1. Birds and Wind Farms M.Ferrer EBD-CSIC
The state of the art in Spain 2017
M.Ferrer
EBD-CSIC

4. CLIMATE CHANGE SPEED: 4-5 Km/year ACCORDING JULY ISOTHERMS
BETWEN 10 AND 25 TIMES FASTER
THAN IN THE LAST GLACIATION
Apollo 17

5. We NEED renewable energies

8. Wind power in different countries in 2007

11. The effects of a wind farm on birds in a migration point: the Strait of Gibraltar
Cádiz 1993

12. STUDY AREA
SPAIN NP WF AM
Atlantic Ocean
Mediterranean Sea

14. Birds changed flight direction when crossing wind farm, increasing altitude and avoiding turbines
Passerines diversity, density and breeding success was equal in and out of the wind farm
Bird mortality was low in this wind farm

16. BEFORE-AFTER CONSTRUCTION STUDIES

17. No differences before-after in both bird and small mammals densities

19. WIND FARM IMPACT ON BIRDS

20. Power 0.8-2.2 MW, Height (without blades) 50-80 m
20 Wind farms, 252 Turbines
Power MW, Height (without blades) m

21. High mortality rates with 337 collided birds per year, 124 of them raptors.
With mean collision rate of 1.33 birds per turbine and year being one of the higher mortality records published in the world

22. Does mortality differ among wind farms ?

23. Test of SS Whole Model vs. SS Residual
Multip
Multipl
Adjuste SS df MS F p
Vulture / year
0,6355
0,4039
0,3555
44,1596 19
2,3242
65,15
232
0,2808
8,27
0,000

24. Mortality per turbine and year was significant different among wind farms
The one with the highest mortality of griffon vultures was causing 23% of total mortality for the species, followed by another one causing 13%

25. Do collisions depend on raptor abundance ?

26. mortality of birds at the wind farm scale
No relationship between density (number of birds crossing the area) and
mortality of birds at the wind farm scale

28. Is mortality stable among years?

30. Univariate Tests of Significance Over-parameterized model Type III decomposition
Effect SS
Degr. of MS
Den.Syn. F p
Intercept
Fixed
12,83083 1
1,0000
0,707976
18,12327
0,146879
Year
Random
0,70798
22,0268
0,848024
0,83485
0,370766
month (year)
18,66778 22
0,84854
168,0000
0,426339
1,99028
0,007895
Error
71,62500
168
0,42634

31. Does mortality change during the year?

33. Does mortality differ among turbines ?

34. Coefficient of variation of vulture mortality:
Observed vs. Expected Frequencies in griffon vultures
Chi-Square = 316,3429 df = 251 p < ,003227
Friedman ANOVA and Kendall Coeff. of Concordance ANOVA Chi Sqr. (N = 251, df = 1) = 68,37052 p = Coeff. of Concordance = ,27239 Aver. rank r = ,26948
Average
Sum of
Mean
Std.Dev.
Vulture / year turbine
1,239044
311,0000
0,128574
0,266456
Expected
1,760956
442,0000
Coefficient of variation of vulture mortality:
Among wind farms: 50% Among turbines: 150%

36. But: How were these high impact wind farms authorized?
Didn't they conduct risk assessment studies?
Did they carry them out in a wrong way?

37. Risk assessment studies in Spain, as in Europe and several states in USA, rely mainly on bird counts in the potential area for the new wind farm.
Some other aspects are considered such distance to breeding areas of sensitive species, bat breeding or roosting sites and others.
The most relevant factor for raptors is considered to be the local density in the potential area, usually measured as the number of birds crossing the whole area of the future wind farm.

39. Observation at risk per hour Deaths per turbine and year
Wind Risk ________________________ ___________________________
Farm level Birds Vultures Raptors Birds Vultures Raptors

40. Observation at risk per hour Deaths per turbine and year
Wind Risk ________________________ ___________________________
Farm level Birds Vultures Raptors Birds Vultures Raptors

41. GLM using Poisson distribution and log link function
Dependent variable
Birds per turbine and year df Wald P
Intercept
Bird / hour
Birds at risk / hour
Risk level
Griffon vultures per turbine and year df Wald P
Intercept
G. vulture / hour
G. vulture at risk / hour
Risk level
Other raptors per turbine and year df Wald P
Intercept
Raptor / hour
Raptor at risk / hour
Risk level

47. And Now?
We need to mitigate
mortality caused by
badly placed turbines.
2) We need to change
our methods to evaluate
the potential risk in
new installations

48. And Now?
We need to mitigate
mortality caused by
badly placed turbines.
2) We need to change
our methods to evaluate
the potential risk in
new installations

51. Since 2008, we are using a selective stopping program to stop turbines when vultures were observed near.
Griffon vulture mortality rate was reduced by 65% with only a reduction in total energy production of the wind farms by 0.07% per year.
The use of selective stopping techniques at turbines with the highest mortality rates mitigate the impacts of wind farms on birds with a minimal affect on energy production.

56. And Now?
We need to mitigate
mortality caused by
badly placed turbines.
2) We need to change
our methods to evaluate
the potential risk in
new installations

57. Using Wind Tunnels to Predict Bird Mortality in Wind Farms: The Case of Griffon Vultures

61. N
Viento Sur
Viento Sureste
Viento Este
No statistical differences were detected between the observed flight trajectories of griffon vultures and the wind passages observed in our wind tunnel model

62. A significant correlation was found between dead vultures and predicted proportion of vultures crossing each turbine according to the aerodynamic model (rs = 0.840, n= 6. P= 0.036).

64. Simulación con ETESIO

65. Ensayo V-45 (400 m)

66. Ensayo V-45 (100 m)

67. Now in Spain, new regulations said that Risk Assessment Studies must be conducted at individual turbine scale and the Wind Tunnel Test would be a good tool.

68. Thank you for your attention