Sorption of selenate on soils and pure phases: kinetic parameters and stabilisation

This study was conducted to identify the principle selenate carrier phases for two selected soils, by comparing their reactivity with selenate to that of pure phases of the solids. Silica, calcium carbonate, aluminium hydroxide, goethite, bentonite and humic acid were selected as the main soil carrier phases. Comparisons were made first on the parameter values obtained with the best fit of a kinetic sorption model which can discriminate instantaneous sorption from kinetically limited sorption. Then comparisons were made of the ability for each solid to stabilise selenate by measuring the ratio of the partition coefficient for sorption (Kd_sorption) over that of the desorption (Kd_desorption). Kinetics and stabilisation were used to help elucidate the nature of interactions with the test solid phases for a large range of selenate concentrations. The experiments were conducted over 165 h in batch reactors, the solid being isolated from the solution by dialysis tubing, at two pH (5.4 and 8) and three selenate concentrations (1 × 10⁻³, 1 × 10⁻⁶ and 1 × 10⁻⁸ mol L⁻¹). The results obtained showed that only aluminium hydroxide can sorb selenate throughout the studied pH range (pH 5.4 to 8.0). The sorption capacity on this mineral was high (Kd_sorption > 100 to 1 × 10⁴ L kg⁻¹) and the selenate was mainly stabilized by the formation of inner sphere complexes. The sorption on goethite occurred at pH 5.4 (Kd_sorption 52 L kg⁻¹), mainly as outer sphere complexes, and was null at pH 8. On silica, a weak sorption was observed only at pH 5.4 and at 165 h (Kd_sorption 4 L kg⁻¹). On bentonite, calcium carbonate and humic acid no significant sorption was observed. Concerning the two soils studied, different behaviours were observed for selenate. For soil Ro (pH 5.4), Kd_sorption was low (8 L kg⁻¹) compared to soil Bu (pH 8) (70 L kg⁻¹). The sorption behaviour of selenate on soil Ro was mainly due to outer sphere complexes, as for goethite, whereas for soil Bu the sorption was mainly attributed to inner sphere complexes followed by reduction mechanisms, probably initiated by microorganisms, in which no steady state was reached at the end of the 165 h experiments. The sorption of selenate decreased when concentrations reached 1 × 10⁻³ mol L⁻¹, due to solid saturation, except for aluminium hydroxide. Reduction of selenate seemed also to occur on goethite and soil Ro, for the same concentration, but without preventing a decrease in sorption. Thus, this work shows that the comparison of selenate behaviour between soil and pure phases helps to elucidate the main carrier phases and sorption mechanisms in soil.     

Models for waste life cycle assessment: Review of technical assumptions

A number of waste life cycle assessment (LCA) models have been gradually developed since the early 1990s, in a number of countries, usually independently from each other. Large discrepancies in results have been observed among different waste LCA models, although it has also been shown that results from different LCA studies can be consistent. This paper is an attempt to identify, review and analyse methodologies and technical assumptions used in various parts of selected waste LCA models. Several criteria were identified, which could have significant impacts on the results, such as the functional unit, system boundaries, waste composition and energy modelling. The modelling assumptions of waste management processes, ranging from collection, transportation, intermediate facilities, recycling, thermal treatment, biological treatment, and landfilling, are obviously critical when comparing waste LCA models.This review infers that some of the differences in waste LCA models are inherent to the time they were developed. It is expected that models developed later, benefit from past modelling assumptions and knowledge and issues. Models developed in different countries furthermore rely on geographic specificities that have an impact on the results of waste LCA models. The review concludes that more effort should be employed to harmonise and validate non-geographic assumptions to strengthen waste LCA modelling.     

A phenomenological approach shows a high coherence of warming patterns in dimictic aquatic systems across latitude

To predict the coherence in local responses to large-scale climatic forcing among aquatic systems, we developed a generalized approach to compare long-term data of dimictic water bodies based on phenomenologically defined hydrographic events. These climate-sensitive phases (inverse stratification, spring overturn, early thermal stratification, summer stagnation) were classified in a dual code (cold/warm) based on threshold temperatures. Accounting for a latitudinal gradient in seasonal timing of phases derived from gradients in cumulative irradiation (2.2?days per degree latitude), we found a high spatial and temporal coherence in warm–cold patterns for six lakes (84?%) and the Baltic Sea (78?%), even when using the same thresholds for all sites. Similarity to CW-codes for the North Sea still was up to 72?%. The approach allows prediction of phase-specific warming trends and resulting instantaneous or time-delayed ecological responses. Exemplarily, we show that warming during early thermal stratification controls food-web-mediated effects on key species during summer.     

The problem of estimating recent genetic connectivity in a changing world

Accurate understanding of population connectivity is important to conservation because dispersal can play an important role in population dynamics, microevolution, and assessments of extirpation risk and population rescue. Genetic methods are increasingly used to infer population connectivity because advances in technology have made them more advantageous (e.g., cost effective) relative to ecological methods. Given the reductions in wildlife population connectivity since the Industrial Revolution and more recent drastic reductions from habitat loss, it is important to know the accuracy of and biases in genetic connectivity estimators when connectivity has declined recently. Using simulated data, we investigated the accuracy and bias of 2 common estimators of migration (movement of individuals among populations) rate. We focused on the timing of the connectivity change and the magnitude of that change on the estimates of migration by using a coalescent‐based method (Migrate‐n) and a disequilibrium‐based method (BayesAss). Contrary to expectations, when historically high connectivity had declined recently: (i) both methods over‐estimated recent migration rates; (ii) the coalescent‐based method (Migrate‐n) provided better estimates of recent migration rate than the disequilibrium‐based method (BayesAss); (iii) the coalescent‐based method did not accurately reflect long‐term genetic connectivity. Overall, our results highlight the problems with comparing coalescent and disequilibrium estimates to make inferences about the effects of recent landscape change on genetic connectivity among populations. We found that contrasting these 2 estimates to make inferences about genetic‐connectivity changes over time could lead to inaccurate conclusions.     

Sympatric sexual signal divergence among North American Calopteryx damselflies is correlated with increased intra- and interspecific male–male aggression

Divergence of sexual signals in sympatry can arise as a consequence of (1) interspecific competition for resources, (2) selection against maladaptive hybridization, or (3) as a result of selection to reduce the cost of interspecific aggression; termed agonistic character displacement (ACD). Calopterygid damselflies have emerged as a model system for studying the evolution of divergent sexual signals due to the repeated evolution of sympatric species pairs with fully and partially melanized wings. Damselfly wing patterns function during both courtship and territory defense. However, the relative contributions of natural and sexual selection to phenotypic divergence and enhanced isolation in sympatry remain unclear in many cases. Here, we investigated the hypothesis that interference competition, in the form of increased interspecific male–male aggression, drives the evolution of character displacement in sympatry between two species of North American damselflies, Calopteryx aequabilis and Calopteryx maculata, that show no evidence of ecological divergence or ongoing hybridization. In paired behavioral trials, we found that interspecific male aggression related to territory defense varied between site, species, and as a function of the relative abundance of con- vs. hetero-specific males. Specifically, we found that large-spotted C. aequabilis males received increased intra- and interspecific aggression but that aggression against large-spotted males declined during the middle of the flight season when both species were equally abundant. Based on these results, we suggest that ACD leads to enhanced species recognition, and may be a common outcome of the antagonism between interspecific male–male competition and the countervailing force of intraspecific sexual selection favoring increased wing melanization among territorial damselfly species.     

Material and energy recovery from Automotive Shredded Residues (ASR) via sequential gasification and combustion

Shredding is the common end-of-life treatment in Europe for dismantled car wrecks. It produces the so-called Automotive Shredded Residue (ASR), usually disposed of in landfill. This paper summarizes the outcome of a study carried out by Politecnico di Milano and LEAP with the support of Actelios SpA on the prospects of a technology based on sequential gasification and combustion of this specific waste stream. Its application to the treatment of ASR allows the recovery of large fractions of metals as non-oxidized, easily marketable secondary raw materials, the vitrification of most of the ash content and the production of power via a steam cycle. Results show that despite the unfavourable characteristics of ASR, the proposed technology can reach appealing energy performances. Three of four environmental impact indicators and the cumulative energy demand index are favourable, the main positive contributes being electricity production and metal recovery (mainly aluminium and copper). The only unfavourable indicator is the global warming index because, since most of the carbon in ASR comes from fossil sources, the carbon dioxide emissions at the stack of the thermal treatment plant are mainly non-renewable and, at the same time, the avoided biogas production from the alternative disposal route of landfilling is minor.     

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.