Impact of wind in the dynamics of prey–predator interactions

Barman, Dipesh; Roy, Jyotirmoy; Alam, Shariful

doi:10.1016/j.matcom.2021.07.022

Cited by 14 publications

(7 citation statements)

References 35 publications

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“…Now, since (x 0 ,y 1 0 ) is an equilibrium point of the system in the (x,y 1 ) plane, we have q 1 x 0 = 0 (see second Equation ( 10)). So, we have stability if, q 2 x 0 < q 1 x 0 = 0 (13) or instability if the sign in Equation ( 13) is >. This result is summarized in the proposition below.…”

Section: Theory Of Competitive Evolution In the Predatory Systemmentioning

confidence: 84%

“…Let (x 0 ,y 1 0 ) be a stable equilibrium point of the system for (x,y 1 ) alone. Then the point (x,y 1 ,0) is a three-dimensional attractor if ( 13) is satisfied, and it is transversely unstable if (13) with sign > is satisfied. A similar result holds for a stable equilibrium in the (x,y 2 )-plane.…”

Section: Theory Of Competitive Evolution In the Predatory Systemmentioning

confidence: 99%

“…We shall see that these elements are important for correctly interpreting the causality and implications of the choices made by evolution. However, let us remark that predatorprey interactions depend not only on biotic factors, but also on many other abiotic factors, such as wind speed, which can crucially alter the predation efficiency of the predator population; see [12] where the impact of wind speed and seasonality on different parameters has been studied for a model proposed in [13].…”

Section: Introductionmentioning

confidence: 99%

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Trends and Paradoxes of Competitive Evolution in the Predation Mechanism

Sanchez-Palencia,

Aziz-Alaoui

2024

Mathematics

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We give a series of numerical examples of competitive evolution in the predation system, showing in some cases how the choice is made to increase the efficiency of the predation mechanism (or other significant parameters) to the detriment of populations (both of prey and predators). We then develop the mathematical theory that enables us to understand the causality involved, and we identify a trend towards the emergence of the functional predation mechanism as such (and not of populations of the species involved). The realization of this trend only takes place when the conditions for it are offered by the hazards proposed to successive competitive choices. The logical structure of this trend is similar to that of the “tendency of rate of profit to fall” in certain economic models.

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Section: Theory Of Competitive Evolution In the Predatory Systemmentioning

confidence: 84%

Section: Theory Of Competitive Evolution In the Predatory Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Trends and Paradoxes of Competitive Evolution in the Predation Mechanism

Sanchez-Palencia,

Aziz-Alaoui

2024

Mathematics

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“…Here, we have considered a specialist predator-prey model from Upadhyay and Iyengar [23] and modified it by implementing the concept that wind reduces the predation efficiency. The modification of the functional response has been done according to the derivation of Barman et al [21]. The functional response has been modified by considering the fact that wind speed increases the prey-handling time of predators.…”

Section: Model Systemmentioning

confidence: 99%

“…All of the aforementioned arguments imply that the concept of wind should be introduced into the model system at the time of creating a mathematical model to estimate the dynamics of a predator-prey system. In this context, Barman et al [21] were the first ones to design a mathematical model by modifying the Holling type-II functional response under windy situations and studying the impacts of it on system dynamics. Later, Barman et al [22] performed another study in a spatio-temporal modelling sense to predict possible complex dynamics by considering herd behaviour of prey species in windy conditions.…”

Section: Introductionmentioning

confidence: 99%

Modelling Predator–Prey Interactions: A Trade-Off between Seasonality and Wind Speed

Barman,

Upadhyay

2023

Mathematics

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Predator–prey interactions do not solely depend on biotic factors: rather, they depend on many other abiotic factors also. One such abiotic factor is wind speed, which can crucially change the predation efficiency of the predator population. In this article, the impact of wind speed along with seasonality on various parameters has been investigated. Here, we present two continuous-time models with specialist and generalist type predators incorporating the effect of wind and the seasonality on the model parameters. It has been observed that wind speed plays a significant role in controlling the system dynamics for both systems. It makes the systems stable for both of the seasonally unperturbed systems. However, it controls the chaotic dynamics that occur in case of no wind for the seasonally perturbed system with the predator as a specialist. On the other hand, for the seasonally perturbed system with a generalist predator, it controls period-four oscillations (which occur considering no wind speed) to simple limit-cycle oscillations. Furthermore, the wind parameter has a huge impact on the survival of predator species. The survival of predator species may be achieved by ensuring a suitable range of wind speeds in the ecosystem. Therefore, we observe that seasonality introduces chaos, but wind reduces it. These results may be very useful for adopting necessary management for the conservation of endangered species that are massively affected by wind speed in an ecosystem.

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Influence of Ecological/Climatic Change

Sahayaraj,

Hassan

2023

Worldwide Predatory Insects in Agroecosystems

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Impact of wind in the dynamics of prey–predator interactions

Cited by 14 publications

References 35 publications

Trends and Paradoxes of Competitive Evolution in the Predation Mechanism

Trends and Paradoxes of Competitive Evolution in the Predation Mechanism

Modelling Predator–Prey Interactions: A Trade-Off between Seasonality and Wind Speed

Influence of Ecological/Climatic Change

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