http://www.cnr.it/ontology/cnr/individuo/prodotto/ID197352
Nonlinear functional response parameter estimation in a stochastic predator-prey model (Articolo in rivista)
- Type
- Label
- Nonlinear functional response parameter estimation in a stochastic predator-prey model (Articolo in rivista) (literal)
- Anno
- 2012-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.3934/mbe.2012.9.75 (literal)
- Alternative label
Gilioli G., Pasquali S., Ruggeri F. (2012)
Nonlinear functional response parameter estimation in a stochastic predator-prey model
in Mathematical biosciences and engineering; American Institute of Mathematical Sciences, Springfield [MO] (Stati Uniti d'America)
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Gilioli G., Pasquali S., Ruggeri F. (literal)
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- http://www.aimsciences.org/journals/displayArticlesnew.jsp?paperID=6845 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
- Rivista
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
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- ISI Web of Science (WOS) (literal)
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- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- G. Gilioli - Università di Brescia; S. Pasquali e F. Ruggeri - CNR IMATI (literal)
- Titolo
- Nonlinear functional response parameter estimation in a stochastic predator-prey model (literal)
- Abstract
- Parameter estimation for the functional response of predator-prey systems is a critical methodological problem in population ecology. In this paper we consider a stochastic predator-prey system with non-linear Ivlev functional response and propose a method for model parameter estimation based on time series of field data. We tackle the problem of parameter estimation using a Bayesian approach relying on a Markov Chain Monte Carlo algorithm. The efficiency of the method is tested on a set of simulated data. Then, the method is applied to a predator-prey system of importance for Integrated Pest Management and biological control, the pest mite Tetranychus urticae and the predatory mite Phytoseiulus persimilis. The model is estimated on a dataset obtained from a field survey. Finally, the estimated model is used to forecast predator-prey dynamics in similar fields, with slightly different initial conditions. (literal)
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