Plankton, plastics, nutrients, and other materials in the ocean can exhibit different dispersion patterns depending on their individual drifting properties. These dispersion patterns can provide information on the effective timescales of interaction between different types of materials in a highly dynamic ocean environment, such as the Benguela system in the southeast Atlantic Ocean. In this study, we compare the timescales and spatial distribution of separation for zooplankton performing Diel Vertical Migration (DVM) while drifting with currents to those of other materials: (i) positively buoyant plastics or planktonic organisms passively floating near the ocean's surface; (ii) nutrients or pollutants passively advecting in the three-dimensional flow; and (iii) sinking biogenic particulate matter. We apply the drift properties of each material type in Lagrangian flow modeling to simulate the movement of virtual particles across the Benguela system. Our results indicate faster separation between zooplankton performing DVM and the other particle types during the upwelling season in the austral spring and summer. We also observe a decrease in the separation timescales between zooplankton performing DVM and other particle types as the zooplankton migration depth increases. Despite the differences in separation timescales across seasons, different particle types can become trapped in coherent features such as eddies, fronts, and filaments, indicating prolonged exposure of zooplankton to prey and pollutants in these coherent ocean features.

Origins of material in the ocean are commonly identified by tracing Lagrangian particle trajectories backward-in-time in two or three dimensions. While this is mathematically consistent, numerical computations are hampered by numerical round-off and truncation errors, leading to discrepancies between forward- and backward-in-time trajectories. The chaotic nature of ocean flows amplifies these errors. We identify an additional issue with Lagrangian backtracking, related to the reversal of stability with regards to velocity convergence and divergence. Trajectories near convergent regions are stable to numerical errors when calculated forward-in-time but become unstable backward-in-time. The timescales at which trajectories reside in convergent zones are thus underestimated in backward-in-time computations, meaning convergent regions (downwelling zones) become underrepresented and divergent zones (upwelling zones, river mouths) overrepresented as trajectory sources. Using mesoscale experiments representing common set-ups, we show that already for timescales of less than half a year, this leads to systematic biases in the regions identified as particle origins. These biases can extend over distances of thousands of kilometers. While this stability bias is linked to divergence, it is not only limited to 2D trajectories in 3D flows, as we discuss how inappropriate treatment of surface boundary conditions in 3D Lagrangian studies can also introduce an effective non-zero divergence. These findings have consequences for source-attribution modeling, for example in the context of water mass tracing, ecology, and pollution studies. Backtracking is typically applied to material that has accumulated in convergent zones, where the stability bias is especially relevant, which further impedes source attribution.