Closely related Symbiodinium spp. differ in relative dominance in coral reef host communities across environmental, latitudinal and biogeographic gradients

The diversity and community structures of symbiotic dinoflagellates are described from reef invertebrates in southern and central provinces of the Great Barrier Reef (GBR), Australia, and Zamami Island, Okinawa, Japan. The symbiont assemblages from region to region were dominated by Clade C Symbiodinium spp. and consisted of numerous host-specific and/or rare types (specialists), and several types common to many hosts (generalists). Prevalence in the host community among certain host-generalist symbionts differed between inshore and offshore environments, across latitudinal (central versus southern GBR) gradients, and over wide geographic ranges (GBR versus Okinawa). One particular symbiont (C3h) from the GBR had a dramatic shift in dominance. Its prevalence ranged from being extremely rare, or absent on high-latitude reefs to dominating the scleractinian diversity on a mid-latitude inshore reef. These changes occurred among coral fauna whose larvae must acquire symbionts from environmental sources (horizontal symbiont acquisition). Such differences did not occur among 'vertical transmitters' such as Porites spp., Montipora spp. and pocilloporids (corals that directly transmit symbionts to their offspring) or among those hosts displaying 'horizontal acquisition', but that associate with specific symbionts. Most host-specialized types were found to be characteristic of a particular geographic region (i.e. Okinawa versus Central GBR versus Southern GBR). The mode of symbiont acquisition may play an important role in how symbiont composition may shift in west Pacific host communities in response to climate change. There is no indication that recent episodes of mass bleaching have provoked changes in host-symbiont combinations from the central GBR.

Macroscopic test of quantum mechanics versus stochastic electrodynamics

We identify a test of quantum mechanics versus macroscopic local realism in the form of stochastic electrodynamics. The test uses the steady-state triple quadrature correlations of a parametric oscillator below threshold.

The shoot controls zeatin riboside export from pea roots. Evidence from the branching mutant rms4

The rms4 mutant of pea (Pisum sativum L.) was used in grafting studies and cytokinin analyses of the root xylem sap to provide evidence that, at least for pea, the shoot can modify the import of cytokinins from the root. The rms4 mutation, which confers a phenotype with increased branching in the shoot, causes a very substantial decrease (down to 40-fold less) in the concentration of zeatin riboside (ZR) in the xylem sap of the roots. Results from grafts between wild-type (WT) and rms4 plants indicate that the concentration of cytokinins in the xylem sap of the roots is determined almost entirely by the genotype of the shoot. WT scions normalize the cytokinin concentration in the sap of rms4 mutant roots, whereas mutant scions cause WT roots to behave like those of self-grafted mutant plants. The mechanism whereby rms4 shoots of pea cause a down-regulation in the export of cytokinins from the roots is unknown at this time. However, our data provide evidence that the shoot transmits a signal to the roots and thereby controls processes involved in the regulation of cytokinin biosynthesis in the root.

Robust algorithms for solving stochastic partial differential equations

A robust semi-implicit central partial difference algorithm for the numerical solution of coupled stochastic parabolic partial differential equations (PDEs) is described. This can be used for calculating correlation functions of systems of interacting stochastic fields. Such field equations can arise in the description of Hamiltonian and open systems in the physics of nonlinear processes, and may include multiplicative noise sources. The algorithm can be used for studying the properties of nonlinear quantum or classical field theories. The general approach is outlined and applied to a specific example, namely the quantum statistical fluctuations of ultra-short optical pulses in chi((2)) parametric waveguides. This example uses a non-diagonal coherent state representation, and correctly predicts the sub-shot noise level spectral fluctuations observed in homodyne detection measurements. It is expected that the methods used wilt be applicable for higher-order correlation functions and other physical problems as well. A stochastic differencing technique for reducing sampling errors is also introduced. This involves solving nonlinear stochastic parabolic PDEs in combination with a reference process, which uses the Wigner representation in the example presented here. A computer implementation on MIMD parallel architectures is discussed. (C) 1997 Academic Press.

Rapid increases in cytokinin concentration in lateral buds of chickpea (Cicer arietinum L) during release of apical dominance

We examined the role of cytokinins (CKs) in release of apical dominance in lateral buds of chickpea (Cicer arietinum L.). Shoot decapitation or application of CKs (benzyladenine, zeatin or dihydrozeatin) stimulated rapid bud growth. Time-lapse video recording revealed growth initiation within 2 h of application of 200 pmol benzyladenine or within 3 h of decapitation. Endogenous CK content in buds changed little in the first 2 h after shoot decapitation, but significantly increased by 6 h, somewhat later than the initiation of bud growth. The main elevated CK was zeatin riboside, whose content per bud increased 7-fold by 6 h and 25-fold by 24 h. Lesser changes were found in amounts of zeatin and isopentenyl adenine CKs. We have yet to distinguish whether these CKs are imported from the roots via the xylem stream or are synthesised in situ in the buds, but CKs may be part of an endogenous signal involved in lateral bud growth stimulation following shoot decapitation. To our knowledge, this is the first detailed report of CK levels in buds themselves during release of apical dominance.

A stochastic frontier production function with flexible risk properties

This paper considers a stochastic frontier production function which has additive, heteroscedastic error structure. The model allows for negative or positive marginal production risks of inputs, as originally proposed by Just and Pope (1978). The technical efficiencies of individual firms in the sample are a function of the levels of the input variables in the stochastic frontier, in addition to the technical inefficiency effects. These are two features of the model which are not exhibited by the commonly used stochastic frontiers with multiplicative error structures, An empirical application is presented using cross-sectional data on Ethiopian peasant farmers. The null hypothesis of no technical inefficiencies of production among these farmers is accepted. Further, the flexible risk models do not fit the data on peasant farmers as well as the traditional stochastic frontier model with multiplicative error structure.

The composite Euler method for stiff stochastic differential equations

In this paper we present the composite Euler method for the strong solution of stochastic differential equations driven by d-dimensional Wiener processes. This method is a combination of the semi-implicit Euler method and the implicit Euler method. At each step either the semi-implicit Euler method or the implicit Euler method is used in order to obtain better stability properties. We give criteria for selecting the semi-implicit Euler method or the implicit Euler method. For the linear test equation, the convergence properties of the composite Euler method depend on the criteria for selecting the methods. Numerical results suggest that the convergence properties of the composite Euler method applied to nonlinear SDEs is the same as those applied to linear equations. The stability properties of the composite Euler method are shown to be far superior to those of the Euler methods, and numerical results show that the composite Euler method is a very promising method. (C) 2001 Elsevier Science B.V. All rights reserved.

Implicit Taylor methods for stiff stochastic differential equations

In this paper we discuss implicit Taylor methods for stiff Ito stochastic differential equations. Based on the relationship between Ito stochastic integrals and backward stochastic integrals, we introduce three implicit Taylor methods: the implicit Euler-Taylor method with strong order 0.5, the implicit Milstein-Taylor method with strong order 1.0 and the implicit Taylor method with strong order 1.5. The mean-square stability properties of the implicit Euler-Taylor and Milstein-Taylor methods are much better than those of the corresponding semi-implicit Euler and Milstein methods and these two implicit methods can be used to solve stochastic differential equations which are stiff in both the deterministic and the stochastic components. Numerical results are reported to show the convergence properties and the stability properties of these three implicit Taylor methods. The stability analysis and numerical results show that the implicit Euler-Taylor and Milstein-Taylor methods are very promising methods for stiff stochastic differential equations.

Stiffly accurate Runge-Kutta methods for stiff stochastic differential equations

In this paper we discuss implicit methods based on stiffly accurate Runge-Kutta methods and splitting techniques for solving Stratonovich stochastic differential equations (SDEs). Two splitting techniques: the balanced splitting technique and the deterministic splitting technique, are used in this paper. We construct a two-stage implicit Runge-Kutta method with strong order 1.0 which is corrected twice and no update is needed. The stability properties and numerical results show that this approach is suitable for solving stiff SDEs. (C) 2001 Elsevier Science B.V. All rights reserved.

Stochastic gauges in quantum dynamics for many-body simulations

Quantum dynamics simulations can be improved using novel quasiprobability distributions based on non-orthogonal Hermitian kernel operators. This introduces arbitrary functions (gauges) into the stochastic equations. which can be used to tailor them for improved calculations. A possible application to full quantum dynamic simulations of BEC's is presented. (C) 2001 Elsevier Science B.V. All rights reserved.

Stochastic Schrodinger equation approach to quantum noise in resonant tunneling current

We apply the quantum trajectory method to current noise in resonant tunneling devices. The results from dynamical simulation are compared with those from unconditional master equation approach. We show that the stochastic Schrodinger equation approach is useful in modeling the dynamical processes in mesoscopic electronic systems.

Predictions of quantum mechanics and stochastic electrodynamics in travelling wave second harmonic generation

We show that stochastic electrodynamics and quantum mechanics give quantitatively different predictions for the quantum nondemolition (QND) correlations in travelling wave second harmonic generation. Using phase space methods and stochastic integration, we calculate correlations in both the positive-P and truncated Wigner representations, the latter being equivalent to the semi-classical theory of stochastic electrodynamics. We show that the semiclassical results are different in the regions where the system performs best in relation to the QND criteria, and that they significantly overestimate the performance in these regions. (C) 2001 Published by Elsevier Science B.V.

The stochastic design of force-minimized compact magnets for high-field magnetic resonance imaging applications

New designs for force-minimized compact high-field clinical MRI magnets are described. The design method is a modified simulated annealing (SA) procedure which includes Maxwell forces in the error function to be minimized. This permits an automated force reduction in the magnet designs while controlling the overall dimensions of the system. As SA optimization requires many iterations to achieve a final design, it is important that each iteration in the procedure is rapid. We have therefore developed a rapid force calculation algorithm. Novel designs for short 3- and 4-T clinical MRI systems are presented in which force reduction has been invoked. The final designs provide large homogeneous regions and reduced stray fields in remarkable short magnets. A shielded 4-T design that is approximately 30% shorter than current designs is presented. This novel magnet generates a full 50-cm diameter homogeneous region.

Patchy populations in stochastic environments: Critical number of patches for persistence

We introduce a model for the dynamics of a patchy population in a stochastic environment and derive a criterion for its persistence. This criterion is based on the geometric mean (GM) through time of the spatial-arithmetic mean of growth rates. For the population to persist, the GM has to be greater than or equal to1. The GM increases with the number of patches (because the sampling error is reduced) and decreases with both the variance and the spatial covariance of growth rates. We derive analytical expressions for the minimum number of patches (and the maximum harvesting rate) required for the persistence of the population. As the magnitude of environmental fluctuations increases, the number of patches required for persistence increases, and the fraction of individuals that can be harvested decreases. The novelty of our approach is that we focus on Malthusian local population dynamics with high dispersal and strong environmental variability from year to year. Unlike previous models of patchy populations that assume an infinite number of patches, we focus specifically on the effect that the number of patches has on population persistence. Our work is therefore directly relevant to patchily distributed organisms that are restricted to a small number of habitat patches.