Browsing by Subject "tundra"
Now showing items 1-4 of 4
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(2023)The ongoing environmental change will cause changes in arctic-alpine environment affecting both abiotic and biotic processes and the distribution of arctic-alpine vegetation that has adapted to the cold environment. Former studies on the distribution of arctic-alpine vegetation have been conducted more from a macroclimatic point of view neglecting the microclimate perspective. Microclimate refers to radiation, temperature, humidity, and wind conditions near the Earth’s surface. These conditions vary notably in the topographically heterogenous mountain tundra. The effect of the microclimatic factors is particularly important when investigating low-growing arctic-alpine vegetation as the microclimatic variables can be expected to describe the climatic conditions of the biotically active layer better than the macroclimatic variables. The purpose of this thesis is to study how the microclimatic conditions vary across different biotopes within mountain tundra and to examine which microclimatic variables best explain the local distribution of the arctic-alpine vegetation. The microclimatic variation in the different biotopes of the mountain tundra was studied by examining the statistical key figures of air and soil temperature and soil moisture measurements. Species distributions modelling was used to examine the distribution of arctic-alpine vascular plants and species correspondence to the microclimate variables as well as the importance of those variables on the species distributions. The research material consists of the microclimate and species data collected on the field as well as data based on topography and remote sensing. The data for the study were collected around Rastigaisa mountain in northern Norway. The explanatory variables used in the species distribution modelling included freezing degree day (FDD), growing degree day, radiation, soil moisture, topographic position index and information on the snow cover persistence. Species distribution modelling was performed using generalized boosted regression. From the modelling results the relative importance of the predictor variables as well as the predicted distributions of the species were interpreted. Microclimate factors varied between biotopes. The biggest variation in air temperature was observed at mountain tundra heath. Soil moisture had a levelling effect on the minimum temperatures and the FDD’s. The species distribution modelling results show that snow and moisture variable have a significant impact on the distribution of the arctic-alpine vegetation. Snow controls both temperature and moisture conditions and hence affects the stress that vegetation undergoes as well as the supply of nutrients.
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(2021)Large amounts of carbon is stored in the soil and vegetation of the tundra ecosystem. Carbon dioxide is stored in the vegetation in photosynthesis and is released into atmosphere from the soil and vegetation in ecosystem respiration. Rising temperatures can cause considerable changes to the delicate tundra ecosystem and create new potential feedbacks to global warming as the environment changes. There are several factors regulating carbon dioxide fluxes and their interactions and temporal changes are not yet fully known. Understanding carbon dioxide fluxes and the factors contributing to them is important in order to study and predict temporal and local changes. This research focuses on describing changes in net ecosystem exchange, primary production, and ecosystem respiration in the tundra as well as the factors contributing to them. The measurements were made with the chamber method in Saana fell, Kilpisjärvi in Finnish Lapland. This study includes 14 nivations with a total of 84 study points that were measured three times during the growing season in the summer of 2019. In addition to flux the measurements, information about controlling environmental variables were collected. These included vegetation, air temperature, soil moisture and soil temperature. The impact of the explanatory variables on fluxes at different times in the growing season was studied using mixed effects model and an estimated carbon budget was calculated for the region. The largest fluxes were measured mid-July during the peak growing season. Ecosystem respiration and primary production declined from the peak of the growing season in August towards the end of the growing season, but net ecosystem exchange increased slightly due to imbalances in the other two fluxes. Vegetation was an important explanatory variable (p ≤ 0,001) in every flux and during different times of the growing season. Air temperature had the greatest impact on net ecosystem exchange and ecosystem respiration, but the intensity of its response varied during different periods of the growing season. In both of these fluxes, higher temperatures increased the flux into the atmosphere. In primary production, the response changed in the middle of the growing season from positive to negative due to high temperatures. Soil moisture had a positive effect especially on ecosystem respiration, but its significance varied during the growing season (p = 0,0012; 0,02; < 0,001) and the response increased towards the end of the growing season. Also in primary production, response intensity and significance (p = 0,02) increased at the end of the growing season and in net ecosystem exchange the response changed from negative to positive at the end of the growing season. The response of soil temperature increased with all fluxes from the beginning of the growing season and decreased with ecosystem respiration and net ecosystem exchange towards the end of the growing season. Soil temperature was only significant in the second measurement campaign for net ecosystem exchange (p = 0,01) and ecosystem respiration (p = 0,005). During the growing season, carbon dioxide fluxes changed considerably and their explanatory factors also varied in time. The responses to soil moisture and air temperatures also turned negative or positive during the growing season. These changes and studying them is very important to understanding the processes behind different fluxes. The change in carbon dioxide fluxes and the variables that affect them in the tundra environment affects the region's carbon budget.
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(2023)Bioklimaattinen mallinnus on keskeinen biogeografinen menetelmä, jolla tutkitaan lajilevinneisyyden ja ilmaston välistä yhteyttä. Tutkimuksessa tarkasteltiin, kuinka hyvin lämpö- ja kosteusolosuhteita kuvaavat bioklimaattiset muuttujat selittivät tundran putkilokasvilajien levinneisyyttä kahdella mittakaavatasolla ja mitkä muuttujat olivat suhteellisesti tärkeimpiä eri lajeille. Lisäksi tarkasteltiin muuttujien alueellista vaihtelua. Biogeografinen tutkimus on erityisen tärkeää tundralla – esimerkiksi Suomen tunturipaljakan putkilokasvilajeista 16 % on uhanalaisia, ja tämän luvun odotetaan kasvavan ilmaston lämpenemisen myötä. Tutkimus sijoittui Mallatuntureiden ja Ailakkavaaran alueille Luoteis-Lappiin. Mallinnettavia putkilokasvilajeja oli 26, joista kahdeksan on arktis-alpiinisia ja muut boreaalisia. Bioklimaattisia muuttujia johdettiin kahdesta ilmastoaineistoista: hienon mittakaavan mikroilmastoaineistosta sekä mesomittakaavan sääasemien mittauksista interpoloidusta aineistosta, joka kuvaa makroilmastollisia olosuhteita. Bioklimaattisten muuttujien alueellista vaihtelua tutkittiin karttatarkastelun avulla ja aineistojen erojen tilastollista merkitsevyyttä arvioitiin tilastollisin tunnusluvuin. Malleja rakennettiin kolmella menetelmällä: yleistetyt lineaariset ja addittiviset mallit sekä yleistetyt luokittelupuut. Mikroilmastomallien muuttujia olivat kasvukauden lämpöolosuhteita kuvaava tehoisa lämpösumma, talven olosuhteita kuvaava helmikuun minimilämpötila ja kesän kosteusolosuhteita kuvaava heinäkuun maaperän kosteus. Makroilmastomalleissa oli muuttujina lämpösumma, helmikuun minimilämpötila ja kesän sademäärä. Mallien suorituskykyä arvioitiin AUC-arvojen avulla ja muuttujien tärkeydet selvitettiin yleistetyt luokittelupuut -menetelmällä. Hienon mittakaavan bioklimaattiset muuttujat kuvasivat selkeästi tarkemmin lämpö- ja kosteusolosuhteiden alueellista vaihtelua lyhyillä etäisyyksillä kuin karkeamman mittakaavan muuttujat. Eri mittakaavojen muuttujien erot olivat myös tilastollisesti merkitseviä. Vaikka bioklimaattisten mallien suorituskyky oli keskimäärin heikko, mikroilmastomallien AUC 0,69 oli korkeampi kuin makroilmastomallien AUC 0,63. Ero suorituskyvyssä oli siis tilastollisesti merkitsevä. Mikroilmastomallit selittivät paremmin yksittäisten putkilokasvilajien levinneisyyttä kuin makroilmastomallit, sillä suorituskyvyltään hyviä tai erinomaisia malleja oli enemmän. Alle puolelle lajeista suhteellisesti tärkein bioklimaattinen muuttuja oli sama eri mittakaavoilla. Tehoisa lämpösumma oli tärkein muuttuja useimmille arktis-alpiinisille ja boreaalisille lajeille karkeammassa mittakaavassa, kun taas heinäkuun keskimääräinen maaperän kosteus oli tärkein muuttuja useimmille arktis-alpiinisille lajeille hienossa mittakaavassa. Tehoisa lämpösumma oli tärkein muuttuja useimmille boreaalisille lajeille myös hienossa mittakaavassa. Tutkimuksen perusteella tundran mikro- ja makroilmastolliset lämpö- ja kosteusolosuhteet eroavat merkittävästi toisistaan, millä on merkitystä esimerkiksi lajien suojelusuunnittelua kehitettäessä ilmaston lämmetessä. On tärkeää huomioida, millaisia ilmasto-olosuhteita bioklimaattisten mallien aineistot kuvaavat, kun tutkitaan tundran putkilokasvilajien suhdetta ympäristöönsä hienossa mittakaavassa.
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(2023)Substratum and environmental variables influence benthic algal species richness and community composition. Benthic habitats form complex connections within and between communities leading to unique water ecosystems. In order to better understand substratum relationships and the effects of environmental covariates towards microorganisms, this study focused on benthic diatoms in subarctic mountain ponds living in different substrata. Moreover, methodological choices are important for field survey in freshwater environments and thus in this study, we also compared sponge and brush sampling techniques to examine possible differences in benthic diatom species richness and community composition. We sampled 23 subarctic ponds between July and August 2022 in northern Fennoscandia. The samples were taken from stones and sediment. To analyse the differences between species richness for substrata and methods, we used paired Wilcoxon signed-rank test and paired t-test. In order to find out the most significant environmental variables influencing diatom species richness, we used generalized linear models (GLM). Differences in diatom community compositions were analysed using non-metric multidimensional scaling (NMDS), analysis of similarities (ANOSIM), and Jaccard similarity index. Finally in order to visualise the variation in community composition between stone and sediment samples explained by environmental variables, a redundancy analysis (RDA) was used. Benthic diatom species richness significantly differed between rock and sediment substrata where sediment was the most species rich substratum. Local environmental variables were influential towards diatom species richness, where water pH was the major determinant for both substrata. Diatom community composition did not differ significantly between rock and sediment substrata but was defined by environmental variables such as pond surface area and water pH having a strong influence on both substrata. No significant differences were found between sampling methods in terms of diatom species richness or community composition. Our results support the theory that sediment substratum contains the highest diatom species richness. Furthermore, the study highlights the importance of water pH on benthic diatoms regardless of substratum, supporting diatom reliability as bioindicators for water pH.
Now showing items 1-4 of 4