Fitness contours (Yield strength (<i>ε</i>) – Mutation probability (<i>x</i>)) for rare disease variants in the presence of non-replicators under varying degrees of kin competition.

<p>(A) α = 0.75, (B) α = 1.0, (C) α = 5.0. Increasing effects of kin competition can reduce optimal levels of relatedness and favour disease variants that produce fewer numbers of infectious pathogens (reduced yield). [Shading: black (low fitness) to white (high fitness)]. (Fitness is the dominant eigenvalue from equation 12).</p

The role of non-replicating parasites on virulence (<i>m</i>(<i>ρ</i>)).

<p>Increases in the optimal replication fraction lead to increases in virulence and the presence of non-replicators can enhance virulence effects even if overall parasite fitness is restricted.</p

Fitness contours for rare disease variants in the presence of non-replicators.

<p>(A) Pathogen longevity (1/<i>d_V</i>) – Mutation probability (<i>x</i>) and (B) Yield strength (<i>ε</i>) – Mutation probability (<i>x</i>). High levels of relatedness (parasite population structure) together with long-lived pathogens and/or high yielding pathogens favoured the invasion of novel disease variants (those that have higher fitness). [Shading: black (low fitness) to white (high fitness)]. (Fitness is the dominant eigenvalue from equation 12).</p

Fitness contours for rare disease variants in the absence of non-replicators.

<p>(A) Pathogen longevity (1/<i>d_V</i>) – Mutation probability (<i>x</i>) and (B) Yield strength (<i>ε</i>) – Mutation probability (<i>x</i>). Long-lived pathogens and/or high yielding pathogens favoured the invasion of novel disease variants (those that have higher fitness). [Shading: black (low fitness) to white (high fitness)]. (Fitness is the dominant eigenvalue from equation 12).</p

<i>The role of parasite replication and relatedness on fitness.</i>

<p>(A) Parasite fitness is a non-linear function of replication fraction (<i>ρ_ih</i>) and declines with increasing kin competition (<i>α</i>). (B) The optimal replication fraction declines with increasing levels of relatedness (<i>R</i>) within a host as prudent exploitation strategies predominant and increases with increasing kin competition (Other parameters <i>η</i> = 1, <i>c</i> = 0.5,  = 0.5).</p

The results of the stochastic simulation can be shown as phase plots of stem cells and transit amplifying cells (uppere panel) or stem cells and fully differentiated cells (lower panel)

<p>The results of the stochastic simulation can be shown as phase plots of stem cells and transit amplifying cells (uppere panel) or stem cells and fully differentiated cells (lower panel)</p

R code for heterogeneous density dependence

This is the R code used to generate Figures 5, S6 and S7 as presented in the paper and supplementary materials

The feedback network affecting a stem cell in its niche.

<p>Here stem cells are clear circles, transit amplifying cells colored circles, and fully differentiated cells in black. A focal stem cell has positive feedback (+) on itself but shares inhibition and negative feedback (−) with other stem cells. Transit amplifying cells receive positive feedback from stem cells and exert positive feedback on fully differentiated cells. Both transit amplifying and fully differentiated cells exhibit negative feedback on stem cells. The symbols that characterize these processes are explained in the <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0001591#s4" target="_blank">Materials and Methods</a>.</p

Representative time series of simulated host (solid, red line) and parasitoid (dotted, blue line abundances from two patch metapopulations (left and middle panels).

<p>Panels at right show host abundances in patch 1 (left panels) against patch 2 (middle panels). Row (a): 10% host dispersal; 10% parasitoid dispersal; row (b): 1% host dispersal; 50% parasitoid dispersal; and row (c): 1% host dispersal; 90% parasitoid dispersal.</p

The stochastic trajectories for 100 simulations of the stem-transit amplifying-differentiated system described in the text and the solution of the differential equations 25–27 (red line).

<p>The stochastic trajectories for 100 simulations of the stem-transit amplifying-differentiated system described in the text and the solution of the differential equations 25–27 (red line).</p