Effects on flying birds in Offshore
Windfarm Egmond aan Zee
(OWEZ)
Sjoerd Dirksen
Karen Krijgsveld, Ruben Fijn, Martin Poot,
Rob Lensink, Mark Collier, Peter van Horssen,
Maarten Japink and others
[email protected]
an overview of methods and results;
cumulative effects as a challenge and
reflections on the way forward
• overview of results of fieldwork, showing methods,
presenting results
• our approach towards assessment of cumulative
impacts
• the way forward: where are the main gaps in
knowledge, what is needed to evaluate present plans
• not everything in detail - further discussions in working
group and breaks
Offshore Wind Farm Egmond aan Zee
• Long-term monitoring program:
• Goal: evaluate economical, technical, social & ecological effects
e.g: marine mammals, fish, benthos,
local and migrating (sea)birds
Offshore Wind Farm Egmond aan Zee
• Long-term monitoring program:
• Goal: evaluate economical, technical, social & ecological effects
e.g: marine mammals, fish, benthos,
local and migrating (sea)birds
• We studied flight patterns of local and migrating (sea)birds:
• baseline study 2003-2005
• effect study 2007-2010
- 53 days of visual observations
- c. 1000 days of radar observations
- c. 400 GB data
Offshore Wind Farm Egmond aan Zee
• Long-term monitoring program:
• Goal: evaluate economical, technical, social & ecological effects
e.g: marine mammals, fish, benthos,
local and migrating (sea)birds
• We studied flight patterns of local and migrating (sea)birds:
• baseline study 2003-2005
• effect study 2007-2010
- 53 days of visual observations
- c. 1000 days of radar observations
- c. 400 GB data
• Reports available at www.noordzeewind.nl
Offshore wind farms & birds
Effects of wind farms:
• collision risks
• barrier effects
• disturbance
Offshore wind farms & birds
Offshore wind farms & birds
Effects of wind farms:
• collision risks
• barrier effects
• disturbance
Effects of wind farms:
• collision risks
• barrier effects
• disturbance
Research questions:
• fluxes
• flight altitudes
• flight paths
Research questions:
• fluxes
• flight altitudes
• flight paths
Species groups:
• seabirds, local & migrating
• migrating terrestrial birds
~ 65 million birds, 170 species
OWEZ offshore wind farm
•
•
•
•
•
wind farm built in 2006
36 turbines
15 km offshore
measurements started April 2007
observations from metmast
Radar observations
•
•
•
•
horizontal & vertical radar
Merlin radar system
DeTect Inc., Florida
automated registration of bird echoes
• for clutterfilter and analysis  report
Krijgsveld et al. 2011
Study methods
• radar observations: flight directions, fluxes, flight altitudes
• continuous measurements: night & day, every day
• visual observations: determine species composition
• standardized counts: panorama scans
• species-specific flight paths
• moon-watching, listening, sound-recording
To make the Results more clear...
Flux
•
•
•
Results from Vertical radar
•
Results from Horizontal radar
•
All year - 24/7
Results from Visual observations
From a total of 405 panorama scans
during 53 fieldwork days throughout
the years.
Flux
Species composition
•
•
•
•
•
•
•
80 groups / km / hr through the wind farm area on average
large variation
during migration: higher numbers at night
in summer (and winter): higher numbers during daytime
70
5
entire scale
30
0
tu
0
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Flight altitude
1400 m -
turbine
height sea level -
16-03-2010 – 04:00
2
1
10
1
0
3
20
be
125000
40
no
se
alc s
ga ids
nn
e
sk t s
ua
div s
e
g rs
ge cor r e b
es mo e s
e ra
& nt
s s
se wa
a n
ot d s
he uc
r ks
du
ck
s
gu
lls
te
ra
r
pt w a n s
or d
s
e
& rs
la ow
nd ls
bir
ds
2
% of all birds
50
250000
lower 5%
4
60
3
Flight altitude
8 Nov 2009
0
n
375000
% of all birds
night
day
ratio night/day
distribution skewed towards shore and further offshore (Leopold et al. in prep)
4
ratio night / day
total number of bird groups/km/month
500000
103 different species observed in 15 species groups
majority gull species, migrating passerines & cormorants
relatively low numbers of birds in area:
os
e
alc s
ga ids
nn
e
sk t s
ua
div s
e
g rs
ge cor r e b
es mo e s
e ra
& nt
s s
se wa
a n
ot d s
he uc
r ks
du
ck
s
gu
lls
te
ra
r
pt w a n s
or d
s
e
& rs
la owls
nd
bir
ds
•
be
•
80 groups / km / hr through the wind farm area on average
large variation
tu
•
All year - 24/7
Flight altitude
measured from 0 to 1400 m altitude
majority of birds < 70 m altitude
low flight altitudes in summer and winter  local seabirds
higher altitudes and more birds at night during migration
1247 - 1385
1108 - 1247
altitude class (m)
970 - 1108
July
October
night
day
night
day
831 - 970
693 - 831
554 - 693
800000
800000
Night
Day
number of bird groups / km / season
•
•
•
•
Flight altitude
600000
above rotors
at rotors
below rotors
600000
400000
400000
200000
200000
above rotors
at rotors
below rotors
416 - 554
277 - 416
0
0
139 - 277
Spring
69 - 139
Summer
Autumn
Winter
Spring
Summer
Autumn
Winter
0 - 69
0
40000
40000
80000
number of120000
tracks /0 km / month
80000
120000
Flight paths
Flight paths
•
•
Do birds avoid flying into the wind farm?
 macro-avoidance
•
Flight paths
•
•
•
Do birds avoid flying into the wind farm?
 macro-avoidance
When they fly into the wind farm, what is behaviour around turbines?
 micro avoidance
Flight paths
Do birds avoid flying into the wind farm?
 macro-avoidance
When they fly into the wind farm, what is behaviour around turbines?
 micro avoidance
What are differences between species groups?
(c.f. Petersen et al. 2006)
Macro-avoidance
•
•
Species-specific avoidance
avoidance was 18-34%
avoidance lowest in winter, highest in autumn
75 %
25 %
nr of tracks inside wind farm,
as % of nr outside
100
36 %
64 %
90
80
70
60
50
40
30
C
B
20
10
A
F
D
E
T
0
winter
spring
summer
autumn
red: flying through wind farm
green: not through wind farm
Species-specific avoidance
Micro-avoidance
•
what % of birds enters the rotor-swept area of a turbine?
Micro-avoidance
Micro-avoidance
• more birds flying where spacing of turbines was larger,
• and when turbines were standing still
• more birds flying where spacing of turbines was larger,
• and when turbines were standing still
• 66% avoided area close to turbines
• 93% of birds within 50 m of turbines avoided the rotor-swept area
• overall micro-avoidance was 97.6%
Towards an estimate of collision rate
• Because collisions could not be measured,
an estimate was made based on fluxes, macro- & micro-avoidance, flight
altitudes, and using the Band-model.
• With overall (micro & macro) avoidance rate between 98.0 and 99.2%
species group
% of birds
flux in area
estimated nr
of victims/yr
60
33
6
1.119.600
611.120
135.330
310
234
37
1.866.000
581
passerines
gulls
all other species
total
Conclusions
• Up to 2.000.000 bird groups passed the wind farm area each year
• Half of these birds flew through the wind farm at ‘risky’ altitudes
Conclusions
Conclusions
• Up to 2.000.000 bird groups passed the wind farm area each year
• Up to 2.000.000 bird groups passed the wind farm area each year
• Half of these birds flew through the wind farm at risky altitudes
• Half of these birds flew through the wind farm at risky altitudes
• The majority of flight paths belonged to migrating passerines and local gulls
• The majority of flight paths belonged to migrating passerines and local gulls
• Avoidance level was high:
-macro-avoidance of the wind farm varied between 18-34%
-macro-avoidance varied strongly between species
-micro-avoidance was very high: 97.6%
Conclusions
From cumulative effects to population impacts
• Up to 2.000.000 bird groups passed the wind farm area each year
• Half of these birds flew through the wind farm at risky altitudes
• The majority of flight paths belonged to migrating passerines and local gulls
• Avoidance level was high:
-macro-avoidance of the wind farm varied between 18-34%
-macro-avoidance varied strongly between species
-micro-avoidance was very high: 97.6%
• Collision rate was estimated at 580 birds in the wind farm per year
Fox et al. 2006
What are the likely cumulative effects of multiple wind farms
in the Dutch North Sea on the populations levels of birds?
Schematic overview of approach and models developed
Adopted a multi-step modelling approach:
Create models of current populations.
•
•
Reconstruction of current population trends
Validated against known population trends
Assess effects of multiple wind farms on the modelled populations.
•
•
Define impacts of multiple wind farms on individual species, i.e. mortality
Apply additional mortality to the modelled populations
Compare to level of mortality needed to bring about a change in the population level.
•
•
1.
Calculate the level of mortality needed for zero-growth
Level of sustainable mortality; Potential Biological Removal (PBR) approach (Dillingham &
Fletcher 2008)
Species population models
1.
Species population models
Species
Popn model
Species
Popn model
Bewick’s swan
Brent goose
Gannet
Great skua
Herring gull
Lesser black-backed gull
Kittiwake
Sandwich tern
Common tern
Guillemot
Razorbill
bewickii
bernicla
Bass Rock
Scotland
NL
NL
Eastern UK
NL
NL
Scotland
E. Scotland
Bewick’s swan
Brent goose
Gannet
Great skua
Herring gull
Lesser black-backed gull
Kittiwake
Sandwich tern
Common tern
Guillemot
Razorbill
bewickii
bernicla
Bass Rock
Scotland
NL
NL
Eastern UK
NL
NL
Scotland
E. Scotland
2.
Calculated collision victims of multiple offshore wind
farms
Collision-related mortality from 10 wind farms
Species
diver spp.
Gannet
Fulmar
Great skua
Great black-backed gull
Herring gull
Lesser black-backed gull
Common gull
Little gull
Kittiwake
Sandwich tern
Common/Arctic tern
Guillemot
Razorbill
Near-shore
Offshore
2
17
<1
<1
9
199
<1
40
209
586
777
356
172
346
29
3
<1
<1
135
698
876
153
75
217
155
61
<1
<1
2.
Effects of multiple wind farms on bird populations
Limited effect on the population
trajectories for both species that
were increasing or decreasing.
Sandwich tern
0% floaters
155 collision victims each year
2.
Effects of multiple wind farms on bird populations
Limited effect on the population
trajectories for both species that
were increasing or decreasing.
Kittiwake
10% floaters
750 collision victims each year
For species with a declining population
the trend was enhanced with the
additional mortality;
Skylark
Meadow pipit
Redwing
Starling
Bewick´s swan
Herring gull
Kittiwake
PBR
Sandwich tern
0% floaters
375 collision victims each year
n. collision victims
Near-shore
Offshore
Zero-growth
Level of additional human-related mortality (Potential Biological Removal - PBR)
that can be sustained by a bird population (Dillingham & Fletcher 2008)
Red-throated diver
Fulmar
Great black-backed gull
Common gull
Little gull
Assess number of collision victims
needed to bring about a stable
population.
Sandwich tern
Additional sustainable mortality - (PBR)
Species
Changes at the population level
Zero-growth model
• Bewick’s swan
• Herring gull
• Kittiwake
these declines are known to be due to
ecological factors, such as low
reproduction and food availability.
3.
3.
3,400
4,900
4,900
20,600
1,600
max. calc.
mortality
9
<1
209
365
172
<1
<1
4
2
11
1,390,000
540,000
750,000
4,180,000
3,400
3,400
3,400
3,400
<1
<1
<1
<1
20
200
1,300
5
698
345
25
+
26
29
155
375
Conclusions
We have made a first attempt to estimate the cumulative effects of multiple
wind farms in part of the North Sea at the population level for a range of
species.
%
Declining populations assessed as ‘near threatened’ species; (all ‘least concern’).
Herring gull;
- number of victims higher than the level of sustainable mortality.
- a higher recovery factor status increases this level to 1,200 per year.
1. Population models reflected observed population trends.
2. Additional mortality of multiple wind farms had a limited effect on
population trends.
3. Additional sustainable mortality was for most species well above the level
of mortality calculated for 10 wind farms.
Only effects of collisions modelled, not disturbance or barrier effects.
For OWEZ barrier and disturbance impacts were small in comparison
with collision related mortality.
Impacts are specific for OWEZ (location, configuration, etc.), future work
needs to be carried out to assess collision rates in other situations.
The way forward
Acknowledgements
• research needs: other species, other locations, other wind farm
characteristics, assessing collision risks for species - all aiming at
better tools for planning (locations, local design)
• All people contributing to fieldwork and data analysis:
• Daniël Beuker, Mark Collier, Sjoerd Dirksen, Ruben Fijn, Jim de Fouw,
Camiel Heunks, Robert Jan Jonkvorst, Karen Krijgsveld, Rob Lensink,
Hein Prinsen, Martin Poot, Eric van der Velde (all Bureau
Waardenburg),
• Mardik Leopold, Hans Verdaat and Martin de Jong (both IMARES),
• Kees Camphuysen (NIOZ),
• Thijs Schrama, Hans Slabbekoorn (both Leiden University) and
• Magnus Robb (Sound Approach).
• cumulative effects (impact at population level) to be explored further,
hopefully ahead of developments before us
• however... in 10 years time, we really made a step forward from
detailed research in just a few windfarms
• seabirds and wind energy is much more like waterbirds in and around
wetlands than seabird pessimists made us believe 15 years ago
• Technical support was provided by Radio Holland and Detect.Inc (Florida).
• Logistical support was provided by NoordzeeWind, WVC Vestas Offshore
IJmuiden, Distel Sail and Rope Access.
• This study was commissioned by ‘Noordzeewind’ (a joint venture of Nuon and
Shell Wind Energy).