Potential role of vegetation feedback in the climate sensitivity of high-latitude regions: a case study at 6000 years B.P.

Previous climate model simulations have shown that the configuration of the Earth's orbit during the early to mid-Holocene (approximately 10–5 kyr) can account for the generally warmer-than-present conditions experienced by the high latitudes of the northern hemisphere. New simulations for 6 kyr with two atmospheric/mixed-layer ocean models (Community Climate Model, version 1, CCMl, and Global ENvironmental and Ecological Simulation of Interactive Systems, version 2, GENESIS 2) are presented here and compared with results from two previous simulations with GENESIS 1 that were obtained with and without the albedo feedback due to climate-induced poleward expansion of the boreal forest. The climate model results are summarized in the form of potential vegetation maps obtained with the global BIOME model, which facilitates visual comparisons both among models and with pollen and plant macrofossil data recording shifts of the forest-tundra boundary. A preliminary synthesis shows that the forest limit was shifted 100–200 km north in most sectors. Both CCMl and GENESIS 2 produced a shift of this magnitude. GENESIS 1 however produced too small a shift, except when the boreal forest albedo feedback was included. The feedback in this case was estimated to have amplified forest expansion by approximately 50%. The forest limit changes also show meridional patterns (greatest expansion in central Siberia and little or none in Alaska and Labrador) which have yet to be reproduced by models. Further progress in understanding of the processes involved in the response of climate and vegetation to orbital forcing will require both the deployment of coupled atmosphere-biosphere-ocean models and the development of more comprehensive observational data sets

The utility and application of mixed-effects models in second language research

Second language acquisition researchers often face particular challenges when attempting to generalize study findings to the wider learner population. For example, language learners constitute a heterogeneous group, and it is not always clear how a study’s findings may generalize to other individuals who may differ in terms of language background and proficiency, among many other factors. In this paper, we provide an overview of how mixed-effects models can be used to help overcome these and other issues in the field of second language acquisition. We provide an overview of the benefits of mixed-effects models and a practical example of how mixed-effects analyses can be conducted. Mixed-effects models provide second language researchers with a powerful statistical tool in the analysis of a variety of different types of data.

Clinical predictors of response to cognitive-behavioural therapy in pediatric anxiety disorders: the Genes for Treatment (GXT) Study

Objective The Genes for Treatment study is an international, multisite collaboration exploring the role of genetic, demographic, and clinical predictors in response to cognitive-behavioral therapy (CBT) in pediatric anxiety disorders. The current article, the first from the study, examined demographic and clinical predictors of response to CBT. We hypothesized that the child’s gender, type of anxiety disorder, initial severity and comorbidity, and parents’ psychopathology would significantly predict outcome. Method A sample of 1,519 children 5 to 18 years of age with a primary anxiety diagnosis received CBT across 11 sites. Outcome was defined as response (change in diagnostic severity) and remission (absence of the primary diagnosis) at each time point (posttreatment, 3-, 6-, and/or 12-month follow-up) and analyzed using linear and logistic mixed models. Separate analyses were conducted using data from posttreatment and follow-up assessments to explore the relative importance of predictors at these time points. Results Individuals with social anxiety disorder (SoAD) had significantly poorer outcomes (poorer response and lower rates of remission) than those with generalized anxiety disorder (GAD). Although individuals with specific phobia (SP) also had poorer outcomes than those with GAD at posttreatment, these differences were not maintained at follow-up. Both comorbid mood and externalizing disorders significantly predicted poorer outcomes at posttreatment and follow-up, whereas self-reported parental psychopathology had little effect on posttreatment outcomes but significantly predicted response (although not remission) at follow-up. Conclusion SoAD, nonanxiety comorbidity, and parental psychopathology were associated with poorer outcomes after CBT. The results highlight the need for enhanced treatments for children at risk for poorer outcomes.

Mixed-phase cloud physics and Southern Ocean cloud feedback in climate models

Increasing optical depth poleward of 45° is a robust response to warming in global climate models. Much of this cloud optical depth increase has been hypothesized to be due to transitions from ice-dominated to liquid-dominated mixed-phase cloud. In this study, the importance of liquid-ice partitioning for the optical depth feedback is quantified for 19 Coupled Model Intercomparison Project Phase 5 models. All models show a monotonic partitioning of ice and liquid as a function of temperature, but the temperature at which ice and liquid are equally mixed (the glaciation temperature) varies by as much as 40 K across models. Models that have a higher glaciation temperature are found to have a smaller climatological liquid water path (LWP) and condensed water path and experience a larger increase in LWP as the climate warms. The ice-liquid partitioning curve of each model may be used to calculate the response of LWP to warming. It is found that the repartitioning between ice and liquid in a warming climate contributes at least 20% to 80% of the increase in LWP as the climate warms, depending on model. Intermodel differences in the climatological partitioning between ice and liquid are estimated to contribute at least 20% to the intermodel spread in the high-latitude LWP response in the mixed-phase region poleward of 45°S. It is hypothesized that a more thorough evaluation and constraint of global climate model mixed-phase cloud parameterizations and validation of the total condensate and ice-liquid apportionment against observations will yield a substantial reduction in model uncertainty in the high-latitude cloud response to warming.

Genome-wide association study of response to cognitive behavioural therapy in children with anxiety disorders

Background Anxiety disorders are common, and cognitive–behavioural therapy (CBT) is a first-line treatment. Candidate gene studies have suggested a genetic basis to treatment response, but findings have been inconsistent. Aims To perform the first genome-wide association study (GWAS) of psychological treatment response in children with anxiety disorders (n = 980). Method Presence and severity of anxiety was assessed using semi-structured interview at baseline, on completion of treatment (post-treatment), and 3 to 12 months after treatment completion (follow-up). DNA was genotyped using the Illumina Human Core Exome-12v1.0 array. Linear mixed models were used to test associations between genetic variants and response (change in symptom severity) immediately post-treatment and at 6-month follow-up. Results No variants passed a genome-wide significance threshold (P = 5×10−8) in either analysis. Four variants met criteria for suggestive significance (P<5×10−6) in association with response post-treatment, and three variants in the 6-month follow-up analysis. Conclusions This is the first genome-wide therapygenetic study. It suggests no common variants of very high effect underlie response to CBT. Future investigations should maximise power to detect single-variant and polygenic effects by using larger, more homogeneous cohorts.

The role of local atmospheric forcing on the modulation of the ocean mixed layer depth in reanalysis and a coupled single column ocean model

The role of the local atmospheric forcing on the ocean mixed layer depth (MLD) over the global oceans is studied using ocean reanalysis data products and a single-column ocean model coupled to an atmospheric general circulation model. The focus of this study is on how the annual mean and the seasonal cycle of the MLD relate to various forcing characteristics in different parts of the world's ocean, and how anomalous variations in the monthly mean MLD relate to anomalous atmospheric forcings. By analysing both ocean reanalysis data and the single-column ocean model, regions with different dominant forcings and different mean and variability characteristics of the MLD can be identified. Many of the global oceans' MLD characteristics appear to be directly linked to different atmospheric forcing characteristics at different locations. Here, heating and wind-stress are identified as the main drivers; in some, mostly coastal, regions the atmospheric salinity forcing also contributes. The annual mean MLD is more closely related to the annual mean wind-stress and the MLD seasonality is more closely to the seasonality in heating. The single-column ocean model, however, also points out that the MLD characteristics over most global ocean regions, and in particular the tropics and subtropics, cannot be maintained by local atmospheric forcings only, but are also a result of ocean dynamics that are not simulated in a single-column ocean model. Thus, lateral ocean dynamics are essentially in correctly simulating observed MLD.