what time of day do bees return to the hive

Introduction

Animals are oft faced with the challenge of foraging on resources whose quality and availability change over infinite and fourth dimension. In order to maximize foraging success, animals have evolved mechanisms to estimate which resources are worth exploiting (Belovsky, 1978; Pyke, 1978; Pleasants, 1989; Van Nest and Moore, 2012). Many animals provender on resources to which they may make multiple trips (such as bees, nectar foraging ants, and birds); in these cases, foragers need to choose when to return to the aforementioned resource and when to abandon information technology to search for a new 1. This is known equally the "exploitation vs. exploration" trade-off (Krebs et al., 1978; McNamara and Houston, 1985). In social animals, both the data available to brand this decision, and the consequences of foraging success, may be shared among individuals. Social insects have been specially well studied in this respect.

Dear bees (Apis mellifera) provide a not bad model for social foraging due to their ability to rapidly adapt their foraging efforts to changing resource availability, studied peculiarly in the context of nectar foraging (Seeley, 1986). This is achieved through the collective actions and decisions of individual foragers, with the benefits and costs of these decisions affecting the colony as a whole. Individual bees integrate several sources of information, including personal and social, when making decisions about foraging (Biesmeijer and Seeley, 2005). Honey bee foragers use information gained in their own experience, such as memory of time and place, sugar concentration and corporeality of nectar previously collected, to decide whether to continue or resume foraging on particular resources (Wainselboim et al., 2002; Grüter and Farina, 2009a; Van Nest and Moore, 2012; Al Toufailia et al., 2013). They besides brand apply of various sources of social information, such every bit information virtually resource location and quality transmitted via the waggle trip the light fantastic (von Frisch, 1967; Grüter and Farina, 2009b), and information about resource quality and type from nectar samples unloaded in the hive (Grüter and Farina, 2009a). Other advice signals and interactions can also affect foraging decisions, such as the tremble trip the light fantastic (nutrient storer activation) and the cease signal (forager inactivation) (Seeley, 1989; Nieh, 1993; Balbuena et al., 2011; Seeley et al., 2012).

But what kind of information practise foragers use to decide when to terminate visiting a particular resources? The colony's dynamic ability to classify foragers to the best resources available can merely exist maintained if foragers frequently re-evaluate their curt-term commitment to resource (Seeley et al., 1991; Detrain and Deneubourg, 2008). While foragers may revisit and check on resources over long periods of fourth dimension (days or weeks), we are particularly interested in how foragers determine on which resources to continue foraging (Beekman, 2005; Al Toufailia et al., 2013). How do foragers brand the decision to end foraging on a particular resource? Ii main processes have been identified. First, an individual personally experiencing a turn down in the quality of the resources is more probable to abandon information technology, and to stop foraging entirely or look for other resource (Seeley et al., 1991; Townsend-Mehler et al., 2010). 2nd, if the colony's need for foragers in general, or the need for the particular provender brought in past that forager (e.thou., if other foragers are bringing higher-quality nectar), has decreased, individuals may besides abandon the resource they are currently exploiting (Lindauer, 1952; Seeley, 1989). Foragers get this information from interactions with nestmates, particularly receiver bees (Lindauer, 1952; Seeley, 1989; Biesmeijer and de Vries, 2001).

In honey bees, foragers can assess resource quality directly when foraging, using several criteria, including concentration and volume of the nectar itself, but also the flying distance to the resources from the hive and the likelihood of predation at the resources (von Frisch, 1967; Tan et al., 2013). These measures are integrated by bees and bear upon both when bees share information near this resource past dancing and the bees' decision to go along foraging on it (Seeley, 1994; De Marco and Farina, 2001). Nectar can be highly temporally and spatially variable, afflicted by abiotic factors (rainfall, sunlight, nutrients) and biotic factors (pollinator visitation and nectar replacement rates) (Real and Rathcke, 1991; Boose, 1997; Border et al., 2011). Even over the class of a day nectar book tin change quite chop-chop, by several microliters in an hour (Raihan and Kawakubo, 2014).

A honey bee forager can besides gain valuable social information about the quality of her resource relative to others exploited by her colony, and the demand for this resources, from her nest mates. Foragers, later gathering liquid food such as flower nectar or honeydew, return to the hive to pass this food to another bee, called a "receiver bee," who will comport information technology deeper into the hive, process it, and either deposit it in a honey store or pass it on to nurse bees (Seeley, 1995). The time information technology takes from inbound a hive to securing a receiver bee we call "wait time," and is thought to reflect colony foraging needs in one of two ways (Seeley and Tovey, 1994). Receiver bees have access to multiple foragers, and may thus feel multiple sources of nectar; in response they may be reluctant to accept a lower-quality or novel resource compared to what they accept recently experienced (Seeley, 1989; Seeley and Tovey, 1994; Gil and Farina, 2002; Wainselboim and Farina, 2003; Goyret and Farina, 2005). Thus a forager who experiences a longer wait time may be informed that her resource is of poorer quality relative to what is existence brought into the hive past others. Difficulty of finding a receiver may also betoken the general state of hive-level foraging to the forager: increased await time could be a result of a redistribution of workers away from unloading to more pressing colony tasks, or a issue suddenly increase in foragers bringing nectar that overwhelms the capacity of the existing receiver bees to process that nectar (Lindauer, 1952; Seeley and Tovey, 1994). In both of these cases, it may be adaptive for a forager experiencing long wait times to stop foraging on its particular resource. Indeed, in an empirical examination using artificial feeders and removal of receiver bees, lower densities of receiver bees resulted in longer wait times, decreased the probability that a forager would perform waggle dances, and increased the probability that a forager would finish foraging on its current resource (Seeley, 1989).

While independently shown to affect foragers' decisions to abandon resources, personal and social information'due south relative contributions to forager decisions, besides as their importance under natural foraging weather with many small, temporally and spatially apace varying resources, take not been investigated. Does personal or social information more than often determine a bee's decision to quit foraging at a resource, and are the bees' decisions fully explained by these 2 factors, or are other processes also important? For case, bees might just cease foraging on any particular resource with a fixed probability, which could assistance the colony maintain flexibility, since information technology prevents large numbers of foragers from being "locked in" to foraging on particular resources (Detrain and Deneubourg, 2008; Lanan et al., 2012). Does this occur, and how relevant is information technology compared to quitting in response to the two known factors?

We thus quantify the influences of decreased trophallaxis elapsing and increased wait fourth dimension on the determination to carelessness resource under natural foraging conditions. Using detailed foraging histories based on in-hive observations of returning foragers, we exam (1) the result of personal information, in the form of a refuse in resource quality, on the decision to cease foraging. To do this nosotros compare the average trophallaxis duration (a proxy for nectar load and thus a potential correlate of resource quality) after the terminal trip before a forager abandons a resource with its previous average trophallaxis duration over recent trips that are likely to be to the aforementioned resource. We too test (2) the effect of social data, in the form of wait time to unload nectar, past measuring this direct in the hive, and comparing wait fourth dimension on the final trip with that on recent trips.

Methods

Set Up and Marking

Each experiment was performed with two colonies of almost 2000 domestic Italian honeybees (Apis mellifera ligustica) each, with roughly 500 bees individually marked in each colony. They were housed in a glass sided, 2 frame ascertainment hive with the exit, a clear plastic tube, connected to the hive near the lesser corner. Foragers were marked at the USDA Carl Hayden Bee Center over a period of 1 week prior to the start of the experiment. Foragers were captured by selectively collecting individuals that had left the hive. Individuals were uniquely marked with a colored/numbered tag and paint. After being sealed into their hives for ~24 h, the colony was transported to a new location and left sealed overnight before the commencement of the experiment the next morn.

Dates and Location

The two experiments took place in two locations in southern Arizona. Experiments 1a and 1b were located at Appleton–Whittell Research Ranch, an Audubon Guild preserve virtually Elgin, Arizona and took place on June 20 and 27, 2010. Experiments 2a and 2b were performed at the Santa Rita Experimental Range Headquarters in Florida Canyon on Aug 9 and 16, 2010. (These dates and locations correspond to experiments iii and 4 in Donaldson-Matasci and Dornhaus, 2012).

Recording

Hives were opened at dawn and remained open until dusk. During that time all marked bees were recorded coming in and out of the hive. From video recordings taken, we observed all returning marked bees and recorded all instances of trophallaxis within 5 min of entering the hive. Wait fourth dimension (amount of time from entering the hive until the beginning of the first trophallaxis, an indication of colony foraging needs) and trophallaxis duration (the sum of all trophallaxis event durations in a single hive visit, a proxy for the profitability of the exploited resource) were determined for each returning bee (Wainselboim and Farina, 2003). Trophallaxis duration has been used equally a metric for non-invasively determining resource quality (Seeley and Visscher, 1988). Nosotros just analyzed foraging histories from foragers who were performing repeated, consistent, successful foraging trips, which we termed to exist "employed" (encounter beneath); we did this to maximize the likelihood that foragers were indeed repeatedly visiting the same resource. To see if a human relationship existed between the conclusion to quit foraging and declines in trophallaxis elapsing and/or increases in wait fourth dimension, we compared these measures on a forager's last trip to the average measure on previous trips of that forager (during its "employment").

Individual Foraging Histories

Foraging histories were synthetic using the following operational definitions, based on the framework in Biesmeijer and de Vries (2001). We consider a forager to be "employed" while information technology consistently keeps foraging at the same resource (e.g., a patches of flowers that a bee would return to repeatedly). Nosotros operationally defined this as a forager who performs 3 or more consecutive successful foraging trips (where trophallaxis is performed in the hive after each trip), with less than 2 min variability in duration, and less than 10 min spent in the hive betwixt trips. This was a consistent pattern that emerged from our foraging data, in other words most bees that performed several consecutive successful trips conformed to this pattern. Through the lens of these foraging histories we are able to determine when an individual stops foraging at a particular resource (see Figure 1). We constitute 29 private bees out of the 227 individuals observed (184 of which showed at least one successful trophallaxis event) over the 4 experiment days and the 2 colonies that showed such consistent foraging patterns. This was peradventure due to many foragers only performing a few short bouts of trophallaxis over the unabridged solar day.

Figure 1. Sample employment histories for 3 employed foragers from experiment 2a. Highlighted portion is the "employment" stage.

Colony Level Foraging Activity

To measure the influence of average trophallaxis duration and look time on colony-level foraging activity, we divided each experiment into 15-min fourth dimension bins. For each bin we recorded the number of marked foragers who left the hive (employed or unemployed), boilerplate length of all trophallaxis events, and the average await time. Due to the likely presence of autocorrelation in these data series, simply testing for correlations among these factors could lead to erroneous results. Instead, nosotros use a cross-correlation test, which measures the correlations between the two fourth dimension series as a function of fourth dimension lag (Venables and Ripley, 2002). If wait time were a major gene affecting foraging activeness, we would see a negative correlation (equally await time increases, number of foragers leaving decreases) with a positive time lag (the decrease in the number of foragers would occur after the increase in await fourth dimension). If, on the other paw, colony-level foraging activity afflicted wait fourth dimension (e.g., because with fewer foragers, bees tin can unload faster), nosotros would see a positive correlation with a negative lag (decreases in the number of foragers would precede decreases in expect time). Similarly, if changes in trophallaxis duration affected foraging activity, we would run into a positive correlation (as resources decline in quality, fewer bees leave the hive) with a positive time lag (a decline in the resources precedes a decline in foragers). Nosotros considered but time lags within biologically relevant time calibration (less than an hour). To business relationship for multiple testing, i.east., consideration of multiple time lags, we applied a Bonferroni correction (significance level α = 0.05/xi, where 11 is the number of potential time lags considered in each experiment). All analyses were performed using the R statistical package (R Cadre Team, 2013).

Results

Individual Level Foraging

Contrary to expectations, we did not find a statically significant effect of either decreased trophallaxis elapsing or of increasing look times on individual bees' decision to cease foraging. That is, foragers did not experience a longer-than-boilerplate wait time just before quitting any more than often than expected by gamble (Binomial test p = 0.326, n = 29, see Table 1). Their trophallaxis durations were as well not shorter than boilerplate any more often than expected by chance (Binomial test p = 0.845, n = 29, see Table 1). Looking at it in a different way, the trophallaxis elapsing experienced by foragers on their last trip before quitting was not significantly shorter than that experienced on previous trips (Wilcoxon signed-rank test p = 0.56, Westward = 370.5, northward = 29). Neither was wait fourth dimension on a forager's last trip significantly longer than on previous trips (Wilcoxon signed-rank exam p = 0.98, W = 336, n = 29) (Figure ii). These analyses were performed on "employed" foragers, which showed trophallaxis durations on boilerplate seven times longer than non-employed categorized foragers (T-test p = 0.0498, n = 4, colony averages for employed and non-employed successful foragers).

Table ane. The number of "employed" foragers in each experiment, and whether they experienced a longer wait time/shorter trophallaxis duration on the last trip of their employed menstruum compared to the average for previous trips.

Effigy 2. Difference between the concluding and average trophallaxis duration/wait time during a forager's employment catamenia.

Colony Level Foraging

The level of colony foraging activity varied considerably throughout the day, every bit did trophallaxis and expect times (Figure 3). Experiments 1a and 1b (in June) showed strong foraging peaks in the morning time, while experiments 2a and 2b (in August) showed more than consistent activeness across the mean solar day, with more foraging in the afternoon.

Figure 3. Daily foraging action, boilerplate trophallaxis duration and await fourth dimension of all marked foragers across the 4 experiments. Hives were opened and recorded from dawn until dusk.

Nosotros found no evidence that changes in trophallaxis duration across all successful foragers affects colony-level foraging action (Figure iv—Trophallaxis duration). If changes in trophallaxis duration afflicted foraging activeness, we would await to see a positive correlation (equally resources decline in quality, fewer bees leave to forage) with a positive time lag (a pass up in the resources is followed by a turn down in foraging activity). However, the just significant correlations we observed were positive correlations with negative time lags, suggesting that decreases in foraging activity preceded decreases in trophallaxis duration (experiments 1b and 2b). In the other experiments, no significant correlations were observed.

Figure 4. Cross correlation exam results showing correlations betwixt either trophallaxis duration or wait time and the number of foragers leaving. Horizontal lines signify critical values corrected for multiple testing (Bonferroni correction: α = 0.0045); a correlation at any time lag above that line is considered statically significant. Time lag is for foragers leaving relative to trophallaxis duration/wait time (i.e., positive fourth dimension lag indicates that changes in the gene precede changes in foraging activeness by the specified time lag).

We as well found no bear witness that the wait fourth dimension experienced by foragers influences the colony's foraging effort (Figure 4—Trophallaxis duration). If expect fourth dimension were a major factor affecting foraging activity, we would expect to see a negative correlation (as wait fourth dimension increases, number of foragers leaving decreases) with a positive fourth dimension lag (the decrease in the number of foragers would occur after the increase in wait time). No significant negative correlation between wait time and foraging endeavour was observed in any experiment. In experiment 2a, pregnant positive correlations were observed with both positive and negative time lags. A positive correlation with a negative time lag might signal that loftier levels of foraging activeness tend to increase wait times (considering receiver bees are busier), merely the occurrence of correlations at positive time lags as well makes it difficult to infer the direction of causation. In the other experiments, there were no significant correlations observed.

Word

Our study aimed to quantify and compare the effects of (ane) personal experience of a turn down in resource quality and (2) social information about a decrease in the colony'southward need for a detail resource, in a natural setting. Both of these factors had independently been shown to affect honey bees' short term decisions to terminate foraging on artificial food sources (Seeley, 1986; Seeley and Tovey, 1994). We besides looked for evidence of these effects at the colony level, by testing whether a honey bee colony's overall foraging activity decreases in response to either cistron. In our experiment, neither factor appeared to accept a noticeable effect: we saw no human relationship between changes in trophallaxis elapsing (our proxy for resources quality) or wait time to unload (a proxy for colony need) and the decision to quit foraging at either the individual or colony levels.

A crucial assumption made here is that trophallaxis duration and wait time are valid proxies for resources quality and colony foraging demand respectively. These two measures accept been tested several times with conflicting results. For trophallaxis duration, Farina and Núñez (1991) and Farina and Wainselboim (2001) found no relationship between resource quality and trophallaxis duration, but Wainselboim and Farina (2003) and Seeley et al. (1991) did. Perhaps these differences are reflections in the variation in methods, especially in terms of feeders used (capillary tubes vs. multi-well feeders) or where the trophallaxis duration measurements were fabricated (in carve up observation chambers or within the hive). In general, no artificial feeder mimics resource delivery of natural resources: flowers evangelize tiny and extremely variable nectar amounts, but secrete nectar so slowly that they effectively accept no "menses rate" where a bee can look to fill upwards, and bees generally visit upward to several hundred flowers on each trip (Castellanos et al., 2001). By utilizing trophallaxis elapsing we are able to brand directly comparisons against previous studies (Seeley, 1986) using the same metric, but with natural resources. Thus, while there is perhaps not a consensus on how trophallaxis time relates to resource quality, it is a non-invasive mensurate previously shown to predict foraging decisions.

Wait time has universally been seen equally a source of social data about the need for the item food brought past a foraging honey bee (Seeley, 1989; Seeley and Tovey, 1994; Gil and Farina, 2002; Wainselboim and Farina, 2003; Goyret and Farina, 2005). What information precisely is independent in this cue, i.eastward., what social processes affect look time, has been interpreted somewhat differently in different studies. It may be that the forager mainly receives information almost the nutritional status of her colony (Seeley, 1989; Seeley and Tovey, 1994); others conclude that await time is a reflection on the quality of the foragers resource relative to other resources exploited past the hive (Lindauer, 1961).

While our colony-level analysis included only marked bees (~500, 25% of the colony), they represented a majority of the foragers, thus providing a good measure of colony foraging effort. Withal, for the individual-level analysis we merely recorded 29 bees foraging consistently ("employed" according to our operational definition). This sample size is like to previous studies of this nature (Seeley and Tovey, 1994: 39 foragers; De Marco and Farina, 2001: 17 foragers), however, a larger study, with more foragers recorded equally well as including more than different days of foraging, would likely have made any effects of both resource quality and colony need for the resources more credible. We do non conclude from our results that neither factor ever plays a role; after all, the possible effects of both had been demonstrated previously (Seeley, 1986; Seeley and Tovey, 1994). Despite this, however, our results do evidence that neither factor explains most of the variation in forager decisions.

1 reason that we may not have seen an effect of either change in resources quality or wait time on the determination to stop foraging is that the magnitude of both of these effects is small nether natural weather. While several previous manipulative studies have demonstrated these effects, this report is the first that uses natural resources and no manipulation of worker allocation (Seeley, 1986; Seeley and Tovey, 1994; Wainselboim and Farina, 2003; Balbuena et al., 2011). Unlike the artificial feeders used in previous experiments, natural resource quality may change quite dramatically or subtly (Real and Rathcke, 1991; Boose, 1997; Edge et al., 2011). Furthermore, the potentially wide variety of resources being exploited may buffer large changes in the overall quantity and quality of nectar being brought into the hive (Donaldson-Matasci and Dornhaus, 2014). Barring any large-scale simultaneous resource mural changes, the colony may experience relatively subtle and wearisome changes in resources intake. Continual adjustments in the ratio of receiver bees to foragers may let the colony to track those changes without ever experiencing long await times (Seeley, 1986). Thus colonies under natural weather condition may rarely feel the dramatic increase in wait time induced by artificially removing receiver bees from the hive. Await times could exist primarily a byproduct of other colony level functions (such as shifts in worker allocation) rather than a result of resource dynamics. For example the density of bees in the entrance expanse (often called the dance floor) may be a good indicator to foragers on such shifts, and take been shown to vary throughout the twenty-four hour period (Seeley, 1995). Such effects would increase the noise in the wait time cue, and may make its consequence on foraging decisions less clear. By comparing these measures over the average fourth dimension to the last, we hope to capture the greatest amount of modify (i.e., the greatest reject in trophallaxis elapsing). Nevertheless, it could be with the noise or subtly that natural conditions bring, that foragers use a series of poor indicators to make foraging decisions.

Another possible caption for the observed lack of effect in our experiment is that both factors are important in nature, but which factor is most influential could alter depending on the observed time frame. Our small sample size precluded analyzing the effects separately over different fourth dimension periods, which might have kept us from finding a significant effect. In the forenoon, when resource are of higher quality, foraging bees might be willing to await longer to unload to capitalize on the loftier quality nectar, in which case these foragers should be relativity insensitive to wait time and highly sensitive to changes in resource quality. Later in the day when there is a higher need for workers elsewhere in the hive (for case cooling or water collecting) no matter the quality of the resources, the look time to unload nectar could take precedence in their decision making (Johnson, 2003). At this after time we might and so see the sensitivity to wait time increase relative to their response to irresolute nectar quality. Equally Effigy three illustrates, resources quality and unload time were dynamic beyond the day, which could accept been due to the effects of changing resource or additional factors affecting colony organization. However, because we had relatively few employed foragers working consistently across the 24-hour interval, we did not have enough statistical ability to examination for changes in the importance of each cistron over the grade of the day. Additionally these factors could bear on the determination much differently over a longer time period. While our study looked only at foraging dynamics within a relatively curt fourth dimension frame, previously studies take shown that bees will be more than persistent on a previously stiff rewarding resource even if it declines in quality (Al Toufailia et al., 2013).

In add-on to variation within a single environment, differences in foraging atmospheric condition betwixt environments could have shaped the foraging patterns we saw (Sherman and Visscher, 2002). Whether personal or social information is most important in an individual's conclusion to cease foraging at a particular resources may alter depending on the foraging environments. For example previous work has shown that the benefit a colony receives from communication via the waggle dance depends on the resource environment (Donaldson-Matasci and Dornhaus, 2012). This could be truthful for the benefits of using a detail type of personal or social information (like waiting times) also. For case, in environments with brusque lived, rich resources, using personal information about resource quality may allow a forager to secure a highly profitable resource before it disappears, regardless of possibly out-of-date social information. If resource are long-lived, the colony-level foraging effort should perhaps be more driven past colony need than resource availability. In that case, following wait time to learn about colony needs may ensure that the colony'due south nectar drove and processing rates are well counterbalanced and efficient. More often than not each of these sources of information accept been shown to vary in their accurateness, with personal information being more authentic about a single exploited resource, but naïve nigh the resource landscape (Franks et al., 2003). Social information is thought to operate on a slower timescale than personal, potentially leading inaccuracy most specific resource due to transmission errors and the potential for it to exist outdated (Rendell et al., 2010). Nevertheless, social information allows for comparison amongst resources without requiring directly comparison by individuals. Thus what may favor the utilise of either social or personal information may exist driven by the need for brusk term accuracy on about a specific resource (personal) or longer term information across resources (social) in a particular context. Further more different types of social and personal information be and may be afflicted past ecology weather condition separately. For instance the waggle dance may be more suitable for ephemeral resources due to its fast response time, while floral odors shared among foragers may lend to steady resource patches.

In addition to beingness context dependent, what data a foraging honey bee uses to quit foraging on a particular resources could vary amid individuals and among colonies. It has been shown that nectar response thresholds (the concentration of sucrose at which individuals respond) vary among individuals and colonies (Pankiw and Page, 2000). Individual variation in nectar response thresholds could provide a mechanism for the variation we run across in the decision to abandon a resource, with high threshold individuals beingness more than likely to carelessness a resource when it declines in quality and depression threshold individuals being more persistent. Similarly, inter-individual variation in sensitivity to wait time could obscure the colony-level correlation between increased expect time and quitting foraging. Future studies with larger numbers of marked individuals foraging over the course of several days could bear witness whether individuals are consistent across their foraging careers in their sensitivity to declines in resource quality and/or expect time.

We take focused on two sources of data that foraging honey bees might use in making the conclusion to abandon a resources: personal information about resources quality, and social data about colony needs. However, it is likely that there is a stochastic element to their decision-making as well. Some accept argued that individuals living in groups can afford to be less precise: private variance in decision-making may be compensated by the reliability of the system every bit a whole (Oster and Wilson, 1978). Furthermore, some randomness in individual behavior can actually exist good, in the context of collective behavior, considering it may allow the group to reply more flexibly to changing environmental weather (Deneubourg et al., 1983, 1986; Seeley et al., 1991; Detrain and Deneubourg, 2008; Townsend-Mehler and Dyer, 2011). For example, individuals may sometimes persist in foraging at even rather poor nectar sources ("inspectors"), just in case the resource increases in quality (Biesmeijer and de Vries, 2001; Biesmeijer and Seeley, 2005; Granovskiy et al., 2012). Too it could exist advantageous for some individuals to abandon even a strong nectar source, in order to keep the colony from overcommitting to whatsoever unmarried resource while potentially missing out on even stronger ones. Given the potential for rapid resources dynamics, a colony beingness "locked into" one or a few resources may miss newly emerging ones (Detrain and Deneubourg, 2008; Lanan et al., 2012).

If there is a strong element of randomness in a forager's decision to abandon a resources, it may be difficult to observe the subtler effects of personal or social information nether natural foraging weather. Our results may reflect a complex interplay of factors influencing honey bee decision making in natural environments, just the potential importance of stochasticity in these systems should not be disregarded.

Conflict of Involvement Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could exist construed equally a potential conflict of interest.

Acknowledgments

MCD was funded past the University of Arizona's Eye for Insect Science through a NIH Training Grant #1K12GM000708. AD was funded by NSF grants no. IOS-1045239 and DBI-1262292. Dear bee colonies were kindly provided by R. Page at Arizona State University and Chiliad. DeGrandi-Hoffman at the USDA Carl Hayden Bee Enquiry Eye, and housed at the latter's facility with assistance from K. Chambers and T. Deeby. We give thanks E. Francis (SASI), L. Kennedy (AWRR), M. Heitlinger (SRER) and R. Smith (UADS) for their cooperation and support at our field sites. Nosotros gratefully acknowledge the field work assistance of N. Matasci, G. Barraza, J. Brownish, J. Chappell, Yard. Hughes, J. Icely, Northward. Narkhede, S. Williams and Y. Zhu.

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