Constitutive and induced chemical defense
To
test the contribution of secondary metabolites to constitutive and
induced defenses, we measured chemicals in leaves that were harvested
from previously healthy and herbivore-damaged plants. Terpenoids and
phenols are important
secondary metabolites for defense
against a wide range of herbivores (Mithöfer & Boland, 2012). Thus, we
used the same non-native species and their native congeners used in the
bioassay to measure total phenolics and total triterpenoids in leaves
harvested from healthy and
herbivore-damaged plants.
Leaves were flash frozen in
liquid nitrogen and stored at -80°C for analysis.
Total
phenolic concentration was calculated as described in Supplementary
Methods 2.
Growth rates
To evaluate the relationship between the strength of induced defenses
and plant growth, we measured the relative growth rate of non-native and
native plants. Two weeks after transplanting, we
harvested ten similar-sized plants
for each species and measured total dry biomass
(weight1). After six more weeks, we harvested
conspecifics and determined total dry biomass (weight2).
We calculated relative growth rate (RGR) of each species as: RGR =
(weight2 - weight1) / 42 days. There were 12 replicates for each
combination of weight1 plants and
weight2 plants for each non-native species and native
congeners.
Statistical
analysis
Herbivore
pressure - To test for difference in herbivore pressure (binary data of
undamaged vs. damaged leaves in a cbind matrix) among the
non-native plant species in the field survey, we used a Wald Chi-square
test applied on a Generalized Linear Mixed Model (GLMM) with a binomial
distribution. Site was a random effect. We used a bootstrap method to
test whether results differed when the number of native plant species
was equal to the number of non-native species. We tested for difference
in herbivore pressure (logit-transformed percentage of damaged leaf
area) among the non-native plant species in the common garden experiment
using a Wald Chi-square test applied on a Linear Mixed Model (LMM) with
blocks as random effects. We conducted same analyses for native species.
To test for differences in herbivore pressure (binary data of undamagedvs. damaged leaves in a cbind matrix) between the non-natives and
natives in the field survey, we used a Wald Chi-square test applied on a
GLMM with a binomial distribution. Site and species nested in origin as
random effects. We also tested for differences in herbivore pressure
(logit-transformed percentage of damaged leaf area) in the common garden
experiment using LMM with blocks and species nested in origin as random
effects. Furthermore, we used GLMM with binomial distribution that
included random terms for sites and species to test whether percentage
of damaged leaves (binary data of undamaged vs. damaged leaves in
a cbind matrix) depended on herbivore biomass in the field survey and
used LMM that included random terms for block and species to test
whether percentage of damaged leaf area (logit-transformed) depended on
herbivore biomass in the common garden experiment. Finally, for
non-native species and their native congeners, in both the field survey
and common garden experiment, we used LM to examine the relationship
between leaf damage and herbivore biomass for the two experiments using
mean values for species.
Constitutive and induced defenses - We assessed constitutive and induced
defenses using larval weight gain and chemical contents for each
species. For constitutive defense, we used larval weight gain on the
leaves of plants that had not been previously attacked. For induced
defense, we calculated the larval weight gain on the leaves of
previously attacked plants minus the mean of larval weight gain on the
leaves of un-attacked plants. Constitutive and induced defenses
expressed by chemicals were evaluated using the same methods. We used
the percentage of herbivore-damaged leaf area for each species in the
common garden experiment as herbivore pressure. To evaluate
relationships among constitutive defense, induced defense and herbivore
pressure, we carried out Pearson correlations in which we multiplied
larval weight with -1 since higher larval weight gain indicates lower
defense. Mean values per species were used for above analyses and
non-native and native species were analyzed separately. To test
constitutive and induced defense between non-native and native species
we used LMM with species as a random effect. Finally, to test whether
changes in chemicals might underly changes in herbivore growth, we
conducted Pearson correlations across both herbivory treatments and all
species to examine the dependence of larval weight gain on phenolics or
triterpenoids using mean values per species.
Strength of growth and induced defense - To test for differences in
relative growth rate between non-native plant species and native
congeners, we used a LMM with species nested within origin as random
effects. Furthermore, we calculated difference in induced defense in
term of larval weight gain and difference in plant growth rate between
non-native species and corresponding native congeners. We then used
Pearson correlation to evaluate relationship between difference in
induced defense and difference in plant growth rate.
Homogeneity of variances and normality of distributions of data were
checked before data analysis and P-values were corrected by False
Discovery Rate (FDR) (Benjamini & Hochberg, 1995). All statistics were
carried out using R (version 4.0.5) with the ‘car’, ‘lme4’, and
‘RVAideMemoire’ packages (Bates, 2014).