The effects of diesel exhaust pollution on floral volatiles and the consequences for honey bee olfaction

There is growing evidence of a substantial decline in pollinators within Europe and North America, most likely caused by multiple factors such as diseases, poor nutrition, habitat loss, insecticides, and environmental pollution. Diesel exhaust could be a contributing factor to this decline, since we found that diesel exhaust rapidly degrades floral volatiles, which honey bees require for flower recognition. In this study, we exposed eight of the most common floral volatiles to diesel exhaust in order to investigate whether it can affect volatile mediated plant-pollinator interaction. Exposure to diesel exhaust altered the blend of common flower volatiles significantly: myrcene was considerably reduced, β-ocimene became undetectable, and β-caryophyllene was transformed into its cis-isomer isocaryophyllene. Proboscis extension response (PER) assays showed that the alterations of the blend reduced the ability of honey bees to recognize it. The chemically reactive nitrogen oxides fraction of diesel exhaust gas was identified as capable of causing degradation of floral volatiles.

Testing projected wild bee distributions in agricultural habitats: predictive power depends on species traits and habitat type

Species distribution models (SDM) are increasingly used to understand the factors that regulate variation in biodiversity patterns and to help plan conservation strategies. However, these models are rarely validated with independently collected data and it is unclear whether SDM performance is maintained across distinct habitats and for species with different functional traits. Highly mobile species, such as bees, can be particularly challenging to model. Here, we use independent sets of occurrence data collected systematically in several agricultural habitats to test how the predictive performance of SDMs for wild bee species depends on species traits, habitat type, and sampling technique. We used a species distribution modeling approach parametrized for the Netherlands, with presence records from 1990 to 2010 for 193 Dutch wild bees. For each species, we built a Maxent model based on 13 climate and landscape variables. We tested the predictive performance of the SDMs with independent datasets collected from orchards and arable fields across the Netherlands from 2010 to 2013, using transect surveys or pan traps. Model predictive performance depended on species traits and habitat type. Occurrence of bee species specialized in habitat and diet was better predicted than generalist bees. Predictions of habitat suitability were also more precise for habitats that are temporally more stable (orchards) than for habitats that suffer regular alterations (arable), particularly for small, solitary bees. As a conservation tool, SDMs are best suited to modeling rarer, specialist species than more generalist and will work best in long-term stable habitats. The variability of complex, short-term habitats is difficult to capture in such models and historical land use generally has low thematic resolution. To improve SDMs’ usefulness, models require explanatory variables and collection data that include detailed landscape characteristics, for example, variability of crops and flower availability. Additionally, testing SDMs with field surveys should involve multiple collection techniques.

Diversity in a honey bee pathogen: first report of a third master variant of the Deformed Wing Virus quasispecies

Treatment of emerging RNA viruses is hampered by the high mutation and replication rates that enable these viruses to operate as a quasispecies. Declining honey bee populations have been attributed to the ectoparasitic mite Varroa destructor and its affiliation with Deformed Wing Virus (DWV). In the current study we use next-generation sequencing to investigate the DWV quasispecies in an apiary known to suffer from overwintering colony losses. We show that the DWV species complex is made up of three master variants. Our results indicate that a new DWV Type C variant is distinct from the previously described types A and B, but together they form a distinct clade compared with other members of the Iflaviridae. The molecular clock estimation predicts that Type C diverged from the other variants ~319 years ago. The discovery of a new master variant of DWV has important implications for the positive identification of the true pathogen within global honey bee populations.

Non-bee insects are important contributors to global crop pollination

Wild and managed bees are well documented as effective pollinators of global crops of economic importance. However, the contributions by pollinators other than bees have been little explored despite their potential to contribute to crop production and stability in the face of environmental change. Non-bee pollinators include flies, beetles, moths, butterflies, wasps, ants, birds, and bats, among others. Here we focus on non-bee insects and synthesize 39 field studies from five continents that directly measured the crop pollination services provided by non-bees, honey bees, and other bees to compare the relative contributions of these taxa. Non-bees performed 25–50% of the total number of flower visits. Although non-bees were less effective pollinators than bees per flower visit, they made more visits; thus these two factors compensated for each other, resulting in pollination services rendered by non-bees that were similar to those provided by bees. In the subset of studies that measured fruit set, fruit set increased with non-bee insect visits independently of bee visitation rates, indicating that non-bee insects provide a unique benefit that is not provided by bees. We also show that non-bee insects are not as reliant as bees on the presence of remnant natural or seminatural habitat in the surrounding landscape. These results strongly suggest that non-bee insect pollinators play a significant role in global crop production and respond differently than bees to landscape structure, probably making their crop pollination services more robust to changes in land use. Non-bee insects provide a valuable service and provide potential insurance against bee population declines.

High-throughput monitoring of wild bee diversity and abundance via mitogenomics

1. Bee populations and other pollinators face multiple, synergistically acting threats, which have led to population declines, loss of local species richness and pollination services, and extinctions. However, our understanding of the degree, distribution and causes of declines is patchy, in part due to inadequate monitoring systems, with the challenge of taxonomic identification posing a major logistical barrier. Pollinator conservation would benefit from a high-throughput identification pipeline. 2. We show that the metagenomic mining and resequencing of mitochondrial genomes (mitogenomics) can be applied successfully to bulk samples of wild bees. We assembled the mitogenomes of 48 UK bee species and then shotgun-sequenced total DNA extracted from 204 whole bees that had been collected in 10 pan-trap samples from farms in England and been identified morphologically to 33 species. Each sample data set was mapped against the 48 reference mitogenomes. 3. The morphological and mitogenomic data sets were highly congruent. Out of 63 total species detections in the morphological data set, the mitogenomic data set made 59 correct detections (93�7% detection rate) and detected six more species (putative false positives). Direct inspection and an analysis with species-specific primers suggested that these putative false positives were most likely due to incorrect morphological IDs. Read frequency significantly predicted species biomass frequency (R2 = 24�9%). Species lists, biomass frequencies, extrapolated species richness and community structure were recovered with less error than in a metabarcoding pipeline. 4. Mitogenomics automates the onerous task of taxonomic identification, even for cryptic species, allowing the tracking of changes in species richness and istributions. A mitogenomic pipeline should thus be able to contain costs, maintain consistently high-quality data over long time series, incorporate retrospective taxonomic revisions and provide an auditable evidence trail. Mitogenomic data sets also provide estimates of species counts within samples and thus have potential for tracking population trajectories.

Comparative study in stingless bees (Meliponini) demonstrates that nest entrance size predicts traffic and defensivity

Stingless bees (Meliponini) construct their own species-specific nest entrance. The size of this entrance is under conflicting selective pressures. Smaller entrances are easier to defend; however, a larger entrance accommodates heavier forager traffic. Using a comparative approach with 26 species of stingless bees, we show that species with greater foraging traffic have significantly larger entrances. Such a strong correlation between relative entrance area and traffic across the different species strongly suggests a trade-off between traffic and security. Additionally, we report on a significant trend for higher forager traffic to be associated with more guards and for those guards to be more aggressive. Finally, we discuss the nest entrance of Partamona, known in Brazil as boca de sapo, or toad mouth, which has a wide outer entrance but a narrow inner entrance. This extraordinary design allows these bees to finesse the defensivity/traffic trade-off.

Mitochondrial DNA Diversity of Orchid Bee Euglossa fimbriata (Hymenoptera: Apidae) Populations Assessed by PCR-RFLP

Euglossa fimbriata is a euglossine species widely distributed in Brazil and occurring primarily in Atlantic Forest remnants. In this study, the genetic mitochondrial structure of E. fimbriata from six Atlantic Forest fragments was studied by RFLP analysis of three PCR-amplified mtDNA gene segments (16S, COI-COII, and cyt b). Ten composite haplotypes were identified, six of which were exclusive and represented singleton mitotypes. Low haplotype diversity (0.085-0.289) and nucleotide diversity (0.000-0.002) were detected within samples. AMOVA partitioned 91.13% of the overall genetic variation within samples and 8.87% (I center dot(st) = 0.089; P < 0.05) among samples. Pairwise comparisons indicated high levels of differentiation among some pairs of samples (I center dot(st) = 0.161-0.218; P < 0.05). These high levels indicate that these populations of E. fimbriata, despite their highly fragmented landscape, apparently have not suffered loss of genetic variation, suggesting that this particular population is not currently endangered.

Genetic structure of Partamona helleri (Apidae, Meliponini) from Neotropical Atlantic rainforest

Stingless bees of the genus Partamona are distributed from southern Mexico to southern Brazil. This genus has been subject to different approaches to solve questions concerning general biology, taxonomy, systematics and biogeography, but population studies applying molecular techniques are inexistent. We analyzed the genetic structure of P. helleri across its geographic distribution along the coastal Atlantic tropical rainforest in Brazil. Ten mtDNA haplotypes were observed in 47 colonies of P. helleri of which some were exclusive and others shared among geographic sub-groups. Statistical analysis showed high genetic differentiation between geographic areas sampled. Fragmentation of the Atlantic forest during Pleistocene glaciations is discussed as a possible cause of the present haplotype distribution and frequency.

New species of the bee genus Augochlorodes Moure (Hymenoptera, Apidae s. I., Halictinae)

Five new species of the bee genus Augochlorodes from Brazil are described and the type species, A. turrifaciens Moure, 1958, is redescribed. The new species are: A. clementis sp. nov. (from the states of Parana, Santa Catarina and Rio Grande do Sul), A. incomitatus sp. nov. (Rio Grande do Sul), A. politus sp. nov. (Parana), A. rostratus sp. nov. (Rio Grande do Sul) and A. vachali sp. nov. (Parana, Santa Catarina, Sao Paulo). A discriminant function analysis using head measurements is presented to help distinguish the species. An identification key for the species is provided.

Design of a Modern Liposome and Bee Venom Formulation for the Traditional VIT-Venom Immunotherapy

Traditional venom immunotherapy uses injections of whole bee venom in buffer or adsorbed in Al (OH)(3) in an expensive, time-consuming way. New strategies to improve the safety and efficacy of this treatment with a reduction of injections would, therefore, be of general interest. It would improve patient compliance and provide socio-economic benefits. Liposomes have a long tradition in drug delivery because they increase the therapeutic index and avoid drug degradation and secondary effects. However, bee venom melittin (Mel) and phospholipase (PLA(2)) destroy the phospholipid membranes. Our central idea was to inhibit the PLA(2) and Mel activities through histidine alkylation and or tryptophan oxidation (with pbb, para-bromo-phenacyl bromide, and/or NBSN-bromosuccinimide, respectively) to make their encapsulations possible within stabilized liposomes. We strongly believe that this formulation will be nontoxic but immunogenic. In this paper, we present the whole bee venom conformation characterization during and after chemical modification and after interaction with liposome by ultraviolet, circular dichroism, and fluorescence spectroscopies. The PLA(2) and Mel activities were, measured indirectly by changes in turbidity at 400(nm), rhodamine leak-out, and hemolysis. The native whole bee venom (BV) presented 78.06% of alpha-helical content. The alkylation (A-BV) and succynilation (S-BV) of BV increased 0.44 and 0.20% of its alpha-helical content. The double-modified venom (S-A-BV) had a 0.74% increase of alpha-helical content. The BV chemical modification induced another change on protein conformations observed by Trp that became buried with respect to the native whole BV. It was demonstrated that the liposomal membranes must contain pbb (SPC:Cho:pbb, 26:7:1) as a component to protect them from aggregation and/or fusion. The membranes containing pbb maintained the same turbidity (100%) after incubation with modified venom, in contrast with pbb-free membranes that showed a 15% size decrease. This size decrease was interpreted as membrane degradation and was corroborated by a 50% rhodamine leak-out. Another fact that confirmed our interpretation was the observed 100% inhibition of the hemolytic activity after venom modification with pbb and NBS (S-A-BV). When S-A-BV interacted with liposomes, other protein conformational changes were observed and characterized by the increase of 1.93% on S-A-BV alpha-helical content and the presence of tryptophan residues in a more hydrophobic environment. In other words, the S-A-BV interacted with liposomal membranes, but this interaction was not effective to cause aggregation, leak-out, or fusion. A stable formulation composed by S-A-BV encapsulated within liposomes composed by SPC:Cho:pbb, at a ratio of 26:7:1, was devised. Large unilamellar vesicles of 202.5 nm with a negative surface charge (-24.29 mV) encapsulated 95% of S-A-BV. This formulation can, now, be assayed on VIT.

BEE COLONIES APPLIED TO MULTIPROCESSOR SCHEDULING

In order to achieve the high performance, we need to have an efficient scheduling of a parallelprogram onto the processors in multiprocessor systems that minimizes the entire executiontime. This problem of multiprocessor scheduling can be stated as finding a schedule for ageneral task graph to be executed on a multiprocessor system so that the schedule length can be minimize [10]. This scheduling problem is known to be NP- Hard.In multi processor task scheduling, we have a number of CPU’s on which a number of tasksare to be scheduled that the program’s execution time is minimized. According to [10], thetasks scheduling problem is a key factor for a parallel multiprocessor system to gain betterperformance. A task can be partitioned into a group of subtasks and represented as a DAG(Directed Acyclic Graph), so the problem can be stated as finding a schedule for a DAG to beexecuted in a parallel multiprocessor system so that the schedule can be minimized. Thishelps to reduce processing time and increase processor utilization. The aim of this thesis workis to check and compare the results obtained by Bee Colony algorithm with already generatedbest known results in multi processor task scheduling domain.

An improved Gbest guided artificial bee colony (IGGABC) algorithm for classification and prediction tasks

Artificial Neural Networks (ANN) performance depends on network topology, activation function, behaviors of data, suitable synapse's values and learning algorithms. Many existing works used different learning algorithms to train ANN for getting high performance. Artificial Bee Colony (ABC) algorithm is one of the latest successfully Swarm Intelligence based technique for training Multilayer Perceptron (MLP). Normally Gbest Guided Artificial Bee Colony (GGABC) algorithm has strong exploitation process for solving mathematical problems, however the poor exploration creates problems like slow convergence and trapping in local minima. In this paper, the Improved Gbest Guided Artificial Bee Colony (IGGABC) algorithm is proposed for finding global optima. The proposed IGGABC algorithm has strong exploitation and exploration processes. The experimental results show that IGGABC algorithm performs better than that standard GGABC, BP and ABC algorithms for Boolean data classification and time-series prediction tasks.

Africanized honey bee (Apis mellifera) venom profiling: Seasonal variation of melittin and phospholipase A(2) levels

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Bee communities (Hymenoptera: Anthophila) of the Cerrado ecosystem in São Paulo State, Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)