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Abstract

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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Journal of Apicultural Research
ISSN: 0021-8839 (Print) 2078-6913 (Online) Journal homepage: https://www.tandfonline.com/loi/tjar20
Loss rates of honey bee colonies during winter
2017/18 in 36 countries participating in the
COLOSS survey, including effects of forage sources
Alison Gray, Robert Brodschneider, Noureddine Adjlane, Alexis Ballis, Valters
Brusbardis, Jean-Daniel Charrière, Robert Chlebo, Mary F. Coffey, Bram
Cornelissen, Cristina Amaro da Costa, Tamás Csáki, Bjørn Dahle, Jiří Danihlík,
Marica Maja Dražić, Garth Evans, Mariia Fedoriak, Ivan Forsythe, Dirk
de Graaf, Aleš Gregorc, Jes Johannesen, Lassi Kauko, Preben Kristiansen,
Maritta Martikkala, Raquel Martín-Hernández, Carlos Aurelio Medina-Flores,
Franco Mutinelli, Solenn Patalano, Plamen Petrov, Aivar Raudmets, Vladimir
A. Ryzhikov, Noa Simon-Delso, Jevrosima Stevanovic, Grazyna Topolska,
Aleksandar Uzunov, Flemming Vejsnaes, Anthony Williams, Marion Zammit-
Mangion & Victoria Soroker
To cite this article: Alison Gray, Robert Brodschneider, Noureddine Adjlane, Alexis Ballis, Valters
Brusbardis, Jean-Daniel Charrière, Robert Chlebo, Mary F. Coffey, Bram Cornelissen, Cristina
Amaro da Costa, Tamás Csáki, Bjørn Dahle, Jiří Danihlík, Marica Maja Dražić, Garth Evans,
Mariia Fedoriak, Ivan Forsythe, Dirk de Graaf, Aleš Gregorc, Jes Johannesen, Lassi Kauko,
Preben Kristiansen, Maritta Martikkala, Raquel Martín-Hernández, Carlos Aurelio Medina-Flores,
Franco Mutinelli, Solenn Patalano, Plamen Petrov, Aivar Raudmets, Vladimir A. Ryzhikov, Noa
Simon-Delso, Jevrosima Stevanovic, Grazyna Topolska, Aleksandar Uzunov, Flemming Vejsnaes,
Anthony Williams, Marion Zammit-Mangion & Victoria Soroker (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, DOI: 10.1080/00218839.2019.1615661
To link to this article: https://doi.org/10.1080/00218839.2019.1615661
© 2019 The Author(s). Published by Informa
UK Limited, trading as Taylor & Francis
Group
Published online: 30 May 2019.
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NOTES AND COMMENTS
Loss rates of honey bee colonies during winter 2017/18 in 36 countries participating
in the COLOSS survey, including effects of forage sources
Alison Gray
a

, Robert Brodschneider
b
, Noureddine Adjlane
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
, Tam
as Cs
aki
k
, Bjørn Dahle
l
,Ji
r
ıDanihl
ık
m
, Marica Maja Dra
zi
c
n
, Garth
Evans
o
, Mariia Fedoriak
p
, Ivan Forsythe
q
, Dirk de Graaf
r
, Ale
s Gregorc
s
, Jes Johannesen
t
,
Lassi Kauko
u
, Preben Kristiansen
v
, Maritta Martikkala
w
, Raquel Mart
ın-Hern
andez
x
,
Carlos Aurelio Medina-Flores
y
, Franco Mutinelli
z
, Solenn Patalano
aa
, Plamen Petrov
ab
, Aivar Raudmets
ac
,
Vladimir A. Ryzhikov
ad
, Noa Simon-Delso
ae
, Jevrosima Stevanovic
af
, Grazyna Topolska
ag
, Aleksandar
Uzunov
ah
, Flemming Vejsnaes
ai
, Anthony Williams
aj
, Marion Zammit-Mangion
ak
and Victoria Soroker
al

a
Department of Mathematics and Statistics, University of Strathclyde, Glasgow, UK;
b
Institute of Zoology, University of Graz, Graz, Austria;
c
Department of Biology, Universit
eMhamed Bougara, Boumerde, Algeria;
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 Poultry Science and
Small Farm Animals, Slovak University of Agriculture, Nitra, Slovakia;
h
Department of Life Sciences, University of Limerick, Limerick,
Ireland;
i
Wageningen Plant Research, Wageningen University & Research, Wageningen, Netherlands;
j
Agriculture School, Polytechnic
Institute of Viseu, Viseu, Portugal;
k
Hungarian Research Institute of Organic Agriculture, Budapest, Hungary;
l
Norwegian Beekeepers
Association, Kløfta, Norway;
m
Department of Biochemistry, Palack
y University Olomouc, Olomouc, Czech Republic;
n
Ministry of Agriculture,
Zagreb, Croatia;
o
Welsh Beekeepers Association, Northop, UK;
p
Department of Ecology and Biomonitoring, Yuriy Fedkovych Chernivtsi
National University, Chernivtsi, Ukraine;
q
The Agri-Food and Biosciences Institute, Belfast, UK;
r
Honeybee Valley, Ghent University, Ghent,
Belgium;
s
Faculty of Agriculture and Life Sciences, University of Maribor, Slovenia;
t
DLR Fachzentrum f
ur Bienen und Imkerei, Mayen,
Germany;
u
Finnish Beekeepers Association, K
oyli
o, Finland;
v
Swedish Board of Agriculture, Joenkoeping, Sweden;
w
Finnish Beekeepers
Association, Helsinki, Finland;
x
Centro de Investigaci
on Ap
ıcola y Agroambiental de Marchamalo (IRIAF), Marchamalo, Spain;
y
Faculty of
Veterinary Medicine and Animal Science, University of Zacatecas, Zacatecas, Mexico;
z
Istituto Zooprofilattico Sperimentale delle Venezie,
NRL for Honey Bee Health, Legnaro (Padova), Italy;
aa
Institute of Basic Biomedical Sciences (IBBS), B.S.R.C Alexander Fleming, Vari,
Greece;
ab
Department of Animal Sciences, Agricultural University Plovdiv, Plovdiv, Bulgaria;
ac
Estonian Beekeepers Association, Tallinn,
Estonia;
ad
Institute for Nature Management, National Academy of Sciences, Minsk, Belarus;
ae
Beekeeping Research and Information
Centre, Louvain la Neuve, Belgium;
af
Department of Biology, Faculty of Veterinary Medicine, University of Belgrade, Belgrade, Serbia;
ag
Department of Pathology and Veterinary Diagnostics, Faculty of Veterinary Medicine, Warsaw University of Life Sciences, Warsaw,
Poland;
ah
Faculty of Agricultural Sciences and Food, Ss. Cyril and Methodius University, Skopje, Macedonia;
ai
Danish Beekeepers
Association, Sorø, Denmark;
aj
School of Computer Science and Informatics, De Montfort University, Leicester, UK;
ak
Department of
Physiology & Biochemistry, University of Malta, Msida, Malta;
al
The Volcani Center, Agricultural Research Organisation, Rishon
LeZion, Israel
(Received 22 March 2019; accepted 22 April 2019)
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 pass-
ing consistency checks in total wintered 544,879 colonies, and reported 26,379 (4.8%, 95% CI 4.75.0%) colonies with
unsolvable queen problems, 54,525 (10.0%, 95% CI 9.810.2%) dead colonies after winter and another 8,220 colonies
(1.5%, 95% CI 1.41.6%) lost through natural disaster. This gave an overall loss rate of 16.4% (95% CI 16.116.6%) 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 sour-
ces for each country and overall.
Keywords: Apis mellifera; mortality; forage sources; colony winter losses; monitoring; beekeeping; survey;
citizen science
*Corresponding author. Email: Robert.Brodschneider@uni-graz.at
Wrote a first draft of the article.
Did data processing and editing, all statistical analysis, and produced the map.
ß2019 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, 2019
https://doi.org/10.1080/00218839.2019.1615661
Monitoring of losses of managed honey bee colonies is
a core activity of the non-profit honey bee research
association COLOSS. The COLOSS monitoring began
in 2008, with a focus on losses over winter, the most
important season for colony loss in Europe though not
necessarily in all other countries. This ongoing research
effort now involves many European and some additional
countries, who undertake annual national surveys of
beekeepers via a self-administered questionnaire involv-
ing standardized questions for comparability of
responses (van der Zee et al., 2013). The data collec-
tion is organized at national level and takes place in dif-
ferent ways depending on the country, including
internet, paper and email surveys and telephone calls.
Here, we present summary results from the
COLOSS survey of losses over winter 2017/18, con-
ducted in spring 2018. This is the third report in a ser-
ies of short communications (Brodschneider et al.,
2016,2018) which together allow comparison of winter
colony losses between countries and over time. These
COLOSS surveys represent many thousands of bee-
keepers over a large and expanding number of
participating countries. Anonymous answers are
optional, to encourage higher response rates. Earlier
studies, including van der Zee et al. (2014), examined
multiple risk factors for colony loss in multi-country
models. In these short reports, we focus each time on
a limited set of potential risk factors but examine their
significance in each country providing the relevant data.
Here we consider the impact of migration, operation
size and the relevance of a few specific sources of for-
age, for winter loss.
As in the 2017 survey (Brodschneider et al., 2018),
beekeepers were asked for the number of colonies win-
tered, 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). To estimate the overall pro-
portion of colonies lost, we calculated 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 as
Figure 1. Color-coded map showing relative risk of overwinter colony loss at regional level for participating 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 gray. Countries not present in the study are indicated in white (blank
areas in the map). Information on region was not available for Mexico, Malta, and Israel; these were each colored at country level.
Island groups/regions are colored as one region provided at least six responses were available. The Netherlands is not represented in
the map, as the data did not allow calculation of overall loss rate at country or regional level, and hence the relative risk was
unavailable.
2A. Gray et al.
Table 1. Winter 2017/18 survey results, showing number of respondents with valid loss data, corresponding number of colonies going into winter, honey bee colony mortality, and loss
rates (with 95% CIs).
Country
No. of
respon-
dents
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
disaster
(95% CI)
Overall
winter
loss rate
(95% CI)
Estimated
%of
beekeepers
represented
Effect of
Orchards
Effect of
Oilseed
Rape
Effect of
Maize
Effect of
Sunflower
Effect of
Heather
Effect of
Autumn
Forage
Crops
Algeria
a
116 12,677 5.2 3.4 1.2 9.8 <1nansna na nsns
(4.46.2) (2.84.1) (0.72.2) (8.711.1)
Austria 1391 28,373 8.6 3.2 0.5 12.2 5 na n <y n<y n<y na ns
(8.09.3) (2.93.4) (0.30.7) (11.513.0)
Belarus 114 2469 3.2 3.8 0.3 7.3 na ns ns nana ns ns
(2.44.4) (2.45.9) (0.10.6) (5.69.6)
Belgium 482 3725 16.5 2.3 0.6 19.4 5 y, n <DK y, n <DKns n <yns n <y, DK
(14.518.8) (1.72.9) (0.41.0) (17.221.7)
Bulgaria
a,b
27 4074 0.7 1.1 0.2 2.0 <1ns ns ns ns na ns
(0.31.9) (0.43.5) (0.10.7) (0.94.5)
Croatia 209 17,430 10.4 2.2 1.2 13.7 2 ns ns y <n, DK ns ns n <y, DK
(8.812.2) (1.82.6) (0.72.0) (11.915.7)
Czech
Republic
1181 20,567 9.0 3.2 0.9 13.0 2 na ns ns ns na ns
(8.110.0) (2.83.6) (0.71.1) (1214.1)
Denmark 1076 11,524 8.9 4.5 0.3 13.7 17 ns ns ns n <DK ns ns
(8.19.8) (4.05.0) (0.20.6) (12.714.8)
England 485 2800 20.2 6.1 1.9 28.1 2 ns ns n, DK <y ns ns ns
(18.022.6) (5.17.2) (1.22.9) (25.730.6)
Estonia 169 5660 8.7 4.3 3.3 16.4 3 ns ns na na ns ns
(7.010.7) (3.65.3) (2.54.3) (14.318.6)
Finland 352 8780 3.9 5.9 0.8 10.7 12 ns y <n, DK ns ns ns n <y
(3.15.0) (5.36.6) (0.61.2) (9.611.9)
France
a
531 16,926 11.0 4.5 0.6 16.1 1 ns n <yn, DK >y y<n<DK ns na
(9.712.5) (4.15.0) (0.40.8) (14.717.7)
Germany 10,167 121,296 15.2 3.1 0.7 18.9 8 n <y n<yn<DK <y n<y, DK n, DK <y na
(14.815.6) (2.93.2) (0.60.8) (18.519.3)
Greece 301 31,187 9.4 7.5 1.4 18.4 1 na DK <nn, DK <y ns ns ns
(7.911.2) (6.09.4) (0.92.3) (15.921.1)
Hungary 208 17,564 13.4 4.9 0.1 18.4 1 ns ns ns ns na ns
(10.816.5) (3.76.4) (0.00.6) (15.621.6)
Ireland 348 2958 12.2 9.2 1.2 22.6 12 na ns ns ns ns n <y
(10.514.2) (7.910.6) (0.81.8) (20.325.0)
Israel 54 26,922 0.5 5.8 1.8 8.2 11 ns na n <yns na na
(0.11.9) (4.57.5) (1.03.4) (6.410.4)
Italy
a
352 12,317 17.2 8.9 3.3 29.4 <1na ns y<n, DKns ns na
(15.618.9) (7.710.3) (2.54.4) (27.231.7)
Latvia 406 12,770 8.7
(7.410.1)
6.7
(5.38.5)
1.2
(0.91.6)
16.6
(14.718.7)
9ns ns y,n<DKn<DK ns ns
(Continued)
Winter 2017/18 loss rates of honey bee colonies 3
Table 1. (Continued).
Macedonia 171 10,918 5.6
(4.76.6)
6.2
(5.47.1)
1.5
(0.92.4)
13.2
(11.415.3)
na ns ns ns ns ns ns
Malta 11 287 4.5 7.7 1.0 13.2 4 insufficient data for tests
(2.010.0) (3.815.0) (0.112.2) (7.522.3)
Mexico 164 29,240 5.1 8.8 5.7 19.6 <1 no data available on forage
(4.16.3) (6.911.0) (4.27.6) (16.722.7)
Netherlands 783 5665 16.3 na na na 9 no data available on forage
(14.917.8)
Northern Ireland 106 515 24.1 5.2 0.6 29.9 11 ns ns ns ns ns ns
(19.429.5) (3.38.1) (0.31.3) (25.035.3)
Norway 727 9102 6.7 3.5 1.5 11.7 18 ns ns ns ns n <y ns
(5.77.8) (3.14.0) (1.12.0) (10.512.9)
Poland 307 13,226 10.1 3.5 0.6 14.2 <1n<DK ns n, DK <y na ns ns
(8.412.0) (2.94.2) (0.31.0) (12.316.3)
Portugal
a
58 6896 15.3 6.1 11.4 32.8 <1y<n na na na ns ns
(11.719.9) (3.89.9) (7.217.5) (26.639.8)
Scotland 345 1852 11.9 7.9 3.9 23.7 19 ns y <n ns ns y <n, DK ns
(9.814.4) (6.69.5) (2.65.8) (20.926.7)
Serbia 224 16,419 5.2 1.7 0.6 7.4 2 ns y <nns ns ns ns
(4.26.4) (1.22.5) (0.31.2) (6.29.0)
Slovakia 420 6499 6.6 2.8 0.6 10.0 2 ns y, n <DK n<DKn<yna n <DK
(5.38.2) (2.33.4) (0.41.0) (8.611.7)
Slovenia 397 8825 9.0 20.3 0.6 29.9 4 ns na n, DK <y ns n <yns
(7.910.2) (17.024.1) (0.41.2) (26.633.5)
Spain
a
173 19,869 14.4 9.0 2.8 26.2 <1DK<yns ns DK <yDK <nn, DK <y
(12.117.1) (6.811.9) (2.03.8) (22.730.1)
Sweden 2260 19,570 9.6 3.6 1.7 14.9 15 n <y ns y <n, DK na ns n <y
(9.010.3) (3.34.0) (1.41.9) (14.215.6)
Switzerland 1370 18,807 7.9 5.2 0.7 13.8 8 ns n <DKns na na na
(7.28.7) (4.85.6) (0.50.9) (12.914.7)
Ukraine 627 22,621 6.7 2.1 2.4 11.3 <1ns y<nns ns na ns
(5.87.7) (1.62.7) (2.03.0) (10.012.6)
Wales 34 214 13.1 10.7 2.8 26.6 2 ns ns ns ns ns ns
(8.918.8) (5.719.3) (0.612.7) (19.435.4)
Overall
c
25,363 544,879 10.0
(9.810.2)
4.8
(4.75.0)
1.5
(1.41.6)
16.4
(16.116.6)
na n <y, DK n<y, DK n<y, DK y, n <DK n<y, DK n<y, DK
Notes: Mortality 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 beekeepers
represented was expressed as the percentage of usable responses per estimated number of beekeepers in each country. Calculation of CIs used the quasi-binomial generalized linear modeling (GzLM)
approach in van der Zee et al. (2013), and effects of flow on forage sources (and operation size and migratory beekeeping; see text) were tested using single factor quasi-binomial GzLMs to model probabil-
ity of loss.
a
Limited geographical coverage of respondents providing data.
b
Professional beekeepers only are represented here, with a maximum of 3 apiaries.
c
Excluding Netherlands.
Significance codes used to represent the p-values of tests are as follows: nsmeans non-significant (p>.05), nameans not available (data were not provided at all or insufficient data were available for tests
comparing loss rates).
y: Yes; n: No; DK: Dont Know represent different categories of responses.
p.001;
.001 <p.01;
.01 <p.05.
4A. Gray et al.
reported in Brodschneider et al. (2018). Responses with
insufficient or illogical answers were excluded, but for
most countries these were a relatively small part of
their data-set. Many of the participating countries now
access the survey questionnaire via a common online
portal which encodes some of the required data con-
sistency checks, hence improving data quality before the
central compilation and further checking of data submit-
ted from all countries prior to analysis.
Thirty-six countries submitted data, compared to 30
and 29 in the previous two surveys in 2017 and 2016
respectively. This is the largest number of countries par-
ticipating in such a survey so far. Here we report for the
first time results on colony losses for Portugal, Greece,
and Bulgaria, as well as data from England and Hungary
after an absence of some years. The Netherlands submit-
ted data after being absent in the 2017 survey for the
first time since the COLOSS monitoring began.
More than 27,000 responses were submitted in total,
of which 783 limited responses from the Netherlands
unfortunately only allowed calculation of the mortality
rate (percentage of wintered colonies which were
reported as dead after winter), but a further 25,363
beekeepers provided valid and usable loss data accord-
ing to the above checks. Of the 544,879 colonies win-
tered by these 25,363 beekeepers, 26,379 (4.8%)
colonies were reported lost due to unsolvable queen
problems, 54,525 (10.0%) colonies were reported dead
after winter and 8,220 (1.5%) colonies were reported
as lost due to natural disaster. The numbers of partici-
pating beekeepers and colonies wintered are also the
largest represented so far in our surveys. For the coun-
tries represented here which are members of the
European Union (EU), which may be of interest for
evaluation of the impact of EU environmental standards
and regulations, again excluding the Netherlands, 21,796
beekeepers provided valid loss data, and, of 395,704
colonies which they wintered, 4.8% of colonies (95% CI
4.74.9%) were reported lost due to unsolvable queen
problems, 11.9% (95% CI 11.712.1%) were reported
dead after winter, and 1.2% (95% CI 1.21.3%) were
reported as lost due to natural disaster, giving an over-
all loss rate of 17.9% (95% CI 17.618.2%). These are
similar results as for the overall data-set, though the
percentage of dead colonies and the overall loss rate
are both slightly higher for the EU countries. For all the
countries which are in Europe, apart from the
Netherlands, the corresponding results were respect-
ively 25,029 beekeepers with valid loss data, who win-
tered 476,040 colonies and reported 4.6% (95% CI
4.54.7%) lost to queen problems, 11.0% (95% CI
10.811.2%) dead after winter, and 1.2% (95% CI
1.21.3%) lost due to natural disaster, giving an overall
loss rate of 16.8% (95% CI 16.517.0%), which are simi-
lar results to those for the EU countries.
As we have previously found (Brodschneider et al.,
2016,2018), loss rates vary considerably between
countries as well as years. Within countries, differences
between regions are also evident. Figure 1 shows a
color-coded map of the level of the colony loss rate
over winter 2017/18 relative to the loss rate for the
same winter over all the regions, in the countries and
regions where sufficient data were available. This allows
visual identification of countries and regions where the
loss rates were relatively high for that winter, compared
to the overall loss rate. For example, the UK had rela-
tively high loss rates, as did most of the regions shown
for Spain, while for Poland and Germany differences in
risk levels can be seen between regions. Unfortunately,
for some countries we still have data only from some
regions, rather than national data. This situation has
improved in Italy and Spain over the years of the
COLOSS surveys, though relatively few regions of
France, Bulgaria and Portugal are covered at present.
Survey conditions in Algeria are difficult, and achieving
national coverage is a challenge.
The overall loss rate in winter 2017/18 was highest
in Portugal (32.8%), a new country to the survey. Other
countries with high losses (above 25%) were Slovenia,
Northern Ireland, England, Wales, Italy, and Spain, coun-
tries mostly in Western Europe. This pattern is similar
to the results for winter 2015/16, but different from
the last year. For winter 2016/17 the highest winter
loss rates were for Germany, Spain, Mexico, Malta, and
Serbia. Bulgaria, another new country to this monitoring
study, had the lowest loss rate, of just 2.0%, though
based on data from only 27 professional beekeepers.
Other low loss rates were found for Belarus, Serbia,
Israel, Algeria, and Slovakia (all 10% or lower). A year
previously, loss rates were lowest in Norway, Northern
Ireland and Algeria, and the year before that in Central
Europe. Although most rates of loss from natural disas-
ter were very low, the two highest rates this time were
above 5% (Mexico) and 10% (Portugal). Winter losses
related to queen problems varied between 1.1% in
Bulgaria to 20.3% in Slovenia, whereas for winter 2016/
17 the rate of this loss for Slovenia was the lowest
among the participating countries.
In the previous two surveys in 2017 and 2016, the
overall rates of loss due to queen problems were 5.1
and 4.4%, respectively, and the mortality rates were
14.1 and 7.6%, but in the 2016 survey dead colonies
included those lost from natural disaster. The loss rate
from natural disaster alone in winter 2016/17 was 1.6%,
very similar to the current result of 1.5%. We conclude
that the loss rate due to natural disaster is very low,
although it does vary between countries (Table 1).
Rates of loss due to queen problems appear usually to
be about 45% overall, and the colony mortality rate is
the most variable between years, accounting for the
main variation in overall loss rates. There is no clear
trend in the overall loss rate, which fluctuates over the
years: 16.4% (95% CI 16.116.6%) of honey bee colo-
nies during winter 2017/18 (Table 1), 20.9% (95% CI
Winter 2017/18 loss rates of honey bee colonies 5
20.621.3%) over winter 2016/17 and 12.0% (95% CI
11.812.2%) over winter 2015/16. Even though these
loss rates over the years are significantly different, the
reasons for those differences remain unclear at present
and require further studies.
Examining some potential risk factors for winter loss,
by fitting a single factor quasi-binomial generalized linear
model (van der Zee et al., 2013), to the overall data-set
and identifying significant effects, we confirmed our pre-
vious results from Brodschneider et al. (2016,2018)
that beekeeping operations with 50 or fewer colonies
(hobbyist beekeepers) experience a significantly higher
overall winter loss rate (p<.001) than larger scale
operations. The very low loss rate cited here for pro-
fessional beekeepers in Bulgaria appears to be consist-
ent with this finding. Brodschneider et al. (2018) also
considered migratory beekeeping, and found a significant
effect only in a minority of countries and the direction
of the effect of migration on the risk of winter loss var-
ied. In the questionnaire for the survey in spring 2018,
beekeepers were asked Did you migrate any of your
colonies at least once for honey production or pollin-
ation in 2017?, with possible responses Yes,No,
and Dont know. This time, the effect of migration
was highly significant overall (p<.001) and those bee-
keepers migrating their colonies had lower losses than
those not migrating, and this level of loss in turn was
much lower than for those responding Dont know.
As the impact of migration is expected to be dependent
on distance as well as the reasons for migration, it
would be worthwhile evaluating those factors and thus
the role of colony migration on colony survival in a sep-
arate but more detailed study.
Since lack of proper forage sources for nutrition can
be one of the main risk factors for colony loss (Goulson,
Nicholls, Bot
ıas, & Rotheray, 2015), we also studied the
relative loss rates for beekeepers reporting whether or
not their colonies had a significant flow on certain forage
sources, namely Orchards, Oilseed Rape, Maize,
Sunflower, Heather, and Autumn Forage Crops (intended
as melliferous plants growing on land lying fallow). Not all
of these forage sources were relevant for every country.
The questionnaire responses are self-reported data, and
beekeepers may not always be fully aware of all forage
sources available to their bees. We found overall that for
all these plant sources except Sunflower, beekeepers
responding Nohad significantly lower losses than those
responding Yesor Dont know. For Sunflower, both
those responding Yesand Nohad lower loss rates
overall than those responding Dont know. For each of
the other forage sources, any effect was only significant
for a minority of countries (Table 1). In these cases, for
Orchards, the beekeepers responding Nousually expe-
rienced a lower loss rate, with an exception for Portugal.
For Oilseed Rape, the nature of the effect varied; for
example, for Finland, Scotland, Serbia and Ukraine those
responding Yeshad a lower loss rate than those
responding No, whereas for Austria, France and
Germany the outcome was the opposite. The greatest
number of significant results was found in the case of
Maize, though the direction of the effect also varied, and
only for Croatia, France, Italy and Sweden did the bee-
keepers responding Yeshave a lower loss rate. For
Sunflower, only for France did those responding Yes
have a lower loss rate. Heather was significant for very
few countries, and only for Scotland did those responding
Yeshave a lower loss rate. Autumn Forage Crops were
also only significant for a small number of countries, but
the beekeepers responding Nohad the lower loss rate.
In considering each of the above forage sources in a
single factor model for each country, many statistical
tests have been carried out. Hence, at country level
some model effects (Table 1) are likely to be significant
by chance alone. Therefore in the text we focus on the
relatively fewer results of the tests for the overall data-
set, each of which is both highly significant and based
on a very large sample size. The sizes of the significant
forage effects for the overall data-set are relatively
small; for example, concerning the question of whether
Maize constituted an important forage source, the loss
rates were 17.6, 15.0, and 17.2% for the beekeepers
responding Yes,No, and Dont know, respect-
ively. Nonetheless, in practice a number of factors, each
with a small effect, acting together on honey bee colo-
nies, could have a considerable impact.
In fact, the variable results between countries for
impact of foraging sources are not surprising. This is a
complex issue. On the one hand these forage plants are
considered as potentially useful sources of nutrition for
bees, helping to build up the colony, for example,
Autumn Forage Crops available when other forage may
be scarce, however, by extending the active season, late
forage availability may also extend length of the reproduc-
tion cycle for Varroa destructor, weakening the colony and
hence making winter losses more likely. Additionally, agri-
cultural crops are also expected to contain agricultural
chemicals that can cause negative effects (at lethal and
sub-lethal doses) if honey bees are exposed to them, and
this may have affected the results for all forage sources
considered here apart from Heather and possibly
Autumn Forage Crops (Goulson et al., 2015; Simon-
Delso et al., 2014). Management of these crops varies
between the countries, affecting honey bee colonies
accordingly. Additionally, environmental conditions can
vary considerably between countries, and within any one
country certain crops may be grown only in some areas
within that country, hence confounding crop effects and
other unspecified factors relating to regional variation.
Combining the data-sets for different countries also
means that larger countries with bigger data-sets tend to
dominate the results, though the effect of this will depend
on effect sizes at country level. In an earlier multi-country
study by van der Zee et al. (2014), access reported by the
beekeeper to foraging on Maize and Oilseed Rape were
6A. Gray et al.
both highly significantly associated with the risk of winter
loss, though the modeling was confined to beekeepers
with at most 50 colonies. In that study, colonies reported
not to have access to Oilseed Rape had significantly lower
risk of loss compared with those reported to have access,
while loss rates of colonies managed by beekeepers
responding Dont knowto this question about access
were not significantly different to those of colonies with
reported access. For Maize, both the colonies reported
as having No accessand those for which the beekeeper
responded Dont knowhad significantly reduced risk of
colony loss compared to those with reported access to
Maize. These results are similar to our results reported
earlier. The presence of Oilseed Rape or Maize, often
grown over large areas, might also be indicative of a lack
of diversity of forage, which could have detrimental
effects on colonies (van der Zee et al., 2014). Given the
various possible explanations for the forage effects in the
current data-set, the impact of agricultural versus natural
forage should remain an important factor for future
evaluation, especially in view of the current ban on vari-
ous uses of widely applied neonicotinoid insecticides by
the EU member states (OJEU, 2018).
In conclusion, even though our current loss data are
based on over 25,000 beekeepers from 36 countries,
we aim in the loss monitoring surveys to obtain higher
response numbers at national level, and high-quality
data. Obtaining a high response rate is important to
avoid bias and to achieve higher precision in loss esti-
mation, but also to enable better dissection of the risk
factors. In practice national co-ordinators in some coun-
tries have reported difficulty in achieving sufficient co-
operation to achieve a large sample size, including in
Malta, Mexico, Israel and Serbia. Beekeepers may need
more motivation to participate in the survey and to
provide full and useful responses. In some other coun-
tries efforts should continue to achieve a fuller repre-
sentation of beekeepers at national level.
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. 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 partners 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 [includ-
ing, in the Republic of Serbia, MPNTR-RS, through Grant No.
(III46002), Slovenian Research Program P1-0164, and Zukunft
Biene(grant number: 100972) in Austria], and 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
Robert Brodschneider http://orcid.org/0000-0002-2535-0280
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
Tam
as Cs
aki http://orcid.org/0000-0002-3548-5461
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
Dirk 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
Noa Simon-Delso http://orcid.org/0000-0003-1729-890X
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
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Winter 2017/18 loss rates of honey bee colonies 7
... 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.
... Observational data are collected at the beekeeping operation level, not colony or apiary level, in an annual spring survey covering the immediately preceding winter. The previous short reports are available in Brodschneider et al. (2016Brodschneider et al. ( , 2018 and Gray et al. (2019Gray et al. ( , 2020. Over time, the number of participating countries represented in these surveys has gradually increased to its present level; for example, 29 countries took part in the survey in 2016 (Brodschneider et al., 2016). ...
... 1.5% respectively, and an overall loss rate of 16.4% (Gray et al., 2019). Again, the loss rates for winter 2019/2020 are a little higher. ...
... By repeating the same tests on datasets collected in different years, for each year separately, effects found to be significant can become more convincing as evidence builds up. In this series of short papers on winter losses we have so far tested several potential risk factors: beekeeping operation size and migration of colonies (Brodschneider et al., 2016(Brodschneider et al., , 2018, effects of various forage sources (Gray et al., 2019), and most recently the effect of the proportion of colonies going into winter with young queens (Gray et al., 2020). The effects of forage sources were found to vary depending on the country and were best examined at the country level. ...
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... 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]. ...
... 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]. COLOSS surveys of winter mortality rates also show that loss rates in Europe may vary considerably among geographical regions in any year [8]. ...
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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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Bees are subject to numerous pressures in the modern world. The abundance and diversity of flowers has declined, bees are chronically exposed to cocktails of agrochemicals, and they are simultaneously exposed to novel parasites accidentally spread by humans. Climate change is likely to exacerbate these problems in the future. Stressors do not act in isolation; for example pesticide exposure can impair both detoxification mechanisms and immune responses, rendering bees more susceptible to parasites. It seems certain that chronic exposure to multiple, interacting stressors is driving honey bee colony losses and declines of wild pollinators, but such interactions are not addressed by current regulatory procedures and studying these interactions experimentally poses a major challenge. In the meantime, taking steps to reduce stress on bees would seem prudent; incorporating flower-rich habitat into farmland, reducing pesticide use through adopting more sustainable farming methods, and enforcing effective quarantine measures on bee movements are all practical measures that should be adopted. Effective monitoring of wild pollinator populations is urgently needed to inform management strategies into the future. Copyright © 2015, American Association for the Advancement of Science.
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As in many other locations in the world, honeybee colony losses and disorders have increased in Belgium. Some of the symptoms observed rest unspecific and their causes remain unknown. The present study aims to determine the role of both pesticide exposure and virus load on the appraisal of unexplained honeybee colony disorders in field conditions. From July 2011 to May 2012, 330 colonies were monitored. Honeybees, wax, beebread and honey samples were collected. Morbidity and mortality information provided by beekeepers, colony clinical visits and availability of analytical matrix were used to form 2 groups: healthy colonies and colonies with disorders (n = 29, n = 25, respectively). Disorders included: (1) dead colonies or colonies in which part of the colony appeared dead, or had disappeared; (2) weak colonies; (3) queen loss; (4) problems linked to brood and not related to any known disease. Five common viruses and 99 pesticides (41 fungicides, 39 insecticides and synergist, 14 herbicides, 5 acaricides and metabolites) were quantified in the samples.The main symptoms observed in the group with disorders are linked to brood and queens. The viruses most frequently found are Black Queen Cell Virus, Sac Brood Virus, Deformed Wing Virus. No significant difference in virus load was observed between the two groups. Three acaricides, 5 insecticides and 13 fungicides were detected in the analysed samples. A significant correlation was found between the presence of fungicide residues and honeybee colony disorders. A significant positive link could also be established between the observation of disorder and the abundance of crop surface around the beehive. According to our results, the role of fungicides as a potential stressor for honeybee colonies should be further studied, either by their direct and/or indirect impacts on bees and bee colonies.
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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.
Official Journal of the European Union
OJEU. (2018). Official Journal of the European Union, L 132.