Factors of Dynamics of Plankton Crustacean Communities under Eutrophic Conditions

Russian Journal of Ecology - It has been shown that the main drivers of the dynamics of cladoceran and copepod abundances can be predators (fish), the quantity and/or quality of food in terms of...     

The Effect of Vaccinium vitis-idaea on Properties of Mountain-Meadow Soil under Alpine Lichen Heath

Russian Journal of Ecology - Abstract—The study of the effect of mycorrhiza symbiosis on the transformation of carbon and nitrogen compounds in soils is important in view of the necessity to...     

Synthesis of functionalized mesoporous material from rice husk ash and its application in the removal of the polycyclic aromatic hydrocarbons

Environmental Science and Pollution Research - The rice husk ash (RHA) was used as an alternative source of silica for the synthesis of the functionalized mesoporous material, which was used in the...     

Spatial population structure of rare orchid species in rich fens in the central part of Murmansk oblast

The spatial structure of 10 populations of rare orchid species (Dactylorhiza incarnata, D. traunsteineri, Listera ovata) has been studied in rich fens sporadically occurring in Murmansk oblast. Two levels of plant aggregation within populations have been distinguished: (1) clusters of individuals and (2) isolated population subsets consisting of clusters. General spatial demographic features of orchid populations in the fens are small area (77 m²) and low ecological density (0.009 ind./m²). Characteristics of the population subsets (their number, area, composition, and distance to the neighboring subset) are species-specific and reflect the degree of species rarity in plant communities.     

Epigenetic variation in the American mink, <Emphasis Type="Italic">Neovison vison</Emphasis>, from eastern Europe: A search for factors of polymorphism

A comparative analysis of epigenetic variation has been performed in nine European populations and population groups of the American mink. It has been shown that differentiation of samples in nonmetric characters is due mainly to endogenous processes that have occurred in introduced populations in the course of colonization of new territory by the invasive species. Environmental factors have played a secondary role, with the influence of the geographic (latitudinal) origin of a given sample being considerable and stronger than that of macroclimatic factors.     

Characteristics of stone moroko population dynamics at different stages of naturalization in lake- and steam-type Dnieper reservoirs

The probable source of stone moroko, Pseudorasbora parva (Temminck & Schlegel, 1846), populations in lake- and stream-type Dnieper reservoirs was revealed. The dynamics and specific growth rates of these populations over 20 years were analyzed. The dynamic phase portrait method was used to determine the timing of stages in the process of invader naturalization and the periods when its populations were in equilibrium. The potential growth rates of P. parva populations in the Kremenchug and Dneprodzerzhinsk reservoirs were estimated.     

Non-invasive matrices in human biomonitoring: a review

Humans and other living organisms are exposed to a variety of chemical pollutants that are released into the environment as a consequence of anthropogenic activities. Environmental pollutants are incorporated into the organism by different routes and can then be stored and distributed in different tissues, which leads to an internal concentration that can induce different alterations, adverse effects and/or diseases. Control measures should be taken to avoid these effects and human biomonitoring is a very useful tool that can contribute to this aim. Human biomonitoring uses different matrices to measure the target chemicals depending on the chemical, the amount of matrix necessary for the analysis and the detection limit (LOD) of the analytical technique. Blood is the ideal matrix for most chemicals due to its contact with the whole organism and its equilibrium with organs and tissues where chemicals are stored. However, it has an important disadvantage of being an invasive matrix. The development of new methodology and modern analytical techniques has allowed the use of other matrices that are less or non-invasive, such as saliva, urine, meconium, nails, hair, and semen or breast milk. The presence of a chemical in these matrices reflects an exposure, but correlations between levels in non-invasive matrices and blood must be established to ensure that these levels are related to the total body burden. The development of new biomarkers that are measurable in these matrices will improve non-invasive biomonitoring. This paper reviews studies that measure Cd, Pb, Hg, polychlorinated biphenyls (PCBs), polychlorinated dibenzo-p-dioxins (PCDDs), polychlorinated dibenzofurans (PCDFs), polycyclic aromatic hydrocarbons (PAHs), polybrominated diphenyl ethers (PBDEs), organochlorine pesticides and phthalates in non-invasive matrices, the most used techniques for measurements and what alternative techniques are available.     

Assessing spatial variability of SO2 field as detected by an air quality network using Self-Organizing Maps,cluster, and Principal Component Analysis

In Bilbao (Spain), an air quality network measures sulphur dioxide levels at 4 locations. The objective of this paper is to develop a practical methodology to identify redundant sensors and evaluate a network's capability to correctly follow and represent SO₂ fields in Bilbao, in the frame of a continuous network optimization process.The methodology is developed and tested at this particular location, but it is general enough to be useable at other places as well, since it is not tied neither to the particular geographical characteristics of the place nor to the phenomenology of the air quality over the area.To assess the spatial variability of SO₂ measured at 4 locations in the area, three different techniques have been used: Self-Organizing Maps (SOMs), cluster analysis (CA) and Principal Component Analysis (PCA). The results show that the three techniques yield the same results, but the information obtained via PCA can be helpful not only for that purpose but also to throw light on the major mechanisms involved. This might be used in future network optimization stages. The main advantage of cluster analysis and SOMs is that they provide readily interpretable results. All the calculations have been carried out using the freely available software R.