Temperature and Tree Size Explain the Mean Time to Fall of Dead Standing Trees across Large Scales

Dead standing trees (DSTs) generally decompose slower than wood in contact with the forest floor. In many regions, DSTs are being created at an increasing rate due to accelerating tree mortality caused by climate change. Therefore, factors determining DST fall are crucial for predicting dead wood turnover time but remain poorly constrained. Here, we conduct a re-analysis of published DST fall data to provide standardized information on the mean time to fall (MTF) of DSTs across biomes. We used multiple linear regression to test covariates considered important for DST fall, while controlling for mortality and management effects. DSTs of species killed by fire, insects and other causes stood on average for 48, 13 and 19 years, but MTF calculations were sensitive to how tree size was accounted for. Species’ MTFs differed significantly between DSTs killed by fire and other causes, between coniferous and broadleaved plant functional types (PFTs) and between managed and unmanaged sites, but management did not explain MTFs when we distinguished by mortality cause. Mean annual temperature (MAT) negatively affected MTFs, whereas larger tree size or being coniferous caused DSTs to stand longer. The most important explanatory variables were MAT and tree size, with minor contributions of management and plant functional type depending on mortality cause. Our results provide a basis to improve the representation of dead wood decomposition in carbon cycle assessments

Synergistic associations of cognitive and motor impairments with functional outcome in covert cerebral small vessel disease

Background Cognitive and motor impairments are the key clinical manifestations of cerebral small vessel disease (SVD), but their combined effects on functional outcome have not been elucidated. This study investigated the interactions and mediating effects of cognitive and motor functions on instrumental activities of daily living (IADL) and quality of life in older individuals with various degrees of white matter hyperintensities (WMH). Methods Participants of the Helsinki Small Vessel Disease Study (n = 152) were assessed according to an extensive clinical, physical, neuropsychological and MRI protocol. Volumes of WMH and gray matter (GM) were obtained with automated segmentation. Results Cognitive (global cognition, executive functions, processing speed, memory) and motor functions (gait speed, single-leg stance, timed up-and-go) had strong interrelations with each other, and they were significantly associated with IADL, quality of life as well as WMH and GM volumes. A consistent pattern on significant interactions between cognitive and motor functions was found on informant-evaluated IADL, but not on self-evaluated quality of life. The association of WMH volume with IADL was mediated by global cognition, whereas the association of GM volume with IADL was mediated by global cognition and timed up-and-go performance. Conclusion The results highlight the complex interplay and synergism between motor and cognitive abilities on functional outcome in SVD. The combined effect of motor and cognitive disturbances on IADL is likely to be greater than their individual effects. Patients with both impairments are at disproportionate risk for poor outcome. WMH and brain atrophy contribute to disability through cognitive and motor impairment.Peer reviewe

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

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

Effects of a dual CCR3 and H1-antagonist on symptoms and eosinophilic inflammation in allergic rhinitis

<p>Abstract</p> <p>Background</p> <p>The CC-chemokine receptor-3 (CCR3) has emerged as a target molecule for pharmacological intervention in allergic inflammation.</p> <p>Objective</p> <p>To examine whether a dual CCR3 and H₁-receptor antagonist (AZD3778) affects allergic inflammation and symptoms in allergic rhinitis.</p> <p>Methods</p> <p>Patients with seasonal allergic rhinitis were subjected to three seven days' allergen challenge series. Treatment with AZD3778 was given in a placebo and antihistamine-controlled design. Symptoms and nasal peak inspiratory flow (PIF) were monitored in the morning, ten minutes post challenge, and in the evening. Nasal lavages were carried out at the end of each challenge series and α₂-macroglobulin, ECP, and tryptase were monitored as indices of allergic inflammation.</p> <p>Results</p> <p>Plasma levels of AZD3778 were stable throughout the treatment series. AZD3778 and the antihistamine (loratadine) reduced rhinitis symptoms recorded ten minutes post challenge during this period. AZD3778, but not the anti-histamine, also improved nasal PIF ten minutes post challenge. Furthermore, scores for morning and evening nasal symptoms from the last five days of the allergen challenge series showed statistically significant reductions for AZD3778, but not for loratadine. ECP was reduced by AZD3778, but not by loratadine.</p> <p>Conclusions</p> <p>AZD3778 exerts anti-eosinophil and symptom-reducing effects in allergic rhinitis and part of this effect can likely be attributed to CCR3-antagonism. The present data are of interest with regard to the potential use of AZD3778 in allergic rhinitis and to the relative importance of eosinophil actions to the symptomatology of allergic rhinitis.</p> <p>Trial registration</p> <p>EudraCT No: 2005-002805-21.</p

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

Carbon cycle uncertainty in the Alaskan Arctic

Climate change is leading to a disproportionately large warming in the high northern latitudes, but the magnitude and sign of the future carbon balance of the Arctic are highly uncertain. Using 40 terrestrial biosphere models for the Alaskan Arctic from four recent model intercomparison projects – NACP (North American Carbon Program) site and regional syntheses, TRENDY (Trends in net land atmosphere carbon exchanges), and WETCHIMP (Wetland and Wetland CH4 Inter-comparison of Models Project) – we provide a baseline of terrestrial carbon cycle uncertainty, defined as the multi-model standard deviation (σ) for each quantity that follows. Mean annual absolute uncertainty was largest for soil carbon (14.0 ± 9.2 kg C m−2), then gross primary production (GPP) (0.22 ± 0.50 kg C m−2 yr−1), ecosystem respiration (Re) (0.23 ± 0.38 kg C m−2 yr−1), net primary production (NPP) (0.14 ± 0.33 kg C m−2 yr−1), autotrophic respiration (Ra) (0.09 ± 0.20 kg C m−2 yr−1), heterotrophic respiration (Rh) (0.14 ± 0.20 kg C m−2 yr−1), net ecosystem exchange (NEE) (−0.01 ± 0.19 kg C m−2 yr−1), and CH4 flux (2.52 ± 4.02 g CH4 m−2 yr−1). There were no consistent spatial patterns in the larger Alaskan Arctic and boreal regional carbon stocks and fluxes, with some models showing NEE for Alaska as a strong carbon sink, others as a strong carbon source, while still others as carbon neutral. Finally, AmeriFlux data are used at two sites in the Alaskan Arctic to evaluate the regional patterns; observed seasonal NEE was captured within multi-model uncertainty. This assessment of carbon cycle uncertainties may be used as a baseline for the improvement of experimental and modeling activities, as well as a reference for future trajectories in carbon cycling with climate change in the Alaskan Arctic and larger boreal region