The integration of available sources of information is a challenge for any attempt to know dynamics populations
for Antarctic Krill (Euphausia superba) in an integrated stock assessment model. Being able to identify
sources of information, systematize and integrate it in a model and estimate krill population variables in
a context of change and fisheries management is vital for management and decision making. The analysis
represents a modern approach for stock assessment of complex dynamics such as krill and the integration of
ecosystem components as environmental variables and ecological aspects such as predators. We have three
main objectives. i)integrate fishing, environmental and ecological variables in an integrated stock assessment
model and test his performance; ii) to consider the spatial heterogeneity of the krill population structure and,
iii) to evaluate the impact of biological and population structure assumptions on the performance of this
type of integrated stock assessment models. Consequently, by acknowledging and integrating different data
sources, the stock assessment model can provide insights into the ecological dynamics of krill populations and
improve CCAMLR fishery management strategies in this region. This study addresses key recommendations
provided by the Working Group on Statistics, Assessment, and Modelling (WG-SAM-2024/26) . The reference
model (s1) performed well in capturing the inter-annual and inter-fleet variability in krill length compositions.
Retrospective analysis showed a slight underestimation bias in spawning biomass; however, this was within
an acceptable range. The model suggests a higher dependence on length composition data compared to
other sources for estimating recruitment. Spatial considerations and assumptions about stock-recruitment
relationships significantly impact population variable estimates. The inclusion of a selectivity block into the
model (s9) improved the fit to some length composition data compared to the reference model (s1). Overall,
this study demonstrates the potential of using a spatially explicit integrated model for krill stock assessment.
The model provides valuable insights into krill population dynamics and can be used to inform sustainable
management practices.