Matthew Pennell

Associate Professor

Research Interests

Computational Biology
Biodiversity Theory and Informatics
Evolutionary change across different time scales
Ecological and evolutionary processes operating in "deep time"
Ecological models for adaptive radiation
Long-term dynamics of evolutionary change
evolutionary genetics

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Affiliations to Research Centres, Institutes & Clusters


Graduate Student Supervision

Master's Student Supervision (2010 - 2020)
Macroevolution of metabolic and morphological traits in vascular plants (2020)

If we hope to mitigate the effects of the climate crisis, it is critical that we accurately represent the contributions of plants in global models and predictions. The need to link global cycles to biological processes that feed into these cycles involves making scaling assumptions. In the case of photosynthesis, most global models use parameters extrapolated from a handful of species. However, the variation in leaf form and function that we observe both within and across species makes one question the biological accuracy of this assumption. Despite advances in quantifying the differences between deeply divergent lineages, there is still a substantial gap in what we know about how C3 photosynthesis evolves both at very deep and very shallow evolutionary timescales. Filling this gap will allow us to better infer and incorporate photosynthetic behaviour in global models. Here we address two specific gaps: i) we assess the evolution of photosynthetic trait variation and ii) we evaluate the relationship between photosynthetic traits and a set of plant functional traits. These latter traits are often used as proxies for metabolic variation even though we don’t know how metabolic and morphological features are coupled through their evolutionary trajectories. We collected data for a phylogenetically structured sample of 106 species growing in a common environment, sampling metabolic and functional traits from the same individuals. Using estimates of phylogenetic half-life, we find significant phylogenetic structure in both metabolic and morphological traits, but the evolution of metabolic traits is much more constrained than that of morphology. We also ask whether changes across traits are coupled, and find that even when there are present day trait correlations, most traits do not seem to share correlated evolutionary history. Our finding of substantial interspecific variation in photosynthetic traits is not captured in current global ecosystem models; further, using functional trait variation as a proxy does not adequately represent this variation. Future work would benefit from using some element of evolutionary history or species identity in modeling photosynthetic behaviour.

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