Migration of contaminants through the unsaturated zone overlying the Hesbaye chalky aquifer in Belgium: a field investigation

This paper presents the results of a detailed field investigation that was performed for studying groundwater recharge processes and solute downward migration mechanisms prevailing in the unsaturated zone overlying a chalk aquifer in Belgium. Various laboratory measurements were performed on core samples collected during the drilling of boreholes in the experimental site. In the field, experiments consisted of well logging, infiltration tests in the unsaturated zone, pumping tests in the saturated zone and tracer tests in both the saturated and unsaturated zones. Results show that gravitational flows govern groundwater recharge and solute migration mechanisms in the unsaturated zone. In the variably saturated chalk, the migration and retardation of solutes is strongly influenced by recharge conditions. Under intense injection conditions, solutes migrate at high speed along the partially saturated fissures, downward to the saturated zone. At the same time, they are temporarily retarded in the almost immobile water located in the chalk matrix. Under normal recharge conditions, fissures are inactive and solutes migrate slowly through the chalk matrix. Results also show that concentration dynamics in the saturated zone are related to fluctuations of groundwater levels in the aquifer. A conceptual model is proposed to explain the hydrodispersive behaviour of the variably saturated chalk. Finally, the vulnerability of the chalk to contamination issues occurring at the land surface is discussed.     

Seasonal distribution and contamination levels of total PHCs, PAHs and heavy metals in coastal waters of the Alang-Sosiya ship scrapping yard, Gulf of Cambay, India

Alang-Sosiya situated on the Gulf of Cambay is one of the largest ship breaking yard in the world. The seasonal distribution and contamination levels of dissolved and/or dispersed total petroleum hydrocarbons (PHCs), total polycyclic aromatic hydrocarbons (PAHs) and heavy metals in seawater during high tide are investigated. The concentrations of petroleum hydrocarbons and heavy metals are higher in the winter than in the monsoon and summer. The concentrations of total PHCs and PAHs are about three times higher in the winter and two times in the monsoon or summer at Along-Sosiya and about twice in all seasons at two stations one on either side 5 km away from it as compared to the reference station at Mahuva, 60 km away towards the south. Further, the levels of PHCs are correlated with salinity and compared with those of other regions. The concentration of all metals is the highest in the winter season followed by the monsoon and summer. We carried out the quantitative analysis of the possible relationships among 13 variables such as Al, Fe, Pb, Mn, Cu, Zn, Cd, Cr, Co, pH, NO3-, NO2 and PO4(3-).     

Quantifying the efficiency of soil sampling designs: A multivariate approach

The objective of this paper is to quantify and compare the loss functions of the standard two-stage design and its composite sample alternative in the context of multivariate soil sampling. The loss function is defined (conceptually) as the ratio of cost over information and measures design inefficiency. The efficiency of the design is the reciprocal of the loss function. The focus of this paper is twofold: (a) we define a measure of multivariate information using the Kullback–Leibler distance, and (b) we derive the variance-covariance structure for two soil sampling designs: a standard two-stage design and its composite sample counterpart. Randomness in the mass of soil samples is taken into account in both designs. A pilot study in Slovenia is used to demonstrate the calculations of the loss function and to compare the efficiency of the two designs. The results show that the composite sample design is more efficient than the two-stage design. The efficiency ratio is 1.3 for pH, 2.0 for C, 2.1 for N, and 2.5 for CEC. The multivariate efficiency ratio is 2.3. These ratios primarily reflect cost ratios; influence of the information is small.     

Efficiency of composite sampling for estimating a lognormal distribution

In many environmental studies measuring the amount of a contaminant in a sampling unit is expensive. In such cases, composite sampling is often used to reduce data collection cost. However, composite sampling is known to be beneficial for estimating the mean of a population, but not necessarily for estimating the variance or other parameters. As some applications, for example, Monte Carlo risk assessment, require an estimate of the entire distribution, and as the lognormal model is commonly used in environmental risk assessment, in this paper we investigate efficiency of composite sampling for estimating a lognormal distribution. In particular, we examine the magnitude of savings in the number of measurements over simple random sampling, and the nature of its dependence on composite size and the parameters of the distribution utilizing simulation and asymptotic calculations.     

Effect of queen quality on interactions between workers and dueling queens in honeybee (Apis mellifera L.) colonies

The fitness of a social insect colony depends greatly on the quality (i.e., mating ability, fecundity, and offspring viability) of its queen(s). In honeybees, there is marked variation in the quality of young queens that compete in a series of lethal duels to replace a colonys previous queen. Workers interact with queens during these duels and could increase their inclusive fitness by biasing the outcomes of the duels in favor of high-quality queens. We predicted that workers will have more antagonistic interactions (chasing, grabbing, clamping) and fewer beneficent interactions (feeding, grooming) with low-quality than high-quality queens. To test this prediction, we reared queens from 0-day-old, 2-day-old, and 3-day-old worker larvae in observation colonies undergoing queen replacement, thus producing high-quality, low-quality, and very low-quality queens, respectively. Immediately after each queen emerged, we observed her for 1 h to record her interactions with the workers. Subsequent morphological measurement of the queens confirmed that initial larval age had a significant effect on queen quality. However, there was no consistent effect of queen quality on the rates of worker–queen interactions, thus falsifying our hypothesis. The mean power of our tests was high (0.599), therefore the probability of a type II error (a false negative) is low. We conclude that if workers actively select high-quality queens, then they do so prior to queen duels, during queen development. We suggest that each worker–queen interaction has a distinct adaptive significance rather than forming a suite of behavior that favors particular queens (e.g., chasing repels any queen that approaches a queen cell, thus protecting all queen cells from destruction).Communicated by M. Giurfa     

Use of genetic algorithms to select input variables in decision tree models for the prediction of benthic macroinvertebrates

Predicting freshwater organisms based on machine learning is becoming more and more reliable due to the availability of appropriate datasets, advanced modelling techniques and the continuously increasing capacity of computers. A database consisting of measurements collected at 360 sampling sites in non-navigable watercourses in Flanders was applied to predict the absence/presence of benthic macroinvertebrate taxa by means of decision trees. The measured variables were a combination of physical–chemical (temperature, pH, dissolved oxygen concentration, conductivity, total organic carbon, Kjeldahl nitrogen and total phosphorus), structural (granulometric analysis of the sediment, width, depth and flow velocity of the river) and two ecotoxicological variables. The predictive power of decision trees was assessed on the basis of the number of Correctly Classified Instances (CCI). A genetic algorithm was introduced to compare the predictive power of different sets of input variables for the decision trees. The number of input variables was reduced from 15 to 2–8 variables without affecting the predictive power of the decision trees significantly. Furthermore, reducing the number of input variables allowed to ease the identification of general data trends.     

Understanding trust development in negotiations: An interdependent approach

What affects the way that trust develops in negotiations? In two studies, we used an actor–partner interdependence model to investigate how both negotiators' trust propensity prior to the negotiation and two types of behavior during the negotiation affect negotiators' trust development. Study 1 demonstrated that both focal negotiators' (actors') and their counterparts' (partners') trust propensity were positively associated with negotiators' trust development. Study 2 showed that actors' and partners' trust propensity had an indirect effect on trust development via both actors' and partners' negotiation behaviors. Negotiators' trust propensity positively affected their use of Q&A (questions and answers about interests) and negatively affected their use of S&O (substantiation about positions and single‐issue offers). Actors and partners' negotiation behaviors in turn affected their own and their partners' trust development. Our studies propose and test a model to understand how negotiators' trust propensity and negotiation behaviors affect the development of trust in negotiation. Copyright © 2016 John Wiley & Sons, Ltd.     

Climatic Controls on Watershed Reference Evapotranspiration Varied during 1961–2012 in Southern China

Reference evapotranspiration (ET_o) is an important hydrometeorological term widely used in understanding and projecting the hydrological effects of future climate and land use change. We conducted a case study in the Qinhuai River Basin that is dominated by a humid subtropical climate and mixed land uses in southern China. Long‐term (1961–2012) meteorological data were used to estimate ET_o by the FAO‐56 Penman–Monteith model. The individual contribution from each meteorological variable to the trend of ET_o was quantified. We found basin‐wide annual ET_o decreased significantly (p < 0.05) by 3.82 mm/yr during 1961–1987, due to decreased wind speed, solar radiation, vapor pressure deficit (VPD), and increased relative humidity (RH). However, due to the increased VPD and decreased RH, the ET_o increased significantly (p < 0.05) in spring, autumn, and annually at a rate of 2.55, 0.56, and 3.16 mm/yr during 1988–2012, respectively. The aerodynamic term was a dominant factor controlling ET_o variation in both two periods. We concluded the key climatic controls on ET_o have shifted as a result of global climate change during 1961–2012. The atmospheric demand, instead of air temperature alone, was a major control on ET_o. Models for accurately predicting ET_o and hydrological change under a changing climate must include VPD in the study region. The shifts of climatic control on the hydrological cycles should be considered in future water resource management in humid regions.     

Streamflow Forecasting Using Singular Value Decomposition and Support Vector Machine for the Upper Rio Grande River Basin

The current study improves streamflow forecast lead‐time by coupling climate information in a data‐driven modeling framework. The spatial–temporal correlation between streamflow and oceanic–atmospheric variability represented by sea surface temperature (SST), 500‐mbar geopotential height (Z₅₀₀), 500‐mbar specific humidity (SH₅₀₀), and 500‐mbar east–west wind (U₅₀₀) of the Pacific and the Atlantic Ocean is obtained through singular value decomposition (SVD). SVD significant regions are weighted using a nonparametric method and utilized as input in a support vector machine (SVM) framework. The Upper Rio Grande River Basin (URGRB) is selected to test the applicability of the proposed model for the period of 1965–2014. The April–August streamflow volume is forecasted using previous year climate variability, creating a lagged relationship of 1–13 months. SVD results showed the streamflow variability was better explained by SST and U₅₀₀ as compared to Z₅₀₀ and SH₅₀₀. The SVM model showed satisfactory forecasting ability with best results achieved using a one‐month lead to forecast the following four‐month period. Overall, the SVM results showed excellent predictive ability with average correlation coefficient of 0.89 and Nash–Sutcliffe efficiency of 0.79. This study contributes toward identifying new SVD significant regions and improving streamflow forecast lead‐time of the URGRB.     

Reorienting job crafting research: A hierarchical structure of job crafting concepts and integrative review

Two dominant perspectives of job crafting—the original theory from Wrzesniewski and Dutton ( 2001 ) and the job demands resources perspective from Tims, Bakker, and Derks ( 2012 )—remain separate in research. To synthesize these perspectives, we propose a three‐level hierarchical structure of job crafting, and we identify the aggregate/superordinate nature of each major job crafting construct. The first level of the structure is job crafting orientation, or approach versus avoidance crafting, which we argue is an essential yet often neglected distinction in the literature. We address the debate surrounding cognitive crafting and identify crafting form (behavioral versus cognitive crafting) as the next hierarchical level of constructs. Finally, we concur that job resources and job demands, or crafting content, capture different ways that individuals craft their jobs. Using this integrated hierarchical structure, we were able to review antecedents and outcomes from both perspectives. We show, for example, that approach crafting in its behavioral form is very similar to other proactive behaviors in the way it functions, suggesting a need for closer synthesis with the broader proactive literature, whereas avoidance crafting appears to be less proactive and often dysfunctional. On the basis of our review, we develop a road map for future research.