Numerical modeling of the beach process of marine plastics: 2. A diagnostic approach with onshore-offshore advection-diffusion equations for buoyant plastics

Hinata, Hirofumi; Ohno, Kazuki; Sagawa, Noa; Kataoka, Tomoya; Takeoka, Hidetaka

doi:10.1016/j.marpolbul.2020.111548

Cited by 5 publications

(2 citation statements)

References 41 publications

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“…Since the AIS, the main sea current governing the large-scale velocity field of our model, is most intense in the depth range 13-30 m and weakens with depth (Sorgente et al, 2011), forcing the vertical movement of the particles in the lower layers could promote retention and reduce dispersion (Calò et al, 2018). This is just what we have observed by comparing the results presented here with preliminary numerical simulations performed without introducing vertical movement for the bility of particles may be meaningful, especially in conjunction with the particle resuspension probability (see Hinata et al, 2020;Liubartseva et al, 2018;Onink et al, 2021 for applications to marine plastic debris), and the vertical migration (see Berline et al, 2013).…”

Section: Discussionsupporting

confidence: 70%

“…In our simulations, similarly to what is generally done in larval dispersal studies (e.g., Melaku Canu et al, 2020; Palatella et al, 2014), we did not consider larval beaching/stranding on the coast but we applied reflective boundary conditions that, depending on the geometry of the domain, the run length and the strength of the velocity field, could affect the GTCs and the hotspot regions. Many models based on Lagrangian computations, analyzed the stranding effect, showing that the stranding probability of particles may be meaningful, especially in conjunction with the particle resuspension probability (see Hinata et al, 2020; Liubartseva et al, 2018; Onink et al, 2021 for applications to marine plastic debris), and the vertical migration (see Berline et al, 2013). However, the stranding effect (mainly applied to the dispersal of pollutants in the cited papers) has a strong impact on Lagrangian simulations in the long run, and becomes quite relevant after months (Mansui et al, 2015; Onink et al, 2021).…”

Section: Discussionmentioning

confidence: 99%

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Where do recruits come from? Backward Lagrangian simulation for the deep water rose shrimps in the Central Mediterranean Sea

Gargano

Garofalo

Quattrocchi

et al. 2022

Fisheries Oceanography

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Backward-in-time Lagrangian dispersion models can efficiently reconstruct drifters trajectories by linking known arrival positions to potential sources. This approach was applied to the deep water rose shrimp (Parapenaeus longirostris) in the Strait of Sicily (central Mediterranean Sea). The objective was to identify the potential spawning areas of the larvae that settle in the known nursery grounds of the northern sector of the Strait of Sicily, thus quantifying the extent of the potential contribution to recruitment from the surrounding regions. Numerical simulations were performed over 11 years (2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015) and for two different periods (spring/summer and autumn/winter) corresponding to the species' spawning peaks in the region. The persistence over time of potential spawning areas was identified through a Hotspot analysis of the backward trajectories end-points, filtered to meet a suitable depth range for spawners. The results confirmed the expected downstream connectivity between spawning and nursery grounds along the Sicilian-Maltese shelf and, notably, indicated that these spawning grounds contribute to the high productivity and resilience of deep water rose shrimp fisheries in the northern Strait of Sicily more than the spawning grounds in surrounding regions. A minor and time-varying contribution is due to potential spawning areas identified on the African shelf. These results are important to adequately define the geographical scale for the assessment and management of this important fishery resource in the Strait of Sicily. In particular, the assumption of a single stock that does not consider the spatial structure of the population should be revised for the purpose of fisheries management.

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