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Collision Mortality Has No Discernible Effect on Population Trends of North American Birds

  • Todd W. Arnold ,

    arnol065@umn.edu

    Affiliation Department of Fisheries, Wildlife, and Conservation Biology, University of Minnesota, St. Paul, Minnesota, United States of America

  • Robert M. Zink

    Affiliation Bell Museum and Department of Ecology, Evolution and Behavior, University of Minnesota, St. Paul, Minnesota, United States of America

Collision Mortality Has No Discernible Effect on Population Trends of North American Birds

  • Todd W. Arnold, 
  • Robert M. Zink
PLOS
x

Abstract

Avian biodiversity is threatened by numerous anthropogenic factors and migratory species are especially at risk. Migrating birds frequently collide with manmade structures and such losses are believed to represent the majority of anthropogenic mortality for North American birds. However, estimates of total collision mortality range across several orders of magnitude and effects on population dynamics remain unknown. Herein, we develop a novel method to assess relative vulnerability to anthropogenic threats, which we demonstrate using 243,103 collision records from 188 species of eastern North American landbirds. After correcting mortality estimates for variation attributable to population size and geographic overlap with potential collision structures, we found that per capita vulnerability to collision with buildings and towers varied over more than four orders of magnitude among species. Species that migrate long distances or at night were much more likely to be killed by collisions than year-round residents or diurnal migrants. However, there was no correlation between relative collision mortality and long-term population trends for these same species. Thus, although millions of North American birds are killed annually by collisions with manmade structures, this source of mortality has no discernible effect on populations.

Introduction

Habitat destruction, overexploitation, climate change and the creation of manmade obstacles have been identified as the major threats to migrating animals [1], especially birds [2]-[4]. Habitat destruction is unquestionably the most important anthropogenic threat to biodiversity [5], but habitat loss does not directly cause mortality among mobile organisms, rather displaced organisms suffer higher mortality or lower fecundity when they are forced into suboptimal habitats [6]. For North American birds, the major anthropogenic sources of mortality include predation by house cats, poisoning, and collisions with windows, communication towers, high-tension wires and motor vehicles [7]. Buildings and towers do not represent absolute barriers to avian migration in the same way that dams impede upstream movements by anadromous fish or fences restrict movements of wild ungulates [1], but such structures increase the mortality risk to migrating birds [8]. Evans Ogden [8] estimated that 70% of migrant birds in eastern North America migrate through at least one major metropolitan area during each migration event. Nocturnal migrants frequently collide with skyscrapers after becoming disoriented by building lights, especially during inclement weather [8], and birds making migratory stopovers in urban areas are especially prone to collision with low-level windows as they forage in unfamiliar environments [8][10]. Eastern North America also has >60,000 communication towers >60m tall and documented kills of migratory birds at individual towers have ranged from 80 to 3,200 birds per year [7], [11].

Despite widespread public attention and more than five decades of research, measures of anthropogenic sources of mortality for North American birds remain speculative. Estimates of total collision mortality from communication towers in North America range from 0.94 to 50 million birds annually [11], [12], whereas estimates of collision mortality with windows range from 3.5 million up to 5 billion birds annually [9], [10], [12]. Using the most frequently cited median estimates of 25 million mortalities from collisions with towers [11] and 1 billion mortalities from collisions with windows [9], these two mortality sources in aggregate represent 21% of the estimated breeding population of 4.9 billion North American landbirds [13].

In this paper, we develop a novel method for assessing the potential impact of a given mortality source on population dynamics that does not require a precise estimate of total mortality, which would be difficult if not impossible to obtain for most migratory wildlife. Our method uses comparative data, including species-specific measures of mortality, relative abundance, and long-term population trends. We utilize long-term records of avian mortality from communication towers [14] and urban buildings [8] combined with population estimates and trend data from the North American Breeding Bird Survey [13], [15] to test the hypothesis that these two mortality sources have influenced population trends among North American birds.

Results

Our analysis was based on 180,832 mortalities of 188 species from 39 different communication towers and 62,271 mortalities of 147 species from three different cities for building collisions (Figure S1). For both communication towers and buildings, there were five species that comprised >5% of the total mortalities, with only one species (ovenbird, Seiurus aurocapillus) among the top five in both data sets. However, total body counts reveal little about relative mortality risk for each species because they are potentially confounded by variation in population size (range: 40,000 to 220 million) and for towers by potential range overlap with monitored collision sites (range: 2 to 39). The correlation between log10 building mortalities (m) and log10 population size (N) was highly significant (r = 0.57, P<0.0001, n = 147), as was the correlation between log10 tower mortalities and log10 population size (r = 0.43, P<0.0001, n = 188) (Figure 1). Tower collisions were additionally affected by overlap with collision sites (S); multiple regression: log10(m+1)  =  -3.52[SE 0.73] + 0.54[SE 0.35]*log10(N) + 1.06[SE 0.35]*log10(S) (R2 = 0.22, F3,186 = 26.12, P<0.0001). To estimate relative vulnerabilities among species, we forced regression coefficients for population size and site overlap to their theoretical values of +1.0 [16] and calculated residuals for each species: relative vulnerability  =  log10(m+1) – Y – [log10(N+1) – X1] - [log10(S+1) – X2], where Y is mean log10 mortalities (buildings: 1.672, towers: 1.698), X1 is mean log10 population size (buildings: 6.651, towers: 6.618), and X2 is mean log10 collision sites (1.539; towers only).

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Figure 1. Collision mortality of eastern North American landbirds with towers and buildings as a function of population size.

Data are from 39 communication towers (top) and three sets of urban buildings (bottom) and each datum represents a single species. Trend lines pass through geometric mean (X,Y) with a slope of 1, so that residuals are measures of relative mortality risk to tower and building collision. The top 5 “super colliders” and “super avoiders” on each figure are labeled; for avoiders the lists from top to bottom correspond to open symbols from left to right along the X-axis.

https://doi.org/10.1371/journal.pone.0024708.g001

These residuals represent relative collision vulnerability, which varied enormously among species. For buildings, the top five species (“super colliders”) were 25 to 57 times more likely to collide with a building than expected by chance (Fig. 1; Table S1). By contrast, the bottom five species of super avoiders were 105 to 208 times less likely to collide with a building than expected by chance. For towers, super colliders were 96 to 236 times more likely to collide than expected by chance, whereas super avoiders were 222 to 688 times less likely to collide. Only two species identified as super colliders based on relative collision vulnerability were also among the top five species based on simple body counts (swamp sparrow at buildings, bay-breasted warbler at towers; for scientific names see Table S1). Black-throated blue warblers were super colliders at both buildings and towers, whereas cliff swallows and horned larks were super avoiders for both structure types.

There was a strong taxonomic component to collision vulnerability. For 13 avian families that contributed five or more species to the tower collision data, relative vulnerability varied significantly among families (F12,132 = 12.47, P<0.0001) with wood warblers (Parulidae, n = 36) averaging 18-fold greater vulnerability and swallows (Hirundinidae, n = 6) averaging 54-fold lower vulnerability (Table S2). Taxonomic effects were also prominent for building collisions (F12,101 = 9.88, P<0.0001), with wood warblers and swallows once again representing the extremes. Although there were notable differences between towers and buildings in relative vulnerabilities for some species, residuals from the two data sets were highly correlated (r = 0.60, P<0.0001, n = 147; see Figure S2) indicating that most species had similar vulnerability to both mortality sources.

Vulnerability to tower collision varied according to migration distance (F2,185 = 16.64, P<0.0001). Species migrating long distances to the Neotropics were 17.3 times more likely to collide with towers than were non-migrants, whereas short-distance migrants were 2.3 times more likely to collide. Migration strategy played a lesser role for building collisions (F2,144 = 3.53, P = 0.03), with Neotropical and short-distance migrants being 3.5 and 2.4-fold more likely to collide with buildings than non-migrants. Timing of migration flights was also important for both data sets (towers: F2,165 = 36.71, P<0.0001; buildings: F2,131 = 31.40, P<0.0001), with nocturnal migrants averaging 30.1 (towers) and 10.9 (buildings) times greater vulnerability than diurnal migrants

Most surprisingly, for 177 species with available data on population trends, there was no correlation between relative collision vulnerability with communication towers and annual rate of population change (Figure 2: r = −0.017, P = 0.83). For buildings there was a weak positive correlation, such that species that collided most frequently with buildings were more likely to exhibit population increases (Figure 2: r = 0.154, P = 0.06, n = 138). We acknowledge that collision mortality is unlikely to be the sole source of population decline, but our analysis had substantial power to detect even partial effects of collision mortality on population change. Using observed variances and sample sizes from the tower and building analyses, respectively, we had 80% power to detect real annual population declines of 0.35 or 0.47% per year associated with 10-fold increases in collision mortality. Alternatively, our analyses had 80% power to detect factors that explained as little as 4.1% of the observed variation in population trends for tower data and 5.2% of the variation for building data.

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Figure 2. Long-term annual population trends of eastern North American landbirds versus relative collision vulnerability with towers and buildings.

Data are from communication towers (top, n = 177) and buildings (bottom, n = 138), with each datum representing a single species. No trend data were available for 11 mostly far-northern species. One outlier not shown in top graph (Bewick's wren: 0.32, −12.6), but trend line and statistics include this species.

https://doi.org/10.1371/journal.pone.0024708.g002

Discussion

Although migrant birds were at greater risk of collision mortality with buildings and towers, our analyses suggest that this conspicuous source of mortality has had no discernible effect on long-term population dynamics among North American landbirds, and this finding was robust to all of the statistical adjustments that we employed. At worst, collision mortality could be described as an added burden for populations already in decline for other reasons, and our list of super colliders (Table S1) includes two such species: golden-winged warbler and Bachman's sparrow, but the list of super colliders also includes two species that are increasing significantly [15].

Simply documenting what species are killed and in what frequencies does not identify whether a particular threat constitutes an additive source of mortality. Even if only 100 million North American birds die annually from collisions with structures [7]-[9], it would seem to be a serious source of mortality. However, many birds are abundant and have high reproductive potentials. For example, ovenbirds are among the top species encountered at most collision sites [8], but the population estimate for ovenbirds is 24 million [13]. At one of the longest monitored collision sites, 15,987 ovenbirds collided with a TV tower during a 38-year monitoring period [17], for an average of 420/yr. To reach a 10% annual mortality level, ovenbirds would need to encounter over 5,500 sites like this tower, but average kill of ovenbirds at several other sites we examined was ∼80 per year. And even this level of mortality might not have population consequences; North American waterfowl hunters annually harvest 10–15% of the fall mallard (Anas platyrhynchos) population with only modest impact on subsequent population size [18]. Most avian collision mortality occurs during fall migration [8], [11], [19], when annual populations are at their zenith. If bird populations are ultimately limited by habitat availability [6], collision mortality will be largely compensatory to natural sources of mortality.

These conclusions need not prevent the deployment of simple design solutions that can greatly reduce avian collision mortality at manmade structures. In particular, shorter towers with flashing lights can minimize collision risk at communication towers [20], [21], whereas turning out lights during peak migratory periods and minimizing vegetation near glass building faces can minimize collisions with buildings [22], [23]. Nevertheless, our analysis suggests that such activities will not halt population declines among North American migratory birds.

The methods we developed in this analysis are well suited to birds due to continental monitoring efforts that provided detailed information on population size and trends [13], [15], but the methods could be easily modified for less-studied taxa using categorical trends (i.e. increasing, stable, declining). We believe that many poorly quantified conservation threats, ranging from topics as diverse as house cat predation [24], wind towers [11] and bushmeat consumption [25], could be assessed using similar methodology.

Materials and Methods

Our analysis was based on existing summaries of birds that accidentally killed themselves by colliding with towers or buildings, and does not require approval by an Institutional Animal Care and Use Committee under official guidelines of the University of Minnesota.

Tower collision data were obtained from a summary of 47 studies from 39 separate sites in eastern North America [14]. We compiled data on landbird collisions with urban buildings from three unpublished data sets: Chicago, Illinois (D. Willard, pers. comm.) [26]; Toronto, Ontario (www.flap.org) [8]; and New York, New York (www.nycaudubon.org) [23]. We assume that monitored sites were representative of potential collision sites throughout eastern North America. Sites were not randomly selected, but monitored towers were widely dispersed throughout eastern North America and relative collision vulnerability was consistently and positively correlated between pairs of towers (see Figure S1, Appendix S1). For the three building sites, correlations of relative collision vulnerability among sites were 0.47, 0.59 and 0.83. Although more data on window collisions would have been desirable, we believe our data to be broadly indicative of collision mortality at any random sample of towers or buildings in eastern North America. Moreover, the strong correlation between tower vulnerability and building vulnerability suggests that we have adequately measured collision risk for most species (Figure S2).

Our methods assume no pronounced biases among species in carcass detection probabilities. Previous studies have documented underestimation of collision mortality due to failure to find carcasses in dense vegetation, scavenging of carcasses by predators and movement away from collision sites by injured birds [7], [8], [11], [23]; however, we are not aware of any studies that have shown detection biases to vary among species. We presume there may be modest detection biases in carcass surveys (see Appendix S1), but that they are trivial in comparison to the massive differences in relative collision vulnerability that we documented.

For communication towers, we quantified the number of collision sites that were within the breeding, migratory or wintering range of each bird species for use as a covariate [14], [27], [28]. For buildings, we restricted the data to species occurring regularly at all three collision sites [27], [28] and standardized each site to 20,000 total mortalities to give each site equal weighting. We used range maps to categorize migration strategy as long-distance (Neotropical), short-distance or partial/non-migratory [27], [28]. Data on timing of migration (primarily diurnal, primarily nocturnal, both or unknown) were obtained from Birds of North America species accounts [28].

Estimated population sizes [13] were based on the North American Breeding Bird Survey (BBS) adjusted for the proportion occurring east of 100° longitude (for tower analyses) or east of the Mississippi River (for buildings). For the tower and building data we also included 38 and 16 species, respectively, that were not recorded as mortalities but were at risk based on range overlap with collision sites [27], [28]. Population trends (1966–2009) were based on recent hierarchical models for the entire eastern BBS region [15], which was our area of inference for collision mortality. Although there is undoubtedly sub-regional variation in population trends among some species of eastern North American landbirds, 55.8% of the total variation in population trends among 11 different Bird Conservation Regions (BCRs) was attributable to species (nested ANOVA, F168,1153 = 10.89, P<0.0001), with the remaining 44.2% of variation comprising real regional variation plus sampling variation. Our sample of 39 communication towers was distributed throughout the entire eastern BBS region (Figure S1), but our analysis of building sites was more limited so we conducted additional analyses based only on the Bird Conservation Regions that included Chicago, Toronto, and New York and obtained similar results (Appendix S1).

To derive species-specific measures of per-capita collision risk we regressed log10 total collision mortality (using log10(X+1) to account for zeros) against log10 population size to derive species-specific measures of per-capita collision risk. Because there was unknown error in both Y and X, neither ordinary least squares (OLS) nor reduced major axis (RMA) regression provides an unbiased estimate of the true slope [16]. Instead we fixed the slope at its theoretical value of +1.0 (i.e., all other things being equal, a 10-fold increase in abundance should lead to a 10-fold increase in collision mortality) and used OLS and RMA regression for verification. We used a similar approach for tower data by concurrently regressing log10 mortalities against log10 population size and log10 number of collision sites exhibiting range overlap with the species in question. We treated species as statistically independent data points for most analyses and analyzed data using general linear models in Program SAS [29]. For analyses involving ecological covariates (e.g., migration distance) that might be similar among closely-related species due to shared evolutionary histories, we used phylogenetic methods [30] (see Appendix S1).

Supporting Information

Figure S1.

Map of approximate locations of communication towers (red dots) and downtown buildings (larger blue dots) used in assessment of collision mortality for eastern North American landbirds. Tower sites were redrawn from Shire et al. [14].

https://doi.org/10.1371/journal.pone.0024708.s001

(PDF)

Figure S2.

Relative vulnerability to collision with towers (i.e., residuals from Fig. 1a) versus buildings (Fig. 1b). With the exception of 3 labeled outliers that had modest vulnerability to buildings but avoided towers, collision risk at towers was a good proxy for collision risk at buildings, and vice versa.

https://doi.org/10.1371/journal.pone.0024708.s002

(TIFF)

Table S1.

List of North American landbird species that collide most frequently with towers (T1-T5) and buildings (B1-B5) (the “super colliders”), as well as the top five super avoiders (T188-184, B147-143).

https://doi.org/10.1371/journal.pone.0024708.s003

(PDF)

Table S2.

Taxonomic variation in collision risk for families of North American birds.

https://doi.org/10.1371/journal.pone.0024708.s004

(PDF)

Acknowledgments

We thank Dave Willard of The Field Museum for sharing unpublished data from the McCormick Place building in Chicago. K. Vicars, H. Vazquez-Miranda, C.-M. Hung, S. Lanyon, B. McKay, D. Andersen, D. Alstad, A. Jones, E. Roche and two anonymous reviewers provided either helpful discussion or comments on earlier drafts.

Author Contributions

Conceived and designed the experiments: TWA RMZ. Analyzed the data: TWA. Wrote the paper: TWA RMZ.

References

  1. 1. Wilcove DS, Wikelski M (2008) Going, going, gone: is animal migration disappearing? PLoS Biology 6: 1361–1364.DS WilcoveM. Wikelski2008Going, going, gone: is animal migration disappearing?PLoS Biology613611364
  2. 2. Robbins CS, Sauer JR, Greenberg RS, Droege S (1989) Population declines in North American birds that migrate to the Neotropics. Proc Natl Acad Sci USA 86: 7658–7662.CS RobbinsJR SauerRS GreenbergS. Droege1989Population declines in North American birds that migrate to the Neotropics.Proc Natl Acad Sci USA8676587662
  3. 3. Sanderson FJ, Donald PF, Pain DJ, Burfield IJ, van Bommel FJ (2006) Long-term population declines in Afro-Palearctic migrant birds. Biol Cons 131: 93–105.FJ SandersonPF DonaldDJ PainIJ BurfieldFJ van Bommel2006Long-term population declines in Afro-Palearctic migrant birds.Biol Cons13193105
  4. 4. Møller AP, Rubolini D, Lehikoinen E (2008) Populations of migratory bird species that did not show a phenological response to climate change are declining. Proc Natl Acad Sci USA 105: 16195–16200.AP MøllerD. RuboliniE. Lehikoinen2008Populations of migratory bird species that did not show a phenological response to climate change are declining.Proc Natl Acad Sci USA1051619516200
  5. 5. Myers N, Mittermeier RA, Mittermeier CG, da Fonseca GAB, Kent J (2000) Biodiversity hotspots for conservation priorities. Nature 403: 853–858.N. MyersRA MittermeierCG MittermeierGAB da FonsecaJ. Kent2000Biodiversity hotspots for conservation priorities.Nature403853858
  6. 6. Rappole JH, McDonald MV (1994) Cause and effect in population declines of migratory birds. Auk 111: 652–660.JH RappoleMV McDonald1994Cause and effect in population declines of migratory birds.Auk111652660
  7. 7. Erickson WP, Johnson GD, Young DP Jr (2005) A summary and comparison of bird mortality from anthropogenic causes with an emphasis on collisions. USDA Forest Service Gen Tech. Rep. pp. PSW–GTR-191.WP EricksonGD JohnsonDP Young Jr2005A summary and comparison of bird mortality from anthropogenic causes with an emphasis on collisions.USDA Forest Service Gen Tech. RepPSWGTR-191
  8. 8. Evans Ogden LJ (1996) Collision course: the hazards of lighted structures and windows to migrating birds. Lincoln, NE: University of Nebraska Press. 53 p.LJ Evans Ogden1996Collision course: the hazards of lighted structures and windows to migrating birds.Lincoln, NEUniversity of Nebraska Press53
  9. 9. Klem D Jr (1990) Collisions between birds and windows: mortality and prevention. J Field Ornithol 61: 120–128.D. Klem Jr1990Collisions between birds and windows: mortality and prevention.J Field Ornithol61120128
  10. 10. Hager SB, Trudell H, McKay KJ, Crandall SM, Mayer L (2008) Bird density and mortality at windows. Wilson J Ornithol 120: 550–564.SB HagerH. TrudellKJ McKaySM CrandallL. Mayer2008Bird density and mortality at windows.Wilson J Ornithol120550564
  11. 11. Drewitt AL, Langston RHW (2008) Collision effects of wind-power generators and other obstacles on birds. Ann NY Acad Sci 1134: 233–266.AL DrewittRHW Langston2008Collision effects of wind-power generators and other obstacles on birds.Ann NY Acad Sci1134233266
  12. 12. Banks RC (1979) Human related mortality of birds in the United States. U.S. Dept. of the Interior, Special Scientific Report – Wildlife No. 215 p.RC Banks1979Human related mortality of birds in the United States.U.S. Dept. of the Interior, Special Scientific Report – Wildlife No215
  13. 13. Rich TD, Beardmore CJ, Berlanga H, Blancher PJ, Bradstreet MSW, et al. (2005) Partners in Flight North American landbird conservation plan. Ithaca, NY: Cornell Lab of Ornithology.TD RichCJ BeardmoreH. BerlangaPJ BlancherMSW Bradstreet2005Partners in Flight North American landbird conservation plan. Ithaca, NY: Cornell Lab of Ornithology.Available: http://www.partnersinflight.org/cont_plan/via the Internet. Accessed 2011 Jun 10. Available: http://www.partnersinflight.org/cont_plan/via the Internet. Accessed 2011 Jun 10.
  14. 14. Shire GG, Brown K, Winegrad G (2000) Communication towers: a deadly hazard to birds. Washington, DC: American Bird Conservancy. 23 p.GG ShireK. BrownG. Winegrad2000Communication towers: a deadly hazard to birds.Washington, DCAmerican Bird Conservancy23
  15. 15. Sauer JR, Hines JE, Fallon JE, Pardieck KL, Ziolkowski DJ Jr, Link WA (2011) The North American Breeding Bird Survey, Results and Analysis 1966-2009. Laurel, MD: US Geological Survey.JR SauerJE HinesJE FallonKL PardieckDJ Ziolkowski JrWA Link2011The North American Breeding Bird Survey, Results and Analysis 1966-2009. Laurel, MD: US Geological Survey.Available: http://www.mbr-pwrc.usgs.gov/bbs/via the Internet. Accessed 2011 Jun 3. Available: http://www.mbr-pwrc.usgs.gov/bbs/via the Internet. Accessed 2011 Jun 3.
  16. 16. Warton DI, Wright IJ, Falster DS, Westoby M (2006) Bivariate line-fitting methods for allometry. Biol Rev 81: 259–291.DI WartonIJ WrightDS FalsterM. Westoby2006Bivariate line-fitting methods for allometry.Biol Rev81259291
  17. 17. Kemper C (1996) A study of bird mortality at a west central Wisconsin TV tower from 1957-1995. Passenger Pigeon 58: 219–235.C. Kemper1996A study of bird mortality at a west central Wisconsin TV tower from 1957-1995.Passenger Pigeon58219235
  18. 18. US Fish & Wildlife Service (2010) Adaptive harvest management: 2010 hunting season. Washington, DC: U.S. Department of Interior. 59 p.US Fish & Wildlife Service2010Adaptive harvest management: 2010 hunting season.Washington, DCU.S. Department of Interior59
  19. 19. Crawford RL, Engstrom RT (2001) Characteristics of avian mortality at a north Florida television tower: a 29-year study. J Field Ornithol 72: 380–388.RL CrawfordRT Engstrom2001Characteristics of avian mortality at a north Florida television tower: a 29-year study.J Field Ornithol72380388
  20. 20. Longcore T, Rich C, Gauthreaux JA Jr (2008) Height, guy wires, and steady-burning lights increase hazard of communication towers to nocturnal migrants: a review and meta-analysis. Auk 125: 485–492.T. LongcoreC. RichJA Gauthreaux Jr2008Height, guy wires, and steady-burning lights increase hazard of communication towers to nocturnal migrants: a review and meta-analysis.Auk125485492
  21. 21. Gehring J, Kerlinger P, Manville AM II (2009) Communication towers, lights, and birds: successful methods of reducing the frequency of avian collisions. Ecol Applications 19: 505–514.J. GehringP. KerlingerAM Manville II2009Communication towers, lights, and birds: successful methods of reducing the frequency of avian collisions.Ecol Applications19505514
  22. 22. Kousky C (2004) A building less bright. Terrain.org 15.C. Kousky2004A building less bright. Terrain.org 15.Available: http://www.terrain.org/articles/15/kousky.htm via the Internet. Accessed 2011 Jul 8. Available: http://www.terrain.org/articles/15/kousky.htm via the Internet. Accessed 2011 Jul 8.
  23. 23. Klem D Jr, Farmer CJ, Delacretaz N, Gelb Y, Saenger PG (2009) Architectural and landscape risk factors associated with bird-glass collisions in an urban environment. Wilson J Ornithol 121: 126–134.D. Klem JrCJ FarmerN. DelacretazY. GelbPG Saenger2009Architectural and landscape risk factors associated with bird-glass collisions in an urban environment.Wilson J Ornithol121126134
  24. 24. Lepczyk CA, Mertig AG, Liu J (2003) Landowners and cat predation across rural-to-urban landscapes. Biol Cons 115: 191–201.CA LepczykAG MertigJ. Liu2003Landowners and cat predation across rural-to-urban landscapes.Biol Cons115191201
  25. 25. Brashares JS, Arcese P, Sam MK, Coppolillo PB, Sinclair ARE, et al. (2004) Bushmeat hunting, wildlife declines, and fish supply in West Africa. Science 306: 1180–1183.JS BrasharesP. ArceseMK SamPB CoppolilloARE Sinclair2004Bushmeat hunting, wildlife declines, and fish supply in West Africa.Science30611801183
  26. 26. MacMynowski DP, Root TL (2007) Climate and the complexity of migratory phenology: sexes, migratory distance, and arrival distributions. Int J Biometeorol 51: 361–373.DP MacMynowskiTL Root2007Climate and the complexity of migratory phenology: sexes, migratory distance, and arrival distributions.Int J Biometeorol51361373
  27. 27. National Geographic Society (1987) Field guide to the birds of North America. Washington, DC: National Geographic Society. National Geographic Society1987Field guide to the birds of North America.Washington, DCNational Geographic Society
  28. 28. Poole A, ed. The birds of North America online. Cornell Lab of Ornithology and American Ornithologists' Union.Poole A, ed. The birds of North America online. Cornell Lab of Ornithology and American Ornithologists' Union.Available: http://bna.birds.cornell.edu/bna/via the Internet. Accessed 2011 Jun 10. Available: http://bna.birds.cornell.edu/bna/via the Internet. Accessed 2011 Jun 10.
  29. 29. SAS Institute (2009) SAS 9.2 for windows. Cary, NC: SAS Institute Inc. SAS Institute2009SAS 9.2 for windows.Cary, NCSAS Institute Inc
  30. 30. Grafen A (2006) A user's guide to the SAS implementation of the phylogenetic regression, version 0.7. Oxford, UK: University of Oxford. A. Grafen2006A user's guide to the SAS implementation of the phylogenetic regression, version 0.7.Oxford, UKUniversity of Oxford