997 resultados para queenless ant colonies


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Nest site selection in arboreal, domatia-dwelling ants, particularly those coexisting on a single host plant, is little understood. To examine this phenomenon we studied the African savannah tree Vachellia erioloba, which hosts ants in swollen-thorn domatia. We found four ant species from different genera (Cataulacus intrudens, Tapinoma subtile, Tetraponera ambigua and an unidentified Crematogaster species). In contrast to other African ant plants, many V. erioloba trees (41 % in our survey) were simultaneously co-occupied by more than one ant species. Our study provides quantitative field data describing: (1) aspects of tree and domatia morphology relevant to supporting a community of mutualist ants, (2) how ant species occupancy varies with domatia morphology and (3) how ant colony size varies with domatia size and species. We found that Crematogaster sp. occupy the largest thorns, followed by C. intrudens, with T. subtile in the smallest thorns. Thorn age, as well as nest entrance hole size correlated closely with ant species occupant. These differing occupancy patterns may help to explain the unusual coexistence of three ant species on individual myrmecophytic trees. In all three common ant species, colony size, as measured by total number of ants, increased with domatia size. Additionally, domatia volume and species identity interact to predict ant numbers, suggesting differing responses between species to increased availability of nesting space. The proportion of total ants in nests that were immatures varied with thorn volume and species, highlighting the importance of domatia morphology in influencing colony structure.

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Namibia has high levels of invertebrate endemism, but biodiversity research has been geographically and taxonomically limited. In South African savannah, species richness of ground-foraging ant assemblages is regulated by dominant ant species, but this pattern has not been tested in other arid environments. In this study, we provide a description of ant diversity at baits in three different Namibian habitats (savannah, saltpan and desert), and we test the relationship between ant dominance and richness for ground-foraging and arboreal species. Forty-two ant species were collected in this study, with species richness being highest in the saltpan, followed by savannah and then desert. Ant assemblages were most similar between the savannah and desert, due to shared arboreal species. Similarity between savannah and saltpan ant assemblages was due to an overlap in ground-foraging species. Ground ants were more diverse than arboreal ants, and several species were observed at baits for both strata, although the degree of overlap varied with habitat type. The dominance-richness relationship varied depending on habitat and sampling strata. We found a unimodal relationship in the saltpan, but not in the savannah. For ground ants the relationship was logarithmic, with increasing abundance of dominants leading to decreasing overall species richness. However, no trend was observed for the arboreal ant assemblage. In the desert, low ant abundance meant that we were unable to assign species dominance, possibly due to reduced foraging activity caused by high temperatures. The lack of a consistent dominance-richness trend across assemblages may be the result of varying degrees of environmental stress or competition. Our study is a preliminary description of diversity and dominance in Namibia, and we hope it stimulates further research on ant assemblages in arid regions of Africa.

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Over the past 50 years, many millions of European honey bee (Apis mellifera) colonies have died as the ectoparasitic mite, Varroa destructor, has spread around the world. Subsequent studies have indicated that the mite's association with a group of RNA viral pathogens (Deformed Wing Virus, DWV) correlates with colony death. Here, we propose a phenomenon known as superinfection exclusion that provides an explanation of how certain A. mellifera populations have survived, despite Varroa infestation and high DWV loads. Next-generation sequencing has shown that a non-lethal DWV variant 'type B' has become established in these colonies and that the lethal 'type A' DWV variant fails to persist in the bee population. We propose that this novel stable host-pathogen relationship prevents the accumulation of lethal variants, suggesting that this interaction could be exploited for the development of an effective treatment that minimises colony losses in the future.The ISME Journal advance online publication, 27 October 2015; doi:10.1038/ismej.2015.186.

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With the fast development of wireless communications, ZigBee and semiconductor devices, home automation networks have recently become very popular. Since typical consumer products deployed in home automation networks are often powered by tiny and limited batteries, one of the most challenging research issues is concerning energy reduction and the balancing of energy consumption across the network in order to prolong the home network lifetime for consumer devices. The introduction of clustering and sink mobility techniques into home automation networks have been shown to be an efficient way to improve the network performance and have received significant research attention. Taking inspiration from nature, this paper proposes an Ant Colony Optimization (ACO) based clustering algorithm specifically with mobile sink support for home automation networks. In this work, the network is divided into several clusters and cluster heads are selected within each cluster. Then, a mobile sink communicates with each cluster head to collect data directly through short range communications. The ACO algorithm has been utilized in this work in order to find the optimal mobility trajectory for the mobile sink. Extensive simulation results from this research show that the proposed algorithm significantly improves home network performance when using mobile sinks in terms of energy consumption and network lifetime as compared to other routing algorithms currently deployed for home automation networks.

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In this study, the ovary morphology of newly emerged ant queens of Atta sexdens rubropilosa was studied in whole mount preparations by confocal microscopy. The ovaries are composed of approximately 40 ovarioles, showing non-synchronic oocyte maturation. The terminal filament with clusters of undifferentiated cells was found at the distal end of the ovarioles. Next to this region is the germarium, composed of several elongated cystocytes interconnected by cytoplasmic bridges. The nurse cells (23-28 cells) result from asymmetric mitosis. Cytoskeleton analysis showed F-actin concentrated at the muscle cells of the external tunica and in fusomes inside the ovarioles. Microtubules were concentrated around the nuclei of the nurse and follicular cells. In contrast, the oocytes and the external tunica showed faint staining for tubulin.

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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.

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The aim of this work is to investigate Ant Colony Algorithm for the traveling salesman problem (TSP). Ants of the artificial colony are able to generate successively shorter feasible tours by using information accumulated in the form of a pheromone trail deposited on the edges of the TSP graph. This paper is based on the ideas of ant colony algorithm and analysis the main parameters of the ant colony algorithm. Experimental results for solving TSP problems with ant colony algorithm show great effectiveness.