Mathematical and Theoretical Epidemiology and Ecology Models

This paper introduces two new population models to describe microbial growth and decay in batch bioreactors, incorporating memory effects through cumulative biomass.

This paper introduces label invariance as a principle for ecological models, showing it ensures consistency in dynamics across population groupings and aids in model selection and evaluation.

The paper links power, efficiency, and bifurcations in consumer-resource systems using mathematical models and shows how ecological principles can be formalized and tested.

This paper introduces a sequential Monte Carlo method for real-time parameter updating in a stochastic plant epidemic model, showing accurate convergence and forecasting capabilities.

This study shows that prey dropping behavior reduces food-chain persistence, with dropper treatments having higher extinction risk than mixed or non-dropper treatments.

This paper introduces ABC GP IPM, a flexible IPM framework using Gaussian Processes and Approximate Bayesian Computation to improve demographic modeling across species.

The paper examines how behavioral plasticity in animals can shift indirect interactions in ecological networks from competition to mutualism or parasitism through changes in predator-prey dynamics.

This study shows that increasing intraguild predation (IGP) in food webs leads to greater temporal variability in biomass across all trophic levels, potentially destabilizing ecosystems.

The paper introduces iPAR, a framework for estimating spatial disease dynamics without knowing the population at risk, and applies it to an ASF outbreak in Estonia.

The paper develops a continuous-time microparasite model that incorporates infection intensity and parasite aggregation, showing how these factors influence host-pathogen dynamics.

This paper challenges the assumption that resource fluctuations limit biodiversity by showing how species can coexist through specialization on different temporal resource patterns.

The paper derives a new functional response model for predators handling multiple prey and shows it can explain coexistence dynamics not captured by traditional Type I, II, or III models.

The paper shows eco-evolutionary feedback can destabilize community dynamics in complex systems, and warming exacerbates this effect.

The paper investigates the top-down mechanisms underlying the predator-prey power law by combining differential equations and agent-based simulations.

The paper infers pairwise bacterial strain interactions from population frequency data across multiple settings using a replicator dynamics framework applied to Streptococcus pneumoniae serotypes.

This study uses an agent-based model to simulate C. elegans populations and finds that chaotic dynamics emerge depending on culling parameters.

This study shows that population fluctuations favor the evolution of dormancy, which stabilizes dynamics and can lead to coexistence of dormancy strategies.

The paper proposes two rules to explain the scaling of trophic interaction strengths using predator functional responses, validated across 2,100 experiments.

This paper introduces a model to study microbial community dynamics by focusing on physiological state transitions rather than fixed interactions, identifying key features of dynamic coexistence.

The paper introduces a framework to predict species persistence after invasion by analyzing community structure and interaction patterns, demonstrating its application in ecological systems with fluctuating abundances.

The paper develops an eco-evolutionary model to study anthelmintic resistance spread in helminths, finding that life cycle parameters influence resistance spread rates across species.

This paper shows that evolving motility in predator-prey interactions prevents Turing patterns and promotes dynamic patterns like waves, extending beyond classical ecological models.

The paper develops a model showing viral evolution balances transmissibility and immune evasion, leading to convergence, periodic patterns, or chaos depending on the trade-off.

The paper extends the Marginal Value Theorem to simple organisms with limited sensory abilities, showing that adjusting feeding speed based on environmental average feeding rates improves foraging efficiency.

This paper provides a guide to implementing individual-based simulations in continuous landscapes, focusing on population dynamics and ecological applications.

The paper models phage-bacteria coexistence in microcolonies, showing that external bacterial influx affects colony size distribution and steady-state dynamics.

EEMtoolbox is an R package that enables flexible ensemble ecosystem modeling using either accept-reject or sequential Monte Carlo methods, supporting multiple model structures for conservation applications.

This paper develops a theory to model how correlated host movements affect disease transmission risk, showing that even weak correlations can significantly increase transmission compared to independent movements.

The paper examines how a resistant host compartment influences virulence evolution in migratory populations using an SIRS model, finding that longer residence in the resistant class promotes more virulent pathogens.

This paper shows that deterministic optimal control strategies are insufficient for eradicating stochastic disease epidemics and proposes heuristics that outperform Model Predictive Control in such scenarios.