Degeneracy is a ubiquitous property of complex adaptive systems, which refers to the ability of structurally different components to perform the same function in some conditions and different functions in other conditions. Here, we suppose a causal link between the level of degeneracy in the system and the strength of long-range correlations in its behavior. In a numerical experiment, we manipulated degeneracy through the number of networks available in a model composed of a chain of correlated networks over which a series of random jumps are performed. Results showed that correlations in the outcome series increased with the number of available networks, and that a minimal threshold of degeneracy was required to generate long-range correlations. We conclude that degeneracy could underlie the presence of long-range correlations in the outcome series produced by complex systems. In turn, we suggest that quantifying long-range correlations could allow to assess the level of degeneracy of the system. Degeneracy affords a maybe more intuitive way than former hypotheses for understanding the effects of complexity on essential properties such as robustness and adaptability.
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