Not logged in
PANGAEA.
Data Publisher for Earth & Environmental Science

Hinrichsen, Hans-Harald; Dierking, Jan; von Dewitz, Burkhard (2017): Data base of timely, vertically, and horizontally highly resolved dispersal, stability, and drift distance of passively drifting particles in the Baltic Sea with the Kiel Baltic Sea Ice-Ocean Model (BSIOM) [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.883821, Supplement to: Hinrichsen, Hans-Harald; von Dewitz, Burkhard; Dierking, Jan (2018): Variability of advective connectivity in the Baltic Sea. Journal of Marine Systems, 186, 115-122, https://doi.org/10.1016/j.jmarsys.2018.06.010

Always quote citation above when using data! You can download the citation in several formats below.

RIS CitationBibTeX Citation

Abstract:
This data set contains results produced by particle drift modeling exercises with the Kiel Baltic Sea Ice-Ocean Model (BSIOM) to analyze the variability of large scale drift patterns within the Baltic Sea. The provided parameters are:
- Mean geographical distance [km], divided into north-south and east-west component
- stability of particle drift distance
- relative dispersal [%]
The parameters were separated and averaged for the following time and space intervals:
- drift duration [days] in 5 days increments from 5 to 50 days drift
- vertical particle drift depth [m] with the following values: 2.5; 7.5; 12.5; 17.5; 25.0; 35.0; 45.0; 55.0; 65.0; 75.0; 85.0
- horizontal resolution: 54.0°N to 66.0°N in 0.5° increments and 10°E to 30°E in 1° increments.
The analyses based on this data set are described in more detail and results are discussed in the article.
Connectivity between different populations of a species is a central parameter in the fields of ecology and evolutionary biology. We here provided decadally, regionally, and depth layer resolved information on connectivity and dispersal patterns for the entire Baltic Sea as a tool for supporting population genetic and ecological studies. The general method to assess dispersal used was bio-physical modelling, which is suitable for biological dispersal that is highly influenced by the physical water transport in ocean circulation. The results were assessed from Lagrangian particle tracking using ocean circulation model outputs. Generally, for the whole Baltic Sea as well as for all subareas, we observed persistent patterns of dispersal that reflected the basin-like structure of the Baltic Sea, with less transport between the basins. At the same time, dispersal distance and in extension, local retention versus dispersal of particles to other sub-areas, varied considerably over four decades (1970–2010) and among regions within the Baltic Sea, corresponding to a range from high connectivity to partial dispersal barriers. Based on the example of Eastern Baltic cod we then investigated how our dispersal distance datasets can serve as a tool to assess dispersal and the expected connectivity among different populations of a species, as long as some biological information is available. For example, our finding of high dispersal of particles from the Bornholm Basin to the other Eastern Baltic basins could help to explain recent results indicating lack of genetic differentiation of cod across the eastern Baltic Sea. Our results also indicate that the shift in spawning time observed in cod over the past decades and the resulting exposure of eggs and larvae in the water column to a time of the year with a different current regime has likely affected egg and larval export. Finally, our case study also demonstrates how inter-annual variability of ocean current speed and direction at the time of peak reproduction is likely to affect the connectivity among the subareas in the Baltic. To conclude, connectivity datasets from this study are freely available, and can represent a powerful tool to apply in evolutionary and ecological studies of a variety of species in the Baltic Sea.
Comment:
The data resulted from research conducted within the BONUS BIO-C3 project and was supported by BONUS (Art 185), funded jointly by the EU and the Forschungszentrum Jülich Beteiligungsgesellschaft mbH (03F0682A) (Germany).
Size:
2.7 MBytes

Download Data

Download dataset