Variation in reproductive success (skew) is required for change in trait/allelic frequencies in a population resulting in evolution. Classically, processes generating this reproductive skew have majorly been studied under the lens of sexual selection. The Darwinian-Bateman paradigm of sexual selection suggests that individuals try to maximise their reproductive success through increased mating opportunities, and difference in gametic investment determines investment in multiple matings. Thus, sexual selection studies have primarily focused on reproductive skew in males, under the assumption that female investment in reproductive success is limited and individuals have relatively uniform number of offspring. In the past 35 years, however, evidence of reproductive skew in females has been found in some species, followed by multiple hypotheses proposed explaining said skew. Multiple researchers suggest that female skew is driven by access to resources rather than sexual processes, but there is still a dearth of quantitative studies. This thesis aims to fill the gap in female reproductive skew studies by looking at the pattern and evolutionary processes generating this skew through a phylogenetic meta-analytic approach.

In the first chapter, we will broadly identify the pattern of reproductive skew in females across the major animal classes and estimate the relative significance of classical sexual selection processes like intrasexual competition and mate choice compared to non-sexual selection (ecology, life history) variables.

Sociality determines the ability of individuals to monopolize resources, avoid predation, and gain access to mates. Reviews have thus partly attributed the ability to reproduce to sociality & social processes in case of females. In the second chapter, we focus specifically on the role of intraspecific social interactions in shaping the skew across taxa.

In the third chapter, we move from large-scale cross-taxa studies to longitudinal studies of individual species. We aim to tease apart the relative importance of viability, sexual and fecundity selection processes across the lifetime of individual females. We will further compare the variation in different fitness components across lifetime in these studies to the cross-taxa pattern observed in the previous two chapters.

This thesis will be one of the first broad-scale quantitative studies to investigate the reproductive skew and selection potential in females, filling the gap left by the classical sexual selection paradigm.

Grouping across taxa is a trade-off between benefits like shared foraging advantages and collective vigilance, and costs including competition for resources. Mixed-species groups (MSG hereafter) are a special class of associations, where two or more species associate with each other. Like other associations, MSGs also depend on cost-benefit ratios. These dynamic groups can differ structurally and functionally, and each functional state can represent different ecological roles or adaptive strategies. The structural organisation of these groups indicates a rule-based assembly. Similar species may group with each other for anti-predation benefits and to reduce the cost of activity matching; alternatively, functionally different species may associate more than expected by chance to avoid competition.
Heterospecific associations have been studied across multiple taxa; however, a majority of studies have been carried out on forest birds, and to a lesser extent on mammals and fish. Little is known about heterospecific grouping in a wetland context. Wetlands are unique, complex, and diverse ecosystems that can support various living organisms. These wetlands are widely different from forest ecosystems in habitat and community structure. Wetlands are open, have patchy resources, and support different life forms, including avifauna. Of the 1350 species of birds recorded in India, more than 300 are classified as waterbirds. Studying grouping dynamics in wetlands is also significant for conservation, as these groups play a vital role in maintaining the wetland ecosystem, both in nutrient cycling and food web regulation.
My study aims to understand patterns and drivers of heterospecific sociality in waterbirds across multiple Indian wetlands. First, I will explore the broad structural, functional, and compositional patterns of MSGs across wetlands and seasons. Then, I plan to examine trait-based group formation rules associated with functional groups and ecological context. In relation to that, I will analyse the dynamics of interactions to understand how centrality works in different functional and ecological contexts. Finally, I will investigate the influence of natural factors (e.g., the presence of avian predators) and anthropogenic disturbance on wetland MSGs, i.e., do species adapt their grouping strategy to cope with disturbance? The ultimate goal of this thesis is to provide a framework to infer how changes in group dynamics affect the broader ecological roles of waterbird MSGs.

Organisms invest in a multitude of traits shaped by different selection pressures to maximise fitness. As resources are limited, extensive investment in costly traits can trade-off against investment in other traits that affect survival or reproduction. Given the huge costs of such investment, why are exaggerated traits so widespread in nature?
In this thesis, I studied the evolution and maintenance of costly exaggerated traits under positive allometry in Psammophilus dorsalis, a short-lived socially polygynous lizard. I investigated how costly exaggerated traits under different selection forces change with fine-scale varying environment, how they affect the use of signals and aggression in fights, and examined trait evolution by measuring inheritance, plasticity, and fitness consequences in a wild population of these lizards.
Changing environments can impose strong selection on traits, yet our knowledge of costly trait response across dynamic environments is limited as longitudinal studies across generations are rare. In the first chapter, I use a long-term 11-generation dataset from 2011 to 2021, to examine how fine-scale spatial and temporal variation in ecological and demographic conditions modify positive allometry in traits across sex and selection process. Positive allometry in male head width (under sexual selection) varied dramatically over generations and space. Limited rainfall, harsh temperatures, and greater competition promoted positive allometry in male head width. In stark contrast, positive allometry in female interlimb length (under fecundity selection) only weakly correlated with environmental conditions. Our study demonstrates that costly traits are sensitive to changing environments depending on the underlying selection pressure and sex.
Contest competition for acquiring resources – territories and mates - typically involves individuals using multiple morphological and behavioural traits. In the second chapter, I explored how male Psammophilus dorsalis balance investment in aggression – between long-term investment in body size and exaggerated weapons, and “labile” and costly aggressive behaviours during intra-sexual contests. Behavioural experiments simulating contests were conducted on males in the wild using 3D-printed lizard models of varying sizes across four breeding seasons (2016 to 2023). The results indicate that males use aggressive displays as honest indicators of competitive ability in Psammophilus dorsalis. Our results suggest that males use a combined suite of aggressive traits, behavioural and morphological, to signal the motivation to fight and the ability to win contests.
Costly exaggerated traits are hypothesized to be maintained through reproductive advantages that outweigh the survival costs. In the third chapter, we empirically investigated the mechanisms maintaining exaggerated traits under different selection processes in a natural population of Psammophilus dorsalis. To enable this study, I developed and optimised 6 microsatellite markers for P. dorsalis. Using two parent–offspring generation pairs (N = 325) sampled across four breeding seasons (2015–2016 and 2021–2022) from six sheetrocks, I quantified heritability, phenotypic plasticity, and selection gradients under varying environmental conditions.
I show that exaggerated traits under sexual selection in males are maintained through inheritance and fitness consequences, which varied with years and environmental conditions. In contrast, exaggerated traits under fecundity selection in females seem to show high environmental plasticity, low inheritance, and negligible fitness consequences. Furthermore, our predicted responses to selection based on heritability were less accurate when environments varied and shifted trait allometry, highlighting the importance of accounting for environmental effects when estimating trait evolution.
Overall, this thesis demonstrates that the maintenance of exaggerated traits is shaped by interactions among environmental variation, selection process, and sex. Our findings emphasise the importance of long-term, longitudinal studies across environment, sex, and selection, for understanding the ecology and evolution of exaggerated traits and predicting evolutionary responses in wild populations.

Many studies have suggested that ecosystems may exhibit multiple stable states and abrupt responses to changes in underlying environmental conditions/drivers. Traditionally, researchers have relied on statistical indicators, such as bimodal frequency distributions, to infer the presence of alternative stable states (bistability) from observational data. However, real-world ecosystems are inherently noisy and rarely stationary, often driven by periodic external forces like seasonal rainfall or temperature cycles.

In Chapter 1, we investigate the interplay of stochasticity and seasonality in ecosystem dynamics. Using canonical ecosystem models and satellite-derived vegetation data (EVI) across a large rainfall gradient, we first demonstrate a critical vulnerability in traditional statistical heuristics. We show that slow seasonal forcing can drive simple unistable systems to exhibit spurious bimodal distributions, and in contrast, in some bistable systems, the interplay of seasonality and stochasticity can mask the underlying bistability of a system by exhibiting unimodal distributions. These counterintuitive impacts of seasonality on ecosystems highlight the dangers of relying solely on statistical patterns to study the underlying ecosystem stability and underscore the need for methods capable of directly uncovering the mechanistic governing equations from data.

To address this, in Chapter 2, we systematically evaluate PyDaDDy, a modern, data-driven equation-discovery framework based on sparse regression. Through rigorous sensitivity analyses, we establish the fundamental limits of this method under ecological data constraints. We reveal a critical bias-variance trade-off governing deterministic drift estimation: sampling too frequently leads to overfitting to environmental noise, while sampling too coarsely yields a biased, flattened model. We quantitatively confirm that drift and diffusion must be characterised at different optimal timescales.

Building on this methodological foundation, in Chapter 3, we develop a novel extension to the sparse regression framework to tackle time-non-homogeneous, seasonally forced systems. We demonstrate that naive applications of equation discovery to seasonal data fail catastrophically, misattributing extrinsic forcing to intrinsic dynamics. By explicitly incorporating the known seasonal driver as an additional input variable, our extended method mathematically decouples these effects. It successfully recovers the true underlying stability landscapes of complex bistable systems across a wide range of seasonal periods and noise levels.

Ultimately, this thesis provides a robust, practical methodology for ecologists to disentangle intrinsic dynamics from periodic external drivers, offering a potential, mechanistic tool to uncover the true resilience of ecosystems in a periodically changing world.

The complex distribution patterns of organisms pose one of the most interesting puzzles in biogeographic studies. Multiple pieces of evidence suggest that these distribution patterns are the outcome of the complex interplay between environmental factors and the dispersal ability and evolutionary history of organisms. Abiotic factors are considered to be an important driver of this pattern, as they exert physiological constraints on the organism’s biology. A species can persist in a region when the environmental conditions fall within its tolerance range, which suggests that physiological tolerance is a potential determinant of species distribution. Yet, it remains unclear which physiological axis sets the limit, especially in multi-stressor systems.
Intertidal gastropods of the genus Littoraria and Echinolittorina along the Indian coast present an interesting distributional pattern. Despite having high dispersal ability through pelagic larval dispersal along the coast, they exhibit significant variation in range size. Within genera, some species show a broad range distribution, occurring along the entire coast, while others are restricted to a small coastal region. Studies indicate that abiotic factors such as sea surface salinity and tidal range may explain this pattern, but they remain correlational and do not provide a mechanistic explanation.
This thesis will experimentally test whether physiological tolerance plays a role in shaping range size at different spatial scales. First, I conducted a pilot study to examine whether variation in habitat structure at a fine scale is sufficient to detect differences in thermal tolerance in two freshwater gastropods in Bengaluru. I then scale up this question to a broad level to examine if environmental variation along latitude affects physiological tolerance and whether broad-range species show higher tolerance than range-restricted species along the east and west coasts of India. Finally, I will examine how habitat filtering shapes physiological tolerance both within- and between-species in intertidal gastropods residing on rocky shores and in mangrove-associated habitats in the same regions. Altogether, this thesis aims to build a comprehensive experimental framework that links physiology to species distribution from small local scales to broad geographic regions using both freshwater and intertidal gastropods as a model system. This multi-species, multi-stressor approach aims to provide key insights into the role of physiology in species distribution patterns.

Coastal fisheries target select species but also catch several non-target or ‘bycatch’ species, which comprise ~40% of global catch. Large-bodied, slow-growing species such as elasmobranchs and cetaceans (marine megafauna) are particularly vulnerable to such mortality. Despite its importance, patterns and drivers of bycatch remain poorly understood. Species susceptibility to bycatch may depend on their traits, environmental conditions, and fishing practices, but it is unclear whether these patterns are governed by general rules or local variables. My thesis addresses these questions by examining interactions of elasmobranchs and cetaceans with fishing gear across multiple contexts in India.
My first chapter investigates drivers of elasmobranch capture in nearshore fisheries on India’s east and west coasts. By integrating fisheries landing data, fishing location information, and fisher interviews, we analysed 2,209 fishing trips recorded across three seasons in 2022–23 that caught 5,578 elasmobranchs from more than 20 species. Catch risk was higher at the eastern site, where species were likely targeted, while catch rates were highest on the west coast. Overall, drivers of elasmobranch capture were highly fishery- and site-specific, although some general patterns emerged, such as greater bycatch risk closer to the coast.
My second chapter addresses the lack of baseline knowledge on cetacean occurrence in the North Indian Ocean. I used species distribution models to map areas of high species richness for 18 species. The east coast of India, south Sri Lanka, and the Lakshadweep and Andaman–Nicobar archipelagos emerged as species rich areas. The central west coast of India emerged as a hotspot for two nearshore species - the Indian Ocean humpback dolphin (Sousa plumbea) and the Indo-Pacific finless porpoise (Neophocaena phocaenoides) - that overlap with high fishing activity, making it an ideal system to study cetacean–fisheries interactions.
My third chapter focuses on mortality dynamics of these two nearshore cetaceans along Goa. Using long-term stranding records (2017–2025), ocean current simulations, carcass decomposition experiments, and population surveys, we estimated their at-sea mortality, which was 42 ± 2.4 individuals for S. plumbea and 23 ± 1.8 for N. phocaenoides. Mortality hotspots were concentrated in coastal areas with high fishing and tourism activity, which have potentially caused a 30% decline in S. plumbea abundance over the past two decades.
While drones provide valuable perspectives on dolphin–fisheries interactions, quantifying movement and behaviour from aerial imagery remains challenging. In my fourth chapter, I combine machine learning with a mathematical approach to geo-reference objects in drone imagery, enabling automated GPS-like tracking without onboard tags. The method achieves a median positional error of 1.5 m - comparable to or better than GPS tags - and enables high-resolution, non-invasive tracking of free-ranging animals.
Finally, my fifth chapter applies drone-based tracking to examine behavioural responses of Indian Ocean humpback dolphins to fisheries, co-occurring with unregulated tourism in Goa. Drone focal follows of 90 dolphin groups were analysed using the above framework. Dolphins avoided tourist boats, while interactions with fishing nets were associated with increased foraging behaviour. Groups near fishing nets were more sensitive to the presence of tourism boats, revealing complex behavioural trade-offs faced by dolphins exposed to multiple human activities.
Together, my thesis combines ecological analyses with methodological advances to understand how marine megafauna interact with fisheries. By integrating empirical data, distribution modelling, methodological advances and drone-based tracking, it provides new insights into the mechanisms underlying bycatch risk and highlights opportunities for conserving threatened marine species in rapidly changing coastal ecosystems.

Snakebite envenomation remains a major yet neglected public health challenge, particularly in Northeast India where several medically important snake species are insufficiently characterized and therapeutic options remain limited. This thesis provides a comprehensive investigation into the biochemical properties of venoms from selected viperid and elapid species, alongside the evaluation of novel therapeutic strategies to counter venom-induced toxicity.

The first chapter presents a comparative biochemical and functional characterization of
venoms from Trimeresurus erythrurus, Ovophis monticola, Trimeresurus popeiorum, Naja kaouthia, and Ophiophagus hannah, revealing significant interspecific variation in enzymatic composition and hemostatic effects. These findings underscore the clinical relevance of region-specific venom profiling for improving treatment outcomes. Subsequent chapters explore alternative therapeutic approaches targeting venom toxicity.

The second chapter evaluates small molecule inhibitors (SMIs), including varespladib and marimastat, demonstrating their strong inhibitory effects on key venom enzymes and their ability to mitigate coagulopathy and cytotoxicity in vitro.

The third chapter investigates naturally derived phytocompounds, caffeic acid and ferulic acid, highlighting their potential as adjunct therapeutics, with notable inhibitory and cytoprotective effects against venom activity.

The final chapter focuses on venom-induced nephrotoxicity, a critical complication of viper envenomation, and assesses the protective role of SMIs in preserving renal tissue architecture and reducing histopathological damage.

Overall, this work integrates venom characterization with therapeutic evaluation, providing important insights into the mechanistic basis of venom toxicity and identifying promising candidates for adjunct or alternative snakebite treatments. These findings contribute to the advancement of more effective and region-specific strategies for snakebite management.

Macroevolution provides a lens to investigate how species originate, adapt, diversify, respond to environmental change, and go extinct over deep time. However, many of the processes that generate large-scale biodiversity patterns ultimately operate through population-level demographic and genetic dynamics. This doctoral thesis leverages tarantulas (family Theraphosidae)—one of the most iconic and globally distributed groups of spiders, as a model system to integrate macroevolutionary, macroecological and population genetic perspectives, thereby linking evolutionary processes across temporal and biological scales.
The first chapter reconstructs the complex biogeographic history of tarantulas, addressing the paradox of decoupled centres of origin and centres of diversity. Using fossil-calibrated phylogenies and model-based ancestral range reconstructions, it reveals how plate tectonics, and asymmetric dispersal shaped their global distribution, challenging classical expectations of diversification centered around regions of origin.
The second chapter examines the drivers of asymmetric species richness among tarantula subfamilies. By disentangling the effects of evolutionary time and trait-mediated diversification, it demonstrates that clade age is the primary determinant of species richness, while defensive innovations such as urticating hairs elevate net diversification rate. This chapter presents an empirical support for “key innovations” correlating with higher diversification.
The third chapter explores the interplay between morphology and ecology, focusing on patterns of miniaturization. It links repeated transitions to non-burrowing terrestrial microhabitats with reduced body size and altered limb proportions, illustrating how ecological opportunity can disrupt long-term stabilizing selection and generate novel phenotypes.
The fourth chapter investigates how recent climatic change has shaped genetic diversity and demographic history across latitudes in tarantulas. By integrating mitochondrial genetic data with ecological niche models projected onto past climatic conditions, it reveals latitudinal variation in demographic responses since the Last Glacial Maximum, connecting macroecological patterns with population-level processes.
The final chapter extends this framework using whole genome sequencing of a Western Ghat endemic tarantula species to show that long-term climatic instability can generate fine-scale genetic structure even in the absence of physical barriers. By linking paleoclimate dynamics to genomic diversity and demographic history, this chapter demonstrates how past habitat dynamics leave enduring signatures at the genomic scale.
Together, these chapters integrate deep-time evolutionary history with contemporary genetic processes, highlighting how geography, traits, ecological transitions, and climate interact across scales to shape biodiversity.

he New India Foundation, based in Bangalore, is a unique non-profit organisation that supports the writing of books on modern India. The NIF Fellowship empowers scholars financially and editorially to write books on post-1947 India. Hear more about the Fellowship, and why you should apply, from Nandini Nair, Associate Director NIF.
https://www.newindiafoundation.org/

Migration is a widespread phenomenon seen across diverse taxa. Species show much variation in migration traits, including the distance covered, social interaction and degree of participation. Migration is particularly interesting in birds because of the large variation in traits and vast geographical distribution of the birds that migrate. Avian migration is thought to have played a crucial role in shaping current avian biodiversity. Most research on avian migration has focused on understanding the causes and mechanisms underlying the evolution of migration. However, the evolutionary history of migration and its evolutionary correlations with associated factors have not been studied comprehensively. Tracing the evolutionary changes in migratory behaviour and its correlations with other factors can help us understand the evolutionary processes that led to the current distribution of migration in extant birds. For understanding such patterns, one needs to reconstruct the ancestral diversification of migratory behaviour using the phylogenetic relationships among extant birds. With around 10000 extant bird species in the world, examining such relationships poses a great challenge. The existing ancestral reconstructions of migratory behaviour have remained limited to a genus or family level and have used methods that do not assess gains and losses of the migratory behaviour over time. We, thus, lack a comprehensive and complete reconstruction of migration across all bird species. Therefore, during my PhD, I gathered data on all extant bird species globally and reconstructed the ancestral trajectory of migratory behaviour on a global phylogeny. For this, I used ancestral character state reconstruction (ACSR) methods in a likelihood framework. Since the efficiency of such methods for large datasets has not been tested systematically before, as a part of my thesis research, I also examined the robustness of ACSR to sampling and dataset properties. Hence, for the first chapter of my thesis, I examined the effect of taxon sampling and character evolution rate on ancestral character state reconstruction efficiency under a likelihood framework. For doing this, I used a simulation approach. I simulated phylogenies with a wide range of taxa, starting from 16 taxa to 16000 taxa. I also examined an extensive range in character evolution rate. The results show that ancestral character state reconstruction under a likelihood framework works best for large datasets and a low character evolution rate. In the second chapter of my thesis, I focused on understanding the evolutionary trajectory of migration. I also tested the effect of uncertainties and biases due to the behavioural data classification, phylogenetic topologies and ascertainment biases on inferences. I used the migratory behavioural data gathered for 9993 bird species and used ancestral reconstruction techniques to determine how migration evolved. The results suggest that migration is an old trait that over time has declined; that is, the rate of loss of this trait is substantially higher than the rate of gain, suggesting overall loss of migration. These results support the idea of a migratory drop-off. This result is robust to data uncertainty, phylogenetic uncertainty and ascertainment biases. In the third chapter, I aimed to understand the evolution of a common form of migration, namely, migrating in groups. Since social interactions are an important part of group migration, I tested whether another key behaviour that involves social interactions, namely foraging in groups, might facilitate the evolution of group migration. I first examined the evolutionary trajectory of group migration. I then tested for an evolutionary correlation between group foraging and group migration to check if group foraging could be one of the facilitators for the evolution of group migration. I extracted data on foraging for each species and used ancestral reconstruction and Pagel's correlation method to test my hypotheses. I found that group migration has evolved early among birds, similar to migration and shows a pattern of losses over time. There is a strong evolutionary correlation between group foraging and group migration, and additionally, there is weak support to show that group foraging may precede and, therefore, facilitate group migration. By comprehensively sampling all extant bird species, using ancestral character state reconstruction methods, and incorporating diverse sources of uncertainty, my thesis contributes towards understanding the evolutionary patterns of migration in birds.