Supplemental data for 'Earth-Observation and 'Earth-Observation and Environmental Vision Transformers Reveal Genome–Environment Associations in Macroalgae'

Macroalgae thrive in extreme environments, yet the genomic basis of their tolerance remains poorly resolved. We described nine Arabian Gulf macroalgae and integrated them with 117 published genomes (126 total; 70 Rhodophyta, 43 Ochrophyta, 13 Chlorophyta) to test genome–environment associations using a dual-scale framework: Google Earth Engine (GEE) for broad-scale oceanography and 10-meter resolution AlphaEarth Foundations (AEF) embeddings for fine-scale habitat heterogeneity. We identified 157 significant correlations with global GEE variables—including a strong negative temperature association with DUF3570—while AEF embeddings uncovered over 1,000 lineage-specific signals within Rhodophyta and identified climate-driven Pfam modules. The von Willebrand factor type-A domain emerged as uniquely robust across all frameworks and enriched in Arabian Gulf species. Given the Arabian Gulf environment, this may reflect selection for stronger, more tunable adhesion to substrates and tissues in conditions of high temperature and high salinity stress. These results demonstrate that converging remote sensing with deep learning identifies conserved and lineage-specific genomic signatures of ecological differentiation across diverse macroalgal lineages.