Biological systems are shaped by interactions that unfold over time, across scales, and under continual feedback between organisms and their environments. The patterns we observe—whether stable ecosystems, rapid diversification, cultural traditions, or disease outbreaks—are the result of processes that are historically contingent, nonlinear, and often counterintuitive. Understanding such systems requires more than describing individual components; it requires identifying the mechanisms that govern how interactions generate collective outcomes.

Research in my lab focuses on these general mechanisms across ecological and evolutionary contexts. Rather than specialising in a single organism or process, we ask how diversity is generated and maintained, when interactions stabilise or destabilise systems, how information is transmitted within and between populations, and how evolutionary conflicts shape ecological dynamics. Much of our work uses mathematical and computational models, alongside empirical data, as tools to clarify assumptions, test intuition, and uncover structure in complex biological systems.

Diversity and Stability

Understanding the mechanisms that shape the diversity and stability of ecosystems is a central goal of ecology. Although diversity and stability have long been thought to be linked, the mechanisms underlying this relationship remain only partly understood, and empirical patterns often diverge from theoretical expectations. My lab uses mathematical and computational models to explore how biological diversity arises, and how diversity can stabilise—or in some cases destabilise—ecological systems.

Selected papers:

Gilman RT, Muldoon MR, Megremis S, Robertson DL, Chanishvili N, Papadopoulos NG. (2024) Lysogeny destabilizes computationally simulated microbiomes. Ecology Letters 27:e14464.

Gilman RT and Kozak GM. (2015) Learning to speciate: the biased learning of mate preferences promotes adaptive radiation. Evolution, 69(11):3004-3012.

Gilman RT, Nuismer SL and Jhwueng D. (2012) Coevolution in multidimensional trait space favors escape from parasites and pathogens. Nature, 483:328-330.

Speciation

The process of speciation is critical to the generation and maintenance of biodiversity. Why speciation occurs can be especially perplexing in sexually reproducing populations that are not spatially or temporally isolated, where gene flow during mating should oppose divergence. Nonetheless, some of the most striking adaptive radiations (e.g., Rift Lake cichlids) have occurred under exactly these conditions. My lab combines mathematical models and empirical data to understand how speciation can evolve despite gene flow, and how behavioural, environmental, or cultural change can interrupt or even reverse divergence.

Selected papers:

*Caspani G, Fujii TG, Mizuhara T, Gilman RT, Okanoya K. (2020) Biased learning of sexual signals by female Bengalese finches. Ornithological Science, 19(1):3-14.

Gilman RT, Fowler-Finn KD and Hebets EA. (2018) A probable case of incipient speciation in Schizocosa wolf spiders driven by allochrony, habitat use and female mate choice. The American Naturalist, 192(3):332-346.

Gilman RT and Kozak GM. (2015) Learning to speciate: the biased learning of mate preferences promotes adaptive radiation. Evolution, 69(11):3004-3012.

Gilman RT and Behm JE. (2011) Hybridization, species collapse, and species reemergence after disturbance to premating mechanisms of reproductive isolation.  Evolution, 65(9):2592-2605.

Cooper IA, Gilman RT and Boughman JW. (2011) Sexual dimorphism and speciation on two ecological coins: patterns from nature and theoretical predictions. Evolution, 65(9):2553-2571.

Information Flow

The flow of information is a central feature of biological systems. Replication requires the transmission of information across generations, but information can also be exchanged among individuals, including competitors and social partners. How such information transfer evolves, and what forms it takes, are open questions with broad implications for behaviour and population dynamics.

Birdsong provides a particularly tractable system for studying these questions. Birds exhibit extraordinary diversity in song structure, yet share common constraints and patterns across species. Despite decades of study, we still have only a limited understanding of what information birdsong conveys and which properties of song encode that information. My lab combines mathematical models with empirical data to study how social information evolves, how birdsong is structured and transmitted across generations, and how maintaining song traditions may influence conservation outcomes.

Selected papers:

*Jepson O, Gilman RT, Williams L, Lewis RN. (2025) Shifting syllable production in an ex situ population of a critically endangered songbird. Zoo Biology.

Gilman RT, *Durrant CD, *Malpas L, Lewis RN. (2025) Does Zipf’s law of abbreviation shape birdsong? PLoS Computational Biology.

Lewis RN, Kwong A, Soma M, de Kort SR, Gilman RT. (2023) Inheritance of temporal song features in Java sparrows. Animal Behaviour, 206:61-74.

Lewis RN, Soma M, de Kort SR, Gilman RT (2021) Like father like son: Cultural and genetic contributions to song inheritance in an estrildid finch. Frontiers in Psychology 12, 2030.

Richardson T, *Waddington M, Gilman RT. (2021) Young, formidable men show greater sensitivity to facial cues of dominance. Evolution and Human Behavior, 42(1):43-50.

Lewis RN, Williams LJ, Gilman RT. (2021) The uses and implications of avian vocalizations for conservation planning. Conservation Biology, 35(1):50-63.

Gilman RT, *Johnson F, Smolla M. (2020) Competition for resources can promote the divergence of social learning phenotypes. Proceedings of the Royal Society B – Biological Sciences, 287:20192770.

*Caspani G, Fujii TG, Mizuhara T, Gilman RT, Okanoya K. (2020) Biased learning of sexual signals by female Bengalese finches. Ornithological Science, 19(1):3-14.

Smolla M, *Rosher C, Gilman RT, Shultz S. (2019) Reproductive skew affects social information use. Royal Society Open Science, 6(7), 182084.

*Invernizzi E and Gilman RT. (2015) The evolution of sexual imprinting in socially monogamous populations. Current Zoology, 61(6):1043-1061.

Smolla M, Gilman RT, Galla T and Shultz S. (2015) Competition for resources can explain patterns of social and individual learning in nature. Proceedings of the Royal Society B – Biological Sciences, 282:20151405.

*Chaffee DW, *Griffin H and Gilman RT. (2013) Sexual imprinting: what strategies should we expect to see in nature? Evolution, 67(12):3588-3599.

Disease Ecology

Pathogens play a key role in shaping ecological and evolutionary dynamics. Disease systems are fascinating because they involve conflicting selective pressures: pathogens must spread to persist, while hosts maximise fitness by limiting that spread. My lab uses mathematical and computational models to explore how these conflicts influence ecosystem diversity and stability, and the conditions under which pathogens may evolve reduced virulence or even mutualistic interactions with their hosts. We have applied these modelsto predict disease spread and evaluate interventions fpor disease comntrol in human populaions. We are currently extending this work using empirical data to understand zoonotic vector-borne disease dynamics may respond to anthropogenic environmental change. 

Selected papers:

Gilman RT, Muldoon MR, Megremis S, Robertson DL, Chanishvili N, Papadopoulos NG. (2024) Lysogeny destabilizes computationally simulated microbiomes. Ecology Letters 27:e14464.

Aylett-Bullock J, Gilman RT, Hall I, et al (2022) Epidemiological modelling in refugee and internally displaced people settlements: challenges and ways forward. BMJ Global Health, 7:e007822.

Gilman RT, Mahroof-Shaffi S, Harkensee C, Chamberlain AT (2020) Modelling interventions to control COVID-19 outbreaks in a refugee camp. BMJ Global Health, 5:e003727.

Gilman RT, Nuismer SL and Jhwueng D. (2012) Coevolution in multidimensional trait space favors escape from parasites and pathogens. Nature, 483:328-330.

(Note: Bold face in author lists indicates members of the lab. * indicates undergraduate authors. Some papers bridge research areas and thus appear in more than one setion.)