Literature DB >> 16701286

Skeletons, noise and population growth: the end of an old debate?

Tim Coulson1, Pejman Rohani, Mercedes Pascual.   

Abstract

Population dynamics models remain largely deterministic, although the presence of random fluctuations in nature is well recognized. This deterministic approach is based on the implicit assumption that systems can be separated into a deterministic part that captures the essential features of the system and a random part that can be neglected. But is it possible, in general, to understand population dynamics without the explicit consideration of random fluctuations? Here, we suggest perhaps not, and argue that the dynamics of many systems are a result of interactions between the deterministic nonlinear skeleton and noise.

Year:  2004        PMID: 16701286     DOI: 10.1016/j.tree.2004.05.008

Source DB:  PubMed          Journal:  Trends Ecol Evol        ISSN: 0169-5347            Impact factor:   17.712


  27 in total

1.  Stochasticity in staged models of epidemics: quantifying the dynamics of whooping cough.

Authors:  Andrew J Black; Alan J McKane
Journal:  J R Soc Interface       Date:  2010-02-17       Impact factor: 4.118

2.  Revealing the ghost in the machine: using spectral analysis to understand the influence of noise on population dynamics.

Authors:  Tim G Benton
Journal:  Proc Natl Acad Sci U S A       Date:  2006-11-27       Impact factor: 11.205

3.  Noise, nonlinearity and seasonality: the epidemics of whooping cough revisited.

Authors:  Hanh T H Nguyen; Pejman Rohani
Journal:  J R Soc Interface       Date:  2008-04-06       Impact factor: 4.118

4.  On methods for studying stochastic disease dynamics.

Authors:  M J Keeling; J V Ross
Journal:  J R Soc Interface       Date:  2008-02-06       Impact factor: 4.118

5.  Decreasing stochasticity through enhanced seasonality in measles epidemics.

Authors:  N B Mantilla-Beniers; O N Bjørnstad; B T Grenfell; P Rohani
Journal:  J R Soc Interface       Date:  2009-10-14       Impact factor: 4.118

6.  Rates of coalescence for common epidemiological models at equilibrium.

Authors:  Katia Koelle; David A Rasmussen
Journal:  J R Soc Interface       Date:  2011-09-15       Impact factor: 4.118

7.  Hybrid Markov chain models of S-I-R disease dynamics.

Authors:  Nicolas P Rebuli; N G Bean; J V Ross
Journal:  J Math Biol       Date:  2016-12-24       Impact factor: 2.259

8.  Experimental evidence for density-dependent survival in mallard (Anas platyrhynchos) ducklings.

Authors:  Gunnar Gunnarsson; Johan Elmberg; Kjell Sjöberg; Hannu Pöysä; Petri Nummi
Journal:  Oecologia       Date:  2006-05-31       Impact factor: 3.225

9.  The challenges to inferring the regulators of biodiversity in deep time.

Authors:  Thomas H G Ezard; Tiago B Quental; Michael J Benton
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2016-04-05       Impact factor: 6.237

10.  Plug-and-play inference for disease dynamics: measles in large and small populations as a case study.

Authors:  Daihai He; Edward L Ionides; Aaron A King
Journal:  J R Soc Interface       Date:  2009-06-17       Impact factor: 4.118

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