The missing pieces for better future predictions in subarctic ecosystems: a Torneträsk case study

Arctic and subarctic ecosystems are experiencing substantial changes in hydrology, vegetation, permafrost conditions, and carbon cycling, in response to climatic change and other anthropogenic drivers, and these changes are likely to continue over this century. The total magnitude of these changes results from multiple interactions among these drivers. Field measurements can address the overall responses to different changing drivers, but are less capable of quantifying the interactions among them. Currently, a comprehensive assessment of the drivers of ecosystem changes, and the magnitude of their direct and indirect impacts on subarctic ecosystems, is missing. The Torneträsk area, in the Swedish subarctic, has an unrivalled history of environmental observation over 100 years, and is one of the most studied sites in the Arctic. In this study, we summarize and rank the drivers of ecosystem change in the Torneträsk area, and propose research priorities identified, by expert assessment, to improve predictions of ecosystem changes. The research priorities identified include understanding impacts on ecosystems brought on by altered frequency and intensity of winter warming events, evapotranspiration rates, rainfall, duration of snow cover and lake-ice, changed soil moisture, and droughts. This case study can help us understand the ongoing ecosystem changes occurring in the Torneträsk area, and contribute to improve predictions of future ecosystem changes at a larger scale. This understanding will provide the basis for the future mitigation and adaptation plans needed in a changing climate

BioTIME: A database of biodiversity time series for the Anthropocene.

MotivationThe BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.Main types of variables includedThe database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record.Spatial location and grainBioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km2 (158 cm2) to 100 km2 (1,000,000,000,000 cm2).Time period and grainBioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year.Major taxa and level of measurementBioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.Software format.csv and .SQL

The Distribution of Phosphatidylinositol 4,5-Bisphosphate in Acinar Cells of Rat Pancreas Revealed with the Freeze-Fracture Replica Labeling Method

Phosphatidylinositol 4,5-bisphosphate [PI(4,5)P2] is a phospholipid that has been implicated in multiple cellular activities. The distribution of PI(4,5)P2 has been analyzed extensively using live imaging of the GFP-coupled phospholipase C-δ1 pleckstrin homology domain in cultured cell lines. However, technical difficulties have prevented the study of PI(4,5)P2 in cells of in vivo tissues. We recently developed a method to analyze the nanoscale distribution of PI(4,5)P2 in cultured cells by using the quick-freezing and freeze-fracture replica labeling method. In principle, this method can be applied to any cell because it does not require the expression of artificial probes. In the present study, we modified the method to study cells of in vivo tissues and applied it to pancreatic exocrine acinar cells of the rat. We found that PI(4,5)P2 in the plasma membrane is distributed in an equivalent density in the apical and basolateral domains, but exists in a significantly higher concentration in the gap junction. The intracellular organelles did not show labeling for PI(4,5)P2. The results are novel or different from the reported distribution patterns in cell lines and highlight the importance of studying cells differentiated in vivo

Psycho-social factors associated with mental resilience in the Corona lockdown

The SARS-CoV-2 pandemic is not only a threat to physical health but is also having severe impacts on mental health. Although increases in stress-related symptomatology and other adverse psycho-social outcomes, as well as their most important risk factors have been described, hardly anything is known about potential protective factors. Resilience refers to the maintenance of mental health despite adversity. To gain mechanistic insights about the relationship between described psycho-social resilience factors and resilience specifically in the current crisis, we assessed resilience factors, exposure to Corona crisis-specific and general stressors, as well as internalizing symptoms in a cross-sectional online survey conducted in 24 languages during the most intense phase of the lockdown in Europe (22 March to 19 April) in a convenience sample of N = 15,970 adults. Resilience, as an outcome, was conceptualized as good mental health despite stressor exposure and measured as the inverse residual between actual and predicted symptom total score. Preregistered hypotheses (osf.io/r6btn) were tested with multiple regression models and mediation analyses. Results confirmed our primary hypothesis that positive appraisal style (PAS) is positively associated with resilience (p < 0.0001). The resilience factor PAS also partly mediated the positive association between perceived social support and resilience, and its association with resilience was in turn partly mediated by the ability to easily recover from stress (both p < 0.0001). In comparison with other resilience factors, good stress response recovery and positive appraisal specifically of the consequences of the Corona crisis were the strongest factors. Preregistered exploratory subgroup analyses (osf.io/thka9) showed that all tested resilience factors generalize across major socio-demographic categories. This research identifies modifiable protective factors that can be targeted by public mental health efforts in this and in future pandemics

Forests dynamics in the montane-alpine boundary: a comparative study using satellite imagery and climate data

14 páginas.- Ilustraciones.- © The authors 2017. Open Access under Creative Commons by Attribution Licence. Use, distribution and reproduction are unrestricted. Authors and original publication must be credited.Over the past decades, the altitudinal and latitudinal advance of forest lines has increased due to global warming and the abandonment of less productive areas previously subject to agricultural activities. The intensity and speed of the forest line advance also depend on numerous physical, biological and human factors that are region-specific. It is important to fully understand the mechanisms behind forest line behaviour, as existing studies do not report global figures. We selected 4 study areas in which to analyse the temporal and spatial behaviour of the forest line and of forest cover based on selection criteria such as minimal human interference and maximal representativeness at the European level. The sites were located in national parks that were evenly spread across some of the dominant European mountain ranges such as the Pyrenees, Alps and Carpathians, at comparable altitudes and latitudes, and with similar land cover proportions in the year 1970. Methodologically, we used cloud-free Landsat satellite images that were acquired in the same month during the growing season. A post-classification comparison technique, using all bands but the thermal one, was implemented to evaluate forest line behaviour, while the accuracy of image classification was evaluated by random sampling. Four time frames were used to evaluate forest cover behaviour in relation to the non-forested areas: 1971-1980, 1981-1990, 1991-2000 and 2001-2014. Also, climate and topography data were included in this study, which enabled comparison and computation of dependence relations. Our results indicate significant differences between the analysed areas. For instance, for the same reference period (1981-1990), the greatest differences in terms of forest cover change were specific to the Austrian Alps (28%), whereas the lowest differences were those from the Spanish Pyrenees (1%). Similar forest line shifts were found in the Austrian Alps and in the Romanian Carpathians, whereas the lowest altitudinal advancement was specific to the Spanish Pyrenees. According to this study, the temperature trend could have significantly influenced tree line behaviour.This article is based on work from COST Action ES1203 SensFor, supported by COST (European Cooperation in Science and Technology, www.cost.eu).Peer reviewe