DEPARTMENT OF COMPUTATIONAL AND DATA SCIENCES
Ph.D. Thesis Colloquium
Speaker : Ms. Anjali. P
S.R. Number : 06-18-01-10-12-20-1-18580
Title : “Human-Wildlife Conflict Modeling and Mitigation: Integrating Agent-Based Simulations, Green Security Games, and Climate Change Analysis”
Research Supervisor: Dr. Deepak Subramani
Date & Time : October 15, 2025 (Wednesday), 10:00 AM
Venue : #102, CDS Seminar Hall
ABSTRACT
Human-Wildlife Conflict (HWC) represents one of the most pressing challenges in biodiversity conservation, particularly in a changing climate, and requires innovative strategies for effective management. This thesis develops and applies Agent-Based Models (ABMs) to understand complex socio-ecological systems experiencing HWC, focusing on two key species: Asian Elephants (Elephas maximus) in the Periyar-Agasthyamalai complex of the Western Ghats and Saltwater Crocodiles (Crocodylus porosus) in the Andaman and Nicobar Islands (ANI). ABMs provide a flexible framework that captures individual differences, social structures, and decision-making processes, making them particularly well-suited for modeling the heterogeneity inherent in these conflict scenarios. Given the distinct ecological contexts and conflict dynamics of these two species, the thesis is structured into two parts, each addressing unique research objectives tailored to the specific challenges of the Human-Elephant Conflict and the Human-Crocodile Conflict problems. Furthermore, ABMs are integrated with a novel green security game formulation to learn effective mitigation strategies for the Human-Elephant Conflict problem. The impact of climate change on the management strategies of the crocodile population is analyzed to recommend science-based data-driven policy for conservation.
The first part of the thesis focuses on Human-Elephant conflict (HEC). We first developed a Random Forest model to estimate the species distribution of Asian elephants in India and examine inter-annual and intra-annual spatiotemporal variability in suitable habitats. Using climatic variables, topographic conditions, and satellite-derived metrics (land use/land cover, net primary productivity, leaf area index, and normalized difference vegetation index) as predictors, alongside species sighting data from the Global Biodiversity Information Reserve, we found that seasonal reductions in suitable habitat may explain elephant migration patterns. Alarmingly, the total available suitable habitat area has declined, further exacerbating HEC.
Building on this foundation, we developed a spatially explicit ABM for Seethathode, Kerala, India, where HEC is a recurring concern. Unlike existing models that only consider food scarcity as a conflict driver, our ABM incorporates a broader range of factors that influence elephant movement: crop habituation, risk-taking behavior, seasonality, and thermoregulation requirements. The prototype ABM was developed to simulate interactions between humans and solitary bull elephants, addressing two main challenges: the complex behavior of elephants and insufficient movement data from the region. Using data from the extensive literature survey, expert insights, and field surveys, we created a behavior model that incorporates crop habituation, thermoregulation, and aggression. To develop the movement model, we designed a four-step calibration method to adapt relocation data from radio-tagged elephants in Indonesia to the model domain. The ABM’s structure, including assumptions, submodels, and data usage, is detailed following the Overview, Design concepts, Details (ODD) protocol. The ABM simulates various food availability scenarios to study elephant behavior and environmental impacts on space use and conflict patterns, successfully reproducing observed movement patterns and revealing the emergence of HEC hotspots within the study area. The simulation results indicate that wet months increase conflict and that thermoregulation significantly influences elephant movements and crop raiding patterns, with starvation and crop habituation intensifying these patterns. This prototype ABM represents an initial model for developing a decision support system in wildlife management that will be further enhanced with layers of complexity in various dimensions.
We then investigated the spatial dynamics of HEC under different water availability scenarios. The main objective was to examine how artificial water sources (water holes) and natural water sources (rivers and streams) affect the spatial distribution of elephants and crop-raiding incidents within the study area. Numerical experimental results emphasize the role of water availability in the evolution of the elephant trajectories. Our findings suggest that crop raiding is not only a foraging behavior but also occurs opportunistically as elephants move into human settlements to access water sources. We also studied the spatial scales at which the ABM generates biologically plausible trajectories by investigating the elephants’ frequency of visits to water sources. This study offers a valuable framework for understanding the dynamics of HEC and implies that effective conservation and conflict mitigation strategies could depend on strategic water management.
Finally, we framed HEC as a challenging variant of a green security game where elephants strategically target crops and water sources, while defenders must allocate scarce patrol resources to protect forest-agricultural boundaries. Unlike typical security game settings, HEC involves adaptive opponents with uncertain behavior and significant observability limitations. We adapted the Follow-the-Perturbed Leader with Uniform Exploration (FPL-UE) algorithm for HEC mitigation, making three key contributions to online green security games: (1) reformulating the defender’s problem for adversarial settings with partial observability, where elephant strategies remain largely unknown; (2) developing a dynamic mechanism for learning and updating rewards and penalties associated with covered and uncovered boundary patches in real-time as elephants adapt to guard deployments; and (3) validating our approach using the calibrated ABM, demonstrating convergence properties against multiple adversarial models. This work presents a first-of-its-kind game-theoretic solution verified against realistic opponent adaptation in the human-wildlife conflict domain, extending security game theory to ecological adversaries with emergent learning behaviors and opening new research directions in adaptive resource allocation under model uncertainty.
The second part of the thesis focuses on Human-Crocodile Conflict (HCC). HCC represents a significant wildlife management issue in the ANI, where saltwater crocodiles are responsible for more human deaths and injuries than any other crocodilian species. The spatial overlap between human populations and optimal crocodile habitats creates a concentrated conflict zone requiring urgent management strategies. The ANI provides an ideal habitat for saltwater crocodiles due to its unique geographical and ecological characteristics. The growing ANI crocodile population may potentially worsen HCC in the coming years.
We developed a prototype ABM to study crocodile population dynamics and demographic changes in the South Andaman Islands, incorporating territorial behavior, site fidelity, and dominance hierarchies observed in saltwater crocodiles. These factors influence population counts by shaping space use. The ABM represents demographic processes without extensive parameterization requirements typical of Population Matrix Models, which is significant given that crocodile population census surveys are massive undertakings with inherent difficulties in accurately quantifying size classes in wild populations. The ABM also integrates temperature-dependent sex determination, where ambient and nest temperatures affect hatchling sex ratios, skewing populations toward females. We investigated how these factors influence population dynamics and their potential contribution to future HCC. Our projections indicate that rising temperatures will drive a significant demographic shift, favoring the production of male crocodiles, which are the highest threat group involved in HCCs. This study marks a significant methodological leap for crocodilian ecology, representing one of the first population models specifically tailored to the unique demographic and environmental constraints of small localized populations such as those found in the South Andaman Islands.
The final component of the thesis focuses on policy recommendations for managing HCC using our ABM. Historically, successful HCC mitigation strategies have controlled population size through adult culling or egg harvesting. Other methods, such as removing and relocating problematic adults, have proven ineffective as removed individuals either return upon re-release or are replaced by other dominant males. Our ABM effectively captures these aspects of territoriality and space use. We determine the minimum necessary intervention required that could potentially yield the maximum possible reduction of HCCs by controlling the demographic growth. The ABM also allows us to study the differential implications of targeted interventions in various demographic groups for long-term population stability and HCC mitigation. Currently, effective data-driven management strategies for HCC are absent in the ANI. Our study is the first evidence-based initiative that aims to generate the data necessary to establish sustainable policies for long-term HCC management.
ALL ARE WELCOME
