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Understanding spatial population structure and biocomplexity is critical for determining a species' resilience to environmental and anthropogenic perturbations. However, integrated population models (IPMs) used to develop management advice for harvested populations have been slow to incorporate spatial dynamics. Therefore, limited research has been devoted to understanding the reliability of movement parameter estimation in spatial population models, especially for spatially dynamic marine fish populations. We implemented a spatial simulation-estimation framework that emulated a generic marine fish metapopulation to explore the impact of ontogenetic movement and climate-induced distributional shifts between two populations. The robustness of spatially stratified IPMs was explored across a range of movement parametrizations, including ignoring connectivity or estimating movement with various levels of complexity. Ignoring connectivity was detrimental to accurate estimation of population-specific biomass, while implementing spatial IPMs with intermediate levels of complexity (e.g. estimating movement in two-year and two-age blocks) performed best when no a priori information about underlying movement was available. One-way distributional shifts mimicking climate-induced poleward migrations presented the greatest estimation difficulties, but the incorporation of auxiliary information on connectivity (e.g. tag-recapture data) reduced bias. The continued development of spatially stratified modelling approaches should allow harvested resources to be better utilized without increased risk. Additionally, expanded collection and incorporation of unique spatially explicit data will enhance the robustness of IPMs in the future.

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