Assessment of myofascial pain syndrome among married female healthcare workers: a cross sectional comparative study in a tertiary care centre

Background: Myofascial pain syndrome (MPS) is common among females between ages 20-40 years. Psychosomatic and mechanical reasons are attributed as causative factors. Female health care workers (FHW) in hospitals with rapid patient turn over are vulnerable to develop MPS. Our aim was to ascertain the prevalence of MPS in married FHW working in various departments of the hospital and its association with poor sleep and work stress. Methods: We selected married FHWs in 20-50 years age group and divided them into two groups, medical and paramedical (those involved directly and indirectly with patient care respectively). MPS was diagnosed after detailed personal interview and clinical examination. Sleep duration was divided into less than 5 hours and more than 5hours. Presence of work-related stress and other medical parameters were also recorded. Results: A total of 150 medical and 150 paramedical FHWs were included in the study. Overall prevalence of MPS among FHWs was 42%, of which, medical group was 32% and paramedical was 52%. The paramedical group showed significantly higher prevalence of MPS (p: 0.02). Sleep was less than 5 hours in 29.3% of medical FHW and 13.3% of paramedical. This difference didn’t show any association to MPS (p=0.8). 38% FHW perceived excessive work stress, 40% were paramedical and 36% were medical. This didn’t correlate with prevalence of MPS (p=0.2) among them. Conclusions: Paramedical FHW experienced more MPS than medical and it was more of mechanical type and not due to work stress or sleep deprivation

Priming effect depending on land use and soil types in a typical semi-arid landscape in Kenya

Addition of labile carbon (C) inputs to soil can accelerate or slow down the decomposition of soil organic matter (SOM), a phenomenon known as priming effect (PE). However, the magnitude and direction of PE is often difficult to predict, consequently making its relationship with labile C inputs and nutrient availability elusive. To assess this relationship, we added 13C labelled glucose (corresponding to 50% of initial soil microbial biomass C) to two soil types (Vertisol and Acrisol) with different concentrations of available N and from four land use systems (agricultural, pasture, grassland and shrubland). Parallel laboratory incubations i.e. short-term (6 days) and long-term (6 months), were set up to determine the effect of land use and soil type (N availability) on PE. Addition of labelled glucose in solution led to the retardation of SOM mineralization (negative PE) in both soil types and across all land use systems. This is attributed to preferential substrate utilization characterized by the higher mineralization of added glucose. Land use systems and soil types with higher N-availability displayed weaker negative PE, which is in line with the stoichiometric decomposition theory. In conclusion, our study demonstrate that N-availability plays a major role in determining mineralization of labile C inputs, magnitude and direction of PE in the studied dryland soils and land use systems. The fact that 15–27% of the added 13C remained in the soil at the end of the 6 months incubation and PE was negative, indicates that continuous labile C inputs could contribute to C immobilization and stabilization in these semiarid soils. Moreover, 13C glucose remaining in soils after 6 months in semi-natural pastures was comparable to those under natural grassland and shrubland systems especially in Acrisols. This demonstrates that incorporation and maintaining a perennial cover of native pastures has the potential to increase C sequestration in African semi-arid agricultural soils and landscapes

Effects of a tree row on greenhouse gas fluxes, growing conditions and soil microbial communities on an oat field in Southern Finland

Agricultural ecosystems are facing critical loss of biodiversity, soil nutrients, and cultural values. Intensive crop production has caused landscape homogenisation, with trees and hedges increasingly disappearing from agricultural land. Changes in farming practices are essential to increase biodiversity and improve soil biogeochemical processes, such as nutrient cycling, soil carbon uptake, and sequestration, as well as to improve the resilience and fertility of farming systems. Agroforestry is an important practice for implementing and improving natural and cultural value of landscapes, but in northern countries, agroforestry methods remain rarely utilised. Our study was conducted in Southern Finland on an agricultural field where a row of willow and alder was planted 6 years prior to our study. We concentrated on the effects of the tree row on crop growing conditions and how far from the trees possible impacts can be observed. We studied soil properties, carbon dioxide (CO2), nitrous oxide (N2O), and methane (CH4) exchange, and soil microbial communities. The impact of trees on crop growing conditions, biomass production, and greenhouse gas fluxes was modest and did not extend further than few meters from the tree row in the warm and dry growing season of 2019. N2O and CH4 fluxes were negligible and the tree row did not increase greenhouse gas emissions from soil. Soil microbial diversity was clearly improved by the presence of trees due to more diverse habitats. The tree row also slightly decreased the estimated annual net emissions of carbon into the atmosphere. Due to positive indications of the effects of agroforestry on biodiversity and carbon uptake, we highly recommend further studies within various agroforestry practices in Nordic countries

Microbial carbon use efficiency along an altitudinal gradient

Soil microbial carbon-use efficiency (CUE), described as the ratio of growth over total carbon (C) uptake, i.e. the sum of growth and respiration, is a key variable in all soil organic matter (SOM) models and critical to ecosystem C cycling. However, there is still a lack of consensus on microbial CUE when estimated using different methods. Furthermore, the significance of many fundamental drivers of CUE remains largely unknown and inconclusive, especially for tropical ecosystems. For these reasons, we determined CUE and microbial indicators of soil nutrient availability in seven tropical forest soils along an altitudinal gradient (circa 900-2200 m a.s.l) occurring at Taita Hills, Kenya. We used this gradient to study the soil nutrient (N and P) availability and its relation to microbial CUE estimates. For assessing the soil nutrient availability, we determined both the soil bulk stoichiometric nutrient ratios (soil C:N, C:P and N:P), as well as SOM degradation related enzyme activities. We estimated soil microbial CUE using two methods: substrate independent O-18-water tracing and C-13-glucose tracing method. Based on these two approaches, we estimated the microbial uptake efficiency of added glucose versus native SOM, with the latter defined by 18O-water tracing method. Based on the bulk soil C:N stoichiometry, the studied soils did not reveal N limitation. However, soil bulk P limitation increased slightly with elevation. Additionally, based on extracellular enzyme activities, the SOM nutrient availability decreased with elevation. The C-13-CUE did not change with altitude indicating that glucose was efficiently taken up and used by the microbes. On the other hand, 18O-CUE, which reflects the growth efficiency of microbes growing on native SOM, clearly declined with increasing altitude and was associated with SOM nutrient availability indicators. Based on our results, microbes at higher elevations invested more energy to scavenge for nutrients and energy from complex SOM whereas at lower elevations the soil nutrients may have been more readily available.Peer reviewe

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

Barriers to predicting changes in global terrestrial methane fluxes: analyses using CLM4Me, a methane biogeochemistry model integrated in CESM

Terrestrial net CH<sub>4</sub> surface fluxes often represent the difference between much larger gross production and consumption fluxes and depend on multiple physical, biological, and chemical mechanisms that are poorly understood and represented in regional- and global-scale biogeochemical models. To characterize uncertainties, study feedbacks between CH<sub>4</sub> fluxes and climate, and to guide future model development and experimentation, we developed and tested a new CH<sub>4</sub> biogeochemistry model (CLM4Me) integrated in the land component (Community Land Model; CLM4) of the Community Earth System Model (CESM1). CLM4Me includes representations of CH<sub>4</sub> production, oxidation, aerenchyma transport, ebullition, aqueous and gaseous diffusion, and fractional inundation. As with most global models, CLM4 lacks important features for predicting current and future CH<sub>4</sub> fluxes, including: vertical representation of soil organic matter, accurate subgrid scale hydrology, realistic representation of inundated system vegetation, anaerobic decomposition, thermokarst dynamics, and aqueous chemistry. We compared the seasonality and magnitude of predicted CH<sub>4</sub> emissions to observations from 18 sites and three global atmospheric inversions. Simulated net CH<sub>4</sub> emissions using our baseline parameter set were 270, 160, 50, and 70 Tg CH<sub>4</sub> yr<sup>−1</sup> globally, in the tropics, in the temperate zone, and north of 45° N, respectively; these values are within the range of previous estimates. We then used the model to characterize the sensitivity of regional and global CH<sub>4</sub> emission estimates to uncertainties in model parameterizations. Of the parameters we tested, the temperature sensitivity of CH<sub>4</sub> production, oxidation parameters, and aerenchyma properties had the largest impacts on net CH<sub>4</sub> emissions, up to a factor of 4 and 10 at the regional and gridcell scales, respectively. In spite of these uncertainties, we were able to demonstrate that emissions from dissolved CH<sub>4</sub> in the transpiration stream are small (<1 Tg CH<sub>4</sub> yr<sup>−1</sup>) and that uncertainty in CH<sub>4</sub> emissions from anoxic microsite production is significant. In a 21st century scenario, we found that predicted declines in high-latitude inundation may limit increases in high-latitude CH<sub>4</sub> emissions. Due to the high level of remaining uncertainty, we outline observations and experiments that would facilitate improvement of regional and global CH<sub>4</sub> biogeochemical models

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

Global wetlands are believed to be climate sensitive, and are the largest natural emitters of methane (CH4). Increased wetland CH4 emissions could act as a positive feedback to future warming. The Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP) investigated our present ability to simulate large-scale wetland characteristics and corresponding CH4 emissions. To ensure inter-comparability, we used a common experimental protocol driving all models with the same climate and carbon dioxide (CO2) forcing datasets. The WETCHIMP experiments were conducted for model equilibrium states as well as transient simulations covering the last century. Sensitivity experiments investigated model response to changes in selected forcing inputs (precipitation, temperature, and atmospheric CO2 concentration). Ten models participated, covering the spectrum from simple to relatively complex, including models tailored either for regional or global simulations. The models also varied in methods to calculate wetland size and location, with some models simulating wetland area prognostically, while other models relied on remotely sensed inundation datasets, or an approach intermediate between the two. Four major conclusions emerged from the project. First, the suite of models demonstrate extensive disagreement in their simulations of wetland areal extent and CH4 emissions, in both space and time. Simple metrics of wetland area, such as the latitudinal gradient, show large variability, principally between models that use inundation dataset information and those that independently determine wetland area. Agreement between the models improves for zonally summed CH4 emissions, but large variation between the models remains. For annual global CH4 emissions, the models vary by ±40% of the all-model mean (190 Tg CH4 yr−1). Second, all models show a strong positive response to increased atmospheric CO2 concentrations (857 ppm) in both CH4 emissions and wetland area. In response to increasing global temperatures (+3.4 °C globally spatially uniform), on average, the models decreased wetland area and CH4 fluxes, primarily in the tropics, but the magnitude and sign of the response varied greatly. Models were least sensitive to increased global precipitation (+3.9 % globally spatially uniform) with a consistent small positive response in CH4 fluxes and wetland area. Results from the 20th century transient simulation show that interactions between climate forcings could have strong non-linear effects. Third, we presently do not have sufficient wetland methane observation datasets adequate to evaluate model fluxes at a spatial scale comparable to model grid cells (commonly 0.5°). This limitation severely restricts our ability to model global wetland CH4 emissions with confidence. Our simulated wetland extents are also difficult to evaluate due to extensive disagreements between wetland mapping and remotely sensed inundation datasets. Fourth, the large range in predicted CH4 emission rates leads to the conclusion that there is both substantial parameter and structural uncertainty in large-scale CH4 emission models, even after uncertainties in wetland areas are accounted for

Microbial carbon use efficiency along an altitudinal gradient

Soil microbial carbon-use efficiency (CUE), described as the ratio of growth over total carbon (C) uptake, i.e. the sum of growth and respiration, is a key variable in all soil organic matter (SOM) models and critical to ecosystem C cycling. However, there is still a lack of consensus on microbial CUE when estimated using different methods. Furthermore, the significance of many fundamental drivers of CUE remains largely unknown and inconclusive, especially for tropical ecosystems. For these reasons, we determined CUE and microbial indicators of soil nutrient availability in seven tropical forest soils along an altitudinal gradient (circa 900–2200 m a.s.l) occurring at Taita Hills, Kenya. We used this gradient to study the soil nutrient (N and P) availability and its relation to microbial CUE estimates. For assessing the soil nutrient availability, we determined both the soil bulk stoichiometric nutrient ratios (soil C:N, C:P and N:P), as well as SOM degradation related enzyme activities. We estimated soil microbial CUE using two methods: substrate independent 18O-water tracing and 13C-glucose tracing method. Based on these two approaches, we estimated the microbial uptake efficiency of added glucose versus native SOM, with the latter defined by 18O-water tracing method. Based on the bulk soil C:N stoichiometry, the studied soils did not reveal N limitation. However, soil bulk P limitation increased slightly with elevation. Additionally, based on extracellular enzyme activities, the SOM nutrient availability decreased with elevation. The 13C-CUE did not change with altitude indicating that glucose was efficiently taken up and used by the microbes. On the other hand, 18O-CUE, which reflects the growth efficiency of microbes growing on native SOM, clearly declined with increasing altitude and was associated with SOM nutrient availability indicators. Based on our results, microbes at higher elevations invested more energy to scavenge for nutrients and energy from complex SOM whereas at lower elevations the soil nutrients may have been more readily available

Sensitivity of wetland methane emissions to model assumptions: application and model testing against site observations

Peer reviewe

The performance of FLake in the Met Office Unified Model

We present results from the coupling of FLake to the Met Office Unified Model (MetUM). The coupling and initialisation are first described, and the results of testing the coupled model in local and global model configurations are presented. These show that FLake has a small statistical impact on screen temperature, but has the potential to modify the weather in the vicinity of areas of significant inland water. Examination of FLake lake ice has revealed that the behaviour of lakes in the coupled model is unrealistic in some areas of significant sub-grid orography. Tests of various modifications to ameliorate this behaviour are presented. The results indicate which of the possible model changes best improve the annual cycle of lake ice. As FLake has been developed and tuned entirely outside the Unified Model system, these results can be interpreted as a useful objective measure of the performance of the Unified Model in terms of its near-surface characteristics