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A mechanistic system dynamics description is developed of the interactions between a single lytic-virus – phytoplankton-host couple. The model has state variables for virus, uninfected and infected host biomass, and describes virus and host allometry and physiology. The model, analogous to experimental laboratory virus-host systems but more amenable to hypothesis testing, enables us to explore the relative importance of some of the poorly understood factors suspected to impact plankton virus-host dynamics. Model behaviour is explored with respect to abiotic factors (light, mixed layer depth, nutrient and suspended particle loading), host traits (size, growth rate, motility) and virus traits (size, latent period and burst size including linkage to compromised host physiology, and decay rates). Simulations show that the optimal performance of a virus (i.e., optimal trait characterisation) is a function of many factors relating to the virus, its host, and the environment. In general, smaller viruses and smaller motile hosts give rise to more productive infection outcomes that result in rapid demise of the host and high post-infection virus abundance. However, the timing of the development of the interaction (relative abundance of virus to host at the start of rapid host population growth), overlain on the growth rate and physiological status of the host, was seen to be critical. Thus, for any one configuration of the model, the inoculum level of the virus (multiplicity of infection- MOI) displayed an optimum time-point between the infection developing too quickly, limiting biomass accumulation, or too late so that nutrient or light limitation compromised host physiology and hence the burst size. Importantly, the success of an infection depended also upon the suspended particle load which, if high enough, adsorbs so many viruses that the infection does not develop. We conclude that adding viruses to plankton ecosystem models in a realistic fashion is a complicated process due to the way that the individual and coupled virus-host processes interact with the environment.

Viruses play a crucial role in the marine environment, promoting nutrient recycling and biogeochemical cycling and driving evolutionary processes. Tiny marine phytoplankton called prasinophytes are ubiquitous and significant contributors to global primary production and biomass. A number of viruses (known as prasinoviruses) that infect these important primary producers have been isolated and characterised over the past decade. Here we review the current body of knowledge about prasinoviruses and their interactions with their algal hosts. Several genes, including those encoding for glycosyltransferases, methyltransferases and amino acid synthesis enzymes, which have never been identified in viruses of eukaryotes previously, have been detected in prasinovirus genomes. The host organisms are also intriguing; most recently, an immunity chromosome used by a prasinophyte in response to viral infection was discovered. In light of such recent, novel discoveries, we discuss why the cellular simplicity of prasinophytes makes for appealing model host organism–virus systems to facilitate focused and detailed investigations into the dynamics of marine viruses and their intimate associations with host species. We encourage the adoption of the prasinophyte Ostreococcus and its associated viruses as a model host–virus system for examination of cellular and molecular processes in the marine environment.

Systematicity is a property of cognitive architecture whereby having certain cognitive capacities implies having certain other "structurally related" cognitive capacities. The predominant classical explanation for systematicity appeals to a notion of common syntactic/symbolic structure among the systematically related capacities. Although learning is a (second-order) cognitive capacity of central interest to cognitive science, a systematic ability to learn certain cognitive capacities, i.e., second-order systematicity, has been given almost no attention in the literature. In this paper, we introduce learned associations as an instance of second-order systematicity that poses a paradox for classical theory, because this form of systematicity involves the kinds of associative constructions that were explicitly rejected by the classical explanation. Our category theoretic explanation of systematicity resolves this problem, because both first and second-order forms of systematicity are derived from the same categorical construction: universal morphisms, which generalize the notion of compositionality of constituent representations to (categorical) compositionality of constituent processes. We derive a model of systematic associative learning based on (co)recursion, which is an instance of a universal construction. These results provide further support for a category theory foundation for cognitive architecture.

Human cognitive capacity includes recursively definable concepts, which are prevalent in domains involving lists, numbers, and languages. Cognitive science currently lacks a satisfactory explanation for the systematic nature of such capacities (i.e., why the capacity for some recursive cognitive abilities-e.g., finding the smallest number in a list-implies the capacity for certain others-finding the largest number, given knowledge of number order). The category-theoretic constructs of initial F-algebra, catamorphism, and their duals, final coalgebra and anamorphism provide a formal, systematic treatment of recursion in computer science. Here, we use this formalism to explain the systematicity of recursive cognitive capacities without ad hoc assumptions (i.e., to the same explanatory standard used in our account of systematicity for non-recursive capacities). The presence of an initial algebra/final coalgebra explains systematicity because all recursive cognitive capacities, in the domain of interest, factor through (are composed of) the same component process. Moreover, this factorization is unique, hence no further (ad hoc) assumptions are required to establish the intrinsic connection between members of a group of systematically-related capacities. This formulation also provides a new perspective on the relationship between recursive cognitive capacities. In particular, the link between number and language does not depend on recursion, as such, but on the underlying functor on which the group of recursive capacities is based. Thus, many species (and infants) can employ recursive processes without having a full-blown capacity for number and language.

In the Gulf of Maine area (GoMA), as elsewhere in the ocean, the organisms of greatest numerical abundance are microbes. Viruses in GoMA are largely cyanophages and bacteriophages, including podoviruses which lack tails. There is also evidence of Mimivirus and Chlorovirus in the metagenome. Bacteria in GoMA comprise the dominant SAR11 phylotype cluster, and other abundant phylotypes such as SAR86-like cluster, SAR116-like cluster, Roseobacter, Rhodospirillaceae, Acidomicrobidae, Flavobacteriales, Cytophaga, and unclassified Alphaproteobacteria and Gammaproteobacteria clusters. Bacterial epibionts of the dinoflagellate Alexandrium fundyense include Rhodobacteraceae, Flavobacteriaceae, Cytophaga spp., Sulfitobacter spp., Sphingomonas spp., and unclassified Bacteroidetes. Phototrophic prokaryotes in GoMA include cyanobacteria that contain chlorophyll (mainly Synechococcus), aerobic anoxygenic phototrophs that contain bacteriochlorophyll, and bacteria that contain proteorhodopsin. Eukaryotic microalgae in GoMA include Bacillariophyceae, Dinophyceae, Prymnesiophyceae, Prasinophyceae, Trebouxiophyceae, Cryptophyceae, Dictyochophyceae, Chrysophyceae, Eustigmatophyceae, Pelagophyceae, Synurophyceae, and Xanthophyceae. There are no records of Bolidophyceae, Aurearenophyceae, Raphidophyceae, and Synchromophyceae in GoMA. In total, there are records for 665 names and 229 genera of microalgae. Heterotrophic eukaryotic protists in GoMA include Dinophyceae, Alveolata, Apicomplexa, amoeboid organisms, Labrynthulida, and heterotrophic marine stramenopiles (MAST). Ciliates include Strombidium, Lohmaniella, Tontonia, Strobilidium, Strombidinopsis and the mixotrophs Laboea strobila and Myrionecta rubrum (ex Mesodinium rubra). An inventory of selected microbial groups in each of 14 physiographic regions in GoMA is made by combining information on the depth-dependent variation of cell density and the depth-dependent variation of water volume. Across the entire GoMA, an estimate for the minimum abundance of cell-based microbes is 1.7×10(25) organisms. By one account, this number of microbes implies a richness of 10(5) to 10(6) taxa in the entire water volume of GoMA. Morphological diversity in microplankton is well-described but the true extent of taxonomic diversity, especially in the femtoplankton, picoplankton and nanoplankton--whether autotrophic, heterotrophic, or mixotrophic, is unknown.

Discriminating infected from healthy cells is the first step to understanding the mechanisms and ecological implications of viral infection. We have developed a method for detecting, sorting, and performing molecular analysis of individual, infected cells of the important microalga Emiliania huxleyi, based on known physiological responses to viral infection. Of three fluorescent dyes tested, FM 1-43 (for detecting membrane blebbing) gave the most unequivocal and earliest separation of cells. Furthermore, we were able to amplify the genomes of single infected cells using Multiple Displacement Amplification. This novel method to reliably discriminate infected from healthy cells in cultures will allow researchers to answer numerous questions regarding the mechanisms and implications of viral infection of E. huxleyi. The method may be transferable to other virus-host systems.