Topic: Learning and the evolution of oviposition behaviour in an agricultural pest: implications for the sustainability of agroecological strategies.
Dates: 1 October 2026 – 30 September 2029
CBGP supervisor: B. Facon
The agroecological transition in agriculture involves a drastic reduction in the use of synthetic pesticides and promotes the development of alternative methods based on manipulating the biological and behavioural characteristics of pests. Among these, semiochemical strategies (trap plants, push-pull strategies, attractants and repellents) directly target the oviposition behaviour of plant-feeding insects. However, the sustainability of these methods remains uncertain, particularly due to the potential for pests to adapt through behavioural plasticity and genetic evolution.
Oviposition behaviour, which determines the choice of egg-laying site by females, is a key trait in the selective value of insects and a central driver of crop damage. This behaviour is particularly susceptible to learning, a form of phenotypic plasticity that allows preferences to be modified in response to individual experience. Whilst learning may promote rapid short-term adaptation, its role in long-term evolutionary dynamics — by slowing down, accelerating or neutralising genetic adaptation — remains a subject of considerable debate.
This thesis aims to analyse the interaction between learning and the genetic evolution of oviposition behaviour in the context of agroecological pest management. The Mediterranean fruit fly, Ceratitis capitata, will be used as a biological model, owing to its significant agronomic importance and high behavioural plasticity. The project will combine learning experiments and evolutionary experiments under controlled conditions.
This thesis will characterise the mechanisms underlying oviposition learning (the nature of visual and olfactory cues, the duration and persistence of memory, and the role of positive or negative experiences) using artificial oviposition substrates and innovative phenotyping tools. Artificial selection experiments spanning several generations will then test how learning influences the rate and direction of genetic evolution of oviposition preferences, in interaction with different environmental conditions. The expected results will provide an original conceptual and methodological framework for assessing the risk of pests adapting their behaviour to alternative methods to pesticides. This thesis will thus contribute to improving the design and deployment of more sustainable crop protection strategies, by explicitly incorporating the evolutionary and plastic dimensions of pests.
