Interactions among bacterial-feeding nematode species at different levels of food availability

Accurate prediction of the biodiversity–ecosystem functioning relationship requires adequate understanding of the interactions among species in a community. Effects of species diversity on ecosystem functioning are usually considered more pronounced with increasing functional dissimilarity, although species within functional groups may also perform non-identical functions and interact with each other. Here we present results of a laboratory experimental study aimed at elucidating whether interspecific interactions among species within a single nematode trophic group, bacterivores, (1) affect population development and community structure, and (2) depend on food availability. We studied the population growth of Rhabditis (Pellioditis) marina, a rhabditid nematode known to favour very high food densities when in monoculture, and of Diplolaimelloides meyli and D. oschei, congeneric Monhysteridae known to perform better in monocultures at intermediate food availability. Both Diplolaimelloides species showed significantly different patterns of food-density dependence in combination culture compared to monoculture. At very high food availability, the rhabditid nematode facilitated growth of both monhysterid species, probably as a result of down-regulation of bacterial density. At the lowest food availabilities, the presence of even low numbers of monhysterid nematodes lead to exclusion of the rhabditid, which at such low food availability has a very inefficient food uptake. At intermediate food availabilities, abundances of both Diplolaimelloides species were strongly depressed in the combination culture, as a result of food depletion by the rhabditid, indirect inhibitory interactions between the two congeneric species, or both. The complexity of the species interactions render predictions on the outcome and functional consequences of changes in within-trophic-group diversity highly problematic.     

Modelling of concentrations along a moving observer in an inhomogeneous plume. Biological application: model of odour-mediated insect flights

We develop a stochastic model for the time-evolution of scalar concentrations and temporal gradients in concentration experienced by observers moving within inhomogeneous plumes that are dispersing within turbulent flows. In this model, scalar concentrations and their gradients evolve jointly as a Markovian process. Underlying the model formulation is a natural generalisation of Thomson’s well mixed condition [Thomson DJ (1987) J Fluid Mech 180:529–556]. As a consequence model outputs are necessarily compatible with statistical properties of scalars observed in experiment that are used here as model input. We then use the model to examine how insects aloft within the atmospheric boundary-layer can locate odour sources by modulating their flight patterns in response to odour cues. Mechanisms underlying odour-mediated flights have been studied extensively at laboratory-scale but an understanding of these flights over landscape scales is still lacking. Insect flights are simulated by combining the stochastic model with a simple model of insect olfactory response. These simulations show the strong influence of wind speed on the distributions of the times taken by insects to locate the source. In accordance with experimental observations [Baker TC, Vickers NJ (1997) In: Insect pheromone research: new directions, pp 248–264; Mafra-Neto A, Cardé RT (1994) Nature 369:142–144], flight patterns are predicted to become straighter and shorter, and source location is predicted to become more likely as the mean wind speed increases. The most probable arrival time to the source decreases with the mean wind speed. It is shown that scale-free movement patterns arising from olfactory-driven foraging stem directly from the power-law distribution of concentration excursion times above/below a threshold level and are robust with respect to variations in Reynolds number. Flight lengths are well represented by a power law distribution in agreement with the observed patterns of foraging bumblebees [Heinrich B (1979) Oecologia 40(3):235–245].     

Eulerian and Lagrangian time scales of the turbulence above staggered arrays of cubical obstacles

Environmental Fluid Mechanics - We present results from water-channel experiments on neutrally-stable turbulent flows over staggered arrays of cubical obstacles modelling idealised urban canopies....     

Arsenic exposure in Hungary, Romania and Slovakia

Inorganic arsenic is a potent human carcinogen and toxicant which people are exposed to mainly via drinking water and food. The objective of the present study was to assess current exposure to arsenic via drinking water in three European countries. For this purpose, 520 individuals from four Hungarian, two Slovakian and two Romanian countries were investigated by measuring inorganic arsenic and methylated arsenic metabolites in urine by high performance liquid chromatography with hydride generation and inductively coupled plasma mass spectrometry. Arsenic in drinking water was determined by atomic absorption spectrometry. Significantly higher concentrations of arsenic were found in both the water and the urine samples from the Hungarian counties (median: 11 and 15 microg dm(-3), respectively; p < 0.001) than from the Slovakian (median: 0.94 and 4.5 microg dm(-3), respectively) and Romanian (median: 0.70 and 2.1 microg dm(-3), respectively) counties. A significant correlation was seen between arsenic in water and arsenic in urine (R(2)= 0.46). At low water arsenic concentrations, the relative amount of dimethylarsinic acid (DMA) in urine was increased, indicating exposure via food. Also, high body mass index was associated with higher concentrations of arsenic in urine (p= 0.03), mostly in the form of DMA. Smokers had significantly higher urinary arsenic concentrations than non-smokers (p= 0.03). In conclusion, elevated arsenic exposure via drinking water was prevalent in some of the counties. Exposure to arsenic from food, mainly as DMA, and cigarette smoke, mainly as inorganic arsenic, are major determinants of arsenic exposure at very low concentrations of arsenic in drinking water.     

Chemical and spectroscopic characterization of organic matter during the anaerobic digestion and successive composting of pig slurry

In this work, anaerobic digestion of pig slurry and successive composting of the digestate after centrifugation were studied by means of chemical analysis, FTIR and fluorescence spectroscopy as excitation–emission matrix (EEM). Chemical analysis highlighted the organic matter transformation occurring during the processes. A decrease of volatile solids and total organic carbon were observed in the digestate with respect to the fresh pig slurry as a consequence of the consumption of sugars, proteins, amino acids and fatty acids used by microorganisms as a C source. Water Extractable Organic Matter (WEOM) was obtained for all samples and fractionated into a hydrophilic and a hydrophobic fraction. The highest WEOM value was found in the pig slurry indicating a high content of labile organic C. The digestate centrifuged and the digestate composted showed lower hydrophilic and higher hydrophobic contents because of the decrease of labile C. Total phenolic content was lower in the digestate with respect to fresh pig slurry sample (36.7%) as a consequence of phenolic compounds degradation. The strong decrease of total reducing sugars in the digestate (76.6%) as compared to pig slurry confirmed that anaerobic process proceed mainly through consumption of sugars which represent a readily available energy source for microbial activity. FTIR spectra of pig slurry showed bands indicative of proteins and carbohydrates. A drop of aliphatic structures and a decrease of polysaccharides was observed after the anaerobic process along with the increase of the peak in the aromatic region. The composted substrate showed an increase of aromatic and a relative decrease of polysaccharides. EEM spectra provided tryptophan:fulvic-like fluorescence ratios which increased from fresh substrate to digestate because of the OM decompostion. Composted substrate presented the lowest ratio due to the humification process.     

Pesticide dissipation curves in peach, pear and tomato crops in Uruguay

Dissipation curves of azoxystrobin and of the neonicotinoids acetamiprid and thiacloprid in peach; azinphos-methyl and carbaryl in pear and azoxystrobin, chlorfenapyr and chlorpyrifos in high-tunnel tomato crops were studied in the Southern region of Uruguay. An analytical methodology based on solid phase extraction (SPE) and detection by High Performance Liquid Chromatography with Diode Array Detector (HPLC/DAD) was used for acetamiprid and thiacloprid. Coupled SPE and detection by Gas Chromatography with Mass Selective Detector (GC/MSD) was used for the detection of azinphos-methyl, azoxystrobin, carbaryl, chlorfenapyr and chlorpyrifos residues. Curves were modeled mathematically with Solver program of Microsoft Excel. The best fit for acetamiprid and thiacloprid in peach was achieved with the exponential model (r(2)=0.961 and 0.944, respectively). In the case of peach fruits there is not a Maximum Residue Limit (MRL) for acetamiprid in the Codex Alimentarius, while 0.5 mg/kg is the value rated for thiacloprid. The MRLs accepted by the European Union (EU) are 0.1 mg/kg for acetamiprid and 0.3 mg/kg for thiacloprid. According to the curves determined in these experiments, thiacloprid residues 10 to 12 days after application (daa) were below the MRLs established by both sources. In the case of acetamiprid, 25 daa would be required, according to the exponential mathematical model, to get residues levels below the MRL values established by the EU. For azinphos methyl in pear, the residues detected were mathematically fitted to an exponential model (r(2)=0.999). According to it, residue levels under the MRL established by the EU (0.05 mg/kg) are gotten in our conditions in 20 daa. In plastic tunnel tomato chlorfenapyr residues were not detected from 16 daa, having the dissipation curve an exponential trend. In the same condition, there was not a decay of the azoxystrobin concentration during a 24-day trial, being it around 0.40 ± 0.05 mg/kg.     

EU-wide survey of polar organic persistent pollutants in European river waters

This study provides the first EU-wide reconnaissance of the occurrence of polar organic persistent pollutants in European river waters. More than 100 individual water samples from over 100 European rivers from 27 European Countries were analysed for 35 selected compounds, comprising pharmaceuticals, pesticides, PFOS, PFOA, benzotriazoles, hormones, and endocrine disrupters. Around 40 laboratories participated in this sampling exercise. The most frequently and at the highest concentration levels detected compounds were benzotriazole, caffeine, carbamazepine, tolyltriazole, and nonylphenoxy acetic acid (NPE₁C). Only about 10% of the river water samples analysed could be classified as “very clean” in terms of chemical pollution. The rivers responsible for the major aqueous emissions of PFOS and PFOA from the European Continent could be identified. For the target compounds chosen, we are proposing “indicative warning levels” in surface waters, which are (for most compounds) close to the 90th percentile of all water samples analysed.     

A stochastic Lagrangian micromixing model for the dispersion of reactive scalars in turbulent flows: role of concentration fluctuations and improvements to the conserved scalar theory under non-homogeneous conditions

Several reaction schemes, based on the conserved scalar theory, are implemented within a stochastic Lagrangian micromixing model to simulate the dispersion of reactive scalars in turbulent flows. In particular, the formulation of the reaction-dominated limit (RDL) reaction scheme is here extended to improve the model performance under non-homogeneous conditions (NHRDL scheme). The validation of the stochastic model is obtained by comparison with the available measurements of reactive pollutant concentrations in a grid-generated turbulent flow. This test case describes the dispersion of two atmospheric reactant species (NO and O₃) and their reaction product (NO₂) in an unbounded turbulent flow. Model inter-comparisons are also assessed, by considering the results of state-of-the-art models for pollutant dispersion. The present validation shows that RDL reaction scheme provides a systematic overestimation (relative error of ca. 85% around the centreline) in computing the local reactant consumption/production rate, whereas the NHRDL scheme drastically reduces this gap (relative error lower than 5% around the centreline). In terms of NO₂ production (or reactant consumption), neglecting concentration fluctuations determines overestimations of the product mean of around 100% and a NO₂ local production of one order of magnitude higher than the reference simulation. In terms of standard deviations, the concentration fluctuations of both the passive and reactive scalars are generally of the same order of magnitude or up to 1 or 2 orders of magnitudes higher than the corresponding ensemble mean values, except for the background reactant close to the plume edges. The study highlights the importance of modelling pollutant reactions depending on the instantaneous instead of the mean concentrations of the reactants, thus quantifying the role of the turbulent fluctuations of concentration, in terms of scalar statistics (mean, standard deviation, intensity of fluctuations, skewness and kurtosis of concentration, segregation coefficient, simulated reaction rate). This stochastic particle method represents an efficient numerical technique to solve the convection–diffusion equation for reactive scalars and involves several application fields: micro-scale air quality (urban and street-canyon scales), accidental releases, impact of odours, water quality and fluid flow industrial processes (e.g. combustion).     

Pesticide dissipation curves in peach,pear and tomato crops in Uruguay*

Dissipation curves of azoxystrobin and of the neonicotinoids acetamiprid and thiacloprid in peach; azinphos-methyl and carbaryl in pear and azoxystrobin, chlorfenapyr and chlorpyrifos in high-tunnel tomato crops were studied in the Southern region of Uruguay. An analytical methodology based on solid phase extraction (SPE) and detection by High Performance Liquid Chromatography with Diode Array Detector (HPLC/DAD) was used for acetamiprid and thiacloprid. Coupled SPE and detection by Gas Chromatography with Mass Selective Detector (GC/MSD) was used for the detection of azinphos-methyl, azoxystrobin, carbaryl, chlorfenapyr and chlorpyrifos residues. Curves were modeled mathematically with Solver program of Microsoft Excel®. The best fit for acetamiprid and thiacloprid in peach was achieved with the exponential model (r²=0.961 and 0.944, respectively). In the case of peach fruits there is not a Maximum Residue Limit (MRL) for acetamiprid in the Codex Alimentarius, while 0.5 mg/kg is the value rated for thiacloprid. The MRLs accepted by the European Union (EU) are 0.1 mg/kg for acetamiprid and 0.3 mg/kg for thiacloprid. According to the curves determined in these experiments, thiacloprid residues 10 to 12 days after application (daa) were below the MRLs established by both sources. In the case of acetamiprid, 25 daa would be required, according to the exponential mathematical model, to get residues levels below the MRL values established by the EU. For azinphos methyl in pear, the residues detected were mathematically fitted to an exponential model (r²=0.999). According to it, residue levels under the MRL established by the EU (0.05 mg/kg) are gotten in our conditions in 20 daa. In plastic tunnel tomato chlorfenapyr residues were not detected from 16 daa, having the dissipation curve an exponential trend. In the same condition, there was not a decay of the azoxystrobin concentration during a 24-day trial, being it around 0.40 ± 0.05 mg/kg.     

Applying the Kuhn–Tucker model to estimate the value of recreational ecosystem services in Sicily

This paper applies the Kuhn–Tucker model to estimate recreation demand of parks in Sicily. We estimate a fixed coefficient specification and a random coefficient specification to take into account heterogeneity across visitors. Estimates suggest a diversity of preferences across the population and that parks with higher level of quality attributes are more likely to be visited. We also simulate two sets of hypothetical policy scenarios to evaluate and compare the recreational value of each park and the welfare impacts of changes in a quality attribute.