Japanese honey bees (Apis cerana japonica) have swarmed more often over the last two decades

Abstract

The impacts of temperature increase are a concern for honey bees, which are major pollinators of crops and wild plants. Swarming is the reproductive behavior of honey bees that increases colony numbers. Honey bee colonies sometimes swarm multiple times, with each swarming termed a “swarming event” and a series of these events called a “swarming cycle.” The number of swarming events per swarming cycle varies widely depending on climatic conditions and subspecies, and the recent temperature increase due to global warming might be affecting the number of swarming events per swarming cycle of native honey bees. We clarified long-term changes in the number of swarming events per swarming cycle of Japanese honey bees (Apis cerana japonica) by collecting beekeepers’ swarming logbooks. The survey showed that between 2000 and 2022, Japanese honey bees swarmed 1 to 8 times per swarming cycle. Generalized linear model analysis indicated that year had a significant positive effect (coefficient, 0.03; 95% CI, 0.01–0.04); that is, the number of swarming events per swarming cycle showed a moderate increase over time. In addition, we found that colonies swarmed more often in a cycle when the swarming process began in early spring, especially in March. Considering the notably strong trend in Japan of warmer temperatures in March, the number of swarming events per swarming cycle may be increasing because reproduction is beginning earlier in the year. Further analyses are needed to verify the causal relationship of temperature increase on the number of swarming events per swarming cycle.

Full text

Vol.:(0123456789)
The Science of Nature (2024) 111:14
https://doi.org/10.1007/s00114-024-01902-y
ORIGINAL ARTICLE
Japanese honey bees (Apis cerana japonica) have swarmed more often
overthelast two decades
KiyohitoMorii1 · YoshikoSakamoto1
Received: 3 August 2023 / Revised: 13 February 2024 / Accepted: 26 February 2024 / Published online: 6 March 2024
© The Author(s) 2024
Abstract
The impacts of temperature increase are a concern for honey bees, which are major pollinators of crops and wild plants.
Swarming is the reproductive behavior of honey bees that increases colony numbers. Honey bee colonies sometimes swarm
multiple times, with each swarming termed a “swarming event” and a series of these events called a “swarming cycle.” The
number of swarming events per swarming cycle varies widely depending on climatic conditions and subspecies, and the
recent temperature increase due to global warming might be affecting the number of swarming events per swarming cycle of
native honey bees. We clarified long-term changes in the number of swarming events per swarming cycle of Japanese honey
bees (Apis cerana japonica) by collecting beekeepers’ swarming logbooks. The survey showed that between 2000 and 2022,
Japanese honey bees swarmed 1 to 8 times per swarming cycle. Generalized linear model analysis indicated that year had a
significant positive effect (coefficient, 0.03; 95% CI, 0.01–0.04); that is, the number of swarming events per swarming cycle
showed a moderate increase over time. In addition, we found that colonies swarmed more often in a cycle when the swarming
process began in early spring, especially in March. Considering the notably strong trend in Japan of warmer temperatures in
March, the number of swarming events per swarming cycle may be increasing because reproduction is beginning earlier in
the year. Further analyses are needed to verify the causal relationship of temperature increase on the number of swarming
events per swarming cycle.
Keywords Asian honey bee· Climate change· Global warming· Native honey bee· Reproductive behavior· Swarming
cycle
Introduction
Climate change is impacting global ecosystems and biodi-
versity (Garcia etal. 2014; Pecl etal. 2017), and understand-
ing these effects is a defining challenge for ecology (Halsch
etal. 2021). In particular, the rate of temperature increase
in the twenty-first century is predicted to be the highest in
the last 65 million years (Diffenbaugh and Field 2013). Cli-
mate change, including temperature increase, is affecting
the behavior of various animals (e.g., Forister and Shapiro
2003; Charmantier etal. 2008; Gutiérrez and Wilson 2020).
For example, in central Europe, 44 species of Lepidoptera
have increased voltinism, with various ecological impacts
of concern, including increased agricultural damage (Alter-
matt 2010). Beyond this example, temperature increase
affects the life histories of many insect species (reviewed
by Harvey etal. 2023). The effects of temperature increase
on poikilotherms (including insects) are highly dependent
on behavioral changes such as phenology, as well as shade
availability (Kearney etal. 2009). Therefore, studying how
rising temperatures affect animal behavior is essential for
accurately assessing the impact of warming on ecosystems.
Honey bees are major pollinators of crops and wild plants
(e.g., Calderone 2012; Aslan etal. 2016), contributing to
the production of 39 of the leading 57 single crops (Klein
etal. 2006). The impacts of climate change, including tem-
perature increase, on important pollinator groups such as
honey bees are a concern (Le Conte and Navajas 2008;
Miller-Struttmann 2015; Hutchings etal. 2018; Nürnberger
etal. 2019). For example, Switanek (2017) reported that hot
and dry summers increase the collapse probability of Apis
Communicated by William Benjamin Walker
* Kiyohito Morii
oh14kmorii@ec.usp.ac.jp
1 National Institute forEnvironmental Studies, 16-2 Onogawa,
Tsukuba, Ibaraki305-8506, Japan
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

The Science of Nature (2024) 111:1414 Page 2 of 8
mellifera colonies in winter, and Alzate-Marin etal. (2021)
demonstrated that temperature increase may alter flower-
visiting behavior. In addition, analyses of long-term records
of A. mellifera in Spain and Poland suggested that tempera-
ture increase has accelerated the timing of emergence from
the hive after overwintering (Gordo and Sanz 2006; Sparks
etal. 2010). However, as revealed by a meta-analysis of 293
papers by Havard etal. (2019), few studies have examined
the impact of temperature increase on honey bees, especially
on reproduction.
Under natural conditions, members of the genus Apis
(Apidae) only increase the number of colonies through
reproductive swarming (hereafter “swarming”), in which
the queen and many workers leave the original colony to
establish a new nest (Grozinger etal. 2014). Honey bees
sometimes swarm multiple times during a swarming cycle
(i.e., a series of swarming events; see Fig.1). In the first
swarming (prime swarming), the mated queen leaves the
nest with workers, and in the second and subsequent swarm-
ings (after-swarming), a newly emerged queen leaves with
workers (Winston 1980). Studies in the USA have reported
that European honey bees A. mellifera ligustica or A. mel-
lifera carnica swarm 1 to 4 times per swarming cycle (Win-
ston 1980; Gilley and Tarpy 2005). Tropical A. mellifera
subspecies swarm more often than temperate ones (Seeley
1985). An exhaustive study of five subspecies of A. mellif-
era in Ethiopia revealed that some subspecies swarmed an
average of 10 times and up to 16 times per colony per year,
whereas others swarmed an average of only 3 times (Nuru
etal. 2002). It has also been reported that Africanized
honey bees swarm 1 to 5 times per swarming cycle (Otis
1991). These findings indicate that the number of swarm-
ing events per swarming cycle varies with climate and sub-
species, even within the same species, suggesting that the
number of swarming events per swarming cycle may also be
affected by temperature. A change in the number of swarm-
ing events per swarming cycle could be demonstrated by
analyzing long-term records, but no such studies have been
done.
The Japanese honey bee (A. cerana japonica), a subspe-
cies of the Asian honey bee that is widely distributed in Asia
(Engel 1999; Su etal. 2023), is a good candidate for use in
large-scale research on long-term changes in the number
of swarming events, unlike the European honey bee, which
is generally managed to prevent natural swarming (Crane
1984). The Japanese honey bee is an endemic subspecies,
distributed across Japan except for Hokkaido and Okinawa.
Although Okada (1997) reported that Japanese honey bees
usually swarm 1 to 2 times and sometimes up to 4 to 5 times
per swarming cycle, no quantitative data on the number of
swarming events per swarming cycle exist, except for reports
from limited areas or a limited number of colonies (e.g.,
Iwasaki and Ihara 1994). Sociometric data are necessary
for understanding the life history of social insects (Tschin-
kel 1991). However, the number of swarming events per
swarming cycle is largely unknown for A. cerana (Hyatt
2012; Aryal 2019).
Because Japanese honey bees are more likely to abscond
and produce less honey than European honey bees, they are
often kept as a hobby rather than for commercial beekeeping
(Yoshida 1997b, 1998). In the hobby beekeeping of Japanese
honey bees, it is common to keep the bees in a frameless
hive, allowing them to swarm naturally like a wild colony.
For many keepers of Japanese honey bees, swarming is an
opportunity to increase their colonies, so most beekeepers
frequently observe the colony during the swarming season
and record the dates of swarms that depart their hives. By
compiling the records of the number of swarming events in
each colony, we may be able to detect long-term changes in
the number of swarming events per swarming cycle.
In this study, we clarified long-term changes in the num-
ber of swarming events per swarming cycle by collecting
past records of the number of swarming events from keep-
ers of Japanese honey bees. In addition, using these data we
Fig. 1 The relationship between
swarming cycles of overwin-
tered and re-swarmed colonies
in this study. Thick arrows
indicate each swarming event.
Thin arrows indicate the pres-
ence of a colony. The dotted
square represents the swarm-
ing cycle, which is a series of
swarming events. This study
did not distinguish whether the
origin of the re-swarmed colony
was prime swarming or after-
swarming
bee
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

The Science of Nature (2024) 111:14 Page 3 of 8 14
produced a frequency distribution of the number of swarm-
ing events per swarming cycle and identified the period
when honey bees swarm most frequently. Considering these
results, we discuss the effects of temperature increase on the
number of swarming events per swarming cycle of Japanese
honey bees.
Materials andmethods
Data collection
On 23 June 2022, we emailed 239 keepers of Japanese
honey bees from across Japan to ask them to share data
on the number of swarming events and swarming dates for
each of their colonies. We distinguish between a swarm-
ing cycle in a colony that had existed since the previous
year and swarmed after overwintering (hereafter “overwin-
tered”; Fig.1) and one that had already swarmed earlier in
the year and swarmed again within the same year (hereafter
“re-swarmed”). We only used data from colonies with com-
plete information, including the number of swarming events
per swarming cycle, swarming dates, and categorization of
colony status as overwintered or re-swarmed. Additionally,
for all data used, we identified the beekeepers by name and
the colony locations to ensure data reliability.
To distinguish between swarming cycles, it is necessary
to establish a threshold for the number of days between
swarming events to be considered part of the same swarming
cycle. In the case of the Japanese honey bee, when a newly
emerged queen is present immediately after a swarming
event, the timeline until this newly emerged queen departs
the hive in the subsequent prime swarm is as follows: mat-
ing flights typically occur 6 days after emergence, egg-
laying begins 2–3 days after mating, larvae hatch 3 days
later, queen cells are sealed 4–5 days after that, the tip of the
queen’s cocoon is exposed from the queen cell as workers
remove the wax cover 4 days later, and the mated queen then
swarms 6–8 days after the exposing of her cocoon (Yoshida
1997a; Sasaki 1999). Therefore, in this study, swarming
events with intervals of 25 days or less were considered part
of the same swarming cycle.
Statistical analysis
In all our analyses, we distinguished between overwintered
and re-swarmed colonies. We calculated the average num-
ber of swarming events per swarming cycle. In addition, to
investigate the temporal change in the number of swarming
events per swarming cycle and in the number of days after
March 1st of the prime swarm, we used a Bayesian general-
ized linear model (GLM) assuming a Poisson distribution.
The response variable was the number of swarming events
in each colony or the number of days after March 1st of the
prime swarm, and the explanatory variables were the year
when the swarming was observed and whether the colony
was overwintered or re-swarmed. In the parameter estima-
tion using the Markov chain Monte Carlo algorithm, 8000
steps are calculated independently four times, the first 2000
steps are removed to eliminate the influence of the initial
value, and then, sampling was performed once every three
steps to mitigate autocorrelation. When the

R
value (Gelman
etal. 2004), which is a criterion for convergence, was less
than 1.1, parameters were judged to have converged. For
this analysis, the rstan package (ver. 2.21.2) and the brms
package (ver. 2.8.0) of R (ver. 4.0.5) were used.
We calculated the average number of swarming events
for each month (March to August) in which prime swarm-
ing was recorded, to indicate the relationship between the
swarming season and the number of swarming events. For
these data, we performed Steel–Dwass multiple-comparison
tests using the asymptotic method to calculate the probabil-
ity that the number of swarming events per swarming cycle
of each group was different. In addition, we calculated the
intervals (days) between prime swarming and the first after-
swarm events, first and second after-swarm events, second
and third after-swarm events, and so on for each swarming
cycle. For these data, we performed Steel–Dwass multiple-
comparison tests using the Monte Carlo method. In these
analyses, a p value ≤ 0.05 was considered significant, and
the NSM3 package (ver. 1.17) of R (ver. 4.0.5) was used.
Results
We collected data on the number of swarming events in
253 swarming cycles between 2000 and 2022 from 20
keepers of Japanese honey bees. Japanese honey bees
exhibited 1 to 8 swarming events per swarming cycle dur-
ing this 23-year period (Fig.2). In an exceptional colony
that swarmed 8 times in a single swarming cycle in 2019,
the second and third after-swarming events occurred on
the same day, as follows: the prime swarm on March 29,
the first after-swarm on April 4, the second on April 6, the
third on April 6, the fourth on April 8, the fifth on April
12, the sixth on April 14, and the seventh on April 17. The
overwintered and the re-swarmed colonies swarmed an
average of 2.5 and 1.8 times per swarming cycle, respec-
tively. All GLM parameters were converged (

R
< 1.00).
The GLM analysis indicated that the number of swarm-
ing events per swarming cycle of overwintered colonies
was significantly higher than that of re-swarmed colonies
(coefficient, 0.40; 95% CI, 0.20 to 0.60; Fig.3a). In addi-
tion, the analysis indicated that year had a significant posi-
tive effect (coefficient, 0.03; 95% CI, 0.01 to 0.04). That
is, the number of swarming events per swarming cycle
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

The Science of Nature (2024) 111:1414 Page 4 of 8
showed a moderate increase over time (by a factor of about
1.03 per year). The GLM analysis of the number of days
after March 1st of the prime swarm indicated that year
had a significant negative effect (coefficient, –0.01; 95%
CI, –0.01 to –0.01; Fig.3b). That is, the swarming pro-
cess started earlier over time (on average, by 0.44 days
per year). For the overwintered colonies in particular, the
average date of the prime swarming was estimated as 24
April in 2000, and it had shifted to 13 April by 2022.
In both overwintered and re-swarmed colonies, the
average number of swarming events was higher when
the colonies swarmed earlier in the year (Fig.4). Those
overwintered colonies that swarmed in March showed a
significantly higher average number of swarming events
per swarming cycle than those that swarmed in the other
months (Steel–Dwass multiple-comparison test, p < 0.05),
except for months in which the sample size was 2 or less.
In addition, the number of swarming events per swarming
cycle in overwintered colonies that swarmed in April was
significantly higher than that of May overwintered, June
re-swarmed, and July re-swarmed colonies (p < 0.05).
The median interval between the prime swarming and
first after-swarming was 6 days (interquartile range, 4–9
days) in the overwintered colonies and 7 days (interquar-
tile range, 3–9 days) in the re-swarmed colonies (Fig.5).
In contrast, the median interval between successive after-
swarming events was less than 3 days. The intervals of
both overwintered and re-swarmed colonies were sig-
nificantly longer between the prime swarming and first
after-swarming than any other combination (Steel–Dwass
multiple-comparison test, p < 0.05), except for intervals in
which the sample size was 6 or less. There was no signifi-
cant difference in the intervals between successive after-
swarming events.
Fig. 2 Frequency distribution of
the number of swarming events
in a swarming cycle. Red bars
indicate overwintered colonies,
and blue bars indicate re-
swarmed colonies (see Fig.1).
The numbers above the bars are
the total number of swarming
cycles (N = 253)
2
4
6
8
2000 2005 2010 2015 2020
Number of swarming events
in a swarming cycle
Sample Size
5
10
Re-swarmed
Overwintered
a
Mar 20
Apr 9
Apr 29
May 19
Jun 8
Jun 28
Jul 18
Aug 7
2000 2005 2010 2015 2020
Year
Date of prime swarming
b
Fig. 3 Temporal changes in the number of swarming events per
swarming cycle (a) and the date of the prime swarm (b). Red and
blue indicate overwintered and re-swarmed colonies, respectively
(see Fig.1). Each circle in (a) shows the total number of swarming
events in a swarming cycle. Each data point in (b) shows the date of
a prime swarm. The lines indicate the expected value of the number
of swarming events (a) or the date of the prime swarm (b) for a given
year. Shaded areas represent 95% Bayesian credible intervals for the
expected value
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

The Science of Nature (2024) 111:14 Page 5 of 8 14
Discussion
This study revealed an increase in the number of swarming
events per swarming cycle in Japanese honey bees between
2000 and 2022. In addition, over time, the swarming process
has started earlier in the year. The colonies swarmed more
often when swarming started in early spring (especially in
March). Considering the notably strong trend of tempera-
ture increase in March over the last two decades in Japan,
as reported by the Japan Meteorological Agency (Fig.S1),
the number of swarming events per swarming cycle may
have been increasing because swarming began earlier in the
year. That is, the increase in winter temperatures in Japan
(Fig.S2) has shortened the period during which pollen and
nectar cannot be collected, allowing more overwintering
bees to survive until spring, and more worker bees could
result in more swarming events per swarming cycle. Asian
honey bees (A. cerana) in tropical northern Vietnam often
swarm only 1 time per swarming cycle (Chinh etal. 2005),
whereas in temperate-mountainous western Pakistan, they
swarm an average of 6 times and up to 10 times per swarm-
ing cycle (Ruttner etal. 1972). Japanese honey bees are a
subspecies endemic to Japan and may also have the ability
to swarm more often than is currently observed. If the cli-
mate continues to become warmer, the number of swarm-
ing events per swarming cycle of Japanese honey bees may
continue to increase in the future.
Other studies have suggested changes in honey bee
behavior due to increasing temperatures. For example, the
0
1
2
3
4
5
6
7
8
9
10
Mar Apr May Jun Jul Aug
Month of prime swarming
Mean number of swarming events per swarming cycle
Overwintered Re-swarmed
a
(12)
b
(152)
c
(16)
c
(9)
c
(29)
bc
(32)
abc
(2)
abc
(1)
Fig. 4 The average number of swarming events per swarming cycle
in each month that prime swarming was recorded. The red and blue
bars indicate overwintered and re-swarmed colonies, respectively (see
Fig.1). Each data point shows the number of swarming events in a
swarming cycle. Error bars indicate standard errors. Different letters
indicate a significant difference according to a Steel–Dwass multiple-
comparison test (p < 0.05). The number in parentheses is the sample
size
Fig. 5 The number of days
between successive swarm-
ing events within a swarming
cycle. Ps and As indicate prime
swarming and after-swarming,
respectively. The number after
As indicates the order within
a swarming cycle. The red and
blue boxes indicate overwin-
tered and re-swarmed colonies,
respectively (see Fig.1). Red
and blue circles show the data
on which the box plot is based.
The number in parentheses is
the sample size. Different letters
indicate a significant difference
according to a Steel–Dwass
multiple-comparison test
(p < 0.05)
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

The Science of Nature (2024) 111:1414 Page 6 of 8
first cleansing flight (so-called spring cleaning) of Euro-
pean honey bees (A. mellifera) in Spain and Poland now
occurs earlier than it did several decades ago (Gordo and
Sanz 2006; Sparks etal. 2010). Considering that European
honey bees in temperate climates usually swarm in spring,
it is possible that not only the number of swarming events
per swarming cycle of Japanese honey bees but also that of
European honey bees has increased. Likewise, changes in
reproductive behavior due to temperature increase have been
noted in various animal species, raising concerns about phe-
nological mismatches with prey animals and plants (Char-
mantier etal. 2008; Altermatt 2010; Gutiérrez and Wilson
2020).
It is not uncommon for Japanese honey bee colonies to
starve and collapse in winter because of diminished col-
ony growth prior to winter caused by excessively repeated
swarming (Matsuura 2003), indicating that an increase in
the number of swarming events per swarming cycle may
not necessarily result in a population increase. In studies
of European honey bees, there was a positive correlation
between the number of workers in a swarming event and
subsequent colony growth (Lee and Winston 1987; Ran-
gel and Seeley 2012). Theoretical studies have shown that
smaller honey bee colonies are more likely to collapse
(Ulgezen etal. 2021), which can result from fewer workers
accompanying the queen to a new nest. European honey bees
and Asian honey bees swarm more often when nectar and
pollen resources are abundant (Seeley and Visscher 1985;
Chinh etal. 2005), which leads to higher colony density
during the swarming season when resources are abundant.
When resources then become scarce, competition intensifies,
and fewer colonies might survive long enough to overwin-
ter. If we can clarify the relationship between colony size
at swarming and/or the colony survival rate and number of
swarming events of Japanese honey bees, we may be able to
predict the effect of rising temperatures on this subspecies.
Our findings reveal several features of Japanese honey
bees. First, both overwintered and re-swarmed colonies
swarm more often early in the season. One hypothesis to
explain this is that early swarming may improve a colony’s
success when competing for nesting sites. Many European
honey bee colonies in temperate areas collapse during winter
(Döke etal. 2015; Seeley 2017). Similarly, in Japan, early
spring is when the most vacant nest sites are available for
Japanese honey bees because more than 20% of colonies fail
to overwinter (or more than 50% if infected with the tracheal
mite Acarapis woodi) between October and April (Maeda
and Sakamoto 2016). Colonies that swarm early would be
more likely to find high-quality nesting sites such that their
fitness would be enhanced. Likewise, swarming later in the
season may be less advantageous due to a relative lack of
nesting sites. In addition, early swarming allows the colony
enough time to stock up on resources to survive the winter
(Seeley and Visscher 1985). This hypothesis could be tested
by investigating changes in nesting site abundance and col-
ony survival rate.
Second, re-swarmed colonies swarm less than overwin-
tered colonies. One factor that may explain this is the limited
amount of time available in spring and summer with good
resource availability for a re-swarmed colony to recover its
worker population. In addition, it may be more advantageous
for re-swarmed colonies to increase the number of workers
per swarming event than overwintered colonies—that is, to
produce fewer after-swarms—because re-swarmed colonies
are at a competitive disadvantage to overwintered colonies
for nesting sites and resources. No other study has yet quan-
tified the differences in the number of swarming events per
swarming cycle between overwintered and re-swarmed colo-
nies. Our findings highlight the need to distinguish between
overwintered and re-swarmed colonies when analyzing the
number of swarming events per swarming cycle of not only
Japanese honey bees, but of all other honey bee populations
in which re-swarming occurs within the same year.
Finally, the period between the prime swarming and first
after-swarming of Japanese honey bees is longer than that
of other inter-swarm intervals. The median interval between
the prime swarming and first after-swarming was 6–7 days,
whereas subsequent swarming events were less than 3 days
apart. This might be related to the fact that the mated queen
generally leaves the nest in the prime swarming (Winston
etal. 1981). When more than one honey bee queen exists
in a nest, they will usually kill each other until there is only
one left (Gilley and Tarpy 2005). Thus, it might be adap-
tive for the mated queen to leave and construct a new nest
before the daughter queens emerge (but for a counterexam-
ple, see Otis 1980). In Africanized honey bees, the interval
between prime swarming and the first after-swarming is
usually around 8–10 days (Otis 1980), slightly longer than
in Japanese honey bees. This difference may arise from
variations in the duration and/or process of queen rearing.
Conversely, intervals between after-swarming events were
similar in Africanized honey bees (Otis 1980) and Japanese
honey bees, suggesting that in both species, numerous new
queens are reared before prime swarming, leading to swarm-
ing at short intervals. Overall, the interval between honey
bee swarming events likely follows a common rule.
This is the first report of the long-term change in the
number of swarming events per swarming cycle of honey
bees, providing a new perspective on the interaction between
the reproductive behavior of honey bees and the environ-
ment. However, the impacts of temperature on the number
of swarming events per swarming cycle of Japanese honey
bees, as well as other species and subspecies of honey bees,
should be verified by analyzing data from regions with vari-
ous temperatures. Many interactions related to swarming,
such as the relationship between the number of swarming
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

The Science of Nature (2024) 111:14 Page 7 of 8 14
events per swarming cycle and colony survival, as well as
the proximate factors that determine the number of swarm-
ing events per swarming cycle, remain unexplained. Future
studies will need to clarify the relationships between swarm-
ing events and biotic and abiotic factors and quantitatively
analyze the impact of each factor.
Supplementary Information The online version contains supplemen-
tary material available at https:// doi. org/ 10. 1007/ s00114- 024- 01902-y.
Acknowledgements We deeply appreciate the 20 keepers of Japanese
honey bees for providing the swarming records. We also thank Dr.
Shumpei Hisamoto for helpful advice regarding the analysis. In addi-
tion, we appreciate the valuable comments and constructive feedback
from the editor and two reviewers, which improved this manuscript.
Author contribution Both authors contributed to the study conception
and design. Material preparation, data collection, and analysis were
performed by Kiyohito Morii. The first draft of the manuscript was
written by Kiyohito Morii, and both authors read and approved the
final manuscript.
Funding Partial financial support was received from JSPS KAKENHI
Grant Numbers JP20H00425 and JP23K13970.
Data availability The datasets generated during and/or analyzed dur-
ing the current study are available from the corresponding author on
reasonable request.
Declarations
Conflict of interest The authors declare no competing interests.
Open Access This article is licensed under a Creative Commons Attri-
bution 4.0 International License, which permits use, sharing, adapta-
tion, distribution and reproduction in any medium or format, as long
as you give appropriate credit to the original author(s) and the source,
provide a link to the Creative Commons licence, and indicate if changes
were made. The images or other third party material in this article are
included in the article’s Creative Commons licence, unless indicated
otherwise in a credit line to the material. If material is not included in
the article’s Creative Commons licence and your intended use is not
permitted by statutory regulation or exceeds the permitted use, you will
need to obtain permission directly from the copyright holder. To view a
copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
References
Altermatt F (2010) Climatic warming increases voltinism in Euro-
pean butterflies and moths. Proc R Soc B 277(1685):1281–1287.
https:// doi. org/ 10. 1098/ rspb. 2009. 1910
Alzate-Marin AL, Rivas PMS, Galaschi-Teixeira JS, etal. (2021)
Warming and elevated CO2 induces changes in the reproductive
dynamics of a tropical plant species. Sci Total Environ 768, Arti-
cle 144899. https:// doi. org/ 10. 1016/j. scito tenv. 2020. 144899
Aryal B (2019) Mating behavior of Apis cerana. Res Rev J Crop Sci
Technol 8:1–5
Aslan CE, Liang CT, Galindo B, Kimberly H, Topete W (2016) The
role of honey bees as pollinators in natural areas. Natural Areas J
36(4):478–488. https:// doi. org/ 10. 3375/ 043. 036. 0413
Calderone NW (2012) Insect pollinated crops, insect pollinators and
US agriculture: trend analysis of aggregate data for the period
1992–2009. PLoS ONE 7(5):e37235. https:// doi. org/ 10. 1371/
journ al. pone. 00372 35
Charmantier A, McCleery RH, Cole LR, Perrins C, Kruuk LEB, Shel-
don BC (2008) Adaptive phenotypic plasticity in response to cli-
mate change in a wild bird population. Science 320(5877):800–
803. https:// doi. org/ 10. 1126/ scien ce. 11571 74
Chinh TX, Boot WJ, Sommeijer MJ (2005) Production of reproduc-
tives in the honey bee species Apis cerana in northern Vietnam.
J Apicult Res 44:41–48. https:// doi. org/ 10. 1080/ 00218 839. 2005.
11101 146
Crane E (1984) Honeybees. Manson IL (ed) Evolution of domesticated
animals. Longman Group, London, 403–415
Diffenbaugh NS, Field CB (2013) Changes in ecologically critical
terrestrial climate conditions. Science 341(6145):486–492.
https:// doi. org/ 10. 1126/ scien ce. 12371 23
Döke MA, Frazier M, Grozinger CM (2015) Overwintering honey
bees: biology and management. Curr Opin Insect Sci 10:185–
193. https:// doi. org/ 10. 1016/j. cois. 2015. 05. 014
Engel MS (1999) The taxonomy of recent and fossil honey bees
(Hymenoptera: Apidae; Apis). J Hymenopt Res 8(2):165–196
Forister ML, Shapiro AM (2003) Climatic trends and advancing
spring flight of butterflies in lowland California. Glob Chang
Biol 9:1130–1135. https:// doi. org/ 10. 1046/j. 1365- 2486. 2003.
00643.x
Garcia RA, Cabeza M, Rahbek C, Araújo MB (2014) Multiple dimen-
sions of climate change and their implications for biodiversity.
Science 344(6183):1247579. https:// doi. org/ 10. 1126/ scien ce.
12475 79
Gelman A, Carlin JB, Stern HS, Rubin DB (2004) Bayesian data analy-
sis, 2nd edn. Chapman and Hall, Boca Raton
Gilley DC, Tarpy DR (2005) Three mechanisms of queen elimination
in swarming honey bee colonies. Apidologie 36:461–474. https://
doi. org/ 10. 1051/ apido: 20050 33
Gordo O, Sanz JJ (2006) Temporal trends in phenology of the honey
bee Apis mellifera (L.) and the small white Pieris rapae (L.) in
the Iberian Peninsula (1952–2004). Ecol Entomol 31(3):261–268.
https:// doi. org/ 10. 1111/j. 1365- 2311. 2006. 00787.x
Grozinger CM, Richards J, Mattila HR (2014) From molecules to soci-
eties: mechanisms regulating swarming behavior in honey bees
(Apis spp.). Apidologie 45:327–346. https:// doi. org/ 10. 1007/
s13592- 013- 0253-2
Gutiérrez D, Wilson RJ (2020) Intra- and interspecific variation in the
responses of insect phenology to climate. J Anim Ecol 90:248–
259. https:// doi. org/ 10. 1111/ 1365- 2656. 13348
Halsch CA, Shapiro AM, Fordyce JA, Forister ML (2021) Insects and
recent climate change. PNAS 118(2):e2002543117. https:// doi.
org/ 10. 1073/ pnas. 20025 43117
Harvey JA, Tougeron K, Gols R etal (2023) Scientists’ warning on
climate change and insects. Ecol Monogr 93(1):e1553. https://
doi. org/ 10. 1002/ ecm. 1553
Havard T, Laurent M, Chauzat MP (2019) Impact of stressors on honey
bees (Apis mellifera; Hymenoptera: Apidae): some guidance for
research emerge from a meta-analysis. Diversity 12(1):7. https://
doi. org/ 10. 3390/ d1201 0007
Hutchings MJ, Robbirt KM, Roberts DL, Davy AJ (2018) Vulnerability
of a specialized pollination mechanism to climate change revealed
by a 356-year analysis. Bot J Linn Soc 186(4):498–509. https://
doi. org/ 10. 1093/ botli nnean/ box086
Hyatt S (2012) Asian honey bee (Apis cerana javana) in Cairns, Far
North Queensland: foraging, nesting and swarming behaviour.
Technical Report. State of Queensland, Brisbane.
Iwasaki Y, Ihara M (1994) Japanese honeybees in Ina Valley (Nagano
Prefecture). Honeybee Science 15:7–18 (in Japanese)
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

The Science of Nature (2024) 111:1414 Page 8 of 8
Kearney M, Shine R, Porter WP (2009) The potential for behavioral
thermoregulation to buffer “cold-blooded” animals against cli-
mate warming. PNAS 106(10):3835–3840. https:// doi. org/ 10.
1073/ pnas. 08089 13106
Klein AM, Vaissière BE, Cane JH, Steffan-Dewenter I, Cunningham
SA, Kremen C, Tscharntke T (2006) Importance of pollinators in
changing landscapes for world crops. Proc R Soc B 274:303–313.
https:// doi. org/ 10. 1098/ rspb. 2006. 3721
Le Conte Y, Navajas M (2008) Climate change: impact on honey
bee populations and diseases. Rev Sci Tech - off Int Épizoot
27(2):499–510
Lee PC, Winston ML (1987) Effects of reproductive timing and colony
size on the survival, offspring colony size and drone production in
the honey bee (Apis mellifera). Ecol Entomol 12:187–195. https://
doi. org/ 10. 1111/j. 1365- 2311. 1987. tb009 97.x
Maeda T, Sakamoto Y (2016) Tracheal mites, Acarapis woodi, greatly
increase overwinter mortality in colonies of the Japanese honey-
bee, Apis cerana japonica. Apidologie 47:762–770. https:// doi.
org/ 10. 1007/ s13592- 016- 0434-x
Matsuura M (2003) Biology and control of social wasps and bees in
urban environments. III. Life cycle characteristics of Apis mel-
lifera and A. cerana in urban area with a note on some troubles
caused by the honeybees in Japan. Honeybee Sci 24:195–207 (in
Japanese)
Miller-Struttmann NE, Geib JC, Franklin JD etal (2015) Functional
mismatch in a bumble bee pollination mutualism under climate
change. Science 349(6255):1541–1544. https:// doi. org/ 10. 1126/
scien ce. aab08 68
Nürnberger F, Härtel S, Steffan-Dewenter I (2019) Seasonal timing
in honey bee colonies: phenology shifts affect honey stores and
varroa infestation levels. Oecologia 189:1121–1131. https:// doi.
org/ 10. 1007/ s00442- 019- 04377-1
Nuru A, Amssalu B, Hepburn HR, Radloff SE (2002) Swarming and
migration in the honey bees (Apis mellifera) of Ethiopia. J Apicult
Res 41:35–41. https:// doi. org/ 10. 1080/ 00218 839. 2002. 11101 066
Okada I (1997) A book on the Japanese honeybee. Tamagawa Univer-
sity press, Tokyo, 40. (in Japanese)
Otis GW (1980) The swarming biology and population dynamics of the
Africanized honey bee. PhD dissertation, University of Kansas,
Lawrence, KS
Otis GW (1991) Population biology of the Africanized honey bee. In:
Spivak M, Fletcher DJC, Breed MD (ed) The African honey bee.
Westview Press, Boulder, Colorado, 403–415. https:// doi. org/ 10.
1201/ 97804 29308 741
Pecl GT, Araújo MB, Bell JD etal (2017) Biodiversity redistribution
under climate change: impacts on ecosystems and human well-
being. Science 355(6332):aai9214. https:// doi. org/ 10. 1126/ scien
ce. aai92 14
Rangel J, Seeley TD (2012) Colony fissioning in honey bees: size and
significance of the swarm fraction. Insect Soc 59:453–462. https://
doi. org/ 10. 1007/ s00040- 012- 0239-5
Ruttner F, Woyke J, Koeniger N (1972) Reproduction in Apis cerana.
1. Mating Behaviour J Apicult Res 11:141–146. https:// doi. org/
10. 1080/ 00218 839. 1972. 11099 714
Sasaki M (1999) Wonders of the Japanese honeybee–Biology of
Northernmost Apis cerana. Kaiyusha, Tokyo, p 40–51 (in
Japanese)
Seeley TD (1985) Honeybee ecology: a study of adaptation in social
life. Princeton University Press, Princeton
Seeley TD (2017) Life-history traits of wild honey bee colonies liv-
ing in forests around Ithaca, NY, USA. Apidologie 48:743–754.
https:// doi. org/ 10. 1007/ s13592- 017- 0519-1
Seeley TD, Visscher PK (1985) Survival of honey bees in cold cli-
mates: the critical timing of colony growth and reproduction. Ecol
Entomol 10(1):1081–1088. https:// doi. org/ 10. 1111/j. 1365- 2311.
1985. tb005 37.x
Sparks TH, Langowska A, Głazaczow A, Wilkaniec Z, Bieńkowska M,
Tryjanowski P (2010) Advances in the timing of spring cleaning
by the honeybee Apis mellifera in Poland. Ecol Entomol 35:788–
791. https:// doi. org/ 10. 1111/j. 1365- 2311. 2010. 01226.x
Su YC, Chiu YF, Warrit N, Otis GW, Smith DR (2023) Phylogeography
and species delimitation of the Asian cavity-nesting honeybees.
Insect Syst Divers 7(4):5. https:// doi. org/ 10. 1093/ isd/ ixad0 15
Switanek M, Crailsheim K, Truhetz H, Brodschneider R (2017) Mod-
elling seasonal effects of temperature and precipitation on honey
bee winter mortality in a temperate climate. Sci Total Environ
579:1581–1587. https:// doi. org/ 10. 1016/j. scito tenv. 2016. 11. 178
Tschinkel WR (1991) Insect sociometry, a field in search of data. Ins
Soc 38:77–82. https:// doi. org/ 10. 1007/ BF012 42715
Ulgezen ZN, Dooremalen CV, Langevelde FV (2021) Understand-
ing social resilience in honeybee colonies. Curr Res Insect Sci
1:100021. https:// doi. org/ 10. 1016/j. cris. 2021. 100021
Winston ML (1980) Swarming, afterswarming, and reproductive rate
of unmanaged honeybee colonies (Apis mellifera). Insect Soc
27:391–398. https:// doi. org/ 10. 1007/ BF022 23731
Winston ML, Dropkin JA, Taylor OR (1981) Demography and life
history characteristics of two honey bee races (Apis mellifera).
Oecologia 48(3):407–413. https:// www. jstor. org/ stable/ 42163 31
Yoshida T (1997a) Japanese honeybee, ecology and its rearing methods
II. Honeybee Sci 18:65–80 (in Japanese)
Yoshida T (1997b) Japanese honeybee, ecology and its rearing methods
IV. Honeybee Sci 18:165–174 (in Japanese)
Yoshida T (1998) Japanese honeybee, ecology and its rearing methods
V. Honeybee Sci 19:27–36 (in Japanese)
Publisher's Note Springer Nature remains neutral with regard to
jurisdictional claims in published maps and institutional affiliations.
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

1.
2.
3.
4.
5.
6.
Terms and Conditions
Springer Nature journal content, brought to you courtesy of Springer Nature Customer Service Center GmbH (“Springer Nature”).
Springer Nature supports a reasonable amount of sharing of research papers by authors, subscribers and authorised users (“Users”), for small-
scale personal, non-commercial use provided that all copyright, trade and service marks and other proprietary notices are maintained. By
accessing, sharing, receiving or otherwise using the Springer Nature journal content you agree to these terms of use (“Terms”). For these
purposes, Springer Nature considers academic use (by researchers and students) to be non-commercial.
These Terms are supplementary and will apply in addition to any applicable website terms and conditions, a relevant site licence or a personal
subscription. These Terms will prevail over any conflict or ambiguity with regards to the relevant terms, a site licence or a personal subscription
(to the extent of the conflict or ambiguity only). For Creative Commons-licensed articles, the terms of the Creative Commons license used will
apply.
We collect and use personal data to provide access to the Springer Nature journal content. We may also use these personal data internally within
ResearchGate and Springer Nature and as agreed share it, in an anonymised way, for purposes of tracking, analysis and reporting. We will not
otherwise disclose your personal data outside the ResearchGate or the Springer Nature group of companies unless we have your permission as
detailed in the Privacy Policy.
While Users may use the Springer Nature journal content for small scale, personal non-commercial use, it is important to note that Users may
not:
use such content for the purpose of providing other users with access on a regular or large scale basis or as a means to circumvent access
control;
use such content where to do so would be considered a criminal or statutory offence in any jurisdiction, or gives rise to civil liability, or is
otherwise unlawful;
falsely or misleadingly imply or suggest endorsement, approval , sponsorship, or association unless explicitly agreed to by Springer Nature in
writing;
use bots or other automated methods to access the content or redirect messages
override any security feature or exclusionary protocol; or
share the content in order to create substitute for Springer Nature products or services or a systematic database of Springer Nature journal
content.
In line with the restriction against commercial use, Springer Nature does not permit the creation of a product or service that creates revenue,
royalties, rent or income from our content or its inclusion as part of a paid for service or for other commercial gain. Springer Nature journal
content cannot be used for inter-library loans and librarians may not upload Springer Nature journal content on a large scale into their, or any
other, institutional repository.
These terms of use are reviewed regularly and may be amended at any time. Springer Nature is not obligated to publish any information or
content on this website and may remove it or features or functionality at our sole discretion, at any time with or without notice. Springer Nature
may revoke this licence to you at any time and remove access to any copies of the Springer Nature journal content which have been saved.
To the fullest extent permitted by law, Springer Nature makes no warranties, representations or guarantees to Users, either express or implied
with respect to the Springer nature journal content and all parties disclaim and waive any implied warranties or warranties imposed by law,
including merchantability or fitness for any particular purpose.
Please note that these rights do not automatically extend to content, data or other material published by Springer Nature that may be licensed
from third parties.
If you would like to use or distribute our Springer Nature journal content to a wider audience or on a regular basis or in any other manner not
expressly permitted by these Terms, please contact Springer Nature at
onlineservice@springernature.com