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.

When a blackbird swallows an earthworm, there is little doubt about the nature of the interaction. Sadly, few microbial interactions are this clear. This is particularly true when bacteria reside inside eukaryotes. Who gains, who loses, and the role of evolution are large questions in the biology of microbial interactions. Many look at the mechanisms of interaction, but here we take a different approach. First we explore the landscape of interactions across the eastern US, determining how commonly specific bacteria interact with amoebae, beginning with the obligate endosymbionts Amoebophilis and Neoclamydia and the eukaryote host Dictyostelium discoideum. We image the interactions and measure health effects on the host. Then we turn to a novel facultative endosymbiont, Paraburkholderia spp. where geographic distribution and health effects can be measured for both host and endosymbiont. We name three new species, two of which are highly dependent on the host and then use experimental evolution techniques to reveal how tightly they have co-evolved. Combining the tools of landscape surveys, microscopy, fitness assays, genomics, and experimental evolution allow a much deeper understanding of host-pathogen or host-mutualist interactions.

This study investigates beta diversity and its partitions to quantify the influence of different processes that drive spatial and temporal variation in ground-dwelling arthropod assemblages. First, ant assemblages across Goa, India, were studied to quantify how different species and functional groups, and human land use contribute to beta diversity over large spatial scales, and whether invasive species have a disproportionate influence on beta diversity. Human land use strongly influenced diversity and distribution of ant assemblages. Human land use spared local species richness, but not functional groups. A small number of invasive species exerted negative influence even in a very speciose community. Second, intra-annual variation in beta diversity and its partitions of ant communities was studied across three seasons in Bhagwan Mahaveer Wildlife Sanctuary, Goa, India, to quantify how loss and gain of species leads to functional redundancy. Ant community composition was highly variable at seasonal scales. But ecological roles were maintained across seasons by species with redundant functional traits. Third, effect of human altered land use on temporal beta diversity and its partitions of ground active arthropods was quantified in the coupled human-natural Trans-Himalayan ecosystem in Spiti, northern India. Human land use altered seasonal trajectories of community dynamics and influenced beta diversity at the taxonomic level. But functional roles were spared due to species replacement and redundancy in traits. Together, the three chapters of this thesis show that community composition rather than species richness is a better indicator of how arthropods respond to human land use. They also establish functional redundancy to be an important feature of ecological resilience and resistance that can be affected by human land use.

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.

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.