Kalahari skinks eavesdrop on sociable weavers to manage predation by pygmy falcons and expand their realized niche

Eavesdropping on community members has immediate and clear benefits. However, little is known regarding its importance for the organization of cross-taxa community structure. Furthermore, the possibility that eavesdropping could allow species to coexist with a predator and access risky foraging habitat, thereby expanding their realized niche, has been little considered. Kalahari tree skinks (Trachylepis spilogaster) associate with sociable weaver (Philetairus socius) colonies as do African pygmy falcons (Polihierax semitorquatus), a predator of skinks and weavers. We undertook observational and experimental tests to determine if skinks eavesdrop on sociable weavers to mitigate any increase in predation threat that associating with weaver colonies may bring. Observations reveal that skinks use information from weavers to determine when predators are nearby; skinks were more active, more likely to forage in riskier habitats, and initiated flight from predators earlier in the presence of weavers compared with when weavers were absent. Playback of weaver alarm calls caused skinks to increase vigilance and flee, confirming that skinks eavesdrop on weavers. Furthermore, skinks at sociable weaver colonies were more likely to flee than skinks at noncolony trees, suggesting that learning is mechanistically important for eavesdropping behavior. Overall, it appears that eavesdropping allows skinks at colony trees to gain an early warning signal of potential predators, expand their realized niche, and join communities, whose predators may otherwise exclude them.

How to make methodological decisions when inferring social networks

ABSTRACTConstructing 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.SIGNIFICANCE 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.