On the Arctic shelves, the benthos plays an integral role in biogeochemical cycling and in channeling energy from primary producers to higher trophic level consumers. With accelerated environmental changes in the Chukchi Sea, an assessment of recent trends in biomass, composition, and diversity of the epibenthic fauna is timely and needed. We used epibenthic community data obtained from beam-trawl catches between 2009 and 2024 to model (Vector Autoregressive Spatio-Temporal modeling, VAST) trends in biomass and diversity over time and across the Chukchi shelf. We also modeled diversity, based on the Delta index, which takes taxonomic relatedness as well as evenness of biomass distribution of the taxa into account. We observed a 3-fold decline in epibenthic biomass on the Chukchi shelf between the years 2010 and 2012, after which biomass remained similarly low. Biomass declines were especially prominent in the northern Chukchi shelf region. Some of the biomass decline is the result of a decrease in brittle stars and snow crab. The decreases in these two taxa also contributed to the slightly greater Delta diversity in more recent years, reflecting a more even distribution of biomass across taxa. We discuss the potential influences of environmental drivers such as sea ice cover and warming temperatures on epibenthic communities but suggest that likely a combination of these environmental drivers may have caused the decline. It is possible that these combined environmental pressures and biological responses such as physiological constraints or environmental effects on recruitment or larval development may hint at a tipping point that caused the abrupt declines in epibenthic biomass.
The spatial distribution of Antarctic krill (Euphausia superba) is highly heterogeneous, making it essential to characterize biomass distribution and detect hotspots for ecological assessment and fisheries management. Although various hotspot analysis methods have been applied in previous studies, different approaches often yield divergent results. Moreover, the choice of spatial scale substantially influences hotspot detection, further complicating the interpretation and comparison of krill spatial patterns. The lack of systematic comparisons across hotspot analysis methods and spatial scales has hindered accurate characterization of krill spatial patterns. In this study, using KRILLBASE records from 2003 to 2011, we developed a multi-method, multi-scale analytical framework to systematically evaluate hotspot analysis methods and their sensitivity to spatial scale in the Northern Antarctic Peninsula. Our results show substantial inconsistency among hotspot analysis methods in hotspot detection, with the degree of divergence varying systematically across spatial scales. Rather than seeking to determine a single optimal approach, this study elucidates the applicability and scale dependence of different hotspot analysis methods. These findings provide a methodological reference for hotspot-based habitat identification and a scientific basis for spatial management in key krill fishing grounds.
Pelagic aggregation patterns in eastern boundary upwelling systems are associated with co-occurring hydrographic, dissolved oxygen, and trophic variation, yet interannual covariation between predator and prey aggregation states remains insufficiently quantified. Using integrated hydroacoustic, plankton-net, and environmental survey data collected during 2023–2025 off northern and central Chile (18.4–33.0°S), we examined associations between the jack mackerel (Trachurus murphyi) acoustic index (sA), euphausiid aggregation states, and contrasting oceanographic conditions across three consecutive assessment cruises.Both responses were classified into ordered Low, Medium, and High aggregation states and analysed against practical salinity, seawater density anomaly, temperature, dissolved oxygen, record-associated depth, distance to coast, and total zooplankton abundance. Models used a stratified random 75:25 split of the pooled 2023–2025 records and five-fold cross-validation within the training partition. This design evaluates discrimination within the sampled domain but provides neither temporal nor spatially independent validation.In the selected fitted-model diagnostics, record-associated depth and dissolved oxygen were the highest-ranked correlates for jack mackerel discrimination, while practical salinity and seawater density anomaly provided additional hydrographic contrasts among aggregation states. For euphausiids, total zooplankton abundance was the leading fitted-model correlate, although its interpretation is constrained by part–whole and shared-sampling dependence. Parallel associations for jack mackerel and euphausiids were ecologically consistent with trophic overlap, while differences among annual joint-state distributions co-occurred with broader oceanographic and productivity variation.These results describe associations of jack mackerel and euphausiid aggregation states with hydrographic structure, dissolved oxygen gradients, and variable plankton fields. Because the observations are spatially structured and station-based variables were interpolated or matched to acoustic sampling units, model importance and performance are interpreted as descriptive within-domain evidence rather than causal or transferable spatial inference.
