Stronger predation in the tropics shapes species richness patterns in marine communities

Species interactions are widely assumed to be stronger at lower latitudes, but surprisingly few experimental studies test this hypothesis, and none ties these processes to observed patterns of species richness across latitude. We report here the first experimental field test that predation is both stronger and has a disproportionate effect on species richness in the tropics relative to the temperate zone. We conducted predator-exclusion experiments on communities of sessile marine invertebrates in four regions, which span 32 degrees latitude, in the western Atlantic Ocean and Caribbean Sea. Over a three-month timescale, predation had no effect on species richness in the temperate zone. In the tropics, however, communities were from two to over ten times more species-rich in the absence of predators than when predators were present. While micro-and macro-predators likely compete for the limited prey resource in the tropics, micropredators alone were able to exert as much pressure on the invertebrate communities as the full predator community. This result highlights the extent to which exposure to even a subset of the predator guild can significantly impact species richness in the tropics. Patterns were consistent in analyses that included relative and total species abundances. Higher species richness in the absence of predators in the tropics was also observed when species occurrences were pooled across two larger spatial scales, site and region, demonstrating a consistent scaling relationship. These experimental results show that predation can both limit local species abundances and shape patterns of regional coexistence in the tropics. When preestablished diverse tropical communities were then exposed to predation for different durations, ranging from one to several days, species richness was always reduced. These findings confirmed that impacts of predation in the tropics are strong and consistent, even in more established communities. Our results offer empirical support for the long-held prediction that predation pressure is stronger at lower latitudes. Furthermore, we demonstrate the magnitude to which variation in predation pressure can contribute to the maintenance of tropical species diversity.     

Latitudinal variation in local interactions and regional enrichment shape patterns of marine community diversity

While communities are shaped by both local interactions and enrichment from the regional species pool, we propose a hypothesis that the balance of these forces shifts with latitude, with regional enrichment dominating at high latitudes and local interactions dominating at low latitudes. To test this hypothesis, we conducted a latitudinal-scale experiment with marine epifaunal communities. In four regions of the North Atlantic Ocean and Caribbean Sea, we used mimics of ecosystem engineers to manipulate biogenic structural complexity. We iteratively evaluated diversity patterns of experimental communities up to one year after deployment. Additional data were also collected from one of our tropical sites 2.5 years after initial deployment. As hypothesized, we found a reciprocal latitudinal gradient in the effects of the structurally complex mimics and regional enrichment. In the tropics, local diversity was always higher in association with the mimics than in exposed areas that were more open to predation. This effect was consistent across two spatial scales and beyond the one-year timescale of the experiment. In temperate communities, no consistent effects of the mimics on diversity were observed. However, the proportion of species from the regional species pool that were present at the local scale increased from the tropics to the temperate zone, consistent with the hypothesis that higher-latitude communities may experience greater influence from the regional species pool than communities at low latitudes. This study represents the first large-scale experimental demonstration that suggests that the relative impact of local interactions and regional enrichment on community diversity may depend on latitude.     

Treatment of copper industry waste and production of sintered glass-ceramic.

Copper waste is iron-rich hazardous waste containing heavy metals such as Cu, Zn, Co, Pb. The results of leaching tests show that the concentration of these elements exceeds the Turkish and EPA regulatory limits. Consequently, this waste cannot be disposed of in its present form and therefore requires treatment to stabilize it or make it inert prior to disposal. Vitrification was selected as the technology for the treatment of the toxic waste under investigation. During the vitrification process significant amounts of the toxic organic and inorganic chemical compounds could be destroyed, and at the same time, the metal species are immobilized as they become an integral part of the glass matrix. The copper flotation waste samples used in this research were obtained from the Black Sea Copper Works of Samsun, Turkey. The samples were vitrified after being mixed with other inorganic waste and materials. The copper flotation waste and their glass-ceramic products were characterized by X-ray analysis (XRD), scanning electron microscopy and by the toxicity characteristic leaching procedure test. The products showed very good chemical durability. The glass-ceramics fabricated at 850 degrees C/2 h have a large application potential especially as construction and building materials.     

Synthesis and potential applications of cyclodextrin-based metal–organic frameworks: a review

Metal–organic frameworks are porous polymeric materials formed by linking metal ions with organic bridging ligands. Metal–organic frameworks are used as sensors, catalysts for organic transformations, biomass conversion, photovoltaics, electrochemical applications, gas storage and separation, and photocatalysis. Nonetheless, many actual metal–organic frameworks present limitations such as toxicity of preparation reagents and components, which make frameworks unusable for food and pharmaceutical applications. Here, we review the structure, synthesis and properties of cyclodextrin-based metal–organic frameworks that could be used in bioapplications. Synthetic methods include vapor diffusion, microwave-assisted, hydro/solvothermal, and ultrasound techniques. The vapor diffusion method can produce cyclodextrin-based metal–organic framework crystals with particle sizes ranging from 200 nm to 400 μm. Applications comprise food packaging, drug delivery, sensors, adsorbents, gas separation, and membranes. Cyclodextrin-based metal–organic frameworks showed loading efficacy of the bioactive compounds ranging from 3.29 to 97.80%.

     

The global solar radiation estimation and analysis of solar energy: Case study for Osmaniye,Turkey

This paper investigates the prediction of solar radiation model and actual solar energy in Osmaniye, Turkey. Four models were used to estimate using the parameters of sunshine duration and average temperature. In order to obtain the statistical performance analysis of models, the coefficient of determination (R²), mean absolute percentage error (MAPE), mean absolute bias error (MABE), and root mean square error (RMSE) were used. Results obtained from the linear regression using the parameters of sunshine duration and average temperature showed a good prediction of the monthly average daily global solar radiation on a horizontal surface. In order to obtain solar energy, daily and monthly average solar radiation values were calculated from the five minute average recorded values by using meteorological measuring device. As a result of this measurement, the highest monthly and yearly mean solar radiation values were 698 (April in 2013) and 549 (2014 year) W/m² respectively. On an annual scale the maximum global solar radiation changes from 26.38 MJ/m²/day by June to 19.19 MJ/m²/day by September in 2013. Minimum global solar radiation changes from 14.05 MJ/m²/day by October to 7.20 MJ/m²/day by January in 2013. Yearly average energy potential during the measurement period was 16.53 MJ/m²/day (in 2013). The results show that Osmaniye has a considerable solar energy potential to produce electricity.     

Modelling cadmium bioaccumulation in Gammarus pulex by using experimental design approach

Recently, although dynamic approaches have been used increasingly to describe metal bioaccumulation in aquatic organisms, the validation of such laboratory-derived modelling is rarely assessed under environmental conditions. The present study aims to evaluate and verify statistical and mathematical models for the bioaccumulation of cadmium (Cd) and to evaluate the suitability of Gammarus pulex as a biomonitor for Cd. To optimise Cd²⁺ ion bioaccumulation conditions a Box–Behnken design was used and whether G. pulex can be used as an estimated tool to assess aquatic quality was investigated. A Box–Behnken experimental design combined with response surface modelling (RSM) was employed for Cd²⁺ bioaccumulation in G. pulex. Independent variables including temperature, contact time and Cd²⁺ ion concentration significance and their interactions were tested using analysis of variance. The selected variables’ optimum values were obtained by solving the quadratic regression model along with by analysing the response surface contour plots. Based on Box–Behnken design, the applied model is significant because model F-value and R² were obtained as 5121.49, 0.9998, respectively. Bioaccumulation of Cd amount was analysed using electrothermal atomic absorption spectrophotometer. The obtained data suggest that G. pulex can be evaluated as Cd biomonitor.     

Recycling bottom ash in production of eco-friendly interlocking concrete paving blocks

Journal of Material Cycles and Waste Management - Coal combustion waste reaches huge amount that causes environmental problem. In modern world, wastes generated from an industry can be used by...     

The effects of drainage basin geomorphometry on minimum low flow discharge: the study of small watershed in Kelang River Valley in Peninsular Malaysia

This study investigate the relationships between genomorphometric properties and the minimum low flow dischare of undisturbed drainage basins in the Taman BukitCahaya Seri Alam Forest Reserve,Peninsular Malaysia.The drainage basins selected were third-order basins so as to facilitate a common base for sampling and performing an unbiased statistical analyses.Three levels of relationships were observed in the study.Significant relationships exised between the genomorphometric properties as shown by the correlation network analysis;secondly,individual geomorphometric properties were observed to influence minimum flow discharge;and finally,the multiple regression model set up showed that minimum flow discharge(Qnub)was dependent of basin area(AU),stream length(LS),maximum relief(Hmax),average relief (HAV) and stream frequency(SF).These findings further enforced other studies of this nature that drainage basins were dynamic and functional entities whose operations were governed by complex interrelationships occurring within the basins.Changes to any of the geomorphometric properties would influence their role as basin regulators thus influencing a change in basin response.In the case of the basin‘s minimum low flow,a change in any of the properties considered in the regression model influenced the “time to peak”of flow.A shorter time period would mean higher discharge,which is generally considered the prerquisite to flooding.This research also conclude that the role of geomorphometric properties to control the water supply within the stream through out the year even though during the drought and less precipitations months .Drainage basins are sensitive entities and any deterioratons involve will generate reciprocals and response to water supply as well as the habitat within the areas.     

Modeling of SO<Subscript>2</Subscript> distribution in Istanbul using artificial neural networks

Urban air pollution is a growing problem in developing countries. Some compounds especially sulphur dioxide (SO₂) is considered as typical indicators of the urban air quality. Air pollution modeling and prediction have great importance in preventing the occurrence of air pollution episodes and provide sufficient time to take the necessary precautions. Recently, various stochastic image-processing algorithms such as Artificial Neural Network (ANN) are applied to environmental engineering. ANN structure employs input, hidden and output layers. Due to the complexity of the problem, as the number of input–output parameters differs, ANN model settings such as the number of neurons of these layers changes. The ability of ANN models to learn, particularly capability of handling large amounts (or sets) of data simultaneously as well as their fast response time, are invariably the characteristics desired for predictive and forecasting purposes. In this paper, ANN models have been used to predict air pollutant parameter in meteorological considerations. We have especially focused on modeling of SO₂ distribution and predicting its future concentration in Istanbul, Turkey. We have obtained data sets including meteorological variables and SO₂ concentrations from Istanbul-Florya meteorological station and Istanbul-Yenibosna air pollution station. We have preferred three-layer perceptron type of ANN which consists of 10, 22 and 1 neurons for input, hidden and output layers, respectively. All considered parameters are measured as daily mean. The input parameters are: SO₂ concentration, pressure, temperature, humidity, wind direction, wind speed, strength of sunshine, sunshine, cloudy, rainfall and output parameter is the future prediction of SO₂. To evaluate the performance of ANN model, our results are compared to classical nonlinear regression methods. The over all system finds an optimum correlation between input–output variables. Here, the correlation parameter, r is 0.999 and 0.528 for training and test data. Thus in our model, the trend of SO₂ is well estimated and seasonal effects are well represented. As a result, we conclude that ANN is one of the compromising methods in estimation of environmental complex air pollution problems.     

Estimation of stream temperature in firtina creek (Rize-Turkiye) using artificial neural network model

Water temperature is one of the most important environmental variables in aquatic ecosystem. Temperature changes may have positive or negative effects on organisms. High water temperatures have caused mortalities in salmonid fishes. Therefore, monitoring and prediction of potential adverse changes in water temperature is very important. Here, we have developed and tested an artificial neural network (ANN) model to predict stream temperature of Firtina Creekin Black Sea region; using local water temperature, dissolved oxygen, pH and other available meteorological data (air temperature, rainfall). Thus, enabling define suitable habitat for native Sea Trout (Salmo trutta labrax, Pallas 1811) under past drought or other adverse envIronmental conditions.