Research Themes
Biological questions and approaches to scientific inference
My scientific interests are broadly situated at the intersection of evolution, ecology, and the biology of disease vectors. I primarily focus on mosquitoes, particularly African malaria vectors of the Anopheles gambiae complex, to investigate these questions. My initial exposure to vector biology came from my first academic mentor, Prof. Mario Coluzzi, whose research utilised the remarkable chromosomal polymorphism found in African anopheline mosquitoes to study adaptation and speciation. This approach has continued to be a significant intellectual influence throughout my scientific career. Mosquitoes are fascinating evolutionary subjects because the traits that contribute to their ecological success are the same ones that make them important disease vectors. For instance, adaptations to climate, aquatic environments, vertebrate hosts, or human-altered landscapes can influence their geographical range, population dynamics, and interactions with humans. Consequently, evolutionary changes can have direct epidemiological impacts. My research is guided mainly by biological questions, rather than by specific technologies or analytical fields. However, addressing these questions increasingly necessitates the integration of field ecology, experimental studies, environmental data, quantitative inference, and diverse molecular and phenotypic datasets.
Biological questions
Adaptation to heterogeneous and changing environments
A central question guiding my research is how mosquito populations adapt to diverse environmental conditions. While insecticide resistance is the most well-documented instance of rapid adaptation in disease vectors, mosquitoes face many other selective forces. Survival and reproduction can be influenced by factors such as temperature, rainfall, aridity, water chemistry, salinity, pollution, land use, and artificial lighting, among others. Human activities are simultaneously creating new environments and transforming existing ones. I am especially interested in cases where populations colonise ecological conditions that were previously marginal or uninhabitable. This expansion into new niches prompts several interconnected questions. Are the observed differences rooted in genetics, environmental induction, or a combination of both? What characteristics enable individuals to survive and reproduce in the new environment? What fitness costs or trade-offs accompany adaptation? Does adaptation lead to ecological divergence from nearby populations? Does this resulting divergence impact geographical distribution, population dynamics, or disease-carrying capabilities? For instance, consider the capacity of those mosquitoes that are found in freshwater to thrive also in brackish aquatic habitats. This presents a biological challenge spanning landscape genetics to the osmoregulatory physiology of mosquito larvae. Tolerance to salinity is significant not just as a physiological trait, but because it can dictate the environments a population can inhabit, and consequently, where disease-vector populations can persist. Urbanisation offers another compelling example. Polluted artificial habitats, altered water flow, heat, artificial light, and high concentrations of humans and domestic animals create a suite of selective pressures that diverge from those under which mosquito populations evolved in the past. More generally, I am interested in understanding how global environmental change reshapes the adaptive landscape encountered by disease vectors.
Ecological divergence, gene flow, and speciation
When different populations face contrasting environments, adaptation becomes especially fascinating. If divergent selection intensifies, populations in different ecological niches can diverge, even with ongoing gene flow. This leads to a core question in evolutionary biology: how do adaptive differences emerge and endure when migration constantly introduces misadaptive alleles from other populations? The Anopheles gambiae complex offers an outstanding natural system to explore this. Its closely related species and populations exhibit differences in ecology, behaviour, and epidemiological significance, while maintaining varying levels of reproductive compatibility. My research interests therefore encompass:
- Ecological divergence across populations and species
- Mechanisms that prevent gene flow
- Patterns of genetic differentiation across genomes
- Processes leading to reproductive isolation
- The study of hidden or cryptic taxa
- Introgression and adaptive introgression
- The spectrum of divergence from locally adapted populations to distinct species
Rather than viewing species as isolated branches on an evolutionary tree, I’m increasingly focused on the reticulate evolutionary history that results from genetic exchange between incompletely isolated populations. Introgression is particularly significant because gene flow isn’t solely an obstacle to divergence; it can also supply beneficial genetic variations that enable populations to colonise new habitats or develop novel traits.
Genomic architecture of adaptation
Evolution hinges on heritable variation, yet how this variation is organised within a genome significantly impacts its evolutionary trajectory. This is precisely where chromosomal inversions have repeatedly surfaced in my research. Paracentric inversions are common in African anopheline mosquitoes and have consistently correlated with environmental gradients, geographical distribution, and ecological divergence. By suppressing recombination between different chromosomal arrangements, inversions can safeguard combinations of locally beneficial alleles, even in the face of gene flow across the rest of the genome. Today we can bridge the gap between classic cytogenetic observations, which first sparked interest in this area, and modern population genomics. The inquiry has broadened from:
What ecological factors maintain chromosomal inversion polymorphisms?
to more encompassing questions such as:
How is adaptive genetic variation distributed throughout the genome? Where are the barriers to gene flow situated? How do recombination, inversions, selection, and introgression interact? Ultimately, how do genomic differences give rise to ecological, physiological, and behavioural phenotypes?
These inquiries link chromosomal biology with population genomics, ecological genetics, and the study of speciation.
Evolution of behaviour and host choice
Behaviour is the interface through which an organism engages with its environment. A significant aspect of my research focuses on mosquito host selection, specifically the strong link between humans and some of the major African malaria vectors. For human malaria parasites or dengue arboviruses, mosquito feeding behaviour is more than just an accident of natural history. Whether mosquitoes repeatedly feed on humans or distribute their blood meals across various vertebrate species has significant implications for parasite transmission. Therefore, my research delves into the mechanisms behind host selection and its evolutionary adaptability. Olfaction is crucial, as mosquitoes react to complex blends of volatile compounds emitted by potential hosts. However, pinpointing a chemical linked to mosquito behaviour isn’t enough. The key question is how that cue functions within the behavioural sequence. A volatile compound might trigger flight, orient movement, facilitate close-range approach, start landing, or influence host acceptance. Broad terms like “attractant” and “repellent” can obscure these mechanistic differences. Consequently, one aim is to dissect complex behaviours into their functional components and understand how sensory information influences each one. An additional evolutionary inquiry is whether the marked preference for humans in some malaria vectors is a permanent species trait or an evolutionarily labile phenotype shaped by genes, ecological circumstances, and the availability of other hosts.
Biological rhythms and temporal behaviour
The environment changes not only across space but also over time. Many crucial mosquito behaviours, such as flying, mating, blood feeding, and egg-laying, exhibit distinct daily patterns. The temporal organisation of behaviour adds another layer to the ecological niche, which has clear implications for epidemiology. Disease control strategies like insecticide-treated bed nets indirectly leverage the overlap between human sleep patterns and the primarily nocturnal activity of many malaria-carrying mosquitoes. Any mosquito activity outside this timeframe can thus contribute significantly to ongoing transmission. My research aims to do more than just record when mosquitoes bite. I’m keen to understand how internal biological rhythms interact with external cues like the natural light-dark cycle, twilight, dim light, and artificial light at night. The overarching question, therefore, is how temporal environmental shifts can alter overt behaviours, and whether these changes are because of plasticity, gradual physiological adjustments, or evolutionary changes.
Population ecology and demography
Evolution ultimately hinges on variations in survival and reproduction among individuals. Similarly, epidemiological transmission relies on demographic factors like mosquito density, lifespan, and movement. Therefore, comprehending natural mosquito populations necessitates estimating key quantities such as:
- Population density
- Dispersal and migration patterns
- Reproductive activity
- The spatial and temporal distribution of individuals
Estimating these parameters proves deceptively challenging. Mosquito populations are huge, highly dynamic, and spatially uneven, while individual insects are small, mobile, and difficult to track consistently. Individuals detected by sampling methods offer only an incomplete picture of the underlying population. For me, this underscores an inseparable link between population ecology and the crucial question: what insights can our field observations genuinely provide about the population processes that created them? This inquiry bridges the gap between biological understanding and methodological approaches.
From vector biology to disease transmission and control
My primary interests are in fundamental biology, but vector biology is unique because even minor ecological or evolutionary shifts can significantly impact disease pathogens’ transmission. Factors like lifespan, population size, how often they bite, which hosts they prefer, when they are active, and how far they spread directly influence vectorial capacity. Therefore, figuring out why mosquitoes bite humans, live in salt water, infest urban areas, alter their biting times, develop insecticide resistance, or swap genes with other populations is both an evolutionary puzzle and a public health concern. For this reason, I view fundamental and applied vector biology as interconnected, not opposing, fields. Some of my work has involved developing mosquito repellents, insecticide strategies, evaluation methods, and behavioural techniques to minimise mosquito-human interaction. More broadly, the core idea is that any interventions will likely be more successful long-term if they are grounded in a solid understanding of the ecological and evolutionary systems they aim to manipulate.
Approaches to scientific inference
Biological questions rarely have simple answers that can be found using just one method or data type. Therefore, a significant part of my methodological focus is on how to integrate diverse observations to draw sound biological conclusions.
Publications on methods and scientific inference →
Field ecology and experiments in natural populations
I’ve consistently prioritised studying organisms in their natural environments. While laboratory experiments offer control, they inherently simplify ecological complexity and reduce genetic diversity. Field studies, conversely, expose organisms to the authentic interplay of environmental variability, competitors, hosts, predators, and population structures that have shaped their phenotypes over time. My work has involved developing and refining methods for studying natural mosquito populations, including:
- Sampling techniques for mosquitoes;
- Mark-release-recapture experiments;
- Estimating population density, survival rates, and dispersal patterns;
- Behavioural choice experiments;
- Semi-field experiments;
- Comparative ecological studies of natural populations;
- Experimental designs aimed at distinguishing environmental influences from inherent phenotypic variations.
It’s crucial to remember that field methods are not passive observation tools. Every trap, sampling strategy, or experimental setup inherently favours certain individuals over others. Therefore, understanding these observation processes and sampling biases is integral to making valid inferences.
Biostatistics, modelling and causal inference
Quantitative inference has always been central to my research, given the inherent noisiness, heterogeneity, and incompleteness of biological observations. My work spans classical and modern biostatistical methods, from multivariate analyses and generalised linear models to hierarchical models for ecological and demographic data. Recently, I’m especially attracted to Bayesian inference, particularly for scenarios involving uncertainty propagation across biological system levels or when observations stem from imperfect detection and sampling. A related fascination lies in differentiating between prediction, association, and causation. While large biological datasets facilitate the discovery of statistical associations, they don’t inherently clarify the underlying reasons. Consequently, I view causal reasoning, explicit articulation of competing biological hypotheses, and rigorous study design as increasingly vital complements to statistical modelling. My goal isn’t just to develop more complex models, but to find out which biological assertions the existing evidence can genuinely substantiate.
Omics and population genomics
Modern sequencing provides an entirely different view of the evolutionary processes that were once inferred principally from phenotype, geography and cytogenetics. My current interests extend across omics, broadly understood as high-dimensional measurements of the organism:
- genomics;
- population genomics;
- transcriptomics;
- epigenomics;
- metabolomics;
- and phenomics, encompassing morphology, physiology and behaviour.
Whole-genome sequence data make it possible to study population structure, barriers to gene flow, introgression, ancestry, chromosomal inversions and candidate regions involved in adaptation at unprecedented resolution.
But omics data are most informative when connected with information about the individual organism from which they were obtained. Genome sequences acquire biological meaning when associated with phenotype, behaviour, population history and environment. This is why I am particularly interested in study designs in which molecular data are not treated as an endpoint, but as another layer of evidence within an ecological and evolutionary analysis.
Bioinformatics and scientific computing
As large-scale molecular, environmental, and ecological data become more prevalent, biological inference is increasingly reliant on computational methods. Consequently, I have a deep methodological interest in bioinformatics, data science, and scientific software. This includes developing reproducible workflows for tasks such as sequence processing, variant discovery, population genomic analysis, and integrating diverse datasets. Reproducibility extends beyond statistical analysis itself, encompassing the organisation and preservation of raw data, metadata, reference resources, software environments, and the lineage of analyses. Therefore, I consider data architecture, workflow automation, version control, and reproducible computational environments to be integral components of the scientific method, rather than simply aspects of information technology. A computational analysis should not only reveal the results obtained, but also precisely document the specific observations, reference resources, transformations, software, and analytical decisions that led to those results.
Environmental data science
To understand adaptation, we must first describe the environments to which organisms are adapting. Today, we have environmental data at scales that were inconceivable when many foundational ecological studies were conducted. Technologies like remote sensing, geographical information systems, climate data, digital elevation models, land-cover datasets, hydrological information, and increasingly granular observations of human activities offer the chance to recreate the ecological context experienced by biological populations. My primary focus isn’t on environmental science as a standalone field, but rather on leveraging it to link organisms with their surroundings. This can involve environmental factors such as climate, hydrology, salinity, land cover, vegetation, farming methods, urban development, human and livestock presence, artificial light, and the spatial arrangement of aquatic habitats. Therefore, GIS and remote sensing serve as a crucial link between data collected on individual mosquitoes and ecological processes that unfold across entire landscapes.
Integrating organism and environment
The methodological direction that interests me most is ultimately integration.
An organism can be described simultaneously by its genome, transcriptome, physiology, morphology and behaviour. Its environment includes not only temperature, rainfall or land cover, but also individuals of its own species, interacting species, hosts, competitors, predators, pathogens and microbial associates. The distinction between these layers is analytically convenient but biologically artificial.
The longer-term objective is therefore to connect information across scales:
genome → phenotype → individual → population → community → landscape → epidemiological consequence
while preserving the uncertainties and causal assumptions involved in moving from one level to another. This requires biology, statistics, informatics and environmental science to interact rather than operate as independent disciplines. For me, these technologies and analytical approaches are not research objectives in themselves. They are instruments for answering the biological questions described above.
Natural history and earlier research
Ornithology
My entry into science preceded my work on mosquitoes and arose from an early fascination with vertebrate natural history, particularly birds. Although ornithology is no longer one of my principal research programmes, it remains part of my scientific background and an enduring personal interest. I have contributed observations and publications on both Western Palearctic and Afrotropical birds, including studies of the biology and distribution of the White-backed Woodpecker in the central Italian Apennines. Years of field work in tropical Africa have also provided many opportunities for opportunistic observations of the Afrotropical avifauna.
Natural history is sometimes treated as something separate from modern quantitative biology. I see it rather differently. Careful observation of organisms in their environment is often where worthwhile scientific questions begin.
A common thread
The subjects and technologies involved in my research have changed considerably over time: chromosomes have been complemented by genomes, field notebooks by large environmental datasets, conventional statistical models by hierarchical Bayesian approaches, and individual datasets by increasingly integrated computational systems.
The underlying questions, however, have changed much less. How do organisms respond to heterogeneous and changing environments? How does adaptive variation arise and persist despite gene flow? How do ecological differences become genetic, physiological and behavioural differences? How do those differences alter populations, species boundaries and interactions with other organisms? And, in the particular case of disease vectors: how do these evolutionary and ecological processes ultimately alter pathogen transmission?
Mosquitoes provide an exceptionally rich system in which to ask these questions—not because they are just organisms that transmit disease, but because their epidemiological relevance makes the consequences of their ecology and evolution extremely important.