Geography - Doctoral Theses

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    Ocean-surface heterogeneity mapping: exploiting hypertemporal datasets in support of seascape ecology research
    (University College Cork, 2022-04) Scarrott, Rory; Cawkwell, Fiona; Jessopp, Mark John; Cronin, Michelle; Cusack, Caroline; O’Rourke, Eleanor; Horizon 2020
    Seascape ecology provides us with a framework to explore the distribution of marine life throughout the world’s oceans. Studies often require both biological and environmental data from a variety of sources, which are increasingly complemented by data acquired using remote sensing and satellite-based sensors. Advances in remote sensing technology have equipped researchers with the capability to visualise environmental conditions, with great precision over large spatial scales. As records of environmental conditions, satellite-derived image data have proven useful in seascape ecology. Indeed, single-date and multi-date satellite imagery are already widely used in support of oceanographic and fisheries research and monitoring. However, with increases in the temporal frequency of imagery, a greater diversity of ocean surface features can be studied, modelled, and understood in terms of their development over time. This research examines the interface between oceanography, marine ecology, and remote sensing. It focuses on the use of a subset of temporally-rich satellite-derived imagery known as hypertemporal data, and its potential utility for seascape ecology studies. These high temporal resolution datasets are characterised by being: univariate in nature (e.g. Sea Surface Temperature); comprised of frequent, equally-spaced discrete time slices; precisely co-registered; and radiometrically consistent between images (i.e. they are measured using the same sensors, or are derived from inter-validated sensor systems). An in-depth review analyses nearly 25 years of available literature on the use of satellite-derived hypertemporal datasets. In general, they have been more widely used in terrestrial environments where in-situ validation costs are lower, and boundaries and features have greater permanency. By contrast, hypertemporal datasets have been under-utilised in ocean sciences. The review examines and describes the range of methodologies that have been adapted specifically for hypertemporal applications, in both marine and terrestrial contexts. It also identifies the priority research that should be done to maximise data usage for the ocean arena. In particular, the review highlighted the importance of prioritising data-driven methodologies in the near-term, and developing methods to map spatio-temporal heterogeneity (i.e. spatial and temporal variations in physical, chemical, or biological conditions) within datasets. A data-driven method to map Spatio-Temporal Heterogeneity (STH) using hypertemporal datasets is then presented. The Ocean-surface Heterogeneity MApping (OHMA) algorithm uses unsupervised ISODATA clustering, an ensemble approach, and a data-driven optimisation process, to identify where boundaries between different ocean regions frequently occur. OHMA effectively produces a suite of complementary datasets – a single STH image dataset that highlights the frequency at which boundaries between regions occur, and an optimised spatio-temporal classification of the ocean surface (both spatial cluster distributions, and their associated temporal profiles). A Sea Surface Temperature (SST) dataset, comprising weekly images of the North Atlantic Ocean from 2011, was used to develop the method. Validation, using Irish Marine Institute temperature measurements acquired along vessel tracks while the vessel is “Underway”, demonstrated an association between higher STH values and areas where locally extreme temperature transitions were more likely to occur. Generalised Linear Modelling of STH versus a combination of possible ocean-surface heterogeneity characteristics (fronts and currents), and oceanographically-known drivers (bathymetry), showed that the drivers of STH vary regionally. This highlighted the utility of OHMA to generate higher-level products. These contain spatial and temporal information that cannot be produced using only in-situ or infrequent satellite data. Following development of the OHMA methodology, the research examined its performance at a range of spatial and temporal scales, and the considerations needed to integrate STH mapping into seascape ecology analyses. Two OHMA-applications on SST data used relatively well-understood waters around the West European Archipelago, and ecologically important thermohaline and tidal front systems, to explore the methodology’s potential. The first OHMA-application focused on the algorithm’s performance at higher spatial scales, and sub-annual timeframes. STH values, derived from a 48-day hypertemporal SST dataset from summer 2019, were compared to a difference grid generated from a network of Conductivity, Temperature and Depth (CTD) measurements, and hydrographic information derived from Underway and CTD cast data. Higher value STH features were also compared to a number of well-documented tidal fronts, and a thermohaline front. Statistically significant positive correlations were identified between STH values and a difference in surface water characteristics between CTD sites. While the approach conveyed detailed spatio-temporal information on tidal fronts, it performed poorly at framing the thermohaline front. Examining the hydrographic information revealed the complexity in interpreting these associations. The study highlighted the value of using STH datasets to objectively characterise the spatio-temporal behaviour of fronts, and the surface structure of stratified shelf seas. It also suggested an annual cycle of STH should be analysed, to clarify whether thermohaline front information could be gathered. The second application examined the use of multiple temporal scales within a preliminary seascape ecology study, comparing SST-derived STH to a number of ecosystem indicators concerning primary producer abundance (phytoplankton) and fishing fleet activity. In doing so, it also further examined temporal scale considerations when using hypertemporal data. STH datasets were produced from different temporal inputs (an annual 7-day SST dataset versus 30/31-day daily SST datasets over 2018). SST-STH, model-derived phytoplankton concentration, and apparent commercial fishing effort data (derived from a behavioural classification of Automatic Identification System data, recording vessel tracks) were compared for February, March, July, and August using a correlation-based approach. Positive associations were found between SST-STH and fishing effort. This study demonstrated there could be important, usable, biophysical linkages between trophic indicators, and the higher-level heterogeneity conveyed by a STH dataset. It also highlighted the challenges the OHMA approach faced when used on multi-temporal, rather than hypertemporal, data. Additionally, it clarified SST-STH maps could convey information on thermohaline fronts when OHMA was used on SST datasets at annual timeframes, or datasets framing times when continental shelf seas are not thermally stratified. The thesis culminates in a discussion of how hypertemporal data could be used to support seascape ecology applications, using the development of the OHMA approach to provide evidence and guidance. Discussions highlight the key advances the research has made. Namely, the research has clarified that there are benefits to exploiting the hypertemporal data resource within seascape ecology research. The high-resolution data records subtle changes that can be used to better characterise ocean surface habitats. The research also produced a methodology that delivers objectively-derived, high-level heterogeneity information from hypertemporal data, demonstrated its use within a seascape ecology study, and described it along with best practice guidance for use. The limitations of the methodology are also clearly outlined, and include a cautionary note concerning the use of OHMA on non-hypertemporal datasets where the image number, or dataset variability, may be insufficient for the process to produce the full range of possible products. Concerning validation, the research highlighted the need for in-situ data to be collected which is spatio-temporally comparable to hypertemporal datasets, to improve quality assessment of, and confidence in, information products derived from hypertemporal datasets. Within this research in particular, the in-situ data should allow for estimates of spatio-temporal heterogeneity to be derived, which are comparable to those which can be derived from hypertemporal datasets. The discussion also emphasises a range of near-term (1-5 year) future research avenues, which include (i) exploiting available hypertemporal datasets from the ESA Climate Change Initiative, (ii) using OHMA-derived STH maps to stratify in-situ sampling of ocean-surface features, (iii) demonstrating the use of OHMA coupled with time-series analysis of ocean-surface parameters, and (iv) examining multi-trophic interactions between primary producers, predators, and STH features in waters around the West European Archipelago and the North Atlantic. Such near-term studies would enhance our understanding of the methodology, and use hypertemporal data to expand our understanding of ocean-surface structure at different spatial and temporal scales. In addition, they would use spatio-temporal heterogeneity mapping to diversify the range of hypertemporal methodologies being deployed on ocean-surface parameters, further enabling seascape ecology studies to exploit the hypertemporal data resource.
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    National farm scale estimates of grass yield from satellite remote sensing
    (University College Cork, 2021-12-03) Marwaha, Richa; Cawkwell, Fiona; Green, Stuart; Teagasc
    Globally, grasslands are an important source of food for livestock and provide additional ecosystem services such as greenhouse gas (GHG) mitigation through carbon sequestration, habitats for biodiversity, and recreational amenities. Grass is the cheapest source of fodder providing Irish farmers with an economic benefit against international competitors. Hence, to maintain profitability, farmers have to maximize the proportion of grazed grass in cow’s diet or save it as silage. The overall objective of the current research project was to build a machine-learning model to estimate grass growth nationally using earth observation imagery from the Sentinel 2 satellite constellation and ancillary meteorological data, which are known to influence grass growth. Firstly, the impact of meteorological data and Growing Degree Days (GDD) was assessed for Teagasc Moorepark experimental farm (Fermoy, Co Cork, Ireland). GDD was modified to include Soil Moisture Deficit (SMD), which included the impact of summer drought conditions in 2018. Results demonstrated the importance of GDD for grass growth estimation using ordinary linear regression (OLS). The potential evapotranspiration (PE) 0.65 (r=0.65) and evaporation (r=0.65) were equally significant variables in 2017, while in 2018 the solar radiation had the highest correlation (r=0.43), followed by potential evapotranspiration and evaporation with r of 0.42. The standard and modified GDD were equally significant variables with r of 0.65 in 2017, but both had a reduced correlation in 2018 with modified GDD (0.38, p<0.01) performing slightly better than the standard GDD (0.26, p<0.01) calculation. These models only explained 53% (RMSE of 18.90 kg DM ha-1day-1) and 36% (RMSE of 27.02 kg DM ha-1day-1) of variability in grass growth for 2017 and 2018, respectively. Considering the importance of meteorological data, an empirical grass model called the Brereton model, previously used for Irish grass growing conditions were tested. Since this model lacks a spatial element, we compared the Brereton model with the previously used machine-learning model ANFIS and Random Forest (RF) with the combination of satellite data and meteorological data for eight Teagasc farms. Overall, the machine-learning algorithms (R2= 0.32 to 0.73 and RMSE=14.65 to 24.76 kg DM ha-1day-1 for the test data) performed better than the Brereton model (range of R2=0.03 to 0.33 and RMSE=41.68 to 82.29 kg DM ha-1day-1). The RF model (with all the variables except rainfall) had the highest accuracy for predicting grass growth rate, with (R2= 0.55, RMSE = 14.65 kg DM ha-1day-1, MSE= 214.79 kg DM ha-1day-1 versus ANFIS with R2 = 0.47, RMSE = 15.95 kg DM ha-1day-1, MSE= 254.40 kg DM ha-1day-1). When developing a national model, meteorological data were missing (except precipitation). A different approach was followed, whereby the grass growing season was subdivided (January-June Agmodel 1 and July–December Agmodel 2). Phenologically, the peak grass growth in Ireland typically occurs in May, with a slow decline in subsequent months. Spring is the most important season for grassland management, where growing conditions can impact the grass supply for the whole year. The national models were developed using Sentinel 2 band metrics, spectral indices (NDVI and NDRE), and rainfall for 179 farms. Data from 2017-2019 was divided into training and testing data (70:30 split), with 2020 data used for independent validation of the final trained model. Test accuracy was higher for Agmodel 1 (R2 = 0.74, RMSE= 15.52 kg DM ha-1day-1) versus Agmodel 2 (R2 = 0.58, RMSE= 13.74 kg DM ha-1day-1). This trained model was used on validation data from 2020, and the results were similar with better performance for Agmodel1 (R2 =0.70) versus Agmodel2 (R2=0.36). The improved spatial resolution of Sentinel 2 and the availability of red-edge bands showed improved results compared with previous work based on coarse resolution satellite imagery.
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    Remembering the 'comfort women': connected histories and the politics of solidarity
    (University College Cork, 2021-02) Park, Gyunghee; Linehan, Denis; Czajka, Agnes; Korea Foundation; University College Cork
    At the height of Japan's military campaign and territorial expansion during World War II, the Imperial army and its colonial government in Korea coordinated the management and organisation of the largest known network of militarised sexual slavery in recorded history. But for over 40 years, it appeared that the world had forgotten its existence. Following the re-emergence of the so-called ‘comfort women’ in the late-1980s, scholars and activists alike have since grappled with questions of what it means to acknowledge the ‘comfort system’ as history, and how we may begin to remedy the exclusion of its victims from our memory. In an examination of the ‘comfort women’ memory movement in South Korea and the United States, this thesis looks at the ways in which state and local actors have attempted to remember the ‘comfort women’ and seek out justice on their behalf. On this account, the author asks not only what it means to reimagine the ‘comfort system’ as having global-historical significance, but also explores the narrative logics that underlie commemorations and inform individual understandings of what it means to act in solidarity with its survivors.
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    Food poverty and charitable food provisioning in Cork
    (University College Cork, 2020-09) Kenny, Tara; Sage, Colin; O'Shaughnessy, Mary; Irish Research Council for the Humanities and Social Sciences
    The issue of food insecurity has moved to the forefront of social policy debates, with inadequate diets affecting one in three people globally (IFPRI, 2016) and with low income persons carrying the largest burden. The impacts of food insecurity on health are extensive and resonate throughout a lifetime which positions issues of food insecurity as a central social justice concern. An increasingly normalized response to food insecurity, more commonly referred to as food poverty in Ireland, is the redistribution of surplus food. In the decade following the economic crisis of 2008-10 Ireland has witnessed a rapid expansion of charitable food services and the establishment of what would become Ireland’s first national system of surplus food redistribution. This growth was also facilitated by multiple co-existing factors and circumstances. These include the historical precedence and primacy afforded to charitable responses, the withdrawal of significant third sector funding post economic crash, Ireland’s persistently high rates of poverty, and a protracted homelessness crisis. An additional critical factor in this trajectory has been the deepening neoliberal ideology promoting novel, business led solutions and Corporate Social Responsibility responses to issues of social inequality. These features of Irish society combined with an increasing awareness of the problem of food waste positioned surplus food as a legitimate and distinguished approach to tackling poverty more generally. This thesis focusses on the contemporary charitable food system in Ireland and is set against the backdrop of increasing diet-related poor health, rising inequality, wider food system trends, and the experiences of charitable food assistance in other high-income countries. Using critical realism as a metatheory and Cork city as an embedded case study, several aspects of Ireland’s contemporary charitable food system are explored. This includes the organisations providing charitable food assistance, the surplus food flowing through it, the circumstances and level of food insecurity and ill-health experienced by its users, and the representation of food poverty at the national level. The overarching goal is to identify the factors influencing food governance within the charitable food system and its impact at the local level. The findings suggest that several dominant ideas and practices influence the governance of food within the charitable food system and work to indirectly support, and legitimize, the use of any surplus food as a response to poverty. This includes the conceptualisation of food poverty and nutritional poverty as separate issues which in turn supports the idea that health concerns are outside the remit and responsibility the organisations responding to food poverty. The local impacts of surplus food redistribution include redistribution beyond demand, in some instances the replacement of food vouchers with surplus and the loss of charity-based support for local food businesses. The findings highlight that the growing role of the charitable sector as a key food waste reduction strategy means that surplus food redistribution is influencing the diets, the health, and food cultures of low income populations using these services. Aligning these concerns with surplus food redistribution would prevent further deepening Ireland’s inequalities. A practical first step in this regard would be the introduction of a healthy food policy across the charitable food. Overall, this thesis demonstrates that the ideological framing surrounding food poverty have changed little since the early 20th Century where the focus was on the ‘personal’ rather than ‘economic or social reform’ (Miller, 2014), on providing food rather than addressing the causes of food poverty and with the local community as duty bearer. This thesis ultimately argues that a more critical reflection on food charity in Ireland is required with questions of social justice and the human right to good food in a socially accepted manner, taking centre stage.
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    Seeking pathways towards improved transboundary environmental governance in contested marine ecosystems
    (University College Cork, 2020-07-03) Twomey, Sarah; Cummins, Valerie; Hickey, Kieran
    In academic circles, international maritime boundaries have received renewed interest as a consequence of geopolitically charged events. As marine resources become scarcer, transboundary ecosystems that were previously looked upon as peripheral are increasing in importance. Over 200 maritime boundaries are as yet unresolved due largely to conflicting and entrenched legal or political positions or limited political will to break to impasse. Intractable conflicts that occur in these contexts are highly political, long-term, complex, dynamic and extremely resistant to change despite genuine efforts to resolve them. Whilst some borders have a legally common delimited line agreed by adjoining states through an international agreement, they can be fiercely contested by one side despite a formally agreed framework. In other border areas, when ownership of a territory is disputed, the absence of an agreement on ownership and a clearly defined boundary line creates potential for conflict. Examples of both of these scenarios within the marine environment were examined as in-depth case studies in this thesis. This study addressed the complexity associated with resolving conflicts in contested transboundary marine ecosystems and explored whether agreed maritime boundaries are essential, or whether some resource conflicts can be successfully managed through informal arrangements or resource sharing regimes in contested marine ecosystems. A multi-perspective interdisciplinary meta-analytical framework and timeline mapping technique was applied in two diverse case studies from the Global North and Global South: Lough Foyle separating the Republic of Ireland and Northern Ireland and Palk Bay separating India and Sri Lanka. Primary and secondary data collection included extensive fieldwork in both study sites, desktop research, media content analyses, participatory GIS conflict hot-spot mapping and 67 semi-structured interviews with key informants representing government, industry, the research community and civil society. Trajectory of Change Timelines were developed for both case studies as a tool for the systematic analysis of the protracted conflicts through the identification of parallel historical and geopolitical transformations that have influenced the status quo. Based on the case study findings, a number of prominent contextual factors and uncertainties that drive resource conflicts in contested regions were identified; (i) the footprint of the past: the legacy of colonialism and arbitrarily drawn boundaries; (ii) coastal border regions: the paradox of spatial proximity to neighbouring States and peripherality from the seats of political power; (iii) strategy or apathy: the consequences of political inaction; (iv) the limitations of LOSC and existing theories of environmental governance; (v) the challenges of moving away from traditional approaches based on political boundaries towards integrated ecosystem-based governance. Transboundary environmental governance in these settings is inherently a political process, ultimately determined by the broader historical and geopolitical context, and often subject to apathy or strategy by neighbouring coastal states. Resource conflicts arising from contested marine ecosystems pose insights into a level of complexity and uncertainty in real-world scenarios that fail to align with conventional principles or theoretical best practice frameworks. Political leadership is critical in addressing transboundary issues through cooperative approaches with neighbouring jurisdictions. Conceptual or theoretical best practice frameworks for environmental governance are immaterial if political leaders are not willing to come to the table and agree on pathways to break the impasse. The following evidence-based insights for future governance options of contested marine ecosystems were formulated within the context of current geopolitical realities: breaking the political deadlock by re-framing the issue; ‘agreeing to agree’ by reaching a bilateral agreement supported and implemented by both Governments on a mutually acceptable boundary line; or ‘agreeing to disagree’ on boundary delimitation but cooperating through a joint development scheme.