M. A. Matias

Mapping the distribution of seagrass meadows from space with deep convolutional neural networks

This paper develops a deep learning framework to map seagrass meadows using satellite imagery and a georeferenced dataset, improving scalability and accuracy for conservation monitoring.

High-resolution climate data reveals increased risk of Pierce's Disease for grapevines worldwide

The paper uses high-resolution climate data to show increased risk of Pierce's Disease in global wine regions under climate change.

Contrasting Patterns of Pierce's Disease Risk in European Vineyards Under Global Warming

This study assesses future Pierce's Disease risk in European vineyards under global warming, identifying a +3°C temperature threshold for expanded spread beyond Mediterranean regions.

A compartmental model for Xylella fastidiosa diseases with explicit vector seasonal dynamics

This paper develops a compartmental model for Xylella fastidiosa diseases that incorporates seasonal vector dynamics and validates it against epidemiological data from two outbreaks.

Global predictions for the risk of establishment of Pierce's disease of grapevines

The paper builds a dynamic epidemiological model to predict the global risk of Pierce's disease establishment in grapevines, showing expansion of epidemic-risk zones by 2050.

Spatial effects in parasite induced marine diseases of immobile hosts

This study develops a spatially-explicit model to analyze how parasite mobility affects disease transmission in sessile marine hosts, showing that higher mobility leads to more severe epidemics and faster extinction.