Implementation of watershed modelling in the Litter-TEP service (Marine Litter Drift Monitoring in the NE Atlantic Shelf Region) to complement CMEMS data inputs.

<p>It has been considered for quite a while that rivers, coastal outlets and flytipping are the main input contributors to Marine litter. After their discharge into the sea, litter is then transported by currents and wind while sunk and/or disintegrated into micro marine litter, some pieces finishing their course at the coast where they wash ashore. Thanks to a Copernicus Marine Environment Monitoring Service (CMEMS) grant, ARGANS Ltd has developed a web-based service, called Litter-TEP, that aims to track marine litter from their source. The service is based on two segments, one Land unit and one Ocean unit, and the issue is with the former: The Land component is made of a parametric model of riverine macro litter discharge at sea which is based on hydrological information and socio-economics data. It feeds the Ocean unit, with drift models using ocean current, wave and wind forecasts from CMEMS to provide a 5-day running forecast of macro-litter density in the sea, potential beach stranding at the coast and, inversely, where a beach litter event is identified to provide the likelihood of where the litter entered the sea. Yet, by lack of real-time land hydrological data from free & public sources, the land-litter input model currently implemented in the service only relies on hydrological information from statistics based on 30 years of daily rivers flow data. Nota: if the hydrological data (river flows) is in open access for the European rivers on the Copernicus service, it is with a 30-day delay. To mitigate this shortage, we have implemented a water discharge model as a prototype; it is based on HYPE v.5.11.2 from SMHI to calculate daily estimation of rivers flow from near real time rainfall (from NASA) & temperature data (from all national Met Offices) and thus to link the volume of litter coming into the sea to Meteorological events to have better estimates of litter’s volume brought into the sea. The model has been validated for Ireland and is currently parametrized for other countries and regions. It shall be implemented in the next version of the LITTER-TEP.</p>

Three-component modelling of C-rich AGB star winds – V. Effects of frequency-dependent radiative transfer including drift★

ABSTRACT Stellar winds of cool carbon stars enrich the interstellar medium with significant amounts of carbon and dust. We present a study of the influence of two-fluid flow on winds where we add descriptions of frequency-dependent radiative transfer (RT). Our radiation hydrodynamic models in addition include stellar pulsations, grain growth and ablation, gas-to-dust drift using one mean grain size, dust extinction based on both the small particle limit (SPL) and Mie scattering, and an accurate numerical scheme. We calculate models at high spatial resolution using 1024 gridpoints and solar metallicities at 319 frequencies, and we discern effects of drift by comparing drift models to non-drift models. Our results show differences of up to 1000 per cent in comparison to extant results. Mass-loss rates and wind velocities of drift models are typically, but not always, lower than in non-drift models. Differences are larger when Mie scattering is used instead of the SPL. Amongst other properties, the mass-loss rates of the gas and dust, dust-to-gas density ratio, and wind velocity show an exponential dependence on the dust-to-gas speed ratio. Yields of dust in the least massive winds increase by a factor 4 when drift is used. We find drift velocities in the range $10\!-\!67\, \mbox{km}\, \mbox{s}^{-1}$, which is drastically higher than in our earlier works that use grey RT. It is necessary to include an estimate of drift velocities to reproduce high yields of dust and low wind velocities.

Connectivity and population structure of albacore tuna across southeast Atlantic and southwest Indian Oceans inferred from multidisciplinary methodology

Albacore tuna (Thunnus alalunga) is an important target of tuna fisheries in the Atlantic and Indian Oceans. The commercial catch of albacore is the highest globally among all temperate tuna species, contributing around 6% in weight to global tuna catches over the last decade. The accurate assessment and management of this heavily exploited resource requires a robust understanding of the species’ biology and of the pattern of connectivity among oceanic regions, yet Indian Ocean albacore population dynamics remain poorly understood and its level of connectivity with the Atlantic Ocean population is uncertain. We analysed morphometrics and genetics of albacore (n = 1,874) in the southwest Indian (SWIO) and southeast Atlantic (SEAO) Oceans to investigate the connectivity and population structure. Furthermore, we examined the species’ dispersal potential by modelling particle drift through major oceanographic features. Males appear larger than females, except in South African waters, yet the length–weight relationship only showed significant male–female difference in one region (east of Madagascar and Reunion waters). The present study produced a genetic differentiation between the southeast Atlantic and southwest Indian Oceans, supporting their demographic independence. The particle drift models suggested dispersal potential of early life stages from SWIO to SEAO and adult or sub-adult migration from SEAO to SWIO.

The Stokes drift in ocean surface drift prediction

<p>Ocean surface drift forecasts are essential for numerous applications. It is a central asset in search and rescue and oil spill response operations, but it is also used for predicting the transport of pelagic eggs, larvae and detritus or other organisms and solutes, for evaluating ecological isolation of marine species, for tracking plastic debris, and for environmental planning and management. The accuracy of surface drift forecasts depends to a large extent on the quality of ocean current, wind and waves forecasts, but also on the drift model used. The standard Eulerian leeway drift model used in most operational systems considers near-surface currents provided by the top grid cell of the ocean circulation model and a correction term proportional to the near-surface wind. Such formulation assumes that the 'wind correction term' accounts for many processes including windage, unresolved ocean current vertical shear, and wave-induced drift. However, the latter two processes are not necessarily linearly related to the local wind velocity. We propose three other drift models that attempt to account for the unresolved near-surface current shear by extrapolating the near-surface currents to the surface assuming Ekman dynamics. Among them two models consider explicitly the Stokes drift, one without and the other with a wind correction term. We assess the performance of the drift models using observations from drifting buoys deployed in the Estuary and Gulf of St. Lawrence, Canada. Drift model inputs are obtained from regional atmospheric, ocean circulation, and spectral wave models. The performance of these drift models is evaluated based on a number of error metrics (e.g. speed, direction, separation distance between the observed and simulated positions) and skill scores determined at different lead times ranging from 3h to 72h. Results show that extrapolating the top-layer ocean model currents to the surface assuming Ekman dynamics for the ageostrophic currents, and adding the Stokes drift predicted by a spectral wave model, leads to the best drift forecast skills without the need to include a wind correction term.</p>

Three-dimensional analysis of the physiologic drift of adjacent teeth following maxillary first premolar extractions

We assessed the three-dimensional (3D) pattern of the physiologic drift of the remaining adjacent teeth after premolar extraction due to orthodontic reasons and the associated factors. Data were collected from 45 patients aged 17.04 ± 5.14 years who were scheduled to receive a fixed appliance after maxillary premolar extraction. Seventy-five drift models were obtained and digitalized via 3D scanning. The average physiologic drift duration was 81.66 ± 70.03 days. Angular and linear changes in the first molars, second premolars, and canines were measured using the 3D method. All the examined teeth had tipped and moved towards the extraction space, leading to space decreases. Posterior teeth primarily exhibited significant mesial tipping and displacement, without rotation or vertical changes. All canine variables changed, including distal inward rotation and extrusion. The physiologic drift tended to slow over time. Age had a limited negative effect on the mesial drift of posterior teeth, whereas crowding had a limited positive effect on canine drift. Thus, the mesial drift of molars after premolar extraction may lead to molar anchorage loss, particularly among younger patients. The pattern of the physiologic drift of maxillary canines can help relieve crowding and facilitate labially ectopic canine alignment, whereas canine drift is accelerated by more severe crowding.

Spatial linkages between geomorphic and hydraulic conditions and invertebrate drift characteristics in a small mountain stream

Although invertebrate drift plays a fundamental role in river ecosystems, spatial linkages between its characteristics and hydrogeomorphic conditions remain poorly understood. This study, conducted in a small stream in British Columbia, provides insight into such relationships. Most notably, drift concentration was positively correlated with bed scour, and mean body size was negatively correlated with bed fill. Although correlational design precludes inference regarding mechanisms, these results are consistent with protracted effects of flood-related bed disturbances on spatial pattern of drift characteristics under low flow conditions. We detected no robust associations between drift and flow characteristics that could not be explained by bed disturbances. Because of high spatial variability, drift characteristics were statistically distinct only in few habitat types. Compared with middepth, invertebrate drift concentration was higher near water surface, and mean body size was larger near the bed. Mean body size was also statistically smaller in riffle–pool transitions, which experienced largest bed fill. Possible legacy effects of bed disturbances could have broader implications for drift-related energy and nutrient fluxes in river corridors and for quantitative drift models.