Sylvester, Zephyr T.; Dinniman, Michael S.; Thorpe, Sally E.
ORCID: https://orcid.org/0000-0002-5193-6955; Bernard, Kim S.; Brooks, Cassandra M..
2026
Modeled connectivity of Antarctic krill spawning and nursery grounds along the Western Antarctic Peninsula.
Marine Ecology Progress Series, 779.
18, pp.
10.3354/meps15059
Abstract
Understanding the connectivity between spawning and nursery grounds of Antarctic krill Euphausia superba is essential for elucidating population dynamics and informing ecosystem-based management of krill. This study employed a regional ocean model and particle tracking to investigate larval krill transport and connectivity along the western Antarctic Peninsula (wAP), a key region for Antarctic krill, over 3 austral summers (2016-2019). Simulations incorporated the descent-ascent cycle of early larval development based on initial embryo sizes, along with varying larval behavior, to examine how physical and biological processes affect habitat connectivity. Results revealed that nursery ground use and retention times were closely linked to local bathymetry. Deeper regions, such as the Bransfield Strait and Marguerite Bay, retained larvae for longer durations (>50 d), while shallower nursery grounds (Gerlache Strait, Grandidier Passage) acted as secondary nursery habitats in simulations with smaller initial embryo sizes. Simulations with larger initial embryo sizes led to notable changes in retention, connectivity, and spawning locations, as more embryos successfully hatched before reaching the seafloor. Interannual wind variability emerged as a key driver of larval supply pathways, influencing connectivity between spawning areas and nursery grounds. These results highlight how a shallower hatching depth expands the range and reliability of the connectivity between spawning and nursery grounds in the wAP. By illustrating how physical forcing and biological traits jointly shape connectivity and retention between spawning and nursery grounds, this study emphasizes the importance of integrating biological parameterization with physical modeling to better understand krill population dynamics.
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