New insights into the environmental factors controlling the ground thermal regime across the Northern Hemisphere : a comparison between permafrost and non-permafrost areas

The thermal state of permafrost affects Earth surface systems and human activity in the Arctic and has implications for global climate. Improved understanding of the local-scale variability in the global ground thermal regime is required to account for its sensitivity to changing climatic and geoecological conditions. Here, we statistically related observations of mean annual ground temperature (MAGT) and active-layer thickness (ALT) to high-resolution (similar to 1 km(2)) geospatial data of climatic and local environmental conditions across the Northern Hemisphere. The aim was to characterize the relative importance of key environmental factors and the magnitude and shape of their effects on MAGT and ALT. The multivariate models fitted well to both response variables with average R-2 values being similar to 0.94 and 0.78. Corresponding predictive performances in terms of root-mean-square error were similar to 1.31 degrees C and 87 cm. Freezing (FDD) and thawing (TDD) degree days were key factors for MAGT inside and outside the permafrost domain with average effect sizes of 6.7 and 13.6 degrees C, respectively. Soil properties had marginal effects on MAGT (effect size = 0.4-0.7 degrees C). For ALT, rainfall (effect size = 181 cm) and solar radiation (161 cm) were most influential. Analysis of variable importance further underlined the dominance of climate for MAGT and highlighted the role of solar radiation for ALT. Most response shapes for MAGTPeer reviewe

Biogeophysical controls on soil-atmosphere thermal differences: implications on warming Arctic ecosystems

Soil temperature (ST) has a key role in Arctic ecosystem functioning and global environmental change. However, soil thermal conditions do not necessarily follow synoptic temperature variations. This is because local biogeophysical processes can lead to a pronounced soil-atmosphere thermal offset (∆T) while altering the coupling (βT) between ST and ambient air temperature (AAT). Here, we aim to uncover the spatiotemporal variation in these parameters and identify their main environmental drivers. By deploying a unique network of 322 temperature loggers and surveying biogeophysical processes across an Arctic landscape, we found that the spatial variation in ∆T during the AAT≤0 period (mean ∆T=-0.6°C, standard deviation ± 1.0°C) was directly and indirectly constrained by local topography controlling snow depth. By contrast, during the AAT>0 period, ∆T was controlled by soil characteristics, vegetation and solar radiation (∆T=6.0°C ± 1.2°C). Importantly, ∆T was not constant throughout the seasons reflecting the influence of βT on the rate of local soil warming being stronger after (mean βT = 0.8 ± 0.1) than before (βT = 0.2 ± 0.2) snowmelt. Our results highlight the need for continuous microclimatic and local environmental monitoring, and suggest a potential for large buffering and non-uniform warming of snow-dominated Arctic ecosystems under projected temperature increase

Topographic Wetness Index as a Proxy for Soil Moisture : The Importance of Flow-Routing Algorithm and Grid Resolution

The Topographic Wetness Index (TWI) is a commonly used proxy for soil moisture. The predictive capability of TWI is influenced by the flow-routing algorithm and the resolution of the Digital Elevation Model (DEM) that TWI is derived from. Here, we examine the predictive capability of TWI using 11 flow-routing algorithms at DEM resolutions 1-30 m. We analyze the relationship between TWI and field-quantified soil moisture using statistical modeling methods and 5,200 study plots with over 46 000 soil moisture measurements. In addition, we test the sensitivity of the flow-routing algorithms against vertical height errors in DEM at different resolutions. The results reveal that the overall predictive capability of TWI was modest. The highest r(2) (23.7%) was reached using a multiple-flow-direction algorithm at 2 m resolution. In addition, the test of sensitivity against height errors revealed that the multiple-flow-direction algorithms were also more robust against DEM errors than single-flow-direction algorithms. The results provide field-evidence indicating that at its best TWI is a modest proxy for soil moisture and its predictive capability is influenced by the flow-routing algorithm and DEM resolution. Thus, we encourage careful evaluation of algorithms and resolutions when using TWI as a proxy for soil moisture.Peer reviewe

Topographic Wetness Index as a Proxy for Soil Moisture : The Importance of Flow-Routing Algorithm and Grid Resolution

The Topographic Wetness Index (TWI) is a commonly used proxy for soil moisture. The predictive capability of TWI is influenced by the flow-routing algorithm and the resolution of the Digital Elevation Model (DEM) that TWI is derived from. Here, we examine the predictive capability of TWI using 11 flow-routing algorithms at DEM resolutions 1-30 m. We analyze the relationship between TWI and field-quantified soil moisture using statistical modeling methods and 5,200 study plots with over 46 000 soil moisture measurements. In addition, we test the sensitivity of the flow-routing algorithms against vertical height errors in DEM at different resolutions. The results reveal that the overall predictive capability of TWI was modest. The highest r(2) (23.7%) was reached using a multiple-flow-direction algorithm at 2 m resolution. In addition, the test of sensitivity against height errors revealed that the multiple-flow-direction algorithms were also more robust against DEM errors than single-flow-direction algorithms. The results provide field-evidence indicating that at its best TWI is a modest proxy for soil moisture and its predictive capability is influenced by the flow-routing algorithm and DEM resolution. Thus, we encourage careful evaluation of algorithms and resolutions when using TWI as a proxy for soil moisture.Peer reviewe

Urban expansion in Zanzibar City, Tanzania : Analyzing quantity, spatial patterns and effects of alternative planning approaches

Rapid urbanization and urban area expansion of sub-Saharan Africa are megatrends of the 21st century. Addressing environmental and social problems related to these megatrends requires faster and more efficient urban planning that is based on measured information of the expansion patterns. Urban growth prediction models (UGPMs) provide tools for generating such information by predicting future urban expansion patterns and allowing testing of alternative planning scenarios. We created an UGPM for Zanzibar City in Tanzania by measuring urban expansion in 2004-2009 and 2009-2013, linking the expansion to explanatory variables with a generalized additive model, measuring the accuracy of the created model, and projecting urban growth until 2030 with the business-as-usual and various alternative planning scenarios. Based on the results, the urban area of Zanzibar City expanded by 40% from 2004 to 2013. Spatial patterns of expansion were largely driven by the already existing building pattern and land-use constraints. The created model predicted future urban expansion moderately well and had an area under the curve value of 0.855 and a true skill statistic result of 0.568. Based on the business-as-usual scenario, the city will expand 89% from 2013 until 2030 and will continue to sprawl to new regions at the outskirts of the current built-up area. Establishing new urban centers had the highest impact on directing urban expansion from the tested alternative planning scenarios. However, the impact of all scenarios was low and therefore also other planning solutions such as vertical development, urban growth boundaries, and gradual improvement of the informal areas should be considered in Zanzibar.Peer reviewe

CLU, CR1 and PICALM genes associate with Alzheimer's-related senile plaques

Introduction APOE is the strongest risk gene for sporadic Alzheimer's disease (AD) so far. Recent genome wide association studies found links for sporadic AD with CLU and CR1 involved in Aβ clearance, and PICALM affecting intracellular trafficking. Methods We investigated the associations of senile plaques (SP) and neurofibrillary tangles (NFT) with the proposed risk genes and APOE, in the Tampere Autopsy Study (TASTY) series (603 cases), a sample of the general population (0 to 97 yrs), who died out-of-hospital. Results Age and the APOEε4 allele associated strongly with all phenotypes of SP, as expected. In age and APOEε4 adjusted analyses, compared to the most common homozygous genotype, burnt out SP were more common among carriers of the C-allele of CLU, whereas the T-allele of PICALM and C-allele of CR1 were linked with lower SP coverage. We found no significant associations between any of the genetic variants and NFT. Conclusions Marginal effects from CLU, CR1 and PICALM suggest that these genes have minimal effects on the development of AD lesions.BioMed Central Open acces

Chironomid-based temperature reconstruction for the Eemian Interglacial (MIS 5e) at Sokli, northeast Finland

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Effectiveness of three interventions for secondary prevention of low back pain in the occupational health setting - a randomised controlled trial with a natural course control

Background: We assessed the effectiveness of three interventions that were aimed to reduce non-acute low back pain (LBP) related symptoms in the occupational health setting. Methods: Based on a survey (n = 2480; response rate 71%) on LBP, we selected a cohort of 193 employees who reported moderate LBP (Visual Analogue Scale VAS > 34 mm) and fulfilled at least one of the following criteria during the past 12 months: sciatica, recurrence of LBP >= 2 times, LBP >= 2 weeks, or previous sickness absence. A random sample was extracted from the cohort as a control group (Control, n = 50), representing the natural course of LBP. The remaining 143 employees were invited to participate in a randomised controlled trial (RCT) of three 1:1:1 allocated parallel intervention arms: multidisciplinary rehabilitation (Rehab, n = 43); progressive exercises (Physio, n = 43) and self-care advice (Advice, n = 40). Seventeen employees declined participation in the intervention. The primary outcome measures were physical impairment (PHI), LBP intensity (Visual Analogue Scale), health related quality of life (QoL), and accumulated sickness absence days. We imputed missing values with multiple imputation procedure. We assessed all comparisons between the intervention groups and the Control group by analysing questionnaire outcomes at 2 years with ANOVA and sickness absence at 4 years by using negative binomial model with a logarithmic link function. Results: Mean differences between the Rehab and Control groups were - 3 [95% CI -5 to - 1] for PHI, - 13 [- 24 to - 1] for pain intensity, and 0.06 [0.00 to 0.12] for QoL. Mean differences between the Physio and Control groups were - 3 [95% CI -5 to - 1] for PHI, -13 [- 29 to 2] for pain intensity, and 0.07 [0.01 to 0.13] for QoL. The main effects sizes were from 0.4 to 0.6. The interventions were not effective in reducing sickness absence. Conclusions: Rehab and Physio interventions improved health related quality of life, decreased low back pain and physical impairment in non-acute, moderate LBP, but we found no differences between the Advice and Control group results. No effectiveness on sickness absence was observed.Peer reviewe

Environmental Controls of InSAR-Based Periglacial Ground Dynamics in a Sub-Arctic Landscape

Periglacial environments are characterized by highly dynamic landscapes. Freezing and thawing lead to ground movement, associated with cryoturbation and solifluction. These processes are sensitive to climate change and variably distributed depending on multiple environmental factors. In this study, we used multi-geometry Sentinel-1 Synthetic Aperture Radar Interferometry (InSAR) to investigate the spatial distribution of the mean annual ground velocity in a mountainous landscape in Northern Norway. Statistical modeling was employed to examine how periglacial ground velocity is related to environmental variables characterizing the diverse climatic, geomorphic, hydrological and biological conditions within a 148 km(2) study area. Two-dimensional (2D) InSAR results document mean annual ground velocity up to 15 mm/yr. Vertical and horizontal velocity components in the East-West plane show variable spatial distribution, which can be explained by the characteristics of cryoturbation and solifluction operating differently over flat and sloping terrain. Statistical modeling shows that slope angle and mean annual air temperature variables are the most important environmental factors explaining the distribution of the horizontal and vertical components, respectively. Vegetation and snow cover also have a local influence, interpreted as indicators of the ground material and moisture conditions. The results show contrasted model performance depending on the velocity component used as a response variable. In general, our study highlights the potential of integrating radar remote sensing and statistical modeling to investigate mountainous regions and better understand the relations between environmental factors, periglacial processes and ground dynamics.Peer reviewe