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Content may be subject to copyright.
J. Raptor Res. 53(4):377–386
Ó2019 The Raptor Research Foundation, Inc.
ENVIRONMENTAL FACTORS AFFECTING THE REPRODUCTIVE
RATE OF URBAN NORTHERN GOSHAWKS
HARUKI NATSUKAWA
1
Graduate School of Environment and Information Sciences, Yokohama, National University, 79-1 Tokiwadai,
Hodogaya-ku, Yokohama-shi, Kanagawa-ken, 240-8501 Japan
KANAME MORI,SHIZUKO KOMURO,TAKASHI SHIOKAWA,AND JUN UMETSU
Wild Bird Society of Japan Kanagawa Branch, 2-8 Sakae-cho, Kanagawa-ku, Yokohama-shi, Kanagawa-ken, 221-
0052, Japan
TOMOHIRO ICHINOSE
Faculty of Environment and Information Studies, Keio University, 5322 Endo, Fujisawa-shi, Kanagawa-ken, 252-
0882, Japan
ABSTRACT.—Urbanization has increased with human population growth and the responses from raptor
species are gaining more attention from both researchers and the public. Northern Goshawks (Accipiter
gentilis) now breed in urban areas in Japan and Europe; however, there are few studies examining the factors
that influence their reproductive rate in urban areas. We investigated the reproductive rate (number of
fledglings per nest) of the Northern Goshawk population in an urbanized area of Japan from 2014 to 2016,
and used a binomial mixture model to examine the relationship between the number of fledglings per nest
and environmental factors such as nesting and foraging environments, anthropogenic disturbance,
predation risk, and intraspecific competition. The goshawk nesting success rate from 2014 to 2016 was
71.6%, with an average reproductive rate of 1.7 fledglings per occupied nest. The percentage of canopy cover
of nesting stands had a significant positive effect on fledgling numbers, and the number of adjacent
occupied nests had a significant negative effect on fledgling numbers. The positive effects of canopy
coverage may be explained by the protection offered by canopy against direct sunlight, wind, and rain. The
negative effect of the adjacent occupied nests may result from an increase in the amount of time and energy
goshawks spent in territory defense, and a decrease in available foraging habitat due to intraspecific
competition.
KEY WORDS:Northern Goshawk; Accipiter gentilis; breeding success;canopy coverage;density effect;interference
competition;reproductive rate;urban.
FACTORES AMBIENTALES QUE AFECTAN LA TASA REPRODUCTIVA DE ACCIPITER GENTILIS EN
´
AREAS URBANAS
RESUMEN.—La urbanizacio´n ha aumentado con el crecimiento poblacional humano. Consecuentemente, se
observa una mayor atencio´ n, por parte del p´
ublico en general y de los investigadores, ala forma en la que las
aves rapaces responden a este feno´ meno. Accipiter gentilis se reproduce actualmente en a´ reas urbanas de
Japo´ n y Europa; sin embargo, son escasos los estudios que examinan los factores que influyen sus tasas
reproductivas en a´ reas urbanas. Entre los a ˜
nos 2014 y 2016 investigamos la tasa reproductiva (n´
umero de
volantones por nido) de una poblacio´n deA. gentilis en un a´rea urbanizada de Japo´ n. Utilizamos un modelo
mixto binomial para examinar la relacio´n entre el n ´
umero de volantones por nido y factores ambientales
tales como los sitios de anidacio´ n y alimentacio´ n, las molestias antropoge´nicas, el riesgo de depredacio´n y la
competencia intraespec´ıfica. El e´ xito reproductor de A. gentilis desde 2014 a 2016 fue 71.6%, con una tasa
reproductiva promedio de 1.7 volantones por nido ocupado. El porcentaje de cobertura del dosel en los
sitios de anidacio´ n tuvo un efecto positivo significativo sobre el n ´
umero de volantones, mientras que el
n´
umero de nidos adyacentes ocupados tuvo un efecto negativo significativo sobre estos. Los efectos positivos
1
Email address: raptorecologist@gmail.com
377
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de la cobertura del dosel pueden explicarse por la proteccio´n que esta ofrece frente a la luz directa del sol, al
viento y a la lluvia. El efecto negativo de los nidos adyacentes ocupados podr´ıa ser resultado del aumento en
la cantidad de tiempo y energ´ıa que los individuos de A. gentilis dedicaron para la defensa del territorio y de
la disminucio´n en la disponibilidad de ha´ bitat de alimentacio´ n debido a la competencia intraespec´ıfica.
[Traduccio´n del equipo editorial]
Successful raptor reproduction requires both a
nesting and foraging habitat (Newton 1979). A good
nesting habitat reduces the risk of predation
(Mainwaring et al. 2014, Anderson et al. 2015),
and creates a suitable microclimate for breeding
(Robertson 2009). The foraging environment is
important for satisfying both parent and nestling
food requirements (Reynolds et al. 2006). The
reproductive rate of raptors is affected by other
environmental factors such as climatic factors (Fair-
hurst and Bechard 2005), artificial disturbance
(Kr¨
uger 2002), intraspecific (Bretagnolle 2008)
and interspecific competition (Kr¨
uger 2002), and
predation (Kr¨
uger 2004). Therefore, to elucidate
factors affecting reproductive rates of raptors, it is
necessary to estimate the correlation between
reproductive rate and various environmental factors.
Increasing urbanization worldwide significantly
affects many animal species (Ramalho and Hobbs
2012). Urbanization has increased with human
population growth, and the responses from species
are gaining more attention from researchers (Bate-
man and Fleming 2012). Urbanization can bring
drastic changes to the behavior and life history of
birds (Dominoni et al. 2013). Sometimes it has a
deleterious effect, such as the extinction or extirpa-
tion of a species or a decrease in population density
(Marzluff and Ewing 2001). Conversely, some
species have expanded their range into urban areas,
not just temporarily, but also to breed (Bird et al.
1996, Boal and Dykstra 2018). Avian responses to
urbanization differ according to species and taxo-
nomic group. Urbanization may provide suitable
conditions for habitation by some raptors due to
reductions in intra- and interspecific competition,
and more abundant prey (Chace and Walsh 2006).
For example, Eastern Screech-Owls (Megascops asio)
breeding in urban areas have higher reproductive
rates than those breeding in rural areas (Gehlback
1996). However, increased risk of disease, chemical
contamination, collision with buildings and vehicles,
and decreased foraging areas have also been
reported (Hager 2009). For example, Eurasian
Kestrels (Falco tinnunculus) breeding in urban areas
have lower reproductive rates than a nearby rural
population (Sumasgutner et al. 2014). The varied
responses of different species to urbanization
underscore the urgent need for more ecological
studies of raptors in urban environments (Morrison
et al. 2016).
The Northern Goshawk (Accipiter gentilis)isa
medium-sized raptor that is widespread in the
northern hemisphere. Typical goshawk breeding
habitat includes remote forested areas that are not
subject to human-induced disturbance (Kenward
2006). Earlier studies on the reproductive rate of the
goshawk, mainly in Europe and the United States,
have been summarized by Kenward (2006). Howev-
er, goshawks have expanded their range to urban
areas in Japan and Europe and have been breeding
in urban environments there (Higuchi et al. 1996,
Rutz et al. 2006b). Urban goshawks’ feeding habits
(W¨
urfels 1994, 1995, Altenkamp 2002, Rutz 2003,
2004, Rutz et al. 2006a), home ranges and space use
(Rutz 2006), foraging strategies (Rutz 2012b),
breeding-site selection (Natsukawa et al. 2017),
reproductive parameters (Solonen 2008, Rutz
2012a, 2012b), and colonization history (Rutz
2008) have been investigated, but studies on the
determinants of their reproductive rate are limited.
Here, we report the results of an investigation of the
reproductive rate of a Northern Goshawk popula-
tion in an urbanized area from 2014 to 2016, in
which we examine the relationship between the
number of fledglings and environmental factors
such as nesting and foraging environments, anthro-
pogenic disturbance, predation risk, and intraspe-
cific competition.
METHODS
Study Area. We studied urban goshawks within 793
km
2
in the Kanagawa Prefecture, central Japan,
which includes Kawasaki City, Yokohama City,
Yamato City, Zama City, Ebina City, Ayase City,
Fujisawa City, Chigasaki City, and Samukawa Town
(Fig. 1; see Natsukawa et al. 2017 for coordinates).
The landscape is generally flat, with rolling hills and
a mean altitude of 159 masl. The climate is mild, with
an average monthly temperature of 15.88C (mean
monthly temperature range: 5.9–26.7). Rainfall is
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Figure 1. Eastern portion of Kanagawa Prefecture, Japan, study area for urban-breeding Northern Goshawks. Black
shading indicates forested area (13.0%), grey indicates open land (11.8%), crosshatch indicates water (2.5%), and white
indicates built-up areas (72.7%).
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high in summer and autumn and lower in winter.
Annual precipitation averages 1689 mm (maximum
monthly average precipitation 234 mm, minimum
monthly average precipitation 55 mm). Land-cover
types in the study area included 13.0% forest, 11.8%
open land (farmland, rice field, and grassland),
2.5% water, and 72.7% built area (paved road,
residential area). Approximately 80% of this area
was classified as Densely Inhabited Districts (DIDs).
A DID refers to a block area (delineated by roads,
rivers, etc., and ranging in size from 3000 to 5000
m
2
) with a population density of 4000 people/km
2
or a similar-sized district of small neighboring
sectors having a total population of 5000. DIDs
are used for distinguishing between urban and rural
areas in Japan.
Surveys of Breeding Goshawks. In 2014–2016, we
investigated all forests in the study area on foot to
find occupied nests of goshawks. We defined
occupied nests as nests with the confirmed existence
of a pair nest-building, copulating, egg-laying, or
rearing young. Following Murase et al. (2015), we
classified nests located within 400 m of a nest from
the previous year as the same breeding site.
To determine the number of fledglings in an
occupied nest, we visited each occupied nest 8 to 12
times, and we used binoculars (123) and a spotting
scope (25–503) to observe the nests. Time per
observation varied from 10 to 40 min, and distance
from the observer to the nest tree varied from 60 to
148 m. We did not conduct these surveys on rainy
days, as we anticipated that visibility would be
compromised. We regarded nestlings that reached
80% of the average age of first flight as fledglings
(Steenhof and Newton 2007), and we calculated
reproductive rate as the number of fledglings per
occupied nest. We defined breeding success as the
proportion of occupied nests at which one or more
nestlings fledged.
Measurements of Potential Covariates. Local
and landscape factors. Following James and Shugart
(1970), we measured canopy coverage within a
radius of 11.3 m from the nest tree. We visually
estimated the canopy coverage in 10% increments.
We determined that a plot of 11.3-m radius was an
appropriate size because our previous surveys of
these forests showed that the vegetation structure
(tree size, number of understory trees and shrubs,
etc.) in the area up to this distance from the nests
clearly differed from other places in the same forest
(see Natsukawa et al. 2017).
We measured landscape-level factors using a land-
cover map (resolution 10 m310 m) of the study area
published by Japan Aerospace Exploration Agency
(JAXA, http://www.eorc.jaxa.jp/ALOS/lulc/jlulc_
jpn.htm), which reflected average land cover from
2006 to 2011. The land-cover map was subdivided
into categories: forest, open land (farmland, rice
fields, and grassland), water, vegetated built-up
lands (total of block areas that have 30% small-
scale vegetation of 900 m
2
), and built-up lands
(total of block areas that have 30% small-scale
vegetation of 900 m
2
).
We plotted a circle of radius 2 km, approximately
the size of a goshawk home range in Japan (Kudo et
al. 2005), around each nest and determined the
percentage of land-cover types in each. Goshawks
inhabiting the surveyed area tended to forage along
forest edges (Natsukawa et al. 2017). Therefore, we
measured the tangent length of forest and open
area, and the tangent length of forest and vegetated
built-up land. In addition, as an index to distur-
bance, we measured the distance from each nest to
the nearest house. For these measurements, we used
GIS software ArcMap 10.3.
Age of female breeders. Molted feathers of goshawks
can be reliably used for sex identification, ageing,
and individual identification without capture (Op-
dam and M¨
uskens 1976). Three age classes (first-
year, second-year, and third-year or older) can be
distinguished by feather shape, coloration and
patterning. We used this method to identify the
age of female breeding birds. In addition, we also
assessed the age of the breeding female bird by
observing the belly feathers with binoculars or scope.
Like molted feathers, this method can be used to
classify ages into three categories (first-year, second-
year, and third-year or older; Morioka et al. 1995).
Intra- and interspecific factors. To investigate the
effect of intraspecific competition, we tallied the
number of known occupied adjacent nests within a
2-km radius of each nest (Table 1). For three nests in
2014, four nests in 2015, and three nests in 2016 that
were on the margin of the surveyed area, it was
possible that there were adjacent occupied nests
outside the study area. Therefore, we did not
measure the potential covariates at these nests.
As an index to the number of potential predators
of goshawk eggs or young, we counted the number
of Large-billed Crows (Corvus macrorhynchos), Carri-
on Crows (C. corone), and Black Kites (Milvus
migrans) within the study area by conducting a spot
census near each nest stand (within 100 m) during
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the time period from incubation (April) to early
nestling-rearing (May). In the spot census, we
counted the number of these species that were seen
within 100 m of the fixed point within 30 min. We
did not conduct the spot census surveys on rainy
days, as we anticipated that visibility would be
compromised.
Weather factors. Climate factors such as tempera-
ture and rainfall influence the reproductive rate of
goshawks (e.g., Fairhurst and Bechard 2005).
Therefore, we calculated average temperature and
average total rainfall in the incubation period
(April) and the nestling period (May–July) of each
year from the meteorological data of the Japanese
Meteorological Agency (http://www.data.jma.go.
jp/obd/stats/etrn/index.php?prec_no¼&block_
no¼&year¼&month¼&day¼&view¼). For the weath-
er information, we used the observation data of the
observatory nearest to each nest.
Statistical Analysis. To help explain the environ-
mental factors affecting reproductive rate (here, the
number of fledglings), we analyzed the data using a
binomial mixture model (Royle 2004). In this
model, it is possible to simultaneously estimate the
number of individuals (the number of fledglings in
this study) and the factors affecting the detection
probability as a function of the covariates. There-
fore, the model provides a powerful framework for
correcting the observation error caused by false
negatives (exist but not observed) and estimating
unbiased true states (Ke´ry and Royle 2016). This
model consists of two equations; a state model
expressing the latent true state and an observation
model expressing measured values including obser-
vation errors. We assumed that the state model
follows a Poisson distribution and the observation
model follows a binomial distribution. The covari-
ates of the state model were local and landscape
factors, age of adult birds, intra- and interspecific
factors, and weather factors. The covariates of the
observation model were the observation time per
each survey and the distance from the survey site to
the nest tree. All covariates used for analysis were
normalized to 0 mean and 1 standard deviation. In
this study, the regression coefficients were estimated
by the maximum likelihood method and models of
combinations of all covariates were created and
ranked based on Akaike information criterion
(AIC). Then, the model with the smallest AIC value
was taken as the best-ranked model (Burnham and
Anderson 2002). To avoid multicollinearity, we
calculated correlation using a combination of all
covariates, and did not use any model including a
combination of covariates with jrj.0.7. The effect
of the covariates was considered significant when 0
was not included in the 95% confidence interval
(Arnold 2010). We used statistical software R version
3.1.1 for all statistical analysis and the package
‘‘unmarked’’ (Fiske and Chandler 2011) to create
the binomial mixture model. In this study, we used
data obtained by pseudo-repeated sampling from
the same breeding site and year. Therefore, we
Table 1. Potential covariates of Northern Goshawk reproductive rate, measured for urban nests in Japan. Sample n¼85
nests (2014–2016).
ENVIRONMENTAL FACTORS UNIT MEAN (SD) RANGE
Distance from nest tree to human residence m 90.5 (57.1) 14.4–201.4
Canopy coverage
a
% 80.1 (30.6) 20.0–100.0
Forest coverage
b
% 14.9 (11.2) 1.5–50.3
Open (field, rice paddy and grass) coverage
b
% 20.3 (13.0) 1.1–46.1
Vegetated built-up land coverage
b
% 20.9 (12.6) 2.0–55.1
Built-up land coverage
b
% 39.1 (18.8) 9.8–85.9
Tangent length between forest and open land
b
km 5.8 (5.4) 0.0–30.5
Tangent length between forest and vegetated built-up land
b
km 4.7 (3.3) 0.1–15.6
Area of forests with nests
b
km
2
0.2 (0.2) 0.0–1.0
Number of adjacent occupied nests
b
nest 0.7 (0.9) 0.0–3.0
Number of predators bird 14.6 (9.8) 2.0–32.0
Average temperature during the incubation period (April) 8C 14.3 (1.5) 13.3–15.7
Average temperature during the nestling-rearing period (May–July) 8C 22.4 (4.2) 18.9–25.9
Total precipitation during the incubation period (April) mm 144.2 (16.6) 88.0–154.5
Total precipitation during the nestling-rearing period (May–July) mm 176.2 (38.2) 103.8–198.2
a
Local-scale variable (11.3-m radius from the nest tree)
b
Landscape-scale variable (2-km radius from the nest tree).
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tested whether there was an effect of territory and
year using a generalized linear mixed model with a
log-link function and Poisson distribution. The
maximum number of fledglings detected at each
breeding site in each year was used as the response
variable, the environmental factors used in the
binomial mixture model were covariates, and
territory and year were included as random vari-
ables. The random variables were assumed to follow
a normal distribution with a mean of zero and a
standard deviation of s or r. The results of this
analysis indicated that the effects of the random
variables were smaller than those of the covariates,
and the results did not differ greatly from those of
the binomial mixture models. Therefore, we did not
consider pseudo-replication in the binomial mixture
model.
RESULTS
Reproductive Rates. We located 31 occupied nests
in 2014, 33 in 2015, and 31 in 2016, for a total of 95
from 2014–2016. All nests in the study were detected
early in the breeding season and goshawks laid eggs
in all occupied nests. Breeding success on the basis
of occupied nests was 71.0% (n¼31) in 2014, 72.7%
(n¼33) in 2015, 71.0% (n¼31) in 2016, and 71.6%
from 2014 to 2016 (n¼95). The average number of
fledglings per occupied nest was 1.7 60.2 in 2014
(mean 6SE, n¼31), 1.7 60.2 in 2015 (n¼33), 1.6
60.3 in 2016 (n¼31), and 1.7 60.3 from 2014 to
2016 (n¼95). The minimum and maximum
number of fledglings per nest in all years was 0
and 4, respectively.
Factors Affecting Reproductive Rate. The 10 nests
on the margin of the surveyed area were excluded
from the analysis as described above, so 85 nests were
used for analysis (Table 1). Most (83 of 85) breeding
females were 3 yr old; the remaining two birds were
2-yr-old females. As a result of model selection, in the
best-ranked model, the state model included canopy
coverage of the nest stand and the number of
adjacent occupied nests within a 2-km radius, and
there were no covariates included in the observation
model (Table 2). Both covariates of the state model
had statistically significant effects (Table 2). Greater
canopy coverage had a large positive effect on the
number of fledglings, while a greater number of
adjacent occupied nests had a small negative effect
(Fig. 2, Table 2). In contrast, no factors affecting the
detection probability could be specified.
DISCUSSION
We found that canopy coverage of the nest stand
and the number of the adjacent occupied nests were
significantly related to reproductive rate (Fig. 2,
Table 2). In addition, our analytical technique
considered the false negative errors often found in
ecological survey data by explicitly modeling the
detection probability. Therefore, the results of this
study should be less biased than those of studies
applying traditional statistical methods that do not
consider detection probability (Ke´ry et al. 2013).
The positive effect of canopy coverage of the nest
stand may have been due to the protection it offers
nestlings and adults from rainfall and increased
temperature due to direct sunlight. Maximum
temperature (Reynolds et al. 2017) and precipita-
tion (Fairhurst and Bechard 2005) had negative
effects on the reproductive rate of goshawks
elsewhere. A closed canopy is thought to create a
microclimate that is more favorable for breeding
than an open canopy (e.g., McGrath et al. 2003).
Peregrine Falcons (F. peregrinus; Anctil et al. 2014)
and Cape Vultures (Gyps coprotheres; Pfeiffer et al.
2017) also have high reproductive rate in locations
with physically protected nests. The early to middle
portions of the goshawk nestling-rearing period
(May–June) in the study area has the most rainfall,
whereas the later part of the nestling-rearing period
(the beginning of July) has the highest temperatures
of the year, with strong direct sunlight. Nest
locations that minimize the adverse effects of rain
Table 2. Determinants of breeding success analyzed using the binomial mixture model. Model with the smallest AIC is
shown. The estimate is the intercept or regression coefficient. Lower is the 95% confidence interval lower limit value.
Upper is the 95% confidence interval upper limit.
MODEL PARAMETER ESTIMATE LOWER UPPER
State (Intercept) 0.34 1.19 0.52
State (Canopy coverage) 1.42 0.44 2.39
State (Number of neighbor nests) 1.13 1.66 0.59
Detection (Intercept) 4.01 3.26 4.76
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and warm temperatures may enhance reproductive
rate. In Japanese urban areas, because of the decline
of forest management, canopy coverage is increas-
ing, providing more suitable nesting habitats.
Furthermore, trees that may hinder the flight of
goshawks are also increasing in potential nest stands.
Goshawks in urban areas prefer nest stands in forest
environments that do not hinder flight, rather than
areas of high canopy coverage (Natsukawa et al.
2017). In the current study, some goshawks used
nesting environments where the canopy coverage
was low, even though these areas were associated
with lower reproductive rates.
The significant negative effect of the number of
adjacent occupied nests on reproductive rate suggests
density effects, such as a decrease in the number or
size of foraging sites and an increase in the time-cost
for territory defense due to an increase in individual
interference (intraspecific competition). This latter is
termed the interference competition hypothesis and
is considered to be the main factor linked to the
density effect (Both 1998). In fact, three pairs of
goshawks that we observed extensively, stayed around
their own nests until sunset after the retreat of an
invading individual goshawk (n¼8 occurrences of
this behavior among three nest sites). During those
periods of vigilance, the nestlings were not fed at all
(H. Natsukawa unpubl. data). Goshawk populations
breeding in urban areas generally breed at a higher
density than populations breeding in rural areas in
Europe (Rutz et al. 2006b). Breeding goshawks are
highly territorial and the nearest neighbor distance
(NND) has little variability in areas where the
environment is uniform (Rutz et al. 2006b). However,
the forests in urbanized areas tend to be fragmented,
and NND has greater variability. Goshawks inhabiting
the study area select breeding sites where there is
both forest and open space (Natsukawa et al. 2017),
and NND can be as low as approximately 700 m in
such sites. Urbanization of the study area is increas-
ing, and forest and open areas each make up
approximately 10% of the study area (see Methods).
In urban areas where nesting and foraging sites are
limited, density effects may occur because goshawk
pairs are already breeding at a high density. The
frequency of individual interference in raptors is
closely related to NND (Newton 1979). Other raptors
such as Ospreys (Pandion haliaetus; Bretagnolle et al.
2008) and White-tailed Eagles (Haliaeetus albicilla;
Heuck et al. 2017) have decreased reproductive rates
due to intraspecific interference competition.
In addition to direct interference as a cause of the
density effect, the habitat heterogeneity hypothesis
may also explain decreasing breeding success as
density increases. This hypothesis posits that breed-
ing density and breeding success are not directly
related (Rodenhouse et al. 1997), but instead high-
quality breeding sites are occupied first according to
Figure 2. Relationships between the reproductive rate (number of fledglings per occupied nest) and covariates of the
best-ranked binomial mixture model for Northern Goshawks in an urbanized area from 2014 to 2016 (n¼85 nests). (A)
indicates the effect of the number of neighboring nests, and (B) shows the effect of canopy coverage. Black lines are fitted
values. Grey lines represent 95% confidence intervals. Variable descriptions in Table 1.
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the ideal despotic distribution (Fretwell and Lucas
1969), with lower-quality breeding sites occupied
later. As breeding density increases, the number of
individuals breeding in low-quality breeding sites will
increase, and thus overall reproductive rate will
decrease. It has been suggested that the habitat
heterogeneity theory explains, at least in part, the
reproductive rate of goshawks (Kr¨
uger and Lind-
stro¨m 2001) and other raptors such as Eurasian
Sparrowhawks (A. nisus; Newton 1991) and Spanish
Imperial Eagles (Aquila adalberti; Ferrer and Dona´zar
1996). However, in our study, the number of
fledglings produced in all nests located in areas
with particularly high density (e.g., seven nests in the
southwestern part of our study area with an average
NND of about 1.2 km) was either one or zero per
nest. This result, which differs from that of Kr ¨
uger
and Lindstro¨m (2001), suggests that interference
competition, rather than habitat heterogeneity,
influences the reproductive rate of goshawks.
Our study suggested that the high canopy coverage
had a significant positive influence on the reproduc-
tive rate of goshawks and the density effect (likely due
to interference competition) had a negative influ-
ence on the reproductive rate of goshawks. We were
unable to investigate the relationship between food
availability and reproductive rate, as has been studied
elsewhere (e.g., Salafsky et al. 2005), due to a lack of
prey data. We acknowledge that food availability is
likely an important variable in the analysis of factors
influencing reproductive rate, as it is in other raptor
species (e.g., Terraube et al. 2012, Therrien et al.
2014), and we encourage other researchers to
investigate this aspect of urban goshawk ecology.
Studies on urban-breeding goshawks are much less
common than studies of populations breeding in
conventional habitats (Rutz et al. 2006b), and
additional data are needed to strengthen the
comparison among populations in different habitats
(Rutz 2006).
ACKNOWLEDGMENTS
We are deeply grateful to the editors and referees for
carefully reading our manuscript and for giving useful
comments. This study was supported by a research study
support project in 2014 by Bird Research (an NPO; http://
www.bird-research.jp/1_event/aid/kifu.html).
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