Characterization of As and trace metals embedded in PM10 particles in Puebla City, México

Forty-eight air-filter samples (PM₁₀) were analysed to identify the concentration level of partially leached metals (PLMs; As, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and V) from Puebla City, México. Samples were collected during 2008 from four monitoring sites: (1) Tecnológico (TEC), (2) Ninfas (NIN), (3) Hermanos Serdán (HS) and (4) Agua Santa (AS). The results indicate that in TEC, As (avg. 424 ng m^?3), V (avg. 19.2 ng m^?3), Fe (avg. 1,202 ng m^?3), Cu (avg. 86.6 ng m^?3), Cr (41.9 ng m^?3) and Ni (18.6 ng m^?3) are on the higher side than other populated regions around the world. The enrichment of PLMs is due to the industrial complexes generating huge dust particles involving various operations. The results are supported by the correlation of metals (Mn, Cd and Co) with Fe indicating its anthropogenic origin and likewise, As with Cd, Co, Fe, Mn, Pb and V. The separate cluster of As, Fe and Mn clearly signifies that it is due to continuous eruption of fumaroles from the active volcano Popocatépetl in the region.     

Development of a new risk-based framework to guide investment in water quality monitoring

An innovative framework for optimising investments in water quality monitoring has been developed for use by water and environmental agencies. By utilising historical data, investigating the accuracy of monitoring methods and considering the risk tolerance of the management agency, this new methodology calculates optimum water quality monitoring frequencies for individual water bodies. Such information can be applied to water quality constituents of concern in both engineered and natural water bodies and will guide the investment of monitoring resources. Here we present both the development of the framework itself and a proof of concept by applying it to the occurrence of hazardous cyanobacterial blooms in freshwater lakes. This application to existing data demonstrates the robustness of the approach and the capacity of the framework to optimise the allocation of both monitoring and mitigation resources. When applied to cyanobacterial blooms in the Swan Coastal Plain of Western Australia, we determined that optimising the monitoring regime at individual lakes could greatly alter the overall monitoring schedule for the region, rendering it more risk averse without increasing the amount of monitoring resources required. For water resources with high-density temporal data related to constituents of concern, a similar reduction in risk may be observed by applying the framework.     

A comparative study on mesozooplankton abundance and diversity between a protected and an unprotected coastal area of Andaman Islands

The study was carried out to understand the variability in phytoplankton production (Chlorophyll a) and mesozooplankton diversity from two different shallow coastal regions of south Andaman viz. Port Blair Bay (PBB), the only real urban area among the islands and Mahatma Gandhi Marine National Park, a Marine Protected Area (MPA) at Wandoor. Seasonal sampling was carried out during the Northeast monsoon (NEM—November 2005), Intermonsoon (IM—April 2006), and Southwest monsoon (SWM—August 2006). Significant (P?<?0.05) seasonal variation was observed in the environmental variables at both the regions. Higher average chlorophyll a (Chl. a) and mesozooplankton standing stock were observed at PBB compared to MPA, but the seasonal variation observed was marginal at both the study areas. Chl. a showed a steep increasing gradient from outer to the inner regions of the PBB. The number of zooplankton taxa recorded at both areas was quite similar, but marked differences were noticed in their relative contribution to the total abundance. Eventhough the Copepoda dominated at both the areas, the non-copepod taxa differed significantly between the regions. Dominance of carnivores such as siphonophores and chaetognaths were noticed at PBB, while filter feeders such as appendicularians and decapod larvae were more abundant at MPA. A total of 20 and 21 copepod families was recorded from PBB and MPA, respectively. Eleven species of chaetognaths were observed as common at both areas. Larval decapods were found to be predominant at MPA with 20 families; whereas, at PBB, only 12 families were recorded. In the light of the recent reports on various changes occurring in the coastal waters of the Andaman Islands, it is suspected that the difference in Chl. a as well as the mesozooplankton standing stock and community structure observed between the two study areas may be related to the various anthropogenic events influencing the coastal waters.     

A pragmatic approach to study the groundwater quality suitability for domestic and agricultural usage,Saq aquifer,northwest of Saudi Arabia

The present study deals with detailed hydrochemical assessment of groundwater within the Saq aquifer. The Saq aquifer which extends through the NW part of Saudi Arabia is one of the major sources of groundwater supply. Groundwater samples were collected from about 295 groundwater wells and analyzed for various physico-chemical parameters such as electrical conductivity (EC), pH, temperature, total dissolved solids (TDS), Na⁺, K⁺, Ca²⁺, Mg²⁺, CO₃ ^?, HCO₃ ^?, Cl^?, SO₄ ^2?, and NO₃ ^?. Groundwater in the area is slightly alkaline and hard in nature. Electrical conductivity (EC) varies between 284 and 9,902?μS/cm with an average value of 1,599.4 μS/cm. The groundwater is highly mineralized with approximately 30 % of the samples having major ion concentrations above the WHO permissible limits. The NO₃ ^? concentration varies between 0.4 and 318.2 mg/l. The depth distribution of NO₃ ^? concentration shows higher concentration at shallow depths with a gradual decrease at deeper depths. As far as drinking water quality criteria are concerned, study shows that about 33 % of samples are unfit for use. A detailed assessment of groundwater quality in relation to agriculture use reveals that 21 % samples are unsuitable for irrigation. Using Piper’s classification, groundwater was classified into five different groups. Majority of the samples show Mix-Cl-SO₄- and Na-Cl-types water. The abundances of Ca²⁺ and Mg²⁺ over alkalis infer mixed type of groundwater facies and reverse exchange reactions. The groundwater has acquired unique chemical characteristics through prolonged rock-water interactions, percolation of irrigation return water, and reactions at vadose zone.     

Use of the land snail Helix aspersa for monitoring heavy metal soil contamination in Northeast Algeria

The objective of this study was to investigate the impact of anthropogenic activities on soil quality using the land snail Helix aspersa as a bioindicator. Soil samples and snails were collected from several sites in Northeast Algeria during the summer and winter of 2010. All of the sites were chosen due to their proximity to industrial factories—a potential source of soil pollution via heavy metal contamination. The concentration of heavy metals (Pb, Cd, Mn, and Fe) in soil samples was analyzed using atomic absorption spectrophotometry. Activity levels of glutathione S-transferase (GST) and acetylcholinesterase (AChE), indicators of oxidative stress and neurotoxicity, respectively, were measured in snails collected from each site. GST and AChE activity were found to vary between sites and by season. The highest levels of GST activity were registered during the summer at sites closest to potential sources of pollution. AChE activity levels also peaked during the summer with the highest values recorded at the site in El Hadjar. These increased levels of bioindicative stress response correlated with increasing metal concentration in soil samples collected at each site.     

Vertical distribution of heavy metals in soil profile in a seasonally waterlogging agriculture field in Eastern Ganges Basin

The accumulation of heavy metals in soil and water is a serious concern due to their persistence and toxicity. This study investigated the vertical distribution of heavy metals, possible sources and their relation with soil texture in a soil profile from seasonally waterlogged agriculture fields of Eastern Ganges basin. Fifteen samples were collected at ～0.90-m interval during drilling of 13.11 mbgl and analysed for physical parameters (moisture content and grain size parameters: sand, silt, clay ratio) and heavy metals (Fe, Mn, Cr, Cu, Pb, Zn, Co, Ni and Cd). The average metal content was in the decreasing order of Fe?>?Mn?>?Cr?>?Zn?>?Ni?>?Cu?>?Co?>?Pb?>?Cd. Vertical distribution of Fe, Mn, Zn and Ni shows more or less similar trends, and clay zone records high concentration of heavy metals. The enrichment of heavy metals in clay zone with alkaline pH strongly implies that the heavy metal distributions in the study site are effectively regulated by soil texture and reductive dissolution of Fe and Mn oxy-hydroxides. Correlation coefficient analysis indicates that most of the metals correlate with Fe, Mn and soil texture (clay and silt). Soil quality assessment was carried out using geoaccumulation index (I _geo), enrichment factor (EF) and contamination factor (CF). The enrichment factor values were ranged between 0.66 (Mn) and 2.34 (Co) for the studied metals, and the contamination factor values varied between 0.79 (Mn) and 2.55 (Co). Results suggest that the elements such as Cu and Co are categorized as moderate to moderately severe contamination, which are further confirmed by I _geo values (0.69 for Cu and 0.78 for Co). The concentration of Ni exceeded the effects-range median values, and the biological adverse effect of this metal is 87 %. The average concentration of heavy metals was compared with published data such as concentration of heavy metals in Ganga River sediments, Ganga Delta sediments and upper continental crust (UCC), which apparently revealed that heavy metals such as Fe, Mn, Cr, Pb, Zn and Cd are influenced by the dynamic nature of flood plain deposits. Agricultural practice and domestic sewage are also influenced on the heavy metal content in the study area.     

Temperature adaptation of the heart in the grass snake (Natrix natrix L.), common European viper (Vipera berus L.), and steppe viper (Vipera renardi Christoph) (Reptilia: Squamata: Serpentes)

Changes in the heart rate (HR) in more and less thermophilic reptiles (Natrix natrix L., Vipera berus L., and V. renardi Christoph) exposed to heating from 0 to 40°C under anesthesia have been found to depend on the previous adaptation of the animals to the temperature parameters characteristic of the natural habitats of their populations.     

Design and evaluation of a local analytic-deliberative process for climate adaptation planning

In the midst of rapidly proliferating engagement efforts around climate adaptation, attention to the design and evaluation of decision support processes and products is warranted. We report on the development and evaluation of a process framework called the Vulnerability, Consequences, and Adaptation Planning Scenarios (VCAPS) process. VCAPS is a systematic approach to integrate local knowledge with scientific understanding by providing opportunities for facilitated, deliberative learning-based activities with local decision makers about climate change vulnerability and adaptation. We introduce the conceptual basis of the process in analytic-deliberation, hazard management, and vulnerability. Our evaluations from eight coastal communities where the approach was applied point to four assets of VCAPS: it promotes synthesis of local and scientific knowledge; it stimulates systems thinking and learning; it facilitates governance by producing action plans with transparent justifications; and it accommodates participant time constraints and preferences.     

Modelling with uncertainty: Introducing a probabilistic framework to predict animal population dynamics

Predictive population models designed to assist managers and policy makers require an explicit treatment of inherent uncertainty and variability. These are particular concerns when modelling non-native and reintroduced species, when data have been collected within one geographical or ecological context but predictions are required for another, or when extending models to predict the consequences of environmental change (e.g., climate or land-use). We present an aspatial, probabilistic framework of hierarchical process models for predicting population growth even when data are sparse or of poor quality. Insight into the factors affecting population dynamics in real landscapes can be provided and Kullback–Leibler distances are used to compare the relative output of models. This flexible yet robust framework gives easily interpretable results, allowing managers as well as modellers to invalidate anomalous models and apply others to real-life scenarios.We illustrate the framework’s power with a meta-analysis of European wild boar (Sus scrofa) data. We test hypotheses about the effect of geographic region, hunting and mast years on wild boar population growth, to build models of wild boar dynamics for the UK. The framework quantifies the importance of hunting pressure as a driver of population growth, and confirms that reproductive success is greatly decreased in poor mast years, suggesting that the key to predicting wild boar dynamics is to ascertain local hunting pressure and to better understand changing food availability. Geography had no significant effect, indicating that it is not a good proxy for modelling the impact of change in climate or land-use on wild boar populations at the European scale. We use the framework to predict population abundance 9 years after an isolated population of wild boar established in the UK; in a comparison with the only field data and two independent modelling exercises, our framework provides the most robust and informative results.     

Modelling plant species richness using functional groups

Conservation biologists increasingly rely on spatial predictive models of biodiversity to support decision-making. Therefore, highly accurate and ecologically meaningful models are required at relatively broad spatial scales. While statistical techniques have been optimized to improve model accuracy, less focus has been given to the question: How does the autecology of a single species affect model quality? We compare a direct modelling approach versus a cumulative modelling approach for predicting plant species richness, where the latter gives more weight to the ecology of functional species groups. In the direct modelling approach, species richness is predicted by a single model calibrated for all species. In the cumulative modelling approach, the species were partitioned into functional groups, with each group calibrated separately and species richness of each group was cumulated to predict total species richness. We hypothesized that model accuracy depends on the ecology of individual species and that the cumulative modelling approach would predict species richness more accurately. The predictors explained plant species richness by ca. 25%. However, depending on the functional group the deviance explained varied from 3 to 67%. While both modelling approaches performed equally well, the models of the different functional groups highly varied in their quality and their spatial richness pattern. This variability helps to improve our understanding on how plant functional groups respond to ecological gradients.