Educating the next generation of atmospheric scientists within a European Network of Excellence

In order to promote the next generation of atmospheric scientists, the task Training and Education (T&E) in ACCENT, the European Network of Excellence in Atmospheric Composition Change (www.accent-network.org) has developed and implemented an Integrated Learning Environment (ILE). For school teachers and their students, the Internet-based “Global Change Magazine” provides up-to-date and freely accessible scientific material in English and five other languages. Additionally, T&E has produced online teaching material for early-career scientists. These e-learning modules are now being used in University Master's courses across Europe. T&E also organised training events for early-career scientists, combining scientific content with development in transferable skills, to focus on interdisciplinary collaboration, interaction with senior scientists, communication with stakeholders, and dissemination to the general public. Evaluation based on participant feedback evidences the effectiveness of these events, e.g., in terms of motivation to remain in the field. Methodologies and materials from T&E are being published in a Handbook on Best Practice, intended for both educators and scientists around the globe who are involved in education in the field of air quality and climate change science.     

The stable isotope signature of methane emitted from plant material under UV irradiation

Recent experiments have shown that dry and fresh leaves, other plant matter, as well as several structural plant components, emit methane upon irradiation with UV light. Here we present the source isotope signatures of the methane emitted from a range of dry natural plant leaves and structural compounds. UV-induced methane from organic matter is strongly depleted in both ¹³C and D compared to the bulk biomass. The isotopic content of plant methoxyl groups, which have been identified as important precursors of aerobic methane formation in plants, falls roughly halfway between the bulk and CH₄ isotopic composition. C3 and C4/CAM plants show the well-established isotope difference in bulk ¹³C content. Our results show that they also emit CH₄ with different δ¹³C value. Furthermore, δ¹³C of methoxyl groups in the plant material, and ester methoxyl groups only, show a similar difference between C3 and C4/CAM plants. The correlation between the δ¹³C of emitted CH₄ and methoxyl groups implies that methoxyl groups are not the only source substrate of CH₄.Interestingly, δD values of the emitted CH₄ are also found to be different for C3 and C4 plants, although there is no significant difference in the bulk material. Bulk δD analyses may be compromised by a large reservoir of exchangeable hydrogen, but no significant δD difference is found either for the methoxyl groups, which do not contain exchangeable hydrogen. The δD difference in CH₄ between C3 and C4 plants indicates that at least two different reservoirs are involved in CH₄ emission. One of them is the OCH₃ group, the other one must be significantly depleted, and contribute more to the emissions of C3 plants compared to C4 plants. In qualitative agreement with this hypothesis, CH₄ emission rates are higher for C3 plants than for C4 plants.     

Effect of interior door position on room-to-room differences in residential pollutant concentrations after short-term releases

Residential interior door positions influence the pollutant concentrations that result from short-term indoor sources, such as cigarettes, candles, and incense. To elucidate this influence, we reviewed past studies and conducted new experiments in three residences: a single-story 714 m³ ranch-style house, a 510 m³ two-story split-level house, and a 200 m³ two-story house. During the experiments, we released sulfur hexafluoride or carbon monoxide tracer gas over short periods (≤30 min) and measured concentrations in the source room and at least one other (receptor) room for various interior door opening positions. We found that closing a door between rooms effectively prevented transport of air pollutants, reducing the average concentration in the receptor room relative to the source room by 57–100% over exposure periods of 1–8 h. When intervening doors were partially or fully open, the reduction in average concentrations ranged from 3% to 99%, varying as a function of door opening width and the distance between source and receptor rooms.     

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.     

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.     

Invasion versus Isolation: Trade-Offs in Managing Native Salmonids with Barriers to Upstream Movement

Abstract: Conservation biologists often face the trade‐off that increasing connectivity in fragmented landscapes to reduce extinction risk of native species can foster invasion by non‐native species that enter via the corridors created, which can then increase extinction risk. This dilemma is acute for stream fishes, especially native salmonids, because their populations are frequently relegated to fragments of headwater habitat threatened by invasion from downstream by 3 cosmopolitan non‐native salmonids. Managers often block these upstream invasions with movement barriers, but isolation of native salmonids in small headwater streams can increase the threat of local extinction. We propose a conceptual framework to address this worldwide problem that focuses on 4 main questions. First, are populations of conservation value present (considering evolutionary legacies, ecological functions, and socioeconomic benefits as distinct values)? Second, are populations vulnerable to invasion and displacement by non‐native salmonids? Third, would these populations be threatened with local extinction if isolated with barriers? And, fourth, how should management be prioritized among multiple populations? We also developed a conceptual model of the joint trade‐off of invasion and isolation threats that considers the opportunities for managers to make strategic decisions. We illustrated use of this framework in an analysis of the invasion‐isolation trade‐off for native cutthroat trout (Oncorhynchus clarkii) in 2 contrasting basins in western North America where invasion and isolation are either present and strong or farther away and apparently weak. These cases demonstrate that decisions to install or remove barriers to conserve native salmonids are often complex and depend on conservation values, environmental context (which influences the threat of invasion and isolation), and additional socioeconomic factors. Explicit analysis with tools such as those we propose can help managers make sound decisions in such complex circumstances.     

土壤优先流的理论研究和试验分析

在活动流场模型的基础上建立了新的溶质运移控制方程,研究了流场分形特征参数的计算方法;采用4组染色示踪试验资料,分析了活动流场模型模拟土壤水流运动和溶质运移宏观非均匀特征的适用性.模拟分析表明,活动流场模型能较准确地捕捉到土壤中的优先流特别是不稳定流的宏观运动特征;土壤存在大孔隙结构的情况下,水流和溶质将更快的迁移到深层土壤,活动流场模型模拟计算的入渗深度偏小,但大于连续性模型的模拟计算结果;当土壤中的大孔隙结构较少时,活动流场模型模拟预测的土壤含水率分布和溶质浓度分布与实测结果比较一致.