Foraging and Drifting Patterns of a Highly Eusocial Neotropical Stingless Bee Species Assessed by Radio-frequency Identification Tags


 Bees play a key role in ecosystem services as the main pollinators of numerous flowering plants. Studying factors influencing their foraging behaviour is relevant not only to understand their biology, but also how populations might respond to changes in their habitat and to the climate. Here, we used radio-frequency identification tags to monitor the foraging behaviour of the neotropical stingless bee Melipona fasciculata with special interest in drifting patterns, i.e. when a forager drifts into a foreign nest. In addition, we collected meteorological data to study how abiotic factors affect bees’ lifespan and behaviour. Our results show that only 35 % of bees never drifted to another hive nearby, and that factors such as temperature, humidity and solar irradiation affected the foragers drifting rates and/or lifespan. Moreover, we tested whether drifting levels would decrease after marking the nest entrances with different patterns. Contrary to our predictions, there was an increase in the proportion of drifting, indicating that this could be a deliberate strategy rather than an orientation mistake. Overall, our results demonstrate how managed bee populations are affected by both nearby hives and climate factors, offering unprecedented insights on their biology and potential commercial application as crop pollinators.

Bees play a key role in ecosystem services as the main pollinators of numerous flowering plants. Studying 23 factors influencing their foraging behaviour is relevant not only to understand their biology, but also how 24 populations might respond to changes in their habitat and to the climate. Here, we used radio-frequency 25 identification tags to monitor the foraging behaviour of the neotropical stingless bee Melipona fasciculata 26 with special interest in drifting patterns, i.e. when a forager drifts into a foreign nest. In addition, we 27 collected meteorological data to study how abiotic factors affect bees' lifespan and behaviour. Our results 28 show that only 35 % of bees never drifted to another hive nearby, and that factors such as temperature, 29 humidity and solar irradiation affected the foragers drifting rates and/or lifespan. Moreover, we tested 30 whether drifting levels would decrease after marking the nest entrances with different patterns. Contrary 31 to our predictions, there was an increase in the proportion of drifting, indicating that this could be a 32 deliberate strategy rather than an orientation mistake. Overall, our results demonstrate how managed 33 bee populations are affected by both nearby hives and climate factors, offering unprecedented insights 34 on their biology and potential commercial application as crop pollinators. 35

Introduction 44
Ecosystem services encompasses a wide range of goods and services provided by nature functioning 45 resulting in increased wellbeing and/or economic benefit to human societies 1,2 . Pollination services, i.e. 46 direct economic benefits derived from natural or managed animal pollinators, are among the most 47 important ecosystem services, with a yearly valuation estimated between US$235-577 billion worldwide 2 . 48 It is estimated that ca. 90% of flowering plants and ca. 75% of crops depend to some extent on animal 49 pollination 3,4 , of which, bees play a major role. Nevertheless, despite the remarkable importance of bee 50 pollination, most studies are focuses on only a handful of bee species, notable the honeybee Apis 51 mellifera, and the effect of other native bee populations are often overlooked and underestimated 5 . In 52 fact, wild pollinators enhance fruit set of crops regardless of honeybee abundance 6 . This scarcity of studies 53 from many bee species in terms of their contribution to ecosystem services is possible a consequence of 54 a general lack of knowledge about basic aspects of their biology and natural history. 55 Stingless bees are a highly diverse group of social bees native to the tropical and subtropical 56 regions of the world that form perennial colonies composed of hundreds to thousands of workers that 57 are common visitors of many flowering plants, including a number of crop species 7,8 . Despite the great 58 potential 9 , the large scale application of stingless bees as crop pollinators is still not as developed when 59 compared to honeybees and bumblebees 10-12 . It is nonetheless important to understand basic aspects of 60 their biology such as foraging activity patterns and lifespan, and also their viability to be managed prior 61 to any potential application of stingless bee populations. Several species of stingless bee species are 62 already managed successfully in small scale, notably those from the genus Melipona that have been 63 traditionally used for honey production in the Americas, with several other stingless bee genera used in 64 Africa, Asia and Oceania 13-15 . 65 Studying the foraging patterns in bees can help to not only increase the knowledge about these 66 important providers of ecosystem services but also to better formulate beekeeping strategies such as 67 colony density and proximity to both natural areas and crops. As yet, little is still known about many 68 aspects of their foraging patterns. In natural conditions, colonies of a single species are usually located 69 somewhat distant from each other with densities ranging between 0.014-16 hives/ha 16,17 . In managed 70 populations, in contrast, there is usually a large number of colonies aggregated next to each other, 71 resulting in increased competition for resources and high levels of orientation mistakes, namely drifting 72 behaviour, when foragers return to their hives. This drifting behaviour is well studied in honeybees but 73 still poorly understood in stingless bees 18 , and it is an important factor to be considered for both honey 74 production and crop pollination, since diseases and pathogens may spread across colonies via drifted 75 workers 19,20 . 76 Here, we used state-of-the-art radio frequency identification (RFID) tags to monitor the long-term 77 foraging behaviour of the stingless bee Melipona fasciculata in a research institute breeding facility, with 78 special interest in the drifting patterns between different colonies. In particular, we tested whether the 79 proportion of drifting behaviour observed would decrease after marking the colony entrances with 80 different geometric patterns, i.e. workers would make fewer orientation mistakes, since different patterns 81 can be used as recognition cues to the hive entrances 21 . In addition, we tested if the position of the 82 colonies had an influence in terms of the direction of the drifting rates and, finally, we correlated the data 83 collected with the RFID system with meteorological data to understand how abiotic climatic factors 84 affected both the bees' lifespan and drifting rates.

Bees foraging activity and lifespan 89
Our results show that the tagged workers lived on average for 9.3 days, ranging from a minimum of 1.2 90 to a maximum of 72.5 days after being tagged ( figure 1a). In addition, bees began foraging on average 2 91 days after being tagged, with some more extreme cases where workers only started foraging after 25 days 92 and beyond, as registered by the first reading of their tags at the colony entrance (figure 1c). Foragers 93 were active throughout the day, with the highest foraging activity being recorded during the early morning 94 hours (figure 1d). Furthermore, our data show that workers in colony four lived significantly less, while in 95 colony one and two significantly more than the average (Poisson GLM, colony four: Wald Z score = -7.602, 96 p < 0.001; colony one: Wald Z score = 2.373, p = 0.047; colony two: Wald Z score = 5.478, p < 0.001). Figure  97 2 illustrates the reconstructed foraging activity of all 2880 bees during the four-month experimental 98 period. 99  Factors affecting drifting behaviour and lifespan 116 Throughout the experimental period, only 35.9 % of all tagged workers never drifted to another colony, 117 with 36.6 % drifting to only one, 19.1% to two, 7.6% to three foreign colonies, and the percentage 118 decreasing below 1% as the number of foreign colonies increased up to a maximum of seven colonies, i.e. 119 all non-natal experimental colonies (figure 3a). It is interesting to note that the majority of drifting events 120 was in the horizontal direction, i.e. workers mostly drifted to colonies on their left or right rather than 121 above or below their natal hives (Binomial GLMM, Wald Z score > 8.568, p < 0.001 for all colonies, figure  122 3b). Moreover, colonies placed on both edges produced fewer drifters than colonies placed between 123 other hives. That is, foragers in colonies two, three, six and seven showed significantly higher levels of 124 drifting behaviour (Poisson GLM, hive two: Wald Z score = 11.880, p < 0.001; hive three: Wald Z score = 125 11.499, p < 0.001; hive six: Wald Z score = 4.125, p < 0.001 and hive seven: Wald Z score = 3.514, p = 0. foragers would then improve recognition of their own hive and drift to fewer foreign hives i.e. make fewer 139 orientation mistakes. Intriguingly, we observed an increase in the proportion of drifting events after 140 marking the hive entrances, with 63.9 % of tagged bees drifting before and 68.7 % after the hive entrances 141 were marked (Binomial GLMM, Wald Z score = 2.508, p = 0.012), suggesting that drifting behaviour could 142 be a deliberate strategy rather than merely an orientation mistake (figure 3a). 143 144  Wald Z score = -3.156, p = 0.001; and wind speed: Wald Z score = -9.901, p < 0.001). 159

Discussion 160
In this study we used radio frequency identification tags to monitor the foraging behaviour of the stingless 161 bee M. fasciculata during the dry season in a mosaic of agricultural crops, forest remnants, and human 162 habitations in eastern Amazon. By reconstructing their daily foraging activity, we could observe that bees 163 are foraging during the entire day with the peak activity in early morning hours (figure 1d). Similarly to 164 honeybees, stingless bee workers perform different tasks along their lives, from taking care of the young 165 and cleaning the colony soon after emerging, to carrying out more dangerous tasks such as defending the 166 hive and foraging towards the end of their lives with some degree of specialization in certain tasks 22 . In 167 the congeneric M. beecheii it was shown that some foragers collected mostly pollen whereas some were 168 specialized in foraging for nectar, with great impact both in their daily activity and lifespan. Nectar foragers 169 were active during the entire day but died approximately 3 days after they began foraging while pollen 170 foragers were only active for 1-3 hours in the early morning but lived on average 9 days after they started 171 foraging 23 . These patterns could explain the differences observed in our experiments, where we detected 172 a wide variation in their lifespan after they become foragers (1. An interesting outcome of our experimental design is the fact the nearly all drifting events took 207 place horizontally, i.e. foragers drifted almost exclusively to colonies placed in the same shelf as their natal 208 hive rather than above or below, and that hives placed in the centre of the rows produced more drifters, 209 similarly to what was observed in honeybees 18 . This finding demonstrates that the spatial distribution of 210 colonies has important management implications for stingless bee populations. Furthermore, ours results 211 also suggest that other factors other than the position of the hives played a role in the rates of drifting 212 behaviour. The average dew point temperature was observed to be positively correlated to the drifting 213 levels, possible because most foraging activity happens in the early morning hours and a higher 214 temperature could be linked with higher metabolic activity. On the other hand, factors like solar 215 irradiation, maximum humidity and minimum daily temperatures were shown to negatively impact 216 drifting rates. These factors are usually linked with lower foraging activity 43 , which could explain the lower 217 rates of drifting merely as an outcome of fewer foraging trips. 218 Stingless bees present great potential to be used in commercial crop pollination 7,44,45 . Indeed, 219 Melipona bees have been demonstrated to be efficient pollinators of many economically important fruits 220 and vegetables including tomatoes 46-49 , eggplant 9 , sweet pepper 50 and annatto 51 . A recent study using the 221 RFID technology with the stingless bee M. fasciculata showed that workers of this species can forage up 222 to a distance of 10 km away from their hives 52 , suggesting that these bees are well suited for pollination 223 of large scale plantations as well. In addition to their potential to be employed as commercial pollinators, 224 stingless bees are also of great importance as providers of ecosystem services 7,53 , being the main 225 pollinators of different ecosystems 54-57 . Our results give support to both applications indicating that 226 stingless bees can be used for extended periods of time in relatively high densities without significant 227 disturbances to both their foraging activities and lifespan. antennae and microcomputer of the RFID system was placed in the front of the hive. The entire system 246 was enclosed inside a box that protected entrance tubes from direct light in order to not disturb the 247 forager's behaviour (figure 4b). Young worker bees that were not yet foraging were randomly sampled 248 from each hive to receive the RFID tags. Bees were tagged every week for 9 consecutive sessions with 40 249 workers tagged per week, amounting to 360 bees per colony and 2880 in total. The process consisted in 250 collecting the young workers in the early morning (8:00-9:00) and placing them in a tube with maximum 251 5 workers per tube prior to tagging them with the RFIDs. The RFID-tags were then glued with 252 cyanoacrylate adhesive onto the worker thorax ( figure 1b) and, after all bees were marked and the glue 253 sufficiently dried, they were returned to their original hive. Workers from M. fasciculata tolerated well 254 the RFID-tags glued on their thorax without any apparent disturbance to their flight behaviour. Finally, 255 after 42 days of the beginning of the experiment, colonies received individual black and white markings 256 with varying shapes at their entrances in order to test whether foragers would then improve recognition 257 of their own hive and drift to fewer unrelated hives i.e. make fewer orientation mistakes. 258

RFID-system setup 259
This study was conducted using the Radio Frequency Identification System Ultra Small Package Tag (USPT)  260 developed by Hitachi Chemical 63 . The system consisted in a single antenna placed below the colony 261 entrance tube connected to an Intel Edison micro-computer to store data (figure 4b). Each tag was 262 recorded with an individual ID that included the bee number and her colony of origin prior to being glued 263 onto the bees. Therefore, whenever a tagged bee passed through the entrance tube both worker ID and 264 time of the day were recorded. A caveat of the experimental design was that our system consisted of only 265 one reader per colony, hence the signal sent to the computer did not inform the directionality of the bee's 266 movement (towards or away from the hive) which was then mitigated during data analysis. Moreover, 267 guard bees staying by the colony entrance would have repeated readings over a short period of time. 268 Hence, only signals that were at least 180 seconds apart were included in the analysis to resolve this issue. 269

Data analysis 275
All statistical analyses were carried out using the R software 64 . Data filtering and merging RFID and 276 meteorological data was performed using a custom R script (available on data repository). Lifespan of 277 foragers was calculated based on the difference between the last recorded data and the date the bees 278 were tagged. First foraging trip was calculated with the difference between the first trip recorded and the 279 tagging date and the density estimates were calculated based on the smoothed histogram using the 280 "geom_density" function in the R package ggplot2. Likewise, the daily foraging activity were also 281 calculated using the density function in the package ggplot2. To analyse the influence that both biotic and 282 abiotic factors have on the observed drifting rates we used a model selection approach using the package 283 glmulti to select the best set of explanatory variables based on the models Akaike's Information Criterion. 284 The selected best model had drifting numbers coded as the dependent variable with lifespan, hive ID, 285 number of days to begin foraging as well as several meteorological factors coded as covariates with a 286 Poisson error distribution. We then used the same approach to select a model with the bees' lifespan 287 coded as the dependent variable but used a quasipoisson error distribution do deal with overdispersion 288 detected in this model. In addition, we tested whether the proportion of drifters present on the colonies 289 was different before and after marking the colony entrances by fitting a binomial GLMM with the 290 proportion of foragers that drifted to an unrelated colony as the dependent variable, colony marking 291 (before or after) as a fixed factor and hive ID and an observation-level random effect variable to cope with 292 overdispersion as random factors. Finally, we tested whether drifters had any preference on the direction 293 they would drift. To this end, we ran a binomial GLM with the direction of the drifting event (i.e. horizontal 294 and vertical) as the dependent variable, both the natal hives ID and the host hives ID as cofactors and 295 individual IDs as a random factor. When appropriate, models were tested for temporal autocorrelation, 296 which was not observed in the data.