There are astonishing differences in whether, how, and how long for, animals care for their offspring. In most species, such as many marine fishes, parents abandon their fertilized eggs to their own destiny, which is mostly being eaten by predators. Conversely, parents of other species provide protection and resources to their offspring. While parental care increases offspring survival, it also comes at considerable costs for the parents because resources and time are limited. Once evolved, not only does care affect the fitness of parents and offspring, but it also alters life history strategies, is related to sexual selection and mating system, leads to cooperation and conflict within the family, and promotes the evolution of sociality. Yet, we know very little about when care evolves and its knock-on effects on species reproduction, population dynamics and extinction risk.
Following our successful approach focusing on diversity in parental care [1,2], this project combines state-of-the-art phylogenetic comparative approaches, datasets of parental care behaviours for hundreds of vertebrate species, and cutting-edge evolutionary modelling, to:
(i) Investigate which ecological conditions promote the evolution of care diversity;
(ii) Unravel how reproductive traits co-evolve with different care forms;
(iii) Evaluate how care diversity influences population trends and extinction risk.
The student will have the opportunity to shape the project by deciding the extent of theoretical modelling vs empirical analyses; selecting the model groups; expanding or reducing the components as best suited to their interests.
The student will be trained on data collection, data management, numeracy, statistical analyses, specifically:
i. Assemble accurate datasets on parental care diversity, ecological and reproductive traits, population trends and extinction risk for hundreds of species, using published data;
ii. Test theoretical predictions with phylogenetic comparative approaches in R and BayesTraits;
iii. Derive quantitative predictions with evolutionary modelling to guide the empirical analyses.
Essential skills: the ideal candidate will hold a first-class degree in biology, ecology, zoology or related discipline; have very strong quantitative skills, outstanding organisational skills, excellent attention to detail, knowledge of phylogenetic methods.