Tephrochronology is a powerful tool to correlate and improve the chronology of sedimentaryarchives in the Arctic Ocean. The Aniakchak Caldera Forming Eruption (CFE) in Alaska at3.6 cal kyr BP ejected ash that were found in a widespread layer in Alaska, and as cryptotephrain the Chukchi Sea, Newfoundland, and Greenland. This study presents data from the coreSWERUS-L2-4-PC1 (4PC) taken at a water depth of 120 m in the Chukchi Sea. The sharp peakin tephra shards concentration permitted to clearly place the isochron. Unfortunately, the microprobeanalyses were unsuccessful, however measurements of trace elements were performedwith Laser Ablated-Inductively Coupled Plasma-Mass Spectrometry (LA-ICP-MS). The geochemicalsignature of the Aniakchak 3.6 eruption was ensured with significant trace elementratios. The isochron of the eruption combined with the radiocarbon dates from 4PC permittedto calculate the local marine radiocarbon reservoir age offset DR=36446 years. This value isrelatively low compared to recent estimates in the Chukchi Sea, especially to the neighbouringcore SWERUS-L2-2-PC1 were DR=47760. The DR value of this study is explained by theinfluence of the "young" Atlantic water mixing with the "old" Pacific water at the depth wherethe core was taken.

No description available.

Rapid warming in the Arctic is highly impacting the cryosphere in the region, causing melting of the sea ice, retreat of glaciers and reduction in the snow cover. If suffering further temperature increase, the albedo of the region would reduce due to higher absorption of the solar radiation in snow-free areas. The variations in seasonal snow cover in Arctic regions can impact a lot of things including the ecosystem, biodiversity, hydrological cycle, and many other physical processes. Therefore, it is beneficial to have the knowledge of processes determining the snow distribution and to understand the trends and patterns of the seasonal snowcover.In this project, seasonal snow cover trends and patterns have been studied for a 30-year period from 1991 to 2020 using a newly developed reanalysis dataset called Copernicus Arctic Regional Reanalysis (CARRA). A validation of the CARRA data set has been done for the snow depth using point observation data from the Norwegian weather stations and a visual snow cover comparison using Sentinel-2 remote sensing data. Thereafter, interannual variability in day of snow disappearance, day of snow onset, duration of snow-free period, and maximum snow depth have been analysed and these trends are then discussed in detail.The results show that for the most non-glaciated regions in Svalbard, the snow onset is happening later in the winter season while the day of snow disappearance is arriving earlier in the spring. Consequently, the duration of snow-free period has increased in almost all regions of Svalbard except a few sites where the duration of the snow free-period has decreased most likely due to local climatic factors. These factors can be better understood by incorporating meteorological elements like precipitation, air temperature and wind speed. Overall, the CARRA reanalysis dataset is very good in determining snow cover trends in non- glaciated regions of Svalbard and with some updates and modifications, it might be able to determine snowcover for the glaciated regions in future.

No description available.

Retention forestry is a key measure in Swedish forestry policy to combine a clearcutting regime and sustainability goals regarding forest biodiversity. The aims of increasing industrial production from forestry and to protect the environment is equally prioritized in the Swedish forestry legislation. Freedom for landowners is a cornerstone in Swedish forestry policy. This position is heavily debated among activists and scholars and is politically questioned, especially from the European Commission which challenges the Swedish position. This study investigates how Swedish landowners interpret and practice retention in forestry, discussed through a theoretical framework of political ecology. Logged areas from 2020 in Trosa municipality in Sweden was investigated through field work and remote sensing through NDVI-analysis. Retention was practiced in all the logged areas, but the measures and level of retention varied greatly. The method can be used for different purposes at different seasons. If production and environment is equally prioritized as the legislation requires is questioned.

The permafrost region covers a vast area of land surface on the northern hemisphere,storing large amounts of carbon. Unfortunately, climate warming leads to permafrostthaw altering the hydrothermal state of permafrost soils. Due to the remoteness of thepermafrost region, access to field measurements is restricted. Therefore, remotesensing is an asset to study the permafrost region. Since permafrost is a sub-surfacephenomenon it cannot be directly observed from space. However, by using differenttypes of satellites the soil properties of the top soil layer, down to 10 cm depth, can beaccessed. To establish soil properties for the deeper soil layers modelling is required.The ERA5-Land (ERA5L) soil moisture is modelled based on climate reanalysis. Inthis study in-situ soil moisture data from the International Soil Moisture Network(ISMN) is used to evaluate the performance of the ERA5L soil moisture data withinthe permafrost region. The performance of the ERA5L soil moisture is found toperform best in soil layer 1 (0-7 cm depth) and worst in soil layer 3 (28-100 cm depth).For both soil layer 1 and 2 (0-7 and 7-28 cm depth) a moderate correlation(0.309 < R < 0.335) was found between ERA5L and in-situ soil moisture data, in Julyand August. The performance of the ERA5L soil moisture is best in Europe and worstin North-America. Compared to other evaluations of ERA5L soil moisture, within thepermafrost region, this study found a relatively low correlation. Therefore, this studyconcludes that on a global scale the ERA5L soil moisture is not ideal for directlyinforming permafrost research and decision making. However, integrating multisourcedatasets, resampled to a finer spatial resolution, could improve the performance ofERA5L soil moisture model on a global level. Moreover, on a local scale theapplication of a bias correction could also improve the performance of the ERA5L soilmoisture model.

The largest wildfire ever observed in Greenland raged through its tundra during august 2017, and it is unknown if there have been similar wildfires in the area before satellite monitoring began in 1999. Arctic wildfires affect permafrost degradation, carbon storage of soils and the surface albedo of the Greenland Ice sheet – despite this, local fires have previously been ignored by researchers. Here, aeolian dust deposits are independently dated by radiocarbon and luminescence techniques and paleoenvironmental proxies and macrocharcoal contents reflecting local fires are analyzed. The dating results indicate that the onset of aeolian deposition coincides with the deglaciation of the area, suggesting that paleoenvironmental proxy records from aeolian dust deposits may extend the entire ice-free period of the area until approximately 8 ka BP. Luminescence signals are generally partially bleached, resulting in age over-estimation of several samples. This effect is quantified using the pIRIR/IR ratio and different integration limit intervals. No evidence for previous wildfires were found during the charcoal analysis, suggesting that the area around the assessed profile has never been burnt since its deglaciation. These first results show promise for the method, and in order to expand this to a regional estimate of the wildfire activity through the Holocene, analysis of more material is needed.

No description available.

The aim in this study was to develop a model for the probability of finding active golden eagle nests during their breeding season. It was done by using environmental variables derived from expert models which were tested against empirical data. This resulted in a habitat suitability index (HSI), which in this case is assumed to indicate the probability of active nests of golden eagles. The study was conducted together with the County Administrative Board of Västernorrland with the purpose to improve golden eagle’s ecological status.To develop the model, different combinations of several explanatory variables were tested in a model selection process, where the most optimal and parsimonious model was chosen. The tested variables have earlier been shown to affect golden eagles, as slope, aspect, forest age, foraging habitat, suitable flight routes, human population density, roads, railways, power lines, wind power plants, hiking trails and clear cuts. The variables where applied in in ArcMAP at three different scales: nest scale (25 x 25 meter), proximate scale (a circle with the radius of 500 meter) and home range scale (a circle with the radius of 8253 meter). A preliminary test of the variables showed that all golden eagle nests were found in slopes with at least 5֯ degreesas well as in home ranges with human population density not more than 8 people/km2. Due to that a stratified analysis wasperformed. The variables where analysed by multiple logistic regression in R, where the occurrence of golden eagles’ nestswas compared towards random points in the landscape. All variables were also tested one by one by logistic regression. Afterperforming the multiple logistic regression, it was possible to apply its equation into ArcMap to obtain suitability maps withHSI values over Västernorrland’s county.The comparisons of different models show that it is better to combine different spatial scales in the model than only using one spatial scale. The result indicate that three different models might be the best, which all had different combinations of slope and aspect at nest scale and power lines at the proximate scale. Two of these models also include hiking trails and human population density, both at home range scale, in their equation. Since it was some unclarity about the causality between hiking trails and human population density, the conclusion was not to choose any of these as the final model. The final model was more parsimonious and had an additive effect from slope and southern aspect at the nest scale and an antagonistic effect from power lines at the proximate scale.This study clarifies that golden eagles’ habitat preferences for nesting sites during their breeding period is steep slopes (at minimum 5֯ degrees) in more southern aspects with few power lines in the proximate area surrounding the nest. Their homeranges are also situated in areas with less than 8 people/km2. The study also pinpoints a potential conflict between golden eagleand wind power planning, as golden eagles prefer steep slopes and remote areas, which also are valuable areas for wind powerplants. Golden eagles’ preference of remote areas also indicate that they might be affected by human persecution, why certainconservation effort should be focused into this issue. Out from the final model, you can find cluster in the landscape where youcan focus conservation management and restrict exploitation. Due to low number of wind power plants in the landscape, nothingcould be concluded about their effect on golden eagle in this study. An advice from the golden eagle’s perspective is to use theprecautionary principle and further plan wind power plants in areas which already have high disturbance, as for example closeto power lines or roads. The result also indicates that forest age from SLU Forest Map is not suitable for telling where to findgolden eagle nests. GIS-data over forest age would facilitate conservation management for plenty of species connected to theforest.Although good statistical results for the final model, cautions need to be taken in general, since neither population viability analysis have been included, nor changes over time in the landscape. Another issue is the low sample size, where a larger sample size would make it possible to perform profound calibration and validation of the data. To develop a more robust model, the advice is to include these into the model and use a larger sample size.

Transportsektorn står för en betydande del av utsläppen av växthusgaser och andra luftföroreningar, som bidrar till den globala uppvärmningen och negativ påverkan på folkhälsan (Dahlstrand, 2020). För att nå klimatmålen räcker inte mer energieffektiva fordon och förnybara drivmedel, utan hela samhället måste bli mer transporteffektivt (Steg & Gifford, 2005). Det görs många olika insatser i både kommuner och på regional nivå för att öka och uppmuntra cykling i form av testresenärsprojekt. I denna uppsats används testresenärsprojekt som ett samlingsbegrepp för olika projekt som implementerats på kommunal- och regional nivå för att främja hållbart resande genom att påverka transporter, resvanor och trafikantbeteende. Det finns idag flera rapporter som lyfter fram exempel på testresenärsprojekt (Energimyndigheten, 2018), men information om projektens effekter och samhällsnytta är väldigt begränsad och den information som finns tenderar vara av varierande kvalitet (Trafikverket, 2012). I denna uppsats studeras hur hållbara testresenärsprojekt för främjande av cykling är. Genom innehållsanalys av projektens utvärderingar studeras projektens fokus på hållbarhet och genom frågeformulär studeras tillämpning och uppföljning av resultat efter projektfas. På grund av varierat resultat går det varken att verifiera eller falsifiera hypotesen om att testresenärsprojekt för främjande av cykling i större kommuner leder till långsiktigt hållbar mobilitet i kommunerna/regionerna efter projektfas.Sammanfattningsvis visar resultatet att en del projekt leder till långsiktig hållbarhet, utifrån tillämpning av lärdomar, uppföljning av resultatet och tillgänglig kunskap om projekten. Men projekten tenderar inte följas upp ur ett längre tidsperspektiv och det finns en avsaknad av information om projektets långsiktiga effekter. Eftersom flera testresenärsprojekt har genomförts under de senaste åren finns egentligen ett stort kunskapsunderlag, men problematiken ligger i att följa upp och nyttja den genererade kunskapen. Många projekt förblir experimentella och försvinner efter en demonstrationsfas, som en konsekvens av detta förblir effekterna av lösningar som utvecklats i projekten ofta begränsade (Vilajosana et al., 2013). / The transport sector accounts for a significant part of the emissions of greenhouse gases and other air pollutants, which contribute to global warming and a negative impact on public health (Dahlstrand, 2020). To achieve the climate goals more energy-efficient vehicles and renewable fuels are not enough, the whole society must become more transport-efficient (Steg & Gifford, 2005). Many efforts are made at municipal- and regional level to increase and encourage cycling in the form of mobility projects (sv. Testresenärsprojekt). In this thesis “mobility projects” is used as a collective term for projects that have been implemented at municipal or regional level to promote sustainable travel by influencing transportation, travel habits and behavior. Today there are several reports that highlight examples of mobility projects (Energimyndigheten, 2018), but information about the projects' effects and societal benefits is very limited and the information available tends to be of varying quality (Trafikverket, 2012). The purpose of this thesis is to study the sustainability of mobilityprojects for the promotion of cycling. Content analysis was used to study several mobilityprojects’ focus on sustainability, and through questionnaires, application of results and follow-up after project phase are studied. Due to varied results, it is not possible to verify or falsify the hypothesis that mobility projects for the promotion of cycling in larger municipalities lead to long-term sustainable mobility after the project phase. In summary, the results show that only some of the reviewed projects lead to long-term sustainability, based on the application of lessons learned, follow-up of the results and available knowledge about the project. The projects do not tend to be followed up from a longer time perspective and there is a lack of knowledge about the project's long-term effects. Since several mobility projects have been carried out in recent years, there is a large knowledge base, but the problem lies in following up and utilizing the generated knowledge. Many projects remain experimental and disappear after a demonstration phase, consequently the effects of solutions developed in the projects often remain limited (Vilajosana et al., 2013).