| 1. |
- Roslin, Tomas, et al.
(författare)
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A molecular-based identification resource for the arthropods of Finland
- 2022
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Ingår i: Molecular Ecology Resources. - : Wiley. - 1755-098X .- 1755-0998. ; 22:2, s. 803-822
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Tidskriftsartikel (refereegranskat)abstract
- To associate specimens identified by molecular characters to other biological knowledge, we need reference sequences annotated by Linnaean taxonomy. In this study, we (1) report the creation of a comprehensive reference library of DNA barcodes for the arthropods of an entire country (Finland), (2) publish this library, and (3) deliver a new identification tool for insects and spiders, as based on this resource. The reference library contains mtDNA COI barcodes for 11,275 (43%) of 26,437 arthropod species known from Finland, including 10,811 (45%) of 23,956 insect species. To quantify the improvement in identification accuracy enabled by the current reference library, we ran 1000 Finnish insect and spider species through the Barcode of Life Data system (BOLD) identification engine. Of these, 91% were correctly assigned to a unique species when compared to the new reference library alone, 85% were correctly identified when compared to BOLD with the new material included, and 75% with the new material excluded. To capitalize on this resource, we used the new reference material to train a probabilistic taxonomic assignment tool, FinPROTAX, scoring high success. For the full-length barcode region, the accuracy of taxonomic assignments at the level of classes, orders, families, subfamilies, tribes, genera, and species reached 99.9%, 99.9%, 99.8%, 99.7%, 99.4%, 96.8%, and 88.5%, respectively. The FinBOL arthropod reference library and FinPROTAX are available through the Finnish Biodiversity Information Facility (www.laji.fi) at https://laji.fi/en/theme/protax. Overall, the FinBOL investment represents a massive capacity-transfer from the taxonomic community of Finland to all sectors of society.
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| 2. |
- Bartels-Rausch, Thorsten, et al.
(författare)
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Ice structures, patterns, and processes: A view across the icefields
- 2012
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Ingår i: Reviews of Modern Physics. ; 84:2, s. 885-944
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Forskningsöversikt (refereegranskat)abstract
- From the frontiers of research on ice dynamics in its broadest sense, this review surveys the structures of ice, the patterns or morphologies it may assume, and the physical and chemical processes in which it is involved. Open questions in the various fields of ice research in nature are highlighted, ranging from terrestrial and oceanic ice on Earth, to ice in the atmosphere, to ice on other Solar System bodies and in interstellar space.
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| 3. |
- Gröger, Matthias, et al.
(författare)
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Coupled regional Earth system modeling in the Baltic Sea region
- 2021
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Ingår i: Earth System Dynamics. - : Copernicus GmbH. - 2190-4979 .- 2190-4987. ; 12:3, s. 939-973
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Forskningsöversikt (refereegranskat)abstract
- Nonlinear responses to externally forced climate change are known to dampen or amplify the local climate impact due to complex cross-compartmental feedback loops in the Earth system. These feedbacks are less well represented in the traditional stand-alone atmosphere and ocean models on which many of today's regional climate assessments rely (e.g., EURO-CORDEX, NOSCCA and BACC II). This has promoted the development of regional climate models for the Baltic Sea region by coupling different compartments of the Earth system into more comprehensive models. Coupled models more realistically represent feedback loops than the information imposed on the region by prescribed boundary conditions and, thus, permit more degrees of freedom. In the past, several coupled model systems have been developed for Europe and the Baltic Sea region. This article reviews recent progress on model systems that allow two-way communication between atmosphere and ocean models; models for the land surface, including the terrestrial biosphere; and wave models at the air-sea interface and hydrology models for water cycle closure. However, several processes that have mostly been realized by one-way coupling to date, such as marine biogeochemistry, nutrient cycling and atmospheric chemistry (e.g., aerosols), are not considered here. In contrast to uncoupled stand-alone models, coupled Earth system models can modify mean near-surface air temperatures locally by up to several degrees compared with their stand-alone atmospheric counterparts using prescribed surface boundary conditions. The representation of small-scale oceanic processes, such as vertical mixing and sea-ice dynamics, appears essential to accurately resolve the air-sea heat exchange over the Baltic Sea, and these parameters can only be provided by online coupled high-resolution ocean models. In addition, the coupling of wave models at the ocean-atmosphere interface allows for a more explicit formulation of small-scale to microphysical processes with local feedbacks to water temperature and large-scale processes such as oceanic upwelling. Over land, important climate feedbacks arise from dynamical terrestrial vegetation changes as well as the implementation of land-use scenarios and afforestation/deforestation that further alter surface albedo, roughness length and evapotranspiration. Furthermore, a good representation of surface temperatures and roughness length over open sea and land areas is critical for the representation of climatic extremes such as heavy precipitation, storms, or tropical nights (defined as nights where the daily minimum temperature does not fall below 20gC), and these parameters appear to be sensitive to coupling. For the present-day climate, many coupled atmosphere-ocean and atmosphere-land surface models have demonstrated the added value of single climate variables, in particular when low-quality boundary data were used in the respective stand-alone model. This makes coupled models a prospective tool for downscaling climate change scenarios from global climate models because these models often have large biases on the regional scale. However, the coupling of hydrology models to close the water cycle remains problematic, as the accuracy of precipitation provided by atmosphere models is, in most cases, insufficient to realistically simulate the runoff to the Baltic Sea without bias adjustments. Many regional stand-alone ocean and atmosphere models are tuned to suitably represent present-day climatologies rather than to accurately simulate climate change. Therefore, more research is required into how the regional climate sensitivity (e.g., the models' response to a given change in global mean temperature) is affected by coupling and how the spread is altered in multi-model and multi-scenario ensembles of coupled models compared with uncoupled ones.
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| 4. |
- Haapala, Jussi, et al.
(författare)
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Coordinated regulation of hyaluronan and aggrecan content in the articular cartilage of immobilized and exercised dogs.
- 1996
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Ingår i: Journal of Rheumatology. - : Journal of Rheumatology. - 0315-162X .- 1499-2752. ; 23:9, s. 1586-1593
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE: To study the influence of joint loading and immobilization on articular cartilage hyaluronan concentration and histological distribution in the knee joints of young dogs subjected to 11 weeks' immobilization by splinting, and 15 weeks' running exercise at a rate of 40 km/day.METHODS: The amount of hyaluronan in articular cartilage was determined by a competitive binding assay using a biotinylated hyaluronan binding complex (HABC) of aggrecan and link protein. Histologic sections were stained for the localization of hyaluronan with the HABC probe. Extracted proteoglycans were characterized by sodium dodecyl sulfate agarose gel electrophoresis.RESULTS: Immobilization significantly reduced the concentration of hyaluronan in all sites studied (tibial and femoral condyles, patellar surface of femur). The proportion of hyaluronan to total uronic acid (mainly from aggrecan) remained unchanged because of a concurrent decrease in aggrecan. The ratio of hyaluronan and aggrecan remained constant also in runners. The staining pattern of free hyaluronan in the tissue sections and the electrophoretic mobility of the extracted proteoglycans were not affected by the different loading regimes.CONCLUSION: Reduced joint loading due to splint immobilization significantly decreases both hyaluronan and aggrecan in the articular cartilage. The remarkably parallel changes in aggrecan and hyaluronan content suggest that joint loading exerts a coordinated influence on their metabolism.
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| 5. |
- Haapala, Jussi, et al.
(författare)
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Remobilization does not fully restore immobilization induced articular cartilage atrophy.
- 1999
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Ingår i: Clinical Orthopaedics and Related Research. - : Lippincott Williams & Wilkins. - 0009-921X .- 1528-1132. ; :362, s. 218-229
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Tidskriftsartikel (refereegranskat)abstract
- The recovery of articular cartilage from immobilization induced atrophy was studied. The right hind limbs of 29-week-old beagle dogs were immobilized for 11 weeks and then remobilized for 50 weeks. Cartilage from the immobilized knee was compared with tissue from age matched control animals. After the immobilization period, uncalcified articular cartilage glycosaminoglycan concentration was reduced by 20% to 23%, the reduction being largest (44%) in the superficial zone. The collagen fibril network showed no significant changes, but the amount of collagen crosslinks was reduced (13.5%) during immobilization. After remobilization, glycosaminoglycan concentration was restored at most sites, except for in the upper parts of uncalcified cartilage in the medial femoral and tibial condyles (9% to 17% less glycosaminoglycans than in controls). The incorporation of 35SO4 was not changed, and remobilization also did not alter the birefringence of collagen fibrils. Remobilization restored the proportion of collagen crosslinks to the control level. The changes induced by joint unloading were reversible at most sites investigated, but full restoration of articular cartilage glycosaminoglycan concentration was not obtained in all sites, even after remobilization for 50 weeks. This suggests that lengthy immobilization of a joint can cause long lasting articular cartilage proteoglycan alterations at the same time as collagen organization remains largely unchanged. Because proteoglycans exert strong influence on the biomechanical properties of cartilage, lengthy immobilization may jeopardize the well being of articular cartilage.
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| 6. |
- Hordoir, Robinson, et al.
(författare)
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Nemo-Nordic 1.0 : a NEMO-based ocean model for the Baltic and North seas - research and operational applications
- 2019
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Ingår i: Geoscientific Model Development. - : Copernicus GmbH. - 1991-959X .- 1991-9603. ; 12:1, s. 363-386
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Tidskriftsartikel (refereegranskat)abstract
- We present Nemo-Nordic, a Baltic and North Sea model based on the NEMO ocean engine. Surrounded by highly industrialized countries, the Baltic and North seas and their assets associated with shipping, fishing and tourism are vulnerable to anthropogenic pressure and climate change. Ocean models providing reliable forecasts and enabling climatic studies are important tools for the shipping infrastructure and to get a better understanding of the effects of climate change on the marine ecosystems. Nemo-Nordic is intended to be a tool for both short-term and long-term simulations and to be used for ocean forecasting as well as process and climatic studies. Here, the scientific and technical choices within Nemo-Nordic are introduced, and the reasons behind the design of the model and its domain and the inclusion of the two seas are explained. The model's ability to represent barotropic and baroclinic dynamics, as well as the vertical structure of the water column, is presented. Biases are shown and discussed. The short-term capabilities of the model are presented, especially its capabilities to represent sea level on an hourly timescale with a high degree of accuracy. We also show that the model can represent longer timescales, with a focus on the major Baltic inflows and the variability in deep-water salinity in the Baltic Sea.
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| 7. |
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| 8. |
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| 9. |
- Rabe, Benjamin, et al.
(författare)
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The MOSAiC Distributed Network: Observing the coupled Arctic system with multidisciplinary, coordinated platforms
- 2024
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Ingår i: Elementa. - 2325-1026. ; 12:1
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Tidskriftsartikel (refereegranskat)abstract
- Central Arctic properties and processes are important to the regional and global coupled climate system. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) Distributed Network (DN) of autonomous ice-tethered systems aimed to bridge gaps in our understanding of temporal and spatial scales, in particular with respect to the resolution of Earth system models. By characterizing variability around local measurements made at a Central Observatory, the DN covers both the coupled system interactions involving the ocean-ice-atmosphere interfaces as well as three-dimensional processes in the ocean, sea ice, and atmosphere. The more than 200 autonomous instruments (“buoys”) were of varying complexity and set up at different sites mostly within 50 km of the Central Observatory. During an exemplary midwinter month, the DN observations captured the spatial variability of atmospheric processes on sub-monthly time scales, but less so for monthly means. They show significant variability in snow depth and ice thickness, and provide a temporally and spatially resolved characterization of ice motion and deformation, showing coherency at the DN scale but less at smaller spatial scales. Ocean data show the background gradient across the DN as well as spatially dependent time variability due to local mixed layer sub-mesoscale and mesoscale processes, influenced by a variable ice cover. The second case (May–June 2020) illustrates the utility of the DN during the absence of manually obtained data by providing continuity of physical and biological observations during this key transitional period. We show examples of synergies between the extensive MOSAiC remote sensing observations and numerical modeling, such as estimating the skill of ice drift forecasts and evaluating coupled system modeling. The MOSAiC DN has been proven to enable analysis of local to mesoscale processes in the coupled atmosphere-ice-ocean system and has the potential to improve model parameterizations of important, unresolved processes in the future.
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| 10. |
- Rutgersson, Anna, 1971-, et al.
(författare)
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Natural hazards and extreme events in the Baltic Sea region
- 2022
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Ingår i: Earth System Dynamics. - : Copernicus Publications. - 2190-4979 .- 2190-4987. ; 13:1, s. 251-301
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Tidskriftsartikel (refereegranskat)abstract
- A natural hazard is a naturally occurring extreme event that has a negative effect on people and society or the environment. Natural hazards may have severe implications for human life and can potentially generate economic losses and damage ecosystems. A better understanding of their major causes, probability of occurrence, and consequences enables society to be better prepared to save human lives as well as to invest in adaptation options. Natural hazards related to climate change are identified as one of the Grand Challenges in the Baltic Sea region. Here, we summarize existing knowledge about extreme events in the Baltic Sea region with a focus on the past 200 years as well as on future climate scenarios. The events considered here are the major hydro-meteorological events in the region and include wind storms, extreme waves, high and low sea levels, ice ridging, heavy precipitation, sea-effect snowfall, river floods, heat waves, ice seasons, and drought. We also address some ecological extremes and the implications of extreme events for society (phytoplankton blooms, forest fires, coastal flooding, offshore infrastructure, and shipping). Significant knowledge gaps are identified, including the response of large-scale atmospheric circulation to climate change and also concerning specific events, for example, the occurrence of marine heat waves and small-scale variability in precipitation. Suggestions for future research include the further development of high-resolution Earth system models and the potential use of methodologies for data analysis (statistical methods and machine learning). With respect to the expected impacts of climate change, changes are expected for sea level, extreme precipitation, heat waves and phytoplankton blooms (increase), and cold spells and severe ice winters (decrease). For some extremes (drying, river flooding, and extreme waves), the change depends on the area and time period studied.
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