APPENDIX C
Methods and Metrics for Wildlife Studies

A wide range of methods are available for assessing the ecological influences of wind-energy and aspects of the ecology and behavior of species that may be affected by wind-energy facilities; most of them are reviewed here. For additional information on methods readers are referred to syntheses presented in Anderson et al. (1999), Braun (2005), and Kunz and Parsons (in press).

Key Variables and Monitoring Methods

Researchers have only begun to investigate the ecological impacts of wind-energy facilities, especially impacts on bats. The possibility of large cumulative impacts on bat populations has not previously been considered in siting plans and wind-energy development in the United States, and thus research and monitoring studies are needed to develop predictive models of cumulative effects and to inform decision makers. Understanding of impacts on birds also is limited because of the lack of replication of studies at existing wind-energy facilities, the lack of information in some regions of the country, and inadequate evaluation of predicted impacts following facility construction and operation.

Bat fatalities at wind turbines have been reported at nearly every windenergy facility where post-construction surveys have been conducted, yet few of these studies have included more than one year of monitoring, and of these none monitored fatalities consistently from spring migration through fall migration at any single site. Moreover, only four studies prior to that of Arnett (2005) used fresh bat carcasses to assess searcher efficiency and/or



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Environmental Impacts of Wind-Energy Projects APPENDIX C Methods and Metrics for Wildlife Studies A wide range of methods are available for assessing the ecological influences of wind-energy and aspects of the ecology and behavior of species that may be affected by wind-energy facilities; most of them are reviewed here. For additional information on methods readers are referred to syntheses presented in Anderson et al. (1999), Braun (2005), and Kunz and Parsons (in press). Key Variables and Monitoring Methods Researchers have only begun to investigate the ecological impacts of wind-energy facilities, especially impacts on bats. The possibility of large cumulative impacts on bat populations has not previously been considered in siting plans and wind-energy development in the United States, and thus research and monitoring studies are needed to develop predictive models of cumulative effects and to inform decision makers. Understanding of impacts on birds also is limited because of the lack of replication of studies at existing wind-energy facilities, the lack of information in some regions of the country, and inadequate evaluation of predicted impacts following facility construction and operation. Bat fatalities at wind turbines have been reported at nearly every windenergy facility where post-construction surveys have been conducted, yet few of these studies have included more than one year of monitoring, and of these none monitored fatalities consistently from spring migration through fall migration at any single site. Moreover, only four studies prior to that of Arnett (2005) used fresh bat carcasses to assess searcher efficiency and/or

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Environmental Impacts of Wind-Energy Projects conducted scavenger-removal experiments to correct estimates for potential biases. Study Design The most important element in designing a study is deciding on the study objective. Once the study objective is determined, other essential issues include the following: The area of interest, Time period of interest, Species of interest, Potentially confounding variables, The time and budget available for the required studies, and The magnitude of the impact being evaluated. The following is a general discussion of methods, metrics, and study design for achieving objectives commonly addressed in the study of wildlife impacts from wind-energy development. For a more detailed discussion of this topic, readers are referred to Green (1979), Underwood (1994), Anderson et al. (1999), Manly (2001), and Morrison et al. (2001). There is no fundamental difference between monitoring and research, but a commonly used criterion for distinguishing them is the duration of study. Monitoring schemes are essentially repeated surveys (Manly 2001) and are usually designed to detect changes and trends in the variable of interest. Because considerations in study design are essentially the same for both monitoring and observational studies, no effort will be made to further discriminate between the two. Reliable study designs available for environmental impact assessments are limited. The before-after/control impact (BACI) design is commonly used in observational studies (e.g., Stewart-Oaten 1986) and has been considered the optimal impact-study design by Green (1979). As the name implies, this type of study involves the collection of data in the assessment area and a similar (control) area both before and after an impact occurs (Morrison et al. 2001). An effect typically is measured as a change in the difference between estimates of a variable for the control and an assessment area following an impact. Confidence intervals can increase the reliability of an impact estimate when data from more than one control area are available (Underwood 1994). Ideally, control areas should be randomly selected from a population of similar sites (Manly 2001). Study areas within the assessment and control area may be matched to reduce the natural variation common in impact studies (Skalski and Robson 1992), although

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Environmental Impacts of Wind-Energy Projects characteristics of study sites may change in longer-term studies, and thus matching may be unreliable. When data are lacking before an impact, the control-impact design may be used. This type of study differs from the BACI design only in the lack of pre-impact data. As in the BACI design, if a significant difference is attributed to the impact of a perturbation the assumption is that nothing else could cause a change of that magnitude (Manly 2001). Before-after designs can be used when data from a control area cannot be obtained. A change immediately following an impact is assumed to be a result of the impact and not from some other cause. In the absence of data from control areas, the attribution of cause may be difficult to support, unless the impact is large and easily attributable to the cause. For example, a decline in bird abundance following the construction of a wind-energy facility might be attributed to the facility by finding large numbers of bird carcasses killed by turbines. In the absence of strong corroborative evidence, attributing the change in abundance to the wind-energy plant may be difficult to defend. The impact-gradient design may be used for quantifying impacts in relatively small assessment areas with homogeneous environments (Anderson et al. 1999; Manly 2001). With this design, an effect is assumed if it appears to be reduced as the distance increases from the source of the impact (Manly 2001). The most important assumption made when using the impact-gradient design is that the environment is homogeneous. Homogeneity is relatively uncommon in the environment and the analysis of data resulting from this study design should take spatial correlation into account (Manly 2001). For example, wind turbines are typically placed on the windiest sites available in a wind-resource area, such as ridge tops. Thus, moderating environmental conditions as a function of distance from the turbines may create subtle differences in the characteristics of the sites that could mask impacts. Morrison et al. (2001) suggested improving observational studies by using several general approaches to study design that can increase precision without requiring increased replication. Their suggestions include: Vary sampling effort (or apply treatments) within homogenous groups of experimental units (blocking). Measure non-treatment factors (co-variates) and use analysis of covariance when analyzing the response to a treatment to consider the added influence of variables having a measurable influence on the dependent variable. Refine experimental techniques, including greater sampling precision within experimental units (Cochran and Cox 1957; Cox 1958). Mensurative studies involve making measurements of uncontrolled

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Environmental Impacts of Wind-Energy Projects events at one or more points in space or time with space and time being the only experimental variable or treatment (Morrison et al. 2001). Mensurative studies are most convincing when the impacts are large and it is difficult or impossible to attribute the impact to some other cause. Nevertheless, mensurative studies often are conducted because there is no alternative, and they give more information than no study at all (Manly 2001). A study of impact should not rely on a single response variable, but should use the strongest design possible and accumulate all available evidence in a weight-of-evidence approach (Anderson et al. 1999) when evaluating the existence and magnitude of an impact. Table C-1, taken from Anderson et al. (1999), provides a decision matrix for selecting the appropriate impact-study design. Methods for Estimating Abundance Estimating abundance of species at proposed and existing wind-energy sites can be important in assessing the ecological impacts of wind-energy facilities. This section reviews several methods that are appropriate for assessing fatalities and effects of habitat alterations on populations of bats and birds. Direct impacts are fatalities resulting from collisions with wind-turbine blades or turbine monopoles while animals are in flight. Direct impacts may alter sex and age ratios, densities of resident or migratory populations, and survivorship and reproductive success. Indirect impacts include animal, plant, or ecosystem responses to habitat alteration caused by wind-energy facilities; they may include altered foraging behavior, breeding activities, migratory patterns, and demographics. Anderson et al. (1999) provided a detailed discussion of methods and metrics for the study of impacts on birds caused by wind-energy development. While many of these methods and metrics were developed for birds, an improved summary for methods and metrics useful in the study of bats and nocturnally active birds is included in this appendix; a complementary document also is being developed by the National Wind Coordinating Committee (Kunz et al. in press b). Abundance of some animals can be determined from a census or estimated using line-transect sampling, point-counts, quadrat sampling, and other techniques (Buckland et al. 2001, 2004; Manly 2001; Morrison et al. 2001). Abundance also can be estimated through indirect approaches such as mark-resight and capture-mark-recapture estimation (Skalski and Robson 1992; Amstrup et al. 2005), catch-per-unit-effort (Laake 1992), survival analysis (Riggs and Pollock 1992), and change-in-ratio methods (Udevitz and Pollock 1992). Censusing wildlife in designated areas or estimating absolute abundance is generally difficult, expensive, and time consuming. Impact-assessment

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Environmental Impacts of Wind-Energy Projects TABLE C-1 Study-Design Decision Matrix for Observational Studies Design Options             Potential   Recommended Study Design Study Conditions Design Conditions Modification Pre-impact data possible BACI Matching of study sites on assessment and reference areas possible Matched pair, design with BACI Reference area indicated BACI Pre-impact data not possible Impact-reference Matching of study sites on assessment and reference areas possible Matched pair, design with impactreference Reference area indicated Impact-reference Pre-impact data possible Before-after     Reference area not indicated Small homogenous area of potential impact       Impact-gradienta     Sampling Plan Options       Sampling Plan Recommended Use     Haphazard/judgment sampling Preliminary reconnaissance Probability-based sampling:       Simple random sampling Homogenous area with respect to impact indicators and covariates Stratified random sampling Strata well defined and relatively permanent, and study of short duration Systematic sampling Heterogeneous area with respect to impact indicators and covariates, and study of long duration Parameters to Measure       Parameter Empirical Description Abundance/relative use Use per unit area and/or per unit time as an indexb Mortality Carcasses per unit area and/or per unit time Reproduction Young per breeding pair of adults Habitat use Use as a function of availability Covariates Vegetation, topography, structure, distance, species, weather, season, etc. aImpact-gradient design can be used in conjunction with BACI, impact reference, and before-after designs. bCan be summarized by activity/behavior for evaluation of risk. SOURCE: Anderson et al. 1999. Reprinted with permission; copyright 1999, National Wind Coordinating Committee.

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Environmental Impacts of Wind-Energy Projects studies often estimate animal use as a surrogate for abundance. Animal use can be estimated by a variety of methods such as counting the animals detected from a given set of observation points, the amount of time spent by individual animals within a survey plot, the number of animals seen moving past a particular point, the number of targets passing through a radar beam, the number of targets within altitude bands, the number of nests present in a given area, the number of animals trapped or netted, the number of calls detected, or the amount of sign (e.g., tracks or scat) recorded within sample plots. Counts are expressed as the number of observations per unit area, per unit time, or both. Estimates of use allow comparisons among defined time periods and areas (Anderson et al. 1999; Hayes and Loeb 2007; Kunz et al. in press a). Comparison of indices such as animal use among studies or sites requires that indices be estimated using similar protocols. Estimates of use also can assist in the interpretation of fatality data. For example, if two wind-energy facilities are being compared based on fatalities alone, the facility with the greater number of fatalities might be considered to have the greater impact. However, if the facility with more fatalities also has much greater use by the species being killed, then the greater use must be taken into account in any comparison. For example, at a minimum, estimation of use should include the intensity of activity, flight paths, flight heights, and the behavior of the animals of interest. Monitoring productivity and survivorship may be an alternative to the direct estimation of fatalities and abundance when looking at the cumulative effects of wind-energy development on wildlife populations. The Monitoring Avian Productivity and Survivorship (MAPS) program was designed to accurately assess changes in bird productivity and survivorship in response to environmental changes (DeSante et al. 2001). The MAPS program provides annual and regional indices of post-fledging productivity from the number and proportion of young birds captured, annual and regional estimates of adult survivorship, recruitment in the adult population, and adult population size from capture-recapture data on adult birds. At the local level, Hunt (2002) used radiotelemetry data on golden eagles in the Altamont Pass Wind Resources Area (APWRA) to estimate the population’s annual growth rate, which was used to evaluate the effect of wind-energy production on fatalities. This type of study often can provide more information about the mechanisms of impact than simply evaluating fatalities. For example, while Hunt (2002) concluded that the population of golden eagles had characteristics of a growing population, the confidence intervals around the point estimate of positive growth rate included zero, thus making it impossible to verify whether the population was growing or declining. Hunt (2002) concluded that golden eagle territories were consistently occupied and a sufficient number of non-territorial (floater) eagles existed to re-populate

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Environmental Impacts of Wind-Energy Projects vacant territories, suggesting a relatively healthy population. Nevertheless, the relatively high fatalities attributable to the wind-energy facilities resulted in a population without sufficient floaters to ensure stability, making the population susceptible to future declines should fatalities increase for any reason. It also was clear from Hunt’s study that the targeted group of eagles was part of a larger population. Thus, the APWRA may represent a mortality sink for the regional population of golden eagles. Certainly, at the current level of eagle fatalities in the APWRA (Smallwood and Thelander 2004, 2005), the viability of the eagle population depends on adequate immigration from surrounding areas. The detection, identification, and counting of diurnally active organisms in the lower atmosphere is rather straightforward, despite the lack of standard protocols for making daytime observations at planned or existing wind-energy facilities. The situation at night is more difficult. Several methods for detecting, identifying, and counting birds, bats, and insects in the atmosphere at night have been developed (Hayes and Loeb 2007; Kunz et al. in press a). Table C-2 (modified from Larkin 2005a) provides a summary of current technology with respect to the detection range of the equipment, the ability to identify the type of animal, the ability to provide information on passage rates or density estimates, measurement of the altitude of a target, and cost of the equipment. When confirmation of the age, sex, and reproductive condition of a species in an area of interest is desirable (as may often be the case during pre-siting and pre-construction surveys), capture is required. Information on species identity, sex, age, and reproductive condition can also be assessed from bats and birds killed by wind turbines. Remote sensing (e.g., radar) can provide information needed to assess risks to bats and birds at larger spatial and temporal scales. In many cases, using a combination of approaches will be of value as no single method can be used for unambiguously assessing natural populations or the effects of wind turbines on biotic communities. Each approach has its own strengths, limitations, and biases. Investigators should understand the limitations, applicability, and operational considerations of each method before deploying them in the field. Local field guides and taxonomic keys for species identification are essential tools for investigators if they wish to identify the species composition at each locality and the identity of animals that are captured or killed. Use of mitochondrial- and nuclear-DNA sequence data that can be derived by extractions from feathers, hair, and skin of carcasses killed by wind turbines offers the potential for estimating population size of birds and bats (e.g., Waits 2004; Kunz et al. in press a; N.B. Simmons, American Museum of Natural History, personal communication 2006). Moreover, similar DNA-sequence data may be needed to verify the identity of some closely related or cryptic species (e.g., Myotis species). In

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Environmental Impacts of Wind-Energy Projects TABLE C-2 Remote-Sensing Tools for Detecting, Tracking, and Quantifying Flying Birds, Bats, and Insects Equipment   Range Identificationa Small marine radar 30 m-6 km with proper siting of unit + Bird bats vs. insects – Birds vs. bats straight flight: unknown Large Doppler surveillance radar (NWS) 10-200 km + Can discriminate targets by speed if winds are known + Waterfowl & raptors vs. other birds & bats + Insects slower than songbirds Thermal infrared Depends on equipment and cost: $75,000 US unit can detect birds at 3 km Size but not species + Discriminates birds, insects and foraging bats – Migrating birds & bats Image intensifier Good equipment: small birds at 400 m cheap equipment: shorter range – Cheap equipment: poor + Good equipment: better + Discriminate birds, bats vs. insects nearby Ceilometer-spotlight < 400 m – Poor for small targets – Insects can sometimes be confused with birds & bats Moon watching Observer-dependent + Skilled observers can identify many types of birds and discriminate birds from bats + Insect contamination rare, butterflies & moths can be identified Radio tracking 0-2 km Perfect Audio microphones for birds 400 m, depends on ambient noise + Some nocturnal songbird species + Data include no insects Ultrasound microphones for bats < 30 m, depends on humidity -? Bats may or may not emit sounds + If they do, may be species-specific a+ indicates capability; – indicates a lack of capability SOURCE: Modified from Larkin 2005a. Modified table reprinted with permission; copyright 2005, Wildlife Society. addition, voucher specimens of killed animals should be collected and deposited in recognized museum collections for future reference. An overview of how different equipment and approaches are being used in studies associated with proposed and existing wind-energy facili-

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Environmental Impacts of Wind-Energy Projects Passage Rates Height Information Cost Good to excellent Unmodified marine radar antenna in vertical surveillance: yes Parabolic antenna: yes Specialized, expensive if done correctly Good in the infrequent cases where a radar siting happens to be opportune Very coarse with poor low altitude coverage Data are cheap; skilled labor for analysis Excellent when altitude of target is known Coarse when calibrated with vertically pointing radar and then used alone Expensive if high-quality equipment used Yes Same as last Rather expensive if highquality equipment used Yes but light may affect flying animals Same as last Inexpensive but labor-intensive 2 days before and 2 days after full moon and with no cloud cover Very crude A good telescope of at least 20× is required; labor-intensive Poor Crude High Only some species call and quantification is assumption-ridden Microphones: Single: no Arrays: possible Recording equipment inexpensive, analysis expensive No, only presence/absence; too many unknowns at present state of knowledge Some; depends on microphones and placement Moderate costs ties, including both remote sensing (including passive acoustic recording, ultrasonic bat detectors, radar, moon-watching, ceilometer, reflectance infrared imaging, thermal infrared imaging, and radiotelemetry) and capture approaches are presented later in this appendix.

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Environmental Impacts of Wind-Energy Projects Estimating Abundance Using Molecular Markers Estimates of population size, population structure, genetic diversity, and effective population size are important parameters for assessing life histories of natural populations and for managing endangered and threatened species at risk (Dinsmore and Johnson 2005; Lancia et al. 2005). Estimates of these parameters for both resident and migrating birds and bats are needed to better understand how populations are likely to respond to naturally occurring perturbations and to anthropogenic factors such as global climate change, deforestation, and habitat alteration. Wind-energy development, along with other anthropogenic factors, may have adverse effects on some animal populations by directly causing fatalities and indirectly altering critical nesting, roosting, and foraging habitats. To adequately assess whether fatalities or altered habitats are of biological significance to resident and migrating birds and bats, knowledge of baseline population levels, population structure, and genetic diversity is needed. These parameters can be expected to differ among species, which will be subject to different risks from local and regional environmental factors. For example, species represented by large populations, large genetic diversity, and little spatial breeding structure are likely to be less affected by anthropogenic factors than species represented by small populations, low genetic diversity, and strong spatial breeding structure (Avise 1992, 2004). Rare and elusive species may be at greatest risk from anthropogenic changes (Thompson et al. 1998). An important challenge for population ecologists has been applying traditional census methods to rare and elusive species (Thompson et al. 1998). For example, for bats, few statistically defensible estimates of population size have been published—and this is especially the case for migratory tree-roosting species (O’Shea and Bogan 2003; O’Shea et al. 2003, 2004). Historically, population estimates of birds and bats have been derived using a variety of methods, including direct counts, point counts, and other estimating procedures such as capture-mark-recapture methods, photographic sampling, probability sampling, maximum likelihood models, and Bayesian methods (Bibby et al. 2000; Braun 2005; Kunz et al. in press a). Direct counts often are not practical, especially for nocturnally active bird and bat species, in part because these animals typically are small, cryptic, or otherwise difficult to census visually using most existing methods, either during daily or nightly emergences from roosts, or during migratory or foraging flights. Relatively recent approaches have been developed to use capture-mark-recapture models where some or all of the assumptions are relaxed; however, these approaches also have limitations in that a proportion of the originally marked individuals must be recaptured. More recently, capture-mark-recapture models have been used to estimate population sizes derived using non-invasive genetic sampling (Waits 2004).

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Environmental Impacts of Wind-Energy Projects For example, using this approach, Puechmaille and Petit (2007) compared estimates of colony sizes of the lesser horseshoe bat (Rhinolophus hipposideros) using DNA extracted from feces with independent estimates based on visual counts conducted during nightly emergence flights. Their results indicate that analysis of DNA extracted from feces can provide accurate estimates of colony size. Large populations accumulate more genetic diversity and retain this diversity longer than do small populations. At the DNA level, these processes have predictable effects on both levels of genetic diversity and how this diversity is distributed among individuals within populations. Because these effects are predictable, it is possible to estimate long-term effective population size based solely on observed patterns of DNA diversity. If a population changes in size, predictable effects on patterns of diversity occur, and these effects are proportional to that change. Thus, significant declines in population size through time can be documented, although there is some time lag between changes in population size and observable effects on genetic diversity. A conceptual description of the “coalescent” process that results in these effects is provided below. Those interested in more detailed descriptions and applications are referred to Roman and Palumbi (2003), Avise (2004), Russell et al. (2005), and references cited therein. The variation at any particular gene in a population can be illustrated as a topology (“gene tree”) reflecting the historical relationships or genealogy of the gene copies found in different individuals. The number of mutations (i.e., nucleotide substitutions) separating these variable DNA sequences is a function of the demographic history of the population. Because mutations accumulate through time, sequences that diverged longer ago will be separated by a larger number of mutations than those that diverged more recently. If a historically large population remains large, its gene trees will have many “branches” of varying lengths that reflect the accumulation and retention of older and younger mutations. If a large population is reduced in size, its gene tree will be “pruned.” That is, genes reflecting both long and short branches will be lost, with the result of less overall diversity. Short branches also will be proportionately fewer in the reduced population because fewer mutations occur, and older ones are less likely to be retained simply because of the smaller population size. Correspondingly, if a population that was historically small expands in size, its gene tree will consist mostly of short branches reflecting the increased occurrence and retention of more recent mutations. Estimates of population size based on gene diversity have been applied to a variety of animals to investigate patterns of change caused by climatic change or human intervention. For example, the historical population sizes of humpback and fin whales prior to hunting by humans were estimated at approximately 240,000 and 360,000 whales, respectively, contrasted to

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Environmental Impacts of Wind-Energy Projects Stable lsotopes and Genetic Markers Stable isotopes used to assess geographic variation in patterns of precipitation and the unique stable-isotope signatures that are transferred from precipitation to biological primary producers (plants) and ultimately to consumers (herbivores and carnivores) have provided new tools for understanding migration of birds and bats (e.g., Chamberlain et al. 1997; Kelly and Finch 1998; Marra et al. 1998; Hobson 1999; Hobson and Wassenaar 2001; Bowen and Wilkinson 2002; Rubenstein et al. 2002; Rubenstein and Hobson 2004), and genetic data (Berthold 1991; Clegg et al. 2003; Royle and Rubenstein 2004; Kelly et al. 2005). Stable-isotope techniques have been used mostly to associate breeding areas (where molt to new plumage or hair growth or replacement occurs) to migratory stopover areas and wintering areas. The resolution of the signatures is rather crude with respect to latitude and longitude so that it may not be possible to precisely discriminate source areas within a small geographical region. However, as geographical distance increases so does the reliability of the isotope signature. Stable-isotope signatures are also sensitive to elevation; thus altitudinal migration may be confounded with latitudinal migration. Analysis of stable isotopes shows promise in differentiating migratory status. Kelly et al. (2002) used stable isotopes of hydrogen contained in feathers to estimate hydrogen stable-isotope ratios (dD) of feathers from breeding, migrating, and wintering Wilson’s warblers (Wilsonia pusilla). They found that feathers from museum specimens collected throughout the western portion of the breeding range indicate that dD values were significantly and negatively related to latitude of collection, which is an indication that dD values provide a good descriptor of the latitude at which breeding occurs. They also found by analyzing feathers collected on the wintering grounds that the hydrogen isotope ratio was significantly positively related to wintering latitude. Gannes et al. (1997) pointed out the importance of identifying assumptions inherent in stable-isotope analysis and called for laboratory experiments to validate the method. Advances in genetic analysis also show promise in determining the population and geographical origin of individual birds (Webster et al. 2002), and may assist in identifying the origin of bird and bat fatalities at wind-energy facilities. Mitochondrial and nuclear DNA markers have provided valuable for determining source populations of animals that move long distances. They could make it possible to identify geographic origin of bats and birds killed at wind-energy facilities if investigators collected hair samples from bats and feather samples from birds, and compared the isotope signatures and genetic markers on a geographic scale. This kind of information could aid in determining whether bats and birds killed at wind-energy facilities were residents or migrants. Moreover, established DNA sequences for different

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Environmental Impacts of Wind-Energy Projects species can aid in the identification of birds and bats (or parts thereof) from the carcass remains of individuals found during fatality searches. CAPTURE TECHNIQUES Capture methods are invaluable for assessing and confirming the presence of a species, although it may not be possible or practical to capture all species in an area. Some forage and migrate well above the practical limits of capture, although many species fly closer to ground level or forage over water or within the subcanopy of forests. While capture may be challenging for many nocturnal species, captures of migrating passerines are more likely during stopovers. Correct identification of species present in the area of interest is essential for assessing potential risks of wind-energy facilities to different species. For bats and migratory birds, this usually requires that live or dead animals be available for study. Methods and equipment used to capture live bats have been thoroughly described (Greenhall and Paradiso 1968; Tuttle 1976; Kunz and Kurta 1988; Kunz et al. 1996a; Kunz et al. in press a). Methods for assessing colony size, demographics, and population status of bat species are in O’Shea and Bogan (2003) and Kunz and Parsons (in press) and methods for landbirds are in Sutherland et al. (2004). Many of the methods used to capture birds and bats are similar, albeit with some differences. If bats are to be captured at roost sites to assess the species present in the vicinity of wind-energy facilities, or to monitor changes in colony size, harp traps are preferable to mist nets (Kunz et al. in press a). Most important, efforts should be made to minimize disturbance to bat colonies. No single capture method is suitable for all bat species, although mist nets and harp traps are the most commonly used devices for capturing these animals while in flight because they are relatively easily deployed and can be used in a variety of situations. A mist net consists of a nylon mesh supported by a variable number of taut, horizontal threads, or shelf strings. Bats and birds are captured after they become entangled in the mesh of the nets. Mist nets are available from manufacturers in different colors and sizes. For nighttime netting black is the preferred color. They may be set as single net at ground level or stacked on top of one another to form a canopy net (Figure C-11). Simple canopy nets can be modified by restringing horizontal nets (Munn 1991; Rinehart and Kunz 2001). Ground-level nets are generally most practical to deploy, but are biased against species or individuals that do not fly close to the ground. Use of elevated canopy nets can provide researchers access to the aerial space where some bats and birds may commute and forage, although even with canopy nets erected into or suspended in the subcanopy, elevated nets are not suitable for capturing species that typically fly above

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Environmental Impacts of Wind-Energy Projects FIGURE C-11 Multiple stacked horizontal mist nets used for capturing bats and birds from ground level into the forest subcanopy. SOURCE: Hodgkison et al. 2002. Reprinted with permission; copyright 2002, Global Canopy Programme. the canopy. In these situations, other tools such as ultrasonic detectors and audible sound recordings may be more appropriate. During pre-construction surveys where the local bat fauna and possible colony sizes are unknown, harp-trapping may be used successfully at expected or potential commuting, foraging, drinking, and roosting sites. Prior assessment of local topography, habitat structure (foliage density), and visual or acoustic surveys often can facilitate the selection of a potential capture site and the appropriate deployment of mist nets and harp traps. VISUAL ESTIMATES OF OCCURRENCE AND USE The most common approach to estimate species occurrence and relative abundance of diurnally active bird species is through visual observation (Ralph et al. 1993; Bibby et al. 2000). Quantification of abundance is achieved by sampling an area of interest, usually using line-transect

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Environmental Impacts of Wind-Energy Projects (Burnham et al. 1980) or point-count (Reynolds et al. 1980) sampling. The opportunity to estimate species-specific abundance and behavior is a valuable asset of visual-estimation methods. While this discussion is focused on visual surveys, the theory and application of line-transect and point-count sampling is well suited to nocturnal surveys using radar and other survey methods. Line-transect sampling is typically applied with a line randomly or systematically located on a baseline as the basic sampling unit, and is extended across the study region (Morrison et al. 2001). Objects on either side of the line are recorded based on some rule of inclusion. Line-transect sampling, where an effort is made to count all organisms within a certain distance, is equivalent to a belt transect (or rectangular plot). When surveys are completed according to a standard protocol, without correction for detection bias, the counts can be considered an index of abundance (e.g., Conroy et al. 1988). Line-transect counts are most often considered incomplete when used to estimate absolute abundance, because objects are always missed and the probability of detection must be estimated. The theory and application of this sampling method have received much attention in the scientific literature (e.g., Burnham et al. 1980; Buckland et al. 1993; Manly et al. 1996; Quang and Becker 1996, 1997; Beavers and Ramsey 1998). Line transects are commonly used in bird surveys and are best suited to grassland and shrub-steppe landscapes. Counts from a variable circular plot often are applied as a variation of the line-transect sampling method for estimating the number of birds in an area (Reynolds et al. 1980). The variable circular plot is more useful than the line transect in dense vegetation and rough terrain, where attention may be diverted from the survey and toward simply negotiating the transect line (Morrison et al. 2001). One major advantage of the circular plot is that the observer can allow the subjects of the counts to become accustomed to the observer. In breeding-bird surveys (Reynolds et al. 1980), observers wait several minutes after their arrival at a point before counts begin. Stationary surveys also allow the observer to use both visual and auditory senses to detect birds. Program DISTANCE (Laake et al. 1993) can be used to estimate densities from circular-plot data (see also Rosenstock et al. 2002). Johnson et al. (2000b) described the use of circular plots in the estimate of relative abundance of songbirds from small plots (i.e., 100-m radius) and large birds from larger plots (i.e., 0.8 km) in pre-project studies at the proposed Buffalo Ridge wind-energy facility in southwestern Minnesota. Estimates of Fatalities Fatalities are typically estimated from carcasses located on standardized search plots at turbines, turbine strings, meteorological towers, and refer-

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Environmental Impacts of Wind-Energy Projects ence areas. Search plots at wind-energy facilities may take many shapes from circular to rectangular and typically contain one or more turbines, depending on the spacing of individual turbines. Plot boundaries are delineated at a minimum distance from the turbines, usually based on the size of the turbine. Plots most often are circular or elliptical and are centered on the turbine or turbine string, with the edge of the plot from 30 to 100 m from the nearest turbine. Studies conducted at wind-energy facilities in Oregon (Erickson et al. 2000, 2003b), Minnesota (Johnson et al. 2003a), Wyoming (Young et al. 2003b), and Washington (Erickson et al. 2003a) found most dead bats (more than 80%) within one half the maximum distance from the tip height to the ground from the monopole of the turbine. Arnett (2005) found that 93% of all fatalities at the Mountaineer site and 84% of all the fatalities at Myersdale were found less than or at 40 m from the nearest turbine. At both sites, fewer than 3% of fatalities were found more than 50 m from the nearest turbine. Preliminary evaluation of the distribution of bird carcasses within search plots at the Stateline wind-energy facility in Oregon and Washington (Erickson et al. 2004) suggests that bird carcasses occur further from turbines than bats. However, few birds were located on the periphery of the 63-m-radius search plots, and thus may not represent what actually occurs. At the Mountaineer wind-energy Center in West Virginia, Kerns and Kerlinger (2004) searched out to 60 m from the base of each tower and found birds and bats out to 60 m, although the majority of the carcasses were between 16 and 30 m of the base of turbine towers. The size of search plots should increase with turbine height and diameter of the rotor, using a minimum plot radius approximately equal to diameter of the rotor. Turbine plots to be searched should be selected through a probabilistic sampling process allowing extrapolation to the entire wind-energy facility, after considering variation in topography and type of vegetation present at each site. A systematic selection process with a random start is the most effective method for most sites (Morrison et al. 2001). Personnel trained in proper search techniques typically conduct standardized carcass searches by walking parallel transects within the search plot at a predetermined speed. The cause of death of each carcass should be determined so that fatalities determined not to be related to the wind-energy facility could be discounted. Suggested criteria for identifying bird and bat remains as a bird or bat carcass are: Intact: A carcass that is completely intact, is not badly decomposed and shows no sign of being fed upon by a predator or scavenger. Scavenged: An entire carcass that shows signs of being eaten by a predator or scavenger, or portions of a carcass in one location (e.g., wings, skeletal remains, legs, pieces of skin, etc.).

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Environmental Impacts of Wind-Energy Projects And for birds only: Feather Spot: 10 or more feathers at one location indicating predation or scavenging. Some bat and bird fatalities that are discovered and used in fatalityrate estimation may not be related to wind-energy projects, even though the cause of death cannot be determined. Natural mortality and predation may be responsible, but the level of this background mortality in project areas typically has not been studied. However, background fatalities can be significant. For example, of the 86 avian fatalities found during a four-year study at the Buffalo Ridge wind-energy facility in Minnesota, Johnson et al. (2002) found 31 fatalities (36%) at reference plots. Thus, including background fatalities in calculations of fatality estimates may contribute to overestimation of project-related fatality rates, particularly for smaller species. By contrast, failure to detect bird and bat fatalities outside a designated search area may underestimate fatality rates. Care should be taken to insure that fatality counts at reference and turbine plots are independent. Carcass Survey Biases Carcass searchers no doubt fail to locate some carcasses in search plots. Carcass detection is affected by topography, vegetation within the plot, the size of the search plot, size of the remains of the bird or bat, climate, weather, and observer skill. Observer-detection bias or searcher-efficiency studies are necessary to estimate the percentage of actual bird and bat fatalities that searchers are able to find (Anderson et al. 1999). Typically, these studies are conducted in the same area in which standardized searches occur and thus should include all habitat types. Trials should be conducted in each season in each monitoring year. Search efficiency can be improved when trained dogs are used to find carcasses (Arnett 2006). Estimates of observer-detection rates are used to adjust the number of carcasses found for detection bias. Carcasses also may be removed from search plots before they are searched. This removal is most often by scavengers, but carcasses could be removed by other causes (e.g., human activity, wind). Carcass-removal bias is estimated by conducting experimental studies that estimate the length of time bird and bat carcasses remain in the search area before being removed by scavengers or other means. Carcass-removal studies should be conducted during each season of each monitoring year in the vicinity of, but not on the search plots. Estimates of carcass removal are used to adjust carcass counts for removal bias. Daily searches are essential when evaluating carcass removal of bats. Arnett (2005) estimated that 35% of randomly placed test

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Environmental Impacts of Wind-Energy Projects carcasses were removed with the first 24 hours, 48% were removed within 48 hours, and by the 18th day more than 90% of the test carcasses were removed. The rate of removal for small birds appears to be less than for bats, and weekly or biweekly searches for birds may be adequate. The mean duration for small-bird test carcasses have ranged from 4.69 days at Buffalo Ridge (Johnson et al. 2003a) to 16.7 days at Stateline (Erickson et al. 2004). Scavenging rates may differ seasonally and from year to year following construction of wind-energy facilities. It is possible that scavenging may actually increase because scavengers develop search images and return to sites more frequently once carcasses have been discovered. Carcass-removal and searcher-detection trials use carcasses placed in areas either in plots used in standardized searches (searcher detection trials) or in nearby areas of similar characteristics (carcass removal trials). Carcasses of varying sizes should be placed in most of the habitats being searched. Carcasses of native bats and birds found within the wind-energy facility are ideal for use. The experimental placement of frozen instead of fresh carcasses and using birds as surrogates for bats may contribute to biases in estimated removal rates. Ideally, fresh carcasses should be used in these experiments, because they more closely mimic what occurs near a wind turbine. However, adequate supplies of native bats and birds are seldom available and surrogate carcasses may be used, even though this approach may yield biased results. The efficacy of using surrogate carcasses and fresh versus frozen specimens needs further investigation. STATISTICAL METHODS FOR FATALITY ESTIMATES Methods for estimation of the total number of wind-facility-related fatalities are taken from Erickson et al. (2004) and are based on: Observed number of bat and bird carcasses found during standardized searches for which the cause of death is either unknown or is probably facility-related; Searcher efficiency expressed as the proportion of planted carcasses found by searchers during the entire survey period; and, Non-removal rates expressed as the estimated average probability that a carcass will remain in the study area and be available for detection by the searchers during the entire survey period. Definition of Variables The following variables are used in equations (1-3) below: ci number of carcasses detected at plot I for the study period of inter

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Environmental Impacts of Wind-Energy Projects   est (e.g., one year) for which the cause of death is either unknown or is attributed to the facility n number of search plots k number of turbines searched (includes the turbines centered within each search plot and a proportion of the number of turbines adjacent to search plots to account for the effect of adjacent turbines within the arch plot buffer area) c average number of carcasses observed per turbine per year s number of carcasses used in removal trials sc number of carcasses in removal trials that remain in the study area after 40 days se standard error (square of the sample variance of the mean) ti time (days) a carcass remains in the study area before it is removed t average time (days) a carcass remains in the study area before it is removed d total number of carcasses placed in searcher efficiency trials p estimated proportion of detectable carcasses found by searchers I average interval between searches in days estimated probability that a carcass is both available to be found during a search and is found m estimated annual average number of fatalities per turbine per year, adjusted for removal and observer-detection bias Observed Number of Carcasses The estimated average number of carcasses observed per turbine per year is: (1) Estimation of Carcass Removal Estimates of carcass removal are used to adjust carcass counts for removal bias. Mean carcass-removal time is the average length of time a carcass remains at the site before it is removed: (2) This estimator is the maximum-likelihood estimator assuming the removal times follow an exponential distribution. When the estimate is that no

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Environmental Impacts of Wind-Energy Projects carcasses will be left, the collection of data ends,or is censored. The probability of finding a carcass decreases with time, by convention to the right from the origin,and thus the data are said to be “right-censored.” Erickson et al.(2004) collected trial bird carcasses still remaining at 40 days, yielding censored observations at 40 days. If all trial bird carcasses are removed before the end of the trial, then sc is 0, and is simply the arithmetic average of the removal times. For bats,carcasses were monitored every day for 20 days. Removal rates are estimated by carcass size (small and large) and season. Estimation of Observer-Detection Rates Observer-detection rates (i.e., searcher-efficiency rates) are expressed as p, the proportion of trial carcasses that are detected by searchers. Observer-detection rates are estimated by carcass size and season. Estimation of Facility-Related Fatality Rates The estimated per-turbine annual fatality rate (m) is calculated by: (3) where includes adjustments for both carcass removal (from scavenging and other means) and observer-detection bias assuming that the carcass removal times follow an exponential distribution. Data for carcass removal and observer-detection bias are pooled across the study to estimate . Under these assumptions, this detection probability is estimated by (4) This equation has been independently verified by Shoenfeld (2004). Fatality estimates should be calculated for the species and size class of interest. Erickson et al. (2004) used 7 groups including all birds, small birds, large birds, raptors, grassland birds, nocturnal migrants, and bats. The final reported estimates of fatalities and associated standard errors and 90% confidence intervals can be calculated using bootstrapping (Manly 1997), a computer-simulation technique that is useful for calculating point estimates, variances, and confidence intervals for complex test statistics.

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Environmental Impacts of Wind-Energy Projects 3 TABLE C-5 Neotropical Migrant Species that Have Shown a Negative Population Trend During the Time Period 1978-1987 Common Name Scientific Name Trend, %/year Broad-winged Hawk Buteo platypterus –2.3 Black-billed Cuckoo Coccyzus erythrophthalmus –5.9 Yellow-billed Cuckoo Coccyzus americanus –5.0 Chuck-will’s Widow Caprimulgus carolinensis –2.0 Whip-poor-will Caprimulgus vociferus –0.8 Olive-sided Flycatchera Contopus borealis –5.7 Eastern Wood-peweea Contopus virens –0.7 Acadian Flycatcher Empidonax virescens –1.3 Least Flycatchera Empidonax minimus –0.2 Great crested Flycatchera Myiarchus crinitus –0.3 Veerya Catharus fuscescens –2.4 Swainson’s Thrusha Catharus ustulatus –0.2 Wood Thrusha Hylocichla mustelina –4.0 Gray Catbird Dumetella carolinensis –1.4 White-eyed Vireo Vireo griseus –1.2 Solitary Vireoa Vireo solitarius –0.1 Yellow-throated Vireo Vireo flavifrons –0.9 Blue-winged Warbler Vermivora pinus –1.0 Golden-winged Warblera Vermivora chrysoptera –1.9 Tennessee Warbler Vermivora peregrina –11.6 Northern Parula Parula americana –2.1 Chestnut-sided Warblera Dendroica pensylvanica –3.8 Cape May Warbler Dendroica tigrina –2.3 Black-throated Green Warblera Dendroica virens –3.1 Blackburnian Warblera Dendroica fusca –1.1 Yellow-throated Warbler Dendroica dominica –0.4 Prairie Warbler Dendroica discolor –0.4 Bay-breasted Warbler Dendroica castanea –15.8 Blackpoll Warbler Dendroica striata –6.3 Cerulean Warblera Dendroica cerulea –0.9 American Redstarta Setophaga ruticilla –1.2 Worm-eating Warblera Helmitheros vermivorus –2.0 Ovenbirda Seiurus aurocapillus –1.0 Louisiana Waterthrush Seiurus motacilla –0.4 Kentucky Warblera Oporornis formosus –1.6 Mourning Warblera Oporornis philadelphia –1.6 Common Yellowthroat Geothlypis trichas –1.9 Wilson’s Warbler Wilsonia pusilla –6.5 Canada Warblera Wilsonia canadensis –2.7 Summer Tanager Piranga rubra –0.8 Scarlet Tanagera Piranga olivacea –1.2 Rose-breasted Grosbeaka Pheucticus ludovicianus –1.4 Indigo Bunting Passerina cyanea –0.7 Baltimore Oriole Icterus galbula –2.9 aDenotes species that breed in the Mid-Atlantic Highlands. All others are known from migration records only. SOURCES: Data from Robbins et al. (1989); breeding status follows Hall (1983) and Buckelew and Hall (1994).

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Environmental Impacts of Wind-Energy Projects TABLE C-6 Bird Species of Conservation Concern that Potentially Occupy Ridge-Top Habitats in the Mid-Atlantic Highlandsa Common Name Scientific Name Statusb Bald Eagle Haliaeetus leucocephalus MD-T Peregrine Falcon Falco peregrinus MD-I, VA-T, PA-E Northern Goshawk Accipter gentilis MD-E Olive-sided Flycatcher Contopus cooperi MD-E Alder Flycatcher Empidonx alnorum MD-I, VA-SC Sedge Wren Cistothorus platensis MD-E, VA-SC, PA-E Winter Wren Troglodytes troglodytes VA-SC Appalachian Bewick’s Wren Thyromanes bewickii altus VA-E Golden-crowned Kinglet Regulus satrapa VA-SC Red-breasted Nuthatch Sitta canadensis VA-SC Blackburnian Warbler Dendroica fusca MD-T Blackpoll Warbker Dendroica striata PA-E Magnolia Warbler Dendroica magnolia VA-SC Swainson’s Warbler Limnothlypis swainsonii MD-E, VA-SC Mourning Warbler Oporornis philadelphia MD-E, VA-SC Nashville Warbler Vermivora ruficapilla MD-I Hermit Thrush Catharus guttatus VA-SC Red Crossbill Loxia curvirostra VA-SC aWV has no statutes requiring the development of State Endangered and Threatened species lists. bMD = Maryland, PA = Pennsylvania, VA = Virginia, E = Endangered, T = Threatened, SC = “Species of Special Concern”, I = “In Need of Conservation.” SOURCES: VA (Roble 2006), MD (MDDNR 2003), PA (PAGC 2006). BIRD SPECIES OF CONCERN FOR THE MID-ATLANTIC HIGHLANDS Concern exists regarding the status of a number of bird species potentially occurring in the Mid-Atlantic Highlands. Table C-5 contains a list of neotropical-migrant bird species and Table C-6 contains a list of bird species of conservation concern. Because such species should receive careful attention when considering the impacts of a proposed wind-energy facility for the Mid-Atlantic Highlands. These lists should be updated as the status of these and other species changes.