Evaluation of water quality in the Ouémé River (Bénin)

Water is an essential element for humankind, animals, and plants. It is also an important element of the aquatic environment (the natural habitat of multiple species), where its quality plays a determining role in their protection and conservation. Unfortunately, the water quality of natural environments has worsened in the last decades. In sub-Saharan Africa and particularly in Bénin, in contrast to river discharges, monitoring the quality of surface water is a very rare activity. Thus, knowledge about physical and chemical properties as a basis for evaluation of the state of the environment and protection measures needed is almost absent. This article presents the results of the first structured, regular monitoring campaign on surface waters in the whole basin of the Ouémé River in Bénin Republic. With 510 km, the Ouémé River’s water quality fluctuates from upstream (Taneka Koko mountains in the north) to downstream (gauging station Bonou in the south) sources. This is due to soil erosion, lack of water treatment plants, and the use of significant quantities of fertilizer in the cotton zone. The present research was initiated to study the resource degradation of this area through chemical and physical water analysis. The monitoring of water quality has been followed for 5 years on twenty physicochemical parameters, from samples taken at four gauging stations on the main channel of the Ouémé River. Means and standard deviations of water analysis results were compared to both the recommendations of the World Health Organization (WHO) and the Maximum Permissible Concentrations (MPC) for drinking water (WHO 1987). Thus, high values were observed for physical parameters, i.e., color and turbidity had peaks of 697.5 uC and 129 FTU at Bétérou station in the wet season, although certain parameters, such as total hardness, present low values compared to the recommended standards. Moreover, excluding the concentrations of NO₂ ⁻ and NH₄ ⁺ with values above the MPC, nutrient concentrations posed no direct risk for human consumption. However, together with phosphate concentrations (which are up to ten times higher than permissible ecological thresholds), they can cause eutrophication of the aquatic ecosystem. Due to the current flow regime, which has very low discharge rates in the dry season and torrential rainfall and high sediment loads in the wet season, the risk of eutrophication, i.e., excessive concentrations of ammonium and phosphates, is present throughout the year. Accumulation of ammonium and the distribution of nitrate and nitrites in the river water suggest that nitrification is impeded due to a lack of oxygen in both dry and wet seasons. Finally, the investigations show that the risk of water pollution exists and it is necessary to take measures of sanitation and water treatment to prevent the further degradation of water along the Ouémé River.     

Air pollution below WHO levels decreases by 40 % the links of terrestrial microbial networks

Air pollution has a deleterious impact on public health and the environment. There is few knowledge on the effect of air pollution on terrestrial microbial communities, despite the major role of microbes in ecosystems. Here, we designed an in situ trial ecosystem to assess the impact of moderate atmospheric pollution, below World Health Organization (WHO) thresholds, on an indigenous microbial communities, including bacteria, fungi, ciliates, algae, cyanobacteria, testate amoebae, rotifers and nematodes, extracted from terrestrial bryophytes. These micro-ecosystems were placed at a rural, an urban and an industrial site in France and were thus exposed to various levels of nitrogen dioxide (NO₂), from 6.6–67.9 μg·m^?3, and particulate matter, from 0.7–7.9 μg·m^?3. Microbial analysis was performed by microscopy. We determined atmospheric temperature, relative humidity and particulate matter with diameter lower than 10 µm (PM₁₀), Cu, Cr, Fe, Ni, Pb, Zn in PM₁₀, and (NO₂). Results show a significant impact of chronic moderate exposure to NO₂ and copper Cu-associated particulate matter on the global microbial network complexity. This is evidenced by a loss of about 40 % of microbial co-occurrence links during incubation. Most lost microbial links are ecologically positive links. Moreover, most changes in community co-occurrence networks are related to testate amoebae, a major top predator of microbes. Overall, our findings demonstrate that air pollution can have strong deleterious effects on microbial interactions, even at levels below WHO thresholds.     

Ecological relevance of performance criteria for species distribution models

Species distribution models have often been developed based on ecological data. To develop reliable data-driven models, however, a sound model training and evaluation procedures are needed. A crucial step in these procedures is the assessment of the model performance, with as key component the applied performance criterion. Therefore, we reviewed seven performance criteria commonly applied in presence-absence modelling (the correctly classified instances, Kappa, sensitivity, specificity, the normalised mutual information statistic, the true skill statistic and the odds ratio) and analysed their application in both the model training and evaluation process. Although estimates of predictive performance have been used widely to assess final model quality, a systematic overview was missing because most analyses of performance criteria have been empirical and only focused on specific aspects of the performance criteria. This paper provides such an overview showing that different performance criteria evaluate a model differently and that this difference may be explained by the dependency of these criteria on the prevalence of the validation set. We showed theoretically that these prevalence effects only occur if the data are inseparable by an n-dimensional hyperplane, n being the number of input variables. Given this inseparability, different performance criteria focus on different aspects of model performance during model training, such as sensitivity, specificity or predictive accuracy. These findings have important consequences for ecological modelling because ecological data are mostly inseparable due to data noise and the complexity of the studied system. Consequently, it should be very clear which aspect of the model performance is evaluated, and models should be evaluated consistently, that is, independent of, or taking into account, species prevalence. The practical implications of these findings are clear. They provide further insight into the evaluation of ecological presence/absence models and attempt to assist modellers in their choice of suitable performance criteria.     

Coregionalization analysis with a drift for multi-scale assessment of spatial relationships between ecological variables 1. Estimation of drift and random components

In two articles, we present ‘coregionalization analysis with a drift’ (CRAD), a method to assess the multi-scale variability of and relationships between ecological variables from a multivariate spatial data set. In phase I of CRAD (the first article), a deterministic drift component representing the large-scale pattern and a random component modeled as a second-order stationary process are estimated for each variable separately. In phase II (this article), a linear model of coregionalization (LMC) is fitted by estimated generalized least squares to the direct and cross experimental variograms of residuals (i.e., after the removal of estimated drifts). Structural correlations and coefficients of determination at smaller scales are then computed from the estimated coregionalization matrices, while the estimated drifts are used to calculate pseudo coefficients at large scale. The performance of five procedures in estimating correlations and coefficients of determination was compared using a Monte Carlo study. In four CRAD procedures, drift estimation was based on local polynomials of order 0, 1, 2 (L₀, L₁, L₂) or a global polynomial with forward selection of the basis functions; the fifth procedure was coregionalization analysis (CRA), in which large-scale patterns were modeled as a supplemental component in the LMC. In bivariate and multivariate analyses, the uncertainty in the estimation of correlations and coefficients of determination could be related to the interference between spatial components within a bounded sampling domain. In the bivariate case, most procedures provided acceptable estimates of correlations. In regionalized redundancy analysis, uncertainty was highest for CRA, while L₁ provided the best results overall. In a forest ecology example, the identification of scale-specific correlations between plant species diversity and soil and topographical variables illustrated the potential of CRAD to provide unique insight into the functioning of complex ecosystems.     

Ethical obligations of veterinarians and animal scientists in animal agriculture

It is patent that society is evolving an ethic for the treatment of animals which goes well beyond the standard prohibitions against cruelty. This new ethic for animals takes the consensus ethic for the treatment of humans in society and extends it,mutatis mutandis, to the treatment of animals. Though this ethic has been applied first to research animals, its extension to agricultural animals is inevitable, and has already begun. This article explores the extent to which veterinary medicine and animal science, the major scientific fields relevant to animal agriculture, can accommodate the emerging ethic.     

Relevance of organic matter fractions as predictors of wastewater sludge mineralization in soil

Seventeen different wastewater sludges were characterized using both chemical and organic matter fractionation methods (water extraction, Van Soest method, and acid hydrolysis) and 6-mo incubation studies to assess their decomposition in soil. Simple correlation and multiple factor analysis (MFA) were then performed to establish relationships between composition and C and N mineralization of sludges. Carbon and N concentrations covered a wide range of values, but organic carbon (C(o)) to organic nitrogen (N(o)) ratios were relatively low (from 5 to 19). Carbon and N were mainly distributed in the most soluble fractions of the Van Soest method and in the water-insoluble fraction at 100 degrees C. Carbon mineralization varied from 180 to 661 g C kg(-1) organic C added during the 168-d incubation. The addition of sludges led to different inorganic N dynamics: from -3.3 to +120.0 g N kg(-1) sludge organic C mineralized after the 168-d incubation. Fractionation studies showed that the most discriminating method was acid hydrolysis. Carbon mineralization was linked with the proportion of sludge N and C present in the lignin-like fraction (r = -0.68 and -0.65, respectively). Significant relationships were established between N mineralization and N(o) to C(o) ratio (0.88 < r < 0.95) and the C(o) to N(o) ratio of sludges, the C to N ratio of the soluble fraction obtained by the Van Soest method, the water-soluble fraction at 100 degrees C, and the C and N present in the acid-hydrolyzable fraction. Finally, multiple factor analysis also enabled establishing a sludge typology using five clusters based on composition and mineralization characteristics.     

Prevalence-adjusted optimisation of fuzzy models for species distribution

Most performance criteria which have been applied to train ecological models focus on the accuracy of the model predictions. However, these criteria depend on the prevalence of the training set and often do not take into account ecological issues such as the distinction between omission and commission errors. Moreover, a previous study indicated that model training based on different performance criteria results in different optimised models. Therefore, model developers should train models based on different performance criteria and select the most appropriate model depending on the modelling objective. This paper presents a new approach to train fuzzy models based on an adjustable performance criterion, called the adjusted average deviation (aAD). This criterion was applied to develop a species distribution model for spawning grayling in the Aare River near Thun, Switzerland. To analyse the strengths and weaknesses of this approach, it was compared to model training based on other performance criteria. The results suggest that model training based on accuracy-based performance criteria may produce unrealistic models at extreme prevalences of the training set, whereas the aAD allows for the identification of more accurate and more reliable models. Moreover, the adjustable parameter in this criterion enables modellers to situate the optimised models in the search space and thus provides an indication of the ecological model relevance. Consequently, it may support modellers and river managers in the decision making process by improving model reliability and insight into the modelling process. Due to the universality and the flexibility of the approach, it could be applied to any other ecosystem or species, and may therefore be valuable to ecological modelling and ecosystem management in general.     

转基因植物和食品保障

为了以可持续方式确保世界食品保障,必须解决许多与安全性、流通及其它因素有关的问题.然而,不应当忘记,生产足够的食品是至关重要的.与食品有关的世界贸易问题(包括涉及生物技术应用的问题)应当成为各国之间和各公司之间不断对话的课题.以共同商定的风险评价程序为基础的、国际和谐的质量和安全性标准,是此类讨论的最合理依据.     

Manipulation of density and viscosity for the optimization of DNAPL recovery by alcohol flooding

Laboratory experiments demonstrate that in situ recovery of pooled tetrachloroethene (PCE) from porous media may be accomplished more efficiently using multiple-step alcohol floods than with single alcohol floods. To optimize flooding efficiency while maintaining a low risk of downward DNAPL mobilization, a three-step flooding process is developed employing an isobutanol preflood, a composite alcohol mainflood, and a polymer solution postflood. The density and viscosity of these solutions are manipulated to prevent the onset and propagation of viscous and gravitational fingers, while maintaining phase behavior critical for efficient miscible NAPL displacement. An aqueous partitioning preflood solution of 10% by volume (10% v) isobutanol reduces the NAPL density in situ to approximately 1.00 g/ml by swelling the NAPL prior to miscible displacement induced by the mainflood. The composite alcohol mainflood, containing 65% v ethylene glycol and 35% v 1-propanol maintains miscibility while achieving neutral buoyancy and near stable displacement of the NAPL. Aqueous solutions of xanthan gum polymer efficiently displace the mainflood, reducing viscous fingering associated with waterfloods. Two-dimensional experiments using the multiple-step technique achieve 99.8% DNAPL mass recovery using a total of 0.45 pore volumes of alcohol, illustrating greater recovery efficiency than previous alcohol flooding formulations under comparable conditions.