|Author(s)||Hufnagl Marc1, Payne Mark2, Lacroix Genevieve3, Bolle Loes J.4, Daewele Ute5, 15, Dickey-Collas Mark2, 6, Gerkema Theo7, Huret Martin8, Janssen Frank9, Kreus Markus1, Paetsch Johannes10, Pohlmann Thomas10, Ruardij Piet7, Schrum Corinna10, 11, 15, Skogen Morten D.12, Tiessen Meinard C. H.7, Petitgas Pierre8, 13, Van Beek Jan K. L.14, Van Der Veer Henk W.7, Callies Ulrich15|
|Affiliation(s)||1 : Univ Hamburg, Ctr Earth Syst Res & Sustainabil CEN, Inst Hydrobiol & Fisheries Sci, Olbersweg 24, D-22767 Hamburg, Germany.
2 : Tech Univ Denmark, DTU Aqua, Joegersborg Alle 1, DK-2920 Charlottenlund, Denmark.
3 : RBINS, Operat Directorate Nat Environm, Gulledelle 100, B-1200 Brussels, Belgium.
4 : Wageningen Marine Res, Inst Marine Resources & Ecosyst Studies, POB 68, NL-1970 AB Ijmuiden, Netherlands.
5 : Hjort Ctr Marine Ecosyst Dynam, Nansen Environm & Remote Sensing Ctr, Thormohlensgate 47, N-5006 Bergen, Norway.
6 : Int Council Explorat Sea, HC Andersen Blvd 44-46, DK-1553 Copenhagen V, Denmark.
7 : Univ Utrecht, Dept Coastal Syst, Royal Netherlands Inst Sea Res, POB 59, NL-1790 AB Den Burg, Netherlands.
8 : IFREMER, Ctr Brest, RBE, STH LBH, BP 70, F-29280 Plouzane, France.
9 : BSH, Bernhard Nocht Str 78, D-20359 Hamburg, Germany.
10 : Hamburg Univ, Inst Oceanog, Bundesstr 53, D-20146 Hamburg, Germany.
11 : Univ Bergen, Inst Geophys, Allegaten 70, N-5007 Bergen, Norway.
12 : Inst Marine Res, Pb 1870 Nordnes, N-5817 Bergen, Norway.
13 : IFREMER, RBE EMH, Rue Ile Yeu,BP 21105, F-44311 Nantes 03, France.
14 : Deltares, POB177, NL-2600 MH Delft, Netherlands.
15 : Helmholtz Zentrum Geesthacht, Inst Coastal Res, Max Planck Str 1, D-21502 Geesthacht, Germany.
|Source||Journal Of Sea Research (1385-1101) (Elsevier Science Bv), 2017-09 , Vol. 127 , P. 133-149|
|WOS© Times Cited||18|
|Keyword(s)||Ocean circulation, Lagrangian approach, Variability, Marine protected areas, Renewable energy, Wind park, Model intercomparison, Ensemble|
Hydrodynamic Ocean Circulation Models and Lagrangian particle tracking models are valuable tools e.g. in coastal ecology to identify the connectivity between offshore spawning and coastal nursery areas of commercially important fish, for risk assessment and more for defining or evaluating marine protected areas. Most studies are based on only one model and do not provide levels of uncertainty. Here this uncertainty was addressed by applying a suite of 11 North Sea models to test what variability can be expected concerning connectivity. Different notional test cases were calculated related to three important and well-studied North Sea fish species: herring (Clupea harengus), and the flatfishes sole (Solea solea) and plaice (Pleuronectes platessa). For sole and plaice we determined which fraction of particles released in the respective spawning areas would reach a coastal marine protected area. For herring we determined the fraction located in a wind park after a predefined time span. As temperature is more and more a focus especially in biological and global change studies, furthermore inter-model variability in temperatures experienced by the virtual particles was determined. The main focus was on the transport variability originating from the physical models and thus biological behavior was not included. Depending on the scenario, median experienced temperatures differed by 3 °C between years. This range between the different models in one year was comparable to the temperature range observed between all modelled years. Connectivity between flatfish spawning areas and the coastal protected area was highly dependent on the release location and spawning time. No particles released in the English Channel in the sole scenario reached the protected area while up to 20% of the particles released in the plaice scenario did. Interannual trends in transport directions and connectivity rates were comparable between models but absolute values displayed high variations. Most models showed systematic biases during all years in comparison to the ensemble median, indicating that in general interannual variation was represented but absolute values varied. In conclusion: variability between models is generally high and management decisions or scientific analysis using absolute values from only one single model might be biased and results or conclusions drawn from such studies need to be treated with caution. We further concluded that more true validation data for particle modelling are required.
Hufnagl Marc, Payne Mark, Lacroix Genevieve, Bolle Loes J., Daewele Ute, Dickey-Collas Mark, Gerkema Theo, Huret Martin, Janssen Frank, Kreus Markus, Paetsch Johannes, Pohlmann Thomas, Ruardij Piet, Schrum Corinna, Skogen Morten D., Tiessen Meinard C. H., Petitgas Pierre, Van Beek Jan K. L., Van Der Veer Henk W., Callies Ulrich (2017). Variation that can be expected when using particle tracking models in connectivity studies. Journal Of Sea Research, 127, 133-149. Publisher's official version : https://doi.org/10.1016/j.seares.2017.04.009 , Open Access version : https://archimer.ifremer.fr/doc/00385/49660/