Climate tipping events, where climatic subsystems shift to alternative equilibria as a consequence of climate forcing, may have abrupt and drastic impacts on global climatic patterns. Such large-scale and irreversible qualitative changes to the state of global circulation may greatly affect ecosystems. In particular, for biodiversity, climate tipping events may produce novel climate conditions that expose species to potentially stressful climatic conditions outside their realized historical limits. To quantify the patterns of these limits for species across different aspects of climate, we introduce the ClimLimits database, a high-resolution record of terrestrial and freshwater species’ realized climatic niche limits in 44 limits. Using this, we then quantify the exposure fractions over their range of 43,320 species worldwide to 16 of these limits in the face of future climate tipping points.

We model future climates with novel projections forcing the emergence of two climate tipping events, namely the weakening of the Atlantic Meridional Overturning Circulation (AMOC) and the dieback of the Amazon Rainforest (ARF), as well as a third control scenario of stabilizing warming without tipping. Our analysis reveals frequency, intensity and duration of heatwaves as primary drivers of exposure across species in all three scenarios.

However, there are critical differences in exposure patterns across other variables - AMOC weakening changes climate variability and extreme event patterns, while the ARF dieback amplifies exposure to extreme rainfall and drought. Additionally, by looking at spatial exposure patterns across ecosystems, we identify the additional impact of AMOC weakening as increasing exposure in the tropics in South America and Africa, while reducing exposure in Europe and North America. The primary effect of ARF dieback is localized largely to South America, but also has appreciable cascading impacts in other tropical ecosystems. Our results suggest that we may underestimate future climate change impacts on biodiversity loss if we do not account for the possibility of long-lasting and irreversible climate tipping point events.

How do many active-sensing agents like echolocating bats move together and show collective movement in large groups? Each individual in the group is constantly emitting intense calls to detect their surroundings, while relying on echoes and other sounds to detect their environment. How do agents manage the cacophony of sounds, relevant and irrelevant - and what to do they to mitigate this potential sensory overload? Such acoustically based groups showing rapid movements are a frontier field for collective behaviours as such and present an exciting nexus from a basic and technological perspective. In this talk I will present my lab's multi-pronged approach at answering this inverse problem using a combination of swarm robotics, computer simulations and multi-sensor rigs in the field. The computational methods to process and analyse such experimental data itself do not currently exist in any form - which we are also driving through collaborations. Bringing together the fields of sensory biology, collective behaviour, swarm robotics, and computational methods development - I will discuss the challenges and advantages of such an approach.

The golden langur (Trachypithecus geei) is one of the most range-restricted colobine monkeys, confined to the region between Sunkosh and Manas rivers in Bhutan and adjoining Assam (India). Despite its conservation significance, several questions regarding the species' population structure, relationship with closely related species, and ecological boundaries remain unresolved. Furthermore, the species occupies a rugged Himalayan landscape characterized by mountains, valleys, rivers, and forests, raising important questions about how these landscape features influence patterns of genetic differentiation and ecological variation.

My thesis addresses these questions by combining molecular genetics and ecological approaches. Using mitochondrial DNA, microsatellite markers, preliminary genomic analyses, and ecological niche modelling, I am investigating population structure within golden langur, its relationship with its sister species, the capped langur (Trachypithecus pileatus), and patterns of ecological niche overlap among the golden, capped, and Himalayan langurs (Semnopithecus schistaceus) at both Bhutan-wide and range-wide scales.

As this study continues to develop, the emerging results suggest that evolutionary relationships among these species cannot be fully understood through a single line of evidence. Instead, patterns of genetic structure, species divergence, and ecological niche overlap appear to reflect the influence of a dynamic Himalayan landscape that functions as both a barrier and a corridor. Thus, my thesis seeks to understand how biological boundaries are formed, maintained, and reshaped across the complex landscapes of Bhutan.

All organisms die, and most become more likely to die with age, a phenomenon called demographic senescence or ageing. Despite the previous sentence saying nothing about the particular shape of a mortality curve, most organisms age in remarkably similar ways. In particular, organisms across the tree of life experience exponentially increasing mortality hazards with age, a pattern called the Gompertz–Makeham law. In this talk, I will argue that senescence is an unavoidable consequence of the progressive accumulation of stochastic damage to, or failures of, intra-organismal subsystems (genes, cells, organs, etc) over time. In many organisms, ‘failure begets failure’ because sub-systems are interdependent. I will demonstrate that this interdependence generically produces Gompertz-Makeham mortality curves, and shows that more complex organisms should exhibit clearer ageing patterns. Since individuals who die can no longer age, observed cohorts become increasingly composed of ‘lucky’ individuals that avoided death by (stochastically) living lives associated with lower mortality, even if individuals have no intrinsic differences in quality at birth. Such "selective disappearance" of unlucky individuals generates deviations from Gompertz-Makeham predictions at advanced ages, producing a late-life mortality plateau. We show that while these deviations must always exist, they may often be difficult to detect because robust detection requires unreasonably large cohort sizes. Our work establishes Gompertz-Makeham curves arising from stochastic failure/damage accumulation as a null expectation in complex organisms with many interdependent sub-systems.

Ecological communities are composed of species spanning orders of magnitude in abundance. A natural and widespread assumption is that the rarest species are the most vulnerable to extinction. But is abundance alone sufficient to assess vulnerability? In this talk, I present a series of interconnected results showing that a species' vulnerability depends critically on the diversity of its dispersal strategies, the structure of its competitive interactions, and the heterogeneity of the landscape it inhabits.
Starting from microscopic individual-level dynamics, macroscopic metapopulation and metacommunity models are derived that naturally incorporate dispersal network structure and environmental heterogeneity. Spatially varying environments can support multispecies coexistence in competitive metacommunities through the spontaneous emergence of spatial niches, even among species that would exclude each other locally. Building on this, a single quantity, the competitive balance, integrates dispersal diversity and interspecific interactions to assess a focal species' vulnerability to extinction. This metric reveals that greater heterogeneity in dispersal strategies can reduce vulnerability for a rare species in unfavorable competitive contexts. These predictions are tested against datasets from two tropical and one temperate forests, where effective per-species dispersal parameters are estimated directly from data, yielding strong agreement with theoretical expectations. Together, these results show that vulnerability is not a single-species property but an emergent community-level quantity, and this requires understanding the ecological context in which a species is embedded.

Animals must consume nutrients in optimal amounts and ratios to maximize their fitness. However, most animals face various constraints to foraging optimally in their natural habitats. While studies conducted in the lab and mesic habitats suggest that animals can sense and meet their transient and long-term needs, we still have little understanding of the nutritional ecology of vertebrates in extreme environments. In this thesis, I attempt to fill this gap by examining the nutritional ecology of the desert-dwelling Indian spiny-tailed lizards Saara hardwickii under various ecological contexts.
In the first chapter, I adopt a global approach to understand whether variation in life-history traits across lizards can be explained by nutritional intakes. Lab based studies on multiple species suggest a strong link between nutrition and life-history traits. However, the results from my study suggest that these associations generally do not reflect in the relationship between nutrition and life-history at an inter-specific level. Absence of a significant relationship between nutrition and life-history at an evolutionary scale might indicate that nutritional responses are more sensitive to demands imposed at ecological timescales.
In the second chapter, I examine whether lizard diet is sensitive to specific nutritional requirements from key life-history events across seasons. For this, I quantified nutritional responses (nutrient consumption and retention) in Indian spiny-tailed lizards Saara hardwickii across four seasons in the Thar desert of northwest India. The results from this work show that S. hardwickii uses both behavioural diet choice and post-ingestive physiology to match seasonal nutritional needs by differentially consuming and retaining nutrients in an extreme environment.
In addition to the long-term demands of life-history traits, animal nutrition is also sensitive to more transient nutritional needs due to various ecological factors, such as predation risk. Lab based studies show that fear of predators can modulate nutritional responses via the physiological stress response. In the third chapter, I examine whether the risk of predation from a feral predator affects stress physiology, and consequently, nutritional responses in S. hardwickii in their natural habitat. Lizards in high-risk habitat adjust both intake and retention of carbon and nitrogen. The lack of physiological stress and changes in diet composition in this species hints to a significant role of behaviour, not physiology, in mitigating predation risk.
I test this in my final chapter by examining the mechanistic links between antipredator responses and their downstream costs on fitness in S. hardwickii. To this end, I quantified behavioural and physiological antipredator responses in S. hardwickii across habitats varying in predation risk and food resources. Using a structural equation modelling approach, I examine how the costs associated with these antipredator responses can result in varying fitness outcomes in heterogenous environments.
Together, this thesis integrates extensive field observations, lab experiments, modelling approaches and a global synthesis to understand the nutritional underpinnings of behavioural, physiological, and life-history trait variation. Understanding the nutritional ecology of these traits can provide mechanistic insights into species responses to various natural and anthropogenic changes in their environment.

Group-living organisms across taxa coordinate their movement to evade threats or predators. However, how information about threats, often available only to a few individuals within the group, efficiently propagates among the group members, and how animals use the information of predator to coordinate their movement, remains less explored. In this thesis, our aim is to study collective escape responses, information propagation and context-dependent hierarchical leadership in collectively escaping groups, using both data and models.

We first investigate the collective responses of a sheep flock (Ovis aries) to a herding dog (border collie). We observed that the sheep flock remained highly cohesive throughout the herding events, consistent with the selfish herd effect, a known mechanism hypothesised to reduce predation risk. Sheep moved faster as the dog increased speed, while being highly polarised but less cohesive. This suggests that cohesion alone may not adequately explain anti-predatory benefits of group-living, especially in groups exhibiting synchronous collective motion as seen in our sheep flock experiments. Using lagged cross-correlation analysis of time series of direction of different individuals, we identified a clear hierarchy among sheep in terms of their directional influence on the flock. We found that the average spatial position of a sheep along the front-back axis of group velocity strongly correlates with its influence on group movement.

To explain these results, we developed a computational model where sheep follow simple interaction rules, namely, repulsion from the dog and a tendency to move towards and align with neighbours. This model can reproduce empirically observed patterns. Consistent with experimental findings, the model predicts that the individuals at the front of the flock had greater directional influence on the group. Furthermore, we developed a null model of herding in which the chasing behaviour of dog is not included. Such a model fails to reproduce the hierarchical information flow, suggesting that the observed empirical patterns are characteristic of collective escape response.

When animals collectively respond to threats, it is difficult to know if the individuals were directly reacting to the threat or to the response of their neighbors. We study high-resolution data from a controlled experimental set up of fish (tiger barbs) where an individual trained to a threat stimulus via aversive conditioning escapes the stimulus, thus precisely controlling the individual reacting to the threat (or thus, having information of the threat). We show that in a group of five fish with only one conditioned fish, the escape behaviour of one conditioned fish could trigger collective escape responses with all the fish. We use lagged cross-correlation analysis of speed of different fish to analyse information propagation and leadership. Under unperturbed conditions, we do not observe any hierarchical leadership. However, when we turn on the green light and the conditioned fish responds to the green light by crossing the barrier, we observe a hierarchical transfer of information from the conditioned fish to the naive ones. Further, by using spatially-explicit agent-based models, we show that the hierarchical transfer of information occurs because, once the green light is turned on, the conditioned fish reduces it’s interaction strength with all the naive fish until it crosses the barrier, while the naive fish respond to the conditioned fish due to its rapid change in speed and direction.

In summary, my thesis reveals that during the initial attack by predators, the information about the threat propagates via sudden changes in the speed of informed individuals. However, when the predator continuously chases the group, information spreads more strongly through changes in the direction of the individuals at the front. Further, we can use computational models to both explain these patterns, as well as make inferences about the broad nature of interactions among group members while they escape threats. Thus, combining results from all these studies, from highly controlled to natural settings, our study revealed some general principles of collective escape dynamics in group-living organisms.

Social behaviour has traditionally been studied through the lens of conspecific interactions, yet animals routinely interact with heterospecifics in ways that shape survival, resource acquisition, and information use. Mixed-species groups (MSGs) are among the most widespread expressions of such heterospecific sociality, occurring across diverse vertebrate lineages, yet their evolutionary origins, the ecological conditions that favour their formation, and the traits determining who associates with whom remain poorly understood. This thesis addresses these questions across three interconnected scales, asking why heterospecific sociality evolves, when mixed-species groups form, and which species interact to form such associations.
The first chapter examines the evolutionary distribution of sociality across vertebrates using a global comparative framework spanning birds, mammals, and fishes. Integrating species-level behavioural and ecological data with phylogenetic methods, I test the relationship between conspecific and heterospecific sociality, asking whether mixed-species grouping is a distinct evolutionary phenomenon or an extension of the pressures favouring sociality more broadly. Heterospecific sociality proves phylogenetically structured rather than randomly distributed and rarely evolves directly from solitary ancestors. Instead, it arises most often in lineages that have already evolved conspecific group living, indicating that mixed-species associations build on foundations established through earlier transitions to sociality. Heterospecific grouping thus emerges not as an isolated ecological phenomenon, but as a recurring outcome of the same selective pressures that favour conspecific sociality, extended across species boundaries to exploit complementarities unavailable within single-species groups.
Chapters 2 and 3 shift scale to ask which species associate, examining the mechanisms structuring MSGs within species-rich coral reef fish communities across two Indian Ocean island groups. Testing whether associations are shaped by phenotypic traits, I find that species do not associate randomly from the pool of ecologically similar co-occurring species. Body size and shape show non-random patterns of similarity, consistent with shared movement and ecological constraints structuring group membership. Extending this to visual traits, associated species are often more visually similar than expected by chance, particularly in body patterning, a pattern consistent across island systems. This reveals a previously underappreciated role for visual phenotypes in group cohesion and species recognition, establishing partner choice, not just ecological opportunity, as a driver of group composition.
The final chapter asks when and why MSGs form, examining ecological drivers of shoaling among herbivorous reef fishes in the Andaman Archipelago. Testing three interacting mechanisms, predation risk, interference competition from territorial damselfishes, and algal resource availability, I find predation influences group size but is not consistently the strongest predictor of grouping dynamics. Resource accessibility and competition with damselfishes emerge as equally or more influential, suggesting MSGs help individuals overcome competitive barriers and access defended resources, not merely reduce predation risk.
Together, these findings show that mixed-species sociality cannot be understood at a single biological scale but reflects a hierarchical process. Evolutionary history determines which species possess the capacity for heterospecific association; ecological conditions determine when that capacity becomes advantageous; and phenotypic compatibility determines who ultimately associates. These mechanisms are complementary components of one scale-dependent process, reconciling long-standing debates over the primary driver of mixed-species grouping. By linking macroevolutionary patterns with ecological mechanisms and species-level associations, this thesis extends the study of social evolution beyond species boundaries, arguing that heterospecific sociality is a structured, recurrent component of animal social systems deserving a central place in contemporary theories of social evolution.

Biological invasion is one of the greatest threats to biodiversity in the Anthropocene. Across multiple taxonomic groups, invasive species have caused substantial declines in native biodiversity, altered the composition of natural ecological communities, disrupted key species interactions and modified essential ecosystem processes such as nutrient cycling, fire patterns, and resource availability. Plant-pollinator interactions assist in the reproduction of most flowering plants; however, invasive plant species may disrupt these mutualisms by competing with native plants for pollinators, thereby altering native plant-pollinator networks and compromising the reproductive processes of native plants. Understanding how invasive plants (i) influence plant-pollinator interactions, (ii) adapt to novel environments through alternative reproductive strategies, and (iii) can be managed to design effective restoration of native vegetation is therefore critical for biodiversity conservation. My thesis investigates these questions in Eaglenest Wildlife Sanctuary (EWS), part of the Eastern Himalaya Global Biodiversity Hotspot. In EWS, historical low-elevation settlements were abandoned ~25 years ago, and the abandoned land is now dominated by three main invasive plant species - Ageratum conyzoides, Chromolaena odorata and Mikania micrantha.
In the first chapter, I compared primary forest (PF) with invasive-dominated habitat (IDH) to understand how invasive plant dominance alters plant-pollinator network (PPN) structure. Using quantitative bipartite network analyses across multiple seasons, I found that although invaded habitats support higher plant and pollinator richness, the overall plant species diversity was higher in PF. Invaded PPNs show higher nestedness and lower modularity, indicating a shift towards more generalized plant-pollinator networks with potentially reduced long-term interaction resilience.
In the second chapter, I investigated whether invasive plants depend on native pollinators for successful reproduction or adopt autonomous reproductive strategies. Through pollination exclusion experiments on three invasive species (A. conyzoides, C. odorata and M. micrantha), I demonstrated substantial differences in reproductive strategies among invaders. While A. conyzoides and C. odorata maintain seed production and average seed mass even under pollinator exclusion suggesting considerable reproductive autonomy, M. micrantha exhibits greater dependence on pollinator-mediated reproduction for both seed quality and quantity. These contrasting reproductive strategies between co-occurring invasive plant species might help explain how different invasive species establish and spread successfully in disturbed landscapes.
In the third chapter, I evaluate restoration strategies for IDH through a field experiment combining invasive plant removal, native seed addition, and soil seed bank assessment to evaluate regeneration potential. I compared alternative restoration treatments for their effectiveness in promoting native vegetation recovery. Complete clearing of vegetation plots combined with native seed addition resulted in the greatest establishment of the target native species (Pogostemon elsholtzioides) and supported enhanced native recruitment, highlighting the importance of active restoration for recovering invaded forest ecosystems.
Together, these chapters integrate plant-pollinator community ecology, reproductive biology and restoration ecology to provide a more comprehensive understanding of how invasive plants adapt to new habitats and alter ecological interactions. By linking invasion impacts with experimentally evaluated restoration strategies, this thesis contributes to a broader understanding of how biodiversity and ecological resilience can be conserved in one of the world's most diverse ecosystems.

We describe diverse species of Lepidoptera in immature stages exhibiting a wide range of previously unreported collective behaviors. These behaviors include coordinated foraging, group defense, trail-marking, resting-site selection, and pupation and demonstrate high levels of synchronization among groups of a dozen up to hundreds of individuals. Our research encompassed twenty groups across ten Lepidoptera species, and employed field monitoring/observations and controlled experiments in the Peruvian Amazon and Karnataka. The behaviors observed are complex and metabolically expensive as they require interaction between many individuals and significant movement. For example, one group of 320 individuals performed a ~40 minute “milling” motion before hour-long foraging bouts involving synchronized processionary travel for ~25 meters (~500 body lengths). The prevalence of these behaviors across multiple taxa suggests they may confer a fitness advantage, leading to its repeated emergence in Lepidoptera. Notably, while individual behaviors such as movement patterns, feeding habits, and chronotypes are highly species-specific, group behaviors like self-organized synchronization and distributed foraging show remarkable conservation across taxa. Our observations expand our understanding of social complexity in insects and the evolution of collective behavior while potentially revealing novel strategies for pest management in ecologically and agriculturally important Lepidoptera species. Furthermore, these principles of self-organization may have broader applications in fields such as swarm robotics and collective decision-making algorithms.