Many biological systems, from flocks of birds, swarms of locusts, shoals of fish, to crowds of humans show collective behaviours which are emergent properties that manifest only at the level of a group. In each of these cases, local, individual-level interactions give rise to highly coordinated and synchronized emergent patterns that are observable at the group level. Theoretical, computational, and empirical research in this field have been used to address questions about various aspects of collective behaviour, from characterizing its structural and dynamical properties to deciphering how the individual behaviour produces emergent group patterns. However, most of these studies examine the group-level properties in terms of their mean values and do not attempt to characterize the variability present in the collective properties which arise due to the stochastic fluctuations. In real groups, stochastic fluctuations in the group-level properties arise due to the probabilistic interactions between finite number of individuals. As a result, this intrinsic noise present in collective systems can produce non-intuitive and non-trivial behaviours. Real groups in finite space will likely have some interaction with the boundary, and the observed collective dynamics may also include effects of interaction with the boundary. To gain comprehensive understanding of collective dynamics in real groups, examining the effect of interaction with the boundary is necessary. However, whether boundary interactions confound analyses of inferred interaction rules have not been investigated rigorously. In the current study, we examine how the parameters of the boundary conditions affect the simulated collective dynamics. We performed stochastic simulations of two data-inspired spatial models developed by Jhawar et al. that have contrasting collective properties: (i) where individuals show pairwise interactions and collective order is driven stochastically (ii) where individuals show ternary interactions and collective order is driven deterministically. We characterize intrinsic noise in the data generated from the simulations and examine the susceptibility of the results to the presence of boundary. In these data-inspired spatial models, we show that the essential features of the group-level dynamics obtained from the simulated time-series do not change because of boundary interactions. Furthermore, our inference of local interactions also remains unaffected by the boundary conditions – at least within the model framework and the context we investigated, which were parameterized to the experimental conditions of our laboratory.

Schools of fish and flocks of birds display an impressive variety of collective movement patterns that emerge from local interactions among group members. These collective phenomena raise a variety of questions about the interactions rules that govern the coordination of individuals’ motions and the emergence of large-scale patterns. While numerous models have been proposed, there is still a strong need for detailed experimental studies to foster the biological understanding of such collective motion phenomena. I will first describe the methods that we developed in the recent years to characterize social interactions between individuals involved in the coordination of swimming in groups of Rummy-nose tetra (Hemigrammus rhodostomus) from data gathered at the individual scale. This species of tropical fish performs burst-and-coast swimming behavior that consists of sudden heading changes combined with brief accelerations followed by quasi-passive, straight decelerations. Our results show that both attraction and alignment behaviors control the reaction of fish to a neighbor. Then I will present how these results can be used to build a model of spontaneous burst-and-coast swimming and social interactions of fish, with all parameters being estimated or directly measured from experiments. This model shows that the simple addition of the pairwise interactions with two neighbors quantitatively reproduces the collective behavior observed in groups of fish. Increasing the number of interacting neighbors does not significantly improve the simulation results. Remarkably, and even without confinement, we find that groups remain cohesive and polarized when each fish interacts with only one of its neighbors: the one that has the strongest contribution to the heading variation of the focal fish, dubbed as the “most influential neighbor". Overall, our results suggest that fish avoid information overload when they move in large groups since individuals only have to acquire a minimal amount of information about the behavior of their neighbors for coordinating their movements.

Mutualisms are known to play a variety of roles in structuring communities and ecosystems. While obligate mutualisms can irreplaceably shape community composition, facultative mutualisms can also play a variety of roles such as in aiding recovery from stressful conditions, accelerating ecosystem processes and modulating the balance between multiple ecosystem processes. Ant-Hemipteran mutualisms are largely facultative, food-reward/protection-driven mutualisms in which ants “tend” many species of insects across unrelated groups of the order Hemiptera including aphids, scale insects, treehoppers and leaf-footed bugs. Honeydew, the excreted product of sap consumption by Hemipterans, is the food-reward to ants in exchange for reduced predation pressure arising from close proximity with ants. The widely context-variant mechanisms and outcomes involved have been well-elucidated in smaller-scale studies of a few species at a time. However, much less is known about the overall diversity of these mutualisms at a single site, and how this diversity impacts their functioning. This is expected to matter in many natural settings, as most species involved are generalists, each interacting with a diverse suite of partners.

I will investigate the patterns and processes structuring ant-Hemipteran mutualisms at a landscape scale across three land use types - grasslands, forests and heavily-logged forests, within Sonai-Rupai Wildlife Sanctuary in Assam. In my first Chapter, I will examine participation in mutualisms by comparing patterns of ant-Hemipteran-host plant networks across the three habitats. I will also consider what can be inferred about the processes shaping participation from the structure of interaction networks alone. In Chapter 2, I will compare three different methods of sampling ant-Hemipteran interactions for purposes of the previous chapter across the land use gradient. This will provide a greater appreciation of the challenges that may be involved in sampling these patchily-distributed interactions in widely differing environments. I will begin Chapter 3 by characterizing mutualisms based on a set of easily observable ecological properties, comment on their relevance and then ask how species traits influence these properties. In my final Chapter, I will perform cafeteria experiments using baits to understand how nutritional balances and competitive dominance and discovery hierarchies influence the use of Hemipteran tending as resources by ants across the land-use types.

Prey species perceive the risk of encountering predators and being predated upon as fear in the landscape. Prey can thus implement behavioral antipredator strategies by altering functional traits such as habitat use, foraging time, and forage choice. Several factors can affect prey perception of predation risk in the landscape, also known as the landscape of fear, including predator traits, prey traits, and habitat characteristics. Humans may also play the role of predators in natural ecosystems. Both predator and prey species may perceive the threat of humans as predation risk, thus generating fear across trophic levels. Over the past century, most predator species have been extirpated from terrestrial and marine systems. Accordingly, humans may also alter the natural landscape of fear indirectly. Here, I attempt to understand how anthropogenic fear qualitatively and quantitatively differs from fear of other predator species. I plan to use a combination of theoretical and empirical approaches to answer my research questions. First, I will review and analyze current literature on anthropogenic fear to determine the extent and magnitude of anthropogenic fear effects across ecosystems and trophic levels. I will contrast the impact of risk from humans and other predators on prey foraging behavior. For the second chapter, I will use a theoretical approach to understand the effect of fear at multiple trophic levels instead of a single trophic level. I hope to generate predictions on the spatial distribution of predators and prey in systems with pervasive fear. The third and fourth chapters will involve field data collection and experiments in South Andaman and Richie’s Archipelago. These sites have varying levels of protection with a strong gradient of coral cover and human activity. In the third chapter, I will quantify the effect of the loss of predators on coral reefs due to fishing on herbivore foraging behavior. My final chapter will be an experiment to quantify the extent of fear generated by fisheries on predator and prey species in coral reefs.

Patterns of space-use are key in understanding predator-prey interactions. The spatial overlap of predators with their prey influence their encounter rates, predation rates, and ultimately predator-prey dynamics. Animals engage in a dynamic behavioural response race, where prey actively try to avoid predators while predators seek out prey-rich spaces. Many extant studies fail to test for the emergent space-use outcome of the dynamic response race by either holding the prey or predator fixed or not addressing the underlying behavioural mechanisms that drive space use in mobile predator and prey.

In a qualitative literature survey, I examined how many studies report spatial correlations between the distributions of mobile predator and prey and identified external constraints or ‘anchors’ that may influence the observed spatial distributions. Anchors can be constraints like fixed resources or presence of refuges that restrict free access to patches of choice. If prey are constrained, predators win the behavioural response race and show a positive spatial overlap with the prey, whereas, a negative spatial correlation is seen if predators are constrained. Our results show that the presence of the identified anchors may drive the reported outcomes of the predator-prey space-use patterns. Such anchors can be important predictors of the emergent space-use patterns in predator-prey systems. I then studied how predators from the African savanna choose to distribute themselves in space across the timescale of years and seasons and how these time scales affect their choice of kill hotspots. I used movement data for tagged leopards and African wild dogs from the Karongwe Game Reserve in South Africa for this analysis. Our results show that the seasons affect where animals choose to hunt within their home range and that the choice of home range itself may also change over seasons and years. There was also a difference in the space-use of leopard and wild dogs as expected from the differences in their behavioural mechanisms and hunting strategies. Overall, we conclude that a positive spatial overlap alone may not translate to uniform predation risk in the landscape as there are certain hotspots with higher encounter and predation activity that are riskier for prey.

Evidence from recent studies on foraging behavior supports the idea that animals optimize for multiple macronutrients and not just energy gain. Such optimization requires animals to know three things – 1) their current nutritional state, 2) nutritional composition of the food item, and 3) how much of the food item is needed to achieve the desired nutritional state. Lab experiments on animals across taxa demonstrate that they can, in fact, achieve this feat. We now also know that optimal nutritional composition of diets, or ‘intake targets’, are plastic, which allows animals to maintain homeostasis under changing environmental conditions. Abiotic factors (such as temperature) and trophic interactions (both bottom-up and top-down) not only affect the nutritional demands, but also constrain acquisition of nutrients in response to those demands. In addition, life-history strategies such as foraging modes might also influence nutritional demands, and therefore, intake targets. Under natural conditions, however, such constraints often prevent animals from achieving these targets.

In many habitats, available resources vary temporally with seasons and spatially across the landscape. Along with these bottom-up constraints on nutritional intake, top-down predation risk effects also affect foraging behavior and nutrient acquisition in the prey species. In a desert ecosystem such as the one in the Thar, an herbivorous agamid, the Indian spiny-tailed lizard Saara hardwickii, experiences great spatio-temporal variation in resource nutritional quality. Temporal variation in temperature and spatial variation in predation risk are also prominent stressors and can influence foraging in these lizards. This provides an opportunity to understand nutritionally explicit foraging decisions in response to environmental factors varying in both space and time. In my thesis, I propose to examine the nutritional intakes of S. hardwickii in response to temporal shifts in nutrient state space and temperature. I will also capture the variation in distribution of nutrients in space to construct a ‘landscape of nutrition’ (LON) for the spiny-tailed lizards. Lizard burrow densities and body condition index will be measured to understand burrow site selection and its consequences along the landscape of nutrition. In addition, I will quantify predation risk to construct a ‘landscape of fear’ (LOF) in the same space. Along the LON and LOF, I will examine various behavioral, nutritional, and physiological variables to understand animal responses as they balance foraging benefits and predation risk. Further, in a manipulative experiment, I will examine the consequences of long-term nutritional constraints on physiological and motor performance. Finally, using published literature on diet composition, I will explore how life-history strategies such as foraging modes shape intake targets over evolutionary timescales in animals across taxa.

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Species interactions are known to shape biological communities. While antagonistic interactions like competition and predation are well known, cooperative interactions have received comparatively less attention. Mixed-species foraging behaviour is a common phenomenon seen across various taxa including fish, birds and mammals, where different species form groups and forage together. Unlike symbiotic associations, these interactions are more dynamic and include a much larger subset of species of the community. We sampled mixed-species groups (MSG) of reef fish in the Lakshadweep islands, off the west coast of India. The data was gathered over four years following a mass-bleaching event which led to massive loss of coral in Lakshadweep in 2010. Though not widely reported, we discovered that mixed-species grouping is a common occurrence in the reef ecosystem. Around 130 of the 305 commonly observed species of fish in the Lakshadweep were seen participating in groups to some extent. Using a cluster analysis on species composition, we categorised the groups that were observed in Lakshadweep into nine compositional categories, which also exhibited variation in behaviour, habitat affinity and group cohesion. We then examined variation in grouping propensity, species richness, species evenness as well as species composition across space, time and habitat for the most commonly observed compositional categories. We found that invertivores tended to form smaller attendant groups, with clear nuclear-follower relationships, and likely form for direct foraging benefits. Herbivorous fish on the other hand formed large shoaling associations indicating benefits gained from increasing group size. We found evidence of the effect of the mass-bleaching event and subsequent ecosystem recovery on the formation of some groups. Reef fish MSGs are thus important components of these ecosystems and can both affect and be impacted by reef structure and function.

Collective movement is a fundamental process affecting the survival and reproductive success of group-living animals. Many of the hypothesized benefits of grouping such as predation evasion and foraging efficiency require the individuals in a group to move in a coordinated way. While moving in groups, animals are not only responding to the environment but also interacting with each other. These interactions give rise to emergent collective movement and behavioural patterns. A novel aspect of emergent behaviour is that a group can exhibit properties that no individual displays on its own. 

Most studies on emergent properties of collective behaviour are conducted in controlled conditions. However, in natural settings, habitat is heterogeneous in terms of resource distribution, availability of hiding places and substrate for movement. Empirical studies have rarely investigated such fine-scale interactions (e.g. alignment, attraction among individuals) in their natural habitat. One reason for the dearth of such studies is the difficulty of data collection. Recent advances in techniques of aerial imagery allow us to observe and record such fine-scale data. For my PhD project, I studied the collective behaviour of blackbuck herds in their natural habitat. More specifically, I investigated the collective response of blackbuck herds during predation-like events. By analyzing multiple interactions among group members simultaneously, I aimed to understand the role of social interactions in shaping the collective response of blackbuck herds when faced with predation-like threats. 

First, we overcome the difficulty of observing fine-scale interactions in animal groups (in their natural habitat) by using UAVs. We recorded blackbuck herding behaviour at high spatio-temporal resolutions (30 frames per second). Using this technique we were able to record the blackbuck herd’s collective escape behaviour in the context of predation using controlled-simulated threats.

Tracking animals in the videos recorded in natural habitat is extremely difficult due to varying background and light conditions and clutter in the background. Relatively basic image processing methods and default tools don’t perform satisfactorily in such a scenario. 

Hence, we developed a machine learning method and GUI tool to extract the spatial locations and movement trajectories of all the individuals in a group from the videos recorded in natural field conditions.

Once we were able to obtain the movement trajectories from the videos, I then analysed these trajectories and interactions between individuals to explore - how the information about predatory risk spreads through a group in natural conditions. Broadly, our results suggest that transient leader-follower relationships emerge in these groups while performing the high-speed coordinated movement. Also, males and females respond differently to the threat scenario: adult females are more likely to be the response initiators whereas adult breeding males are more likely to influence the group movement during the escape response. Our results indicate that in fission-fusion groups associations are likely to last for short time scales and spatial positions of the individuals only affect their response-time (vigilance behaviour) but not their influence on the group.