Honeybees (<Emphasis Type="Italic">Apis mellifera</Emphasis>) as a biological barrier for contamination of honey by environmental toxic metals

The aim of the study was to investigate the transfer of toxic metals from honeybee workers (Apis mellifera L.) to bee honey in relation to the ecological state of the environment. The materials of the study consisted of samples of honeybee bodies and varietal honeys taken from the same apiary located in three areas: R1—urbanized (16), R2—ecologically clean (16) and R3—industrialized (15) of south-eastern Poland. The contents of 14 elements in all tested samples, including toxic metals (Cd, Pb, Hg, Al, Ni, Tl) as well as bioelements (K, Mg, Ca, Mn, Fe, Zn, Cu, Se), were analysed by the ICP-OES method with prior microwave mineralization. The concentrations of the majority of the studied elements, excluding aluminum and lead, were significantly higher in bee bodies than in honey samples (P?<?0.05). The pollution of bee bodies by toxic metals was dependent on the environmental cleanliness, and the most pollution was observed in the industrialized area. The bee body was the most effective barrier for Cd and Tl transfer to the honey, while the level of Ni was similar in both tested materials. The Al concentration was significantly higher in honey than bee bodies (14.81?±?24.69 and 6.51?±?5.83 mg kg^?1, respectively), which suggests the possibility of secondary contamination of honey. The greatest sensitivity to heavy metal pollution was observed in honeydew honey compared to nectar honeys (P?<?0.05). It was proved for the first time that bees work as biofilters for toxic metals and prevent honey contamination.     

Historical carbon fluxes in the expanding deforestation frontier of Southern Brazilian Amazonia (1985–2012)

In tropical areas, pioneer occupation fronts steer the rapid expansion of deforestation, contributing to carbon emissions. Up-to-date carbon emission estimates covering the long-term development of such frontiers depend on the availability of high spatial–temporal resolution data. In this paper, we provide a detailed assessment of carbon losses from deforestation and potential forest degradation from fragmentation for one expanding frontier in the Brazilian Amazon. We focused on one of the Amazonia’s hot-spots of forest loss, the BR-163 highway that connects the high productivity agricultural landscapes in Mato Grosso with the exporting harbors of the Amazon. We used multi-decadal (1984–2012) Landsat-based time series on forested and non-forested area in combination with a carbon book-keeping model. We show a 36% reduction in 1984s biomass carbon stocks, which led to the emission of 611.5 TgCO₂ between 1985 and 1998 (43.6 TgCO₂ year⁻¹) and 959.8 TgCO₂ over 1999–2012 (68.5 TgCO₂ year⁻¹). Overall, fragmentation-related carbon losses represented 1.88% of total emissions by 2012, with an increasing relevance since 2004. We compared the Brazilian Space Agency deforestation assessment (PRODES) with our data and found that small deforestation polygons not captured by PRODES had increasing importance on estimated deforestation carbon losses since 2000. The comparative analysis improved the understanding of data-source-related uncertainties on carbon estimates and indicated disagreement areas between datasets that could be subject of future research. Furthermore, spatially explicit, annual deforestation and emission estimates like the ones derived from this study are important for setting regional baselines for REDD+ or similar payment for ecosystem services frameworks.

     

Comparison between UVA- and zero-valent iron-activated persulfate processes for degrading propylparaben

Conventional wastewater treatments are not efficient in removing parabens, which may thus end up in surface waters, posing a threat to aquatic biota and hu     

Social representations of governance for change towards sustainability: perspectives of sustainability advocates

There is a substantial body of literature on public understandings of large-scale ‘environmental’ phenomena such as climate change and resource degradation. At the same time, political science and economics analyse the governance arrangements to deal with such issues. These realms of research rarely meet: there has been little research into people’s understandings of the governance of environmental change. This study adds a psychological perspective to governance research by investigating social representations of governance that promotes societal change towards sustainability, and related practices. It examines data from qualitative interviews with sustainability-interested people in seven European countries (n = 105). The analysis identified building blocks of representations suitable as an analytical framework for future research on governance representations. The diversity of their content reflected a range of pathways to societal change. Representations often seemed to have a creative function as a guiding vision for individuals’ own practices, but their wider transformative potential was constrained.     

Influence of community-based natural resource management strategies in the resilience of social-ecological systems

Different social-ecological systems around the world are managed under community-based natural resource management (CBNRM) strategies. This paper analyses how CBNRM strategies influence the resilience of social-ecological systems to the disturbances they face, drawing upon the experience of three Latin American cases (two in Mexico and one in Colombia). The cases differ in their CBNRM approach and in the time these governance systems have been in place. By using a mixed-method approach, we review the socio-ecological history and describe each CBNRM characteristics. We then assess their resilience to socioeconomic and environmental disturbances through a set of indicators. We found that CBNRM strategies influence positively and negatively resilience and that internal decisions might address important threats. On the positive side, the social-ecological systems with longer tradition of CBNRM and more local buy-in of commonly agreed objectives appear to be more resilient to environmental challenges. But, internal governance factors such as power imbalances, poor income distribution, and gender inequities linked to CBNRM undermine resilience and foster out migration. Finally, communities appear to have limited capacities to cope with external disturbances such as global drivers of change or national policies that negatively affect their social-ecological resilience.

     

Guarana improves behavior and inflammatory alterations triggered by methylmercury exposure: an in vivo fruit fly and in vitro neural cells study

Environmental Science and Pollution Research - Methylmercury (MeHg) is a well-known environmental pollutant associated with neurological and developmental deficits in animals and humans. However,...     

Mercury species accumulation and trophic transfer in biological systems using the Almadén mining district (Ciudad Real,Spain) as a case of study

The impact of mercury (Hg) pollution in the terrestrial environments and the terrestrial food chains including the impact on human food consumption is still greatly under-investigated. In particular, studies including Hg speciation and detoxification strategies in terrestrial animals are almost non-existing, but these are key information with important implications for human beings. Therefore, in this work, we report on Hg species (inorganic mercury, iHg, and monomethylmercury, MeHg) distribution among terrestrial animal tissues obtained from a real-world Hg exposure scenario (Almadén mining district, Spain). Thus, we studied Hg species (iHg and MeHg) and total selenium (Se) content in liver and kidney of red deer (Cervus elaphus; n?=?41) and wild boar (Sus scrofa; n?=?16). Similar mercury species distribution was found for both red deer and wild boar. Major differences were found between tissues; thus, in kidney, iHg was clearly the predominant species (more than 81 %), while in liver, the species distribution was less homogeneous with a percentage of MeHg up to 46 % in some cases. Therefore, Hg accumulation and MeHg transfer were evident in terrestrial ecosystems. The interaction between total Se and Hg species has been evaluated by tissue and by animal species. Similar relationships were found in kidney for both Hg species in red deer and wild boar. However, in liver, there were differences between animals. The possible underlying mechanisms are discussed.     

Heavy metal contamination in sediments of an artificial reservoir impacted by long-term mining activity in the Almadén mercury district (Spain)

Sediments from the Castilseras reservoir, located downstream on the Valdeazogues River in the Almadén mercury district, were collected to assess the potential contamination status related to metals(oids) associated with river sediment inputs from several decommissioned mines. Metals(oids) concentrations in the reservoir sediments were investigated using different physical and chemical techniques. The results were analyzed by principal component analysis (PCA) to explain the correlations between the sets of variables. The degree of contamination was evaluated using the enrichment factor (EF) and the geoaccumulation index (Igeo). PCA revealed that the silty fraction is the main metals(oids) carrier in the sediments. Among the potentially harmful elements, there is a group (Al, Cr, Cu, Fe, Mn, Ni, and Zn) that cannot be strictly correlated to the mining activity since their concentrations depend on the lithological and edaphological characteristics of the materials. In contrast, As, Co, Hg, Pb, and S showed significant enrichment and contamination, thus suggesting relevant contributions from the decommissioned mines through fluvial sediment inputs. As far as Hg and S are concerned, the high enrichment levels pose a question concerning the potential environmental risk of transfer of the organic forms of Hg (mainly methylmercury) from the bottom sediments to the aquatic food chain.     

A Novel Formulation for Designing a Monitoring Strategy: Application to the Design of a River Quality Monitoring System

In this work, we propose a technique to automatically optimize the monitoring of any distributed indicator (concentration of a substance along a river, blood pressure of a patient over time, etc.) for which a reliable estimate is previously available. From a mathematical point of view, the problem is based on obtaining a reliable estimate of the chosen indicator (e.g., by numerical simulation), and then solving a multi-objective optimization problem (with mixed real and integer variables) whose solution must provide an efficient and satisfactory monitoring strategy. As an illustrative case, we show the steps to follow in order to implement that strategy when designing a system for monitoring water quality in a river. Finally, we present and analyze the results when applying the proposed technique to study a real case in the Neuse River (North Carolina, USA).