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Adult honey bees (Apis mellifera) usually maintain colony brood rearing temperature between 34-35°C by thermoregulation. The brood may, however, also be subjected to suboptimal temperature. Here we investigated whether a decrease of brood rearing temperature may have effects on larval mortality, adult emergence, longevity, morphology and susceptibility to poisoning by pesticides (dimethoate). Using the in vitro rearing protocol of Aupinel (2005), we were able for the first time to control the brood temperature not only during the pupal stage but also during the larval stage. Honey bee larvae were reared in vitro at 35°C (optimal) and 33°C (suboptimal) from 12 h after hatching for 15 days. Dimethoate was tested by ingestion either on 4-day old larvae or on 7-day old adults. Our results showed that lower rearing temperature had no significant effects on larval mortality and adult emergence, but adult bee mortality was strongly affected. Moreover, adult workers emerging at 33°C were significantly more susceptible to dimethoate. Larval LD50 (48 h) was, however, 28 times higher at 33°C than at 35°C. The striking differences between larvae and adults may be explained by differential larval metabolism at 33°C and resulting slower active ingredient absorption. We conclude that adult honey bees reared at even slightly suboptimal brood temperature may be more susceptible to pesticide poisoning and be characterised by reduced longevity. Thus, low temperature brood rearing could be another stress factor for colonies.
Influence of brood rearing temperature on honey bee
development and susceptibility to poisoning by pesticides
Piotr Medrzycki1, Fabio Sgolastra2, Laura Bortolotti1, Gherardo Bogo1, Simone Tosi1, Erica Padovani1,
Claudio Porrini2 and Anna Gloria Sabatini1
1Consiglio per la Ricerca e la Sperimentazione in Agricoltura, Unità di Ricerca di Apicoltura e Bachicoltura, Via di Saliceto 80,
40128 Bologna, Italy.
2Dipartimento di Scienze e Tecnologie Agroambientali - Area Entomologia, Università di Bologna, Viale G. Fanin 42,
40127 Bologna, Italy.
Received 30 April 2009, accepted subject to revision 2 December 2009, accepted for publication 13 December 2009.
*Corresponding author: Email:
Adult honey bees (
Apis mellifera
) usually maintain colony brood rearing temperature between 34-35°C by thermoregulation. The brood may,
however, also be subjected to suboptimal temperature. Here we investigated whether a decrease of brood rearing temperature may have
effects on larval mortality, adult emergence, longevity, morphology and susceptibility to poisoning by pesticides (dimethoate). Using the
rearing protocol of Aupinel (2005), we were able for the first time to control the brood temperature not only during the pupal stage but
also during the larval stage. Honey bee larvae were reared
in vitro
at 35°C (optimal) and 33°C (suboptimal) from 12 h after hatching for 15
days. Dimethoate was tested by ingestion either on 4-day old larvae or on 7-day old adults. Our results showed that lower rearing
temperature had no significant effects on larval mortality and adult emergence, but adult bee mortality was strongly affected. Moreover, adult
workers emerging at 33°C were significantly more susceptible to dimethoate. Larval LD50 (48 h) was, however, 28 times higher at 33°C than
at 35°C. The striking differences between larvae and adults may be explained by differential larval metabolism at 33°C and resulting slower
active ingredient absorption. We conclude that adult honey bees reared at even slightly suboptimal brood temperature may be more
susceptible to pesticide poisoning and be characterised by reduced longevity. Thus, low temperature brood rearing could be another stress
factor for colonies.
Influencia de la temperatura de la cría en el desarrollo de la
abeja de la miel y susceptibilidad a la intoxicación por los
Las abejas adultas (
; Himenoptera: Apidae) mantienen normalmente la temperatura de la cría dentro de un rango estrecho
(34-35°C) mediante la termorregulación. En ciertas situaciones, sin embargo, la cría puede estar sometida a condiciones de temperatura
subóptima. El objetivo de este estudio fue investigar si la disminución de la temperatura de la cría solamente de 2°C puede tener efectos
sobre la mortalidad larvaria y sobre la emergencia de los adultos y otroa parámetros vitales. Por otra parte la susceptibilidad a la intoxicación
por los pesticidas (dimetoato) fue estudiada en larvas y en los adultos emergidos de la cría mantenida en las temperaturas probadas. Para
estos propósitos, las larvas de la abeja de la miel fueron criadas
in vitro
en dos temperaturas distintas: 35°C (óptimo) y 33°C (subóptimo),
desde 12 h después de la incubación hasta los 15 días de edad. En diversos experimentos, el dimetoato fue administrado a las larvas o a los
adultos. La mortalidad larvaria, la emergencia de adultos y la longevidad fueron medidas. Nuestros resultados mostraron que la temperatura
Journal of Apicultural Research
49(1): 52-59 (2010) © IBRA 2010
DOI 10.3896/IBRA.
Since the escalation of honey bee colony loss phenomena and the
definition of “Colony Collapse Disorder” (CCD), many scientific studies
have been carried out each year to determine possible damage
factors and to estimate their relative importance, with the ultimate
aim of establishing preventive and damage limiting measures
(Connor, 2007; Cox-Foster
., 2007; Henderson
et al
., 2007a; b;
et al
., 2007; 2009). It is commonly agreed that there is no one
single factor causing bee/colony losses, rather there are many factors
belonging to different categories of stress factors (Oldroyd, 2007; Cox
-Foster and vanEngelsdorp, 2009; Neumann and Carreck, 2010).
Moreover, synergistic effects probably pose obstacles and
complications in experimental procedures, since many factors can
change their importance when administered in combination with
others. Synergism has been studied to test the effects of several
pesticides applied at the same time on honey bees (Colin and
Belzunces, 1992; Pilling and Jepson, 1993; Pilling
et al
., 1995; Meled
et al
., 1998). The sublethal effects of some factors make the problem
complex, because there is often no direct link between the factor and
the damage. The former may cause some behavioural modifications in
workers and, since the honey bee is eusocial, these modifications can
lead to severe damage at the colony level, even if there is no
apparent effect at the individual level (Vandame
et al
., 1995;
et al
., 2003; Medrzycki
et al
., 2003; Decourtye
et al
., 2004;
2005; Kralj and Fuchs, 2006; Kralj
et al
., 2007; Desneuz
et al
., 2007).
Colony loss is probably often a multifactorial syndrome, and if bees
are stressed by some causes, they may be less able to produce an
effective immune response to pathogens. For example, several studies
(Bowen-Walker and Gunn, 2001; Amdam
et al
., 2004; Yang and Cox-
Foster, 2007) showed the effects of the ectoparasitic mite
(Acari: Varroidae) on honey bee physiology. The altered
bee physiology may increase susceptibility to infective agents or other
stressing factors such as pesticides that may lead the colony to
collapse. The situation is more complicated when the sublethal effect
of one factor acts in synergism with other factors.
Another phenomenon, hypothesised by us and which makes the
problem even more complex, concerns a causal factor which has
invisible direct effects, but may cause delayed indirect damage. In this
case it is much more difficult to demonstrate a link between this
factor and the visible damage.
Brood rearing temperature is one of the most precisely controlled
physiological parameters in a honey bee colony. Adult workers keep
the central brood area at 34-35°C (Himmer, 1927; Seeley and
Heinrich, 1981). In order to maintain the temperature within this
narrow range, the high or low external temperature is contrasted by
thermoregulation behaviours (Kronenberg and Heller, 1982; Jones
., 2004). Thus, normally only slight deviations from the optimal level
will occur. Nevertheless, in particular situations, the brood may be
subject to conditions of suboptimal temperature. Several studies
et al
., 2003; Groh
et al
., 2004; Jones
et al
., 2005; Becher
., 2009) report the effects of the temperature of pupal incubation on
adult workers. Negative effects on short-term learning, memory
capacities and orientation were shown when pupae were exposed to
suboptimal temperature instead of the optimal one (34.5°C). In
particular, bees reared at low temperatures showed reduced dance
performances and proboscis extension reflex. McMullan and Brown
(2005) showed that bees newly emerged from brood pupated at lower
temperature (30°C) are more susceptible to tracheal mite infestation
than those emerged from brood pupated at normal temperature. In
all of these studies the brood was incubated at several temperatures
from the moment in which it was capped. We have hypothesised that
incubating the larvae at the suboptimal temperature during the whole
developmental period could have even stronger effects on the
emerging adults. Probably, these weak bees will be more susceptible
to other stressors (even at sublethal level) with slow but important
consequences on the whole colony. Recently, the
in vitro
rearing method has been established (Aupinel
et al
., 2005), thereby
allowing the exposure of larvae to precisely determined temperatures.
It was hypothesised that a slight poisoning, causing the loss of an
apparently insignificant quantity of adult bees in early spring, i.e. in
conditions of low external temperatures, could potentially reduce the
ability of the colony to maintain brood at constant optimal temperature.
The aim of the present study was therefore to analyse the effects of
suboptimal brood rearing temperature on larvae and emerging adults.
Temperature was studied both as a single factor and in synergism
with poisoning by dimethoate, a commonly used organophosphorous
pesticide and the reference active ingredient for many toxicological
studies (EPPO, 2001).
Effects of brood rearing temperature on honey bees 53
de cría más baja no tiene ningún efecto sobre la mortalidad larvaria, o en la tasa de emergencia de adultos, mientras que la mortalidad de
abeja adulta se vio fuertemente afectada. Por otra parte, las abejas adultas que emergieron de la cría mantenida en la temperatura subóptima
fueron más susceptibles a la intoxicación por el dimetoato. Por el contrario, el LD50 larvario (48 h) fue 28 veces más alto a una temperatura
más baja que la temperatura óptima. Esto se puede explicar por el metabolismo larvario más lento en la temperatura más baja, con la
consecuente absorción más lenta de ingredientes activos. Con este estudio podemos concluir que las abejas adultas que derivaban de la cría
mantenida a temperatura subóptima tienen una aptitud más baja y son más susceptibles a la intoxicación por pesticidas.
Key words: bee losses, brood temperature, CCD, development, mortality, longevity, malformations, pesticide toxicity
Materials and methods
The experiments were carried out by applying the
in vitro
bee brood
rearing protocol of Aupinel
et al
. (2005). The in hive phase consisted
of isolation of the queen on an empty comb for 26 hours. After that,
the larvae (aged about 12 hours) were grafted using a thin paintbrush
(00), into previously prepared 48-well tissue culture plates containing
a plastic queen cell (Nicoplast©) in each well. The appropriate semi-
artificial diet was provided. All the larvae used in one experiment were
taken from the same hive according to the protocol. The plates with
the larvae were then incubated in an airtight Plexiglas desiccator at
95% RH and at the desired temperature, according to the
experimental group. The “warm” larvae were incubated at the optimal
temperature (35°C), while the “cold” larvae were incubated at a
suboptimal temperature (33°C). Some preliminary trials were
54 Medrzycki, Sgolastra, Bortolotti, Bogo, Tosi, Padovani, Porrini, Sabatini
Rearing day "warm" rearing (35°C) "col d" reari ng (33°C)
D4 30µ diet
30µ diet
D5 40µ diet
D6 50µ diet
40µ diet
D7 50µ diet
D8 transfer to 75% R
D9 transfer to 75% R
D19 emer
D20 emergence
graf ting, 20µl diet A, 95% RH
20µl diet B
Table 1.
Brood rearing management according to the incubation
35 124 43
33 120 48
35 133 50
33 130 65
35 90 79 18
33 183 52 31
35 131 18 77
33 132 23 53
35 40 10 85
33 123 15 26
35 40 20 75
33 81 20 72
35 137 47 50
33 261 28 66
0.000 *
08/08/2008 (2)
05/09/2008 (1)
05/09/2008 (2)
Dev elopm ent m ortality Em erged adults
G rafting date Brood rearing
te m p .(°C )
n of larvae
on D4
08/08/2008 (1)
Table 2.
Experiment 1. Development mortality (
-test) and adult emergence (
test) related to the brood rearing temperature. Results of 7
separate trials. * significant difference
necessary in order to calibrate Aupinel’s protocol for the conditions of
suboptimal temperature. The “cold” larvae showed slower metabolism
dynamics, thus the diet consumption was slightly slower.
Consequently, one-day delay of the last two feedings was
necessary, while assuring the constant diet availability and the equal
amount of diet consumed for both temperatures (Table 1). Adult
emergence was also delayed by one day, so the longevity
measurements had to take this parameter into account. On the 8th
and 9th day (for “warm” and “cold” larvae respectively), the cells were
moved to another desiccator with the temperature set at 35°C or 33°
C (respectively) and 75% RH. In order to study the influence of brood
temperature on larval development, adult longevity and susceptibility
both of larvae and adults to poisoning by dimethoate, five
experiments were carried out. Experiments 1 and 2 were repeated in
different periods of the year (from spring to late summer).
Experiment 1 Development mortality
During development of both groups of larvae (“warm” and “cold”),
mortality was checked at the end of the larval stage (day 15) and
adult emergence was recorded on day 23, i.e. when no further adult
workers would emerge (Table 2). Since live individuals are in the
pupal stage at day 15 (which corresponds to the 19th day of individual
life), the mortality check was based exclusively on visual assessment.
Pupae appearing normal were considered alive, whilst those which
appeared abnormally developed (shape of larva, lack of appendages,
abnormal colour) were considered dead. Regarding the adult
emergence rate assessment, only workers which had completely left
the cell were considered emerged, and those remaining were
considered non-emerged. The development mortality test was
repeated seven times but only five of the tests were continued until
emergence of adults. The remaining two experiments were
at the end of the pupal stage, so no emergence data are available
Table 2
). The results were processed separately for each experimental
date. The % development mortality (D15) and the % adult
emergence were calculated by referring to the number of larvae alive
at D4. Mortality occurring before D4 was considered to have been
by manipulation during grafting. For the development mortality,
-test (after arcsine-transformation) was applied, considering single
plates as experimental units. The % adult emergence was compared
by the
Experiment 2: Adult worker survival
Two groups of grafted larvae were incubated according to the rearing
protocol until D15. After that, the cells containing the pupae were
moved to emergence boxes (16 x 12 x 5cm), equipped with two
feeders: one containing organic
honey, and the other one
containing a mix of organic pollen and honey. The pupae and,
subsequently, the emerged adult workers were kept at 35°C and 75%
RH. The experiment was repeated three times in different periods of
the year: in May, July and August, 2008. Survival was assessed
periodically and the results were processed separately for each trial.
The % survival of “cold” and “warm” bees” was compared at different
intervals using the
test (Table 3).
Effects of brood rearing temperature on honey bees 55
Experiment 3: Larval susceptibility to poisoning
by dimethoate
The larval LD50 (48 h and 72 h) of dimethoate was studied. Both for
the “warm” and the “cold” group, six multiwell plates were prepared,
each containing 48 grafted larvae. On day 4, except for the control
plates, the diet provided was contaminated with progressive amounts
of dimethoate. The quantities of active ingredient provided to the
tested larvae were: 0.83 µg, 1.65 µg, 3.30 µg, 6.60 µg and 13.30 µg;
all 48 larvae on each plate received the same dose (Aupinel
et al
2007). Thus, for each group, one untreated and five treated plates
were obtained. 48 and 72 hours after poisoning, mortality was checked.
The calculation of % mortality was the number of larvae alive at D4.
Subsequently the LD50 value was calculated using probit analysis.
Experiment 4: Adult worker susceptibility to
poisoning by dimethoate
Two groups of adult workers were obtained from the brood reared at
the two temperatures. 144 and 288 larvae were grafted respectively
for the optimal and suboptimal temperature incubation. Before
emergence (day 15), the cells with the pupae were moved to
emergence boxes as described for experiment 2. The adult workers
were then kept at 35°C and 75% RH for seven days and then divided
in groups of 10 individuals which were transferred to Perspex cages
7th day p13th day p20th day p
35 61 93.4 93.4 88.8
33 46 3.2 0.0 0.0
35 16 - 62.5 -
33 56 - 0.0 -
35 101 97.0 97.0 96.0
33 70 0.0 0.0 0.0
0.002 *
< 0.001 *
< 0.001 *
< 0.001 *
< 0.001 *
Grafting date
< 0.001 *
< 0.001 *
Brood rearing
tem p .(°C ) n
16/05/2008 **
% survival
Table 3.
Experiment 2. Adult worker survival (at the 7th, 13th and 20th day of adult life) related to the brood rearing temperature. Results of
three separate trials are shown. *significant difference (
); ** observations taken on the 8th, 14th, and 20th day.
a b so lu te c o rre c te d
33 0 62 62
35 5 85 84
33 0 100 100
35 5 100 100
33 6 100 100
35 20 20
33 50 50
n of bees
Brood rearing
te m p. (°C )
Tim e (h) p
% control
% Dim ethoate m ortality
0.001 *
Table 4.
Experiment 4. Adult bee mortality 8, 24 and 48 hours after the administration of 0.15µg of dimethoate per bee. Data corrected with
Schneider-Orelli formula. *significant difference (
for the toxicological tests. In order to facilitate handling, the workers
were anesthetised by keeping them at 4°C for 2 hours. The cages
(13 x 6 x 11 cm) had two opposite walls made of transparent Perspex
to allow visual control, and were equipped with a small frame with
bee wax foundation. 200 µl of aqueous sucrose test solution (0.5 g w/w)
was provided to each group of 10 workers, accordingly to EPPO
guidelines. In this way, thanks to trophallaxis, each bee received ~20 µl
of the solution (EPPO, 2001). The test solution was pure for the
control workers, and contaminated with dimethoate for the treated
ones. Every treated worker received in average 0.15 µg of the active
ingredient which is the equivalent of the LD50 (24 h) (Gough
et al
1994). When the test solution was consumed, the cages were
equipped with feeders containing sucrose solution (0.5g w/w)
. The cages were then kept at 35°C during the test. The
mortality was checked at 8, 24 and 48 hours. The % mortality of
treated workers was corrected with the formula Schneider-Orelli and
analysed with
- test. The number of treated and control workers
deriving from the “cold” and “warm” rearing is shown in Table 4.
Experiment 1: Development mortality
The decrease of brood temperature by 2°C had no effect either on the
development mortality, or on adult emergence (except for only one of
the five trials; Table 2). Thus from the “cold” brood an apparently
unaffected number of adult workers emerged. The trials conducted in
different periods produced different results in terms of development
mortality. Nevertheless, the difference between the “cold” and “warm”
larvae was never significant.
Experiment 2: Adult worker survival
Workers emerging from brood reared at suboptimal temperature lived
significantly less than the “warm” ones (Table 3, Fig. 1). The group of
“cold” bees reached the 0% survival level very rapidly, while the
“warm” ones were still characterised by low mortality. The differences
were significant for all three trials, even though they were carried out
in different periods.
Experiment 3: Larval susceptibility to poisoning
by dimethoate
The larval LD50 at 48 and 72 hours are shown in Table 5. It is clear
that the “cold” larvae responded more slowly to poisoning by
dimethoate than the “warm” ones. In fact, after 48 hours from
poisoning the mortality was almost stable in the “warm” larvae, while
it was still growing significantly in the “cold” ones.
Medrzycki, Sgolastra, Bortolotti, Bogo, Tosi, Padovani, Porrini, Sabatini
2 4 6 8 10 12 14 16 18 20
Adult bee age (days)
% survived bees
grafting date: 16/05/08
Adult bee age (days)
% survived bees
grafting date: 25/07/08
Adult bee age (days)
% survived bees
grafting date: 08/08/08
Fig. 1.
Experiment 2. Survival of adult workers emerging from the
brood reared at optimal (35°C; white squares) and suboptimal
temperature (33°C; black stars). Results of three different trials are
Experiment 4: Adult bee susceptibility to
poisoning by dimethoate
The adult bees originating from the “cold” larvae were significantly
more susceptible to poisoning by dimethoate (Table 4). In dimethoate
treated bees, mortality increased rapidly, reaching 62% after 8 hours.
At that time, bees emerged from the “warm” brood, still had 0%
Our data suggest that across different experimental time windows
there are significant effects of suboptimal brood rearing temperature
on adult viability (longevity and susceptibility to dimethoate) but not
on bee development. Our results on adult emergence (Experiment 1)
are consistent with earlier findings (Tautz
et al.
, 2003) in that there
were no significant differences in adult emergence between brood
rearing temperatures of 32°C, 34.5°C and 36°C. Due to
in vitro
rearing (Aupinel
et al
., 2005; 2007), we were also able to study the
effects of temperature on larval development, which also yielded no
significant effects. Moreover, larval susceptibility to poisoning by
dimethoate was also not increased by temperature reduction
(Experiment 3). On the contrary, it appeared that lower temperatures
could “protect” the brood against the temporary food contamination,
probably due to reduction of metabolism dynamics with the
consequent slower assimilation of the active ingredient (Petz
et al
2004). Indeed, the LD50 (48h) was 28 times higher when the larvae
were incubated at the suboptimal temperature than at the optimal
temperature. After 72 hours, this difference was much lower. This
result suggests that larval response to dimethoate strongly depends
on the test temperature. In our study, the LD50 (48h) of dimethoate
calculated at 35°C was lower than the value calculated by Aupinel
. (2007) (0.67
1.9 µg / larva), although both studies followed the
same protocol. This discrepancy might be explained either by
differences in the quality of royal jelly used for the diets, or by
different honey bee ecotype (French
Italian) of the
Apis mellifera
subspecies used in the tests. In addition, slight deviations
from the fixed temperature (35°C) in both studies may have
significantly influenced the LD50 value.
Although we found no significant effect of the brood rearing
temperature on the worker emergence rate, adult bee viability was
significantly affected. In fact the “cold” adult workers showed a
shorter lifespan (Experiment 2), and were more susceptible to
poisoning by dimethoate (Experiment 4).
These results suggest that the workers emerging from
brood reared at suboptimal temperature are characterised by a lower
viability and might be unable to complete their normal tasks because
of their shortened lifespan. Other authors (Tautz
et al
., 2003; Jones
Effects of brood rearing temperature on honey bees 57
., 2005) have seen a significant negative effect of lower temperature
during the pupal stage on other aspects of bee life such as waggle
dance performance, learning and memory.
We therefore hypothesise that the studied factor may have severe
negative effects on the entire colony. In the future it will be important
to further study the behavioural effects of the lower brood
temperature in the first hours of larval life. Moreover, it seems that
the effects of the brood temperature on the viability of emerged
adults vary in relationship to the period (Experiment 2). The cold
brood rearing always caused a significant reduction of adult longevity
in comparison to the warm brood rearing. Nevertheless, this reduction
differed according to the season in which the test was performed. In
fact, the “cold” bee longevity seemed to be higher in spring (0%
survival on 14th day) than in summer (0% survival on 7th day). If such
seasonal effect of low brood temperature on adult bees could be
confirmed by further studies, it might well be that brood is able to
better tolerate lower temperatures in colder seasons. Since the
experimental rearing conditions were the same in all seasons it is
feasible that this mechanism should depend on the first 12 h of larval
life (maternal effect, food and temperature conditions in the hive).
Bee mortality and colony losses are complex phenomena and
often it is not easy to find the link between the causes and the
effects. Based on the results of our study, we hypothesize the
following scenario: during early spring, the ratio between adult
workers and reared brood is very delicate due to low external
temperatures at night and the low number of adult workers. In this
period, a moderate bee mortality (e.g. caused by pesticides) could
break this delicate equilibrium and the colony may lose the capacity to
maintain brood temperature at optimal level. The brood would be
reared at suboptimal temperature, producing an apparently normal
quantity of workers, but these new workers will be characterized by
reduced longevity and increased susceptibility to pesticides and,
probably, to other stressors. This will result in the number of new
workers again being insufficient to maintain the brood at the optimal
temperature which, combined with their behavioural dysfunctions
et al
., 2003; Jones
et al
., 2005) will lead to chronic colony
weakening until collapse. This scenario may explain the cases of
mysterious bee losses especially in spring apparently disconnected in
time from the possible cause such as pesticide poisoning.
This is the first investigation of the effects of suboptimal brood
temperature on honey bees, with the stress factor applied since the
first larval instar (12 h age). Future studies are required to analyse
the mechanisms in detail.
Research made within the project “APENET: monitoring and research
in apiculture”, funded by the Italian Ministry of Agricultural Food and
Forestry Policies.
We are grateful to Cecilia Costa and Peter Neumann for valuable
comments on the manuscript.
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... The suitable temperature range in which honeybees can breed successfully is significantly smaller than their survivable temperature range. The honeybee brood consists of eggs, larvae and pupae, and the temperature in the brood chamber (see Fig. 1) should be between 34 • C and 36 • C (Medrzycki et al., 2010) for brood to hatch as healthy young bees. A variation of more than a few degrees can kill or debilitate the brood (Medrzycki et al., 2010). ...
... The honeybee brood consists of eggs, larvae and pupae, and the temperature in the brood chamber (see Fig. 1) should be between 34 • C and 36 • C (Medrzycki et al., 2010) for brood to hatch as healthy young bees. A variation of more than a few degrees can kill or debilitate the brood (Medrzycki et al., 2010). All the young bees take on the role of foragers after a few weeks of hatching. ...
Decision making capability of a system is highly dependent upon the quality and quantity of training data. Majority of beehive monitoring systems developed for research purposes are designed to collect data through a small set of sensors, and from locations with little geographic diversity. This hinders the development of a dataset that can be used to effectively train machine learning models. In this work, we explain the design and development of a multi-sensory, remote data acquisition system for beehives (BeeDAS), with focus on low-power consumption and long-range communication. We address design challenges associated with such systems and highlight the critical issues that need consideration. The proposed system enables collection of data from beehives at remote locations and harsh environment. Results of field deployments elucidate the effectiveness of various sensors which measure temperature, humidity, atmospheric pressure, CO, acoustics, vibrations and the weight of a hive in hostile environment. This work also uses random forest regression to evaluate the feature importance of different sensors, environmental variables such as temperature, humidity, rain, wind speed as well as the information related to seasons, towards estimating the daily hive weight change, on a dataset comprised of 1,250 days of sensor recordings. We also evaluate the protocol designed for communication using Narrow Band Internet of Things (NB-IoT). The issues related to power optimization, sleep intervals and data storage in remote monitoring are also discussed. #### You can request a full version of this article by emailing at ####
... Biochemical mechanisms involved in insecticide detoxification or in protection against extreme temperatures have been thoroughly investigated individually, but only few studies focused on those involved in the influence of temperature on insecticides' toxicity. Among potential explanations, increased insecticide toxicity may be due to an increase in locomotor activity and feeding rate occurring at high temperature in insects, therefore increasing the penetration of the product into pest's body (Boina et al., 2009;Medrzycki et al., 2010). Such mechanism is however unable to explain the negative relationship between temperature and toxicity observed for some products or pest species and other mechanisms should thus be involved. ...
... However, this lower mortality was only temporary as the mortality increased again within few hours for deltamethrin. Medrzycki et al. (2010) observed that developmental temperature differently influenced the toxicity of dimethoate in Apis mellifera according to their age. Adult workers emerging at 33 • C were indeed more susceptible to this insecticide than those emerging at 35 • C while the opposite pattern was observed in larvae. ...
As temperature is expected to strongly increase in the future, understanding temperature-mediated toxicity of insecticides is determinant to assess pest management efficiency in a warming world. Investigating molecular and biochemical mechanisms associated with cross mechanisms of temperature and insecticides on pests' tolerance would also be useful in this context. This study aimed to investigate cross effects between temperature and insecticides on the survival of a major pest, the codling moth Cydia pomonella, and their underlying mechanisms. The effect of three insecticidal active ingredients, i.e. chlorantraniliprole, emamectin and spinosad, was assessed at different temperatures on: (i) C. pomonella larval survival; (ii) detoxification enzymes activities (cytochrome P450 multi-function oxygenases, carboxylesterases and glutathione S-transferases) and (iii) genes expression of some detoxification enzymes, heat shock proteins and receptors targeted by the insecticides. We observed a decreased efficiency of emamectin and spinosad at high temperature to control the codling moth while no influence of temperature on chlorantraniliprole efficacy was observed. Detoxification enzymes activities were improved by heat stress alone but not by double stress (temperature + insecticides). Moreover, two detoxification genes (Cyp9A61 and Gst1) were over-expressed by a single stress but not by two stresses while Hsp70 and Cyp6B2 genes may be involved in tolerance to two stresses in C. pomonella. These results confirmed the cross effects of temperature and insecticides on C. pomonella for emamectin and spinosad and provided clues to understand how temperature affects the susceptibility of C. pomonella to insecticides. They illustrate however the complexity of molecular and biochemical responses of individuals facing multiple stresses.
... Although the preferred temperature for individual honey bees is 28 °C (Schmolz et al. 2002;McAfee et al. 2020), the honey bee colony thermoregulates efficiently via active heat production, evaporation, or ventilation and maintains the in-hive temperature at 32-36 °C for proper development of the brood (Jones and Oldroyd 2006). Failure of thermoregulation during the brood and pupal stages of honey bee colonies is known to negatively affect susceptibility to pesticides (Medrzycki et al. 2010), behavioral performance (Tautz et al. 2003), synaptic organization of the brain (Groh et al. 2004), and memory of adult bees (Jones et al. 2005). ...
With the rising occurrence of sudden heat waves, honey bees are at risk of exposure to unprecedented heat stress. We investigated the synergistic effects of imidacloprid (IMD) and high temperature on honey bees. Mini hives were treated with IMD (20 ppb for 14 days) and high temperature (41 °C for 6 h) either singly or in combination. Heat shock protein 70 and 90 genes were upregulated in bees exposed to the combined treatment compared to those exposed to each single treatment. Transcriptome analysis revealed that metabolic pathways remained intact in the high temperature treatment, whereas several metabolic pathways were altered by either the IMD treatment (downregulation of cellular respiration pathways) or the combined treatment (upregulation of protein synthesis and signaling pathways). These findings suggest that IMD and high temperature have negative synergistic effects on honey bees.
... Capped brood is vulnerable to changes in hive temperature because it requires temperatures between 34 • C and 36 • C to mature properly into adult bees. A variation of more than a few degrees can kill or debilitate the brood [146]. If the temperature is below 34 • C, hive bees form clusters over capped brood, consume honey and metabolise rapidly to generate heat with their flight muscles [28]. ...
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Honeybees play a vital role in sustaining our agricultural economy and maintaining the ecosystem. A healthy and well spread bee population is crucial for better pollination of local crops as well as non-agricultural flora. The decline in global bee population and increased instances of Colony Collapse Disorder (CCD) have drawn attention of researchers all over the world. Recent technological advancements have impacted the bee-keeping industry in numerous ways, and electronic beehive monitoring has significantly improved over the past few years. Monitoring systems have been developed to observe temperature, humidity and acoustics inside the hive, overall weight of the hive and outgoing/incoming bee traffic to gauge the health of beehives. These monitoring systems aided by various wireless communication technologies make it possible for the beekeepers to monitor a large number of hives continuously, simultaneously, from a distance, and only intervene when required. The most important characteristic of a monitoring system is the set of parameters used for monitoring. Each commercially available solution makes use of its own set of parameters to determine the health of bees. Most of the research carried out in this area focuses on a small set of two to three sensors in each study, rather than examining a bigger set for its collective usefulness. For communication, the monitoring systems rely on either 3G/4G or WiFi networks which are not accessible everywhere, or on satellite communication which can be very expensive. Despite having a high price tag, most of the monitoring systems provide beekeepers with just the raw data from sensors without any analysis on bee health. Proposed systems in the literature have also not been able to make the most of deep learning algorithms, mostly because the data used for training is collected over a short period of time, and from hives with little geographic diversity. Use of such small datasets with limited variations often leads to inconclusive and unreliable results. Beekeepers, in particular from Australia, have not been able to take full advantage of these electronic monitoring systems because of the aforementioned limitations. The vast landscape with no cellular coverage, and the high associated costs of using such monitoring systems are the major challenges faced by the local honeybee industry. This work addresses the design and development of a beehive monitoring system capable of long range communication with low power consumption. Appropriate sensors for the proposed system are selected after an extensive review of literature. This selection is based on the relevance of sensor with bee health/activity, suitability for long distance transmission over low capacity channels, and optimal use of power. Extraction of appropriate features from sensor data is the key requirement for remote deployment. Different experiments were performed to evaluate various sensors and their features for their importance, and viability for hive deployment. A total of eight sensor systems were deployed in multiple hives, at different locations, and in varying environmental conditions over a 12 month period. During these deployments, Narrow Band Internet of Things (NB-IoT) was thoroughly tested for its communication feasibility from remote sites. Based on the findings, use of NB-IoT is proposed for low cost and reliable communication from remote beehives. The design of this system has also been made available for other researches to use and improve upon. The aim of sensor deployments in this study is not only to test different sensors and communication for beehive monitoring, but also to build a quality sensor dataset from beehives deployed at different sites. Beehive data collection is a slow process based on the natural activity and life cycle of honeybees. The harsh environment of remote sites, sensor failures, and communication issues make it a very challenging task. A dataset of 2,170 days of beehive sensor data, weather data, and seasonal information has been collected during this study. The resolution of 144 data points per day in this dataset provides a good picture of daily bee activity, and facilitates the use of machine learning in beehive health monitoring. Random forests are used to evaluate the contribution of different sensors in this dataset, as well as of the performance of monitoring system. Daily hive weight variations are a crucial aspect of hive health and bee activity. Hive weight is affected by multiple complex internal and external factors. Traditionally, an expensive and difficult to deploy weighing scale is used to monitor the hive weight. This is the first work to propose the use of machine learning for beehive weight estimation. Latest machine learning algorithms were tested for their suitability with beehive monitoring and weight estimation, and modified to make most of the information available in beehive sensor data. This work presents two deep learning models for beehive weight estimation, WE-Bee and Apis-Prime. The features for training and testing these models were selected after an in-depth study of bee behaviour, and the impact of environment on bee foraging activity. WE-Bee uses Long Short Term Memory (LSTM) encoders and decoders with temporal attention, whereas Apis-Prime uses self-attention encoders for the same task. These models were tested on sensor systems and hives which were not part of the training set. The promising results validate the good performance of both networks for unseen data. The hives used for the data collection were allowed their natural variations in colony strengths and forager activity, and were moved to sites at a significant distance from each other to collect geographically diverse data. The diversity of the training data played a significant role in the quality of estimations. Use of these machine learning models has the potential to eliminate expensive beehive weighing scales, and reduce the cost of beehive monitoring systems by more than half. Evaluation of sensors and contribution of features towards a specific task is important for improving and fine-tuning the design of monitoring systems. This work proposes the use of attention weights of self-attention encoders to evaluate sensors and sensor features, as well as to identify the times of day when sensor data carries most information. This enables a significant reduction in the number of features used for estimation. The equally good results of weight estimation with reduced features signify the usefulness of self-attention encoders for feature selection. These findings not only help assess the bee health/activity remotely, but also significantly reduce the monitoring costs. The estimates about hive weight variations using machine learning provide the beekeepers with important information about the hive without using an expensive weighing scale. The promising weight estimates indicate that the proposed system collects important data from the hive, which can also be utilized for a variety of beehive health monitoring tasks.
... Maintaining the correct hive temperature is particularly important in the case of bees (Wang et al., 2016). The bees derived from a brood growing in abnormal temperatures are characterized by cognitive disorders (Jones et al., 2005), they are less resistant to environmental pollution (Medrzycki et al., 2010) in effect bring less food to the hives, which may affect the condition of the entire colony (Tautz et al., 2003). ...
Plant protection products may affect the behavior of organisms which are not a target of control. The effect of Karate Zeon 050 CS (λ-Cyhalothrin -based insecticide; λ-CBI) and Amistar 250 SC (Azoxystrobin-based fungicide; ABF) was determined on Apis mellifera worker attraction towards their own colony odour, along with temperature preferences. Bees exposed to pesticides prefer the environment with the odour of their nest less often than the control group, and that insecticide-treated bees chose warmer environments than the control insects. The observed differences in the bees, especially with attraction towards their own colony, were dependent on the time of day. Chromatographic analyses indicated that λ-Cyhalothrin elimination was half that of Azoxystrobin in bee organisms, and both agents retarded each other’s clearance. Mathematical modeling estimated that despite a relatively high disappearance rate, both compounds might have been bio-accumulated at relatively high level.
... For instance, honey bee colonies typically maintain their brood nests at 32.0-37.0ºC (Meikle et al., 2017;Medrzycki et al., 2010;Bujok et al., 2002). Also, an individual body temperature is crucial in restricting fungal infections. ...
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Insect pollination sustains the biodiversity of 90% of wild plants, and 75% of crop species for food and nutritional security. Chemical pesticides used to manage arthropod pests constitute a key driver to the unprecedented declines of insect pollinators worldwide. Hence, biopesticides based on entomopathogenic fungi (EPF) are being promoted as safer alternatives. The effects of EPF on insect pollinators have not been investigated in detail for the application in pollinator-resourced crop systems. Thus, this study screened EPF isolates of Metarhizium anisopliae (ICIPE 7, ICIPE 20, ICIPE 62, ICIPE 69 and ICIPE 78), and Beauveria bassiana (ICIPE 284) for their effect on the Western honey bee (Apis mellifera) and African stingless bee (Meliponula ferruginea). The study was undertaken at the international centre of Insect Physiology and Ecology (icipe), Nairobi, Kenya, from November 2019 through February 2021. In the first part of the study, groups of 25–30 bees/cage were exposed to surfaces sprayed separately with six isolates (108 conidial/mL) or sterile water (control) and incubated for 10 days. The exposure assay was replicated four times and repeated twice for each bee species, and conidial acquisition was evaluated on five bees/cage. Apis mellifera acquired more conidia (2.8 × 104–1.3 × 105 colony-forming units [CFU]/bee) than M. ferruginea (1.1 × 104–2.3 × 104 CFU/bee) based on the analysis of variance. Except for ICIPE 7, ICIPE 20 and ICIPE 69 which caused significant A. mellifera mortality (25.8–40.4%) in the first experiment, none of the isolates had a significant effect on either of the bee species according to survival analysis. The isolates are harmless and/or slightly harmful to bees according to the International Organization of Biological Control classification. Bee colonies inherently thermoregulate their hives and, thus, the second part of the study evaluated the performance of six isolates in bee colonies using eight predictive models describing thermal requirements; (minimum [Tmin], optimal [Topt] and maximum [Tmax] thresholds; and maximal performance [Pmax]). The isolates were incubated at 12, 16, 20, 24, 28, 32 and 36°C, and conidial germination and mycelial growth were measured and fitted to the models. Models were compared numerically (the Akaike information criterion [AIC], adjusted R2) and statistically (likelihood ratio test). The best models were the cardinal temperature model with inflection (CTMI) and Ratkowsky 3 for germination; and CTMI, Ratkowsky 2 and Lactin 1 for growth. Temperature nonlinearly affected the isolates’ performance and the isolates had different thermal requirements. Germination had Tmin, Topt, Tmax and Pmax of 13.2–14.2°C, 26.2–28.9°C, 35.7–36.3°C and 95.4–100.0%; while growth had 7.0–13.2°C, 25.9–28.4°C, 34.5–37.9°C and 1.36–2.28 mm/day, respectively. The low Topt indicate that the isolates are unlikely to operate in bee colonies. Best-fitting models can be routinely used in the selection and re-evaluation of EPF candidates. The third part of the study involved the application of M. anisopliae ICIPE 69 in two greenhouses. Greenhouses were partitioned into plots and planted with cucumber (Cucumis sativus) following good agricultural practices. Each plot was installed with a colony of M. ferruginea at blooming inception and the crops were sprayed with either ICIPE 69 or sterile water (control). The trials were repeated three times in a completely randomized block design. Colony survival, pollination behaviour, fruit set and yield, and persistence on crops were recorded within 9 days before until 18 days after treatment application. Collected data were analysed using generalized linear models. ICIPE 69 isolate did not result in a significant effect on these parameters while conidial acquisition by foragers and persistence on crops declined periodically. These tiered studies establish that EPF developed in Africa can be safely used in integrated pest and pollinator management (IPPM) programmes.
... where the first part is the quadratic function for temperature and the second part is the product of impact from different food resource. It is worth noting that development rate is zero when the temperature term is negative, but this will result in mortality (Medrzycki et al 2010). ...
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The ApisRAM model is an agent-based colony model for honey bees in which each bee is modelled as an individual agent. The behaviour of the colony emerges from the decisions and actions taken by individuals in the colony and the interactions between agents. The bees interact with, and react to, both other bees and the resources in the colony, the hive physical and chemical properties, and the environment outside the colony. A key feature of ApisRAM is the approach to representing bee health. This is a ‘vitality’ model which is used to integrate multiple stressors (unfavourable temperature, food shortage, infectious agents and pesticides) for each individual bee. The vitality of each model bee interacts with all the four stressors. The environment in which the colony is modelled is implemented as a dynamic landscape simulation within ALMaSS (the Animal Landscape and Man Simulation System). The ALMaSS landscape model is a spatially and temporally dynamic model which combines land use, detailed farm practices, weather, crop growth, semi-natural habitats, and flower resource models. With the combination of the colony and landscape models, the ApisRAM model provides a framework for in silico experiments, e.g., pesticides applications, designed to explore the effects of combined stressors on honey bee colonies under a variety of environmental and human (e.g. beekeeping management practices) factors.
... Honeybee declines have been observed in different regions of the world (Neumann and Carreck, 2010;Potts et al., 2010;vanEngelsdorp et al., 2012a,b;van der Zee et al., 2012;Greenpeace, 2013;Cepero et al., 2014) and are usually related to several factors rather than to a single one (AFSSA, 2009;ANSES, in press;Goulson et al., 2015). The main causes that are most often listed are parasites such as Varroa mites (Carreck et al., 2010b;Dahle, 2010;Martin et al., 2010) viruses (Berthoud et al., 2010;Carreck et al., 2010a, b;Martin et al., 2010), Nosema (Paxton, 2010;Santrac et al., 2010;Hatjina et al., 2011) nutrition (Broadschneider and Crailsheim, 2010) and pesticides (Chauzat et al., 2010a, b;Medrzycki et al., 2010;Chauzat et al., 2011;Belzunces et al., 2012;Hatjina et al., 2013;Rondeau et al., 2014) and acaricides (Harz et al., 2010). ...
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The Panel has interpreted the Terms of Reference by carrying out a stepwise evaluation of the BEEHAVE simulation model with a view to assessing its suitability for use in a regulatory context and for risk assessment of multiple stressors at the landscape level. The EFSA opinion on good modelling practice was used to evaluate the model and its documentation systematically. The overall conclusion is that BEEHAVE performs well in modelling honeybee colony dynamics, and the supporting documentation is generally good but does not fully meet the criteria of the good modelling opinion. BEEHAVE is not yet usable in a regulatory context primarily because it needs a pesticide module. BEEHAVE has a Varroa/virus module, although this seems to underestimate the impact of Varroa/virus on colony survival, and additional stressors (chemical and biological) would need to be added to allow investigation of the effects of interactions of pesticides with multiple stressors. BEEHAVE currently uses a very simple representation of a landscape and this should be extended. There is only one environmental scenario in the present version of BEEHAVE (European central zone-weather scenarios for Germany and the UK) and extension to other European zones would be needed. The supporting data and default parameter values should be further evaluated and justified. The modelling environment used by BEEHAVE (NetLogo) has an excellent user interface but provides limited opportunities for extending the model. The Panel recommends that BEEHAVE should be adopted as the basis for modelling the impact on honeybee colonies of pesticides and other stressors, but that further development should use a standard, object-oriented language rather than NetLogo.
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Insecticide toxicity may strongly vary with temperature, and interspecific differences have been commonly reported for this relationship. A differential influence of temperature on insecticide toxicity between pests and their natural enemies may have important consequences on biological control in a global warming context. This study aimed to investigate cross effects between temperature and three insecticides - i.e., chlorantraniliprole, emamectin and spinosad - on the mortality of a major pest in orchards, Cydia pomonella L., and two of its natural enemies in southern France, the predatory earwig Forficula auricularia L. and the introduced parasitoid Mastrus ridens Horstmann. We observed a decreased efficiency of emamectin and spinosad with increasing temperature on mortality of codling moth, while no influence of temperature on chlorantraniliprole efficacy was observed. Increasing temperatures increased the toxicity of all insecticides against M. ridens and only for emamectin on F. auricularia . This study provides essential insight to make recommendations for using these insecticides in combination with two natural enemies to control the codling moth in a warming world. Our results suggest that the use of spinosad may become sub-optimal under higher temperatures. In contrast, chlorantraniliprole should remain suitable under warmer climatic conditions to control C. pomonella , conserve F. auricularia and facilitate the establishment of M. ridens . For conservation biological control relying on F. auricularia , alternating use of emamectin during early spring, when its toxicity is the lowest on this natural enemy, and chlorantraniliprole during summer could limit resistance risks in codling moth populations and reduce the insecticides' impact on the populations of natural enemies.
Honey bees are exposed to various pesticides through pollinating and in-hive Varroa mite control. The most basic method for evaluating pesticide toxicity is the indoor bioassay using worker bees, in which newly emerged adults are matured in incubators for conditioning before use. However, little information is available on the optimum maturation temperature from a toxicological point of view, even though it can affect honey bee responses to pesticides. In this paper, to evaluate the optimal maturation temperature for pesticide toxicity testing, several indices related to the development, gene transcription, and toxicological properties of honey bee adults following maturation at 25, 30, and 35 °C were compared with those of field bees. The body weight and developmental state of hypopharyngeal glands were highest in the bees matured at 30 °C, and the overall transcription profiles of detoxification-related genes in the field bees were closest to those of bees matured at 30 °C, whereas immaturity and features of thermal stress were observed in the 25 °C and 35 °C bee groups, respectively. In the bioassay results, the effects of maturation temperature on the toxic response of honey bees varied significantly depending on the type of pesticide. By considering all the biological and toxicological aspects examined, we confirmed that 30 °C is a recommended maturation temperature for adult honey bee toxicity test.
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Under certain circumstances, the effects of imidacloprid on honey bees may not be immediately perceived. The aim of this study was to investigate if imidacloprid, provided in sub-lethal doses, could influence honey bee behaviour in the laboratory. Imidacloprid (supplied as Confidor®) was offered to bees in 50 % sucrose solution at two different concentrations (100 ppb and 500 ppb of active ingredient). Each dose was administered both as single dose and ad libitum, to three sets of 10 honey bee fora- gers. Bees fed with 50% sucrose solution were used as a control. Feeding occurred in holding cages in an incubator in complete darkness. After administration, in each treatment, the behaviour of the bees was recorded with an IR camera, and then analysed with "The Observer" computer program. In each treatment bees were significantly less active (in terms of mobility) than bees in the untreated control. Furthermore, in the treated bees, the communicative capacity seemed to be impaired, and this could cause a decline in the social behaviour. Never- theless, the negative effects appeared only after a certain period of time following administration (30-60 minutes) and vanished after several hours. Imidacloprid therefore has an inhibiting, even though transitory, effect on honey bees. We assume that the period of time in which honey bee behaviour is altered could negatively affect both the individual and the entire colony.
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An in vitro method for rearing bee larvae has been improved by studying three parameters of feeding: 1-the mode of feeding, 2-the amount of diet per larva, 3-the diet composition according to the age of larvae. The use of a uniform model of providing diet instead of adjusting the quantity according to the size of the larvae increased the homogeneity of larval weights. The total quantity of diet influenced the weight and the emergence rate. This last variable was also improved by increasing dry matter rate of the diet from the first to the last larval instar. This standardised method may be recommended to conduct various kinds of studies on brood, in particular regulatory trials for assessing pesticide toxicity to larvae.
The contact and oral acute toxicity of technical dimethoate to worker honey bees (Apis mellifera) was determined between May and October for 12 consecutive years, 1981–1992 (63 contact tests and 62 oral tests), using standard laboratory methods. The 24-h LD50 values ranged from 0.11 to 0.26 (mean 0.16) μg a.i./bee for contact toxicity, and from 0.11 to 0.33 (mean 0.18) μg a.i./bee for oral toxicity. The 48-h LD50 values were similar to the 24-h ones, indicating that there were no delayed toxic effects. There were no significant seasonal trends in contact or oral toxicity nor were there any consistent trends over the 12-year period. A comparison of British bees with a strain of New Zealand bees indicated that variability between individual colonies was greater than between the two strains. Published results from studies carried out elsewhere in the UK and in Germany are similar (LD50 values within a factor of about two of the mean values presented here). It is concluded that technical dimethoate is suitable as a reference compound for laboratory toxicity tests with honey bees.
Ergosterol biosynthesis-inhibiting fungicides have been found to synergize the toxicity of pyrethroid insecticides to the honeybee (Apis mellifera L.). The mechanism by which the fungicide prochloraz enhances the toxicity of the pyrethroid insecticide λ-cyhalothrin was investigated. In vitro incubations with honeybee midguts were used to study the metabolism of [14C]λ-cyhalothrin. The principal metabolite was identified as 4-hydroxy-3-phenoxybenzyl alcohol (4′-OH-3-PBAlc) with small amounts of 3-phenoxybenzoic acid (3-PBAc). Both are products of ester bond cleavage, but microsomal oxidation was implicated in the formation of 4′-OH-3-PBAlc. After treating midguts with prochloraz, metabolism was predominantly to 3-PBAc, with little formation of 4′-OH-3-PBAlc, strongly indicating an inhibition of microsomal monooxygenase activity. In vivo investigations showed the major metabolic products of [14C]λ-cyhalothrin extracted from frass of treated honeybees were 4′-OH-3-PBAlc, 2′-hydroxy-3-phenoxybenzyl alcohol, and 4′-hydroxy-3-phenoxybenzoic acid. However, when bees were simultaneously dosed with prochloraz, there was an absence of metabolites detected in the frass of bees for 16 hr post-treatment Thus, prochloraz delayed the metabolism, detoxication, and excretion of λ-cyhalothrin by inhibition of microsomal oxidation, effectively enhancing the toxicity of the pyrethroid to the honeybee.
The synergistic effect of a range of ergosterol-biosynthesis-inhibiting (EBI) fungicides and a pyrethroid insecticide was studied in the honeybee (Apis mellifera L.). Various EBI fungicides were combined separately with the pyrethroid lambda-cyhalothrin at ratios derived from their recommended application rates to represent tank-mixing in the field. The mixture was then applied topically to the thorax of honeybees, and mortality assessed 24 h post-treatment. All the fungicides tested increased the toxicity of lambda-cyhalothrin to honeybees. The fungicide propiconazole was found to have the strongest synergistic effect, decreasing the LD50 of lambda-cyalothrin from 68.0 ng bee−1 to 4.2 ng, thus having a synergistic ratio of 16.2. Hazard ratios were calculated for lambda-cyhalothrin and fungicide mixtures using a recommended application rate of 7.5 g a.i. ha−1. The hazard ratio for lambda-cyhalothrin alone was 110, but when mixed with fungicide synergists, the hazard ratio ranged from 366 with flutriafol to 1786 with propiconazole. A blank formulation of a fungicide (without the active ingredient prochloraz) had little effect on the toxicity of lambda-cyhalothrin, indicating that it is primarily the fungicide active ingredient that is responsible for the synergistic effect. The results are discussed in terms of the potential hazard posed by pesticide synergism to honeybees in the field.
Honeybee colony collapse is a sanitary and ecological worldwide problem. The features of this syndrome are an unexplained disappearance of adult bees, a lack of brood attention, reduced colony strength, and heavy winter mortality without any previous evident pathological disturbances. To date there has not been a consensus about its origins. This report describes the clinical features of two professional bee-keepers affecting by this syndrome. Anamnesis, clinical examination and analyses support that the depopulation in both cases was due to the infection by Nosema ceranae (Microsporidia), an emerging pathogen of Apis mellifera. No other significant pathogens or pesticides (neonicotinoids) were detected and the bees had not been foraging in corn or sunflower crops. The treatment with fumagillin avoided the loss of surviving weak colonies. This is the first case report of honeybee colony collapse due to N. ceranae in professional apiaries in field conditions reported worldwide.
We have studied the synergistic action of deltamethrin and prochloraz in bees in laboratory experiments that allowed us to express dosages in terms of field rates (g ha−1). It was established that, used alone, deltamethrin at 0·125 g ha−1 and prochloraz at 25 g ha−1 did not produce mortalities different from that of the control during 96 h of observation. Sprayed as a mixture of these doses, deltamethrin and prochloraz produced 67·5% corrected mortality within 24 h and 74·1% corrected mortality within 50 h. Sequential treatments of deltamethrin and prochloraz spaced by a 0·8-day interval reduced the synergistic action of both molecules. At 50 h, the lethal effects were 27·5% corrected mortality for the treatment of deltamethrin followed by prochloraz and 23·8% corrected mortality for the treatment of prochloraz followed by deltamethrin. Results are discussed in terms of mode of action and sub-lethal effects.
The synergistic action of prochloraz and deltamethrin was investigated in summerand winter bees. Prochloraz and deltamethrin were used at sublethal doses that did not induce any significant mortality. Bees were treated with different doses of deltamethrin, either alone or in combination with prochloraz, at the constant field rate of 25 g/ha. In summer bees, the combination of prochloraz and deltamethrin at 125 mg/ha triggered a synergy that produced approx. 63 ± 5% mortality (corrected) after 24 h. At 62.5 mg/ha, deltamethrin still acted in synergy with prochloraz by inducing about 32.5 ± 3.5% mortality (corrected) after 24 h. The field rate of 31.25 mg/ha was the lowest dose at which deltamethrin acted in synergy with prochloraz in summer bees. In winter bees, no synergy occurred between prochloraz and deltamethrin at doses of 125 and 250 mg/ha. The deltamethrin dose had to be increased to 500 mg/ha to observe a synergy that produced only 47 ± 11.7% mortality (corrected) after 24 h. Considering the deltamethrin doses at which synergy occurred, summer bees appeared to be approximately eightfold more susceptible than winter bees to the synergistic action of prochloraz and deltamethrin.
Foraging activity of bees is currently disturbed by treatments with pyrethroid agrochemicals. To discover eventual troubles of spatial orientation of the foragers, we exposed bees to sublethal doses of deltamethrin sufficiently low to avoid motor incoordination or muscular troubles. In an insect-proof tunnel, bees were trained to forage at a feeder 8 m from their nucleus. When temperature and global radiance conditions were optimal, some foragers were caught, exposed to a deltamethrin dose 27 times lower than its LD50, and released after 20 min of recovering. Among the contaminated bees, 54% took flight toward the sun and 81% did not come back to their nest within 30 s (which is 3 times longer than the mean time of control bees). Because pyrethroids are known to disturb learning and memory, we cannot conclude if this disorientation is due either to a trouble of information storage (wrong spatial perception or phototropism increase), or to a trouble of information retrieval (bad comparison of actual and memorized patterns). Routine chemical analysis of exposed bees does not detect residues of deltamethrin 3 h after bee sublethal exposure, although bees evidenced alteration in the flight.