Journal of Threatened Taxa |
www.threatenedtaxa.org | 26 March 2020 | 12(4): 15414–15425
ISSN 0974-7907 (Online) | ISSN 0974-7893
(Print)
doi: https://doi.org/10.11609/jott.5165.12.4.15414-15425
#5165 | Received 13 June 2019 | Final
received 14 February 2020 | Finally accepted 06 March 2020
Hazards of wind turbines on
avifauna - a preliminary appraisal within the Indian context
Himika Deb 1, Tanmay Sanyal 2, Anilava Kaviraj 3 & Subrata Saha
4
1 Lalgola S.M. Girls High School (H.S.), Lalgola,
Murshidabad, West Bengal 742148, India.
2 Krishnagar
Govt. College, Krishnagar, Nadia, West Bengal 741101, India.
3 Department of
Zoology, University of Kalyani, Kalyani, West Bengal 741235, India.
4 Department of
Materials and Production, Aalborg University, DK 9220, Denmark .
1 himika.msc@gmail.com,
2 tanmaysanyal@gmail.com, 3 akaviraj@gmail.com, 4 subrata.scm@gmail.com
(corresponding author)
Abstract: Wind farms are substantial sources of renewable energy
in India; however, their spread across the country potentially present new
hazards to local and migratory birds.
Thais study explored the risk of electrocution and collision of birds
with wind turbines close to eco-sensitive zones in India, including Bakkhali, a UNESCO World Heritage site. Geographic information system and remote
sensing technology were used. The
results indicate vulnerability of local bird species such as barn owl, Indian Scops Owl, Blue Rock Pigeon, Asian Koel,
House Crow, Common Sandpiper, Common Snipe, Ruddy Shelduck, Lesser Whistling
Duck, Cattle Egret, Great Egret, and Pond Herons, as well as migratory species
such as Bar-headed Goose, Red-crested Pochard, and American Black Duck. Modification of wind turbine design and
location were considered determinant factors to reduce risk of bird collisions.
Keywords: Biodiversity, birds, geographic information system, remote
sensing, transect chart.
Editor: Mário G.
Santiago dos Santos, Universidade de Trás-os-Montes e Alto Douro, Vila
Real, Portugal. Date of publication: 26 March 2020 (online & print)
Citation: Deb,
Himika, T. Sanyal, A. Kaviraj & S. Saha (2020). Hazards of
wind turbines on avifauna - a preliminary appraisal within the Indian context.
Journal
of Threatened Taxa 12(4): 15414–15425. https://doi.org/10.11609/jott.5165.12.4.15414-15425
Copyright: © Deb et al 2020. Creative Commons Attribution 4.0 International
License. JoTT
allows unrestricted use, reproduction, and distribution of this article in any
medium by providing adequate credit to the author(s) and the source of
publication.
Funding: This research received no external funding.
Competing interests: The authors declare no competing interests.
Author details: Himika Deb received the BSc degree in Geography from the
University of Kalyani, India, and the MSc degree in Geography from C.S.J.M.
University, India. She is currently an Assistant Teacher with the Lalgola S.M. Girls’ High School. Her research interests
include fluvial and soil erosion risk assessment, GIS, environmental
degradation. Tanmay Sanyal did his PhD in
Zoology under the supervision of Prof. Anilava Kaviraj. He is now Assistant Professor of Zoology in the
Krishnagar Government College. He has six research publications in peer
reviewed journals to his credit. Anilava Kaviraj PhD, is a Professor (retired) in the
Department of Zoology, University of
Kalyani, India. He served this
department for 33 years as teacher and researcher. He supervised 23 students for
PhD degree and published more than 108 research papers in peer reviewed
international journals. Subrata Saha received PhD degree in mathematics from the
University of Kalyani. He was a post-doctoral researcher in the Seoul National
University, South Korea, and served as faculty in the Institute of Engineering
and Management, Kolkata. Currently he is a post-doctoral researcher in the
Aalborg University, Denmark. He published 60 articles in internationally
reputed journals.
Author contribution: TS collected the data and has full access to all data
used in this study. HD and SS are responsible for data analyses. All
authors equally contributed in manuscript writing. AK and SS provided critical
inputs on results interpretation, modification, and approved it for submission.
Acknowledgements: This study benefitted from comments on earlier
versions by anonymous reviewers. The
authors sincerely thank Mr Shekhar Mandal for his
help during the study.
Introduction
Wind energy is touted as an eco-friendly and sustainable
alternative to fossil fuel (Nazir et al. 2019).
As fossil fuel sources are more and more limited, increase in wind
energy production has been growing over the last decade (Morinha
et al. 2014). The global wind energy
council (GWEC) has predicted a 17-fold increase in generation of wind energy by
2030 (Lu et al. 2009). Such expansion in
wind energy production poses serious threats to flying vertebrates (Peron et
al. 2013; Singh et al. 2015). Birds and
bats often collide with rotor blades of wind turbines (WTs) and associated
structures such as meteorological towers and power lines (Barclay et al. 2007; Zimmerling et al. 2013; Korner-Nievergelt
et al. 2013; Ferreira et al. 2015; Beston et al.
2016; Anoop et al. 2018). Mortality of
birds and bats due to such collisions has been frequently reported from the
USA, Canada (Johnson 2005; Arnett et al 2008; Loss et al. 2013, Smales et al. 2013; Erickson et al. 2014; Marques et al.
2014), Europe (Bach & Rahmel 2004; Dürr & Bach 2004; Welling et al. 2018), Australia (Hull
et al. 2013), New Zealand (Powlesland 2009), India (Pande et al. 2013; Kumar et al. 2019), and many other
countries. WTs were initially installed
in coastal areas (Larsen & Guillemette 2007; Larsen & Guillemette
2007), then subsequently extended to inland agricultural areas (Rydell et al.
2010) and ecologically sensitive areas such as hills and mountains (Aschwanden et al. 2018).
Several factors have been identified as contributing
to collision of birds and bats with WTs.
These include morphology of birds, sensorial perception, phonology, behavior, habit richness or abundance, landscape, flight
path, food availability, weather, turbine type, lightening, among others
(Marques et al. 2014). Hull et al.
(2013) identified key morphological, behavioural, and ecological features that
make birds prone to collision. These
include the ability of birds to detect and avoid moving turbine blades, mode of
flight and foraging strategies. Pescador et al. (2019) observed that abundance of potential
prey makes predator birds prone to collision with WTs. In an offshore wind park in Denmark, Larsen
& Guillemette (2007) observed visibility conditions as a major factor for
collision of birds with WTs. Plonczkier & Simms (2012) also pointed out visibility
conditions as the major factor for collision and associated mortality of birds
at offshore wind farms in England. As a
result, nocturnal migrants face a high risk of collision with WTs (Aschwanden et al. 2018).
De Lucas et al. (2012) indicated a link between wind conditions,
topography, and flight behaviour as factors associated with mortality of
griffon vultures within and between wind farms.
In Hokkaido, Japan, Kitano et al. (2013) observed highest fatality of
birds at the turbines on a costal cliff where the rotor zones of wind turbines
overlapped the frequent flight paths of large birds. Pande et al. (2013)
used collision index (CI) to measure avian seasonal collision rate due to WT
and noted that maximum collision risk with raptors occurred predominantly
during monsoon periods. In Germany,
Lehnert et al. (2014) observed that both local and migratory bats were
vulnerable to WTs, and fatalities varied with age and sex. Studying Alauda
arvensis in northern Portugal, Morinha et
al. (2014) found a sex biased mortality.
Mortality of birds and bats was also found to vary with turbine hub
height (Everaert et al. 2006; Rothery
et al. 2009). Also, the modern wind
turbine towers are much taller than in the past, putting more risks to birds
and bats (Welling et al. 2018).
In recent articles, wetland birds have been reported
as most susceptible to collision with WT in Turkey and Netherlands (Graff et
al. 2016; Arikan & Turan
2017). Similar susceptibility of
collision of wetland birds with WT near freshwater bodies have been found in
Taiwan (Lin 2017). The Black Shag Phalacrocorax carbo and Cattle Egret Bubulcus ibis are the only species of water
birds of New Zealand that often face fatal injury after collision with WT (Powlesland 2009).
There is possibility that other species of water birds may also be
affected. The IUCN Red List reveals a
steady and continuing deterioration; according to the World’s birds report
2018, one in eight bird species are threatened with extinction
(www.birdlife.org). Therefore, it is necessary
to prevent fatalities of birds from WTs.
Risk of collision of birds from WTs have not been
explored in India aside from sporadic attempts in Gujarat (Kumar et al. 2019)
and the Western Ghats (Pande et al. 2013). India is the fourth largest producer of wind
energy, with an installed capacity of 32.85GW at the end of 2017. Tamil Nadu, Maharashtra, Gujarat, Rajasthan,
Karnataka, and Andhra Pradesh are the leading states in the generation of wind
energy in India (Chaurasiya et al. 2019). India has four biodiversity hotspots, namely:
(1) the Western Ghats, (2) the eastern Himalaya, (3) the Indo-Burma region, and
(4) the Sunda Islands. India is also the home to 12.6% of all avian
species found in the world. Huge amount
of anthropogenic activities including collision of avifauna with WT, however,
have put many birds in India at a high risk of extinction (Chitale
et al. 2014). This has forced the
necessity to explore risk of collision of avifauna from WT in India. The main objective of this study was to
investigate the collision risk of avian species, and loss of habitat due to
allocation of WT in India.
Methods
Study Area
This study considered three geographically distinct
locations, namely: (i) Gujarat and its adjoining
areas (68.245–75.0610E and 23.770–17.0930N) in the
western part of India; (ii) Tamil Nadu and its adjoining areas (76.018–81.9670E
and 9.358–17.4610N) in the southern part of India, and (iii) Bakkhali, South 24-Parganas, West Bengal (88.231–88.2880E
and 21.511–21.5630N) located in the eastern part of India (location
3). For the first two locations we used secondary data however, we used GIS
technique to identify nearby ecologically sensitive areas in these two
locations and attempted to explain the collision of birds in these areas. In the third location (Bakkhali),
which is situated 125km south of Kolkata in Sunderban
Biosphere Reserve (Figure 1), extensive fieldwork was conducted to collect
primary data on death and injuries of birds due to collision with WT of Frezerganj Wind Farm, near Bakkhali
during the period February 2017 to January 2018. We interacted with local people living around
WTs through printed questionnaires, and collected carcasses of 15 bird species
from this location. These species included
Barn Owl, Indian Scops Owl, Blue Rock Pigeon, Asian Koel, House Crow, Common Sandpiper, Common Snipe, Ruddy
Shelduck, Lesser Whistling Duck, Cattle Egret, Great Egret, Indian Pond Heron,
Bar-headed Goose, Red-crested Pochard, American Black Duck from this
location. WTs present in Bakkhali have been presented in Figure 2.
Remote Sensing and Geographical Information System
Techniques
Remote sensing (RS) and geographic information system
(GIS) technology were used to identify whether actual positions of WTs caused
any obstacle to bird’s movement. With
the help of RS and GIS technique, it is easy to prepare the map without coming
into physical contact with the object under study (Effat
2014). Satellite image of the Indian
subcontinent was downloaded from Google Earth Pro followed by georeferencing by
GIS (TNTmips) Software. WT locations were identified and digitized on
raster map (Wald and Ranchin 1995). GIS map was drawn to establish relationship
between WT areas and the bird species of various ecologically sensitive areas
such as national park, biosphere reserve, and biodiversity hotspot region. Seasonal wind direction was taken into
consideration to assessing the bird migration direction because wind direction
sometime influenced their path (Kemp et al. 2010). The map of these ecologically sensitive areas
and location of WTs were downloaded and digitized on raster maps of the Indian
subcontinent to generate a complete vector map of intersection between bird
habitat area and location of WTs.
B-spline curve (Origin Lab), the natural way to represent a continuous
curve from a set of discrete points, was used to represent collision data
collected from the Bakkhali (Eilers
& Marx 1996; Cao & Wang 2008).
Transect Chart
Transect charts were used to assess collision of bird
with WT (Xie et al. 2015; Roeleke
et al. 2016; Sivakumar & Ghosh 2017; Tucker et al. 2018). A transect represents a line
following a route along which observations are considered. Transect chart is a geographic tool which
demonstrates the changes and interdependency of human characteristics on
physical object from one place to another (Jcngsma et
al. 1989). In this study, we used the
line transect method to illustrate a particular gradient or linear pattern
along which birds’ location and WTs are intersected based on the latitude and
longitude of that location. This tool
can potentially illustrate collision risk of birds with WTs location (Saha et al. 2019).
At first, a GIS map was made for three study areas by incorporating WTs
location in that area (TNTmips). Then, latitude, longitude, and altitude were
measured of those areas. Altitude was
identified from Google Earth Pro. Then
horizontal transect lines were drawn between those latitudes and longitudes. From the GIS map location of WTs, national
park, biosphere reserve, biodiversity hotspot, and habitat of 15 bird species
were transferred to the edge of the screen from one end of transect line to the
other. The x-axis represented horizontal
distance covered by transects. In this
way, we tried to demonstrate whether biosphere reserve, biodiversity hotspots
or any national parks are in the area of influence of installed WTs.
Results
Figure 3 represents GIS and RS mapping of seasonal
wind movement, WTs locations and key biodiversity areas. It demonstrates that WTs are installed near
national parks, biosphere reserves & biodiversity hotspots, and thus can
potentially interrupt the natural movement of birds. This figure also identifies the direction of
monsoon winds in summer and winter, which fall along the path of movements of
some local and migratory birds.
Distributions of 15 bird species found in location-3 have been presented
in Figure 4. Figures 5a–c present data
of collision of birds with WT generated from location 3. These figures reflect seasonal variation in
collision. The dead and wounded birds
included Barn Owl, Indian Scops Owl, Rock Pigeon, Asian Koel,
House Crow, Common Sandpiper, Common Snipe, Great Egret, Ruddy Shelduck, Lesser
Whistling Duck, Cattle Egret, Indian Pond Heron, and migratory bird species
such as Bar-headed Goose, Red-crested Pochard, and American Black Duck (Table
1). The transect charts were used to
visualize the location of WTs along a transect line to inspect whether their
loci intersected birds’ movement directly in Gujarat (Figure 6a), Tamil Nadu
(Figure 6b), and Bakkhali (Figure 6c).
Discussion
The IUCN Red List status of the birds sampled from
location-3 (Bakkhali) is listed in Table 1. All these birds belong to IUCN category
‘Least Concern’. Bakkhali
is also home to Spoon-billed Sandpiper, a ‘Critically Endangered’ species. Further observations are required to assess
if this bird species is vulnerable to WTs installed in this area.
The casualty of birds found in location-3 may be
attributed to seasonal variation in concentration of migratory birds as well as
seasonal variation in food habits of local birds. The probability of collision of birds with
WT, however, cannot be concluded from the raster map alone. This study reveals maximum mortality of
Cattle Egret, Indian Pond Heron, and Great Egret (Ardeidae)
in location-3 followed by Common Sandpiper,
Common Snipe (Scolopacidae), Bar-headed Goose,
Red-crested Pochard, Lesser Whistling Duck, American Black Duck, Ruddy Shelduck
(Anatidae), Rock Pigeon (Columbidae),
and House Crow (Corvidae). Barn Owl, Asian Koel,
and Indian Scops Owl were the least affected species
of birds. Maximum number of species killed or wounded by WT belonged to the
family Anatidae with five species, followed by the
family Ardeidae with three species, Scolopacidae with two species, and Tytonodae,
Columbidae, Cuculidae, Strigidae & Corvidae with one
species each (Table 1, Figure 5a,b).
The birds belonging to the families Ardeidae and Anatidae are mostly
water birds (such as Indian Pond Heron) and are abundant in this location. Wetlands of southern part of West Bengal are
the preferred habitats for many birds, including the Bar-headed Goose and
Red-crested Pochard that migrate annually from trans Himalayan region during
December–January (Majumder et al. 2007).
There are sporadic evidences from Turkey and Netherlands also that
wetland birds are susceptible to collision with WTs (Krigsveld
et al. 2009; Arikan et al. 2017), probably because of
affinity of the migratory birds to wetlands.
Habitat association (Thaxter et al. 2017) and
abundance appeared to be key factors behind collision of the birds of the
family Ardeidae and Anatidae
in Bakkhali.
Kumar et al. (2019) observed several bird species
around Kutch District (part of Location-1, Gujarat) between October 2011 and
July 2014, and found carcasses of 47 birds belonging to 11 species. Since a few national parks are situated in
this area (Figure 3), many more species are at risk from the WTs. Pande et al. (2013)
observed 89 species of birds, from July 2008 to June 2010 in Bhambarwadi Wind Farm Plateau in northern Western Ghats,
out of which 27 birds were under risk by rotor blades. During this period, the authors found 12 dead
birds belonging to seven different species, viz., Black Kite Milvus migrans, Bonelli’s Eagle Aquila
fasciata, Changeable Hawk Eagle Nisaetus cirrhatus, Red-rumped
Swallow Cecropis
daurica, Dusky Crag-martin Ptyonoprogne
concolor, Slaty-legged
Crake Rallin aeurizonoides,
and Common Crow. These birds, however,
are not depicted in Figures 6a–6c, which consider only 15 birds whose carcasses
are recorded from location-3. Western
Ghats is a biodiversity hotspot region and is home to many birds, which are vulnerable
to collision with WTs installed in this region.
Another ‘Critically Endangered’ species of bird, the Great Indian
Bustard (Dasgupta 2017) is found mostly in Rajasthan, a state with high wind
energy installations.
In India, more than 95% of the wind power capacity is
installed in the two southern states, Tamil Nadu & Karnataka and three
western states, Gujarat, Rajasthan & Maharashtra (Chaurasiya
et al. 2019). Since many wildlife
protected areas are situated in these states, there is possibility of overlap
of home range of the local and migratory birds and the WT installations.
4.1 Mitigation Measures
Bose et al. (2018) used ecological niche factor
analysis (ENFA) to identify overlaps collision niche between species of birds,
which are susceptible to injuries from WTs.
Wind energy is a dominant renewable energy source in India, and there is
possibility of expansion of the WT installation capacities in many other states
including within ecologically sensitive areas.
Therefore, it is necessary to develop environmentally sustainable
planning at wind turbine installations to prevent collision of birds with
WTs. Since birds that migrate during the
day have a lower risk of colliding with WTs (Nichols et al. 2018), restriction
of WTs during daytime may be an effective measure to reduce collision
probabilities. Temporary shutdown during
high risk period has also been recommended by a few authors (Marques et al.
2014; May 2015). Visual approaches to
alert birds by painting wind turbine blades with conspicuous and contrast colors or using ultraviolet reflective paint on rotor
blades for UV-sensitive species and using pulsating lights or other wavelengths
may also reduce fatalities (Arnet & May
2016). Although use of bio-acoustic
sound and electromagnetic signals have been found effective for some species of
birds and bats (Marques et al. 2014; May et al. 2015), effectiveness of radar
as a potential measure to deter birds and bats is questionable (Arnett et al.
2008).
Conclusions
We examined distribution of bird species across India
and possibility of their collision with WTs.
From digitization on raster maps, this study demonstrates that wind
farms in India are located along the ecologically sensitive zones like national
parks, biosphere reserves, biodiversity hotspots, and coastal areas. Transect charts ensure the possibility of
collision of birds with WTs in these areas.
Bakkhali is located in Sundarban
Biosphere Reserve, an ecologically sensitive zone and a UNESCO World Heritage
site. This study reveals that 12 local
and three migratory species of birds in Bakkhali are
vulnerable to collision with wind turbines.
There is utmost urgency to modify design of wind turbines to save these
birds from collision. Further studies
are required to assess accurate causes of bird fatalities near wind farms in
India, detailed assessment of the most affected local and migratory species of
birds, their dependency with other species, and implementation of additional
& complementary measures to protect birds from wind turbines. As a future extension, one needs to conduct
risk analysis through robust statistical analysis.
Table 1. IUCN status of the bird species collision
found in location -3 (www.iucnredlist.org)
Family |
Name |
Scientific name |
IUCN status |
Anatidae |
Bar-headed Goose |
Anser indicus |
Least Concern |
Red-crested Pochard |
Netta rufina |
Least Concern |
|
Lesser Whistling Duck |
Dendrocygna javanica |
Least Concern |
|
American Black Duck |
Anas rubripes |
Least Concern |
|
Ruddy Shelduck |
Tadoma ferruginea |
Least Concern |
|
Ardeidae |
Cattle Egret |
Bubulcus ibis |
Least Concern |
Indian Pond Heron |
Ardeola grayii |
Least Concern |
|
Great Egret |
Ardae alba |
Least Concern |
|
Tytonidae |
Barn Owl |
Tyto alba |
Least Concern |
Strigidae |
Indian Scops Owl |
Otus bakkamoena |
Least Concern |
Scolopacidae |
Common Sandpiper |
Actitis hypoleucos |
Least Concern |
Common Snipe |
Gallinago gallinago |
Least Concern |
|
Columbidae |
Rock Pigeon |
Columba livia |
Least Concern |
Cuculidae |
Asian Koel |
Eudynamys scolopaceus |
Least Concern |
Corvidae |
House Crow |
Corvus splendens |
Least Concern |
For
figures & Appendix - - click here
References
Arnett, E.B. & R. F. May (2016). Mitigating wind energy impacts on wildlife:
approaches for multiple taxa. Human
Wildlife Interactions 10(1):28–41. https://doi.org/10.26077/1jeg-7r13
Aschwanden, J., H. Stark, D. Peter, T. Steuri, B. Schmid &
F. Liechti (2018). Bird collisions at wind turbines in a mountainous
area related to bird movement intensities measured by radar. Biological
Conservation 220: 228–236. https://doi.org/10.1016/j.biocon.2018.01.005
Arikan, K. & S.L. Turan
(2017). Estimation of bird fatalities
caused by wind turbines in Turkey. Fresenius Environmental Bulletin 26(11):
6543–6550.
Arnett, E.B., W.K. Brown, W.P. Erickson, J.K. Fiedler,
B.L. Hamilton, T.H. Henry, A. Jain, G.D. Johnson, J.Kerns,
R.R. Koford, C.P. Nicholson, T.J. O’Connell, M.D. Piorkowski & R.D. Tankersley (2008). Patterns of bat fatalities at wind energy facilities
in North America. Journal of Wildlife Management 72: 61–78. https://doi.org/10.2193/2007-221
Anoop, V., P.R. Arun &
R. Jayapal (2018). Do Black-naped Hares Lepus
nigricollis (Mammalia: Lagomorpha:
Leporidae) have synanthropic association with wind
farms? Journal of Threatened Taxa 10(7): 11925–11927. http://doi.org/10.11609/jott.3411.10.7.11925-11927
Bach, L. & U. Rahmel
(2004). Summary of wind turbine impacts
on bats—assessment of a conflict. Bremer BeiträgefürNaturkunde
und Naturschutz 7: 245–252.
Barclay, R.M., E.F. Baerwald
& J.C. Gruver (2007). Variation in
bat and bird fatalities at wind energy facilities: assessing the effects of
rotor size and tower height. Canadian Journal of Zoology 85(3):
381–387. https://doi.org/10.1139/Z07-011
Bose, A., T. Dürr, R.A. Klenke & K. Henle (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): 3777. https://doi.org/10.1038/s41598-018-22178-z
Beston, J.A., J.E. Diffendorfer,
S.R. Loss & D.H. Johnson (2016). Prioritizing avian species for their risk of
population-level consequences from wind energy development. PloS One 11(3): e0150813. https://doi.org/10.1371/journal.pone.0150813
Cao, J. & G. Wang (2008). The structure of uniform B-spline curves with
parameters, Progress in Natural Science 18(3): 303–308. https://doi.org/10.1016/j.pnsc.2007.09.005
Chitale, V.S., M.D. Behera,& P.S. Roy (2014). Future of endemic flora of biodiversity hotspots in
India. PloS One 9(12):
e115264. https://doi.org/10.1371/journal.pone.0115264
Chaurasiya, P.K., V. Warudkar & S
Ahmed (2019). Wind energy development and policy
in India: A review. Energy Strategy Reviews 24: 342–357. https://doi.org/10.1016/j.esr.2019.04.010
Dasgupta, S. (2017). Critically Endangered Great Indian
Bustards burn up on power lines. Date of download 17-05-2018.
https://india.mongabay.com/2017/12/27/video-critically-endangered-great-indian-bustards-burn-up-on-power-lines/
De Lucas, M., M. Ferrer & G.F. Janss
(2012). Using wind tunnels to predict bird
mortality in wind farms: the case of griffon vultures. PloS
One 7(11): e48092. https://doi.org/10.1371/journal.pone.0048092
Dürr, T. & L. Bach (2004). Bat deaths and wind turbines: a review of current
knowledge, and of the information available in the database for Germany. Bremer Beiträge für Naturkunde und Naturschutz 7: 253–264.
Eilers, P.H. & B.D. Marx (1996). Flexible
smoothing with B-splines and penalties. Statistical Science 1:
89–102. https://doi.10.1214/ss/1038425655
Effat, H.A. (2014). Spatial modeling of optimum zones for wind farms using remote
sensing and geographic information system, application in the Red Sea, Egypt. Journal
of Geographic Information System 6: 358–374. https://doi.org/10.4236/jgis.2014.64032
Erickson, W.P., M.M. Wolfe, K.J. Bay, D.H. Johnson
& J.L. Gehring (2014). A
comprehensive analysis of small-passerine fatalities from collision with
turbines at wind energy facilities. PLoS
One 9(9): e107491.
https://doi.org/10.1371/journal.pone.0107491
Everaert, J. & E.W. Stienen
(2006). Impact of wind turbines on birds
in Zeebrugge (Belgium). Biodiversity and Conservation 16:
3345–3359. https://doi.org/10.1007/s10531-006-9082-1
Ferreira, D., C. Freixo, J.
Cabral, R. Santos & M. Santos (2015). Do habitat characteristics determine mortality risk
for bats at wind farms? Modelling susceptible species activity patterns
and anticipating possible mortality events. Ecological Informatics 28: 7–18.
https://doi.org/10.1016/j.ecoinf.2015.04.001
Graff, B.J., J.A. Jenks, J.D. Stafford, K.C. Jensen
& T.W. Grovenburg (2016). Assessing spring direct mortality to avifauna from
wind energy facilities in the Dakotas. Journal of Wildlife Management
80(4): 736–745. https://doi.org/10.1002/jwmg.1051
Hull, C.L., E.M. Stark, S. Peruzzo
& C.C. Sims (2013). Avian
collisions at two wind farms in Tasmania, Australia: taxonomic and ecological
characteristics of colliders versus non colliders. New Zealand Journal of
Zoology 40(1): 47–62. https://doi.10.1080/03014223.2012.757243
Jcngsma, D., J.M.
Woodside, W. Huson, S. Suparka
& D. Kadarisman (1989).
Geophysics and tentative late cenozoic seismic
stratigraphy of the Banda arc-Australian continent collision zone along three transects.
Netherlands Journal of Sea Research 24(2/3): 205–229. https://doi.org/10.1016/0077-7579(89)90150-6
Johnson, G.D. (2005). A review of bat mortality at wind-energy developments
in the United States. Bat Research News 46: 45–49.
Kemp, M.U., J. Shamoun-Baranes,
H. van Gasteren, W. Bouten
& E.E. van Loon (2010).
Can wind help explain seasonal differences in avian migration speed? Journal
of Avian Biology 41: 672–677. https://doi.org/10.1111/j.1600-048X.2010.05053.x
Kitano, M. & S. Shiraki
(2013). Estimation of bird fatalities at
wind farms with complex topography and vegetation in Hokkaido, Japan. Wildlife
Society Bulletin 37(1): 41–48. https://doi.org/10.1002/wsb.255
Korner-Nievergelt, F., R.
Brinkmann, I. Niermann & O. Behr (2013). Estimating bat and bird mortality occurring at wind
energy turbines from covariates and carcass searches using mixture
models. PloS One 8(7):
p.e67997. https://doi.10.1371/journal.pone.0067997
Krijgsveld, K.L., K. Akershoek, F.
Schenk, F. Dijk & S. Dirksen (2009). Collision risk of birds with modern large wind
turbines. Ardea 97(3):
357–366. https://doi.org/10.5253/078.097.0311
Kumar, S.R., V.K. Anoop, P.R. Arun,
R. Jayapal & A.M. Ali (2019). Avian mortalities from two wind farms at Kutch,
Gujarat and Davangere, Karnataka, India. Currrent
Science 116(9): 1587–1592. https://doi.10.18520/cs/v116/i9/1587-1592
Larsen, J.K. & M. Guillemette (2017). Effects of wind turbines on flight behaviour of
wintering common eiders: implications for habitat use and collision risk. Journal
of Applied Ecology 44: 516–522. https://doi.org/10.1111/j.1365-2664.2007.01303.x
Lehnert, L.S., S. Kramer-Schadt,
S. Schönborn, O. Lindecke,
I. Niermann & C.C. Voigt (2014). Wind farm facilities in Germany kill noctule bats
from near and far. PloS One 9(8):
p.e103106. https://doi.10.1371/journal.pone.0103106
Lin, S.C. (2017). A survey and study of tower kills and wind turbine
kills. Applied Ecology and Environmental Research 15(1):
589–607. https://doi.10.15666/aeer/1501_589607
Loss, S.R., T. Will & P.P. Marra (2013).
Estimates of bird collision mortality at wind facilities in the contiguous
United States. Biological Conservation 168: 201–209. https://doi.org/10.1016/j.biocon.2013.10.007
Lu, X., M.B. McElroy & J. Kiviluoma
(2009). Global potential for
wind-generated electricity. Proceedings of the National Academy of
Sciences 106(27): 10933–10938. https://doi.org/10.1073/pnas.0904101106
Mazumdar, S., K. Mookherjee
& G.K. Saha (2007). Migratory water birds of wetlands of southern West
Bengal, India. Indian Birds 3(2): 42–45.
Marques, A.T., H. Batalha,
S. Rodrigues, H. Costa, M.J.R. Pereira, C. Fonseca, M. Mascarenhas
& J. Bernardino (2014). Understanding bird collisions at wind farms: An
updated review on the causes and possible mitigation strategies. Biological
Conservation 179: 40–52. https://doi.org/10.1016/j.biocon.2014.08.017
May, R.F. (2015). A unifying framework for the underlying mechanisms of
avian avoidance of wind turbines. Biological Conservation 190: 179–187. https://doi.org/10.1016/j.biocon.2015.06.004
Morinha, F., P. Travassos, F. Seixas, A. Martins, R. Bastos, D. Carvalho, P. Magalhães, M. Santos, E. Bastos & J.A. Cabral (2014). Differential mortality of birds killed at wind farms
in Northern Portugal. Bird Study 61(2): 255–259. https://doi.org/10.1080/00063657.2014.883357
Nazir, M.S., A.J. Mahdi, M. Bilal, H.M. Sohai, N. Ali & Iqbal (2019). Environmental impact and pollution-related challenges
of renewable wind energy paradigm – A review. Science of the Total
Environment 683: 436–444. https://doi.org/10.1016/j.scitotenv.2019.05.274
Nichols, K.S., T. Homayoun,
J. Eckles & R.B. Blair (2018).
Bird-building collision risk: an assessment of the collision risk of birds with
buildings by phylogeny and behavior using two citizen
science datasets. PLoS One 13(8):
e0201558. https://doi.10.1371/journal.pone.0201558
Pande, S., A. Padhye, P. Deshpande, A. Ponkshe, P. Pandit, A. Pawashe, S. Pednekar & R. Pandit (2013). Avian collision threat assessment at Bhambarwadi Wind Farm Plateau in northern Western Ghats,
India. Journal of Threatened Taxa 5(1): 3504–3515. https://doi.10.11609/JoTT.o3096.210
Péron, G., J.E. Hines, J.D. Nichols, W.L. Kendall, K.A.
Peters & D.S. Mizrahi (2013).
Estimation of bird and bat mortality at wind-power farms with superpopulation
models. Journal of Applied Ecology 50(4): 902–911. https://doi.org/10.1111/1365-2664.12100
Pescador, M., J.I.G.
Ramírez & S.J. Peris (2019). Effectiveness of a mitigation measure for the Lesser
Kestrel (Falco naumanni) in wind farms in
Spain. Journal of Environmental Management 231: 919–925. https://doi.org/10.1016/j.jenvman.2018.10.094
Plonczkier, P. & I.C. Simms (2012). Radar monitoring of migrating Pink-footed Geese:
behavioural responses to offshore wind farm development. Journal of Applied
Ecology 49: 1187–1194. https://doi.org/10.1111/j.1365-2664.2012.02181.x
Powlesland, R. (2009). Impact of wind farms on birds: a review. Science
for Conservation 289: 5–41. Retrieved on 03/05/2018 from www.doc.govt.nz/Documents/science-and-technical/sfc289entire.pdf
Roeleke, M., T. Blohm, S. Kramer-Schadt, Y. Yovel & C.C.Voigt (2016). Habitat use of bats in relation to wind turbines
revealed by GPS tracking. Scientific Reports 6: 28961. https://doi.10.1038/srep28961
Rothery, P., I. Newton & B. Little (2009). Observations of seabirds at offshore wind turbines
near Blyth in northeast England. Bird Study 56(1): 1–14. https://doi.org/10.1080/00063650802648093
Saha, S., G.C. Paul, & T.K. Hembram
(2019). Classification of terrain based
on geo-environmental parameters and their relationship with land use/land cover
in Bansloi River basin, eastern India: RS-GIS
approach. Applied Geomatics 12: 55–71: https://doi.org/10.1007/s12518-019-00277-4
Singh, K., E.D. Baker & M.A. Lackner (2015). Curtailing wind turbine operations to reduce avian
mortality. Renewable Energy 78: 351–356. https://doi.org/10.1016/j.renene.2014.12.064
Rydell J., L. Bach, M. Dubourg-Savage,
M. Green, L. Rodrigues & A. Hedenström (2010). Bat mortality at wind turbines in northwestern
Europe. Acta Chiropterologica 12(2): 261–274. https://doi.10.3161/150811010X537846
Sivakumar, R. & S. Ghosh (2017). Determination of threshold energy for the development
of seismic energy anomaly model through integrated geotectonic
and geoinformatics approach. Natural Hazards 86(2): 711–740. https://doi.10.1007/s11069-016-2713-2
Smales, I., S. Muir, C. Meredith & R. Baird (2013). A description of the biosis
model to assess risk of bird collisions with wind turbines. Wildlife
Society Bulletin 37(1): 59–65 https://doi.org/10.1002/wsb.257
Thaxter C.B., G.M. Buchanan, J. Carr,
S.H. Butchart, T. Newbold, R.E. Green, J.A. Tobias, W.B. Foden, S. O’Brien,
J.W. Pearce-Higgins (2017). Bird
and bat species’ global vulnerability to collision mortality at wind farms
revealed through a trait-based assessment. Proceedings of the Royal Society
B: Biological Sciences 284(1862): 20170829. https://doi.org/10.1098/rspb.2017.0829
Tucker, M.A., K. Böhning-Gaese,
W.F. Fagan, J. M. Fryxell, B. Van Moorter,
S.C. Alberts, A.H. Ali, A.M. Allen, N. Attias, T. Avgar & H .Bartlam-Brooks (2018). Moving in the anthropocene:
global reductions in terrestrial mammalian movements. Science 359(6374):
466–469. https://doi.10.1126/science.aam9712
Xie, H., G. Yao & G Liu (2015). Spatial evaluation of the ecological importance based
on GIS for environmental management: a case study in Xingguo
county of China. Ecological Indicators 51: 3–12. https://doi.org/10.1016/j.ecolind.2014.08.042
Wald, L. & T. Ranchin
(1995). Fusion of images and raster-maps
of different spatial resolutions by encrustation: an improved approach. Computers,
Environment and Urban Systems 19(2): 77–87. https://doi.org/10.1016/0198-9715(95)00014-Y
Wellig, S.D., S. Nussle, D. Miltner,
O. Kohle, O. Glaizot, V. Braunisch, M.K. Obrist & R. Arlettaz
(2018). Mitigating the negative impacts
of tall wind turbines on bats: vertical activity profiles and relationships
to wind speed. PLoS One 13(3):
e0192493. https://doi.org/10.1371/journal.pone.0192493
Zimmerling,
J.R., A. Pomeroy, M. d’Entremont & C.M. Francis
(2013). Canadian estimate of
bird mortality due to collisions and direct habitat loss associated with wind
turbine developments. Avian Conservation and Ecology 8(2): 10.
https://doi.org/10.5751/ACE-00609-080210