Triclosan affects the microbial community in simulated sewage-drain-field soil and slows down xenobiotic degradation

Effects of the common antibacterial agent triclosan on microbial communities and degradation of domestic xenobiotics were studied in simulated sewage-drain-field soil. Cultivable microbial populations decreased 22-fold in the presence of 4 mg kg⁻¹ of triclosan, and triclosan-resistant Pseudomonas strains were strongly enriched. Exposure to triclosan also changed the general metabolic profile (Ecoplate substrate profiling) and the general profile (T-RFLP) of the microbial community. Triclosan degradation was slow at all concentrations tested (0.33-81 mg kg⁻¹) during 50-days of incubation. Mineralization experiments (¹⁴C-tracers) and chemical analyses (LC-MS/MS) showed that the persistence of a linear alkylbenzene sulfonate (LAS) and a common analgesic (ibuprofen) increased with increasing triclosan concentrations (0.16-100 mg kg⁻¹). The largest effect was seen for LAS mineralization which was severely reduced by 0.16 mg kg⁻¹ of triclosan. Our findings indicate that environmentally realistic concentrations of triclosan may affect the efficiency of biodegradation in percolation systems.     

Sperm competition and sexual selection: a meta-analysis of paternity studies of birds

Sperm competition (the competition among the sperm of different males for fertilization of the eggs of a female) has been suggested to be an important component of sexual selection, but no general assessment has been made of this proposition. We used a meta-analytic approach to assess the extensive literature on paternity (the proportion of offspring in a focal nest sired by an attending male) in birds based on allozyme and molecular techniques. The relative variance in male mating success was on average increased by a factor of 4.6 over the variance in apparent male success. Males with more extravagant secondary sexual characters had higher paternity in their own nests than less adorned males. There was a weak effect of male age being positively associated with paternity in own nests. Male body size measured as the length of wing and tarsus was weakly positively associated with paternity in own nests. Male survival prospect was positively associated with paternity in own nests. Polygynous males generally had decreased paternity of their broods compared to monogamous males. Paternity of the resident male decreased with increasing population density and breeding asynchrony. The intensity of paternity guards such as within-pair copulation rate and mate guarding were not significantly related to extra-pair paternity. Sperm competition was thus an important component of sexual selection by increasing the variance in male mating success, and by being associated with the expression of secondary sexual characters, in particular in dense and asynchronously breeding populations of birds. Received: 12 February 1998 / Accepted after revision: 31 May 1998     

Software sensor design based on empirical data

Software sensor design consists of building an estimate of some quantity of interest. This estimate can be used either to replace a physical measurement, or to validate an existing one. This paper provides some general guidelines for the design of software sensors based on empirical data. When the model is a priori unknown, the problem can be stated in terms of non-parametric regression or black-box modelling. Complexity control is the main difficulty in this setting. A trade-off must be achieved between two antagonist goals: the model should not be too simple, and model identification should not be too variable. We propose to address this issue by a penalization algorithm, which also estimates the relevance of input features in the identification process. A data-driven software sensor should also provide accuracy and validity indexes of its prediction. We show how these indexes can be estimated for complex non-parametric methods, such as neural networks. An application in environmental monitoring, the design of an ammonia software sensor, illustrates each step of the approach.     

Modeling the Effect of Liming on Calcium Concentration in Swedish Lakes

To abate the severe acidification of Swedish lakes are about 7% directly limed (AL-lakes). These are important to include when assessing acidification. Consequently, we need to estimate their chemical status as if they were not lime-affected. We hypothesize that there is a spatial dependence for calcium (Ca) and magnesium (Mg) concentrations. Spatial variation is determined using variograms. We study lakes within two 150 ∗ 150 km quadrates (EMEP150-grid) in the middle and southern parts of Sweden. We model Ca in AL-lakes using the Ca and Mg concentrations in nearby, unaffected lakes (UL-lakes). The mean Ca/Mg for the three or seven closest UL-lakes is used. We assume that Ca/Mg is constant for UL-lakes and that Mg unaltered by liming. For UL-lakes, Ca and Mg are spatially dependent. For AL-lakes, there is a spatial dependence for Mg, but, as anticipated, not for Ca. The modeled Ca for UL-lakes show a good correspondence with measured Ca; r ² > 0.6; slopes close to 1 and intercepts almost 0. Using three or seven nearby lakes when modeling Ca give similar results. Modeled Ca was higher than measured Ca for 36% (three closest lakes) and 38% (seven closest) of the modeled AL-lakes in the middle part of Sweden. The corresponding results for the southern part were 10% and 9%, respectively. This model is an acceptable estimator of Ca in limed lakes and for estimating critical loads and acidification status on an EMEP-scale.     

Dynamics of de novo vitellogenesis in fish with indeterminate fecundity: an application of oocyte packing density theory to European anchovy, <Emphasis Type="Italic">Engraulis encrasicolus</Emphasis>

De novo vitellogenesis is common among teleosts; however, its dynamics and the timing of batch recruitment are poorly understood. In this study, we combine a suite of methods and theories in fish reproductive biology (oocyte packing density, stereology, ovarian allometry, oocyte size frequencies and postovulatory follicle [POF] ageing) to reconstruct the steps and timing of batch recruitment in European anchovy. Using general linear modelling to standardize oocyte numbers, we demonstrate that the fractions of primary growth, cortical alveoli and vitellogenic oocytes in the ovary are relatively stable in females with migratory nucleus oocytes (MN) or with POFs 1 and 2 days old (POF-1 and POF-2), but they change abruptly at hydration. These results imply that batch recruitment in European anchovy occurs in pulses of very short duration (less than a day). The standing crop of vitellogenic oocytes in MN, POF-1 and POF-2 females equals the number of eggs contained in two mature batches.     

New approaches to modelling fish-habitat relationships

Ecologists often develop models that describe the relationship between faunal communities and their habitat. Coral reef fishes have been the focus of numerous such studies, which have used a wide range of statistical tools to answer an equally wide range of questions. Here, we apply a series of both conventional statistical techniques (linear and generalized additive regression models) and novel machine-learning techniques (the support vector machine and three ensemble techniques used with regression trees) to predict fish species richness, biomass, and diversity from a range of habitat variables. We compare the techniques in terms of their predictive performance, and we compare a subset of the models in terms of the influence each habitat variable has for the predictions. Prediction errors are estimated by cross-validation, and variable importance is assessed using permutations of individual variable values. For predictions of species richness and diversity the tree-based models generally and the random forest model specifically are superior (produce the lowest errors). These model types are all able to model both nonlinear and interaction effects. The linear model, unable to model either effect type, performs the worst (produces the highest errors). For predictions of biomass, the generalized additive model is superior, and the support vector machine performs the worst. Depth range, the difference between maximum and minimum water depth at a given site, is identified as the most important variable in the majority of models predicting the three fish community variables. However, variable importance is highly dependent upon model type, which leads to questions regarding the interpretation of variable importance and its proper use as an indicator of causality. The representation of ecological relationships by tree-based ensemble learners will improve predictive performance, and provide a new avenue for exploring ecological relationships, both statistical and causal.     

Watershed land use effects on lake water quality in Denmark

Mitigating nutrient losses from anthropogenic nonpoint sources is today of particular importance for improving the water quality of numerous freshwater lakes worldwide. Several empirical relationships between land use and in-lake water quality variables have been developed, but they are often weak, which can in part be attributed to lack of detailed information about land use activities or point sources. We examined a comprehensive data set comprising land use data, point-source information, and in-lake water quality for 414 Danish lakes. By excluding point-source-influenced lakes (n = 210), the strength in relationship (R2) between in-lake total nitrogen (TN) and total phosphorus (TP) concentrations and the proportion of agricultural land use in the watershed increased markedly, from 10-12% to 39-42% for deep lakes and from 10-12% to 21-23% for shallow lakes, with the highest increase for TN. Relationships between TP and agricultural land use were even stronger for lakes with rivers in their watershed (55%) compared to lakes without (28%), indicating that rivers mediate a stronger linkage between landscape activity and lake water quality by providing a "delivery" mechanism for excess nutrients in the watershed. When examining the effect of different near-freshwater land zones in contrast to the entire watershed, relationships generally improved with size of zone (25, 50, 100, 200, and 400 m from the edge of lake and streams) but were by far strongest using the entire watershed. The proportion of agricultural land use in the entire watershed was best in explaining lake water quality, both relative to estimated nutrient surplus at agricultural field level and near-lake land use, which somewhat contrasts typical strategies of management policies that mainly target agricultural nutrient applications and implementation of near-water buffer zones. This study suggests that transport mechanisms within the whole catchment are important for the nutrient export to lakes. Hence, the whole watershed should be considered when managing nutrient loadings to lakes, and future policies should ideally target measures that reduce the proportion of cultivated land in the watershed to successfully improve lake water quality.     

Understanding knowledge hiding in organizations

In our introduction to this special issue on understanding knowledge hiding in organizations, we provide some context to how and why this phenomenon should be studied. We then describe the five articles that comprise the special issue, and we note some common themes and divergences in this collection. Our introduction concludes with some suggestions for future research on knowledge hiding in organizations.