Abstract :
Niche construction, a term referring to the modification of their environments by any organism, can profoundly influence the genetic structure and evolutionary dynamics of population. In the paper, we established a 2D individual-based lattice model of niche construction with probabilistic transition rule to explore the typical spatial distribution and evolutional dynamics of polymorphism, environmental resource and genotype frequency. The effect of extinction on polymorphism was also discussed. In simulation, the model presents random, aggregative and uniform distribution patterns of different genotypes. Compared with the results in the present/absent of niche construction, it is an active force for polymorphism if without heterozygote superiority. The positive feedback between genotype and environmental resource contributes population to fit the environment better by the self-regulation of different genotypes and when the external force changes the environment, even altering the direction of niche construction. Niche construction results in the spatial heterogeneity of environmental resource, which is an ecological imprint of organism on environment and a foundation of polymorphic formation. With habitat deterioration, niche construction accelerates the formation of steady polymorphism and impedes the harmful influence of environment on the population, which embody a life-history strategy of organism under unfavorable environment. These results suggest that niche construction can lead to the coexistence with alterative polymorphism through genotype-environment feedback.
Keywords :
ecology; environmental management; evolutionary computation; polymorphism; 2D individual-based lattice model; environmental resource; evolutionary dynamics; genetic structure; genotype frequency; genotype-environment feedback; habitat deterioration; niche construction; polymorphic formation; population; positive feedback; probabilistic transition rule; spatial distribution; spatial polymorphism; uniform distribution pattern; Africa; Biological system modeling; Educational technology; Environmental factors; Force feedback; Frequency; Genetic mutations; Laboratories; Mathematics; Organisms;