About me
From field naturalist to integrative vector evolutionary ecologist
Keywords: evolutionary ecologist · mosquito biologist · quantitative naturalist
As an evolutionary ecologist, I’m fascinated by how organisms adapt to diverse and shifting environments. I’m also interested in the reverberating effects of these adaptations on populations, species boundaries, and interspecies interactions. My primary focus has become mosquitoes, especially African malaria vectors, making me, above all, a mosquito biologist. These insects are a powerful subject of study because they show how ecology, evolution, behaviour, physiology, genetics, and disease pathogens spread by mosquitoes all connect. My research explores questions like: How do populations adapt to novel environments? How is adaptive variation preserved despite gene flow? How do ecological variations translate into physiological, behavioural, and genomic differences? At what point does divergence lead to speciation? And, for disease vectors, how do these evolutionary processes ultimately influence pathogen transmission? My scientific journey began as a field naturalist and ornithologist. My curiosity hasn’t changed, despite the shift from binoculars and mist-nets to tools like mosquito traps and genome sequencing. I still want to observe organisms in their habitats, and understand the forces that create the diverse patterns we find.
Scientific profile
Evolutionary ecologist by question. My research focuses on how insect vectors adapt, how they evolve, how new species form, how genes spread between populations, and the evolution of traits that help them spread diseases.
Mosquito biologist by system. I am obsessed with African malaria mosquitoes like Anopheles funestus and Anopheles gambiae, but my interests also cover mosquito ecology, behaviour, and evolution more broadly.
Field biologist by instinct. Natural populations matter. Much of my work starts with mosquitoes in real landscapes rather than idealised laboratory populations.
Naturalist by origin. I entered science through ornithology and field observation. That background still shapes how I think about biological variation and ecological context.
Quantitative biologist by necessity. Population processes are noisy, observations are incomplete, and biological systems are hierarchical. Biostatistics, statistical modelling, Bayesian inference, and causal reasoning are essential, not just superfluous details.
Genomicist by opportunity. Whole-genome sequencing has transformed questions that I once approached through chromosomes, phenotypes, and geography. Population genomics now allows precise examination of barriers to gene flow, introgression, ancestry, and the genomic architecture of adaptation and speciation.
Computational biologist by practice. Biological research now extensively uses computation for managing genetic data, modelling populations, incorporating environmental data, and developing reproducible analytical workflows. I see scientific computing, data architecture, provenance, and reproducibility as parts of biological inference, not merely technical tools.
Environmental data scientist by scale. Mosquitoes experience landscapes, not spreadsheets. GIS, remote sensing, climate products, and other environmental datasets allow individual organisms and populations to be placed back into their ecological context.
Methodological pluralist by conviction. No particular technology defines my research. Field experiments, genomics, behavioural assays, environmental data, statistical modelling, and computation are useful only where they help discriminate among biological explanations.
Organism × Environment
A useful shorthand for how I portray biology is:
organism × environment
Many interconnected levels describe each organism:
genome · epigenome · transcriptome · metabolome · physiology · morphology · behaviour
The environment is equally multidimensional:
climate · hydrology · landscape · conspecifics · communities · hosts · pathogens · human activities
The interesting biology lies in the interactions between them. This is why my research combines evolutionary biology, ecology, population genetics and genomics, behavioural science, environmental science, biostatistics, and informatics. I do not regard these as separate research identities. They are different viewpoints and tools for understanding the same biological systems.
Why mosquitoes?
Mosquitoes are significant because some species transmit ravaging diseases. However, their role as disease vectors isn’t the sole reason they are biologically fascinating. They inhabit an astonishing array of environments, evolve quickly, exhibit intricate behavioural and physiological adaptations, interbreed between incompletely separated groups, possess remarkable chromosomal variations, and constantly adapt to environmental changes. Their importance in disease transmission merely simply the outcomes of these evolutionary processes exceptionally explicit. When a mosquito population alters its preferred host, colonises saltwater habitats, changes its biting schedule, adapts to urban settings, or acquires from another population genes conferring insecticide resistance, it simultaneously conducts an evolutionary experiment and changes the conditions for pathogen transmission. My research broadly focuses on this intersection between core evolutionary ecology and its impact on human health.
How I approach science
I’m wary of rigid disciplinary boundaries and the tendency for methods to become the goal rather than the tool. A genome, in itself, doesn’t explain phenomena. Similarly, a statistical association on its own doesn’t reveal a mechanism. A complex model can’t compensate for a flawed sampling design, and a massive dataset isn’t inherently insightful. My preference is to start with the biological question, clearly state any assumptions, identify observations that could distinguish between competing explanations, and only then select the most suitable methods. This could include tasks like sampling mosquito larvae in muddy rice paddies, studying many genomes in front of a computer screen, or figuring out past or future environmental changes using satellite images. It could even mean painstakingly troubleshooting a bioinformatics pipeline that yields an unexpected variant. Ultimately, all these activities are just different facets of the same core endeavour: drawing biological inferences from observations and hypotheses.
Research
This page is intentionally the short version. For more information on my biological research and the methods I use, check out: → Research Themes
In one sentence: I study how mosquitoes thrive and evolve in changing environments, using whatever combination of field biology, experiments, genomics, environmental data, and quantitative inference is necessary to understand why.