Owing to the present global biodiversity crisis, the biodiversity-stability relationship and the effect of biodiversity on ecosystem functioning have become major topics in ecology. Biodiversity is a complex term that includes taxonomic, functional, spatial and temporal aspects of organismic diversity, with species richness (the number of species) and evenness (the relative abundance of species) considered among the most important measures. With few exceptions (see, for example, ref. 6), the majority of studies of biodiversity-functioning and biodiversity-stability theory have predominantly examined richness. Here we show, using microbial microcosms, that initial community evenness is a key factor in preserving the functional stability of an ecosystem. Using experimental manipulations of both richness and initial evenness in microcosms with denitrifying bacterial communities, we found that the stability of the net ecosystem denitrification in the face of salinity stress was strongly influenced by the initial evenness of the community. Therefore, when communities are highly uneven, or there is extreme dominance by one or a few species, their functioning is less resistant to environmental stress. Further unravelling how evenness influences ecosystem processes in natural and humanized environments constitutes a major future conceptual challenge.

Due to its well-defined genome, the fruitfly Drosophila melanogaster has become a very important model organism in olfactory research. Despite all the research invested, few natural odour ligands have been identified. By using a combined gas chromatographic-single receptor neurone recording technique (GC-SC), we set out to identify active odour molecules in head space-collected volatiles from preferred food sources, i.e. different overripe or rotting fruit. In total, we performed 101 GC-SC experiments on 85 contacted sensilla. Using GC-mass spectrometry, we identified 24 active compounds. Synthetic samples of these compounds were used to establish dose-response curves for several of the receptor neurone types encountered. The response patterns of individual neurones were repeatable, and neurones were found to reside in stereotyped pairs. In total, we identified eight distinct sensillum types based on response profiles of 12 olfactory receptor neurone types. In most recordings, a single GC peak would produce a strong response, whereas a few other, often chemically related, compounds would produce weaker responses. The GC-SC recordings revealed that the olfactory receptor neurones investigated were often selective and could be divided into distinct functional types with discrete characteristics. Dose-response investigations revealed very low response thresholds to the tested compounds. Six of the novel ligands were also tested for their behavioural effect in a T-maze set up. Of these, five elicited attraction and one elicited repulsion.

Since a few decades, apiculture is facing important economic losses worldwide with general major consequences in many areas of agriculture. A strong attention has been paid towards the phenomenon named Colony Collapse Disorder in which colonies suddenly disappear with no clear explanations. Honeybee colonies can be affected by abiotic factors, such as environmental pollution or insecticide applications for agricultural purposes. Also biotic stresses cause colony losses, including bacterial (e.g. Paenibacillus larvae) and fungal (e.g. Ascosphaera apis) pathogens, microsporidia (e.g. Nosema apis), parasites (i.e. Varroa destructor) and several viruses. In the light of recent research, intestinal dysbiosis, considered as the relative disproportion of the species within the native microbiota, has shown to affect human and animal health. In arthropods, alteration of the gut microbial climax community has been shown to be linked to health and fitness disequilibrium, like in the medfly Ceratitis capitata for which low mate competitiveness is determined by a gut microbial community imbalance. According to these observations, it is possible to hypothesize that dysbiosis may have a role in disease occurrence also in honeybees. Here we aim to discuss the current knowledge on dysbiosis in the honeybee and its relation with honeybee health by reviewing the investigations of the microbial diversity associated to honeybees and the recent experiments performed to control bee diseases by microbial symbionts. We conclude that, despite the importance of a good functionality of the associated microbiota in preserving insect health has been proved, the mechanisms involved in honeybee gut dysbiosis are still unknown. Accurate in vitro, in vivo and in field investigations are required under healthy, diseased and stressed conditions for the host.

SummaryMicroorganisms establish with their animal hosts close interactions. They are involved in many aspects of the host life, physiology and evolution, including nutrition, reproduction, immune homeostasis, defence and speciation. Thus, the manipulation and the exploitation the microbiota could result in important practical applications for the development of strategies for the management of insect‐related problems. This approach, defined as ‘Microbial Resource Management’ (MRM), has been applied successfully in various environments and ecosystems, as wastewater treatments, prebiotics in humans, anaerobic digestion and so on. MRM foresees the proper management of the microbial resource present in a given ecosystem in order to solve practical problems through the use of microorganisms. In this review we present an interesting field for application for MRM concept, i.e. the microbial communities associated with arthropods and nematodes. Several examples related to this field of applications are presented. Insect microbiota can be manipulated: (i) to control insect pests for agriculture; (ii) to control pathogens transmitted by insects to humans, animals and plants; (iii) to protect beneficial insects from diseases and stresses. Besides, we prospect further studies aimed to verify, improve and apply MRM by using the insect–symbiont ecosystem as a model.