International Letters of Natural Sciences Vol. 82

Abstract: Nematodes are plant-parasitic organisms that cause alterations in the chemical and physical environment of soils. This study investigates the relationship between nematode occurrence and some soil parameters. The results showed that the proportion of nematodes in soil was negatively correlated with soil pH (r²= 0.89); however, it increased with increasing electrical conductivity (EC) (r² = 0.95), soil moisture (SM) (r² = 0.60), and organic matter (OM) content (r²= 0.78). A positive correlation was found between the proportion of nematodes in the roots and the amount of coarse sand, while a negative correlation existed between the proportion of nematodes and the amount of fine sand, clay, and silt. The degree of colonization by nematodes increased with increasing coarse sand content (r²= 0.91). Conversely, the soil nematode population decreased with increasing fine sand content (r²= 0.83), clay (r²= 0.80), and silt content (r²= 0.97). The nematode population in banana roots correlated with soil phosphorus (r² = 0.88), potassium (r² = 69), calcium (r² = 0.78), and magnesium levels (r²=0.78). Conversely, a negative correlation was found between nitrogen concentration and the nematode population in banana roots (r²=0.76). Overall, the population of nematodes in soil affects its pH, EC, SM, and OM content.

Abstract: The production functions of water-dependent sectors of the economy can include the water level in the lake as a natural resource. This characteristic must be able to reliably predict for the effective functioning of sectors of the economy. In the article the main attention is paid to the methods of forecasting based on the extrapolation of natural variations of the large lakes water level. As an example, is considered. In this paper, it is assumed that the level varies accordingly to a stochastic multi-cycle process with principal energy-containing zones in frequency bands associated with seasonal and multi-annual variations. Hence, the multi-year monthly and yearly averaged time series are represented by the ARIMA (auto-regression integrated moving average) processes. Forecasts are generated by using of the seasonal ARIMA-models, which take into account not only the seasonal but also the evolution non-stationarity. To compare the forecasts and the actual values, the relative errors are computed. It is shown that implementation of the models mainly allows receiving good and excellent forecasts. Subject Classification Numbers: UDC 556.555.2.06(4)

Abstract: In the global outlook, letting of untreated sewage in existing river bodies deteriorates the water quality. The seepage likely depreciates the quality of ground water too. The quality of groundwater with special reference to India has tremendously gone down in the past twenty years leading to sour taste. On the other hand, agriculture sector is deprived of water in many places of India. A solution can be arrived concurrently by treating sewage and consuming the effluent in agricultural sector. First order kinetics was applied in constructed wetland system at different flow rates and optimised. At optimised HLR, effluent met the standards of discharge that can be utilized for agricultural/ irrigational purpose. The emanating major pollutants can be effectively treated using constructed wetland system under tropical climate. A few clippings at the onsite treatment illustrated the diversity of species thus adjoining sustainable biodiversity and treatment. Thus in tropical countries like India, constructed wetland system might pave solution not only for the treatment of sewage but in deploying the effluent in agricultural sector. A clean ecosystem can be achieved with sustainability.

Abstract: The role of spatial variables, soil properties and overstorey structure in spatial variation of the herb-layer community in a riparian mixed forest was shown. The research were conducted in the "Dnipro-Orils’kiy" Nature Reserve (Ukraine). The research polygon was laid in a forest in the floodplain of the River Protich, which is a left inflow of the River Dnipro. Plant abundance was quantified by measuring cover within experimental polygon. The experimental polygon consisted of 7 transects and each transect was made up of 15 test points. The distance between rows in the site was 3 m. At the site we established a plot of 45×21 m, with 105 subplots of 3×3 m organized in a regular grid. Vascular plant species lists were recorded for each 3×3 m subplot along with visual estimates of species cover projection. The plant community was represented by 43 species, of which 18.6% were phanerophytes, 39.5% were hemikriptophytes, 9.3% were therophytes, 7.0% were geophytes. An overall test of random labelling revealed the total nonrandom distribution of the tree stems within the site. Constrained correspondence analysis (CCA) was applied as ordination approach. The forward selection procedure allowed us to select 6 soil variables, which explain 28.3% of the herb-layer community variability. The list of the important soil variables includes soil mechanical impedance (at the depth 0–5, 30–35, 75–80, and 95–10 cm), soil moisture, and soil bulk density. The variation explained by pure spatial variables is equal to 11.0 %. The majority of the tree-distance structured variation in plant community composition was broad-scaled. The significant relationship was found between the pure spatial component of the community variation and a lot of phytoindicator estimations of which the variability of damping and humidity were of the greatest importance. Trees stand was demonstrated to be a considerable factor structuring both the herb-layer community and spatial variation of the physical properties of soil.