Chemosensory discrimination of familiar and unfamiliar conspecifics by lizards: implications of field spatial relationships between males

The ability of territorial lizards to discriminate between scents of neighbors and non-neighbors might contribute to decreasing the costs of aggressive interactions. To test this hypothesis, we conducted a field study to analyze the spatial relationships between male Iberian rock-lizards, Lacerta monticola. We then used the same individuals in a laboratory experiment to test whether male lizards can use chemical cues to discriminate between familiar conspecific males (those whose home ranges overlapped) and unfamiliar conspecific males (those whose home ranges did not overlap, and whose home range centers were at least 50 m apart). Differences in tongue-flick rates in the presence of chemical cues suggested that male L. monticola discriminated between odors of familiar and unfamiliar males. The behavioral responses were also dependent on relative differences in body size between the responding male and the unfamiliar male that donated the scent: There was a significant negative correlation between tongue-flick rates emitted in cages of unfamiliar males and the body size differences between males. In contrast, when the donor of the scent was a familiar male, the tongue-flick rate was not dependent on body size differences. These results are compatible with individual discrimination through chemical cues in male L. monticola.     

Particulate matter levels in a South American megacity: the metropolitan area of Lima-Callao,Peru

The temporal and spatial trends in the variability of PM₁₀ and PM_2.5 from 2010 to 2015 in the metropolitan area of Lima-Callao, Peru, are studied and interpreted in this work. The mean annual concentrations of PM₁₀ and PM_2.5 have ranges (averages) of 133–45 μg m^?3 (84 μg m^?3) and 35–16 μg m^?3 (26 μg m^?3) for the monitoring sites under study. In general, the highest annual concentrations are observed in the eastern part of the city, which is a result of the pattern of persistent local winds entering from the coast in a south-southwest direction. Seasonal fluctuations in the particulate matter (PM) concentrations are observed; these can be explained by subsidence thermal inversion. There is also a daytime pattern that corresponds to the peak traffic of a total of 9 million trips a day. The PM_2.5 value is approximately 40% of the PM₁₀ value. This proportion can be explained by PM₁₀ re-suspension due to weather conditions. The long-term trends based on the Theil-Sen estimator reveal decreasing PM₁₀ concentrations on the order of ?4.3 and ?5.3% year^?1 at two stations. For the other stations, no significant trend is observed. The metropolitan area of Lima-Callao is ranked 12th and 16th in terms of PM₁₀ and PM_2.5, respectively, out of 39 megacities. The annual World Health Organization thresholds and national air quality standards are exceeded. A large fraction of the Lima population is exposed to PM concentrations that exceed protection thresholds. Hence, the development of pollution control and reduction measures is paramount.     

Assessing regulatory violations of disinfection by-products in water distribution networks using a non-compliance potential index

Inactivating pathogens is essential to eradicate waterborne diseases. However, disinfection forms undesirable disinfection by-products (DBPs) in the presence of natural organic matter. Many regulations and guidelines exist to limit DBP exposure for eliminating possible health impacts such as bladder cancer, reproductive effects, and child development effects. In this paper, an index named non-compliance potential (NCP) index is proposed to evaluate regulatory violations by DBPs. The index can serve to evaluate water quality in distribution networks using the Bayesian Belief Network (BBN). BBN is a graphical model to represent contributing variables and their probabilistic relationships. Total trihalomethanes (TTHM), haloacetic acids (HAA5), and free residual chlorine (FRC) are selected as the variables to predict the NCP index. A methodology has been proposed to implement the index using either monitored data, empirical model results (e.g., multiple linear regression), and disinfectant kinetics through EPANET simulations. The index’s usefulness is demonstrated through two case studies on municipal distribution systems using both full-scale monitoring and modeled data. The proposed approach can be implemented for data-sparse conditions, making it especially useful for smaller municipal drinking water systems.     

The use of sensory perception indicators for improving the characterization and modelling of total petroleum hydrocarbon (TPH) grade in soils

This paper proposes a multistep approach for creating a 3D stochastic model of total petroleum hydrocarbon (TPH) grade in potentially polluted soils of a deactivated oil storage site by using chemical analysis results as primary or hard data and classes of sensory perception variables as secondary or soft data. First, the statistical relationship between the sensory perception variables (e.g. colour, odour and oil–water reaction) and TPH grade is analysed, after which the sensory perception variable exhibiting the highest correlation is selected (oil–water reaction in this case study). The probabilities of cells belonging to classes of oil–water reaction are then estimated for the entire soil volume using indicator kriging. Next, local histograms of TPH grade for each grid cell are computed, combining the probabilities of belonging to a specific sensory perception indicator class and conditional to the simulated values of TPH grade. Finally, simulated images of TPH grade are generated by using the P-field simulation algorithm, utilising the local histograms of TPH grade for each grid cell. The set of simulated TPH values allows several calculations to be performed, such as average values, local uncertainties and the probability of the TPH grade of the soil exceeding a specific threshold value.     

Climate change effect on outdoor ambiences in Iranian cities

In present research work the effect of climate change over the humidex in Iran is analyzed. From this research, we can conclude that the PD_IAQ index showed a special sensibility to changes in temperature and relative humidity, hence, it can be an interesting tool, may be even better than the humidex to show the expected effect of climate change in perception of air quality. Thus, it was found that the humidex expected in the future will be more elevated than that in the preceding period and, on the other hand, the PD_WRC has clearly reached a lower value than in the preceding period. The same effects, other than those using the earlier indexes in a more detailed manner, were observed with the PD_IAQ. This index showed a higher sensitivity to variations in temperature and relative humidity, than the humidex. Finally, the main results obtained must be considered at the time of design and during construction of future buildings, since buildings that are being constructed today will be occupied in the future years of the 2100s.     

Seasonal baseline of nutrients and stable isotopes in a saline lake of Argentina: biogeochemical processes and river runoff effects

The seasonal variability of inorganic and organic nutrients and stable isotopes and their relations with plankton and environmental conditions were monitored in Lake Chasicó. Principal component analysis evidenced the strong influence of the river runoff on several biogeochemical variables. Silicate concentrations were controlled by diatom biomass and river discharge. Higher values of nitrate and soluble reactive phosphorus (SRP) indicated agricultural uses in the river basin. Elevated pH values (～9) inhibiting nitrification in the lake explained partially the dominance of ammonium: ～83 % of dissolved inorganic nitrogen (DIN). The low DIN/SRP ratio inferred nitrogen limitation, although the hypotheses of iron and CO₂ limitation are relevant in alkaline lakes. Particulate organic matter (POM) and dissolved organic matter (DOM) were mainly of autochthonous origin. The main allochthonous input was imported by the river as POM owning to the arid conditions. Dissolved organic carbon was likely top-down regulated by the bacterioplankton grazer Brachionus plicatilis. The δ¹³C signature was a good indicator of primary production and its values were influenced probably by CO₂ limitation. The δ¹⁵N did not evidence nitrogen fixation and suggested the effects of anthropogenic activities. The preservation of a good water quality in the lake is crucial for resource management.     

A methodology to identify representative configurations of sensors for monitoring soil moisture

Soil moisture is the key link among hydroecological compartments, responding dynamically to sequences of atmospheric processes and management conditions and modulating physical, chemical, and biological processes in the soil. Currently, there are a variety of monitoring techniques to measure, directly or indirectly, the soil moisture. However, some practical issues remain open like the definition a priori of the number, location and depth of the monitoring points, and the impact of failing or poor performance soil moisture sensors. Here, we present a set of techniques, namely Δθ time series, wavelet filtering, and time stability, to identify representative points and monitoring depths through an analysis of hourly soil moisture time series for different configuration of the monitoring network. We used real data from a monitoring network consisting of seven monitoring points, each one with four EC-5 probes (Decagon Devices Inc., Pullman, WA) at 20, 40, 60, and 100?cm. The use of simple time series of Δθ allowed us to assess the spatiotemporal influence of the monitoring points, while the wavelet periodograms allowed us to get insight about the response of the monitoring points at different time scales. Both methods are easy to implement or adapt to specific conditions, being coherent to the results derived from time stability analysis. For our case study, we concluded that we could reallocate 16 sensors (out of 28) without a significant loss of information. However, the final decision strongly relies on a deep knowledge of the site features and the objectives of the monitoring network.