How the ecological process of community assembly interacts with intra-species diversity and evolutionary change is a longstanding question. Two contrasting hypotheses have been proposed: Diversity Begets Diversity (DBD), in which taxa tend to become more diverse in already diverse communities, and Ecological Controls (EC), in which higher community diversity impedes diversification. Previously, using 16S rRNA gene amplicon data across a range of microbiomes, we showed a generally positive relationship between taxa diversity and community diversity at higher taxonomic levels, consistent with the predictions of DBD (Madi et al., 2020). However, this positive 'diversity slope' plateaus at high levels of community diversity. Here we show that this general pattern holds at much finer genetic resolution, by analyzing intra-species strain and nucleotide variation in static and temporally sampled metagenomes from the human gut microbiome. Consistent with DBD, both intra-species polymorphism and strain number were positively correlated with community Shannon diversity. Shannon diversity is also predictive of increases in polymorphism over time scales up to ~4-6 months, after which the diversity slope flattens and becomes negative – consistent with DBD eventually giving way to EC. Finally, we show that higher community diversity predicts gene loss at a future time point. This observation is broadly consistent with the Black Queen Hypothesis, which posits that genes with functions provided by the community are less likely to be retained in a focal species' genome. Together, our results show that a mixture of DBD, EC, and Black Queen may operate simultaneously in the human gut microbiome, adding to a growing body of evidence that these eco-evolutionary processes are key drivers of biodiversity and ecosystem function.

Global change is causing unprecedented degradation of the Earth’s biological systems and thus undermining human prosperity. Past practices have focused either on monitoring biodiversity decline or mitigating ecosystem services degradation. Missing, but critically needed, are management approaches that monitor and restore species interaction networks, thus bridging existing practices. Our overall aim here is to lay the foundations of a framework for developing network management, defined here as the study, monitoring, and management of species interaction networks. We review theory and empirical evidence demonstrating the importance of species interaction networks for the provisioning of ecosystem services, how human impacts on those networks lead to network rewiring that underlies ecosystem service degradation, and then turn to case studies showing how network management has effectively mitigated such effects or aided in network restoration. We also examine how emerging technologies for data acquisition and analysis are providing new opportunities for monitoring species interactions and discuss the opportunities and challenges of developing effective network management. In summary, we propose that network management provides key mechanistic knowledge on ecosystem degradation that links species- to ecosystem-level responses to global change, and that emerging technological tools offer the opportunity to accelerate its widespread adoption.