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Bird collisions in wind turbines are a fact and will be on the rise with the increase in the number of wind farms around the world. Existing bird control tools like radar, HD camera or human visual detections have a number of drawbacks each and have not been able to prove their efficiency up to the standards of wildlife protection national organizations and supranational groups. Precision and range of thermal imaging combined with appropriate software provide for likely the most reliable bird and bat detection capability today. Detection recordings present a way of objectively analyzing the performance and accuracy, while custom-designed sounds invoking acoustic startle reflex deter virtually all avian species already at 400+ meters without allowing for habituation and minimizing the need for WTG stoppage, thus maximizing wind farms’ production efficiency.
Martin Georgiev, Bulgarian Academy of Science, Bulgaria,
Prof. Pavel Zehtindjiev, Bulgarian Academy of Science, Bulgaria,
Real-time bird detection and
risk control in wind farms
SUMMARY .............................................................................................................. 3
1. Introduction ....................................................................................................................... 4
2. Methods ............................................................................................................................ 5
2.1. Experimental design .......................................................................................................... 5
3. Results ............................................................................................................................... 8
3.1. Detection rate ................................................................................................................... 8
4. Discission ........................................................................................................................... 9
5. Conclusion ....................................................................................................................... 10
REFERENCES ......................................................................................................... 11
Real-time bird detection and risk control in wind farms I
Bird collisions in wind turbines are a fact and will be on the rise with the increase in the number of wind
farms around the world. Existing bird control tools like radar, HD camera or human visual detections have
a number of drawbacks each and have not been able to prove their efficiency up to the standards of
wildlife protection national organizations and supranational groups. Precision and range of thermal
imaging combined with appropriate software provide for likely the most reliable bird and bat detection
capability today. Detection recordings present a way of objectively analyzing the performance and
accuracy, while custom-designed sounds invoking acoustic startle reflex deter virtually all avian species
already at 400+ meters without allowing for habituation and minimizing the need for WTG stoppage, thus
maximizing wind farms’ production efficiency.
Do we value short-term advantages above the welfare of the Earth? Or will we think on longer
time scales, with concern for our children and our grandchildren, to understand and protect the
complex life-support systems of our planet? The Earth is a tiny and fragile world. It needs to be
Carl Sagan, Astronomer
Real-time bird detection and risk control in wind farms I
The constant expansion of wind energy requires fast and effective innovative solutions for bird detection
and collision risk mitigation. This is true for both currently operational and under-construction wind farms.
Different bird species are at different risks of collision, with large thermal soarers such as eagles (Aquila),
pelicans (Pelecanus) and vultures (Gypinae & Gypaetinae) being some of the most likely victims [1]. Often,
wind parks are located in regions of high biodiversity, with turbines being built in valleys acting as natural
wind tunnels, increasing turbines’ efficiency [2]. These wind tunnels, however, are also used by various
birds in the area, creating a funnel effect by connecting both metapopulations of locally breeding species
in addition to migratory ones [3]. Likewise, when turbines are built on mountain ridges wind generated
by orographic uplift is utilized by both turbines and soaring birds. One solution aimed at reducing mortality
risk from wind turbines is the installation of camera-based detection systems monitoring the surrounding
area for bird activity [4]. Following a bird detection, the system may use acoustic emittance to deter it
from the WTG zone or stop the turbine as a last-resort measure for preventing collision. As the results
below show, the system is applicable to detections of bats as well. This study assessed the efficiency of
one such system installed in the high-avian-biodiversity NATURA 2000-protected Kaliakra region of NE
Bulgaria (Black Sea coast). Currently, the main methods for bird registration, that meet the standards of
international wildlife organizations and the European Commission, are radars day cameras and human
visual detections [5].
We aimed to assess the precision of a novel tool: the thermal imaging camera, combined with appropriate
detection software:
a) We analyzed the camera’s reliability as bird and bat detection tool.
b) The system’s detection recordings were assessed as a way of objectively analyzing the
performance and accuracy of the detected objects.
c) The capacity of such a system to minimize the need for WTG stoppage, thus maximizing wind
farms’ production, efficiency was evaluated.
Real-time bird detection and risk control in wind farms I
We analyzed the detection rate efficiency of a thermal imaging camera-based bird collision avoidance
system installed on an operating wind turbine and capable of autonomous detection at 500+ meters with
precise azimuth. The experiment was carried out in NE Bulgaria during the months of August and October
2020, within the period of autumn bird migration (Figure 1, Figure 2).
Figure 1. The position within the Balkan peninsula where the study took place, with Volacom’s BCAS
highlighted in a yellow pin.
Figure 2. The study site, with Volacom’s BCAS highlighted in a yellow pin. The Black Sea coast is visible
alongside multiple rows of wind turbine generators.
Real-time bird detection and risk control in wind farms I
The system was equipped with a custom-built detection software providing live picture and video logs of
each recorded detection. Human observations were conducted every day by ornithologists with visual
detections recorded in a log book for comparison purposes after. After the end of the experiment the
video recordings were analyzed individually to filter bird and bat detections from others. The results were
then compared to ornithologists’ log books records (Figure 3).
Figure 3. Volacom’s BCAS, installed in the Kaliakra region, NE Bulgaria.
The thermal imaging camera had the following technical specifications.
Vertical field of view: 26 °
Horizontal field of view per frame: 32 °
Total horizontal field of view: 192 °
Detection ranges:
60 cm wingspan: up to 350 m
100 cm wingspan: up to 600 m
150 cm wingspan: up to 1050 m
The experiment was carried out at an operating wind turbine park in NE Bulgaria during the months of
August and October 2020, within the period of autumn bird migration. The system was equipped with a
custom-built detection software providing live picture and video logs of each recorded detection. After
the end of the experiment the video recordings were analyzed individually in order to assess the validity
of each detection.
Real-time bird detection and risk control in wind farms I
Each detection, recorded by the bird collision avoidance system (BCAS), was stored on a hard drive and
was available for review as shown (Figure 4). The exact time and date of the detections are visible.
Multiple objects were recorded as such.
Figure 4. Bird detections as seen by the Volacom thermal software user interface.
Real-time bird detection and risk control in wind farms I
All data records were analyzed individually by two ornithologists to arrive at accurate and objective
results. True positive detections by the thermal camera-based system and software for August 2020 were
805 birds and bats out of 965 total detections (83.1% accuracy) (Figure 6). False positive detections were
mainly insects (7%), turbine blades (3%), picture distortion by vibrations (2%) (Figure 5). True positives for
October 2020 were 780 birds out of 850 detections (91.8% accuracy). Insects were comparatively less due
to colder weather (4.7%). Correlation of system detections vs actual human detections was strong
although limitations of human eyesight made it difficult to quantify the results. Specific sound emittance
had persistent efficiency in deterring birds away from WTGs.
Figure 5. Structure of all detections for months August and October 2020.
Overall, the rates of true positive detections were 83.1% and 91.8% respectively (Figure 6).
Figure 6. Percentages of true and false detections for months August and October 2020.
Real-time bird detection and risk control in wind farms I
The difference between the true positive detection rates in August (83.1) and October (91.8) occurred
due to the calibration of the system (Figure 6). Calibration involves activities such as masking (marking
moving objects like WTGs and trees), positioning the horizontal and vertical fields of view of the camera
(HFOV and VFOV) to make better use of the camera’s capabilities, taking into consideration the local
topography [6]. Throughout the literature, multiple assessments of various bird detection techniques and
technologies have been made [7] [8]. Currently, the two most popular methods are radar and visual
observations. Thermal vision is comparatively new technology, and its use in bird monitoring and
detection is completely novel.
Each method has its pros and cons and thy are important to consider when assessing discussing the “best”
one. Radar generally is able to detect around two-to-three times the number of birds as visual
observations and is able to detect birds at night, which is critical since high-risk bird species like waders,
ducks and geese are both nocturnal and diurnal migrants [9]. Furthermore, cuckoos, flycatchers, warblers,
vireos, thrushes, orioles and sparrows migrate exclusively at night, making nocturnal detection a
requirement for bird strike mitigation technologies at wind farms [10]. The detection distances of radar
are another plus, being able to detect geese at ~ 2km, provided favourable weather conditions. At night,
the only option for human observations are moon-watching surveys and sonogram analysis, which are
both highly specialized and require highly trained experts, whose labour is highly expensive, in addition
to working night shifts [11]. Furthermore, radar often produces a large amount of “noise”, triggering false
detections. Last but not least it is important to take into consideration the price of radar technology, which
often outweighs both human labour and thermal-based cameras [12]. Day cameras are often overlooked
since their detection distance rarely exceeds 300 meters and they are completely inefficient during the
night or bad weather.
Thermal vision tends to combine the benefits of pros of radar (detection distance, nocturnal efficiency)
and day cameras (video records) while bypassing the limitations. Taking into consideration that thermal
rarely manages to detect objects are over 1.5 km (depending on size of course) the benefit from a video
log which can then be analyzed and stored for later viewing is notable. For a wind park, a combination of
all available technologies and methods would be the best solution for bird risk mitigation, however in
reality limited budgets do not tend to allow of the best possible solution.
Real-time bird detection and risk control in wind farms I
Globally, bird collisions into with man-made structures cost the lives of millions of birds annually. In the
past this added mortality has largely been considered insignificant on population level but research in
recent years shows selected species being particularly vulnerable, especially in protected wildlife areas.
The BCAS system successfully generated 1582 true positive detections. Considering the camera’s field of
view, we consider this to be a correct estimate of bird activity in the area. The analysis of all 1815
detections revealed that the system had a success rate (true positive detections) of 83.1% for August and
91.8% for October. In our opinion the high sensitivity of the thermal sensor, combined with the high
success rate of the detection algorithm: 87.5% (two-month average) meets the requirements for use as a
bird control tool at wind farms. High-precision weather conditions-independent imaging devices like
thermal cameras with sophisticated detection and automation software built-in provide the necessary
tool for detecting likely every bird in the area. Specially developed acoustic deterrence signals can mitigate
the collision risk down to single-digit percentages without causing physical harm or stress to avian species.
Operation of last-resort WTG stop control modules can be minimized and automated.
Real-time bird detection and risk control in wind farms I
[1]. Bose, A., Dürr, T., Klenke, R. A., & Henle, K. (2018). Collision sensitive niche profile of the worst affected
bird-groups at wind turbine structures in the Federal State of Brandenburg, Germany. Scientific
reports, 8, 1-13.
[2]. Kuvlesky Jr, W. P., Brennan, L. A., Morrison, M. L., Boydston, K. K., Ballard, B. M., & Bryant, F. C. (2007).
Wind energy development and wildlife conservation: challenges and opportunities. The Journal of Wildlife
Management, 71, 2487-2498.
[3]. Drewitt, A. L., & Langston, R. H. (2008). Collision effects of wind-power generators and other obstacles
on birds. Annals of the New York Academy of Sciences, 1134, 233-266.
[4]. Smallwood, K.S., 2007. Estimating wind turbine-caused bird mortality. The Journal of Wildlife
Management, 71,2781-2791.
[5]. European Comission (2020) Guidance document on wind energy developments and EU nature
legislation. Available at (Accessed 05.10.2021).
[6]. Premalatha, M., Abbasi, T., & Abbasi, S. A. (2014). Wind energy: Increasing deployment, rising
environmental concerns. Renewable and Sustainable Energy Reviews, 31, 270-288.
[7]. Ronconi, R.A. and CASSADY ST. CLAIR, C.O.L.L.E.E.N., (2006). Efficacy of a radar-activated on-demand
system for deterring waterfowl from oil sands tailings ponds. Journal of Applied Ecology, 43, 111-119.
[8]. McCafferty, D. J. (2013). Applications of thermal imaging in avian science. Ibis, 155, 4-15.
[9]. Zimmerling, J., Pomeroy, A., d'Entremont, M., & Francis, C. (2013). Canadian estimate of bird mortality
due to collisions and direct habitat loss associated with wind turbine developments. Avian Conservation
and Ecology, 8.
[10]. Perold, V., Ralston-Paton, S., & Ryan, P. (2020). On a collision course? The large diversity of birds
killed by wind turbines in South Africa. Ostrich, 91, 228-239.
[11]. Zehtindjiev, P., & Liechti, F. (2003). A quantitative estimate of the spatial and temporal distribution
of nocturnal bird migration in south-eastern Europe-a coordinated moon-watching study. Avian
Science, 3, 37-45.
[12]. Zalakevicius, M., (2000). Global climate change, bird migration and bird strike problems. In 25th IBSC
meeting, Amsterdam (509-525).
ResearchGate has not been able to resolve any citations for this publication.
Full-text available
In SE Europe, the spatial and temporal distribution of nocturnal migration is hardly known. With the moon-watching technique the passage of 5603 nocturnal migrants was recorded during 419 observation hours at 28 sites spread over Bulgaria, SE Romania and northern Greece. Mean migratory traffic rate was 1400 in autumn and 900 in spring. Migration intensity was similar along both E-W and N-S gradients. Flight directions were virtually opposite between seasons, with a slight shift from SSW to S during the autumn and from NNE to N during the spring. These results indicate that a high proportion of nocturnal migrants along the eastern flyway do not circumvent the eastern Mediterranean Sea, but cross the sea on a broad front. This is in contrast to the migration along the western flyway, where a majority of mainly long distance migrants take southwesterly directions towards the Iberian Peninsula and thus avoid a long sea crossing. Key-words: Nocturnal migration, moon-watching, migratory intensity, flight direction, SE-Europe.
Full-text available
Biodiversity-related impacts at wind energy facilities have increasingly become a cause of conservation concern, central issue being the collision of birds. Utilizing spatial information of their carcass detections at wind turbines (WTs), we quantified the detections in relation to the metric distances of the respective turbines to different land-use types. We used ecological niche factor analysis (ENFA) to identify combinations of land-use distances with respect to the spatial allocation of WTs that led to higher proportions of collisions among the worst affected bird-groups: Buntings, Crows, Larks, Pigeons and Raptors. We also assessed their respective similarities to the collision phenomenon by checking for overlaps amongst their distance combinations. Crows and Larks showed the narrowest “collision sensitive niche”; a part of ecological niche under higher risk of collisions with turbines, followed by that of Buntings and Pigeons. Raptors had the broadest niche showing significant overlaps with the collision sensitive niches of the other groups. This can probably be attributed to their larger home range combined with their hunting affinities to open landscapes. Identification of collision sensitive niches could be a powerful tool for landscape planning; helping avoid regions with higher risks of collisions for turbine allocations and thus protecting sensitive bird populations.
Full-text available
We estimated impacts on birds from the development and operation of wind turbines in Canada considering both mortality due to collisions and loss of nesting habitat. We estimated collision mortality using data from carcass searches for 43 wind farms, incorporating correction factors for scavenger removal, searcher efficiency, and carcasses that fell beyond the area searched. On average, 8.2 +/- 1.4 birds (95% C.I.) were killed per turbine per year at these sites, although the numbers at individual wind farms varied from 0 - 26.9 birds per turbine per year. Based on 2955 installed turbines (the number installed in Canada by December 2011), an estimated 23,300 birds (95% C.I. 20,000 - 28,300) would be killed from collisions with turbines each year. We estimated direct habitat loss based on data from 32 wind farms in Canada. On average, total habitat loss per turbine was 1.23 ha, which corresponds to an estimated total habitat loss due to wind farms nationwide of 3635 ha. Based on published estimates of nest density, this could represent habitat for similar to 5700 nests of all species. Assuming nearby habitats are saturated, and 2 adults displaced per nest site, effects of direct habitat loss are less than that of direct mortality. Installed wind capacity is growing rapidly, and is predicted to increase more than 10-fold over the next 10-15 years, which could lead to direct mortality of approximately 233,000 birds / year, and displacement of 57,000 pairs. Despite concerns about the impacts of biased correction factors on the accuracy of mortality estimates, these values are likely much lower than those from collisions with some other anthropogenic sources such as windows, vehicles, or towers, or habitat loss due to many other forms of development. Species composition data suggest that < 0.2% of the population of any species is currently affected by mortality or displacement from wind turbine development. Therefore, population level impacts are unlikely, provided that highly sensitive or rare habitats, as well as concentration areas for species at risk, are avoided.
Full-text available
There is extensive literature on avian mortality due to collision with man-made structures, including wind turbines, communication masts, tall buildings and windows, power lines, and fences. Many studies describe the consequences of bird-strike rather than address the causes, and there is little data based on long-term, standardized, and systematic assessments. Despite these limitations, it is apparent that bird-strike is a significant cause of mortality. It is therefore important to understand the effects of this mortality on bird populations. The factors which determine avian collision risk are described, including location, structural attributes, such as height and the use of lighting, weather conditions, and bird morphology and behavior. The results of incidental and more systematic observations of bird-strike due to a range of structures are presented and the implications of collision mortality for bird populations, particularly those of scarce and threatened species susceptible to collisions, are discussed. Existing measures for reducing collision mortality are described, both generally and specifically for each type of structure. It is concluded that, in some circumstances, collision mortality can adversely affect bird populations, and that greater effort is needed to derive accurate estimates of mortality levels locally, regionally, and nationally to better assess impacts on avian populations. Priority areas for future work are suggested, including further development of remote technology to monitor collisions, research into the causes of bird-strike, and the design of new, effective mitigation measures.
Wind energy is a clean, renewable alternative to fossil fuel-derived energy sources, but many birds are at risk from collisions with wind turbines. We summarise the diversity of birds killed by turbine collisions at 20 wind energy facilities (WEFs) across southwest South Africa. Monitoring from 2014 to 2018 recovered 848 bird carcasses across all WEFs, at a crude rate of 1.0 ± 0.6 birds turbine⁻¹ y⁻¹ at 16 WEFs with at least 12 months of postconstruction monitoring. However, mortality estimates adjusted for detection and scavenger bias were appreciably higher: 4.6 ± 2.9 birds turbine⁻¹ y⁻¹ or 2.0 ± 1.3 birds MW⁻¹ y⁻¹ (n = 14 WEFs with site-specific bias correction factors), which is slightly lower than mean rates reported in the northern hemisphere, but still well within range. A striking result was the high diversity of birds killed: 130 species from 46 families, totalling 30% of bird species recorded at and around WEFs, including some species not recorded by specialist surveys at WEF sites (e.g. flufftails Sarothruridae). Species accumulation models suggest that 184 (±22) species will be killed at these facilities, some 42% of species found in the vicinity of WEFs. This is despite the smaller number of migrants in the study region, compared with the north temperate zone. Diurnal raptors were killed most often (36% of carcasses, 23 species) followed by passerines (30%, 49 species), waterbirds (11%, 24 species), swifts (9%, six species), large terrestrial birds (5%, 10 species), pigeons (4%, six species) and other near passerines (1%, seven species). Species of conservation concern killed include endangered Cape Vultures Gyps coprotheres and Black Harriers Circus maurus, both of which are endemic to southern Africa. Every effort must be made to site wind energy facilities away from important areas for birds, particularly raptors.
Of all the renewable energy sources (RESs)―except direct solar heat and light―wind energy is believed to have the least adverse environmental impacts. It is also one of the RES which has become economically affordable much before several other RESs have. As a result, next to biomass (and excluding large hydro), wind energy is the RES being most extensively tapped by the world at present. Despite carrying the drawback of intermittency, wind energy has found favor due to its perceived twin virtues of relatively lesser production cost and environment-friendliness. But with increasing use of turbines for harnessing wind energy, the adverse environmental impacts of this RES are increasingly coming to light. The present paper summarizes the current understanding of these impacts and assesses the challenges they are posing. One among the major hurdles has been the NYMBI (not in my backyard) syndrome due to which there is increasing emphasis on installing windfarms several kilometers offshore. But such moves have serious implications for marine life which is already under great stress due to impacts of overfishing, marine pollution, global warming, ozone hole and ocean acidification. Evidence is also emerging that the adverse impacts of wind power plants on wildlife, especially birds and bats, are likely to be much greater than is reflected in the hitherto reported figures of individuals killed per turbine. Likewise recent findings on the impact of noise and flicker generated by the wind turbines indicate that these can have traumatic impacts on individuals who have certain predispositions. But the greatest of emerging concerns is the likely impact of large wind farms on the weather, and possibly the climate. The prospects of wind energy are discussed in the backdrop of these and other rising environmental concerns.
Thermal imaging, or infrared thermography, has been used in avian science since the 1960s. More than 30 species of birds, ranging in size from passerines to ratites, have been studied using this technology. The main strength of this technique is that it is a non‐invasive and non‐contact method of measuring surface temperature. Its limitations and measurement errors are well understood and suitable protocols have been developed for a variety of experimental settings. Thermal imaging has been used most successfully for research on the thermal physiology of captive species, including poultry. In comparison with work on mammals, thermal imaging has been less used for population counts, other than for some large bird species. However, more recently it has shown greater success for detection of flight paths and migration. The increasing availability and reduced cost of thermal imaging systems is likely to lead to further application of this technology in studies of avian welfare, disease monitoring, energetics, behaviour and population monitoring.
Wind energy development represents significant challenges and opportunities in contemporary wildlife management. Such challenges include the large size and extensive placement of turbines that may represent potential hazards to birds and bats. However, the associated infrastructure required to support an array of turbines—such as roads and transmission lines—represents an even larger potential threat to wildlife than the turbines themselves because such infrastructure can result in extensive habitat fragmentation and can provide avenues for invasion by exotic species. There are numerous conceptual research opportunities that pertain to issues such as identifying the best and worst placement of sites for turbines that will minimize impacts on birds and bats. Unfortunately, to date very little research of this type has appeared in the peer-reviewed scientific literature; much of it exists in the form of unpublished reports and other forms of gray literature. In this paper, we summarize what is known about the potential impacts of wind farms on wildlife and identify a 3-part hierarchical approach to use the scientific method to assess these impacts. The Lower Gulf Coast (LGC) of Texas, USA, is a region currently identified as having a potentially negative impact on migratory birds and bats, with respect to wind farm development. This area is also a region of vast importance to wildlife from the standpoint of native diversity, nature tourism, and opportunities for recreational hunting. We thus use some of the emergent issues related to wind farm development in the LGC—such as siting turbines on cropland sites as opposed to on native rangelands—to illustrate the kinds of challenges and opportunities that wildlife managers must face as we balance our demand for sustainable energy with the need to conserve and sustain bird migration routes and corridors, native vertebrates, and the habitats that support them. (JOURNAL OF WILDLIFE MANAGEMENT 71(8):2487-2498; 2007)
ABSTRACT  Mortality estimates are needed of birds and bats killed by wind turbines because wind power generation is rapidly expanding worldwide. A mortality estimate is based on the number of fatalities assumed caused by wind turbines and found during periodic searches, plus the estimated number not found. The 2 most commonly used estimators adjust mortality estimates by rates of searcher detection and scavenger removal of carcasses. However, searcher detection trials can be biased by the species used in the trial, the number volitionally placed for a given fatality search, and the disposition of the carcass on the ground. Scavenger removal trials can be biased by the metric representing removal rate, the number of carcasses placed at once, the duration of the trial, species used, whether carcasses were frozen, whether carcasses included injuries consistent with wind turbine collisions, season, distance from the wind turbines, and general location. I summarized searcher detection rates among reported trials, and I developed models to predict the proportion of carcasses remaining since the last fatality search. The summaries I present can be used to adjust previous and future estimates of mortality to improve comparability. I also identify research directions to better understand these and other adjustments needed to compare mortality estimates among wind farms.
Summary • Oil sands mining is one of several industrial activities that produces effluent that is dangerous to waterfowl. Such industries require effective systems to deter birds, but current deterrents are not always successful, presumably because wildlife ignore or habituate to them. • We tested a new radar-activated on-demand system of deterrence in the oil sands region of Alberta, Canada, by comparing the proportion of birds that landed on a tailings pond while it was activated with the proportion that landed during two other treatments: a continuous, randomly activated, deterrent system, and control periods with no deterrents. We also assessed the efficacy of different stimuli types within the on-demand system. • Across several bird guilds, only the on-demand deterrent system significantly reduced the probability of birds landing in comparison with the control treatment. In addition to treatment effects, birds were more likely to land earlier in the spring and when they flew at lower altitudes, and shorebirds were more likely to land than ducks, geese and gulls. • The comparison of stimuli revealed that cannons elicited significantly more response by birds in flight than mechanized peregrine falcon effigies with speakers broadcasting peregrine sounds. • Synthesis and applications. Our results promote the use of on-demand systems for waterfowl deterrence at tailings ponds and recommend cannons over effigies as stimuli. We suggest that oil sands deterrence efforts should (i) be operational in the early spring, when tailings ponds appear to be most attractive to migrating waterfowl, (ii) target low-flying waterfowl and shorebirds and (iii) be effective during both day and night. These results and recommendations have potential application for problems of bird deterrence at several other industrial sites. Journal of Applied Ecology (2005) doi: 10.1111/j.1365-2664.2005.01121.x