Interactions with combined chemical cues inform harvester ant foragers' decisions to leave the nest in search of food.

Social insect colonies operate without central control or any global assessment of what needs to be done by workers. Colony organization arises from the responses of individuals to local cues. Red harvester ants (Pogonomyrmex barbatus) regulate foraging using interactions between returning and outgoing foragers. The rate at which foragers return with seeds, a measure of food availability, sets the rate at which outgoing foragers leave the nest on foraging trips. We used mimics to test whether outgoing foragers inside the nest respond to the odor of food, oleic acid, the odor of the forager itself, cuticular hydrocarbons, or a combination of both with increased foraging activity. We compared foraging activity, the rate at which foragers passed a line on a trail, before and after the addition of mimics. The combination of both odors, those of food and of foragers, is required to stimulate foraging. The addition of blank mimics, mimics coated with food odor alone, or mimics coated with forager odor alone did not increase foraging activity. We compared the rates at which foragers inside the nest interacted with other ants, blank mimics, and mimics coated with a combination of food and forager odor. Foragers inside the nest interacted more with mimics coated with combined forager/seed odors than with blank mimics, and these interactions had the same effect as those with other foragers. Outgoing foragers inside the nest entrance are stimulated to leave the nest in search of food by interacting with foragers returning with seeds. By using the combined odors of forager cuticular hydrocarbons and of seeds, the colony captures precise information, on the timescale of seconds, about the current availability of food

Using multilayer network analysis to explore the temporal dynamics of collective behavior

This work was supported by the National Science Foundation IOS grant 1456010 and the National Institute of Health grant GM115509 to N.P.-W.Peer reviewedPublisher PD

The use of multilayer network analysis in animal behaviour

Network analysis has driven key developments in research on animal behaviour by providing quantitative methods to study the social structures of animal groups and populations. A recent formalism, known as \emph{multilayer network analysis}, has advanced the study of multifaceted networked systems in many disciplines. It offers novel ways to study and quantify animal behaviour as connected 'layers' of interactions. In this article, we review common questions in animal behaviour that can be studied using a multilayer approach, and we link these questions to specific analyses. We outline the types of behavioural data and questions that may be suitable to study using multilayer network analysis. We detail several multilayer methods, which can provide new insights into questions about animal sociality at individual, group, population, and evolutionary levels of organisation. We give examples for how to implement multilayer methods to demonstrate how taking a multilayer approach can alter inferences about social structure and the positions of individuals within such a structure. Finally, we discuss caveats to undertaking multilayer network analysis in the study of animal social networks, and we call attention to methodological challenges for the application of these approaches. Our aim is to instigate the study of new questions about animal sociality using the new toolbox of multilayer network analysis.Comment: Thoroughly revised; title changed slightl

The impact of the built environment on health behaviours and disease transmission in social systems

The environment plays an important role in disease dynamics and in determining the health of individuals. Specifically, the built environment has a large impact on the prevention and containment of both chronic and infectious disease in humans and in non-human animals. The effects of the built environment on health can be direct, for example, by influencing environmental quality, or indirect by influencing behaviours that impact disease transmission and health. Furthermore, these impacts can happen at many scales, from the individual to the society, and from the design of the plates we eat from to the design of cities. In this paper, we review the ways that the built environment affects both the prevention and the containment of chronic and infectious disease. We bring examples from both human and animal societies and attempt to identify parallels and gaps between the study of humans and animals that can be capitalized on to advance the scope and perspective of research in each respective field. By consolidating this literature, we hope to highlight the importance of built structures in determining the complex dynamics of disease and in impacting the health behaviours of both humans and animals.This article is part of the theme issue 'Interdisciplinary approaches for uncovering the impacts of architecture on collective behaviour'

The use of multilayer network analysis in animal behaviour

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.We gratefully acknowledge the 806 supporters of MX16: the UC Davis Institute for Social Sciences, the U.S. Army Research Office 807 under Multidisciplinary University Research Initiative Award No. W911NF-13-1-0340, the UC 808 Davis Complexity Sciences Center, the UC Davis Anthropology Department, the UC Davis 809 Graduate Student Association, the UC Davis Department of Engineering, and the UC Davis 810 Office of Research.Network analysis has driven key developments in research on animal behaviour by providing quantitative methods to study the social structures of animal groups and populations. A recent formalism, known as multilayer network analysis, has advanced the study of multifaceted networked systems in many disciplines. It offers novel ways to study and quantify animal behaviour through connected ‘layers’ of interactions. In this article, we review common questions in animal behaviour that can be studied using a multilayer approach, and we link these questions to specific analyses. We outline the types of behavioural data and questions that may be suitable to study using multilayer network analysis. We detail several multilayer methods, which can provide new insights into questions about animal sociality at individual, group, population and evolutionary levels of organization. We give examples for how to implement multilayer methods to demonstrate how taking a multilayer approach can alter inferences about social structure and the positions of individuals within such a structure. Finally, we discuss caveats to undertaking multilayer network analysis in the study of animal social networks, and we call attention to methodological challenges for the application of these approaches. Our aim is to instigate the study of new questions about animal sociality using the new toolbox of multilayer network analysis.Natural Environment Research Council (NERC)National Science Foundation (NSF) Graduate Research FellowshipNFS IOS grantNIH R01NERC standard gran

Can multilayer networks advance animal behavior research?

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.Interactions among individual animals — and between these individuals and their environment — yield complex, multifaceted systems. The development of multilayer network analysis offers a promising new approach for studying animal social behavior and relating it to eco-evolutionary dynamics

Predicting the impacts of chemical pollutants on animal groups

Wildlife are exposed to an increasing number and diversity of chemical pollutants.Chemical pollutants can elicit a range of sublethal effects on individual organisms, but research on how these contaminants affect social interactions and animal groups is severely lacking.It is imperative that perspectives from behavioural ecology and ecotoxicology are integrated, to increase our understanding of how contaminant effects on individuals might cascade to group-level processes.We present a conceptual framework for researchers and practitioners to guide the study of how chemical pollutants might affect the emergence, organisation, and function of animal social groups.Chemical pollution is among the fastest-growing agents of global change. Synthetic chemicals with diverse modes-of-action are being detected in the tissues of wildlife and pervade entire food webs. Although such pollutants can elicit a range of sublethal effects on individual organisms, research on how chemical pollutants affect animal groups is severely lacking. Here we synthesise research from two related, but largely segregated fields – ecotoxicology and behavioural ecology – to examine pathways by which chemical contaminants could disrupt processes that govern the emergence, self-organisation, and collective function of animal groups. Our review provides a roadmap for prioritising the study of chemical pollutants within the context of sociality and highlights important methodological advancements for future research