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Abstract Protists and viruses dynamically alter the flow of mass and energy through microbial food webs via predation. Simple microbial food web models show that the addition of microbial predators can increase the primary production of a microbial community but only for some configurations of food web structure. Under the conjecture that systems self-organize to maximize energy dissipation, known as the maximum entropy production (MEP) principle, we developed an MEP-based model that predicts microbial food web structure, and we examine how food web structure differs when entropy production is maximized over short versus long timescales. The model design follows from an experimental system and uses a trait-based variational method to set trait values by maximizing entropy production over a specified interval of time. Model results show that short-term MEP optimization produces microbial communities that specialize in substrate preference and consumers that have fewer trophic levels than solutions based on long-term optimization that have substrate generalists and more trophic levels. Our MEP-based approach provides an alternative to food web structure synthesis that does not depend on assumptions of community stability. 

Phytoplankton support complex bacterial microbiomes that rely on phytoplankton-derived extracellular compounds and perform functions necessary for algal growth. Recent work has revealed sophisticated interactions and exchanges of molecules between specific phytoplankton–bacteria pairs, but the role of host genotype in regulating those interactions is unknown. Here, we show how phytoplankton microbiomes are shaped by intraspecific genetic variation in the host using global environmental isolates of the model phytoplankton host Thalassiosira rotula and a laboratory common garden experiment. A set of 81 environmental T. rotula genotypes from three ocean basins and eight genetically distinct populations did not reveal a core microbiome. While no single bacterial phylotype was shared across all genotypes, we found strong genotypic influence of T. rotula , with microbiomes associating more strongly with host genetic population than with environmental factors. The microbiome association with host genetic population persisted across different ocean basins, suggesting that microbiomes may be associated with host populations for decades. To isolate the impact of host genotype on microbiomes, a common garden experiment using eight genotypes from three distinct host populations again found that host genotype influenced microbial community composition, suggesting that a process we describe as genotypic filtering, analogous to environmental filtering, shapes phytoplankton microbiomes. In both the environmental and laboratory studies, microbiome variation between genotypes suggests that other factors influenced microbiome composition but did not swamp the dominant signal of host genetic background. The long-term association of microbiomes with specific host genotypes reveals a possible mechanism explaining the evolution and maintenance of complex phytoplankton–bacteria chemical exchanges.