ArticlePDF Available

Abstract and Figures

The wind wake effect of offshore wind farms affects the hydrodynamical conditions in the ocean, which has been hypothesized to impact marine primary production. So far only little is known about the ecosystem response to wind wakes under the premisses of large offshore wind farm clusters. Here we show, via numerical modeling, that the associated wind wakes in the North Sea provoke large-scale changes in annual primary production with local changes of up to ±10% not only at the offshore wind farm clusters, but also distributed over a wider region. The model also projects an increase in sediment carbon in deeper areas of the southern North Sea due to reduced current velocities, and decreased dissolved oxygen inside an area with already low oxygen concentration. Our results provide evidence that the ongoing offshore wind farm developments can have a substantial impact on the structuring of coastal marine ecosystems on basin scales.
This content is subject to copyright. Terms and conditions apply.
ARTICLE
Offshore wind farms are projected to impact
primary production and bottom water
deoxygenation in the North Sea
Ute Daewel 1, Naveed Akhtar 1, Nils Christiansen1& Corinna Schrum1,2
The wind wake effect of offshore wind farms affects the hydrodynamical conditions in the
ocean, which has been hypothesized to impact marine primary production. So far only little is
known about the ecosystem response to wind wakes under the premisses of large offshore
wind farm clusters. Here we show, via numerical modeling, that the associated wind wakes in
the North Sea provoke large-scale changes in annual primary production with local changes
of up to ±10% not only at the offshore wind farm clusters, but also distributed over a wider
region. The model also projects an increase in sediment carbon in deeper areas of the
southern North Sea due to reduced current velocities, and decreased dissolved oxygen inside
an area with already low oxygen concentration. Our results provide evidence that the ongoing
offshore wind farm developments can have a substantial impact on the structuring of coastal
marine ecosystems on basin scales.
https://doi.org/10.1038/s43247-022-00625-0 OPEN
1Institute for Coastal Systems - Analysis and Modelling, Helmholtz-Zentrum Hereon, Max-Planck-Str. 1, D-21502 Geesthacht, Germany. 2Institute of
Oceanography, CEN, Universität Hamburg, Hamburg, Germany. email: ute.daewel@hereon.de
COMMUNICATIONS EARTH & ENVIRONMENT | (2022) 3:292 | https://doi.org/10.1038/s43247-022-00625-0 |www.nature.c om/commsenv 1
1234567890():,;
Content courtesy of Springer Nature, terms of use apply. Rights reserved
The North Sea is a shallow shelf sea system in which the
interactions between bathymetry, tides and a strong
freshwater supply at the continental coast foster a complex
frontal system, which separates well-mixed coastal waters from
seasonally stratied deeper areas. The shallow coastal areas and
sandbanks combined with stable wind resources make the North
Sea an ideal area for renewable energy production and have made
the North Sea a global hotspot for offshore wind energy
production1. The recently negotiated European Green Deal to
support the European target to phase out dependence on fossil
fuels will further accelerate the development of offshore renew-
able energy2and a substantial increase of installed capacity
(212 GW by 20503) is planned in the North Sea as a consequence
to Europe´s strategy to be carbon neutral by 2050. The size and
magnitude of the already installed (28 GW European offshore
wind farm capacity by 20214) and the planned offshore wind
farm (OWF) installation5has raised concerns about their impact
on the marine environment6and scientic efforts have increased
to understand and assess the implications of these large structures
for the marine system. In addition to impacts on the regional
atmosphere7, multiple physical8,9, biological6,10 and chemical11
impacts on the marine system have been identied. The under-
water structures, such as foundations and piles may cause tur-
bulent current wakes, which impact circulation, stratication,
mixing, and sediment resuspension1214. Most studies conclude
that the direct hydrodynamic consequences of the windfarm
structures are mainly restricted to the area within the wind
farms15,16. However, some speculate also, that the cumulative
impacts of an increasing number of offshore installations might
result in substantial impacts on the larger scale stratication13,17.
Larger scale effects of offshore wind energy production, well
beyond the wind farm areas, are introduced to the atmosphere by
infrastructures above the sea level and the energy extraction
itself18. Atmospheric wakes appearing in the lee of wind farms
extend on scales up to 65 km and beyond, depending on atmo-
spheric stability, with a wind speed reduction of up to 43% inside
the wakes18 leading to upwelling and downwelling dipoles in the
ocean beneath19. Previous modeling studies9,19 showed that these
dipoles are associated with vertical velocities in the order of
meters per day and consequent changes in mixing, stratication,
temperature, and salinity. Recently, Floeter et al.20 provided
empirical evidence for the existence of these upwelling/down-
welling dipoles showing distinct structural changes in mixed layer
depth and potential energy anomaly inside the wind wake area of
OWFs in the summer stratied area of the southern North Sea. A
rst assessment of the large-scale integrated impact of atmo-
spheric wakes from already existing OWFs on the hydrography of
the southern North Sea revealed the emergence of large-scale
oceanic structures with respect to currents, sea surface elevation,
and stratication8.
For the marine ecosystem the effects of OWFs might or might
not be severe, positive or negative. As van Berkel et al.16 explain,
the evaluation of ecosystem effects through BACI (before-after-
control-impact) surveys are challenging due to the spatio-
temporal variability of the natural system, regional and global
trends, as well as other anthropogenic impacts, such as changes
in shing effort, eutrophication, and noise levels, while the focus
of investigations is on selected sh and seabird species. In the
literature we nd, so far, a number of studies related to immediate
impacts of OWFs on marine fauna6, such as the articial reefs
effect21,22 or the impacts of acoustic disturbances on sh and
marine mammals23,24. Indirect impacts are, however, likely even
more important, more complex, and more difcult to investigate.
This includes consequences of restricted sheries inside the
OWFs25 as well as the impacts of the above-described modulation
of the physical environment on the structuring of the pelagic10
and benthic22 ecosystem. It is well known that modications in
mixing and stratication also impacts nutrient availability in the
euphotic zone26,27, however, the picture of the ecosystem impacts
is less clear for some obvious reasons: (i) The changes in nutrient
concentration would start a cause-effect chain that translates into
changes in primary production and effectively alters the food
chain; (ii) In a dynamic system like the southern North Sea,
which is characterized by strong tidal and residual currents,
changes in the biotic and abiotic environment are exposed to
advective processes; (iii) The expected changes depend strongly
on the prevailing hydrodynamic conditions, which makes it dif-
cult to disentangle natural from inicted changes. Other than a
high-density suite of physical and biological observations,
numerical modeling studies are the only means to build BACI
studies as scenarios with and without the disturbance can be
simulated28. In a previous modeling study, van der Molen et al.28
proposed such an approach for an OWF at Dogger Bank, a
relatively shallow, well-mixed area of the North Sea using a
relatively coarse hydrodynamics-ecosystem model in combina-
tion with a wave model. Their study, however, was restricted to a
single OWF, which was parameterized simply as a reduction in
wind speed above the OWF.
Future OWF installations are planned to be far more
extensive29 and the consequences of accelerated deployment for
atmospheric dynamics and thermodynamics were shown to be
substantial and large scale in the area of the North Sea7. The
implications of these atmospheric changes for the future ocean
dynamics are still unclear. The question on how and to what
degree the emergent large-scale structural changes in atmosphere
and ocean7,8, under the premisses of large OWF clusters, might
affect marine ecosystem productivity remains yet unanswered.
Here we address this question while concentrating on the effects
of atmospheric wakes to the ocean. Mixing induced by the turbine
foundations in the ocean was neglected. For a future offshore
wind farm installation scenario, we consider the atmospheric
impact as simulated by a high-resolution (~2 km) atmospheric
model7to force a fully coupled physical-biogeochemical model
for the North Sea and Baltic Sea30. Different to earlier studies8we
employ an atmospheric model including a dynamical para-
meterization of OWFs, which takes into account the size of the
windfarm and the number of turbines7, and estimates impacts not
only on the wind eld but on the entire atmospheric physics. The
experiment including OWFs (Exp. 1: OWF) follows the design
given in Akhtar et al.7that includes all existing and planned
OWFs in the North Sea area based on information available in
2015 (see Supplementary Fig. 1) and is compared to a reference
simulation (Exp. 2: REF) without OWFs. For our idealized sce-
nario simulation, wind farm parameterization for 5 MW turbines
and hub heights of 90 m are used, the rotor diameter was con-
sidered as 126 m. The density of installed turbines was chosen to
be comparable to currently used densities for similar turbine
types. For the spatial distribution of installed capacity all planned
wind farm areas (planning status 2015) were used to distribute
the turbines for the wind farm parameterization. The installed
capacity for this scenario amounts to 120 GW, which is between
the 2030 high scenario of 65 GW for the North Sea and the
recently agreed commitment of the four countries Denmark,
Netherlands, Germany and Belgium (Esbjerg declaration) to
install a capacity of at 150 GW by 205031 in the North Sea. The
EUs overall plan for the installed capacity in 2050 in the North
Sea amounts to 212 GW. Hence, our simplied scenario corre-
sponds approximately to the installed capacity reached in about
15 yrs, by 2037.
The scenario simulations provide evidence that the increasing
amount of future OWF installations will substantially impact and
restructure the marine ecosystem of the southern and central
ARTICLE COMMUNICATIONS EARTH & ENVIRONMENT | https://doi.org/10.1038/s43247-022-00625-0
2COMMUNICATIONS EARTH & ENVIRONMENT | (2022) 3:292 | https://doi.org/10.1038/s43247-022-00625-0 | www.nature.com/commsenv
Content courtesy of Springer Nature, terms of use apply. Rights reserved
North Sea. Changing atmospheric conditions will propagate
through ocean hydrodynamics and change stratication intensity
and pattern, slow down circulation and systematically decrease
bottom shear stress. The model projects that wind wakes of large
OWF clusters in the North Sea provoke large scale changes in
annual primary production with local changes (increase/decrease)
of up to 10%, while region-wide averages in estimated annual
primary production remain almost unchanged. In addition, the
results show an increase in sediment carbon in deeper areas of the
southern North Sea with local increases of up to 10%, and
reduced dissolved oxygen at the Oyster Grounds, which is an area
where oxygen levels can occasionally fall below 3 mg l132.
Results and discussion
Average system response to OWFs. Our results conrm the
direct ocean response identied by earlier studies8,9to the
alterations in the wind eld (Supplementary Fig. 2) with clearly
dened upwelling and downwelling dipoles in the vicinity of the
OWF clusters. However, none of the earlier studies could show
the systematic, large-scale, time-integrated response of the ocean
to large OWF clusters as they are planned to be implemented in
the southern North Sea. As a consequence of the substantial
amount of energy that is extracted from the lower atmosphere7,
the ocean responds with a clear and systematic change in strati-
cation, both in strength of stratication (Supplementary Fig. 3)
and depths of the seasonal mixed layer. The latter was estimated
to be, on average, 12 m shallower in and around the OWF
clusters (Fig. 1a). This effect occurred most clearly in the deeper
stratied German Bight area and around the Dogger Bank region.
For OWFs in mixed areas this effect is per denition not relevant
and in frontal, less stratied areas the effect is less clear as the
stratication becomes naturally interrupted by changes in the
frontal position. Changes in mixed layer depth have been
reported earlier as a consequence of offshore wind farm wakes
due to the reduced wind induced mixing8, but also due to the
upwelling and downwelling dipoles20. Since the dipole structure is
associated with both an uplift and a depression in mixed layer
depth20 and is variable in dependence of the wind direction
(Supplementary Fig. 2), we hypothesize that the annual average
response is mainly a consequence of the reduced wind mixing.
Apart from the effect on the stratication, our simulations show
that the ocean responds with a substantial decrease in the annual
mean of the vertically-averaged horizontal current velocities in the
range of 0.003 m s1in large parts of the southern North Sea, but
which can locally reach up to 0.0087 m s1at the OWFs at Dogger
Bank and 0.0091 m s1in the seasonally stratied reach of the
German Bight (Fig. 1b). In both of these areas this means a
reduction of 15% of the prevailing residual current. At the same
time there are also local increases in mean current velocities in the
German Bight area and, specically between the OWF clusters in
that area. These result locally in changes in current velocities of
about ±10% of the prevailing residual currents, which corroborates
the ndings by Christiansen et al.8, who studied the impacts of
existing OWFs in the German Bight area by using an unstructured
grid model and a very simple satellite-derived wind wake
parameterization. This also shows that the large-scale circulation
of the area will be strongly altered with potential consequences for
sediment transport as shown below.
Ecosystem impacts. In the southern North Sea, areas with par-
ticularly high primary production are co-located with the frontal
belt off the coast and around Dogger Bank (Fig. 2a, insert). The
majority of future OWF installations are planned in exactly those
highly productive areas, which are known to be ecologically
highly important33. Our model results show that the systematic
modications of stratication and currents alter the spatial pat-
tern of ecosystem productivity (Fig. 2a). Annual net primary
production (netPP) changes in response to OWF wind wake
effects in the southern North Sea show both areas with a decrease
and areas with an increase in netPP of up to 10%. Most obvious is
the decrease in the center of the large OWF clusters in the inner
German Bight and at Dogger Bank, which are both clearly situ-
ated in highly productive frontal areas, and an increase in areas
around these clusters in the shallow, near-coastal areas of the
German Bight and at Dogger Bank. The latter might be fueled by
nutrient supply from subsurface waters as a consequence of the
upwelling and downwelling dipole as suggested in earlier
studies20. Additionally, we also nd changes in netPP in areas
further away from the OWF clusters, such as a decrease along the
fresh water front of the German and Danish coasts and an
increase south-east of Dogger Bank at Oyster Grounds, which is
typically seasonally stratied and shows lower productivity.
Identifying the robustness of these patterns with respect to dif-
ferent weather conditions and interannual variations requires
additional analysis and simulations. When integrated over a lar-
ger area, the estimated positive and negative changes tend to even
Fig. 1 Annual mean ocean response to atmospheric changes due to offshore windfarms. a Estimated change (OWF-REF) in mixed layer depth (MLD);
bvertically averaged current velocity for REF (arrows) and changes (OWF-REF) (color). Gray polygons indicate location of offshore wind farms. (OWF:
simulation experiment considering offshore wind farms; REF: reference simulation).
COMMUNICATIONS EARTH & ENVIRONMENT | https://doi.org/10.1038/s43247-022-00625-0 ARTICLE
COMMUNICATIONS EARTH & ENVIRONMENT | (2022) 3:292 | https://doi.org/10.1038/s43247-022-00625-0 |www.nature.c om/commsenv 3
Content courtesy of Springer Nature, terms of use apply. Rights reserved
out. Regional averages for the whole North Sea (model area with
longitude <9°E) as well as for the southern North Sea area (as in
Fig. 2a) and the German Bight (latitude: 53.555.5°N; longitude:
49°E) only show reductions down to 0.5%, while the average
reductions in netPP directly at the OWF locations adds up to
1.2 %. The direct response of the ecosystem at the OWF sites
can be assigned to the changed hydrodynamic conditions. This
includes, on the one hand, the clearly dened upwelling and
downwelling patterns (Supplementary Fig. 2), which have been
hypothesized to play a major role in the changes OWFs provoke
in marine ecosystems10,20. Those patterns depend on the wind
direction and can be expected to modify the nutrient exchange at
the thermocline, as has been shown for temperature and salinity9,
at and around the OWF clusters. On the other hand, the pro-
duction changes are directly related to the changes in stratica-
tion. A closer look at the vertical distribution of netPP change
(Fig. 2b) averaged over the areas with OWF installations (parti-
tioned spatially into OWFs at strongly stratied and less stratied
regions and temporally into spring and summer periods) shows
that OWFs in clearly seasonally stratied waters experience an
upward shift of the vertical production maximum, which occurs
typically at the mixed layer depth in summer. This is a con-
sequence of the shallower mixed layer depth, due to reduced wind
mixing. This signal is more prominent in summer than in spring.
In contrast, OWFs in less stratied and frequently mixed waters
show a decrease in production in the upper 20 m of the water
column in spring and at the depth of the thermocline in summer.
Additionally, changes in netPP might translate into changes in
trophic interactions. The changes in netPP are clearly converted
into changes in phytoplankton biomass (Supplementary Fig. 4).
However, the response in phytoplankton biomass is relatively
small; on average below 1% both inside and outside the OWF
clusters (Fig. 3), but can reach up to 10% locally (Supplementary
Fig. 4). An exception is the biomass change inside OWF clusters
positioned in stratied areas, where the average response is about
2.4% but with large variations. Interestingly these locations also
show a relatively strong increase in zooplankton biomass (12%),
which indicates that the local ecosystem is additionally structured
by top-down control through increased grazing pressure34.In
reality the increased zooplankton production at these locations
might be mitigated by additional higher trophic levels feeding on
zooplankton, which is not represented in the model used here. In
contrast, outside OWF clusters and OWF clusters in less stratied
and mixed areas the model estimates a slight average reduction in
zooplankton biomass (<0.5%). In these regions it is difcult to
conclude on the overall trophic response, since the average
fractional change in biomass is very small and shows a large
regional variation (Fig. 3).
Besides the changes in the pelagic ecosystem our model results
highlight a substantial impact on sedimentation and seabed
processes. The overall, large-scale reduction in average current
velocities (Fig. 1b) results in reduced bottom-shear stress to up to
10% locally (Fig. 4a). The reduced resuspension of organic carbon
from the sediments results in an increased amount of organic
carbon in the sediments in large parts of the southern North Sea
(Fig. 4b). This becomes specically evident at and close to the
OWF locations in deeper areas and at the Dogger Bank. The
average increase in sediment organic carbon amounts to almost
Fig. 2 Annual mean response of net primary productions (netPP) to atmospheric changes due to offshore wind farms. a Relative change in annual
averaged net primary production for 2010 (OWF-REF). Black contour line indicates potential energy anomaly (PEA) of 85 J m3roughly separating seasonally
stratied from mixed areas; gray polygons indicate location of considered offshore wind farms (insert: annual average of netPP simulated for 2010). bVertical
proles of change (mean and standard deviation) in netPP inside the offshore wind farm areas; blue: less stratied and mixed areas (PEA < 85 J m3); green:
stratied areas (PEA 85 J m3) (solid lines: spring; dashed lines: summer). (OWF: simulation experiment considering offshore wind farms; REF: reference
simulation).
Fig. 3 Fractional change ((OWF-REF)/REF) in annually and vertically
averaged phytoplankton and zooplankton biomass. Mean and standard
deviation for areas inside and outside the OWF clusters separated based on
the potential energy anomaly (PEA) into stratied (PEA 85 J m3) and
less stratied and mixed areas (PEA < 85 J m3). Note, for the analysis
areas deeper than 60 m were excluded. (OWF: simulation experiment
considering offshore wind farms; REF: reference simulation).
ARTICLE COMMUNICATIONS EARTH & ENVIRONMENT | https://doi.org/10.1038/s43247-022-00625-0
4COMMUNICATIONS EARTH & ENVIRONMENT | (2022) 3:292 | https://doi.org/10.1038/s43247-022-00625-0 | www.nature.com/commsenv
Content courtesy of Springer Nature, terms of use apply. Rights reserved
10% directly at the OWF locations and 6% in the German Bight
area. However, averaged over larger areas the effect is less
pronounced with only a 0.2% increase North Sea wide. Our
ndings on reduced resuspension are consistent with ndings
from van der Molen et al.28 for his case study of an OWF located
on Dogger Bank. Their model indicated an associated reduction
in light attenuation in the water column leading to a slight
increase in primary production. In large parts of the southern
North Sea light can be considered the major limiting factor for
primary production in summer26. Our results conrm changes in
light availability (Supplementary Fig. 4c) in the subsurface,
however, the pattern is strongly related to the pattern of change in
primary production, which indicates a dominant effect of
phytoplankton self-shading. In addition, our results do not show
that the reduction in resuspension is necessarily related to an
overall reduction of particulate organic matter concentration in
the water column. Considering the cause-effect chain that leads to
higher-primary production under improved light conditions, but
would in turn increase phytoplankton self-shading, the quanti-
cation of this effect on longer time scales remains to be studied
in the future.
In addition to changes in sediment-carbon distribution the
model indicates an impact of OWF on bottom water oxygen in
the southern North Sea (Fig. 4c). Oxygen is a key biogeochemical
component in marine ecosystems, and often considered as an
indicator for ecosystem health35. Even though the highly dynamic
North Sea is not known for extensive low oxygen areas, earlier
studies reported the potential for low oxygen events in the central
North Sea, more specically at the Oyster Grounds32,36. The
Oyster Grounds denotes a bathymetric depression, which partly
limits the exchange with the surrounding water and supports the
development of summer stratication. As a consequence, organic
material tends to accumulate in bottom waters at the Oyster
Grounds, which is associated with enhanced oxygen consump-
tion. Observations in this area show that dissolved oxygen
concentrations in bottom waters can occasionally fall below
3mgl
132, and also in our reference simulation dissolved oxygen
in bottom water was below 4 mg l1in late summer and autumn.
According to our simulation the Oyster Grounds is an area,
which would be especially impacted by large-scale OWF
installations. Due to increased primary production on the one
hand, but also by the reduced advective currents and bottom
shear stress the dissolved oxygen concentrations in late summer
and autumn were further reduced by about 0.3 mg l1on average
and up to 0.68 mg l1locally in our simulations. In other areas of
the southern North Sea, the effect was estimated to be less severe,
or even showing an increase in dissolved oxygen concentration,
like e.g., along the edges of Dogger Bank.
Consequences for higher tropic levels and management.Within
this study, we estimated the so far underrated effects of the changed
atmospheric conditions by OWFs on the large-scale features of the
lower trophic levels of the marine ecosystem in the southern North
Sea. The results highlight that, considering the extensive OWF
installation plans for the area, the marine ecosystem responds very
clearly to the changes in the atmosphere leading to changes in
ocean stratication, advective processes and a systematic decrease
in bottom shear stress. These changes can be expected to progress
into higher trophic levels of the marine ecosystem. The southern
North Sea is well-known for supporting a diversity of marine
fauna37,38 and especially the near-coastal areas are nursery grounds
for many economically relevant sh stocks. The estimated changes
in the spatial distribution of primary production might impact the
survival of sh early life stages in specic areas due to e.g., varia-
tions in the match-mismatch dynamics39 with their prey or as a
consequence of low oxygen conditions. Understanding these
changes is pivotal for successful future sheries management in the
North Sea and could inuence the identication and imple-
mentation of marine protected areas. Additionally, the estimated
changes in organic sediment distribution and quantity could have
an effect on the habitat quality for benthic species such as lesser
sandeel (Ammodytes marinus) and other benthic species that live in
the sediments in the deeper areas of the southern North Sea40.
Their spatial distributions might change as it has been shown to
depend on the available food quantity and quality41 as well as the
prevailing bottom shear stress42.
The quantication of the effects on species distribution and
diversity remains a topic for future studies as the model used here
is truncated at the secondary production level and does not allow
for species-specic estimates. In addition, the high computational
demand for running both models (atmosphere and ocean) on a
high resolution currently limits our simulation to one year only,
without an additional spinup period to allow for the system to
adjust to the OWF-induced changes. The average physical
response can be, at least partly (e.g., with respect to mixed layer
depth and reduced residual currents), considered immediate and
is mainly related to the reduced energy in the wind eld.
The ecosystem components, in contrast, might need a transition
phase to establish a new ecosystem state under OWF inuence.
Still, the changes we see are a systematic response to the energy
Fig. 4 Annual mean response of benthic processes to atmospheric changes due to offshore wind farms. a Relative change in annually averaged bottom
shear stress; brelative change in annually averaged sediment organic carbon; cabsolute change in dissolved bottom water oxygen (average July-
September). Black contour line indicates potential energy anomaly of 85 J m3; gray polygons indicate location of considered OWFs. (OWF: simulation
experiment considering offshore wind farms; REF: reference simulation).
COMMUNICATIONS EARTH & ENVIRONMENT | https://doi.org/10.1038/s43247-022-00625-0 ARTICLE
COMMUNICATIONS EARTH & ENVIRONMENT | (2022) 3:292 | https://doi.org/10.1038/s43247-022-00625-0 |www.nature.c om/commsenv 5
Content courtesy of Springer Nature, terms of use apply. Rights reserved
extraction from the atmosphere and will likely consolidate after a
few years of simulation, but with interannual variations related to
changes in the environmental conditions. A repetition of the
simulation experiments with an end-to-endmodel approach43
and multi-annual simulations are required to shed further light
on the robustness of the estimated pattern, the transfer of the
changes into the food web and its implications for ecosystem
services and management. Additionally, further research on the
combined effects of atmospheric wakes and anthropogenic
mixing induced by the pile structures17 in the ocean is necessary,
as this might counteract the stabilizing effect of the wind wakes.
Under the ambitious plans for OWF constructions in the North
Sea17 space becomes one of the major limiting resources for a
large number of partly conicting usage interests44. Our results
can serve to support the inevitable development of co-use
management strategies under the given conditions.
Methods
ECOSMO model description and setup. ECOSMO is a well-established, fully
coupled marine ecosystem model for the North Sea and Baltic Sea area. The version
of ECOSMO II used here has been presented in detail before45 and contains a total
of 16 state variables that describes the lower trophic components (phytoplankton
and zooplankton) of the marine ecosystem as well as the major macro-nutrient
cycles (nitrogen, phosphorus, silicon) relevant for the North Sea and Baltic Sea
system. The sediment compartment is included through a simple bottom layer
which accumulates organic material. Benthic uxes of the different nutrients are
estimated separately in a non-Redeld manner to account for oxygen-dependent
chemical processes in the sediment. On the basis of the free-surface 3D baroclinic
coupled sea-ice model HAM(burg)S(chelf)O(cean) M(odel)46, the non-linear pri-
mitive equations are solved on a staggered Arakawa-C grid with a horizontal
resolution of ~2 km and a time step of 90 s. The impacts of the OWF wind wakes
were earlier found to be related to the internal radius of deformation19, which is
about 10 km in the North Sea area47. The smallest scales resolved by the model are
twice the grid size (approx. 4 km). Hence, the internal radius of deformation is well
resolved by the model. The vertical dimension is simulated with z-level coordinates
with a maximum of 30 layers, with a higher resolution in the upper layers the
surface to represent ocean stratication, and increasing level thickness in deeper
layers (5 m for the rst two layers; 4 m up to depths of 50 m; 6 m for depths
between 50 and 92 m; 100 m; 120 m; 140 m; 160 m; 180m; 200 m; 250 m; 300 m;
400 m; 500 m; 630 m). In total, this adds up to 2516251 wet grid cells. The model
uses a second-order LaxWendroff advection scheme that was made TVD (total
variation diminishing) by a superbee-limiter48 that has been described in detail in
an earlier study49, and which has been shown to adequately represent the frontal
structures in the southern North Sea.
The overall model setup including forcing data is comparable to the setup used
in Zhao et al.26 but with a different set of open boundary conditions for
temperature and salinity. The latter were provided by a global simulation using the
Max Planck Institute Ocean Model (MPI-OM)50 in a higher resolution setup51
forced with the NCEP/NCAR reanalysis52.
Atmospheric forcing and Windfarm scenarios. A non-hydrostatic model
COSMO-CLM with atmospheric grid resolution of ~ 2 km (1100 × 980 grid cells)
has been used to simulate the regional climate with and without OWFs in the North
Sea. It uses 62 vertical levels with 5 levels within the rotor area. To include the
impact of OWFs in COSMO-CLM a wind farm parameterization7,53 has been
implemented that represents wind-turbine effects as momentum sink and source of
turbulent kinetic energy. In this experiment, a theoretical OWF model was used
based on the theoretical National Renewable Energy Laboratory (NREL) 5 MW
reference wind turbine. It uses a wind turbine with a hub height of 90 m and rotor
diameter of 126 m54. These turbines have a cut-in wind speed of 3 ms1, rated wind
speed of 11.4 ms1, and a cut-out wind speed of 25 ms1. The atmospheric model
used a wind turbine density of about 1.8 × 106m2. Due to coarse atmospheric
grid resolution (~2 km), the average effect of the wind turbines within the gridbox is
estimated using the average grid box velocity. For both the experiments, with and
without wind farms, initial and boundary conditions from coastDat3 simulations55
were used. The latter were forced by the European Center for Medium-Range
Weather Forecast (ECMWF) ERA-Interim reanalysis56. A more detailed description
of the experimental conguration, wind farm parameterization and a validation of
the parameterization can be found in a previous study7.
Strategy for using the models and data analysis. ECOSMO was forced by the
COSMO-CLM simulations with and without OWF parameterization for the year
2010. The change in forcing is thereby not constrained to the change in the wind
eld but comprises changes in all required forcing parameters including pressure,
short wave radiation, 2 m air temperature, humidity, and precipitation. The
simulations in 2010 were initialized using a 2-year long (20082009) spinup
simulation also forced by COSMO-CLM (without OWF parameterization). Con-
sidering that the characteristic time scale of the North Sea is in the order of 13
years a two-year spinup is sufcient for initializing the simulation, especially since
the initial elds for physical state variables were retrieved from a previously con-
ducted simulation with a similar model setup but a different atmospheric and river
forcing. The latter simulation started in 1995 with the same setup but atmospheric
forcing from the COSMO REA6 reanalysis57 and freshwater discharges provided
by the mesoscale hydrological model (mHM)58, which is a calibrated, grid-based
hydrological model for Europe59. Ecosystem state variables were initialized from
climatological values based on the World Ocean Atlas60. Since the atmospheric
simulation is computationally very demanding, only one year of the simulation is
currently available covering the full ocean model domain.
Model data output has been postprocessed based on daily mean values available
for all state variables as well as for biogeochemical uxes and bottom-shear stress.
Potential energy anomaly61, the energy required to homogenize the water column,
provides a measure for the strength of stratication. For the denition of the mixed
layer depth we used a temperature criterion suggested by de Boyer Montégut
et al.62 where the mixed layer depth is dened as the depths at which ΔT0.2 °C
with respect to the surface layer temperature. Figures were compiled with matlab
using the cmocean colormap63.
Reporting summary. Further information on research design is available in the Nature
Portfolio Reporting Summary linked to this article.
Data availability
The datasets generated and/or analyzed during the current study are publicly available at
the world data center for climate (www.wdc-climate.de) under http://hdl.handle.net/21.
14106/d116dd4f38f47f150e655ab9441601b34b312583.
Code availability
Model code access for the marine ecosystem model ECOSMO can be obtained upon
request.
Received: 13 June 2022; Accepted: 11 November 2022;
References
1. WindEurope. Offshore wind in Europe - Key trends and statistics 2019.
Technical Report https://windeurope.org/wp-content/uploads/les/about-
wind/statistics/WindEurope-Annual-Offshore-Statistics-2019.pdf (2019).
2. The European Green Deal. Communication from the commission to the
European parliament, the European Council, the council., the European
economic and social committee and the committee of the regions https://eur-
lex.europa.eu/resource.html?uri=cellar:b828d165-1c22-11ea-8c1f-
01aa75ed71a1.0002.02/DOC_1&format=PDF (2019).
3. Freeman, K. et al. Our Energy Our Future - How offshore wind will help Europe
go carbon-neutral https://windeurope.org/about-wind/reports/our-energy-
our-future/ (2019).
4. WindEurope. Wind energy in Europe - 2021 Statistics and the outlook for
20222026 https://windeurope.org/intelligence-platform/product/wind-
energy-in-europe-2021-statistics-and-the-outlook-for-2022-2026/ (2022).
5. Díaz, H. & Guedes Soares, C. Review of the current status, technology and
future trends of offshore wind farms. Ocean Eng. 209, 107381 (2020).
6. Bergström, L. et al. Effects of offshore wind farms on marine wildlifeA
generalized impact assessment. Environ. Res. Lett. 9, 034012 (2014).
7. Akhtar, N., Geyer, B., Rockel, B., Sommer, P. S. & Schrum, C. Accelerating
deployment of offshore wind energy alter wind climate and reduce future
power generation potentials. Sci. Rep. 11,112 (2021).
8. Christiansen, N., Daewel, U., Djath, B. & Schrum, C. Emergence of large-scale
hydrodynamic structures due to atmospheric offshore wind farm wakes. Front.
Mar. Sci. 9,117 (2022).
9. Ludewig, E. Inuence of Offshore Wind Farms on Atmosphere and Ocean
Dynamics (University of Hamburg, 2014).
10. Floeter, J. et al. Pelagic effects of offshore wind farm foundations in the
stratied North Sea. Prog. Oceanogr. 156, 154173 (2017).
11. Reese, A., Voigt, N., Zimmermann, T., Irrgeher, J. & Pröfrock, D.
Characterization of alloying components in galvanic anodes as potential
environmental tracers for heavy metal emissions from offshore wind
structures. Chemosphere 257, 127182 (2020).
12. Lass, H. U., Mohrholz, V., Knoll, M. & Prandke, H. Enhanced mixing
downstream of a pile in an estuarine ow. J. Marine Syst. 74, 505527 (2008).
ARTICLE COMMUNICATIONS EARTH & ENVIRONMENT | https://doi.org/10.1038/s43247-022-00625-0
6COMMUNICATIONS EARTH & ENVIRONMENT | (2022) 3:292 | https://doi.org/10.1038/s43247-022-00625-0 | www.nature.com/commsenv
Content courtesy of Springer Nature, terms of use apply. Rights reserved
13. Carpenter, J. R. et al. Potential impacts of offshore wind farms on North Sea
stratication. PLoS One 11,128 (2016).
14. Forster, R. M. The effect of monopile-induced turbulence on local suspended
sediment pattern around UK wind farms. An IECS report to The Crown Estate
https://ore.catapult.org.uk/wp-content/uploads/2018/12/The-Effect-of-
Monopile-Induced-Turbulence-on-Local-Suspended-Sediment-Pattern-
around-UK-Wind-Farms.pdf (2018).
15. Mittendorf, W., Hoyme, H. & Zielke, K. Beeinussung der Meeresströmung
durch Windparks. In 1.Symposium Offshore - Windenergie Bau- und
umwelttechnische Aspekte, Hannover 2001 (2001).
16. van Berkel, J. et al. The effects of offshore wind farms on hydrodynamics and
implications for shes. Oceanography 33, 108117 (2020).
17. Dorrell, R. M. et al. Anthropogenic mixing in seasonally stratied shelf seas by
offshore wind farm infrastructure. Front. Mar. Sci. 9,125 (2022).
18. Platis, A. et al. Long-range modications of the wind eld by offshore wind
parksresults of the project WIPAFF. Meteorologische Zeitschrift 29, 355376
(2020).
19. Broström, G. On the inuence of large wind farms on the upper ocean
circulation. J. Marine Syst. 74, 585591 (2008).
20. Floeter, J., Pohlmann, T., Harmer, A. & Möllmann, C. Chasing the offshore
wind farm wind-wake-induced upwelling/downwelling dipole. Front. Marine
Sci. https://doi.org/10.3389/fmars.2022.8 (2022).
21. Degraer, S. et al. Offshore wind farm articial reefs affect ecosystem structure
and functioning: A synthesis. Oceanography 33,4857 (2020).
22. Hutchison, Z. L. et al. Offshore wind energy and benthic habitat changes
lessons from block island wind farm. Oceanography 33,5869 (2020).
23. Mooney, T. A., Andersson, M. & Stanley, J. Acoustic impacts of offshore wind
energy on shery. Oceanography 33,8295 (2020).
24. Madsen, P. T., Wahlberg, M., Tougaard, J., Lucke, K. & Tyack, P. Wind
turbine underwater noise and marine mammals: implications of current
knowledge and data needs. Mar. Ecol. Prog. Ser. 309, 279295 (2006).
25. Barbut, L. et al. The proportion of atsh recruitment in the North Sea
potentially affected by offshore windfarms. ICES J. Marine Sci. 77, 12271237
(2020).
26. Zhao, C., Daewel, U. & Schrum, C. Tidal impacts on primary production in
the North Sea. Earth Syst. Dyn. Discuss. 10, 287317 (2019).
27. Lozier,M.S.,Dave,A.C.,Palter,J.B.,Gerber,L.M.&Barber,R.T.On
the relationship between stratication and primary productivity in the
North Atlantic. Geophys. Res. Lett. https://doi.org/10.1029/2011GL049414
(2011).
28. van der Molen, J., Smith, H. C. M., Lepper, P., Limpenny, S. & Rees, J.
Predicting the large-scale consequences of offshore wind turbine array
development on a North Sea ecosystem. Cont. Shelf Res. 85,6072 (2014).
29. 4cOffshore. Global Offshore Renewable Map. https://map.4coffshore.com/
offshorewind/ (2022).
30. Daewel, U. & Schrum, C. Low-frequency variability in North Sea and Baltic
Sea identied through simulations with the 3-D coupled physical-
biogeochemical model ECOSMO. Earth Syst. Dyn. 8, 801815 (2017).
31. THE ESBJERG DECLARATION on The North Sea as a Green Power Plant of
Europe.https://www.bundesregierung.de/resource/blob/974430/2040932/
b357fa6726099a0304ee97c3a64e411c/2022-18-05-erklaerung-nordsee-gipfel-
data.pdf?download=1(2022).
32. Weston, K. et al. Sedimentary and water column processes in the Oyster
Grounds: A potentially hypoxic region of the North Sea. Mar. Environ. Res.
65, 235249 (2008).
33. Munk, P. et al. Spawning of North Sea shes linked to hydrographic features.
Fish Oceanogr. 18, 458469 (2009).
34. Chust, G. et al. Biomass changes and trophic amplication of plankton in a
warmer ocean. Glob. Chang. Biol. 20, 212439 (2014).
35. Best, M. A., Wither, A. W. & Coates, S. Dissolved oxygen as a physico-
chemical supporting element in the Water Framework Directive. Mar. Pollut.
Bull. 55,5364 (2007).
36. Greenwood, N. et al. Detection of low bottom water oxygen concentrations in
the North Sea; implications for monitoring and assessment of ecosystem
health. Biogeosciences 7, 13571373 (2010).
37. Daan, N., Bromley, P. J., Hislop, J. R. G. & Nielson, N. A. Ecology of North Sea
sh. Netherlands J. Sea Res. 26, 343386 (1990).
38. Fransz, H. G., Colebrook, J. M., Gamble, J. C. & Krause, M. The Zooplankton
of the North Sea. J. Sea Res. 28,152 (1991).
39. Daewel, U., Peck, M. A. & Schrum, C. Life history strategy and impacts of
environmental variability on early life stages of two marine shes in the North
Sea: An individual-based modelling approach. Can. J. Fisheries Aquatic Sci. 68,
426443 (2011).
40. Rindorf, A., Wright, P. J., Jensen, H. & Maar, M. Spatial differences in growth
of lesser sandeel in the North Sea. J. Exp. Mar. Biol. Ecol. 479,919 (2016).
41. Reiss, H. & Krönke, I. Seasonal variability of infaunal community structures in
three areas of the North Sea under different environmental conditions. Estuar
Coast Shelf Sci. 65, 253274 (2005).
42. Donadi, S. et al. The body-size structure of macrobenthos changes predictably
along gradients of hydrodynamic stress and organic enrichment. Mar. Biol.
162, 675685 (2015).
43. Daewel, U., Schrum, C. & MacDonald, J. I. Towards end-to-end (E2E)
modelling in a consistent NPZD-F modelling framework (ECOSMO E2E-
v1.0): application to the North Sea and Baltic Sea. Geosci. Model Dev. 12,
17651789 (2019).
44. Bundesministerium der Justiz und für Verbraucherschutz. Anlage zur
Verordnung über die Raumordnung in der deutschen ausschließlichen
Wirtschaftszone in der Nordsee und in der Ostsee vom 19. August 2021. In
Bundesgesetzblatt Teil I Nr. 58 vom 26. August 2021 44 (Bundesanzeiger
Verlag GmbH, 2021).
45. Daewel, U. & Schrum, C. Simulating long-term dynamics of the coupled
North Sea and Baltic Sea ecosystem with ECOSMO II: Model description and
validation. J. Marine Syst. 119120,3049 (2013).
46. Schrum, C. & Backhaus, J. O. Sensitivity of atmosphere-ocean heat exchange
and heat content in the North Sea and the Baltic Sea. Tellus - Series A: Dyn.
Meteorol. Oceanogr. 51, 526549 (1999).
47. Chelton, D. B., Deszoeke, R. A., Schlax, M. G., el Naggar, K. & Siwertz, N.
Geographical variability of the rst baroclinic Rossby radius of deformation. J.
Phys. Oceanogr. 28, 433460 (1998).
48. Harten, A. High resolution schemes for hyperbolic conservation laws. Appl.
Math. Sci. 278, 260278 (1997).
49. Barthel, K. et al. Resolving frontal structures: On the computational costs and
pay-off using a less diffusive but computational more expensive advection
scheme. Ocean Dyn. https://doi.org/10.1007/s10236-012-0578-9 (2012).
50. Marsland, S. J., Haak, H., Jungclaus, J. H., Latif, M. & Röske, F. The Max-
Planck-Institute global ocean/sea ice model with orthogonal curvilinear
coordinates. Ocean Model 5,91127 (2003).
51. Müller, W. A. et al. A Higher-resolution Version of the Max Planck Institute
Earth System Model (MPI-ESM1.2-HR). J. Adv Model Earth Syst. 10,
13831413 (2018).
52. Kalnay, E. et al. The NCEP/NCAR 40-year reanalysis project. Bull. Am.
Meteorol. Soc. 77, 437471 (1996).
53. Fitch, A. C., Olson, J. B. & Lundquist, J. K. Parameterization of wind farms in
climate models. J. Clim. 26, 64396458 (2013).
54. Jonkman, J. M., Buttereld, S., Musial, W. & Scott, G. Denition of a 5MW
Reference Wind Turbine for Offshore System Development.Technical Report
NREL/TP-500-38060 February 2009 https://doi.org/10.2172/947422 (2009).
55. Geyer, B., Weisse, R., Bisling, P. & Winterfeldt, J. Climatology of North Sea
wind energy derived from a model hindcast for 19582012. J. Wind Eng.
Indus. Aerodyn. 147,1829 (2015).
56. Dee, D. P. et al. The ERA-Interim reanalysis: conguration and performance
of the data assimilation system. Q. J. R. Meteorol. Soc. 137, 553597 (2011).
57. Bollmeyer, C. et al. Towards a high-resolution regional reanalysis for the
european CORDEX domain. Q. J. R. Meteorol. Soc. 141,115 (2015).
58. Rakovec, O. & Kumar, R. Mesoscale Hydrologic Model based historical
streamow simulation over Europe at 1/16 degree. World Data Center for
Climate (WDCC) at DKRZ. https://doi.org/10.26050/WDCC/
mHMbassimEur (2022).
59. Samaniego, L., Kumar, R. & Attinger, S. Multiscale parameter regionalization
of a grid-based hydrologic model at the mesoscale. Water Resour. Res. 46,
125 (2010).
60. Conkright, M. E. et al. World Ocean Atlas 2001: Objective Analyses, Data
Statistics, and Figures, CD-ROM Documentation. pp. 17 (National
Oceanographic Data Center, Silver Spring, MD, 2002).
61. Simpson, J. H. The shelf-sea fronts: implications of their existence and
behaviour. Philos. Trans. R. Soc. London Ser. A, Math. Phys. Sci. 302, 531546
(1981).
62. de Boyer Montégut, C., Madec, G., Fischer, A. S., Lazar, A. & Iudicone, D.
Mixed layer depth over the global ocean: An examination of prole data and a
prole-based climatology. J. Geophys. Res. Oceans 109,120 (2004).
63. Thyng, K. M., Greene, C. A., Hetland, R. D., Zimmerle, H. M. & DiMarco, S.
F. True colors of oceanography. Oceanography 29,913 (2016).
Acknowledgements
The study is a contribution to the BMBF funded project CoastalFutures (03F0911E), the
Helmholtz Research Program Changing Earth- Sustaining our Futureand the EXC
2037 Climate, Climatic Change, and Society(Project Number: 390683824 funded by the
German Research Foundation (DFG)). The authors would like to acknowledge the
German Climate Computing Center (DKRZ) for providing computational resources.
Author contributions
C.S. and U.D. conceived the study and designed the study setup. U.D. performed the
model simulation with ECOSMO, data analysis, and prepared the manuscript with
contributions from all co-authors. N.A. performed the atmospheric model simulation
COMMUNICATIONS EARTH & ENVIRONMENT | https://doi.org/10.1038/s43247-022-00625-0 ARTICLE
COMMUNICATIONS EARTH & ENVIRONMENT | (2022) 3:292 | https://doi.org/10.1038/s43247-022-00625-0 |www.nature.c om/commsenv 7
Content courtesy of Springer Nature, terms of use apply. Rights reserved
and prepared the atmospheric forcing data for the ecosystem model. U.D., C.S., N.A., and
N.C. contributed to data analysis and manuscript writing.
Funding
Open Access funding enabled and organized by Projekt DEAL.
Competing interests
The authors declare no competing interests.
Additional information
Supplementary information The online version contains supplementary material
available at https://doi.org/10.1038/s43247-022-00625-0.
Correspondence and requests for materials should be addressed to Ute Daewel.
Peer review information Communications Earth & Environment thanks Rodney Forster,
Göran Broström and the other, anonymous, reviewer(s) for their contribution to the peer
review of this work. Primary Handling Editors: Olivier Sulpis, Clare Davis, Heike
Langenberg. Peer reviewer reports are available.
Reprints and permission information is available at http://www.nature.com/reprints
Publishers note Springer Nature remains neutral with regard to jurisdictional claims in
published maps and institutional afliations.
Open Access This article is licensed under a Creative Commons
Attribution 4.0 International License, which permits use, sharing,
adaptation, distribution and reproduction in any medium or format, as long as you give
appropriate credit to the original author(s) and the source, provide a link to the Creative
Commons license, and indicate if changes were made. The images or other third party
material in this article are included in the articles Creative Commons license, unless
indicated otherwise in a credit line to the material. If material is not included in the
articles Creative Commons license and your intended use is not permitted by statutory
regulation or exceeds the permitted use, you will need to obtain permission directly from
the copyright holder. To view a copy of this license, visit http://creativecommons.org/
licenses/by/4.0/.
© The Author(s) 2022
ARTICLE COMMUNICATIONS EARTH & ENVIRONMENT | https://doi.org/10.1038/s43247-022-00625-0
8COMMUNICATIONS EARTH & ENVIRONMENT | (2022) 3:292 | https://doi.org/10.1038/s43247-022-00625-0 | www.nature.com/commsenv
Content courtesy of Springer Nature, terms of use apply. Rights reserved
1.
2.
3.
4.
5.
6.
Terms and Conditions
Springer Nature journal content, brought to you courtesy of Springer Nature Customer Service Center GmbH (“Springer Nature”).
Springer Nature supports a reasonable amount of sharing of research papers by authors, subscribers and authorised users (“Users”), for small-
scale personal, non-commercial use provided that all copyright, trade and service marks and other proprietary notices are maintained. By
accessing, sharing, receiving or otherwise using the Springer Nature journal content you agree to these terms of use (“Terms”). For these
purposes, Springer Nature considers academic use (by researchers and students) to be non-commercial.
These Terms are supplementary and will apply in addition to any applicable website terms and conditions, a relevant site licence or a personal
subscription. These Terms will prevail over any conflict or ambiguity with regards to the relevant terms, a site licence or a personal subscription
(to the extent of the conflict or ambiguity only). For Creative Commons-licensed articles, the terms of the Creative Commons license used will
apply.
We collect and use personal data to provide access to the Springer Nature journal content. We may also use these personal data internally within
ResearchGate and Springer Nature and as agreed share it, in an anonymised way, for purposes of tracking, analysis and reporting. We will not
otherwise disclose your personal data outside the ResearchGate or the Springer Nature group of companies unless we have your permission as
detailed in the Privacy Policy.
While Users may use the Springer Nature journal content for small scale, personal non-commercial use, it is important to note that Users may
not:
use such content for the purpose of providing other users with access on a regular or large scale basis or as a means to circumvent access
control;
use such content where to do so would be considered a criminal or statutory offence in any jurisdiction, or gives rise to civil liability, or is
otherwise unlawful;
falsely or misleadingly imply or suggest endorsement, approval , sponsorship, or association unless explicitly agreed to by Springer Nature in
writing;
use bots or other automated methods to access the content or redirect messages
override any security feature or exclusionary protocol; or
share the content in order to create substitute for Springer Nature products or services or a systematic database of Springer Nature journal
content.
In line with the restriction against commercial use, Springer Nature does not permit the creation of a product or service that creates revenue,
royalties, rent or income from our content or its inclusion as part of a paid for service or for other commercial gain. Springer Nature journal
content cannot be used for inter-library loans and librarians may not upload Springer Nature journal content on a large scale into their, or any
other, institutional repository.
These terms of use are reviewed regularly and may be amended at any time. Springer Nature is not obligated to publish any information or
content on this website and may remove it or features or functionality at our sole discretion, at any time with or without notice. Springer Nature
may revoke this licence to you at any time and remove access to any copies of the Springer Nature journal content which have been saved.
To the fullest extent permitted by law, Springer Nature makes no warranties, representations or guarantees to Users, either express or implied
with respect to the Springer nature journal content and all parties disclaim and waive any implied warranties or warranties imposed by law,
including merchantability or fitness for any particular purpose.
Please note that these rights do not automatically extend to content, data or other material published by Springer Nature that may be licensed
from third parties.
If you would like to use or distribute our Springer Nature journal content to a wider audience or on a regular basis or in any other manner not
expressly permitted by these Terms, please contact Springer Nature at
onlineservice@springernature.com
... Studies on impacts of offshore wind development on plankton communities are limited and not specific to copepod abundance and distribution (Daewel et al. 2022;Floeter et al. 2017;Paskyabi 2015); however, energy extraction by offshore wind farms, including due to wind wakes, could potentially impact local to regional ocean circulation and transport processes that are thought to influence copepod aggregations. Wind wakes may induce changes to primary productivity (i.e., phytoplankton that copepods feed on) including potential local increases, or decreases, and regional scale dispersion (Daewel et al. 2022). ...
... Studies on impacts of offshore wind development on plankton communities are limited and not specific to copepod abundance and distribution (Daewel et al. 2022;Floeter et al. 2017;Paskyabi 2015); however, energy extraction by offshore wind farms, including due to wind wakes, could potentially impact local to regional ocean circulation and transport processes that are thought to influence copepod aggregations. Wind wakes may induce changes to primary productivity (i.e., phytoplankton that copepods feed on) including potential local increases, or decreases, and regional scale dispersion (Daewel et al. 2022). Fixed-bottom foundation structures from offshore wind development in the North Sea were found to impact oceanographic conditions including stratification resulting in bottom-up food web impacts such as increases in primary productivity and densities of larval echinoderms (Floeter et al. 2017). ...
... • Daewel et al. (2022) modeled hydrodynamic impacts of energy loss from wind turbine wakes showing potential changes in primary productivity and declines in dissolved oxygen levels that could result in food web and ecosystem impacts. The need for future research leading to better understanding of the consequences to higher trophic levels is implied and studies on changes to species distributions are directly recommended. ...
Technical Report
To support a detailed understanding of how the presence of wind turbine structures may alter hydrodynamics and provide guidance on how the offshore wind industry can best support research to understand and mitigate impacts, ACP sought to develop this white paper, which serves three key goals. First, it synthesizes the current state of the science on the hydrodynamic effects of offshore wind turbines, including recently published and ongoing research efforts. To support this synthesis, the white paper also presents an overview of the effects of climate change and natural environmental variability in the Western North Atlantic, providing context for ongoing and potential future changes in NARW distribution and habitat utilization. Second, the white paper outlines short- and long-term research questions and strategies to address those questions. Third, it describes how the offshore wind industry can be involved in addressing those questions to avoid, minimize, and mitigate potential impacts. This white paper is intended to serve as a useful public reference, and to complement efforts by other organizations and entities who share an interest in offshore wind’s potential impacts on the surrounding environment, in particular, the ongoing efforts by the National Academies of Science, Engineering, and Medicine as part of their Committee on Evaluation of Hydrodynamic Modeling and Implications for Offshore Wind Development: Nantucket Shoals.1 While the white paper does evaluate the state of the science and make recommendations for industry, it does not evaluate or make any recommendations on present or future policy decisions.
... The impacts of OWFs on the marine environment is studied from different perspectives (Degraer et al., 2019;Gușatu et al., 2021), such as the influence of noise emissions during construction on mammals (Carstensen et al., 2006;Dolman and Jasny, 2015;Kastelein et al., 2019;Rose et al., 2019), seabird habitat changes (Best and Halpin, 2019;Busch et al., 2013;Goodale et al., 2019;Larsen and Guillemette, 2007), fish avoidance and attraction behaviours (Degraer et al., 2021;Gill et al., 2020;Glarou et al., 2020), impacts of biofouling species inhabiting offshore structures Slavik et al., 2018), changes in benthic communities (Coolen et al., 2022), effects of ocean turbulence (Callies et al., 2018;Carpenter et al., 2016;Grashorn and Stanev, 2016;Schultze et al., 2017),and consequences of decreasing wind speeds (Christiansen et al., 2022a;Christiansen et al., 2022b;Daewel et al., 2022). ...
Thesis
The North Sea is bordered by heavily populated and highly industrialised countries. The anthropogenic pressure on the marine ecosystem is undisputed: pollutants from the inland reach the sea via rivers and the sea itself has long been used by humans. Shipping, fishing, dumping and, more recently, offshore wind energy production all take place in the North Sea. These anthropogenic activities pose the risk of additional pollutant inputs. Valid analytical methods are therefore required for the targeted monitoring and source differentiation of both new and known pollutants. This doctoral thesis lays the foundation for the inorganic monitoring of potential pollutants induced by offshore wind farms. In Publication I (doi: 10.1016/j.chemosphere.2020.127182), galvanic anodes for corrosion protection of offshore wind turbines were analysed and inorganic tracers were identified. These tracers include the main anode components aluminium and zinc, the toxicologically relevant and already well-studied elements cadmium and lead as well as the technology-critical and wind farm or corrosion protection-specific elements indium and gallium. In addition, the analysed anodes showed specific lead isotope ratios, which can potentially also be used for source attribution. The valid quantification of metals in seawater samples is a challenge due to two factors: low concentrations of the target analytes and the high salt content of the seawater matrix itself. In addition, there are no certified values for the tracer metals indium and gallium identified in Publication I in natural water reference materials. Publication II (doi: 10.1111/ggr.12422) therefore presents a further developed analytical method for the quantification of 34 metals in water samples. It utilises matrix separation and pre-concentration via an extraction resin combined with online measurement using inductively coupled plasma tandem mass spectrometry. This method was applied to 17 certified water reference materials. Combined with a comprehensive literature review, consensus values for non-certified elements were proposed and values for gallium and indium in various water reference materials were published for the first time. The analysis of sediments in the Elbe estuary in Publication III (doi: 10.1016/j.scitotenv.2019.02.401) also aimed to investigate source signatures and possible transport routes of pollutants into the German Bight in more detail. The sediments were analysed for the mass fractions of 48 elements using a multi-element method. In addition, strontium, neodymium and lead isotope ratios were measured. Six extreme stations in the estuary showed particularly remarkable lead isotope signatures. The combination of multi-element analysis, isotope ratio determinations and statistical methods enabled the development of a multi-tracer approach that revealed the high variability and dynamics in the Elbe estuary and made it possible to create a fingerprint of the estuary. The tracers identified in Publication I and the methodology presented in Publication III were finally applied to real samples from the vicinity of offshore wind farms in Publication IV (doi: 10.1016/j.marpolbul.2023.115396). The multi-element analysis and Strontium isotope ratios in the sediment samples have not yet shown any clear accumulation of offshore tracers. However, it was found that the Strontium isotope signatures of the sediments in one of the wind farm regions are very similar to the sediments of the Elbe estuary from publication II, which indicates that Elbe sediments are transported into the North Sea and that some of the increased metal mass fractions may originate from Elbe sediments instead of from galvanic anodes of the offshore wind farms.
... There is therefore a pressing need to understand and quantify any potential impacts of these offshore developments on the physical oceanography of coastal seas [4][5][6]. These potential physical changes are expected to have cascading effects that may have the potential to alter marine productivity [7,8] and higher trophic levels, such as fish and whale populations [4,9]. ...
Article
The continued development of shallow continental shelf regions with offshore wind farm (OWF) structures raises the question of what potential hydrodynamic impacts may be expected. One such impact is a reduction in the ocean currents that results from the additional frictional drag from the turbine foundation structures. To understand this potential "blocking" effect, we construct a fluid mechanical model consisting of an idealized circular patch of OWF with increased friction. The idealized OWF is then subjected to a steady mean flow superimposed on much stronger elliptical tidal currents—a common scenario in shelf seas with OWF installations. Due to the quadratic dependence of friction on fluid velocity, the elliptical tidal currents result in a linearized friction acting on the mean flow that is no longer parallel to the mean flow. This "anisotropic" friction has the effect of deflecting, in addition to reducing, the mean flow in the region of the OWF. However, it is found that a good approximation to the reduction of flow caused by OWFs can be obtained by the simplest linear, isotropic representation of the friction, i.e., a linear drag law. The flow reduction within the OWFs is found to be primarily dependent on the ratio of the increase in drag coefficient inside the farm to that of the surroundings, with weaker dependencies on the parameters describing the tidal ellipse. The magnitudes of the flow reductions in the idealized model appear to be in approximate agreement with more realistic modeling results, and are expected to capture the basic balance of the mean flow in the blocking of ocean currents by many OWFs in the North Sea, especially with increasing size in future development scenarios.
... OSW energy development drives a variety of ecosystem changes, including in hydrodynamic conditions and primary production (Daewel et al. 2022) and the development of artificial reefs on turbine foundations and scour protection (Degraer et al. 2020). Sounds are also generated by geophysical and geotechnical surveys (primarily during the preconstruction period), pile-driving and other construction activities (including multiple piling technologies with different sound characteristics), the operation and maintenance of offshore wind turbines and associated infrastructure, and vessel activity during all development phases (Fig. 1). ...
... The dipole interacts with the horizontal windforced Ekman transport, ultimately preserving net upwelling ( Figure 1) (Liu et al., 2023). These artificially induced upwellings are instrumental in elevating nutrient-rich water to the surface and ventilating the lower layers, thereby playing a vital role in regulating marine ecosystems (Pan et al., 2016;Daewel et al., 2022). ...
Article
Full-text available
Introduction Offshore wind farms (OWFs) generate extensive wind wakes in their leeward areas, which can induce marine upwelling and downwelling. These processes significantly affect marine stratification and ecosystems, leaving detectable patterns on the sea surface. Materials and Methods By utilizing MODIS data, we analyzed six representative OWFs worldwide to identify these wake signatures. Result Notably, we observed pronounced signatures near an OWF located in the coastal waters of Jiangsu Province, China. Conversely, no coherent wake signatures were detected at other selected European and Chinese OWFs. Discussion This absence may be attributed to inactive upwelling, weak marine stratification, unsteady wind directions, and land-sea distribution. This research offers a fresh perspective on the environmental impacts of OWFs and, for the first time, underscores the potential of global gridded satellite dataset in detecting OWF-induced wind wake signatures.
... 22 respectively. Recent studies showed that offshore wind farms cause notable disturbances in ocean circulation and strati cation themselves 17,[22][23][24][25][26] , and thus should be accounted for when studying the impact of offshore hydrogen production. ...
Preprint
Full-text available
Offshore production of hydrogen powered by offshore wind energy offers a promising alternative to fossil fuels. However, current technologies return generated waste heat and brine into the sea, raising questions of potential effects on local and regional hydrography. This study evaluates the hydrographic footprint of offshore hydrogen in the context of anthropogenic pressures, focusing on a scenario for the German Bight. Cross-scale modeling shows that waste heat emerges as the primary influence, causing temperature changes of up to 2°C within 10's of meters around a 500 MW hydrogen plant. While tides prove to be decisive for the dilution of density plumes, we demonstrate that production capacity and discharge method determine the hydrographic footprint. Large-scale effects are minor and become negligible compared to the impact of offshore wind farm wakes, however, waste heat can raise annual mean sea surface temperature by up to 0.2°C within wind farm areas.
... The exact effect of large-scale floating solar arrays on stratification patterns is still uncertain and requires more field and modelling research studies (Karpouzoglou et al., 2020). As stratification controls the vertical distribution of algae, nutrients, and oxygen, it is one of the key abiotic factors controlling marine ecosystem functioning (Daewel et al. (2022)). ...
Article
Full-text available
Offshore solar is seen as a promising technology for renewable energy generation. It can be particularly valuable when co-located within offshore wind farms, as these forms of energy generation are complementary. However, the environmental impact of offshore solar is not fully understood yet, and obtaining a better understanding of the possible impact is essential before this technology is applied at a large scale. An important aspect which is still unclear is how offshore solar affects the local hydrodynamics in the marine environment. This article describes the hydrodynamic wake generated by an offshore solar array, arising from the interaction between the array and a tidal current. A computational fluid dynamic (CFD) modeling approach was used, which applies numerical large eddy simulations (LES) in OpenFOAM. The simulations are verified using the numerical model TUDFLOW3D. The study quantifies the wake dimensions and puts them in perspective with the array size, orientation, and tidal current magnitude. The investigation reveals that wake width depends on array size and array orientation. When the array is aligned with the current, wake width is relatively confined and does not depend on the array size. When the array is rotated, the wake width experiences exponential growth, becoming approximately 30% wider than the array width. Wake length is influenced by factors such as horizontal array dimensions and current magnitude. The gaps in between the floaters decrease this dependency. Similarly, the wake depth showed similar dependencies, except for the current magnitude, and only affected the upper meters of the water column. Beneath the array, flow shedding effects occur, affecting a larger part of the water column than the wake. Flow shedding depends on floater size, gaps, and orientation.
... Any potential mechanism by which a platform influences or provides opportunity for a biological community scales with size (for a consistent platform type or design (Lawrence and Fernandes 2022 )). Such mechanisms include providing a hard substrate on which sessile organisms can settle (Stachowitsch et al. 2002, Love et al. 2019c ), providing complex 3D structures which act as potential refugia or resting places for fish or invertebrates (Rogers et al. 2014, Komyakova et al. 2019, Price et al. 2019, and affecting local hydrodynamics, creating a wake or increasing vertical mixing downstream potentially affecting local productivity and fish behaviour (Floeter et al. 2017, Schultze et al. 2020, Daewel et al. 2022. ...
Article
Full-text available
Thousands of offshore oil and gas platforms have been installed worldwide and are known to act as artificial reefs. Many platforms are nearing the end of their operational lives and will soon require decommissioning, but uncertainty remains about the impacts of these structures, and their removal, on the environment. Fish aggregate at platforms, but little is known about the extent of these effects in the North Sea and the causes of variability in these associations. Here, an uncrewed surface vessel (USV) was used to collect fisheries acoustic data on distributions of schooling and non-schooling fish around six oil platforms, collecting data within tens of metres of four of the surveyed platforms. In areas with more platforms, more non-schooling fish were found, and the probability of detecting fish schools was higher. Interplatform variability was found in trends in non-schooling fish density with increasing distance from platform, but the relationship was found to be strongest and most negative at the larger platforms. These findings may influence future management decisions around the decommissioning of these platforms, particularly if some structure is to be left in place to maximize the potential benefits associated with these artificial reef effects.
Article
Full-text available
The rapid growth of offshore wind farms (OWFs) is driven by concerns for energy security and climate change mitigation. However, their impact on marine environments remains poorly understood due to limited research. This study analyzes the effects of an OWF along China's Jiangsu Coast on seawater quality using data from different development phases. Results show the major pollutants were different across phases. Heavy metal pollution reached alert levels during construction compared to the safe levels observed in the pre-construction and operational phases, mainly due to increases in Pb, Cd, and Hg concentrations. Eutrophication was mild throughout all periods but exhibited a continuous decrease, primarily attributed to reductions in PH and COD concentrations. As a result, the comprehensive pollution level during construction was increased, but it was improved to a clean level during the operational phase. Besides, significant variations were observed in the spatial distribution patterns of major pollutant indices across different scenarios. These changes may stem from a combination effect of land-based pollution, aquaculture, OWF-induced disturbances to atmosphere and hydrodynamics, OWF-related drain and leakage contamination, and marine management policies. Understanding these effects informs OWF optimization, rational wind resource utilization, and marine ecology protection.
Article
Full-text available
The offshore wind energy sector has rapidly expanded over the past two decades, providing a renewable energy solution for coastal nations. Sector development has been led in Europe, but is growing globally. Most developments to date have been in well-mixed, i.e., unstratified, shallow-waters near to shore. Sector growth is, for the first time, pushing developments to deep water, into a brand new environment: seasonally stratified shelf seas. Seasonally stratified shelf seas, where water density varies with depth, have a disproportionately key role in primary production, marine ecosystem and biogeochemical cycling. Infrastructure will directly mix stratified shelf seas. The magnitude of this mixing, additional to natural background processes, has yet to be fully quantified. If large enough it may erode shelf sea stratification. Therefore, offshore wind growth may destabilize and fundamentally change shelf sea systems. However, enhanced mixing may also positively impact some marine ecosystems. This paper sets the scene for sector development into this new environment, reviews the potential physical and environmental benefits and impacts of large scale industrialization of seasonally stratified shelf seas and identifies areas where research is required to best utilize, manage, and mitigate environmental change.
Article
Full-text available
The potential impact of offshore wind farms through decreasing sea surface wind speed on the shear forcing and its consequences for the ocean dynamics are investigated. Based on the unstructured-grid model SCHISM, we present a new cross-scale hydrodynamic model setup for the southern North Sea, which enables high-resolution analysis of offshore wind farms in the marine environment. We introduce an observational-based empirical approach to parameterize the atmospheric wakes in a hydrodynamic model and simulate the seasonal cycle of the summer stratification in consideration of the recent state of wind farm development in the southern North Sea. The simulations show the emergence of large-scale attenuation in the wind forcing and associated alterations in the local hydro- and thermodynamics. The wake effects lead to unanticipated spatial variability in the mean horizontal currents and to the formation of large-scale dipoles in the sea surface elevation. Induced changes in the vertical and lateral flow are sufficiently strong to influence the residual currents and entail alterations of the temperature and salinity distribution in areas of wind farm operation. Ultimately, the dipole-related processes affect the stratification development in the southern North Sea and indicate potential impact on marine ecosystem processes. In the German Bight, in particular, we observe large-scale structural change in stratification strength, which eventually enhances the stratification during the decline of the summer stratification toward autumn.
Article
Full-text available
The European Union has set ambitious CO 2 reduction targets, stimulating renewable energy production and accelerating deployment of offshore wind energy in northern European waters, mainly the North Sea. With increasing size and clustering, offshore wind farms (OWFs) wake effects, which alter wind conditions and decrease the power generation efficiency of wind farms downwind become more important. We use a high-resolution regional climate model with implemented wind farm parameterizations to explore offshore wind energy production limits in the North Sea. We simulate near future wind farm scenarios considering existing and planned OWFs in the North Sea and assess power generation losses and wind variations due to wind farm wake. The annual mean wind speed deficit within a wind farm can reach 2–2.5 ms ⁻¹ depending on the wind farm geometry. The mean deficit, which decreases with distance, can extend 35–40 km downwind during prevailing southwesterly winds. Wind speed deficits are highest during spring (mainly March–April) and lowest during November–December. The large-size of wind farms and their proximity affect not only the performance of its downwind turbines but also that of neighboring downwind farms, reducing the capacity factor by 20% or more, which increases energy production costs and economic losses. We conclude that wind energy can be a limited resource in the North Sea. The limits and potentials for optimization need to be considered in climate mitigation strategies and cross-national optimization of offshore energy production plans are inevitable.
Article
Full-text available
We review the state of knowledge about offshore wind farm (OWF) development-related effects on hydrodynamics and their possible secondary effects on fishes derived from European studies. Theoretical, modeling, and observational studies of OWF developments are relatively advanced and identify potential impacts resulting from OWF changes to local or regional hydrodynamics through modification of (1) the wind fields, and (2) oceanographic parameters including turbulence, mixing, and vertical stratification. While limited, studies discuss local OWF (i.e., within the OWF footprint) impacts on fishes due to sediment resuspension or sedimentation, temperature change, nutrient transport, and substrate availability. These studies largely neglect possible effects further afield and generally conclude that any hydrodynamic impact of OWFs on fishes cannot be distinguished when compared to natural variability. To further understanding of the cumulative risk from extensive OWF developments requires additional research on OWF-related spillover effects on surrounding ecosystems and on natural oceanographic connectivity. The use of dynamic habitat or agentbased models coupled with refined hydrodynamic models can help quantify the scale of spatial and temporal effects of hydrodynamic cues on the movement of fishes and their habitats, which is not currently possible via conventional modeling, quantitative analysis approaches, or field-based observational studies and surveys.
Article
Full-text available
Offshore wind farms (OWFs) are proliferating globally. The submerged parts of their structures act as artificial reefs, providing new habitats and likely affecting fisheries resources. While acknowledging that the footprints of these structures may result in loss of habitat, usually soft sediment, we focus on how the artificial reefs established by OWFs affect ecosystem structure and functioning. Structurally, the ecological response begins with high diversity and biomass in the flora and fauna that gradually colonize the complex hard substrate habitat. The species may include nonindigenous ones that are extending their spatial distributions and/or strengthening populations, locally rare species (e.g., hard substrate-associated fish), and habitat-forming species that further increase habitat complexity. Functionally, the response begins with dominant suspension feeders that filter organic matter from the water column. Their fecal deposits alter the surrounding seafloor communities by locally increasing food availability, and higher trophic levels (fish, birds, marine mammals) also profit from locally increased food availability and/or shelter. The structural and functional effects extend in space and time, impacting species differently throughout their life cycles. Effects must be assessed at those larger spatiotemporal scales.
Article
Full-text available
The Block Island Wind Farm (BIWF), situated offshore of Block Island, Rhode Island, is the first commercial offshore wind farm (OWF) in the United States. We briefly review pre-siting studies, which provide contextual information about the benthic habitats and fish in the Block Island Sound area before the BIWF jacket foundations were installed in 2015. We focus on benthic monitoring that took place within the BIWF. This monitoring allowed for assessments of spatiotemporal changes in sediment grain size, organic enrichment, and macrofauna, as well as the colonization of the jacket structures, up to four years post-installation. The greatest benthic modifications occurred within the footprint of the foundation structures through the development of mussel aggregations. Within four years, changes in benthic habitats (defined as biotopes) were observed within the 90 m range of the study, clearly linked to the musseldominated colonization of the structures, which also hosted numerous indigenous fish species. We discuss the evident structural and functional effects and their ecological importance at the BIWF and for future US OWFs, drawing on similarities with European studies. While reviewing lessons learned from the BIWF, we highlight the need to implement coordinated monitoring for future developments and recommend a strategy to better understand environmental implications.
Article
Full-text available
ARTICLE INFO Keywords Offshore wind farms Offshore wind support structures Offshore wind turbines Renewable energy Wind farm layout Worldwide coastline offshore projects ABSTRACT The present paper provides an overview of the current state and future trends of the offshore wind farms worldwide along with the technological challenges, especially the wind farm layout and the main components. First, this paper provides a review of the operative wind farms, main components characteristics and the wind farms dimensions. This is followed by a correlation analysis between offshore wind farm layout parameters such as the number of turbines, the installed capacity, the distance from shore and the water depth. Moreover, the present paper reviews the available data regarding the future projects' portfolio. The evolution of offshore wind technology related to the pre-and under-construction projects is discussed. The data showed an increase in the wind farm dimensions and the capacity of the turbines for wind power generation more in line with that from other energy resources, which is, thereby, enhancing the potential and attractiveness of offshore wind industry for future investors. Finally, a discussion of future previsions related to offshore wind farm layout and capacity concludes the paper.
Article
Full-text available
The impact of offshore constructions on the marine environment is unknown in many aspects. The application of Al- and Zn-based galvanic anodes as corrosion protection results in the continuous emission of inorganic matter (e.g. >80 kg Al-anode material per monopile foundation and year) into the marine environment. To identify tracers for emissions from offshore wind structures, anode materials (Al-based and Zn-based) were characterized for their elemental and isotopic composition. An acid digestion and analysis method for Al and Zn alloys was adapted and validated using the alloy CRMs ERM®-EB317 (AlZn6CuMgZr) and ERM®-EB602 (ZnAl4Cu1). Digests were measured for their elemental composition by ICP-MS/MS and for their Pb isotope ratios by MC ICP-MS. Ga and In were identified as potential tracers. Moreover, a combined tracer approach of the elements Al, Zn, Ga, Cd, In and Pb together with Pb isotope ratios is suggested for a reliable identification of offshore-wind-farm-induced emissions. In the Al anodes, the mass fractions were found to be >94.4% of Al, >2620 mg kg⁻¹ of Zn, >78.5 mg kg⁻¹ of Ga, >0.255 mg kg⁻¹ of Cd, >143 mg kg⁻¹ of In and >6.7 mg kg⁻¹ of Pb. The Zn anodes showed mass fractions of >2160 mg kg⁻¹ of Al, >94.5% of Zn, >1.31 mg kg⁻¹ of Ga, >254 mg kg⁻¹ of Cd, >0.019 mg kg⁻¹ of In and >14.1 mg kg⁻¹ of Pb. The n(²⁰⁸Pb)/n(²⁰⁶Pb) isotope ratios in Al anodes range from 2.0619 to 2.0723, whereas Zn anodes feature n(²⁰⁸Pb)/n(²⁰⁶Pb) isotope ratios ranging from 2.0927 to 2.1263.
Article
Full-text available
This publication synthesizes the results of the WIPAFF (WInd PArk Far Fields) project. WIPAFF focused on the far field of large offshore wind park wakes (more than 5 km downstream of the wind parks) located in the German North Sea. The research project combined in situ aircraft and remote sensing measurements, satellite SAR data analysis and model simulations to enable a holistic coverage of the downstream wakes. The in situ measurements recorded on-board the research aircraft DO‑128 and remote sensing by laser scanner and SAR prove that wakes of more than 50 kilometers exist under certain atmospheric conditions. Turbulence occurs at the lateral boundaries of the wakes, due to shear between the reduced wind speed inside the wake and the undisturbed flow. The results also reveal that the atmospheric stability plays a major role in the evolution of wakes and can increase the wake length significantly by a factor of three or more. On the basis of the observations existing mesoscale and industrial models were validated and updated. The airborne measurement data is available at PANGAEA/ESSD.
Article
Full-text available
Understanding the influence of man-made infrastructures on fish population dynamics is an important issue for fisheries management. This is particularly the case because of the steady proliferation of offshore wind farms (OWFs). Several flatfish species are likely to be affected because areas with OWFs in place or planned for show a spatial overlap with their spawning grounds. This study focuses on six commercially important flatfish species in the North Sea: common sole (Solea solea), European plaice (Pleuronectes platessa), turbot (Scophthalmus maximus), brill (Scophtalmus rhombus), European flounder (Platichthys flesus), and common dab (Limanda limanda). We used a particle-tracking model (Larvae&Co) coupled to a 3D hydrodynamic model to assess the effects of spatial overlap of OWFs with the species’ spawning grounds on the larval fluxes to known nursery grounds. An important overlap between planned areas of OWFs and flatfish spawning grounds was detected, with a resulting proportion of settlers originating from those areas varying from 2% to 16%. Our study suggests that European plaice, common dab, and brill could be the most affected flatfish species, yet with some important local disparities across the North Sea. Consequently, the study represents a first step to quantify the potential impact of OWFs on flatfish settlement, and hence on their population dynamics.