Search

Springs are crucial for maintaining surface-water resources and healthy ecosystems and provide a valuable source of information about groundwater. Monthly, seasonal and annual trends in spring yield of 138 springs in Czechia over the period 1971–2020 were evaluated. Furthermore, field significant trends in spring yields in 18 hydrogeological regions were identified. Monotonic deterministic trends were detected by the trend-free pre-whitening modification of the Mann–Kendall test using mean monthly values. Most of the series (70%) did not exhibit any long-term trends in annual data. However, considering statistically significant changes, the decrease prevailed over the increase. A reduction in the yield was observed at 28% of the springs, while an increase only at 2% of them. In the seasonal cycle, the yield decreased mostly in summer (32% of springs), in other seasons the yield decreased at 23–28% of the springs. Most often, the yield decreased in May (42% of springs), June (38%), and July (36%), least often in March (14%) and February (18%). Monthly long-term yield increases were observed only at a maximum of 5% of the springs in any of the months. In past years, a spring maximum shift from April to March or even to February was observed (compared to the 1981–2010 period). However, the increase in March and February spring yield expected due to this shift, probably caused by the air temperature rise and earlier snowmelt, has not been detected yet. Annual time series at 7 of 18 hydrogeological regions exhibited a significant decreasing trend (p < 0.05). No increasing trend was detected in any of the regions when analyzing annual data. The decrease prevailed in crystalline bedrock hydrogeological regions (4 of the 7 regions). However, a significant spring yield decrease in the region of the North Bohemian Cretaceous Basin (area between the Jizera and the Lower Elbe) is worth noting since this area represents a protected area of natural water accumulation. Similar to individual site trends, the most field significant trends occurred in summer (11 of 18 regions) and the least in winter (5 of 18 regions).

Statistical detection of trends in hydrometeorological time series is a crucial task when revealing how river systems react to environmental and human-induced changes. It was shown that the autocorrelation structure of a series influences the power of parametric and nonparametric trend tests. While the order of short-memory processes can be sufficiently captured by AR(I)MA models, the determination of the Hurst exponent, which describes the long memory, is still challenging, considering that the available methods partially give different results. In the Elbe River basin, Europe, several studies focusing on the detection (or description) of long-term persistence were performed. However, different lengths of series and different methods were used. The aim of the present work is to gather the results gained in various parts of the Elbe basin in Central Europe and to compare them with our estimation of the Hurst exponent using six discharge series observed in selected subbasins. Instead of the dependence of the exponent on the catchment area suggested by the theory of aggregated short-memory processes, we rather found a relationship between this parameter and the series length. As the theory is not supported by our findings, we suppose that the Hurst phenomenon is caused by a complex interplay of low-frequency climate variability and catchment processes. Experiments based on distributed water balance models should be the further research objective, ideally under the umbrella of mutual international projects.

In the environment of the changing climate in Central Europe, the seasonality and magnitude of low flow events and hydrological droughts are projected to change in the near future. Ongoing increases in the air temperature, rates of evaporation and decreasing snow cover will significantly affect the summer deficit volumes even in the rivers of humid montane and highland areas in mid-latitudes. However, what if the significant changes have already been happening during the last decades? Therefore, this research is focused on analysis of the variability and seasonality of low flow events and hydrological drought events in fifteen near-natural catchments along the Czech–German and Czech–Polish national borders. To quantify the low flow regime changes of the study regions in the last 52 years (1968–2019), we applied tools from the R package lfstat. The 30-year moving averages of seasonality ratio (SR) and the seasonality index (SI) were derived to address the degree of change in each catchment. Moreover, the 7-day and 30-day mean summer minimum discharges were computed, as well as the streamflow deficit volumes for every episode of hydrological drought. The results showed a continual increase in the proportion of summer low flow and drought events during the study period along with a significant shift in the average date of low flow occurrence towards the beginning of the year. The most marked shifts in low flow seasonality were found mainly in catchments with the average altitude 800–1000 m a. s. l. Conversely, the low flow regime in catchments above 1000 m a. s. l. and also in the catchments below 800 m a. s. l. remained nearly stable throughout the 1968–2019 period. Moreover, the analysis of 7- and 30-day mean summer minimum discharges indicated a much-diversified pattern in the behavior of long-term trends than it was expected.

The territory of Czechia currently suffers from a long-lasting drought period which has been a subject of many studies, including the hydrological ones. Previous works indicated that the basin of the Morava River, a left-hand tributary of the Danube, is very prone to the occurrence of dry spells. It also applies to the development of various hydrological time series that often show decreases in the amount of available water. The purpose of this contribution is to extend the results of studies performed earlier and, using the most updated daily time series of discharge, to look at the situation of the so-called streamflow drought within the basin. 46 water-gauging stations representing the rivers of diverse catchment size were selected where no or a very weak anthropogenic influences are expected and the stability and sensitivity of profiles allow for the proper measurement of low flows. The selected series had to cover the most current period 1981-2018 but they could be much longer, which was considered beneficial for the next determination of the development direction. Various series of drought indices were derived from the original discharge series. Specifically, 7-, 15- and 30-day low flows together with deficit volumes and their durations were tested for trends using the modifications of the Mann– Kendall test that account for short-term and long-term persistence. In order to better reflect the drivers of streamflow drought, the indices were considered for summer and winter seasons separately as well. The places with the situation critical to the future water resources management were highlighted where substantial changes in river regime occur probably due to climate factors. Finally, the current drought episode that started in 2014 was put into a wider context, making use of the information obtained by the analyses.

The streamflow seasonality in mountain catchments is often influenced by snow. However, a shift from snowfall to rain is expected in the future. Consequently, a decrease in snow storage and earlier snowmelt is predicted, which will cause changes not only in seasonal runoff distribution in snow-dominated catchments, but it may also affect the total annual runoff. The objectives of this study were to quantify (1) how inter-annual variations in snow storages affect spring and summer runoff, including summer low flows, and (2) the importance of snowmelt in generating runoff compared to rainfall. The snow storage, groundwater recharge and streamflow were simulated for 59 mountain catchments in Czechia in the period from 1980 to 2014 using a bucket-type catchment model. The model output was evaluated against observed daily runoff and snow water equivalent. Hypothetical scenarios were performed, which allowed for analysing the effect of inter-annual variations in snow storage on seasonal runoff separately from other components of the water balance. The results showed that 17 %–42 % (26 % on average) of the total runoff in the study catchments originates as snowmelt, despite the fact that only 12 %–37 % (20 % on average) of the precipitation falls as snow. This means that snow is more effective in generating catchment runoff compared to liquid precipitation. This was demonstrated by modelling experiments which showed that total annual runoff and groundwater recharge decrease in the case of a precipitation shift from snow to rain. In general, snow-poor years were clearly characterized by a lower snowmelt runoff contribution compared to snow-rich years in the analysed period. Additionally, snowmelt started earlier in these snow-poor years and caused lower groundwater recharge. This also affected summer baseflow. For most of the catchments, the lowest summer baseflow was reached in years with both relatively low summer precipitation and snow storage. This showed that summer low flows (directly related to baseflow) in our study catchments are not only a function of low precipitation and high evapotranspiration, but they are significantly affected by the previous winter snowpack. This effect might intensify drought periods in the future when generally less snow is expected.

The streamflow seasonality in mountain catchments is largely influenced by snow. However, a shift from snowfall to rain is expected in the future. Consequently, a decrease in snow storage and earlier snowmelt is predicted, which will cause changes in spring and summer runoff. The objectives of this study were to quantify 1) how inter-annual variations in snow storages affect spring and summer runoff, including summer low flows and 2) the importance of snowmelt in generating runoff compared to rainfall. The snow storage, groundwater recharge and streamflow were simulated for 59 mountain catchments in Czechia in the period 1980–2014 using a bucket-type catchment model. The model performance was evaluated against observed daily runoff and snow water equivalent. Hypothetical simulations were performed, which allowed us to analyse the effect of inter-annual variations in snow storage on seasonal runoff separately from other components of the water balance. This was done in the HBV snow routine using the threshold temperature TT that differentiates between snow and rain and sets the air temperature of snowmelt onset. By changing the TT, we can control the amount of accumulated snow and snowmelt timing, while other variables remain unaffected.The results showed that 17-42% (26% on average) of the total runoff in study catchments originates as snowmelt, despite the fact that only 12-37% (20% on average) of the precipitation falls as snow. This means that snow is more effective in generating catchment runoff compared to liquid precipitation. This was documented by modelling experiments which showed that total annual runoff and groundwater recharge decreases in the case of a precipitation shift from snow to rain. In general, snow-poor years are clearly characterized by a lower snowmelt runoff contribution compared to snow-rich years in the analysed period. Additionally, snowmelt started earlier in these snow-poor years and caused lower groundwater recharge. This also affected summer baseflow. For most of the catchments, the lowest summer baseflow was reached in years with both relatively low summer precipitation and snow storage. This showed that summer low flows (directly related to baseflow) in our study catchments are not only a function of low precipitation and high evapotranspiration, but they are significantly affected by previous winter snowpack. This effect might intensify the summer low flows in the future when generally less snow is expected.Modelling experiments also opened further questions related to model structure and parameterization, specifically how individual model procedures and parameters represent the real natural processes. To understand potential model artefacts might be important when using HBV or similar bucket-type models for impact studies, such as modelling the impact of climate change on catchment runoff.

Honeybee (Apis mellifera L.) workers act as passive vectors of Paenibacillus larvae spores, which cause the quarantine disease American foulbrood (AFB). We assessed the relative proportions of P. larvae within the honeybee microbiome using metabarcoding analysis of the 16 S rRNA gene. The microbiome was analyzed in workers outside of the AFB zone (control - AFB0), in workers from asymptomatic colonies in an AFB apiary (AFB1), and in workers from colonies exhibiting clinical AFB symptoms (AFB2). The microbiome was processed for the entire community and for a cut-off microbiome comprising pathogenic/environmental bacteria following the removal of core bacterial sequences; varroosis levels were considered in the statistical analysis. No correlation was observed between AFB status and varroosis level, but AFB influenced the worker bee bacterial community, primarily the pathogenic/environmental bacteria. There was no significant difference in the relative abundance of P. larvae between the AFB1 and AFB0 colonies, but we did observe a 9-fold increase in P. larvae abundance in AFB2 relative to the abundance in AFB1. The relative sequence numbers of Citrobacter freundii and Hafnia alvei were higher in AFB2 and AFB1 than in AFB0, whereas Enterococcus faecalis, Klebsiella oxytoca, Spiroplasma melliferum and Morganella morganii were more abundant in AFB0 and AFB1 than in AFB2.

Climate change has led to concerns about increasing river floods resulting from the greater water-holding capacity of a warmer atmosphere1. These concerns are reinforced by evidence of increasing economic losses associated with flooding in many parts of the world, including Europe2. Any changes in river floods would have lasting implications for the design of flood protection measures and flood risk zoning. However, existing studies have been unable to identify a consistent continental-scale climatic-change signal in flood discharge observations in Europe3, because of the limited spatial coverage and number of hydrometric stations. Here we demonstrate clear regional patterns of both increases and decreases in observed river flood discharges in the past five decades in Europe, which are manifestations of a changing climate. Our results—arising from the most complete database of European flooding so far—suggest that: increasing autumn and winter rainfall has resulted in increasing floods in northwestern Europe; decreasing precipitation and increasing evaporation have led to decreasing floods in medium and large catchments in southern Europe; and decreasing snow cover and snowmelt, resulting from warmer temperatures, have led to decreasing floods in eastern Europe. Regional flood discharge trends in Europe range from an increase of about 11 per cent per decade to a decrease of 23 per cent. Notwithstanding the spatial and temporal heterogeneity of the observational record, the flood changes identified here are broadly consistent with climate model projections for the next century4,5, suggesting that climate-driven changes are already happening and supporting calls for the consideration of climate change in flood risk management. Analysis of a comprehensive European flood dataset reveals regional changes in river flood discharges in the past five decades that are consistent with models suggesting that climate-driven changes are already happening.

The main scope of this study was to present the possibility of developing a heavy rainfall regional model, based on a probabilistic approach. Following the methods and conclusions of the scientific and technical work of the research team in the Upper and Middle Oder basin, carried out on rainfall data between 1961 and 2010, it was found that the generalized exponential distribution enables a satisfactory probabilistic description of heavy rainfall, and the results of the models constructed on its basis are obtained in an accessible and not time-consuming way. The regional model presented in the article sufficiently describes the empirical heavy rainfall at eight analyzed meteorological stations, especially in the range of rainfall amounts occurring most frequently from a statistical point of view, i.e. with the p-value from 0.3 to 1.0.

Tyrophagus putrescentiae is inhabited by bacteria that differ among mite populations (strains) and diets. Here, we investigated how the microbiome and fitness of T . putrescentiae are altered by dietary perturbations and mite populations. Four T. putrescentiae populations, referred to as dog, Koppert, laboratory, and Phillips, underwent a perturbation, i.e., a dietary switch from a rearing diet to two experimental diets. The microbiome was investigated by sequencing the V1-V3 portion of the 16S rRNA gene, and selected bacterial taxa were quantified by quantitative PCR (qPCR) using group/taxon-specific primers. The parameters observed were the changes in mite population growth and nutritional status, i.e., the total glycogen, lipid, saccharide, and protein contents in mites. The effect of diet perturbation on the variability of the microbiome composition and population growth was lower than the effect induced by mite population. In contrast, the diet perturbation showed a greater effect on nutritional status of mites than the mite population. The endosymbionts exhibited high variations among T. putrescentiae populations, including Cardinium in the laboratory population, Blattabacterium -like bacteria in the dog population, and Wolbachia in the dog and Phillips populations. Solitalea -like and Bartonella -like bacteria were present in the dog, Koppert, and Phillips populations in different proportions. The T. putrescentiae microbiome is dynamic and varies based on both the mite population and perturbation; however, the mites remain characterized by robust bacterial communities. Bacterial endosymbionts were found in all populations but represented a dominant portion of the microbiome in only some populations. IMPORTANCE We addressed the question of whether population origin or perturbation exerts a more significant influence on the bacterial community of the stored product mite Tyrophagus putrescentiae . The microbiomes of four populations of T. putrescentiae insects subjected to diet perturbation were compared. Based on our results, the bacterial community was more affected by the mite population than by diet perturbation. This result can be interpreted as indicating high stability of the putative intracellular symbionts in response to dietary perturbation. The changes in the absolute and relative numbers of Wolbachia , Blattabacterium -like, Solitalea -like, and Cardinium bacteria in the T. putrescentiae populations can also be caused by neutral processes other than perturbation. When nutritional status is considered, the effect of population appeared less important than the perturbation. We hypothesize that differences in the proportions of the endosymbiotic bacteria result in changes in mite population growth.

Most hydrometeorological data from Czechia are still provided for a fee. This especially applies to time series with a finer step than monthly. The fact that the data must be paid with respect to an expert’s appraisement and that the proper licence agreement ratification has to be performed causes a considerable delay in the data transfer to potential customers, unfortunately including scientists as well. Naturally, this time-consuming process is unpleasant to the experts on both sides. Due to a substantial rise of university students’ requests for data, the Czech Hydrometeorological Institute’s hydrologists launched a website from which long mean daily discharge series representing ten selected water-gauging stations can be downloaded. Besides other assessments, the series may play an important role when studying climate change impacts on water resources in Czechia. Therefore, the objective here was to extract from these series some preliminary information on long-term changes such as abrupt and gradual trends caused either by the construction of reservoirs or by climate variability itself. The main tool used was nonparametric trend analysis. Mainly different months were of interest so as to determine if there have been recorded some changes in seasonality. The results may be easily expanded by students.

Trend analysis is a frequently used tool in hydrology and climatology for the identification of long-term changes. However, studies are usually only oriented on local trends. This paper rather focuses on the spatial application of trend analysis in groundwater data. For this purpose, a modification of the Mann-Kendall test was developed, based on the trend-free pre-whitening approach. This method was successfully tested on 157 series of yields from headwater springs collected in Czechia during the 1971–2007 period. The analysis was done separately for year, each season and each month. Field significant trends in spring yields were identified in hydrogeological regions. The results showed that the field significant trends are outnumbered when cross-correlation is not taken into account. In the case of annual series, 4 of 18 hydrogeological regions investigated showed a significant decreasing trend after corrections for cross-correlation, compared to 12 regions with field significant trend when not considering cross-correlation.

Worker honeybees (Apis mellifera) transmit Melissococcus plutonius between colonies. However, the transmission of M. plutonius, which causes European foulbrood (EFB), is poorly understood. To analyze the first EFB outbreak in 40 years in Czechia, we collected 49 hive worker samples from 18 beehives in two diseased apiaries for bacteriome analysis of the V1-V3 portion of the 16S rRNA gene. When we compared control samples obtained outside of the EFB zone, bees from an EFB apiaries containing colonies without clinical symptoms and bees from colonies with EFB clinical symptoms, there was a 100-fold higher occurrence of M. plutonius in colonies with EFB symptoms. The presence of M. plutonius in controls indicated that this pathogen exists in an enzootic state. EFB influenced the core bacteria in the worker bacteriome because the number of Snodgrassella alvi, Lactobacillus mellis, Lactobacillus melliventris, and Fructobacillus fructosus sequences increased, while Bartonella apis, Frischella perrara, and Commensalibacter intestine sequences decreased. Together, the results of this study suggest worker bees from EFB-diseased apiaries serve as vectors of M. plutonius, and eliminating such colonies is an appropriate method to overcome disease outbreaks. Because M. plutonius exists in honeybee colonies in an enzootic state, there may be similar abundances in control colonies outside the EFB zone to those in asymptomatic colonies from EFB apiaries. High-throughput Illumina next-generation sequencing permitted the quantitative interpretation of M. plutonius within the honeybee worker bacteriome. Future studies focusing on honeybee diseases, colony losses, detection of bacterial pathogens and interactions of bacteriome with pathogenic bacteria will benefit of this study.

Background Melissococcus plutonius is an entomopathogenic bacterium that causes European foulbrood (EFB), a honeybee (Apis mellifera L.) disease that necessitates quarantine in some countries. In Czechia, positive evidence of EFB was absent for almost 40 years, until an outbreak in the Krkonose Mountains National Park in 2015. This occurrence of EFB gave us the opportunity to study the epizootiology of EFB by focusing on the microbiome of honeybee workers, which act as vectors of honeybee diseases within and between colonies. Methods The study included worker bees collected from brood combs of colonies (i) with no signs of EFB (EFB0), (ii) without clinical symptoms but located at an apiary showing clinical signs of EFB (EFB1), and (iii) with clinical symptoms of EFB (EFB2). In total, 49 samples from 27 honeybee colonies were included in the dataset evaluated in this study. Each biological sample consisted of 10 surface-sterilized worker bees processed for DNA extraction. All subjects were analyzed using conventional PCR and by metabarcoding analysis based on the 16S rRNA gene V1–V3 region, as performed through Illumina MiSeq amplicon sequencing. Results The bees from EFB2 colonies with clinical symptoms exhibited a 75-fold-higher incidence of M. plutonius than those from EFB1 asymptomatic colonies. Melissococcus plutonius was identified in all EFB1 colonies as well as in some of the control colonies. The proportions of Fructobacillus fructosus, Lactobacillus kunkeei, Gilliamella apicola, Frischella perrara, and Bifidobacterium coryneforme were higher in EFB2 than in EFB1, whereas Lactobacillus mellis was significantly higher in EFB2 than in EFB0. Snodgrassella alvi and L. melliventris, L. helsingborgensis and, L. kullabergensis exhibited higher proportion in EFB1 than in EFB2 and EFB0. The occurrence of Bartonella apis and Commensalibacter intestini were higher in EFB0 than in EFB2 and EFB1. Enterococcus faecalis incidence was highest in EFB2. Conclusions High-throughput Illumina sequencing permitted a semi-quantitative analysis of the presence of M. plutonius within the honeybee worker microbiome. The results of this study indicate that worker bees from EFB-diseased colonies are capable of transmitting M. plutonius due to the greatly increased incidence of the pathogen. The presence of M. plutonius sequences in control colonies supports the hypothesis that this pathogen exists in an enzootic state. The bacterial groups synergic to both the colonies with clinical signs of EFB and the EFB-asymptomatic colonies could be candidates for probiotics. This study confirms that E. faecalis is a secondary invader to M. plutonius; however, other putative secondary invaders were not identified in this study.

The honey bee, Apis mellifera, is a globally important species that suffers from a variety of pathogens and parasites. These parasites and pathogens may have sublethal effects on their bee hosts via an array of mechanisms, including through a change in symbiotic bacterial taxa. Our aim was to assess the influence of four globally widespread parasites and pathogens on the honey bee bacteriome. We examined the effects of the ectoparasitic mite Varroa destructor, the fungal pathogens Nosema apis and Nosema ceranae, and the trypanosome Lotmaria passim. Varroa was detected by acaricidal treatment, Nosema and L. passim by PCR, and the bacteriome using MiSeq 16S rRNA gene sequencing. Overall, the 1,858,850 obtained sequences formed 86 operational taxonomic units (OTUs) at 3 % dissimilarity. Location, time of year, and degree of infestation by Varroa had significant effects on the composition of the bacteriome of honey bee workers. Based on statistical correlations, we found varroosis more important factor than N. ceranae, N. apis, and L. passim infestation influencing the honey bee bacteriome and contributing to the changes in the composition of the bacterial community in adult bees. At the population level, Varroa appeared to modify 20 OTUs. In the colonies with high Varroa infestation levels (varroosis), the relative abundance of the bacteria Bartonella apis and Lactobacillus apis decreased. In contrast, an increase in relative abundance was observed for several taxa including Lactobacillus helsingborgensis, Lactobacillus mellis, Commensalibacter intestini, and Snodgrassella alvi. The results showed that the “normal” bacterial community is altered by eukaryotic parasites as well as displaying temporal changes and changes associated with the geographical origin of the beehive.

The ectoparasitic mite Varroa destructor is a major pest of the honeybee Apis mellifera. In a previous study, bacteria were found in the guts of mites collected from winter beehive debris and were identified using Sanger sequencing of their 16S rRNA genes. In this study, community comparison and diversity analyses were performed to examine the microbiota of honeybees and mites at the population level. The microbiota of the mites and honeybees in 26 colonies in seven apiaries in Czechia was studied. Between 10 and 50 Varroa females were collected from the bottom board, and 10 worker bees were removed from the peripheral comb of the same beehive. Both bees and mites were surface sterilized. Analysis of the 16S rRNA gene libraries revealed significant differences in the Varroa and honeybee microbiota. The Varroa microbiota was less diverse than was the honeybee microbiota, and the relative abundances of bacterial taxa in the mite and bee microbiota differed. The Varroa mites, but not the honeybees, were found to be inhabited by Diplorickettsia. The relative abundance of Arsenophonus, Morganella, Spiroplasma, Enterococcus, and Pseudomonas was higher in Varroa than in honeybees, and the Diplorickettsia symbiont detected in this study is specific to Varroa mites. The results demonstrated that there are shared bacteria between Varroa and honeybee populations but that these bacteria occur in different relative proportions in the honeybee and mite bacteriomes. These results support the suggestion of bacterial transfer via mites, although only some of the transferred bacteria may be harmful.

Quite recently, freely available mean daily discharge series representing the territory of Czechia were complemented by ten daily series of nine climate variables, spanning usually from 1961 to the present. Their length thus allows the analyses similar to those conducted approximately a year ago in relation to the long series of discharge. Besides this possibility, the current paper goes further and shows how these long series (including discharge) can be used in order to assess the presence of the so-called Hurst phenomenon. Using a wavelet-based approach, several important differences in the wavelet spectra and values of the Hurst exponent (as well as the uncertainty in their estimation) were found when focusing on discharge, air temperature and precipitation. Furthermore, using the stationarity and unit root tests, it was revealed that, unlike precipitation, air temperature and discharge series may be characterized by long-memory processes in many cases. Finally, as the paper is devoted mainly to students, a short R script is presented in Appendix that makes it easier to work with the online files offered by Czech climatologists.

BackgroundMelissococcus plutoniusis an entomopathogenic bacterium that causes European foulbrood (EFB), a honeybee (Apis melliferaL.) disease that necessitates quarantine in some countries. In Czechia, positive evidence of EFB was absent for almost 40 years, until an outbreak in the Krkonose Mountains National Park in 2015. This occurrence of EFB gave us the opportunity to study the epizootiology of EFB by focusing on the microbiome of honeybee workers, which act as vectors of honeybee diseases within and between colonies.MethodsThe study included worker bees collected from brood combs of colonies (i) with no signs of EFB (EFB0), (ii) without clinical symptoms but located at an apiary showing clinical signs of EFB (EFB1), and (iii) with clinical symptoms of EFB (EFB2). In total, 49 samples from 27 honeybee colonies were included in the dataset evaluated in this study. Each biological sample consisted of 10 surface-sterilized worker bees processed for DNA extraction. All subjects were analyzed using conventional PCR and by metabarcoding analysis based on the 16S rRNA gene V1–V3 region, as performed through Illumina MiSeq amplicon sequencing.ResultsThe bees from EFB2 colonies with clinical symptoms exhibited a 75-fold-higher incidence ofM. plutoniusthan those from EFB1 asymptomatic colonies.Melissococcus plutoniuswas identified in all EFB1 colonies as well as in some of the control colonies. The proportions ofFructobacillus fructosus,Lactobacillus kunkeei,Gilliamella apicola,Frischella perrara, andBifidobacterium coryneformewere higher in EFB2 than in EFB1, whereasLactobacillus melliswas significantly higher in EFB2 than in EFB0.Snodgrassella alviandL. melliventris,L. helsingborgensisand,L. kullabergensisexhibited higher proportion in EFB1 than in EFB2 and EFB0. The occurrence ofBartonella apisandCommensalibacter intestiniwere higher in EFB0 than in EFB2 and EFB1.Enterococcus faecalisincidence was highest in EFB2.ConclusionsHigh-throughput Illumina sequencing permitted a semi-quantitative analysis of the presence ofM. plutoniuswithin the honeybee worker microbiome. The results of this study indicate that worker bees from EFB-diseased colonies are capable of transmittingM. plutoniusdue to the greatly increased incidence of the pathogen. The presence ofM. plutoniussequences in control colonies supports the hypothesis that this pathogen exists in an enzootic state. The bacterial groups synergic to both the colonies with clinical signs of EFB and the EFB-asymptomatic colonies could be candidates for probiotics. This study confirms thatE. faecalisis a secondary invader toM. plutonius; however, other putative secondary invaders were not identified in this study.

The effects of possible climate change on water resources in prescribed areas (e.g. river basins) are intensively studied in hydrology. These resources are highly dependent on precipitation totals. When focusing on long-term changes in climate variables, one has to rely on station measurements. However, hydrologists need the information on spatial distribution of precipitation over the areas. For this purpose, the spatial interpolation techniques must be employed. In Czechia, where the addition of elevation co-variables proved to be a good choice, several GIS tools exist that are able to produce time series necessary for climate change analyses. Nevertheless, these tools are exclusively based on commercial software and there is a lack of free-of-charge tools that could be used by everyone. Here, selected free-of-charge geostatistical tools were utilized in order to produce monthly precipitation time series representing six river basins in the Ore Mountains located in NW Bohemia, Czechia and SE Saxony, Germany. The produced series span from January 1961 to December 2012. Rain-gauge data from both Czechia and Germany were used. The universal kriging technique was employed where a multiple linear regression (based on elevation and coordinates) residuals were interpolated. The final time series seem to be homogeneous.

Fiala et al. (2010) performed a study focused on the evolution of dry spells at 144 water-gauging stations covering the entire territory of Czechia. They investigated several indicators such as series of 7-day low flows, and deficit volumes and durations (both delimited based on two quantiles, Q330 and Q355, under which the flows are commonly considered as low). Using the Mann-Kendall (MK) test and its reliable modification that accounts for short-term persistence (STP) in data, they evaluated trends in their series. However, as stated in Khaliq et al. (2008), low flow data may also reveal so-called long-term persistence (LTP) that may cause the MK test to detect trends falsely. Therefore, the current study aims to find out if LTP was present before Fiala et al. (2010) applied the MK test to the 7-day low flow series. This was done through the Hurst exponent estimation. Also, testing for a unit root was carried out, similar to Fatichi et al. (2009).