PhD Oral Exam - Hammed Adedamola Akande, Biology

When studying for a doctoral degree (PhD), candidates submit a thesis that provides a critical review of the current state of knowledge of the thesis subject as well as the student’s own contributions to the subject. The distinguishing criterion of doctoral graduate research is a significant and original contribution to knowledge.

Once accepted, the candidate presents the thesis orally. This oral exam is open to the public.

Abstract

Ecologists have long used the concept of the ecological niche to explain patterns of species distributions, persistence, and diversity across spatial and temporal scales. Broadly defined, a species’ niche encompasses the set of biotic and abiotic conditions necessary for population persistence. An important dimension of the niche concept is niche breadth, or the degree of specialization, which reflects the range of conditions and resources a species can exploit and has important implications for its tolerance to environmental variability. However, despite its widespread use, there exists uncertainty regarding how niche breadth is quantified, how specialization changes over time, and how reliably it predicts species’ responses to global environmental change across ecosystems. In this thesis, I advance a quantitative and integrative understanding of species specialization by combining methodological evaluation, spatiotemporal ecological inference, and global evidence synthesis. The work is structured around three interconnected research chapters, all centred on ecological niches and specialization, but operating at complementary scales and levels of inference. I first address the methodological foundations of niche breadth quantification by systematically comparing commonly used specialization metrics through simulation and empirical analysis. By evaluating metric behaviour across controlled ecological scenarios and empirical data, this work establishes a foundation for interpreting niche breadth estimates and clarifies the limitations inherent to different classes of metrics, thereby providing a robust basis for empirical inference. Building on this framework, I then investigate how climatic niche breadth varies through time within a major vertebrate group, birds, and whether life-history strategy mediates these dynamics. Focusing on migratory and resident species, I use spatiotemporal Bayesian modelling to examine temporal changes in realized climatic specialization across broad geographic extents, addressing how behavioural strategies such as migration shape niche lability under climate variability. Finally, I scale the analysis to a global perspective by synthesizing evidence across taxa, biomes, and study systems to evaluate whether generalist species are consistently favoured under global environmental change. To do so, I develop and apply a human-in-the-loop, Large Language Model–integrated pipeline for systematic evidence synthesis in ecology, situating patterns observed at local and continental scales within a broader macroecological context while demonstrating how emerging Artificial Intelligence tools can be responsibly integrated into quantitative ecological research. Collectively, the chapters in this thesis conceptualize ecological specialization as a dynamic, context-dependent attribute shaped by environmental variability, species traits, and community structure. By clarifying how specialization is measured, how it changes through time, and how it mediates biodiversity responses across scales, my research contributes to a more predictive understanding of biodiversity change in the Anthropocene and offers practical insights for biodiversity forecasting and conservation planning under accelerating climate change.