Diel patterns of movement reveal temporal strategies during dispersal

Movement is a key part of life for many animals. However, a number of temporal constraints, from changes in light and temperature to varying risks of predation, limit not only where animals can move, but also when. Such constraints are likely to be most pronounced when animals must make large displacements, as is the case when individuals disperse. However, little is known about how dispersers overcome temporal constraints on movement, despite significant implications for the success of dispersal. We outline a general framework for identifying the strategies animals use to achieve large displacements in the face of constraints on when and how to move, which we predict should follow one of three patterns: increasing their movements during those times when they typically move more, uniformly across the day, or when they previously moved least. Using high-resolution GPS tracking of dispersing and resident vulturine guineafowl, Acryllium vulturinum, we show that dispersers expressed the greatest increases in movement at the same times of day that they moved most prior to dispersing. Our results suggest that individuals face the same ecological constraints during dispersal as they do in daily life and achieve large displacements by maximizing movement when conditions are most favourable.publishe

A guide to sampling design for GPS‐based studies of animal societies

GPS-based tracking is widely used for studying wild social animals. Much like traditional observational methods, using GPS devices requires making a number of decisions about sampling that can affect the robustness of a study's conclusions. For example, sampling fewer individuals per group across more distinct social groups may not be sufficient to infer group- or subgroup-level behaviours, while sampling more individuals per group across fewer groups limits the ability to draw conclusions about populations. Here, we provide quantitative recommendations when designing GPS-based tracking studies of animal societies. We focus on the trade-offs between three fundamental axes of sampling effort: (1) sampling coverage—the number and allocation of GPS devices among individuals in one or more social groups; (2) sampling duration—the total amount of time over which devices collect data and (3) sampling frequency—the temporal resolution at which GPS devices record data. We first test GPS tags under field conditions to quantify how these aspects of sampling design can affect both GPS accuracy (error in absolute positional estimates) and GPS precision (error in the estimate relative position of two individuals), demonstrating that GPS error can have profound effects when inferring distances between individuals. We then use data from whole-group tracked vulturine guineafowl Acryllium vulturinum to demonstrate how the trade-off between sampling frequency and sampling duration can impact inferences of social interactions and to quantify how sampling coverage can affect common measures of social behaviour in animal groups, identifying which types of measures are more or less robust to lower coverage of individuals. Finally, we use data-informed simulations to extend insights across groups of different sizes and cohesiveness. Based on our results, we are able to offer a range of recommendations on GPS sampling strategies to address research questions across social organizational scales and social systems—from group movement to social network structure and collective decision-making. Our study provides practical advice for empiricists to navigate their decision-making processes when designing GPS-based field studies of animal social behaviours, and highlights the importance of identifying the optimal deployment decisions for drawing informative and robust conclusions

Machine learning reveals cryptic dialects that explain mate choice in a songbird

Culturally transmitted communication signals – such as human language or bird song – can change over time through cultural drift, and the resulting dialects may consequently enhance the separation of populations. However, the emergence of song dialects has been considered unlikely when songs are highly individual-specific, as in the zebra finch (Taeniopygia guttata). Here we show that machine learning can nevertheless distinguish the songs from multiple captive zebra finch populations with remarkable precision, and that ‘cryptic song dialects’ predict strong assortative mating in this species. We examine mating patterns across three consecutive generations using captive populations that have evolved in isolation for about 100 generations. We cross-fostered eggs within and between these populations and used an automated barcode tracking system to quantify social interactions. We find that females preferentially pair with males whose song resembles that of the females’ adolescent peers. Our study shows evidence that in zebra finches, a model species for song learning, individuals are sensitive to differences in song that have hitherto remained unnoticed by researchers

Movement strategies for large-scale displacements in Vulturine guineafowl (Acryllium vulturinum)

Dispersal—the process by which individuals depart their natal range, transit through the environment, and settle into new areas—is one of the most fundamental and pervasive life history phases in the animal kingdom. Typically, dispersal is motivated by individuals’ need to avoiding breeding—and competing—with kin, or to secure access to the resources necessary to reproduce. In order to reap the benefits of dispersing, individuals often have to travel large distances—a process which can be subject to constraints on behavior and impose significant physiological costs. For dispersal to retain its adaptive value, selection should therefore favor behaviors which mitigate the costs of dispersing. In this thesis, I aimed to understand how the behavior of dispersing animals reflects the costs that they face in making such large movements, with the ultimate goal of understanding the strategies that have evolved to overcome these costs.Much of the study of dispersal to date has focused on individuals’ decisions to depart or settle in a given area. By contrast, there has been relatively little attention paid to the movements of transient individuals, despite transience being the active component of dispersal, and encompassing many of its associated behaviors. Many of the greatest barriers to successful dispersal are thought to be most present during this active stage, from increased risks of predation, to energy use, to navigational challenges. By investigating not only where, but how and when dispersers move while transient, research into this critical stage of dispersal will prove key to understanding how animals respond to these costs. However, studying transience behaviors is a particularly difficult endeavor, not only because of the challenge of tracking dispersing individuals, but also because of the need to establish a meaningful frame of reference against which to evaluate these behaviors. In this thesis, I studied the dispersal movements of transient animals through the use of high-resolution GPS tracking devices deployed in a wild population of free ranging vulturine guineafowl (Acryllium vulturinum) in Laikipia county, Kenya. In each of my chapters, I examined the changes in movement behaviors exhibited by transient individuals, and drew inferences about the strategies that they express by making direct comparisons between dispersing individuals’ behavior across different stages, and between dispersing and non-dispersing birds in similar time frames.In my first chapter, I integrated high-resolution GPS data with physiological models of the metabolic costs of movement to test a long-standing hypothesis that dispersal should be an energetically-costly endeavor given the distances that dispersers traverse. I hypothesized that such costs are result of 4 how animals move, and not only how far. My results show that dispersing animals are able to substantially increase the energetic efficiency of their movements during their transience period, primarily as a result of distinct changes in the speed and straightness of their movements.In my second chapter, I further examined the fine-scale changes in how dispersing animals move, using their diel patterns of movement as lens into the ways that ecological constraints affect when and how they move. A wide array of ecological constraints, from predation risks to elevated temperatures, can limit animals’ movements, resulting in distinct diel cycles with peaks and valleys in activity. I first proposed a general framework to help make inference about how animals might respond to constraints on movement, and predicted three possible patterns of correlation between the timing of dispersers’ normal movements and when they make the largest movements during dispersal. My results show that guineafowl express a positive correlation between the times when they typically move most, and the hours when they make the largest increases in their movement, suggesting that the ecological effects that constrain their movements outside of dispersal persist during transience.Finally, in my third chapter, I built upon the findings of chapter one by using the efficient movements of dispersing animals as a lens through which to re-examine the costs of movement in group-living animals. By extracting the largest movements made by groups, and comparing them to the highly-efficient movements of lone dispersers, I was able to test whether individuals’ capacity for efficient movements is constrained when moving as part of a collective. I found that individuals in groups are able to increase the energetic efficiency of their movements when making large collective movements, but that the scale of this increase is substantially less than that achieved by lone individuals, revealing a previously hidden cost of group living. These results also further highlight the strength of selection for efficient movement during dispersal.Together, these three chapters form the basis for a for a new understanding of the factors driving the evolution of strategies that allow animals to achieve extraordinary, landscape-scale movements, and the fine-scale, moment-by-moment behaviors that animals express in the face of significant energetic, environmental, and social constraints.publishe

Efficient movement strategies mitigate the energetic cost of dispersal

Dispersal is a critical, but costly, stage of life. During the active phase of dispersal—called transience—individuals face many costs, from increased mortality to reduced foraging opportunities. One cost that is often assumed, but rarely explicitly tested, is the energy expended in making large dispersal movements. However, this cost is not only determined by the distance individual’s move, but also how they move. Using high‐resolution GPS tracking of dispersing and resident vulturine guineafowl (Acryllium vulturinum), we show that transient individuals exhibit distinct movement behaviours—travelling farther, faster and straighter—that result in a significant reduction in the energetic costs of making large displacements. This strategy allows dispersing birds to travel, on average, 33.8% farther each day with only a 4.1% cost increase and without spending more time moving. Our study suggests that adaptive movement strategies can largely mitigate movement costs during dispersal, and that such strategies may be common.publishe

A guide to sampling design for GPS-based studies of animal societies

1. GPS-based tracking is widely used for studying wild social animals. Much like traditional observational methods, using GPS devices requires making a number of decisions about sampling that can affect the robustness of a study's conclusions. For example, sampling fewer individuals per group across more distinct social groups may not be sufficient to infer group- or subgroup-level behaviours, while sampling more individuals per group across fewer groups limits the ability to draw conclusions about populations.2. Here, we provide quantitative recommendations when designing GPS-based tracking studies of animal societies. We focus on the trade-offs between three fundamental axes of sampling effort: (1) sampling coverage—the number and allocation of GPS devices among individuals in one or more social groups; (2) sampling duration—the total amount of time over which devices collect data and (3) sampling frequency—the temporal resolution at which GPS devices record data.3. We first test GPS tags under field conditions to quantify how these aspects of sampling design can affect both GPS accuracy (error in absolute positional estimates) and GPS precision (error in the estimate relative position of two individuals), demonstrating that GPS error can have profound effects when inferring distances between individuals. We then use data from whole-group tracked vulturine guineafowl Acryllium vulturinum to demonstrate how the trade-off between sampling frequency and sampling duration can impact inferences of social interactions and to quantify how sampling coverage can affect common measures of social behaviour in animal groups, identifying which types of measures are more or less robust to lower coverage of individuals. Finally, we use data-informed simulations to extend insights across groups of different sizes and cohesiveness.4. Based on our results, we are able to offer a range of recommendations on GPS sampling strategies to address research questions across social organizational scales and social systems—from group movement to social network structure and collective decision-making.5. Our study provides practical advice for empiricists to navigate their decision-making processes when designing GPS-based field studies of animal social behaviours, and highlights the importance of identifying the optimal deployment decisions for drawing informative and robust conclusions.publishe

Un sistema de seguimiento de códigos de barras automatizado para estudios de comportamiento en aves

Los recientes avances en tecnología permiten a los investigadores automatizar la medición del comportamiento animal. Estos métodos tienen múltiples ventajas sobre las observaciones directas y la entrada manual de datos, ya que reducen el sesgo relacionado con la percepción humana y la fatiga, y brindan conjuntos de datos más extensos y completos que mejoran el poder estadístico. Un desafío importante que la automatización puede superar es la observación de muchos individuos a la vez, lo que permite el seguimiento de todo el grupo o de toda la población.Recent advances in technology allow researchers to automate the measurement of animal behavior. These methods have multiple advantages over direct observations and manual data entry, reducing bias related to human perception and fatigue, and providing larger and more comprehensive data sets that improve statistical power. A major challenge that automation can overcome is the observation of many individuals at once, allowing the monitoring of the entire group or the entire population

Un sistema de seguimiento de códigos de barras automatizado para estudios de comportamiento en aves

Los recientes avances en tecnología permiten a los investigadores automatizar la medición del comportamiento animal. Estos métodos tienen múltiples ventajas sobre las observaciones directas y la entrada manual de datos, ya que reducen el sesgo relacionado con la percepción humana y la fatiga, y brindan conjuntos de datos más extensos y completos que mejoran el poder estadístico. Un desafío importante que la automatización puede superar es la observación de muchos individuos a la vez, lo que permite el seguimiento de todo el grupo o de toda la población.Recent advances in technology allow researchers to automate the measurement of animal behavior. These methods have multiple advantages over direct observations and manual data entry, reducing bias related to human perception and fatigue, and providing larger and more comprehensive data sets that improve statistical power. A major challenge that automation can overcome is the observation of many individuals at once, allowing the monitoring of the entire group or the entire population

Redes sociales animales: revelando las causas e implicaciones de la estructura social en la ecología y la evolución

The social decisions that individuals make, in terms of where to move, who to interact with and how frequently, scale up to generate social structure. Such structure has profound consequences: individuals each have a unique social environment, social interactions can amplify or dampen individual differences at the population level, and population-level ecological and evolutionary processes can be governed by higher-level ‘emergent properties’ of animal societies