Host location in Oomyzus gallerucae (Hymenoptera: Eulophidae), an egg parasitoid of the elm leaf beetle Xanthogaleruca luteola (Coleoptera: Chrysomelidae)

Eggs of the elm leaf beetle Xanthogaleruca luteola are often heavily attacked by the chalcidoid wasp Oomyzus gallerucae. We studied the chemical signals mediating interactions between the egg parasitoid, its host, and the plant Ulmus campestris. Olfactometer bioassays with O. gallerucae showed that volatiles of the host-plant complex attract the parasitoid. In order to determine the source of attractive volatiles within this host-plant-complex, we tested separately the effect of odours of eggs, gravid elm leaf beetle females, faeces of the beetles and elm twigs (with undamaged leaves and leaves damaged either mechanically or by feeding of the beetles). Odours of faeces of the elm leaf beetle were attractive, whereas neither volatiles from eggs nor from gravid females acted as attractants. Volatiles from undamaged or damaged plants did not elicit a positive reaction in O. gallerucae, whereas volatiles from feeding-damaged plants onto which host eggs had been deposited were attractive. This latter result suggests that it is not feeding but deposition of host eggs onto elm leaves that induces the production of plant volatiles attractive to the egg parasitoid. Investigations of the search patterns of O. gallerucae within the habitat by laboratory bioassays revealed that the egg parasitoid encounters host eggs by chance. Contact kairomones from faeces were demonstrated to be important in microhabitat acceptance, while contact kairomones isolated from the host eggs are relevant for host recognition. Received: 12 February 1997 / Accepted: 29 April 1997     

Nervous system development in the fairy shrimp Branchinella sp. (Crustacea: Branchiopoda: Anostraca): Insights into the development and evolution of the branchiopod brain and its sensory organs

Using immunohistochemical labeling against acetylated a‐tubulin and serotonin in combination with confocal laser scanning microscopy and 3D‐reconstruction, we investigated the temporary freshwater pond inhabitant Branchinella sp. (Crustacea: Branchiopoda: Anostraca) for the first time to provide detailed data on the development of the anostracan nervous system. Protocerebral sense organs such as the nauplius eye and frontal filament organs are present as early as the hatching stage L0. In the postnaupliar region, two terminal pioneer neurons grow from posterior to anterior to connect the mandibular neuromeres. The first protocerebral neuropil to emerge is not part of the central complex but represents the median neuropil, and begins to develop from L0+ onwards. In stage L3, the first evidence of developing compound eyes is visible. This is followed by the formation of the visual neuropils and the neuropils of the central complex in the protocerebrum. From the deutocerebral lobes, the projecting neuron tract proceeds to both sides of the lateral protocerebrum, forming a chiasma just behind the central body. In the postnaupliar region, the peripheral nervous system, commissures and connectives develop along an anterior–posterior gradient after the fasciculation of the terminal pioneer neurons with the mandibular neuromere. The peripheral nervous system in the thoracic segments consists of two longitudinal neurite bundles on each side which connect the intersegmental nerves, together with the ventral nervous system forming an orthogon‐like network. Here, we discuss, among other things, the evidence of a fourth nauplius eye nerve and decussating projecting neuron tract found in Branchinella sp., and provide arguments to support our view that the crustacean frontal filament (organ) and onychophoran primary antenna are homologous. J. Morphol. 277:1423–1446, 2016. © 2016 Wiley Periodicals, Inc.     

Characteristics of neuronal systems in the visual cortex

The coupling complexity of cortical areas makes it very difficult to analyse them experimentally. Studies of model systems provide the possibility of adapting the analysis to the available data base and elaborating the fundamental properties that depend on the structure of the system. We propose a model system of variable complexity that is spatially two-dimensional and time-dependent, uses feedback for iteration and smoothing, includes the mapping of the cortical networks and can be nonlinear as the case requires. Combining such elementary systems on the basis of neuroanatomical findings enables us to simulate cortical mappings and to interpret neurophysiological data. The decisive factor is that the dynamics of the system and the neuroanatomically based spatial coupling are closely connected with each other.