M. B. Joseph

Reintroduction of resistant frogs facilitates landscape-scale recovery in the presence of a lethal fungal disease

This study shows reintroducing Bd-resistant frogs can recover populations despite the disease, with genetic evidence of evolutionary resistance.

Data science competition for cross-site delineation and classification of individual trees from airborne remote sensing data

This paper runs a data science competition to improve methods for delineating and classifying individual trees from remote sensing data across multiple sites.

Effectiveness of antifungal treatments during chytridiomycosis epizootics in populations of an endangered frog

This study evaluates antifungal treatments for chytridiomycosis in frogs, finding that while treatments reduce Bd load temporarily, they fail to ensure long-term population persistence.

Data fusion for abundance estimation: community science augments systematically collected removal-in-time distance sampling data

The paper integrates removal-in-time distance sampling data with BBS and eBird data to improve abundance estimation for Grasshopper Sparrows.

Estimating occupancy dynamics and encounter rates with species misclassification: a semi-supervised individual-level approach

The paper develops a semi-supervised occupancy model that accounts for species misclassification and non-detection in biodiversity monitoring, showing improved classification performance for abundant species.

Predicting subsurface sonar observations with satellite-derived ocean surface data in the California Current Ecosystem

This study evaluates using satellite data to predict subsurface sonar biomass in the California Current Ecosystem with random forest models, finding limited predictive performance across sonar frequencies and depths.

Using visual encounter data to improve capture-recapture abundance estimates

This paper improves capture-recapture abundance estimates by incorporating visual encounter data, showing it increases precision when capture probabilities are low and surveys are few.

Neural hierarchical models of ecological populations

This paper introduces neural hierarchical models, combining neural networks with hierarchical modeling to analyze ecological population dynamics, demonstrating their effectiveness on bird population data.

Untangling the dynamics of persistence and colonization in microbial communities

This study introduces a dynamic statistical model to distinguish direct biotic interactions from shared environmental effects in microbial communities, applied to HPV coexistence data showing sparse direct interactions.

Spatiotemporal prediction of wildfire extremes with Bayesian finite sample maxima

This study predicts wildfire extremes in the contiguous US using Bayesian models, finding dryness, temperature, and housing density strongly influence fire occurrence and size.

Disease and climate effects on individuals jointly drive post-reintroduction population dynamics of an endangered amphibian

The paper analyzes the impact of disease and climate on the population dynamics of reintroduced amphibians using mark-recapture data.