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