Supporting environmental modelling with Taverna workflows, web services and desktop grid technology

Ecosystem functioning, climate change, and multiple interactions among biogeochemical cycles, climate system, site conditions and land use options are leading-edge topics in recent environmental modelling. Terrestrial ecosystem models are widely used to support carbon sequestration and ecosystem studies under various ecological circumstances. Our team uses the Biome-BGC model (Numerical Terradynamic Simulation Group, University of Montana), and develops an improved model version of it, called Biome-BGC MuSo. Both the original and the improved model estimate the ecosystem scale storage and fluxes of energy, carbon, nitrogen and water, controlled by various physical and biological processes on a daily time-scale. Web services were also developed and integrated with parallel processing desktop grid technology. Taverna workflow management system was used to build up and carry out elaborated workflows like seamless data flow to model simulation, Monte Carlo experiment, model sensitivity analysis, model-data fusion, estimation of ecosystem service indicators or extensive spatial modelling. Straightforward management of complex data analysis tasks, organized into appropriately documented, shared and reusable scientific workflows enables researchers to carry out detailed and scientifically challenging ‘in silico’ experiments and applications that could open new directions in ecosystem research and in a broader sense it supports progress in environmental modelling. The workflow approach built upon these web services allows even the most complicated computations to be initiated without the need of programming skills and deep understanding of model structure and initialization. The developments enable a wider array of scientists to perform ecosystem scale simulations, and to perform analyses not previously possible due to high complexity and computational demand

Prevalence of other autoimmune diseases in polyglandular autoimmune syndromes type II and III

Polyglandular autoimmune syndromes (PAS) are complex, heterogeneous disorders in which various autoimmune diseases can occur, affecting both endocrine and non-endocrine organs. In this meta-analysis, the prevalence of associated autoimmune disorders was investigated in PAS II and III.A comprehensive search in MEDLINE and Embase databases identified 479 studies with the keywords of PAS II and PAS III. 18 records containing a total of 1312 patients fulfilled our inclusion criteria (original studies reporting at least 10 cases and containing the combination of other autoimmune disorders) and were selected for further analysis. A meta-analysis of prevalence was performed using the random-effects model with the calculation of 95% confidence intervals (CI). Results of each meta-analysis were displayed graphically using forest plots.Distinction between PAS II and PAS III was made in 842 cases, of which 177 and 665 were PAS II and III (21.1 vs 78.9%), respectively. The prevalence of Hashimoto's thyroiditis was significantly higher than that of Graves's disease (39% [95% CI 17-65%] vs. 4% [95% CI 0-10%], respectively; p = 0.001). In PAS II, Addison's disease (AD) coexisted with AITDs, T1DM or the combination of these conditions in 65, 18 and 10% of cases, respectively. In addition, one other endocrine and five non-endocrine organ-specific autoimmune disorders were reported. In PAS III, two other autoimmune endocrinopathies, six non-endocrine organ-specific, and four systemic autoimmune disorders were found in combination with AITDs.AITDs, T1DM and AD are the most common combinations in PAS, thus screening for these conditions seems to be reasonable

Mapping and linking supply- and demand-side measures in climate-smart agriculture. A review

Climate change and food security are two of humanity’s greatest challenges and are highly interlinked. On the one hand, climate change puts pressure on food security. On the other hand, farming significantly contributes to anthropogenic greenhouse gas emissions. This calls for climate-smart agriculture—agriculture that helps to mitigate and adapt to climate change. Climate-smart agriculture measures are diverse and include emission reductions, sink enhancements, and fossil fuel offsets for mitigation. Adaptation measures include technological advancements, adaptive farming practices, and financial management. Here, we review the potentials and trade-offs of climate-smart agricultural measures by producers and consumers. Our two main findings are as follows: (1) The benefits of measures are often site-dependent and differ according to agricultural practices (e.g., fertilizer use), environmental conditions (e.g., carbon sequestration potential), or the production and consumption of specific products (e.g., rice and meat). (2) Climate-smart agricultural measures on the supply side are likely to be insufficient or ineffective if not accompanied by changes in consumer behavior, as climate-smart agriculture will affect the supply of agricultural commodities and require changes on the demand side in response. Such linkages between demand and supply require simultaneous policy and market incentives. It, therefore, requires interdisciplinary cooperation to meet the twin challenge of climate change and food security. The link to consumer behavior is often neglected in research but regarded as an essential component of climate-smart agriculture. We argue for not solely focusing research and implementation on one-sided measures but designing good, site-specific combinations of both demand- and supply-side measures to use the potential of agriculture more effectively to mitigate and adapt to climate change

Time matters: Resilience of a post-disturbance forest landscape

Present-day disturbances are transforming European forest landscapes, and their legacies determine the vulnerability and resilience of the emergent forest generation. To understand these legacy effects, we investigated the resilience of the aboveground forest biomass (Babg) to a sequence of disturbances affecting the forest in different recovery phases from the initial large-scale impact. We used the model iLand to simulate windthrows that affected 13–24% of the Babg in a Central European forest landscape. An additional wind event was simulated 20, 40, 60, or 80 years after the initial impact (i.e., sequences of two windthrows were defined). Each windthrow triggered an outbreak of bark beetles that interacted with the recovery processes. We evaluated the resistance of the Babg to and recovery after the impact. Random Forest models were used to identify factors influencing resilience. We found that Babg resistance was the lowest 20 years after the initial impact when the increased proportion of emergent wind-exposed forest edges prevailed the disturbance-dampening effect of reduced biomass levels and increased landscape heterogeneity. This forest had a remarkably high recovery rate and reached the pre-disturbance Babg within 28 years. The forest exhibited a higher resistance and a slower recovery rate in the more advanced recovery phases, reaching the pre-disturbance Babg within 60–80 years. The recovery was enhanced by higher levels of alpha and beta diversity. Under elevated air temperature, the bark beetle outbreak triggered by windthrow delayed the recovery. However, the positive effect of increased temperature on forest productivity caused the recovery rate to be higher under the warming scenario than under the reference climate. We conclude that resilience is not a static property, but its magnitude and drivers vary in time, depending on vegetation feedbacks, interactions between disturbances, and climate. Understanding these mechanisms is an essential step towards the operationalization of resilience-oriented stewardship

Autoimmune polyendocrine syndrome in a standard poodle with concurrent non-endocrine immune-mediated diseases

A 6-year-old female neutered standard poodle was referred with a 4-week history of rapidly progressive weight loss, muscle atrophy, hyporexia, hind limb weakness and lethargy. In the preceding 3-month period, the dog had been diagnosed with both keratoconjunctivitis sicca (KCS) and hypoadrenocorticism. Clinical deterioration had occurred despite treatment for hypoadrenocorticism. Following referral, the dog was diagnosed with concurrent hypothyroidism, exocrine pancreatic insufficiency (EPI) and suspected generalised myositis. Treatment with hormone replacement therapy, pancreatic enzyme supplementation and immunosuppressive doses of prednisolone and mycophenolate resulted in marked clinical improvement. This case describes a rapidly progressive, presumed autoimmune, polyglandular endocrinopathy in a dog with concurrent non-endocrine autoimmune diseases