Stochasticity in the Parasite-Driven Trait Evolution of Competing Species Masks the Distinctive Consequences of Distance Metrics
| Autor: | Ariel L. Babierra, Maica Krizna Areja Gavina, Genaro A. Cuaresma, Jomar F. Rabajante, Anthony L. Cueno, Dylan Antonio S. J. Talabis, Christian Alvin H. Buhat |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Mathematical optimization
Computer science parasitism Population Bioengineering Biology Quantitative trait locus lcsh:Chemical technology quantitative trait lcsh:Chemistry evolutionary dynamics Manhattan norm Euclidean norm Chebyshev norm exploitation egalitarianism Econometrics Chemical Engineering (miscellaneous) Carrying capacity Quantitative Biology::Populations and Evolution lcsh:TP1-1185 Evolutionary dynamics education Randomness Selection (genetic algorithm) education.field_of_study applied_mathematics Process Chemistry and Technology Euclidean distance lcsh:QD1-999 Trait |
| Zdroj: | Processes; Volume 5; Issue 4; Pages: 74 Processes, Vol 5, Iss 4, p 74 (2017) |
| ISSN: | 2227-9717 |
| DOI: | 10.3390/pr5040074 |
| Popis: | Various distance metrics and their induced norms are employed in the quantitative modeling of evolutionary dynamics. Minimization of these distance metrics when applied to evolutionary optimization are hypothesized to result in different outcomes. Here, we apply the different distance metrics to the evolutionary trait dynamics brought about by the interaction between two competing species infected by parasites (exploiters). We present deterministic cases showing the distinctive selection outcomes under the Manhattan, Euclidean and Chebyshev norms. Specifically, we show how they differ in the time of convergence to the desired optima (e.g., no disease), and in the egalitarian sharing of carrying capacity between the competing species. However, when randomness is introduced to the population dynamics of parasites and to the trait dynamics of the competing species, the distinctive characteristics of the outcomes under the three norms become indistinguishable. Our results provide theoretical cases when evolutionary dynamics using different distance metrics exhibit similar outcomes. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|