Oceanic diel vertical migration (DVM) constitutes the daily movement of various mesopelagic organisms migrating vertically from depth to feed in shallower waters and return to deeper water during the day. Accurate classification of taxa that participate in DVM remains non-trivial, and there can be discrepancies between methods. DEEPEND consortium (www.deependconsortium.org) scientists have been characterizing the diversity and trophic structure of pelagic communities in the northern Gulf of Mexico (nGoM). Profiling has included scientific echosounders to provide accurate and quantitative estimates of organismal density and timing as well as quantitative net sampling of micronekton. The use of environmental DNA (eDNA) can detect uncultured microbial taxa and the remnants that larger organisms leave behind in the environment. eDNA offers the potential to increase understanding of the DVM and the organisms that participate. Here we used real-time shipboard echosounder data to direct the sampling of eDNA in seawater at various time-points during the ascending and descending DVM. This approach allowed the observation of shifts in eDNA profiles concurrent with the movement of organisms in the DVM as measured by acoustic sensors. Seawater eDNA was sequenced using a high-throughput metabarcoding approach. Additionally, fine-scale acoustic data using an autonomous multifrequency echosounder was collected simultaneously with the eDNA samples and changes in organism density in the water column were compared with changes in eDNA profiles. Our results show distinct shifts in eukaryotic taxa such as copepods, cnidarians, and tunicates, over short timeframes during the DVM. These shifts in eDNA track changes in the depth of sound scattering layers (SSLs) of organisms and the density of organisms around the CTD during eDNA sampling. Dominant taxa in eDNA samples were mostly smaller organisms that may be below the size limit for acoustic detection, while taxa such as teleost fish were much less abundant in eDNA data compared to acoustic data. Overall, these data suggest that eDNA, may be a powerful new tool for understanding the dynamics and composition of the DVM, yet challenges remain to reconcile differences among sampling methodologies.