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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/96444| Title: | Modelling Fish Species Distributions Under Ocean Acidification and Hypoxia in the North Sea Modelling Fish Species Distributions Under Ocean Acidification and Hypoxia in the North Sea |
| Authors: | Kristina Kryzhova Kristina Kryzhova |
| Advisor: | 柯佳吟 Chia-Ying Ko |
| Keyword: | Species distribution modelling,North Sea,Fishery,Model comparison,Climate change, Species distribution modelling,North Sea,Fishery,Model comparison,Climate change, |
| Publication Year : | 2025 |
| Degree: | 碩士 |
| Abstract: | None The increasing impact of climate change on marine ecosystems requires robust modeling approaches to project future species distributional shifts. These biogeographical reorganizations are fundamentally transforming the global fishing industry, as traditional fishing grounds experience declining productivity or ecological regime shifts toward novel species assemblages, while simultaneously creating emerging opportunities in previously marginal areas, though these new fishing frontiers often lack the necessary infrastructure and regulatory frameworks to support sustainable resource exploitation. Some projections that rely solely on temperature as the main parameter may fail to capture the complex interplay of multiple environmental stressors, including dissolved oxygen, pH, and their complex effects on marine ecosystems, potentially leading to oversimplified or inaccurate future projections. This study aims to investigate if adding dissolved oxygen concentration, and pH as predictor variables, can better predict the distribution shifts of 16 demersal and 5 pelagic fish species in the North Sea. To project marine fish response to abiotic factors under SSP1-2.6, SSP2-4.5, SSP5-8.5 scenarios for 2050 and 2100, the ensemble of Species Distribution Models (SDMs) was implemented. While SSP5-8.5 scenario incorporated declining oxygen levels (projected decrease of 31-34% from when to when) and ocean acidification (pH decrease of 5-6% from when to when under which scenarios) by 2100, model performance analysis revealed that temperature alone created the best ensemble model, with the best validation metrics (TSS = 0.950±0.001). Under the most pessimistic scenario - SSP5-8.5, temperature-driven models projected mean north-west shifts of distributional centroids at 245±223 km for most demersal species and eastwards 193±62 km shifts for pelagic species by 2100, while combination of parameters projected generally south and south-eastwards movements for both functional groups up to 143±57 km. When comparing single-factor and multi-factor models, the similarity comes in projection up to 2050 when the southern and central areas tend to be the most suitable ones, however later projections for 2100 showed disparity in direction and magnitude of distributional shifts, especially for the demersal species, seeking refugia in different locations. These findings suggest that while numerous stressors affect marine ecosystems, statistically, temperature’s impact is the strongest for selected species in the North Sea region based on the applied data. The findings reveal significant implications for improving climate impact assessments of marine wildlife through the integration of species distribution models into unified frameworks that enable robust analysis of migration patterns. |
| URI: | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/96444 |
| DOI: | 10.6342/NTU202500202 |
| Fulltext Rights: | 同意授權(全球公開) |
| metadata.dc.date.embargo-lift: | 2026-01-01 |
| Appears in Collections: | 生物多樣性國際碩士學位學程 |
Files in This Item:
| File | Size | Format | |
|---|---|---|---|
| ntu-113-1.pdf | 25.49 MB | Adobe PDF | View/Open |
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