scholarly journals Rapid aggregation of biofilm-covered microplastics with marine biogenic particles

2018 ◽  
Vol 285 (1885) ◽  
pp. 20181203 ◽  
Author(s):  
Jan Michels ◽  
Angela Stippkugel ◽  
Mark Lenz ◽  
Kai Wirtz ◽  
Anja Engel
Keyword(s):  
Surface Layer ◽  
Sea Ice ◽  
Baltic Sea ◽  
Deep Sea ◽  
Ecosystem Health ◽  
Laboratory Experiments ◽  
Plastic Pollution ◽  
Microbial Biofilms ◽  
Aggregation Behaviour ◽  
Plastic Surfaces

Ocean plastic pollution has resulted in a substantial accumulation of microplastics in the marine environment. Today, this plastic litter is ubiquitous in the oceans, including even remote habitats such as deep-sea sediments and polar sea ice, and it is believed to pose a threat to ecosystem health. However, the concentration of microplastics in the surface layer of the oceans is considerably lower than expected, given the ongoing replenishment of microplastics and the tendency of many plastic types to float. It has been hypothesized that microplastics leave the upper ocean by aggregation and subsequent sedimentation. We tested this hypothesis by investigating the interactions of microplastics with marine biogenic particles collected in the southwestern Baltic Sea. Our laboratory experiments revealed a large potential of microplastics to rapidly coagulate with biogenic particles, which substantiates this hypothesis. Together with the biogenic particles, the microplastics efficiently formed pronounced aggregates within a few days. The aggregation of microplastics and biogenic particles was significantly accelerated by microbial biofilms that had formed on the plastic surfaces. We assume that the demonstrated aggregation behaviour facilitates the export of microplastics from the surface layer of the oceans and plays an important role in the redistribution of microplastics in the oceans.

scholarly journals Surface Layer Salinity of Young Sea Ice

1985 ◽  
Vol 6 ◽  
pp. 298-299 ◽  
Author(s):  
Nobuo Ono ◽  
Takashi Kasai
Keyword(s):  
Surface Layer ◽  
Sea Ice ◽  
Surface Temperature ◽  
Laboratory Experiments ◽  
High Salinity ◽  
Ice Sheet ◽  
Surface Salinity ◽  
Seawater Salinity ◽  
Fast Ice

The high-salinity surface layer of young sea ice was subjected to field and laboratory experiments. Artificial pools, in which young ice was formed, were opened within a fast-ice sheet in the Saroma lagoon, Hokkaido, in February of 1983 and 1984. The salinity of 1 mm thick surface layer of the young ice was observed as high as 42.4‰, which exceeds the seawater salinity of 31‰. The surface salinity increased with rising surface temperature. When a load was placed on the fast ice near the pool, seeped brine of salinity 72.5‰ was observed on the surface of the young ice; and when the load was removed, the brine disappeared. Meanwhile, brine permeabilities, both upward and downward, were measured in the laboratory, Both permeabilities decreased logarithmically with lowering surface temperature. A remarkable anisotropy was observed: the upward permeability was greater than downward, and the ratio of upward to downward premeability increased with lowering surface temperature from 5 at -3 °C to 33 at -5°C. Upward and downward permeabilities in ms-1 were respectively 1x10-4 and 2x10-5 at -3°C, 2x10-5 and 6x10-7 at -5°C, and at -10°C upward permeability was 3x10-7.

scholarly journals Surface Layer Salinity of Young Sea Ice

1985 ◽  
Vol 6 ◽  
pp. 298-299 ◽  
Author(s):  
Nobuo Ono ◽  
Takashi Kasai
Keyword(s):  
Surface Layer ◽  
Sea Ice ◽  
Surface Temperature ◽  
Laboratory Experiments ◽  
High Salinity ◽  
Ice Sheet ◽  
Surface Salinity ◽  
Seawater Salinity ◽  
Fast Ice

The high-salinity surface layer of young sea ice was subjected to field and laboratory experiments. Artificial pools, in which young ice was formed, were opened within a fast-ice sheet in the Saroma lagoon, Hokkaido, in February of 1983 and 1984. The salinity of 1 mm thick surface layer of the young ice was observed as high as 42.4‰, which exceeds the seawater salinity of 31‰. The surface salinity increased with rising surface temperature. When a load was placed on the fast ice near the pool, seeped brine of salinity 72.5‰ was observed on the surface of the young ice; and when the load was removed, the brine disappeared. Meanwhile, brine permeabilities, both upward and downward, were measured in the laboratory, Both permeabilities decreased logarithmically with lowering surface temperature. A remarkable anisotropy was observed: the upward permeability was greater than downward, and the ratio of upward to downward premeability increased with lowering surface temperature from 5 at -3 °C to 33 at -5°C. Upward and downward permeabilities in ms-1 were respectively 1x10-4 and 2x10-5 at -3°C, 2x10-5 and 6x10-7 at -5°C, and at -10°C upward permeability was 3x10-7.

Discovery of bacterial polyhydroxyalkanoate synthase (PhaC)-encoding genes from seasonal Baltic Sea ice and cold estuarine waters

Extremophiles ◽  
2014 ◽  
Vol 19 (1) ◽  
pp. 197-206 ◽  
Author(s):  
Katariina Pärnänen ◽  
Antti Karkman ◽  
Marko Virta ◽  
Eeva Eronen-Rasimus ◽  
Hermanni Kaartokallio
Keyword(s):  
Sea Ice ◽  
Baltic Sea ◽  
Estuarine Waters ◽  
Polyhydroxyalkanoate Synthase ◽  
Encoding Genes

Physical properties and spatial distribution of the sea ice surface layer (SSL/snow) during the autumn phase of the MOSAiC expedition

2021 ◽  
Author(s):  
Ruzica Dadic ◽  
Martin Schneebeli ◽  
Henna-Reeta Hannula ◽  
Amy Macfarlane ◽  
Roberta Pirazzini
Keyword(s):  
Surface Layer ◽  
Spatial Distribution ◽  
Sea Ice ◽  
Physical Properties ◽  
Surface Scattering ◽  
Climate Feedback ◽  
Energy Fluxes ◽  
Scattering Layer ◽  
Near Surface ◽  
Ice Surface

<p>Snow cover dominates the thermal and optical properties of sea ice and the energy fluxes between the ocean and the atmosphere, yet data on the physical properties of snow and its effects on sea ice are limited. This lack of data leads to two significant problems: 1) significant biases in model representations of the sea ice cover and the processes that drive it, and 2) large uncertainties in how sea ice influences the global energy budget and the coupling of climate feedback. The  MOSAiC research initiative enabled the most extensive data collection of snow and surface scattering layer (SSL) properties over sea ice to date. During leg 5 of the MOSAiC expedition, we collected multi-scale (microscale to 100-m scale) measurements of the surface layer (snow/SSL) over first year ice (FYI) and MYI on a daily basis. The ultimate goal of our measurements is to determine the spatial distribution of physical properties of the surface layer. During leg 5 of the MOSAiC expedition, that surface layer changed from the  surface scattering layer (SSL),   characteristic for the melt season, to an early autumn snow pack. Here,  we will present data showing both a) the physical properties and the spatial distribution of the SSL during the late melt season and b) the transition of the sea ice surface from the SSL to the fresh autumn snowpack. The structural properties of this transition period are poorly documented, and this season is critical  for the initialization of sea ice and snow models. Furthermore, these data are crucial to interpret simultaneous observations of surface energy fluxes, surface optical and remote sensing data (microwave signals in particular), near-surface biochemical activity, and to understand the sea ice  processes that occur as the sea ice transitions from melting to freezing.</p>

Rhinella icterica and Rhinella ornata (Anura: Bufonidae) tadpoles do not recognise siblings

2021 ◽  
pp. 214-220
Author(s):  
Alexandre Polettini Neto
Keyword(s):  
Environmental Factors ◽  
Laboratory Experiments ◽  
Inclusive Fitness ◽  
Costs And Benefits ◽  
Environmental Characteristics ◽  
Ecological Processes ◽  
Aggregation Behaviour ◽  
Rearing Methods

Benefits conferred to animals living in groups may be greater if groups are formed by relatives rather than non-relatives, because cooperating with relatives increases the probability of their own genes being passed on to group offspring (inclusive fitness). Non-social aggregations are formed in response to environmental characteristics, while social aggregations are formed from the attraction among individuals. The attraction or repulsion between individuals is mediated by recognition mechanisms, which mediate important ecological processes and behaviours. Here, we conducted laboratory experiments to test if tadpoles of two sympatric bufonids, Rhinella icterica and R. ornata, are able to recognise siblings. We collected eggs of the two species in the field and raised them in laboratory settings, according to three different methods: siblings and non-siblings reared in separated containers; siblings and non-siblings reared in the same container separated by a plastic net; and eggs from the same spawn reared separately, each one in an individual container. Later, we tested if tadpoles could choose between groups of siblings and non-siblings. The results indicate that tadpoles of neither species were able to discriminate between siblings and non-siblings, regardless of the rearing methods. Therefore, kinship is less important than environmental factors in tadpole aggregation behaviour of these species, and it may be dependent on the balance between costs and benefits. Our results can be used as a start point to better understand tadpole aggregation behaviour and recognition mechanisms in these species.

Application of the Regional Ocean Modelling System (ROMS) for Baltic Sea area

2021 ◽  
Author(s):  
Maciej Muzyka ◽  
Jaromir Jakacki ◽  
Anna Przyborska
Keyword(s):  
Sea Ice ◽  
Baltic Sea ◽  
Atmospheric Model ◽  
Horizontal Resolution ◽  
Shortwave Radiation ◽  
Ocean Modelling ◽  
Efficient System ◽  
Curvilinear Grid ◽  
The Baltic ◽  
Modelling System

<p>The Regional Ocean Modelling System has been begun to implement for region of Baltic Sea.  A preliminary curvilinear grid with horizontal resolution ca. 2.3 km has been prepared based on the grid, which was used in previous application in our research group (in Parallel Ocean Program and in standalone version of Los Alamos Sea Ice Model - CICE).  Currently the grid has 30 sigma layers, but the final number of levels will be adjusted accordingly.</p><p>So far we’ve successfully compiled the model on our machine, run test cases and created Baltic Sea case, which is working with mentioned Baltic grid. The following parameters: air pressure, humidity, surface temperature, long and shortwave radiation, precipitation and wind components are used as an atmospheric forcing. The data arrive from our operational atmospheric model - Weather Research and Forecasting Model (WRF).</p><p>Our main goal is to create efficient system for hindcast and forecast simulations of Baltic Sea together with sea ice component by coupling ROMS with CICE. The reason for choosing these two models is an active community that takes care about model’s developments and updates. Authors also intend to work more closely with the CICE model to improve its agreement with satellite measurements in the Baltic region.<br><br>Calculations were carried out at the Academic Computer Centre in Gdańsk.</p>

scholarly journals Operational SAR-based sea ice drift monitoring over the Baltic Sea

Ocean Science ◽  
2012 ◽  
Vol 8 (4) ◽  
pp. 473-483 ◽  
Author(s):  
J. Karvonen
Keyword(s):  
Sea Ice ◽  
Baltic Sea ◽  
Vector Fields ◽  
Phase Correlation ◽  
The Baltic Sea ◽  
Sar Images ◽  
Envisat Asar ◽  
Ice Drift ◽  
Sea Ice Drift ◽  
The Baltic

Abstract. An algorithm for computing ice drift from pairs of synthetic aperture radar (SAR) images covering a common area has been developed at FMI. The algorithm has been developed based on the C-band SAR data over the Baltic Sea. It is based on phase correlation in two scales (coarse and fine) with some additional constraints. The algorithm has been running operationally in the Baltic Sea from the beginning of 2011, using Radarsat-1 ScanSAR wide mode and Envisat ASAR wide swath mode data. The resulting ice drift fields are publicly available as part of the MyOcean EC project. The SAR-based ice drift vectors have been compared to the drift vectors from drifter buoys in the Baltic Sea during the first operational season, and also these validation results are shown in this paper. Also some navigationally useful sea ice quantities, which can be derived from ice drift vector fields, are presented.

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