Characterizing the Width of Amphibian Movements During Postbreeding Migration

Habitat linkages can help maintain connectivity of animal populations in developed landscapes. However, the lack of empirical data on the width of lateral movements (i.e., the zigzagging of individuals as they move from one point to point another) makes determining the width of such linkages challenging. We used radiotracking data from wood frogs (Lithobates sylvaticus) and spotted salamanders (Ambystoma maculatum) in a managed forest in Maine (U.S.A.) to characterize movement patterns of populations and thus inform planning for the width of wildlife corridors. For each individual, we calculated the polar coordinates of all locations, estimated the vector sum of the polar coordinates, and measured the distance from each location to the vector sum. By fitting a Gaussian distribution over a histogram of these distances, we created a population‐level probability density function and estimated the 50th and 95th percentiles to determine the width of lateral movement as individuals progressed from the pond to upland habitat. For spotted salamanders 50% of lateral movements were ≤13 m wide and 95% of movements were ≤39 m wide. For wood frogs, 50% of lateral movements were ≤17 m wide and 95% of movements were ≤ 51 m wide. For both species, those individuals that traveled the farthest from the pond also displayed the greatest lateral movement. Our results serve as a foundation for spatially explicit conservation planning for pond‐breeding amphibians in areas undergoing development. Our technique can also be applied to movement data from other taxa to aid in designing habitat linkages. Caracterización de la Amplitud de Movimiento de Anfibios durante la Migración Pos‐Reproducción     

Seaweeds as bioindicators of heavy metals off a hot spot area on the Egyptian Mediterranean Coast during 2008–2010

Concentrations of Cu, Zn, Cd, Pb, Ni, Co, Fe, Mn, and Hg were measured successively in water, sediments, and six macroalgal species belonging to three algal classes during 3 years (2008–2010) from Abu Qir Bay, Alexandria, Egypt: Chlorophyceae (Enteromorpha compressa, Ulva fasciata), Phaeophyceae (Padina boryana), and Rhodophyceae (Jania rubens, Hypnea musciformis, Pterocladia capillacea). The study aimed to assess the bioaccumulation potential of the seaweeds, as well as to evaluate the extent of heavy metal contamination in the selected study site. Metals were analyzed using atomic absorption spectrophotometry coupled with MH-10 hydride system. The obtained data showed that the highest mean concentrations of Cu, Zn, Fe, and Mn were recorded in E. compressa; Cd, Ni, and Hg exhibited their highest mean concentrations in P. boryana, while Pb and Co were found in J. rubens. Abundance of the heavy metals in the algal species was as follow: Fe?>?Mn?>?Zn?>?Pb?>?Ni?>?Co?>?Cu?>?Cd?>?Hg. E. compressa showed the maximum metal pollution index (MPI) which was 11.55. Bioconcentration factor (BCF) for the metals in algae was relatively high with a maximum value for Mn. The Tomlinson pollution load index (PLI) values for the recorded algal species were low, which ranged between 1.00 in P. boryana and 2.72 in E. compressa. Enrichment factors for sediments were low fluctuating between 0.43 for Hg to 2.33 for Mn. Accordingly, the green alga E. compressa, brown alga P. boryana, and red alga J. rubens can be nominated as bioindicators. Based on MPI and PLI indices, Abu Qir Bay in the present study is considered as low-contaminated area.     

Combined Municipal Solid Waste and biomass system optimization for district energy applications

Municipal Solid Waste (MSW) disposal has been a controversial issue in many countries over the past years, due to disagreement among the various stakeholders on the waste management policies and technologies to be adopted. One of the ways of treating/disposing MSW is energy recovery, as waste is considered to contain a considerable amount of bio-waste and therefore can lead to renewable energy production. The overall efficiency can be very high in the cases of co-generation or tri-generation. In this paper a model is presented, aiming to support decision makers in issues relating to Municipal Solid Waste energy recovery. The idea of using more fuel sources, including MSW and agricultural residue biomass that may exist in a rural area, is explored. The model aims at optimizing the system specifications, such as the capacity of the base-load Waste-to-Energy facility, the capacity of the peak-load biomass boiler and the location of the facility. Furthermore, it defines the quantity of each potential fuel source that should be used annually, in order to maximize the financial yield of the investment. The results of an energy tri-generation case study application at a rural area of Greece, using mixed MSW and biomass, indicate positive financial yield of investment. In addition, a sensitivity analysis is performed on the effect of the most important parameters of the model on the optimum solution, pinpointing the parameters of interest rate, investment cost and heating oil price, as those requiring the attention of the decision makers. Finally, the sensitivity analysis is enhanced by a stochastic analysis to determine the effect of the volatility of parameters on the robustness of the model and the solution obtained.     

Application of activated M/ZnO (M = Mn,Co, Ni,Cu, Ag) in photocatalytic degradation of diazo textile coloring dye

Activated ZnO powder has been prepared by procedures involving first its dissolution in nitric acid, then simultaneous treatment by adding NH₄OH and CO₂ bubbling leading to precipitation as Zn(OH)CO₃ (ZH) and further thermal decomposition of ZH at 400 °C. The gas evolution leads to formation of pores and increase in the specific surface area. Chemically activated M/ZnO powders doped with Mn, Co, Ni, Cu, and Ag have been obtained by the impregnation method. The samples have been characterized by ultraviolet-visible (UV-Vis) spectroscopy, diffuse reflectance (DR) UV-Vis, X-ray diffraction (XRD), single point Brunauer–Emmet–Teller (BET), scanning electron microscope (SEM), and X-ray photoelectron spectroscopy (XPS) methods. The experiments have shown that metal-doped activated ZnO powders possess higher photocatalytic activities in oxidative discoloration of model contaminant textile coloring dye Reactive Black 5 in slurry reactor compared to that of the pure ZnO. The XRD and XPS data have shown the presence of defects, nonstoichiometricity implying the formation of solid solutions. Copper-doped (1.5 wt%) activated ZnO (Cu²⁺ replaces Zn²⁺) is outstanding in its photocatalytic performance in discoloration of the dye due to the higher specific surface area and improved charge carrier separation.     

Rainwater toxicity and contamination study from São Paulo Metropolitan Region, Brazil

Wet deposition is an important process that removes pollutants from the atmosphere and transfers them to waters and soil. The goal of this study was to assess the biological effects of the atmospheric contamination of rainwater in the metropolitan area of São Paulo (MASP) using Daphnia similis, Ceriodaphnia dubia, and Vibrio fischeri. Experimental assays were carried out according to standard toxicity methodology. Twenty-three rainwater samples were collected from October 2007 to December 2008, at the Nuclear Research Institute (IPEN), in MASP. Major ions were determined by ionic chromatography, which showed NH₄ ⁺ and NO₃ ^? as prevalent ions. Ecotoxicological results confirmed toxic potential of rainwater, as all samples were toxic to D. similis and C. dubia. The V. fischeri luminescence reduction confirmed those negative effects of rainwater and percentage inhibition of relative luminescence ranged from 0.2 to 0.9 for 16 samples. Worse conditions were observed during the rainy season, suggesting convective rains are more effective in transferring contaminants and toxicity from atmosphere to surface.     

Predictive Model of Avian Electrocution Risk on Overhead Power Lines

Electrocution on overhead power structures negatively affects avian populations in diverse ecosystems worldwide, contributes to the endangerment of raptor populations in Europe and Africa, and is a major driver of legal action against electric utilities in North America. We investigated factors associated with avian electrocutions so poles that are likely to electrocute a bird can be identified and retrofitted prior to causing avian mortality. We used historical data from southern California to identify patterns of avian electrocution by voltage, month, and year to identify species most often killed by electrocution in our study area and to develop a predictive model that compared poles where an avian electrocution was known to have occurred (electrocution poles) with poles where no known electrocution occurred (comparison poles). We chose variables that could be quantified by personnel with little training in ornithology or electric systems. Electrocutions were more common at distribution voltages (≤33 kV) and during breeding seasons and were more commonly reported after a retrofitting program began. Red‐tailed Hawks (Buteo jamaicensis) (n = 265) and American Crows (Corvus brachyrhynchos) (n = 258) were the most commonly electrocuted species. In the predictive model, 4 of 14 candidate variables were required to distinguish electrocution poles from comparison poles: number of jumpers (short wires connecting energized equipment), number of primary conductors, presence of grounding, and presence of unforested unpaved areas as the dominant nearby land cover. When tested against a sample of poles not used to build the model, our model distributed poles relatively normally across electrocution‐risk values and identified the average risk as higher for electrocution poles relative to comparison poles. Our model can be used to reduce avian electrocutions through proactive identification and targeting of high‐risk poles for retrofitting. Modelo Predictivo del Riesgo de Electrocución de Aves en Líneas Eléctricas Elevadas     

Developing Metapopulation Connectivity Criteria from Genetic and Habitat Data to Recover the Endangered Mexican Wolf

Restoring connectivity between fragmented populations is an important tool for alleviating genetic threats to endangered species. Yet recovery plans typically lack quantitative criteria for ensuring such population connectivity. We demonstrate how models that integrate habitat, genetic, and demographic data can be used to develop connectivity criteria for the endangered Mexican wolf (Canis lupus baileyi), which is currently being restored to the wild from a captive population descended from 7 founders. We used population viability analysis that incorporated pedigree data to evaluate the relation between connectivity and persistence for a restored Mexican wolf metapopulation of 3 populations of equal size. Decreasing dispersal rates greatly increased extinction risk for small populations (<150–200), especially as dispersal rates dropped below 0.5 genetically effective migrants per generation. We compared observed migration rates in the Northern Rocky Mountains (NRM) wolf metapopulation to 2 habitat‐based effective distance metrics, least‐cost and resistance distance. We then used effective distance between potential primary core populations in a restored Mexican wolf metapopulation to evaluate potential dispersal rates. Although potential connectivity was lower in the Mexican wolf versus the NRM wolf metapopulation, a connectivity rate of >0.5 genetically effective migrants per generation may be achievable via natural dispersal under current landscape conditions. When sufficient data are available, these methods allow planners to move beyond general aspirational connectivity goals or rules of thumb to develop objective and measurable connectivity criteria that more effectively support species recovery. The shift from simple connectivity rules of thumb to species‐specific analyses parallels the previous shift from general minimum‐viable‐population thresholds to detailed viability modeling in endangered species recovery planning. Desarrollo de Criterios de Conectividad Metapoblacional a Partir de Datos Genéticos y de Hábitat para Recuperar al Lobo Mexicano en Peligro de Extinción     

Implications of different population model structures for management of threatened plants

Population viability analysis (PVA) is a reliable tool for ranking management options for a range of species despite parameter uncertainty. No one has yet investigated whether this holds true for model uncertainty for species with complex life histories and for responses to multiple threats. We tested whether a range of model structures yielded similar rankings of management and threat scenarios for 2 plant species with complex postfire responses. We examined 2 contrasting species from different plant functional types: an obligate seeding shrub and a facultative resprouting shrub. We exposed each to altered fire regimes and an additional, species‐specific threat. Long‐term demographic data sets were used to construct an individual‐based model (IBM), a complex stage‐based model, and a simple matrix model that subsumes all life stages into 2 or 3 stages. Agreement across models was good under some scenarios and poor under others. Results from the simple and complex matrix models were more similar to each other than to the IBM. Results were robust across models when dominant threats are considered but were less so for smaller effects. Robustness also broke down as the scenarios deviated from baseline conditions, likely the result of a number of factors related to the complexity of the species’ life history and how it was represented in a model. Although PVA can be an invaluable tool for integrating data and understanding species’ responses to threats and management strategies, this is best achieved in the context of decision support for adaptive management alongside multiple lines of evidence and expert critique of model construction and output.