Journal of Ecology 2013, 101, 277–286
doi: 10.1111/1365-2745.12042
SPECIAL FEATURE
PLANT–SOIL FEEDBACKS IN A CHANGING WORLD
Soil heterogeneity generated by plant–soil feedbacks
has implications for species recruitment and
coexistence
Angela J. Brandt1*, Hans de Kroon2, Heather L. Reynolds3 and Jean H. Burns1
1
Department of Biology, Case Western Reserve University, Cleveland, OH 44106 USA; 2Department of Experimental
Plant Ecology, Institute for Water and Wetland Research, Radboud University Nijmegen, 6500 GL Nijmegen, The
Netherlands; and 3Department of Biology, Indiana University, Bloomington, IN 47405, USA
Summary
1. Most studies of soil heterogeneity have focused on underlying abiotic factors such as soil nutrients. However, increasing recognition of plant–soil feedback (PSF) effects on plant growth, combined with the observation that PSFs operate at small spatial scales, suggests that heterogeneity due
to PSF could affect plant population and community dynamics. The consequences of PSF-generated
heterogeneity for coexistence depend on heterogeneity’s effects on vital rates and how those vital
rates influence population-level recruitment dynamics.
2. We measured vital rates and recruitment dynamics of three congeneric pairs of introduced perennial plants grown as monocultures in experimental PSF-generated soil environments. Field soils collected from conspecifics and congeners were alternated in patches or mixed together to produce
heterogeneous and homogeneous soils, respectively.
3. We quantified the effects of PSF-generated heterogeneity on germination and establishment and
determined how these vital rates affected recruitment. We calculated net pairwise interaction coefficients to predict whether PSFs could mediate coexistence between congeners.
4. Soil heterogeneity altered the relationship of vital rates to recruitment dynamics for some species.
For example, Solanum dulcamara recruited later into heterogeneous than homogeneous soils, and
germination was a stronger predictor of the timing of recruitment in heterogeneous soil, while mortality was a stronger predictor in homogeneous soil. Contrasts between soils of different origin suggest that mixing soils had non-additive effects on vital rates (e.g. Rumex crispus mortality was
higher in homogeneous than in conspecific or congener soil). Interaction coefficients predicted that
PSFs in heterogeneous soils might mediate stable coexistence only of Rumex congeners.
5. Synthesis. Heterogeneity generated by PSFs had species-specific effects on vital rates, with consequences for recruitment dynamics. Mixing soils of different origin often resulted in non-additive
effects, which may indicate an interaction between soil abiotic and/or biotic properties and could
predict non-additive responses to soil disturbance. Finally, quantifying the reciprocal effects of PSFs
on congeners suggests that PSF-generated heterogeneity may promote coexistence of certain species,
which was not evident from individual PSF responses. Future studies should determine whether such
mechanisms might operate for more distantly related species.
Key-words: environmental heterogeneity, net pairwise soil feedbacks, plant population and
community dynamics, recruitment dynamics, soil history, spatial heterogeneity, vital rates
Introduction
*Correspondence author. E-mail: [email protected]
Soil may be heterogeneous in abiotic factors (e.g. nutrients) or
biotic factors (e.g. microbes), and this heterogeneity is recog-
© 2013 The Authors. Journal of Ecology © 2013 British Ecological Society
278 A. J. Brandt et al.
nized as an important driver of plant community structure and
dynamics (Lundholm 2009). Soil heterogeneity may be driven
by underlying physiochemical variation or generated by the
activities of organisms, but most studies of plant responses to
soil heterogeneity have focused on underlying heterogeneity in
factors such as nutrients and water (Hutchings, John & Wijesinghe 2003; Lundholm 2009; Reynolds & Haubensak 2009).
Increasing recognition of plant–soil feedback (PSF) effects on
plant growth, combined with the observation that PSFs operate
at small spatial scales, suggests that the consequences of PSFgenerated soil heterogeneity for plant population and community dynamics deserve more attention (Petermann et al. 2008;
Bever et al. 2010). Soil heterogeneity, such as that generated
by PSFs, is expected to affect plant vital rates (i.e. germination
and seedling survival), which in turn influence recruitment
dynamics (Fig. 1) and can provide insight into potential mechanisms for species coexistence. Here, we present the first experimental study of PSF-generated soil heterogeneity to determine
how the spatial context of PSFs affects plant vital rates and
recruitment dynamics and the potential consequences of such
heterogeneity for coexistence.
Considerable empirical evidence suggests that PSFs are
common and can have important species-specific effects on
individual plant fitness (reviewed in Kulmatiski et al. 2008;
Brinkman et al. 2010). However, we rarely know both individual responses to PSFs and their population consequences,
which is important because individual plant responses, such
as fecundity, might be different from the response of the
whole population (Ehrlen 2003; Halpern & Underwood
2006). Furthermore, we do not know whether all vital rates,
such as germination and survival, respond similarly to PSF
and how these responses contribute to population dynamics.
We expect PSFs are important for population dynamics
because effects of PSF on recruitment of tropical forest seedlings have been shown to be stronger than above-ground
herbivory or pathogen pressure (Mangan et al. 2010). The
direction of PSF effects sometimes correlates with patterns of
species abundance in both forest (Mangan et al. 2010) and
grassland systems (Klironomos 2002; but see Diez et al.
2010), providing evidence for the role of PSFs in structuring
communities. To begin to address the mechanisms driving
population consequences of PSFs, we assess whether the relative roles of vital rates in recruitment dynamics change in
response to PSF-generated soil heterogeneity.
Vital rate:
Germination
Vital rate:
Seedling
survival
Recruitment dynamics
(population size, timing
& rate of recruitment)
Soil
heterogeneity
Fig. 1. Soil heterogeneity, such as spatial heterogeneity generated by
plant–soil feedbacks, is predicted to affect individual vital rates (i.e.
germination and seedling survival) in a fashion that would scale up to
alter recruitment dynamics (e.g. final population size, timing of
recruitment and recruitment rate).
Knowing how vital rate responses to spatially structured
PSFs influence population dynamics could yield a more
mechanistic understanding of both population- and community-level effects of soil heterogeneity. For example, PSFs
may differentially affect individual vital rates of co-occurring
plant species, which may promote phenological divergence,
or differing rates of recruitment, among soil patches.
Differences between species in the timing of germination
could enhance coexistence in a heterogeneous environment. If
species germinate earlier in heterospecific than in conspecific
soil patches, this could allow reciprocal invasion into each
other’s soil patches, leading to coexistence. Consistent with
this, negative PSFs within functional groups of a suite of
grassland species suggest that PSFs promote temporal turnover in species distributions across the community (Petermann
et al. 2008). Thus, soil heterogeneity generated by PSFs may
be an important driver of heterogeneity–diversity patterns,
and examining detailed information about vital rates and phenology may yield insights into the coexistence consequences
of PSF-generated heterogeneity.
While PSFs have been most commonly calculated for individual species (Kulmatiski et al. 2008), a significant body of
theory has established that understanding PSF effects on conspecifics relative to heterospecifics, or net pairwise feedback,
is a key component to determining the potential for PSFs to
mediate coexistence between species pairs (Bever, Westover
& Antonovics 1997; Bever 2003). Determining the reciprocal
effects of two species’ PSFs on each other in a net pairwise
approach provides a useful complement to measuring PSF
effects on individual species. For example, reciprocal negative
feedbacks, even if individual effects are weak, may promote
coexistence of two competitors (Bever, Westover & Antonovics 1997). Combining a net pairwise feedback approach with
measurement of vital rates and their population consequences
would provide insight into the mechanisms responsible for
potential coexistence outcomes due to PSF-generated heterogeneity.
We conducted an experiment to determine the consequences of heterogeneity in soil origin for recruitment of six
co-occurring old-field perennial plant species in north-eastern
Ohio, USA, using congeneric pairs to control for relatedness.
Coexistence between close relatives and ecologically similar
species can be difficult to explain, given the expectation of
their high niche overlap and the consequent intensity of competition between them (Darwin 1859; MacArthur & Levins
1967; Cavender-Bares et al. 2009). The strength of competition between close relatives or more distantly related plants
can depend on soil origin (Burns & Strauss 2011). Also, species phylogeny and provenance (i.e. native vs. introduced)
both contribute to patterns in PSF responses (reviewed in
Kulmatiski et al. 2008; Brandt, Seabloom & Hosseini 2009;
Diez et al. 2010). Here we provide an initial, conservative
test of the role of PSF-generated heterogeneity in recruitment
dynamics and coexistence by focusing on congeneric pairs of
perennial plants of the same provenance (introduced).
To quantify the mechanistic links among soil heterogeneity,
vital rates and recruitment, we first determined whether PSF-
© 2013 The Authors. Journal of Ecology © 2013 British Ecological Society, Journal of Ecology, 101, 277–286
Heterogeneity in feedback affects recruitment 279
generated heterogeneity altered the role of individual vital
rates in multiple aspects of recruitment (Fig. 1). Second, to
assess the potential for PSF-generated heterogeneity to lead to
coexistence between closely related species, we calculated net
pairwise interaction coefficients (Bever, Westover &
Antonovics 1997) for congeneric plant pairs. We hypothesized that: (i) vital rates (i.e. germination and seedling survival) will be higher in congener than in conspecific soil
patches, as PSFs are most commonly found to be negative
(Kulmatiski et al. 2008); (ii) vital rates in homogeneous
(mixed) soils will be an average of those in conspecific and
congener soils; (iii) given patch-scale vital rate responses as
described in H1 and H2, the relative importance of each vital
rate to recruitment dynamics at the population scale will not
differ between heterogeneous and homogeneous soil treatments incorporating multiple patches; (iv) differentiation in
vital rates between conspecific and congener soil will result in
negative pairwise interaction coefficients, indicating that PSFgenerated heterogeneity promotes coexistence between close
relatives.
Materials and methods
EXPERIMENTAL DESIGN
We established a common garden at Case Western Reserve University’s Valley Ridge Farm in Hunting Valley, Ohio, USA (41°29′ N,
81°25′ W), in summer 2011 to compare recruitment dynamics of six
introduced perennial plant species grown in experimentally manipulated heterogeneous and homogeneous soil. We sank 57-L pots
(45 cm diameter at top 9 42 cm deep) into the ground in five rows
within a deer exclosure in an old field and laid landscape fabric to
prevent growth of vegetation around the pots. Treatments were randomly assigned to pots, with a total sample size of 120 (6 species 9 2 soil treatments 9 10 replicates). Plant host–influenced soils
for use in feedback tests can be obtained from manipulative experiments where homogeneous soil is conditioned by different plant hosts
or by sampling soil close to established adult plants in the field
(Bever et al. 2010). We used the latter approach, collecting field soil
to a maximum 18-cm depth within a 25-cm radius of each of three
Heterogeneous
(a)
(b)
Homogeneous
α
ß
α
αß
αß
αß
ß
α
ß
αß
αß
αß
Fig. 2. Field-collected soil from a congeneric plant pair was potted in
a (a) heterogeneous and (b) homogeneous arrangement to test the
effects of soil heterogeneity generated by plant–soil feedbacks on
recruitment dynamics. Soil a was collected from species A, and soil
ß was collected from species B. The area outside of the grid was
filled with coarse sand. Seeds were planted into two locations within
each grid cell (represented by black triangles).
congeneric pairs of weedy perennial plants (Plantago lanceolata L.,
Plantago major L., Rumex crispus L., Rumex obtusifolius L., Solanum carolinense L. and Solanum dulcamara L.) that are common and
co-occur in old fields on the farm. Soil was collected in approximately six batches for each congeneric species pair, and batches were
haphazardly used to fill pots. Heterogeneous and homogeneous soil
environments within pots were created by potting field soil into a
plastic grid of 2 9 3 cells inserted into the pot (Fig. 2). Each grid
cell was 10 cm 9 10 cm, and field soil was potted to a depth of
18 cm with an 18-cm layer of coarse sand beneath (except for soil
collected from Solanum spp., which was potted to a depth of 9 cm,
with a 27-cm layer of coarse sand beneath, due to limited availability
of Solanum soils on the farm). The heterogeneous soil treatment was
created by alternately filling grid cells with spadefuls of soil from
each species in the congeneric pair (Fig. 2a). The homogeneous soil
treatment was created by filling each cell with alternating spadefuls of
soil from each species to produce a 1:1 mixture of soil from both species in the pair (Fig. 2b). The area of the pot outside the grid was
filled with coarse sand, and the grid was gently removed from the
pot. Collection and potting of soil in both treatments resulted in similar disturbance to soil structure, and the design’s goal was to vary the
heterogeneity in soil origin while maintaining a constant mean in soil
properties.
Seeds of the six focal plant species were hand-collected on the farm
in 2010 and pooled from several mothers from 1 to 3 populations. Each
species was sown as a monoculture into heterogeneous and homogeneous soils collected from its corresponding congeneric pair. Seeds
were glued individually onto plastic toothpicks and sown two at a time
into opposite corners of each cell of the soil grid (Fig. 2), for a total of
12 planting locations within each pot, and 24 seeds planted per pot in
the initial sowing during the first week of July. Pots were censused
weekly from 14 July to 4 October for the number of plants present at
each planting location. To establish populations of equal density for
future studies, we added two seeds on 27 July and 16 August to each
planting location lacking established plants in the prior census (thus up
to six seeds total were planted at each of the two locations within grid
cells; Fig. 2). Seedlings germinating from the soil seed bank were
removed during weekly censuses.
VITAL RATES – GERMINATION AND SEEDLING
MORTALITY
The proportion of planted seeds that germinated and the proportion of
individuals that died were calculated for each grid cell (i.e. soil patch;
Fig. 2) to determine effects of conspecific soil, congener soil and
homogeneous soil on vital rates. For all analyses, mortality was used
as a vital rate in place of survival because the total number of surviving individuals was equivalent to population size at the final census.
RECRUITMENT DYNAMICS
We fit logistic growth curves to the time-series census data from each
pot to estimate recruitment rate parameters: initial population size (i.e.
population size at t0), maximum estimated population size (i.e. horizontal asymptote at high values of t), time to reach half of the estimated maximum population size (i.e. value of t at the curve’s
inflection point) and the inverse of maximum recruitment rate (i.e.
steepest slope of the curve) (Gurney & Nisbet 1998). We fit both a
self-starting model estimating all four parameters and a self-starting
three-parameter model where initial population size was assumed to
be zero in R version 2.14.2 (R Development Core Team 2012). When
© 2013 The Authors. Journal of Ecology © 2013 British Ecological Society, Journal of Ecology, 101, 277–286
280 A. J. Brandt et al.
both models successfully fit the data, we chose the model with the
lowest AIC. Parameters could not be determined for 21 pots, often
due to low population size or herbivory leading to a population
decline at the end of the season, and an additional pot was excluded
from recruitment analysis as an outlier due to poor fit of the curve,
for a total sample size of 98 pots in recruitment analyses. See Fig. S1
in Supporting Information for example figures showing fits of the
growth curves. We used population size at the final census, time to
half of maximum population size and maximum recruitment rate as
recruitment responses.
STATISTICAL ANALYSES
To determine whether vital rate responses differed by soil origin
(Hypothesis 1) and whether homogeneous soil produced an average
response (Hypothesis 2), proportion germination and proportion mortality within a grid cell type (conspecific, congener or homogeneous
mixture of the two soil types) were analysed using mixed effects
models in the lme4 R package (Bates, Maechler & Bolker 2011) with
a binomial error distribution, where ‘pot’ was included as a random
effect. The full model included the effects of soil type, species and
their interaction, using orthogonal contrasts to compare homogeneous
to unmixed soil, conspecific to congener soil and species within a
congeneric pair. To interpret significant interactions, we constructed
orthogonal contrasts comparing the effects of homogeneous to
unmixed soil and conspecific to congener soil within each species in
an additional mixed effects model for each vital rate.
To determine whether PSF-generated heterogeneity altered the relative importance of vital rates to recruitment dynamics (Hypothesis 3),
we estimated the effects of soil treatment, species, total germination and
total mortality on recruitment parameters (final population size, time to
half of maximum population size and maximum recruitment rate) with
multivariate regression using Pillai’s test statistic from a Type III MANOVA to control for type I error when analysing multiple response variables
in the car R package (Fox & Weisberg 2011) because the design was
unbalanced. We included the number of seeds planted per pot as a covariate because it differed among species and soil treatments (see Fig.
S2 in Supporting Information). We constructed orthogonal contrasts to
compare species within each congeneric pair. We square -root-transformed germination, mortality and final population size, natural logtransformed recruitment rate and squared the number of seeds planted
to achieve normal distributions of the data. The model included threeway interactions between soil treatment, species and each vital rate;
interactions between the vital rates were excluded to reduce multicollinearity. Transformed germination and mortality were uncorrelated
(r = 0.098, P = 0.3), and variance inflation factors were low (VIF < 3)
when both vital rates were included as main effects in univariate linear
models with each recruitment response; thus, we do not expect multicollinearity to be a concern. We examined residual plots to determine
whether the data met model assumptions. To interpret significant interactions, we constructed orthogonal contrasts comparing the effects of
heterogeneous and homogeneous soil within each species in an additional multivariate regression including interactions with vital rates and
number of seeds planted as a covariate. For each multivariate analysis,
we used false discovery rates to determine the appropriate a for interpreting t-test results from individual predictors as significant. We calculated q-values with the bootstrap method for p0 using the qvalue R
package (Storey, Taylor & Siegmund 2004). Q-values indicated that
8.63% of the 11 P-values < 0.012 from the initial multivariate model
and 6.81% of the 11 P-values < 0.012 from the model contrasting soil
effects within species were expected to be false positives (i.e. less than
one of the P-values from each analysis is expected to be a false positive); thus, we considered a = 0.012 to be an acceptable significance
level.
To determine whether heterogeneity in PSFs might mediate coexistence among congeneric pairs of species (Hypothesis 4), we estimated
pairwise interaction coefficients as Is = G(A)a – G(A)ß – G(B)a + G
(B)ß, where a soil is cultured by species A and ß soil is cultured by
species B, and G represents a measure of plant species response, such
as growth (Bever, Westover & Antonovics 1997; Bever 2003). Here,
three interaction coefficients were calculated based on proportion germination, proportion mortality and standardized final population size
(population size at the final census divided by the total number of
seeds planted) within each soil type in a pot. The other recruitment
parameters, time to half-max and maximum recruitment rate, could
not be used to calculate interaction coefficients because these parameters were determined at the scale of the entire pot. Soil feedback
responses within a species were calculated as the difference in a
response between soil collected from conspecifics and soil collected
from congeners in each of the 10 pots with heterogeneous soil (i.e. G
(A)a – G(A)ß and G(B)ß – G(B)a; Fig. 2a). The within-species feedback responses to the different soil types were thus non-independent.
Feedback responses of each congeneric species pair were summed for
all possible pairwise combinations of pots to obtain mean pairwise
interaction coefficients (n = 100 coefficients per genus, except n = 80
coefficients for proportion mortality of Plantago spp. because P.
major did not germinate in one of the soil types in two pots). We
constructed 95% confidence intervals by sampling with replacement
for 1000 iterations to determine whether the mean coefficient was significantly different from zero.
Results
All six species were able to establish in both heterogeneous
and homogeneous soils (Fig. 3).
WERE VITAL RATES HIGHER IN CONGENER THAN IN
CONSPECIFIC SOIL? (H1)
Soil origin affected germination for only two species, while
mortality did not differ between patch types (Fig. 4 and see
Table S3 in Supporting Information). Consistent with expectations, proportion germination of S. carolinense was higher in
congener than in conspecific soil (z = 1.84, P = 0.066;
Fig. 4a and Table S3). Contrary to expectations, proportion
germination of P. lanceolata was higher in conspecific than
in congener soil (z = 2.07, P = 0.039; Fig. 4a and Table
S3). Proportion germination differed within each congeneric
pair of species, with higher germination of P. lanceolata
(z = 4.51, P < 0.0001), R. obtusifolius (z = 2.66,
P = 0.008) and S. carolinense (z = 10.21, P < 0.0001) than
each of their respective congeners (Fig. 4a and Table S3).
WERE VITAL RATES IN HOMOGENEOUS SOIL AN
AVERAGE OF THOSE IN CONSPECIFIC AND CONGENER
SOIL? (H2)
Contrary to our hypothesis, the effect of the homogeneous
soil treatment on vital rates was not always an additive function of the two soil patch types within the heterogenous
© 2013 The Authors. Journal of Ecology © 2013 British Ecological Society, Journal of Ecology, 101, 277–286
Heterogeneity in feedback affects recruitment 281
Plantago lanceolata
12
Number of individuals
10
Rumex crispus
Solanum carolinense
12
Heterogeneous soil
Homogeneous soil
10
8
8
6
6
4
4
2
2
20
15
10
5
0
0
1 2 3 4 5 6 7 8 9 10 11 12 13
0
1 2 3 4 5 6 7 8 9 10 11 12 13
Plantago major
1 2 3 4 5 6 7 8 9 10 11 12 13
Rumex obtusifolius
Solanum dulcamara
6
12
12
5
10
10
4
8
8
3
6
6
2
4
4
1
2
2
0
0
1 2 3 4 5 6 7 8 9 10 11 12 13
14 July
4 Oct
0
1 2 3 4 5 6 7 8 9 10 11 12 13
14 July
Week
4 Oct
1 2 3 4 5 6 7 8 9 10 11 12 13
14 July
4 Oct
Fig. 3. Mean number of individuals per pot ( SE) of six species sown in heterogeneous or homogeneous soil treatments and censused for
13 weeks in 2011. Arrows indicate two additional plantings of two seeds to each planting location lacking an individual in the previous census.
Note: Scale of the y-axis differs among species.
Proportion germination
1.0
0.8
*
***
0.6
0.2
1.0
**
***
0.4
0.0
Proportion mortality
(a)
*
PLALAN
PLAMAJ
RUMCRI RUMOBT SOLCAR
(b)
SOLDUL
Conspecific soil
Congener soil
Homogeneous soil
0.8
0.6
*
0.4
0.2
0.0
PLALAN
PLAMAJ
RUMCRI RUMOBT SOLCAR
SOLDUL
Species
Fig. 4. (a) Proportion germination and (b) proportion mortality of six
species sown into heterogeneous and homogeneous soil treatments,
where soil patches consisted of conspecific soil, congener soil or a homogeneous mixture of the two soil types. Brackets indicate significant differences determined by contrasts of responses among species within a
congeneric pair and within species in homogeneous vs. unmixed soil
types and in conspecific vs. congener soil (*P < 0.05, **P < 0.01,
***P < 0.0001). PLALAN = Plantago lanceolata, PLAMAJ = P.
major, RUMCRI = Rumex crispus, RUMOBT = R. obtusifolius, SOLCAR = Solanum carolinense, SOLDUL = S. dulcamara.
treatment (Fig. 4 and Table S3). Proportion germination of S.
carolinense was lower in a homogeneous mixture of soils
than in patches containing soil of one origin (z = 2.21,
P = 0.028; Fig. 4a and Table S3). Proportion mortality of
Rumex congeners responded differently to homogeneous and
unmixed soils (z = 2.73, P = 0.006 for the interaction
between species and soil type), where R. crispus had higher
mortality, and thus lower survival, in homogeneous soil
(z = 2.32, P = 0.020), and R. obtusifolius exhibited the opposite response, although it was not statistically significant
(z = 1.52, P = 0.13; Fig. 4b and Table S3).
MAIN EFFECTS OF VITAL RATES ON RECRUITMENT
Each of the measured vital rates (germination and mortality)
was a significant predictor of recruitment dynamics, although
their effects differed among recruitment parameters (Table 1
and see Table S4 in Supporting Information). Higher germination led to larger final population sizes within a pot (t = 12.96,
P < 0.0001; Table S4). Higher mortality led to smaller final
population sizes (t = 9.64, P < 0.0001), a shorter time to
reach half of maximum population size (t = 4.11,
P = 0.0001) and a higher maximum recruitment rate (t = 3.77,
P = 0.0004; Table S4). According to these t-statistics, the relative importance of germination for determining final population
size was greater than the importance of mortality. However, the
opposite was true for time to half-max and maximum recruitment rate, where mortality (t = 4.11 and 3.77, respectively)
was a more important driver than germination (t = 2.49 and
t = 2.18, respectively; Table S4).
© 2013 The Authors. Journal of Ecology © 2013 British Ecological Society, Journal of Ecology, 101, 277–286
282 A. J. Brandt et al.
Table 1. Effects of species, soil treatment (heterogeneous vs. homogeneous), germination, mortality and the number of seeds planted on recruitment, measured as final population size, time to half of maximum estimated population size and maximum recruitment rate, from a Type III
MANOVA using Pillai’s test statistic
Predictor
d.f.
Pillai’s statistic
Approximate, F
Numerator, d.f.
Denominator, d.f.
P
Intercept
Species
Soil treatment
Germination
Mortality
Seeds planted
Species 9 soil
Species 9 germination
Soil 9 germination
Species 9 mortality
Soil 9 mortality
Species 9 soil 9 germination
Species 9 soil 9 mortality
1
5
1
1
1
1
5
5
1
5
1
5
5
0.073
0.36
0.043
0.74
0.64
0.60
0.39
0.36
0.074
0.46
0.23
0.36
0.39
1.56
1.67
0.88
54.77
34.65
29.71
1.84
1.65
1.56
2.19
5.80
1.65
1.85
3
15
3
3
3
3
15
15
3
15
3
15
15
59
183
59
59
59
59
183
183
59
183
59
183
183
0.21
0.060
0.45
< 0.0001
< 0.0001
< 0.0001
0.032
0.064
0.21
0.008
0.002
0.065
0.031
Orthogonal contrasts were performed to compare species within congeneric pairs. n = 98 due to some pots having poor fits to logistic growth
curves and removal of an outlier. Significant P-values are in bold.
DID RELATIVE IMPORTANCE OF VITAL RATES TO
RECRUITMENT DIFFER WITH SOIL HETEROGENEITY?
(H3)
Soil heterogeneity altered effects of vital rates on the timing
and rate of recruitment for some species (Table 1 and see
Table S4 in Supporting Information). Time to half-max and
maximum recruitment rate were more strongly related to mortality in heterogeneous soil (slope of linear model = 0.72
and 0.86, respectively) than in homogeneous soil
(slope = 0.11 and 0.24, respectively; t = 2.64, P = 0.011
and t = 3.36, P = 0.001 for interactions between soil and
mortality, respectively; Table S4 and see Fig. S5 in Supporting Information). Solanum dulcamara recruited later into heterogeneous soil (t = 3.68, P = 0.0005; Table S4 and see Fig.
S6 in Supporting Information), and the relationship of individual vital rates to its time to half-max differed by soil treatment (t = 2.98, P = 0.004 for interaction between soil and
germination; t = 3.40, P = 0.001 for interaction between
soil and mortality; Table S4). Germination of S. dulcamara
was more strongly related to time to half-max in heterogeneous soil (slope of linear model = 1.26) than in homogeneous soil (slope = 0.90), while mortality was more strongly
related to time to half-max in homogeneous soil
(slope = 1.70) than in heterogeneous soil (slope = 0.67; Fig.
S6). Plantago major had a higher maximum recruitment rate
in heterogeneous soil (t = 3.13, P = 0.003; Table S4 and
Fig. 3), but this result was largely driven by one pot’s high
recruitment rate.
DID PSF-GENERATED HETEROGENEITY PRODUCE
NEGATIVE PAIRWISE INTERACTION COEFFICIENTS?
(H4)
Net pairwise interaction coefficients indicated that reciprocal
effects of PSFs on congeneric species grown in heterogeneous
soils differed by genus and by the response measured
(Fig. 5). The mean interaction coefficients for proportion germination and final population size were significantly positive
for Plantago spp. and significantly negative for Rumex spp.
(Fig. 5a,c). For Solanum spp., the mean interaction coefficient
for germination was significantly negative (Fig. 5a), while the
mean interaction coefficient for population size was not
significantly different from zero (Fig. 5c). For all three congeneric pairs, interaction coefficients for proportion mortality
were not significantly different from zero (Fig. 5b). Germination coefficients for Plantago and Rumex spp. were thus more
similar to population size coefficients than were coefficients
calculated from mortality data, while the mortality coefficient
was more similar to the population size coefficient for Solanum spp. Germination and population size coefficients predict
that PSFs in heterogeneous soil may mediate coexistence
between Rumex congeners.
Discussion
In a common garden experiment, we conducted the first direct
manipulation of spatial variation in plant–soil feedbacks
(PSFs) and present a conceptual framework to evaluate how
effects of PSF-generated heterogeneity on vital rates may ultimately affect recruitment dynamics (Fig. 1). Across six introduced perennial plant species that commonly co-occur at our
field site, we demonstrated that PSF-generated heterogeneity
altered vital rates and their relationship to recruitment dynamics in a species-specific fashion. Homogeneous soils also had
non-additive effects on vital rates for some species. Speciesspecific differences in recruitment can have important consequences for coexistence, which can be difficult to explain for
closely related and ecologically similar species (Darwin 1859;
MacArthur & Levins 1967; Cavender-Bares et al. 2009). Net
pairwise interaction coefficients indicated that PSFs could
contribute to stable coexistence between Rumex congeners in
heterogeneous soil, but are unlikely to contribute to stable
coexistence for Plantago and Solanum species (Fig. 5)
© 2013 The Authors. Journal of Ecology © 2013 British Ecological Society, Journal of Ecology, 101, 277–286
Heterogeneity in feedback affects recruitment 283
Germination
0.10
(a)
0.05
0.00
–0.05
0.2
Mortality
Interaction coefficients
–0.10
(b)
0.1
0.0
–0.1
–0.2
Population size
0.10
(c)
0.05
0.00
–0.05
–0.10
Plantago
Rumex
Solanum
Genus
Fig. 5. Mean interaction coefficients for net pairwise soil feedbacks
in three congeneric plant pairs based on (a) proportion germination,
(b) proportion mortality and (c) standardized final population size
with 95% bootstrapped confidence intervals. Pairwise interaction coefficients for each congeneric pair were obtained by summing feedback
responses from each species of the pair for all possible pairwise combinations of pots. Feedback responses for each species were calculated as G(A)a – G(A)ß, where a soil was field-collected from species
A and ß soil from its congener, species B, and G(A) was the response
of species A. Confidence intervals were calculated by sampling with
replacement for 1000 iterations to determine whether the mean coefficient was significantly different from zero (n = 100 coefficients
per genus, except n = 80 coefficients for Plantago spp. mortality
coefficients (b)).
(Bever, Westover & Antonovics 1997; Bever 2003). Decomposing population size interaction coefficients by vital rates
suggests that differences in germination between soil types
lead to these population-level predictions, while differences in
mortality between soil types do not appear to contribute to
these population-level predictions (Fig. 5).
Soil origin affected germination of only two species of the
six tested. A recent meta-analysis found that soils conditioned
in a greenhouse tend to produce stronger PSFs (Kulmatiski
et al. 2008), so the low frequency of PSF effects obtained
with field-collected soil and outdoor mesocosms in our experiment may be more representative of natural PSFs. Additionally, Kulmatiski et al. (2008) demonstrated that native species
had significantly more negative PSFs on average than invasive species, potentially explaining why we did not observe
strong or frequent negative PSFs for the introduced species in
our experiment (but see Diez et al. 2010). The strongest PSF
effect we observed was higher germination of P. lanceolata
in conspecific than congener soil (Fig. 4a). The relative positive effect of conspecific soil on P. lanceolata’s germination
coupled with the strong role of germination in recruitment
(Tables 1 and S4) suggests that P. lanceolata might be experiencing facilitation mediated by the soil environment, which
may lead to the unstable dynamics between Plantago congen-
ers predicted by net pairwise interaction coefficients (Fig. 5).
This interpretation is consistent with the mutualism facilitation
hypothesis of invasion (Wolfe & Klironomos 2005; Mitchell
et al. 2006), as P. lanceolata is considered a more noxious
invader than its congener, P. major (listed as a noxious weed
in two states vs. none, respectively) (USDA NRCS 2012).
We asked whether patchiness in abiotic and/or biotic soil
properties caused by PSF has consequences for vital rates and
therefore recruitment, which can be important for the population dynamics of perennial plants (Silvertown et al. 1993;
Ramula et al. 2008). The PSF literature has been inconsistent
in which measure of plant performance is evaluated, where
biomass, aspects of recruitment and reproductive output are
commonly used to assess PSF effects (e.g. Bever 1994; Klironomos 2002; Petermann et al. 2008; Brandt, Seabloom &
Hosseini 2009; Mangan et al. 2010; Burns & Strauss 2011;
Shannon, Flory & Reynolds 2012). The differences we
observed in the relative importance of different vital rates
among species and recruitment parameters suggest that studies
of PSF effects on a single response variable (e.g. germination
or total biomass) might miss important population consequences of PSFs. Seeds were not limiting in this experiment;
therefore, effects of heterogeneity on recruitment could be
greater in a seed-limited environment. Furthermore, recruitment is only one part of the life cycle, and our design could
not determine the relative importance of the different recruitment parameters to population growth rate, so future studies
should incorporate complete measures of population dynamics. This is the first experiment to manipulate heterogeneity in
PSFs, but previous work manipulating soil nutrient heterogeneity also found that effects of heterogeneity can influence
vital rates and thus population dynamics (Hutchings, John &
Wijesinghe 2003; but see Casper & Cahill 1996).
Contrasts between soil types suggest that mixing soils of
different origin have non-additive effects on vital rates, at
least for some species, and understanding such non-additive
effects is widely recognized as crucial for understanding species interactions (Agrawal et al. 2007). For example, S. carolinense had lower germination, and R. crispus had higher
mortality in homogeneous soil than would be predicted from
either conspecific or congener soil (Fig. 4), resulting in a
negative effect of soil homogenization on vital rates. This
result may represent an interaction between soil heterogeneity and abiotic and/or biotic properties of the soil. For example, if conspecific and congener soil contain different
microbial communities, mixing the soils may result in interactions among microbes that synergistically affected germination of S. carolinense and mortality of R. crispus.
Alternatively, mixing soils may alter nutrient availability or
water-holding capacity in each soil. This is the first study to
our knowledge to examine PSF effects of mixed soils; thus,
the generality of our results are unclear (but see mid-successional soil fauna effects in De Deyn et al. 2003). The prevalence of soil disturbance, through both anthropogenic
practices and bioturbation (Cramer, Hobbs & Standish 2008;
Wilkinson, Richards & Humphreys 2009), suggests that
further understanding of how soil mixing affects plant
© 2013 The Authors. Journal of Ecology © 2013 British Ecological Society, Journal of Ecology, 101, 277–286
284 A. J. Brandt et al.
recruitment, and thus diversity, compared with undisturbed
soil is important to inform both ecological knowledge and
restoration efforts. In addition, comparing the PSF effects of
a mixture of two species’ soils to soil collected from the
zone of root overlap between those species would provide a
useful complement to this study in determining how the spatial context of PSFs in the field affects plant population
dynamics and coexistence.
Non-additive effects of PSFs may help us understand conflicts between theoretical predictions and observations of environmental heterogeneity’s effects on community structure.
Theory often predicts that heterogeneity will increase species
diversity in communities, but empirical studies have found
both positive and negative correlations between heterogeneity
and species diversity (reviewed in Lundholm 2009 and
Reynolds & Haubensak 2009). In this system, we might
expect S. carolinense to be dominant compared with S. dulcamara based on its higher total germination (Fig. 4a) and status as a more noxious invader (listed as a noxious weed in
seven states vs. one, respectively) (USDA NRCS 2012).
However, lower total germination of S. carolinense in homogeneous soils compared with conspecific and congener soils
(Fig. 4a) could leave more open spaces for its congener to
colonize, which could promote coexistence in the homogeneous environment. Moreover, PSF-generated heterogeneity
was not predicted to mediate coexistence for Solanum congeners (Fig. 5). Thus, negative or non-significant relationships
between environmental heterogeneity and species diversity
may result from non-additive effects in homogeneous environments that affect recruitment of better colonizers or
competitors.
Environmental heterogeneity could promote multiple mechanisms of coexistence by affecting different aspects of plant
recruitment, such as the number of recruits in a growing season and the timing of recruitment. Net pairwise PSFs differed
among the three congeneric pairs in our study and among
vital rate and population size responses, where germination
appeared to be a better predictor of the final population size
interaction coefficient than was mortality (Fig. 5), consistent
with recruitment analyses on individual species (Tables 1 and
S4). A negative system-level interaction coefficient is predictive of feedbacks mediating coexistence (Bever, Westover &
Antonovics 1997) and was observed for germination and population size responses of Rumex spp. Although individual
PSF effects on each species’ vital rates did not indicate significant differences between soil types (Fig. 4), the marginally
higher germination of each Rumex spp. in its congener’s soil
led to a negative pairwise effect in both germination and population size coefficients. These results suggest that coexistence
predictions based on individual PSF effects may not always
be adequate to predict coexistence outcomes (Kulmatiski
et al. 2008), and understanding the roles of vital rates may
yield insight into mechanisms governing coexistence.
Although our experimental design rendered differences in a
species’ response to each soil type non-independent, our
results suggest that explicitly considering the spatial context of
PSFs may be important to predicting their role in coexistence.
The relatively few studies examining net pairwise feedback
dynamics to date have observed both negative and positive
interaction coefficients (e.g. Shannon, Flory & Reynolds
2012; Smith & Reynolds 2012), suggesting that the role of
PSFs in mediating coexistence is species specific. More studies are needed to determine whether there are generalities in
net pairwise PSFs, particularly among whole plant
communities, and to test the predictions made by these coefficients using coexistence theory criteria, such as by comparing
reciprocal invasibility in heterogeneous and homogeneous
soils.
Effects of heterogeneity on recruitment could also mediate
coexistence through effects on timing (Chesson et al. 2004).
We found that S. dulcamara recruited later into heterogeneous
than homogeneous soils, particularly when total germination
was low. This could leave more open niches early in the season, facilitating greater recruitment of other species into heterogeneous environments compared with homogeneous
environments, and thus facilitating greater coexistence
between congeners in more heterogeneous soils. Because timing and rate of recruitment were determined only at the pot
scale using logistic growth curves, we could not calculate net
pairwise interaction coefficients for these responses to compare them directly to population size coefficients. However,
our results suggest that measuring phenological responses,
and not just mean differences in vital rates, may be important
for understanding coexistence consequences of PSFs. Further
studies directly estimating coexistence are necessary to determine the importance of differences in phenology, relative to
other processes, in determining coexistence outcomes of
heterogeneity (Chesson et al. 2004).
By using congeneric species pairs, we provided a conservative test of the role of PSF-generated heterogeneity on vital
rates and recruitment dynamics because PSF effects of conspecific and congener soil are often similar (Diez et al. 2010),
potentially due to species specificity of plant pathogens
(Parker & Gilbert 2004). Our goal in examining co-occurring
congeners under spatially patchy or homogeneous PSFs was
to integrate a test of coexistence theory with the mechanism
of PSFs. Coexistence between closely related species may be
especially difficult to explain because close relatives are
expected to have similar niches and thus compete more
strongly than distant relatives (MacArthur & Levins 1967;
Cavender-Bares et al. 2009), a pattern which can be mediated
through the soil (Burns & Strauss 2011). Future studies that
explicitly address the potential for PSF-generated soil heterogeneity to mediate coexistence among more distantly related
species would provide a useful integration of this study’s
findings with previous work on community-scale reciprocal
PSFs (e.g. Petermann et al. 2008; Shannon, Flory &
Reynolds 2012; Smith & Reynolds 2012) to determine the
generality of our results.
Here, we have addressed two main gaps in PSF studies to
date: (i) including PSFs as a driver of soil heterogeneity and
(ii) examining the links between vital rates and recruitment
dynamics, including the framework of net pairwise feedback,
to predict coexistence outcomes mediated by PSF-generated
© 2013 The Authors. Journal of Ecology © 2013 British Ecological Society, Journal of Ecology, 101, 277–286
Heterogeneity in feedback affects recruitment 285
heterogeneity. This is also the first study to demonstrate that
PSFs can have non-additive effects that influence plant
responses to soil heterogeneity. By linking vital rate and
recruitment responses, we have gained insight into potential
mechanisms by which PSF-generated heterogeneity may
mediate coexistence. Future comparative studies incorporating
plant characteristics (e.g. provenance, invasiveness,
life-history strategies, successional stage (Kardol, Bezemer &
van der Putten 2006; Kulmatiski et al. 2008; Brandt,
Seabloom & Hosseini 2009; Shannon, Flory & Reynolds
2012; Smith & Reynolds 2012)) that are predictive of PSF
responses might elucidate the mechanisms behind species-specific responses and improve predictions of heterogeneity’s
role in coexistence. Finally, we found PSFs on individual
vital rates were not always sufficient to predict net pairwise
interactions and thus potential coexistence outcomes of heterogeneity, suggesting that more studies quantifying net pairwise interaction coefficients (Kulmatiski et al. 2008) and
direct assessments of coexistence as a function of whole-soil
heterogeneity are greatly needed.
Acknowledgements
We thank Case Western Reserve University’s Squire Valleevue and Valley
Ridge Farms, especially C. Bond and A. Alldridge, for help establishing the
common garden. L. Huffman, S. C. Leahy and N. M. Zimmerman provided field
assistance. P. R. Hosseini provided scripts for fitting growth curves to the data
and K. S. Moriuchi provided statistical advice. We thank two anonymous
reviewers and associate editor W. H. van der Putten for comments that improved
the manuscript. A.J.B. and J.H.B. were funded by start-up funds from CWRU to
J.H.B. This work was also supported by National Science Foundation funding to
J.H.B. (DEB 1250170). We thank the organizers of the ‘Plant-soil feedback: the
past, the present and the future’ symposium at the Ecological Society of
America’s annual meeting in 2012 for inviting us to contribute to this special
feature.
References
Agrawal, A.A., Ackerly, D.D., Adler, F., Arnold, A.E., Caceres, C., Doak, D.F.
et al. (2007) Filling key gaps in population and community ecology. Frontiers in Ecology and the Environment, 5, 145–152.
Bates, D.M., Maechler, M. & Bolker, B.M. (2011) lme4: Linear mixed-effects
models using S4 classes.
Bever, J.D. (1994) Feedback between plants and their soil communities in an
old field community. Ecology, 75, 1965–1977.
Bever, J.D. (2003) Soil community feedback and the coexistence of competitors: conceptual frameworks and empirical tests. New Phytologist, 157, 465–
473.
Bever, J.D., Westover, K.M. & Antonovics, J. (1997) Incorporating the soil
community into plant population dynamics: the utility of the feedback
approach. Journal of Ecology, 85, 561–573.
Bever, J.D., Dickie, I.A., Facelli, E., Facelli, J.M., Klironomos, J., Moora, M.,
Rillig, M.C., Stock, W.D., Tibbett, M. & Zobel, M. (2010) Rooting theories
of plant community ecology in microbial interactions. Trends in Ecology and
Evolution, 25, 468–478.
Brandt, A.J., Seabloom, E.W. & Hosseini, P.R. (2009) Phylogeny and provenance affect plant-soil feedbacks in invaded California grasslands. Ecology,
90, 1063–1072.
Brinkman, E.P., Van der Putten, W.H., Bakker, E.-J. & Verhoeven, K.J.F.
(2010) Plant-soil feedback: experimental approaches, statistical analyses and
ecological interpretations. Journal of Ecology, 98, 1063–1073.
Burns, J.H. & Strauss, S.Y. (2011) More closely related species are more ecologically similar in an experimental test. Proceedings of the National Academy of Sciences, 108, 5302–5307.
Casper, B.B. & Cahill, J.F. Jr. (1996) Limited effects of soil nutrient heterogeneity on populations of Abutilon theophrasti (Malvaceae). American Journal
of Botany, 83, 333–341.
Cavender-Bares, J., Kozak, K.H., Fine, P.V.A. & Kembel, S.W. (2009) The
merging of community ecology and phylogenetic biology. Ecology Letters,
12, 693–715.
Chesson, P., Gebauer, R.L.E., Schwinning, S., Huntly, N., Wiegand, K., Ernest,
S.K.M., Sher, A., Novoplansky, A. & Weltzin, J.F. (2004) Resource pulses,
species interactions and diversity maintenance in arid and semi-arid environments. Oecologia, 141, 236–253.
Cramer, V.A., Hobbs, R.J. & Standish, R.J. (2008) What’s new about old
fields? Land abandonment and ecosystem assembly. Trends in Ecology and
Evolution, 23, 104–112.
Darwin, C. (1859) On the Origin of Species, 1st edn. John Murray, London.
De Deyn, G.B., Raaijmakers, C.E., Zoomer, H.R., Berg, M.P., de Ruiter, P.C.,
Verhoef, H.A., Bezemer, T.M. & van der Putten, W.H. (2003) Soil invertebrate
fauna enhances grassland succession and diversity. Nature, 422, 711–713.
Diez, J.M., Dickie, I., Edwards, G., Hulme, P.E., Sullivan, J.J. & Duncan, R.P.
(2010) Negative soil feedbacks accumulate over time for non-native plant
species. Ecology Letters, 13, 803–809.
Ehrlen, J. (2003) Fitness components versus total demographic effects: evaluating herbivore impacts on a perennial herb. American Naturalist, 162, 796–
810.
Fox, J. & Weisberg, S. (2011) An {R} Companion to Applied Regression, 2nd
edn. Sage, Thousand Oaks, CA.
Gurney, W.S.C. & Nisbet, R.M. (1998) Ecological Dynamics. Oxford University Press, New York.
Halpern, S.L. & Underwood, N. (2006) Approaches for testing herbivore
effects on plant population dynamics. Journal of Applied Ecology, 43, 922–
929.
Hutchings, M.J., John, E.A. & Wijesinghe, D.K. (2003) Toward understanding
the consequences of soil heterogeneity for plant populations and communities. Ecology, 84, 2322–2334.
Kardol, P., Bezemer, T.M. & van der Putten, W.H. (2006) Temporal variation
in plant-soil feedback controls succession. Ecology Letters, 9, 1080–1088.
Klironomos, J.N. (2002) Feedback with soil biota contributes to plant rarity
and invasiveness in communities. Nature, 417, 67–70.
Kulmatiski, A., Beard, K.H., Stevens, J.R. & Cobbold, S.M. (2008) Plant-soil
feedbacks: a meta-analytical review. Ecology Letters, 11, 980–992.
Lundholm, J.T. (2009) Plant species diversity and environmental heterogeneity:
spatial scale and competing hypotheses. Journal of Vegetation Science, 20,
377–391.
MacArthur, R. & Levins, R. (1967) The limiting similarity, convergence, and
divergence of coexisting species. American Naturalist, 101, 377–385.
Mangan, S.A., Schnitzer, S.A., Herre, E.A., Mack, K.M.L., Valencia, M.C.,
Sanchez, E.I. & Bever, J.D. (2010) Negative plant-soil feedback predicts tree-species relative abundance in a tropical forest. Nature, 466, 752–
755.
Mitchell, C.E., Agrawal, A.A., Bever, J.D., Gilbert, G.S., Hufbauer, R.A.,
Klironomos, J.N. et al. (2006) Biotic interactions and plant invasions. Ecology Letters, 9, 726–740.
Parker, I.M. & Gilbert, G.S. (2004) The evolutionary ecology of novel plantpathogen interactions. Annual Review of Ecology, Evolution and Systematics,
35, 675–700.
Petermann, J.S., Fergus, A.J.F., Turnbull, L.A. & Schmid, B. (2008) JanzenConnell effects are widespread and strong enough to maintain diversity in
grasslands. Ecology, 89, 2399–2406.
R Development Core Team (2012) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.
Ramula, S., Knight, T.M., Burns, J.H. & Buckley, Y.M. (2008) General guidelines for invasive plant management based on comparative demography of
invasive and native plant populations. Journal of Applied Ecology, 45, 1124–
1133.
Reynolds, H.L. & Haubensak, K.A. (2009) Soil fertility, heterogeneity, and
microbes: towards an integrated understanding of grassland structure and
dynamics. Applied Vegetation Science, 12, 33–44.
Shannon, S., Flory, S.L. & Reynolds, H. (2012) Competitive context alters
plant-soil feedback in an experimental woodland community. Oecologia,
169, 235–243.
Silvertown, J., Franco, M., Pisanty, I. & Mendoza, A. (1993) Comparative
plant demography - relative importance of life-cycle components to the finite
rate of increase in woody and herbaceous perennials. Journal of Ecology, 81,
465–476.
Smith, L.M. & Reynolds, H.L. (2012) Positive plant-soil feedback may drive
dominance of a woodland invader, Euonymus fortunei. Plant Ecology, 213,
853–860.
Storey, J.D., Taylor, J.E. & Siegmund, D. (2004) Strong control, conservative
point estimation, and simultaneous conservative consistency of false discov-
© 2013 The Authors. Journal of Ecology © 2013 British Ecological Society, Journal of Ecology, 101, 277–286
286 A. J. Brandt et al.
ery rates: a unified approach. Journal of the Royal Statistical Society, Series
B, 66, 187–205.
USDA NRCS (2012) The PLANTS Database (http://plants.usda.gov). National
Plant Data Team, Greensboro, NC.
Wilkinson, M.T., Richards, P.J. & Humphreys, G.S. (2009) Breaking ground:
pedological, geological, and ecological implications of soil bioturbation.
Earth-Science Reviews, 97, 254–269.
Wolfe, B.E. & Klironomos, J.N. (2005) Breaking new ground: soil communities and exotic plant invasion. BioScience, 55, 477–487.
Received 30 July 2012; accepted 14 November 2012
Handling Editor: Wim van der Putten
heterogeneous or homogeneous soil.
Table S3. Model coefficients and z-tests for effects of species and
soil origin of a patch on proportion germination and proportion
mortality.
Table S4. Model coefficients and t-tests for recruitment contrasts,
demonstrating the effects of species, soil treatment, germination,
mortality and seeds planted on recruitment parameters.
Fig. S5. Soil heterogeneity and mortality interacted to affect time to
reach half of maximum estimated population size and maximum
recruitment rate.
Supporting Information
Additional Supporting Information may be found in the online version of this article:
Fig. S1. Example logistic growth curves for each species fit to recruitment data from individual pots.
Fig. S6. Germination, mortality and soil treatment interacted to
affect time to reach half of maximum estimated population size for
Solanum dulcamara.
Fig. S2. Number of seeds of six species planted per pot containing
© 2013 The Authors. Journal of Ecology © 2013 British Ecological Society, Journal of Ecology, 101, 277–286