Our research seeks to improve the understanding of the interactions within and beyond tropical coastal areas using modeling. We use a variety of modeling approaches (conceptual, mechanistic, empirical, data-driven, numerical) to theoretically investigate the complexities of coastal ecosystems, socio-economic communities, social-ecological networks, climate, resource management and biodiversity.
A special emphasis is on addressing processes across spatial and temporal scales: in ecology, these can range from metabolic processes to organismal, communities and ecosystems. In the climate system and biogeochemistry, scales often span the entire cascade of energy dissipation, from global to the molecular dissipation scale.
Our research is curiosity-driven and highly inter-disciplinary and encompasses a range of methodologies from applied mathematics and complex systems analysis. We use agent-based models or cellular automata to explore emergent phenomena and for treating non-ergodic, computationally irreducible complex systems (e.g., social or ecological systems). We employ dynamical models to investigate systems that can be described with mean-field approaches and equilibrium theories (such as predator-prey interaction or weather). We apply graph theoretical methods to address network-structured data or problems such as trophic structures and energy flow through foodwebs. We further use modern statistical learning tools such as deep learning and data engineering to form predictive statistical models.