A macroecological law describes correlations as a function of phylogenetic similarity in microbial ecosystems

Fuente: Surkova Tatʹjana (Wikimedia Commons)

The question of how coexistence of species is generated and maintained is as old as ecology itself. Many ecological “forces” such as competition, cooperation, demographic fluctuation, environmental fluctuation and filtering, migration, predation etc. are expected to act together in ecosystems. Disentangling the effect and intensity of each of theses forces in natural communities is the focus of present research. Thanks to a recent revolution in the availability of high quality data, natural microbial ecosystems offer an invaluable possibility to tackle this question. Here, we explore if it is possible to discriminate a dominant force at a give resolution of genetic similarity. By using both relative-abundances and metagenomic data, we reveal the presence of a new macroecological law relating correlation and phylogenetic similarity. In particular, the average correlation of species abundance fluctuation decays with phylogenetic distance from positive to null values following a stretch exponential function consistently in all empirically analyzed biomes both across communities (hosts) and in temporal data for each community. By scrutinizing different ecological models, we show that competition cannot reproduce the observed pattern. Instead, the elucidated macroecological law is explained quantitatively by the “correlated stochastic logistic model” (CSLM) pointing to environmental filtering as the dominant ecological force at this resolution level. We conclude by arguing that in order to understand interactions in microbial ecosystems one needs to abandon the concept of species and study the system from different scales, much as done in physics exploiting renormalization-group ideas.

Ponente: Matteo Sireci. Universidad de Granada.

Fecha y hora: viernes, 4 de febrero de 2022 a las 12:00. 

Lugar: Seminario de Física Computacional, planta baja del edificio de Física (junto a las pantallas). Facultad de Ciencias. Online a través de Google Meet en el siguiente enlace: https://meet.google.com/vub-uoiw-piz