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  • A constructive approach to the epistemological problem of emergence in complex systems.

    Pascual-García, A

    , 2018, PloS One

    Emergent patterns in complex systems are related with many intriguing phenomena in modern science. One question that has sparked vigorous debates is if difficulties in the modelization of emergent behaviours are a consequence of ontological or epistemological limitations. To elucidate this question, we propose a novel approximation through constructive logic. Under this framework, experimental measurements will be considered conceptual building blocks from which we aim to achieve a description of the microstates ensemble mapping the macroscopic emergent observation. This procedure allow us to have full control of any information loss, thus making the analysis of different systems fairly comparable. In particular, we aim to look for compact descriptions of the constraints underlying a dynamical system, as a necessary a prioristep to develop explanatory (mechanistic) models. We apply our proposal to a synthetic system to show that the number and scope of the system’s constraints hinder our ability to build compact descriptions, being those systems under global constraints a limiting case in which such a description is unreachable. This result clearly links the epistemological limits of the framework selected with an ontological feature of the system, leading us to propose a definition of emergence strength which we make compatible with the scientific method through the active intervention of the observer on the system, following the spirit of Granger causality. We think that our approximation clarifies previous discrepancies found in the literature, reconciles distinct attempts to classify emergent processes, and paves the way to understand other challenging concepts such as downward causation.

  • Strain-level diversity drives alternative community types in millimetre-scale granular biofilms

    Leventhal GE, Boix C, Kuechler U, Enke TN, Sliwerska E, Holliger C, Cordero OX

    , 2018, Nat Microbiol 3: 1295–1303

    Microbial communities are often highly diverse in their composition, both at a coarse-grained taxonomic level, such as genus, and at a highly resolved level, such as strains, within species. This variability can be driven by either extrinsic factors such as temperature and or by intrinsic ones, for example demographic fluctuations or ecological interactions. The relative contributions of these factors and the taxonomic level at which they influence community composition remain poorly understood, in part because of the difficulty in identifying true community replicates assembled under the same environmental parameters. Here, we address this problem using an activated granular sludge reactor in which millimetre-scale biofilm granules represent true community replicates. Differences in composition are then expected to be driven primarily by biotic factors. Using 142 shotgun metagenomes of single biofilm granules we found that, at the commonly used genus-level resolution, community replicates varied much more in their composition than would be expected from neutral assembly processes. This variation did not translate into any clear partitioning into discrete community types, that is, distinct compositional states, such as enterotypes in the human gut. However, a strong partition into community types did emerge at the strain level for the dominant organism: genotypes of Candidatus Accumulibacter that coexisted in the metacommunity (the reactor) excluded each other within community replicates (granules). Individual granule communities maintained a significant lineage structure, whereby the strain phylogeny of Accumulibacter correlated with the overall composition of the community, indicating a high potential for co-diversification among species and communities. Our results suggest that due to the high functional redundancy and competition between close relatives, alternative community types are most probably observed at the level of recently differentiated genotypes but not at higher orders of genetic resolution.