A new mathematical method for the dynamic analysis of nonlinear compartmental systems in the context of ecology has recently been developed by the author and was presented in a separate article. Based on this methodology, multiple new dynamic ecological system measures and indices of matrix, vector, and scalar types are systematically introduced in the present paper. These mathematical system analysis tools are quantitative ecological indicators that monitor the flow distribution and storage organization, quantify the direct, indirect, acyclic, cycling, and transfer (diact) effect and utility of one compartment directly or indirectly on another, identify the system efficiency and stress, measure the compartmental exposure to system flows, determine the residence time and compartmental activity levels, and ascertain the restoration time and resilience in the case of disturbances. The proposed dynamic system measures and indices, thus, extract detailed information about ecosystems' characteristics, as well as their functions, properties, behaviors, and various other system attributes that are potentially hidden in and even obscured by data. A dynamic technique for the quantitative characterization and classification of main interspecific interactions and the determination of their strength within food webs is also developed based on the diact effect and utility indices. Moreover, major concepts and quantities in the current static network analyses are also extended to nonlinear dynamic settings and integrated with the proposed dynamic measures and indices in this unifying mathematical framework. Therefore, the proposed methodology enables a holistic view and analysis of ecological systems. We consider that the proposed methodology brings a novel complex system theory to the service of urgent and challenging environmental problems of the day and has the potential to lead the way to a more formalistic ecological science.Key words. complex systems theory, dynamic ecological network analysis, nonlinear dynamic compartmental systems, dynamic system and subsystem partitioning, diact flows and storages, diact effect measures and indices, diact system efficiencies and stress, diact utility measures and indices, diact exposures and residence times, system resilience, dynamic cycling index, dynamic indirect effects, food webs, interspecific interactions, dynamic input-output analysis, dynamic input-). paths within subsystems. The dynamic direct, indirect, acyclic, cycling, and transfer (diact) flows and associated storages transmitted from one compartment, directly or indirectly, to any other are also analytically characterized, systematically classified, and mathematically formulated. Consequently, the evolution of the initial stocks, environmental inputs, and arbitrary intercompartmental system flows, as well as the associated storages derived from these stocks, inputs, and flows can be tracked individually and separately within the system.The proposed methodology constructs a foundation for the development of new mathemat...