Predator foraging altitudes reveal the structure of aerial insect communities

The atmosphere is populated by a diverse array of dispersing insects and their predators. We studied aerial insect communities by tracking the foraging altitudes of an avian insectivore, the Purple Martin (Progne subis). By attaching altitude loggers to nesting Purple Martins and collecting prey delivered to their nestlings, we determined the flight altitudes of ants and other insects. We then tested hypotheses relating ant body size and reproductive ecology to flight altitude. Purple Martins flew up to 1,889 meters above ground, and nestling provisioning trips ranged up to 922 meters. Insect communities were structured by body size such that species of all sizes flew near the ground but only light insects flew to the highest altitudes. Ant maximum flight altitudes decreased by 60% from the lightest to the heaviest species. Winged sexuals of social insects (ants, honey bees, and termites) dominated the Purple Martin diet, making up 88% of prey individuals and 45% of prey biomass. By transferring energy from terrestrial to aerial food webs, mating swarms of social insects play a substantial role in aerial ecosystems. Although we focus on Purple Martins and ants, our combined logger and diet method could be applied to a range of aerial organisms.This work was funded by US NSF award IDBR-1014891 to ESB, and a US NSF Graduate Research Fellowship, OU Alumni Fellowship, OU Biological Station Graduate Summer Research Fellowship, and George Miksch Sutton Avian Research Scholarship to JAH.Ye

A New (Old), Invasive Ant in the Hardwood Forests of Eastern North America and Its Potentially Widespread Impacts

Biological invasions represent a serious threat for the conservation of biodiversity in many ecosystems. While many social insect species and in particular ant species have been introduced outside their native ranges, few species have been successful at invading temperate forests. In this study, we document for the first time the relationship between the abundance of the introduced ant, Pachycondyla chinensis, in mature forests of North Carolina and the composition, abundance and diversity of native ant species using both a matched pair approach and generalized linear models. Where present, P. chinensis was more abundant than all native species combined. The diversity and abundance of native ants in general and many individual species were negatively associated with the presence and abundance of P. chinensis. These patterns held regardless of our statistical approach and across spatial scales. Interestingly, while the majority of ant species was strongly and negatively correlated with the abundance and presence of P. chinensis, a small subset of ant species larger than P. chinensis was either as abundant or even more abundant in invaded than in uninvaded sites. The large geographic range of this ant species combined with its apparent impact on native species make it likely to have cascading consequences on eastern forests in years to come, effects mediated by the specifics of its life history which is very different from those of other invasive ants. The apparent ecological impacts of P. chinensis are in addition to public health concerns associated with this species due to its sometimes, deadly sting

Persistent ER Stress Induces the Spliced Leader RNA Silencing Pathway (SLS), Leading to Programmed Cell Death in Trypanosoma brucei

Trypanosomes are parasites that cycle between the insect host (procyclic form) and mammalian host (bloodstream form). These parasites lack conventional transcription regulation, including factors that induce the unfolded protein response (UPR). However, they possess a stress response mechanism, the spliced leader RNA silencing (SLS) pathway. SLS elicits shut-off of spliced leader RNA (SL RNA) transcription by perturbing the binding of the transcription factor tSNAP42 to its cognate promoter, thus eliminating trans-splicing of all mRNAs. Induction of endoplasmic reticulum (ER) stress in procyclic trypanosomes elicits changes in the transcriptome similar to those induced by conventional UPR found in other eukaryotes. The mechanism of up-regulation under ER stress is dependent on differential stabilization of mRNAs. The transcriptome changes are accompanied by ER dilation and elevation in the ER chaperone, BiP. Prolonged ER stress induces SLS pathway. RNAi silencing of SEC63, a factor that participates in protein translocation across the ER membrane, or SEC61, the translocation channel, also induces SLS. Silencing of these genes or prolonged ER stress led to programmed cell death (PCD), evident by exposure of phosphatidyl serine, DNA laddering, increase in reactive oxygen species (ROS) production, increase in cytoplasmic Ca2+, and decrease in mitochondrial membrane potential, as well as typical morphological changes observed by transmission electron microscopy (TEM). ER stress response is also induced in the bloodstream form and if the stress persists it leads to SLS. We propose that prolonged ER stress induces SLS, which serves as a unique death pathway, replacing the conventional caspase-mediated PCD observed in higher eukaryotes

Examining the link between price regulation and pharmaceutical R&D investment

This paper examines the link between price regulation and pharmaceutical research and development (R&D) investment. I identify two mechanisms through which price regulation may exert an influence on R&D: an expected-profit effect and a cash-flow effect. Using established models of the determinants of pharmaceutical R&D, I exploit a unique fact to quantify firm exposure to pharmaceutical price regulation: relative to the rest of the world, the U.S. pharmaceutical market is largely unregulated with respect to price. Using this fact within the context of a system of quasi-structural equations, I simulate how a new policy regulating pharmaceutical prices in the U.S. will affect R&D investment. I find that such a policy will lead to a decline in industry R&D by between 23.4 and 32.7%. This prediction, however, is accompanied by several caveats. Moreover, it says nothing about the implications for social welfare; therefore, these issues are also discussed. Copyright © 2004 John Wiley & Sons, Ltd.

Interrelationship among and repeatability of seven stability indices estimated from commercial cotton (Gossypium hirsutum L.) variety evaluation trials in three Mediterranean countries

Multi-environment trial data are required, to obtain variety stability performance parameters as selection tools for effective cultivar evaluation. The interrelationship among seven stability parameters and their association with mean yield, along with the repeatability of these parameters across consecutive years was the objective of this study. Cottonseed yield data of 31 cotton cultivars, proprietary of Delta and Pine Land Co and other companies, evaluated in 20 locations over the 1999-2005 year period in Greece, Spain and Turkey were used for combined analysis of variance in four datasets. Across locations in a single evaluation year (dataset A), across locations in each of two single consecutive evaluation year (dataset B), across locations and two consecutive years (dataset C) and across locations and three consecutive years (dataset D). For each dataset, cultivar phenotypic variance (sigma(2)(p)) was appropriately partitioned in its components and the h(2) and sigma(2)(ge) component estimated. Furthermore, following the appropriate stability analysis b(i); sd(i)(2), sigma(2)(i); YS(i) and AMMI1 along with the GGE Biplot distance (GGED) and instability (GGEIN) parameters were obtained. The interrelationship among the parameters and their association with mean yield based on Spearman rank correlation was studied in each of the seven single evaluation years (dataset A). Rank correlation coefficients were also used as estimates of the repeatability of these stability parameters across consecutive year combinations (dataset B, C and D). The parameters GGED and YS(i) were consistently highly correlated with each other and mean yield in five out of seven single evaluation years. The data provided evidence that single year evaluation across locations might be sufficient to reliably rank cotton cultivars, based on mean yield along with GGED and YS(i). Combined analysis across two consecutive years (dataset C) was more effective as compared to single year evaluation. GGED was relatively more repeatable than YS(i) and mean yield in single (dataset B) and 2-year comparisons (dataset C). Although GGED is an index depended and proportional to yield, provides a superior way to integrate mean performance and stability into a single measure, which can be assessed visually on biplots. Regarding the other stability parameters, the results were contradicting and of low repeatability across single years and two consecutive years. Cultivar evaluation combined across locations in 3 years did not improve the repeatability of cultivar variance effects but resulted in very high repeatability of GGED, YS(i) and mean yield