Background and aims Ecosystem respiration (R _eco ) is controlled by thermal and hydrologic regimes, but their relative importance in defining the CO₂ emissions in peatlands seems to be site specific. The aim of the paper is to investigate the sensitivity of R _eco to variations in temperature and water table depth (WTD) in a wet, geogenous temperate peatland with a wide variety of vegetation community groups. Methods The CO₂ fluxes were measured using chambers. Measurements were made at four microsites with different vegetation communities and peat moisture and temperature conditions every 3 to 4 weeks during the period 2008–2009, 2 years with contrasting WTD patterns. Models were used to examine the relative response of each microsite to variations in peat temperature and WTD and used to estimate annual total R _eco . Results Temporal variations in R _eco were strongly related to peat temperature at the 5 cm depth. However, two of the microsites did not show any significant change in this relationship while two others showed contrasting responses including an increase and decrease in temperature sensitivity with deeper WTD. Average R _eco varied among the microsites and tended to be greatest for those with greatest leaf area which also positively correlated with deeper WTD, ash content and degree of peat decomposition at 20 cm. A combined temperature and WTD model explained up to 94 % of the temporal variation in daily average R _eco and was used to show that on an annual basis, R _eco was between 5 and 18 % greater in the warmer year with deeper WTD. Conclusion Microsite-specific responses were related to differences in vegetation and peat characteristics among microsites. R _eco may have remained insensitive to WTD variations at one microsite due to the dominance of autotrophic respiration from abundant sedge biomass. At a Sphagnum-dominated microsite, a lack of response may have been due to relatively small variations in WTD that did not greatly influence microbial respiration or due to offsets between decreasing and increasing respiration rates in near-surface and deeper peat. The microsite with the most recalcitrant peat had reduced R _eco sensitivity to temperature under more aerobic conditions while another microsite showed the opposite response, perhaps due to less nutrient availability during the wet year. Ultimately, micro-site specific models with both soil temperature and WTD as explanatory variables described temporal variations in R _eco and highlighted the significant spatial variations in respiration rates that may occur within a single wetland.

The taxonomic and functional diversity of bacteria in seven different experimental variants applied to soil under a maize plantation was determined by means of next-generation sequencing and biochemical methods. The aim of the study was to discover differences in the structure of bacteria and the level of soil enzymatic activity (BIF—biochemical index of fertility) after the application of a biofertiliser made of lignocellulosic substrate and biochar containing various microorganisms (algae, mycorrhizal fungi of the Glomus genus or the consortium of Bacillus sp. bacteria). The chemical composition and yield of crops was a measurable indicator of the effectiveness of the fertilisers. The biofertilisers influenced both the structure and the percentage share of individual bacterial operational taxonomic units (OTU). The cultivation of maize also modified qualitative and quantitative changes in the soil bacterial microbiome. A canonical variate analysis (CVA) showed that the soil pH exhibited a minimal positive correlation with the soil enzymatic activity and selected plant parameters, with the exception of the biofertiliser variant with arbuscular mycorrhiza (AM). Moreover, the AM biofertiliser significantly increased the BIF value, the yield of maize seeds and the starch content in the plants. The comprehensive nature of the research allowed for a deepening and systematization of the existing knowledge on the influence of biochar with the addition of selected microorganisms on the biochemical parameters of the soil and the bacterial biodiversity of the soil environment. Additionally, the inclusion of the chemical, sanitary composition and yield of maize in the research brought a measurable view of the changes taking place in the soil and plant environment under the influence of the discussed factor. Apart from the agronomic aspect (integrated crop cultivation—Directive 2009/128/EC) of our study, it was also closely related to environmental protection, as it proved that biochar-based biofertilisers could be an alternative to mineral fertilisation.

The study focused on modelling of macropyte indices against physico-chemical parameters of waters by artificial neural networks. Several macrophyte diversity indices were analysed (species richness—N, the Shannon index—H′, the Simpson index—D, and the Pielou index—J) as well as the ecological status index (the Macrophyte Index for Rivers—MIR). The aim of the study was to verify knowledge about potential application of macrophytes in the environmental monitoring. A Multi-Layer Perceptron type of network was used in the analyses. The study included 260 river sites located throughout Poland. Alkalinity, conductivity, pH, nitrate and ammonium nitrogen, reactive and total phosphorus, and biochemical oxygen demand were used as the explanatory variables. The quality of the constructed models was assessed using calculated errors (RMSE and NRMSE) and r Pearson’s linear correlation coefficient. The neural network for the MIR index was characterised by the highest quality. Neural networks for other diversity indices (N, H′, D, and J) did not provide adequate results for modelling, which shows their ineffectiveness biological monitoring. Sensitivity analysis revealed the influence of each variable to the models. It indicated that modelled values of MIR are most strongly influenced by total phosphorus and alkalinity.

The variation of a number of parameters characterizing aquatic plant assemblages in rivers across a wide trophic gradient was investigated to evaluate their usefulness for a Polish national river monitoring system. Analyses were conducted at 100 sites included in the national river monitoring system, representing a uniform river type, i.e., small- and medium-sized lowland rivers with a sandy substrate. Results of botanical surveys, which were supplemented with comprehensive monthly quality records, were obtained from the national monitoring database. By analyzing the Jaccard distances of the botanical metrics using the adonis function, the variation in species composition between rivers of different trophic status was determined. The group consisting of the most degraded rivers was the most homogeneous in terms of botanical composition. The cleanest rivers displayed a high level of heterogeneity within their group, as numerous different unique species were found there at low frequencies. The variation of the macrophyte metrics used to assess the ecological status (Macrophyte Index for Rivers (MIR) and River Macrophyte Nutrient Index (RMNI)) reflected a trophic gradient. We confirmed that vegetation diversification along a trophic gradient is evident enough to detect degradation in a five quality class system.

Financial liquidity and profitability are two critical phenomena present in the financial economy of a company, whose relations depend on each other and may course in different directions. At the same time, they are an example of the complexity of the problem, which demands a proper approach, allowing one to reconcile two opposing objectives of any enterprise, i.e., maximizing the benefits for the owners and minimizing the risk of losing financial liquidity. Until now, the relationship between liquidity and profitability has not been examined explicitly, using multidimensional methods in particular. Nevertheless, the links between profitability and financial liquidity maintenance ensure the sustainable development of enterprises in different branches. This paper formulates two aims: scientific and practical. The scientific one concerns adopting the canonical variate analysis method to visualize the differences and relationships between food industry companies regarding financial liquidity and profitability. The practical one relates to indicating the relationship between financial liquidity and profitability in different groups of food industry companies. To study the relationships between the selected groups of enterprises and describe them, the liquidity and profitability ratios were utilized, involving canonical variate analysis based on transformation by linear combination and singular value decomposition. The analysis found that the most important feature highlighting the group of the examined entities regarding financial liquidity was the cash conversion cycle. The research results showed the existence of multidirectional relationships between liquidity and profitability. The research indicates that they depend on indicators describing financial dependencies and the industries in which they operate. This led to a much deeper and broader interpretation of the assessment of the financial situation of companies to support their sustainable development.