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Direct observation of foraging behavior is not always possible, especially for marine species that hunt underwater. However, biologging and tracking devices have provided detailed information about how various species use their habitat. From these indirect observations, researchers have inferred behaviors to address a variety of research questions, including the definition of ecological niches. In this study, we deployed video cameras with GPS and time-depth recorders on 16 chinstrap penguins (Pygoscelis antarcticus) during the brood phase of the 2018–2019 breeding season on Signy (South Orkney Islands). More than 57 h of footage covering 770 dives were scrutinized by two observers. The outcome of each dive was classified as either no krill encounter, individual krill or krill swarm encounter and the number of prey items caught per dive was estimated. Other variables derived from the logging devices or from the environment were used to train a machine-learning algorithm to predict the outcome of each dive. Our results show that despite some limitations, the data collected from the footage was reliable. We also demonstrate that it was possible to accurately predict the outcome of each dive from dive and horizontal movement variables in a manner that has not been used for penguins previously. For example, our models show that a fast dive ascent rate and a high density of dives are good indicators of krill and especially of swarm encounter. Finally, we discuss how video footage can help build accurate habitat models to provide wider knowledge about predator behavior or prey distribution.

1. The social decisions that individuals make—who to interact with and how frequently—gives rise to social structure. The resulting social structure then determines how individuals interact with their surroundings—resources and risks, pathogens and predators, competitors and cooperators. 2. However, despite intensive research on (i) how individuals make social decisions and (ii) how social structure shapes social processes (e.g. cooperation, competition and conflict), there are still few studies linking these two perspectives. These perspectives represent two halves of a feedback loop: individual behaviour scales up to define the social environment, and this environment, in turn, feeds back by shaping the selective agents that drive individual behaviour. 3. We first review well-established research areas that have captured both elements of this feedback loop—host-pathogen dynamics and cultural transmission. We then highlight areas where social structure is well studied but the two perspectives remain largely disconnected. Finally, we synthesise existing research on 14 distinct research topics to identify new prospects where the interplay between social structure and social processes are likely to be important but remain largely unexplored. 4. Our review shows that the inherent links between individuals’ traits, their social decisions, social structure, and social evolution, warrant more consideration. By mapping the existing and missing connections among many research areas, our review highlights where explicitly considering social structure and the individual-to-society feedbacks can reveal new dimensions to old questions in ecology and evolution.

Predators and prey are locked in an evolutionary arms race that shapes their behavior and life history. Predators target prey vulnerabilities to maximize hunting success, while prey trade-off foraging against predation avoidance. Though studies have demonstrated how predation risk can alter how prey allocate daily foraging effort, little work has considered the implications of this temporal component of behavior from a predator’s perspective, or assessed its influence on broad-scale predator–prey interactions. We develop a method to compare daily activity patterns of avian predators and prey using data from 2 large citizen science datasets collected on different continents. Our analyses reveal evidence for convergent daily hunting strategies across avian predators, with distinct differences according to prey type. By comparing predator data with correspondent data from songbirds, our study suggests that predators (Accipiters) specialized to hunt songbirds match the activity patterns of their prey species. These results indicate predators have evolved common temporal hunting strategies to exploit temporal patterns in prey behavior. published

Social predation—the act of hunting and feeding with others—is one of the most successful life-history traits in the animal kingdom. Although many predators hunt and feed together, a diversity of mechanisms exist by which individuals forage socially. However, a comprehensive framework capturing this diversity is lacking, preventing us from better understanding cooperative forms of predation, and how such behaviours have evolved and been maintained over time. We outline a framework of social predation that describes five key behavioural dimensions: sociality, communication, specialization, resource sharing, and dependence. By reviewing examples of social predation, we demonstrate the strength of a multidimensional approach, highlighting key commonalities and differences among species, and informative cross-dimensional correlations. These patterns highlight different potential evolutionary pathways and end-points across a multidimensional social predation spectrum. Hunting in groups allows predators to forage more efficiently. Here, the authors outline a framework for evaluating social predation strategies according to five key behavioural dimensions.

Animals need to manage the combined risks of predation and starvation in order to survive. Theoretical and empirical studies have shown that individuals can reduce predation risk by delaying feeding (and hence fat storage) until late afternoon. However, little is known about how individuals manage the opposing pressures of resource uncertainty and predation risks. We suggest that individuals should follow a two-part strategy: prioritizing the discovery of food early in the day and exploiting the best patch late in the day. Using automated data loggers, we tested whether a temporal component exists in the discovery of novel foraging locations by individuals in a mixed-species foraging guild. We found that food deployed in the morning was discovered significantly more often than food deployed in the afternoon. Based on the diurnal activity patterns in this population, overall rates of new arrivals were also significantly higher than expected in the morning and significantly lower than expected in the afternoon. These results align with our predictions of a shift from patch discovery to exploitation over the course of the day.