Insect herbivory in an experimental agroecosystem: the relative importance of habitat area, fragmentation, and the matrix

Habitat area, fragmentation, and the surrounding matrix influence levels of herbivory in various ecosystems, but the relative importance of these effects has rarely been assessed. We compared levels of herbivory and densities of dominant arthropod herbivores (the hemipteran insects Agallia constricta, Empoasca fabae, Therioaphis trifolii, Lygus lineolaris and Halticus bractatus ) among experimental plots that varied in the area and fragmentation of clover habitat and the composition of the matrix (bare ground or grass) surrounding clover habitat. To assess levels of herbivory, we compared clover biomass within herbivore exclosures to the biomass accessible to herbivores. The area and fragmentation of clover habitat, as well as matrix composition, significantly influenced the collective densities of herbivores, although each species exhibited unique responses to habitat structure. Herbivory was strongest in plots with large (64  m²) as compared to small (16  m²) amounts of clover habitat. The difference in clover biomass between the inside and outside of exclosures increased significantly with increasing density of Empoasca fabae but was unrelated to the densities of the other herbivores, suggesting that Empoasca fabae was an exceptionally important herbivore in this system. This study supports the view that herbivore densities and herbivory generally increase with increasing area of plant monocultures, but emphasizes that levels of herbivory may be driven primarily by one or a few key herbivore species.     

Predator interference alters foraging behavior of a generalist predatory arthropod

Interactions between predators foraging in the same patch may strongly influence patch use and functional response. In particular, there is continued interest in how the magnitude of mutual interference shapes predator–prey interactions. Studies commonly focus on either patch use or the functional response without attempting to link these important components of the foraging puzzle. Predictions from both theoretical frameworks suggest that predators should modify foraging efforts in response to changes in feeding rate, but this prediction has received little empirical attention. We study the linkage between patch departure rates and food consumption by the hunting spider, Pardosa milvina, using field enclosures in which prey and predator densities were manipulated. Additionally, the most appropriate functional response model was identified by fitting alternative functional response models to laboratory foraging data. Our results show that although prey availability was the most important determinant of patch departure rates, a greater proportion of predators left enclosures containing elevated predator abundance. Functional response parameter estimation revealed significant levels of interference among predators leading to lower feeding rates even when the area allocated for each predator was kept constant. These results suggest that feeding rates determine patch movement dynamics, where interference induces predators to search for foraging sites that balance the frequency of agonistic interactions with prey encounter rates.     

Selfhood, Immunity, and the Biological Imagination: The Thought of Frank Macfarlane Burnet

The language of self and nonself has had a prominent place inimmunology. This paper examines Frank Macfarlane Burnet's introductionof the language of selfhood into the science. The distinction betweenself and nonself was an integral part of Burnet's biological outlook– of his interest in the living organism in its totality, itsactivities, and interactions. We show the empirical and conceptualwork of the language of selfhood in the science. The relation betweenself and nonself tied into Burnet's ecological vision of host-parasiteinteraction. The idiom of selfhood also enabled Burnet to organizeand unify a diversity of immune phenomena. Rather than approach thelanguage of self and nonself as a bluntly imposed metaphor, we focuson its endogenous origins and immanent uses in immunology.     

Up-regulation of neuropeptide Y levels and modulation of glutamate release through neuropeptide Y receptors in the hippocampus of kainate-induced epileptic rats

Kainate-induced epilepsy has been shown to be associated with increased levels of neuropeptide Y (NPY) in the rat hippocampus. However, there is no information on how increased levels of this peptide might modulate excitation in kainate-induced epilepsy. In this work, we investigated the modulation of glutamate release by NPY receptors in hippocampal synaptosomes isolated from epileptic rats. In the acute phase of epilepsy, a transient decrease in the efficiency of NPY and selective NPY receptor agonists in inhibiting glutamate release was observed. Moreover, in the chronic epileptic hippocampus, a decrease in the efficiency of NPY and the Y(2) receptor agonist, NPY13-36, was also found. Simultaneously, we observed that the epileptic hippocampus expresses higher levels of NPY, which may account for an increased basal inhibition of glutamate release. Consistently, the blockade of Y(2) receptors increased KCl-evoked glutamate release, and there was an increase in Y(2) receptor mRNA levels 30 days after kainic acid injection, suggesting a basal effect of NPY through Y(2) receptors. Taken together, these results indicate that an increased function of the NPY modulatory system in the epileptic hippocampus may contribute to basal inhibition of glutamate release and control hyperexcitability.     

Correlation Networks from Flows. The Case of Forced and Time-Dependent Advection-Diffusion Dynamics

Complex network theory provides an elegant and powerful framework to statistically investigate different types of systems such as society, brain or the structure of local and long-range dynamical interrelationships in the climate system. Network links in climate networks typically imply information, mass or energy exchange. However, the specific connection between oceanic or atmospheric flows and the climate network’s structure is still unclear. We propose a theoretical approach for verifying relations between the correlation matrix and the climate network measures, generalizing previous studies and overcoming the restriction to stationary flows. Our methods are developed for correlations of a scalar quantity (temperature, for example) which satisfies an advection-diffusion dynamics in the presence of forcing and dissipation. Our approach reveals that correlation networks are not sensitive to steady sources and sinks and the profound impact of the signal decay rate on the network topology. We illustrate our results with calculations of degree and clustering for a meandering flow resembling a geophysical ocean jet.