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Swarming Behavior of Honey Bees (Hymenoptera: Apidae) in Southeastern Louisiana
Abstract
Reproductive swarming phenology, swarm sizes, and cavity selection were studied in a European-derived population of Apis mellifera L. in southeastern Louisiana before and immediately after the initial detection in 1992 of Varroa destructor Anderson & Trueman (Acari: Varroidae). Frequency of swarms was highest between early April and early May in each of 6 yr. Swarm weight averaged 1.42 kg (range 0.17–4.30 kg) and did not change significantly the year after detection of V. destructor. Swarms spent an average of ≈20 daylight hours scouting for a new nest-site from a temporary location and moved more frequently to cavities of 30-liter than to those of 13-liter volume. Swarms were random in direction of movement. Dance tempos at the time of swarm departure indicated movement to cavities at distances from 200 m to ≈10 km. The genetic composition of this honey bee population is likely to change after natural and artificial selection for resistance to new parasites, such as V. destructor and Aethina tumida Murray (Coleoptera: Nitidulidae), and as Africanized bees expand their range. Swarming characteristics are also likely to change both from direct effects of parasites on colony reproduction, and by changes toward bee populations with differing life histories.
... In relation to the weight change during swarming, colonies can suddenly lose several kg. In the example in Figure 1b, the weight dropped by 2.6 kg, which concurs with swarm weights identified by Villa [36]. Beekeepers apply different bee colony management techniques to reduce swarming events. ...
... These numbers are derived from the assumption of the average swarming period-the time between the event of a swarm leaving the hive to a close-by bush or tree, and to the event of the swarm departing to a new home [37]. In this study, we assume that after 3 h (sometimes swarms can stay longer [36,37]), a swarm is usually gone, so, taking the average travelling speed into account, in 3 h a beekeeper can go as far as 150 km one way. As the model operates with round-trip costs, we assume that the average travelling distance until the swarm flies away is as far as 300 km. ...
... The model suggests that even travelling more than 200 km to a remote apiary yields economic benefit for the beekeeper, which does not seem very practical. This model does not consider the success rate of catching a swarm, as the swarm could have found a new nest site by the time the beekeeper reaches the apiary [36,46]. Even if beekeepers arrive at the apiary a few minutes after the swarm leaves the hive, they may not find the swarm. ...
Precision beekeeping, or precision apiculture, focuses on individual beehive remote monitoring using different measurement systems and sensors. Sometimes, there are debates about the necessity for such systems and the real-life benefits of the substitution of bee colony manual inspection by automatic systems. Remote systems offer many advantages, but also have their disadvantages and costs. We evaluated the economic benefits of the remote detection of the bee colonies’ reproductive state of swarming. We propose two economic models for predicting differences in the benefits of catching a swarm depending on its travel distance. Models are tested by comparing the situation in four different countries (Austria, Ethiopia, Indonesia, and Latvia). The economic model is based on financial losses caused by bee colony swarming and considers the effort needed to catch the swarm following a remote swarm detection event. The economic benefit of catching a swarm after a remote precision beekeeping notification is shown to be a function of the distance/time to reach the apiary. The possible technical range is tempting, but we demonstrated that remote sensing is economically limited by the ability to physically reach the apiary and interact in time, or alternatively, inform a person living close by. An advanced economic model additionally includes the swarm catching probability, which decreases based on travel distance/time. Based on exemplary values from the four countries, the economic potential of detecting and informing beekeepers about swarming events is calculated.
... Each honeybee genotypes that genetically different have their own peculiar behavior traits. Within the endemic range of the honeybee, the variation between the behavioral traits, such as swarming and defensive, provides the basis for subspecific classification 9,10 . ...
... The survival of local or native honeybee populations results from a number of traits commonly perceived as adaptive, many of which are related to reproductive swarming and defensive behavior 6,10,25 . This present study clearly showed that Yığılca genotype is more inclined to swarm and is more defensive than A.m. anatoliaca and A.m. caucasica crosses. ...
... Similarly, Yücel and Kösoğlu 25 found that Muğla ecotype showed better performance for adaptation to environmental conditions and had more defensive behavior than Italian cross. The variation in swarming tendency and defensive behavior can be used for classification of honeybee population 9,10 . Morphometric and genetic studies also suggested that endemic honeybee in Yığılca provience of Düzce distinct from the other population and the conservation of this genotype in its native range may be worthwhile [18][19][20] . ...
In this study, swarming tendency and defensive behavior of Yi{dotless}ǧi{dotless}lca local honeybee were determined and compared with other commonly used honeybee genotypes in Turkey. Colonies were headed by naturally mated queens and 10 colonies of Yi{dotless}ǧi{dotless}lca local honeybee, 12 colonies of of Apis mellifera caucasica cross and 12 colonies of of Apis mellifera anatoliaca cross were used in the experiment. In swarming season, Yi{dotless}ǧi{dotless}lca honeybee colonies constructed more queen cells (49.86±18.00) than both A.m. anatoliaca cross (13.00±7.00) and A.m. caucasica (8.00±1.15) cross colonies. Similarly, according to results of sting test, the highest number of stings was determined in Yi{dotless}ǧi{dotless}lca honeybee colonies (18.38±4.24), followed by A.m. anatoliaca (5.50±2.15) and A.m. caucasica (3.75±0.62) crosses. Results showed that Yi{dotless}ǧi{dotless}lca local honeybee genotype has a more swarming tendency and is more defensive than A.m. anatoliaca and A.m. caucasica crosses.
... Honey bee colony nest space, volume and size of the colony are reported as important aspects in determining the comb construction and subsequent survival and colony performance (Hepburn et al., 2014) [6] . One of the criteria by which honey bee naturally select their nest sites is mainly based on nest cavity volume that is size of the bee hive (Villa, 2004) [16] . Honey bee colonies energy requirements, nest defense, labor and homeostasis conditions are known as the most important factors in determining the upper limit of their nest size indicating that nest size is an essential element in colony performance and survival (Prange and Nelson, 2007) [11] . ...
... Honey bee colony nest space, volume and size of the colony are reported as important aspects in determining the comb construction and subsequent survival and colony performance (Hepburn et al., 2014) [6] . One of the criteria by which honey bee naturally select their nest sites is mainly based on nest cavity volume that is size of the bee hive (Villa, 2004) [16] . Honey bee colonies energy requirements, nest defense, labor and homeostasis conditions are known as the most important factors in determining the upper limit of their nest size indicating that nest size is an essential element in colony performance and survival (Prange and Nelson, 2007) [11] . ...
This investigation is aimed to evaluate the influence of hive volume on the brood area, honey production,pollen stores as well as bee strength during July 2020 to June 2021 in sub temperate region of HimachalPradesh, India. Five treatments viz., Modified BIS type A hive of 20 L, 5 frame hive of 25 L, 6 framehive of 30 L, 8 frame hive of 33 L and Langstroth hive of 42 L having four replications were used. Thecolony parameters with respect to brood production, honey and pollen stores were significantly affectedby bee strength in different hive volumes. The development of brood (4906.50 cm2), honey production(1740.00 g), pollen stores (1158.00 cm2) as well as bee strength (8.76 bee frames) was recordedmaximum for 8-frame (33-liter) as compared to Langstroth hive (10-frame, 42-liter). The supering isrequired in 8 frame hive in the month of May 2021, whereas supering was not required in 10-frame hive(Langstroth) due to low bee strength (8.31 bee frames in June). Based on performance of colonies inhives with different volumes it can be concluded that 8 frame hive of 33 L was optimum for keeping theexisting honey bee species A. mellifera ligustica colonies. It can additionally make a contribution toenhance the honey production in Himachal Pradesh, India (PDF) Impact of hive volume on colony performance in Apis mellifera ligustica colonies in sub temperate zone India. Available from: https://www.researchgate.net/publication/364283887_Impact_of_hive_volume_on_colony_performance_in_Apis_mellifera_ligustica_colonies_in_sub_temperate_zone_India [accessed Jun 22 2023].
... Therefore, an apparent option for SHB reproduction is associated with afterabsconding events (Hepburn et al. 1999), when colony defence is obviously absent. Both African and European honeybee colonies respond to heavy SHB infestations by absconding (Hepburn and Radloff 1998;Ellis et al. 2003a;Villa 2004;Neumann et al. 2016). Since African honeybee subspecies are more efficient in preparations for absconding (Spiewok et al. 2006) compared to European ones (Hepburn and Radloff 1998;Hepburn 2006), abandoned nests of the former may leave fewer resources behind for SHB reproduction. ...
... In sharp contrast, European honeybee subspecies are very reluctant to abscond (Butler 1967;Winston 1987) and so-called hunger swarms are very rare (Zander and Weiss 1964). The exact causes for the absconding events in this study remain unclear, but SHBs are known to induce such events in African (Fletcher 1975(Fletcher , 1976Hepburn and Radloff 1998) and even in European honeybee colonies (Ellis et al. 2003b;Villa 2004;Neumann et al. 2016). In any case, absconding European colonies left significantly more stores and brood behind than African ones. ...
Small hive beetle (SHB) is an invasive species in populations of European honeybee subspecies, but underlying reasons for SHB success are not well understood. African and European honeybee, Apis mellifera, subspecies differ in absconding, and small hive beetle, greater wax moth (GWM) and ants all can exploit abandoned nests. However, the impact of host absconding on SHB reproduction and the role of GWM and ants as competitors are not known. Here, we conducted a survey in South Africa, Australia and the USA to evaluate SHB and GWM reproduction and foraging by ants in abandoned honeybee colonies. While the impact of competing ants and GWM was not significant, the data show higher SHB reproduction in abandoned nests of European honeybees compared to African ones, but less for GWM. The positive correlation between abandoned protein sources (brood, pollen) on SHB reproduction suggests that the less efficient preparation for absconding by European honeybee subspecies combined with their large colony sizes is a key factor for the invasion success of SHB.
... Honey bee colony nest space, volume and colony size are reported as important factors in determining wax production, comb construction and subsequent colony performance and survival (Szabo, 1977;Wright, 2003;Hepburn et al., 2014). Moreover, one of the criteria by which honey bee naturally select their nest sites is mainly based on nest cavity volume (Seeley and Morse, 1976;Schmidt and Hureley, 1995;Villa, 2004). Under natural conditions within A. mellifera; nest volumes vary greatly from race to race and ecology to ecology (Prange and Nelson, 2007;Phiancharoen et al., 2011). ...
... In this regard Villa (2004) reported a preference for smaller cavities by honey bee in Louisiana, USA. Moreover, unlike A. mellifera races of the temperate zone, Morse et al. (1993) observed 10.2 -13.2 l nest boxes naturally occupied by some A. mellifera colonies for over five years. ...
Apis mellefera jemenitica is the smallest race of A. mellifera both in its body and colony sizes. In the current study we assessed the natural nest volume, workers brood cell dimensions and bee space of the race through measuring their dimensions from naturally built combs in log hives. The optimum box hive volume and surface area requirement were assessed by keeping colonies at different volumes of frame hives with four replications each and monitored for a period of one year. The average occupied nest volume and comb surface area of the race in log hives were 12.28 ± 5.98 l and 8017.2 ± 3110.60 cm 2 respectively which are significantly smaller than other A. mellifera races. The worker brood cells width and depth of the race were 4.07 ± 0.17 mm and 9.39 ± 0.42 mm respectively and the race builds an average of 262.5 more worker brood cells/dm 2 than is built on embossed foundation sheets. The race maintains an average of 7.27 ± 1.35 mm bee space and naturally builds 30% more combs per unit length than other races. Based on the performances of colonies, box hives with seven standard frames were found to be the optimum for the race in the region. The study indicates the importance of designing box hives and accessories that match with the natural nest volumes, their body and colony sizes which may contribute to enhance the productivity of the race.
... The outcome of this process is an increase in the number of bees visiting and dancing for sites of good quality, and a decrease in the number dancing for sites of poor quality (Seeley 2003). Eventually, one site comes to dominate in visitation and dancing, a process that may take several days in A. mellifera (Villa 2004). When one site under consideration is being visited by a sufficient number of bees, the bees at the new nest site sense that a quorum has been reached (Seeley and Visscher 2004b). ...
... Visscher and Camazine (1999) reached this conclusion after they found no effect of removing 'unfaithful' bees from the swarm. However, the decision-making process of A. mellifera swarms takes much longer than in A. dorsata (about 13 (Visscher and Camazine 1999) to 20 h (Villa 2004) in A. mellifera versus approximately 3 h in A. dorsata Makinson et al. 2014). It could well be that a change in dance direction by scouts plays a role in the rapid decision-making process of A. dorsata. ...
The last few years have seen a renewed interest in the mechanisms behind nest-site selection in honeybees. Most studies have focused on the cavity-nesting honeybee Apis mellifera, but more recently studies have included the open-nesting A. florea. Amongst species comparisons are important if we want to understand how the process has been adapted over evolutionary time to suit the particular species’ nest-site requirement. Here, we describe the behaviour of scout bees of the giant Asian honeybee A. dorsata on three artificially created swarms to determine the mechanisms used to collectively decide on a location to move to, either in the same environment (nest-site selection) or somewhere further afield (migration). In all swarms, scouts’ dances converged on a general direction prior to lift-off and this direction corresponded to the direction that swarms flew. Scouts from one swarm danced for sites that were far away. These dances did not converge onto a specific distance, implying they were migration dances. Dances for different sites differed in the number of circuits per dance suggesting that A. dorsata scouts make an assessment of site quality. Similarly to A. florea, but in contrast to A. mellifera, A. dorsata scouts did not reduce dance duration after repeated returns from scouting flights. We found that many scouts that dance for a non-preferred location changed dance location during the decision-making process after following dances for the consensus direction. We conclude that the consensus-building process of A. dorsata swarms relies on the interaction of scout bees on the swarm. © 2016 International Union for the Study of Social Insects (IUSSI)
... It appears as if the host becomes alerted by newly intruded beetles Removal of eggs SHB eggs are eaten by workers (Neumann and Härtel 2004), both protected underneath cell cappings (Ellis et al. 2003a, e) or in gaps and unprotected ones Removal of larvae Workers can carry larvae out of the hive at some distance (Neumann and Härtel 2004). Appears to be efficient in strong colonies Absconding When heavily infested with SHBs, both African and European honeybee colonies abscond (Hepburn and Radloff 1998;Villa 2004) Given that adult SHBs were able to bypass patrolling workers and intrude the comb area, they may oviposit on the combs ( Figure 3 and Table II). Honeybee workers can then remove eggs or hatched larvae (Table III), but SHBs may oviposit in gaps thereby protecting their offspring (Neumann and Härtel 2004). ...
... Such a damage threshold appears to be different between African and European colonies. Absconding is also induced in SHB-infested European honeybee colonies (Ellis et al. 2003a;Villa 2004). Because African subspecies are more prone to absconding than European subspecies (Hepburn and Radloff 1998), this may be yet another reason for better SHB resistance/less pest severity in African bees as they are more efficient in preparation for absconding . ...
Small hive beetles (SHBs) are generalists native to sub-Saharan Africa and reproduce in association with honeybees, bumblebees, stingless bees, fruits and meat. The SHB has recently become an invasive species and introductions have been recorded from America, Australia, Europe and Asia since 1996. While SHBs are usually considered a minor pest in Africa, they can cause significant damage to social bee colonies in their new ranges. Potential reasons for differential impact include differences in bee behaviour, climate and release from natural enemies. Here, we provide an overview on biology, distribution, pest status, diagnosis, control and prevention to foster adequate mitigation and stimulate future research. SHBs have become a global threat to both apiculture and wild bee populations, but our knowledge of this pest is still limited, creating demand for more research in all areas of its biology.
... In a choice study in Louisiana, however, swarms accepted cavities with volumes ranging from 10 to 40 liters, with no apparent preference between these extremes (Rinderer et al. 1982). Villa (2004) also documented use of both 13-and 31-liter cavities in Louisiana. Although 31-liter cavities were chosen more frequently, Villa (2004) reported that preference for larger cavities was less pronounced than that observed in New York (Seeley 1977), Illinois (Jaycox and Parise 1980,1981), and Arizona (Schmidt and Hurley 1995). ...
... Swarm size could in turn be proportional to the volume of the swarm's future home, but there is little evidence in support of this relationship. No correlation between swarm size and choice of cavity volume was observed in Arizona (Schmidt and Hurley 1995), Louisiana (Villa 2004), or New York (Seeley 1977), although Seeley (1977) cautioned that this relationship might not hold for very small swarms, as swarms with < 1000 bees rejected nest boxes that larger swarms accepted (Lindauer 1961). In Louisiana, Rinderer et al. (1982) found a significant correlation between swarm weight and volume of accepted cavities, but after omission of the largest swarm no correlation remained. ...
Previous studies have documented that cavities < 10 liters are consistently rejected as nest sites by Apis mellifera (European honey bees). During a study of Glaucomys volans (southern flying squirrel) ecology in Alabama, however, honey bees occupied a total of 10 nest boxes with volumes of 5–6.7 liters. These observations are significant because they represent the smallest documented cavity volume accepted by honey bees, and also because they lend support to the theory that minimum acceptable cavity volume varies geographically. Small volume cavities may be accepted in the southeastern United States due to milder climates, a paucity of natural cavities, genetic differences in honey bees among regions, or some combination of these factors. Consequently, there may be increased potential for competition between honey bees and other cavity-nesting species in the Southeast.
... The nest size, volume and space for a honey bee colony play a significant role in determining the comb construction and subsequent survival and colony productivity (Hepburn et al., 2014). Honey bees use nest cavity volume, or the size of the bee hive i.e., bee population as one of the factors in choosing where to build their nests naturally (Villa, 2004). Honey bees raise agricultural yields by pollinating them, which ultimately boosts farm revenues (Goyal et al., 1989). ...
Correlation of bee activity with bee strength in Apis mellifera colonies
... Scout bees will then search for a new permanent location, reporting back to the swarm and recruiting other workers to evaluate the site until a suitable location is determined via a consensus. Honey bee swarms can fly several kilometers from their parent colony to establish, although, on average fly 300-600 meters from the parent colony (Lindauer, 1955;Seeley & Buhrman, 1999;Villa, 2004). The swarm then migrates and colonizes the new location (Seeley et al., 2006;Seeley & Visscher, 2003. ...
... The new splinter colony will then typically fly away to start a new hive [4]. Swarming typically occurs during the spring months in the Northern Hemisphere [5]. The process can take from a few hours to a few days [6] during which the swarming bees and their queen are vulnerable to both predators and the elements. ...
... Reproductive swarms are produced from parent colonies through fission and consist of a single, mated queen with a portion of the previous colony's worker force [17,18]. These reproductive swarms establish a new nest away from the parent colony, at distances from as little as a few hundred meters [18] to up to 10 km [19]. The first queen that leaves in a reproductive swarm is the queen of the original colony, while the last virgin queen to emerge may either stay to inherit the old nest, or swarm herself so that the old nest is abandoned. ...
The modes through which individuals disperse prior to reproduction has important consequences for gene flow in populations. In honey bees (Apis sp.), drones (males) reproduce within a short flight range of their natal nest, leaving and returning each afternoon within a narrow mating window. Drones are assumed to return to their natal nests as they depend on workers to feed them. However, in apiaries, drones are reported to regularly make navigation errors and return to a non-natal nest, where they are accepted and fed by unrelated workers. If such a “drone drift” occurred in wild populations, it could facilitate some further degree of dispersal for males, particularly if drones drift into host nests some distance away from their natal nest. Here, we investigated whether drone drift occurs in an invasive population of the Asian honey bee (Apis cerana). Based on the genotypes of 1462 drones from 19 colonies, we found only a single drone that could be considered a candidate drifter (~0.07%). In three other colonies, drones whose genotypes differed from the inferred queen were best explained by recent queen turnover or worker-laying. We concluded that drone drift in this population is low at best, and A. cerana drones either rarely make navigation errors in wild populations or are not accepted into foreign nests when they do so. We therefore confirm that drone dispersal distance is limited to the distance of daily drone flights from natal nests, a key assumption of both colony density estimates based on sampling of drone congregation areas and population genetic models of gene flow in honey bees.
... Por otra parte, el proceso de enjambrazón natural provoca un sistemático e incontrolable desplazamiento de colonias hacia y desde cualquier rumbo (Villa 2004). A pesar de que morfológicamente las abejas de origen europeo y las africanizadas son muy parecidas, su comportamiento es bastante diferente. ...
... Through a remarkable decision-making procedure (Seeley, 2010), the colony chooses its new nest site and settles there permanently. This new nest site may be up to 10 km from their original hive (Villa, 2004). Although swarming is a natural process, it is not welcomed by beekeepers since it represents a potential economic loss, in the form of a decrease in the honey bee population and the expected honey harvest. ...
Swarm control is of major importance to beekeepers worldwide. Many techniques and manipulations have been applied to try to decrease the swarming tendencies of colonies, attract swarms, and catch swarms as they leave their hives. The attractiveness of three differ- ent lures, based on a blend of attractive substances, is described and assessed: a paraffin gel and spray applications in two doses, are compared to evaluate their attractiveness to pri- mary and secondary swarms. A total of 76 of 81 swarms (93.82%) were attracted by the lures; the gel application being the most effective, attracting 69.13% of all the swarms.
... Suddenly #10 colony weight dropped by 2.6 kg: from 120.54 kg to 117.91 kg, and beekeeper on-site approved that the colony swarmed. This weight change during the swarming agrees with swarm weight identified by (Villa, 2004). Effect of the rain on the foraging activity During the foraging period weather conditions were excellent, without much precipitation. ...
Beekeeping in Latvia has a long tradition and it is a classical branch of agriculture. In Latvia, there is no traditional beekeeping region, and beekeeping is performed in all regions. Honey yield is influenced by various factors-variety of crops (nectar plants) around the apiary, man-made changes in land/forests (deforestation), climate change, beekeepers' actions, etc. Application of information and communication technologies (ICT) in the field of beekeeping can bring benefits to the beekeepers. To be more specific, continuous remote monitoring of certain bee colony parameters can improve beekeeper's apiary management, by informing timely about the nectar flow (or even provide information on bee colony states, e.g., swarming). In such a way, beekeepers can plan their next actions-prepare supers or even choose to move the apiary to a different geographical location. Within this research, weight gain of the ten honey bee colonies was remotely monitored and analysed during two-week period at the beginning of the summer 2021 in Vecauce, Latvia, using the precision beekeeping approach. This monitoring period corresponded to intensive flowering of the winter rapeseed and field beans. Colonies were equipped with the automatic scales. In addition, colony and environmental temperature was monitored. Measurements were taken every thirty minutes. Analysing the obtained data, weight increase can be observed in all colonies, from 17 to 48 kg. As well, based on weight data, swarming event can be identified. Constant monitoring of weight change can also help to identify daily patterns in honey bee activity.
... 2.3.3.1. Swarming: Swarming is the process by which a new honeybee colony is formed when the queen bee leaves the colony with a large group of worker bees (Avitabile et al. 1975 andVilla, (2004). Also, Waily et al. (2010) stated that queen presence in over-congestion colony with maintaining high number of the queen cells is indicator of preparing of swarming. ...
Two groups of honeybee colonies (Apis mellifera L.) were used, the first group located in the west of Minia Governorate where organic agriculture of chamomile (Matricaria chamomilla) cultivation was existed and the other group were placed in the south of Minia governorate where conventional agriculture of the same plant was found. The present work was aimed to study the effect of model of agriculture on the activity and productivity of honeybee colonies. The results showed that the numbers of the going out foragers (per minute) of the honeybee colonies located in either conventional or organic agriculture areas were very close to each other, but number of coming back foragers (per minute) of the colonies located in organic agriculture area surpassed those of the conventional agriculture area. With concerning the productivity of the honeybee colonies, the obtained data revealed that the honeybee colonies placed in organic agriculture of chamomile produced more stored honey and royal jelly, while less amount of stored pollen than those colonies of conventional agriculture of the same crop. On the other hand the results showed that the workers of the colonies located in organic agriculture area lived long time than those workers of the colonies located in the conventional agriculture area which clearly contributed in high population of those colonies. In addition, it was noticed that the honeybee colonies maintained in organic cultivation did not show any tendency towards swarming or absconding.
... Autonomous, locally interacting agents can collectively organize to accomplish a variety of complex tasks such as foraging for food, building large-scale structures, and transporting objects many times heavier than their weight, as is routinely observed in the living world, in swarms of ants, flocks of birds, and schools of fish [34,39,38,33]. A key component of these diverse self-organized behaviors is achieving consensus in large collectives of autonomous agents with only local interactions. ...
We present local distributed, stochastic algorithms for \emph{alignment} in self-organizing particle systems (SOPS) on two-dimensional lattices, where particles occupy unique sites on the lattice, and particles can make spatial moves to neighboring sites if they are unoccupied. Such models are abstractions of programmable matter, composed of individual computational particles with limited memory, strictly local communication abilities, and modest computational capabilities. We consider oriented particle systems, where particles are assigned a vector pointing in one of $q$ directions, and each particle can compute the angle between its direction and the direction of any neighboring particle, although without knowledge of global orientation with respect to a fixed underlying coordinate system. Particles move stochastically, with each particle able to either modify its direction or make a local spatial move along a lattice edge during a move. We consider two settings: (a) where particle configurations must remain simply connected at all times and (b) where spatial moves are unconstrained and configurations can disconnect. Taking inspiration from the Potts and clock models from statistical physics, we prove that for any $q \geq 2,$ these self-organizing particle systems can be made to collectively align along a single dominant direction (analogous to a solid or ordered state) or remain non-aligned, in which case the fraction of particles oriented along any direction is nearly equal (analogous to a gaseous or disordered state). Moreover, we show that with appropriate settings of the input parameters, we can achieve \emph{compression} and \emph{expansion}, controlling how tightly gathered the particles are, as well as \emph{alignment} or \emph{nonalignment}, producing a single dominant orientation or not.
... Furthermore, studies on volume choices for different swarm sizes (e.g. (Schmidt & Hurley, 1995;Seeley, 2017;Villa, 2004)) have revealed that there is no correlation between swarm size and volume acceptance by a colony, even for very small swarms when suitable cavities are available. We caution that colonisation of smaller volumes by honey bees should not be interpreted solely as a behaviour of this species, but other factors such as availability of suitable nesting sites should also be taken into account. ...
... Bees are social insects that live in hollow trees or small caves. They work in groups in colonies called hives [46]. There are three kinds of bees in a natural colony: queen bees, worker bees, and drones or scout bees. ...
In recent years, the one-dimensional bin packing problem (1D-BPP) has become one of the most famous combinatorial optimization problems. The 1D-BPP is a robust NP-hard problem that can be solved through optimization algorithms. This paper proposes an adaptive procedure using a recently optimized swarm algorithm and fitness-dependent optimizer (FDO), named the AFDO, to solve the BPP. The proposed algorithm is based on the generation of a feasible initial population through a modified wellknown first fit (FF) heuristic approach. To obtain a final optimized solution, the most critical parameters of the algorithm are adapted for the problem. To the best of our knowledge, this is the first study to apply the FDO algorithm in a discrete optimization problem, especially for solving the BPP. The adaptive algorithm was tested on 30 instances obtained from benchmark datasets. The performance and evaluation results of this algorithm were compared with those of other popular algorithms, such as the particle swarm optimization (PSO) algorithm, crow search algorithm (CSA), and Jaya algorithm. The AFDO algorithm obtained the smallest fitness values and outperformed the PSO, CS, and Jaya algorithms by 16%, 17%, and 11%, respectively. Moreover, the AFDO shows superiority in terms of execution time with improvements over the execution times of the PSO, CS, and Jaya algorithms by up to 46%, 54%, and 43%, respectively. The experimental results illustrate the effectiveness of the proposed adaptive algorithm for solving the 1DBPP.
... Distance from collector to the measuring device should be at least 30 m. Radio transmitter has to be insensitive for the nearby flora presence. The authors' interests is swarming phenoma [26] which is slow-changing processes so the frequency of data upload was set to one package per hour. Having such requirements in mind we extended our platform with energy-saving concepts which led to use of particular architecture. ...
... This observation was previously attributed to colony founding events. Bumble bees have an annual social lifecycle and colonies are founded by a single queen after hibernation (Goulson et al. 2008), while honey bees found colonies through swarming of a queen and many workers (Villa 2004). While these founding events may contribute to the maintenance of strain diversity within a colony, genotype-by-genotype interactions may also be involved. ...
There has been a proliferation of studies demonstrating an organism's health is influenced by its microbiota. However, factors influencing beneficial microbe colonization and the evolution of these relationships remain understudied relative to host‐pathogen interactions. Vertically transmitted beneficial microbes are predicted to show high levels of specificity in colonization, including genotype matching, which may transpire through coevolution. We investigate how host and bacterial genotypes influence colonization of a core coevolved microbiota member in bumble bees. The hindgut colonizing Snodgrassella alvi confers direct benefits, but, as an early colonizer, also facilitates the further development of a healthy microbiota. Due to predominantly vertical transmission promoting tight evolution between colonization factors of bacteria and host lineages, we predict that genotype‐by‐genotype interactions will determine successful colonization. Germ‐free adult bees from seven bumble bee colonies (host genotypic units) were inoculated with one of six genetically distinct strains of S. alvi. Subsequent colonization within host‐genotype and microbe‐genotype combinations ranged from zero to one hundred percent, and an interaction between host and microbe genotypes determined colonization success. This novel finding of a genotype‐by‐genotype interaction determining colonization in an animal host‐beneficial microbe system has implications for the ecological and evolutionary dynamics of host and microbe, including associated host‐fitness benefits. This article is protected by copyright. All rights reserved
... Finally, scout bees explore the environment and exploit the preferable targets, which is the most important feature of this work. Usually, when the number of bees in the hive increases and the inside colony conditions and outside weather conditions are suitable, then the queen lays eggs into the queen cells, and the bee colony starts the reproductive processes by swarming [25] [26]. [27] Swarming is mostly a late spring phenomenon; it is the process by which a new honeybee colony is formed. ...
In this paper, a novel swarm intelligent algorithm is proposed, known as the fitness dependent optimizer (FDO). The bee swarming reproductive process and their collective decision-making have inspired this algorithm; it has no algorithmic connection with the honey bee algorithm or the artificial bee colony algorithm. It is worth mentioning that FDO is considered a particle swarm optimization (PSO)-based algorithm that updates the search agent position by adding velocity (pace). However, FDO calculates velocity differently; it uses the problem fitness function value to produce weights, and these weights guide the search agents during both the exploration and exploitation phases. Throughout the paper, the FDO algorithm is presented, and the motivation behind the idea is explained. Moreover, FDO is tested on a group of 19 classical benchmark test functions, and the results are compared with three well-known algorithms: PSO, the genetic algorithm (GA), and the dragonfly algorithm (DA), additionally, FDO is tested on IEEE Congress of Evolutionary Computation Benchmark Test Functions (CEC-C06, 2019 Competition) [1]. The results are compared with three modern algorithms: (DA), the whale optimization algorithm (WOA), and the salp swarm algorithm (SSA). The FDO results show better performance in most cases and comparative results in other cases. Furthermore, the results are statistically tested with the Wilcoxon rank-sum test to show the significance of the results. Likewise, FDO stability in both the exploration and exploitation phases is verified and performance-proofed using different standard measurements. Finally, FDO is applied to real-world applications as evidence of its feasibility.
... Rather than recording each mission as a discrete event, the overall behavior is defined as a foraging role. Departed bees (DB): Bees that leave the hive and never return, either because they die or because they swarm (including absconding) [35], [36]. Swarming was not observed in our hives during the experiment. ...
This paper proposes a method to address misreadings and consequent inadequacy of Radio- Frequency Identification (RFID) data for social insect monitoring. Six months worth of field experiment data were collected to demonstrate the application of the method. The data is transformed into a linear combination of Gaussian model and curve-fitted using evolutionary algorithm. The results show that the proposed method allows us to improve the quality of data that infer honey bee behaviour at the colony level.
... The outcome of this process is an increase in the number of bees visiting and dancing for sites of high quality, and a decreasing number of bees dancing for sites of lesser quality [21]. Eventually, dances tend to converge to one site only, a process that may take several days in A. mellifera [22]. Once a site has attracted a sufficient number of bees, a quorum [23], bees that have sensed the quorum will now return to rstb.royalsocietypublishing.org Phil. ...
During reproductive swarming, a honeybee swarm needs to decide on a new nest site and then move to the chosen site collectively. Most studies of swarming and nest-site selection are based on one species, Apis mellifera . Natural colonies of A. mellifera live in tree cavities. The quality of the cavity is critical to the survival of a swarm. Other honeybee species nest in the open, and have less strict nest-site requirements, such as the open-nesting dwarf honeybee Apis florea . Apis florea builds a nest comprised of a single comb suspended from a twig. For a cavity-nesting species, there is only a limited number of potential nest sites that can be located by a swarm, because suitable sites are scarce. By contrast, for an open-nesting species, there is an abundance of equally suitable twigs. While the decision-making process of cavity-nesting bees is geared towards selecting the best site possible, open-nesting species need to coordinate collective movement towards areas with potential nest sites. Here, we argue that the nest-site selection processes of A. florea and A. mellifera have been shaped by each species' specific nest-site requirements. Both species use the same behavioural algorithm, tuned to allow each species to solve their species-specific problem.
This article is part of the theme issue ‘Collective movement ecology’.
... In addition, other behavioural patterns observed in African honey bees, such as prison building (Ellis et al., 2003b;Neumann et al., 2001) and being tricked into feeding the beetles (Ellis et al., 2002b) (Fig. 4) were not only observed in African honey bees but also in European colonies (Ellis et al., 2003b). The presence of SHB in colonies of European honey bees are said to trigger absconding behaviour (Ellis et al., 2003d); non -reproductive swarming (Fig. 7) as a reaction to unfavourable conditions at the nesting site (Allsopp & Hepburn, 1997;Hepburn, 1988;Villa, 2004). The absconding behaviour was actually similar between Cape honey bees (A. m. capensis) in South Africa, and European honey bees in the USA when they are artificially infested with SHB (Ellis et al., 2003e). ...
http://www.ibrabee.org.uk/component/k2/item/3633-the-small-hive-beetle-a-growing-problem-in-the-21st-century
... Because scouts visiting a high quality site start with more dance circuits and the reduction in the number of dance circuits declines linearly on average, sites of high quality are advertised for longer than sites of low quality (Seeley 2003). As a result the number of scouts visiting and dancing for sites of good quality increases while the number of scouts dancing for sites of poor quality decreases (Seeley 2003) so that one site comes to dominate in visitation and dancing, a process that may take several days (Villa 2004). The decision-making process comes to an end once a quorum has been reached at one of the sites under consideration (Seeley and Visscher 2004b). ...
Most studies on collective decision making in honeybees have been performed on the cavity-nesting Western honeybee, Apis mellifera. In more recent years, the open-nesting red dwarf honeybee Apis florea has been developed as a model organism of collective decision making in the context of nest-site selection. These studies have shown that the specifics of the species’ nest-site requirements affect collective decision making. In particular, when potential nesting sites are abundant, as is the case in A. florea, the process of collective decision making can be simplified. Here, we ask if A. florea simply follows the availability of floral resources in their environment when deciding on an area to move into. We determined the locations danced for by three colonies the day before, of and after reproductive swarming. Our results suggest that colonies of A. florea indeed track the availability of forage in their environment and that swarms move in the general direction of forage rather than towards a specific nest site.
... In addition to genetic and morphometric differences, the variation between the behavioral and physiological traits is also considered when identifying of honeybee population (Hunt et al., 1998;Villa, 2004). While some physiological characters correlate with the morphological characters (Guler, 1999), others such as brood cycle, are genetically determined (Louveaux, 1973;Strange et al., 2007). ...
Populations of locally adapted honeybee (Apis mellifera L.) have adaptive traits in their native habitat to take maximum advantage of the local flora. In this study, the annual brood production and colony population development of the Yiʇilca local honeybee colonies in their natural habitat were determined and compared with the other commonly used honeybee hybrids to expose adaptation to local ecological conditions. A total of 34 colonies headed by naturally mated queens were used in the experiment; 10 colonies of Yiʇilca local honey bee, 12 colonies of A. m. Caucasica hybrid and 12 colonies of A. m. Anatoliaca hybrid. The present results demonstrated that the Yiʇilca local honeybee colonies adapted to their local ecological conditions and regulated the brood production and population development according to regional flora. Although there were no differences in the worker populations between the genotype groups at the end of the winter, Yiʇilca honeybee colonies produce more broods before the main nectar flow and had a larger worker population during period of nectar flow than A.m. Anatoliaca and A.m. Caucasica hybrids. The results demonstrated that Yiʇilca local honey bee is a valuable genotype in their native habitat. However, experiments should be repeated at different locations for their use in breeding programs.
... In our situation, increased resistance to mite infestation may have been produced by natural selection on the resident population, or by introgression of other honey bees into the feral population. Natural selection seems likely given that large numbers of the swarms were captured much longer distances from known beekeeping than the average swarm movement distance of 3 km recorded for Louisiana (Villa 2004). Introgression from Africanized bees did not contribute to these changes given that the Þrst detections occurred in 2005. ...
The impact of Varroa destructor Anderson & Trueman (Mesostigmata: Varroidae) on colonies of Apis mellifera L. (Hymenoptera: Apidae) in southern Louisiana was evaluated by analyzing changes in swarming and longevity of colonies for 17 yr. Swarming rates were calculated from yearly captures of swarms in bait hives placed in five areas of Louisiana from 1991 to 2006. Colony longevity was monitored in 104 swarms established from 1990 to 2000 and followed until 2004. In the first years, before V. destructor, average swarm capture rates ranged from 0.85 to 0.95 swarms per bait hive-year, and survival of colonies established from swarms averaged 14 mo. In years immediately after the arrival of V. destructor (1993–1996), swarming rates and colony longevity decreased to 0.36–0.60 swarms per bait hive-year and 10 mo, respectively. After ≈5 yr in the presence of V. destructor, both rates recovered to levels at least as high as those seen before varroa arrived; swarm capture rates were 0.75–1.04 swarms per bait hive-year and average longevity was 26 mo. Analysis of varroa infestations in three colonies established from swarms in 1997 showed the presence of varroa at oscillating densities for 5 to 8 yr. Possible causes for this apparent recovery are natural selection for resistance in honey bees, introgression of selected resistant genetic material or reduced virulence of the mites.
... competition' among the scouts affiliated with the different sites, at the end of which one site comes to dominate in visits and dancing (Lindauer 1955; Seeley & Visscher 2004). Once this agreement is reached, the swarm takes flight again and moves to the chosen site, often several kilometres away (Seeley & Morse 1977; Villa 2004). An intriguing feature of the flight of a honeybee swarm is that only about 5% of a swarm's members have visited the new nest site before swarm liftoff (Seeley et al. 1979). ...
When a honeybee swarm lifts off to fly to a new nest site, only the scouts know in what direction the swarm must fly, and they constitute only about 5% of the bees in a swarm. Nevertheless, a swarm will fly quickly and directly to its destination. How does the small minority of informed scouts indicate the swarm's flight direction to the large majority of uninformed bees? Two hypotheses have been suggested. The first proposes that the flying scouts streak through the swarm cloud in the direction of the goal, thereby indicating the travel direction visually (vision hypothesis). The second proposes that flying scouts release pheromones from their Nasanov glands at the front of the cloud of flying bees, thereby indicating the travel direction chemically (olfaction hypothesis). We tested both hypotheses by studying the flights of normal swarms and comparing them to the flights of swarms composed of bees whose Nasanov glands were sealed shut. Our results support the vision hypothesis and contradict the olfaction hypothesis. We identified fast-flying bees (‘streakers’) in swarms, as predicted by the vision hypothesis, but we found no effect of sealing the Nasanov glands of swarming bees. Sealed-bee swarms were perfectly capable of flying directly to a new nest site.
... Over the next day or so, the clustered swarm bees conduct a sophisticated process of group decision making to choose their future home site (reviewed by Seeley et al., 2006;Passino et al., 2008). Once they have made their choice, the swarm bees launch again into flight and fly together to their new dwelling place, generally a tree cavity a kilometer or more away (Seeley and Morse, 1977;Villa, 2004). A curious feature of the home-site selection process is that it involves only 3-5% of the bees in a swarm, the so-called 'scout bees' (Seeley et al., 1979;Seeley and Visscher, 2007). ...
When a honeybee swarm takes off to fly to its new home site, less than 5% of the bees in the swarm have visited the site and thereby know in what direction the swarm must fly. How does the small minority of informed bees indicate the swarm's flight direction to the large majority of uninformed bees? Previous simulation studies have suggested two possible mechanisms of visual flight guidance: the informed bees guide by flying in the preferred direction but without an elevated speed (subtle guide hypothesis) or they guide by flying in the preferred direction and with an elevated speed (streaker bee hypothesis). We tested these hypotheses by performing a video analysis that enabled us to measure the flight directions and flight speeds of individual bees in a flying swarm. The distributions of flight speed as a function of flight direction have conspicuous peaks for bees flying toward the swarm's new home, especially for bees in the top of the swarm. This is strong support for the streaker bee hypothesis.
he reproductive swarms usually include queens, young worker bees and drones, leaving the native hive to explore the pre-selected site and construct a hive there. Various factors which accelerate swarming events include congestion in the colony, reduced queen pheromones, limited available food resource, different ecological conditions, genetic possession of the colony, etc. Swarming is a significant event for a honey bee colony but drastically affects beekeeping. Therefore apiarists generally take specific measures to control packing events, including proper management of the colony, clipping of queen honey bee's wings, destruction of a queen cell, maintenance of adequate strength of the colony, re-queening of the colony and use of swarm resistance honey bees.
This datasheet on Varroa destructor covers Identity, Overview, Distribution, Dispersal, Hosts/Species Affected, Vectors & Intermediate Hosts, Diagnosis, Biology & Ecology, Impacts, Prevention/Control, Further Information.
This datasheet on varroosis of honey bees covers Identity, Overview, Associated Diseases, Pests or Pathogens, Distribution, Hosts/Species Affected, Diagnosis, Pathology, Epidemiology, Impacts, Prevention/Control, Further Information.
This chapter presents the main features of the biology of Apis mellifera , viral diseases, bacterial diseases, parasites of the honey bee, and in particular the mite Varroa destructor , pests and predators of the hives, and finally intoxication of the honey bee colonies. Honey bees are classified in the family Apidae, which includes the orchid bees, bumblebees, and stingless bees. Apis mellifera is a social insect with individual features and a complex social organization. The digestive tract allows breakdown of foods and absorption of nutrients. The nervous system of the honey bee is complex and allows for environmental adaptation. Destruction of infected colonies is a sanitary and reliable method to control American foulbrood. Chronic bee paralysis RNA virus frequently persists as a covert infection in honey bee colonies throughout the year. Acute Bee Paralysis Virus is a single-stranded RNA Discitroviridae virus . Kashmir Bee Virus is a single-stranded RNA Discitroviridae virus .
Departure of swarms from honey bee (Apis mellifera Linnaeus (Hymenoptera: Apidae)) nests is an important reproductive event for wild honey bee colonies and economically costly in managed bee colonies. The seasonal timing of swarm departure varies regionally and annually, creating challenges for honey bee management and emphasizing the potential for swarming behavior to be affected by plant-pollinator phenological mismatch. In this study, we first document variability in the timing of swarm departure across the large and heterogeneous geographical area of New Jersey over 4 years using 689 swarm-cluster observations. Second, hypothesizing that honey bee colonies adaptively tune the timing of swarm departure to match floral food-resource availability, we predicted that growing degree-days could be used to account for regional and annual variability. To test this idea, we used local weather records to determine the growing degree-day on which each swarm cluster was observed and tested for differences among climate regions and years. The state-wide mean swarm cluster date was May 15 (± 0.6 d), with moderate but significant differences among the state's five climate regions and between years. Use of degree-day information suggests that local heat accumulation can account for some climate-region differences in swarm-departure timing. Annual variation existed on a scale of only several days and was not accounted for by growing degree-days, suggesting little adaptive tuning of swarm-departure timing with respect to local heat accumulation.
The natural distribution of Aethina tumida (SHB) is limited to sub-Saharan Africa, where SHB is considered to be a minor and negligible pest. The introduction into countries outside of Africa, like Australia, the USA, and the recent introduction into Italy, had devastating effects. This suggests that the SHB can be a serious threat to beekeeping operations when using European stock of A. mellifera. Nevertheless, comparative research in Africa and North America over the last decade suggests that there are only quantitative and no qualitative differences between the subspecies, which makes the one subspecies susceptible and the other one resistant. The scientific evidences indicate that general aspects like colony activity levels may play a crucial role in resistance. Therefore, changes in the management practice can significantly decrease the susceptibility of colonies toward SHB. The rule of thumb is to help the colonies to help themselves by maintaining strong colonies, ensuring workers have access to all parts of the hive where beetles hide and/or reproduce. Preventative measures should also be put in place so SHBs are unable to reproduce outside the hive, in the honeyroom or in old, stored comb.
The collective mobility of active matter (self-propelled objects that transduce energy into mechanical work to drive their motion, most commonly through fluids) constitutes a new frontier in science and achievable technology. This review surveys the current status of the research field, what kinds of new scientific problems can be tackled in the short term, and what long-term directions are envisioned. We focus on: (1) attempts to formulate design principles to tailor active particles; (2) attempts to design principles according to which active particles interact under circumstances where particle–particle interactions of traditional colloid science are augmented by a family of nonequilibrium effects discussed here; (3) attempts to design intended patterns of collective behavior and dynamic assembly; (4) speculative links to equilibrium thermodynamics. In each aspect, we assess achievements, limitations, and research opportunities.
A crowdsourced dataset of 1,335 honey bee (Apis mellifera L.) swarm events in Germany in 2011 was created by beekeepers, public institutions, and members of the public and analyzed with respect to prevailing weather. The emergence of swarms appeared to be influenced by temperature and rainfall. On successive warm days in May the number of swarming events increased noticeably, but during a mid-month frost event the number of swarming events dropped markedly. Swarming events also occurred only rarely on rainy days. This study showed how crowdsourcing can be used to generate large, useful, phenological datasets.
The spectacular success of eusocial insects can be attributed to their sophisticated cooperation, yet cooperation is conspicuously absent during colony foundation when queens are alone. Selection against this solitary stage has led to a dramatically different strategy in thousands of eusocial insect species in which colonies are started by groups of nestmates and the benefits of sociality are retained continuously. Dependent colony foundation (DCF) evolved recurrently multiple times across the ants, bees, and wasps, though its prevalence in termites remains unclear. We review adaptations at both the colony level (reproductive investment shifts from sexuals to workers) and the individual-level (wingless queens evolve in ants), and other consequences for life history (invasiveness, parasite transmission). Although few studies have focused on DCF, the accumulated data from anecdotal reports, supported by indirect information including morphology, population genetics, and colony demographics, make it clear that this strategy is more diverse and widespread than is usually recognized. Expected final online publication date for the Annual Review of Entomology Volume 58 is December 03, 2013. Please see http://www.annualreviews.org/catalog/pubdates.aspx for revised estimates.
A six-year study of natural swarming in Ithaca, NY, USA, showed a bimodal distribution for date of swarm emergence, with a peak during the first two weeks in June and a lesser peak during the last week in August and the first week in September. The mean swarm size for 126 swarms was 1·53 kg (11 800 bees). The mean weight of 116 swarm queens was 195·9 mg; of mated queens 203·4 mg, and of virgin queens 185·0 mg. Data from 1976 suggest that a virgin or a young mated queen may accompany a prime swarm.
The natural honey bee nest was studied in detail to better understand the honey bee's natural living conditions. To describe the nest site we made external observations on 39 nests in hollow trees. We collected and dissected 21 of these tree nests to describe the nest architecture. No one tree genus strongly predominates among bee trees. Nest cavities are vertically elongate and approximately cylindrical. Most are 30 to 60 liters in volume and at the base of trees. Nest entrances tend to be small, 10 to 40 cm2, and at the nest bottom. Rough bark outside the entrance is often smoothed by the bees. Inside the nest, a thin layer of hardened plant resins (propolis) coats the cavity walls. Combs are fastened to the walls along their tops and sides, but bees leave small passageways along the comb edges. The basic nest organization is honey storage above, brood nest below, and pollen storage in between. Associated with this arrangement are differences in comb structure. Compared to combs used for honey storage, combs of the brood nest are generally darker and more uniform in width and in cell form. Drone comb is located on the brood nest's periphery. Comparisons among Apis nests indicate the advanced characters in Apis mellifera nests arose in response to Apis mellifera's adoption of tree cavities for nest sites.
Colony division (swarming) is a natural method of reproduction in honey bees, Apis mellifera L. It also represents a potential economic loss for beekeepers, and management practices have been devised to reduce its incidence. Simpson (1957) estimated that in an average year 10-40% of the colonies in a commercial apiary will swarm if left unattended.
The spatial distribution and nesting biology were examined for naturally occurring colonies of the African honey bee race Apis mellifera scutellata (Lepeletier) in the Okavango River Delta, Botswana. Colonies had a density of 4.2/km2 but exhibited considerable spatial clumping. Nest aggregations did not appear to result from short swarm dispersal distances, clumped resources or benefits derived from increased nest defense. Nests occurred predominantly in wooden cavities, particularly in abandoned woodpecker nests in dead palm trees. Nest cavities had a volume of ≍33 liters and south-facing, top-located entrances. Colonies constmcted ≍6,000 cm2 of comb, devoted the majority of comb area to worker brood production, stored relatively little food, and allocated ≍8% of comb area to drone rearing. A comparison of the A. m. scutellata colonies in the Okavango with neotropical African colonies throughout Central and South America revealed that the neotropical colonies were more likely to construct exposed comb nests and less likely to occupy wooden cavities. However, no differences were found between the Okavango and neotropical colonies in nest density, cavity volume, total comb area, or the proportions of comb devoted to worker brood production, food storage or drone rearing. Thus, the aspects of nesting biology examined appear to have remained largely unchanged from the ancestral African condition during the colonization of Central and South America.
1. The adaptive significance of the timing of growth and reproduction by honeybee, Apis mellifera L., colonies in cold climates was studied by describing the seasonal patterns of food storage, brood rearing, and swarming, and then observing the consequences of experimentally perturbing the seasonal cycles of brood rearing and swarming.
2. Colonies consume large amounts of food over winter (20+ kg of honey), but have only a brief period (about 14 weeks) for food collection each year.
3. The honeybee's striking habits of starting brood rearing in midwinter and swarming in late spring evidently help colonies achieve maximum use of the short summer season. Colonies whose onset of‐brood rearing was experimentally postponed until early spring showed greatly retarded colony growth and swarming. Other experiments demonstrated that late swarms starve more often during winter than do early swarms.
4. We conclude that the timings of colony growth and reproduction are essential elements in the honeybee's suite of adaptations for winter survival.
The movement patterns of neotropical African honey bee colonies were investigated by monitoring the waggle dance activity associated with nest site selection by 10 artificially created swarm clusters. Eight of the swarms carried African mitochondrial DNA (mtDNA) and 2 had European mtDNA. The latter were classified as Africanized hybrids, ie European matrilines mated to African drones. Scout bees performed recruitment dances for a mean ± SD of 12.2 ± 6.6 different potential nest sites located 3 429 ± 894 m from the swarm clusters. The mean distance communicated for the nest site ultimately selected was 4 693 ± 1 728 m. Neotropical African and hybrid swarms did not differ in the number of nest sites investigated or the mean distances communicated. Swarming behavior may account for 6-18% of the total distance traveled by neotropical African bees each year.
The overall pattern of nest-box occupations by European bees in Louisiana indicated a minimum acceptable volume of c. 10 litres, a maximum acceptable volume of c. 40 litres, and no preference between these extremes. Africanized bees in Venezuela had a nest-box occupation pattern indicating a minimum acceptable volume of c. 20 litres, no maximum acceptable volume within the limits of the sizes available in the experiment, and no clear preference between volumes from 20 to 120 litres. These data suggest a model of nest-cavity selection formulated as a hierarchical set of choices.
Africanized swarms weighed more, although the individual bees in them weighed less, and they always built a smaller total area of comb and tended to include fewer drones, than swarms of European bees.
Twelve honey bee Apis mellifera nest cavities (swarm traps) were placed at each of the four distances, 100, 250, 500 and 1000m, from a single source European apiary. Of 63 swarms, 11 were caught at 100m, 18 at 250m, 18 at 500m, and 16 at 1000m, for an overall swarm capture rate of 90%. No preferential direction of travel by swarms was observed. -Author
Natural nests of the Africanized honey bee near Tapachula, Chiapas, Mexico, were examined during March and April 1988, approximately 18 months after initial colonization. Most were in hollow trees, but open nests and nests in arboreal termite nests occurred. All nests were less than 6 months old and most less than 2 months. The modal cavity volume was 10–20 L. No brood diseases were seen. Colony density was estimated to be about six per square kilometre, higher than the density of man-kept hives.
The effect of swarm size and date of issue on comb construction was examined in honeybee (Apis mellifera L.) colonies founded by swarms. Significant positive correlations were found between the swarm size and the total amount of comb and percentage of drone comb constructed. Significant negative correlations were found between the date of swarm issue and the total amount of comb and percentage of drone comb produced. The rate of total comb production was rapid, with 90% of all comb being built within 44 days of colony founding. Drone comb construction began an average of 22 days after colony founding, with 90% of the drone comb being built within 42 days after the first drone cells. When temperate and tropically evolved bee races were compared, temperate colonies produced a lower proportion of drone comb than tropical colonies at small colony sizes, but more drone comb in larger colonies.
The effect of swarm size and date of issue on comb construction was examined in honeybee (Apis mellifera L.) colonies founded by swarms. Significant positive correlations were found between the swarm size and the total amount of comb and percentage of drone comb constructed. Significant negative correlations were found between the date of swarm issue and the total amount of comb and percentage of drone comb produced. The rate of total comb production was rapid, with 90% of all comb being built within 44 days of colony founding. Drone comb construction began an average of 22 days after colony founding, with 90% of the drone comb being built within 42 days after the first drone cells. When temperate and tropically evolved bee races were compared, temperate colonies produced a lower proportion of drone comb than tropical colonies at small colony sizes, but more drone comb in larger colonies.
Approximately 3.2 million honey bee colonies are maintained by beekeepers in the United States and many are headed by commercially bred queens. We used mitochondrial DNA (mtDNA) and allozyme variation to characterize 142 breeder queen colonies from 22 apiaries in the southeastern United States that produced ≍483,900 commercial honey bee queens in 1993. Analysis of mtDNA haplotypes showed that 4% of the 142 commercial breeder queen colonies were maternal descendants of Apis mellifera mellifera, a subspecies that was' imported into the United States by the 17th century but is no longer used commercially. The other 96% were probably descendants of A. m. ligustica. or A. m. carnica, subspecies imported in the 19th century which are still sold as commercial strains. Malate dehydrogenase allele frequencies for the 142 breeder queen colonies were determined to be Mdh65 = 0.50, Mdh80 = 0.23, and Mdh100 = 0.27. Five other enzymes known to be polymorphic in adult honey bees were invariant. Significant genetic differences between commercial and feral populations suggest that the feral population may represent a novel source of genetic variation for breeding programs.
Africanized honey bees, Apis mellifera scutellata L., are expected to arrive in southern Texas in 1988 or 1989. Currently no tested and effective means of survey or control of these bees are available for implementation. A swarm trap that is inexpensive, effective, and apparently competitive in capturing honey bee swarms is described. When tested in an environment in which Africanized bees are expected to become well established, these traps at 24 stations captured 43 swarms over the 7-wk swarming season. These traps could become a valuable means for surveying and helping to control populations of Africanized honey bees.
Honey Bee, Apis mellifera L., swarming dynamics and Africanization rates were monitored over a 5-yr period from 1988 to 1993 in the northeast Mexican State of Tamaulipas and in the lower Rio Grande Valley of southern Texas before, during, and after the arrival of the neotropical African honey bee, Apis mellifera scutellata Ruttner, to these areas. The study reports results obtained from 95,586 site-days of monitoring activities in northeastern Mexico (63 sites on a 200 km long east-west transect), and 68,428 site-days in southern Texas (36 sites on a 120 km long, east-west transect). Africanized honey bee capture rates were higher than European honey bee rates for gulf coastal areas in Mexico where both bee types also showed higher capture rates in agricultural lowlands versus montane areas. In the Texas location, European honey bee capture rates were slightly higher near the gulf coast, but otherwise swarm capture rates were similar across the transect for both Africanized honey bee and European honey bee. Pre-Africanization, European honey bee swarm capture rates were found to vary widely from year to year at each location, ranging from 0.138 to 0.446 swarms/site-month in Mexico and from 0.190 to 0.555 swarms/site-month in Texas. Post-Africanization capture rates were not appreciably different from pre-Africanization rates, ranging from 0.491 to 0.519 swarms/site-month in Mexico and 0.195 to 0.648 swarms/site-month in Texas. Africanization proceeded more quickly in northeastern Mexico where it reached 98% within 2.5 yr after the detection of the 1st Africanized honey bee. In southern Texas Africanization rates reached only 69% during an equivalent time frame.
A summary of 50 years' work on the biology and behavior of honeybees. Liberally illustrated. Harvard Book List (edited) 1971 #215 (PsycINFO Database Record (c) 2012 APA, all rights reserved)
1.
Honey bee swarms exercise considerable care when selecting a nest site. One nest site variable evaluated by bees is cavity volume.
2.
The volume distribution of natural nests (Fig. 1) has a wide range (12 to 4431 observed), but most nest volumes are clustered in the 20- to 100-1 subrange. The modal volume is approximately 351. This distribution reflects a process of volume selection among potential nest cavities when a swarm chooses its nest site. For example, swarms prefer 40-1 to 10 and 100-1 nest cavities. In nature, the volume-selection process operates primarily by rejecting undersized cavities, but also by rejecting oversized cavities.
3.
The observed limit in resolution power of volume perception was discrimination between cubes differing by 151.
4.
A swarm's preference in nest cavity volume is independent of swarm size.
5.
A scout bee's inspection of a nest site spans approximately 40 min. During this time a scout spends, most of her time at the nest site, engaged in numerous brief inspections inside and outside the nest cavity. When inside a cavity, a scout's principal behavior is rapid walking about the cavity's inner surfaces. The pattern of walking movements over successive interior inspections shows (1) a general progression from walking mostly near the entrance to walking deeper inside the cavity, and (2) a tendency to traverse different regions of the cavity's interior surface on different inspections.
6.
Honey bees can measure cavity volume if at least one of two conditions is fulfilled: (1) the cavity interior is well illuminated, or (2) the cavity's inner surfaces can be completely traversed by walking. The natural conditions for volume perception are probably low (
The indication of distance in the honey bee dance-the number of meters signified by each waggle-varies by more than a factor of ten among geographic races. Experiments in which artificial swarms were offered a choice of nest boxes indicate that A. m. carnica, the long-distance German race, clearly prefers larger and more distant cavities than the intermediate-dialect Italian race, ligustica. From these results on preferred dispersal distance and cavity size, combined with a general trend among the many races of honey bee toward dialects adapted for indicating longer distances occurring in colder latitudes, I propose that the dialect is probably an adaptation to each race's typical foraging range. That range is in large part a necessary consequence of population size, which in turn is determined by the thermal load imposed on clusters by winters in different climates.
Africanized honey bee swarms in Costa Rica displayed no size preference among pulp-based nest cavities molded to internal volumes of 13.5, 24 and 31 I. In a crossover experiment where only one cavity volume was available at a site, European honey bee swarms selected 68 cavities of 31 I volume and only 22 cavities of 13.5 I volume. When given a choice of either 31 or 13.5 I cavities, European swarms occupied the larger cavities in 84% of the choices. No correlations between swarm size, swarm date, and size of cavity inhabited by a swarm were observed among 82 European swarms measured in Tucson, Arizona during the 1993 spring swarming season. The results indicate that 13.5 I cavities are best for trapping Africanized bee swarms since they are rejected by most European swarms.
Swarm emergence date and cluster location in honey bees
- D M Caron
Caron, D. M. Swarm emergence date and cluster location in honey bees. Am. Bee J 1979. 119: 24-25.
The swarming season for honey bees in Manitoba
- A Mitchener
Mitchener, A. V. The swarming season for honey bees in Manitoba. J. Econ. Entomol 1948. 41: 646.
Selection of nest cavity volume and entrance size by honey bees in Florida
- R A Morse
- J N Layne
- P K Visscher
- F Ratnieks
Morse, R. A., J. N. Layne, P. K. Visscher, and F. Ratnieks. Selection of nest cavity volume and entrance size by honey bees in Florida. Fla. Sci 1993. 56: 163-167.
Bicentennial bees, early records of honey bees in the eastern United States. Part I, IV
- E Oertel
Oertel, E. Bicentennial bees, early records of honey bees in the eastern United States. Part I, IV. Am. Bee J 1976. 116: 70-71, 214–215.
The seasonal occurrence of honey bee swarms in North-Central California
- R E Page
Page, R. E. The seasonal occurrence of honey bee swarms in North-Central California. Am. Bee J 1981. 121: 266. 272.
STAT user’s guide, version 6
- Sas Institute
SAS Institute SAS/STAT user’s guide, version 6. 1990. Cary SAS Institute, NC.
The African bee in Louisiana
- S I I I Taber
Taber, S. I. I. I. The African bee in Louisiana. Am. Bee J. 153, 160. 1977. 152.