Aaron M. Ellison

The paper introduces a triple power law methodology integrating Taylor's, Smith's, and diversity power laws to analyze diversity and heterogeneity in microbial ecosystems using human gut and vaginal microbiome data.

This paper introduces a methodology for estimating, testing, and inferring network heterogeneity in ecological systems using the Earth Microbiome Project dataset.

This study shows herbarium specimens reliably track plant phenological responses to climate change in montane biomes, matching direct observations in some aspects but showing differences in sensitivity estimates.

The paper develops phenology-informed species distribution models that predict lower species loss and turnover under climate change compared to standard models.

The paper sequenced six Aphaenogaster ant genomes across a latitudinal climate gradient and found genome size correlates with minimum temperature, suggesting temperature extremes may influence genome evolution.

The paper uses metaproteomics to identify biomarkers of ecosystem state changes in aquatic systems caused by detrital enrichment.