Evaluating and reducing a model of radiocaesium soil-plant uptake

An existing model of radiocaesium transfer to grasses was extended to include wheat and barley and parameterised using data from a wide range of soils and contact times. The model structure was revised and evaluated using a subset of the available data which was not used for model parameterisation. The resulting model was then used as a basis for systematic model reduction to test the utility of the model components. This analysis suggested that the use of 4 model variables (relating to radiocaesium adsorption on organic matter and the pH sensitivity of soil solution potassium concentration) and 1 model input (pH) are not required. The results of this analysis were used to develop a reduced model which was further evaluated in terms of comparisons to observations. The reduced model had an improved empirical performance and fewer adjustable parameters and soil characteristic inputs.     

Radiological maps for Trabzon, Turkey

The activity concentrations and absorbed gamma dose rates due to primordial radionuclides and ¹³⁷Cs have been ascertained in 222 soil samples in 18 counties of the Trabzon province of Turkey using a HPGe detector. The mean activity concentrations of ²³⁸U, ²³²Th, ⁴⁰K and ¹³⁷Cs in soil samples were 41, 35, 437 and 21 Bq kg⁻¹, respectively. Based on the measured concentrations of these radionuclides, the mean absorbed gamma dose in air was calculated as 59 nGy h⁻¹ and hence, the mean annual effective dose due to terrestrial gamma radiation was calculated as 72 μSv y⁻¹. In addition, outdoor in situ gamma dose rate (D) measurements were performed in the same 222 locations using a portable NaI detector and the annual effective dose was calculated to be 66 μSv y⁻¹ from these results. The results presented in this study are compared with other parts of Turkey. Radiological maps of the Trabzon province were composed using the results obtained from the study.     

Effect of americium-241 on luminous bacteria. Role of peroxides

The effect of americium-241 (²⁴¹Am), an alpha-emitting radionuclide of high specific activity, on luminous bacteria Photobacterium phosphoreum was studied. Traces of ²⁴¹Am in nutrient media (0.16-6.67 kBq/L) suppressed the growth of bacteria, but enhanced luminescence intensity and quantum yield at room temperature. Lower temperature (4 °C) increased the time of bacterial luminescence and revealed a stage of bioluminescence inhibition after 150 h of bioluminescence registration start. The role of conditions of exposure the bacterial cells to the ²⁴¹Am is discussed. The effect of ²⁴¹Am on luminous bacteria was attributed to peroxide compounds generated in water solutions as secondary products of radioactive decay. Increase of peroxide concentration in ²⁴¹Am solutions was demonstrated; and the similarity of ²⁴¹Am and hydrogen peroxide effects on bacterial luminescence was revealed. The study provides a scientific basis for elaboration of bioluminescence-based assay to monitor radiotoxicity of alpha-emitting radionuclides in aquatic solutions.     

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.     

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.     

Atmospheric composition change research: Time to go post-normal?

For more than two decades a number of frameworks for scientific knowledge production are being proposed by science and technology researchers. They all advocate an extended involvement of non-specialists, in particular when it comes to knowledge production applicable to practical societal problems. We look to what extent these new frameworks have taken ground within a particular research community: the ACCENT Network of Excellence which coordinates European atmospheric chemistry and physics research applicable to air pollution and climate change. We did so by stimulating a debate through a “blog”, a survey and in-depth interviews with ACCENT scientists about the interaction between science, policy making and civil society, to which a great deal of ACCENT member contributed in writing or verbally. Most of them had interactions with policy makers and/or the general public, and they generally believe that interactions with spheres other than the scientific are needed. While such interactions give personal insight and satisfaction, they seem to have little impact on the goals and the practice of the scientific work itself. Extended frameworks of science production that go beyond the disciplinary mode seem to emerge at the level of individual scientists, yet they still need to find their way to the level of scientific project management. In this paper we discuss the justifications and barriers to implement a higher degree of extended knowledge integration in applied science projects such as ACCENT. It is felt that the community of atmospheric chemists and physicists is mature for such an implementation and recommendations are given to help and make this happen.     

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.