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Table 1.

Values of parameters used in the case-studies.

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Table 2.

Parameter definition and values.

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Figure 1.

Examples of pathogen evolutionary trajectories (a, b and c) and host dynamics (d).

a and b: , ; c and d: , . a, c and d: ; b: . An exponential dispersal function () is used and the metapopulation covers 5% of the environment. The grey intensity indicates the frequency of pathogen genotypes, white: the frequency is equal to 0, black: the frequency is equal to 1.

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Figure 2.

The 95% confidence envelopes for the spatial covariance function for the host genotype when the pathogen mean dispersal distance is and .

a: (solid line) and (dashed line), b: (solid line) and (dashed line), c: (solid line) and (dashed line). Significant discrepancies are highlighted in grey.

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Figure 3.

Example of population aggregates synchrony.

The top row displays the dynamics of and of the two main pathogen genotypes present in the metapopulation on three different populations. The bottom row displays the population spatial structure. a and b: black, frequency; light grey, specialist frequency; dark grey, specialist frequency. c, d and e: , specialist and specialist proportions at the local population level at the time indicated by the vertical solid line in a and b, respectively. The darker the grey, the higher the proportion is. Parameters are: , , , and .

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Figure 4.

Stable coexistence among pathogen genetic clusters as a function of pathogen and host mean dispersal distances and for the case-study A.

a: ; b: . For clarity only the mean dispersal distances below 25% are displayed (see Fig. S4 in Text S1 for more details).

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Figure 5.

Distribution of the pathogen genetic clusters according to their proportion in each sub-population.

This graph is issued from an example of simulation of the case-study A. The generalist cluster did not persist (c) and evolution led to the coexistence of the two fully (a and d) and two moderately (b and e) specialised clusters. Other parameters are: , and (see Fig. 1a for the global evolutionary trajectory).

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Figure 6.

Infection efficacy (a) and efficacy range (b) of the moderately specialised genetic clusters as a function of pathogen mean dispersal distance and for limited host dispersal ().

Parameters are those of the case-study A and . Only one genetic cluster is represented but two symmetric genetic clusters were present.

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Figure 7.

Infection efficacy (a) and efficacy range (b) of the moderately specialised genetic clusters as a function of host mean dispersal distance and for limited pathogen dispersal ().

Parameters are those of the case-study A and . Only one genetic cluster is represented but two symmetric genetic clusters were present.

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Figure 8.

Examples of the dynamics of the main specialists present in the pathogen population.

a: ; b: . Parameters are those of case-study A, and .

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Figure 9.

Efficacy range of the generalist genetic cluster as a function of pathogen and host mean dispersal distance.

Parameters are those of the case-study A and .

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Figure 10.

Examples of pathogen evolutionary trajectories (a and b) and the corresponding host dynamics (c and d, respectively).

a and c: ; b and d: . Parameters are those of case-study A, and .

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