perhaps we can glean some insight into better understanding the functioning of social ecosystems and where their evolutionary pathway might still be taking them.

We just saw that the hierarchy of needs has both an ontogenic and a phylogenic component. Moreover, the hierarchy correspondingly reflects evolution along both those dimensions, essentially comprising a vector of selection. From that description alone, it suggests the similarity of the hierarchy of needs in social ecosystems and DNA in physical ecosystems. The importance of that observation is that it provides a foundation for a common view of evolution across the two ecosystems. Instead of defining, as Richard Dawkins does in The Selfish Gene, on one hand a constituent molecule of DNA with its genes, and on the other hand an equivalent to genes called memes that is lacking a constituent organization, we can see a parallel between physical and social ecosystems, with DNA (physical) and the hierarchy of needs (social) as organizational entities, where parts of each carry vectors of evolution. From our perspective, the needs hierarchy itself, with its constituents across the ontogenic and phylogenic dimensions of the pretergenesis table, seems to naturally map to the well-understood function of genes in biology.

Model of Social Ecosystems

Social ecosystems are the enablers of groups. Groups exist because they comprise effective mechanisms for survival as judged by natural selection. Groups have been essential to the ascendance of the human species; without groups it would be problematic whether individual humans could long survive. A variety of group types are found among the species today. While each type may exhibit different capabilities, they come from a common mold and can be characterized by a high-level model of organization and operation. The capabilities of groups or perhaps more appropriately, of grouping mechanisms, have expanded over time due to a series of evolutionary changes affecting the individual human and through which have arisen enhanced capabilities for the establishment and functioning of increasingly complex multi-person ensembles. These changes presented in the evolutionary development of the individual and then were expressed through groups of individuals.

We propose a model of social ecosystems through which various grouping mechanisms can be represented and compared; a model that offers the prospect of specialization, allowing a characterization of each of the grouping mechanisms that have been identified. With some degree of rigor, we can use this model to consider the mechanisms through which interactions within the groups and among the groups are effected. We observe that this same model provides a means for analyzing the structure and function of computers and computer networks. The model is that of a trust infrastructure which subsequently encompasses one or more policy infrastructures.

In the physical world that we experience, all activity proceeds through interactions that are grounded in the basic laws of physical processes. The process of interactions effects activity and the laws of physical processes posit a causality of this activity. From the assumption of causality, we derive trust in the conduct of interactions. Without interactions, any environment is static and unchanging, which in turn makes the elaboration of causality problematic. As a consequence, we have difficulty in establishing trust within a completely static environment.

We have observed that social ecosystems are more complex than the physical ecosystems we experience. This derives from the fact that a social ecosystem presents a larger number of basic forces than does a physical ecosystem. When the stimulus for interactions comes from people, then the interactions are a function of the needs hierarchy of humans. Consequently, interactions

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