The Arctic Ocean is changing rapidly, causing shifts in species composition and distributions. While a future "jellification" is projected on a pan-Arctic scale and within the Atlantic Gateway, we identified a regional anomaly within the Pacific Gateway, the narrowest and shallowest entrance to the Arctic Ocean. We investigated the environmental drivers shaping epipelagic gelatinous and soft-bodied zooplankton communities using data from 54 vertical net casts collected during the 2024 Arctic summer. A trait-based Joint Species Distribution Model was applied to 17 taxa encompassing five phyla-Cnidaria, Ctenophora, Tunicata, Chaetognatha, and Mollusca-integrated with eight environmental covariates and one life-cycle trait (meroplanktonic vs. holoplanktonic). We hypothesized that while standard oceanographic variables drive community-wide distributions, meroplanktonic taxa are specifically constrained by regional topography due to their limiting benthic stages. Spatio-temporal projections to 2100 under the CMIP6 SSP245 scenario revealed a widespread biogeographical contraction of suitable habitat. Most taxa (seven), particularly meroplanktonic ones such as Tiaropsis multicirrata and Sarsia tubulosa, showed significant decreases in probability of presence over time, while three taxa remained stable and two increased. These results indicate a future suitable habitat contraction in the Pacific Gateway, driven by a synergy of salinity-induced freshening and strict topographic constraints. Specifically, the transition from a shallow shelf to a deep basin acted as a selective environmental bottleneck, resisting the uniform expansion observed in other Arctic regions. While active predatory taxa, including most hydromedusae, ctenophores, and scyphozoans, were projected to decline, the trachymedusa Aglantha digitale and the pteropod Limacina helicina expanded their ranges, potentially reshaping future trophic dynamics. Our findings highlight the importance of integrating topography and life-history strategies alongside oceanographic variables to accurately predict biological responses within regional transition zones.
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