107 research outputs found
Seasonality constraints to livestock grazing intensity
Increasing food production is essential to meet the future food demand of a growing world population. In the light of pressing sustainability challenges like climate change and the importance of the global livestock system for food security as well as GHG emissions, finding ways to increasing food production sustainably and without increasing competition for food crops is essential. Yet, many unknowns relate to livestock grazing, in particular grazing intensity, an essential variable to assess the sustainability of livestock systems. Here we explore ecological limits to grazing intensity (GI; i.e., the fraction of Net Primary Production consumed by grazing animals) by analysing the role of seasonality in natural grasslands. We estimate seasonal limitations to GI by combining monthly Net Primary Production data and a map of global livestock distribution with assumptions on the length of non-favourable periods that can be bridged by livestock (e.g., by browsing dead standing biomass, storage systems or biomass conservation). This allows us to derive a seasonality-limited potential GI, which we compare with the GI prevailing in 2000. We find that GI in 2000 lies below its potential on 39% of the total global natural grasslands, which has a potential for increasing biomass extraction of up to 181 MtC/yr. In contrast, on 61% of the area GI exceeds the potential, made possible by management. Mobilizing this potential could increase milk production by 5%, meat production by 4%, or contribute to free up to 2.8 Mio kmÂČ of grassland area at the global scale if the numerous socio-ecological constraints can be overcome. We discuss socio-ecological trade-offs, which may reduce the estimated potential considerably and require the establishment of sound monitoring systems and an improved understanding of livestock systemâs role in the Earth system
Towards a Learning System for University Campuses as Living Labs for Sustainability
Universities, due to their sizeable estates and populations of staff and students, as well as their connections with, and impact within, their local and wider communities, have significant environmental, social and economic impacts. There is a strong movement for universities to become leaders in driving society towards a more sustainable future, through improving the sustainability of the built environment and the universitiesâ practices and operations, and through their educational, research and wider community engagement missions. Around the globe the concept of âLiving Labsâ has emerged as an instrument to integrate these different aspects to deliver sustainability improvements, through engaging multiple stakeholders in all of these areas, and through the co-creation of projects to improve the sustainability of the campus environment and operations, and to link these to the education, research, and wider community missions of the institution. This chapter describes a living, shared framework and methodology, the âCampus as Living Labâ learning system, created through global participatory workshops and Living Lab literature, aimed at supporting universities and their Sustainability (Coordinating) Offices in the development and monitoring of Living Lab projects. The framework includes seven categories of supportive data collection and three levels of details to meet different requirements of potential users. The Living Lab framework presented in this chapter, aims to create value and help universities maximise the benefit of Living Lab projects within an institution, support monitoring, reflection and learning from projects, and facilitate communication with stakeholders, and the sharing of practices and learning between peers across the globe. As a living shared, framework and learning system, the framework will adapt and develop over time and within different contexts. To provide feedback and fast (practical) learning from users, the system will be further developed to facilitate transparent peer reviewing
An Agent-Based Model of a Hepatic Inflammatory Response to Salmonella: A Computational Study under a Large Set of Experimental Data
Citation: Shi, Z. Z., Chapes, S. K., Ben-Arieh, D., & Wu, C. H. (2016). An Agent-Based Model of a Hepatic Inflammatory Response to Salmonella: A Computational Study under a Large Set of Experimental Data. Plos One, 11(8), 39. doi:10.1371/journal.pone.0161131We present an agent-based model (ABM) to simulate a hepatic inflammatory response (HIR) in a mouse infected by Salmonella that sometimes progressed to problematic proportions, known as "sepsis". Based on over 200 published studies, this ABM describes interactions among 21 cells or cytokines and incorporates 226 experimental data sets and/or data estimates from those reports to simulate a mouse HIR in silico. Our simulated results reproduced dynamic patterns of HIR reported in the literature. As shown in vivo, our model also demonstrated that sepsis was highly related to the initial Salmonella dose and the presence of components of the adaptive immune system. We determined that high mobility group box-1, C-reactive protein, and the interleukin-10: tumor necrosis factor-a ratio, and CD4+ T cell: CD8+ T cell ratio, all recognized as biomarkers during HIR, significantly correlated with outcomes of HIR. During therapy-directed silico simulations, our results demonstrated that anti-agent intervention impacted the survival rates of septic individuals in a time-dependent manner. By specifying the infected species, source of infection, and site of infection, this ABM enabled us to reproduce the kinetics of several essential indicators during a HIR, observe distinct dynamic patterns that are manifested during HIR, and allowed us to test proposed therapy-directed treatments. Although limitation still exists, this ABM is a step forward because it links underlying biological processes to computational simulation and was validated through a series of comparisons between the simulated results and experimental studies
Advances in reforming and partial oxidation of hydrocarbons for hydrogen production and fuel cell applications
One of the most attractive routes for the production of hydrogen or syngas for use in fuel cell applications is the reforming and partial oxidation of hydrocarbons. The use of hydrocarbons in high temperature fuel cells is achieved through either external or internal reforming. Reforming and partial oxidation catalysis to convert hydrocarbons to hydrogen rich syngas plays an important role in fuel processing technology. The current research in the area of reforming and partial oxidation of methane, methanol and ethanol includes catalysts for reforming and oxidation, methods of catalyst synthesis, and the effective utilization of fuel for both external and internal reforming processes. In this paper the recent progress in these areas of research is reviewed along with the reforming of liquid hydrocarbons, from this an overview of the current best performing catalysts for the reforming and partial oxidizing of hydrocarbons for hydrogen production is summarized
Exploring paths of chemical transformations in molecular and periodic systems: An approach utilizing force
Theoretical and computational studies of non-equilibrium and non-statistical dynamics in the gas phase, in the condensed phase and at interfaces
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