O. J. Robinson

This study improves species distribution estimates from eBird data by refining data processing and addressing biases, showing that complete checklists and effort covariates enhance model performance.

This study integrates citizen science data with expert surveys to improve the accuracy and spatial coverage of species distribution models for shorebirds in California.

This study translates a rodent negative affective bias measure to humans, finding increased bias and reduced drift rate in those with mood/anxiety symptoms, but no effect from induced anxiety.

The paper uses eBird citizen science data in integrated population models to estimate population trends and identify conservation strategies for tricolored blackbirds.

This study uses reinforcement-learning models to analyze avoidance behavior in anxious individuals under stress, finding increased reliance on a Pavlovian bias parameter in the anxious group.