Stochastic sensitivity technique in a persistence analysis of randomly forced population systems with multiple trophic levels / Bashkirtseva Irina,Ryashko Lev,Ryazanova Tatyana // MATHEMATICAL BIOSCIENCES. - 2017. - V. 293, l. . - P. 38-45.

ISSN/EISSN:

0025-5564 / 1879-3134

Type:

Article

Abstract:

Motivated by important ecological applications we study how noise can reduce a number of trophic levels in hierarchically related multidimensional population systems. A nonlinear model with three trophic levels under the influence of external stochastic forcing is considered as a basic conceptual example. We analyze a probabilistic mechanism of noise-induced extinction of separate populations in this ``prey predator-top predator{''} system. We propose a new general mathematical approach for the estimation of the proximity of equilibrium regimes of this stochastic model to hazardous borders where abrupt changes in dynamics of ecological systems can occur. Our method is based on the stochastic sensitivity function technique and visualization method of confidence domains. Constructive abilities of this mathematical approach are demonstrated in the analysis of different scenaria of noise-induced reducing of the number of trophic levels. (C) 2017 Elsevier Inc. All rights reserved.

Author keywords:

Trophic levels; Population systems; Noise-induced extinction; Stochastic sensitivity function FOOD-CHAIN; CATASTROPHIC SHIFTS; EXTINCTION RISK; CHAOS; MODELS; ECOSYSTEMS; DYNAMICS; NOISE; BIODIVERSITY

DOI:

10.1016/j.mbs.2017.08.007

Web of Science ID:

ISI:000413387200005

Соавторы в МНС:

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Другие поля

Поле	Значение
Month	NOV
Publisher	ELSEVIER SCIENCE INC
Address	360 PARK AVE SOUTH, NEW YORK, NY 10010-1710 USA
Language	English
EISSN	1879-3134
Keywords-Plus	FOOD-CHAIN; CATASTROPHIC SHIFTS; EXTINCTION RISK; CHAOS; MODELS; ECOSYSTEMS; DYNAMICS; NOISE; BIODIVERSITY
Research-Areas	Life Sciences \& Biomedicine - Other Topics; Mathematical \& Computational Biology
Web-of-Science-Categories	Biology; Mathematical \& Computational Biology
Author-Email	irina.bashkirtseva@urfu.ru lev.ryashko@urfu.ru tatyana.ryazanova@urfu.ru
Funding-Acknowledgement	Russian Science Foundation {[}16-11-10098]
Funding-Text	The work was supported by Russian Science Foundation (N 16-11-10098).
Number-of-Cited-References	40
Usage-Count-Last-180-days	2
Usage-Count-Since-2013	2
Journal-ISO	Math. Biosci.
Doc-Delivery-Number	FK3LS