On the role of spatial stochastic models in understanding landscape indices in ecology

Oikos ◽  
2003 ◽  
Vol 102 (1) ◽  
pp. 203-212 ◽  
Author(s):  
M.-J. Fortin ◽  
B. Boots ◽  
F. Csillag ◽  
T.K. Remmel
Keyword(s):  
Stochastic Models ◽  
Landscape Indices

Stochastic models in cell kinetics

1988 ◽  
Vol 25 (A) ◽  
pp. 91-111
Author(s):  
Peter J. Brockwell
Keyword(s):  
Life Cycle ◽  
Stochastic Models ◽  
Death Rate ◽  
Cell Kinetics ◽  
Branching Processes ◽  
Experimental Studies ◽  
Renewal Theory ◽  
Biological Cell ◽  
Age Dependent

We discuss the role of stochastic processes in modelling the life-cycle of a biological cell and the growth of cell populations. Results for multiphase age-dependent branching processes have proved invaluable for the interpretation of many of the basic experimental studies of the life-cycle. Moreover problems from cell kinetics, in particular those related to diurnal rhythm in cell-growth, have stimulated research into ‘periodic' renewal theory, and the asymptotic behaviour of populations of cells with periodic death rate.

Mathematical Modeling of Supply Chain Management Systems

2010 ◽  
pp. 344-357
Author(s):  
N. Anbazhagan
Keyword(s):  
Mathematical Modeling ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Mathematical Models ◽  
Stochastic Models ◽  
Management System ◽  
Raw Materials ◽  
Chain Management ◽  
Supply Chain Management System

Supply Chain Management (SCM) is the practice of coordinating the flow of goods, services, information and finances as they move from raw materials to parts supplier to manufacturer to wholesaler to retailer to consumer. Different supply chains have been designed for a variety of firms and this chapter discusses some issues in this regard. This chapter attempts to find why we require different supply chain for different companies. In this chapter we discuss the role of stochastic models in supply chain management system, and also discuss other mathematical models for SCM.

Stochastic models in cell kinetics

1988 ◽  
Vol 25 (A) ◽  
pp. 91-111
Author(s):  
Peter J. Brockwell
Keyword(s):  
Life Cycle ◽  
Stochastic Models ◽  
Death Rate ◽  
Cell Kinetics ◽  
Branching Processes ◽  
Experimental Studies ◽  
Renewal Theory ◽  
Biological Cell ◽  
Age Dependent

We discuss the role of stochastic processes in modelling the life-cycle of a biological cell and the growth of cell populations. Results for multiphase age-dependent branching processes have proved invaluable for the interpretation of many of the basic experimental studies of the life-cycle. Moreover problems from cell kinetics, in particular those related to diurnal rhythm in cell-growth, have stimulated research into ‘periodic' renewal theory, and the asymptotic behaviour of populations of cells with periodic death rate.

scholarly journals Effects of Patchiness on Surface Soil Moisture of Alpine Meadow on the Northeastern Qinghai-Tibetan Plateau: Implications for Grassland Restoration

2020 ◽  
Vol 12 (24) ◽  
pp. 4121
Author(s):  
Wei Zhang ◽  
Shuhua Yi ◽  
Yu Qin ◽  
Yi Sun ◽  
Donghui Shangguan ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Tibetan Plateau ◽  
Surface Soil ◽  
Alpine Meadow ◽  
Alpine Grassland ◽  
Grassland Restoration ◽  
Landscape Indices ◽  
Surface Soil Moisture ◽  
Bare Patch

Surface soil moisture (SSM) is a key limiting factor for vegetation growth in alpine meadow on the Qinghai-Tibetan Plateau (QTP). Patches with various sizes and types may cause the redistribution of SSM by changing soil hydrological processes, and then trigger or accelerate alpine grassland degradation. Therefore, it is vital to understand the effects of patchiness on SSM at multi-scales to provide a reference for alpine grassland restoration. However, there is a lack of direct observational evidence concerning the role of the size and type of patches on SSM, and little is known about the effects of patches pattern on SSM at plot scale. Here, we first measured SSM of typical patches with different sizes and types at patch scale and investigated their patterns and SSM spatial distribution through unmanned aerial vehicle (UAV)-mounted multi-type cameras at plot scale. We then analyzed the role of the size and type of patchiness on SSM at both patch and plot scales. Results showed that: (1) in situ measured SSM of typical patches was significantly different (P < 0.01), original vegetation patch (OV) had the highest SSM, followed by isolate vegetation patch (IV), small bare patch (SP), medium bare patch (MP) and large bare patch (LP); (2) the proposed method based on UAV images was able to estimate SSM (0–40 cm) with a satisfactory accuracy (R2 = 0.89, P < 0.001); (3) all landscape indices of OV, with the exception of patch density, were positively correlated with SSM at plot scale, while most of the landscape indices of LP and IV showed negative correlations (P < 0.05). Our results indicated that patchiness intensified the spatial heterogeneity of SSM and potentially accelerated the alpine meadow degradation. Preventing the development of OV into IV and the expansion of LP is a critical task for alpine meadow management and restoration.

scholarly journals Culture without copying or selection

2021 ◽  
pp. 1-31
Author(s):  
Alberto Acerbi ◽  
Mathieu Charbonneau ◽  
Helena Miton ◽  
Thom Scott-Phillips
Keyword(s):  
Cultural Evolution ◽  
Stochastic Models ◽  
Selection Process ◽  
Population Level ◽  
Fundamental Question ◽  
High Fidelity ◽  
Formal Support ◽  
Random Transformation ◽  
Degree Of Similarity

Abstract Typical examples of cultural phenomena all exhibit a degree of similarity across time and space at the level of the population. As such, a fundamental question for any science of culture is, what ensures this stability in the first place? Here we focus on the evolutionary and stabilizing role of ‘convergent transformation’, in which one item causes the production of another item whose form tends to deviate from the original in a directed, non-random way. We present a series of stochastic models of cultural evolution investigating its effects. Results show that cultural stability can emerge and be maintained by virtue of convergent transformation alone, in the absence of any form of copying or selection process. We show how high-fidelity copying and convergent transformation need not be opposing forces, and can jointly contribute to cultural stability. We finally analyse how non-random transformation and high-fidelity copying can have different evolutionary signatures at population level, and hence how their distinct effects can be distinguished in empirical records. Collectively, these results supplement existing approaches to cultural evolution based on the Darwinian analogy, while also providing formal support for other frameworks — such as Cultural Attraction Theory — that entail its further loosening.

scholarly journals Stochastic models of receptor oligomerization by bivalent ligand

2006 ◽  
Vol 3 (9) ◽  
pp. 545-559 ◽  
Author(s):  
Tomás Alarcón ◽  
Karen M Page
Keyword(s):  
Stochastic Models ◽  
Cellular Response ◽  
Cell Activation ◽  
Design Principle ◽  
Ligand Concentration ◽  
Bivalent Ligand ◽  
Oligomer Formation ◽  
Receptor Oligomerization ◽  
Stochastic Fluctuations

In this paper, we develop stochastic models of receptor binding by a bivalent ligand. A detailed kinetic study allows us to analyse the role of cross-linking in cell activation by receptor oligomerization. We show how oligomer formation could act to buffer intracellular signalling against stochastic fluctuations. In addition, we put forward the hypothesis that formation of long linear oligomers increases the range of ligand concentration to which the cell is responsive, whereas formation of closed oligomers increases ligand concentration specificity. Thus, different physiological functions requiring different degrees of specificity to ligand concentration would favour formation of oligomers with different lengths and geometries. Furthermore, provided that ligand concentration specificity is taken as a design principle, our model enables us to estimate parameters, such as the minimum proportion of receptors, that must engage in oligomer formation in order to trigger a cellular response.

scholarly journals A Stochastic Compartmental Model for COVID-19

2020 ◽  
Author(s):  
Giorgio Sonnino ◽  
Fernando Mora ◽  
Pasquale Nardone
Keyword(s):  
Health Care ◽  
Probability Density Function ◽  
Stochastic Models ◽  
Compartmental Model ◽  
Real Data ◽  
Third Wave ◽  
Theoretical Predictions ◽  
Massive Distribution ◽  
Hospital Capacities

AbstractWe propose two stochastic models for the Coronavirus pandemic. The statistical properties of the models, in particular the correlation functions and the probability density function, have duly been computed. Our models, which generalises a model previously proposed and published in a specialised journal, take into account the adoption of the lockdown measures as well as the crucial role of the hospitals and Health Care Institutes. To accomplish this work we have analysed two scenarios: the SIS-model (Susceptible ⇒ Infectious ⇒ Susceptible) in presence of the lockdown measures and the SIS-model integrated with the action of the hospitals (always in presence of the lockdown measures). We show that in the case of the pure SIS-model, once the lockdown measures are removed, the Coronavirus will start growing again. However, in the second scenario, beyond a certain threshold of the hospital capacities, the Coronavirus is not only kept under control, but its capacity to spread tends to diminish in time. Therefore, the combined effect of the lockdown measures with the action of the hospitals and health Institutes is able to contain and dampen the spread of the SARS-CoV-2 epidemic. This result can be used during a period of time when the massive distribution of delivery of a limited number of vaccines in a given population is not yet feasible. By way of example, we analysed the data for USA and France where the intensities of the noise have been estimated by Statistical Mechanics. In particular, for USA we have analysed two possible hypotheses: USA is still subject to the first wave of infection by and USA is in the second (or third) wave of SARS-CoV-2 infection.The agreement between theoretical predictions and real data confirms the validity of our approach.

Modelling Extreme Market Events. A Report of the Benchmarking Stochastic Models Working Party

2009 ◽  
Vol 15 (1) ◽  
pp. 99-201 ◽  
Author(s):  
R. Frankland ◽  
A. D. Smith ◽  
T. Wilkins ◽  
E. Varnell ◽  
A. Holtham ◽  
...  
Keyword(s):  
Interest Rate ◽  
Stochastic Models ◽  
Financial Services ◽  
Working Party ◽  
Prior Beliefs

ABSTRACTThis paper focusses on some practical issues that can arise when developing methodologies for calculating benchmark figures for extreme market events, particularly in the context of the Financial Services Authority's ICAS regime. The paper limits discussion to equity and interest rate risks. Whilst not intended to constitute formal guidance, it is hoped that the material contained within the paper will be useful to practitioners. The paper acknowledges the role of prior beliefs in the choice of data to be used for modelling and its influence upon the ensuing results.

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