Abundance versus presence/absence data for modelling fish habitat preference with a genetic Takagi–Sugeno fuzzy system

This study compared the accuracy of fuzzy habitat preference models (FHPMs) and habitat preference curves (HPCs) obtained from the FHPMs in order to assess the effect of two types of data [log-transformed fish population density (LOG) and presence-absence (P/A) data] on the habitat preference evaluation of Japanese medaka (Oryzias latipes). Three independent data sets were prepared for each type of data. The results differed according to the data sets and the types of data used. The HPCs showed a similar trend, whilst the degrees of preference were different. The model accuracy also differed according to the data sets used. Although almost no statistical difference was observed, on average, the P/A-based models showed a better performance according to the threshold-independent performance measures, whilst the LOG-based models showed better performance in predicting absence of the fish. These results can be explained partly from the different shapes of HPCs. This case study of Japanese medaka demonstrated the effect of different types of data on habitat preference evaluation. Further studies should build on the present finding and evaluate the effects of data characteristics such as the size of data sets and the prevalence for better understanding and reliable assessment of the habitat for target species.     

Selecting Variables for Habitat Suitability of <Emphasis Type="Italic">Asellus</Emphasis> (Crustacea,Isopoda) by Applying Input Variable Contribution Methods to Artificial Neural Network Models

This study aimed to compare different methods to analyse the contribution of individual river characteristics to predict the abundance of Asellus (Crustacea, Isopoda). Six methods which provide the relative contribution and/or the contribution profile of the input variables of artificial neural network models were therefore compared: (1) the ‘partial derivatives’ method; (2) the ‘weights’ method; (3) the ‘perturb’ method; (4) the ‘profile’ method; (5) the ‘classical stepwise’ method; (6) the ‘improved stepwise’ method. Consequently, the key variables which affect the habitat preferences of Asellus could be identified. To evaluate the performance of the artificial neural network model, the model predictions were compared with the results of a multiple linear regression analysis. The dataset consisted of 179 samples, collected over a 3-year period in the Zwalm catchment in Flanders, Belgium. Twenty-four environmental variables as well as the log-transformed abundance of Asellus were used in this study. The different contribution methods seemed to give similar results concerning the order of importance of the input variables. Nevertheless, their diverse computation led to differences in sensitivity and stability of the methods and the derived outcomes on the habitat preferences. From an ecological point of view, the environmental variables describing the stream type (width, depth, stream order and distance to mouth) were the most significant variables for Asellus in the Zwalm catchment during the period 2000–2002 for all applied methods. Indirectly, one can conclude that the water quality is not the limiting factor for the survival of Asellus in the Zwalm catchment.     

环境中的药物——LC-MS/MS分析地表水和地下水

成百上千的活性物质正被用于人药和兽药处方中.由于药物的广泛应用,它们的残留物可通过多种途径进入环境.虽然主要通过尿和粪便的排泄,但是药品生产中的排放也应被考虑.当抗生素用于水产业,就会产生更直接的影响.污水处理设备不能完全除去药物,因此药物会出现在地表和地下水样品中.近年来,人们对环境中药物的兴趣正在增加,需要建立一种快速、灵敏、有选择性的方法来分析水样.     

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.     

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.     

Does a parthenogenesis-inducing <Emphasis Type="Italic">Wolbachia</Emphasis> induce vestigial cytoplasmic incompatibility?

Wolbachia is a maternally inherited bacterium that manipulates the reproduction of its host. Recent studies have shown that male-killing strains can induce cytoplasmic incompatibility (CI) when introgressed into a resistant host. Phylogenetic studies suggest that transitions between CI and other Wolbachia phenotypes have also occurred frequently, raising the possibility that latent CI may be widespread among Wolbachia. Here, we investigate whether a parthenogenesis-inducing Wolbachia strain can also induce CI. Parthenogenetic females of the parasitoid wasp Asobara japonica regularly produce a small number of males that may be either infected or not. Uninfected males were further obtained through removal of the Wolbachia using antibiotics and from a naturally uninfected strain. Uninfected females that had mated with infected males produced a slightly, but significantly more male-biased sex ratio than uninfected females that had mated with uninfected males. This effect was strongest in females that mated with males that had a relatively high Wolbachia titer. Quantitative PCR indicated that infected males did not show higher ratios of nuclear versus mitochondrial DNA content. Wolbachia therefore does not cause diploidization of cells in infected males. While these results are consistent with CI, other alternatives such as production of abnormal sperm by infected males cannot be completely ruled out. Overall, the effect was very small (9%), suggesting that if CI is involved it may have degenerated through the accumulation of mutations.     

Cross-sectional biomonitoring study of pesticide exposures in Queensland,Australia, using pooled urine samples

A range of pesticides are available in Australia for use in agricultural and domestic settings to control pests, including organophosphate and pyrethroid insecticides, herbicides, and insect repellents, such as N,N-diethyl-meta-toluamide (DEET). The aim of this study was to provide a cost-effective preliminary assessment of background exposure to a range of pesticides among a convenience sample of Australian residents. De-identified urine specimens stratified by age and sex were obtained from a community-based pathology laboratory and pooled (n = 24 pools of 100 specimens). Concentrations of urinary pesticide biomarkers were quantified using solid-phase extraction coupled with isotope dilution high-performance liquid chromatography–tandem mass spectrometry. Geometric mean biomarker concentrations ranged from <0.1 to 36.8 ng/mL for organophosphate insecticides, <0.1 to 5.5 ng/mL for pyrethroid insecticides, and <0.1 to 8.51 ng/mL for all other biomarkers with the exception of the DEET metabolite 3-diethylcarbamoyl benzoic acid (4.23 to 850 ng/mL). We observed no association between age and concentration for most biomarkers measured but noted a “U-shaped” trend for five organophosphate metabolites, with the highest concentrations observed in the youngest and oldest age strata, perhaps related to age-specific differences in behavior or physiology. The fact that concentrations of specific and non-specific metabolites of the organophosphate insecticide chlorpyrifos were higher than reported in USA and Canada may relate to differences in registered applications among countries. Additional biomonitoring programs of the general population and focusing on vulnerable populations would improve the exposure assessment and the monitoring of temporal exposure trends as usage patterns of pesticide products in Australia change over time.     

Strike-induced chemosensory searching is absent in the cordylid lizard,Cordylus cordylus,a scleroglossan ambush forager

Summary Strike-induced chemosensory searching (SICS) was not detected experimentally in the cordylid lizard,Cordylus cordylus. Both components of SICS, a post-strike elevation in tongue-flick rate (PETF) and searching movements for attacked and released prey, were absent. The findings are consistent with previous data showing that PETF and/or SICS are lacking in all lizard families yet studied that forage primarily by ambush, but are present in actively foraging scleroglossan families and the herbivorous iguanian family Iguanidae. It is suggested that foraging behavior is a primary determinant of the presence or absence of SICS in lizards. Nevertheless, in most families in the two major clades, Iguania and Scleroglossa, the plesiomorphic foraging mode is retained. The findings agree with the prediction that SICS is absent in families lacking lingually mediated prey chemical discrimination (PCD), presumably due to selection against movement by ambush foragers that avoid being detected by either prey or predators because they remain motionless. Although PETF and SICS were absent, labial-licking and lingual movements similar to those observed after swallowing increased after biting prey, suggesting that the functions of these lingual movements may have been related to grooming. Locomotory movements did not increase following biting and appeared to represent avoidance of the experimenter.