Date of Completion


Embargo Period



Bayesian, Biodiversity, Ecology, Functional Traits, Pelargonium, Range Size

Major Advisor

Carl D. Schlichting

Associate Advisor

Cynthia S. Jones

Associate Advisor

Kent E. Holsinger

Associate Advisor

Robert Bagchi

Field of Study

Ecology and Evolutionary Biology


Doctor of Philosophy

Open Access

Open Access


Current threats to biodiversity are driving a research focus on understanding how environmental changes influence patterns of biodiversity at global and continental scales, deemphasizing research done at regional scales. I examined the role of environmental gradients in driving diversity patterns in the Greater Cape Floristic Region (GCFR) of South Africa, a biodiversity hotspot, renowned for its floristic diversity and high endemism levels.

The plant genus Pelargonium is centered in the winter-rainfall region of the GCFR, and varies considerably in morphology and growth form: remarkably, leaf size varies over 15000-fold across species. Pelargonium comprises 6 well-supported subclades that have diversified within the last 30 Ma. This diversity is arrayed along steep environmental gradients of temperature and amount and seasonality of rainfall.

Chapter 1 examined trait-trait and trait-environment associations across ~120 Pelargoniumspecies. Bayesian phylogenetic mixed-effects models revealed strong associations between climate and functional traits: height, leaf area, leaf mass per area (LMA), and leaf nitrogen content. Relationships between environments and these traits were subclade-dependent, i.e., subclades differed significantly in the signs of their trait-environment associations.

Chapter 2 explored how environmental gradients shape trait variation within the widespread species, Pelargonium scabrum. A Bayesian multiple-response multiple-regression model showed that P. scabrum leaves tended to decrease in size, effective leaf width and LMA with increasing winter minimum temperatures, suggestive of local adaptation. Trait-environment associations were influenced by rainfall seasonality, and by changing covariation between environmental variables across the range.

Chapter 3 evaluated niche breadth-range size relationships in Pelargonium. I generated Bayesian models that simulated random environments and preserved the spatial structure of the original temperature and precipitation climate layers. Observed niche breadth-range size relationships were no stronger than expected based on 999 random temperature and precipitation variables. Spatial autocorrelation reduces estimates of niche breadth, positively biasing estimates of niche breadth-range size relationships.

Overall, I demonstrate that evolutionary history matters for trait-environment associations at regional scales, and that local adaptation is mediated by the covariation among climate variables, and I show that spatial autocorrelation leads to a bias in estimates of niche breadth-range size relationships, and needs to be considered before inferring any causal relationship.