Southern Ocean larval fish communities remain poorly understood because systematic sampling across spatial and temporal scales is logistically difficult. During an RSV Nuyina voyage to Heard Island and Casey research station, passive underway sampling through the ship’s wet-well system collected more than 240 larval fishes, largely as bycatch from other activities. This collection demonstrates the potential to develop voyage sampling into a repeatable observing program.
We propose establishing a medium- to long-term program that standardises wet-well sampling and metadata collection during future Nuyina voyages. Species will be identified using morphological and molecular approaches and linked to sampling effort, location, season and environmental observations, including temperature, productivity, sea-ice conditions, fronts and water masses.
The program will document which species occur along voyage routes, identify areas of elevated abundance and examine assemblage composition across environmental gradients. Community analyses will investigate whether distinct larval assemblages or biogeographic zones can be detected and identify their characteristic species. Repeated sampling will explore whether occurrence, abundance and community composition vary among voyages and years and whether distributions are associated with oceanographic features.
Sampling will be opportunistic and restricted to vessel tracks, limiting spatial coverage and the power to distinguish temporal change from variation in routes, seasons and sampling effort. Unlike the automated Continuous Plankton Recorder, wet-well collection currently requires personnel to undertake sampling; consistency will therefore depend on voyage activities and staff availability. Standardised methods and effort records will be essential, while options for automated collection will be investigated.
Initial analyses will include occurrence mapping, clustering and multivariate community analysis. As observations accumulate, their suitability for spatiotemporal models and, ultimately, a joint species distribution model integrating species, environmental conditions, space and time will be evaluated. The program will improve understanding of spawning, dispersal, recruitment and ecosystem connectivity while establishing a baseline for detecting climate-related change.