Academic literature on the topic '049999 Earth Sciences not elsewhere classified'

This article presents AgriExp, a remote-based workflow for the rapid mapping and monitoring of archaeological and cultural heritage locations endangered by new agricultural expansion and encroachment. Our approach is powered by the cloud-computing data cataloguing and processing capabilities of Google Earth Engine and it uses all the available scenes from the Sentinel-2 image collection to map index-based multi-aggregate yearly vegetation changes. A user-defined index threshold maps the first per-pixel occurrence of an abrupt vegetation change and returns an updated and classified multi-temporal image aggregate in almost-real-time. The algorithm requires an input vector table such as data gazetteers or heritage inventories, and it performs buffer zonal statistics for each site to return a series of spatial indicators of potential site disturbance. It also returns time series charts for the evaluation and validation of the local to regional vegetation trends and the seasonal phenology. Additionally, we used multi-temporal MODIS, Sentinel-2 and high-resolution Planet imagery for further photo-interpretation of critically endangered sites. AgriExp was first tested in the arid region of the Cholistan Desert in eastern Pakistan. Here, hundreds of archaeological mound surfaces are threatened by the accelerated transformation of barren lands into new irrigated agricultural lands. We have provided the algorithm code with the article to ensure that AgriExp can be exported and implemented with little computational cost by academics and heritage practitioners alike to monitor critically endangered archaeological and cultural landscapes elsewhere.

AbstractField investigations at Dugway Proving Ground in western Utah have produced new data on the chronology and human occupation of late Pleistocene and early Holocene lakes, rivers, and wetlands in the Lake Bonneville basin. We have classified paleo-river channels of these ages as “gravel channels” and “sand channels.” Gravel channels are straight to curved, digitate, and have abrupt bulbous ends. They are composed of fine gravel and coarse sand, and are topographically inverted (i.e., they stand higher than the surrounding mudflats). Sand channels are younger and sand filled, with well-developed meander-scroll morphology that is truncated by deflated mudflat surfaces. Gravel channels were formed by a river that originated as overflow from the Sevier basin along the Old River Bed during the late regressive phases of Lake Bonneville (after 12,500 and prior to 11,000 14C yr B.P.). Dated samples from sand channels and associated fluvial overbank and wetland deposits range in age from 11,000 to 8800 14C yr B.P., and are probably related to continued Sevier-basin overflow and to groundwater discharge. Paleoarchaic foragers occupied numerous sites on gravel-channel landforms and adjacent to sand channels in the extensive early Holocene wetland habitats. Reworking of tools and limited toolstone diversity is consistent with theoretical models suggesting Paleoarchaic foragers in the Old River Bed delta were less mobile than elsewhere in the Great Basin.

Winter wheat is one of the major cereal crops in China. The spatial distribution of winter wheat planting areas is closely related to food security; however, mapping winter wheat with time-series finer spatial resolution satellite images across large areas is challenging. This paper explores the potential of combining temporally aggregated Landsat-8 OLI and Sentinel-2 MSI data available via the Google Earth Engine (GEE) platform for mapping winter wheat in Shandong Province, China. First, six phenological median composites of Landsat-8 OLI and Sentinel-2 MSI reflectance measures were generated by a temporal aggregation technique according to the winter wheat phenological calendar, which covered seedling, tillering, over-wintering, reviving, jointing-heading and maturing phases, respectively. Then, Random Forest (RF) classifier was used to classify multi-temporal composites but also mono-temporal winter wheat development phases and mono-sensor data. The results showed that winter wheat could be classified with an overall accuracy of 93.4% and F1 measure (the harmonic mean of producer’s and user’s accuracy) of 0.97 with temporally aggregated Landsat-8 and Sentinel-2 data were combined. As our results also revealed, it was always good to classify multi-temporal images compared to mono-temporal imagery (the overall accuracy dropped from 93.4% to as low as 76.4%). It was also good to classify Landsat-8 OLI and Sentinel-2 MSI imagery combined instead of classifying them individually. The analysis showed among the mono-temporal winter wheat development phases that the maturing phase’s and reviving phase’s data were more important than the data for other mono-temporal winter wheat development phases. In sum, this study confirmed the importance of using temporally aggregated Landsat-8 OLI and Sentinel-2 MSI data combined and identified key winter wheat development phases for accurate winter wheat classification. These results can be useful to benefit on freely available optical satellite data (Landsat-8 OLI and Sentinel-2 MSI) and prioritize key winter wheat development phases for accurate mapping winter wheat planting areas across China and elsewhere.

Signet-ring cell carcinoma of the prostate gland (SRCCP) an uncommon and aggressive malignant tumour of the prostate gland which is characterized by histopathology examination features of compression of the nucleus into the form of a crescent by a large cytoplasmic vacuole. SRCCPs that have so far been reported have been either (a) primary tumours, metastatic tumours with the primary tumour elsewhere with the gastro-intestinal tract being the site of the primary tumour but the primary tumour could originate elsewhere, and additionally some reported SRCCPs have been classified as carcinoma of unknown primary. SRCCP could be a pure tumour or a tumour that is contemporaneously associated with other types of tumour including various variants of adenocarcinoma. SRCCP can manifest in various ways including: Incidental finding following prostatectomy that has been undertaken for a presumed benign prostatic hyperplasia, lower urinary tract symptoms, visible and non-visible haematuria, raised levels of serum PSA but some SRCCPs have been diagnosed with normal / low levels of serum PSA, there may be a history of dyspepsia in cases of metastatic signet-ring cell carcinoma in association with contemporaneous primary signet-ring cell carcinoma of the stomach or there may be a past history of surgical treatment for signet-ring cell carcinoma of the gastrointestinal tract, or bleeding from the gastrointestinal tract in cases of upper gastrointestinal tract and rectal bleeding as well as change in bowel habit for primary tumours of the anorectal region, retention of urine, and rarely a rectal mass in the case of SRCCP with an anorectal primary tumour. In order to exclude a primary signet ring cell carcinoma elsewhere, a detailed past medical history is required as well as radiology imaging including contrast – enhanced computed tomography (CECT) scan and contrast-enhanced magnetic resonance imaging (CEMRI) scan as well as upper gastrointestinal endoscopy and colonoscopy to exclude a primary lesion within the gastrointestinal tract. Diagnosis of SRCCP requires utilization of the histopathology and immunohistochemistry examination features of prostate biopsy, prostatic chips obtained from trans-urethral resection of prostate specimen or radical prostatectomy specimen. SRCCPs upon immunohistochemistry staining studies tend to show tumour that tend to exhibit positive staining for the following tumour markers as follows: PSA – positive staining for PSA has been variable in some studies, AE1/AE3, CAM 5.2, Ki-67 with a mean of 8%, PAS-diastase, Mucicarmine (50%), Alcian blue (60%), Alpha-methyl-acyl coenzyme A racemase (P504S), and Cytokeratin 5/6. SRCCPs also tend to exhibit negative staining for: Bcl2 (rare positive), and CEA (80%). Traditionally the treatment of Primary Signet-Ring Cell Carcinoma of the Prostate Gland has tended to be similar to the treatment of the traditional adenocarcinoma of the prostate gland which does include: hormonal treatment, radiotherapy, and surgery. Nevertheless, considering that primary SRCCPs and metastatic SRCCPs that have been reported in the literature have generally tended to be associated with an aggressive biological behaviour, even though there is no consensus opinion on the treatment of the disease it would be strongly recommended that these tumours that tend to be associated with rapid progress of the disease and poor survival there is an urgent need to treat all these tumours with aggressive surgery including radical prostatectomy plus adjuvant therapies including: radical radiotherapy, combination chemotherapy, selective prostatic angiography and super-selective embolization of the artery feeding the tumour including intra-arterial infusion of chemotherapy agents directly to the tumour, radiofrequency ablation of the tumour as well as irreversible electroporation of the tumour which should form part of a global multicentre study of various treatment options. With regard to metastatic signet-ring cell carcinomas of the prostate gland with a contemporaneous primary tumour elsewhere the primary tumour should also be treated by radical and complete excision of the primary tumour plus radical surgery and aggressive adjuvant therapy. Considering that SRCCPs have tendered not to respond well to available chemotherapy agents, there is need for urologists, oncologists, and pharmacotherapy research workers to identify new chemotherapy medicaments that would more effectively and safely destroy signet-ring cell tumours in order to improve upon the prognosis.

Two lander-based devices, the Bubble-Box and GasQuant-II, were used to investigate the spatial and temporal variability and total gas flow rates of a seep area offshore Oregon, United States. The Bubble-Box is a stereo camera–equipped lander that records bubbles inside a rising corridor with 80 Hz, allowing for automated image analyses of bubble size distributions and rising speeds. GasQuant is a hydroacoustic lander using a horizontally oriented multibeam swath to record the backscatter intensity of bubble streams passing the swath plain. The experimental set up at the Astoria Canyon site at a water depth of about 500 m aimed at calibrating the hydroacoustic GasQuant data with the visual Bubble-Box data for a spatial and temporal flow rate quantification of the site. For about 90 h in total, both systems were deployed simultaneously and pressure and temperature data were recorded using a CTD as well. Detailed image analyses show a Gaussian-like bubble size distribution of bubbles with a radius of 0.6–6 mm (mean 2.5 mm, std. dev. 0.25 mm); this is very similar to other measurements reported in the literature. Rising speeds ranged from 15 to 37 cm/s between 1- and 5-mm bubble sizes and are thus, in parts, slightly faster than reported elsewhere. Bubble sizes and calculated flow rates are rather constant over time at the two monitored bubble streams. Flow rates of these individual bubble streams are in the range of 544–1,278 mm3/s. One Bubble-Box data set was used to calibrate the acoustic backscatter response of the GasQuant data, enabling us to calculate a flow rate of the ensonified seep area (∼1,700 m2) that ranged from 4.98 to 8.33 L/min (5.38 × 106 to 9.01 × 106 CH4 mol/year). Such flow rates are common for seep areas of similar size, and as such, this location is classified as a normally active seep area. For deriving these acoustically based flow rates, the detailed data pre-processing considered echogram gridding methods of the swath data and bubble responses at the respective water depth. The described method uses the inverse gas flow quantification approach and gives an in-depth example of the benefits of using acoustic and optical methods in tandem.

The potential of hyperspectral proximal sensing to quantify sward characteristics important in making critical decisions on the management of sheep and dairy pastures in New Zealand has been investigated. Hyperspectral data were acquired using an ASD FieldSpec® Pro FR spectroradiometer attached to the Canopy Pasture Probe (CAPP). The CAPP was developed to enable the collection of in situ reflectance data from New Zealand pasture canopies independent of ambient light conditions. A matt white ceramic tile was selected as a reflectance standard to be used with the CAPP, after testing a variety of materials. Pasture reflectance factor spectra between 350-2500 nm (with spectral resolutions of 3 nm between 350-1000 nm and 10 nm between 1000-2500 nm) and pasture samples were collected from six hill country and lowland areas, across all seasons (August 2006 to September 2007) in a number of regions in the North Island of New Zealand. After pre-processing (e.g. spectral averaging, de-stepping, elimination of noisy wavelengths, smoothing) the spectral data collected from sites were correlated against pasture botanical composition (expressed as proportions of grass, legume and weed) and pasture nutrients (nitrogen, phosphorus, potassium, calcium, magnesium, sodium and sulphur) expressed in percentage of dry matter (%) and amount (kg ha-1) using partial least squares regressions (PLSR). The accuracy and precision of the calibrations were tested using either the full cross-validation leave-one-out method or testing datasets. Regressions were carried out using the reflectance factor data per se and after mathematical transformation, including first derivative, absorbance and continuum-removed spectra. Overall best results were obtained using the first derivative data. The quality of predictions varied greatly with the pasture attribute, site and season. Some reasonable results were achieved for the prediction of pasture grass and legume proportions when analysing samples collected during autumn (grass: R2 > 0.81 and SD/RMSEP 2.3 and legume: R2 > 0.80 and SD/RMSEP 2.2), but predicting pasture weed content was poor for all sites and seasons (R2 = 0.44 and SD/RMSEP = 1.2). The inaccurate predictions might be explained by the fact that the diversity found in the field and observed in the pasture spectral data was not taken into account in the pasture botanical separation. The potential for using proximal sensing techniques to predict pasture nutrients in situ was confirmed, with the sensing of pasture N, P and K increased by the procedure of separating the data according to the season of the year. The full potential of the technology will only be realised if a substantial dataset representing all the variability found in the field is gathered. The importance of obtaining representative datasets that embrace all the biophysical factors (e.g. pasture type, canopy structure) likely to affect the relat ionship, when building prediction calibrations, was highlighted in this research by the variance in the predictions for the same nutrient using different datasets, and by the inconsistency in the number of common wavelengths when examining the wavelengths contributing to the relationship. The ability to use a single model to predict multiple nutrients, or indeed individual nutrients, will only come through a good understanding of the factors likely to influence any calibration function. It has been demonstrated in this research that reasonably accurate and precise pasture nutrient predictions (R2 > 0.74 and SD/RMSEP 2.0) can be made from fresh in situ canopy measurements. This still falls short of the quality of the predictions reported for near infrared reflectance spectroscopy (NIRS) for dried, ground samples analysed under controlled laboratory conditions

The land ecosystems in northern high latitudes (>45° N) occupy 22% of the global surface and store more than 1600 Pg soil organic carbon. Warming in this region has been documented during the past decades. Warming-induced changes in regional carbon dynamics are expected to loom large in the global carbon cycle and exert large feedbacks to the global climate system. Numerous Earth System Models have been widely used to quantify the response of terrestrial ecosystem carbon dynamics to climatic changes. However, predictions of terrestrial ecosystem carbon responses to increasing levels of atmospheric carbon dioxide (CO2) and climate change is still uncertain due to model limitations. The limitations include relatively low levels of representation of ecosystem processes that determine the exchanges of water, energy, and carbon between land ecosystems and the atmosphere and omitting some key biogeochemical mechanisms. To improve model realism and provide a better projection of the Arctic carbon dynamics, this dissertation developed three new versions of a process-based biogeochemistry models that involve more fundamental processes of terrestrial ecosystems. First, microbial dynamics and enzyme kinetics that catalyze soil carbon decomposition have been incorporated into the extant terrestrial ecosystem model TEM to remedy the inadequate representation of soil decomposition process. Furthermore, a vital microbial life-history trait, microbial dormancy, has been implemented into previous microbial-based model to consider the impacts of microbial dormancy in modeling. Additionally, the role of moss in the Arctic terrestrial ecosystem carbon quantification was also demonstrated by incorporating moss and higher plant interactions in modelling.

All of the work described in this dissertation involves the use of Indigenous research frameworks to design research projects, to facilitate communication with Indigenous communities that I have collaborated with, and also to teach and mentor undergraduate and graduate students. Indigenous research frameworks emphasize the importance of place in relation to the integrity of cultural values espoused by many Indigenous communities. This entails a respect for the spirituality component of Indigenous people because this is often directly tied to relationships between the land, animals, and plants of their local environments.

While some research has been conducted to help understand Indigenous people’s understandings of geoscience, less emphasis has been placed on recognizing and leveraging common connections Indigenous students make between their Traditional cultures and Western science. Thus, the research presented in this dissertation identifies connections Indigenous learners make between geology concepts and their everyday lives and cultural traditions in both formal and informal settings. Some of these connections have been integrated into place-based geoscience education modules that were implemented within an introductory environmental science course.

Qualitative analysis, using a socioTransformative constructivism theoretical lens, of semi-structured interviews after implementation of a Sharing/Learning program for an Acoma pilot project, implemented informally, and for a series of geoscience education modules at a private university provides evidence that elements reflective of the use of sociotransformative constructivism (e.g. connections between global and localized environmental issues) were acknowledged by the participants as particularly impactful to their experience during implementation of the geoscience-focused activities. In addition to the socioTransformative theoretical perspective, Indigenous research frameworks (i.e. Tribal Critical Race Theory) were used to contextualize the educational interventions for two different Indigenous communities, Acoma Pueblo and the Confederated Tribes and Bands of the Yakama Nation. Tribal Critical Race Theory was not used to analyze the semi-structured interviews. Instead the Indigenous research frameworks were used to ensure that the research practices undertaken within these Indigenous communities were respectful of the Indigenous community’s cultural values, that Indigenous data sovereignty was paramount, and so that the research objectives were transparent. In addition, permission to publish the results of this research was sought from the governing entities of both Tribal Councils of Acoma Pueblo and the Yakama Nation.

The research presented in this dissertation provides evidence that academic research can be undertaken in respectful ways that benefit Indigenous communities. The connections that participants in the Acoma Sharing/Learning program could potentially be used to create more culturally relevant educational materials for the Acoma Pueblo community, if that is what the governing entities of the Acoma Pueblo community desire. The modules implemented more formally at a private university could potentially, with permission from the governing entities of the Yakama Nation, be integrated into geoscience programs at a broader level creating opportunities for contemporary Indigenous perspectives to be valued alongside Western modern science. Moving forward, this could potentially increase interest among Indigenous community members in pursuing academic pathways within geoscience disciplines.

The research pursued in this dissertation is only a beginning. Approaches to research that promote the agency of local communities in the types of research questions asked and how that research is conducted should be a priority for Western scientists to maintain a respectful relationship with the many communities, Indigenous and non-Indigenous, in which they work. It is my intention to be part of this revolution in how academic researchers interact with contemporary Indigenous communities as well as the next generation of scientists. In the future, my research will continue to serve and benefit Indigenous communities, but I will also begin asking research questions that will help increase the use of diverse and equitable practices within academia. In this way, I hope to bridge the two worlds of Indigenous Knowledge systems and Western science with the primary purpose of maintaining respect among these two communities. In the future, my research will focus on how these respectful practices can move beyond academic research and pedagogy into the realms of professional development, mentoring, and community revitalization.

Tropical ecosystems play a key role in regulating the global climate and the carbon cycle thanks to the large amounts of water and carbon exchanged with the atmosphere. These biogeochemical fluxes are largely the result of high photosynthetic rates. Photosynthetic activity is highly dependent on climate and vegetation, and therefore can be easily modified along with changes in those two factors. A better understanding of what drives or alters photosynthetic activity in the tropics will lead to more accurate predictions of climate and subsequent effects on ecosystems. The seasonal pattern of photosynthetic activity is one of the main uncertainties that we still have about tropical ecosystems. However, this seasonality of tropical vegetation and its relationship to climate change and land cover is key to understanding how these ecosystems could be affected and have an effect on climate.

In this dissertation, I present three projects to improve our understanding about tropical ecosystems and how their photosynthetic activity is affected by climate and land cover change. The lack of field-based data has been one of the main limiting factors in our study of tropical ecosystems. Therefore, in these projects I extensively use remote sensing-derived data to analyze large scale and long term patterns. In the first study, I looked at the seasonal relationship between photosynthetic activity and climate, and how model simulations represent it. Vegetation in most of the tropics is either positively correlated with both water and light, or positively correlated with one of them and negatively with the other. Ecosystem models largely underestimate positive correlations with light and overestimate positive correlations with water. In the second study, I focus on the effect of land cover change in photosynthetic activity and transpiration in a highly deforested region in the Amazon. I find that land cover change decreases tropical forests photosynthetic activity and transpiration during the dry season. Also, land cover change increases the range of photosynthetic activity and transpiration in forests and shrublands. These effects are intensified with increasing land cover change. In the last project, I quantify the amount of change in evapotranspiration due to land cover change in the entire Amazon basin. Our remote sensing-derived estimates are well aligned with model predictions published in the past three decades. These results increase our confidence in climate models representation of evapotranspiration in the Amazon.

Findings from this dissertation highlight (1) the importance of the close relationship between climate and photosynthetic activity and (2) how land cover change is altering that relationship. We hope our results can build on our knowledge about tropical ecosystems and how they could change in the future. We also expect our analysis to be used for model benchmarking and tropical ecosystem monitoring.

The Geologic TimeScale Creator (TSCreator) project has compiled a range of paleo-environmental and bio-diversity data which provides the opportunity to explore origination, speciation and extinction events. My PhD research has four major interconnected themes which include the visualization methods of evolutionary tree and the impacts of climate change on the evolution of life in longer and shorter timeframes: (1) Evolutionary range data of planktonic foraminifera and nannofossils over the Cenozoic era have been updated with our latest geological timescale. These evolutionary ranges can be visualized in the form of interactive, extensible evolutionary trees and can be compared with other geologic data columns. (2) A novel approach of integrating morphospecies and lineage trees is proposed to expand the scope of exploration of the evolutionary history of microfossils. It is now possible to visualize morphological changes and ancestor-descendant lineage relationships on TSCreator charts which helps mutual learning of these species based on genetic and bio-stratigraphic studies. (3) These evolutionary datasets have been used to analyze semi-periodic cycles in the past bio-diversity and characteristic rates of turnover. Well-known Milankovitch cycles have been found as the drivers of fluctuations in the speciation and extinction processes. (4) Within a shorter 2000-year time period, global cooling events might have been a factor of human civilization turnover. Using our regional and global cultural turnover time series data, the effect of climate change on human culture has been proposed. The enhancement of the evolutionary visualization system accomplished by this research will hopefully allow academic and non-academic users across the world to research and easily explore Earth history data through publicly available TSCreator program and websites.

Shape and attitude of near-Earth objects directly affect the orbit propagation via drag and solar radiation pressure. Obtaining information beyond the object states (position and velocity) is integral to identifying an object. It also enables tracing origin and can improve the orbit accuracy. For objects that have a significant distance to the observer, only non-resolved imaging is available, which does not show any details of the object. So-called non-resolved light curve measurements, i.e. photometric measurements over time can be used to determined the shape of space objects using a two step inversion scheme. It follows the procedure to first determine the Extended Gaussian Image and then going through the shape reconstruction process to retrieve the closed shape even while measurement noise is present. Furthermore, it is also possible to generate high confidence candidates when follow-up observations are provided through a multi-hypotheses process.

Methane (CH₄) is the second most powerful greenhouse gas (GHG) behind carbon dioxide (CO₂), and is able to trap a large amount of long-wave radiation, leading to surface warming. Carbon monoxide (CO) plays an important role in controlling the oxidizing capacity of the atmosphere by reacting with OH radicals that affect atmospheric CH₄ dynamics. Terrestrial ecosystems play an important role in determining the amount of these gases into the atmosphere. However, global quantifications of CH₄ emissions from wetlands and its sinks from uplands, and CO exchanges between land and the atmosphere are still fraught with large uncertainties, presenting a big challenge to interpret complex atmospheric CH₄ dynamics in recent decades. In this dissertation, I apply modeling approaches to estimate the global CH₄ and CO exchanges between land ecosystems and the atmosphere and analyze how they respond to contemporary and future climate change.

Firstly, I develop a process-based biogeochemistry model embedded in Terrestrial Ecosystem Model (TEM) to quantify the CO exchange between soils and the atmosphere at the global scale (Chapter 2). Parameterizations were conducted by using the CO in situ data for eleven representative ecosystem types. The model is then extrapolated to global terrestrial ecosystems. Globally soils act as a sink of atmospheric CO. Areas near the equator, Eastern US, Europe and eastern Asia will be the largest sink regions due to their optimum soil moisture and high temperature. The annual global soil net flux of atmospheric CO is primarily controlled by air temperature, soil temperature, SOC and atmospheric CO concentrations, while its monthly variation is mainly determined by air temperature, precipitation, soil temperature and soil moisture.

Secondly, to better quantify the global CH₄ emissions from wetlands and their uncertainties, I revise, parameterize and verify a process-based biogeochemical model for methane for various wetland ecosystems (Chapter 3). The model is then extrapolated to the global scale to quantify the uncertainty induced from four different types of uncertainty sources including parameterization, wetland type distribution, wetland area distribution and meteorological input. Spatially, the northeast US and Amazon are two hotspots of CH₄ emissions, while consumption hotspots are in the eastern US and eastern China. The relationships between both wetland emissions and upland consumption and El Niño and La Niña events are analyzed. This study highlights the need for more in situ methane flux data, more accurate wetland type and area distribution information to better constrain the model uncertainty.

Thirdly, to further constrain the global wetland CH₄ emissions, I develop a predictive model of CH₄ emissions using an artificial neural network (ANN) approach and available field observations of CH₄ fluxes (Chapter 4). Eleven explanatory variables including three transient climate variables (precipitation, air temperature and solar radiation) and eight static soil property variables are considered in developing the ANN models. The models are then extrapolated to the global scale to estimate monthly CH₄ emissions from 1979 to 2099. Significant interannual and seasonal variations of wetland CH₄ emissions exist in the past four decades, and the emissions in this period are most sensitive to variations in solar radiation and air temperature. This study reduced the uncertainty in global CH₄ emissions from wetlands and called for better characterizing variations of wetland areas and water table position and more long-term observations of CH₄ fluxes in tropical regions.

Finally, in order to study a new pathway of CH₄ emissions from palm tree stem, I develop a two-dimensional diffusion model. The model is optimized using field data of methane emissions from palm tree stems (Chapter 5). The model is then extrapolated to Pastaza-Marañón foreland basin (PMFB) in Peru by using a process-based biogeochemical model. To our knowledge, this is among the first efforts to quantify regional CH₄ emissions through this pathway. The estimates can be improved by considering the effects of changes in temperature, precipitation and radiation and using long-period continuous flux observations. Regional and global estimates of CH₄ emissions through this pathway can be further constrained using more accurate palm swamp classification and spatial distribution data of palm trees at the global scale.

Understanding climate-driven changes in global land-based ice volume is a critical component in our capability to predict how global sea level will rise as a consequence of the current human-driven climate change. At the last glacial maximum (LGM, which peaked around 20 ka), ephemeral ice sheets covered vast regions of the northern hemisphere while both the Greenland and Antarctic ice sheets were more extensive than at present. As global temperatures rose at the transition into the Holocene, driving the LGM deglaciation, eustatic sea level rose by approximately 125 m. The east Antarctic ice sheet (EAIS) is the largest ice sheet on Earth today, holding an ice volume equivalent to ca. 53 m rise in global sea level. Considering current trends in global climate, specifically rapidly increasing atmospheric CO₂ levels and global temperature, it is important to improve our understanding of how the EAIS will respond to global warming so that we can make better predictions of future sea level changes to guide community adaptation and planning efforts. Numerical ice sheet models which inform projections of future ice volume changes, and can, therefore, yield projections of sea level rise, rely on empirical data to test their ability to accurately represent former and present ice configurations. However, there is a general lack of data on the paleoglaciology of the EAIS along the western Dronning Maud Land (DML) margin. In order to address this situation, the paleoglaciology of western DML forms the focus of the work presented in this thesis.

Together with collaborators within the MAGIC-DML consortium (Mapping, Measuring and Modelling Antarctic Geomorphology and Ice Change in Dronning Maud Land) that provides the funding for this MS project, the author has performed geomorphological mapping across western DML; an area of approximately 200,000 km². The results of the mapping presented in this thesis will provide the basis for a detailed glacial reconstruction of the region. The geomorphological mapping was completed almost entirely by remote sensing using very high-resolution (sub-meter in the panchromatic) WordView-2 and WorldView-3 (WV) satellite imagery, combined with ground validation studies during field work. Compared to Landsat products, the improved spatial resolution provided by WV imagery has fundamentally changed the scale and detail at which remote sensing based geomorphological mapping can be completed. The mapping presented here is focused on the glacial geomorphology of mountain summits and flanks that protrude through the ice sheet’s surface (nunataks). In our study area of western DML these nunatak surfaces make up <0.2 % of the total surface area, and the landforms mapped here are generally smaller than can be identified from Landsat products (30 m spatial resolution). The detail achieved in our mapping, across such a vast, remote area that presents numerous obstacles to accessibility highlights the benefits of utilizing the new VHR WV data. As such an evaluation of the WV data, as applied to geomorphological mapping is presented here together with our mapping of the glacial geomorphology of western DML. The results of which provides evidence of ice having overridden sites at all elevations across the entire study area; from the highest elevation inland nunataks that form the coast-parallel escarpment, to low-elevation emerging nunataks close to the coast. Hence from our studies of the glacial geomorphology of this region we can ascertain that, at some point in the glacial history of western DML, ice covered all of the mountain summits that are exposed today, indicating an ice sheet surface lowering of up to 700 m in some places.