Ecological dynamics and predictive modeling
Project Overview
Phytoplasma transmission is governed by ecological processes operating across spatial and temporal scales. While evolutionary history shapes long-term diversification, short-term ecological dynamics, including host switching, vector dispersal ability, and pathogen-induced behavioral manipulation determine when and where novel pathogen–host associations emerge.
This research theme investigates how ecological interactions, environmental variability, and landscape structure interact to influence transmission dynamics and the establishment of emerging and re-emerging disease systems. By integrating mechanistic modeling with empirical data, we aim to move from descriptive association patterns to predictive frameworks of pathogen spread.
Research Questions
- How does ecological host switching influence transmission dynamics?
- Does phytoplasma-induced behavioral modification increase the probability of colonizing novel hosts?
- How do movement behavior and landscape structure shape transmission risk?
- Under what ecological conditions do host repertoire expand or contract?
Approach
We use individual-based models (IBMs) and machine learning approaches to evaluate the mechanisms driving host switching and to quantify how climatic and landscape variables influence the risk of emerging and re-emerging disease through novel pathogen–host associations.
Broader Impact
By linking evolutionary processes, behavioral ecology, and predictive modeling, this work advances mechanistic understanding of pathogen emergence. The integration of empirical experiments with simulation-based forecasting supports proactive disease management and informs landscape-level intervention strategies.
🎵 Bonus Music Track
Struggle for Pleasure – a metaphor for host manipulation