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Sediment cores. Two sediment cores were taken. Core 1 had a diameter of 5 cm and was
taken in October 2002 and sliced in depth increments of 2 cm. Core 2 had a diameter of 15
cm and was taken in January 2006 and sliced in increments of 1 cm. The outer millimeters
of each slice were removed. Dating of the core was performed based on the assumption of
constant sedimentation rates in terms of sediment mass (as in Cousyn et al. 2001, PNAS). As
the time axis should be considered indicative, only rough statements with respect to time
of the sediment cores can be made.
Daphnia clones and parasite isolates. Daphnia host clones and parasite isolates were
derived from the two sediment cores. Up to nine depth increments were used covering a
time interval of about 18 to 36 years (about 2–4 years per 2-cm depth). This represents 2-4
phases of sexual recombination and at least 10 to 20 asexual generations. On the basis of
the similar profile of the number of dormant eggs in the different depths of both cores, we
numbered the depths similarly between the two cores (see SI1 in Decaestecker et al. 2007).
Host clones were obtained through hatching of dormant eggs from each depth. Parasite
isolates were obtained by exposing a random set of Daphnia clones (isolated over the
whole range of sediment depths used) to sediment from each depth. For Core 1, 16 clones
were used in the random set and we obtained three parasite isolates per depth. For Core 2,
20 clones were used in the random set, but we obtained only one parasite isolate per depth
and only from the first seven depths. The random set of clones used was different for the
two cores.
Cross-infection experiment. In the cross-infection experiment, Daphnia host clones (other
than those used to pick up the parasite isolates) from either recent or old depths were
confronted with the same set of parasite genotypes isolated from intermediate depths, in
three replicates. Thus, hosts from recent depths were in principle experienced to the
parasite genotypes, while hosts from the oldest depths were in principle naive. From Core
1, whenever possible, three Daphnia clones of the oldest and youngest depth were exposed
to three parasite isolates from 2-cm depth each in three replicates (only two parasite
isolates were used in depth five and only one in depth eight). From Core 2, eight Daphnia
clones from the oldest and youngest depths were exposed to a parasite isolate of each 2cm depth in three replicates.
Before performing the final cross-infection experiment, we isolated adult female
Daphnia from clonal stock cultures that had been kept in the laboratory for several
generations. Each clonal stock culture was derived from a single dormant egg. Three adult
Daphnia were kept individually as a maternal line, with the number of maternal lines being
equal to the number of replicates that were used in the cross-infection experiment.
Neonates of the second clutch of the second generation maternal lines were then isolated
and individually exposed to a parasite treatment in 100 ml (Core 1) or 50 ml (Core 2) jars in
the cross-infection experiment.
The Daphnia clones of Core 1 were exposed to a Pasteuria spore solution with a
concentration of 2.5 x 105 spores ml-1 at day one, and 2.5 x 104 spores ml-1 at day seven.
Because we had obtained fewer parasite spores from Core 2, these Daphnia clones were
exposed to a Pasteuria solution with 1.3 x 103 spores ml-1 at day one, and 0.65 x 103 spores
ml-1 at day three. The Core 1 Daphnia were fed daily with a concentration of 0.8 x 105 algal
cells ml-1; the Core 2 Daphnia were fed with 0.5 x 105 algal cells ml-1 for the first six days,
and afterwards with 1.5 x 105 algal cells ml-1. The difference in feeding regime between the
exposures of Core 1 and Core 2 was due to the fact that a smaller number of parasite
spores were obtained for Core 2 than for Core 1. We assumed that lower food levels at the
start, but increasing food levels after a few days of parasite exposure, would result in
stronger infectivity levels, so that parasite exposure would be better comparable between
the two core experiments. Food levels were relatively equal and low in the exposures of the
first days, to ensure that parasite uptake would be high. The medium was refreshed every
time the host released a clutch, or at least every fourth day. After 26 (core 1) or 23 days
(core 2), all the Daphnia were checked for Pasteuria infection. An inevitable point with
respect to the experimental design (testing naive hosts with parasites from all sediment
depths above and experienced hosts with all parasites from sediment depths below) is that
it tests a lot of virtual combinations that ‘rarely’ occur in nature. The ‘rarely’ refers to the
fact that our sediment cores show low disturbance, given that otherwise we would not
have detected the adaptive pattern in the first place (and the consistency of the dormant
egg profile and the adaptive pattern between different sediment cores, see SI1 on the
dormant egg profile of the sediment cores in Decaestecker et al. 2007). The naive host
confrontations reflect what would happen to hosts who would ‘wake up’ from the seed
bank. The experimental design reflects changes both in the parasite and in the host. In the
case of the host we evaluated the changes on a longer time scale than in the case of the
parasite. We admit that our design does not explicitly test whether these long-term
changes in the host over time could or could not be encountered by the parasite (as might
be the case in nature), but given that we assumed that the parasite is adapting on shorter
time frames than the host, we are convinced that this design is appropriate to mimic what
the most important host adaptations were on longer time frames in our system.
Standard Matching allele Model (MAM). The MAM is implemented with the parameters
described in Table S1. Infection occurs when the alleles match. The diploid hosts are
infected when one of the alleles or both match the allele of the parasite. Infectivity upon
allele matching between the host and the parasite is represented by the interaction matrix
M int . In the case considered, M int is a unit diagonal matrix. Between successive
generations, mutation occurs. This is represented by two mutation matrices M 
and
host
M parasite . In the case considered, M 
and M parasite have entries host and parasite
host
and the diagonal entries are put to zero because alleles do not mutate to themselves. The
host and parasite allele frequencies are stored in the vectors h and p , respectively. These
vectors are initiated by random numbers. Both are scaled in such a way that the sums of
their elements equal 1. Time stepping occurs over the generations ( i denotes the
generation number).
The parasite genotype fitness is described as Wp  Mint h , and is thus determined
by its possibility to infect hosts. Wp is a vector containing a fitness value per parasite
T
genotype. The host genotype fitness is described as Wh  1  VM int p . The host genotype
fitness remains 1 unless the hosts are infected, in which case their fitness is reduced by
virulence V . Wh is a vector containing one fitness value per host genotype. The new host
and parasite allele frequencies are

hi 1   hiWh   M host  hiWh   sum M host
hi 1  hi 1 / sum  hi 1 
  hiWh 





pi 1  piW p  M parasite piW p  sum M parasite
 p W 
i
p
pi 1  pi 1 / sum  pi 1 
The vector of allele frequencies in the next generation is obtained by considering allele
frequency changes due to infection, mutation from other alleles and mutation to other
alleles. The allele frequencies are scaled in such a way that their sum remains 1. The
contemporary performance is measured with respect to reference generation iref :
C  hiT M int piref . The allotemporary performance of past associations is measured with
ref
respect to the reference generation iref1 : Ag  hiT M int piref 1  g with g representing the
ref1
shift between host and parasite generations ( g is negative in past associations). The
allotemporary performance of future associations is measured with respect to the
reference generation iref2 : Ag  hiT M int piref 2  g ( g is positive in future associations).
ref2
Measuring future and past associations for different host populations has been performed
to mimic the experimental set-up (Figure 1B). The same system is simulated ncarlo times
independently for different sets of randomly chosen host and parasite allele frequencies at
the start. The system is simulated for nbefore generations before measuring the infection
rate in order to allow the system to develop stationary behavior. At generation iref1 and
generation iref2 the contemporary and allotemporary performances are calculated for
each independent Monte-Carlo run. The results for the contemporary and allotemporary
performances are averaged over all Monte-Carlo runs.
We took a shorter generation time into account or an increased mutation rate by
including them in the standard MAM, but found that they did not account for the
asymmetric effect found in the empirical results (Figure S1A&B).
Modeled effects over time (Extended MAMs). We further extended the MAM with
additional effects over time. With respect to traits determined by variation in the host, we
estimated the most important parameter to be an increase in the number of the alleles that
occurred over time in our host population. Genetic diversity is the basis that fuels Red
Queen dynamics and is the weapon that the host uses in the arms race against its fast
evolving parasites. Similar to dilution effects buffering host communities against parasitism,
our hypothesis is that an increase in genetic diversity over time may act as a buffer in the
sense of predictability against parasitism within a single host species. Such an effect has not
yet been considered in earlier Red Queen coevolutionary models. With respect to
mechanisms due to variation in the parasite, we included increased virulence of the
parasites over time, because we have direct evidence (in Decaestecker et al. 2007) that
experienced hosts have been confronted with more virulent parasites than naive hosts.
We first investigated whether increasing the number of active alleles in the host
affected the amplitude of Red Queen dynamics. At generation 150, one additional allele
becomes active, i.e. the dimension of the host-parasite infectivity matrix is increased. The
frequency of that allele starts at zero and slowly increases due to mutation. Three one locus
models were simulated starting with 2, 3 or 4 alleles and ending with 3, 4 or 5 alleles
respectively. We took a shorter generation time into account or an increased mutation rate
by including it in the extended MAM, but did not found that it changed the asymmetric
effect when increased host genetic diversity over time was included into the model (Figure
S1C). We could analogous have investigated whether the loss of parasite alleles due to drift
induced the damped effect. However, we consider this as unlikely given that the parasite
population tended to increase over time (Decaestecker et al. 2004), thus scenarios involving
drift are not likely to explain the pattern we observed.
We then studied the effect of increased virulence over time on the Red Queen
based infectivity dynamics. From the beginning to generation iVmin , the virulence is kept
constant to Vmin . Between generation iVmin and generation iVmax , the virulence is linearly
increasing. After iVmax , the virulence is kept constant to Vmax . The MAM has been
simulated for three different virulence levels ( Vmin  0.60 , Vmin  0.80 , and a reference
simulation in which the virulence level is kept at V  0.95 ).
Immigration is also a strong candidate to explain this increase in allelic diversity that
the host can use to resist the parasite. Nevertheless, immigration has been estimated to be
low in this pond, given the low genetic differentiation that has been detected between the
Daphnia populations from the sediment depths of this pond. Low Fst values were detected
among the temporal replicates (i.e. sediment cores indicated strong stability in the genetic
structure of our host population, see Decaestecker et al. 2007), which suggests that
immigration and the establishment of new, successful genotypes has been a rare event in
the pond we studied. This is further strengthened by the gene flow paradox and the
associated monopolisation hypothesis, which assumes that founder effects due to a small
number of genotypes can have long lasting genetic implications in the host population. In
such a scenario, local adaptation and rapid population growth of a few founder clones
colonizing a new habitat result in the effective monopolization of resources, yielding a
strong priority effect and the establishment of a limited number of clones. This is an effect
that limits gene flow between populations and which is typically present in the zooplankton
ponds, one of which we study here (De Meester et al. 2002).
A number of mechanisms associated with evolved “experience” in the host do not
involve a role for genetic diversity, but cannot be excluded at present. For example, there is
proof for maternal transfer of strain-specific immunity with respect to Pasteuria ramosa in
Daphnia (Little et al. 2003, Current Biology). Frost et al. (2010, Oecologia) suggested that
offspring from food quality stressed mothers are more susceptible to Pasteuria infection in
Daphnia. One way in which such maternal effects may be realized is through
transgenerational inheritance of environmentally induced epigenetic changes. Phenotypic
variation has in some cases been attributed to epigenetic methods of inheritance and may
thus have influenced Red Queen dynamics (Mostowy et al. 2012). Given that our
experiment substantially controlled for maternal effects, we assume that epigenetic effects
were absent from our experiment. Moreover, as shown by Mostowy et al. (2012),
epigenetic effects tend to stabilize allele frequency dynamics and therefore would have
resulted in the opposite pattern from the one we observed.
Table S1. Description of the model parameters used in all simulations unless specified
otherwise.
number of Monte Carlo runs
ncarlo
100
number of generations before collecting statistics
nbefore
100
number of generations while collecting statistics
nwhile
151
maximal shift between generations
nshift
60
first reference host generation
iref1
120
second reference host generation
iref2
180
number of loci
nloci
1
number of alleles
nallele
4
number of genotypes
ngenotype  nallelenloci 4
Virulence
V
0.95
host mutation probability
host
10-6
parasite mutation probability
parasite
10-6
interaction matrix (represents infection)
M int
host mutation matrix
M host
parasite mutation matrix
M parasite
host allele frequencies
h
parasite allele frequencies
p
parasite genotype fitness
Wp
Table S2. Infection success, standard error (SE), lower and upper 95% confidence limit
(CL), and sample size for each experiment × host depth × parasite depth combination.
The first column contains the factor level combination x:y:z in which x indicates the
experiment (core 1 or core 2), y the host depth (1 or 7 in core 1, and 1 or 9 in core 2), and z
the parasite depth (1 to 8).
Infection
success
SE
lower CL upper CL
N
1:1:1 0.8125000 0.07967218 0.65634540 0.9686546 24
1:1:2 0.6250000 0.09682458 0.43522730 0.8147727 25
1:1:3 0.6666667 0.09428090 0.48187949 0.8514538 25
1:1:4 0.5909091 0.09833322 0.39817953 0.7836387 25
1:1:5 0.7857143 0.09951865 0.59066132 0.9807673 17
1:1:6 0.7272727 0.08734263 0.55608432 0.8984611 26
1:1:7 0.5600000 0.09552971 0.37276520 0.7472348 27
1:1:8 0.6000000 0.15491933 0.29636369 0.9036363 10
1:7:1 0.6666667 0.09072184 0.48885512 0.8444782 27
1:7:2 0.5833333 0.09487917 0.39737357 0.7692931 27
1:7:3 0.5000000 0.09622504 0.31140238 0.6885976 27
1:7:4 0.4230769 0.09507947 0.23672459 0.6094293 27
1:7:5 0.5882353 0.11600156 0.36087641 0.8155942 18
1:7:6 0.6666667 0.09245003 0.48546793 0.8478654 26
1:7:7 0.8695652 0.06481356 0.74253297 0.9965975 27
2:1:1 0.5652174 0.10119015 0.36688835 0.7635464 24
2:1:2 0.4347826 0.10119015 0.23645357 0.6331116 24
2:1:3 0.3750000 0.09882118 0.18131405 0.5686859 24
2:1:4 0.3636364 0.09819304 0.17118154 0.5560912 24
2:1:5 0.2608696 0.08963273 0.08519264 0.4365465 24
2:1:6 0.2857143 0.09631427 0.09694179 0.4744868 22
2:1:7 0.4000000 0.10215078 0.19978814 0.6002119 23
2:9:1 0.3888889 0.11490439 0.16368043 0.6140973 18
2:9:2 0.7058824 0.11051017 0.48928640 0.9224783 17
2:9:3 0.6470588 0.11590404 0.41989107 0.8742266 17
2:9:4 0.9285714 0.06883029 0.79366653 1.0634763 14
2:9:5 0.1428571 0.09035079 -0.03422715 0.3199414 15
2:9:6 0.7692308 0.11685454 0.54020007 0.9982615 13
2:9:7 0.1333333 0.08777075 -0.03869417 0.3053608 15
Figure S1. Integration of shorter generation times and faster mutation rate for the
parasite in comparison with the host. Infectivity dynamics with shorter parasite generation
time (A) and faster mutation rate (B) in the standard MAM and the extended MAM with
increasing active alleles over time (C). Reading from left to right is from positive time shifts
representing naive hosts (confronted with future associations) to negative time shifts
representing experienced hosts (confronted with past parasites). Although both effects
show dampening in the standard MAM, they do not show asymmetry in the dynamics
between past (negative time shifts, experienced host) and future (positive time shifts, naive
hosts) associations (Figures A&B), whereas including an increase in the number of active
alleles over time does (Figure C), independently of whether the generation time and the
mutation rate between the host and the parasite differ. The number of active alleles (at the
start situation in C) is 3.
Figure S2. Results of the cross-infection experiment. Parasite infectivity averaged by clone
depth and parasite depth. Experiment 1 in A) experienced, B) naive clones; Experiment 2 in
C) experienced, D) naive clones. Error bars represent standard errors. Depth numbers are
labeled from young to old depths (1 to 8) respectively.
Figure S3. Effect of increased parasite virulence over time according to an extended
MAM. Parasite infectivity (W, allo- and contemporary performance) versus time shift (D) of
the parasite to the host according to an extended MAM incorporating an increase in
parasite virulence. Reading from left to right is from positive time shifts representing naive
hosts (confronted with future associations) to negative time shifts representing
experienced hosts (confronted with past parasites). Time shift zero indicates contemporary
associations. The infectivity is monitored for the different hosts in accordance with the
experimental data: the most naive hosts are infected by all parasites for studying future
associations, whereas the most experienced hosts are infected by the same set of parasites
for studying past associations. The number of active alleles is 4.
Reference List
Mostowy, R., Engelstadter, J. & Salathe, M. (2012). Non-genetic inheritance and the
patterns of antagonistic coevolution. BMC Evol. Biol., 12, 93.