Quality assessment of atmospheric surface fields over the Baltic Sea from an ensemble of regional climate model simulations with respect to ocean dynamics

Climate model results for the Baltic Sea region from an ensemble of eight simulations using the Rossby Centre Atmosphere model version 3 (RCA3) driven with lateral boundary data from global climate models (GCMs) are compared with results from a downscaled ERA40 simulation and gridded observations from 1980-2006. The results showed that data from RCA3 scenario simulations should not be used as forcing for Baltic Sea models in climate change impact studies because biases of the control climate significantly affect the simulated changes of future projections. For instance, biases of the sea ice cover in RCA3 in the present climate affect the sensitivity of the model's response to changing climate due to the ice-albedo feedback. From the large ensemble of available RCA3 scenario simulations two GCMs with good performance in downscaling experiments during the control period 1980-2006 were selected. In this study, only the quality of atmospheric surface fields over the Baltic Sea was chosen as a selection criterion. For the greenhouse gas emission scenario A1B two transient simulations for 1961-2100 driven by these two GCMs were performed using the regional, fully coupled atmosphere-ice-ocean model RCAO. It was shown that RCAO has the potential to improve the results in downscaling experiments driven by GCMs considerably, because sea surface temperatures and sea ice concentrations are calculated more realistically with RCAO than when RCA3 has been forced with surface boundary data from GCMs. For instance, the seasonal 2 m air temperature cycle is closer to observations in RCAO than in RCA3 downscaling simulations. However, the parameterizations of air-sea fluxes in RCAO need to be improved

Global parameter identification of stochastic reaction networks from single trajectories

We consider the problem of inferring the unknown parameters of a stochastic biochemical network model from a single measured time-course of the concentration of some of the involved species. Such measurements are available, e.g., from live-cell fluorescence microscopy in image-based systems biology. In addition, fluctuation time-courses from, e.g., fluorescence correlation spectroscopy provide additional information about the system dynamics that can be used to more robustly infer parameters than when considering only mean concentrations. Estimating model parameters from a single experimental trajectory enables single-cell measurements and quantification of cell--cell variability. We propose a novel combination of an adaptive Monte Carlo sampler, called Gaussian Adaptation, and efficient exact stochastic simulation algorithms that allows parameter identification from single stochastic trajectories. We benchmark the proposed method on a linear and a non-linear reaction network at steady state and during transient phases. In addition, we demonstrate that the present method also provides an ellipsoidal volume estimate of the viable part of parameter space and is able to estimate the physical volume of the compartment in which the observed reactions take place.Comment: Article in print as a book chapter in Springer's "Advances in Systems Biology

Synergistic and antagonistic effects of land use and non‐native species on community responses to climate change

Climate change, land‐use change and introductions of non‐native species are key determinants of biodiversity change worldwide. However, the extent to which anthropogenic drivers of environmental change interact to affect biological communities is largely unknown, especially over longer time periods. Here, we show that plant community composition in 996 Swedish landscapes has consistently shifted to reflect the warmer and wetter climate that the region has experienced during the second half of the 20th century. Using community climatic indices, which reflect the average climatic associations of the species within each landscape at each time period, we found that species compositions in 74% of landscapes now have a higher representation of warm‐associated species than they did previously, while 84% of landscapes now host more species associated with higher levels of precipitation. In addition to a warmer and wetter climate, there have also been large shifts in land use across the region, while the fraction of non‐native species has increased in the majority of landscapes. Climatic warming at the landscape level appeared to favour the colonization of warm‐associated species, while also potentially driving losses in cool‐associated species. However, the resulting increases in community thermal means were apparently buffered by landscape simplification (reduction in habitat heterogeneity within landscapes) in the form of increased forest cover. Increases in non‐native species, which generally originate from warmer climates than Sweden, were a strong driver of community‐level warming. In terms of precipitation, both landscape simplification and increases in non‐natives appeared to favour species associated with drier climatic conditions, to some extent counteracting the climate‐driven shift towards wetter communities. Anthropogenic drivers can act both synergistically and antagonistically to determine trajectories of change in biological communities over time. Therefore, it is important to consider multiple drivers of global change when trying to understand, manage and predict biodiversity in the future

Doubtful outcome of the validation of the Rome II questionnaire: validation of a symptom based diagnostic tool

<p>Abstract</p> <p>Background</p> <p>Questionnaires are used in research and clinical practice. For gastrointestinal complaints the Rome II questionnaire is internationally known but not validated. The aim of this study was to validate a printed and a computerized version of Rome II, translated into Swedish. Results from various analyses are reported.</p> <p>Methods</p> <p>Volunteers from a population based colonoscopy study were included (n = 1011), together with patients seeking general practice (n = 45) and patients visiting a gastrointestinal specialists' clinic (n = 67). The questionnaire consists of 38 questions concerning gastrointestinal symptoms and complaints. Diagnoses are made after a special code. Our validation included analyses of the translation, feasibility, predictability, reproducibility and reliability. Kappa values and overall agreement were measured. The factor structures were confirmed using a principal component analysis and Cronbach's alpha was used to test the internal consistency.</p> <p>Results and Discussion</p> <p>Translation and back translation showed good agreement. The questionnaire was easy to understand and use. The reproducibility test showed kappa values of 0.60 for GERS, 0.52 for FD, and 0.47 for IBS. Kappa values and overall agreement for the predictability when the diagnoses by the questionnaire were compared to the diagnoses by the clinician were 0.26 and 90% for GERS, 0.18 and 85% for FD, and 0.49 and 86% for IBS. Corresponding figures for the agreement between the printed and the digital version were 0.50 and 92% for GERS, 0.64 and 95% for FD, and 0.76 and 95% for IBS. Cronbach's alpha coefficient for GERS was 0.75 with a span per item of 0.71 to 0.76. For FD the figures were 0.68 and 0.54 to 0.70 and for IBS 0.61 and 0.56 to 0.66. The Rome II questionnaire has never been thoroughly validated before even if diagnoses made by the Rome criteria have been compared to diagnoses made in clinical practice.</p> <p>Conclusion</p> <p>The accuracy of the Swedish version of the Rome II is of doubtful value for clinical practice and research. The results for reproducibility and reliability were acceptable but the outcome of the predictability test was poor with IBS as an exception. The agreement between the digital and the paper questionnaire was good.</p

Integrating isotopes and documentary evidence : dietary patterns in a late medieval and early modern mining community, Sweden

We would like to thank the Archaeological Research Laboratory, Stockholm University, Sweden and the Tandem Laboratory (Ångström Laboratory), Uppsala University, Sweden, for undertaking the analyses of stable nitrogen and carbon isotopes in both human and animal collagen samples. Also, thanks to Elin Ahlin Sundman for providing the δ13C and δ15N values for animal references from Västerås. This research (Bäckström’s PhD employment at Lund University, Sweden) was supported by the Berit Wallenberg Foundation (BWS 2010.0176) and Jakob and Johan Söderberg’s foundation. The ‘Sala project’ (excavations and analyses) has been funded by Riksens Clenodium, Jernkontoret, Birgit and Gad Rausing’s Foundation, SAU’s Research Foundation, the Royal Physiographic Society of Lund, Berit Wallenbergs Foundation, Åke Wibergs Foundation, Lars Hiertas Memory, Helge Ax:son Johnson’s Foundation and The Royal Swedish Academy of Sciences.Peer reviewedPublisher PD

High Temperature Triggers Latent Variation among Individuals: Oviposition Rate and Probability for Outbreaks

It is anticipated that extreme population events, such as extinctions and outbreaks, will become more frequent as a consequence of climate change. To evaluate the increased probability of such events, it is crucial to understand the mechanisms involved. Variation between individuals in their response to climatic factors is an important consideration, especially if microevolution is expected to change the composition of populations.Here we present data of a willow leaf beetle species, showing high variation among individuals in oviposition rate at a high temperature (20 °C). It is particularly noteworthy that not all individuals responded to changes in temperature; individuals laying few eggs at 20 °C continued to do so when transferred to 12 °C, whereas individuals that laid many eggs at 20 °C reduced their oviposition and laid the same number of eggs as the others when transferred to 12 °C. When transferred back to 20 °C most individuals reverted to their original oviposition rate. Thus, high variation among individuals was only observed at the higher temperature. Using a simple population model and based on regional climate change scenarios we show that the probability of outbreaks increases if there is a realistic increase in the number of warm summers. The probability of outbreaks also increased with increasing heritability of the ability to respond to increased temperature.If climate becomes warmer and there is latent variation among individuals in their temperature response, the probability for outbreaks may increase. However, the likelihood for microevolution to play a role may be low. This conclusion is based on the fact that it has been difficult to show that microevolution affect the probability for extinctions. Our results highlight the urge for cautiousness when predicting the future concerning probabilities for extreme population events

Comparing correction methods of RCM outputs for improving crop impact projections in the Iberian Peninsula for 21st century

Assessment of climate change impacts on crops in regions of complex orography such as the Iberian Peninsula (IP) requires climate model output which is able to describe accurately the observed climate. The high resolution of output provided by Regional Climate Models (RCMs) is expected to be a suitable tool to describe regional and local climatic features, although their simulation results may still present biases. For these reasons, we compared several post-processing methods to correct or reduce the biases of RCM simulations from the ENSEMBLES project for the IP. The bias-corrected datasets were also evaluated in terms of their applicability and consequences in improving the results of a crop model to simulate maize growth and development at two IP locations, using this crop as a reference for summer cropping systems in the region. The use of bias-corrected climate runs improved crop phenology and yield simulation overall and reduced the inter-model variability and thus the uncertainty. The number of observational stations underlying each reference observational dataset used to correct the bias affected the correction performance. Although no single technique showed to be the best one, some methods proved to be more adequate for small initial biases, while others were useful when initial biases were so large as to prevent data application for impact studies. An initial evaluation of the climate data, the bias correction/reduction method and the consequences for impact assessment would be needed to design the most robust, reduced uncertainty ensemble for a specific combination of location, crop, and crop management