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Soil mesofauna play pertinent roles in soil processes. For example, microarthropods strongly influence rates of microbial decomposition. The relationship between mesofauna and their environment are understudied in low Arctic ecosystems compared to other regions. A more detailed grasp of these soil assemblages is necessary for understanding the current functioning of these ecosystems. We characterized the soil mesofauna community across different low Arctic habitats to determine which soil properties commonly correlated with soil fauna would best explain their distribution, abundance, and diversity. Samples were taken near five different lakes in northern Finland, in both alpine meadows and sub-alpine birch forests, across a span of available soil habitats (measured by pH, salinity, organic and nitrogen content, soil moisture). Total abundance of the mesofauna community was influenced by a combination of soil factors, but most individual taxa, as well as measures of diversity were best explained by models of one or two influential soil parameters. Poduromorpha springtails and Oribatid mites were best modeled by measures of resource availability, although only Oribatids were significantly, positively related to these resources. All mites and Entomobryomorphid springtails were positively influenced by physicochemical soil moisture and/or salinity. Salinity, in particular, had a strong influence on overall mesofauna community composition. Our results provide further insight into soil fauna assemblages in Northern Finland and further, more extensive research would contribute to a more comprehensive foundation. This will allow for better monitoring of community changes and responses in the face of climate change in the low Arctic. [ABSTRACT FROM AUTHOR]

All ecosystems face ecological challenges in this century. Therefore, it is becoming increasingly important to understand the ecology and degree of local adaptation of functionally important Arctic‐alpine biomes by looking at the most diverse taxon of metazoans: the Arthropoda. This is the first study to utilize metabarcoding in the Alpine tundra, providing insights into the effects of micro‐environmental parameters on alpha‐ and beta‐diversity of arthropods in such unique environments. To characterize arthropod diversity, pitfall traps were set at three middle‐alpine sampling sites in the Scandinavian mountain range in Norway during the snow‐free season in 2015. A metabarcoding approach was then used to determine the small‐scale biodiversity patterns of arthropods in the Alpine tundra. All DNA was extracted directly from the preservative EtOH from 27 pitfall traps. In order to identify the controlling environmental conditions, all sampling locations were equipped with automatic data loggers for permanent measurement of the microenvironmental conditions. The variables measured were: air temperature [°C] at 15 cm height, soil temperature [°C] at 15 cm depth, and soil moisture [vol.%] at 15 cm depth. A total of 233 Arthropoda OTUs were identified. The number of unique OTUs found per sampling location (ridge, south‐facing slope, and depression) was generally higher than the OTUs shared between the sampling locations, demonstrating that niche features greatly impact arthropod community structure. Our findings emphasize the fine‐scale heterogeneity of arctic–alpine ecosystems and provide evidence for trait‐based and niche‐driven adaptation. The spatial and temporal differences in arthropod diversity were best explained by soil moisture and soil temperature at the respective locations. Furthermore, our results show that arthropod diversity is underestimated in alpine‐tundra ecosystems using classical approaches and highlight the importance of integrating long‐term functional environmental data and modern taxonomic techniques into biodiversity research to expand our ecological understanding of fine‐ and meso‐scale biogeographical patterns. [ABSTRACT FROM AUTHOR]

An important uncertainty in the modelling of methane (CH4) emissions from natural wetlands is the wetland area. It is 10 difficult to model wetlands CH4 emissions because of several factors, including its spatial heterogeneity on a large range of scales. In this study, we investigate the impact of model resolution on the simulated wetland methane emission for the Fenno-Scandinavian Peninsula. This is done using a high-resolution wetland map (100x100m² ) and soil carbon map (250x250m² ) in combination with a highly simplified CH4 emission model that is coarsened in six steps from 0.005° to 1°. We find a strong relation between wetland emissions and resolution, which is sensitive, however, to the sub-grid treatment 15 of the wetland fraction. In our setup, soil carbon and soil moisture are positively correlated at high-resolution with wetland location leading to increasing CH4 emissions with increasing resolution. Keeping track of wetland fraction reduces the impact of resolution. However, uncertainties in CH4 emissions remain high because of the large uncertainty in the representation of wetland area, as demonstrated using output of the Wet Chimp inter comparison over our study domain. Because of wetlands mapping uncertainties, the existing models are unlikely to realistically represent the correlation 20 between soil moisture and soil carbon availability. The correlation is positive in our simplified model, but may be different in more complex models depending on their method of representing substrate availability. Therefore, depending on the correlation, CH4 emissions may be over or underestimated. As increasing the model resolution is an effective approach to mitigate the problem of accounting for the correlation between soil moisture and soil carbon and improve the accuracy of models, the main message of this study is that increasing the resolution of global wetland models, and especially the input 25 datasets that are used, should receive high priority. [ABSTRACT FROM AUTHOR]

Potential land–climate feedbacks in subarctic regions, where rapid warming is driving forest expansion into the tundra, may be mediated by differences in transpiration of different plant functional types. Here, we assess the environmental controls of overstorey transpiration and its relevance for ecosystem evapotranspiration in subarctic deciduous woodlands. We measured overstorey transpiration of mountain birch canopies and ecosystem evapotranspiration in two locations in northern Fennoscandia, having dense (Abisko) and sparse (Kevo) overstories. For Kevo, we also upscale chamber‐measured understorey evapotranspiration from shrubs and lichen using a detailed land cover map. Subdaily evaporative fluxes were not affected by soil moisture and showed similar controls by vapour pressure deficit and radiation across sites. At the daily timescale, increases in evaporative demand led to proportionally higher contributions of overstorey transpiration to ecosystem evapotranspiration. For the entire growing season, the overstorey transpired 33% of ecosystem evapotranspiration in Abisko and only 16% in Kevo. At this latter site, the understorey had a higher leaf area index and contributed more to ecosystem evapotranspiration compared with the overstorey birch canopy. In Abisko, growing season evapotranspiration was 27% higher than precipitation, consistent with a gradual soil moisture depletion over the summer. Our results show that overstorey canopy transpiration in subarctic deciduous woodlands is not the dominant evaporative flux. However, given the observed environmental sensitivity of evapotranspiration components, the role of deciduous trees in driving ecosystem evapotranspiration may increase with the predicted increases in tree cover and evaporative demand across subarctic regions. [ABSTRACT FROM AUTHOR]

The study focuses on the derivation of transformation models for undrained shear strength ( su) of Finnish soft sensitive clays. Specific correlation equations for su of Finnish clays are presented in this work for the first time. Field and laboratory measurements from 24 test sites in Finland are exploited for this purpose and a multivariate database is constructed. The multivariate data consist of su from the field vane test, preconsolidation stress, vertical effective stress, liquid limit, plastic limit, natural water content, and sensitivity. The main objective is to evaluate the interdependence of su, consolidation stresses, and index parameters and provide a consistent framework for practical use. The new correlations are established through regression analyses. The constructed framework is further validated by another independent multivariate database of clays from Sweden and Norway as well as by empirical equations for Swedish and Norwegian clays. Existing correlations are evaluated for Finnish and Scandinavian clays. Finally, bias and uncertainties of the new correlations are presented. [ABSTRACT FROM AUTHOR]

Time series of daily mean temperature obtained from the European Climate Assessment data set is analyzed with respect to their extremal properties. A time-series clustering approach which combines Bayesian methodology, extreme value theory and classification techniques is adopted for the analysis of the regional variability of temperature extremes. The daily mean temperature records are clustered on the basis of their corresponding predictive distributions for 25-, 50- and 100-year return values. The results of the cluster analysis show a clear distinction between the highest altitude stations, for which the return values are lowest, and the remaining stations. Furthermore, a clear distinction is also found between the northernmost stations in Scandinavia and the stations in central and southern Europe. This spatial structure of the return period distributions for 25-, 50- and 100-years seems to be consistent with projected changes in the variability of temperature extremes over Europe pointing to a different behavior in central Europe than in northern Europe and the Mediterranean area, possibly related to the effect of soil moisture and land-atmosphere coupling. [ABSTRACT FROM AUTHOR]

In order to evaluate the reliability of the soil moisture product obtained by means of the LISFLOOD hydrological model (De Roo et al., 2000), we compare it to soil moisture estimates derived from ERS scatterometer data (Wagner et al., 1999b). Once evaluated the effect of scale mismatch, we calculate the root mean square error and the correlation between the two soil moisture time series on a pixel basis and we assess the fraction of variance that can be explained by a set of input parameter fields that vary from elevation and soil depth to rainfall statistics and missing or snow covered ERS images. The two datasets show good agreement over large regions, with 90% of the area having a positive correlation coefficient and 66% having a root mean square error minor than 0.5 pF units. Major inconsistencies are located in mountainous regions such as the Alps or Scandinavia where both the methodologies suffer from insufficiently resolved land surface processes at the given spatial resolution, as well as from limited availability of satellite data on the one hand and the uncertainties in meteorological data retrieval on the other hand. [ABSTRACT FROM AUTHOR]

Abstract: The cold climate of Fennoscandia allows soils to experience ephemeral freezing and snow cover. Snowmelt impacts on runoff and solute transport, but is also one of the most important contributors to recharge of ground water reserves. The presence of a snowpack governs the length of a growing season, but limited information is available on the response of partially frozen soil to mild climatic events in winter. We studied time series of soil temperature and unfrozen soil water content during freezing cycles and mild climatic events during two climatically contrasting winters (2001–2002, 2002–2003) at five sites differing in texture and hydraulic features in Finland. Frost penetration was found to be attributable to snowpack thickness, such that soil temperatures seldom fell below −1.5 °C, when a snow cover of more than 30 cm was present. Soil surface temperatures can fall below 0 °C and soil water freezes to 10-cm depth, but soil water is predominantly unfrozen during winter in deeper soil horizons, 30- to 90-cm depths. Water released by snowmelt during mild climatic events in winter was observed to infiltrate through partially frozen soil, hence contributing significant recharge to ground water resources. [Copyright &y& Elsevier]