88 resultados para spatial markov Chains


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A stochastic metapopulation model accounting for habitat dynamics is presented. This is the stochastic SIS logistic model with the novel aspect that it incorporates varying carrying capacity. We present results of Kurtz and Barbour, that provide deterministic and diffusion approximations for a wide class of stochastic models, in a form that most easily allows their direct application to population models. These results are used to show that a suitably scaled version of the metapopulation model converges, uniformly in probability over finite time intervals, to a deterministic model previously studied in the ecological literature. Additionally, they allow us to establish a bivariate normal approximation to the quasi-stationary distribution of the process. This allows us to consider the effects of habitat dynamics on metapopulation modelling through a comparison with the stochastic SIS logistic model and provides an effective means for modelling metapopulations inhabiting dynamic landscapes.

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Many populations have a negative impact on their habitat or upon other species in the environment if their numbers become too large. For this reason they are often subjected to some form of control. One common control regime is the reduction regime: when the population reaches a certain threshold it is controlled (for example culled) until it falls below a lower predefined level. The natural model for such a controlled population is a birth-death process with two phases, the phase determining which of two distinct sets of birth and death rates governs the process. We present formulae for the probability of extinction and the expected time to extinction, and discuss several applications. (c) 2006 Elsevier Inc. All rights reserved.

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This paper has three primary aims: to establish an effective means for modelling mainland-island metapopulations inhabiting a dynamic landscape: to investigate the effect of immigration and dynamic changes in habitat on metapopulation patch occupancy dynamics; and to illustrate the implications of our results for decision-making and population management. We first extend the mainland-island metapopulation model of Alonso and McKane [Bull. Math. Biol. 64:913-958,2002] to incorporate a dynamic landscape. It is shown, for both the static and the dynamic landscape models, that a suitably scaled version of the process converges to a unique deterministic model as the size of the system becomes large. We also establish that. under quite general conditions, the density of occupied patches, and the densities of suitable and occupied patches, for the respective models, have approximate normal distributions. Our results not only provide us with estimates for the means and variances that are valid at all stages in the evolution of the population, but also provide a tool for fitting the models to real metapopulations. We discuss the effect of immigration and habitat dynamics on metapopulations, showing that mainland-like patches heavily influence metapopulation persistence, and we argue for adopting measures to increase connectivity between this large patch and the other island-like patches. We illustrate our results with specific reference to examples of populations of butterfly and the grasshopper Bryodema tuberculata.

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Consider a haploid population and, within its genome, a gene whose presence is vital for the survival of any individual. Each copy of this gene is subject to mutations which destroy its function. Suppose one member of the population somehow acquires a duplicate copy of the gene, where the duplicate is fully linked to the original gene's locus. Preservation is said to occur if eventually the entire population consists of individuals descended from this one which initially carried the duplicate. The system is modelled by a finite state-space Markov process which in turn is approximated by a diffusion process, whence an explicit expression for the probability of preservation is derived. The event of preservation can be compared to the fixation of a selectively neutral gene variant initially present in a single individual, the probability of which is the reciprocal of the population size. For very weak mutation, this and the probability of preservation are equal, while as mutation becomes stronger, the preservation probability tends to double this reciprocal. This is in excellent agreement with simulation studies.

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We describe methods for estimating the parameters of Markovian population processes in continuous time, thus increasing their utility in modelling real biological systems. A general approach, applicable to any finite-state continuous-time Markovian model, is presented, and this is specialised to a computationally more efficient method applicable to a class of models called density-dependent Markov population processes. We illustrate the versatility of both approaches by estimating the parameters of the stochastic SIS logistic model from simulated data. This model is also fitted to data from a population of Bay checkerspot butterfly (Euphydryas editha bayensis), allowing us to assess the viability of this population. (c) 2006 Elsevier Inc. All rights reserved.

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Let (Phi(t))(t is an element of R+) be a Harris ergodic continuous-time Markov process on a general state space, with invariant probability measure pi. We investigate the rates of convergence of the transition function P-t(x, (.)) to pi; specifically, we find conditions under which r(t) vertical bar vertical bar P-t (x, (.)) - pi vertical bar vertical bar -> 0 as t -> infinity, for suitable subgeometric rate functions r(t), where vertical bar vertical bar - vertical bar vertical bar denotes the usual total variation norm for a signed measure. We derive sufficient conditions for the convergence to hold, in terms of the existence of suitable points on which the first hitting time moments are bounded. In particular, for stochastically ordered Markov processes, explicit bounds on subgeometric rates of convergence are obtained. These results are illustrated in several examples.

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Arriving in Brisbane some six years ago, I could not help being impressed by what may be prosaically described as its atmospheric amenity resources. Perhaps this in part was due to my recent experiences in major urban centres in North America, but since that time, that sparkling quality and the blue skies seem to have progressively diminished. Unfortunately, there is also objective evidence available to suggest that this apparent deterioration is not merely the result of habituation of the senses. Air pollution data for the city show trends of increasing concentrations of those very substances that have destroyed the attractiveness of major population centres elsewhere, with climates initially as salubrious. Indeed, present figures indicate that photochemical smog in unacceptably high concentrations is rapidly becoming endemic also over Brisbane. These regrettable developments should come as no surprise. The society at large has not been inclined to respond purposefully to warnings of impending environmental problems, despite the experiences and publicity from overseas and even from other cities within Australia. Nor, up to the present, have certain politicians and government officials displayed stances beyond those necessary for the maintenance of a decorum of concern. At this stage, there still exists the possibility for meaningful government action without the embarrassment of losing political favour with the electorate. To the contrary, there is every chance that such action may be turned to advantage with increased public enlightenment. It would be more than a pity to miss perhaps the final remaining opportunity: Queensland is one of the few remaining places in the world with sufficient resources to permit both rational development and high environmental quality. The choice appears to be one of making a relatively minor investment now for a large financial and social gain the near future, or, permitting Brisbane to degenerate gradually into just another stagnated Los Angeles or Sydney. The present monograph attempts to introduce the problem by reviewing the available research on air quality in the Brisbane area. It also tries to elucidate some seemingly obvious, but so far unapplied management approaches. By necessity, such a broad treatment needs to make inroads into extensive ranges of subject areas, including political and legal practices to public perceptions, scientific measurement and statistical analysis to dynamics of air flow. Clearly, it does not pretend to be definitive in any of these fields, but it does try to emphasize those adjustable facets of the human use system of natural resources, too often neglected in favour of air pollution control technology. The crossing of disciplinary boundaries, however, needs no apology: air quality problems are ubiquitous, touching upon space, time and human interaction.

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Contrary to the common pattern of spatial terms being metaphorically extended to location in time, the Australian language Jingulu shows an unusual extension of temporal markers to indicate location in space. Light verbs, which typically encode tense, aspect, mood and associated motion, are occasionally found on nouns to indicate the relative location of the referent with respect to the speaker. It is hypothesised that this pattern resulted from the reduction of verbal clauses used as relative modifiers to the nouns in question.

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This paper reviews the potential use of three types of spatial technology to land managers, namely satellite imagery, satellite positioning systems and supporting computer software. Developments in remote sensing and the relative advantages of multispectral and hyperspectral images are discussed. The main challenge to the wider use of remote sensing as a land management tool is seen as uncertainty whether apparent relationships between biophysical variables and spectral reflectance are direct and causal, or artefacts of particular images. Developments in satellite positioning systems are presented in the context of land managers’ need for position estimates in situations where absolute precision may or may not be required. The role of computer software in supporting developments in spatial technology is described. Spatial technologies are seen as having matured beyond empirical applications to the stage where they are useful and reliable land management tools. In addition, computer software has become more user-friendly and this has facilitated data collection and manipulation by semi-expert as well as specialist staff.

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We have measured the spatial diffusion of atoms in a three-dimensional sigma(+)-sigma(-) optical molasses over twenty milliseconds timescale, starting from the initial interaction of the atoms with the molasses. We find that the diffusion constants agree well with a linear model for these short time scales and also compare favourably to other studies of diffusion made over longer time scales. These measurements enable us to quantify the detection method known as freezing molasses. We discuss this method, for detecting and measuring the momentum distribution of cold atoms, which relies on the slow diffusion of atoms in optical molasses to produce a freeze-frame of the spatial distribution of the atoms. This method enables a longer interrogation interval, providing a greatly increased signal-to-noise ratio. (C) 1998 Elsevier Science B.V.

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Using Reshetikhin's construction for multiparametric quantum algebras we obtain the associated multiparametric quantum spin chains. We show that under certain restrictions these models can be mapped to quantum spin chains with twisted boundary conditions, We illustrate how this general formalism applier; to construct multiparametric versions of the supersymmetric t-J and Li models.

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The integrable open-boundary conditions for the model of three coupled one-dimensional XY spin chains are considered in the framework of the quantum inverse scattering method. The diagonal boundary K-matrices are found and a class of integrable boundary terms is determined. The boundary model Hamiltonian is solved by using the coordinate space Bethe ansatz technique and Bethe ansatz equations are derived. (C) 1998 Elsevier Science B.V.

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The cost of spatial join processing can be very high because of the large sizes of spatial objects and the computation-intensive spatial operations. While parallel processing seems a natural solution to this problem, it is not clear how spatial data can be partitioned for this purpose. Various spatial data partitioning methods are examined in this paper. A framework combining the data-partitioning techniques used by most parallel join algorithms in relational databases and the filter-and-refine strategy for spatial operation processing is proposed for parallel spatial join processing. Object duplication caused by multi-assignment in spatial data partitioning can result in extra CPU cost as well as extra communication cost. We find that the key to overcome this problem is to preserve spatial locality in task decomposition. We show in this paper that a near-optimal speedup can be achieved for parallel spatial join processing using our new algorithms.

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Faecal pellets were collected under trees used by free-ranging koalas in south-western, central and southeastern Queensland to determine the spatial and temporal distribution of pellets with respect to the activity of koalas. Deposition of faecal pellets by koalas was analysed according to the time of day at which the tree was occupied. For free-ranging koalas, 47% of daily faecal pellet output was recovered using a collection mat of 8 x 8 m placed under a day-roost tree. The best predictor of pellet production was the presence of a koala in a tree between 1800 hours and midnight. For other periods, there was no relationship between period of tree occupancy and faecal pellet recovery. There was a significant relationship between the average length of tree occupancy and the time of day that a koala entered a tree.