scholarly journals Dynamics induced by environmental stochasticity in a phytoplankton-zooplankton system with toxic phytoplankton

2021 ◽  
Vol 18 (4) ◽  
pp. 4101-4126
Author(s):  
He Liu ◽  
◽  
Chuanjun Dai ◽  
Hengguo Yu ◽  
Qing Guo ◽  
...  
Keyword(s):  
Environmental Stochasticity ◽  
Toxic Phytoplankton

Environmental Stochasticity and Extinction Risk in a Population of a Small Songbird, the Great Tit

1998 ◽  
Vol 151 (5) ◽  
pp. 441
Author(s):  
Saether ◽  
Engen ◽  
Islam ◽  
McCleery ◽  
Perrins
Keyword(s):  
Extinction Risk ◽  
Great Tit ◽  
Environmental Stochasticity

Carry‐over effects of environmental stochasticity of the California Current on body condition and wing length of breeding Black‐vented Shearwaters ( Puffinus opisthomelas )

Ibis ◽  
2021 ◽  
Author(s):  
Cecilia Soldatini ◽  
Martha Patricia Rosas Hernandez ◽  
Yuri V. Albores‐Barajas ◽  
Giulia Bambini ◽  
Adrian Munguia‐Vega ◽  
...  
Keyword(s):  
Body Condition ◽  
Wing Length ◽  
California Current ◽  
Environmental Stochasticity ◽  
Carry Over

ECPSES: Estimating Critical Population Size in the Presence of Environmental Stochasticity

1987 ◽  
Vol 41 (4) ◽  
pp. 334
Author(s):  
Charles J. Mode ◽  
Marc D. Cain ◽  
Marc E. Jacobson
Keyword(s):  
Population Size ◽  
Environmental Stochasticity

scholarly journals On the Dynamical Behavior of Toxic-Phytoplankton-Zooplankton Model with Delay

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Mehbuba Rehim ◽  
Weixin Wu ◽  
Ahmadjan Muhammadhaji
Keyword(s):  
Time Delay ◽  
Phytoplankton Bloom ◽  
Dynamical Behavior ◽  
Time Lag ◽  
Toxic Substance ◽  
Predation Rate ◽  
Dynamical Behaviour ◽  
Toxic Substances ◽  
Toxic Phytoplankton ◽  
Discrete Time Delay

A toxin producing phytoplankton-zooplankton model with inhibitory exponential substrate and time delay has been formulated and analyzed. Since the liberation of toxic substances by phytoplankton species is not an instantaneous process but is mediated by some time lag required for maturity of the species and the zooplankton mortality due to the toxic phytoplankton bloom occurs after some time laps of the bloom of toxic phytoplankton, we induced a discrete time delay to both of the consume response function and distribution of toxic substance term. Furthermore, based on the fact that the predation rate decreases at large toxic-phytoplankton density, the system is modelled via a Tissiet type functional response. We study the dynamical behaviour and investigate the conditions to guarantee the coexistence of two species. Analytical methods and numerical simulations are used to obtain information about the qualitative behaviour of the models.

scholarly journals Chaos and the (un)predictability of evolution in a changing environment

2017 ◽  
Author(s):  
Artur Rego-Costa ◽  
Florence Débarre ◽  
Luis-Miguel Chevin
Keyword(s):  
Evolutionary Dynamics ◽  
Initial Conditions ◽  
Strong Dependence ◽  
Environmental Stochasticity ◽  
Phenotypic Evolution ◽  
Evolutionary System ◽  
Chaotic Oscillations ◽  
Changing Environment ◽  
Environmental Forcing ◽  
Evolutionary Trajectories

Among the factors that may reduce the predictability of evolution, chaos, characterized by a strong dependence on initial conditions, has received much less attention than randomness due to genetic drift or environmental stochasticity. It was recently shown that chaos in phenotypic evolution arises commonly under frequency-dependent selection caused by competitive interactions mediated by many traits. This result has been used to argue that chaos should often make evolutionary dynamics unpredictable. However, populations also evolve largely in response to external changing environments, and such environmental forcing is likely to influence the outcome of evolution in systems prone to chaos. We investigate how a changing environment causing oscillations of an optimal phenotype interacts with the internal dynamics of an eco-evolutionary system that would be chaotic in a constant environment. We show that strong environmental forcing can improve the predictability of evolution, by reducing the probability of chaos arising, and by dampening the magnitude of chaotic oscillations. In contrast, weak forcing can increase the probability of chaos, but it also causes evolutionary trajectories to track the environment more closely. Overall, our results indicate that, although chaos may occur in evolution, it does not necessarily undermine its predictability.

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