Projected 21st century decrease in marine productivity: a multi-model analysis

Changes in marine net primary productivity (PP) and export of particulate organic carbon (EP) are projected over the 21st century with four global coupled carbon cycle-climate models. These include representations of marine ecosystems and the carbon cycle of different structure and complexity. All four models show a decrease in global mean PP and EP between 2 and 20% by 2100 relative to preindustrial conditions, for the SRES A2 emission scenario. Two different regimes for productivity changes are consistently identified in all models. The first chain of mechanisms is dominant in the low- and mid-latitude ocean and in the North Atlantic: reduced input of macro-nutrients into the euphotic zone related to enhanced stratification, reduced mixed layer depth, and slowed circulation causes a decrease in macro-nutrient concentrations and in PP and EP. The second regime is projected for parts of the Southern Ocean: an alleviation of light and/or temperature limitation leads to an increase in PP and EP as productivity is fueled by a sustained nutrient input. A region of disagreement among the models is the Arctic, where three models project an increase in PP while one model projects a decrease. Projected changes in seasonal and interannual variability are modest in most regions. Regional model skill metrics are proposed to generate multi-model mean fields that show an improved skill in representing observation-based estimates compared to a simple multi-model average. Model results are compared to recent productivity projections with three different algorithms, usually applied to infer net primary production from satellite observations.

Webinar Training: an acceptable, feasible and effective approach for multi-site medical record abstraction: the BOWII experience

Background Abstractor training is a key element in creating valid and reliable data collection procedures. The choice between in-person vs. remote or simultaneous vs. sequential abstractor training has considerable consequences for time and resource utilization. We conducted a web-based (webinar) abstractor training session to standardize training across six individual Cancer Research Network (CRN) sites for a study of breast cancer treatment effects in older women (BOWII). The goals of this manuscript are to describe the training session, its participants and participants' evaluation of webinar technology for abstraction training. Findings A webinar was held for all six sites with the primary purpose of simultaneously training staff and ensuring consistent abstraction across sites. The training session involved sequential review of over 600 data elements outlined in the coding manual in conjunction with the display of data entry fields in the study's electronic data collection system. Post-training evaluation was conducted via Survey Monkey©. Inter-rater reliability measures for abstractors within each site were conducted three months after the commencement of data collection. Ten of the 16 people who participated in the training completed the online survey. Almost all (90%) of the 10 trainees had previous medical record abstraction experience and nearly two-thirds reported over 10 years of experience. Half of the respondents had previously participated in a webinar, among which three had participated in a webinar for training purposes. All rated the knowledge and information delivered through the webinar as useful and reported it adequately prepared them for data collection. Moreover, all participants would recommend this platform for multi-site abstraction training. Consistent with participant-reported training effectiveness, results of data collection inter-rater agreement within sites ranged from 89 to 98%, with a weighted average of 95% agreement across sites. Conclusions Conducting training via web-based technology was an acceptable and effective approach to standardizing medical record review across multiple sites for this group of experienced abstractors. Given the substantial time and cost savings achieved with the webinar, coupled with participants' positive evaluation of the training session, researchers should consider this instructional method as part of training efforts to ensure high quality data collection in multi-site studies.

Is the relation between early post-session reports and treatment outcome an epiphenomenon of intake distress and early response? A multi-predictor analysis in outpatient psychotherapy

The early phase of psychotherapy has been regarded as a sensitive period in the unfolding of psychotherapy leading to positive outcomes. However, there is disagreement about the degree to which early (especially relationship-related) session experiences predict outcome over and above initial levels of distress and early response to treatment. The goal of the present study was to simultaneously examine outcome at post treatment as a function of (a) intake symptom and interpersonal distress as well as early change in well-being and symptoms, (b) the patient's early session-experiences, (c) the therapist's early session-experiences/interventions, and (d) their interactions. The data of 430 psychotherapy completers treated by 151 therapists were analyzed using hierarchical linear models. Results indicate that early positive intra- and interpersonal session experiences as reported by patients and therapists after the sessions explained 58% of variance of a composite outcome measure, taking intake distress and early response into account. All predictors (other than problem-activating therapists' interventions) contributed to later treatment outcomes if entered as single predictors. However, the multi-predictor analyses indicated that interpersonal distress at intake as well as the early interpersonal session experiences by patients and therapists remained robust predictors of outcome. The findings underscore that early in therapy therapists (and their supervisors) need to understand and monitor multiple interconnected components simultaneously

Carbon dioxide and climate impulse response functions for the computation of greenhouse gas metrics: a multi-model analysis

The responses of carbon dioxide (CO2) and other climate variables to an emission pulse of CO2 into the atmosphere are often used to compute the Global Warming Potential (GWP) and Global Temperature change Potential (GTP), to characterize the response timescales of Earth System models, and to build reduced-form models. In this carbon cycle-climate model intercomparison project, which spans the full model hierarchy, we quantify responses to emission pulses of different magnitudes injected under different conditions. The CO2 response shows the known rapid decline in the first few decades followed by a millennium-scale tail. For a 100 Gt-C emission pulse added to a constant CO2 concentration of 389 ppm, 25 ± 9% is still found in the atmosphere after 1000 yr; the ocean has absorbed 59 ± 12% and the land the remainder (16 ± 14%). The response in global mean surface air temperature is an increase by 0.20 ± 0.12 °C within the first twenty years; thereafter and until year 1000, temperature decreases only slightly, whereas ocean heat content and sea level continue to rise. Our best estimate for the Absolute Global Warming Potential, given by the time-integrated response in CO2 at year 100 multiplied by its radiative efficiency, is 92.5 × 10−15 yr W m−2 per kg-CO2. This value very likely (5 to 95% confidence) lies within the range of (68 to 117) × 10−15 yr W m−2 per kg-CO2. Estimates for time-integrated response in CO2 published in the IPCC First, Second, and Fourth Assessment and our multi-model best estimate all agree within 15% during the first 100 yr. The integrated CO2 response, normalized by the pulse size, is lower for pre-industrial conditions, compared to present day, and lower for smaller pulses than larger pulses. In contrast, the response in temperature, sea level and ocean heat content is less sensitive to these choices. Although, choices in pulse size, background concentration, and model lead to uncertainties, the most important and subjective choice to determine AGWP of CO2 and GWP is the time horizon.

An optimized multi-proxy, multi-site Antarctic ice and gas orbital chronology (AICC2012): 120--800 ka

An accurate and coherent chronological framework is essential for the interpretation of climatic and environmental records obtained from deep polar ice cores. Until now, one common ice core age scale had been developed based on an inverse dating method (Datice), combining glaciological modelling with absolute and stratigraphic markers between 4 ice cores covering the last 50 ka (thousands of years before present) (Lemieux-Dudon et al., 2010). In this paper, together with the companion paper of Veres et al. (2013), we present an extension of this work back to 800 ka for the NGRIP, TALDICE, EDML, Vostok and EDC ice cores using an improved version of the Datice tool. The AICC2012 (Antarctic Ice Core Chronology 2012) chronology includes numerous new gas and ice stratigraphic links as well as improved evaluation of background and associated variance scenarios. This paper concentrates on the long timescales between 120–800 ka. In this framework, new measurements of δ18Oatm over Marine Isotope Stage (MIS) 11–12 on EDC and a complete δ18Oatm record of the TALDICE ice cores permit us to derive additional orbital gas age constraints. The coherency of the different orbitally deduced ages (from δ18Oatm, δO2/N2 and air content) has been verified before implementation in AICC2012. The new chronology is now independent of other archives and shows only small differences, most of the time within the original uncertainty range calculated by Datice, when compared with the previous ice core reference age scale EDC3, the Dome F chronology, or using a comparison between speleothems and methane. For instance, the largest deviation between AICC2012 and EDC3 (5.4 ka) is obtained around MIS 12. Despite significant modifications of the chronological constraints around MIS 5, now independent of speleothem records in AICC2012, the date of Termination II is very close to the EDC3 one.

Can the carbon isotopic composition of methane be reconstructed from multi-site firn air measurements?

Methane is a strong greenhouse gas and large uncertainties exist concerning the future evolution of its atmospheric abundance. Analyzing methane atmospheric mixing and stable isotope ratios in air trapped in polar ice sheets helps in reconstructing the evolution of its sources and sinks in the past. This is important to improve predictions of atmospheric CH4 mixing ratios in the future under the influence of a changing climate. The aim of this study is to assess whether past atmospheric δ13C(CH4) variations can be reliably reconstructed from firn air measurements. Isotope reconstructions obtained with a state of the art firn model from different individual sites show unexpectedly large discrepancies and are mutually inconsistent. We show that small changes in the diffusivity profiles at individual sites lead to strong differences in the firn fractionation, which can explain a large part of these discrepancies. Using slightly modified diffusivities for some sites, and neglecting samples for which the firn fractionation signals are strongest, a combined multi-site inversion can be performed, which returns an isotope reconstruction that is consistent with firn data. However, the isotope trends are lower than what has been concluded from Southern Hemisphere (SH) archived air samples and high-accumulation ice core data. We conclude that with the current datasets and understanding of firn air transport, a high precision reconstruction of δ13C of CH4 from firn air samples is not possible, because reconstructed atmospheric trends over the last 50 yr of 0.3–1.5 ‰ are of the same magnitude as inherent uncertainties in the method, which are the firn fractionation correction (up to ~2 ‰ at individual sites), the Kr isobaric interference (up to ~0.8 ‰, system dependent), inter-laboratory calibration offsets (~0.2 ‰) and uncertainties in past CH4 levels (~0.5 ‰).

Cardiopulmonary Bypass has No Significant Impact on Survival in Patients Undergoing Nephrectomy and Level III-IV Inferior Vena Cava Thrombectomy. A Multi-Institutional Analysis.

PURPOSE The impact of cardiopulmonary bypass in level III-IV tumor thrombectomy on surgical and oncologic outcomes is unknown. We determine the impact of cardiopulmonary bypass on overall and cancer specific survival, as well as surgical complication rates and immediate outcomes in patients undergoing nephrectomy and level III-IV tumor thrombectomy with or without cardiopulmonary bypass. MATERIALS AND METHODS We retrospectively analyzed 362 patients with renal cell cancer and with level III or IV tumor thrombus from 1992 to 2012 at 22 U.S. and European centers. Cox proportional hazards models were used to compare overall and cancer specific survival between patients with and without cardiopulmonary bypass. Perioperative mortality and complication rates were assessed using logistic regression analyses. RESULTS Median overall survival was 24.6 months in noncardiopulmonary bypass cases and 26.6 months in cardiopulmonary bypass cases. Overall survival and cancer specific survival did not differ significantly in both groups on univariate analysis or when adjusting for known risk factors. On multivariate analysis no significant differences were seen in hospital length of stay, Clavien 1-4 complication rate, intraoperative or 30-day mortality and cancer specific survival. Limitations include the retrospective nature of the study. CONCLUSIONS In our multi-institutional analysis the use of cardiopulmonary bypass did not significantly impact cancer specific survival or overall survival in patients undergoing nephrectomy and level III or IV tumor thrombectomy. Neither approach was independently associated with increased mortality on multivariate analysis. Greater surgical complications were not independently associated with the use of cardiopulmonary bypass.

How do subordinate and dominant species in semi-natural mountain grasslands relate to productivity and land-use change?

Changes in agricultural practices of semi-natural mountain grasslands are expected to modify plant community structure and shift dominance patterns. Using vegetation surveys of 11 sites in semi-natural grasslands of the Swiss Jura and Swiss and French Alps, we determined the relative contribution of dominant, subordinate and transient plant species in grazed and abandoned communities and observed their changes along a gradient of productivity and in response to abandonment of pasturing. The results confirm the humpbacked diversity–productivity relationship in semi-natural grassland, which is due to the increase of subordinate species number at intermediate productivity levels. Grazed communities, at the lower or higher end of the species diversity gradient, suffered higher species loss after grazing abandonment. Species loss after abandonment of pasturing was mainly due to a higher reduction in the number of subordinate species, as a consequence of the increasing proportion of dominant species. When plant biodiversity maintenance is the aim, our results have direct implications for the way grasslands should be managed. Indeed, while intensification and abandonment have been accelerated since few decades, our findings in this multi-site analysis confirm the importance of maintaining intermediate levels of pasturing to preserve biodiversity.

A Multi-Breed Genome-Wide Association Analysis for Canine Hypothyroidism Identifies a Shared Major Risk Locus on CFA12.

Hypothyroidism is a complex clinical condition found in both humans and dogs, thought to be caused by a combination of genetic and environmental factors. In this study we present a multi-breed analysis of predisposing genetic risk factors for hypothyroidism in dogs using three high-risk breeds-the Gordon Setter, Hovawart and the Rhodesian Ridgeback. Using a genome-wide association approach and meta-analysis, we identified a major hypothyroidism risk locus shared by these breeds on chromosome 12 (p = 2.1x10-11). Further characterisation of the candidate region revealed a shared ~167 kb risk haplotype (4,915,018-5,081,823 bp), tagged by two SNPs in almost complete linkage disequilibrium. This breed-shared risk haplotype includes three genes (LHFPL5, SRPK1 and SLC26A8) and does not extend to the dog leukocyte antigen (DLA) class II gene cluster located in the vicinity. These three genes have not been identified as candidate genes for hypothyroid disease previously, but have functions that could potentially contribute to the development of the disease. Our results implicate the potential involvement of novel genes and pathways for the development of canine hypothyroidism, raising new possibilities for screening, breeding programmes and treatments in dogs. This study may also contribute to our understanding of the genetic etiology of human hypothyroid disease, which is one of the most common endocrine disorders in humans.

A multi-model comparison of Atlantic multidecadal variability

A multi-model analysis of Atlantic multidecadal variability is performed with the following aims: to investigate the similarities to observations; to assess the strength and relative importance of the different elements of the mechanism proposed by Delworth et al. (J Clim 6:1993–2011, 1993) (hereafter D93) among coupled general circulation models (CGCMs); and to relate model differences to mean systematic error. The analysis is performed with long control simulations from ten CGCMs, with lengths ranging between 500 and 3600 years. In most models the variations of sea surface temperature (SST) averaged over North Atlantic show considerable power on multidecadal time scales, but with different periodicity. The SST variations are largest in the mid-latitude region, consistent with the short instrumental record. Despite large differences in model configurations, we find quite some consistency among the models in terms of processes. In eight of the ten models the mid-latitude SST variations are significantly correlated with fluctuations in the Atlantic meridional overturning circulation (AMOC), suggesting a link to northward heat transport changes. Consistent with this link, the three models with the weakest AMOC have the largest cold SST bias in the North Atlantic. There is no linear relationship on decadal timescales between AMOC and North Atlantic Oscillation in the models. Analysis of the key elements of the D93 mechanisms revealed the following: Most models present strong evidence that high-latitude winter mixing precede AMOC changes. However, the regions of wintertime convection differ among models. In most models salinity-induced density anomalies in the convective region tend to lead AMOC, while temperature-induced density anomalies lead AMOC only in one model. However, analysis shows that salinity may play an overly important role in most models, because of cold temperature biases in their relevant convective regions. In most models subpolar gyre variations tend to lead AMOC changes, and this relation is strong in more than half of the models.

Automatic multi-resolution shape modeling of multi-organ structures.

Point Distribution Models (PDM) are among the most popular shape description techniques and their usefulness has been demonstrated in a wide variety of medical imaging applications. However, to adequately characterize the underlying modeled population it is essential to have a representative number of training samples, which is not always possible. This problem is especially relevant as the complexity of the modeled structure increases, being the modeling of ensembles of multiple 3D organs one of the most challenging cases. In this paper, we introduce a new GEneralized Multi-resolution PDM (GEM-PDM) in the context of multi-organ analysis able to efficiently characterize the different inter-object relations, as well as the particular locality of each object separately. Importantly, unlike previous approaches, the configuration of the algorithm is automated thanks to a new agglomerative landmark clustering method proposed here, which equally allows us to identify smaller anatomically significant regions within organs. The significant advantage of the GEM-PDM method over two previous approaches (PDM and hierarchical PDM) in terms of shape modeling accuracy and robustness to noise, has been successfully verified for two different databases of sets of multiple organs: six subcortical brain structures, and seven abdominal organs. Finally, we propose the integration of the new shape modeling framework into an active shape-model-based segmentation algorithm. The resulting algorithm, named GEMA, provides a better overall performance than the two classical approaches tested, ASM, and hierarchical ASM, when applied to the segmentation of 3D brain MRI.

Working Alliance Inventory-Short Revised (WAI-SR): psychometric properties in outpatients and inpatients

The Working Alliance Inventory-Short Revised (WAI-SR) is a recently refined measure of the therapeutic alliance that assesses three key aspects of the therapeutic alliance: (a) agreement on the tasks of therapy, (b) agreement on the goals of therapy and (c) development of an affective bond. The WAI-SR demonstrated good psychometric properties in an initial validation in psychotherapy outpatients in the USA. The generalizability of these findings is limited because in some countries a substantial portion of individual psychotherapy is delivered in inpatient settings. This study investigated and compared the psychometric properties of the WAI-SR in German outpatients (N = 88) and inpatients (N = 243). In both samples reliability (alpha > 0.80) and convergent validity with the Helping Alliance Questionnaire were good (r > 0.64). Confirmatory factor analysis showed acceptable to good model fit for the proposed Bond-Task-Goal model in both samples. Multi-group analysis demonstrated that the same constructs were measured across settings. Alliance ratings of outpatients and inpatients differed regarding the overlap of alliance components and the magnitude of the alliance ratings: The differentiation of the alliance components was poorer in inpatients and they reported lower alliances. Unique aspects of the alliance in inpatient treatment are discussed and a need for further research on the alliance in inpatient settings is pointed out. Overall, the WAI-SR can be recommended for alliance assessment in both settings.

Deep ocean ventilation, carbon isotopes, marine sedimentation and the deglacial CO2 rise

The link between the atmospheric CO2 level and the ventilation state of the deep ocean is an important building block of the key hypotheses put forth to explain glacial-interglacial CO2 fluctuations. In this study, we systematically examine the sensitivity of atmospheric CO2 and its carbon isotope composition to changes in deep ocean ventilation, the ocean carbon pumps, and sediment formation in a global three-dimensional ocean-sediment carbon cycle model. Our results provide support for the hypothesis that a break up of Southern Ocean stratification and invigorated deep ocean ventilation were the dominant drivers for the early deglacial CO2 rise of ~35 ppm between the Last Glacial Maximum and 14.6 ka BP. Another rise of 10 ppm until the end of the Holocene is attributed to carbonate compensation responding to the early deglacial change in ocean circulation. Our reasoning is based on a multi-proxy analysis which indicates that an acceleration of deep ocean ventilation during the early deglaciation is not only consistent with recorded atmospheric CO2 but also with the reconstructed opal sedimentation peak in the Southern Ocean at around 16 ka BP, the record of atmospheric δ13CCO2, and the reconstructed changes in the Pacific CaCO3 saturation horizon.