Wildlife and Wind Farms - Conflicts and Solutions: Onshore: Monitoring and Mitigation

Wind farms are an essential component of global renewable energy policy and the action to limit the effects of climate change. There is, however, considerable concern over the impacts of wind farms on wildlife, leading to a wide range of research and monitoring studies, a growing body of literature and several international conferences on the topic.

This unique multi-volume work provides a comprehensive overview of the interactions between wind farms and wildlife.

Volume 2 provides a state-of-the-science guide to monitoring and mitigation to minimise or even eliminate impacts on wildlife from wind farms. The survey and monitoring section includes detailed chapters on birds and bats followed by chapters on modelling of collision risk and populations and the statistical principles of fatality monitoring. The following mitigation section comprises chapters on spatial planning and effective mitigation strategies for bats, birds and raptors including through repowering. A synopsis of international best planning and practice concludes the volume.

The authors have been carefully selected from across the globe from the large number of academics, consultants and practitioners now engaged in wind farm studies, for their influential contribution to the science. Edited by Martin Perrow and with contributions by over 30 leading researchers including: Ed Arnett, Cris Hein, Manuela Huso, Johann Köppel, Roel May, Ian Smales & Shawn Smallwood. The authors represent a wide range of organisations and institutions including Bat Conservation International, Birdwatch Ireland, Norwegian Institute for Nature Research, Spanish Council for Scientific Research, Swiss Ornithological Institute, Technische Universität Berlin and US Geological Survey as well as several leading consultancies.

Each chapter includes informative figures, tables, photographs and detailed case studies. Several of the latter are produced stand-alone from invited additional authors to ensure geographic spread and to showcase exciting new research.

This book is designed for practitioners, researchers, managers and for a range of students in higher education, particularly those involved with environmental, ecological, conservation, impact assessment and climate change studies.

Other volumes:
Volume 1: Onshore: Potential Effects (978-1-78427-119-0)
Volume 3: Offshore: Potential Effects (978-1-78427-127-5)
Volume 4: Offshore: Monitoring and Mitigation (978-1-78427-131-2)

• Language: English
• Publisher: Pelagic Publishing
• Release date: May 2, 2017
• ISBN: 9781784271244

Book preview

Preface

Wind farms are seen to be an essential component of global renewable energy policy and the action to limit the effects of climate change. There is, however, considerable concern over the effects of wind farms on wildlife especially on birds and increasingly on bats. Environmental impact assessment, which has been adopted in many countries, should, in theory, reduce any impacts to an acceptable level. Although a wide range of monitoring and research studies have been undertaken, only a small body of that work appears to make it to the peer-reviewed literature. The latter is, however, burgeoning, concomitant with the interest in the interactions between wind energy and wildlife as expressed by the continuing CWW (Conference on Wind Energy and Wildlife Impacts) series of international conferences on the topic. In 2015, 391 participants from 33 countries attended CWW 2015 in Berlin. This will hopefully be exceeded at Estoril in Portugal in September 2017. It is hoped that relationships with researchers in key global producers of wind energy such as China and India, and the emerging markets in Brazil and Africa can become established. Lessons learned in mostly temperate Europe and North America need to be applied to subtropical and tropical climes. Here, in areas with higher biodiversity, it will be even more critical first to understand and then reduce and hopefully eliminate impacts upon wildlife.

Even with specific knowledge of the literature and participation at CWW meetings, I came to the conclusion that it remained difficult for an interested party to judge possible effects on flora and flora and especially the prospects of ecosystem effects focusing on ecological interactions between affected habitats and their dependent species, or between species, one or more of which could be affected by wind farms. In other words, there was a clear need for a coherent overarching review of potential and actual effects of wind farms and perhaps even more importantly, once that had been attained, how impacts could be successfully avoided or mitigated. Understanding the tools available to conduct meaningful research is also clearly fundamental to any research undertaken.

A meeting with Nigel Massen of Pelagic Publishing in Cardiff in late 2012 at the Chartered Institute of Ecology & Environmental Management Renewable Energy and Biodiversity Impacts conference (where else?) crystallised the notion of a current treatise and the opportunity to bring it to reality. Even then, the project could not have been undertaken without the financial support of ECON Ecological Consultancy Ltd expressed as my time and the administrative help of Dr Sarah Eglington in selecting and inviting many of the authors.

The industry is effectively divided into onshore and offshore disciplines that share many similarities such as potential displacement and collision of birds, but also differences such as the relative importance of noise, in the type and strength of effects upon wildlife. This provided a natural division into two compendia sharing common themes and threads within a similar framework. Each was to document current knowledge of the effects – the conflicts with wildlife – and to provide a state-of-the-science guide to the tools monitoring and assessment and the means of avoiding, minimising and mitigating potential impacts – the solutions.

The scope of coverage was to be global, although as a result of the concentration of different forms of the technology in different parts of the world, there was an inevitable bias in experience of the invited authors of the chapters within the different sections. Potential authors were carefully selected from the large number of academics and consultants now engaged in wind farm studies, for their influential contribution to the science. Fortunately, the rate of take-up was high. Many authors also proved keen to significantly extend their chapters, which resulted in the division of the two parts of the onshore compendium into two volumes; this one, Volume 2, describing the potential solutions and Volume 1 outlining the conflicts, as described above.

In this Volume 2, the concept was to focus largely on birds and bats as the two groups that have been the focus of both monitoring and mitigation efforts. The volume opens with Monitoring birds followed by Monitoring bats. These two chapters review available techniques used in both pre-construction characterisation surveys as well as post-construction surveys. The former chapter also provides something of a critique of use or utilisation surveys that have been the mainstay of bird monitoring at wind farms. Modelling of collision risk and populations and Statistical principles of fatality monitoring form a short subsection outlining these essential techniques for predicting and confirming impacts, respectively. To date, modelling has focused on birds, but could equally be used to begin to predict impacts on bats, bearing in mind that little is currently known of the latter’s population demography and dynamics. It is essential that researchers follow the principles outlined in the latter chapter if fatality monitoring, irrespective of whether searching is conducted using humans or dogs, is to provide meaningful estimates in order to judge impacts.

What could be viewed as a mitigation subsection is fronted by Spatial planning, which has generally been applied to birds, but is conceivably of relevance to any wildlife taxon. Mitigation for birds provides an overview of all options using the mitigation hierarchy. Turbine siting for raptors then focuses on an aspect of mitigation for a particularly vulnerable group of birds, describing research driven by repowering – the replacement of old-generation turbines with fewer, larger turbines – within the Altamont Pass Wind Resource Area, one of the best-studied localities in the world. The subsection is concluded with Mitigation for bats, which involves processes quite different to those for birds as a result of the different sensory systems of the two groups and the potential attraction of bats to turbines. The final chapter of the nine in the volume, A best practice approach to future planning, provides a overview of how mitigation should be incorporated into the planning framework and emphasises the need for adaptive management.

To promote coherence within and across volumes, a consistent style was adopted for all chapters, with seven sub-headings: Summary, Introduction, Scope, Themes, Concluding remarks, Acknowledgments and References. For ease of reference, the latter are reproduced after each chapter. The carefully selected sub-headings break from standard academic structure (i.e. some derivative of Abstract, Introduction, Methods, Results, Conclusions) in order to provide flexibility for the range of chapters over the two volumes, many of which are reviews of information, whilst others provide more prescriptive recommendations or even original research. Some sub-headings require a little explanation. For example, the Summary provides a ~300 word overview of the entire chapter, whilst the Concluding remarks provide both conclusions and any recommendations in a section of generally ~500 words. The Scope sets the objectives of the chapter, and for the benefit of the reader describes what is, and what is not, included. Any methods are also incorporated therein. The Themes provide the main body of the text, generally divided into as few subheading levels as possible. Division between effects during construction and operation was generally avoided as this increased the number of sub-headings and led to unwieldy structure. Any clear differences in effects between different stages of wind farm construction and operation are incorporated into specific sub-headings.

As well as being liberally decorated with tables, figures and especially photographs, which are reproduced in colour courtesy of sponsorship by Vattenfall, most chapters also contain Boxes of information. These were designed to be provide particularly important examples of a particular point or case or suffice as an all-round exemplar and ‘stand-alone’ from the text. In some cases, these have been written by an invited author(s) with the principal that it is better to see the words from the hands of those involved that to paraphrase published studies. Boxes also provided an opportunity to widen the geographic spread of information in the chapter.

I take any deficiencies in the scope and content in this and its sister volume to be my responsibility, particularly as both closely align to my original vision, and many authors have patiently tolerated and incorporated my sometimes extensive editorial changes to initial outlines and draft manuscripts. My sincere thanks to all 15 chapter authors and 15 additional Box (case study) authors for their contributions. From my perspective, at least, there can be no satisfaction without at least a little pain. I hope the authors feel the same. I also hope that these volumes are a further step towards the sustainable development of wind farms and the ultimate goal of win–win¹ scenario for renewable energy and wildlife

Martin R. Perrow

ECON Ecological Consultancy Ltd

7 November 2016

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1 Kiesecker, J.M., Evans, J.S., Fargione, J., Doherty, K., Foresman, K.R., Kunz, T.H., Naugle, D., Nibbelink, N.P. & Niemuth, N.D. (2011) Win–win for wind and wildlife: a vision to facilitate sustainable development. PLoS ONE 6: e17566.

CHAPTER 1

Monitoring birds

K. SHAWN SMALLWOOD

In memory of Robert Anderson: a champion of the Golden Eagle.

Summary

Studies are usually performed before the development of a wind farm to determine whether the study area, or specific locations within the study area, will pose an unreasonable avian collision risk. It has long been suspected that the terrain presents an uneven collision risk by channelling bird activity, and pre-construction surveys can inform sound decisions over wind turbine layout. Post-construction surveys are also needed to measure displacement and barrier effects, improve understanding of wind turbine collision mechanisms and test the efficacy of mitigation measures. Visual scans have been favoured for obtaining use rates to be compared to use and fatality rates elsewhere and to predict fatality rates at a proposed wind farm. This chapter reviews those survey methods for wind farm assessment. It then examines use rates in North America for sources of bias and uncertainty and whether use rates are predictive. Use rates are compared from 82 wind farms, including 43 based on pre-construction surveys, 32 with post-construction surveys (21 from the Altamont Pass Wind Resource Area in California, USA), 7 with both pre- and post-construction surveys and 54 with accompanying fatality rate estimates. Potential biases are serious and sources of uncertainty are many, meaning that use rates are often poor predictors of fatality rates. The assumptions used to justify survey methods need testing and efforts to standardise methods need more effective direction. Use surveys can be improved and telemetry expanded, and radar, thermal imaging and behaviour surveys should be developed for predicting and minimising avian collision impacts at wind farms.

Introduction

Environmental studies, typically referred to as ‘baseline studies’ in North America, often precede construction of new wind farms to assess potential impacts on birds, bats and other wildlife. This process is analogous to Environmental Impact Assessment (EIA) adopted in Europe. Wind farms can adversely affect birds in several ways: (1) modifying or destroying habitat by the construction of wind turbine pads and access roads; (2) displacing some birds that avoid the new facilities (Leddy et al. 1999; Whitfield & Madders 2006; Pearce-Higgins et al. 2009; Garvin et al. 2011; Langston 2013); and (3) injuring and killing birds when they collide with wind turbines (Smallwood & Thelander 2004; 2005; de Lucas et al. 2007; 2008; 2012a; Smallwood 2007; 2013; Dahl et al. 2012). Less obvious impacts include collision of birds with turbine towers, birds being struck by automobiles on the access roads, electrocution of birds along electric circuit lines, on transformers or other electrical infrastructure, oiling of feathers of birds entering the nacelles, and entrapment of birds within nacelle and tower spaces. Despite the variety of wind farm impacts, most of the focus of pre-construction environmental assessments has been on the risks of collision with wind turbines.

Baseline studies typically include on-site surveys to assess utilisation as an indicator of relative abundance. Utilisation rates, also known as use rates, and usually expressed by the metric ‘birds seen per unit time’, are typically assessed by comparing them to use rates at other wind farms where impacts had also been estimated following post-construction fatality surveys. Surveys to estimate use rates are typically intended to predict impacts so that an informed decision can be made whether the wind farm should be developed. According to the objectives typically appearing in baseline study reports, a long-established secondary objective has often been to guide wind turbine siting, also known as ‘micro-siting’, to minimise collisions with flying birds [Morrison 1998; Anderson et al. 1999; California Energy Commission California Department of Fish and Game (CEC CDFG) 2007; see Chapters 16 and 17 in this volume].

An important element of baseline studies and EIAs is learning from the impacts already experienced at existing wind farms (New et al. 2015). Studying causal factors of fatalities at existing wind farms can help to predict impacts at new wind farms. It is important to learn how eagles and other birds react to wind turbines (Osborn et al. 1998; Leddy et al. 1999; Hoover & Morrison 2005; Smallwood et al. 2009a; 2009c; May et al. 2010; Dahl et al. 2013; Hull & Muir 2013; Kitano & Shiraki 2013). Also needed are more accurate fatality rate estimates for comparison with predictor variables such as use rates, so that investigators can develop predictive tools and formulate mitigation strategies.

The prediction of wind turbine impacts benefits from knowing the sensitivity of local species to wind energy development, where sensitivity links to the conservation importance or relative rarity of the species (Percival 2007; Desholm 2009). It also benefits from understanding the collision susceptibility of bird species due to flight behaviours, relative abundance and reactions to wind turbines. It benefits further from understanding vulnerability to collisions posed by the planned arrangement and design of wind turbines, including the wind farm’s size (rated capacity), spatial extent, tower heights, rotor diameters, rotational speed, inter-turbine spacing and locations of turbines on the landscape. That is, susceptibility is a species’ predisposition to being harmed by wind turbines due to morphology, ecology and environmental perception, whereas vulnerability is the likelihood of individuals being harmed once wind turbines are installed (Smallwood & Thelander 2004; 2005).

Understanding susceptibility and vulnerability has been hampered by five major problems. First, the distinction between susceptibility and vulnerability can be muddled by changes in behaviour or relative abundance caused by wind turbine installations. Patterns of behaviour and abundance seen before construction may not resemble the patterns seen after construction, or they may differ in small but significant ways. Experimental designs and more thorough investigations are needed to discern how and to what degree susceptibility translates to vulnerability following a wind farm development (Dahl et al. 2012). Secondly, comparing observational studies among wind farms by opportunity rather than by sampling design can lead to pseudoreplication (Huso & Dalthorp 2014). Thirdly, European studies found poor prediction of fatality rates based on pre-construction use rates (de Lucas et al. 2008; Ferrer et al. 2012), but no serious verification has been attempted elsewhere. Fourthly, the degree to which relative abundance and behaviours vary within and between species is often unknown and can confound comparisons of fatality rates. Relative abundance measured at a certain place and time may differ from the relative abundance measured after wind farm construction for reasons independent of the site’s construction. By not surveying far enough beyond the boundaries of wind farms, investigators often miss measures of aggregation within wind farms that would be more predictive of collision impacts (Carrete et al. 2012). Behaviours can also vary temporally and spatially in response to wind, topography, food and social conditions. Finally, high uncertainty and large biases are likely in the methods used to estimate use rates. Whereas uncertainty and biases in fatality rate estimates have been debated, little debate has been directed towards sources and magnitudes of error and bias in use rates other than potential biases pointed out by Madders and Whitfield (2006).

The development of North American baseline study methods focused on standardisation and comparability of metrics (Gauthreaux 1995). Many guidelines documents have been prepared, usually emphasising methodological standardisation (Table 1.1). Despite the emphasis on standardisation, guidelines have varied considerably in their goals and objectives and level of detail (Table 1.1). Guidelines in Japan, England and California also collectively recommended recording certain details associated with use surveys, including the observer’s name, station number, survey date, start time, temperature, wind speed (average, maximum), wind direction, weather (cloud cover, precipitation), visibility, time of each bird observation, species, number of birds composing an observation, social context (single, pair, flock), behaviour (perching, nesting, flying, type of flight), mapped location or distance from the observer, slope aspect or habitat, flight direction and distance of the bird from the nearest wind turbine (if post-construction). Guidance conspicuously absent from the guidance documents reviewed in Table 1.1 includes the assessment of barrier effects or avian energetic costs associated with birds having to fly around wind turbines or wind farms (Drewitt & Langston 2006), and the use of peer review in formulating survey plans and in reporting results.

It is also immediately clear from the guidance documents that a range of methods may be recommended in particular circumstances and according to survey goals and objectives. The metrics potentially derived from the different methods include: (1) use rates, including use rates within heights above ground equal to the anticipated low and high reaches of the turbine blades, for use in a collision risk index and modelling collision risk (New et al. 2015); (2) passage rates, which are at least theoretically the basis of collision risk models based on avoidance rates (Band et al. 2007; Smales et al. 2013; see Chapter 13 in this volume); (3) behaviour rates, such as hovering time or aggressive encounters per hour, which are used for spatially explicit collision hazard models (see Chapter 17 in this volume); and (4) nesting densities, which are also used for spatially explicit collision hazard models (Smallwood et al. 2009a).

The same survey methods can also be used during post-construction monitoring to estimate barrier effects and displacement (Garvin et al. 2011; Loesch et al. 2012), to test mitigation measures or to compare use rates and fatality rates directly for sensitive species. In at least one case, post-construction monitoring also included nocturnal surveys to quantify behaviour rates, passage rates and avoidance rates of owls and nocturnal migrants (Smallwood, unpublished data 2015). Post-construction monitoring was used by de Lucas et al. (2012a) to shut down select turbines as soaring Griffon Vultures Gyps fulvus approached during the migratory months of October and November, hence reducing Griffon Vulture fatalities by 50% with negligible impacts on wind farm energy generation.

Table 1.1 Recommendations (X) and implied recommendations (I) in guidance documents.

aCanadian guidelines apply to wind farms of one to ten turbines, otherwise the coverage would apply to a subsample of candidate turbine sites.

A: Japan (Smallwood 2009); B: Scottish Natural Heritage (Whitfield et al. 2005); C: England (Drewitt & Smith 2010); D: South Africa (Jenkins et al. 2012); E: Canada (Kingsley & Whittam 2003); F: USA Eagle conservation plan guidance [United States Fish and Wildlife Service (USFWS) 2013]; G: USA land-based guidelines (USFWS 2012); H: California (CDFG & CEC 2008); SE: standard error; CI: confidence interval.

Avoidance rates for use in collision risk models can also be estimated from post-construction behaviour surveys (May et al. 2010), but obviously cannot be estimated during pre-construction surveys unless followed up by post-construction surveys to measure differences in passage rates through the wind farm or wind turbine rotors (e.g. Hull & Muir 2013; Johnston et al. 2014). For avoidance rates to be effective, however, explicit definitions are needed, such as whether a bird’s avoidance action was directed towards the entire wind farm, individual wind turbines, rotors or blades; or, another way of looking at it, whether the bird’s avoidance was measured while within the bounds of a wind farm, within a certain distance of a wind turbine, within the rotor plane of a turbine, or within a certain distance of a blade. Hull and Muir (2013) developed an explicit definition for avoidance at the wind turbine level. According to Cook et al. (2014), micro-avoidance is a last-second action taken within 10 m of a rotor to avoid collision, meso-avoidance is any behavioural response to individual turbines from the tower base to the outer reaches of the rotor, and macro-avoidance is any behavioural response to the presence of the wind farm, measured from the outermost turbines. Cook et al. (2014) assigned distance thresholds to meso- and macro-avoidance, but the distance could change with species and with the size of wind turbines or wind farms. In addition to the need for more explicit definitions, Chamberlain et al. (2006) pointed out that avoidance behaviours may be less frequent during conditions when visual scans are not undertaken, such as during cold weather, fog, rain or darkness. Upon reviewing collision risk models, Masden and Cook (2016) advocated testing assumptions underlying the models. Owing to variation in the meaning of avoidance and the need for testing assumptions related to how birds behave while flying near wind turbines, it may be prudent to regard most avoidance rates as overoptimistic until evidence suggests otherwise.

Scope

The first objective of this chapter is to present methods used to survey wind farms for birds, particularly in relation to their susceptibility to collision impacts. Avian survey methods assessed herein were identified from accumulated worldwide literature on wind farm assessment and monitoring, but this is not exhaustive. The second objective is to assess the value of each of these methods for their comparability of rates and predictability of impacts according to the principles of wind farm assessment. The third objective is to explore sources of bias and uncertainty in estimating use rates from use surveys, which are most often used to predict impacts and sometimes subsequently applied in post-construction monitoring to help measure or explain impacts, including fatalities and displacement.

For the last objective, all the publicly available monitoring data used were collected in North America, where standardisation of methods has been strongly advocated to achieve comparability of use rates and fatality rates (Gauthreaux 1995; Anderson et al. 1999); and the research and monitoring data used were collected in the Altamont Pass Wind Resource Area (APWRA). No attempt is made to identify sources of uncertainty and bias in fatality rate estimates because this was the target of previous publications (Smallwood 2007; 2013).

Themes

Survey methods

Survey methods used in wind farm assessment have included point counts or visual scans conducted both by day and increasingly at night, behaviour surveys, radar, telemetry, nest surveys and transect surveys. The basic methodology and a brief discussion of strengths and weaknesses are provided in the sections below. Every survey method used for pre-construction site assessment or post-construction impact assessment should be examined closely for the value of the data in meeting objectives or testing hypotheses outlined in Table 1.2. Wind turbines potentially affect many bird species in multiple ways and these species vary greatly in daily and seasonal activity periods, and in numbers, behaviours and detectability. As a result, no single method is available for assessing wind energy impacts on all bird species.

Table 1.2 Pre-construction survey methods and typical types of predictions for impacts of wind farms on birds based on current knowledge.

Diurnal use surveys

Circular (360-degree) visual scans, also known as variable distance circular point observations (Reynolds et al. 1980), are usually performed by observers stationed at designated locations in a proposed or existing wind farm, consistent with scenario A in Figure 1.1 (Osborn et al. 1998; Rugge 2001; Lekuona & Ursúa 2007; Smallwood et al. 2009b). Each station, vantage point (VP) or observation point (OP) is typically selected for maximum vantage over long distances. The maximum survey radius and session duration are established before the surveys begin, and the observers follow a survey schedule that varies according to wind farm size and available budgets. Detected birds are identified to species level, using binoculars if necessary, and counted, and the counts are divided by the session duration to arrive at use rates. By changing the location and restricting the area surveyed, diurnal use surveys can be easily adapted to meet the requirements of scenario B or C in Figure 1.1.

Nocturnal use surveys

Thermal and infrared imaging is available for nocturnal surveys of owls, nocturnal migrants and nocturnal activities of particular species that may be adversely affected by wind turbines, including energetics related to foraging. Thermal imaging was first used in wind farms to quantify behavioural responses of bats to wind turbines (Horn et al. 2008; , Cryan et al. 2014), but has also been used to calculate passage rates of bats, foraging owls and nocturnal migrants through or near the rotors of wind turbines (Smallwood, unpublished data). Thermal cameras mounted on tripods can be panned for 360-degree scans or fixed on particular wind turbine rotors during timed sessions, as required for scenario C in Figure 1.1.

Figure 1.1 Hypothetical use survey design scenarios intended to inform micro-siting of four candidate wind turbine sites (numbered open circles). In scenario A, surveys generate use rates within a plot that fails to cover turbine 1 and is too large for differentiating use rates among turbines 2–4 or for achieving equitable detection rates across the plot (detection rates decline with lesser shading of grey from 0 to 800 m of the station). In B, each candidate wind turbine site is assigned a dedicated survey station to generate use rates more representative of each site. In C, surveys are directed towards each turbine site to quantify comparable passage rates within the airspace that will expose birds to collision risk once turbines are installed. In D, individual birds are tracked visually and mapped to count flight path intersections with each analytical grid cell. These flight paths may be associated with specific behaviours and interactions with other birds, and each grid cell can be associated with terrain features so that predictive models can be developed from wind, terrain, activity level and behaviour.

Behaviour surveys

Surveys directed towards understanding how birds behave in wind resource areas and how these behaviours connote collision risk began during the 1990s with Lawrence et al. (2007), de Lucas et al. (2007), Barrios and Rodríguez (2007), Rugge (2001) and Lekuona and Ursúa (2007). Behaviour surveys have evolved methodologically ever since (Smallwood & Thelander 2004; 2005; Hoover & Morrison 2005; Smallwood et al. 2009a; 2009c; Smallwood, unpublished data 2015). In these surveys, individual birds are detected and followed visually until either the bird disappears from the plot or a higher priority species appears. Results of behaviour surveys showed promise for understanding how birds react to wind turbines (de Lucas et al. 2007; Smallwood et al. 2009b; Johnston et al. 2014) and for predicting wind turbine impacts (Barrios & Rodríguez 2007; Smallwood et al. 2009a), and have since been used to develop map-based predictive models for collision hazard (Smallwood et al. 2009b; see Chapter 17 in this volume). De Lucas et al. (2012b) related Griffon Vulture flight trajectories to wind flows to conclude that these vultures follow wind patterns to minimise travel effort, and proposed using this strategy to guide micro-siting.

Radar

Radar has been used to detect and count flying targets consisting of bats, local nocturnal birds, nocturnal migrants and even diurnal birds. It may thus be used in Scenario D of Figure 1.1. One of the strengths of radar is its ability to measure nocturnal flight activity, and another is to detect many more targets simultaneously than can be detected by visual scans. For example, Harmata et al. (1998) reported detection rates of flying birds using radar that were 7–17 times greater than those using visual scans. With the higher detection rates it is also possible to detect patterns of avoidance around wind farms and turbine rows (Dirksen et al. 2000; Villegas-Patraca et al. 2014), to quantify timing and flight heights associated with passage rates, and to estimate collision risk and barrier effects of wind turbines (Dirksen et al. 2007; Plonczkier & Simms 2012).

Weaknesses of radar include the inability in many cases to identify targets to species level, and bias in estimating distributions of flight heights due to ground clutter and other sources of low-altitude interference. Radar requires clear weather (Hanowski & Hawrot 2000), so can bias observations towards conditions that pose less collision risk to birds. It also suffers a similar decline in detection rates with increasing distance from the radar as experienced with visual scans. The most important weakness is insufficient verification that the number of targets per hour detected by radar can predict fatality rates at wind farms or wind turbines. However, knowing the species using roosting and feeding sites on opposite sides of a wind farm, or the species typically migrating over the area during a particular time of year, and visually verifying radar targets to species level can greatly improve the utility of radar (Dirksen et al. 2007; Villegas-Patraca et al. 2014).

Mabee et al. (2006) used radar to evaluate avian passage rates and flight heights of nocturnal migrants over a proposed wind farm, although the passage rates were incomparable to passage rates measured by radar elsewhere and it was unclear whether the results of the study influenced micro-siting. May et al. (2009) used radar to detect bird movements across an existing wind farm. They established which tracks related to White-tailed Eagles Haliaeetus albicilla killed by wind turbines by filtering those tracks ending within 50 m of a wind turbine. All such tracks were made during late evening and early morning, which indicates the appropriate timing of use or behaviour surveys.

Telemetry

Telemetry tracking of individual birds has been used to estimate home ranges, habitat use, terrain associations and flight paths of Golden Eagle Aquila chrysaetos, Griffon Vulture and other birds susceptible to wind turbine collisions. It is thus useful in scenario D in Figure 1.1, albeit without knowing interactions with other birds, although flight height may be recorded with altimeters within tags (Cleasby et al. 2015) and some behaviours such as foraging may be inferred from flight patterns and tag signal patterns (Perrow et al. 2006; Cleasby et al. 2015). Following the lead of Perrow et al. (2006) in their use of radio-telemetry to establish distance buffers between offshore wind turbines and foraging Little Terns Sternula albifrons, Watson et al. (2014) used Global Positioning System (GPS) transmitters on ten Golden Eagles to estimate home ranges, and terrain associations to recommend wind energy buffers from nest sites. Mammen et al. (2009) used radio-telemetry on Red Kites Milvus milvus in Germany to also estimate home range size and recommend buffer distance around nest sites. Grajetzky et al. (2009) used radio-telemetry on Montagu’s Harriers Circus pygargus to estimate home range overlap into a wind farm and to estimate the