The thesis introduces a new integrated approach to ecological and evolutionary modeling, the goal of which is to create an analytical platform for applied interdisciplinary researches. This Conspecific Community Dynamics Model (CCDM) approach establishes links between the ecology of the individual, community ecology, behavioral ecology, population dynamics and natural selection. The approach related to co-selection timescale and singlespecies (conspecific) community scale. The co-selection timescale extends from several to several hundreds of generations. Presumably, at this timescale, viable mutations leading to a change in the underlying physiology of the species do not occur, but the interaction between individuals within a conspecific community can lead to a change in the frequency distribution of certain functional traits. The conspecific community scale is an organizational scale, which is intermediate between entire population and the individual. This is the scale on which an organism can be recognized not only as a representative of their own species, not only as a passive carrier of genetic material, but also as a member of the conspecific community in which its reproductive success depends on other members of this community. This is the scale on which the differences between the two conspecific communities can potentially undergo a critical transition and becomes differences between species, and thus, this scale may occur at the earliest stages of reproductive isolation. Finally, this is the scale at which apparently random differences between individuals are added to the overall mosaic of an intrinsically organized system. This approach emphasizes that the phenomenon of single-species organisms within a population organizing themselves into conspecific communities has deep natural reasons and cannot be ignored; furthermore, this fact may become a key nodal point of the synthesis of ecology and evolution. The approach also stresses that such synthesis can hardly be realized at the level of mechanical combinations of existing models, but requires a special analytical platform that would (i) include the basic postulates of population ecology, quantitative genetics and evolutionary biology, (ii) allow, despite the inherent stochasticity, the investigation of conspecific communities at the level of cause-effect relationships. Half of the thesis relates to the basic issues associated with the mathematical formalization of the approach, the other half is entirely devoted to its various applications in the fields of demography, fish population dynamics, community ecology, microbiology and community epidemiology. For each of these fields a set of CCDM models are constructed, subsequent analyses of which lead to interesting results. These results are intended to demonstrate the great potential of this approach, its ability to integrate various aspects of the population and its analytical power. It should be emphasized that this approach does not create any new entities, but is instead based on the widely-accepted (within each particular field) postulates. Nevertheless, the consideration of these postulates in combination sometimes leads to much unexpected results. However, the distinguishing feature of the approach is its analyticity, that is, any result that at first glance seems unusual, can be traced to these basic tenets.