L. Karp-Boss

The paper analyzes global ocean data to show that physical and biological patchiness are decoupled, using variance slope to quantify spatial patterns.

The paper compares methods for determining phytoplankton community composition, finding strong correlations for some taxa but not others, and highlights implications for ocean color remote sensing.

The paper uses satellite data and machine learning to predict global plankton community distributions with 67% accuracy, outperforming temperature and chlorophyll a alone.

The paper develops an ecosystem model that sustains phytoplankton diversity across size classes under varying nutrient concentrations, challenging previous assumptions about resource-based competitive exclusion.

The paper analyzes plankton genomic distribution across oceans to show how large-scale currents shape biogeography, revealing size-dependent patterns and basin-scale transport effects.

The paper assesses the vulnerability of the global ocean plankton community interactome to environmental change using niche modeling and Tara Oceans data.

The paper reconstructs metagenomic bins from Arctic Ocean samples to characterize microbial communities and their metabolic capabilities, identifying novel species and active MAGs that may serve as climate change sentinels.