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Honey bee colony winter loss rates for 35 countries participating in the COLOSS survey for winter 2018-2019, and the effects of a new queen on the risk of colony winter loss

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This article presents managed honey bee colony loss rates over winter 2018/19 resulting from using the standardised COLOSS questionnaire in 35 countries (31 in Europe). In total, 28,629 beekeepers supplying valid loss data wintered 738,233 colonies, and reported 29,912 (4.1%, 95% confidence interval (CI) 4.0–4.1%) colonies with unsolvable queen problems, 79,146 (10.7%, 95% CI 10.5–10.9%) dead colonies after winter and 13,895 colonies (1.9%, 95% CI 1.8–2.0% lost through natural disaster. This gave an overall colony winter loss rate of 16.7% (95% CI 16.4–16.9%), varying greatly between countries, from 5.8% to 32.0%. We modelled the risk of loss as a dead/empty colony or from unresolvable queen problems, and found that, overall, larger beekeeping operations with more than 150 colonies experienced significantly lower losses (p<0.001), consistent with earlier studies. Additionally, beekeepers included in this survey who did not migrate their colonies at least once in 2018 had significantly lower losses than those migrating (p<0.001). The percentage of new queens from 2018 in wintered colonies was also examined as a potential risk factor. The percentage of colonies going into winter with a new queen was estimated as 55.0% over all countries. Higher percentages of young queens corresponded to lower overall losses (excluding losses from natural disaster), but also lower losses from unresolvable queen problems, and lower losses from winter mortality (p<0.001). Detailed results for each country and overall are given in a table, and a map shows relative risks of winter loss at regional level.
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Honey bee colony winter loss rates for 35 countries participating in the
COLOSS survey for winter 2018-2019, and the effects of a new queen on the
risk of colony winter loss
ArticleinJournal of Apicultural Research · August 2020
DOI: 10.1080/00218839.2020.1797272
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Honey bee colony winter loss rates for 35
countries participating in the COLOSS survey for
winter 2018–2019, and the effects of a new queen
on the risk of colony winter loss
Alison Gray , Noureddine Adjlane , Alireza Arab , Alexis Ballis , Valters
Brusbardis , Jean-Daniel Charrière , Robert Chlebo , Mary F. Coffey , Bram
Cornelissen , Cristina Amaro da Costa , Bjørn Dahle , Jiří Danihlík , Marica
Maja Dražić , Garth Evans , Mariia Fedoriak , Ivan Forsythe , Anna Gajda ,
Dirk C. de Graaf , Aleš Gregorc , Iliyana Ilieva , Jes Johannesen , Lassi Kauko ,
Preben Kristiansen , Maritta Martikkala , Raquel Martín-Hernández , Carlos
Aurelio Medina-Flores , Franco Mutinelli , Solenn Patalano , Aivar Raudmets ,
Gilles San Martin , Victoria Soroker , Jevrosima Stevanovic , Aleksandar
Uzunov , Flemming Vejsnaes , Anthony Williams , Marion Zammit-Mangion &
Robert Brodschneider
To cite this article: Alison Gray , Noureddine Adjlane , Alireza Arab , Alexis Ballis , Valters
Brusbardis , Jean-Daniel Charrière , Robert Chlebo , Mary F. Coffey , Bram Cornelissen , Cristina
Amaro da Costa , Bjørn Dahle , Jiří Danihlík , Marica Maja Dražić , Garth Evans , Mariia Fedoriak ,
Ivan Forsythe , Anna Gajda , Dirk C. de Graaf , Aleš Gregorc , Iliyana Ilieva , Jes Johannesen ,
Lassi Kauko , Preben Kristiansen , Maritta Martikkala , Raquel Martín-Hernández , Carlos Aurelio
Medina-Flores , Franco Mutinelli , Solenn Patalano , Aivar Raudmets , Gilles San Martin , Victoria
Soroker , Jevrosima Stevanovic , Aleksandar Uzunov , Flemming Vejsnaes , Anthony Williams ,
Marion Zammit-Mangion & Robert Brodschneider (2020): Honey bee colony winter loss rates for 35
countries participating in the COLOSS survey for winter 2018–2019, and the effects of a new queen
on the risk of colony winter loss, Journal of Apicultural Research
To link to this article: https://doi.org/10.1080/00218839.2020.1797272
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NOTES AND COMMENTS
Honey bee colony winter loss rates for 35 countries participating in the COLOSS
survey for winter 20182019, and the effects of a new queen on the risk of colony
winter loss
Alison Gray
a
 , Noureddine Adjlane
b
, Alireza Arab
c
, Alexis Ballis
d
, Valters Brusbardis
e
, Jean-Daniel
Charri
ere
f
, Robert Chlebo
g
, Mary F. Coffey
h
, Bram Cornelissen
i
, Cristina Amaro da Costa
j
, Bjørn
Dahle
k
,Ji
r
ıDanihl
ık
l
, Marica Maja Dra
zi
c
m
, Garth Evans
n
, Mariia Fedoriak
o
, Ivan Forsythe
p
, Anna
Gajda
q
, Dirk C. de Graaf
r
, Ale
s Gregorc
s
, Iliyana Ilieva
t
, Jes Johannesen
u
, Lassi Kauko
v
, Preben
Kristiansen
w
, Maritta Martikkala
x
, Raquel Mart
ın-Hern
andez
y
, Carlos Aurelio Medina-Flores
z
, Franco
Mutinelli
aa
, Solenn Patalano
bb
, Aivar Raudmets
cc
, Gilles San Martin
dd
, Victoria Soroker
ee
, Jevrosima
Stevanovic
ff
, Aleksandar Uzunov
gg
, Flemming Vejsnaes
hh
, Anthony Williams
ii
, Marion Zammit-Mangion
jj
and
Robert Brodschneider
kk
a
Department of Mathematics and Statistics, University of Strathclyde, Glasgow, UK;
b
Department of Agronomy, Universit
eMhamed
Bougara, Boumerde, Algeria;
c
Department of Animal Science, University of Tehran, Karaj, Iran;
d
Chambre d'agriculture d'Alsace,
Strasbourg, France;
e
Latvian Beekeepers Association, Jelgava, Latvia;
f
Agroscope, Swiss Bee Research Center, Bern, Switzerland;
g
Department of Animal Science, Slovak University of Agriculture, Nitra, Slovakia;
h
Department of Biological Sciences, University of Limerick,
Limerick, Ireland;
i
Wageningen Plant Research, Wageningen University & Research, Wageningen, Netherlands;
j
Agriculture School,
Politechnic Institute of Viseu, Viseu, Portugal;
k
Norwegian Beekeepers Association, Kløfta, Norway;
l
Department of Biochemistry, Palack
y
University Olomouc, Olomouc, Czech Republic;
m
Ministry of Agriculture, Zagreb, Croatia;
n
Welsh Beekeepers Association, Northop, UK;
o
Department of Ecology and Biomonitoring, Yuriy Fedkovych Chernivtsi National University, Chernivtsi, Ukraine;
p
The Agri-Food and
Biosciences Institute, Belfast, UK;
q
Institute of Veterinary Medicine, Department of Pathology and Veterinary Diagnostics, Warsaw
University of Life Sciences, Warsaw, Poland;
r
Honeybee Valley, Ghent University, Ghent, Belgium;
s
Faculty of Agriculture and Life Sciences,
University of Maribor, Maribor, Slovenia;
t
Department of Developmental Biology, University of Plovdiv "Paisii Hilendarski", Plovdiv, Bulgaria;
u
DLR Fachzentrum f
ur Bienen und Imkerei, Mayen, Germany;
v
Finnish Beekeepers Association, K
oyli
o, Finland;
w
Swedish Board of
Agriculture, Joenkoeping, Sweden;
x
Finnish Beekeepers Association, Kangasala, Finland;
y
Centro de Investigaci
on Ap
ıcola y Agroambiental de
Marchamalo (IRIAF), Marchamalo, Spain;
z
Faculty of Veterinary Medicine and Animal Science, University of Zacatecas, Zacatecas, Mexico;
aa
Istituto Zooprofilattico Sperimentale delle Venezie, NRL for honey bee health, Legnaro, Italy;
bb
Institute of Basic Biomedical Sciences
(IBBS), B.S.R.C «Alexander Fleming», Vari, Greece;
cc
Estonian Beekeepers Association, Tallinn, Estonia;
dd
Walloon Agricultural Research
Centre (CRA-W), Gembloux, Belgium;
ee
The Volcani Center, Agricultural Research Organisation, Rishon LeZion, Israel;
ff
Department of
Biology, Faculty of Veterinary Medicine, University of Belgrade, Belgrade, Serbia;
gg
Faculty of Agricultural Sciences and Food, Ss. Cyril and
Methodius University, Skopje, North Macedonia;
hh
Danish Beekeepers Association, Sorø, Denmark;
ii
School of Computer Science and
Informatics, De Montfort University, Leicester, UK;
jj
Department of Physiology and Biochemistry, University of Malta, Msida, Malta;
kk
Institute of Biology, University of Graz, Graz, Austria
(Received 2 June 2020; accepted 14 July 2020)
This article presents managed honey bee colony loss rates over winter 2018/19 resulting from using the standardised
COLOSS questionnaire in 35 countries (31 in Europe). In total, 28,629 beekeepers supplying valid loss data wintered
738,233 colonies, and reported 29,912 (4.1%, 95% confidence interval (CI) 4.04.1%) colonies with unsolvable queen
problems, 79,146 (10.7%, 95% CI 10.510.9%) dead colonies after winter and 13,895 colonies (1.9%, 95% CI 1.82.0%)
lost through natural disaster. This gave an overall colony winter loss rate of 16.7% (95% CI 16.416.9%), varying greatly
between countries, from 5.8% to 32.0%. We modelled the risk of loss as a dead/empty colony or from unresolvable
queen problems, and found that, overall, larger beekeeping operations with more than 150 colonies experienced signifi-
cantly lower losses (p<0.001), consistent with earlier studies. Additionally, beekeepers included in this survey who did
not migrate their colonies at least once in 2018 had significantly lower losses than those migrating (p<0.001). The per-
centage of new queens from 2018 in wintered colonies was also examined as a potential risk factor. The percentage of
colonies going into winter with a new queen was estimated as 55.0% over all countries. Higher percentages of young
queens corresponded to lower overall losses (excluding losses from natural disaster), but also lower losses from unre-
solvable queen problems, and lower losses from winter mortality (p<0.001). Detailed results for each country and
overall are given in a table, and a map shows relative risks of winter loss at regional level.
Keywords: Apis mellifera; mortality; colony winter losses; queens; queen replacement; monitoring surveys; beekeeping;
citizen science
Corresponding author: E-mail: Robert.Brodschneider@uni-graz.at
Did data processing and editing, all statistical analysis and produced the map and plots.
ß2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group
This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/
licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not
altered, transformed, or built upon in any way.
Journal of Apicultural Research, 2020
https://doi.org/10.1080/00218839.2020.1797272
The COLOSS monitoring group has been active in
studying honey bee colony losses through national sur-
veys of beekeepers since 2008, and now consists of
over 30 countries regularly taking part in this central
activity of the COLOSS research association. This short
article is the fourth in a series of bulletins presenting
summary results from the annual colony winter loss
survey of the COLOSS monitoring group
(Brodschneider et al., 2016,2018; Gray et al., 2019).
Each such survey is carried out via a network of
national co-ordinators organising sample selection and
using a self-administered standardised questionnaire
developed by the monitoring group (van der Zee et al.,
2013), which is reviewed and improved each year as it
is felt necessary or desirable. This standardisation ena-
bles comparison of results between countries and also
over time. Here we examine colony loss rates over
winter 2018/19, from the survey carried out in
spring 2019.
In addition to reporting winter loss rates for each
participating country and for the overall data set across
all the participating countries, here we also examine
possible association of the effect of queen age or re-
queening on the probability of winter loss. Earlier
articles examined the effects of operation size, migra-
tion, and of six specific sources of forage
(Brodschneider et al., 2016, 2018; Gray et al., 2019),
both overall for all countries taking part and individually
at country level.
To study winter loss rates, beekeepers were asked
to state the number of colonies wintered, and how
many of these colonies after winter (a) were alive but
had unsolvable queen problems (e.g., a missing queen,
laying workers, or a drone-egg laying queen), (b) were
dead or reduced to a few hundred bees and (c) were
lost through natural disaster (from various possible
causes). The overall proportion of colonies lost was
found by calculating the sum given by (a þbþc), which
was then divided by the number of colonies going into
winter. The data files from each country were checked
for consistency of loss data using established checks
reported in Brodschneider et al. (2018). Responses with
insufficient or illogical answers were excluded, but the
number of such responses is, in general, relatively small
and has been declining over the last few years owing to
several factors: greater awareness of these issues on
the part of the national co-ordinators, efforts made to
give clearer guidance to the beekeepers completing the
questionnaire, data checks now built in to the online
survey platform used by a large number of the partici-
pating countries, and more filtering of inconsistent
answers being done at national level before data submis-
sion. Hence the quality of data sent for central process-
ing is improving.
A strength of these studies is in the number of bee-
keepers and colonies represented over many countries,
giving greater power to the statistical analysis. In this
article the results derive from 28,629 beekeepers in 35
countries (compared to 36, 30 and 29 countries in the
previous three surveys in 2018, 2017 and 2016, respect-
ively). A notable addition to the countries providing
data for winter 2018/19 is Iran, from where 1,653 bee-
keepers submitted data on 230,093 colonies. This
expands the limited number of non-European countries
participating in the COLOSS monitoring: the others are
Algeria and Israel, which have participated consistently
over the years, and Mexico, which joined relatively
recently. Some other countries do carry out similar
work independently of this COLOSS monitoring group.
In total, 28,822 responses were received from bee-
keepers, of which 28,629 (99.3%) satisfied checks for
consistency of colony loss data provided, the largest
number yet represented in these surveys. These 28,629
beekeepers collectively managed 738,233 colonies going
into winter, a considerable increase on the 544,879 col-
onies studied in the previous monitoring group survey.
This time, 29,912 (4.1%) colonies were reported lost
due to unsolvable queen problems, 79,146 (10.7%) colo-
nies were reported dead after winter and 13,895 (1.9%)
colonies were reported as lost due to natural disaster
(Table 1), with an overall loss rate of 16.7%. These are
similar to the results from the 2018 survey (4.8% of col-
onies reported lost due to unsolvable queen problems,
10.0% reported dead after winter and 1.5% reported as
lost due to natural disaster) which found an overall loss
rate of 16.4%. For the present study, considering the
European countries only, and also the countries belong-
ing to the European Union (EU countries, including the
UK, which was a member state over winter 2018/
2019), respectively, the results were as follows: 26,690
and 23,618 beekeepers had valid loss data, wintering
466,839 and 381,813 colonies, 3.8% in each case were
reported as lost due to queen problems, 9.8% in each
case were reported dead/empty after winter, and 0.94%
and 0.90% for the European and EU countries, respect-
ively were reported lost due to natural disaster, giving
overall loss rates of 14.5% in each case, a little lower
than for the overall data set. The rates of loss resulting
from queen problems and natural disasters are consist-
ent with those in the previous years of study (Gray
et al., 2019).
The overall loss rates for winter 2018/19 vary con-
siderably between countries, as we have found in all of
our studies so far (Table 1,Figure 1(a)). The highest
loss rate of 32.0% was in Slovenia, and (as for the previ-
ous winter; Gray et al., 2019) the lowest loss rate was
in Bulgaria, at 5.8%. Slovenia also had one of the highest
loss rates in winter 2017/18. The next highest loss rate
for winter 2018/19 was for Serbia, at 25.4%, while the
highest ones after that, between 20% and 25%, were for
Spain, Croatia, Iran, Greece and Portugal, in descending
size of loss rate. In contrast, Serbia had one of the low-
est loss rates (7.4%) the previous winter. A relatively
high rate of loss (22.1%) over winter 2018/19 was
2A. Gray et al.
Table 1. Winter 2018/19 survey results, showing number of respondents with valid loss data, corresponding number of colonies going into winter, honey bee colony mortality rate and
rates of loss due to queen problems and natural disasters (each with 95% confidence intervals (CIs)).
Country
No. of
respondents
No. of
colonies
going into
winter
% Mortality
Rate
(95% CI)
% Rate of loss of
colonies due to
queen problems
(95% CI)
% Rate of loss of
colonies due
to natural
disasters
(95% CI)
Overall
winter
loss rate
(95% CI)
Estimated %
of beekeepers
represented
Effect of % of
new queens
on losses
excluding
natural disaster
Effect of % of new
queens on queen
problem losses
Effect of % of
new queens
on dead/empty
colonies
EU countries
Austria 1534 33651 11.4 (10.612.2) 3.9 (3.64.1) 0.5 (0.40.7) 15.7 (14.916.6) 5  1>2,3,4; 2 >4 1>2,3,4  1>3,4; 2 >4
Belgium 814 6326 7.3 (6.38.3) 3.1 (2.73.6) 0.4 (0.20.6) 10.7 (9.711.9) 9 ns ns nsd
Bulgaria
1,2
34 5876 3.7 (2.06.7) 1.3 (0.53.5) 0.9 (0.15.9) 5.8 (3.310.2) <1ns ns ns
Croatia 135 7968 20.4 (16.824.6) 2.9 (2.33.7) 0.6 (0.31.4) 24.0 (20.328.1) 2 ns ns ns
Czech Republic 1209 20724 8.9 (8.19.9) 3.1 (2.83.4) 0.7 (0.50.9) 12.7 (11.713.7) 2  1>2,3,4 ns  1>2,3,4
Denmark 1132 12941 5.8 (5.16.7) 3.4 (2.93.8) 0.6 (0.40.8) 9.8 (8.910.7) 17  1>2,4; 2,3 >4 1,3 >4 1>3,4
England 715 3851 4.4 (3.75.4) 4.6 (4.05.4) 0.4 (0.20.8) 9.5 (8.510.6) 2  2>1,3,4 nsd  2>3
Estonia 125 4567 8.3 (6.111.2) 3.1 (2.43.9) 1.8 (1.22.6) 13.2 (10.416.6) 2  1>2,3,4 ns  1>2,3,4
Finland 250 8011 3.7 (2.94.6) 2.0 (1.62.4) 0.6 (0.41.1) 6.3 (5.47.4) 8 ns ns ns
France
1
317 11915 6.3 (5.27.7) 3.2 (2.83.8) 0.6 (0.31.2) 10.2 (8.911.6) <1 ns (just) 4 >2ns 4>2
Germany 10461 124168 11.6 (11.312.0) 2.9 (2.83.0) 0.3 (0.30.4) 14.8 (14.515.2) 8  2>3 2,4 >1 1,2 >3
Greece 232 23216 13.4 (10.816.6) 6.0 (5.27.0) 1.8 (1.12.8) 21.2 (18.324.4) 1  1>2,3,4 ns  1>2,3,4
Ireland 376 3610 3.9 (3.24.8) 6.4 (5.47.5) 0.4 (0.20.9) 10.7 (9.412.2) 13 2>3ns1>3
Italy
1
381 24021 8.8 (7.89.8) 5.0 (4.45.6) 2.7 (2.33.3) 16.5 (15.217.9) <11>3ns
 1,2 >3
Latvia 319 12893 8.4 (7.110.0) 4.5 (3.26.2) 1.2 (0.81.9) 14.1 (12.116.4) 7 ns nsd ns
Malta 33 907 7.4 (4.312.5) 5.8 (3.210.5) 3.5 (2.06.2) 16.8 (11.923.1) 11 ns  3>1ns
Netherlands 1740 12378 3.6 (3.24.0) 8.2 (7.29.3) 0.3 (0.20.5) 12.1 (11.113.3) 19  3>4 3>4 1,2 >4
Northern Ireland 94 493 4.7 (2.97.5) 4.7 (3.17.0) 1.6 (0.46.3) 11.0 (7.715.3) 7 ns ns ns
Poland 462 17379 5.6 (4.56.9) 4.8 (3.95.9) 0.3 (0.10.7) 10.7 (9.312.3) <1nsd ns ns
Portugal
1
109 10519 10.8 (8.913.0) 4.2 (3.15.6) 5.7 (4.37.5) 20.6 (17.723.8) 1 nsd  2>1ns
Scotland 323 1764 7.5 (5.89.7) 10.9 (9.512.6) 0.5 (0.21.6) 18.9 (16.621.6) 16 ns ns ns
Slovakia 433 8427 11.4 (9.613.6) 3.4 (2.64.4) 0.6 (0.31.2) 15.5 (13.417.8) 2  1>2,3,4; 2 >3 1>2,3  1>2,3,4; 2 >3
Slovenia 56 1556 13.7 (9.419.4) 18.1 (10.529.5) 0.2 (0.10.4) 32.0 (23.342.1) <1 1,4 >3 4>22>3
Spain
1
47 3764 17.6 (13.023.4) 5.5 (2.710.8) 1.3 (0.44.4) 24.5 (19.530.2) <1ns 2>3ns
Sweden 2253 20664 7.1 (6.57.8) 3.0 (2.63.3) 1.3 (1.01.5) 11.4 (10.612.2) 14  1>2,3 ns  1>2,3
Wales 34 224 7.1 (4.810.5) 2.7 (1.06.7) 0 (na) 9.8 (7.013.6) 2 ns ns ns
Over all EU
countries
23618 381813 9.8 (9.69.9) 3.8 (3.74.0) 0.90 (0.850.96) 14.5 (14.314.8) 4 _ _ _
Non-EU European countries
Macedonia 115 6982 6.4 (4.88.4) 4.4 (3.35.7) 2.5 (1.15.5) 13.2 (10.516.6) na 1>3ns1>3
Norway 623 8774 4.2 (3.55.2) 3.6 (3.24.1) 0.4 (0.30.7) 8.3 (7.49.4) 14  1>3ns
 1>2,3
Serbia 205 16956 23.9 (19.229.3) 1.4 (1.11.8) 0.1 (0.00.3) 25.4 (20.830.8) 2  1>2,3,4 ns  1>2,3,4
Switzerland 1452 19979 7.4 (6.78.1) 5.7 (5.36.1) 0.6 (0.40.8) 13.6 (12.814.5) 8  2>3ns  2>3
Ukraine 677 32335 6.0 (5.16.9) 3.4 (2.74.2) 1.9 (1.52.4) 11.2 (9.912.6) <1 1>2,4 ns  1>2,3,4
Over all
European
countries
26690 466839 9.8 (9.610.0) 3.8 (3.73.9) 0.94 (0.890.99) 14.5 (14.314.8) na _ _ _
(Continued)
Honey bee colony winter loss rates for 35 countries 3
observed in Iran in this first year of its monitoring sur-
vey. Over the previous winter of 2017/18, several more
countries had loss rates above 25%. Spain has been
observed to be consistently among those countries with
high winter loss rates, however in the regions with
more than a few participating beekeepers this time the
loss rates were not especially high, as seen in the map
(Figure 1(a)). Portugal is a more recent participant in
these surveys, but seems also to suffer from a high win-
ter loss rate, a finding which may be confirmed in fur-
ther surveys. Further investigation of the reasons for
high losses in Spain, Portugal and Slovenia would be
worthwhile. Scotland and Italy had moderately high loss
rates (18.9% and 16.5%, respectively) in this survey, but
in general the Western European countries had lower
loss rates, unlike during the previous winter. As well as
for Bulgaria, low loss rates (up to 10%) were also
observed for Finland, Israel, Norway, England, Denmark
and Wales, mostly Northern countries. The loss rate
for France was only slightly above this level, at 10.2%.
Rates of loss from natural disasters ranged from
none in Wales (with a low number of respondents) to
5.7% in Portugal, with the next highest at 3.8% in Iran.
In most countries, these rates were below 1% and
almost all were below 3%. Portugal also had the highest
loss rate due to natural disasters during the previous
winter (winter 2017/18); it was even higher that winter
in fact, at 10%.
Winter losses due to queen problems varied
between 1.3% in Bulgaria (also the lowest in winter
2017/18 at 1.1%) to a rather high 18.1% in Slovenia
(also the highest in winter 2017/18 at 20.3%) and
Scotland was next highest at 10.9% (compared to 7.9%
the previous year). For comparison, in winter 2016/17
this type of loss rate for Slovenia was found to be the
lowest observed. Therefore, although overall our stud-
ies are finding the loss rate from queen problems rela-
tively constant at 45%, there can be great fluctuation
in this rate for individual countries from year to year.
Apart from losses due to natural disasters, usually
rather low, and losses due to queen problems, we also
observe losses due to mortality (dead or empty colo-
nies). The lowest mortality rate was for Israel, at 2.1%,
and the highest was for Serbia, at 23.9%. Croatia also
had a high mortality rate, of 20.4%. The low mortality
in Israel may be explained by the fact that most of the
participating beekeepers are professionals.
Bulgaria participated for the first time in the survey
conducted in spring 2018, and it was observed that the
beekeepers participating were professional beekeepers,
possibly not typical of the whole beekeeper population.
In the survey of spring 2019, reported here, there were
only two beekeepers from Bulgaria with small numbers
of colonies. This may explain to some extent why the
reported loss rates in Bulgaria are all very low, as larger
beekeeping operations are known to have lower winter
Table 1. (Continued).
Country
No. of
respondents
No. of
colonies
going into
winter
% Mortality
Rate
(95% CI)
% Rate of loss of
colonies due to
queen problems
(95% CI)
% Rate of loss of
colonies due
to natural
disasters
(95% CI)
Overall
winter
loss rate
(95% CI)
Estimated %
of beekeepers
represented
Effect of % of
new queens
on losses
excluding
natural disaster
Effect of % of new
queens on queen
problem losses
Effect of % of
new queens
on dead/empty
colonies
Non-European countries
Algeria
1
115 11350 6.6 (5.77.5) 1.8 (1.42.2) 2.2 (1.33.7) 10.5 (9.211.9) <1ns ns ns
Iran 1653 230093 13.7 (12.914.6) 4.6 (4.25.0) 3.8 (3.34.5) 22.1 (21.123.2) 2 ns ns ns
Israel 41 18843 2.1 (1.23.7) 3.8 (2.36.1) 0.7 (0.23.5) 6.6 (4.210.3) 8 3>4nsd 2>4
Mexico 130 11108 7.3 (6.48.3) 6.2 (5.57.1) 2.9 (2.13.9) 16.4 (14.718.3) <1na na na
Over all
participating
countries
28629 738233 10.7 (10.510.9) 4.1 (4.04.1) 1.9 (1.82.0) 16.7 (16.416.9) na  1>2>3,4  1,2,3 >4; 1 >3 1>2,3,4;
2,4 >3
The mortality rate and loss rates, respectively, were calculated as a percentage of colonies wintered which died or were lost due to unresolvable queen problems or to natural disaster. Percentage of bee-
keepers represented was expressed as the percentage of usable responses per estimated number of beekeepers in each country. Calculation of CIs used the quasi-binomial generalised linear modelling
(GLM) approach in van der Zee et al. (2013), and effects of percentage of wintered colonies with new queens (as well as operation size and migratory beekeeping; see text) were tested using single factor
quasi-binomial GLMs to model probability of loss.
Notes: Significance codes used to represent the p-values of tests are as follows:  p0.001;  0.001 <p0.01; 0.01 <p0.05; nsmeans non-significant (p>0.05); na indicates data not available;
nsd means that while the factor was significant in the model, significant differences were not found between any two categories on the basis of confidence intervals.
Labels 1, 2, 3 and 4 are used to represent the categories of percentage of new queens: 025% inclusive, above 25% and up to 50% inclusive, above 50% and up to 75% inclusive, and above 75%, respectively.
1 Limited geographical coverage of respondents providing data.
2 Mostly professional beekeepers.
4A. Gray et al.
Honey bee colony winter loss rates for 35 countries 5
loss rates (e.g., Brodschneider et al., 2016,2018; Gray
et al., 2019; see also below).
The effects of several potential risk factors for win-
ter losses were considered individually, by fitting uni-
variate quasi-binomial generalised linear models (van der
Zee et al., 2013). Firstly, on the overall data set we
examined the effects of operation size and migration of
colonies. In this analysis we did not consider winter
losses due to natural disasters, so we modelled the risk
of loss arising from a dead/empty colony or from an
unresolvable queen problem. For operation size, in
which we compared operations with up to 50 colonies,
51150 colonies and over 150 colonies, we found once
more a highly significant effect (p<0.001), indicating a
lower loss rate for beekeeping operations with over
150 colonies. However, the size of this effect was rela-
tively small (loss rates in each group were 15.1%, 15.6%
and 14.0%, respectively for smaller to larger numbers of
colonies). The effect of migration was also highly signifi-
cant (p<0.001), with loss rates of 15.1% and 14.2% for
those responding Yesand No,respectively (and
9.4% for the Dont knows, a relatively small group).
The differences between the categories were all signifi-
cant, so we conclude that the Nocategory has lower
losses than the Yesgroup. While the results for oper-
ation size are consistent with those in Brodschneider
et al. (2016, 2018) and Gray et al. (2019), the results
for migration do vary from year to year and also
between countries. For example, in Gray et al. (2019)
those who did migrate their colonies at least once in
the season had lower losses overall than those not
migrating. This may suggest that the effect of operation
size is related to management, while the effect of migra-
tion depends on seasonal or local environmen-
tal factors.
Additionally, we examine the effect of new queens
on colony winter losses. Among other factors, queen
vitality has been shown to be closely related to colony
health or failure (Akyol et al., 2008; vanEngelsdorp
et al., 2013; Giacobino et al., 2016). One of the bio-
logical influences is likely to be the age of queen bees
going into winter. The percentage of young queens in
wintered colonies was found by van der Zee et al.
(2014) to be significantly linked to winter loss, as was
the extent of queen problems in summer. To examine
the effect of queen age, to some extent at least, we
consider the percentage of colonies going into winter
with a new queen (queens bred in the year before win-
ter, 2018 in this investigation). Beekeepers were asked
How many of the wintered colonies had a new queen
in 2018?,and the percentage of colonies with new
queens going into winter was then calculated for each
beekeeping operation. The results were filtered to
remove Dont knowresponses and any in which the
stated number of new queens was higher than the
stated number of colonies going into winter.
Of 28,629 beekeeper responses with valid loss data,
26,483 (92.5%) also had valid data relating to new
queens, representing 687,502 colonies wintered. Of
these 687,502 colonies going into winter, 377,998
(55.0%) had a new queen. The percentage of new
queens was similar for the countries geographically in
Europe (56.3%) and for the EU countries (56.0%).
These figures reflect the new queens introduced by hive
management, although the actual numbers of new
queens could be higher as a result of supersedure
unrecognised by beekeepers.
For the overall data set, the actual percentage of
new queens was used as a covariate in the model to
explain the risk of colony loss at operation level, and as
the effect of new queens on the risk of colony loss may
not be linear, additionally percentage of new queens
was categorised into four classes, namely 025% inclu-
sive, above 25% and up to 50% inclusive, above 50%
and up to 75% inclusive and above 75%, labelled as cate-
gories 1, 2, 3 and 4, respectively. This categorical vari-
able was used as a factor in the fitted model for the
risk of colony loss. The effect of the latter factor was
also considered for each country, in models to explain
the risk of colony loss due to dead or empty colonies,
and loss due to irresolvable queen problems, and also
for both sources of colony loss.
The percentage of new queens varied per operation
from 0 to 100%, with a median of 57.1%, and, of the
four categories of percentage of young queens, category
4 (above 75%) was most common (8642 beekeepers),
followed by category 2 (7962 beekeepers), category 3
(5494 beekeepers) and category 1 (up to 25%) was least
3
Figure 1. (a) Map with traffic-light colour coding showing relative risk of overwinter colony loss at regional level for participat-
ing countries.
Notes: Regions with a relative risk of loss (loss rate divided by the loss rate over all regions) that is significantly higher/lower than 1 are
shown in red/green, respectively. Regions with a relative risk not significantly different from 1 are shown in yellow. Where no data were
available or data were available from fewer than 6 beekeepers in a region within a participating country, this was treated as insufficient
for reliable calculation and the region is shown in grey. Countries not present in the study are indicated in white (blank areas in the map).
Information on region was not available for Poland, nor Malta (a small country), which were coloured at country level, as was Bulgaria (as
numerous regions were represented but none with more than 5 beekeepers). Island groups/regions are also coloured as one region pro-
vided at least 6 responses were available.
(b) Barplots of results for percentage of young queens: distribution of beekeepers across each category of response (top-left), loss rates
and 95%confidence intervals for each category of response for total losses excluding natural disasters (top-right), losses from queen prob-
lems (bottom-left) and losses from dead/empty colonies (mortality rate; bottom-right). Non-overlapping confidence intervals indicate cate-
gories that have significantly different loss rates.
6A. Gray et al.
common (4385 beekeepers); see also Figure 1(b),
top-left.
Overall, the risk of colony winter loss decreases as
percentage of new queens increases (p<0.001). For
example, estimates (and 95% confidence intervals) for
the loss rate for operations with percentages of new
queens of 0%, 57.1% (the median value) and 100% are
16.9% (16.417.4%), 14.6% (14.414.8%) and 13.1%
(12.713.4%), respectively, and these are all significantly
different. Using percentage of new queens as a four-cat-
egory factor, the effect of the factor on risk of winter
loss was also highly significant (p<0.001), with esti-
mated loss rates of 17.8% (17.218.3%) for category 1,
14.9% (14.515.3%) for category 2, 13.4% (12.913.8%)
for category 3 and 13.8% (13.414.2%) for category 4.
The conclusion is that the loss rate is significantly lower
for more than 50% new queens than for above 25% and
up to 50% new queens, which in turn is significantly bet-
ter than for up to 25% new queens (Figure 1(b), top-
right). The size of the effect of percentage of new
queens on the risk of winter loss is larger than for
operation size (see above).
Considering losses due to queen problems only
(Figure 1(b), lower-left), again differences in loss rates
are highly significant (p<0.001), with estimated loss
rates of 4.6% (4.34.8%), 4.3% (4.14.5%), 4.0%
(3.84.2%) and 3.5% (3.33.7%), respectively for catego-
ries 1, 2, 3 and 4 of percentage of new queens. We
conclude that for queen problem losses, losses are low-
est with more than 75% new queens, and losses are
lower with above 50% and up to 75% new queens than
with 25% or fewer new queens. The effects are small
but statistically significant. For losses from dead or
empty colonies, differences in loss rates are also highly
significant (p<0.001), with estimated loss rates of
13.2% (12.713.7%), 10.6% (10.210.9%), 9.3%
(9.09.7%) and 10.3% (9.910.7%) for categories 1, 2, 3
and 4 of new queens, respectively. We conclude that
for winter mortality, losses are significantly lower with
above 25% new queens. Figure 1(b) shows these results
graphically.
Results per country are shown in Table 1. While the
findings are not uniform across all countries, in many
countries we tend to observe that the estimated loss
rate or probability of loss decreases for apiaries with a
higher percentage of new queens. However, the differ-
ences in the loss rates between the four categories or
classes were not always statistically significant. This is
likely, in some cases at least, to be due to a limited
number of beekeepers in one or more of these classes
representing the percentage of new queens in wintered
colonies. Where significant results were found, in all
three cases (for losses from dead/empty colonies, for
losses from queen problems, and for total losses from
these causes), lower loss rates mostly correspond to a
higher percentage of new queens.
It should be noted that proportions of wintered col-
onies with a new queen are not strictly comparable
between all beekeepers, as beekeeping operations vary
considerably in size. However, overall, across many bee-
keeping operations of varying size we have found that
operations with higher percentages of young queens
experienced significantly lower loss rates during the
winter of 2018/19. The effect is widely observed, for
overall winter losses excluding natural disasters, and
separately for queen problem losses and for losses from
dead/empty colonies. Due to our methodology, it is not
possible to say whether the lost colonies are the ones
that had the older queens, however our findings suggest
that replacing the queen in more than 50% of a bee-
keepers colonies is best. Young queens may be better
in colony build-up, due to greater fertility or better
health status, often being less likely to contract diseases,
and in general producing more healthy bees. Young
queens often originate from colony splitting hive man-
agement practices or regular queen replacement prac-
tice, which may both be an indication of good hive
management in general. The finding is in accordance
with previous studies, although these did not differenti-
ate between losses related to queen problems and dead
colonies (Genersch et al., 2010; van der Zee et al.,
2014). The annual replacement of old queens therefore
is a practical recommendation for beekeepers to help
improve their colony winter loss rate. Replacing at least
half of a beekeepers queens each year can be justified
from our results. However, this could incur consider-
able cost in larger-scale beekeeping. The biological
mechanisms behind the better survival of colonies with
new queens also require scientific study in order to be
better understood.
Concerning colony losses, the accuracy of the esti-
mated loss rates depends on the accuracy and repre-
sentativeness of the data reported by the beekeepers.
There are competing influences at work in this regard.
Some beekeepers will be more motivated to participate
if they feel that their own losses are high or in a season
when losses generally are thought to be high, and less
interested in participation in other years. Some other
beekeepers are motivated when they can report scarce
losses and tend to hide higher losses. In some other
cases beekeepers experiencing high losses may be con-
cerned that, if they report their true level of losses,
they will be identified, even if they are responding
anonymously, and may fear that their colonies will be
subject to unwanted investigation by extension workers
or official bee inspectors. This may be true even when,
for reporting purposes, losses for all beekeepers in a
region or country are aggregated. In practice we hope
that these competing effects balance out. It should be
recognised that in this uniquely large long-term inter-
national study of colony losses any biases are likely to
persist over time, as the methodology used each year is
the same. It is therefore important, in order to achieve
Honey bee colony winter loss rates for 35 countries 7
unbiased results, to continue to work towards a high
and representative response from beekeepers in every
country conducting this colony loss monitoring.
Acknowledgements
The colony loss monitoring group which carried out this study
is a core project of the COLOSS research association (pre-
vention of honey bee colony losses), which supports regular
workshops facilitating research discussions and collaboration
between group members. COLOSS is supported by the Ricola
Foundation Nature and Culture and V
eto-pharma. The
authors thank very much all the beekeepers who gave their
time to complete the COLOSS questionnaire providing the
data for this work, and the additional COLOSS members who
contributed to survey organisation, data collection and/or data
processing. The authors are also grateful to various national
funding sources for their support of some of the monitoring
surveys, including, in the Republic of Serbia, MPNTR-RS,
through Grant No. III46002, Slovenian Research Program P1-
0164, and Zukunft Biene 2(grant number 101295/2) in
Austria. In Macedonia, the technical support was provided by
the MacBee association (www.macbee.mk) and its member
Miroljub Golubovski. The authors acknowledge the financial
support by the University of Graz for open access.
Disclosure statement
No potential conflict of interest was reported by the authors.
ORCID
Alison Gray http://orcid.org/0000-0002-6273-0637
Noureddine Adjlane http://orcid.org/0000-0002-0369-2968
Alireza Arab http://orcid.org/0000-0003-0267-8504
Jean-Daniel Charri
ere http://orcid.org/0000-0003-3732-4917
Robert Chlebo http://orcid.org/0000-0001-8715-0578
Bram Cornelissen http://orcid.org/0000-0001-6610-0811
Cristina Amaro da Costa http://orcid.org/0000-0001-
8625-2206
Ji
r
ıDanihl
ıkhttp://orcid.org/0000-0002-6936-1766
Marica Maja Dra
zi
chttp://orcid.org/0000-0002-7817-0419
Mariia Fedoriak http://orcid.org/0000-0002-6200-1012
Ivan Forsythe http://orcid.org/0000-0002-8642-102X
Anna Gajda http://orcid.org/0000-0003-3900-7368
Dirk C. de Graaf http://orcid.org/0000-0001-8817-0781
Jes Johannesen http://orcid.org/0000-0002-8496-4100
Lassi Kauko http://orcid.org/0000-0001-7836-6553
Preben Kristiansen http://orcid.org/0000-0001-6718-2214
Maritta Martikkala http://orcid.org/0000-0001-5761-8627
Raquel Mart
ın-Hern
andez http://orcid.org/0000-0002-
1730-9368
Carlos Aurelio Medina-Flores http://orcid.org/0000-0002-
9330-565X
Franco Mutinelli http://orcid.org/0000-0003-2903-9390
Solenn Patalano http://orcid.org/0000-0002-1880-7692
Gilles San Martin http://orcid.org/0000-0002-0434-9416
Jevrosima Stevanovic http://orcid.org/0000-0003-0906-5911
Anthony Williams http://orcid.org/0000-0002-5383-3183
Marion Zammit-Mangion http://orcid.org/0000-0003-
2940-0780
Robert Brodschneider http://orcid.org/0000-0002-2535-0280
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... Further improvement in the questionnaire's administration and targeting of different specific topics each year could contribute to a better understanding of this phenomenon. Data on winter losses have been collected through the Coloss questionnaire at European Union, European, and extra-Europe levels since 2008 [59][60][61][62][63][64]. In Italy, these data have been gathered since 2008 (in hardcopy format and online since 2019-2020). ...
... The Coloss questionnaire has been used in Italy since 2008 [58][59][60][61][62][63][64] to collect data on winter honeybee colony losses. It consists of about 27 questions which mainly require numerical entries and are closed-ended (single or multiple choice), except for a few openended questions. ...
... In general, the percentage losses due to queen-related problems remained lower than 8%, which could be explained by the expertise of the beekeepers participating in the questionnaire. Furthermore, data collected in previous years through the Coloss questionnaire indicated queen-related losses of between 5 and 8.9% [59][60][61][62][63]. The percentage of lost colonies associated with natural disasters was very low (<2%) and could be attributed to the attention paid by beekeepers to the locations of their apiaries and to monitoring of weather-related natural events. ...
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The Italian beekeeping industry has grown steadily during the last decade, according to data from the national beekeeping registry, which came into existence in February 2015. Winter colony losses remain a matter of concern for beekeepers in Italy, and administration of the questionnaire defined by the Coloss Association could contribute to a better understanding of this phenomenon. To evaluate the percentage trends over time in honeybee colony losses arising from various causes, we used the quasi-binomial generalized linear modelling (GzLM) approach, taking the year as an independent variable. We set our level of significance at 5% and performed the data analysis only for the seven regions that sent data continuously from 2014 to 2020. We considered the percentage of losses due to queen-related problems, natural disasters, and dead or empty colonies, given that these questions remained unchanged over the years. The survey also revealed that the percentage trend for respondents using drone brood removal showed a significant increase. In general, the percentage of colony losses due to queen-related problems remained lower than 8%, and the percentage of colony losses associated with natural disasters was very low (<2%). The mean percentages of losses due to dead or empty colonies ranged from 6 to 17% in the considered period. In addition, we took account of the responses relating to treatments against Varroa mite infestation, given the importance attributed to this honeybee parasite. Unlike the other variables, we calculated the percentages related to the types of beekeeper treatments against Varroa destructor based on the respondents, not on the colonies. What emerged was that almost every beekeeper used at least one type of treatment against V. destructor. In general, the trend of respondents appeared stable at 0.3% during the last four years.
... Surveys have proven a reliable way of estimating overwintering losses in temperate climate zones [5][6][7][8][9][10][11], where loss rates may fluctuate highly between years. In Europe, loss rates may exceed 30% [6,7,12], and overwintering mortality rates in the US have been estimated at up to 53.3% [9,10]. ...
... In Europe, loss rates may exceed 30% [6,7,12], and overwintering mortality rates in the US have been estimated at up to 53.3% [9,10]. COLOSS surveys of winter mortality rates also show that loss rates in Europe may vary considerably among geographical regions in any year [8]. In Germany, where most beekeeper operations are of similar size (96% of all registered operations have less than 26 colonies [13]) and have similar Varroa destructor-management strategies [14], annual winter loss rates have fluctuated between 6% and 30% since 2003 [15]. ...
... mid October until the end of November of each year (2012-2021). The online survey for estimating winter losses assessed mortality between December and April by asking the questions: (1) "how many colonies did you have before winter?" and (2) "how many of these (winter) colonies have you lost?" Winter losses were reported to COLOSS (see e.g., Gray et al. [8]) but here we included additional data that did not meet all requirements of COLOSS, e.g., we included apiaries without postal code information. The winter questionnaires were online from approx. ...
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Winter loss rates of honey bee colonies may fluctuate highly between years in temperate climates. The present study combined survey data of autumn and winter loss rates in Germany (2012–2021) with estimates of honey flow—assessed with automated hive scales as the start of honey flow in spring and its magnitude in summer—with the aim of understanding annual fluctuations in loss rates. Autumn colony loss rates were positively and significantly correlated with winter loss rates, whereas winter loss rates were inversely related to loss rates in autumn of the following year. An early start of net honey flow in spring predicted high loss rates in both autumn and winter, whereas high cumulative honey flow led to lower loss rates. The start of net honey flow was related to temperature sums in March. Combined, the results implied that the winter loss rate in one year was influenced by the loss rate of the preceding winter and shaped by honey flow dynamics during the following year. Hence, the rate of colony loss in winter can be viewed as a cumulative death process affected by the preceding one and a half years.
... This virus is the most common cause of queen larval death [63,64], but it has not been found to cause overt symptoms in queens despite the detection of high infection loads [65]. Viruses of the ABPV complex and SBV have been found in eggs [54,[66][67][68], but they were rarely detected in this study. The higher virulence of BQCV, SBV and ABPV [4,48,[69][70][71][72] compared to the lower virulence of DWV [69] could explain why they are less likely to be transmitted vertically without causing queen supersedure or colony health issues [73]. ...
... For BQCV, only the infection load was significantly lower in queens aged 0 years than in queens aged 1 year from TMCs. In beekeeping practices, queens are often renewed yearly, as young queens are associated with lower winter mortality [66,102]. This study suggests that older queens from colonies that are treated against the Varroa mite might be able to adapt their antiviral responses to DWV and thereby reduce the infection loads transmitted via their eggs. ...
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Monitoring virus infections can be an important selection tool in honey bee breeding. A recent study pointed towards an association between the virus-free status of eggs and an increased virus resistance to deformed wing virus (DWV) at the colony level. In this study, eggs from both naturally surviving and traditionally managed colonies from across Europe were screened for the prevalence of different viruses. Screenings were performed using the phenotyping protocol of the ‘suppressed in ovo virus infection’ trait but with qPCR instead of end-point PCR and a primer set that covers all DWV genotypes. Of the 213 screened samples, 109 were infected with DWV, 54 were infected with black queen cell virus (BQCV), 3 were infected with the sacbrood virus, and 2 were infected with the acute bee paralyses virus. It was demonstrated that incidences of the vertical transmission of DWV were more frequent in naturally surviving than in traditionally managed colonies, although the virus loads in the eggs remained the same. When comparing virus infections with queen age, older queens showed significantly lower infection loads of DWV in both traditionally managed and naturally surviving colonies, as well as reduced DWV infection frequencies in traditionally managed colonies. We determined that the detection frequencies of DWV and BQCV in honey bee eggs were lower in samples obtained in the spring than in those collected in the summer, indicating that vertical transmission may be lower in spring. Together, these patterns in vertical transmission show that honey bee queens have the potential to reduce the degree of vertical transmission over time.
... The increased honeybee mortality rate has become a worrying issue in the last three decades for both the scientific and general population. A Colony Losses Monitoring (COLOSS) survey showed a winter beehive loss rate around 20-25% in Europe [11]. In A cohort study was planned using 12 hives, including 6 highly infected by varroa mites (Nos. ...
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The European honeybee contributes to the agriculture by its pollination; however, the overwintering loss rate over the last decades is worrisome. Varroa destructor is considered one of the most important causes of bee colony declines. This project aims to correlate the infestation by varroa to the hemolymph sugar concentrations and bacterial and viral coinfections. Six highly infested and six control hives were compared over time. Pooled hemolymph samples from honeybees were collected for sugar concentration measurements using a previously validated portable glucometer. The hemolymph samples were submitted for bacteriology. Multiplex RT-PCR analysis was performed on honeybees for six viruses: DWV-A, DWV-B, BQCV, ABPV, KBV, and IAPV. There was also no predominance of pathogenic bacteria. In September, sugar concentrations in hemolymph were significantly lower in highly infested hives than in control hives. Infested hives showed markedly higher viral loads except for ABPV. DWV-A and BQCV viral loads from highly infested hives were significantly higher in September compared to July. A continued and severe exposure to varroa leads to increased viral charges and decreased sugar concentrations, suggesting alterations in immunity, metabolism, and reserve mobilization. These parameters contribute to the weakening and mortality of the colonies.
... The overall mortality at the CIAPA (40.9%), CIMO (26.7%), and ARO (20.1%) apiaries could be considered high, when compared to the percentage of winter mortality rate of 10.7% reported in 35 countries for the same time frame (2018-2019) [74], although overall mortality is expected to be higher than during overwintering. In this way, although no infection rate could be established as a marker for colony mortality, it is possible that the N. ceranae infection plays a role in the losses, as this microsporidium can cause the death of the infected honey bees [14], impacting on the viability of the colonies [14,15,18,29,[75][76][77]. High levels of infection have been reported as a cause of colony losses [14,62]. ...
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Nosema ceranae is a highly prevalent intracellular parasite of honey bees’ midgut worldwide. This Microsporidium was monitored during a long-term study to evaluate the infection at apiary and intra-colony levels in six apiaries in four Mediterranean countries (France, Israel, Portugal, and Spain). Parameters on colony strength, honey production, beekeeping management, and climate were also recorded. Except for São Miguel (Azores, Portugal), all apiaries were positive for N. ceranae, with the lowest prevalence in mainland France and the highest intra-colony infection in Israel. A negative correlation between intra-colony infection and colony strength was observed in Spain and mainland Portugal. In these two apiaries, the queen replacement also influenced the infection levels. The highest colony losses occurred in mainland France and Spain, although they did not correlate with the Nosema infection levels, as parasitism was low in France and high in Spain. These results suggest that both the effects and the level of N. ceranae infection depends on location and beekeeping conditions. Further studies on host-parasite coevolution, and perhaps the interactions with other pathogens and the role of honey bee genetics, could assist in understanding the difference between nosemosis disease and infection, to develop appropriate strategies for its control.
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This short article presents loss rates of honey bee colonies over winter 2017/18 from 36 countries, including 33 in Europe, from data collected using the standardized COLOSS questionnaire. The 25,363 beekeepers supplying data passing consistency checks in total wintered 544,879 colonies, and reported 26,379 (4.8%, 95% CI 4.7–5.0%) colonies with unsolvable queen problems, 54,525 (10.0%, 95% CI 9.8–10.2%) dead colonies after winter and another 8,220 colonies (1.5%, 95% CI 1.4–1.6%) lost through natural disaster. This gave an overall loss rate of 16.4% (95% CI 16.1–16.6%) of honey bee colonies during winter 2017/18, but this varied greatly from 2.0 to 32.8% between countries. The included map shows relative risks of winter loss at regional level. The analysis using the total data-set confirmed findings from earlier surveys that smaller beekeeping operations with at most 50 colonies suffer significantly higher losses than larger operations (p < .001). Beekeepers migrating their colonies had significantly lower losses than those not migrating (p < .001), a different finding from previous research. Evaluation of six different forage sources as potential risk factors for colony loss indicated that intensive foraging on any of five of these plant sources (Orchards, Oilseed Rape, Maize, Heather and Autumn Forage Crops) was associated with significantly higher winter losses. This finding requires further study and explanation. A table is included giving detailed results of loss rates and the impact of the tested forage sources for each country and overall.
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In this short note we present comparable loss rates of honey bee colonies during winter 2016/2017 from 27 European countries plus Algeria, Israel and Mexico, obtained with the COLOSS questionnaire. The 14,813 beekeepers providing valid loss data collectively wintered 425,762 colonies, and reported 21,887 (5.1%, 95% confidence interval 5.0–5.3%) colonies with unsolvable queen problems and 60,227 (14.1%, 95% CI 13.8–14.4%) dead colonies after winter. Additionally we asked for colonies lost due to natural disaster, which made up another 6,903 colonies (1.6%, 95% CI 1.5–1.7%). This results in an overall loss rate of 20.9% (95% CI 20.6–21.3%) of honey bee colonies during winter 2016/2017, with marked differences among countries. The overall analysis showed that small operations suffered higher losses than larger ones (p < 0.001). Overall migratory beekeeping had no significant effect on the risk of winter loss, though there was an effect in several countries. A table is presented giving detailed results from 30 countries. A map is also included, showing relative risk of colony winter loss at regional level.
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In this short note we present comparable loss rates of honey bee colonies during winter 2015/16 from 29 countries, obtained with the COLOSS questionnaire. Altogether, we received valid answers from 19,952 beekeepers. These beekeepers collectively wintered 421,238 colonies, and reported 18,587 colonies with unsolvable queen problems and 32,048 dead colonies after winter. This gives an overall loss rate of 12.0% (95% confidence interval 11.8–12.2%) during winter 2015/16, with marked differences among countries. Beekeepers in the present study assessed 7.6% (95% CI 7.4–7.8%) of their colonies as dead or empty, and 4.4% (95% CI 4.3–4.5%) as having unsolvable queen problems after winter. The overall analysis showed that small operations suffered higher losses than larger ones. A table with detailed results and a map showing response and relative risks at regional level are presented.
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This article presents results of an analysis of winter losses of honey bee colonies from 19 mainly European countries, most of which implemented the standardised 2013 COLOSS questionnaire. Generalised linear mixed effects models (GLMMs) were used to investigate the effects of several factors on the risk of colony loss, including different treatments for Varroa destructor, allowing for random effects of beekeeper and region. Both winter and summer treatments were considered, and the most common combinations of treatment and timing were used to define treatment factor levels. Overall and within country colony loss rates are presented. Significant factors in the model were found to be: percentage of young queens in the colonies before winter, extent of queen problems in summer, treatment of the varroa mite, and access by foraging honey bees to oilseed rape and maize. Spatial variation at the beekeeper level is shown across geographical regions using random effects from the fitted models, both before and after allowing for the effect of the significant terms in the model. This spatial variation is considerable.
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This chapter addresses survey methodology and questionnaire design for the collection of data pertaining to estimation of honey bee colony loss rates and identification of risk factors for colony loss. Sources of error in surveys are described. Advantages and disadvantages of different random and non-random sampling strategies and different modes of data collection are presented to enable the researcher to make an informed choice. We discuss survey and questionnaire methodology in some detail, for the purpose of raising awareness of issues to be considered during the survey design stage in order to minimise error and bias in the results. Aspects of survey design are illustrated using surveys in Scotland. Part of a standardized questionnaire is given as a further example, developed by the COLOSS working group for Monitoring and Diagnosis. Approaches to data analysis are described, focussing on estimation of loss rates. Dutch monitoring data from 2012 were used for an example of a statistical analysis with the public domain R software. We demonstrate the estimation of the overall proportion of losses and corresponding confidence interval using a quasi-binomial model to account for extra-binomial variation. We also illustrate generalized linear model fitting when incorporating a single risk factor, and derivation of relevant confidence intervals.
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Using standard epidemiological methods, this study set out to quantify the risk associated with exposure to easily diagnosed factors on colony mortality and morbidity in three migratory beekeeping operations. Fifty-six percent of all colonies monitored during the 10-month period died. The relative risk (RR) that a colony would die over the short term (∼50 days) was appreciably increased in colonies diagnosed with Idiopathic Brood Disease Syndrome (IBDS), a condition where brood of different ages appear molten on the bottom of cells (RR=3.2), or with a "queen event" (e.g., evidence of queen replacement or failure; RR=3.1). We also found that several risk factors-including the incidence of a poor brood pattern, chalkbood (CB), deformed wing virus (DWV), sacbrood virus (SBV), and exceeding the threshold of 5 Varroa mites per 100 bees-were differentially expressed in different beekeeping operations. Further, we found that a diagnosis of several factors were significantly more or less likely to be associated with a simultaneous diagnosis of another risk factor. These finding support the growing consensus that the causes of colony mortality are multiple and interrelated.
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The Western honey bee, Apis mellifera, is the most important animal pollinator in agriculture worldwide providing more than 90% of the commercial pollination services. Due to the development in agriculture the demands for honey bee pollination are steadily increasing stressing the pollination capacity of the global managed honey bee population. Hence, the long-term decline of managed honey bee hives in Europe and North-America is of great concern and stimulated intensive research into the possible factors presumably causing honey bee colony collapse. We here present a four-year study involving more than 1200 bee colonies from about 120 apiaries which were monitored for the entire study period. Bee samples were collected twice a year to analyze various pathogenic factors including the ectoparasitic mite Varroa destructor, fungi (Nosema spec., Ascosphaera apis), the bacterium Paenibacillus larvae, and several viruses. Data on environmental factors, beekeeping management practice, and pesticides were also collected. All data were statistically analyzed in respect to the overwintering mortality of the colonies. We can demonstrate for several factors that they are significantly related to the observed winter losses of the monitored honey bee colonies: (i) high varroa infestation level, (ii) infection with deformed wing virus (DWV) and acute bee paralysis virus (ABPV) in autumn, (iii) queen age, and (iv) weakness of the colonies in autumn. No effects could be observed for Nosema spec. or pesticides. The implications of these findings will be discussed.
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This study was conducted to determine the effects of the queen’s age on performance of the honeybee (A. mellifera anatoliaca) colonies at nomad beekeeping conditions. Performances of the colonies, which had 0, 1, 2 and 3 year-old queens, were compared. The number of combs, brood areas, wintering ability survival rate and honey yield were determined as performance criteria. The average number of combs with bees throughout the experiment in Group I, Group II, Group III and Group IV was 10.92±0.78, 14.68±0.55, 10.10±0.60, 7.88±0.45 number combs/colony; the average of brood areas was 3078±372.5 cm2, 3668±460.3 cm2, 2215±294.0 cm2, 1665.38±241.8 cm2; the average of wintering ability was 84.3±2.9%, 88.0±3.7%, 46.6±19.0%, 26.8±16.5%; the survival rate was 100%, 100%, 60%, 40%; and the average of honey yields was 31.4±1.89 kg, 41.5±1.05 kg, 20.4±2.62 kg and 12.0±1.41 kg per colony, respectively. A significant and negative correlation between queen age and brood production (r=-80.2), colony strength (r=-62.5), wintering ability (r=-66) and honey yield (r=-75.6) were calculated (P<0.01). The colonies headed by young queens had more brood areas, longer worker colony population, better wintering ability and greater honey yield in comparison to colonies headed by old queens.
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Honey bee colony losses during winter are a multi-factorial phenomenon. Environmental conditions, beekeeping practices and different pathogens are all considered as potential causes of honey bee colony losses. However, these factors may be diverse in different regions and there are no regional studies about winter losses in South America. The objective of this study was to identify risks factors associated with winter losses in temperate climate honey bee colonies in Argentina. Parasitic mite infestation level, colony strength measures, and percentage of colonies losses during winter 2013 were evaluated in 62 apiaries distributed in four different regions in east-central Argentina. Data regarding management practices in each apiary were collected by means of a questionnaire. A logistic regression model was constructed to associate management variables with the risk of winter losses higher than 10% of the colonies. Beekeepers who reported replacing less than 50% of the queens in their apiaries showed higher winter losses than apiaries who replaced more than 50% of their queens (OR = 18.15; CI 95%: 1.76–187.43; p = 0.01). There were no significant spatial clusters detected in our analysis (p > 0.05). Even considering that the winter colony losses can be explained by a complex interaction of factors, requeening appears as one of the most important management practices to reduce this phenomenon in Argentina.
Loss rates of honey bee colonies during winter 2017/18 in 36 countries participating in the COLOSS survey, including effects of forage sources
  • A Gray
  • R Brodschneider
  • N Adjlane
  • A Ballis
  • V Brusbardis
  • J.-D Charri Ere
  • R Chlebo
  • F Coffey
  • M Cornelissen
  • B Amaro Da Costa
  • C Cs Aki
  • T Dahle
  • B Danihl Ik
  • J Dra Zi C
  • M M Evans
  • G Fedoriak
  • M Forsythe
  • I De Graaf
  • D Gregorc
  • A Soroker
Gray, A., Brodschneider, R., Adjlane, N., Ballis, A., Brusbardis, V., Charri ere, J.-D., Chlebo, R., F. Coffey, M., Cornelissen, B., Amaro da Costa, C., Cs aki, T., Dahle, B., Danihl ık, J., Dra zi c, M. M., Evans, G., Fedoriak, M., Forsythe, I., de Graaf, D., Gregorc, A., … Soroker, V. (2019). Loss rates of honey bee colonies during winter 2017/18 in 36 countries participating in the COLOSS survey, including effects of forage sources. Journal of Apicultural Research, 58(4), 479-485. https://doi.org/10.1080/00218839.2019.1615661