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

s.dirksen@buwa.nl

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).