Nest distribution affects behaviour and mating success in a marine fish

The distribution of breeding resources, such as nest sites, can have a pronounced impact on a population by affecting the proportion of individuals that succeed to breed and hence, the variation in reproductive success. Aggregation of important resources can lead to resource monopolisation by a limited number of individuals and thus affect the intensity of sexual selection. In this study, we tested, by contrasting two experimental treatments (dispersed vs. aggregated), how nest distribution affects: (1) mating behaviour, (2) male nest occupation and mating success, and (3) reproductive success and the opportunity for selection. We used the two-spotted goby (Gobiusculus flavescens), a small marine fish with a resource-based mating system, as our model species. When nests were aggregated, a larger proportion of the males behaved aggressively, fewer males succeeded in occupying a nest, fewer males became mated, and those males that mated received fewer eggs from spawning females. These effects resulted in a higher variance in reproductive success and hence, a higher opportunity for selection (I _rs ), in the aggregated treatment. We suggest that the results are a direct consequence of males defending a territory around their nest, preventing competitively inferior males from breeding. However, we found no significant selection differentials for body length or condition of males in either treatment. Our results support the hypothesis that aggregation of essential resources like nests promotes resource monopolisation. In species facing highly clumped nesting resources in the wild, monopolisation may negatively impact population productivity but could lead to strong selection on traits that promote male competitive ability.     

Biosorption of zinc ions from aqueous solution by the microalga Scenedesmus obliquus

Aquatic environments are often exposed to toxic heavy metals, which gain access to the food chain via microalgae and may cause severe problems at higher trophic levels. However, such a metabolic specificity can be taken advantage of in bioremediation strategies. The potential of a novel wild strain of Scenedesmus obliquus, previously isolated from a heavy metal-contaminated site in northern Portugal, to remove Zn from aqueous solutions was thus studied, using several initial concentrations. The removal extent reached its maximum by 1 day: 836.5 mg Zn/g biomass, at the initial concentration of 75 mg/L, mainly by adsorption onto the cell surface. Comparative studies encompassing a commercially available strain of the same microalgal species led to a maximum removal extent of only 429.6 mg Zn/g biomass, under identical conditions. Heat-inactivated cells permitted a maximum removal of 209.6 mg Zn/g biomass, at an initial concentration of 50 mg Zn/L. The maximum adsorption capacity of Zn, estimated via Langmuir’s isotherm, was 330 mg Zn/g biomass. Finally, Zn removal was highest at pH 6.0–7.0. It was proven, for the first time, that such a wild microalga can uptake and adsorb Zn very efficiently, which unfolds a particularly good potential for bioremediation. Its performance is far better than similar (reference) species, especially near neutrality, and even following heat-treatment.     

The carajas iron ore project: The strategy of a third world state- owned enterprise in a depressed market

This paper describes how the Carajas iron ore project was set up in February 1985 at a time of deep recession in the iron ore and steel industries. Development of the project was met with much criticism, mainly from North American steel makers, who argued that the project would only be successful through the support of a Third World government, highly dependent on foreign exchange, without any consideration being given to its economic feasibility or to the fundamentals of the market. The authors explain why the World Bank took the step of setting up the project and how its development can be partly explained by the interests of the Japanese and European steel makers. The role of the Brazilian government is explained and the authors conclude that the relatively low rate of investment anticipated by the project will be overshadowed by the high gains in foreign exchange.     

Methodological Development of an Index of Coastal Water Quality: Application in a Tourist Area

With the aim of obtaining an index of coastal water quality, a methodological procedure based on numerical classification and discriminant analysis is presented. The procedure was applied to nutrient data (ammonia, nitrite, nitrate, and phosphate) analyzed along the coastal waters of a Spanish tourist area. Using numerical classification, three levels of nutrient loading were revealed, characterizing oligotrophic, mesotrophic, and potentially eutrophic waters. Discriminant analysis was shown to be an effective methodological tool in the discrimination between trophic groups. For every group, the discriminant procedure generated the centroids. The centroids representing oligotrophic and potentially eutrophic conditions were used to establish the two extremes of the continuum of mesotrophic conditions in these coastal waters: Standardizing values from -1 to 1, the centroids for oligotrophic and potentially eutrophic waters yielded an interval that defined the range of mesotrophic conditions. This interval is proposed as a water quality index. The ability of the coastal water quality index to successfully predict mesotrophic conditions was proved with random samples.     

The plant physical features selected by wildcats as signal posts: an economic approach to fecal marking

The chemical signals of solitary and territorial felid species are essential for their intraspecific communication. We studied the selection of plant substrates during the fecal marking behavior of the European wildcat Felis silvestris from September 2008 to June 2009 in a protected area in Northwest Spain. The aim of the study was to examine the selection of plants as signal posts with respect to their physical characteristics. We hypothesized that wildcats deposit their fecal marks on plants with physical characteristics (e.g., size, species, and visual conspicuousness) that enhance the olfactory and visual effectiveness of the signal. Our results indicate that diameter, plant group, visual conspicuousness, and interaction between the diameter and plant group influence the decision of wildcats to deposit their fecal marks on plants. The wildcats chose plants with greater diameters and greater visual conspicuousness as scent-marking posts. Moreover, the wildcats chose woody and herbaceous plants, and certain plant species were marked more frequently than expected at random. Indeed, our results indicate that the fecal marks were not randomly distributed on the plants: the wildcats chose to place their marks on plants with certain physical characteristics that maximized the detectability of the signal by intruders and potential mates, thus facilitating the spatial distribution of the species.     

Determination of sorbent point zero charge: usefulness in sorption studies

Potentiometric mass titration (PMT) technique has been adapted to determine the pH _pzc of four vegetable wastes: grape stalks, cork, yohimbe bark and olive stones wastes used for Cu(II) removal. The pH at the point zero charge (pH _pzc), determined by PMT, are compared with that obtained by two classical techniques: mass titration (MT) and immersion technique (IT). PMT has been found to be an easy and appropriate technique to determine pH _pzc of the studied materials. From the results, the knowledge of sorbents pH _pzc provides information about the possible attraction and repulsion between sorbent and sorbate but in any case enables to ensure that electrostatic force is one of the mechanisms that takes place in metal sorption.     

Stochastic Transfer Function Model and Neural Networks to Estimate Soil Moisture1

Abstract: A practical methodology is proposed to estimate the three‐dimensional variability of soil moisture based on a stochastic transfer function model, which is an approximation of the Richard’s equation. Satellite, radar and in situ observations are the major sources of information to develop a model that represents the dynamic water content in the soil. The soil‐moisture observations were collected from 17 stations located in Puerto Rico (PR), and a sequential quadratic programming algorithm was used to estimate the parameters of the transfer function (TF) at each station. Soil texture information, terrain elevation, vegetation index, surface temperature, and accumulated rainfall for every grid cell were input into a self‐organized artificial neural network to identify similarities on terrain spatial variability and to determine the TF that best resembles the properties of a particular grid point. Soil moisture observed at 20 cm depth, soil texture, and cumulative rainfall were also used to train a feedforward artificial neural network to estimate soil moisture at 5, 10, 50, and 100 cm depth. A validation procedure was implemented to measure the horizontal and vertical estimation accuracy of soil moisture. Validation results from spatial and temporal variation of volumetric water content (vwc) showed that the proposed algorithm estimated soil moisture with a root mean squared error (RMSE) of 2.31% vwc, and the vertical profile shows a RMSE of 2.50% vwc. The algorithm estimates soil moisture in an hourly basis at 1 km spatial resolution, and up to 1 m depth, and was successfully applied under PR climate conditions.