 at which viruses affect ecosystem functions.
Modelling efforts to link viral lysis with carbon and nutrient availability
Dynamic models of viral-host interactions in marine environments have, at their core, the same set of assumptions as were made for dynamics of Escherichia coli and associated phage in chemostats . These now-classic “box” models consider how abundances of hosts, viruses and resources change with time due to the effects of resource uptake, cell division, viral-induced mortality of hosts, and viral reproduction via lysis. Extensions have taken into account a greater complexity of factors, including the possible covariation of bacterial life history traits and viral life history traits [34,35,60]. The most prominent extension to ocean systems is termed “Kill-the-Winner” [28,61], in which viruses specialize in distinct hosts and contribute to the successive decline of host strains that rise to dominance. Kill-the-Winner assumes one-to-one relationships between individual viruses and hosts. The cross-infection of viruses and hosts is more complex. For example, empirical assays of viral-host cross-infectivity reveal that viruses can infect many microbial hosts, and, similarly, microbes can be infected by many viruses [13,24-26]. A reanalysis of phage-bacteria cross-infection assays found a characteristic nested pattern . The nested pattern implies there is a hierarchy of infection ability (amongst viruses) and susceptibility to infection (amongst bacteria) within the re-examined studies. Hence, a major question moving forward is: do the predictions of Kill-the-Winner and other population ecology models change given other cross-infection assumptions? In the context of the first direct effect outlined earlier, it would be important to quantify the relationship between who infects whom and the relative abundance and survival of host and viral strains.
Perhaps the biggest impediment to predictive modelling of direct and indirect effect of viruses of microbes on microbial community composition and ecosystem function is the empirical observation that rare genotypes can rise to observable levels rapidly and frequently [62-66]. These changes may be the result of de novo mutation of successful genotypes as well as emergence of pre-existing, yet rare, microbes that experience changes in conditions that dramatically affect fitness. Unifying ecological and evolutionary dynamics in a single model is difficult, and most models of host-viral dynamics neglect evolution entirely. A few models are available that have begun to assess how such evolutionary details matter. First, it has been proposed that evolutionary changes in allocation of phytoplankton to virus resistance vs. growth would lead to the evolution of co-limitation by hosts rather than the maximization of host productivity in a given environment . However, the cost of resistance to viral infection remains largely uncharacterized in natural communities (see  for a laboratory study using marine cyanobacteria). Second, an evolutionary Kill-the-Winner model predicts that constant total diversity can emerge at the community level even if the identities of strains are in constant flux . This model predicts that at the community scale there may be invariants for which fine-scale evolutionary details do not matter. Some empirical support for this idea comes from one study in which changes in system nutrient levels were buffered despite rapid changes in strains coevolving over a multi-month experiment . Third, multiple coevolutionary models of viral-host interactions mediated by receptor resistance [71,72] and CRISPR immune defense  demonstrate principles under which coevolutionary-induced diversification may arise. Linking models to data and understanding when and which details matter is an issue relevant to the study of viruses of microbes and to problems in microbial ecology more generally .
Viruses are everywhere, but what are they doing and how important are they?
The potential role of viruses in marine biogeochemical cycles [75,76] and the viral shunt  has been disc