Climatic forcing and larval dispersal capabilities shape the replenishment of fishes and their habitat‐forming biota on a tropical coral reef

Fluctuations in marine populations often relate to the supply of recruits by oceanic currents. Variation in these currents is typically driven by large‐scale changes in climate, in particular ENSO (El Nino Southern Oscillation). The dependence on large‐scale climatic changes may, however, be modified by early life history traits of marine taxa. Based on eight years of annual surveys, along 150 km of coastline, we examined how ENSO influenced abundance of juvenile fish, coral spat, and canopy‐forming macroalgae. We then investigated what traits make populations of some fish families more reliant on the ENSO relationship than others. Abundance of juvenile fish and coral recruits was generally positively correlated with the Southern Oscillation Index (SOI), higher densities recorded during La Niña years, when the ENSO‐influenced Leeuwin Current is stronger and sea surface temperature higher. The relationship is typically positive and stronger among fish families with shorter pelagic larval durations and stronger swimming abilities. The relationship is also stronger at sites on the coral back reef, although the strongest of all relationships were among the lethrinids (r = .9), siganids (r = .9), and mullids (r = .8), which recruit to macroalgal meadows in the lagoon. ENSO effects on habitat seem to moderate SOI–juvenile abundance relationship. Macroalgal canopies are higher during La Niña years, providing more favorable habitat for juvenile fish and strengthening the SOI effect on juvenile abundance. Conversely, loss of coral following a La Niña‐related heat wave may have compromised postsettlement survival of coral dependent species, weakening the influence of SOI on their abundance. This assessment of ENSO effects on tropical fish and habitat‐forming biota and how it is mediated by functional ecology improves our ability to predict and manage changes in the replenishment of marine populations.     

Protein diffusion in crowded electrolyte solutions

We report on a combined cold neutron backscattering and spin-echo study of the short-range and long-range nanosecond diffusion of the model globular protein bovine serum albumin (BSA) in aqueous solution as a function of protein concentration and NaCl salt concentration. Complementary small angle X-ray scattering data are used to obtain information on the correlations of the proteins in solution. Particular emphasis is put on the effect of crowding, i.e. conditions under which the proteins cannot be considered as objects independent of each other. We thus address the question at which concentration this crowding starts to influence the static and in particular also the dynamical behaviour. We also briefly discuss qualitatively which charge effects, i.e. effects due to the interplay of charged molecules in an electrolyte solution, may be anticipated. Both the issue of crowding as well as that of charge effects are particularly relevant for proteins and their function under physiological conditions, where the protein volume fraction can be up to approximately 40% and salt ions are ubiquitous. The interpretation of the data is put in the context of existing studies on related systems and of existing theoretical models.     

A Financial Market Model Incorporating Herd Behaviour

Herd behaviour in financial markets is a recurring phenomenon that exacerbates asset price volatility, and is considered a possible contributor to market fragility. While numerous studies investigate herd behaviour in financial markets, it is often considered without reference to the pricing of financial instruments or other market dynamics. Here, a trader interaction model based upon informational cascades in the presence of information thresholds is used to construct a new model of asset price returns that allows for both quiescent and herd-like regimes. Agent interaction is modelled using a stochastic pulse-coupled network, parametrised by information thresholds and a network coupling probability. Agents may possess either one or two information thresholds that, in each case, determine the number of distinct states an agent may occupy before trading takes place. In the case where agents possess two thresholds (labelled as the finite state-space model, corresponding to agents’ accumulating information over a bounded state-space), and where coupling strength is maximal, an asymptotic expression for the cascade-size probability is derived and shown to follow a power law when a critical value of network coupling probability is attained. For a range of model parameters, a mixture of negative binomial distributions is used to approximate the cascade-size distribution. This approximation is subsequently used to express the volatility of model price returns in terms of the model parameter which controls the network coupling probability. In the case where agents possess a single pulse-coupling threshold (labelled as the semi-infinite state-space model corresponding to agents’ accumulating information over an unbounded state-space), numerical evidence is presented that demonstrates volatility clustering and long-memory patterns in the volatility of asset returns. Finally, output from the model is compared to both the distribution of historical stock returns and the market price of an equity index option.     

Stability and degradation of mRNA

Differential mRNA stability plays an important role in the regulation of gene expression. Several recent advances have helped to define the general pathways by which mRNA is degraded in prokaryotic cells, although many details remain to be elucidated. Much less is known about the pathways of degradation in eukaryotic cells, but recent studies on specific systems have highlighted both differences from and similarities to prokaryotic pathways.     

A Mathematical Framework for Combining Decisions of Multiple Experts toward Accurate and Remote Diagnosis of Malaria Using Tele-Microscopy

We propose a methodology for digitally fusing diagnostic decisions made by multiple medical experts in order to improve accuracy of diagnosis. Toward this goal, we report an experimental study involving nine experts, where each one was given more than 8,000 digital microscopic images of individual human red blood cells and asked to identify malaria infected cells. The results of this experiment reveal that even highly trained medical experts are not always self-consistent in their diagnostic decisions and that there exists a fair level of disagreement among experts, even for binary decisions (i.e., infected vs. uninfected). To tackle this general medical diagnosis problem, we propose a probabilistic algorithm to fuse the decisions made by trained medical experts to robustly achieve higher levels of accuracy when compared to individual experts making such decisions. By modelling the decisions of experts as a three component mixture model and solving for the underlying parameters using the Expectation Maximisation algorithm, we demonstrate the efficacy of our approach which significantly improves the overall diagnostic accuracy of malaria infected cells. Additionally, we present a mathematical framework for performing ‘slide-level’ diagnosis by using individual ‘cell-level’ diagnosis data, shedding more light on the statistical rules that should govern the routine practice in examination of e.g., thin blood smear samples. This framework could be generalized for various other tele-pathology needs, and can be used by trained experts within an efficient tele-medicine platform.     

Estimating recent growth in the cuttlefish Sepia officinalis: are nucleic acid-based indicators for growth and condition the method of choice?

A laboratory calibration study was undertaken with juvenile Sepia officinalis (80-85 g initial wet weight) to investigate the effects of different food rations and different starving intervals on RNA/dry weight (DW) ratios and RNA/DNA ratios in cephalopod mantle muscle at two different temperatures. The digestive gland index was also used as an additional indicator of recent growth. High food rations and low temperature went along with high RNA/DW ratios and high RNA/DNA ratios. Starving resulted in a linear decline in growth performance and a concomitant decrease in RNA/DW and RNA/DNA ratio, with RNA/DNA ratios representing the growth data better. RNA/DNA ratios decreased faster at higher temperatures. A fluorimetric assay for nucleic acid analysis was optimized for cephalopod mantle tissues and yielded reproducible RNA/DNA ratios with a relative variance below 10%. Thus, it may be possible to use this estimator of recently encountered feeding regime for the evaluation of mortality rates of early teuthid paralarvae to eventually support stock management. Also, log relative digestive gland weight showed a strong relationship with starving time, but, surprisingly, not with temperature. Data from the two temperatures analyzed could be combined to form a common regression line of relative digestive gland index with starving time. This indicator for recent growth might be especially suitable for large specimens with a well-developed digestive gland.     

Can zoosporic true fungi grow or survive in extreme or stressful environments?

Zoosporic true fungi are thought to be ubiquitous in many ecosystems, especially in cool, moist soils and freshwater habitats which are rich in organic matter. However, some of the habitats where these fungi are found may periodically experience extreme conditions, such as soils in extremely dry, hot and cold climates, acidic and alkaline soils, polluted rivers, anaerobic soil and water, saline soil and water, periglacial soils, oligotrophic soils, tree canopies and hydrothermal vents. It is clear that many ecotypes of zoosporic true fungi have indeed adapted to extreme or stressful environmental conditions. This conclusion is supported by studies in both the field and in the laboratory. Therefore, in our opinion, at least some true zoosporic fungi can be considered to be extremophiles.