Theron, F. | Search bioRxiv

bioRxiv2026

Sex-specific Flexibility in Breeding and Helping Strategies in the Sociable Weaver (Philetairus socius)

Helping-at-the-nest is often viewed as a precursor to reproduction, but switching between breeder and helper roles has been documented in some species. Such flexibility should depend on the opportunities and benefits of helping, which could differ between sexes due to dispersal strategies and social structure. However, whether breeding-helping flexibility is widespread and sex-specific remains unknown. Here, we investigated sex-specific strategies in breeding-helping flexibility using a 10-year dataset (1955 individuals) on sociable weavers (Philetairus socius), a colonial cooperative breeder in which males are typically philopatric whereas females disperse. Both sexes helped for several years, with males helping more frequently than females and for twice as long (0-13 vs 0-10 years). Around 40% of non-dispersing birds never became breeders and 50% of individuals bred without helping first. Both sexes switched roles between- and within-seasons but males were more likely to alternate (respectively four and six times more than females and up 15 switches across seven years). Our study reveals important flexibility and sex differences in breeder-helper roles, consistent with sex-biased dispersal, spatial breeding proximity and possible indirect fitness benefits. These factors could play a role promoting the evolution of helping across life-stages, not only pre-reproduction, but also reproductive and post-reproductive individuals.

evolutionary biology↗

bioRxiv2019

How to make methodological decisions when inferring social networks

Constructing and analysing social networks data can be challenging. When designing new studies, researchers are confronted with having to make decisions about how data are collected and networks are constructed, and the answers are not always straightforward. The current lack of guidance on building a social network for a new study system might lead researchers to try several different methods, and risk generating false results arising from multiple hypotheses testing. We suggest an approach for making decisions when developing a network without jeopardising the validity of future hypothesis tests. We argue that choosing the best edge definition for a network can be made using a priori knowledge of the species, and testing hypotheses that are known and independent from those that the network will ultimately be used to evaluate. We illustrate this approach by conducting a pilot study with the aim of identifying how to construct a social network for colonies of cooperatively breeding sociable weavers. We first identified two ways of collecting data using different numbers of feeders and three ways to define associations among birds. We then identified which combination of data collection and association definition maximised (i) the assortment of individuals into breeding groups (birds that contribute towards the same nest and maintain cohesion when foraging), and (ii) socially differentiated relationships (more strong and weak relationships than expected by chance). Our approach highlights how existing knowledge about a system can be used to help navigate the myriad of methodological decisions about data collection and network inference.\n\nSIGNIFICANCE STATEMENTGeneral guidance on how to analyse social networks has been provided in recent papers. However less attention has been given to system-specific methodological decisions when designing new studies, specifically on how data are collected, and how edge weights are defined from the collected data. This lack of guidance can lead researchers into being less critical about their study design and making arbitrary decisions or trying several different methods driven by a given preferred hypothesis of interest without realising the consequences of such approaches. Here we show that pilot studies combined with a priori knowledge of the study species social behaviour can greatly facilitate making methodological decisions. Furthermore, we empirically show that different decisions, even if data are collected under the same context (e.g. foraging), can affect the quality of a network.

animal behavior and cognition↗