Young, Old, and Weathered Carbon—Part 2: Using Radiocarbon and Stable Isotopes to Identify Terrestrial Carbon Support of the Food Web in an Alkaline, Humic Lake

Carbon (C) and nitrogen (N) stable isotope analysis (SIA) has been used to identify the terrestrial subsidy of freshwater food webs. However, SIA fails to differentiate between the contributions of old and recently fixed terrestrial C and consequently cannot fully determine the source, age, and biochemical quality of terrestrial carbon. Natural abundance radiocarbon (∆14C) was used to examine the age and origin of carbon in Lower Lough Erne, Northern Ireland. 14C and stable isotope values were obtained from invertebrate, algae, and fish samples, and the results indicate that terrestrial organic C is evident at all trophic levels. High winter δ15N values in calanoid zooplankton (δ15N = 24‰) relative to phytoplankton and particulate organic matter (δ15N = 6‰ and 12‰, respectively) may reflect several microbial trophic levels between terrestrial C and calanoid invertebrates. Winter and summer calanoid ∆14C values show a seasonal switch between autochthonous and terrestrial carbon sources. Fish ∆14C values indicate terrestrial support at the highest trophic levels in littoral and pelagic food webs. 14C therefore is useful in attributing the source of carbon in freshwater in addition to tracing the pathway of terrestrial carbon through the food web.

GeneGrid: Architecture, Implementation and Application

The emergence of Grid computing technology has opened up an unprecedented opportunity for biologists to share and access data, resources and tools in an integrated environment leading to a greater chance of knowledge discovery. GeneGrid is a Grid computing framework that seamlessly integrates a myriad of heterogeneous resources spanning multiple administrative domains and locations. It provides scientists an integrated environment for the streamlined access of a number of bioinformatics programs and databases through a simple and intuitive interface. It acts as a virtual bioinformatics laboratory by allowing scientists to create, execute and manage workflows that represent bioinformatics experiments. A number of cooperating Grid services interact in an orchestrated manner to provide this functionality. This paper gives insight into the details of the architecture, components and implementation of GeneGrid.

A meta-analysis of the association between Caesarean section and childhood asthma

Background: Children born by Caesarean section have modified intestinal bacterial colonization and consequently may have an increased risk of developing asthma under the hygiene hypothesis. The results of previous studies that have investigated the association between Caesarean section and asthma have been conflicting.

Objective: To review published literature and perform a meta-analysis summarizing the evidence in support of an association between children born by Caesarean section and asthma.

Methods: MEDLINE, Web Science, Google Scholar and PubMed were searched to identify relevant studies. Odds ratio (OR) and 95% confidence interval (CI) were calculated for each study from the reported prevalence of asthma in children born by Caesarean section and in control children. Meta-analysis was then used to derive a combined OR and test for heterogeneity in the findings between studies.

Results: Twenty-three studies were identified. The overall meta-analysis revealed an increase in the risk of asthma in children delivered by Caesarean section (OR=1.22, 95% CI 1.14, 1.29). However, in this analysis, there was evidence of heterogeneity (I2=46%) that was statistically significant (P<0.001). Restricting the analysis to childhood studies, this heterogeneity was markedly decreased (I2=32%) and no longer attained statistical significance (P=0.08). In these studies, there was also evidence of an increase (P<0.001) in the risk of asthma after Caesarean section (OR=1.20, 95% CI 1.14, 12.6).

Conclusion: In this meta-analysis, we found a 20% increase in the subsequent risk of asthma in children who had been delivered by Caesarean section.

The Movebank data model for animal tracking

Studies of animal movement are rapidly increasing as tracking technologies make it possible to collect more data of a larger variety of species. Comparisons of animal movement across sites, times, or species are key to asking questions about animal adaptation, responses to climate and land-use change. Thus, great gains can be made by sharing and exchanging animal tracking data. Here we present an animal movement data model that we use within the Movebank web application to describe tracked animals. The model facilitates data comparisons across a broad range of taxa, study designs, and technologies, and is based on the scientific questions that could be addressed with the data.

An on-line application for ΔR calculation

A regional offset (ΔR) from the marine radiocarbon calibration curve is widely used in calibration software (eg CALIB, OxCal) but often is not calculated correctly. While relatively straightforward for known age samples, such as mollusks from museum collections or banded corals, it is more difficult to calculate ΔR and the uncertainty in ΔR for 14C dates on paired marine and terrestrial samples. Previous researchers have often utilized classical intercept methods (Reimer et al. 2002; Dewar et al. 2012, Russell et al. 2011) but this does not account for the full calibrated probability density function (PDF). We have developed an on-line application for performing these calculations for known age, paired marine and terrestrial 14C dates, or U-Th dated corals which is available at http://calib.qub.ac.uk/deltar

Directional genetic differentiation and relative migration

Understanding the population structure and patterns of gene flow within species is of fundamental importance to the study of evolution. In the fields of population and evolutionary genetics, measures of genetic differentiation are commonly used to gather this information. One potential caveat is that these measures assume gene flow to be symmetric. However, asymmetric gene flow is common in nature, especially in systems driven by physical processes such as wind or water currents. As information about levels of asymmetric gene flow among populations is essential for the correct interpretation of the distribution of contemporary genetic diversity within species, this should not be overlooked. To obtain information on asymmetric migration patterns from genetic data, complex models based on maximum-likelihood or Bayesian approaches generally need to be employed, often at great computational cost. Here, a new simpler and more efficient approach for understanding gene flow patterns is presented. This approach allows the estimation of directional components of genetic divergence between pairs of populations at low computational effort, using any of the classical or modern measures of genetic differentiation. These directional measures of genetic differentiation can further be used to calculate directional relative migration and to detect asymmetries in gene flow patterns. This can be done in a user-friendly web application called divMigrate-online introduced in this study. Using simulated data sets with known gene flow regimes, we demonstrate that the method is capable of resolving complex migration patterns under a range of study designs.