Evaluating the Quality of Citizen‐Scientist Data on Pollinator Communities

Abstract: Concerns about pollinator declines have grown in recent years, yet the ability to detect changes in abundance, taxonomic richness, and composition of pollinator communities is hampered severely by the lack of data over space and time. Citizen scientists may be able to extend the spatial and temporal extent of pollinator monitoring programs. We developed a citizen‐science monitoring protocol in which we trained 13 citizen scientists to observe and classify floral visitors at the resolution of orders or super families (e.g., bee, wasp, fly) and at finer resolution within bees (superfamily Apoidea) only. We evaluated the protocol by comparing data collected simultaneously at 17 sites by citizen scientists (observational data set) and by professionals (specimen‐based data set). The sites differed with respect to the presence and age of hedgerows planted to improve habitat quality for pollinators. We found significant, positive correlations among the two data sets for higher level taxonomic composition, honey bee (Apis mellifera) abundance, non‐Apis bee abundance, bee richness, and bee community similarity. Results for both data sets also showed similar trends (or lack thereof) in these metrics among sites differing in the presence and age of hedgerows. Nevertheless, citizen scientists did not observe approximately half of the bee groups collected by professional scientists at the same sites. Thus, the utility of citizen‐science observational data may be restricted to detection of community‐level changes in abundance, richness, or similarity over space and time, and citizen‐science observations may not reliably reflect the abundance or frequency of occurrence of specific pollinator species or groups.     

ABC算法优化SVR的磨损故障预测模型

目的为了提高故障预测的精度,针对支持向量回归SVR(Support vector machine for regression,SVR)参数选择困难的问题,提出一种采用人工蜂群(artificial bee colony,ABC)算法优化支持向量回归(SVR)的故障预测模型(ABC-SVR)。方法该模型先对样本数据进行重构,然后将故障预测误差(适应度)作为优化目标,通过ABC算法寻优找到最优的SVR参数,建立故障预测模型。最后通过实例仿真验证模型的优越性。结果采用ABC算法优化的SVR故障预测模型进行时间序列预测,能够较好地跟踪发动机滑油金属元素浓度的变化过程,并且能够提前2个取样时间预测异常情况的出现。结论 ABC-SVR模型有效解决了SVR参数选择难题,能够更加准确地表现故障变化规律,提高了故障预测精度。     

Experience,but not distance,influences the recruitment precision in the stingless bee <Emphasis Type="Italic">Scaptotrigona mexicana</Emphasis>

Recruitment precision, i.e. the proportion of recruits that reach an advertised food source, is a crucial adaptation of social bees to their environment. Studies with honeybees showed that recruitment precision is not a fixed feature, but it may be enhanced by factors like experience and distance. However, little is known regarding the recruitment precision of stingless bees. Hence, in this study, we examined the effects of experience and spatial distance on the precision of the food communication system of the stingless bee Scaptotrigona mexicana. We conducted the experiments by training bees to a three-dimensional artificial patch at several distances from the colony. We recorded the choices of individual recruited foragers, either being newcomers (foragers without experience with the advertised food source) or experienced (foragers that had previously visited the feeder). We found that the average precision of newcomers (95.6 ± 2.61%) was significantly higher than that of experienced bees (80.2 ± 1.12%). While this might seem counter-intuitive on first sight, this “loss” of precision can be explained by the tendency of experienced recruits to explore nearby areas to find new rewarding food sources after they had initially learned the exact location of the food source. Increasing the distance from the colony had no significant effect on the precision of the foraging bees. Thus, our data show that experience, but not the distance of the food source, affected the patch precision of S. mexicana foragers.     

基于人工蜂群算法与BP神经网络的水质评价模型

针对BP网络水质评价模型的不足,引入人工蜂群(ABC)算法,将求解BP神经网络各层权值、阀值的过程转化为蜜蜂寻找最佳蜜源的过程,提出了一种新的结合人工蜂群算法的BP网络水质评价方法(ABC-BP)。并以2000—2006年渭河监测断面的10组实测数据作为测试样本对其水质进行了评价,实验结果表明该方法得到的水质评价结果准确,并具有很强的稳定性和鲁棒性。     

Geographic Variation in the Seasonal Reproductive Strategy of the Mite Varroa jacobsoni in the Honeybee Nest

Variation in the reproduction of Varroa jacobsoni mite was studied in relation to the expansion of the range of its parasitism on the honeybee. Geographic differences in the seasonal dynamics of mite reproduction in the nests of bee families were revealed. Variation in the sex ratio of mites and the factors inhibiting their reproduction at the northern boundary of the honeybee range are considered. The forms of parthenogenetic reproduction in V. jacobsoni are discussed.     

Pipeline leakage detection and isolation: An integrated approach of statistical and wavelet feature extraction with multi-layer perceptron neural network (MLPNN)

Leakage diagnosis of hydrocarbon pipelines can prevent environmental and financial losses. This work proposes a novel method that not only detects the occurrence of a leakage fault, but also suggests its location and severity. The OLGA software is employed to provide the pipeline inlet pressure and outlet flow rates as the training data for the Fault Detection and Isolation (FDI) system. The FDI system is comprised of a Multi-Layer Perceptron Neural Network (MLPNN) classifier with various feature extraction methods including the statistical techniques, wavelet transform, and a fusion of both methods. Once different leakage scenarios are considered and the preprocessing methods are done, the proposed FDI system is applied to a 20-km pipeline in southern Iran (Goldkari-Binak pipeline) and a promising severity and location detectability (a correct classification rate of 92%) and a low False Alarm Rate (FAR) were achieved.     

Trophic aspects of caste determination in Halictus ligatus,a primitively eusocial sweat bee

Caste determination in primitively eusocial sweat bees is thought to be due to an interacting suite of factors, including size of the larval provision mass, time of year, and social context of the nest into which a young female emerges. Newly emerged gynes are significantly fatter than newly emerged workers, suggesting the existence of larval caste determination cues. Since photoperiod, temperature, and interactions with nestmates were unlikely to affect larval caste determination, we compared the sizes and contents of larval provision masses destined to produce either workers or gynes. Gyne-destined larvae consumed pollen masses that were larger and contained slightly more sugar than those of worker-destined larvae. We suggest that sugar content is one cue which prompts the development of fat reserves in gyne-destined females but not in worker-destined females. The amount of fat possessed by a newly emerged female influences her chances of successfully entering diapause shortly after emergence. Therefore, small, lean females may be more susceptible to behavioural control by queens and more likely to become workers, while large, fat females would be more likely to become gynes. Correspondence to: M.H. Richards     

Strategic exploitation in a socially parasitic bee: a benefit in waiting?

Social parasitism has evolved at least ten times in the allodapine bees but studies that explore the parasite’s integration and exploitation of host colonies are lacking. Using colony content and dissection data, we examine how Inquilina schwarzi affects the social organisation of its host Exoneura robusta. Our samples include three critical periods in the host life cycle: initial formation of dominance hierarchies in late autumn, commencement of oviposition by host queens in late winter, and development of secondary reproductives in late spring. I. schwarzi preferentially parasitises larger host colonies in autumn, but during autumn and winter, the parasite appears to be socially invisible, living in the nest without disrupting the normal functioning of these colonies. Inquilines begin egg laying much later than their hosts, and by late spring, they have disrupted host reproductive hierarchies, leading to lower skew in ovarian sizes of their host nestmates. Living invisibly within the host nest for the first 6 months and waiting until well after host reproduction has begun before disrupting their social organisation appear to be unique among social insects. Such a change in strategy may be facilitated by the different social systems found in allodapine bees, with the social parasites possibly disrupting the reproductive hierarchies during spring to prevent or reduce the normal dispersal of some host females from their natal nests.     

On interacting bee/mite populations: a stochastic model with analysis using cumulant truncation

Parasitism by the Varroa mite has had recent drastic impact on both managed and feral bee colonies. This paper proposes a stochastic population dynamics model for interacting African bee colony and Varroa mite populations. Cumulant truncation procedures are used to obtain approximate transient cumulant functions, unconstrained by the usual assumption of bivariate Normality, for an assumed large-scale model. The apparent size of the variance and skewness functions suggest the importance of the proposed truncation procedure which retains some higher-order cumulants, but determining the accuracy of the approximations is problematical. A smaller-scale bee/Varroa mite model is hence proposed and investigated. The accuracy for the means is exceptional, for the second-order cumulants is moderate, and for some third-order cumulants is poor. Notwithstanding the poor accuracy of a skewness approximation, the saddlepoint approximations for the marginal transient population size distributions are excellent. The cumulant truncation methodology is very general, and research is continuing in its application to this new class of host-parasite models.