Macroecological and macroevolutionary patterns emerge in the universe of GNU/Linux operating systems

Abstract

What leads to classically recognized patterns of biodiversity remains an open and contested question. It remains unknown if observed patterns are generated by biological or non-biological mechanisms, or if we should expect the patterns to emerge in nonbiological systems. Here, we employ analogies between GNU/Linux operating systems (distros), a non-biological system, and biodiversity, and we look for a number of wellestablished ecological and evolutionary patterns in the Linux universe. We demonstrate that patterns of the Linux universe generally match macroecological patterns. Particularly, Linux distro commonness and rarity follow a skewed distribution with a clear excess of rare distros, we observed a power law mean-variance scaling of temporal fluctuation, but there is only a weak relationship between niche breadth (number of software packages) and commonness. The diversity in the Linux universe also follows general macroevolutionary patterns: the number of phylogenetic lineages increases linearly through time, with clear per-species diversification and extinction slowdowns, something that has been indirectly estimated, but not directly observed in biology. Moreover, the composition of functional traits (software packages) exhibits significant phylogenetic signal. The emergence of macroecological patterns across Linux suggests that the patterns are produced independently of system identity, which points to the possibility of non-biological drivers of fundamental biodiversity patterns. At the same time, our study provides a step towards using Linux as a model system for exploring macroecological and macroevolutionary patterns.

A brief history and popularity of methods and tools used to estimate micro‐evolutionary forces

“…Analysis of citation records was performed in R v. 3.6.3 (R Core Team, 2018 ) using customized versions of the scripts published by Keil et al. ( 2018 ). These are provided in the Appendix S1 .…”

“…An identical approach to sampling as in Keil et al. ( 2018 ) was done, with the average of 500 model runs taken for generating the expected values. For Taylor's power law, we adopted the number of times the software was cited as its citation bias, according to its publication record on ISI web of knowledge.…”

The Natural Evolution of Computing

“…Evolutionary constrains are also evidenced by common patterns in the internal structure of software, that is, structural heterogeneity [59,60,61,62], smallworld behaviour [63], motif distribution [64], and modular organisation [63,65,66,67]. This set of topological features is shared by many evolving systems [68,69], and thus likely to be displayed by other technological and cultural systems. An explanation for this universal behaviour resides in the ubiquity of tinkering mechanisms [70].…”

Empirical abundance distributions are more uneven than expected given their statistical baseline

“…In fact, the nearly ubiquitous shape of the SAD may transcend ecological processes and instead reflect mathematical properties inherent to abundance distributions. Complex systems across domains ranging from economics to information technology often exhibit empirical abundance distributions with hollow‐curve forms similar to ecological SADs (Blonder et al, 2014; Gaston et al, 1993; Keil et al, 2018; Nekola & Brown, 2007; Shockley, 1957). This suggests that the hollow curve is a common feature of abundance distributions and not necessarily an ecological phenomenon.…”