Fourth-corner correlation is a score test statistic in a log-linear trait–environment model that is useful in permutation testing

Ecologists wish to understand the role of traits of species in determining where each species occurs in the environment. For this, they wish to detect associations between species traits and environmental variables from three data tables, species count data from sites with associated environmental data and species trait data from data bases. These three tables leave a missing part, the fourth-corner. The fourth-corner correlations between quantitative traits and environmental variables, heuristically proposed 20 years ago, fill this corner. Generalized linear (mixed) models have been proposed more recently as a model-based alternative. This paper shows that the squared fourth-corner correlation times the total count is precisely the score test statistic for testing the linear-by-linear interaction in a Poisson log-linear model that also contains species and sites as main effects. For multiple traits and environmental variables, the score test statistic is proportional to the total inertia of a doubly constrained correspondence analysis. When the count data are over-dispersed compared to the Poisson or when there are other deviations from the model such as unobserved traits or environmental variables that interact with the observed ones, the score test statistic does not have the usual chi-square distribution. For these types of deviations, row- and column-based permutation methods (and their sequential combination) are proposed to control the type I error without undue loss of power (unless no deviation is present), as illustrated in a small simulation study. The issues for valid statistical testing are illustrated using the well-known Dutch Dune Meadow data set.     

A graphical assessment and spatial clustering of the Deepwater Horizon oil spill impact on Laughing Gulls

The Deepwater Horizon oil spill occurred in the Gulf of Mexico on April 20, 2010. Considered the largest accidental marine oil spill in history, oil flowed for three months and approximately five million barrels of oil spilled through by mid-July 2010. In this article, we analyze bird data to assess the impact of the oil spill on the Gulf wildlife. Particularly, we want to determine in which regions Laughing Gulls were mostly affected by the oil spill, and whether those regions spatially shifted throughout the year 2010. Though our data sets have some limitations to apply statistical analysis methods, we obtained very interesting results. Our analyses showed the general consistency of the results based on two population data sets (from the 2011 Data Expo and from the eBird community) and justified the use of both publicly available data sets. We showed that the closer the surface oil spill area approached to the Laughing Gulls habitats, the more significant clusters of bird cases were observed.     

Estimation bias under model selection for distance sampling detection functions

Many simulation studies have examined the properties of distance sampling estimators of wildlife population size. When assumptions hold, if distances are generated from a detection model and fitted using the same model, they are known to perform well. However, in practice, the true model is unknown. Therefore, standard practice includes model selection, typically using model comparison tools like Akaike Information Criterion. Here we examine the performance of standard distance sampling estimators under model selection. We compare line and point transect estimators with distances simulated from two detection functions, hazard-rate and exponential power series (EPS), over a range of sample sizes. To mimic the real-world context where the true model may not be part of the candidate set, EPS models were not included as candidates, except for the half-normal parameterization. We found median bias depended on sample size (being asymptotically unbiased) and on the form of the true detection function: negative bias (up to 15% for line transects and 30% for point transects) when the shoulder of maximum detectability was narrow, and positive bias (up to 10% for line transects and 15% for point transects) when it was wide. Generating unbiased simulations requires careful choice of detection function or very large datasets. Practitioners should collect data that result in detection functions with a shoulder similar to a half-normal and use the monotonicity constraint. Narrow-shouldered detection functions can be avoided through good field procedures and those with wide shoulder are unlikely to occur, due to heterogeneity in detectability.     

Experimental assessment of characteristic turbulent scales in two-phase flow of hydraulic jump: from bottom to free surface

A hydraulic jump is a turbulent shear flow with a free-surface roller. The turbulent flow pattern is characterised by the development of instantaneous three-dimensional turbulent structures throughout the air–water column up to the free surface. The length and time scales of the turbulent structures are key information to describe the turbulent processes, which is of significant importance for the improvement of numerical models and physical measurement techniques. However, few physical data are available so far due to the complexity of the measurement. This paper presents an investigation of a series of characteristic turbulent scales for hydraulic jumps, covering the length and time scales of turbulent flow structures in bubbly flow, on free surface and at the impingement point. The bubbly-flow turbulent scales are obtained for Fr = 7.5 with 3.4 × 10⁴ < Re < 1.4 × 10⁵ in both longitudinal and transverse directions, and are compared with the free-surface scales. The results highlight three-dimensional flow patterns with anisotropic turbulence field. The turbulent structures are observed with different length and time scales respectively in the shear flow region and free-surface recirculation region. The bubbly structures next to the roller surface and the free-surface fluctuation structures show comparable length and time scales, both larger than the scales of vortical structures in the shear flow and smaller than the scales of impingement perimeter at the jump toe. A decomposition of physical signals indicates that the large turbulent scales are related to the unsteady motion of the flow in the upper part of the roller, while the high-frequency velocity turbulence dominates in the lower part of the roller. Scale effects cannot be ignored for Reynolds number smaller than 4 × 10⁴, mainly linked to the formation of large eddies in the shear layer. The present study provides a comprehensive assessment of turbulent scales in hydraulic jump, including the analyses of first data set of longitudinal bubbly-flow integral scales and transverse jump toe perimeter integral scales.     

A mathematical model for type II profile of concentration distribution in turbulent flows

This paper presents a mathematical model to investigate type II profile of suspension concentration distribution (i.e., the concentration profile where the maximum concentration appears at some distance above the bed surface) in a steady, uniform turbulent flow through open-channels. Starting from the mass and momentum conservation equations of two-phase flow, a theoretical model has been derived. The distribution equation is derived considering the effects of fluid lift force, drag force, particle inertia, particle–particle interactions, particle velocity fluctuations and drift diffusion. The equation is solved numerically and is compared with available experimental data as well as with other models existing in the literature. Good agreement between the observed value and computed result, and minimum error in comparison to other models indicate that the present model can be applied in predicting particle concentration distribution for type II profile for a wide range of flow conditions. The proposed model is also able to show the transition from type I profile to type II profile.     

Comparison of analytical descriptions of nocturnal low-level jets within the Ekman model framework

This study focuses on the inertial oscillation aspect of the nocturnal low-level jet (NLLJ). In the context of the Ekman model solutions, conceptual NLLJ inertial oscillation analytical frameworks proposed by Blackadar in 1957 and Shapiro and Fedorovich and van de Wiel et al. in 2010 are compared. Considering a NLLJ produced via direct numerical simulation over flat terrain with no baroclinic influence as a reference case, the deficiencies of each framework in representing a realistic NLLJ are assessed. The Blackadar theory results in unrealistic wind profiles near the surface. While extensions of Blackadar’s framework by Shapiro and Fedorovich and van de Wiel et al. produce more realistic NLLJs, the simpler approach taken by van de Wiel et al. does not describe the NLLJ wind hodograph at later times sufficiently in qualitative terms.     

Efficacy of woody biomass and biochar for alleviating heavy metal bioavailability in serpentine soil

Crops grown in metal-rich serpentine soils are vulnerable to phytotoxicity. In this study, Gliricidia sepium (Jacq.) biomass and woody biochar were examined as amendments on heavy metal immobilization in a serpentine soil. Woody biochar was produced by slow pyrolysis of Gliricidia sepium (Jacq.) biomass at 300 and 500 °C. A pot experiment was conducted for 6 weeks with tomato (Lycopersicon esculentum L.) at biochar application rates of 0, 22, 55 and 110 t ha^?1. The CaCl₂ and sequential extractions were adopted to assess metal bioavailability and fractionation. Six weeks after germination, plants cultivated on the control could not survive, while all the plants were grown normally on the soils amended with biochars. The most effective treatment for metal immobilization was BC500-110 as indicated by the immobilization efficiencies for Ni, Mn and Cr that were 68, 92 and 42 %, respectively, compared to the control. Biochar produced at 500 °C and at high application rates immobilized heavy metals significantly. Improvements in plant growth in biochar-amended soil were related to decreasing in metal toxicity as a consequence of metal immobilization through strong sorption due to high surface area and functional groups.     

Characteristics of PM<Subscript>2.5</Subscript>, CO<Subscript>2</Subscript> and particle-number concentration in mass transit railway carriages in Hong Kong

Fine particulate matter (PM_2.5) levels, carbon dioxide (CO₂) levels and particle-number concentrations (PNC) were monitored in train carriages on seven routes of the mass transit railway in Hong Kong between March and May 2014, using real-time monitoring instruments. The 8-h average PM_2.5 levels in carriages on the seven routes ranged from 24.1 to 49.8 µg/m³, higher than levels in Finland and similar to those in New York, and in most cases exceeding the standard set by the World Health Organisation (25 µg/m³). The CO₂ concentration ranged from 714 to 1801 ppm on four of the routes, generally exceeding indoor air quality guidelines (1000 ppm over 8 h) and reaching levels as high as those in Beijing. PNC ranged from 1506 to 11,570 particles/cm³, lower than readings in Sydney and higher than readings in Taipei. Correlation analysis indicated that the number of passengers in a given carriage did not affect the PM_2.5 concentration or PNC in the carriage. However, a significant positive correlation (p < 0.001, R ² = 0.834) was observed between passenger numbers and CO₂ levels, with each passenger contributing approximately 7.7–9.8 ppm of CO₂. The real-time measurements of PM_2.5 and PNC varied considerably, rising when carriage doors opened on arrival at a station and when passengers inside the carriage were more active. This suggests that air pollutants outside the train and passenger movements may contribute to PM_2.5 levels and PNC. Assessment of the risk associated with PM_2.5 exposure revealed that children are most severely affected by PM_2.5 pollution, followed in order by juveniles, adults and the elderly. In addition, females were found to be more vulnerable to PM_2.5 pollution than males (p < 0.001), and different subway lines were associated with different levels of risk.     

Geochemical disturbance of soil cover in the nonferrous mining centers of the Selenga River basin

The anthropogenic geochemical transformation of soil cover in large nonferrous mining centers of the Selenga River basin was assessed. The results of the geochemical survey of 2010–2012 revealed the spatial distribution patterns and abundances of 18 hazardous heavy metals and metalloids in the soils of Erdenet (Mongolia) and Zakamensk (Buryat republic, Russian Federation). In both cities, mining activities disturbed soil cover which accumulates Mo, Cu, As, Sb, W in Erdenet and Bi, W, Cd, Be, Pb, Mo, Sb in Zakamensk. Maximum accumulation of elements in Erdenet is restricted to the industrial zone. In Zakamensk, it has spread on ½ of the territory with the degree of multielemental pollution exceeding the extremely dangerous level by 16 times. The effect of mining centers on the state of the river system is local and does not spread to the Selenga River. Downstream from Erdenet, an artificial pool intercepts heavy metal and metalloid flows of the Erdenetii-Gol River. By contrast, downstream from the tailing dumps of the Dzhida tungsten–molybdenum plant the concentrations of ore elements W and Mo and their accessories Bi and Cd in the Modonkul River exceed background values by 146, 20, 57, and 21 times, respectively, decreasing by an order of magnitude 30 km downstream.     

Atrazine contamination in agricultural soils from the Yangtze River Delta of China and associated health risks

Atrazine is one of the most widely applied and persistent herbicides in the world. In view of limited information on the regional contamination of atrazine in soils in China, this study investigated the spatial distribution and environmental impacts of atrazine in agricultural soils collected from the Yangtze River Delta (YRD) as an illustrative analysis of rapidly developing regions in the country. The results showed that the concentrations of atrazine in the YRD agricultural soils ranged from <1.0 to 113 ng/g dry weight, with a mean of 5.7 ng/g, and a detection rate of 57.7 % in soils. Pesticide factory might be a major source for the elevated levels of atrazine in Zhejiang Province. The contamination of atrazine was closely associated with land use types. The concentrations and detection rates of atrazine were higher in corn fields and mulberry fields than in rice paddy fields. There was no significant difference in compositions of soil microbial phospholipids fatty acids among the areas with different atrazine levels. Positive relationship (R = 0.417, p < 0.05, n = 30) was observed between atrazine and total microbial biomass. However, other factors, such as soil type and land management practice, might have stronger influences on soil microbial communities. Human health risks via exposure to atrazine in soils were estimated according to the methods recommended by the US EPA. Atrazine by itself in all the soil samples imposed very low carcinogenic risks (<10^?6) and minimal non-cancer risks (hazard index <1) to adults and children.