STOCHASTICITY AND COOPERATIVE HUNTING IN PREDATOR–PREY INTERACTIONS

DOI10.1142/S0218339021400040zbMath1469.92090OpenAlexW3141350746WikidataQ115523334 ScholiaQ115523334MaRDI QIDQ5003695

Xiaochuan Hu, Sophia R.-J. Jang

Publication date: 29 July 2021

Published in: Journal of Biological Systems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1142/s0218339021400040

zbMATH Keywords

cooperative huntingcontinuous-time Markov chains: Itô differential equations

Mathematics Subject Classification ID

Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Population dynamics (general) (92D25)

Related Items (2)

EXTINCTION AND PERSISTENCE OF A HARVESTED PREY–PREDATOR MODEL INCORPORATING GROUP DEFENCE AND DISEASE IN PREY: SPECIAL EMPHASIS ON STOCHASTIC ENVIRONMENT ⋮ Effects of prey refuge and predator cooperation on a predator–prey system

Uses Software

• sde

Cites Work

• Persistence in variable-yield nutrient-plankton models
• Effects of spatial grouping on the functional response of predators
• Numerical solution of SDE through computer experiments. Including floppy disk
• Deterministic and stochastic nutrient-phytoplankton-zooplankton models with periodic toxin producing phytoplankton
• Stochastic modeling of phytoplankton allelopathy
• Impacts of foraging facilitation among predators on predator-prey dynamics
• Hunting cooperation and Allee effects in predators
• Simulation and inference for stochastic differential equations. With R examples.
• A comparison of persistence-time estimation for discrete and continuous stochastic population models that include demographic and environmental variability
• Hunting Cooperation in a Discrete-Time Predator–Prey System
• Cooperative hunting in a discrete predator–prey system II
• Modeling with Itô Stochastic Differential Equations
• STOCHASTIC MODELING OF PHYTOPLANKTON–ZOOPLANKTON INTERACTIONS WITH TOXIN PRODUCING PHYTOPLANKTON
• Models of cytokine dynamics in the inflammatory response of viral zoonotic infectious diseases
• Persistence in dynamical systems

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