ArticlePDF Available

Species traits and local abundance affect bird-window collision frequency

Authors:

Abstract and Figures

Studies on bird-window collisions have generally drawn inferences about species’ differential vulnerability from collision tallies. However, this common methodology is potentially biased because the number of collisions may simply reflect prevalence of species at the study site rather than species-specific vulnerability. Building on recent studies of abundance and collision rates, we offered a complementary methodology based on point count data that could be widely applied alongside carcass surveys. Additionally, we broadened our analysis beyond previously applied taxonomic and migratory classifications to include functional classifications of feeding guild, breeding status, and synanthropy. Our null hypothesis was that collision frequencies reflect a species’ or classification group’s prevalence at study sites. To test this possibility, we used collision data collected at three sites in the Research Triangle Area of North Carolina, United States. At one of these sites, Duke University’s Main Campus, we also gathered relative abundances from the local bird community to develop a case study assessment of how background prevalence compared to number of collisions. Using the larger, three-site dataset, we developed an initial picture of collision susceptibility based solely on frequency, the standard practice. Then, by bootstrapping our Duke abundance data, we generated confidence intervals that simulated collision based on chance versus prevalence. We identified several instances where collision tallies produced misleading perception of species-specific vulnerability. In the most extreme case, frequencies from our Triangle Area dataset indicated locally breeding species were highly vulnerable to collisions while our abundance-based case study suggested this same group was actually adept at avoiding collisions. Through our case study, we also found that foliage gleaning was linked to increased risk, and omnivory and ground foraging were associated with decreased risk. Although our results are based on a limited sample, we argue that abundance needs to be incorporated into future studies and recommend point counts as a noninvasive and adaptable alternative to area-searches and mist netting.
Content may be subject to copyright.
VOLUME 12, ISSUE 1, ARTICLE 17
Wittig, T. W., N. L. Cagle, N. Ocampo-Peñuela, R. Scott Winton, E. Zambello, and Z. Lichtneger. 2017. Species traits and local abundance affect
bird-window collision frequency. Avian Conservation and Ecology 12(1):17. https://doi.org/10.5751/ACE-01014-120117
Copyright © 2017 by the author(s). Published here under license by the Resilience Alliance.
Research Paper
Species traits and local abundance affect bird-window collision
frequency
Thomas W. Wittig 1, Nicolette L. Cagle 1, Natalia Ocampo-Peñuela 1,2, R Scott Winton 1,2, Erika Zambello 1,3 and Zane Lichtneger 4
1Nicholas School of the Environment, Duke University, Durham, North Carolina, USA, 2Department of Environmental System
Science, Ecosystem Management, ETH Zürich, Switzerland, 3Choctawhatchee Basin Alliance, Santa Rosa Beach, Florida, USA,
4SAS Institute Inc., Environmental Program, Cary, North Carolina, USA
ABSTRACT. Studies on bird-window collisions have generally drawn inferences about species’ differential vulnerability from collision
tallies. However, this common methodology is potentially biased because the number of collisions may simply reflect prevalence of
species at the study site rather than species-specific vulnerability. Building on recent studies of abundance and collision rates, we offered
a complementary methodology based on point count data that could be widely applied alongside carcass surveys. Additionally, we
broadened our analysis beyond previously applied taxonomic and migratory classifications to include functional classifications of
feeding guild, breeding status, and synanthropy. Our null hypothesis was that collision frequencies reflect a species’ or classification
group’s prevalence at study sites. To test this possibility, we used collision data collected at three sites in the Research Triangle Area of
North Carolina, United States. At one of these sites, Duke University’s Main Campus, we also gathered relative abundances from the
local bird community to develop a case study assessment of how background prevalence compared to number of collisions. Using the
larger, three-site dataset, we developed an initial picture of collision susceptibility based solely on frequency, the standard practice.
Then, by bootstrapping our Duke abundance data, we generated confidence intervals that simulated collision based on chance versus
prevalence. We identified several instances where collision tallies produced misleading perception of species-specific vulnerability. In
the most extreme case, frequencies from our Triangle Area dataset indicated locally breeding species were highly vulnerable to collisions
while our abundance-based case study suggested this same group was actually adept at avoiding collisions. Through our case study, we
also found that foliage gleaning was linked to increased risk, and omnivory and ground foraging were associated with decreased risk.
Although our results are based on a limited sample, we argue that abundance needs to be incorporated into future studies and recommend
point counts as a noninvasive and adaptable alternative to area-searches and mist netting.
Traits spécifiques à l'espèce et abondance affectent la fréquence des collisions d'oiseaux aux fenêtres
RÉSUMÉ. Les études sur les collisions d'oiseaux aux fenêtres infèrent généralement la vulnérabilité d'une espèce à partir des décomptes
de collisions. Toutefois, cette méthodologie fréquemment utilisée est potentiellement biaisée parce que le nombre de collision reflète
simplement la prévalence de certaines espèces au site d'étude plutôt que la vulnérabilité réelle de l'espèce. À partir des récentes études
d'abondance et de taux de collision, nous offrons une méthodologie complémentaire basée sur des recensements ponctuels qui pourrait
être appliquée à large échelle en parallèle avec les décomptes de carcasses. De plus, nous avons élargit nos analyses au-delà des
classifications taxonomiques et migratoires utilisées auparavant, afin d'inclure les classifications fonctionnelles de guilde alimentaire,
statut de reproduction, et le facteur de synanthropie. Notre hypothèse nulle est que la fréquence des collisions reflète une prévalence
d'une espèce ou d'un groupe de même classe au site d'étude. Afin de tester cette possibilité, nous avons utilisé les données de collision
collectées sur trois sites dans la Zone Triangle de Recherche en Caroline du Nord, aux États-Unis. Sur l'un des sites, le Campus Principal
de l'Université de Duke, nous avons aussi amassé les abondances relatives de la communauté locale aviaire, afin de développer une
étude de cas sur la comparaison de la prévalence en arrière-plan et le nombre de collision. Utilisant la banque de donnée des trois sites,
plus vaste, nous avons développé une image initiale de susceptibilité de collision basée seulement sur la fréquence, la méthode courante.
Ensuite, en utilisant le bootstrap sur nos données d'abondance de Duke, nous avons généré des intervalles de confiance simulant les
collisions basées par chance comparé à la prévalence. Nous avons identifié plusieurs instances où les totaux de collisions ont produit
une fausse perception de vulnérabilité spécifique due à l'espèce. Dans les cas les plus extrêmes, nos données de la Zone Triangle indiquèrent
que les espèces se reproduisant localement étaient grandement vulnérable aux collisions, alors que notre étude de cas basée sur
l'abondance suggérait que ce même groupe était adepte à éviter les collisions. À partir de notre étude de cas, nous avons aussi découvert
que les glaneurs de feuillage étaient liés à un risque plus élevé, alors que l'omnivorisme et l'alimentation au sol étaient associés à une
diminution du risque. Malgré que nos résultats soient basés sur un échantillon limité, nous avançons que l'abondance devrait être incluse
dans les études futures et recommandons l'utilisation de recensements ponctuels comme alternative adaptable et non-invasive au-lieu
de d'aires de décomptes ou de filets japonais.
Key Words: carcass survey; classifications; collision vulnerability; local abundance; point count; window strikes
Address of Correspondent: Nicolette L. Cagle, 9 Circuit Drive, Durham, NC , United States, 27708, nicolette.cagle@duke.edu
Avian Conservation and Ecology 12(1): 17
http://www.ace-eco.org/vol12/iss1/art17/
INTRODUCTION
Window collisions are the second largest source of human-caused
avian mortality in North America (Loss et al. 2015), killing an
estimated one billion birds annually (Loss et al. 2014). Window
hazards potentially reduce the North American bird population
by 2 to 9% (Loss et al. 2014), and could have cascading effects on
ecosystems and the goods and services they provide (Longcore
and Smith 2013).
Since the foundational work of Klem in the late 1970s (Klem
1989, Klem 1990a,b), researchers have begun asking a wide range
of questions about this phenomenon: What building qualities
increase collision risk? Are habitat conditions surrounding
buildings relevant? How do collision frequencies vary across
seasons? One question continues to trouble researchers and
remains largely unresolved: Which birds are most susceptible?
An improved understanding of susceptibility would have
significant implications for both collision mitigation and broader
conservation efforts. It could inform collision deterrent methods
and facilitate the integration of window collision threats into bird
conservation frameworks. Collision mortality may have additive
effects on species that are already suffering from habitat loss and
degradation (Klem 2009, 2010). Failing to recognize
compounding relationships among threats may harm species’
long-term survival.
To properly address which groups of birds are most susceptible
to collisions with windows, researchers must first deal with the
confounding effect of local abundance. It is clear that collision
frequencies are at least partly attributable to background
prevalence (Kahle et al. 2016, Sabo et al. 2016). This attribute has
the power to inflate collision frequencies among locally abundant
birds and suppress frequencies among scarcer species,
independent of the degree of inherent susceptibility among these
various groups. Many studies have found it difficult to account
for abundance when characterizing species-specific susceptibility
or have entirely neglected its influence. Of those studies that have
acknowledged this issue, some have offered anecdotal evidence of
relationships between local abundance and collision (Blem and
Willis et al. 1998, O’Connell et al. 2001) and others have
systematically observed bird communities near study sites, but in
limited spatial or seasonal contexts (Dunn 1993, Hager et al.
2008).
Some of the geographically broader investigations of abundance
and vulnerability have come from Arnold and Zink (2011) and
Loss et al. (2014). In these studies, the authors gathered collision
rates from other investigations and compared these values with
population estimates from the North American Breeding Bird
Survey to index the relative vulnerability of species. Although
broadly informative, this approach assumes similarity of local
study site communities and regional scale populations and
introduces the possibility of spurious correlations because of
pseudocorrelation with variables related to those upon which data
was not actually collected (see Schaub et al. 2011 for examples).
To date, only a handful of studies have attempted to explore the
association between local abundance and collisions. Kahle et al.
(2016) collected collision data at a museum building in California
and conducted area search surveys adjacent to the museum
multiple times per week for a year to establish an understanding
of local avifauna abundance. Although their results offered
valuable insight into the relationship between abundance and
collision, the study’s West Coast location means the findings are
difficult to relate to the majority of collision literature, which is
based in the eastern United States. Migratory bird behavior is
very different in eastern North America along the Mississippi and
Atlantic flyways, compared to migration in the western half of
the continent. Sabo et al. (2016) produced a similar study at a zoo
in Virginia, using mist nets to survey local abundance. These
studies represent a major advancement in methodology for bird-
window collision surveys. Yet, these studies have only considered
collision susceptibility in terms of demographics (e.g., age, sex),
taxonomy, and migratory status.
In this study, we expand the general knowledge of collision
vulnerability to inform future mitigation and conservation efforts.
We begin by (1) investigating patterns of taxonomy, residency and
breeding status, guild, and synanthropy on bird-window collision
rates at three sites in North Carolina’s Research Triangle region,
hereafter referred to as the Triangle Study. In the Triangle Study,
we replicate the standard research practice of carcass surveys. We
complement this effort by (2) testing whether collision patterns
are the product of differential susceptibilities among taxonomic
and functional groups, or the product of random chance and
relative abundance, using a one-year case study of point counts
and collisions at Duke University, hereafter referred to as the
Duke Case Study.
We seek to test the following specific hypotheses about bird
susceptibility to window-collisions: (1) Resident birds are less
susceptible to collisions than migratory species because they have
familiarity with windows in their local environment; (2)
Synanthropic birds have low susceptibility to window collisions
either as an adaptation to survive in human-dominated
landscapes or because innate resistance to window-collisions
allowed them to become synanthropic; (3) Birds in foliage-
gleaning foraging guilds will be more susceptible than others
because reflected foliage represents a potential food source and
is a strong attractant.
METHODS
Study areas
We conducted our Triangle Study at three locations in the Raleigh-
Durham-Chapel Hill area of North Carolina, United States (Fig.
1A). At each site, we chose buildings with a wide range of stories,
glass coverage, age, and floor area (Ocampo-Peñuela et al. 2016).
We selected six buildings per site.
Carcass surveys
We conducted carcass surveys for the Triangle Study during 21
days of the peak migration period in fall 2015 (19 September–9
October), following methods described by Hager and Consentino
(2014). One day prior to this period (18 September), we conducted
a clean-up survey to free the study area of lingering carcasses that
would otherwise bias our results. Each day during the subsequent
21-day survey period, two observers independently looked for
dead and stunned birds within 2 m of each building. These
observers removed carcasses and recorded collisions to species
level when the carcass allowed for visual identification, as well as
building name and side (compass direction, i.e., N, S, E, W). We
conducted the surveys in the afternoon, as recommended by
Hager et al. 2012 to reduce impacts of scavengers on the dataset.
Avian Conservation and Ecology 12(1): 17
http://www.ace-eco.org/vol12/iss1/art17/
Fig. 1. (A) Sites for bird window collision study in the Triangle
region of North Carolina, (B) Duke University study site with
sampled buildings highlighted, (C) 1-m resolution EPA land
cover (US EPA 2013), (D) survey points over aerial imagery.
We also conducted an additional carcass survey at Duke
University in spring 2015, cleaning on 31 March 2015, and
surveying from 1 to 21 April following the same methodology
(Hager and Consentino 2014). We only used this data in the Duke
Case Study. (See Ocampo-Peñuela et al. 2016 for further details
of carcass surveys at Duke University, including methodology
and campus description.)
If observers were unable to identify what species collided, we
excluded the observation from our analysis. Scavenging often
reduces carcasses to an unidentifiable state such as a pile of
feathers or partial remains. Our surveys were timed to limit the
impact of scavenging. Nonetheless, unidentified collisions
accounted for 20% and 14% of total collisions in the Triangle
Study and Duke Case Study, respectively.
Further classifications
To investigate the potential influences of taxonomy, behavior, and
life history on bird species susceptibility to window collisions, we
classified species based on taxonomic family, breeding and
migration status, feeding guild and location, and synanthropy.
We defined breeding status as whether or not the species had been
recorded breeding locally (within the Triangle area, including
Durham, Orange, Wake, and Chatham Counties) by expert local
observers from the Chapel Hill Bird Club (Cook 2008, LeGrande
et al. 2016). By using the term “locally breeding,” we did not mean
to indicate individual birds were observed actively breeding in the
study area; our methods did not include the mark and recapture,
territory mapping, or telemetry necessary to glean this detail.
Rather, we applied this term to identify a behavior exhibited by
at least some members of a given species within our study region.
Migration status (binary variable: migratory, year round) was
determined from seasonal, local fluctuations in abundance
reported by Cook (2008). Birds that were not reported or were
only very rarely reported in some seasons, but were common or
abundant in other seasons, were considered migratory. As with
breeding status, this term does not reflect knowledge of individual
birds, but a broader categorization of species behavior in the
Triangle area.
We defined feeding guilds based on González-Salazar et al.’s
(2014) classification. Broad guilds (e.g., insectivore, granivore)
were then subdivided by feeding strategy, feeding location, and
height.
For synanthropy, the degree of positive association with human
environments, we applied Johnston’s (2001) classification of
North American avifauna. Under this classification, bird species
were defined as full synanthropes, casual synanthropes, tangential
synanthropes, or nonsynanthropes. Synanthropy “includes a wide
degree of relationship to humans” from dependence on human
ecology for survival (full), exploitation without dependence
(causal), occasional exploitation (tangential), to no positive
synanthropic relationship (nonsynanthropes; Johnston 2001:50).
Duke case study: point count survey
We complemented our spring and fall carcass surveys at Duke
with relative abundance data gathered from point counts around
Main Campus (Fig. 1B). To assign survey point locations, we used
a stratified random sampling technique, applied in ArcMap 10.3.1
(ESRI 2015). Beginning with 1-m resolution EPA land cover
classification (US EPA 2013), we used a focal calculation to
remove irrelevant features such as trees in parking lots. Duke’s
Main Campus contained four classes: forest, impervious, grass,
and bare earth (Fig. 1C). The last two classes were combined
because of the negligible area of the latter. We limited the
sampling frame for forest and impervious classes to locations with
at least 85% coverage in a 25-m radius and 30% for the much
scarcer grass class. To avoid surveying habitat outside the purview
of Duke, we removed areas 25 m from the Main Campus
boundary from sampling consideration.
We then randomly placed 21 points to the remaining areas, with
the number of points assigned to each class roughly proportional
to their relative area and separated by at least 90 m to improve
independence of observations. The result was 12 forest, 5
impervious, and 4 grass points (Fig. 2D).
A single observer (TW) conducted point counts during the same
peak migration survey periods as the spring and fall 2015 Duke
University carcass surveys. TW visited every point three times
during both survey seasons, altering the order of visitation to
avoid bias. At survey locations, we reported all birds seen or heard
within a 25-m-fixed radius, not counting flyovers (Bibby et al.
2000). We attempted to avoid counting individuals more than
once per visit by maintaining awareness of individual positioning
Avian Conservation and Ecology 12(1): 17
http://www.ace-eco.org/vol12/iss1/art17/
and using a short, 10-minute period of observation. Additionally,
we completed surveys within 2.5 hours of sunrise to take
advantage of higher activity and detectability of birds. We did
not conduct surveys during strong winds or precipitation.
Construction and maintenance projects at Duke required two
alterations to our original survey design. In spring 2015, Duke
University converted approximately 2 ha of forest cover to a water
reclamation pond. We incorporated this water feature and
maintained our ratio of points to cover area by relocating a nearby
forest survey point to the pond shore and reclassifying it as water.
Additionally, between spring 2015 and fall 2015, two survey points
became inaccessible because of construction. We compensated
for this loss by randomly assigning two new survey points for fall
2015 using the same sampling technique. These new points were
similar to the original points in vegetation composition and
structure, as well as degree of development, justifying comparison
across seasons.
Duke case study: analysis of bird-window
collision abundance and susceptibility
To test if species’ local abundance has an effect on number of
collisions at Duke University, we compared the observed rate of
collision in each classification category (e.g., Parulidae, casual
synanthrope, granivore) to a simulated rate for those categories
based on chance and background occurrence rates. This analysis
drew on the point count data from spring and fall 2015 and the
Duke carcass data from those same periods. Our comparison of
random collision used 95% confidence intervals (CIs) based on
distributions of random sampling rates for each bird category in
our point count dataset.
We constructed these random distributions by applying a
bootstrapping sampling procedure to the Duke Main Campus
abundance data in R, v. 3.2.2 (R Development Core Team 2015).
Pulling from a pool of all spring and fall point count observations,
we sampled a number of individuals equal to the number of
collisions observed at Duke during the 2015 spring and fall carcass
surveys. Each individual in the sample pool had an equal
probability of being selected, simulating collision in the absence
of differential vulnerability.
We repeated the sampling 10,000 times and recorded the
proportion of birds sampled from each category after every run.
These 10,000 runs created a frequency distribution of random
sampling rates for each avian category based solely on their
campus abundance. We identified our 95% CIs by pulling out the
275th and 9750th values from the ordered vector of sampling rates
for each bird category. We repeated this procedure on all
classification approaches (e.g., foraging location guild, family,
synanthropy).
We then compared these intervals to the observed rate of collision
among different bird groups. To calculate the observed rates, we
divided the collision frequency in each class by the total number
of collisions. Placing these values alongside the CIs, we noted
whether a class fell below, within, or above the expected rate of
collision. We deemed species with values above the simulated rates
as disproportionately susceptible to collisions and species with
values below as less susceptible to collisions.
RESULTS
Triangle Study frequencies
Between 18 September and 9 October 2015, we recorded 151 birds
colliding with survey buildings at our three study sites in the
Research Triangle Area (Table 1). Among these 138 casualties
(the remaining 13 casualties were not visually identifiable), we
observed 40 species, 14 families, and 4 orders. The vast majority
of collisions were Passeriformes (81%), and the remaining
causalities were nonpasserine orders.
Taxonomy
The Parulidae, Turdidae, and Trochilidae families accounted for
approximately two-thirds of all collisions (Fig. 2A). The
Parulidae had more collisions than Turdidae and Trochilidae
combined. Although the Parulidae collisions represented a wide
diversity of species (15), the Trochilidae consisted of only one,
the Ruby-throated Hummingbird (Archilochus colubris).
Breeding and migration status
Collision frequencies indicated local breeders collided roughly
twice as much as nonlocal breeders (Fig. 2B). Birds that migrate
(i.e., nonyear-round residents) showed an even greater disparity
between its two classes (Fig. 2C). There was an approximately
14:1 ratio of casualties of species known to migrate compared to
year round residents.
Feeding guild
Insectivores collided far more than any other feeding group (Fig.
2D). Nectarivores were also well represented in the collision tally,
but as with the Trochilidae results, this finding was solely
attributable to Ruby-throated Hummingbirds. Of the 114
insectivore collisions, 94 belonged to just 3 subgroups: lower
canopy foliage gleaners, ground gleaners, and upper canopy
foliage gleaners (Fig. 2E).
Synanthropy
Collisions were nearly evenly split between nonsynanthropes and
tangential synanthropes (Fig. 2F). Conversely, the more
synanthropic classes (casual and full) had very few collisions.
Duke case study: local abundance and
collision susceptibility
During carcass surveys at Duke University in spring and fall 2015,
we documented 36 birds, representing 19 species and 11 families.
The majority (72%) of individual casualties classified as
migratory species, 58% were insectivores (22% of which were
lower canopy gleaners), and the majority of birds (89%) were
tangential synanthropes or nonsynanthropic.
During the point count surveys, we recorded 477 birds
representing 40 species and 21 families (Table 2). The five most
frequently observed species were, in decreasing order, Northern
Cardinal (Cardinalis cardinalis, 60 individuals), House Finch
(Haemorhous mexicanus, 51 individuals), Eastern Towhee (Pipilo
erythrophthalmus, 37 individuals), Northern Mockingbird
(Mimus polyglottos, 35 individuals), and Carolina Chickadee
(Poecile carolinensis, 35 individuals). The top 10 most abundant
species accounted for 69% of observations. We observed 17 of the
40 species fewer than four times. These rarer birds included four
Parulidae, two Picidae, and two Sittidae species.
Avian Conservation and Ecology 12(1): 17
http://www.ace-eco.org/vol12/iss1/art17/
Table 1. Taxonomic classification, guild, feeding location, synanthropy (SY), local breeding status (LB), and migration status (MG)
of birds that collided with windows on the three Triangle campuses from September 18 until October 9, 2015.
Common Name Scientific Name Family Total #
Birds
GuildLocationLocal BreedersMigrants§Synanthropy|
Ruby-throated
Hummingbird
Archilochus colubris Trochilidae 16 nectarivore nectarivore L M T
Common Yellowthroat Geothlypis trichas Parulidae 9 insectivore lower canopy foliage
gleaner
L M T
Northern Parula Setophaga americana Parulidae 9 insectivore upper canopy foliage
gleaner
L M X
Red-eyed Vireo Vireo olivaceus Vireonidae 9 insectivore lower canopy foliage
gleaner
L M T
Swainson’s Thrush Catharus ustulatus Turdidae 8 insectivore lower canopy foliage
gleaner
M T
Yellow-bellied
Sapsucker
Sphyrapicus varius Picidae 7 insectivore bark excavator M X
Black-throated Blue
Warbler
Setophaga caerulescens Parulidae 6 insectivore lower canopy foliage
gleaner
M X
Gray-cheeked Thrush Catharus minimus Turdidae 6 insectivore ground gleaner M X
American Redstart Setophaga ruticilla Parulidae 5 insectivore air hawker under
canopy
L M T
Wood Thrush Hylocichla mustelina Turdidae 5 insectivore ground gleaner L M X
Chestnut-sided Warbler Setophaga pensylvanica Parulidae 4 insectivore lower canopy foliage
gleaner
M X
Gray Catbird Dumetella carolinensis Mimidae 4 insectivore ground gleaner L M T
Pine Warbler Setophaga pinus Parulidae 4 insectivore bark gleaner L M X
American Robin Turdus migratorius Turdidae 3 insectivore ground gleaner L M C
Black-and-white
Warbler
Mniotilta varia Parulidae 3 insectivore bark gleaner L M X
Brown Thrasher Toxostoma rufum Mimidae 3 insectivore ground gleaner L M X
Cape May Warbler Setophaga tigrina Parulidae 3 insectivore lower canopy foliage
gleaner
M X
Mourning Dove Zenaida macroura Columbidae 3 granivore ground to undergrowth
gleaner
L T
Ovenbird Seiurus aurocapilla Parulidae 3 insectivore ground gleaner L M X
Summer Tanager Piranga rubra Cardinalidae 3 insectivore upper canopy foliage
gleaner
L M X
Black-throated Green
Warbler
Setophaga virens Parulidae 2 insectivore lower canopy foliage
gleaner
M X
Carolina Chickadee Poecile carolinensis Paridae 2 insectivore lower canopy foliage
gleaner
L T
Philadelphia Vireo Vireo philadelphicus Vireonidae 2 insectivore lower canopy foliage
gleaner
M X
Rose-breasted Grosbeak Pheucticus ludovicianus Cardinalidae 2 insectivore upper canopy foliage
gleaner
M X
Scarlet Tanager Piranga olivacea Cardinalidae 2 insectivore upper canopy foliage
gleaner
L M X
American Goldfinch Spinus tristis Fringillidae 1 granivore lower to upper canopy
gleaner
L M T
Blue Jay Cyanocitta cristata Corvidae 1 omnivore ground forager L M T
Brown-headed
Nuthatch
Sitta pusilla Sittidae 1 insectivore bark gleaner L X
Canada Warbler Cardellina canadensis Parulidae 1 insectivore lower canopy foliage
gleaner
M X
Golden-crowned
Kinglet
Regulus satrapa Regulidae 1 insectivore lower canopy foliage
gleaner
M X
Indigo Bunting Passerina cyanea Cardinalidae 1 granivore ground to undergrowth
gleaner
L M X
Lincoln’s Sparrow Melospiza lincolnii Emberizidae 1 granivore ground to undergrowth
gleaner
M T
Magnolia Warbler Setophaga magnolia Parulidae 1 insectivore lower canopy foliage
gleaner
M X
Northern Cardinal Cardinalis cardinalis Cardinalidae 1 granivore ground to undergrowth
gleaner
L T
Northern Mockingbird Mimus polyglottos Mimidae 1 insectivore ground gleaner L T
Palm Warbler Setophaga palmarum Parulidae 1 insectivore ground gleaner M X
Ruby-crowned Kinglet Regulus calendula Regulidae 1 insectivore lower canopy foliage
gleaner
M T
Tufted Titmouse Baeolophus bicolor Paridae 1 insectivore lower canopy foliage
gleaner
L T
Worm-eating Warbler Helmitheros vermivorum Parulidae 1 insectivore lower canopy foliage
gleaner
M X
Yellow Warbler Setophaga petechia Parulidae 1 insectivore lower canopy foliage
gleaner
M T
Feeding guild and feeding location subclass based on González-Salazar et al. (2014) classification scheme.
Local breeding status is gathered from Cook (2008).
§ Migratory status is drawn from Cook’s (2008) seasonal abundances.
| Synanthropy is based on Johnston’s (2001) appended list. “T” designates tangential synanthrope, “C” designates casual synanthrope, and “X” indicates nonsynanthrope. Local breeders
are indicated by “L” and migrants by “M.”
Avian Conservation and Ecology 12(1): 17
http://www.ace-eco.org/vol12/iss1/art17/
Table 2. Total observations of each species from point counts during spring and fall 2015 at Duke University.
Common Name Scientific Name Family Code
NameMain
Campus
Total
GuildLocationLocal
Breeders§Migrants|Synanthropy
Northern Cardinal Cardinalis cardinalis Cardinalidae NOFL 60 granivore ground to
undergrowth
gleaner
L T
House Finch Haemorhous
mexicanus
Fringillidae HOFI 51 granivore ground to
undergrowth
gleaner
L C
Eastern Towhee Pipilo
erythrophthalmus
Emberizidae EATO 37 granivore ground to
undergrowth
gleaner
L X
Northern Mockingbird Mimus polyglottos Mimidae NOMO 35 insectivore ground gleaner L T
Carolina Chickadee Poecile carolinensis Paridae CACH 35 omnivore arboreal forager L T
American Robin Turdus migratorius Turdidae AMRO 28 insectivore ground gleaner L M C
Gray Catbird Dumetella
carolinensis
Mimidae GRCA 23 insectivore ground gleaner L M T
Tufted Titmouse Baeolophus bicolor Paridae TUTI 22 insectivore lower canopy
foliage gleaner
L X
Blue Jay Cyanocitta cristata Corvidae BLJA 19 omnivore ground forager L M T
Carolina Wren Thryothorus
ludovicianus
Troglodytidae CARW 19 insectivore lower canopy
foliage gleaner
L X
White-throated Sparrow Zonotrichia albicollis Emberizidae WTSP 18 granivore ground to
undergrowth
gleaner
M T
American Crow Corvus
brachyrhynchos
Corvidae AMCR 14 omnivore ground forager L T
Red-bellied Woodpecker Melanerpes carolinus Picidae RBWO 14 insectivore bark excavator L T
Song Sparrow Melospiza melodia Emberizidae SOSP 13 granivore ground to
undergrowth
gleaner
L M T
Downy Woodpecker Picoides pubescens Picidae DOWO 12 insectivore bark excavator L T
European Starling Sturnus vulgaris Sturnidae EUST 9 insectivore ground gleaner L F
Mourning Dove Zenaida macroura Columbidae MODO 8 granivore ground to
undergrowth
gleaner
L T
Pine Warbler Setophaga pinus Parulidae PIWA 7 insectivore bark gleaner L M X
Brown Thrasher Toxostoma rufum Mimidae BRTH 6 insectivore ground gleaner L M X
Wood Thrush Hylocichla mustelina Turdidae WOTH 6 insectivore ground L M X
Rock Pigeon Columba livia Columbidae ROPI 5 granivore ground to
undergrowth
gleaner
L F
American Goldfinch Spinus tristis Fringillidae AMGO 5 granivore lower to upper
canopy gleaner
L M T
Ovenbird Seiurus aurocapilla Parulidae OVEN 5 insectivore ground L M X
Black-and-white Warbler Mniotilta varia Parulidae BAWW 3 insectivore bark gleaner L M X
Red-eyed Vireo Vireo olivaceus Vireonidae REVI 3 insectivore lower canopy
foliage gleaner
L M T
Northern Rough-winged
Swallow
Stelgidopteryx
serripennis
Hirundinidae NRWS 2 insectivore air hawker above
canopy
L M T
Brown-headed Cowbird Molothrus ater Icteridae BHCO 2 granivore ground to
undergrowth
gleaner
L T
Black-throated Green
Warbler
Setophaga virens Parulidae BTNW 2 insectivore lower canopy
foliage gleaner
M X
White-breasted Nuthatch Sitta carolinensis Sittidae WBNU 2 insectivore bark gleaner L M T
Hermit Thrush Catharus guttatus Turdidae HETH 2 insectivore ground gleaner M X
Red-tailed Hawk Buteo jamaicensis Accipitridae RTHA 1 carnivore ground hawker L T
Great Blue Heron Ardea herodias Ardeidae GBHE 1 carnivore freshwater
forager
L T
Blackburnian Warbler Setophaga fusca Parulidae BLWB 1 insectivore upper canopy
foliage gleaner
M X
Yellow-rumped Warbler Setophaga coronata Parulidae YRWA 1 insectivore lower canopy
foliage gleaner
M T
Hairy Woodpecker Picoides villosus Picidae HAWO 1 insectivore bark excavator L T
Northern Flicker Colaptes auratus Picidae NOFL 1 insectivore ground gleaner L M T
Pied-billed Grebe Podilymbus podiceps Podicipedidae PBGR 1 L M T
Spotted Sandpiper Actitis macularius Scolopacidae SPSA 1 M X
Brown-headed Nuthatch Sitta pusilla Sittidae BHNU 1 insectivore bark gleaner L X
Scarlet Tanager Piranga olivacea Thraupidae SCTA 1 insectivore upper canopy
foliage gleaner
L M X
From American Ornithologists Union.
Feeding guild and feeding location subclass based on González-Salazar et al. (2014) classification scheme.
§Local breeding status is gathered from Cook (2008).
|Migratory status is drawn from Cook’s (2008) seasonal abundances.
Synanthropy is based on Johnston’s (2001) appended list. “T” designates tangential synanthrope, “C” designates casual synanthrope, and “X” indicates nonsynanthrope. Local breeders
are indicated by “L” and migrants by “M.”
Avian Conservation and Ecology 12(1): 17
http://www.ace-eco.org/vol12/iss1/art17/
Fig. 2. Frequency of collision victims by (A) family, (B) breeding status, (C) migratory status, (D) feeding guild,
(E) location guild, and (F) synanthropy. Other family = Columbidae (2.6%), Paridae (2.0%), Corvidae (1.3%),
Regulidae (1.3%), Emberizidae (0.7%), Fringillidae (0.7%), and Sittidae (0.7%). Other location = ground to
undergrowth gleaner (5.3%), bark excavator (4.6%), air hawker under canopy (3.3%), ground forager (1.3%), and
lower to upper canopy gleaner (0.7%).
Taxonomy and collision susceptibility
Of the 40 species we recorded during the campus point count
survey, 36 had a collision total on or within their confidence
intervals (CI), meaning their number of collisions could not be
differentiated from chance. However, many of these results (31)
occurred simply because the species was never observed during
the collision survey and their background abundance was too low
to lift their lower CI above zero. Additionally, 11 species collided
with windows, but were not seen or heard during point counts.
Despite these limitations, the CI results provided cases of
noteworthy deviation from expected number of collisions (Fig.
3A). Three species, American Goldfinch (Spinus tristis), Ovenbird
(Seiurus aurocapilla), and Red-eyed Vireo (Vireo olivaceus),
collided more than their abundance-based collision estimates,
indicating susceptibility to collisions. Conversely, one species, the
House Finch, showed a lower than expected number of collisions.
Scaling up to taxonomic family, Parulidae and Vireonidae had
collision numbers above their CI, representing a level of
susceptibility that could not be attributed to chance (Fig. 3B).
However, Vireonidae vulnerability simply reflected the
susceptibility of one species, the Red-eyed Vireo. Paridae offered
a contrasting case of collision, an observed collision number
below the CI. Additionally, the Mimidae had collision numbers
equal to their lower CI, but the family was prevalent enough that
this lower value was not equal to zero. Of the 21 families observed
during point counts, 11 were not detected as collision victims and
had a lower CI of zero. Only two families, Trochilidae and
Regulidae, were recorded in the collision survey, but not in the
point count survey. Six families collided more than zero, but
remained within their confidence intervals, i.e., collided at rates
expected based on abundance, including Cardinalidae, Turdidae,
and Picidae. All taxonomic orders occurred within their
confidence intervals.
Breeding and migration status
Although they accounted for a substantial proportion of
collisions at Duke in 2015 (81%), species with populations that
breed locally still collided less often than expected when factoring
in their local abundance. This result is in contrast to nonlocally
breeding species that collided more than expected based on
background prevalence (Fig. 4A). A similar, though more
pronounced pattern emerged between resident and migratory
species. Year round residents’ collision numbers were well below
the CI and migrants’ well above (Fig. 4B). Migratory species were
disproportionally vulnerable to collisions, regardless of their
abundance.
Feeding strategies
Grouping based on feeding guild indicated that omnivores, which
with the exception of one Blue Jay (Cyanocitta cristata), were
entirely absent from carcass surveys, were abundant enough to be
considered less susceptible to colliding with windows (Fig. 4C).
In the location classification, the ground to undergrowth gleaners
had lower than expected collision numbers (Fig. 4D), despite
relatively high observed numbers of collisions. Conversely,
multiple types of lower to upper canopy foliage gleaners collided
at rates higher than the 95% CI.
Avian Conservation and Ecology 12(1): 17
http://www.ace-eco.org/vol12/iss1/art17/
Fig. 3. Confidence intervals (bars) and observed rates (dots) for
(A) 9 species. The following species were omitted with a lower
confidence interval equal to zero and no collisions during the
Spring and Fall 2015 Duke collision surveys: AMCR, BAWW,
BHCO, BHNU, BLJA, BLWB, BTNW, CACH, CARW,
DOWO, EATO, EUST, GBHE, GRCA, HAWO, HETH,
NOFL, NOMO, NRSW, PBGR, PIWA, RBWO, ROPI,
RTHA, SCTA, SPSA, TUTI, UYRW, WBNU, WOTH, and
WTSP (see Table 2 for AOU codes). (B) 21 families observed
during campus point count survey.
Synanthropy
Our ordinal measure of positive human association did not give
any clear indication of susceptibility or immunity. Casual,
tangential, and nonsynanthropes’ collision numbers all reflected
their prevalence on Duke’s Main Campus. Full synanthropes were
not observed in the carcass survey and were not prevalent enough
to lift their lower CI above zero (Fig. 4E).
DISCUSSION
The findings of the Duke Case Study provide evidence counter
to the hypothesis that collision numbers across species and other
categories were simply a reflection of relative abundances,
corroborating the results of other recent studies (Kahle et al 2016,
Sabo et al. 2016). We witnessed several instances where locally
abundant birds rarely collided and opposite cases where locally
scarce birds frequently collided. Therefore, we conclude that there
are significant differences in a species’ susceptibility to collide
against or avoid windows. These qualities emerged at nearly every
level of classification: species, family, breeding status, migratory
status, feeding guild, and feeding location. The recurrence of
vulnerability and resistance indicates the complex nature of
collisions; they are not reducible to a single behavior or trait, but
are related to diverse and likely interacting factors.
Fig. 4. (A) Comparison of expected and observed collision
rates for local and nonlocal breeders, as defined by Cook
(2008). (B) Similar comparison for migratory status derived
from weekly checklist (Cook 2008). (C) Confidence interval
comparison based on González-Salazar et al.’s guild
classification (2014). Nectarivores were absent from this
comparison despite making up 14% (n = 5) of collisions at
Duke in spring and fall 2015 because they were not observed
during the campus point survey. (D) Finer guild comparison
using González-Salazar et al.’s subclassification related to
feeding location (2014). Guilds were loosely sorted left to right
on foraging height. (E) Comparison of simulated versus
observed collision rates among Johnston’s (2001) synanthropic
classes.
There were also many instances in our analyses of individual bird
groups where we could not find evidence to suggest that the
observed number of collisions was driven by factors other than
chance and abundance. These cases neither disprove the general
role of species traits nor prove an entirely random nature to
window collisions. Instead, these findings underscore the
importance of considering local species prevalence. Kahle et al.
(2016) and Sabo et al. (2016) found many similar instances where
number of collisions was not discernable from chance and
abundance. This observation has major implications for how
collision tallies are considered and any subsequent understanding
of collision vulnerability. Factoring in local abundance provides
Avian Conservation and Ecology 12(1): 17
http://www.ace-eco.org/vol12/iss1/art17/
greater appreciation for the inherent uncertainty behind collision
frequency data in terms of species-specific vulnerability.
Within the context of our case study, there were multiple
occasions where collision frequencies alone did not give enough
information about the collision patterns of a species. For example,
the Northern Cardinal, which accounted for 6% of collisions and
has often been reported as a frequent victim (Dunn 1993, Blem
and Willis 1998, Hager et al. 2008), was actually within the
expected range of collision numbers. Sabo et al. (2016) reported
this same species colliding less often than expected based on their
mist netting captures. Complementing the standard carcass
survey method, we found that the vulnerability of ground to
undergrowth gleaners is better informed by putting number of
collisions in the context of relative local abundance. Although
this group had the third highest number of collisions, it was also
so abundant around Duke’s Main Campus that its collision
numbers were lower than expected, indicating a tendency to avoid
collisions.
Although differences in spatial extent, timing, and survey effort
limited how much direct comparison we could make between the
Triangle Study and Duke Case Study, we did find two major
discrepancies in results worth noting. In the Triangle Study, locally
breeding species appeared to collide disproportionately with
buildings. However, the Duke Case Study showed this same group
actually collided less often than expected. Additionally, the near
absence of full synanthropes on Duke University’s Main Campus
suggested the Triangle Study’s lack of full synanthrope casualties
was not due to any acclimation to urban settings, but to a general
scarcity of these birds.
In addition to illustrating the importance of putting bird collision
data in the context of local species abundance, our results also
indicate categories of birds that appear to be especially vulnerable
to window collisions. For example, the finer guild classification
analysis suggests that the vertical location of foraging affects the
vulnerability of birds. Although leaf gleaners exhibited notably
high numbers of collision relative to their abundances, ground-
based feeders fared as well as chance would predict or better.
Species adapted to foraging under the canopy, like foliage
gleaners, fly through small spaces in the thick, forested understory.
This behavior may increase their vulnerability to window
collisions as they potentially confuse windows for understory
openings or are simply unable to cope with the unfamiliar
obstacles of urban settings.
Additionally, the more transitory groups of birds, migrants and
nonlocal breeders, showed considerable susceptibility to window
collisions in the case study. This finding on migratory status is
also supported by several previous studies (Arnold and Zink 2011,
Loss et al. 2014), including those that accounted for the local
abundances (Kahle et al. 2016, Sabo et al. 2016). These relatively
high numbers of collisions may be due to unfamiliarity with the
local landscape and human structures, though investigation into
the causality underlying these relationships is beyond the scope
of this study. We consider the vulnerability of migrants to be of
particular concern because this group contains many species that
already face a large number of threats such as land development,
invasive species, and climate change (Kirby et al. 2008).
Limitations of analysis
There were several limitations to our survey of campus birds that
may have affected our confidence interval analysis. First, we
assumed that we surveyed at the correct spatial scale to capture
an accurate impression of the potential pool of collision victims.
However, it is possible that birds outside our sampling frame, from
neighboring Duke Forest for example, may have shared some of
the risk of collision with our six surveyed buildings. It is also
possible that abundance at a finer spatial scale could be important
for collisions, for example birds may be susceptible to collisions
because they are attracted to ornamental vegetation surrounding
buildings. Second, we observed high levels of ambient noise at
several survey points. It was difficult in these cases to disentangle
the effect of ambient noise as a distraction to observation and a
deterrent to birds. Third, and possibly most significantly, we did
not count flyovers during our surveys. This technique almost
certainly led to an underestimation of species that forage on the
wing such as hummingbirds, swallows, and hawks. Fourth, we
were not able to carry out scavenging experiments, so our carcass
surveys might be underestimating the number of collisions.
Overall, our analyses are not able to estimate the relative impact
of collisions on species’ populations; our results are a hint of
which species might be most affected, but we recommend detailed
population studies for better risk assessments.
Another phenomenon in the data suggests further limitations.
Ten out of 18 species observed during spring and fall 2015 carcass
surveys at Duke were not observed during point counts. This trend
could be caused by several factors. These species may be so rare
their prevalence is too low for detection with standard point count
methods, but their susceptibility to collisions is high enough to
reveal their presence in the collision survey. Alternatively, species
observed only during the collision survey may be relatively
abundant, but secretive, with low detection probabilities.
Nonetheless, there was substantial and often complete overlap
between the carcass and point count datasets when considered in
the context of our other classification methods.
Finally, it is possible that the susceptibility of various bird groups
may be related to characteristics of the buildings themselves and/
or the habitats immediately proximate to the buildings. In a
previous study assessing relationships between building
characteristics and collisions we found that buildings with large
surface areas of glass contribute disproportionately to collisions
on Duke’s campus (Ocampo-Peñuela et al. 2016). We emphasize
that the bird groups we find to be susceptible to collisions in this
study, are specifically susceptible to the dominant buildings in our
study area. Other types of buildings, such as single-family
residences, may be more threatening to different types of birds.
The presence of feeders at residences has been shown to have a
strong influence on collision risk (Kummer et al. 2016), but we
observed no feeding stations at any of the study buildings
throughout the course of the study.
CONCLUSIONS AND FUTURE DIRECTIONS
Our research demonstrates that local abundance and species traits
together offer a better explanation of collision frequencies than
either factor taken alone. We found evidence for susceptibility to
window collisions among both taxonomic and functional bird
classes, even when accounting for the potentially confounding
Avian Conservation and Ecology 12(1): 17
http://www.ace-eco.org/vol12/iss1/art17/
effect of abundance. We hope other researchers will incorporate
considerations of functional groups into future analyses of
collision vulnerability. Additionally, we recommend conducting
bird surveys in parallel with carcass surveys when evaluating
collision vulnerability in different groups of birds. Once larger
datasets with paired relative abundance and carcass data become
available, we suggest researchers analyze the interactions and
relative influence of the species traits we have linked to collision.
Point counts may be preferable to other bird survey techniques in
this research context. Although mist-net surveys may capture
many of those birds traveling at window level (Sabo et al. 2016)
and area searches may better reveal secretive species (Kahle et al.
2016), point counts are adaptable, easily implemented, and
noninvasive. The flexibility of this survey approach allowed us to
adjust easily for construction, local events, and other
inconveniences likely to be encountered in future suburban and
urban collision studies. Relative to Kahle et al. (2016) and Sabo
et al. (2016), point counts allowed us to develop a comparable
understanding of the influence of local abundance without the
complications of permitting or additional field hours. Ideally,
point counts can be widely and easily adopted alongside studies
of collision vulnerability.
Taking this approach may help limit the amount of disagreement
between studies, creating a more cohesive understanding of
collision vulnerability. This effort must also involve a move toward
consistent definitions of migratory status and other functional
classifications, otherwise future researchers will have difficulty
comparing results across studies. We also suggest that future
research on window collisions begin to consider the year-to-year
variability in collision frequencies. Many studies, ours included,
have only captured a “snapshot” of the problem. Long-term
datasets are needed to assess the annual variation in collision
frequencies. This insight will reveal how reliable one-year studies
are for understanding general patterns of collision. Finally, we
acknowledge a need for greater understanding of the relevant
scales of local abundance, specifically, an empirical definition of
the distance at which birds are at legitimate risk of collision with
a given building. By addressing these issues and adopting these
methodologies, researchers can better understand bird-window
collisions and consequently improve and accelerate mitigation
efforts.
Responses to this article can be read online at:
http://www.ace-eco.org/issues/responses.php/1014
Acknowledgments:
We would like to thank the many volunteers at all campuses who
contributed carcass data to our study. Additional thanks go to Dr.
Dean Urban and Dr. John Poulsen for their guidance on technical
components of this study.
LITERATURE CITED
Arnold, T. W., and R. M. Zink. 2011. Collision mortality has no
discernable effect on population trends of North American birds.
PLoS ONE 6(9):e24708. http://dx.doi.org/10.1371/journal.
pone.0024708
Bibby, C. J., N. D. Burgess, D. A. Hill, and S. H. Mustoe. 2000.
Bird census techniques. Academic Press, San Diego, California,
USA.
Blem, C. R., and B. A. Willis. 1998. Seasonal variation of human-
caused mortality of birds in the Richmond area. Raven 69(1):3-8.
Cook, W. 2008. Chapel Hill Bird Club weekly frequency checklist.
Chapel Hill Bird Club, North Carolina, USA.
Dunn, E. H. 1993. Bird mortality from striking residential
windows in winter. Journal of Field Ornithology 63(3):302-309.
Environmental Systems Resource Institute (ESRI). 2015.
ArcMap 10.3.1. ESRI, Redlands, California, USA.
González-Salazar, C., E. Martínez-Meyer, and G. López-
Santiago. 2014. A hierarchical classification of trophic guilds for
North American birds and mammals. Revista Mexicana de
Biodiversidad 85(3): 931-941. http://dx.doi.org/10.7550/rmb.38023
Hager, S. B., and B. J. Consentino. 2014. Surveying for bird
carcasses resulting from window collisions: a standardized
protocol. PeerJ PrePrints 2:e406v1. http://dx.doi.org/10.7287/
peerj.preprints.406v1
Hager, S. B., B. J. Consentino, and K. J. McKay. 2012. Scavenging
affects persistence of avian carcasses resulting from window
collisions in an urban landscape. Journal of Field Ornithology 83
(2):203-211. http://dx.doi.org/10.1111/j.1557-9263.2012.00370.x
Hager, S. B., H. Trudell, K. J. McKay, S. M. Crandall, and L.
Mayer. 2008. Bird density and mortality at windows. Wilson
Journal of Ornithology 120(3):550-564. http://dx.doi.org/10.1676/07-075.1
Johnston, R. F. 2001. Synanthropic birds of North America.
Pages 49-67 in J. M. Mazluff, R. Bowman, and R. Donnelly,
editors. Avian ecology and conservation in an urbanizing world.
Kluwer Academic, Norwell, Massachusetts, USA. http://dx.doi.
org/10.1007/978-1-4615-1531-9_3
Kahle, L. Q., M. E. Flannery, and J. P. Dumbacher. 2016. Bird-
window collisions at a West-Coast urban park museum: analyses
of bird biology and window attributes from Golden Gate Park,
San Francisco. PLoS ONE 11(1):e0144600. http://dx.doi.
org/10.1371/journal.pone.0144600
Kirby, J. S., A. J. Stattersfield, S. H. Butchart, M. I. Evans, R. F.
A. Grimmett, V. R. Jones, J. O’Sullivan, G. M. Tucker, and I.
Newton. 2008. Key conservation issues for migratory land- and
waterbird species on the world's major flyways. Bird Conservation
International 18(1):S49-S73. http://dx.doi.org/10.1017/s0959270908000439
Klem, D. Jr. 1989. Bird-window collisions. Wilson Bulletin
101:606-620.
Klem, D. Jr. 1990a. Bird injuries, cause of death, and recuperation
from collisions with windows (Heridas, Causas de Muerte y
Restablecimiento de Aves que Chocan con Ventanas). Journal of
Field Ornithology. 61(1):115-119.
Avian Conservation and Ecology 12(1): 17
http://www.ace-eco.org/vol12/iss1/art17/
Klem, D. Jr. 1990b. Collisions between birds and windows:
mortality and prevention (Colisiones de pájaros con ventanas:
mortalidad y prevención). Journal of Field Ornithology. 61
(1):120-128.
Klem, D. Jr. 2009. Avian mortality at windows: the second largest
human source of bird mortality on earth. Pages 244-251 in T. D.
Rich, C. Arizmendi, D. Demarests, and C. Thompson, editors.
Proceedings of the Fourth International Partners in Flight
Conference: tundra to tropics. Partners in Flight, McAllen, Texas,
USA.
Klem, D. Jr. 2010. Sheet glass as a principle human associated
avian mortality factor. Pages 276-289 in S. K. Majumdar, T. L.
Master, M. Brittingham, R. M. Ross, R. Mulvihill, and J.
Huffman, editors. Avian ecology and conservation: a Pennsylvania
focus with national implications. Pennsylvania Academy of
Science, Easton, Pennsylvania, USA.
Kummer, J. A., E. M. Bayne, and C. S. Machtans. 2016. Use of
citizen science to identify factors affecting bird-window collision
risk at houses. Condor 118(3):624-639. http://dx.doi.org/10.1650/
condor-16-26.1
LeGrande, H., J. Haire, N. Swick, and T. Howard. 2016. Birds of
North Carolina: their distribution and abundance. Carolina Bird
Club, Raleigh, North Carolina, USA. [online] URL: http://
ncbirds.carolinabirdclub.org/
Longcore, T., and P. A. Smith. 2013. On avian mortality associated
with human activities. Avian Conservation and Ecology 8(2):1.
http://dx.doi.org/10.5751/ace-00606-080201
Loss, S. R., T. Will, and P. P. Marra. 2015. Direct mortality of
birds from anthropogenic causes. Annual Review of Ecology,
Evolution, and Systematics 46:99-120. http://dx.doi.org/10.1146/
annurev-ecolsys-112414-054133
Loss, S. R., T. Will, S. S. Loss, and P. P. Marra. 2014. Bird-building
collisions in the United States: estimates of annual mortality and
species vulnerability. Condor 116(1):8-23. http://dx.doi.
org/10.1650/condor-13-090.1
O’Connell, T. J. 2001. Avian window strike mortality at a
suburban office park. Raven 72(2):141-149.
Ocampo-Peñuela, N., R. S. Winton, C. J. Wu, E. Zambello, T. W.
Wittig, and N. L. Cagle. 2016. Patterns of bird-window collisions
inform mitigation on a university campus. PeerJ 4:e1652. http://
dx.doi.org/10.7717/peerj.1652
R Development Core Team. 2015. R: a language and environment
for statistical computing, version 3.2.2. R Foundation for
Statistical Computing, Vienna, Austria.
Sabo, A. M., N. D. G. Hagemeyer, A. S. Lahey, and E. L. Walters.
2016. Local avian density influences risk of mortality from
window strikes. PeerJ 4:e2170. http://dx.doi.org/10.7717/
peerj.2170
Schaub, M., M. Kéry, P. Korner, and F. Korner-Nievergelt. 2011.
A critique of ‘Collision mortality has no discernable effect on
population trends of North American Birds.’ PLoS One
Comment. [online] URL: http://journals.plos.org/plosone/article/
comment?id=info%3Adoi%2F10.1371%2Fannotation%2F68b2f3ba-
a22b-499c-ae55-4aaf7013e6b1
U.S. Environmental Protection Agency. 2013. EnviroAtlas - Meter
Resolution Urban Area Land Cover Map for Durham, NC (2010).
In U.S. EPA Office of Research & Development (ORD) - National
Exposure Research Laboratory (NERL), editor. Research
Triangle Park, North Carolina, USA.
Editor-in-Chief: Ryan Norris
Subject Editor: Erin Bayne
... To rank species on their vulnerability to window collision mortality, studies begin with carcass count data which then must be compared to indices of species abundance (Loss et al. 2014, Kahle et al. 2016, Aymí et al. 2017, Wittig et al. 2017, Nichols et al. 2018, Winger et al. 2019, De Groot et al. 2021, Elmore et al. 2021. These studies differ in their spatial scales (e.g., building, city, region, campus, or continental) and timing, leading to the use of different data sources for species abundance (point counts, mist net surveys, breeding bird surveys, or eBird citizen science data), different types of abundance indices (cumulative counts or occurrence days), and also statistical approaches (e.g., linear models of catch, tests of goodness-of-fit). ...
... Prior studies during migration periods typically find that some species are overrepresented in carcass surveys relative to their local or population abundance, suggesting that intrinsic factors play a role (Arnold and Zink 2011, Kahle et al. 2016, Wittig et al. 2017, Nichols et al. 2018, Winger et al. 2019, Elmore et al. 2021. Differential vulnerability to window collision mortality among feeding guilds has been suggested, with higher risk in canopyforaging insectivores than in ground-foraging birds (Wittig et al. 2017), or in insectivores than in non-insectivores (Elmore et al. 2021). ...
... Prior studies during migration periods typically find that some species are overrepresented in carcass surveys relative to their local or population abundance, suggesting that intrinsic factors play a role (Arnold and Zink 2011, Kahle et al. 2016, Wittig et al. 2017, Nichols et al. 2018, Winger et al. 2019, Elmore et al. 2021. Differential vulnerability to window collision mortality among feeding guilds has been suggested, with higher risk in canopyforaging insectivores than in ground-foraging birds (Wittig et al. 2017), or in insectivores than in non-insectivores (Elmore et al. 2021). Such differences are thought to be due to behavioral differences in foraging (darting flights vs. hopping; Wittig et al. 2017). ...
Article
Full-text available
Hundreds of millions of birds are estimated to die annually in North America by colliding with windows, and understanding the species-level correlates of collision mortality is an important step towards mitigation. We used a 16-year window collision dataset for 35 migratory songbird species from Toronto's (Canada) Fatal Light Awareness Program (FLAP) to quantify species differences in vulnerability to urban window collision mortality and potential correlates during the autumn period by applying generalized linear models. To control for annual abundance, we used migration monitoring data from two stations. Our index of vulnerability was the catch ratio, defined as the ratio of annual catch-per-unit effort in each station's mist net program to annual catch-per-unit effort in FLAP. Catch ratios varied among species with Ovenbird (Seiurus aurocapilla), Common Yellowthroat (Geothlypis trichas), and Lincoln's Sparrow (Melospiza lincolnii) being most vulnerable to window collision mortality and Blue-headed Vireo (Vireo solitarius), Yellow-rumped Warbler (Setophaga coronata), and Ruby-crowned Kinglet (Regulus calendula) being least vulnerable. Foraging guild had a minor effect on the catch ratio, but species with a propensity for nocturnal migration had lower catch ratios (greater vulnerability) than those that did not. Based on a subset of species (n = 4) and years (n = 2), hatch-year birds were overrepresented relative to after-hatch-year birds in FLAP compared to the nearby migration monitoring station in 3 of 4 species. This study provides the first ranked list of species vulnerability to urban window collision mortality for songbirds migrating through downtown Toronto, provides evidence that juveniles are more vulnerable to window collision mortality than adults in some species, and highlights the need for more comparative studies of migratory movement behavior to investigate why some species are more vulnerable to urban window collision mortality than others.
... Understanding differences in species' vulnerability to building collisions is central to predicting potential population-level effects of this source of mortality (Loss et al. 2012, Cusa et al. 2015, Elmore et al. 2020), but species with primarily western North American distributions comprised only 4 of 100 species reported to be more vulnerable to collision mortality in the United States (Loss et al. 2014, Elmore et al. 2020. Broad-scale analyses suggest that life history characteristics such as nocturnal migration, insectivory, and preference for forested habitat are most commonly associated with increased vulnerability to collisions (Arnold and Zink 2011, Wittig et al. 2017, Elmore et al. 2020). These traits are not unique to eastern North American species, therefore, the relative absence of western species from lists of species most vulnerable to collision mortality may be an artifact of sampling bias. ...
... Similar to Loss et al. (2014) and Wittig et al. (2017), we found that highly urban-adapted species such as the American Crow, Glaucous-winged Gull, and European Starling were among the least vulnerable species to collisions. This may be due to a greater familiarity with façade features at our study site, as a result of their tendency to perch atop campus buildings. ...
... Although there is anecdotal evidence that the Varied Thrush is prone to collisions with windows (Ching 1993, George 2020, this species has only been reported as an infrequent collider in 2 prior collision studies (Johnson andHudson 1976, Dunn 1993). Forestdwelling birds, such as the Varied Thrush and American Robin, may be more likely to collide with reflected vegetation in windows as a consequence of adaptations to living and foraging in forested environments, such as differences in visual perception and the ability to fly quickly through small gaps in foliage (Klem 1989, Wittig et al. 2017, Elmore et al. 2020). In addition, Varied Thrush flush easily at the approach of humans (George 2020), and panicked flights, e.g., from feeders, is a mechanism thought to increase fatality rates, whereby birds are forced into sudden flight by the abrupt appearance of a predator (Dunn 1993, Bracey et al. 2016. ...
Article
Full-text available
Bird–window collisions are a leading cause of direct anthropogenic avian mortality, yet our state of knowledge regarding this threat relies heavily on eastern North American studies. Seasonal patterns of collision mortality may differ along the Pacific coast, and western North American species remain understudied. We therefore surveyed a stratified random sample of 8 buildings for collisions at the University of British Columbia, Vancouver, Canada over 45-day periods during 2 winters, 1 spring, 1 summer, and 1 fall season between January 22, 2015 and March 15, 2017. After accounting for the rate of scavenging and efficiency of observers in finding carcasses, we estimated that 360 collision fatalities (95% CI: 281–486) occurred over 225 days of collision monitoring. Collision mortality was highest in fall, but in contrast to most published research, collision mortality was intermediate in both winter and spring and was lowest in summer. In winter 2017, we performed point-count surveys to assess whether individual species are disproportionately vulnerable to collisions when accounting for population size and found that the Varied Thrush (Ixoreus naevius) was 76.9 times more likely to collide with buildings, relative to average species vulnerability in winter. To our knowledge, this is the first study to report the Varied Thrush as a species that is disproportionately vulnerable to collisions. Further studies are needed to assess the vulnerability of Western North American species and subspecies, and to determine whether similar patterns of seasonal collision mortality are found elsewhere.
... Another major source of avian mortality in urban areas is bird-building collision (Loss et al., 2014;Pavisse, Vangeluwe, & Clergeau, 2019). Although building-collision has been shown to affect species during migration most (Loss et al., 2014;Wittig et al., 2017), local foliage gleaning species are also susceptible (Wittig et al., 2017). While such species are represented in our dataset too (great tit, blue tit, Eurasian blackcap, common chiffchaff), and buildingcollisions likely contribute to mortality, we cannot directly link it to patterns in our results. ...
... Another major source of avian mortality in urban areas is bird-building collision (Loss et al., 2014;Pavisse, Vangeluwe, & Clergeau, 2019). Although building-collision has been shown to affect species during migration most (Loss et al., 2014;Wittig et al., 2017), local foliage gleaning species are also susceptible (Wittig et al., 2017). While such species are represented in our dataset too (great tit, blue tit, Eurasian blackcap, common chiffchaff), and buildingcollisions likely contribute to mortality, we cannot directly link it to patterns in our results. ...
Article
Full-text available
Urbanization forms one of the most drastic alterations of the environment and poses a major threat to wildlife. The human–induced modifications of the landscape may affect individual's fitness resulting in population declines. Research on how urbanization affects fitness traits has shown mixed results. However, studies typically contrasted data from a single species from few urban and non‐urban sites collected over short timeframes. Examining multiple species across a broad urbanization gradient enables a more robust comparison and understanding of how different species are impacted by urbanization‐knowledge crucial for generating population predictions, which are essential for conservation management. Here, we use data from a nation‐wide citizen science project to examine variation in survival and relative body mass and size (wing length) of common passerine birds, collected along an urbanization gradient in the Netherlands over an 8‐year period. Urbanization was measured as the distance from the city's border and the proportion of impervious surface area. Although the overall association between urbanization and survival was slightly negative, there was support for lower survival closer to the city in three species (chiffchaff Phylloscopus collybita, European robin Erithacus rubecula, European greenfinch Chloris chloris) and higher survival closer to the city in two (great tit Parus major and house sparrow Passer domesticus) of the 11 species examined. The contrasting survival successes among species suggest that ongoing urbanization may lead to shifts in community structure and loss of biodiversity. Impacts of urbanization on relative mass and size also exhibited varying effects, albeit less pronounced, and these effects were not correlated with the effects on survival. This implies that body mass and size cannot be used as indicators for urban‐associated patterns of survival. Our results further imply that effective conservation management targeting bird communities should involve a range of diverse actions, as focusing on single measures is unlikely to simultaneously impact multiple species due to the variation in responses to urbanization.
... The façade and vegetation factors that influence collision risk are expected to vary geographically and seasonally because of variation in bird abundance, community composition, and vulnerability of species across different ecological contexts. Bird behavior, morphological traits, flight velocity, and seasonal-and regionalspecific habitat use and diet can all interact with façade and vegetation characteristics to influence collision risk (Cusa et al. 2015, Wittig et al. 2017, Nichols et al. 2018, De Groot et al. 2021, Elmore et al. 2021a, Samuels et al. 2022; E. K. Jackson, J. A. Elmore, S. R. Loss, B. M. Winger, and R. Dakin, 2020, unpublished manuscript). For example, in the Eastern USA during the peak fall migration (September/October), after accounting for relative abundance, midupper canopy foragers were more susceptible to collisions compared to groups that foraged on the ground or in shrubs (Wittig et al. 2017). ...
... Bird behavior, morphological traits, flight velocity, and seasonal-and regionalspecific habitat use and diet can all interact with façade and vegetation characteristics to influence collision risk (Cusa et al. 2015, Wittig et al. 2017, Nichols et al. 2018, De Groot et al. 2021, Elmore et al. 2021a, Samuels et al. 2022; E. K. Jackson, J. A. Elmore, S. R. Loss, B. M. Winger, and R. Dakin, 2020, unpublished manuscript). For example, in the Eastern USA during the peak fall migration (September/October), after accounting for relative abundance, midupper canopy foragers were more susceptible to collisions compared to groups that foraged on the ground or in shrubs (Wittig et al. 2017). However, in the Toronto region (Eastern Canada), during the migratory seasons (April-May, September-October), susceptibility of foraging guilds depended on landscape context, such that ground foragers were likely to collide with buildings in highly urbanized areas, and foliage gleaners were more likely to collide in areas surrounded by abundant greenery (Cusa et al. 2015). ...
... Although some locally protected species were found, the majority of the victims observed in our carcass survey were common resident birds with no clear or urgent conservation priority at present (Gill et al. 2020, IUCN 2021). However, these results may not reflect relative collision vulnerability among species because total carcass counts are confounded by each species' population size (Schaub et al. 2011, Klem Jr. et al. 2012, Loss et al. 2014, Wittig et al. 2017. To assess the actual species-specific vulnerability of TNB collisions, long-term information on population trends and other mortality causes is needed as well as collision mortality (Schaub et al. 2011). ...
... As there is little organised information about the bird population trends in this region (Kim et al. 2021), it is still beyond our knowledge whether TNB collision affects birds at a species-specific or population-specific scale at this stage. In the current situation, in which there is no regulation of TNB construction to mitigate bird collisions, it is important to investigate the vulnerability of high-risk species (Loss et al. 2014, Wittig et al. 2017, IUCN 2021) and locally protected species (see Table S1 in the online Supplementary Materials for details) to support future actions and national legislation. We considered the PR, DR, and side bias as correction factors. ...
Article
Full-text available
Birds in flight are prone to collide with various transparent or reflective structures. While bird–window collision has been recognised as a critical conservation issue, collision with other transparent structures has been less understood. Noise barriers made of transparent materials are considered critical hazards for birds; however, little is known about the bird mortality they cause. We conducted the first nationwide-scale estimates of bird-collision mortality caused by transparent noise barriers (TNBs) along roads in the Republic of Korea. The total length of existing roadside transparent noise barriers was estimated at 1,416 km nationwide (as of 2018), and it had been increasing exponentially. Based on carcass surveys at 25 sites, daily mortality at the observed barriers was 0.335 ± 1.132 birds/km on average, and no difference in observed mortality was detected between both sides of a single barrier and between road types (i.e. local roads and motorways). Finally, we estimated that approximately 186,000 birds (95% confidence interval: 162,465–204,812 birds) are killed annually by collisions with roadside TNBs. As privately installed barriers were not considered in this study, the actual mortality is likely be higher than our estimates. Thus, collision with TNBs could become an emerging threat to avian conservation, especially in developing and urbanising regions around the world. As such structures are not formally recognised as conservation issues of importance, more systematic surveys aided by citizen science, both for the status of TNBs and bird-collision mortality, are needed in addition to management and mitigation policies.
... Some species suffer disproportionate levels of collision-related mortality relative to their local abundance, indicating that species-specific traits increase the susceptibility of specific taxa (Loss et al., 2014;Wittig et al., 2017;Elmore et al., 2020;De Groot et al., 2021). For example, nocturnal migrants (Arnold & Zink, 2011;Loss et al., 2014) and forest-dwelling insectivorous songbirds appear to have increased vulnerability to collisions (Wittig et al., 2017;Elmore et al., 2020). ...
... Some species suffer disproportionate levels of collision-related mortality relative to their local abundance, indicating that species-specific traits increase the susceptibility of specific taxa (Loss et al., 2014;Wittig et al., 2017;Elmore et al., 2020;De Groot et al., 2021). For example, nocturnal migrants (Arnold & Zink, 2011;Loss et al., 2014) and forest-dwelling insectivorous songbirds appear to have increased vulnerability to collisions (Wittig et al., 2017;Elmore et al., 2020). Omnivorous birds, particularly those that switch to a diet of fruit outside of the breeding season, have also been shown to be more susceptible to collisions during the nonbreeding period (Brown et al., 2019;De Groot et al., 2021). ...
Article
Full-text available
Background In North America, up to one billion birds are estimated to die annually due to collisions with glass. The transparent and reflective properties of glass present the illusion of a clear flight passage or continuous habitat. Approaches to reducing collision risk involve installing visual cues on glass that enable birds to perceive glass as a solid hazard at a sufficient distance to avoid it. Methods We monitored for bird-window collisions between 2013 and 2018 to measure response to bird protection window treatments at two low-rise buildings at the Alaksen National Wildlife Area in Delta, British Columbia, Canada. After 2 years of collision monitoring in an untreated state, we retrofitted one building with Feather Friendly® circular adhesive markers applied in a grid pattern across all windows, enabling a field-based assessment of the relative reduction in collisions in the 2 years of monitoring following treatment. An adjacent building that had been constructed with a bird protective UV-treated glass called ORNILUX® Mikado, was monitored throughout the two study periods. Carcass persistence trials were conducted to evaluate the likelihood that carcasses were missed due to carcass removal between scheduled searches. Results and Conclusions After accounting for differences in area of glass between the two buildings, year, and observer effects, our best-fit model for explaining collision risk included the building’s treatment group, when compared to models that included building and season only. We found that the Feather Friendly® markers reduced collision risk at the retrofitted building by 95%. Collision incidence was also lower at the two monitored façades of the building with ORNILUX® glass compared to the building with untreated glass. Although more research is needed on the effectiveness of bird-protection products across a range of conditions, our results highlight the benefit of these products for reducing avian mortality due to collisions with glass.
Article
Full-text available
Осенью 2023 года в г. Уссурийске Приморского края вновь зафиксирована массовая гибель мигрирующих птиц от столкновений с оконными стеклами. Данной проблеме в 2019 году уже была посвящена наша статья. В новой работе дается оценка гибели птиц от столкновения с оконными стеклами в г. Уссурийске Приморского края осенью 2023 г., а также выявляются новые закономерности столкновения птиц со стеклами. За время наблюдений было отмечено 489 случаев столкновения 12 видов птиц с оконными стеклами, 479 из которых закончились гибелью птицы. Снова, как и в 2019 году, абсолютное большинство пострадавших птиц составили поползни (Sitta europaea).
Article
Full-text available
Background With urbanization, collision with man-made objects, such as buildings and windows, has become a major threat for birds. Because of the transparency and reflection of the glass, birds may not be able to recognize and avoid the glass, which leads them to collide with the buildings or windows. The outcomes of bird-building collisions are often fatal. This phenomenon is relatively well-researched in North America. In the United States alone, bird-building collision is estimated to cause between 300 million to 1 billion birds to die annually, making it one of the most significant direct anthropogenic causes of bird mortality. Despite being recognized as a major bird conservation issue in North America, bird-building collision has received limited attention in China. Progress In this paper, we reviewed and summarized the factors influencing bird-building collisions, including seasonality, weather, building characteristics, the surrounding environment, and bird ecology. In addition, we introduced the current progress in mitigating bird-building collision and methods of conducting bird-building collision research. Finally, we presented the first systemic bird-building collision study in China. Prospects Based on the existing studies, we proposed several suggestions for future research. This includes generating an overall assessment of the bird-building collision phenomenon in China, establishing standards for systematic bird collision survey and data collection, studying the mechanism of bird-building collisions, promoting public awareness, and advocating for eco-friendly urban planning and architectural innovation.
Article
Accelerated rates of urbanization negatively impact natural habitats and biodiversity. Studies of the effects of urbanization on fauna have emphasized taxonomic diversity, but this does not necessarily reflect effects on the evolutionary history of assemblages. Here, we study how urbanization influences phylogenetic diversity (PD) of bird assemblages in a small–medium city in the Central Andes of Colombia. Between 2016 and 2017, we performed bird surveys in 76 urban cells and 23 rural cells around the city. Then, we measured habitat characteristics (e.g. anthropogenic noise level, impervious and forested area) in sampled cells. PD of birds was between 1.37–1.42 MY higher in the rural than in the urban habitat. Within the urban habitat, the PD of birds reduces as impervious area and noise levels increase, while in the urban cells with most forested areas reach the highest PD values. Most of these differences and relationships disappear when we performed similar analysis controlling for differences in species richness. A low turnover of PD between assemblages of birds recorded inside Armenia and its less urbanized surroundings suggest green areas in the study area could mitigate the effects of urbanization in native fauna, and ameliorate connectivity between urban cells.
Chapter
The twentieth-century biologists Jakob von Uexküll and Adolf Portmann both discussed the role of stable cognitive and perceptual schemes in guiding and grounding the perception and behaviour of animals. Given the speed of current environmental change, it is rather common that inherited ancestral cognitive structures and recognition templates are not adequate for the environment an organism is born into. Hence perceptual structures that in stable environments have allowed for rapid recognition and behavioural responses might lead the animal astray and result in a novel ecological mismatch between the organism and the environment. This paper will demonstrate the role of such mismatches in recent species decline and animal welfare problems and discuss the relevance of Uexküll’s and Portmann’s theories for the corresponding research.
Article
Full-text available
Bird-window collisions at houses have been identified as a significant source of mortality for North American birds, but which types of houses and windows are most problematic remains poorly understood. We assessed how neighborhood type, yard conditions, house attributes, and window type influenced collision rates. Data were collected from citizen scientists across Alberta, Canada, who surveyed their houses daily. In relation to the best-fitting model, the yard model explained 58.1% of the explained deviance, the neighborhood model 45.6%, and the house model 42.6%. The factors that had the largest effect for predicting collision risk included season and whether the house was in a rural or an urban area (rural areas in the fall had a 6.0× higher collision risk than urban areas in the winter), the height of vegetation in the front yard of the house (trees >2 stories high increased collision risk by 3.6× compared to houses with no trees), and the presence of a bird feeder (which increased collision risk by 1.7×). This suggests that multiple factors affect collision rates and that the suitability of a yard as bird habitat is likely a key driver. Given that few homeowners are likely to take an approach that reduces the number of birds in their yards, future focus needs to be given to bird-friendly urban design and developing the most effective window deterrents so that collisions can be reduced and birds enjoyed in urban environments.
Article
Full-text available
Up to a billion birds die per year in North America as a result of striking windows. Both transparent and reflective glass panes are a cause for concern, misleading birds by either acting as invisible, impenetrable barriers to desired resources, or reflecting those resources over a large surface area. A high number of window strikes occur during migration, but little is known about the factors of susceptibility, or whether particular avian taxa are more vulnerable than others. We report on a study of window strikes and mist-netting data at the Virginia Zoological Park (Norfolk, Virginia, USA), conducted in the autumn of 2013 and 2014. We focused on three factors likely to contribute to an individual’s predisposition to collide with windows: (i) taxonomic classification, (ii) age, and (iii) migrant vs. resident status. Thrushes, dominated by the partial migrant American Robin ( Turdus migratorius ), were significantly less likely to strike glass than be sampled in mist nets (χ 2 = 9.21, p = 0.002), while wood-warblers (Parulidae) were more likely to strike than expected (χ 2 = 13.55, p < 0.001). The proportion of juveniles striking windows (45.4%) was not significantly different (χ 2 = 0.05, p = 0.827) than the population of juvenile birds naturally occurring at the zoo (48.8%). Migrants, however, were significantly more susceptible to window strikes than residents (χ 2 = 6.35, p = 0.012). Our results suggest that resident birds are able to learn to avoid and thus reduce their likelihood of striking windows; this intrinsic risk factor may help explain the apparent susceptibility of certain taxa to window strikes.
Article
Full-text available
Bird-window collisions are a major and poorly-understood generator of bird mortality. In North America, studies of this topic tend to be focused east of the Mississippi River, resulting in a paucity of data from the Western flyways. Additionally, few available data can critically evaluate factors such as time of day, sex and age bias, and effect of window pane size on collisions. We collected and analyzed 5 years of window strike data from a 3-story building in a large urban park in San Francisco, California. To evaluate our window collision data in context, we collected weekly data on local bird abundance in the adjacent parkland. Our study asks two overarching questions: first-what aspects of a bird's biology might make them more likely to fatally strike windows; and second, what characteristics of a building's design contribute to bird-window collisions. We used a dataset of 308 fatal bird strikes to examine the relationships of strikes relative to age, sex, time of day, time of year, and a variety of other factors, including mitigation efforts. We found that actively migrating birds may not be major contributors to collisions as has been found elsewhere. We found that males and young birds were both significantly overrepresented relative to their abundance in the habitat surrounding the building. We also analyzed the effect of external window shades as mitigation, finding that an overall reduction in large panes, whether covered or in some way broken up with mullions, effectively reduced window collisions. We conclude that effective mitigation or design will be required in all seasons, but that breeding seasons and migratory seasons are most critical, especially for low-rise buildings and other sites away from urban migrant traps. Finally, strikes occur throughout the day, but mitigation may be most effective in the morning and midday.
Article
Full-text available
Understanding and reversing the widespread population declines of birds require estimating the magnitude of all mortality sources. Numerous anthropogenic mortality sources directly kill birds. Cause-specific annual mortality in the United States varies from billions (cat predation) to hundreds of millions (building and automobile collisions), tens of millions (power line collisions), millions (power line electrocutions, communication tower collisions), and hundreds of thousands (wind turbine collisions). However, great uncertainty exists about the independent and cumulative impacts of this mortality on avian populations. To facilitate this understanding, additional research is needed to estimate mortality for individual bird species and affected populations, to sample mortality throughout the annual cycle to inform full life-cycle population models, and to develop models that clarify the degree to which multiple mortality sources are additive or compensatory. We review sources of direct anthropogenic mortality in relation to the fundamental ecological objective of disentangling how mortality sources affect animal populations.
Article
Full-text available
The identification and analysis of ecological guilds have been fundamental to understand the processes that determine the structure and organization of communities. However, reviewing studies that have tried to categorize species into trophic guilds we found many different criteria on which such categorizations are based; consequently, a single species may have several guild designations, limiting its accuracy and applicability. In this paper we propose a classification scheme for trophic guilds as a first step to establish a common terminology. For this purpose we considered 1502 species of mainland birds and mammals from North America (Mexico, USA, and Canada). This classification takes into account 3 main criteria to identify each guild: main food type, foraging substrate and activity period. To determine the trophic guilds and assign species to them, we performed a cluster analysis to classify species according to their similarities in feeding patterns. The resulting hierarchical classification distinguishes 6 main levels of organization, which may occur in different combinations among taxonomic groups and sites: 1) taxon (e. g., birds or mammal), 2) diet (e. g. granivore, insectivore), 3) foraging habitat (e. g., terrestrial, arboreal), 4) substrate used for foraging (e. g., ground, foliage), 5) foraging behavior (e. g., gleaner, hunter), and 6) activity period (e. g., nocturnal, diurnal). We identified 22 guilds for birds and 27 for mammals. This approach aims to group together species that use similar resources in a similar way, and extend the usefulness of this approach to studies intend to analyze the organization of biotic communities.
Article
Full-text available
Collisions of birds with windows were studied by reviewing the literature, collecting data from museums and individuals, monitoring man-made structures, and conducting field experiments. Approximately 25% (225/917) of the avian species in the United States and Canada have been documented striking windows. Sex, age, or residency status have little influence on vulnerability to collision. There is no season, time of day, and almost no weather condition during which birds elude the window hazard. Collisions occur at windows of various sizes, heights, and orientations in urban, suburban, and rural environments. Analyses of experimental results and observations under a multitude of conditions suggest that birds hit windows because they fail to recognize clear or reflective glass panes as barriers. Avian, manmade structural, or environmental features that increase the density of birds near windows can account for strike rates at specific locations. A combination of interacting factors must be considered to explain strike frequency at any particular impact site. The earliest account of a bird hitting a window in North America is by Nuttall (1832:88). He described a Sharp-shinned Hawk (Accipiter striatus) which, in the pursuit of prey, flew through two panes of greenhouse glass only to be stopped by a third. Townsend (1931) described a series of five fatalities of the Yellow-billed Cuckoo (Coccyzus americanus). His paper was the first to suggest that avian vulnerability to windows may be more marked in some species than in others and that specific windows claim a succession of victims. He termed the victims "tragedies" and apparently regarded them as rare, self-destroying incompetents. Picture windows were relatively uncommon through the end of World War II, and there was little reason for concern about their threat to birds. In the postwar period, a building boom stimulated the rapid expansion of the sheet glass industry, and large glass windows were incorporated into the designs of new and remodeled structures. Today, it is not uncommon to find modern buildings that are entirely surfaced with glass. I found 88 papers reporting bird-window collisions, primarily after the mid-1940s (Klein 1979). They document strikes in North America, South America, West Indies, Europe, and Africa, and, with few exceptions are cited in annotated bibliographies on man-caused mortality to birds (Weir 1976, Avery et al. 1980). However, most textbooks and encyclopedia treatments of ornithology present little, if any, description of the fatal hazards that windows pose to birds. The sheet glass industry and its commercial allies appear to be unaware of the problem. On the other hand, I found avian fatalities resulting from window strikes to be common knowledge among the general public. Birds have been reported to strike two general types of windows as classified according to their visual effects on the human eye. These are transparent windows which appear invisible and reflective windows which mirror the facing outside habitat. Two general types of collisions have been described (Wallace and Mahan 1975:456) and both reveal the ability of glass to misinform and misguide at least some birds. One primarily involves birds such as Northern Cardinal (Cardinalis cardinalis) that commonly flutter against picture windows and harmlessly peck the glass during the spring and summer. These birds seldom, if ever, stun or injure themselves or shatter the glass and usually are males defending their territories against their reflected images. In the second type, birds fly into transparent or reflective windows as if unaware of their presence. These collisions often have fatal consequences, and are the subject of this paper. In this paper my objectives are: (1) to propose an explanation for why birds collide with windows, (2) to describe and analyze species, environmental and manmade structural characteristics associated with bird-window collisions in the United States and Canada, and (3) to suggest how these select characteristics account for the differential frequency with which birds strike windows in various man-made structures.
Article
Bird-window collisions cause an estimated one billion bird deaths annually in the United States. Building characteristics and surrounding habitat affect collision frequency. Given the importance of collisions as an anthropogenic threat to birds, mitigation is essential. Patterned glass and UV-reflective films have been proven to prevent collisions. At Duke University’s West campus in Durham, North Carolina, we set out to identify the buildings and building characteristics associated with the highest frequencies of collisions in order to propose a mitigation strategy. We surveyed six buildings, stratified by size, and measured architectural characteristics and surrounding area variables. During 21 consecutive days in spring and fall 2014, and spring 2015, we conducted carcass surveys to document collisions. In addition, we also collected ad hoc collision data year-round and recorded the data using the app iNaturalist. Consistent with previous studies, we found a positive relationship between glass area and collisions. Fitzpatrick, the building with the most window area, caused the most collisions. Schwartz and the Perk, the two small buildings with small window areas, had the lowest collision frequencies. Penn, the only building with bird deterrent pattern, caused just two collisions, despite being almost completely made out of glass. Unlike many research projects, our data collection led to mitigation action. A resolution supported by the student government, including news stories in the local media, resulted in the application of a bird deterrent film to the building with the most collisions: Fitzpatrick. We present our collision data and mitigation result to inspire other researchers and organizations to prevent bird-window collisions.
Chapter
Biological synanthropy refers to human-mediated symbioses. Synanthropic birds are thus avian symbionts of humans. Such birds have a wide degree of relationship to humans, ranging from the almost obligate to the tangential. Avian synanthropy, which includes urbanized and urbanizing birds, is a common ecological relationship, to which at least 25% of North American birds can be referred. Species known to be specialists on early stages of ecological succession, as well as habitat generalists, may be predisposed to be synanthropic. This paper presents certain details on the scope of the behavior and discusses the taxonomic range of birds that can be judged to be synanthropic. Synanthropy may have demographic consequences, such as decreased longevity and increased fecundity.