Global oceanographic monitoring initiatives started by measuring abiotic essential ocean variables but are currently incorporating biological and metagenomic sampling. There is, however, a large gap between the taxonomic information produced by bacterial genomic analyses and information on bacterial functions, which is sought by biogeochemists, ecologists, and modellers. Here, we provide a mechanistic understanding of how a bacterial marker gene (16S rRNA) can be used to derive latitudinal trends for core metabolic pathways and, ultimately, be used for mapping ecosystem function change in global monitoring campaigns. From a transect spanning 7000 km in the South Pacific Ocean we identified ten metabolic pathways, which were related to ecological processes of primary productivity, temperature-regulated growth, coping strategies for nutrient limitation, energy metabolism, and degradation. We compared and contrasted these metabolic pathways with measured physico-biochemical parameters within and between oceanographic provinces, and found that functional diversity is as affected by oceanographic boundaries as is taxonomic composition. This study demonstrates that bacterial marker gene data, sampled and analysed with low costs and high throughput, can be used to infer on metabolic changes at the community scale. Such analyses may provide insight into the drivers of ecological changes and, overall, into the effects of biodiversity on marine ecosystem functioning.