Prevalence of tail biting in pigs and associations to carcass condemnations - a Finnish pilot study

The aim of this study was to investigate the prevalence of tail biting in Finland and the relationship between tail biting and carcass condemnation

Evaluation of land surface models in reproducing satellite-derived LAI over the high-latitude northern hemisphere. Part I: Uncoupled DGVMs

PublishedJournal ArticleLeaf Area Index (LAI) represents the total surface area of leaves above a unit area of ground and is a key variable in any vegetation model, as well as in climate models. New high resolution LAI satellite data is now available covering a period of several decades. This provides a unique opportunity to validate LAI estimates from multiple vegetation models. The objective of this paper is to compare new, satellite-derived LAI measurements with modeled output for the Northern Hemisphere. We compare monthly LAI output from eight land surface models from the TRENDY compendium with satellite data from an Artificial Neural Network (ANN) from the latest version (third generation) of GIMMS AVHRR NDVI data over the period 1986-2005. Our results show that all the models overestimate the mean LAI, particularly over the boreal forest. We also find that seven out of the eight models overestimate the length of the active vegetation-growing season, mostly due to a late dormancy as a result of a late summer phenology. Finally, we find that the models report a much larger positive trend in LAI over this period than the satellite observations suggest, which translates into a higher trend in the growing season length. These results highlight the need to incorporate a larger number of more accurate plant functional types in all models and, in particular, to improve the phenology of deciduous trees. © 2013 by the authors.The corresponding author also thanks the CONACYT-CECTI and the University of Exeter for their funding during the PhD studies. The National Center for Atmospheric Research is sponsored by the National Science Foundation

Sources of uncertainty in modeled land carbon storage within and across three MIPs: Diagnosis with three new techniques

This is the final version. Available from the American Meteorological Society via the DOI in this recordTerrestrial carbon cycle models have incorporated increasingly more processes as a means to achieve more-realistic representations of ecosystem carbon cycling. Despite this, there are large across-model variations in the simulation and projection of carbon cycling. Several model intercomparison projects (MIPs), for example, the fifth phase of the Coupled Model Intercomparison Project (CMIP5) (historical simulations), Trends in Net Land-Atmosphere Carbon Exchange (TRENDY), and Multiscale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), have sought to understand intermodel differences. In this study, the authors developed a suite of new techniques to conduct post-MIP analysis to gain insights into uncertainty sources across 25 models in the three MIPs. First, terrestrial carbon storage dynamics were characterized by a three-dimensional (3D) model output space with coordinates of carbon residence time, net primary productivity (NPP), and carbon storage potential. The latter represents the potential of an ecosystem to lose or gain carbon. This space can be used to measure how and why model output differs. Models with a nitrogen cycle generally exhibit lower annual NPP in comparison with other models, and mostly negative carbon storage potential. Second, a transient traceability framework was used to decompose any given carbon cycle model into traceable components and identify the sources of model differences. The carbon residence time (or NPP) was traced to baseline carbon residence time (or baseline NPP related to the maximum carbon input), environmental scalars, and climate forcing. Third, by applying a variance decomposition method, the authors show that the intermodel differences in carbon storage can be mainly attributed to the baseline carbon residence time and baseline NPP (>90% in the three MIPs). The three techniques developed in this study offer a novel approach to gain more insight from existing MIPs and can point out directions for future MIPs. Since this study is conducted at the global scale for an overview on intermodel differences, future studies should focus more on regional analysis to identify the sources of uncertainties and improve models at the specified mechanism level.This paper is financially supported by the Research and Development Special Fund for Public Welfare Industry of the Ministry of Water Research in China (201501028). JBF and CRS were supported in part by NASA’s Carbon Cycle Science program. JBF was also supported in part by NASA’s Terrestrial Ecology and Carbon Monitoring System programs. JT acknowledges RCN funded project EVA (229771) and BCCR-BIGCHANGE

Sources of uncertainty in modeled land carbon storage within and across three MIPs: Diagnosis with three new techniques

This is the final version. Available from the American Meteorological Society via the DOI in this recordTerrestrial carbon cycle models have incorporated increasingly more processes as a means to achieve more-realistic representations of ecosystem carbon cycling. Despite this, there are large across-model variations in the simulation and projection of carbon cycling. Several model intercomparison projects (MIPs), for example, the fifth phase of the Coupled Model Intercomparison Project (CMIP5) (historical simulations), Trends in Net Land-Atmosphere Carbon Exchange (TRENDY), and Multiscale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), have sought to understand intermodel differences. In this study, the authors developed a suite of new techniques to conduct post-MIP analysis to gain insights into uncertainty sources across 25 models in the three MIPs. First, terrestrial carbon storage dynamics were characterized by a three-dimensional (3D) model output space with coordinates of carbon residence time, net primary productivity (NPP), and carbon storage potential. The latter represents the potential of an ecosystem to lose or gain carbon. This space can be used to measure how and why model output differs. Models with a nitrogen cycle generally exhibit lower annual NPP in comparison with other models, and mostly negative carbon storage potential. Second, a transient traceability framework was used to decompose any given carbon cycle model into traceable components and identify the sources of model differences. The carbon residence time (or NPP) was traced to baseline carbon residence time (or baseline NPP related to the maximum carbon input), environmental scalars, and climate forcing. Third, by applying a variance decomposition method, the authors show that the intermodel differences in carbon storage can be mainly attributed to the baseline carbon residence time and baseline NPP (>90% in the three MIPs). The three techniques developed in this study offer a novel approach to gain more insight from existing MIPs and can point out directions for future MIPs. Since this study is conducted at the global scale for an overview on intermodel differences, future studies should focus more on regional analysis to identify the sources of uncertainties and improve models at the specified mechanism level.This paper is financially supported by the Research and Development Special Fund for Public Welfare Industry of the Ministry of Water Research in China (201501028). JBF and CRS were supported in part by NASA’s Carbon Cycle Science program. JBF was also supported in part by NASA’s Terrestrial Ecology and Carbon Monitoring System programs. JT acknowledges RCN funded project EVA (229771) and BCCR-BIGCHANGE

Multicriteria evaluation of discharge simulation in Dynamic Global Vegetation Models

PublishedJournal Article© 2015. American Geophysical Union. All Rights Reserved. In this study, we assessed the performance of discharge simulations by coupling the runoff from seven Dynamic Global Vegetation Models (DGVMs; LPJ, ORCHIDEE, Sheffield-DGVM, TRIFFID, LPJ-GUESS, CLM4CN, and OCN) to one river routing model for 16 large river basins. The results show that the seasonal cycle of river discharge is generally modeled well in the low and middle latitudes but not in the high latitudes, where the peak discharge (due to snow and ice melting) is underestimated. For the annual mean discharge, the DGVMs chained with the routing model show an underestimation. Furthermore, the 30 year trend of discharge is also underestimated. For the interannual variability of discharge, a skill score based on overlapping of probability density functions (PDFs) suggests that most models correctly reproduce the observed variability (correlation coefficient higher than 0.5; i.e., models account for 50% of observed interannual variability) except for the Lena, Yenisei, Yukon, and the Congo river basins. In addition, we compared the simulated runoff from different simulations where models were forced with either fixed or varying land use. This suggests that both seasonal and annual mean runoff has been little affected by land use change but that the trend itself of runoff is sensitive to land use change. None of the models when considered individually show significantly better performances than any other and in all basins. This suggests that based on current modeling capability, a regional-weighted average of multimodel ensemble projections might be appropriate to reduce the bias in future projection of global river discharge.National Natural Science Foundation of China. Grant Numbers: 41125004, 31321061, Chinese Ministry of Environmental Protection. Grant Number: 201209031, 111 Project. Grant Number: B14001, National Youth Top-notch Talent Support Program in China, Imbalance-P ERC-synergy, TRENDY, Global River Discharge Cente

Conformational and Structural Relaxations of Poly(ethylene oxide) and Poly(propylene oxide) Melts: Molecular Dynamics Study of Spatial Heterogeneity, Cooperativity, and Correlated Forward-Backward Motion

Performing molecular dynamics simulations for all-atom models, we characterize the conformational and structural relaxations of poly(ethylene oxide) and poly(propylene oxide) melts. The temperature dependence of these relaxation processes deviates from an Arrhenius law for both polymers. We demonstrate that mode-coupling theory captures some aspects of the glassy slowdown, but it does not enable a complete explanation of the dynamical behavior. When the temperature is decreased, spatially heterogeneous and cooperative translational dynamics are found to become more important for the structural relaxation. Moreover, the transitions between the conformational states cease to obey Poisson statistics. In particular, we show that, at sufficiently low temperatures, correlated forward-backward motion is an important aspect of the conformational relaxation, leading to strongly nonexponential distributions for the waiting times of the dihedrals in the various conformational statesComment: 13 pages, 13 figure

Study of Vibrations in a Short-Span Bridge Under Resonance Conditions Considering Train-Track Interaction

[EN] Resonance is a phenomenon of utmost importance in railways engineering, leading to vast damages both in track and vehicles. A short-span bridge has been modeled by means of a finite elements method model, calibrated and validated with real data, to study resonance vibrations induced by the passage of trains. Furthermore, the influence of vehicle speed and track damping on the vibrations registered on the rail, the sleeper and the bridge has been assessed. Different track and vehicle pathologies have been proposed and their effect on the resonance of the bridge has been evaluated.Ribes-Llario, F.; Velarte-González, JL.; Pérez-Garnes, JL.; Real Herráiz, JI. (2016). Study of Vibrations in a Short-Span Bridge Under Resonance Conditions Considering Train-Track Interaction. Latin American Journal of Solids and Structures. 13(7):1236-1249. doi:10.1590/1679-78252773S12361249137Ahlström, J., & Karlsson, B. (1999). Microstructural evaluation and interpretation of the mechanically and thermally affected zone under railway wheel flats. Wear, 232(1), 1-14. doi:10.1016/s0043-1648(99)00166-0Bian, X., Chao, C., Jin, W., & Chen, Y. (2011). A 2.5D finite element approach for predicting ground vibrations generated by vertical track irregularities. Journal of Zhejiang University-SCIENCE A, 12(12), 885-894. doi:10.1631/jzus.a11gt012Grassie, S. L., & Kalousek, J. (1993). Rail Corrugation: Characteristics, Causes and Treatments. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 207(1), 57-68. doi:10.1243/pime_proc_1993_207_227_02Gupta, A., & Singh Ahuja, A. (2014). Dynamic Analysis of Railway Bridges under High Speed Trains. Universal Journal of Mechanical Engineering, 2(6), 199-204. doi:10.13189/ujme.2014.020604Ju, S. H., & Lin, H. T. (2003). Resonance characteristics of high-speed trains passing simply supported bridges. Journal of Sound and Vibration, 267(5), 1127-1141. doi:10.1016/s0022-460x(02)01463-3Kwark, J. W., Choi, E. S., Kim, Y. J., Kim, B. S., & Kim, S. I. (2004). Dynamic behavior of two-span continuous concrete bridges under moving high-speed train. Computers & Structures, 82(4-5), 463-474. doi:10.1016/s0045-7949(03)00054-3Lu, Y., Mao, L., & Woodward, P. (2012). Frequency characteristics of railway bridge response to moving trains with consideration of train mass. Engineering Structures, 42, 9-22. doi:10.1016/j.engstruct.2012.04.007Makino, T., Yamamoto, M., & Fujimura, T. (2002). Effect of material on spalling properties of railroad wheels. Wear, 253(1-2), 284-290. doi:10.1016/s0043-1648(02)00117-5Mao, L., & Lu, Y. (2013). Critical Speed and Resonance Criteria of Railway Bridge Response to Moving Trains. Journal of Bridge Engineering, 18(2), 131-141. doi:10.1061/(asce)be.1943-5592.0000336Museros, P., Romero, M. ., Poy, A., & Alarcón, E. (2002). Advances in the analysis of short span railway bridges for high-speed lines. Computers & Structures, 80(27-30), 2121-2132. doi:10.1016/s0045-7949(02)00261-4Pal, S., Valente, C., Daniel, W., & Farjoo, M. (2012). Metallurgical and physical understanding of rail squat initiation and propagation. Wear, 284-285, 30-42. doi:10.1016/j.wear.2012.02.013Sheng, X., Jones, C. J. C., & Thompson, D. J. (2004). A theoretical model for ground vibration from trains generated by vertical track irregularities. Journal of Sound and Vibration, 272(3-5), 937-965. doi:10.1016/s0022-460x(03)00782-xSimon, S., Saulot, A., Dayot, C., Quost, X., & Berthier, Y. (2013). Tribological characterization of rail squat defects. Wear, 297(1-2), 926-942. doi:10.1016/j.wear.2012.11.011Wang, Y., Wei, Q., Shi, J., & Long, X. (2010). Resonance characteristics of two-span continuous beam under moving high speed trains. Latin American Journal of Solids and Structures, 7(2), 185-199. doi:10.1590/s1679-78252010000200005Xia, H., Zhang, N., & Guo, W. W. (2006). Analysis of resonance mechanism and conditions of train–bridge system. Journal of Sound and Vibration, 297(3-5), 810-822. doi:10.1016/j.jsv.2006.04.022Yang, Y. B., & Lin, C. W. (2005). Vehicle–bridge interaction dynamics and potential applications. Journal of Sound and Vibration, 284(1-2), 205-226. doi:10.1016/j.jsv.2004.06.03