Subproject responsibility: Pernille Lund Hoel, Kjetil Bevanger, Hans Chr. Pedersen, Eivin Røskaft, Bård Stokke
Objectives: Observation of WTE behaviour inside the wind-power plant area and in an adjacent control area, to collect data on possible behavioural differences as a response to the wind-power plant.
5.5.1 Methods
To investigate behavioural differences related to the distance from the turbines, data on flight activ-ity (moving flight, social behaviour and soaring) and flight height (below, in and above the rotor zone) were collected at 12 vantage points, 6 from inside the SWPP area and 6 from control areas close to the SWPP. In order to investigate possible differences inside SWPP versus the control area, observations from the 12 vantage points have been separated into two groups (6 vantage points in each) in some of the analysis and named control area (CA) and the SWPP.
First, possible explanatory variables that could account for variation in general activity were tested.
Second, variables that could account for variation in flight activity and flight height were tested, and third variables that could explain differences between the flight activities and flight heights were testeded.
Any variation in the two response variables (flight activity and flight height) could possibly be ex-plained by several different explanatory variables. In order to test which variables that influence on variation in the response variables, data were collected on distance to nearest turbine, distance to nearest active nest, number of individuals observed together, date, time of day, weather (precipita-tion, temperature and wind speed), and age of individuals. Data collected from 144 observation hours, during mid-March to the end of May 2008, were analyzed using ANOVA, Chi-square tests and multinomial logistic regression.
5.5.2 Results
The only explanatory variables that showed a statistically significant effect on the general activity were week, number and distance to nearest, active nest. The results showed a statistically signifi-cant difference in activity among the weeks. The general activity peaked in April (week 15 and 17) which is the first part of the breeding period for the WTE (Figure A)
.
Moreover, more activity was observed at distance 0-500 m than further away from the nearest active nest. There was more ac-tivity at 0-500 m than further away from the nest, which probably could be due to defending territo-ries and delivering food to the nest (Dementavicius & Treinys 2009).
Neither distance to nearest turbine, nor the locations seem to have any effect on the general activity.The results showed, furthermore, a statistically significant difference in age distribution between the two locations, with a higher percentage of adults in the CA and a higher percentage of subadults in the SWPP area (Figure B). There was also a statistically significant difference between the age categories in the different observation weeks with more adults than subadults represented throughout the whole study period.
Figure A. Observed flight activity (%) of WTE of total observation time pr.
observation week. N=number of two-hour observation periods.
Figure B. Age distribution (%) of WTE in the control area and the wind-power plant area (NCAadult=182, NCASubadult=79, NWPAadult=135,
N =106).
Regarding flight activity, the results from the multinomial regression analyses showed a statistically significant difference between moving flight and soaring in number of individuals observed to-gether, with more individuals observed together in moving flight than in soaring (Figure C). This could possibly be caused by pairs of individuals performing moving flight when moving back and forth between territories and feeding areas (Dementavicius & Treinys 2009).
Furthermore, there was a statistically significant difference between social behaviour and the two other activity categories in number of individuals observed together, with more individuals observed together in social behaviour than in moving flight and soaring. There was also a significant differ-ence between social behaviour and the other two activities related to age, with more adults than subadults in social behaviour than in moving flight and soaring. Since adults are reproductively ac-tive in contrast to subadults, and therefore more likely to participate in social behaviour in order to increase their fitness, this result is as expected.
Soaring was statistically significant different from the two other activity categories in relation to flight height, with soaring only occurring in – and above the rotor height, while moving flight and social behaviour occurred in all three flight-height categories. One reason for this is that the WTE can climb in altitude during sustained soaring and in this way gain high altitudes.
Figure C. Observed age distribution (%) of WTE in the different flight activity categories.
Furthermore, a statistically significant difference in age distribution between the two locations ap-peared, with a higher percentage of adults in the CA and a higher percentage of subadults in the SWWP area. This could indicate that the adults are either behavioural displaced away from the SWPP, or that there are a higher percentage of adults than subadults killed inside the SWPP area.
One possible reason for this difference could be connected to social behaviour. A much higher percentage of adults than subadults are involved with this type of behaviour, and this can possible impose a greater risk due to decreased awareness of the surroundings, or/and the fact that there
Because of low sample sizes due to low breeding densities, raptors are among the most difficult group of birds to demonstrate effects of disturbance, thus more long-term studies are needed. In order to test the assumption about social behaviour imposing greater risk to collision than the other flight activities, it is therefore necessary to conduct more long-term studies. More studies will also give larger sample sizes, which can give the opportunity to distinguish between more types of flight behaviour (e.g. more types of social behaviour).
Other studies (Henderson et al. 1996) indicate that moving flight could impose a greater risk than the flight activities because adults are flying more frequently under or between man-made struc-tures in order to reduce their journey time when rising young. This study show that moving flight is the activity that is most observed both inside the SWPP and the CA, and in both age categories.
One alternative explanation for the high amount of adults found killed could therefore be that mov-ing flight in relation to parental care could impose a higher risk for the adults than the subadults.
5.5.3 Conclusion
The overall conclusion is that white-tailed eagles on Smøla do not seem to have any behavioral responses to the wind-power plant construction. This may explain the number of killed individuals recorded in the wind-power plant. The behavioural differences between adults and subadults found, increase our understanding of the age difference among the individuals found killed inside the wind-power plant area. A higher number of adults than subadults found killed can be due to behavioural differences, like more time spent on social behaviour and flying back and forth be-tween nests and feeding areas. Furthermore, if such behaviour is increasing the risk of collisions for adult individuals, this can contribute to explain the higher number of recorded subadults inside the wind power plan area found in this study. This should be carefully considered when looking at the possible long-term effects of the wind-power plant on the white-tailed eagle population on Smøla. Assuming that the overall conclusion is correct, it clearly imposes limits to the possibilities for mitigating measures to decrease the white-tailed eagle collision hazard. The results underline the importance of conducting thorough pre-construction studies to identify wind-power plant siting with low densities of species vulnerable to collision. A more accurate prediction of high-hazard col-lision periods based on environmental variables like air temperature, wind and precipitation trigger-ing high flight activity in March-May, would make it possible to advise the wind-power plant opera-tor when to close down the wind-power plant during high-hazard conditions to reduce eagle mortal-ity.
6 Bird radar
Subproject responsibility: Roel May, Yngve Steinheim
Objectives: To develop radar as a tool for learning more about the effects of single wind turbines and wind-power plants on birds.
The study of behavioural responses of birds to man-made structures like the wind-power plant at Smøla, requires ways to observe and document the movement of birds in the area of interest. Hu-man visual observation remain an indispensable prerequisite and a key method, but a dedicated radar system is a powerful instrument which greatly extends the observation capability, both in terms of observation period, and the size of the surveillance area. E.g. the radar can be set to cover the relatively large area of wind-power plant, and operated 24 hours a day all year round at all types of weather conditions, which is a task impossible to achieve with the use of human ob-servers alone. At the same time the radar offers means for continuously recording of the radar pic-ture which provides documentation of the activities in the surveillance area. However, the use of radar for this purpose has site- and system-specific limitations that are important to be aware of when the data output is evaluated.
An important task in the project has been to start using radar as an instrument to monitor and re-cord bird behaviour in the vicinity of large wind turbines. To our knowledge, it is the first time ra-dar has been deployed for this kind of research in Norway. Important objectives of this work package have therefore been to experiment and develop the necessary methods, and gain gen-eral experience using radar as a research instrument. The following paragraphs give an overview over the activities performed on this subject.