Search Results (7)

Modeling peatland hydraulic processes in cold regions requires defining near-surface hydraulic parameters. The current study aims to determine the soil freezing and water characteristic curve parameters for organic soils from peatland-dominated permafrost mires. The three research objectives are as follows: (i) Setting up an in situ soil freezing characteristic curve experiment by installing sensors for measuring volumetric water content and temperature in Storflaket mire, Abisko region, Sweden; (ii) Conducting laboratory evaporation experiments and inverse numerical modeling to determine soil water characteristic curve parameters and comparing three soil water characteristic curve models to the laboratory data; (iii) Deriving a relationship between soil freezing and water characteristic curves and optimizing this equation with sensor data from (i). A long-lasting in situ volumetric water content station has been successfully set up in sub-Arctic Sweden. The soil water characteristic curve experiments showed that bimodality also exists for the investigated peat soils. The optimization results of the bimodal relationship showed excellent agreement with the soil freezing cycle measurements. To the best of our knowledge, this is one of the first studies to establish and test bimodality for frozen peat soils. The estimated hydraulic parameters could be used to better simulate permafrost dynamics in peat soils. Full article

We sequenced and analyzed the complete mitogenome of a Norwegian isolate of the octocoral Alcyonium digitatum using the Ion Torrent sequencing technology. The 18,790 bp circular mitochondrial genome was found to harbor the same set of 17 genes, which encode 14 protein subunits, two structural ribosomal RNAs and one tRNA, as reported in other octocorals. In addition, we detected a new tRNA^Pro-like gene sequence nested within the MutS protein coding region. This putative tRNA gene feature appears to be conserved among the octocorals but has not been reported previously. The A. digitatum mitogenome was also shown to harbor an optional gene (ORFA) that encodes a putative protein of 191 amino acids with unknown function. A mitogenome-based phylogenetic analysis, presented as a maximum likelihood tree, showed that A. digitatum clustered with high statistical confidence with two other Alcyonium species endemic to the Mediterranean Sea and the Southeast Pacific Ocean. Full article

A land cover map of two arctic catchments near the Abisko Scientific Research Station was obtained based on a classification from a Sentinel-2 satellite image and a ground survey performed in July 2022. The two contiguous catchments, Miellajokka and Stordalen, are covered by various ecotypes, from boreal forest to alpine tundra and peatland. Two classification algorithms, support vector machine and random forest, were tested and gave very similar results. The percentage of correctly classified pixels was over 88% in both cases. The developed workflow relies solely on open-source software and acquired ground observations. Space organization was directed by the altitude as demonstrated by the intersection of the land cover with the topography. Comparison between this new land cover map and previous ones based on data acquired between 2008 and 2011 shows some trends in vegetation cover evolution in response to climate change in the considered area. This land cover map is key input data for permafrost modeling and, hence, for the quantification of climate change impacts in the studied area. Full article

Soils represent the largest store of carbon in the biosphere with soils at high latitudes containing twice as much carbon (C) than the atmosphere. High latitude tundra vegetation communities show increases in the relative abundance and cover of deciduous shrubs which may influence net ecosystem exchange of CO₂ from this C-rich ecosystem. Monitoring soil respiration (Rs) as a crucial component of the ecosystem carbon balance at regional scales is difficult given the remoteness of these ecosystems and the intensiveness of measurements that is required. Here we use direct measurements of Rs from contrasting tundra plant communities combined with direct measurements of aboveground plant productivity via Normalised Difference Vegetation Index (NDVI) to predict soil respiration across four key vegetation communities in a tundra ecosystem. Soil respiration exhibited a nonlinear relationship with NDVI (y = 0.202e^{3.508 x}, p < 0.001). Our results further suggest that NDVI and soil temperature can help predict Rs if vegetation type is taken into consideration. We observed, however, that NDVI is not a relevant explanatory variable in the estimation of SOC in a single-study analysis. Full article

Streambed morphology, streamflow dynamics, and the heterogeneity of streambed sediments critically controls the interaction between surface water and groundwater. The present study investigated the impact of different flow regimes on hyporheic exchange in a boreal stream in northern Sweden using experimental and numerical approaches. Low-, base-, and high-flow discharges were simulated by regulating the streamflow upstream in the study area, and temperature was used as the natural tracer to monitor the impact of the different flow discharges on hyporheic exchange fluxes in stretches of stream featuring gaining and losing conditions. A numerical model was developed using geomorphological and hydrological properties of the stream and was then used to perform a detailed analysis of the subsurface water flow. Additionally, the impact of heterogeneity in sediment permeability on hyporheic exchange fluxes was investigated. Both the experimental and modelling results show that temporally increasing flow resulted in a larger (deeper) extent of the hyporheic zone as well as longer hyporheic flow residence times. However, the result of the numerical analysis is strongly controlled by heterogeneity in sediment permeability. In particular, for homogeneous sediments, the fragmentation of upwelling length substantially varies with streamflow dynamics due to the contribution of deeper fluxes. Full article

Rising global temperatures tied to increases in greenhouse gas emissions are impacting high latitude regions, leading to changes in vegetation composition and feedbacks to climate through increased methane (CH₄) emissions. In subarctic peatlands, permafrost collapse has led to shifts in vegetation species on landscape scales with high spatial heterogeneity. Our goal was to provide a baseline for vegetation distribution related to permafrost collapse and changes in biogeochemical processes. We collected unmanned aerial system (UAS) imagery at Stordalen Mire, Abisko, Sweden to classify vegetation cover types. A series of digital image processing routines were used to generate texture attributes within the image for the purpose of characterizing vegetative cover types. An artificial neural network (ANN) was developed to classify the image. The ANN used all texture variables and color bands (three spectral bands and six metrics) to generate a probability map for each of the eight cover classes. We used the highest probability for a class at each pixel to designate the cover type in the final map. Our overall misclassification rate was 32%, while omission and commission error by class ranged from 0% to 50%. We found that within our area of interest, cover classes most indicative of underlying permafrost (hummock and tall shrub) comprised 43.9% percent of the landscape. Our effort showed the capability of an ANN applied to UAS high-resolution imagery to develop a classification that focuses on vegetation types associated with permafrost status and therefore potentially changes in greenhouse gas exchange. We also used a method to examine the multiple probabilities representing cover class prediction at the pixel level to examine model confusion. UAS image collection can be inexpensive and a repeatable avenue to determine vegetation change at high latitudes, which can further be used to estimate and scale corresponding changes in CH₄ emissions. Full article

A novel, 10 kb RNA virus—tentatively named ‘Abisko virus’—was discovered in the transcriptome data of a diseased autumnal moth (Epirrita autumnata) larva, as part of a search for the possible causes of the cyclical nature and mortality associated with geometrid moth dynamics and outbreaks in northern Fennoscandia. Abisko virus has a genome organization similar to that of the insect-infecting negeviruses, but phylogenetic and compositional bias analyses also reveal strong affiliations with plant-infecting viruses, such that both the primary host origin and taxonomic identity of the virus remain in doubt. In an extensive set of larval, pupal, and adult autumnal moth and winter moth (Operophtera brumata) outbreak samples, the virus was only detected in a few adult E. autumnata moths as well as the single larval transcriptome. The Abisko virus is therefore unlikely to be a factor in the Fennoscandia geometrid population dynamics. Full article