Your browser doesn't support javascript.
loading
Quantifying population dynamics via a geometric mean predator-prey model.
da Silva, S L; Carbone, A; Kaniadakis, G.
Afiliação
  • da Silva SL; Department of Applied Science and Technology, Politecnico di Torino, 10129 Turin, Italy.
  • Carbone A; GISIS, Fluminense Federal University, Campus Praia Vermelha, 24210-346 Niterói/RJ, Brazil.
  • Kaniadakis G; Department of Applied Science and Technology, Politecnico di Torino, 10129 Turin, Italy.
Chaos ; 33(8)2023 Aug 01.
Article em En | MEDLINE | ID: mdl-37535023
ABSTRACT
An integrable Hamiltonian variant of the two species Lotka-Volterra (LV) predator-prey model, shortly referred to as geometric mean (GM) predator-prey model, has been recently introduced. Here, we perform a systematic comparison of the dynamics underlying the GM and LV models. Though the two models share several common features, the geometric mean dynamics exhibits a few peculiarities of interest. The structure of the scaled-population variables reduces to the simple harmonic oscillator with dimensionless natural time TGM varying as ωGMt with ωGM=c12c21. We found that the natural timescales of the evolution dynamics are amplified in the GM model compared to the LV one. Since the GM dynamics is ruled by the inter-species rather than the intra-species coefficients, the proposed model might be of interest when the interactions among the species, rather than the individual demography, rule the evolution of the ecosystems.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Ecossistema / Modelos Biológicos Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Revista: Chaos Assunto da revista: CIENCIA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Itália

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Ecossistema / Modelos Biológicos Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Revista: Chaos Assunto da revista: CIENCIA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Itália