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ÖgeEstimation of PM10 variations in the Southeastern and Eastern Anatolia regions of Türkiye using remote sensing and statistical models(Graduate School, 2024-07-25)The significance of air quality extends to both indoor and outdoor settings, with poor air quality directly impacting the quality of life. Particulate Matters smaller than 10 μm in diameter (PM10) are of particular concern. Penetration to the airways is easier with these types of particles. Particulate Matters (PMs) can contribute to both respiratory and cardiovascular diseases (i.e. asthma, emphysema, and lung cancer). Air quality in Türkiye is affected by dust coming from Sahara Desert and Arabian Peninsula. Our study aims to research PM10 variations in the Southeastern and Eastern Anatolia regions of Türkiye from 2014 to 2016 using remote sensing and statistical models. The Moderate Resolution Imaging Spectroradiometer (MODIS) derived Level-3 Aerosol Optical Depth (AOD) data, air quality data and meteorological variables of 15 ground-observed stations present in the Southeastern and Eastern Anatolia regions of Türkiye were used in this study to assess PM10 estimations in the study area. The PM10 ground observations used in the study for the years 2014, 2015 and 2016 were received from the Republic of Türkiye Ministry of Environment and Urbanization and Climate Change. Hourly PM10 and meteorological data were converted to daily data and days having more than 30% missing values were not included into the study in order to find out PM10 variations. Moreover, statistical methods such as Multiple Linear Regression (MLR) model, Linear Mixed Effect (LME) model and Machine Learning (ML) techniques were used to anticipate the Particulate Matter (PM) concentration in the region using satellite-based AOD and meteorological variables such as temperature, wind speed, relative humidity, precipitation and atmospheric pressure. Since some cities are located on the same grid in the AOD study area map obtained from MODIS in the PM10 estimation studies, 12 out of 15 stations were included in the statistical analysis to avoid extra PM10 calculations. The results indicated that aerosol pollution in the region as a result of transported dust from the Arabian Peninsula in spring time was high enough and the PM10 concentration in the cities close to the borders of Iraq and Suria such as Hakkari and Mardin was observed more than 200 µg/m3 in spring of 2015. Both local heating emissions and long-range dust transport could have significantly impact on PM10 levels in Southeastern Anatolia in study period. In addition, stubble burning in those years may also be effective in the high PM10 levels in the region in the fall. Significant amounts of dust, pollution, or biomass combustion make contribution to higher atmospheric aerosol concentrations. MODIS data from the AOD maps of 2014, 2015 and 2016 show that the Southeastern and Eastern Anatolia regions were exposed to aerosol pollution. The results of statistical models for prediction of PM10 indicated that PM10 was very dependent on AOD and temperature. The statistical parameters such as Correlation Coefficient (R), R-Squared (R2) and Root Mean Square Error (RMSE) were calculated to understand performances of models applied in the study. In the MLR method, PM10 was estimated by including only one meteorological factor other than AOD. Each meteorological factor was used with AOD in the equation respectively in the MLR method. When PM10 was predicted by using all meteorological factors respectively, it showed that among these parameters, temperature affected PM10 values more. Based on the outcomes, performance of all statistical models was improved when AOD values with all meteorological parameters were used in estimating PM10. For example, the R, R2 and RMSE values of MLR for averaged data for summer season were calculated about 0.69, 0.47 and 8.21 with best performance in the study period, while winter accounted to the lower performance with R, R2 and RMSE values of 0.40, 0.16 and 25.10, respectively. MLR for all 12-station data gave its best result in autumn season with an R, R2 and RMSE values of 0.57, 0.33 and 42.46 respectively. For the LME model, the random effect parameter selected AOD enabled the model to have R, R2 and RMSE values of 0.51, 0.26 and 36.60, respectively for all study period. Atmospheric pressure also had a random effect in the LME model, with R, R2 and RMSE values of 0.86, 0.73 and 28.26, respectively for all studied years. AOD and atmospheric pressure had a significant impact on improving the LME model results. For whole study period Extreme Gradient Boosting (XGBoost) having 0.73, 0.54 and 17.88 values as R, R2 and RMSE, respectively for averaged data and having 0.69, 0.44 and 32.13 values as R, R2 and RMSE, respectively for non-averaged data making a moderate performance in estimating PM10 levels. Among all statistical methods, Random Forest performed the best in terms of fitting the regression line, with R, R2 and RMSE values of 0.97, 0.93 and 17.90, respectively, when averaged variables are included in the model, and R, R2 and RMSE values of 0.97, 0.93 and 29.26, respectively, when all variables are included in the model. While MLR depended on factors like quantity of meteorological variables included, its performance also was affected by which meteorological variable is chosen with AOD in PM10 estimation. In this study, the LME model also showed variability in performance depending on which meteorological variable was selected as a random effect for PM10 estimation. XGBoost's performance was moderate and it also had better results than MLR method for overall. In conclusion, satellite data with meteorological variables gives us the best performance when it is introduced to the Random Forest Model in order to forecast PM10 in study area. The correlation between PM10 and AOD is influenced by weather conditions, local pollutant emissions and the chemical composition of aerosols. Ground-based monitoring data is commonly used in health effect research. Because satellite data is readily available and inexpensive, AOD images can be used to estimate PM10 via using Machine Learning methods which processes factors that affect abundance of PM10.
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ÖgePhylogeography of the Savi's pipistrelle (Vespertilionidae, chiroptera) complex based on whole mitochondrial genome analysis(Graduate School, 2024-07-01)Understanding the phylogeography of species provides insight into the historical processes that lead the formation of their current geographic distributions and also how they evolve and adapt to variable environments over time. Intraspecific and interspecific genetic variations stand as a great indicator for elucidation of the evolutionary history of organisms in diverged phylogeographical patterns. Bats represent an immensely diverged group among mammals. They inhabit a wide variety of ecosystems, with the tropical belt hosting the highest number of bat species, similar to many other life forms. While the oldest known fossil of Chiroptera is approximately 52 million years old, they are hypothesized to be evolved around the Cretaceous-Tertiary boundary. During their evolution, they settled to the nocturnal niche. Echolocation and flight capabilities have affected the phylogenetic classification in the era of morphological and physiological taxonomy. However, the taxonomic classification of Chiroptera is a more complex phenomenon. The developments of modern genetic techniques transformed the historical perception of taxonomy. The introduction of high-throughput sequencing, which enables the sequencing of an organism's whole genetic material, has made genomic studies increasingly popular in biodiversity research. This powerful technique has revealed that organisms can exhibit significant genetic variation, even when their phenotypic characteristics do not reflect this diversity. Cryptic species, which arise from the discordance between morphological similarity and genetic divergence, exemplify this phenomenon. Resolving cryptic diversity is cruicial for identying evolutionary significant units and provides a new dimension for investigating the ecological dynamics of species. Furthermore, it is a significant concept in biodiversity assessment and monitoring, essential for inforimg conservation actions. Past studies have showned that the Palearctic Region hosts a rich fauna with signifacnt cryptic diversity, including among bats. Savi's Pipistrelle, Hypsugo savii, is a small-sized, vespertilionid bat species with a broad distribution range across various ecoregions in Europe, Asia, and North Africa. The accumulation of studies showing intraspecific variation within the species has drawn attention to the investigation of possible divergence within the taxon. Several studies idenfied deeply diverged mitochondrial lineages of H. savii. Two of such lineages have been proposed as distinct species statuses, H. darwinii and H. stubbei, based on their significant divergence from H.savii. Hypsugo savii hosts possibly further cryptic diversity. It is composed of deeply diverged clades, with sympatric occurences in Northwestern Africa, the Iberian Peninsula, Italy, and some Mediterranean islands (Sardinia, Sicily, and Malta). These studies, however, are based on limited sampling from a very broad geographical range. Furthermore, they utilize realtively short mitochondrial markers and marker selection is not usually consistent among studies. This study aims to invesitage the whole mitogemones of the previously identified H. savii lineages and the recently suggested related species. There are three main objectives: 1) establishing a reproducible workflow to de novo assemble mitogenome from whole genome sequencing data; 2) de novo assembling complete mitogenome of H. savii and the related species; and 3) reconstructing their phylogenetic relationships based on whole mitogenome sequences. Thirty samples from various regions including Central Asia, Sinai Peninsula, North Africa, continental Europea, and Mediterranean islands were analysed. High-throughput shotgun sequencing data was used for the analysis. The analysis workflow covers data filtering, de novo assembling of complete mitogenomes, and annotating the obtained mitogenomes. Complete mitochondrial genomes were succesfully de novo assembled for thirty samples, representing all of the previously identified lineages, as well as the closely related species, H. stubbei and H. alaschanicus. Mitochondrial genes were annotated on the assembled genomes. The read pool of each sample was mapped to the assembled mitogenomes to assess their coverage and also to edit possible misallignments and gaps. The samples which had uncircular genomes were manual edited and circularized. The tRNA profiles were analyzed with tRNAscan-SE. Phylogenetic relations of the analysed samples were investigated reconstructing phylogenetic trees. The sequences were aligned and the pairwise distance of the sequences were calculated with MEGA11. The phylogenies were obtained with Maximum-Likelihood model with IQ-TREE and RAxML tools. The trees were visualized with FigTree abd iTOL WebServer. The alignments were analysed with PopArt for a haplotype network analysis. The highly variable non-coding D-loop regions were removed from the sequences for all these analysis . All thirty-seven mitochondrial genes were annotated: two of them were ribosomal RNAs; twenty-two were transfer RNAs; and thirteen were protein-coding genes. D-loop regions of mitogenomes were also annotated. The secondary stuctures of the tRNA profiles were calculated and illustrated. The tRNA for serine amino acid was lacking the D- arm in the secondary stucture, which had no significant impact on its functionality. Phylogenetic analysis revealed that there are three main H. savii lineages in the Western Palearctic region. The related species, H. ariel, H.alaschanicus, and H. stubbei, also formed three distinct clusters. The latter was identified in Kyrgyzstan, which is outside of its known range. The distribution of Hypsugo savii lineages were in three main regions: Eastern Mediterranean, Western Mediterranean, and North African-Southwestern Mediterranean. In Sardinia, the latter of these three lineages were found together. The pairwise genetic distance between the clades in Europe were between 8 and 10%, close to the difference observed between H. alaschanicus and the other species. Similar levels of divergences were also found between newly proposed species, H. stubbei, and the European clades. These observed high levels of mitogenomic differences suggest that the H. savii complex probably harbours further cryptic diversity.
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ÖgeAssessing the Bosphorus as a migratory corridor for Pipistrellus nathusii using acoustic monitoring methods(Graduate School, 2024-07-02)Türkiye has one of the richest bat diversity in the Mediterranean region. However, essential ecological information about bat species, such as population sizes, distributions and their migration behaviour is lacking. This information gap is primarily due to the elusive behavior of bats. Most of the bat research in Türkiye is about cave-dwelling species, which are relatively easier to study. Studies on other species, on the other hand, are generally based on opportunistic and non-systematic surveys. In this context, acoustic ecology methods offer an effective approach to investigating bats. This study aims to conduct a systematic acoustic ecology investigation in İstanbul, Türkiye, with a specific focus on the role of Bosphorus as a migratory corridor for bats. In particular, the migration patterns of Pipistrellus nathusii, a long-distance migratory bat species, were investigated. Additionally, the relationship between bat activity and meteorological parameters, as well as moon phases were explored to assess their impact on migration. Ultrasonic sound recordings were collected from four different locations along the Bosphorus, spanning from north to south, between April and November 2022. Recordings were preliminary analysed with Kaleidoscope Pro software and then processed manually. Analysis revealed that bat activity was positively related to temperature. Wind speed and direction affect bat activity in different ways depending on the season. In particular, light winds are positively associated with bat activity. When the effect of moon phases on bat activity was examined, it was found that the P. nathusii activity level in Yıldız City Park and ITU Campus was more affected by the moon phases, and especially the Nathusius Pipistrelle acoustic group activity decreased during the full moon phase. Pipistrellus nathusii activity in Yıldız City Park increased from mid-August and decreased towards the end of October. Activity on the ITU Campus started to increase in mid-August, peaked towards the end of September, and decreased at the end of October. Activity in the Atatürk City Forest started to increase in mid-August, peaked in September, and continued to decrease slightly in the autumn. In the Sarıyer Forest, there was an increase in August, the highest activity was seen in September and decreased with the end of the autumn. These findings show that the Bosphorus is a migratory corridor for P. nathusii. The insights gained from this study will contribute to the conservation of migratory bat routes between Europe and Asia.
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ÖgeStudying the ancient settlement of Hacılar Büyük Höyük with integrated methods(Graduate School, 2022)Archaeology has great potential to illustrate the long-term human-environment interactions especially when it is supported by other disciplines and computational modeling. This holistic perspective provides a detailed analysis of landscape with a multidisciplinary framework that might provide an understanding of complex systems, including land use, interactions of the elements, and adaptation. The Hacılar Büyük Höyük, a major Early Bronze Age-I (ca. 3100 – 2900 BC) site in Burdur, (Turkey), has been the focus of this thesis. It has significant contribution to the knowledge of the Early Bronze Age-I (EBA-I, hereafter) and II phases in Southwest Anatolia with its settlement plan, defense system, archaeological remains, and its material culture. The primary goal of this research is to assess the long-term human-environment interactions at the site from an interdisciplinary perspective. In this research, three different digital-computational approaches have been used to assess the long-term changes in landscape around the site; GIS-based morphometric analysis, Ground Penetrating Radar (GPR, hereafter), and Agent Based Modelling (ABM, hereafter). Data was collected via unmanned aerial vehicle (UAV, hereafter) photography, and sub-surface geophysical measurements. Through the use of GPR and GIS-based morphometric analyses, I will calculate the scale of settlement and its agro-pastoral (i.e., farming and herding) catchment areas. I will then integrate cultural, economic, and environmental parameters into an agent-based modeling platform where I will visualize the spatio-temporal impacts of human activities (e.g., de-vegetation, erosion, deposition) at the site. The geomorphometric analysis is used to figure out how geomorphological features on and around the settlement are distributed. To gain a better understanding of the landscape, the sky-view factor (SVF, hereafter) map and red relief image mapping (RRIM, hereafter) approaches were applied. A combination of morphometric analysis and field observation provides complementary information about the site, land, and surroundings. Then, GPR data were implemented and results analyzed. The geomorphic units are mapped and the estimated agricultural catchment area is identified based on the slope of the area and distance from the settlement as the flat area limited by the river considering the geomorphic units were similar with modern data. Based on the site's layout, it is possible to calculate the approximate population of the settlement considering that the casemates surround the mound. ABM is used to evaluate the effects of land use on surface processes as well as to calculate agricultural catchment areas based on precipitation and population data. The Macrophysical climate model (MCM) results were used in the model as the input climate data. The ABM used in this study is Medland Modeling Laboratory (MML, hereafter) to simulate how dry farming and ovicaprid-based, site-tethered pastoralism affected the landscape around the site. As a result of the study, possible archaeological structures buried underground were determined by using GPR. Then, model results show agricultural exploitation of the landscape and husbandry practices between 3100-2900 BC had varying degrees of impact on the environment and that population density is the most critical factor. Within the scope of the study, GPR and geomorphological analyses enabled to visualize to combine incorporate unearthed archaeological remains in the ABM for calculating the approximate human and animal population of the settlement. Then, four scenarios have been tested by changing the climate and increasing population variables for 200 years. The cumulative changes in the woodland vegetation, erosion, and deposition provide critical information about the land use patterns and anthropogenic impacts around the Hacılar Büyük Höyük during EBA-I. This thesis study illustrates that integrating the existing archaeological and anthropological data with the numerical models can benefit the interpretation of social structure at the settlement.
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ÖgeInvestigating the genomic differentiation landscape of the large mouse-eared bats(Graduate School, 2024-05-23)Interspecific gene flow, through shaping the evolution of species over time, plays a pivotal role in evolutionary biology. Often complex and multifaceted, this process presents a rich area to explore the intricate dynamics that drive the evolution of species. The large mouse-eared bats, specifically Myotis myotis and M. blythii, present a particularly intriguing species complex for studying interspecific gene flow. Myotis myotis and M. blythii have substantially overlapping ranges across Europe and Anatolia. These species also exhibit evidence of gene flow, identified in the previous studies. Their shared mitochondrial lineage suggests past hybridization events. Additionally, nuclear marker based analyses identified evidence of recent gene flow events. Despite their sympatric distribution coupled with past and present hybridization events, the mechanism underlying the maintenance of separate gene pools remains an intriguing question. This study aims to contribute in the understanding of the evolutionary history of the large Myotis bats through a whole-genome approach. In this regard, genomic differentiation landscapes were considered within and between Large Myotis bats. For the genomic analysis, whole-genome shotgun sequencing data was generated from a total of thirty-four samples, representing M. myotis, M. blythii, and their closely related species, M. punicus. To assess the population structures and differentiation levels, Principal Component and Admixture analyses were conducted. Both analyses identified three distinct clusters in accordance with the three large Myotis taxa. Within M. blythii, a further split separating the individuals from Kyrgyzstan and Mongolia from the rest was present. Genomic landscapes of differentiation were explored through Manhattan plots of fixation index, nucleotide diversity and genomic divergence. The genomic differentiation assessments supported the nuclear divergence of M. myotis and M. blythii. Within M. blythii, East and West populations exhibited a significant divergence, although not to a level comparable to the divergence seen between two different species. Potentially introgressed genomic regions were investigated. Although a slightly increased gene flow signal was observed across the entire genome between M. myotis and Eastern M. blythii, localized introgression regions that would indicate recent hybridization could not be detected. Further exploration of introgressed genomic regions may reveal the genomic basis for species differentiation. This study contributes to future studies on large Myotis bats and other cryptic species complexes, while also demonstrating the power of whole-genome data in unraveling the complex processes that shape the evolution of species.