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Cite this article: Greig EI, Wood EM, Bonter
DN. 2017 Winter range expansion of a
hummingbird is associated with urbanization
and supplementary feeding. Proc. R. Soc. B
284: 20170256.
http://dx.doi.org/10.1098/rspb.2017.0256
Received: 7 February 2017
Accepted: 6 March 2017
Subject Category:
Ecology
Subject Areas:
behaviour, ecology, evolution
Keywords:
Anna’s hummingbirds, bird feeding,
Calypte anna, climate change, housing density,
migration
Author for correspondence:
Emma I. Greig
e-mail: eig9@cornell.edu
Electronic supplementary material is available
online at rs.figshare.com.
Winter range expansion of a
hummingbird is associated with
urbanization and supplementary feeding
Emma I. Greig1, Eric M. Wood1,2 and David N. Bonter1
1
Cornell Laboratory of Ornithology, 159 Sapsucker Woods Road, Ithaca, NY 14850, USA
2
Department of Biological Sciences, California State University Los Angeles, Los Angeles, CA 90032, USA
EIG, 0000-0002-8900-538X; DNB, 0000-0003-1768-1941
Anthropogenic changes to the landscape and climate cause novel ecological
and evolutionary pressures, leading to potentially dramatic changes in the
distribution of biodiversity. Warm winter temperatures can shift species’ dis-
tributions to regions that were previously uninhabitable. Further, urbanization
and supplementary feeding may facilitate range expansions and potentially
reduce migration tendency. Here we explore how these factors interact to
cause non-uniform effects across a species’s range. Using 17 years of data
from the citizen science programme Project FeederWatch, we examined the
relationships between urbanization, winter temperatures and the availability
of supplementary food (i.e. artificial nectar) on the winter range expansion
(more than 700 km northward in the past two decades) of Anna’s humming-
birds (Calypte anna). We found that Anna’s hummingbirds have colonized
colder locations over time, were more likely tocolonize sites with higher hous-
ing density and were more likely to visit feeders in the expanded range
compared to the historical range. Additionally, their range expansion mirrored
a corresponding increase over time in the tendency of people to provide nectar
feeders in the expanded range. This work illustrates how humans may alter
the distribution and potentially the migratory behaviour of species through
landscape and resource modification.
1. Introduction
The increase in temperatures globally has allowed many species to colonize
regions that were previously inhospitable [1]. This has led to widespread changes
in species’ distributions, particularly poleward range shifts [1–8]. Concurrently,
urbanization is changing biodiversity in dramatic ways, such as by reducing
the number of species in urban areas and shifting the composition towards
generalists [9,10]. Climate change and urbanization may interact and lead to
non-uniform consequences across a species’s range. For example, urban micro-
climates at range margins may facilitate geographical expansion [11,12] or
reduced migratory behaviour [13– 16]. This climate-tempering effect of urbaniz-
ation may be related to the local retention of heat in urban areas (‘heat island
effect’) [17], increased availability of non-native fruit, seeds or flowers that
provide food throughout the winter [18], or increased availability of supple-
mentary food (e.g. seed, suet, meat or nectar) [19– 21]. Interactions between
urbanization and climate change may make both effects even more pronounced
and impactful to species’ distributions [11,22].
Supplementary feeding is an aspect of urbanization that has the potential to
affect both the distribution and behaviour of avian taxa on a broad geographical
scale [19– 21,23–27]. Up to half of households in the United States, United King-
dom and Australia have been estimated to offer supplementary food to wild birds
[28]. The ecological and evolutionary impacts of this widespread hobby are poten-
tially vast; for example, many species show increased reproductive success in
response to supplementary food [20,24]. Other potential consequences of sup-
plementary feeding include increased winter survival and decreased migration
&2017 The Author(s) Published by the Royal Society. All rights reserved.
tendency, documented in a few species of birds and even mam-
mals [29– 33]. This possible consequence of supplementary
feeding has not been explored in nectivorous birds, despite a
pattern of northward winter range expansions observed in
several North American hummingbirds [34– 37].
The Anna’s hummingbird (Calypte anna) provides a case
study in which to investigate the relative contributions of cli-
mate, urbanization and supplementary feeding on potential
changes in migratory behaviour and resulting shifts in range.
This species has shown a significant northward winter range
expansion over the past two decades (figure 1) [38 – 40]. The
first record in Alaska was in 1971 [38], and there is now a con-
siderable post-breeding movement northward into Canada
and Alaska [41]. Historically, Anna’s hummingbirds at the
northern limits of their range would move south for winter
and return the following spring to breed. Now many individ-
uals overwinter and presumably breed at these northern
latitudes, potentially eliminating or shortening their south-
ward movement [40]. Because Anna’s hummingbirds are
small (5– 6 grams) and require reliable, daily access to food
to maintain their high metabolism, the northern edge of
their winter range is likely to be limited by both temperature
and nectar availability [42,43]. The cause of their winter expan-
sion remains speculative, but may be driven by warming
winter temperatures, increased urbanization or increased
winter supplementary feeding [35].
Here, we quantitatively documented the range expansionof
the Anna’s hummingbird using an occupancy modelling
framework [44] and data from Project FeederWatch, a long-
term citizen science programme [45]. We used climate data,
urbanization indices and estimates of supplementary feeding
prevalence from 1997– 2013 to test two alternative hypotheses
for explaining their winter range expansion: (i) that the
expansion has been facilitated by increased availability of
anthropogenically provided habitat or food, or (ii) that the
expansion is due solely to warming winter temperatures.
Specifically, we predicted that if anthropogenic habitat and
food provisioning has facilitated the winter range expansion
of Anna’s hummingbirds, then (i) hummingbirds should be
occurring in areas with lower temperatures than previously
occupied, (ii) hummingbirds should be preferentially coloniz-
ing areas with higher urbanization in the expanded range, but
not in the historical range, and (iii) hummingbirds should be
more dependent upon supplementary food (i.e. nectar feeders)
in the expanded range than in the historical range. In contrast, if
increasingly mild winters have facilitated the range expansion
irrespective of anthropogenic habitat and food, then we pre-
dicted that (i) hummingbirds should be occurring in areas
with the same climate envelope as previously occupied, even
though those areas are now farther north, (ii) hummingbirds
should be equally associated with urban locations in the
expanded range and the historical range, and (iii) humming-
birds should be equally dependent upon supplementary
feeders in the expanded range and the historical range.
2. Methods
(a) Study species
Anna’s hummingbirds inhabit the west coast of North America,
as far south as northwest Baja California and Mexico, and as far
north as southwest British Columbia [35]. They are one of the
few species of hummingbirds in North America that are not
long-distance migrants, and their local seasonal movements are
complex, poorly understood and thought to be related to harsh-
ness of weather conditions [35,41]. Nesting occurs between
December and June depending upon the latitude, with earlier nest-
ing at lower latitudes. In late summer in southern locations there is
a movement to higher elevations following peaks in flower abun-
dance [35]. Birds are commonly found in scrubby or suburban
habitat with suitable bushy vegetation and are frequently attracted
to yards with nectar feeders and flowering plants [35].
(b) Data sources
(i) Project FeederWatch
Data on Anna’s hummingbird occupancy were collected through
the citizen science programme Project FeederWatch (PFW), run
through the Cornell Laboratory of Ornithology and Bird Studies
Canada [45]. PFW participants follow a standardized protocol to
count the maximum number of every species seen in the proximity
of a bird feeding station during periodic 2-day counts. These
counts are repeated as often as every week from November–
April each year. By requiring that participants only report the
maximum number of each species in view at one time during the
count, the protocol ensures that participants are not repeatedly
recording the same individual birds within a count. Additionally,
participants report all of the species seen, so the protocol allows
120°0¢0¢¢ W
50°0¢0¢¢ N
40°0¢0¢¢ N
50°0¢0¢¢ N
40°0¢0¢¢ N
110°0¢0¢¢ W
mean birds
per count
0
<1
>2
1–2
120°0¢0¢¢ W 110°0¢0¢¢ W 120°0¢0¢¢ W 110°0¢0¢¢ W
120°0¢0¢¢ W130°0¢0¢¢ W 110°0¢0¢¢ W120°0¢0¢¢ W130°0¢0¢¢ W 110°0¢0¢¢ W120°0¢0¢¢ W130°0¢0¢¢ W 110°0¢0¢¢ W
1990–1997 1998–2005 2006–2013
Figure 1. The distribution of Anna’s hummingbirds in winter (January and February) at Project FeederWatch count sites (small black dots) over 24 years. Mean
maximum birds by site, binned into three time periods: 1990–1997 (n¼1913 sites), 1998–2005 (n¼3583 sites) and 2006–2013 (n¼3151 sites). Maps
generated using ARCGIS 10.0, kriging interpolation (ESRI Inc., 1999–2010).
rspb.royalsocietypublishing.org Proc. R. Soc. B 284: 20170256
2
inference about both presence and absence (detection and non-
detection) of species in every count. All participants report an
estimate of the amount of time that they watched their feeders
(effort) and the date of the observation (date).
We extracted Anna’s hummingbird occupancy data from PFW
sites in Arizona, California, Oregon and Washington from 1997 to
2013. We restricted all occupancy analyses to sites with nectar fee-
ders because sites offering nectar at some point between
November and April were much more likely to have humming-
birds than sites without nectar feeders (79% of sites with nectar
feeders had a hummingbird compared with only 28% of sites with-
out nectar feeders; likelihood ratio test:
x
2
1¼575:3, p,0.001, n¼
2306 sites). We also restricted all occupancy analyses to obser-
vations made during the months of December–February so late
autumn (November) or early spring (March– April) hummingbird
movements would not influence our results.
(ii) Climate and elevation data
We extracted the daily minimum temperature (Tmin), averaged
over all days for the month of January (mean minimum January
temperature) and the total monthly precipitation (Ppt) for the
month of January (total January precipitation) for each site and
year, from the PRISM Climate Group gridded dataset (Oregon
State University, http://www.prism.oregonstate.edu). We chose
January as the representative winter month because that month
was temporally central to the bird occupancy data (December–
February). To control for the potential effects of topography on
occupancy, given that there are known elevational movements of
Anna’s hummingbirds [35], we extracted elevation data for each
site from the CGIAR Consortium for Spatial Information SRTM
90 m Digital Elevation Database (http://www.cgiar-csi.org/
data/srtm-90m-digital-elevation-database-v4-1).
(iii) Housing density and land cover data
We calculated housing density, defined as the total number of
housing units per area, following methodology in [46]. Housing
units were based on a nationwide, spatially explicit dataset at the
partial block group level, which corrects for variation introduced
into census blocks by political boundaries. Housing units include
permanent residences, seasonal houses and vacant units [46].
At each partial block group throughout the conterminous US,
housing density was estimated based on the 2000 US decennial
census [46], and we used these estimates to characterize housing
development throughout our study area. To quantify housing
density at each site, we summarized housing density within
1 km circular buffers of each site using the tool ‘intersect’ in
ARCGIS v. 10.1. We used the 1 km radius buffer because this
was an approximate home range given for several breeding
Anna’s hummingbirds [41]. Due to the presence of outliers, we
log-transformed the housing density data before analysis.
We extracted the proportion of urban land cover for each site
from the 2011 National Landcover Database, with land cover
classes 21 (developed, open space), 22 (developed, low intensity),
23 (developed, medium intensity), and 24 (developed, high
intensity; http://www.mrlc.gov/nlcd11_leg.php). Within each
1 km circular buffer of each site we divided the total number of
cells (30 30 m resolution) of the focal urban land cover by the
total number of cells within the buffer, which gave us the
proportion of urban land cover at each site.
(c) Statistical analysis
We explored the range expansion of Anna’s hummingbirds using
an occupancy-modelling framework implemented with the R pack-
age unmarked [47]. Occupancy models estimate the probability of a
focal species occupying a site given imperfect detection [48]. Fol-
lowing [11], we used the single-season modelling framework [48]
to explore how the relationships between occupancy, latitude and
temperature changed over time. Single-season models assume a
closed system with no extinction or colonization, which approxi-
mates our expectations for a December– February sampling
interval. Although mortality and emigration are certainly possible
during this (orany) sampling interval, we focused on a time period
when the species is largely sedentary. To quantify the northward
expansion, we created three single-season models of hummingbird
occupancy as a function of latitude for the years 1997 (n¼98 sites),
2005 (n¼356 sites) and 2013 (n¼434 sites) with date and effort as
observation covariates. Sample sizes differed across years because
of different rates of participation in PFW, but occupancy models
are robust to such variation as long as the sampled sites are repre-
sentative of the regionor time period of interest. We have no reason
0
0.2
0.4
0.6
0.8
1.0
latitude mean minimum January temperature (°C)
predicted occupancy probability (y)
34.3 39.7 45 50.3
2013
2005
1997
0
0.2
0.4
0.6
0.8
1.0
–7.6 –4.5 –1.5 1.6 4.6 7.6 10.7
Figure 2. Predicted occupancy probability (
c
) of Anna’s hummingbirds as a function of (a) latitude and (b) minimum January temperature (8C) for 1997 (n¼98
sites; light grey), 2005 (n¼356 sites; medium grey) and 2013 (n¼434 sites; dark grey). 95% CIs are shown. Model results given in table 2.
rspb.royalsocietypublishing.org Proc. R. Soc. B 284: 20170256
3
to suspect that sampled sites were not representative of their
respective regions and time periods. To test the prediction that
contemporary hummingbirds are occupying sites with lower
temperatures than historically occupied, we created three single-
season models of hummingbird occupancy as a function of mean
minimum January temperature for the same sites and years
(1997, 2005 and 2013). Although there are known long-term pat-
terns of warming that have occurred in the Pacific Northwest
[49,50], we also tested how the mean minimum January tempera-
ture has changed at PFW sites from 1997 to 2013 using a linear
mixed model with year as a fixed effect and site ID as a random
effect, implemented with the R package lme4. For this analysis
we included sites that did not offer nectar feeders because we
were not assessing hummingbird occupancy. We binned sites
into those from the historical winter range (below 428latitude,
n¼1269 sites) and those from the expanded winter range (above
428latitude, n¼1037 sites). We chose this geographical demar-
cation based on the distribution of hummingbirds in the early
years of the study (1990–1997; figure 1).
To test the hypothesis that the winter range expansion
was associated with colonization of urban habitats (and potentially
provisioning of supplementary food) rather than winter tempera-
tures irrespective of habitat, we used a multi-season modelling
framework. Multi-season models allow for both extinction and
colonization between seasons and are therefore appropriate for
modelling occupancy over a multiple year sampling interval [51].
We used the subset of sites from 2002 to 2013 that offered nectar fee-
ders and for which we had housing density and land-cover data.
We omitted years preceding 2002 because of small sample sizes
(fewer than 45 sites per year). We binned sites into those from the
historical range (n¼539 sites) and the expanded range (n¼366
sites), and for each region modelled hummingbird colonization
as a function of the site covariates: housing density, proportion of
urban land cover, elevation, mean minimum January temperature
and total January precipitation. Because we wanted to compare
all site covariates in a consistent quantitative way, but some covari-
ates were static across years (housing density, proportion of urban
land cover and elevation) and some temporally dynamic (tempera-
ture and precipitation), we transformed the dynamic variables to
static variables by calculating a mean across years. All site covari-
ates were weakly correlated (r,0.4) except housing density and
proportion of urban land cover, which were strongly correlated
(r¼0.8). We included observation effort and date as observation-
covariates influencing detection, and latitude as a site covariate
influencing occupancy.
In addition to comparing the explanatory power of each site
covariate in models with all covariates (global models), we used
a model-selection approach with a criterion of DAIC ,2 indicat-
ing equivalent models to assess the importance of each site
covariate on colonization in the historical versus the expanded
range. We compared models with all but one of each site covari-
ate, univariate models with only one of each site covariate, the
putative best models for each region (for the historical range,
the univariate model with elevation as the site covariate and
for the expanded range, a model with housing density and temp-
erature as the site covariates), the global model, and a null model
with no site covariates. All models converged and produced
reasonable estimates and standard errors. Null models had low
Table 1. Single-season model estimates relating Anna’s hummingbird
occupancy (
c
) to latitude and mean minimum January temperature for 3
years (models estimates correspond to figure 2). Effort and date were
included in all models as observation-covariates. p-values ,0.05 are given
in italics.
predictor year (nsites) estimate s.e. zp
latitude 1997 (98) 21.64 0.32 25.21 0.000
2005 (356) 20.71 0.14 25.23 0.000
2013 (434) 20.02 0.15 20.14 0.891
temperature 1997 (98) 1.33 0.32 4.22 0.000
2005 (356) 1.02 0.18 5.69 0.000
2013 (434) 0.64 0.15 4.27 0.000 2000 2005 2010
–4
–2
0
2
4
6
(a)
(b)
(c)
historical range
expanded range
year
2000 2005 2010
0
0.2
0.4
0.6
0.8
1.0
proportion of sites with nectar feeders mean minimum January temperature (°C)
2000 2005 2010
0
0.2
0.4
0.6
0.8
1.0
proportion of sites with hummingbirds
Figure 3. (a) Mean minimum January temperature (8C) from 1997 to 2013
in the historical range (below 428latitude; grey circles, n¼1269 sites for all
panels) and the expanded range (above 428latitude; black circles, n¼1037
sites for all panels). Error bars indicate standard error. (b) Proportion of sites
offering nectar feeders from 1997 to 2013 in the historical range and the
expanded range. Error bars indicate binomial standard error. (c) Proportion
of sites supporting Anna’s hummingbirds from 1997 to 2013 in the historical
range and the expanded range. Error bars indicate binomial standard error.
rspb.royalsocietypublishing.org Proc. R. Soc. B 284: 20170256
4
support based on AIC ranking, indicating that covariates
improved model fit. Following [11], to evaluate the adequacy
of models we calculated the area under the curve (AUC) statistic
[52,53] for each year for global models in the historical and
expanded range. The AUC statistic represents the predictive
power of each model for each year. Values of AUC lower than
0.70 indicate poor discriminatory power, 0.70– 0.80 indicate
acceptable discriminatory power and more than 0.80 indicate
excellent discriminatory power [53].
To test the hypothesis that hummingbirds were more reliant
upon nectar feeders in the expanded range compared with the his-
torical range, we used a multi-season model and included all sites
from 2002 to 2013 with nectar feeders and for which we had land
cover data (n¼905 sites). We did not bin sites into the historical
versus expanded range because we wanted to assess how detection
varied across the entire latitudinal range. We included all site and
observation covariates in the model and allowed detectability to
vary with latitude. Detectability indicates the probability that a
hummingbird will be detected at a site given that a hummingbird
occupies the site. Therefore, modelling detection probability as a
function of latitude at PFW sites can be interpreted as how likely
it is for a hummingbird to visit nectar feeders at any given latitude
(for a similar use of detection probability to infer feeder visitation
rate, see [11]).
We used the presence and absence of hummingbird feeders
reported by participants across years to document a pattern of
northward expansion of supplementary nectar provisioning
from 1997 to 2013 (n¼2306 sites). A feeder was considered ‘pre-
sent’ at a site if the observer indicated that a hummingbird
feeder was used at some point between November and April.
We used mixed-effects logistic regression models, implemented
with the R package lme4, to assess how the tendency to offer
nectar feeders changed across years in the historical versus
expanded range. In these models we treated year as a continuous
predictor variable, feeder presence as a binary response variable,
historical versus expanded range as a binary predictor variable
and site ID as a random effect.
Finally, to visualize the northward expansion of hummingbirds
in a manner quantitatively comparable with the northward expan-
sion of nectar feeders, we calculated the proportion of sites from
1997 to 2013 (n¼2306 sites) supporting hummingbirds for each
year in the historical and expanded range. Because these data
included sites without nectar feeders and omitted details of
repeated counts at sites, we did not use it for any quantitative
comparisons, but present it for visual comparison only.
3. Results
The winter range expansion of the Anna’s hummingbird north-
ward along the west coast of North America from 1997 to 2013
was unambiguous (figures 1 and 2a, and table 1). Anna’s hum-
mingbirds were more likely to be found at colder sites in later
years (figure 2band table 1). Contrary to global temperature
trends, mean minimum January temperatures at our sampling
locations slightly decreased from 1997 to 2013 (
b
¼20.117
t¼211.9, p,0.001 for 1269 sites in the historical range,
and
b
¼20.146, t¼214.4, p,0.001 for 1037 sites in the
expanded range; figure 3a). Temperature was a significant pre-
dictor of colonization in the expanded range but not in the
historical range, according to multi-season occupancy models
(tables 2 and 3).
Housing density was a significant predictor of colonization
in the expanded range but not in the historical range (tables 2
and 3). In the historical range, the only near-significant pre-
dictor of occupancy was elevation, with lower elevations
tending to have higher occupancy probability (table 2). AIC
model comparisons complemented these results (table 3); in
the historical range, the highest-ranking model (DAIC ,2)
included only elevation. In the expanded range, however,
the highest-ranking model contained housing density and
mean minimum January temperature. AUC statistics for
Table 2. Multi-season model estimates for years 2002– 2013 relating Anna’s hummingbird colonization (
g
) to all site covariates (‘predictor’) in the historical
range and the expanded range. Effort and date were included in each model as predictors of detection ( p) and latitude as a predictor of occupancy (
c
).
p-values ,0.05 are given in italics.
location predictor parameter estimate s.e. zp
expanded range (above 428)
n¼366 sites
effort p0.02 0.04 0.44 0.657
date p20.22 0.04 25.82 0.000
latitude c20.75 0.22 23.42 0.001
proportion urban g20.13 0.18 20.73 0.467
elevation g0.01 0.21 0.04 0.965
housing density g0.73 0.20 3.57 0.000
temperature g0.63 0.20 3.16 0.002
precipitation g20.15 0.15 21.04 0.299
historical range (below 428)
n¼539 sites
effort p0.11 0.03 3.54 0.000
date p20.16 0.03 25.63 0.000
latitude c0.56 0.27 2.09 0.037
proportion urban g0.73 0.47 1.56 0.119
elevation g20.63 0.34 21.86 0.063
housing density g20.34 0.42 20.80 0.423
temperature g0.14 0.36 0.40 0.693
precipitation g0.12 0.31 0.38 0.704
rspb.royalsocietypublishing.org Proc. R. Soc. B 284: 20170256
5
global models for each year indicated excellent discriminatory
power in the expanded range (AUC mean +s.d. ¼0.82 +0.07
across years) and poor discriminatory power in the historical
range (AUC mean +s.d. ¼0.64 +0.08 across years).
Hummingbird detectability (approx. 0.80 in global models)
increased with increasing latitude despite decreased occupancy
at higher latitudes (
b
¼0.165, s.e. ¼0.024, z¼6.86, p,0.001,
n¼905 sites). Thus, sites that supported hummingbirds at
higher latitudes were more likely to detect hummingbirds
during count periods than sites at lower latitudes.
Finally, nectar provisioning bypeople increased over time in
the expanded range, but not in the historical range. The pro-
portion of participants with nectar feeders varied significantly
among years at sites in the expanded range (
b
¼0.351, z¼
14.41, p,0.001, n¼1037 sites), but not in the historical range
(
b
¼0.038, z¼1.06, p¼0.287, n¼1269 sites; figure 3b).
People in the historical range were more likely to offer hum-
mingbird feeders compared with people in the expanded
range, with these proportions converging by 2009 (
b
¼21.99,
z¼22.00, p¼0.045, n¼2306 sites; figure 3b). Likewise, the
proportion of sites with hummingbirds in the historical and
expanded range converged by the late 2000s (figure 3c).
4. Discussion
We documented a clear northward winter range expansion of
Anna’s hummingbird over the past 20 years using data from
Project FeederWatch. We found strong support for the
hypothesis that the range expansion was facilitated by urban-
ization and provisioning of supplementary food resources.
First, we found that Anna’s hummingbirds have been colo-
nizing colder locations over time, suggesting that they are
not merely following warming winter temperatures north.
Despite long-term trends of increasing temperature in the
Pacific Northwest [49,50], we found no evidence of a sys-
tematic and directional warming of winter temperatures at
the sites in this study, suggesting that the time period was
too brief to reflect these long-term changes or that the specific
sites did not reflect this geographically broad trend.
Further, we found that Anna’s hummingbirds were more
associated with human-modified habitat in the expanded
range than in the historical range. This suggests that urban
habitat is most beneficial to these hummingbirds, where they
experience the strongest thermal limits. The benefits provided
by urban habitat could include the local retention of heat
Table 3. Model selection for multi-season models for years 2002–2013 relating Anna’s hummingbird colonization (g) to site covariates in the historical range
and the expanded range. Effort and date were included in all models as predictors of detection ( p) and latitude as a predictor of occupancy (c).
location model parameters AIC DAIC weight
expanded range (above 428)
n¼366 sites
HþT 9 5091.6 0.00 0.57
HþTþPþU 11 5094.2 2.53 0.16
HþTþEþP 11 5094.7 3.07 0.12
HþTþEþU 11 5095.3 3.65 0.09
HþTþEþPþU
a
12 5096.2 4.53 0.06
HþEþPþU 11 5103.7 12.1 0.00
TþEþPþU 11 5109.0 17.3 0.00
H 8 5112.0 20.4 0.00
T 8 5122.9 31.3 0.00
U 8 5128.7 37.1 0.00
E 8 5132.2 40.6 0.00
null 7 5151.0 59.4 0.00
P 8 5152.1 60.4 0.00
historical range (below 428)
n¼539 sites
E 8 8365.9 0.00 0.49
HþTþEþU 11 8368.5 2.61 0.13
HþEþPþU 11 8368.5 2.62 0.13
TþEþPþU 11 8369.0 3.11 0.10
HþTþEþPþU
a
12 8370.3 4.46 0.05
HþTþEþP 11 8370.9 4.98 0.04
HþTþPþU 11 8372.3 6.43 0.02
T 8 8373.0 7.15 0.01
HþT 9 8374.0 8.10 0.01
U 8 8381.3 15.4 0.00
H 8 8391.2 25.3 0.00
null 7 8396.4 30.5 0.00
P 8 8397.0 31.1 0.00
a
Global model ¼housing density (H) þmean min January temperature (T) þelevation (E) þtotal January precipitation (P) þproportion urban land cover (U).
rspb.royalsocietypublishing.org Proc. R. Soc. B 284: 20170256
6
(e.g. the ‘heat island effect’ [17]), increased availability of
non-native flowers that bloom throughout the winter or
increased availability of supplementary food (nectar feeders).
Importantly, we found higher hummingbird detection prob-
abilities with increasing latitude, despite lower hummingbird
occupancy at higher latitudes. These higher detection probabil-
ities at northern sites suggest higher visitation rates at feeders
and potentially greater reliance on feeders at northern lati-
tudes. This result complements recent work showing that
some species may rely upon supplementary food to survive
outside of their core environmental envelope (e.g. Eurasian
blackcaps, Sylvia atricapilla, in England [31]; rose-ringed
parakeets, Psittacula krameri, in Paris [33]). Similar analyses are
warranted in ruby-throated hummingbirds (Arhilochus colu-
bris), which are increasingly overwintering in the southeastern
United States rather than migrating to Central America [34].
Finally, we found evidence that human behaviour may be
changing along with hummingbird behaviour. There was an
increased likelihood of people providing nectar feeders over
time in the expanded range compared with the historical
range. The hummingbird range expansion may have instigated
a change in human behaviour, or increased provisioning of
nectar feeders may have facilitated the hummingbird range
expansion; it is likely that these two outcomes are intertwined.
People in the expanded range who provide nectar feeders in
summer may leave those feeders out later into the year if
hummingbirds remain in the area, and those feeders may sim-
ultaneously enhance the winter survival of hummingbirds that
do not migrate. Although we cannot disentangle these two pat-
terns with our current dataset, we can conclude that more
supplementary food resources are available to hummingbirds
in the expanded range now compared with two decades ago.
The long-term ecological consequences of the Anna’s
hummingbird range expansion remain uncertain. Their
expansion may affect the migratory or breeding behaviour
of other hummingbirds. For example, rufous (Selasphorus
rufus), calliope (S. calliope) and black-chinned (A. alexandri)
hummingbirds breed in northwestern North America [35],
and may experience increased competition with Anna’s hum-
mingbirds. Additionally, if humans are facilitating the range
expansion to the extent that we suspect from this study, then
it is unclear if the expansion would be sustained in the
absence of supplementary nectar provisioning or non-native
plantings. Assessing the indirect effects of range expansions
on other species and the long-term dependence of native
species on human-provided resources remains an important
yet difficult task [20,21,25].
Understanding the nuances of how Anna’s hummingbird
migratory movements have changed over the past two decades
will benefit from studies of marked individuals. Nonetheless,
the broad pattern is clear: Anna’s hummingbirds are more
abundant in winter at northern latitudes now than they were
several decades ago, implying a reduction in the proportion
of individuals that migrate. Anna’s hummingbirds are also
more closely associated with human-modified landscapes in
more northern latitudes, implying that people have facilitated
this reduction in migratory behaviour and corresponding
winter range expansion. Our study complements previous
work showing that urban habitat and supplementary feeding
may facilitate range expansions into colder climates
[11,12,32,33] and potentially changes in migratory behaviour
[13,14,31]. This pattern of human-assisted colonization is not
unique to northward range shifts, as demonstrated by the colo-
nization of novel areas by invasive species (e.g. Eurasian
collared doves, Streptopelia decaocto [54,55]; house sparrows,
Passer domesticus [56]), population growth around urban
areas (e.g. Allen’s hummingbird, Selasphorus sasin [57]), and
even elevational range expansions (e.g. montane plants [58]).
Overall, this work highlights how the effects of anthropogenic
landscape modifications may interact with climate, in this case
furthering northward expansion beyond what would be
expected by historical thermal envelopes. It also highlights
how our seemingly benign hobby of feeding birds may have
far-reaching ecological consequences.
Data accessibility. All data are accessible through Project FeederWatch
(Cornell Laboratory of Ornithology) or through public sources
described in the methods. The specific datasets supporting this
manuscript have been uploaded as electronic supplementary
material.
Authors’ contributions. E.I.G. conceived the study, wrote the manuscript,
conducted data analysis. D.N.B. conceived the study, revised the
manuscript and assisted with analyses. E.M.W. assisted with ana-
lyses and revised the manuscript. All authors gave final approval
for publication.
Competing interests. We declare we have no competing interests.
Funding. We received no funding for this study.
Acknowledgements. We thank Wesley M. Hochachka, Benjamin Zucker-
berg, Viviana Ruiz Gutierrez, Walt Koenig and Janis Dickinson for
valuable advice on interpretation and analyses, two anonymous
reviewers for significantly improving the manuscript, Kerrie Wilcox
at Bird Studies Canada and Anne Marie Johnson and Chelsea
Benson at the Cornell Laboratory of Ornithology for managing Pro-
ject FeederWatch across the United States and Canada, and Project
FeederWatch participants for collecting the data used in this study
and supporting the programme.
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