Microbial community structure and soil pH correspond to methane production in Arctic Alaska soils

While there is no doubt that biogenic methane production in the Arctic is an important aspect of global methane emissions, the relative roles of microbial community characteristics and soil environmental conditions in controlling Arctic methane emissions remains uncertain. Here, relevant methane‐cycling microbial groups were investigated at two remote Arctic sites with respect to soil potential methane production (PMP). Percent abundances of methanogens and iron‐reducing bacteria correlated with increased PMP, while methanotrophs correlated with decreased PMP. Interestingly, α‐diversity of the methanogens was positively correlated with PMP, while β‐diversity was unrelated to PMP. The β‐diversity of the entire microbial community, however, was related to PMP. Shannon diversity was a better correlate of PMP than Simpson diversity across analyses, while rarefied species richness was a weak correlate of PMP. These results demonstrate the following: first, soil pH and microbial community structure both probably control methane production in Arctic soils. Second, there may be high functional redundancy in the methanogens with regard to methane production. Third, iron‐reducing bacteria co‐occur with methanogens in Arctic soils, and iron‐reduction‐mediated effects on methanogenesis may be controlled by α‐ and β‐diversity. And finally, species evenness and rare species abundances may be driving relationships between microbial groups, influencing Arctic methane production

Tundra water budget and implications of precipitation underestimation

Difficulties in obtaining accurate precipitation measurements have limited meaningful hydrologic assessment for over a century due to performance challenges of conventional snowfall and rainfall gauges in windy environments. Here, we compare snowfall observations and bias adjusted snowfall to end-of-winter snow accumulation measurements on the ground for 16 years (1999–2014) and assess the implication of precipitation underestimation on the water balance for a low-gradient tundra wetland near Utqiagvik (formerly Barrow), Alaska (2007–2009). In agreement with other studies, and not accounting for sublimation, conventional snowfall gauges captured 23–56% of end-of-winter snow accumulation. Once snowfall and rainfall are bias adjusted, long-term annual precipitation estimates more than double (from 123 to 274 mm), highlighting the risk of studies using conventional or unadjusted precipitation that dramatically under-represent water balance components. Applying conventional precipitation information to the water balance analysis produced consistent storage deficits (79 to 152 mm) that were all larger than the largest actual deficit (75 mm), which was observed in the unusually low rainfall summer of 2007. Year-to-year variability in adjusted rainfall (±33 mm) was larger than evapotranspiration (±13 mm). Measured interannual variability in partitioning of snow into runoff (29% in 2008 to 68% in 2009) in years with similar end-of-winter snow accumulation (180 and 164 mm, respectively) highlights the importance of the previous summer's rainfall (25 and 60 mm, respectively) on spring runoff production. Incorrect representation of precipitation can therefore have major implications for Arctic water budget descriptions that in turn can alter estimates of carbon and energy fluxes

Group Psychological Treatment Preferences of Individuals Living With Chronic Disease: Brief Report of a Saskatchewan-Based Cross-Sectional Survey

Given that individuals with chronic diseases comorbid with psychological distress experience worse clinical outcomes than those without psychological distress, treatment of the psychological sequalae that accompanies chronic diseases is of utmost importance. Thus, the present study aimed to examine group treatment preferences among adults living with chronic disease in Saskatchewan, Canada. An online survey regarding group treatment preferences was administered to 207 participants living with chronic disease comorbid with psychological distress. The most often reported treatment scenario was virtual sessions (45%) lasting 1 h (51%) and occurring every other week (45%) in the evening (63%) for 3 to4 months (40%). Preferences included a medium group (48%), a relatively closed group nature (ie, only occasional new members; 44%), and group leadership including at least 1 professional living with chronic disease (54%). Future-oriented (81%), supportive (83%), skill-based (95%), and group discussions (78%) were desired treatment characteristics among participants. Survey results showed clear preferences on treatment content and session logistics. Slight variations exist by gender and age, but a consensus can be identified and act as a preliminary treatment plan. This study contributes to the body of literature on psychological treatment preferences for individuals living with chronic disease by outlining the preferred format and composition of groups according to those with lived experience. Group-based psychological treatment for chronic disease patients should account for these preferences to improve its acceptability and usefulness among patients

Mapping arctic tundra vegetation communities using field spectroscopy and multispectral satellite data in North Alaska, USA

The Arctic is currently undergoing intense changes in climate; vegetation composition and productivity are expected to respond to such changes. To understand the impacts of climate change on the function of Arctic tundra ecosystems within the global carbon cycle, it is crucial to improve the understanding of vegetation distribution and heterogeneity at multiple scales. Information detailing the fine-scale spatial distribution of tundra communities provided by high resolution vegetation mapping, is needed to understand the relative contributions of and relationships between single vegetation community measurements of greenhouse gas fluxes (e.g., ~1 m chamber flux) and those encompassing multiple vegetation communities (e.g., ~300 m eddy covariance measurements). The objectives of this study were: (1) to determine whether dominant Arctic tundra vegetation communities found in different locations are spectrally distinct and distinguishable using field spectroscopy methods; and (2) to test which combination of raw reflectance and vegetation indices retrieved from field and satellite data resulted in accurate vegetation maps and whether these were transferable across locations to develop a systematic method to map dominant vegetation communities within larger eddy covariance tower footprints distributed along a 300 km transect in northern Alaska. We showed vegetation community separability primarily in the 450-510 nm, 630-690 nm and 705-745 nm regions of the spectrum with the field spectroscopy data. This is line with the different traits of these arctic tundra communities, with the drier, often non-vascular plant dominated communities having much higher reflectance in the 450-510 nm and 630-690 nm regions due to the lack of photosynthetic material, whereas the low reflectance values of the vascular plant dominated communities highlight the strong light absorption found here. High classification accuracies of 92% to 96% were achieved using linear discriminant analysis with raw and rescaled spectroscopy reflectance data and derived vegetation indices. However, lower classification accuracies (~70%) resulted when using the coarser 2.0 m WorldView-2 data inputs. The results from this study suggest that tundra vegetation communities are separable using plot-level spectroscopy with hand-held sensors. These results also show that tundra vegetation mapping can be scaled from the plot level (<1 m) to patch level (<500 m) using spectroscopy data rescaled to match the wavebands of the multispectral satellite remote sensing. We find that developing a consistent method for classification of vegetation communities across the flux tower sites is a challenging process, given thespatial variability in vegetation communities and the need for detailed vegetation survey data for training and validating classification algorithms. This study highlights the benefits of using fine-scale field spectroscopy measurements to obtain tundra vegetation classifications for landscape analyses and use in carbon flux scaling studies. Improved understanding of tundra vegetation distributions will also provide necessary insight into the ecological processes driving plant community assemblages in Arctic environments

Group Psychological Treatment Preferences of Individuals Living With Chronic Disease: Brief Report of a Saskatchewan-Based Cross-Sectional Survey

Given that individuals with chronic diseases comorbid with psychological distress experience worse clinical outcomes than those without psychological distress, treatment of the psychological sequalae that accompanies chronic diseases is of utmost importance. Thus, the present study aimed to examine group treatment preferences among adults living with chronic disease in Saskatchewan, Canada. An online survey regarding group treatment preferences was administered to 207 participants living with chronic disease comorbid with psychological distress. The most often reported treatment scenario was virtual sessions (45%) lasting 1 h (51%) and occurring every other week (45%) in the evening (63%) for 3 to4 months (40%). Preferences included a medium group (48%), a relatively closed group nature (ie, only occasional new members; 44%), and group leadership including at least 1 professional living with chronic disease (54%). Future-oriented (81%), supportive (83%), skill-based (95%), and group discussions (78%) were desired treatment characteristics among participants. Survey results showed clear preferences on treatment content and session logistics. Slight variations exist by gender and age, but a consensus can be identified and act as a preliminary treatment plan. This study contributes to the body of literature on psychological treatment preferences for individuals living with chronic disease by outlining the preferred format and composition of groups according to those with lived experience. Group-based psychological treatment for chronic disease patients should account for these preferences to improve its acceptability and usefulness among patients

Environmental controls on ozone fluxes in a poplar plantation in Western Europe

Tropospheric O-3 is a strong oxidant that may affect vegetation and human health. Here we report on the O-3 fluxes from a poplar plantation in Belgium during one year. Surprisingly, the winter and autumn O-3 fluxes were of similar magnitude to ones observed during most of the peak vegetation development. Largest O-3 uptakes were recorded at the beginning of the growing season in correspondence to a minimum stomatal uptake. Wind speed was the most important control and explained 44% of the variability in the nighttime O-3 fluxes, suggesting that turbulent mixing and the mechanical destruction of O-3 played a substantial role in the O-3 fluxes. The stomatal O-3 uptake accounted for a seasonal average of 59% of the total O-3 uptake. Multiple regression and partial correlation analyses showed that net ecosystem exchange was not affected by the stomatal O-3 uptake. (C) 2013 The Authors. Published by Elsevier Ltd. All rights reserved

Characterizing permafrost active layer dynamics and sensitivity to landscape spatial heterogeneity in Alaska

An important feature of the Arctic is large spatial heterogeneity in active layer conditions, which is generally poorly represented by global models and can lead to large uncertainties in predicting regional ecosystem responses and climate feedbacks. In this study, we developed a spatially integrated modeling and analysis framework combining field observations, local-scale ( ∼ 50 m resolution) active layer thickness (ALT) and soil moisture maps derived from low-frequency (L + P-band) airborne radar measurements, and global satellite environmental observations to investigate the ALT sensitivity to recent climate trends and landscape heterogeneity in Alaska. Modeled ALT results show good correspondence with in situ measurements in higherpermafrost-probability (PP ≥ 70 %) areas (n = 33; R = 0.60; mean bias = 1.58 cm; RMSE = 20.32 cm), but with larger uncertainty in sporadic and discontinuous permafrost areas. The model results also reveal widespread ALT deepening since 2001, with smaller ALT increases in northern Alaska (mean trend = 0.32 ± 1.18 cm yr−1 ) and much larger increases (> 3 cm yr−1 ) across interior and southern Alaska. The positive ALT trend coincides with regional warming and a longer snow-free season (R = 0.60 ± 0.32). A spatially integrated analysis of the radar retrievals and model sensitivity simulations demonstrated that uncertainty in the spatial and vertical distribution of soil organic carbon (SOC) was the largest factor affecting modeled ALT accuracy, while soil moisture played a secondary role. Potential improvements in characterizing SOC heterogeneity, including better spatial sampling of soil conditions and advances in remote sensing of SOC and soil moisture, will enable more accurate predictions of active layer conditions and refinement of the modeling framework across a larger domain

Mechanistic Modeling of Microtopographic Impacts on CO2 and CH4 Fluxes in an Alaskan Tundra Ecosystem Using the CLM-Microbe Model

Spatial heterogeneities in soil hydrology have been confirmed as a key control on CO2 and CH4 fluxes in the Arctic tundra ecosystem. In this study, we applied a mechanistic ecosystem model, CLM-Microbe, to examine the microtopographic impacts on CO2 and CH4 fluxes across seven landscape types in Utqiaġvik, Alaska: trough, low-centered polygon (LCP) center, LCP transition, LCP rim, high-centered polygon (HCP) center, HCP transition, and HCP rim. We first validated the CLM-Microbe model against static-chamber measured CO2 and CH4 fluxes in 2013 for three landscape types: trough, LCP center, and LCP rim. Model application showed that low-elevation and thus wetter landscape types (i.e., trough, transitions, and LCP center) had larger CH4 emissions rates with greater seasonal variations than high-elevation and drier landscape types (rims and HCP center). Sensitivity analysis indicated that substrate availability for methanogenesis (acetate, CO2&nbsp;+&nbsp;H2) is the most important factor determining CH4 emission, and vegetation physiological properties largely affect the net ecosystem carbon exchange and ecosystem respiration in Arctic tundra ecosystems. Modeled CH4 emissions for different microtopographic features were upscaled to the eddy covariance (EC) domain with an area-weighted approach before validation against EC-measured CH4 fluxes. The model underestimated the EC-measured CH4 flux by 20% and 25% at daily and hourly time steps, suggesting the importance of the time step in reporting CH4 flux. The strong microtopographic impacts on CO2 and CH4 fluxes call for a model-data integration framework for better understanding and predicting carbon flux in the highly heterogeneous Arctic landscape