Experimental systems are essential for strengthening ecological modeling of microbiomes beyond observational data.

Disentangling the ecological mechanisms shaping the assembly of complex communities with thousands of interacting species remains a significant challenge. Ecological models derived from observational data are valuable tools for describing community states and generating hypotheses. Integrating these models with experimental approaches is crucial for addressing the challenges of uncovering the complex mechanisms and dynamics underlying microbiome assembly. Strategic experimental designs can complement observational data, improving inference accuracy and advancing efforts to restore microbiota and enhance their therapeutic potential. Building on insights from previous studies, this paper organizes core concepts into four main themes where controlled, trackable experiments are particularly effective in advancing our understanding of microbiome assembly rules and mechanisms: resolving the role of (i) ecological drift and (ii) priority effects in microbiome assembly, (iii) subspecies-level microbial dynamics, and (iv) controlled replication of community assembly dynamics.