Hydrocarbon biodegradation and soil microbial community response to repeated oil exposure

Bioremediation strategies continue to be developed to mitigate the environmental impact of petroleum hydrocarbon contamination. This study investigated the ability of soil microbiota, adapted by prior exposure, to biodegrade petroleum. Soils from Barrow Is. (W. Australia), a class A nature reserve and home to Australia’s largest onshore oil field, were exposed to Barrow production oil (50 ml/kg soil) and incubated (25 °C) for successive phases of 61 and 100 days. Controls in which oil was not added at Phase I or II were concurrently studied and all treatments were amended with the same levels of additional nutrient and water to promote microbial activity. Prior exposure resulted in accelerated biodegradation of most, but not all, hydrocarbon constituents in the production oil. Molecular biodegradation parameters measured using gas chromatography–mass spectrometry (GC–MS) showed that several aromatic constituents were degraded more slowly with increased oil history. The unique structural response of the soil microbial community was reflected by the response of different phospholipid fatty acid (PLFA) sub-classes (e.g. branched saturated fatty acids of odd or even carbon number) measured using a ratio termed Barrow PLFA ratio (B-PLFAr). The corresponding values of a previously proposed hydrocarbon degrading alteration index showed a negative correlation with hydrocarbon exposure, highlighting the site specificity of PLFA-based ratios and microbial community dynamics. B-PLFAr values increased with each Phase I and II addition of production oil. The different hydrocarbon biodegradation rates and responses of PLFA subclasses to the Barrow production oil probably relate to the relative bioavailability of production oil hydrocarbons. These different effects suggest preferred structural and functional microbial responses to anticipated contaminants may potentially be engineered by controlled pre-exposure to the same or closely related substrates. The bioremediation of soils freshly contaminated with petroleum could benefit from the addition of exhaustively bioremediated soils rich in biota primed for the impacting hydrocarbons.

A structural time series approach to modelling multiple and resurgent meat scares in Italy

This paper exploits a structural time series approach to model the time pattern of multiple and resurgent food scares and their direct and cross-product impacts on consumer response. A structural time series Almost Ideal Demand System (STS-AIDS) is embedded in a vector error correction framework to allow for dynamic effects (VEC-STS-AIDS). Italian aggregate household data on meat demand is used to assess the time-varying impact of a resurgent BSE crisis (1996 and 2000) and the 1999 Dioxin crisis. The VEC-STS-AIDS model monitors the short-run impacts and performs satisfactorily in terms of residuals diagnostics, overcoming the major problems encountered by the customary vector error correction approach.

Electro-optical properties of liquid crystal copolymers and their relationship to structural order

A range of side chain liquid crystal copolymers have been prepared using mesogenic and non-mesogenic units. It is found that high levels of the non-mesogenic moieties may be introduced without completely disrupting the organization of the liquid crystal phase. Incorporation of this comonomer causes a marked reduction in the glass transition temperature (Tg), presumably as a result of enhanced backbone mobility and a corresponding lowering of the nematic transition temperature, thereby restricting the temperature range for stability of the liquid crystal phase. The effect of the interactions between the various components of these side-chain polymers on their electro-optic responses is described. Infrared (i.r.) dichroism measurements have been made to determine the order parameters of the liquid crystalline side-chain polymers. By identifying a certain band (CN stretching) in the i.r. absorption spectrum, the order parameter of the mesogenic groups can be obtained. The temperature and composition dependence of the observed order parameter are related to the liquid crystal phase transitions and to the electro-optic response. It is found that the introduction of the non-mesogenic units into the polymer chain lowers the threshold voltage of the electro-optic response over and above that due to the reduction in the order parameter. The dynamic electro-optic responses are dominated by the temperature-dependent viscosity and evidence is presented for relaxation processes involving the polymer backbone which are on a time scale greater than that for the mesogenic side-chain units.

Response theory for equilibrium and non-equilibrium statistical mechanics: causality and generalized Kramers-Kronig relations

We consider the general response theory recently proposed by Ruelle for describing the impact of small perturbations to the non-equilibrium steady states resulting from Axiom A dynamical systems. We show that the causality of the response functions entails the possibility of writing a set of Kramers-Kronig (K-K) relations for the corresponding susceptibilities at all orders of nonlinearity. Nonetheless, only a special class of directly observable susceptibilities obey K-K relations. Specific results are provided for the case of arbitrary order harmonic response, which allows for a very comprehensive K-K analysis and the establishment of sum rules connecting the asymptotic behavior of the harmonic generation susceptibility to the short-time response of the perturbed system. These results set in a more general theoretical framework previous findings obtained for optical systems and simple mechanical models, and shed light on the very general impact of considering the principle of causality for testing self-consistency: the described dispersion relations constitute unavoidable benchmarks that any experimental and model generated dataset must obey. The theory exposed in the present paper is dual to the time-dependent theory of perturbations to equilibrium states and to non-equilibrium steady states, and has in principle similar range of applicability and limitations. In order to connect the equilibrium and the non equilibrium steady state case, we show how to rewrite the classical response theory by Kubo so that response functions formally identical to those proposed by Ruelle, apart from the measure involved in the phase space integration, are obtained. These results, taking into account the chaotic hypothesis by Gallavotti and Cohen, might be relevant in several fields, including climate research. In particular, whereas the fluctuation-dissipation theorem does not work for non-equilibrium systems, because of the non-equivalence between internal and external fluctuations, K-K relations might be robust tools for the definition of a self-consistent theory of climate change.

Relevance of sampling schemes in light of Ruelle's linear response theory

We reconsider the theory of the linear response of non-equilibrium steady states to perturbations. We �rst show that by using a general functional decomposition for space-time dependent forcings, we can de�ne elementary susceptibilities that allow to construct the response of the system to general perturbations. Starting from the de�nition of SRB measure, we then study the consequence of taking di�erent sampling schemes for analysing the response of the system. We show that only a speci�c choice of the time horizon for evaluating the response of the system to a general time-dependent perturbation allows to obtain the formula �rst presented by Ruelle. We also discuss the special case of periodic perturbations, showing that when they are taken into consideration the sampling can be �ne-tuned to make the de�nition of the correct time horizon immaterial. Finally, we discuss the implications of our results in terms of strategies for analyzing the outputs of numerical experiments by providing a critical review of a formula proposed by Reick.

The effect of nonlinearity in CO2 heating rates on the attribution of stratospheric ozone and temperature changes

An analysis of the attribution of past and future changes in stratospheric ozone and temperature to anthropogenic forcings is presented. The analysis is an extension of the study of Shepherd and Jonsson (2008) who analyzed chemistry-climate simulations from the Canadian Middle Atmosphere Model (CMAM) and attributed both past and future changes to changes in the external forcings, i.e. the abundances of ozone-depleting substances (ODS) and well-mixed greenhouse gases. The current study is based on a new CMAM dataset and includes two important changes. First, we account for the nonlinear radiative response to changes in CO2. It is shown that over centennial time scales the radiative response in the upper stratosphere to CO2 changes is significantly nonlinear and that failure to account for this effect leads to a significant error in the attribution. To our knowledge this nonlinearity has not been considered before in attribution analysis, including multiple linear regression studies. For the regression analysis presented here the nonlinearity was taken into account by using CO2 heating rate, rather than CO2 abundance, as the explanatory variable. This approach yields considerable corrections to the results of the previous study and can be recommended to other researchers. Second, an error in the way the CO2 forcing changes are implemented in the CMAM was corrected, which significantly affects the results for the recent past. As the radiation scheme, based on Fomichev et al. (1998), is used in several other models we provide some description of the problem and how it was fixed.

Intensification of winter transatlantic aviation turbulence in response to climate change

Atmospheric turbulence causes most weather-related aircraft incidents1. Commercial aircraft encounter moderate-or-greater turbulence tens of thousands of times each year worldwide, injuring probably hundreds of passengers (occasionally fatally), costing airlines tens of millions of dollars and causing structural damage to planes1, 2, 3. Clear-air turbulence is especially difficult to avoid, because it cannot be seen by pilots or detected by satellites or on-board radar4, 5. Clear-air turbulence is linked to atmospheric jet streams6, 7, which are projected to be strengthened by anthropogenic climate change8. However, the response of clear-air turbulence to projected climate change has not previously been studied. Here we show using climate model simulations that clear-air turbulence changes significantly within the transatlantic flight corridor when the concentration of carbon dioxide in the atmosphere is doubled. At cruise altitudes within 50–75° N and 10–60° W in winter, most clear-air turbulence measures show a 10–40% increase in the median strength of turbulence and a 40–170% increase in the frequency of occurrence of moderate-or-greater turbulence. Our results suggest that climate change will lead to bumpier transatlantic flights by the middle of this century. Journey times may lengthen and fuel consumption and emissions may increase. Aviation is partly responsible for changing the climate9, but our findings show for the first time how climate change could affect aviation.

Minor structural abnormalities in the infant face disrupt neural processing: a unique window into early caregiving responses

Infant faces elicit early, specific activity in the orbitofrontal cortex (OFC), a key cortical region for reward and affective processing. A test of the causal relationship between infant facial configuration and OFC activity is provided by naturally occurring disruptions to the face structure. One such disruption is cleft lip, a small change to one facial feature, shown to disrupt parenting. Using magnetoencephalography, we investigated neural responses to infant faces with cleft lip compared with typical infant and adult faces. We found activity in the right OFC at 140 ms in response to typical infant faces but diminished activity to infant faces with cleft lip or adult faces. Activity in the right fusiform face area was of similar magnitude for typical adult and infant faces but was significantly lower for infant faces with cleft lip. This is the first evidence that a minor change to the infant face can disrupt neural activity potentially implicated in caregiving.

Sensitivity of terrestrial precipitation trends to the structural evolution of sea surface temperatures

Pronounced intermodel differences in the projected response of land surface precipitation (LSP) to future anthropogenic forcing remain in the Coupled Model Intercomparison Project Phase 5 model integrations. A large fraction of the intermodel spread in projected LSP trends is demonstrated here to be associated with systematic differences in simulated sea surface temperature (SST) trends, especially the representation of changes in (i) the interhemispheric SST gradient and (ii) the tropical Pacific SSTs. By contrast, intermodel differences in global mean SST, representative of differing global climate sensitivities, exert limited systematic influence on LSP patterns. These results highlight the importance to regional terrestrial precipitation changes of properly simulating the spatial distribution of large-scale, remote changes as reflected in the SST response to increasing greenhouse gases. Moreover, they provide guidance regarding which region-specific precipitation projections may be potentially better constrained for use in climate change impact assessments.

Nonlinearity of ocean heat uptake during warming and cooling in the FAMOUS climate model

Atmospheric CO2 concentration is expected to continue rising in the coming decades, but natural or artificial processes may eventually reduce it. We show that, in the FAMOUS atmosphere-ocean general circulation model, the reduction of ocean heat content as radiative forcing decreases is greater than would be expected from a linear model simulation of the response to the applied forcings. We relate this effect to the behavior of the Atlantic meridional overturning circulation (AMOC): the ocean cools more efficiently with a strong AMOC. The AMOC weakens as CO2 rises, then strengthens as CO2 declines, but temporarily overshoots its original strength. This nonlinearity comes mainly from the accumulated advection of salt into the North Atlantic, which gives the system a longer memory. This implies that changes observed in response to different CO2 scenarios or from different initial states, such as from past changes, may not be a reliable basis for making projections.

Discovering biomarkers for antidepressant response: protocol from the Canadian biomarker integration network in depression (CAN-BIND) and clinical characteristics of the first patient cohort

Background Major Depressive Disorder (MDD) is among the most prevalent and disabling medical conditions worldwide. Identification of clinical and biological markers (“biomarkers”) of treatment response could personalize clinical decisions and lead to better outcomes. This paper describes the aims, design, and methods of a discovery study of biomarkers in antidepressant treatment response, conducted by the Canadian Biomarker Integration Network in Depression (CAN-BIND). The CAN-BIND research program investigates and identifies biomarkers that help to predict outcomes in patients with MDD treated with antidepressant medication. The primary objective of this initial study (known as CAN-BIND-1) is to identify individual and integrated neuroimaging, electrophysiological, molecular, and clinical predictors of response to sequential antidepressant monotherapy and adjunctive therapy in MDD. Methods CAN-BIND-1 is a multisite initiative involving 6 academic health centres working collaboratively with other universities and research centres. In the 16-week protocol, patients with MDD are treated with a first-line antidepressant (escitalopram 10–20 mg/d) that, if clinically warranted after eight weeks, is augmented with an evidence-based, add-on medication (aripiprazole 2–10 mg/d). Comprehensive datasets are obtained using clinical rating scales; behavioural, dimensional, and functioning/quality of life measures; neurocognitive testing; genomic, genetic, and proteomic profiling from blood samples; combined structural and functional magnetic resonance imaging; and electroencephalography. De-identified data from all sites are aggregated within a secure neuroinformatics platform for data integration, management, storage, and analyses. Statistical analyses will include multivariate and machine-learning techniques to identify predictors, moderators, and mediators of treatment response. Discussion From June 2013 to February 2015, a cohort of 134 participants (85 outpatients with MDD and 49 healthy participants) has been evaluated at baseline. The clinical characteristics of this cohort are similar to other studies of MDD. Recruitment at all sites is ongoing to a target sample of 290 participants. CAN-BIND will identify biomarkers of treatment response in MDD through extensive clinical, molecular, and imaging assessments, in order to improve treatment practice and clinical outcomes. It will also create an innovative, robust platform and database for future research.