Vitality club:a proof-of-principle of peer coaching for daily physical activity by older adults

Many age-related diseases can be prevented or delayed by daily physical activity. Unfortunately, many older adults do not perform physical activity at the recommended level. Professional interventions do not reach large numbers of older adults for a long period of time. We studied a peer-coach intervention, in which older adults coach each other, that increased daily physical activity of community dwelling older adults for over 6 years. We studied the format and effects of this peer coach intervention for possible future implementation elsewhere. Through interviews and participatory observation we studied the format of the intervention. We also used a questionnaire (n = 55) and collected 6-min walk test data (n = 261) from 2014 to 2016 to determine the motivations of participants and effects of the intervention on health, well-being and physical capacity. Vitality Club is a self-sustainable group of older adults that gather every weekday to exercise coached by an older adult. Members attend on average 2.5 days per week and retention rate is 77.5% after 6 years. The members perceived improvements in several health measures. In line with this, the 6-min walk test results of members of this Vitality Club improved with 21.7 meters per year, compared with the decline of 2-7 meters per year in the general population. This Vitality Club is successful in durably engaging its members in physical activity. The members perceive improvements in health that are in line with improvements in a physical function test. Because of the self-sustainable character of the intervention, peer coaching has the potential to be scaled up at low cost and increase physical activity in the increasing number of older adults

Tailoring information about climate change and its impacts

Resultaten van onderzoek naar klimaatverandering en de mogelijke effecten zijn vaak niet beschikbaar in een vorm waarin ze direct door anderen gebruikt kunnen worden. Gebruikers van klimaat- en impactinformatie hebben vaak ook geen goed overzicht over de beschikbare gegevens van alle sectoren en resultaten zijn soms inconsistent

N deposition and elevated CO2 on methane emissions: Differential responses of indirect effects compared to direct effects through litter chemistry feedbacks

Increases in atmospheric CO2 concentration and N deposition are expected to affect methane (CH4) production in soils and emission to the atmosphere, directly through increased plant litter production and indirectly through changes in substrate quality. We examined how CH4 emission responded to changes in litter quality under increased N and CO2, beyond differences in CH4 resulting from changes in litter production. We used senesced leaves from 13C-labeled plants of Molinia caerulea grown at elevated and ambient CO2 and affected by N fertilization to carry out two experiments: a laboratory litter incubation and a pot experiment. N fertilization increased N and decreased C concentrations in litter whereas elevated CO2 decreased litter quality as reflected in litter C and N concentrations and in the composition of lignin and saturated fatty acids within the litter. In contrast to our expectations, CH4 production in the laboratory incubation decreased when using litter from N-fertilized plants as substrate, whereas litter from elevated CO2 had no effect, compared to controls without N and at ambient CO2. Owing to high within-treatment variability in CH4 emissions, none of the treatment effects were reflected in the pot experiment. C mineralization rates were not affected by any of the treatments. The decrease in CH4 emissions due to indirect effects of N availability through litter quality changes (described here for the first time) contrast direct effects of N fertilization on CH4 production. The complex interaction of direct effects with indirect effects of increased N on litter quality may potentially result in a net decrease in CH4 emissions from wetlands in the long term.Fil: Pancotto, Veronica Andrea. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas; ArgentinaFil: Bodegom, P. M. van. University Of Amsterdam; Países BajosFil: Hal, J. van. University Of Amsterdam; Países BajosFil: Logtestijn, R. S. P. van. University Of Amsterdam; Países BajosFil: Blokker, P.. University Of Amsterdam; Países BajosFil: Toet, S.. University Of Amsterdam; Países Bajos. University Of York; Reino UnidoFil: Aerts, R.. University Of Amsterdam; Países Bajo

Do we (need to) care about canopy radiation schemes in DGVMs? Caveats and potential impacts

Dynamic global vegetation models (DGVMs) are an essential part of current state-of-the-art Earth system models. In recent years, the complexity of DGVMs has increased by incorporating new important processes like, e.g., nutrient cycling and land cover dynamics, while biogeophysical processes like surface radiation have not been developed much further. Canopy radiation models are however very important for the estimation of absorption and reflected fluxes and are essential for a proper estimation of surface carbon, energy and water fluxes. The present study provides an overview of current implementations of canopy radiation schemes in a couple of state-of-the-art DGVMs and assesses their accuracy in simulating canopy absorption and reflection for a variety of different surface conditions. Systematic deviations in surface albedo and fractions of absorbed photosynthetic active radiation (faPAR) are identified and potential impacts are assessed. The results show clear deviations for both, absorbed and reflected, surface solar radiation fluxes. FaPAR is typically underestimated, which results in an underestimation of gross primary productivity (GPP) for the investigated cases. The deviation can be as large as 25% in extreme cases. Deviations in surface albedo range between −0.15 ≤ Δα ≤ 0.36, with a slight positive bias on the order of Δα ≈ 0.04. Potential radiative forcing caused by albedo deviations is estimated at −1.25 ≤ RF ≤ −0.8 (W m−2), caused by neglect of the diurnal cycle of surface albedo. The present study is the first one that provides an assessment of canopy RT schemes in different currently used DGVMs together with an assessment of the potential impact of the identified deviations. The paper illustrates that there is a general need to improve the canopy radiation schemes in DGVMs and provides different perspectives for their improvement

Methane emissions from floodplains in the Amazon Basin: challenges in developing a process-based model for global applications

Tropical wetlands are estimated to represent about 50% of the natural wetland methane (CH₄) emissions and explain a large fraction of the observed CH₄ variability on timescales ranging from glacial–interglacial cycles to the currently observed year-to-year variability. Despite their importance, however, tropical wetlands are poorly represented in global models aiming to predict global CH₄ emissions. This publication documents a first step in the development of a process-based model of CH₄ emissions from tropical floodplains for global applications. For this purpose, the LPX-Bern Dynamic Global Vegetation Model (LPX hereafter) was slightly modified to represent floodplain hydrology, vegetation and associated CH₄ emissions. The extent of tropical floodplains was prescribed using output from the spatially explicit hydrology model PCR-GLOBWB. We introduced new plant functional types (PFTs) that explicitly represent floodplain vegetation. The PFT parameterizations were evaluated against available remote-sensing data sets (GLC2000 land cover and MODIS Net Primary Productivity). Simulated CH₄ flux densities were evaluated against field observations and regional flux inventories. Simulated CH₄ emissions at Amazon Basin scale were compared to model simulations performed in the WETCHIMP intercomparison project. We found that LPX reproduces the average magnitude of observed net CH₄ flux densities for the Amazon Basin. However, the model does not reproduce the variability between sites or between years within a site. Unfortunately, site information is too limited to attest or disprove some model features. At the Amazon Basin scale, our results underline the large uncertainty in the magnitude of wetland CH₄ emissions. Sensitivity analyses gave insights into the main drivers of floodplain CH₄ emission and their associated uncertainties. In particular, uncertainties in floodplain extent (i.e., difference between GLC2000 and PCR-GLOBWB output) modulate the simulated emissions by a factor of about 2. Our best estimates, using PCR-GLOBWB in combination with GLC2000, lead to simulated Amazon-integrated emissions of 44.4 ± 4.8 Tg yr⁻¹. Additionally, the LPX emissions are highly sensitive to vegetation distribution. Two simulations with the same mean PFT cover, but different spatial distributions of grasslands within the basin, modulated emissions by about 20%. Correcting the LPX-simulated NPP using MODIS reduces the Amazon emissions by 11.3%. Finally, due to an intrinsic limitation of LPX to account for seasonality in floodplain extent, the model failed to reproduce the full dynamics in CH₄ emissions but we proposed solutions to this issue. The interannual variability (IAV) of the emissions increases by 90% if the IAV in floodplain extent is accounted for, but still remains lower than in most of the WETCHIMP models. While our model includes more mechanisms specific to tropical floodplains, we were unable to reduce the uncertainty in the magnitude of wetland CH₄ emissions of the Amazon Basin. Our results helped identify and prioritize directions towards more accurate estimates of tropical CH₄ emissions, and they stress the need for more research to constrain floodplain CH₄ emissions and their temporal variability, even before including other fundamental mechanisms such as floating macrophytes or lateral water fluxes

Local ecosystem feedbacks and critical transitions in the climate

Global and regional climate models, such as those used in IPCC assessments, are the best tools available for climate predictions. Such models typically account for large-scale land-atmosphere feedbacks. However, these models omit local vegetationenvironment 5 feedbacks that are crucial for critical transitions in ecosystems. Here, we reveal the hypothesis that, if the balance of feedbacks is positive at all scales, local vegetation-environment feedbacks may trigger a cascade of amplifying effects, propagating from local to large scale, possibly leading to critical transitions in the largescale climate. We call for linking local ecosystem feedbacks with large-scale land10 atmosphere feedbacks in global and regional climate models in order to yield climate predictions that we are more confident about

Антибіотикопрофілактика в хірургії

Наук. кер.: М.Г. КононенкоГнійно-запальні післяопераційні ускладнення за останні десятиріччя набувають все більшої актуальності. Це вже стає проблемою. Такі ускладнення необхідно попереджувати. Для забезпечення тканин операційного поля антибіотиком у ефективній (бактерицидній) концентрації на весь період хірургічного втручання проводять антибіотикопрофілактику (АБП). Вона є складовою частиною комплексної профілактики гнійно-запальних ускладнень. При цитуванні документа, використовуйте посилання http://essuir.sumdu.edu.ua/handle/123456789/2734

Quantification of uncertainties in global grazing systems assessments

Livestock systems play a key role in global sustainability challenges like food security and climate change, yet, many unknowns and large uncertainties prevail. We present a systematic, spatially explicit assessment of uncertainties related to grazing intensity (GI), a key metric for assessing ecological impacts of grazing, by combining existing datasets on a) grazing feed intake, b) the spatial distribution of livestock, c) the extent of grazing land, and d) its net primary productivity (NPP). An analysis of the resulting 96 maps implies that on average 15% of the grazing land NPP is consumed by livestock. GI is low in most of worlds grazing lands but hotspots of very high GI prevail in 1% of the total grazing area. The agreement between GI maps is good on one fifth of the world's grazing area, while on the remainder it is low to very low. Largest uncertainties are found in global drylands and where grazing land bears trees (e.g., the Amazon basin or the Taiga belt). In some regions like India or Western Europe massive uncertainties even result in GI > 100% estimates. Our sensitivity analysis indicates that the input-data for NPP, animal distribution and grazing area contribute about equally to the total variability in GI maps, while grazing feed intake is a less critical variable. We argue that a general improvement in quality of the available global level datasets is a precondition for improving the understanding of the role of livestock systems in the context of global environmental change or food security

Present state of global wetland extent and wetland methane modelling: methodology of a model inter-comparison project (WETCHIMP)

The Wetland and Wetland CH4 Intercomparison of Models Project (WETCHIMP) was created to evaluate our present ability to simulate large-scale wetland characteristics and corresponding methane (CH4) emissions. A multi-model comparison is essential to evaluate the key uncertainties in the mechanisms and parameters leading to methane emissions. Ten modelling groups joined WETCHIMP to run eight global and two regional models with a common experimental protocol using the same climate and atmospheric carbon dioxide (CO2) forcing datasets. We reported the main conclusions from the intercomparison effort in a companion paper (Melton et al., 2013). Here we provide technical details for the six experiments, which included an equilibrium, a transient, and an optimized run plus three sensitivity experiments (temperature, precipitation, and atmospheric CO2 concentration). The diversity of approaches used by the models is summarized through a series of conceptual figures, and is used to evaluate the wide range of wetland extent and CH4 fluxes predicted by the models in the equilibrium run. We discuss relationships among the various approaches and patterns in consistencies of these model predictions. Within this group of models, there are three broad classes of methods used to estimate wetland extent: prescribed based on wetland distribution maps, prognostic relationships between hydrological states based on satellite observations, and explicit hydrological mass balances. A larger variety of approaches was used to estimate the net CH4 fluxes from wetland systems. Even though modelling of wetland extent and CH4 emissions has progressed significantly over recent decades, large uncertainties still exist when estimating CH4 emissions: there is little consensus on model structure or complexity due to knowledge gaps, different aims of the models, and the range of temporal and spatial resolutions of the models