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Impacts of piscicide-induced fish removal on resource use and trophic diversity of lake invertebrates
No full textChemical eradication of non-native species has become a widely used method to mitigate the potential negative im- pacts of altered competitive or predatory dynamics on biodiversity and natural ecosystem processes. However, the re- sponses of non-target species can vary from rapid full recovery to delayed or absent recolonization, and little is known about the potential shifts in resource use and trophic diversity of native species following chemical treatments. We used a before-after-control-impact approach to study the effects of rotenone piscicide treatment on abundance and tro- phic niche of benthic invertebrates in three untreated and three treated lakes in central Norway, the latter group hosting non-native roach (Rutilus rutilus) and pike (Esox lucius) prior to rotenone treatment. Based on community com- position data, the relative abundance of invertebrate grazers and collectors decreased while that of predators increased following fish removal in the treated lakes. The stable isotope data indicated minor shifts in resource use of, and tro- phic diversity among, benthic invertebrate communities. While the predatory dragonfly larvae (Odonata) and grazer snails (Lymnaeidae) showed increased δ13C values indicating increased reliance on littoral benthic algae, the collector mayfly larvae (Leptophlebia) showed decreased δ13C values following fish removal in treated lakes. Grazer snails also showed a shift to a lower trophic position, while the predatory dragonflies and collector mayflies showed no changes in δ15N values following fish removal. The community-level isotopic niches of benthic invertebrates showed no consis- tent changes, although the sample-size corrected and Bayesian estimates of standard ellipse areas (SEAC and SEAB) slightly increased in two of the three treated lakes due to an increased range in δ15N. In conclusion, our study findings indicate some changes in species assemblages but minor shifts in the resource use and trophic diversity of benthic in- vertebrate communities following fish removal in rotenone treated lakes Chemical eradication Community dynamics Food web Rotenone Species interactions Stable isotope analysi
Variations in molecular and isotopes composition of seepage gases in the north-western and south-eastern parts of Lake Baikal
No full textThe paper presents results of gas-geochemical studies of bottom sediments and petroleum potential assessment of Baikal Rift Basin. During the expeditions of the Class@Baikal project in 2014–2019, gases from the Lake Baikal bottom sediments were analyzed. The results showed a clear difference in chemical and isotopic composition of the seeping gases collected in the northwestern and southeastern parts of the lake. The seepage released from northwest part were relatively enriched by methane and had a low concentration of C2+ compounds. The seepage gases had relatively lighter carbon isotopes composition of CH4 (from -72,7 to -50,1 ‰ VPDB) and the high variability of δ13C in C2H6 (from -65 to -22 ‰ VPDB). The gases released from southeastern part of the lake had an increase in C2+ compounds and had relatively lighter carbon isotopes composition of methane (from –57,2 to –41,0 ‰ VPDB). The carbon isotopes composition of ethane varies from -32 to -25 ‰ VPDB. Asymmetric structure of the Baikal rift basin and various processes of gas migration within it might cause the variations. Diffusive process led to the lighter carbon isotopes composition of the seepage gases from the northwestern part of lake and the gas molecular composition enrichment by methane. Such molecular and isotopic fractionations caused by geochemical processes helps to understand the migration of gas from source rocks to the earth’s surface. Similar geochemical indicators of fractionation should be taken into consideration when assessing oil and gas source rocks and basin potential from gas geochemical studies data
Stochastic Volterra integral equations and a class of first-order stochastic partial differential equations
No full textWe investigate stochastic Volterra equations and their limiting laws. The stochastic Volterra equations we consider are driven by a Hilbert space valued Lévy noise and integration kernels may have non-linear dependence on the current state of the process. Our method is based on an embedding into a Hilbert space of functions which allows to represent the solution of the Volterra equation as the boundary value of a solution to a stochastic partial differential equation. We first gather abstract results and give more detailed conditions in more specific function spaces
Pharmacological and genetic approaches to modulate energy metabolism in skeletal muscle cells
No full textThe prevalence of obesity and related metabolic illnesses have rapidly increased over the last decades. One of these diseases is type 2 diabetes (T2D), characterized by chronic hyperglycaemia and insulin resistance in several organs including skeletal muscle, an organ of particular interest when it comes to further understand metabolic conditions. In this thesis, we aimed to study the effects of different pharmacological and genetic approaches on skeletal muscle energy metabolism.
The results presented in this thesis shows that activation of β2-adrenergic receptors and the cold-sensing transient receptor potential ion channels (TRP), inhibiting diacylglycerol acyltransferase (DGAT) and ablation of the α2 subunit of adenosine 5’-monophosphate (AMP)-activated protein kinase (AMPK) affected energy metabolism in myotubes. The β2- agonist terbutaline increased glucose uptake, glucose and fatty acid oxidation, upregulated mitochondrial and oxidative pathways and increased protein synthesis. Activation of TRPA1 resulted in an increased glucose uptake and oxidation, whereas inhibiting of DGAT and ablation of α2 subunit of AMPK resulted in alterations in lipid metabolism
Simulation of 3D hydrothermal circulation and application to faulted oceanic ridge systems
No full textHydrothermal circulation in locations close to oceanic spreading ridges gives dissolved minerals from the crustal rock a chance to reach the seafloor. Temperature is increasing steadily with depth, heating water which resides within the permeable and faulted crust. At sufficient permeability, this causes the fluid to rise due to a lower density, allowing for dissolved minerals from the surrounding rock to be convected upwards. Natural convection in porous media heated from below is a thoroughly studied field, and we have studied this for faulted domains with parameters representative for the subseafloor. We have numerically solved the fully coupled conservation equations for fluid volume and energy with code based on tools from the open-source Python framework PorePy. The 3D domain where the equations have been solved are represented as a mixed-dimensional domain, where the porous rock, faults and fault intersections are treated as individual subdomains. The key concept behind a mixed-dimensional domain is that the different subdomains have different dimensions, meaning that within a 3D rock, the faults will be 2D, and fault intersections are 1D. Verification of the code has been done by confirming consistency in solutions with different initial conditions, and by numerical benchmarking against theoretical critical Rayleigh numbers for three different 3D domains. For fluid flow in faulted domains, it is expected that the fluid mainly flows through the faults as they are more permeable than the surrounding rock, and this is confirmed by the simulations. The results also present clearly how convection patterns are greatly impacted by different permeability ratios between the faults and the host rock, which may motivate further research considering layered or anisotropic porous media. The presence of faults is shown important for occurrence of hydrothermal convection in locations containing less permeable rock. Hence, the thesis illustrate how simulations can aid in understanding of governing processes for fluid circulation and transport of minerals in the subseafloor
Med matematikken i sikte. En aksjonsforskningsstudie om elevers opplevelse av et yrkesrettet undervisningsopplegg i matematikk, rettet mot børsemakeryrket
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Attitudes towards the Covid-19 vaccine on Twitter in Norway
No full textThe goal of this thesis is to characterize the distribution of attitudes present on Norwegian Twitter concerning the Covid-19 vaccine by implementing methods for text analysis and social media network analysis. The first analysis performed was manually classifying a sample of the dataset into four categories: irrelevant, neutral, vaccine hesitancy and anti-vaccine hesitancy. This sample dataset was used to train a supervised machine learning model, using BoW and SVM, in order to classify the total dataset. Furthermore, two methods for topic modeling were implemented: Latent Dirichlet Allocation and Biterm. Lastly, three main social networks were created: a mentioning-network containing users mention or mentioning in the dataset, a retweet-network containing users retweeted/quoted or retweeting/quoting and a sentiment network only including users classified as vaccine hesitancy and anti-vaccine hesitancy in the sample network. The ten users with highest scores for in-degree, out-degree and betweenness from the retweet network were analyzed to determine sentiment. The main findings are that the methods for topic modeling did not fit expectations and gave limited findings concerning topics in the theme, but topic modeling illustrated the amount of noise in the dataset. The manual classification resulted in approximately 30% vaccine hesitancy, while the trained supervised machine learning model resulted in only 10% vaccine hesitancy. The mentioning-network illustrated that the debate evolved and then stabilized through the autumn/winter of 2020. The most mentioned users were positive towards the vaccine. There was a separation regarding sentiment for the most retweeted and users retweeting most. Users displaying vaccine hesitancy sentiment tended to retweet slightly more than users displaying anti-vaccine hesitancy sentiment, and there were signs of echo chambers