http://hdl.handle.net/1893/28 This community contains the ePrints and eTheses produced by Biological and Environmental Sciences staff and students. 2026-11-14T17:47:42Z http://hdl.handle.net/1893/38457 Title: Revealing the influence of volcanic plumes on lake water quality parameters derived using remote sensing methods Author(s): Flower, Verity; Jiang, Dalin; Spyrakos, Evangelos Abstract: Satellite-derived observations of inland waters are widely used in environmental monitoring, often forming the basis of long-term analyses in the absence of continuous in situ measurements. However, the influence of transient atmospheric phenomena, such as volcanic plumes, on these datasets remains insufficiently quantified. We investigate the impact of volcanic plumes generated during the 2011-2012 eruption of Puyehue-Cordón Caulle, on the availability of remotely observed lake data (lake surface water temperature [LSWT], turbidity and chlorophyll-a) compiled from the ESA Climate Change Initiative (CCI) Lakes dataset. We subsequently extend the assessment of LSWT observations, combining these with coincident plume observations from the Multi-angle Imaging SpectroRadiometer (MISR) and the Moderate Resolution Imaging Spectroradiometer (MODIS), to identify the impacts of diffuse volcanic plumes on remote lake observations. Linear mixed-effects models assessed plume effects, while accounting for lake-specific variability during plume events. These findings indicate that while existing cloud masking removes LSWT observations in the presence of dense ash-rich plumes, diffuse volcanic plumes frequently remain undetected while significantly impacting LSWT records. Plume impacts varied seasonally, with LSWT observations being lower in winter months, and warmer in summer. At the pixel scale, plume interference was associated with LSWT8 reductions of up to 12°C beneath dense ash-plumes, and 1-5°C beneath diffuse plumes. Geographic conditions influenced overall data availability, with measurable effects extending to ~270 km from the volcanic source. A random forest classification achieved an overall accuracy of 78% classification accuracy for distinguishing plumes from cloud and background regions, demonstrating the potential to develop an automated flag for CCI Lake data. These findings demonstrate that diffuse volcanic plumes can introduce substantial uncertainty into satellite-derived LSWT observations, although the magnitude and spatial extent of the observed effects are case-specific. This highlights the need for further investigation across diverse volcanic events and geographical settings to support the development of dedicated quality flags for diffuse and transient aerosol features. 2026-12-31T00:00:00Z http://hdl.handle.net/1893/38456 Title: Analytical Optimization of Polarimetric Change Detectors for Mapping Open and Grassland Flooding Using Sentinel-1. Case of Rupununi, Guyana Author(s): Isundwa, Felix Kasiti; Marino, Armando; Berardi, Andrea; Bovolo, C Isabella; Hunter, Peter; Neil, Claire; Silva, Thiago S. F. Abstract: Quantifying flood inundation beneath vegetation is critical for understanding flood dynamics in complex wetland environments, where conventional remote sensing approaches often struggle to distinguish between open-water flooding and vegetation-covered inundation. In this study, we propose four novel detectors for the characterization of both open flooding and flooding beneath vegetation using radar-based signal analysis. The methods are developed from two fundamental signal models: the additive model of optimization of power difference and the multiplicative model of optimization of power ratio. Our objective is to investigate additive signal changes can inform or be combined with multiplicative ones. Based on these models, we developed four detectors through different combinations: First, monomial unitary combination, which represents the product of additive and multiplicative models; Second, monomial combination, a parameterized product-based model; Third, linear combination, based on additive integration; Fourth, mixed combination, a data-driven approach. The proposed detectors demonstrated strong potential for quantifying two types of flooding open-water flooding and grassland flooding beneath vegetation with the data-driven detector achieving the best overall performance. 2026-01-01T00:00:00Z http://hdl.handle.net/1893/38451 Title: Progressive shifts in soil respiration response to long-term nitrogen enrichment across global forests and grasslands Author(s): Xing, Aijun; Zhao, Mengying; Liu, Shangshi; Broadbent, Arthur A D; Du, Enzai; Shen, Haihua; Fang, Jingyun Abstract: Soil stores the largest pool of actively cycling carbon (C) on land, and its dynamics under global changes are critical for projecting climate feedbacks. Global nitrogen (N) deposition has more than doubled since the 1860s; however, the temporal dynamics of soil C emissions under prolonged N deposition are poorly understood. Here, using a global time-series dataset compiled from 38 long-term experiments in forests and grasslands, we find that the response of soil respiration (Rs) to N addition systematically shifts from a transient increase persisting for approximately 2 y to a sustained suppression over time (mean effect = −6%; 95% CI = [−10%, −3%]). Rs in forests and grasslands followed consistent nonlinear trajectories, characterized by a rapid initial decline in the magnitude of the response, which progressively leveled off. Notably, suppression of Rs emerged when cumulative N inputs exceeded a threshold of ~100 kg N ha−1. Consequently, the suppression was both stronger and occurred more rapidly under high-level N additions (>50 kg N ha−1 y−1). These temporal dynamics were associated with N-induced soil acidification and related changes in microbial properties. Overall, these findings indicate that accurate prediction of land–atmosphere C fluxes under global change requires models to capture the reported temporal dynamics. 2026-11-10T00:00:00Z http://hdl.handle.net/1893/38442 Title: Diatom-based treatment of geothermal brines to selectively remove silicon, retain lithium for downstream recovery, and produce omega-3 fatty acids Author(s): Rehmanji, Mohammed; Skeffington, Alastair; Hudson-Edwards, Karen A; Newsome, Laura Abstract: Summary Silica (SiO2) scaling in geothermal brines processing can hinder energy production and downstream lithium (Li) recovery. Here, we investigate diatom-based selective silicon (Si) removal from brines to support downstream recovery of lithium (Li) and generating biomass for valorization. Screening of six diatom strains identified Halamphora sp. as the most effective for Si removal. When cultivated in geothermal brine supplemented with urea, Halamphora sp. removed 34 mg L−1 of Si (97.14%) within 48 h, while retaining over 99% of Li (75 mg L−1) in solution. Urea supplementation also enhanced biomass production, reaching 0.45 g L−1. The resulting biomass contained the omega-3 fatty acids eicosapentaenoic acid (EPA; 47 mg g−1) and docosahexaenoic acid (DHA; 24 mg g−1). These results demonstrate the potential for coupling biological Si removal and Li retention with production of value-added biomass during geothermal brine processing. 2026-11-20T00:00:00Z