habitats occur separately from one another. These phases co-occur in human settlements and at different altitudes, in particular at the boundary of the lowland and piedmont zones and of piedmont and mountainbelts. The aim of the present study was to find some other morphological differences between the red squirrel’s phases in Ukraine beyond their coat colouration and to reveal the possible interaction between colouration and morphological variation of the squirrels. Eighteen craniometric and four external characters were measured and analysed. Results have shown that the squirrel’s colour phases differ among themselves by some characters, although the most visible differences were revealed when all measurents were analysed together. It has been revealed that the three colour phases are stabilized types (populations) manifested in a multidimensional space as different populations with minimal overlap (up to 10%). The population of dark squirrels in Ukraine is morphologically the most distant from the light red phase and less so from the red one. The dark phase significantly differs from the red phase by 9 of 18 craniometric characters with Mayr’s coefficient of divergence (CDmin = 0.62, CDmax = 0.96). The dark phase significantly differs from the light red phase by two craniometric characters according to ANOVA, but only by one character according to Mayr’scoefficient of divergence (CD = 0.96). The red and light red phases significantly differ by four parameters having CDmin = 0.64 and CDmax = 0.76. The geographically transitional red phase is morphologically intermediate according to the results of discriminant analysis.