Effects on flying birds in OffshoreWindfarm Egmond aan Zee
(OWEZ)
Sjoerd Dirksen
Karen Krijgsveld, Ruben Fijn, Martin Poot,Rob Lensink, Mark Collier, Peter van Horssen,
Maarten Japink and others
an overview of methods and results;cumulative effects as a challenge andreflections on the way forward• overview of results of fieldwork, showing methods,
presenting results
• our approach towards assessment of cumulativeimpacts
• the way forward: where are the main gaps inknowledge, what is needed to evaluate present plans
• not everything in detail - further discussions in workinggroup 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
Effects of wind farms:• collision risks• barrier effects• disturbance
Offshore wind farms & birds
Effects of wind farms:• collision risks• barrier effects• disturbance
Offshore wind farms & birds
Research questions:• fluxes• flight altitudes• flight paths
Effects of wind farms:• collision risks• barrier effects• disturbance
Offshore wind farms & birds
Research questions:• fluxes• flight altitudes• flight paths
Species groups: • seabirds, local & migrating• migrating terrestrial birds
~ 65 million birds, 170 species
• wind farm built in 2006• 36 turbines• 15 km offshore• measurements started April 2007• observations from metmast
OWEZ offshore wind farm
• 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
Study methods
Radar observations
• horizontal & vertical radar• Merlin radar system• DeTect Inc., Florida• automated registration of bird echoes
• for clutterfilter and analysis reportKrijgsveld et al. 2011
To make the Results more clear...
• Results from Vertical radar• All year - 24/7
• Results from Horizontal radar• All year - 24/7
• Results from Visual observations• From a total of 405 panorama scans
during 53 fieldwork days throughoutthe years.
Flux• 80 groups / km / hr through the wind farm area on average• large variation
Flux• 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
0
125000
250000
375000
500000
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
tota
l nu
mb
er o
f bir
d g
rou
ps/
km/m
on
th
0
1
2
3
4
ratio
nig
ht /
day
nightdayratio night/day
Species composition
• 103 different species observed in 15 species groups• majority gull species, migrating passerines & cormorants• relatively low numbers of birds in area:
distribution skewed towards shore and further offshore (Leopold et al. in prep)
entire scale
0
10
20
30
40
50
60
70
tubenose
s
alcids
gannets
skua
sdiv
ers
greb
es
corm
oran
ts
gees
e & s
wans
sea
duck
s
other
duc
ksgu
llster
ns
wader
s
rapto
rs & o
wls
landb
irds
% o
f all
bird
s
lower 5%
0
1
2
3
4
5
tubenose
salc
ids
gannets
skua
sdiv
ers
greb
es
corm
oran
ts
gees
e & s
wans
sea
duck
s
other
duc
ksgu
llster
ns
wader
s
rapto
rs & o
wls
landb
irds
% o
f all
bird
s
Flight altitude
16-03-2010 – 04:001400 m -
sea level -
turbine height -
Flight altitude
8 Nov 2009
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
July
0 40000 80000 120000
0 - 69
69 - 139
139 - 277
277 - 416
416 - 554
554 - 693
693 - 831
831 - 970
970 - 1108
1108 - 1247
1247 - 1385
altit
ude
clas
s (m
)
nightday
October
0 40000 80000 120000
nightday
number of tracks / km / month
Flight altitude
0
200000
400000
600000
800000
Spring Summer Autumn Winter
num
ber
of b
ird g
roup
s / k
m /
seas
on
above rotorsat rotorsbelow rotors
Day
0
200000
400000
600000
800000
Spring Summer Autumn Winter
above rotorsat rotorsbelow rotors
Night
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?
Flight paths
(c.f. Petersen et al. 2006)
Macro-avoidance
• avoidance was 18-34%• avoidance lowest in winter, highest in autumn
0
10
20
30
40
50
60
70
80
90
100
winter spring summer autumn
nr o
f tra
cks
insi
de w
ind
farm
,as
% o
f nr o
utsi
de
A
BC
D
T
FE
Species-specific avoidance
red: flying through wind farmgreen:not through wind farm
75 %25 %
36 %64 %
Species-specific avoidance Micro-avoidance
• what % of birds enters the rotor-swept area of a turbine?
Micro-avoidance• more birds flying where spacing of turbines was larger, • and when turbines were standing still
Micro-avoidance• 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, flightaltitudes, 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
passerines 60 1.119.600 310gulls 33 611.120 234all other species 6 135.330 37
total 1.866.000 581
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• 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
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
• 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• 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
From cumulative effects to population impacts
Fox et al. 2006
What are the likely cumulative effects of multiple wind farmsin the Dutch North Sea on the populations levels of birds?
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.• Calculate the level of mortality needed for zero-growth• Level of sustainable mortality; Potential Biological Removal (PBR) approach (Dillingham &
Fletcher 2008)
Schematic overview of approach and models developed
bewickiiBewick’s swanberniclaBrent goose
Popn modelSpecies
E. ScotlandRazorbillScotlandGuillemotNLCommon ternNLSandwich ternEastern UKKittiwakeNLLesser black-backed gullNLHerring gullScotlandGreat skuaBass RockGannet
1. Species population models
bewickiiBewick’s swanberniclaBrent goose
Popn modelSpecies
E. ScotlandRazorbillScotlandGuillemotNLCommon ternNLSandwich ternEastern UKKittiwakeNLLesser black-backed gullNLHerring gullScotlandGreat skuaBass RockGannet
1. Species population models
2. Calculated collision victims of multiple offshore windfarms
Collision-related mortality from 10 wind farms
<1<1Razorbill<1<1Guillemot613Common/Arctic tern
15529Sandwich tern217346Kittiwake75172Little gull
153356Common gull876777Lesser black-backed gull698586Herring gull135209Great black-backed gull
40<1Great skua<1<1Fulmar
19917Gannet92diver spp.
OffshoreNear-shoreSpecies
2. Effects of multiple wind farms on bird populations
Sandwich tern0% floaters155 collision victims each year
Limited effect on the populationtrajectories for both species thatwere increasing or decreasing.
2. Effects of multiple wind farms on bird populations
Kittiwake10% floaters750 collision victims each year
Limited effect on the populationtrajectories for both species thatwere increasing or decreasing.
For species with a declining populationthe trend was enhanced with theadditional mortality;
• Bewick’s swan• Herring gull• Kittiwakethese declines are known to be due to
ecological factors, such as lowreproduction and food availability.
Sandwich tern0% floaters375 collision victims each year
Assess number of collision victimsneeded to bring about a stablepopulation.
Zero-growth model
375Zero-growth155Offshore29Near-shore
n. collision victimsSandwich tern
3. Changes at the population level
Level of additional human-related mortality (Potential Biological Removal - PBR)that can be sustained by a bird population (Dillingham & Fletcher 2008)
25520Bewick´s swan+698200Herring gull
<13,4004,180,000Starling<13,400750,000Redwing
263451,300Kittiwake
<13,400540,000Meadow pipit<13,4001,390,000Skylark
111721,600Little gull236520,600Common gull42094,900Great black-backed gull
<1<14,900Fulmar<193,400Red-throated diver
%max. calc.mortality
PBRSpecies
3. Additional sustainable mortality - (PBR)
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.
Conclusions
We have made a first attempt to estimate the cumulative effects of multiplewind farms in part of the North Sea at the population level for a range ofspecies.
1. Population models reflected observed population trends.
2. Additional mortality of multiple wind farms had a limited effect onpopulation trends.
3. Additional sustainable mortality was for most species well above the levelof 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 comparisonwith collision related mortality.
Impacts are specific for OWEZ (location, configuration, etc.), future workneeds to be carried out to assess collision rates in other situations.
The way forward• research needs: other species, other locations, other wind farm
characteristics, assessing collision risks for species - all aiming atbetter tools for planning (locations, local design)
• 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 fromdetailed research in just a few windfarms
• seabirds and wind energy is much more like waterbirds in and aroundwetlands than seabird pessimists made us believe 15 years ago
Acknowledgements• 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 BureauWaardenburg),
• 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).
• Technical support was provided by Radio Holland and Detect.Inc (Florida).
• Logistical support was provided by NoordzeeWind, WVC Vestas OffshoreIJmuiden, Distel Sail and Rope Access.
• This study was commissioned by ‘Noordzeewind’ (a joint venture of Nuon andShell Wind Energy).