Compilation of EINECS: Descriptions and definitions used for substances,impurities and mixtures

The European INventory of Existing commercial Chemical Substances (EINECS) lists all substances which were on the European Community Market between 1 January 1971 and 18 September 1981. Substances on EINECS are known as ‘existing’ substances. The EINECS inventory was drawn up by the European Commission to meet the requirements of article 13 of Directive 79/831/EEC [1]. EINECS was published in the Official Journal of the European Communities in 1990 [2]. This paper describes how individual substances, impurities and mixtures were defined and dealt with when registered for the EINECS inventory. It is the first in a series of such papers.     

Determining patterns of variability in ecological communities: time lag analysis revisited

All ecological communities experience change over time. One method to quantify temporal variation in the patterns of relative abundance of communities is time lag analysis (TLA). It uses a distance-based approach to study temporal community dynamics by regressing community dissimilarity over increasing time lags (one-unit lags, two-unit lags, three-unit lags). Here, we suggest some modifications to the method and revaluate its potential for detecting patterns of community change. We apply Hellinger distance based TLA to artificial data simulating communities with different levels of directional and stochastic dynamics and analyse their effects on the slope and its statistical significance. We conclude that statistical significance of the TLA slope (obtained by a Monte Carlo permutation procedure) is a valid criterion to discriminate between (i) communities with directional change in species composition, regardless whether it is caused by directional abundance change of the species or by stochastic change according to a Markov process, and (ii) communities that are composed of species with population sizes oscillating around a constant mean or communities whose species abundances are governed by a white noise process. TLA slopes range between 0.02 and 0.25, depending on the proportions of species with different dynamics; higher proportions of species with constant means imply shallower slopes; and higher proportions of species with stochastic dynamics or directional change imply steeper slopes. These values are broadly in line with TLA slopes from real world data. Caution must be exercised when TLA is used for the comparison of community time series with different lengths since the slope depends on time series length and tends to decrease non-linearly with it.     

Bridging the gap between ecophysiological and genetic knowledge to assess the adaptive potential of European beech

In this study we aimed to combine knowledge of the ecophysiology and genetics of European beech to assess the potential of this species to adapt to environmental change. Therefore, we performed field and experimental studies on the genetic and ecophysiological functioning of beech. This information was integrated through a coupled genetic–ecophysiological model for individual trees that was parameterized with information derived from our own studies or from the literature. Using the model, we evaluated the adaptive response of beech stands in two ways: firstly, through sensitivity analyses (of initial genetic diversity, pollen dispersal distance, heritability of selected phenotypic traits, and forest management, representing disturbances) and secondly, through the evaluation of the responses of phenotypic traits and their genetic diversity to four management regimes applied to 10 study plots distributed over Western Europe. The model results indicate that the interval between recruitment events strongly affects the rate of adaptive response, because selection is most severe during the early stages of forest development. Forest management regimes largely determine recruitment intervals and thereby the potential for adaptive responses. Forest management regimes also determine the number of mother trees that contribute to the next generation and thereby the genetic variation that is maintained. Consequently, undisturbed forests maintain the largest amount of genetic variation, as recruitment intervals approach the longevity of trees and many mother trees contribute to the next generation. However, undisturbed forests have the slowest adaptive response, for the same reasons.Gene flow through pollen dispersal may compensate for the loss in genetic diversity brought about by selection. The sensitivity analysis showed that the total genetic diversity of a 2 ha stand is not affected by gene flow if the pollen distance distribution is varied from highly left-skewed to almost flat. However, a stand with a prevailing short-distance gene flow has a more pronounced spatial genetic structure than stands with equal short- and long-distance gene flows. The build-up of a spatial genetic structure is also strongly determined by the recruitment interval. Overall, the modelling results indicate that European beech has high adaptive potential to environmental change if recruitment intervals are short and many mother trees contribute to the next generation.The findings have two implications for modelling studies on the impacts of climate change on forests. Firstly: it cannot be taken for granted that parameter values remain constant over a time horizon of even a few generations – this is particularly important for threshold values subject to strong selection, like budburst, frost hardiness, drought tolerance, as used in species area models. Secondly: forest management should be taken into account in future assessments, as management affects the rate of adaptive response and thereby the response on trees and forests to environmental change, and because few forests are unmanaged. We conclude that a coupled ecophysiological and quantitative genetic tree model is a useful tool for such studies.     

Spatial elements of mortality risk in old-growth forests

For many species of long-lived organisms, such as trees, survival appears to be the most critical vital rate affecting population persistence. However, methods commonly used to quantify tree death, such as relating tree mortality risk solely to diameter growth, almost certainly do not account for important spatial processes. Our goal in this study was to detect and, if present, to quantify the relevance of such processes. For this purpose, we examined purely spatial aspects of mortality for four species, Abies concolor, Abies magnifica, Calocedrus decurrens, and Pinus lambertiana, in an old-growth conifer forest in the Sierra Nevada of California, USA. The analysis was performed using data from nine fully mapped long-term monitoring plots. In three cases, the results unequivocally supported the inclusion of spatial information in models used to predict mortality. For Abies concolor, our results suggested that growth rate may not always adequately capture increased mortality risk due to competition. We also found evidence of a facilitative effect for this species, with mortality risk decreasing with proximity to conspecific neighbors. For Pinus lambertiana, mortality risk increased with density of conspecific neighbors, in keeping with a mechanism of increased pathogen or insect pressure (i.e., a Janzen-Connell type effect). Finally, we found that models estimating risk of being crushed were strongly improved by the inclusion of a simple index of spatial proximity. Not only did spatial indices improve models, those improvements were relevant for mortality prediction. For P. lambertiana, spatial factors were important for estimation of mortality risk regardless of growth rate. For A. concolor, although most of the population fell within spatial conditions in which mortality risk was well described by growth, trees that died occurred outside those conditions in a disproportionate fashion. Furthermore, as stands of A. concolor become increasingly dense, such spatial factors are likely to become increasingly important. In general, models that fail to account for spatial pattern are at risk of failure as conditions change.     

Sustainable nations: what do aggregate indexes tell us?

What is a ‘sustainable nation’ and how can we identify and rank ‘sustainable nations?’ Are nations producing and consuming in a sustainable way? Although several aggregate indexes have been proposed to answer such questions, comprehensive and internationally comparable data are not available for most of these. This paper quantitatively compares three aggregate indexes of sustainability: the World Bank’s ‘Genuine Savings’ measure, the ‘Ecological Footprint,’ and the ‘Environmental Sustainability Index.’ These three indexes are available for a large number of countries and also seem to be the most influential among the aggregate indexes. This paper first discusses the main limitations and weaknesses of each of these indexes. Subsequently, it shows that rankings of sustainable nations and aggregate assessments of unsustainable world population and world GDP shares vary considerably among these indexes. This disagreement leads to suggestions for analysis and policy. One important insight is that climate change, arguable the most serious threat currently faced by humanity, is not or arbitrarily captured by the indexes.     

Conceptualising climate change in rural Australia: community perceptions, attitudes and (in)actions

Public engagement and support is essential for ensuring adaptation to climate change. The first step in achieving engagement is documenting how the general public currently perceive and understand climate change issues, specifically the importance they place on this global problem and identifying any unique challenges for individual communities. For rural communities, which rely heavily on local agriculture industries, climate change brings both potential impacts and opportunities. Yet, to date, our knowledge about how rural residents conceptualise climate change is limited. Thus, this research explores how the broader rural community—not only farmers—conceptualises climate change and responsive activities, focussing on documenting the understandings and risk perceptions of local residents from two small Australian rural communities. Twenty-three semi-structured interviews were conducted in communities in the Eden/Gippsland region on the border of New South Wales and Victoria and the north-east of Tasmania. There are conflicting views on how climate change is conceptualised, the degree of concern and need for action, the role of local industry, who will ‘win’ and ‘lose’, and the willingness of rural communities to adapt. In particular, residents who believed in anthropogenic or human-induced factors described the changing climate as evidence of ‘climate change’, whereas those who were more sceptical termed it ‘weather variability’, suggesting that there is a divide in rural Australia that, unless urgently addressed, will hinder local and national policy responses to this global issue. Engaging these communities in the twenty-first-century climate change debate will require a significant change in terminology and communication strategies.     

Could wastewater analysis be a useful tool for China? — A review

Analysingwastewater samples is an innovative approach that overcomesmany limitations of traditional surveys to identify and measure a range of chemicals that were consumed by or exposed to people living in a sewer catchment area. First conceptualised in 2001, much progress has been made to make wastewater analysis (WWA) a reliable and robust tool for measuring chemical consumption and/or exposure. At the moment, the most popular application of WWA, sometimes referred as sewage epidemiology, is to monitor the consumption of illicit drugs in communities around the globe, including China. The approach has been largely adopted by lawenforcement agencies as a device tomonitor the temporal and geographical patterns of drug consumption. In the future, themethodology can be extended to other chemicals including biomarkers of population health (e.g. environmental or oxidative stress biomarkers, lifestyle indicators or medications that are taken by different demographic groups) and pollutants that people are exposed to (e.g. polycyclic aromatic hydrocarbons, perfluorinated chemicals, and toxic pesticides). The extension of WWA to a huge range of chemicals may give rise to a field called sewage chemical-information mining (SCIM) with unexplored potentials. China has many densely populated cities with thousands of sewage treatment plants which are favourable for applying WWA/SCIM in order to help relevant authorities gather information about illicit drug consumption and population health status. However, there are some prerequisites and uncertainties of the methodology that should be addressed for SCIM to reach its full potential in China.     

Modeling of Cs migration in soils using an 80-year soil archive: role of fertilizers and agricultural amendments

An 80-year soil archive, the 42-plot experimental design at the INRA in Versailles (France), is used here to study long-term contamination by ¹³⁷Cs atmospheric deposition and the fate of this radioisotope when associated with various agricultural practices: fallow land, KCl, NH₄(NO₃), superphosphate fertilizers, horse manure and lime amendments. The pertinence of a simple box model, where radiocaesium is supposed to move downward by convectional mechanisms, is checked using samples from control plots which had been neither amended, nor cultivated since 1928. This simple model presents the advantage of depending on only two parameters: α, a proportional factor allowing the historical atmospheric ¹³⁷Cs fluxes to be reconstructed locally, and k, an annual loss coefficient from the plow horizon. Another pseudo-unknown is however necessary to run the model: the shape of historical ¹³⁷Cs deposition, but this function can be easily computed by merging several curves previously established by other surveys. A loss of ∼1.5% per year from the plow horizon, combined with appropriate fluxes, provides good concordance between simulated and measured values. In the 0–25 cm horizon, the residence half time is found to be ∼18 yr (including both migration and radioactive decay). Migration rate constants are also calculated for some plots receiving continuous long-term agricultural treatments. Comparison with the control plots reveals significant influence of amendments on ¹³⁷Cs mobility in these soils developed from a unique genoform.