The evolutionary history of Ginkgo is poorly understood for the Cenozoic Era because of the rarity of fossil reproductive organs. We here describe a new species, Ginkgo cranei sp. nov., on the basis of well-preserved ovulate organs and associated leaves from the Upper Paleocene Sentinel Butte Formation of North Dakota, USA. The ovulate organ is of the modern type, which lacks a pedicel supporting each of the two ovules. The ovules are seated in separate collars directly attached to the peduncle, but only one of them is mature. Stomatal complexes are mostly amphicyclic, with deeply sunken guard cells and slightly raised subsidiary cells. They are sparsely distributed among epidermal cells characterized by domelike, strongly bulging periclinal walls and developed anticlinal wall flanges in integument and collar cuticles. The associated leaves are generally similar to the ovulate organ in cuticular structure. Ginkgo cranei is the only Tertiary species of the genus described in which the ovulate organs are studied in some detail. The study further corroborates the hypothesis that modern Ginkgo evolved from its ancestors by reduction and is helpful to classify Cenozoic ginkgos in a natural system.

In the past 40 years, floods have become a bane of Mozambique’s inhabitants and economy. The latest of them, caused by the cyclone Idai, has devastated the area resulting in loss of life and property. It was estimated that around 715 000 hectares of farmland was destroyed as a result of the cyclone. The main goal of this thesis was to assess the extent of the flooding and to determine the types of land cover that were affected. This was done in Google Earth Engine, using SAR change detection on Sentinel 1 data to create a mask for the flooded areas, followed by a supervised image classification on Sentinel 2 data to identify the types of land cover that were flooded. Two classifications were done, using imagery from early periods of the country’s plant growing season and later periods of the same season, respectively. The results of both classifications were below standard, with the main problems stemming from difficulties with differentiating between agriculture and roads along with agriculture and vegetation. Multiple ways to improve the results and avoid the errors in future similar projects were discussed, including using multi temporal data and utilizing a road map for the area to create a large amount of training points for the classification. In conclusion, while the results were not as good as was envisioned, the thesis provided ample opportunity to analyze errors and to theorize methods for improving future work.

Snow represents an important resource in mountainous regions. Monitoring its extent and amount is relevant for several applications, such as hydrology, ecology, avalanche monitoring, or hydropower production. However, a correct understanding of the high spatial and temporal variability of snow accumulation, redistribution and ablation processes requires its monitoring in a spatialized and detailed way. Recently, the launch of the Sentinel missions has opened the doors to new approaches that mainly exploit high resolution (HR) data having a spatial detail of few dozens of m. In this thesis, we aimed at exploiting these new sources of information to retrieve important parameters related to the snowmelt processes. In detail, we i) investigated the use of Sentinel-1 Synthetic Aperture Radar (SAR) observations to evaluate snowmelt dynamics in alpine regions, ii) developed a novel approach based on a hierarchical multi-resolution analysis of optical time-series to reconstruct the daily HR snow cover area (SCA), and iii) explored the combination of HR SCA time-series, SAR snowmelt information and other multi-source data to reconstruct a daily HR snow water equivalent (SWE) time-series. In detail, in the first work we analyzed the relationship between the snowmelt phases of a snowpack and the multi-temporal SAR backscattering. We found that the SAR is able to provide useful information about the moistening, ripening and runoff phases. In the second work, we exploited the snow pattern repetition on an inter-annual basis driven by the geomorphological features of a study area to carry out historical analyses. Thus, we took advantage of these repeated patterns to fuse low resolution and HR satellite optical data and set up a gap filling to derive daily HR snow cover area (SCA) time-series. These two research works are the pillars for the last contribution, which aims at combining all these information sources together with both in-situ data and a simple yet robust degree day model that provides an estimate of the potential melting to derive daily HR SWE time-series. These final results have an unprecedented spatial detail, that allows to sample the phenomena linked to the complex snow accumulation, redistribution and ablation processes with the required spatial and temporal resolution. The methodology and the results of each experimental work are illustrated and discussed in detail in the chapters of this thesis, with a look on further research and potential applications.

Permafrost deformation is expected to increase due to climatic perturbations such as amplified air and soil temperatures, resulting in permafrost thawing and subsequent subsidence. Palsas and peat plateaus are uplifted ice-rich peat mounds that experience permafrost subsidence. This is due to the uppermost layer of permafrost, known as the Active Layer (AL), that seasonally thaws and freezes. Interferometric Synthetic Aperture Radar (InSAR) is an interferometric stacking technique successfully applied over permafrost regions when monitoring ground subsidence. The Small Baseline Subset (SBAS) technique is based on interferograms produced by stacking Synthetic Aperture Radar (SAR) acquisitions with small normal baselines. In this study, seasonal Sentinel-1 SAR C-band data obtained during June, July, August and September (JJAS) was used to generate seasonal Line of Sight (LoS) deformation time series of palsas and peat plateaus in Tavvavuoma (Sweden) by using the SBAS technique. Chersky (Russia) has documented permafrost subsidence and was used as a reference site. Findings include that seasonal stacks with short normal baselines generated more robust results than inter-annual stacks with longer normal baselines and temporal data gaps. No instances of pronounced subsidence were reported during JJAS. Nevertheless, minor subsidence during the early season and negative development trends were identified in the Tavvavuoma 2020 andChersky 2020-2021 stacks, respectively. Increased subsidence during the mid-and late thaw season was detected. The SBAS technique performed better and resulted in less temporal and seasonal decorrelation in areas above the tree line (Tavvavuoma) compared to the lowlands in the forest-tundra (Chersky). The challenge lies in whether surface subsidence of palsas and peat plateaus in sporadic permafrost regions experience irreversible long-term changes or seasonally cyclic changes in the permafrost ground regime. Future studies are recommended to implement annual intervals, including winter images over Tavvavuoma.

Inland water has for a long time showed vast stress due to eutrophication, mainly caused by increased levels of phosphorus. Applying remote sensing as a tool for monitoring water parameters has long been used. In the past, inland watercourses measurements have proven to be challenging, often due to the limitations of satellite missions' spectral resolution or difficulties in implementing the appropriate methodology. This project investigates the potential to use a high-resolution satellite mission, Sentinel 2, to monitor phosphorus with the proxies total suspended matter (TSM) and turbidity in two smaller watercourses, Fyrisån and Sävjaån, in Uppsala, Sweden. From April to November, a period spanning three years (2018, 2019, and 2021), empirical modeling was employed to conduct investigations. The three years all represent different weather patterns and discharge velocities. The bands 2 to 8 were investigated individually and together to see if there was a potential using a single band correlation or multiple to correlate with turbidity or TSM. The two optically active water parameters are known to have a high correlation with the non-optically active phosphorus. There was no correlation found between the proxies and each band individually for any of the years investigated. Using a multi regression analysis both 2018 and 2019 showed high correlation for TSM, and 2019 for turbidity. While the results for 2021 were not significant for any of the proxies. The conclusion indicates that with right surrounding factors it’s possible to use TSM and turbidity as a proxy for phosphorus when using Sentinel 2 in these smaller watercourses. Nevertheless, further studies are needed to investigate how the proxy and the nutrient acts together with satellite data for peaks etc. before using Sentinel 2 results as a direct interpretation.

The launch of Sentinel-1A/B satellites in 2014 and 2016 marked a pivotal moment in Synthetic Aperture Radar (SAR) technology, ushering in a golden era for SAR. With a revisit time of 6–12 days, these satellites facilitated the acquisition of extensive stacks of high-resolution SAR images, enabling advanced time series analysis. However, processing these stacks posed challenges like interferometric phase degradation and tropospheric phase delay. This study introduces an advanced Small Baseline Subset (SBAS) algorithm that optimizes interferometric pairs, addressing systematic errors through dyadic downsampling and Delaunay Triangulation. A novel statistical framework is developed for elite pixel selection, considering distributed and permanent scatterers, and a tropospheric error correction method using smooth 2D splines effectively identifies and removes error components with fractal-like structures. Beyond geodetic technique advancements, the research explores geological phenomena, detecting five significant slow slip events (SSEs) along the Southern San Andreas Fault using multitemporal SAR interferometric time series from 2015-2021. These SSEs govern aseismic slip dynamics, manifesting as avalanche-like creep rate variations. The study further investigates Managed Aquifer Recharge (MAR) as a nature-engineering-based solution in the Santa Ana Basin. Analyzing surface deformation from 2004 to 2022 demonstrates MAR's effectiveness in curbing land subsidence within Orange County, CA. Additionally, MAR has the potential to stabilize nearby faults by inducing a negative Coulomb stress change. Projecting into the future, a suggested 2% annual increase in recharge volume through 2050 could mitigate land subsidence and reduce seismic hazards in coastal cities vulnerable to relative sea level rise. This integrated approach offers a comprehensive understanding of geological processes and proposes solutions to associated risks. / Doctor of Philosophy / The launch of Sentinel-1A/B satellites in 2014 and 2016 marked a big step forward in radar technology, especially Synthetic Aperture Radar (SAR). These satellites, which revisit the same area every 6-12 days, allowed us to collect many high-quality radar images. This helped us study changes over time in a more advanced way. However, there were challenges in handling all these images, like errors in the radar signals and delays caused by the Earth's atmosphere. We devised a smart algorithm based on the Small Baseline Subset (SBAS) to tackle these challenges. It helps optimize how we use pairs of radar images, reducing errors. We also developed a new method to pick the best pixels in the images and corrected errors caused by the atmosphere using mathematical methods. Moving beyond just technology, our research also looked at interesting Earth events. We found five major slow slip events along the Southern San Andreas Fault by studying radar data from 2015 to 2021. These events are like slow-motion slips along the fault, influencing how the ground moves. We also explored Managed Aquifer Recharge (MAR) as a solution in the Santa Ana Basin. By studying ground movement from 2004 to 2022, we found that MAR helped prevent the land from sinking in Orange County, California. It even has the potential to make nearby faults more stable. Looking ahead, increasing MAR activities by 2% each year until 2050 could protect against land sinking and reduce earthquake risks in coastal cities facing rising sea levels. This combined approach gives us a better understanding of Earth's processes and suggests ways to tackle related problems.

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Not many studies are currently devoted to the estimation of soil moisture from space-borne SAR data at the field scale. Superficial soil moisture is indeed generally estimated from SAR images at lower resolutions, rarely reaching the sub-kilometric scale. This is mainly due to the lack of in situ data, such as measured soil moisture and parameters indicative of the soil roughness and vegetation conditions. Moreover, when working at the kilometric scale, some hypothesis assumed while modelling the backscattered SAR signal over a vegetated area are more likely satisfied, whereas when working at higher resolutions such as the field scale, other interactions should be taken into account. Indeed, over a vegetated area the total backscattered SAR signal is usually modelled as the incoherent sum of the vegetation and the soil components, and only in the last years has been added a further contribution provoked from the presence of subsurface scatterers. In the present thesis, the just mentioned contributions are considered and modelled at the field scale for soil moisture estimation purposes. A long term Change Detection method is applied to copolarized Sentinel-1 data, with a focus on taking into account the component of the total backscattering coefficient due to the presence of subsurface scatterers, recently proposed in literature. By exploiting the strong relationships detected over the study area between the copolarized signal and the observed soil moisture, the inversion algorithm for soil moisture retrieval is adapted for considering the cases of dominant subsurface scattering mechanism. Moreover, the proper time scale of detection of subsurface scattering is identified at the field scale, providing helpful information for correcting retrieval algorithms based on SAR data also at lower spatial scales.

1.) Sentinel traps were used to survey for parasitoids of frugivorous drosophilids in Virginia fruit cropping systems, and determine if parasitoids were attacking invasive flies Drosophila suzukii (Matsumura) and Zaprionus indianus Gupta (Diptera: Drosophilidae) in the field. Two parasitoids of frugivorous drosophilids, Leptopilina boulardi (Barbotin, Carton, and Kelner-Pillault) (Hymenoptera: Figitidae) and Pachycrepoideus vindemiae (Rondani) (Hymenoptera: Pteromalidae), were reared, but only one P. vindemiae was reared from D. suzukii, and no parasitoids were reared from Z. indianus. Most parasitoids were reared from alternate host Drosophila melanogaster Meigen and other wild drosophilids. 2.) The ability of these parasitoids to attack D. melanogaster, D. suzukii and Z. indianus under controlled conditions was tested. Larval parasitoid L. boulardi did not develop on D. suzukii or Z. indianus, just D. melanogaster. Pupal parasitoid P. vindemiae successfully developed on all three fly species, but also increased pupal fly mortality. 3.) Olfactometry was used to ascertain if L. boulardi and P. vindemiae are selective about the type of fruit their hosts feed in. Results showed that among cherry, raspberry, blueberry, grape, and banana, L. boulardi preferred raspberry and banana to cherry, and preferred grape least, but no fruit was most preferred. Insufficient data were obtained for P. vindemiae. We conclude that parasitoids of Virginia are unlikely to provide effective biological control for D. suzukii or Z. indianus, and classical biological control should be investigated as a pest management option. Olfactometry results indicate tritrophic selectivity by Drosophila parasitoids, suggesting multiple parasitoids could be required for effective biological control. / Master of Science in Life Sciences / The spotted wing drosophila (henceforth SWD) is a globally invasive vinegar fly originating from southeast Asia, and is economically damaging to producers of small fruit, such as berries, cherries, and grapes. The African fig fly (henceforth AFF), a relative of SWD, is another recently invasive species to North America (originating from Africa) that often occurs simultaneously with SWD infestations, but its economic threat to North America is still unclear. With the economic threat posed by SWD, and potential threat posed by AFF, it is important to understand their relationships with other organisms in their environment, especially natural enemies, such as parasitoid wasps. Such information is integral for researchers to develop effective control methods, and will help determine if natural enemies can be used to our advantage as biological control agents. Biological control also helps to limit the use of chemical insecticides, mitigating the development of insecticide resistance in the pests. This project employed unique field trapping methods and laboratory bioassays to investigate the relationships of SWD and AFF with parasitoid wasps in affected fruit cropping systems in southwestern Virginia. We discovered that parasitoids of vinegar flies are present in Virginia fruit cropping systems, but they do not help to control populations of SWD and AFF. The parasitoids that are present prefer to attack other fly species, are unable to attack SWD and AFF, or do not attack in high enough numbers to have an impact on SWD or AFF populations. Biological control success is more likely to come from parasitoid species that have co-evolved with SWD and AFF in their native ranges.

1 ABSTRACT Background Breast cancer cell population characteristics are used in common clinical practice for estimation of prognosis of the malignant disease (prognostic factors) and for prediction of reactivity of the tumor to certain therapeutic modality (predictive factors). Also axillary lymph node status is an independent prognostic factor in women with early breast cancer. Therefore, surgical excision and following histopathological examination of the nodes is the obligatory part of primary breast cancer surgery. The extension of axillary surgery varies widely, although sentinel lymph node biopsy is considered to be the standard procedure. However, it must be admitted that this type of procedure need not be optimal for all the breast cancer patients. Aims of the study The aim of this study is the verify the hypothesis whether or not the axillary lymph node metastatic affection can be effectively estimated using non-surgical methods - i.e. by evaluation of the combination of prognostic and predictive factors of the primary breast tumor. Statistical model composed on the basis of data of early breast cancer patients is the basic tool for this prediction. Application of this model In everyday practice can enable to adjust the extent of axillary surgery for each individual patient. Patients and methods A...