The mammalian gut microbiome is a powerful and clinically relevant system to study processes of microbial adaptation, as it is a highly dynamic ecosystem that plays a wide variety of roles in host health and disease processes. Although an expansive foundational literature has established correlational relationships between the gut microbiome and various aspects of host health, these have largely been drawn from cross-sectional studies that compare data from a single timepoint across healthy and diseased individuals. While such frameworks are effective for identifying long-term selective pressures, they neglect the temporal dynamics that underlie the transitions between states, and therefore assume that the adaptational process is not contingent upon transient or intermediate dynamics en route to the endpoint. This dissertation challenges that assumption, instead conceptualizing microbial adaptation as a temporal and iterative feedback-driven process of environmental change and microbial response. In this work, I use two experimental model systems to characterize the ways that microbes adapt to different environments and resource schemes over time: in the first, I assess population-level adaptation to a new host resource landscape, and in the second, I evaluate community-level response to an ecosystem perturbation under different resource conditions. In Chapter 1, I examine how a human-derived bacterium, Bacteroides thetaiotaomicron (Bt), adapts to the mouse gut over the course of monocolonization. Using a temporally granular three-pronged approach that includes a functional genetics screen, transcriptomic analysis, and a long-term evolution experiment, I find that Bt proceeds through distinct adaptational stages with characteristic patterns of spatial localization, gene expression, and functional requirements, and identify strong selective pressure for efficient metabolism of easily accessible dietary polysaccharides. In Chapter 2, I evaluate how different dietary resource environments impact gut microbiome robustness and resilience to a brief antibiotic perturbation. I perform extensive multi-omics analysis including 16S rRNA sequencing, shotgun metagenomic sequencing, and metabolomics, and find that mice on a high-fat, low-fiber “Western diet” exhibit markedly impaired microbiome recovery after antibiotic perturbation. I then perform intervention experiments to assess the relative contributions of dietary resource environment and microbial re-seeding to recovery, and find that diet plays a greater role in recovery than microbial re-seeding. Finally, I evaluate the consequences of impaired microbiome resilience for host health by performing colonization resistance experiments with Salmonella enterica serovar Typhimurium, and find that colonization resistance is impaired in antibiotic-treated mice on WD for up to 2 weeks after antibiotic treatment has ended. Together, these results suggest that by carefully examining the temporal dynamics of microbial population- and community-level adaptation, we can generate powerful insights into the mechanisms that allow microbiomes to adapt and change.