# A minimal model for microbial biodiversity can reproduce experimentally observed ecological patterns

## TL;DR

This paper demonstrates that a minimal microbial community model, the MiCRM, can replicate key ecological patterns observed in large-scale survey data, providing insights into underlying ecological processes.

## Contribution

The study shows that the MiCRM can qualitatively reproduce diverse ecological patterns from survey data, linking them to specific mechanistic assumptions.

## Key findings

- MiCRM reproduces compositional gradients and nestedness.
- Environmental harshness influences community richness.
- Shared environments explain dissimilarity-overlap correlations.

## Abstract

Surveys of microbial biodiversity such as the Earth Microbiome Project (EMP) and the Human Microbiome Project (HMP) have revealed robust ecological patterns across different environments. A major goal in ecology is to leverage these patterns to identify the ecological processes shaping microbial ecosystems. One promising approach is to use minimal models that can relate mechanistic assumptions at the microbe scale to community-level patterns. Here, we demonstrate the utility of this approach by showing that the Microbial Consumer Resource Model (MiCRM) -- a minimal model for microbial communities with resource competition, metabolic crossfeeding and stochastic colonization -- can qualitatively reproduce patterns found in survey data including compositional gradients, dissimilarity/overlap correlations, richness/harshness correlations, and nestedness of community composition. By using the MiCRM to generate synthetic data with different environmental and taxonomical structure, we show that large scale patterns in the EMP can be reproduced by considering the energetic cost of surviving in harsh environments and HMP patterns may reflect the importance of environmental filtering in shaping competition. We also show that recently discovered dissimilarity-overlap correlations in the HMP likely arise from communities that share similar environments rather than reflecting universal dynamics. We identify ecologically meaningful changes in parameters that alter or destroy each one of these patterns, suggesting new mechanistic hypotheses for further investigation. These findings highlight the promise of minimal models for microbial ecology.