Ornaments and condition: plumage patch sizes,nutritional reserve state,reserve accumulation,and reserve depletion

Behavioral Ecology and Sociobiology - Cooperation plays a crucial role in primate social life. However, the evolution of large-scale human cooperation from the cognitive fundamentals found in other...     

Sampling for weed spatial distribution mapping need not be adaptive

Weeds are species of interest for ecologists because they are competitors of the crop for resources but they also play an important role in maintaining biodiversity in agroecosystems. To study their spatial distribution at the field scale, only sampled observations are available due to the cost of sampling. Weeds sampling strategies are static. However, in the domain of spatial sampling, adaptive strategies have also been developed with, for some of them, an important on-line or off-line computational cost. In this article we provide answers to the following question: Are the current adaptive sampling methods efficient enough to motivate a wider use in practice when sampling a weed species at a field scale? We provide a comparison of the behaviour of 8 static strategies and 3 adaptive ones on four criteria: density class estimation, map restoration, spatial aggregation estimation, and sampling duration. From two weeds data sets, we estimated six contrasted Markov Random Field (MRF) models of weed density class spatial distribution and a model for sampling duration. The MRF models were then used to compare the strategies on a large set of simulated maps. Our main finding was that there is no clear gain in using adaptive sampling strategies rather than static ones for the three first criteria, and adaptive strategies were associated to longer sampling duration. This conclusion points out that for weed mapping, it is more important to build a good model of spatial distribution, than to propose complex adaptive sampling strategies.     

Fine-scale flower-visiting behavior revealed by using a high-speed camera

Most estimations of the pollination efficiency of insects have been based on observation by the naked human eye. However, insect behaviors are often too rapid to analyze sufficiently this way. Here we demonstrate the use of high-speed cameras to analyze the fine-scale behaviors of Macroglossum pyrrhosticta, Xylocopa appendiculata, and Papilio dehaanii when visiting Clerodendrum trichotomum. The fine-scale nectar drinking time, number of contacts with anthers and/or stigmas, and frequencies of body part contact with anthers and/or stigmas differed significantly among pollinator species. Pollination efficiency was not equal among pollinators. In addition, M. pyrrhosticta made the least number of contacts with anthers and/or stigmas even though it showed the highest visitation frequency. These results demonstrate that when examined from the viewpoint of rapid visitation behaviors, pollination dynamics differ among pollinator species, and flower visits and pollination rates are not equal.     

SIMCA principal component analysis of fatty acid patterns in Day-1 and Day-8 cod (Gadus morhua) and haddock (Melanogrammus aeglefinus) eggs

Single cod [Gadus Morhua (L.)] and haddock [Melanogrammus aeglefinus (L.)] eggs from the first day and the eighth day after fertilization were acid hydrolised. Fatty acids were liberated and derivatized to methyl esters in a one-step reaction. The non-polar hexane extract was analysed by High Resolution Gas Chromatography (HRGC). Selected peaks, occuring in both types of samples and in all chromatograms, were used to create a matrix for multivariate analysis. HRGC and Mass Spectrometry have been used to identify the fatty acids. The approach is shown to be useful in distinguishing between cod and haddock eggs at both stages and information regarding changes in the fatty acid distributions are obtained. Implications on future possibilities within chemosystematics are discussed.     

The performance of state-of-the-art modelling techniques depends on geographical distribution of species

We explored the effects of prevalence, latitudinal range and clumping (spatial autocorrelation) of species distribution patterns on the predictive accuracy of eight state-of-the-art modelling techniques: Generalized Linear Models (GLMs), Generalized Boosting Method (GBM), Generalized Additive Models (GAMs), Classification Tree Analysis (CTA), Artificial Neural Network (ANN), Multivariate Adaptive Regression Splines (MARS), Mixture Discriminant Analysis (MDA) and Random Forest (RF). One hundred species of Lepidoptera, selected from the Distribution Atlas of European Butterflies, and three climate variables were used to determine the bioclimatic envelope for each butterfly species. The data set consisting of 2620 grid squares 30′ × 60′ in size all over Europe was randomly split into the calibration and the evaluation data sets. The performance of different models was assessed using the area under the curve (AUC) of a receiver operating characteristic (ROC) plot. Observed differences in modelling accuracy among species were then related to the geographical attributes of the species using GAM. The modelling performance was negatively related to the latitudinal range and prevalence, whereas the effect of spatial autocorrelation on prediction accuracy depended on the modelling technique. These three geographical attributes accounted for 19–61% of the variation in the modelling accuracy. Predictive accuracy of GAM, GLM and MDA was highly influenced by the three geographical attributes, whereas RF, ANN and GBM were moderately, and MARS and CTA only slightly affected. The contrasting effects of geographical distribution of species on predictive performance of different modelling techniques represent one source of uncertainty in species spatial distribution models. This should be taken into account in biogeographical modelling studies and assessments of climate change impacts.     

Trace metal speciation and fluxes within a major French wastewater treatment plant: impact of the successive treatments stages

Seven metals (Cd, Co, Cr, Cu, Fe, Ni and Pb) were monitored at the Seine-Aval wastewater treatment plant during 6 sampling campaigns in April 2004. Particulate and dissolved metals have been measured in 24 h composite samples at each treatment stage (primary settling, secondary activated sludge and tertiary flocculation by FeCl₃). In addition, the diffusive gradient in thin film technique (DGT) was used to determine the dissolved inert and labile metal fraction. Although all treatment stages were able to decrease particulate metals concentrations in wastewater, most dissolved metals concentrations were mainly affected during primary settling. This unexpected result was attributed to tertiary sludge filtrate recirculation. Metals added via the FeCl₃ reagent at the tertiary treatment were shown to lower the overall Cr removal from wastewater and to enrich Ni in effluents. The plant operating conditions (recirculation and reagent addition) appear therefore as important as treatment processes for the metals removal. Total metal fluxes were highly decreased by the whole treatment plant for Cd, Cr, Cu and Pb and to a lesser extend for Co and Ni. However, the labile metal fluxes were poorly decreased for Cu (18%), not significantly decreased for Ni and increased for Fe. The labile fraction of Cd, Co and Cr was not detectable at any stage of the plant. Discharged labile fluxes, at least for Ni, were potentially significant compared to the labile metal fluxes in the river measured downstream the plant. Treated urban wastewater discharges should be carefully considered as a possible source of bioavailable trace metals.     

Effect of textile auxiliaries on the biodegradation of dyehouse effluent in activated sludge

The textile industry is confronted with serious environmental problems associated with its immense wastewater discharge, substantial pollution load, extremely high salinity, and alkaline, heavily coloured effluent. Particular sources of recalcitrance and toxicity in dyehouse effluent are two frequently used textile auxiliaries; i.e. dye carriers and biocidal finishing agents. The present experimental work reports the observation of scientific and practical significance related with the effect of two commercially important textile dye carriers and two biocidal finishing agents on biological activated sludge treatment at a textile preparation, dyeing and finishing plant in Istanbul. Respirometric measurements of the dyehouse effluent spiked with the selected textile chemicals were carried out for the assessment of the "readily biodegradable COD fraction" of the wastewater. The respirometric data obtained to visualize the effect of the selected textile auxiliaries on biomass activity was evaluated by an adopted activated sludge model. Results have indicated that the tested biocides did not exert any significant inhibitory effect on the treatment performance of the activated sludge reactor at the concentrations usually encountered in the final, total dyehouse effluent. The situation with the dye carriers was inherently different; one dye carrier appeared to be highly toxic and caused serious inhibition of the microbial respirometric activity, whereas the other dye carrier, also known as the more ecological alternative, i.e. the "Eco-Carrier", appeared to be biodegradable. Finally, the respirometric profile obtained for the Eco-Carrier was described by a simplified respirometric model.