Connectivity is considered to be essential in enhancing biodiversity conservation efforts and for benefiting adjacent areas. In the marine environment, connectivity among populations arises from dispersal during the larval stage for most sedentary species and particularly among sessile benthic invertebrates. Offspring released into the water column are transported and dispersed almost passively by water flow due to limited larval motility as compared to the horizontal flow speed. As a consequence, the spatio-temporal variability of hydrodynamics primarily shapes larval transport, which is the integration of larval dispersal over the pelagic larval duration of a species. Ocean modelling works well for hindcasting realistic coastal circulation, and can provide a comprehensive description of flow variability at high spatial and temporal resolutions, which improves the description of larval transport. In this talk, I will examine how larval transport estimates derived from bio-physical modelling can be useful to marine biodiversity conservation through the design of Marine Protected Areas (MPAs), by taking examples from the Mediterranean Sea. Species persistence in both isolated MPAs and in a network of MPAs will be discussed.

Wings in insects come in many forms. I will show how coloration and wings in insect wings are shaped by different and conflicting selection pressures. I will do this by presenting results and conclusions from several studies. 1) By estimating damselfly wing reflectance, and use receptor noise models we have explored the visual discriminability of wing coloration in a three level system: bird, damselfly and fly. Results show that males are more discriminable. 2) I will also show how bird predation selects for wing shape and wing coloration in a damselfly system. 3) By using a phylogenetic approach we have shown that wing shape and wing coloration are associated. Our results show interesting differences in wing shape among species that probably are shaped by sexual selection. 4) Finally, I will present results from a study exploring how range size and migration affects wing shape in North American dragonflies.

Phylogeography is an important tool when studying how genetic variation is distributed in space within and among species. In a conservation genetic context, phylogeographic information can be used to identify Evolutionary Significant Units and Management Units. Such are important when identifying unique evolutionary lineages among species and when preserving local adaptations.

In this talk I will present my research on the phylogeography of two closely related cold adapted grouse species: the willow grouse (Lagopus lagopus) and the rock ptarmigan (L. muta). I will show that local rock ptarmigan populations are highly differentiated and while such structure also can be revealed among willow grouse populations the phylogeographic signal is often less clear. This is what is expected from microhabitat use and the extent of habitat distribution of each species. Nevertheless, local adaptation to climate can be seen in peripheral some populations on the British isles where whole genome data suggest differentiation among a number of candidate genes but also regions of the genome with low variation.

This thesis is spurred by the overarching question “why is a plant where it is in space and time?”, asked in the context of a tropical dry forest plant community in southern India, based on long-term research conducted in a large (0.5 km2) permanent sampling plot. We attempted to deconstruct the structure and dynamics of the plant community by first establishing the spatial structure of soils, topography and lithology in the plot. We then assessed how this spatial structure, together with temporal variation in precipitation, affected abundances of the eight most dominant species in the plot. Finally, we broke up abundance variation into the components of recruitment, mortality and stem radial growth and assessed how these respond to variation in environmental factors (precipitation, temperature, soils, topography and fire) and biotic neighborhoods.

Local-scale lithological variation was an important first-order control over soil variability at the hillslope scale in this tropical dry forest, by both direct influence on nutrient stocks and indirect influence via control of local relief. Species separated into two broad groups in niche space – one consisting of three canopy species and the other of a canopy species and four understory species – along axes that corresponded mainly to variation in soil P, Al and a topographic index of wetness. Our results suggest that this tropical dry forest community consists of several tree species with broadly overlapping niches, and where significant niche differences do exist, they are parsimoniously viewed as autecological differences between species that exist independently of interspecific interactions. Temporal environmental factors (time since last fire, precipitation, and minimum and maximum temperatures) appear to be the strongest drivers of dynamics in this community, followed by conspecific and heterospecific neighborhoods, followed by spatial environmental factors (soils and topography). It is hoped these results will provide information relevant to understanding, managing, and predicting the future of this ecosystem and contribute towards the development of general theories of plant community ecology

Hi! My name is Sandhya and I am an alumnus of CES. I passed out in 2013, and I transitioned into a career in popular science.
In this talk, I will wander through my career trajectory from academia to science writing, a detour into entrepreneurship and onto my current role as Programme Manager for
Mongabay-India. It all may look neat when summed up in one line, but I will share the questions and doubts that were an integral part of this journey. It will not be all
about me though -- I will entertain questions throughout and try to put across larger themes that everyone can take home and adapt to their individual journeys.

Ecosystems can exhibit multiple stable states at similar external conditions. Such systems shift from one stable state to another abruptly and discontinuously, when they cross certain threshold parameters. Some examples of such abrupt shifts include coral bleaching, woodland encroachment of grasslands and desertification in semi-arid ecosystems. These transitions in ecosystems are often associated with loss of biodiversity and economic impacts, therefore are important to predict. These systems with multiple stable states, in some cases, can be understood as systems with a free energy functional having multiple local minima. In this theoretical framework, these abrupt transitions in ecosystems are similar to the discontinuous or first order phase transitions. In this thesis, we use the tools from the theory of non-equilibrium phase transitions to understand the mechanisms that cause abrupt transitions in spatially extended ecosystems and the statistical properties of these systems which can help us predict them.

Previous studies have shown that strong local positive feedback among individuals is an important mechanism for systems to have multiple stable states. In our study, we use a lattice based model of vegetation dynamics with basic processes as birth, death and positive feedback among individuals. In its simple version, this model is in the same universality class as directed percolation which is well known to exhibit a continuous phase transition from an active state to an absorbing state. Using master equation expansion for finite sized systems, we construct stochastic differential equations for our discrete state lattice model. We analytically show that systems with finite size can have multiple stable states even in the absence of positive feedbacks. Our numerical simulations of the spatial models confirm these results. Small sized ecological systems, therefore, can undergo discontinuous transition from an active high density state to a bare state where larger ecosystems would have survived.

It is well-known that systems close to a continuous phase transition show slow recovery from the perturbations. This phenomenon is known as critical slowing down. Since ecological systems are finite in extent and rarely in steady states, signatures of critical slowing down are seen before the discontinuous transition as well. In spatial systems, critical slowing down manifests as increase in spatial correlations and spatial variance in the system. Theoretical studies have shown that these signatures can be used as early warning signals for the imminent transitions. These spatial signals have been tested in microbial systems in lab, but few studies show their validity in the field. We hypothesize that above spatial metrics increase when a transition occurs along the gradient of driver in space. We first test this “space-for-time substitution” in a lattice model where driver changes along space. This model shows a transition from one state to another across space. We show that spatial metrics like variance and correlations show an increase even before the transition along the spatial gradient of driver. We, then, test these theoretical predictions in a savanna ecosystem using remotely-sensed and the ground-truthed data. In this ecosystem, grassland and woodland states co-occur at similar rainfall values and the abrupt transition occurs along the rainfall gradient in space. We show that critical slowing down based spatial indicators show theoretically expected trends before the transition. Therefore, we argue that simple spatial metrics can be used to anticipate the abrupt shifts in large-scale ecosystems.

In addition to the early warning signals, it is important to quantitatively estimate the threshold parameter at which the system is likely to shift to another state. To estimate this threshold, we use the property of phase transitions that systems show diverging correlations at the critical point. Therefore, in finite ecosystems showing alternative stable states, we hypothesize that the spatial location at which variance and correlation in the state variable are maximum will be closest to the transition. We used a spatially-explicit model of vegetation dynamics in which the driver value shows a gradient in space. We show that the point at which spatial variance and correlation in vegetation are maximum, is indeed the critical point of the system. We then test this method of finding the critical point in real ecosystems by analysing spatial data from regions of Africa and Australia that exhibit alternative vegetation biomes.

In summary, we employ a model from non-equilibrium statistical physics to understand abrupt transitions in ecological systems. We show that stochasticity caused by finite sized systems can lead to abrupt transitions in spatial ecosystems. We suggest simple spatial metrics to quantify critical points in real ecosystems, offering a significant advance from current studies that only proposed qualitative metrics of proximity to critical points. This thesis presents an elegant example of how principles of nonequilibrium phase transitions can be applied to a complex biological system, by modelling and testing their predictions with data from ecosystems.

The expectation that dispersal abilities evolve in response to resource dispersion is implicit in theoretical treatments of dispersal evolution but scant empirical evidence supports this claim. Further, constraints on dispersal trait expressions likely influence dispersal evolution. Dispersal is also expected to have implications for community membership via species sorting, but its influence on community trait distributions via an adaptive response to a selection pressure has never been investigated. Fig–fig wasp systems are multitrophic insect communities obligately associated with a single Ficus species. Wasps depend entirely on the fig microcosm for development and mating and exhibit varied life-history strategies. Only females disperse from natal figs to other figs for oviposition; inter-specific variation in oviposition resource availability is the result of fig flowering phenology and the unique association of each species to a fig developmental stage (oviposition window, OW) when it is suitable for oviposition.

Using simulations of fig phenology in a spatially implicit landscape and by incorporating known phenological parameters of Ficus racemosa, we demonstrate that despite stochasticity in resource initiation, smaller OWs reduce wasp colonization success independent of the spatial dispersion of host plant species. These results have profound implications for the persistence of species within the community.

By measuring dispersal traits such as tethered flight durations, metabolic rates and available flight fuel of the wasp community of F. racemosa, we find a negative relationship between dispersal traits and OW. However, our data also indicate phylogenetic and life-history constraints on dispersal trait expression.
By investigating a sister wasp community associated with a spatially clumped host plant (Ficus hispida) we demonstrate that the entire F. hispida wasp community exhibited lower dispersal capacities than that of the more widely dispersed F. racemosa.

Our work shows that resource dispersion selects for dispersal in natural communities and that community functional trait distributions can be influenced by an adaptive response of community members to ecological selection pressures.

An important area of interest in behavioural ecology is to understand the large diversity in traits related to reproduction and one explanation is that this diversity is adaptive and is shaped by natural selection. In wild populations, multiple selection pressures are likely to shape trait evolution. While these multiple selection pressures can manifest through different ecological or demographic conditions, these conditions themselves could vary predictably over space or time, or in an unpredictable manner, a relatively less studied form of environmental variability.

​In my thesis, I attempt to understand how oviposition site selection, a behaviour where multiple selection pressure regimes are rarely considered, is shaped by multiple factors in a variable environment. Using Aedes aegypti and Ae. vexans as model systems, I first measured fitness trade-offs associated with larval predation risk and conspecific competition risk at potential oviposition sites through experimental manipulation in the laboratory. I also quantified spatial and temporal variation in two risk factors, pool desiccation risk and larval predation risk, through an observational study under natural conditions. Considering these trade-offs, I predicted and tested female oviposition site selection response to these varying multiple risk factors in the field. My findings indicate that oviposition site selection responses are complex, sensitive to interactions between multiple risk factors and influenced by patterns in variability in some of these factors.

As a visiting doctoral student at IISc (2010-14) , I and my collaborators had two major streams of research. First, we attempted to understand whether elephants were functionally unique or redundant as seed dispersers in Buxa Tiger Reserve, testing the ecological theory and intuition that physiologically and behaviorally distinct species are also functionally non-redundant. Realizing that human activities near Buxa had drastically altered the forest's seed dispersal ecology, I began wondering how ecological communities might be restored in a way that is fair to local human communities. I conducted research on how purportedly voluntary village relocation from Melghat Tiger Reserve had affected socioeconomic outcomes for relocated and non-relocated villagers. After reviewing the main results from these efforts, I will explain how I hope to combine functional ecological and socioeconomic inquiry to understand how conservation interventions affect both people and ecological processes.

Structured Decision Modelling: Making Science-Based Conservation Decisions

It is becoming increasingly recognised that we need structured approaches to scientifically and transparently make conservation decisions. I will talk about Adaptive Resource Management, and Structured Decision Modelling, two linked approaches that simultaneously achieve a dual objective. First, it uses scientific information and understanding to direct conservation decisions, and second, it treats conservation decisions as natural 'experiments' to further our scientific understanding of species population dynamics. I will explain the process involved in implementing Adaptive Resource Management, in the particular context of waterfowl management. I will show how science was used to decide on hunting regulations, while simultaneously, monitoring of waterfowl allowed us to understand the impacts of hunting on waterfowl population dynamics. I will also talk to different forms of uncertainty in conservation decision-making and provide examples for each type of uncertainty. Using an illustrative example, I will then describe how Stochastic Decision Modelling uses science to direct conservation decisions. I will explain the utility function, and how it can be modified to consider future benefits, in addition to current benefits. I will cite an example of the use of Structured Decision Modelling to decide on tourism regulations in Denali National Park, such that impacts on the golden eagle Aquila chrysaetos are minimal. I will conclude by detailing the utility of such a framework for conservation contexts of India.