Dispersal Dynamics of the Bivalve Gemma Gemma in a Patchy Environment

The purpose of this study was to analyze the dispersal dynamics of the ovoviviparous bivalve Gemma gemma (hereafter referred to as Gemma) in an environment disturbed by the pit-digging activities of horseshoe crabs, Limulus polyphemus. Gemma broods its young and has no planktonic larval stage, so all dispersal is the result of juvenile and adult movement. Animal movement was measured using natural crab pits, hand-dug simulated crab pits, and cylindrical bottom traps in the intertidal zone at Tom\u27s Cove, Virginia, USA. This study demonstrated that horseshoe crabs create localized patches with reduced densities of Gemma, that all sizes and ages of Gemma quickly disperse into these low density patches, and that the mechanism of dispersal is passive bedload and suspended load transport. Freshly excavated natural pits had significantly lower Gemma densities than did undisturbed background sediment, but there were no significant differences in total density of other species, number of species, and species diversity (H\u27). Equitability (J\u27) was greater in pits than in controls because of the reduced abundance of Gemma, the numerically dominant species. Newly dug simulated crab pits also had significantly lower Gemma densities than controls and returned to control levels by the next day. Density recovery trajectories for individually marked pits showed consistent responses in summer and fall, but not in winter when low Gemma abundance resulted in greater variability among pits. Significant positive correlations between the volume of sediment and the number of Gemma collected per bottom trap support the hypothesis that Gemma dispersal is a passive transport phenomenon. Assuming no active, density-dependent movement, the product of the Gemma density frequency distribution in undisturbed background sediment and the frequency distribution of sediment volume collected per trap created a predicted Gemma frequency distribution in traps that matched the actual distribution. Absolute dispersal rates and relative dispersal rates (absolute dispersal rate divided by background density in undisturbed sediment) into pits and traps were greater in summer than winter. Dispersal rate results suggest that increased horseshoe crab disturbance in summer may cause an increase in Gemma transport. Because Gemma individuals are dispersed by hydrodynamic action, it was expected that small, young individuals would be most easily transported in the bedload. There was, however, little evidence that movement into pits and traps was size- or age-selective. Most recent benthic dispersal research has focused on the large-scale movement and settlement patterns of invertebrate larvae. The results from this study illustrate that dispersal of bottom-dwelling juveniles and adults plays an important role in regulating the local distribution and abundance of Gemma. Previous workers have shown that young Gemma live in dense aggregations and that growth and fecundity are reduced at such high densities, leading to population crashes. This study demonstrated a mechanism by which Gemma disperses into low-density patches where intraspecific competition may be mitigated, possibly resulting in enhanced individual reproductive success and population fitness

Photosynthetic and Respiratory Acclimation of Understory Shrubs in Response to in situ Experimental Warming of a Wet Tropical Forest

Despite the importance of tropical forests to global carbon balance, our understanding of how tropical plant physiology will respond to climate warming is limited. In addition, the contribution of tropical forest understories to global carbon cycling is predicted to increase with rising temperatures, however, in situ warming studies of tropical forest plants to date focus only on upper canopies. We present results of an in situ field-scale +4°C understory infrared warming experiment in Puerto Rico (Tropical Responses to Altered Climate Experiment; TRACE). We investigated gas exchange responses of two common understory shrubs, Psychotria brachiata and Piper glabrescens, after exposure to 4 and 8 months warming. We assessed physiological acclimation in two ways: (1) by comparing plot-level physiological responses in heated versus control treatments before and after warming, and (2) by examining physiological responses of individual plants to variation in environmental drivers across all plots, seasons, and treatments. P. brachiata has the capacity to up-regulate (i.e., acclimate) photosynthesis through broadened thermal niche and up-regulation of photosynthetic temperature optimum (Topt) with warmer temperatures. P. glabrescens, however, did not upregulate any photosynthetic parameter, but rather experienced declines in the rate of photosynthesis at the optimum temperature (Aopt), corresponding with lower stomatal conductance under warmer daily temperatures. Contrary to expectation, neither species showed strong evidence for respiratory acclimation. P. brachiata down-regulated basal respiration with warmer daily temperatures during the drier winter months only. P. glabrescens showed no evidence of respiratory acclimation. Unexpectedly, soil moisture, was the strongest environmental driver of daily physiological temperature responses, not vegetation temperature. Topt increased, while photosynthesis and basal respiration declined as soils dried, suggesting that drier conditions negatively affected carbon uptake for both species. Overall, P. brachiata, an early successional shrub, showed higher acclimation potential to daily temperature variations, potentially mitigating negative effects of chronic warming. The negative photosynthetic response to warming experienced by P. glabrescens, a mid-successional shrub, suggests that this species may not be able to as successfully tolerate future, warmer temperatures. These results highlight the importance of considering species when assessing climate change and relay the importance of soil moisture on plant function in large-scale warming experiments

Ocean acidification affects marine chemical communication by changing structure and function of peptide signalling molecules

Ocean acidification is a global challenge that faces marine organisms in the near future with a predicted rapid drop in pH of up to 0.4 units by the end of this century. Effects of the change in ocean carbon chemistry and pH on the development, growth and fitness of marine animals are well documented. Recent evidence also suggests that a range of chemically mediated behaviours and interactions in marine fish and invertebrates will be affected. Marine animals use chemical cues, for example, to detect predators, for settlement, homing and reproduction. But while effects of high CO₂ conditions on these behaviours are described across many species, little is known about the underlying mechanisms, particularly in invertebrates. Here we investigate the direct influence of future oceanic pH conditions on the structure and function of three peptide signalling molecules with an interdisciplinary combination of methods. NMR spectroscopy and quantum chemical calculations were used to assess the direct molecular influence of pH on the peptide cues and we tested the functionality of the cues in different pH conditions using behavioural bioassays with shore crabs (Carcinus maenas) as a model system. We found that peptide signalling cues are susceptible to protonation in future pH conditions, which will alter their overall charge. We also show that structure and electrostatic properties important for receptor-binding differ significantly between the peptide forms present today and the protonated signalling peptides likely to be dominating in future oceans. The bioassays suggest an impaired functionality of the signalling peptides at low pH. Physiological changes due to high CO₂ conditions were found to play a less significant role in influencing the investigated behaviour. From our results we conclude that the change of charge, structure and consequently function of signalling molecules presents one possible mechanism to explain altered behaviour under future oceanic pH conditions

PC program extending the two-stage polynomial growth curve model to allow missing data

A stand-alone, menu-driven PC program, written in GAUSS386i, extending the analysis of one-sample longitudinal data sets satisfying the two-stage polynomial growth curve model (Ten Have et al., Am J Hum Biol, 3 (1991) 269-279) to allow missing data is described, illustrated and made available to interested readers. The method and the program are illustrated using data previously analyzed by the authors (Schneiderman and Kowalski, Am J Phys Anthropol, 67 (1985) 323-333) but with several randomly chosen data points discarded and treated as missing.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/30475/1/0000103.pd

Predicting Worst-Case Execution Time Trends in Long-Lived Real-Time Systems

In some long-lived real-time systems, it is not uncommon to see that the execution times of some tasks may exhibit trends. For hard and firm real-time systems, it is important to ensure these trends will not jeopardize the system. In this paper, we first introduce the notion of dynamic worst-case execution time (dWCET), which forms a new perspective that could help a system to predict potential timing failures and optimize resource allocations. We then have a comprehensive review of trend prediction methods. In the evaluation, we make a comparative study of dWCET trend prediction. Four prediction methods, combined with three data selection processes, are applied in an evaluation framework. The result shows the importance of applying data preprocessing and suggests that non-parametric estimators perform better than parametric methods

Complex-valued wavelet lifting and applications

Signals with irregular sampling structures arise naturally in many fields. In applications such as spectral decomposition and nonparametric regression, classical methods often assume a regular sampling pattern, thus cannot be applied without prior data processing. This work proposes new complex-valued analysis techniques based on the wavelet lifting scheme that removes ‘one coefficient at a time’. Our proposed lifting transform can be applied directly to irregularly sampled data and is able to adapt to the signal(s)’ characteristics. As our new lifting scheme produces complex-valued wavelet coefficients, it provides an alternative to the Fourier transform for irregular designs, allowing phase or directional information to be represented. We discuss applications in bivariate time series analysis, where the complex-valued lifting construction allows for coherence and phase quantification. We also demonstrate the potential of this flexible methodology over real-valued analysis in the nonparametric regression context

Evaluation of the inter-annual variability of stratospheric chemical composition in chemistry-climate models using ground-based multi species time series

The variability of stratospheric chemical composition occurs on a broad spectrum of timescales, ranging from day to decades. A large part of the variability appears to be driven by external forcings such as volcanic aerosols, solar activity, halogen loading, levels of greenhouse gases (GHG), and modes of climate variability (quasi-biennial oscillation (QBO), El Niño-Southern Oscillation (ENSO)). We estimate the contributions of different external forcings to the interannual variability of stratospheric chemical composition and evaluate how well 3-D chemistry-climate models (CCMs) can reproduce the observed response-forcing relationships. We carry out multivariate regression analyses on long time series of observed and simulated time series of several traces gases in order to estimate the contributions of individual forcings and unforced variability to their internannual variability. The observations are typically decadal time series of ground-based data from the international Network for the Detection of Atmospheric Composition Change (NDACC) and the CCM simulations are taken from the CCMVal-2 REF-B1 simulations database. The chemical species considered are column O3, HCl, NO2, and N2O. We check the consistency between observations and model simulations in terms of the forced and internal components of the total interannual variability (externally forced variability and internal variability) and identify the driving factors in the interannual variations of stratospheric chemical composition over NDACC measurement sites. Overall, there is a reasonably good agreement between regression results from models and observations regarding the externally forced interannual variability. A much larger fraction of the observed and modelled interannual variability is explained by external forcings in the tropics than in the extratropics, notably in polar regions. CCMs are able to reproduce the amplitudes of responses in chemical composition to specific external forcings. However, CCMs tend to underestimate very substantially the internal variability and hence the total interannual variability for almost all species considered. This lack of internal variability in CCMs might partly originate from the surface forcing of these CCMs by analysed SSTs. The results illustrate the potential of NDACC ground-based observations for evaluating CCMs

The Role of Macroeconomic Fundamentals in Malaysian Post Recession Growth

This study aims to find out the role of macroeconomic fundamentals in Malaysian post recession growth. The selected macroeconomic variables are exports, imports, price level, money supply, interest rate, exchange rate and government expenditure. The technique of cointegration was employed to assess the long run equilibrium relationships among the variables. Then, this study performs the Granger causality tests based on VECM to establish the short run causality among the variables. The long-run cointegrating relationship shown that an increase in exports, government expenditure or depreciation of exchange rate will promote long-term economic growth while increase in inflation, interest rate and imports will tamper the Malaysian economic growth. The results of short-run Granger-causality indicated that price level and government spending Granger-caused economic growth in the short-run. In conclusion, based on the results of long-run and short run analysis, the fiscal policy is probably the most appropriate tool in promoting economic growth in Malaysia during the post recession period