scholarly journals The adaptive dynamics of function-valued traits

2006 ◽  
Vol 241 (2) ◽  
pp. 370-389 ◽  
Author(s):  
Ulf Dieckmann ◽  
Mikko Heino ◽  
Kalle Parvinen
Keyword(s):  
2005 ◽  
Vol 52 (1) ◽  
pp. 1-26 ◽  
Author(s):  
Kalle Parvinen ◽  
Ulf Dieckmann ◽  
Mikko Heino

2018 ◽  
Vol 4 (1) ◽  
Author(s):  
María Arribas ◽  
Jacobo Aguirre ◽  
Susanna Manrubia ◽  
Ester Lázaro
Keyword(s):  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ulrich K. Steiner ◽  
Shripad Tuljapurkar ◽  
Deborah A. Roach

AbstractSimple demographic events, the survival and reproduction of individuals, drive population dynamics. These demographic events are influenced by genetic and environmental parameters, and are the focus of many evolutionary and ecological investigations that aim to predict and understand population change. However, such a focus often neglects the stochastic events that individuals experience throughout their lives. These stochastic events also influence survival and reproduction and thereby evolutionary and ecological dynamics. Here, we illustrate the influence of such non-selective demographic variability on population dynamics using population projection models of an experimental population of Plantago lanceolata. Our analysis shows that the variability in survival and reproduction among individuals is largely due to demographic stochastic variation with only modest effects of differences in environment, genes, and their interaction. Common expectations of population growth, based on expected lifetime reproduction and generation time, can be misleading when demographic stochastic variation is large. Large demographic stochastic variation exhibited within genotypes can lower population growth and slow evolutionary adaptive dynamics. Our results accompany recent investigations that call for more focus on stochastic variation in fitness components, such as survival, reproduction, and functional traits, rather than dismissal of this variation as uninformative noise.


2021 ◽  
Author(s):  
Vu Nguyen ◽  
Dervis Vural

In a complex community, species continuously adapt to each other. On rare occasions, the adaptation of a species can lead to the extinction of others, and even its own. ``Adaptive dynamics'' is the standard mathematical framework to describe evolutionary changes in community interactions, and in particular, predict adaptation driven extinction. Unfortunately, most authors implement the equations of adaptive dynamics through computer simulations, that require assuming a large number of questionable parameters and fitness functions. In this study we present analytical solutions to adaptive dynamics equations, thereby clarifying how outcomes depend on any computational input. We develop general formulas that predict equilibrium abundances over evolutionary time scales. Additionally, we predict which species will go extinct next, and when this will happen.


Author(s):  
Michael Doebeli

This chapter discusses partial differential equation models. Partial differential equations can describe the dynamics of phenotype distributions of polymorphic populations, and they allow for a mathematically concise formulation from which some analytical insights can be obtained. It has been argued that because partial differential equations can describe polymorphic populations, results from such models are fundamentally different from those obtained using adaptive dynamics. In partial differential equation models, diversification manifests itself as pattern formation in phenotype distribution. More precisely, diversification occurs when phenotype distributions become multimodal, with the different modes corresponding to phenotypic clusters, or to species in sexual models. Such pattern formation occurs in partial differential equation models for competitive as well as for predator–prey interactions.


Author(s):  
Masanari Asano ◽  
Takahisa Hashimoto ◽  
Andrei Khrennikov ◽  
Masanori Ohya ◽  
Yoshiharu Tanaka

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