APPENDIX S1: Supplementary methods
Sampling
To minimize the reduction of herbivore numbers over consecutive sampling rounds,
each transect was moved one meter away from that sampled during the previous month, such
that the same plants were not sampled on multiple rounds. To better quantify the number of
interactions between herbivores and parasitoids (i.e. to make webs more representative of the
diverse interactions occurring at a site), extra plants were sampled in sites where the total
number of herbivores collected was less than fifty. These samples were taken as close to the
transect as possible, and were used to increase the sample size of herbivores and parasitoids
that emerged from them.
Plant biomass estimation
To estimate the plant biomass sampled, we counted the number of leaves from each
plant species that were beaten on each transect, and then multiplied this number by the
average leaf mass per species. To calculate an average leaf mass (dry weight) per species, we
weighed between 30-60 dried leaves of each plant species (depending on how variable they
were in size). For 14 out of 99 species sampled, we estimated their weights based on the leaf
weights of other species of similar leaf size (13 of them within the same genus), because of
their scarce presence at the locations sampled. To obtain dry weight of leaves, foliage was
dried in a drying oven at 60 C° for two weeks.
Morphological identification of herbivores
Lepidoptera specimens were identified at least to genus level, according to current
taxonomic classification. The only exception to this was the family Psychidae (Lepidoptera),
for which only two species could be identified and the rest (6 specimens) were lumped into a
1
family-level morphospecies which we excluded from analyses to be consistent with other
identifications (which were at least to the genus level), though their inclusion would not have
qualitatively affected the results.
Molecular identification of parasitoids
We identified parasitoids morphologically after their emergence. However, for male
parasitoids that could not be identified to species level using morphology, we used molecular
techniques. For molecular identification, we sequenced a region of the mitochondrial
cytochrome C oxidase subunit I (COI), used in previous studies for parasitoid identification
(Kaartinen et al. 2010), of unidentified specimens and representative specimens of each
species within those families. DNA was extracted using a prepGEM™ Insect kit (Zygem,
USA). A portion of the COI gene was amplified using primer pair HCO2198 and LCO1490
(Folmer et al. 1994) using the KAPA Blood PCR Kit (Kapa Biosystems, USA) following, in
both cases, the manufacturer’s protocol. PCR products, of approximately 658 bp, were
purified and then Sanger sequenced by Macrogen Inc (Seoul, Korea).
We then related the unidentified specimen sequences to those of specimens that had
been identified morphologically. Specimens with sequences that had a pairwise similarity >
96% were considered to be the same species, as this captured most of the species defined
without molecular means (Smith et al. 2013).
Phylogenies
An ultrametric plant phylogeny was extracted from the Phylomatic megatree for
plants (R20120829), using the Phylomatic software (Webb & Donoghue 2005). Branch
lengths were assigned using the bladj function in Phylocom (Webb, Ackerly & Kembel 2008)
(Fig. S2a).
2
An herbivore phylogenetic tree (Fig. S2b) was constructed using one nuclear marker
(Wgl) and one mitochondrial marker (COI) sequence, both obtained from GenBank (Benson
et al. 2005). The Wgl marker sequence was used at the family level (i.e. the same Wgl
sequence for all the genera within the same family) to create a backbone phylogeny at the
family level, and the COI marker at the genus/species level (i.e. for each species or genus a
different COI sequence) (Table S1). We could not use Wgl for every genus/species because
they were not available for all our genera/species, nor were other markers. We aligned the
Wgl and COI sequences separately using MUSCLE (Edgar 2004) and then concatenated
them in MEGA6 (Tamura et al. 2013), resulting in a concatenated two-gene sequence (Wgl +
COI) for each herbivore species. We included Pogonomyrmex subdentatus (Hymenoptera:
Formicidae) as outgroup. We used BEAST v 1.8.0 (Drummond et al. 2006, Drummond &
Rambaut 2007) to infer phylogenies in a Bayesian ultrametric approach. The tree prior was
set using Yule speciation model. The searches used a lognormal uncorrelated relaxed
molecular clock, and were run for 10000000 generations, sampling parameters every 1000
trees. A maximum credibility tree was obtained using Tree Annotator v 1.8.0 (available as
part of the BEAST package). A burn-in of the initial 1000 trees was applied and the final tree
was reconstructed from the remaining trees.
Herbivore species for which no sequences were available, even at the genus level,
were not included in the herbivore phylogeny or considered in the analyses. From a total of
59 herbivore genera collected and taxonomically identified, 37 were included in the analyses
(a total of 39 genera/species), with 12 out of 14 families represented in the analyses (5322
herbivores were used in the analyses out of 5744 collected).
To construct the parasitoid phylogeny (Fig S2c), we used ribosomal marker (28s)
sequences obtained from GenBank (Benson et al. 2005) and mitochondrial marker (COI)
sequences obtained from field samples (see Appendix S1: Molecular identification of
3
parasitoids) or, for those species that we did not sequence, COI sequences available in
GenBank (Table S1). We used the same phylogeny construction methods as explained for
herbivores, but this time using the 28s ribosomal sequences at the genus level and the COI
sequences at the species level (Table S1). From 719 parasitoids reared, 535 could be
accurately placed on the phylogeny and were therefore used in the analyses, representing 36
out of 60 species and morpho-species collected in the field (14 out of 26 genera and 4 out of
4 families were represented). Finally, distance matrices for plants, herbivores and parasitoids
were derived from the phylogenies using the cophenetic function in the ape R package
(Paradis et al. 2004).
Phylogenetic diversity metrics
To determine the phylogenetic community composition of plants, herbivores and
parasitoids, we selected two metrics that merge species phylogenies with different aspects of
community composition: phylogenetic species variability (PSV) and phylogenetic species
evenness (PSE) (Helmus et al. 2007). These metrics assume that there is an unspecified trait
shared by all the species in the phylogeny, which evolves neutrally at a fixed rate.
Phylogenetic species variability (PSV) quantifies the variance of this hypothetical trait by
combining phylogeny and species variability with community information. The higher the
relatedness among species in a community, the lower the variance of this hypothetical trait,
and PSV decreases towards zero. PSV equals 1 when all species in a community evolved
independently (i.e. they are equally distant) from a common ancestor, a pattern known as a
‘star’ phylogeny (Helmus et al. 2007). This metric is particularly useful for comparing
between habitat types because it is unbiased by differences in species richness (Helmus et al.
2007a, Helmus et al. 2007b).
4
Phylogenetic species evenness (PSE) incorporates species abundances into PSV and is
therefore a measure of both phylogenetic and species evenness. If all species have the same
abundance, PSE equals PSV; if species were to evolve in the form of a ‘star’ phylogeny, PSE
represents the evenness in species abundances, with PSE reaching its maximum value of 1
when all species have the same abundances (Helmus et al. 2007).
In order to avoid biased in PSV and PSE due to differences in sampling effort
between sites, we used Monte-Carlo rarefaction for calculating PSV and PSE of each trophic
level. To accomplish this, we used the phyloRarefy function (Bennet 2013) in R.
ParaFit and ParaFitLink2 tests
The null hypothesis of the ParaFit test is that consumers use resources randomly with
respect to the phylogenetic tree of the resources, while the alternative hypothesis is that
consumers and their resources occupy corresponding positions in their phylogenetic trees. To
test this, the ParaFit test maps the principal components of the consumer and resource
phylogenies onto adjacent sides of the presence/absence interaction matrix, to generate a
‘fourth corner’ matrix (Legendre, Galzin & Harmelin-Viven 1997). A global statistic is then
derived from the fourth corner matrix by using the sum of squares of the elements of the
matrix, and its significance is tested by performing permutations of the resources associated
with each consumer and creating a distribution of the statistic under permutation.
Subsequently, the ParaFitLink2 test assesses the null hypothesis that each individual
trophic interaction might have arisen by chance with respect to the phylogenetic structure of
the interacting groups (Legendre, Desdevises & Bazin 2002). Those interactions (pairwise
consumer-resource associations) for which the null hypothesis is rejected are considered to
have a signal of coevolution (Legendre, Desdevises & Bazin 2002).
5
References
Bennet, J.D. Phylogenetic rarefaction.
https://github.com/DomBennett/EcoDataTools/wiki/Phylogenetic-Rarefacation
Benson, D.A., Karsch-Mizrachi, I., Lipman, D.J., Ostell, J. & Wheeler, D.L. (2005)
GenBank. Nucleic Acids Research, 33, D34-D38.
Drummond, A.J., Ho, S.Y.W., Phillips, M.J. & Rambaut, A. (2006) Relaxed phylogenetics
and dating with confidence. PLoS Biology, 4, e88.
Drummond, A.J. & Rambaut, A. (2007) BEAST: Bayesian evolutionary analysis by
sampling trees. BMC Evolutionary Biology, 7, 214.
Edgar, R.C. (2004) MUSCLE: multiple sequence alignment with high accuracy and high
throughput. Nucleic Acids Research, 32, 1792–1797.
Folmer, O., Black, M., Hoeh, W., Lutz, R. & Vrijenhoek, R. (1994) DNA primers for
amplification of mitochondrial cytochrome c oxidase subunit I from diverse metazoan
invertebrates. Molecular Marine Biology and Biotechnology, 3, 294-299.
Helmus, M.R., Bland, T.J., Williams, C.K. & Ives, A.R. (2007a) Phylogenetic measures of
biodiversity. The American Naturalist, 169, E68-E83.
Helmus, M.R., Savage, K., Diebel, M.W., Maxted, J.T. & Ives, A.I. (2007b) Separating the
determinants of phylogenetic community structure. Ecology Letters, 10, 917–925.
Kaartinen, R., Stone, G.N., Hearn, J., Lohse, K. & Roslin, T. (2010) Revealing secret
liaisons: DNA barcoding changes our understanding of food webs. Ecological
Entomology, 35, 623–638.
Kembel, S.W., Cowan, P.D., Helmus, M.R., Cornwell, W.K., Morlon, H., Ackerly, D.D.,
Blomberg, S.P. & Webb, C.O. (2010) Picante: R tools for integrating phylogenies and
ecology. Bioinformatics, 26, 1463-1464.
6
Legendre, P., Galzin, R. & Harmelin-Viven, M.L. (1997) Relating behavior to habitat:
Solutions to the fourth-corner problem. Ecology, 78, 547-562.
Paradis, E., Claude, J. & Strimmer, K. (2004) APE: analyses of phylogenetics and evolution
in R language. Bioinformatics, 20, 289-290.
Smith, M.A., Fernández-Triana, J.L., Eveleigh, E., Gómez, J., Guclu, C., Hallwachs, W.,
Hebert, P.D.N., Hrcek, J., Huber, J.T., Janzen, D., Mason, P.G., Miller, S., Quicke,
D.L.J., Rodriguez, J.J., Rougerie, R., Shaw, M.R., Várkonyi, G., Ward, D.F.,
Whitfield, J.B. & Zaldívar-Riverón, A. (2013) DNA barcoding and the taxonomy of
Microgastrinae wasps (Hymenoptera, Braconidae): impacts after 8 years and nearly
20.000 sequences. Molecular Ecology, 13, 168-176.
Tamura, K., Stecher, G., Peterson, D., Filipski, A. & Kumar, S. (2013) MEGA6: Molecular
evolutionary genetics analysis version 6.0. Molecular Biology and Evolution, 30,
2725-2729.
Webb, C.O., Ackerly, D.D. & Kembel, S.W. (2008) Phylocom: software for the analysis of
phylogenetic community structure and trait evolution. Bioinformatics, 24, 2098-2100.
Webb, C.O. & Donoghue, M.J. (2005) Phylomatic: tree assembly for applied phylogenetics.
Molecular Ecology Notes, 5, 181-183.
7
APPENDIX S2: Species richness and abundance across a habitat edge gradient
We used GLMMs with plant richness, plant biomass, herbivore richness, herbivore
abundance, parasitoid richness and parasitism rates as response variables and forest type,
location (edge vs. interior) and their interaction as predictors. We also incorporated sampling
plot nested within site as random factors to account for the non-independence of samples
within a site. For the species richness models, we included abundance of the trophic level (or
biomass for plants) as covariates, to control for differences in the sample size. For testing
herbivore abundance, we also included plant biomass as a covariate (first in the model, before
all the other fixed terms), and to test abundance of parasitoids we used parasitism rates as the
response variable to weight the number of parasitoids by the number of herbivores collected.
For all the species richness models we used a Poisson error distribution, for parasitism rates
we used binomial errors, and for plant biomass we used a Gaussian error distribution. For the
herbivore abundance model we used a negative binomial distribution because the
equidispersion assumption of the Poisson model was not achieved (Zuur 2009). We checked
for overdispersion in all Poisson and binomial models, and to fulfill the homoscedasticity and
normality assumptions of the Gaussian model, we log transformed plant biomass.
We found that plant species richness in native forest interiors was significantly lower
than in native edges (Z = 2.03, P = 0.042), but higher than in plantation forest interiors (Z = 4.48, P < 0.001) (Fig. S3, Table S2). Despite these differences in species richness across
habitats, plant biomass did not change across forest types (Z = 1.87, P = 0.083), and location
(edge vs. interior) was not even retained in the best-fitting model. In contrast, no differences
were observed for herbivore or parasitoid species richness between forest types (Z = -1.012,
P = 0.311, and Z = 0.992, P = 0.321 respectively), nor was location (edge vs. interior)
retained in the best-fitting models for herbivore and parasitoid richness (Fig. S3, Table S2).
8
The abundance of herbivores tended to increase from the native interior across the
edge to the plantation interior (Fig. S3, Table S2). Herbivore abundance was lower in native
forest interior compared with plantation forest edge (interaction term: Z = -3.76, P <0.001),
and plantation interior (Z = 4.50, P < 0.001) and native edge, although in this case there was
no significant difference (Z = 1.79, P = 0.073). Finally, we found no differences in parasitism
rates across edge vs. interior locations (Z = 1.50, P = 0.134), nor was forest type retained in
the best-fitting model (Fig. S3, Table S2). However, parasitism rates by native parasitoids
were higher in plantation than native forests (Z = 2.49, P = 0.013) (Table S2).
References
Zuur, A.F., Ieno, E.N., Wlaker, N.J., Saveliev, A.A., Smith, G. (2009) Mixed Effects Models
and Extensions in Ecology with R. Springer, New York.
9
APPENDIX S3: Phylogenetic diversity of native species
Phylogenetic diversity of native plants
To determine if differences in phylogenetic diversity in the plant communities across
habitat types were due to the presence of introduced, non-native species, we removed nonnative species from the dataset and re-calculated the phylogenetic diversity metrics (PSV,
PSE). Species were classified as non-native if they were introduced into New Zealand by
humans, deliberately or accidentally. We used GLMMs (with a Gaussian error distribution) in
order to determine whether there were differences across habitats in the phylogenetic
diversity of plant communities, considering only native plant species. We used forest type,
location (edge vs. interior), and their interaction as predictor variables, and sampling plot
nested within site as a random factor. We tested for normality, homoscedasticity of variances
and for outliers, and one of our sampling plots exhibited strong leverage for both plant PSV
and PSE. Therefore, we removed it from these analyses, in order to avoid spurious trends,
even though the results did not change qualitatively. Finally, we used the same model
selection procedure as explained in the Methods section (main text).
The best-fitting GLMM model for native plant PSV was the full model. PSV of native
plants was higher in native interior forest than plantation edge (interaction term: t = -3.58, P =
0.003), with no significant differences between interior and edge of native forest (t = 2.09, P
= 0.056) or between native interior and interior plantation (t = 1.500, P = 0.166). Despite the
differences in PSV of native plants between native interior and plantation edge, we found no
differences in PSE of native plants across forest types (t = -0.08, P = 0.140) nor was location
(edge vs. interior) retained in the best fitting model (Fig. S4, Table S3).
Phylogenetic diversity of native parasitoids
10
To determine whether there were differences in phylogenetic diversity of parasitoids
when only considering native species, we used the same procedure/analyses as for native
plants. Given that some of our parasitoids were only identified to morphospecies level, we
only conducted this analysis for specimens formally identified to species by Linnaean
classification, and specimens belonging to a genus for which no non-native species have been
registered in New Zealand (Aleiodes, Campoletis, Campoplex, Carria, Casinaria, Choeras,
Ophion). Morphospecies that belonged to genera containing both native and non-native
species were excluded from the analyses, because we could not be certain of their origin. Six
sampling plots (out of the 32) presented only one native parasitoid species and since PSV and
PSE cannot be calculated for single species communities, these plots were not included in the
analyses. For the parasitoid PSE model, we included herbivore abundance as a covariate
before the fixed terms, in order to account for potential variability in parasitoid abundance
due to herbivore abundance.
Phylogenetic species variability (PSV) of native parasitoids was lower in interior
forests compared to edges (t = 3.50, P = 0.002) (Fig. S4, Table S3). Similarly, parasitoid
phylogenetic species evenness was higher in edges than interiors habitats (t = 3.51, P =
0.002).
11
Table S1: GenBank a) herbivore and b) parasitoid sequence accession numbers. For
herbivores, one nuclear marker (Wgl) at the family level and one mitochondrial marker (COI)
sequence at the genus/species level were used. Pogonomyrmex subdentatus (Hymenoptera:
Formicidae) was used as outgroup in the construction of the herbivore phylogeny. For
constructing the parasitoid phylogeny, we used ribosomal marker (28s) sequences at the
genus level and mitochondrial marker (COI) sequences at the species level.
a) HERBIVORES (LEPIDOPTERA)
family
Carposinidae
Carposinidae
Gelechiidae
Oecophoridae
Oecophoridae
Oecophoridae
Oecophoridae
Oecophoridae
Oecophoridae
Geometridae
Geometridae
Geometridae
Geometridae
Geometridae
Geometridae
Geometridae
Geometridae
Geometridae
Geometridae
Geometridae
Gracillariidae
Erebidae
Noctuidae
Crambidae
Crambidae
Tineidae
Tortricidae
Tortricidae
Tortricidae
Tortricidae
Tortricidae
Tortricidae
Tortricidae
Tortricidae
Tortricidae
Tortricidae
Tortricidae
genus
Heterocrossa
Paramorpha
Thiotricha
Eutorna
Gymnobathra
Nymphostola
Phaeosaces
Proteodes
Stathmopoda
Cleora
Declana
Ischalis
Pseudocoremia
Austrocidaria
Chloroclystis
Helastia
Hydriomena
Pasiphila
Poecilasthena
Tatosoma
Caloptilia
Rhapsa
Chrysodeixis
Musotima
Deana
Erechthias
Holocola
Strepsicrates
Cnephasia
Ctenopseustis
Dipterina
Epichorista
Epiphyas
Leucotenes
Planotortrix
Planotortrix
Planotortrix
species
sp.
sp.
sp.
phaulocosma
sp.
galactina
sp.
sp.
sp.
sp.
sp.
sp.
sp.
sp.
sp.
sp.
sp.
sandycias
sp.
sp.
sp.
sp.
eriosoma
nitidalis
hybreasalis
sp.
sp.
sp.
sp.
sp.
sp.
sp.
postvittana
coprosmae
excessana
notophaea
octo
GenBank accessions
(Wgl)
GU829699
GU829699
GU829604
JF818596
JF818596
JF818596
JF818596
JF818596
JF818596
GU593337
GU593337
GU593337
GU593337
GU593337
GU593337
GU593337
GU593337
GU593337
GU593337
GU593337
GU829617
GU829660
JN674977
JF497070
JF497070
GU829657
HQ541597
HQ541597
HQ541597
HQ541597
HQ541597
HQ541597
HQ541597
HQ541597
HQ541597
HQ541597
HQ541597
GenBank accessions
(COI)
GU929815
KF390278
JF818795
KF392848
JF818751
JF818771
JF818778
JF818782
JF818792
JF784734
JF784716
JF784723
KF394835
KF388840
KF395068
JF784719
EU443350
JF784725
JF784720
JF784721
KF394999
KF392511
KF394354
GU929784
JF497029
KF396896
KF399527
KF399800
JF859655
FJ225574
KF404521
KF399534
GU827570
AF016473
AF016475
AF016477
AF016478
12
Plutellidae
Yponomeutidae
Formicidae
(outgroup)
Orthenches
Kessleria
sp.
sp.
GU829637
GU829672
KF405319
HQ968333
Pogonomyrmex
subdentatus
JQ742895
JQ742639
b) PARASITOIDS
family
Tachinidae
Eulophidae
Braconidae
Braconidae
Braconidae
Braconidae
Braconidae
Braconidae
Braconidae
Braconidae
Braconidae
Braconidae
Braconidae
Braconidae
Braconidae
Braconidae
Braconidae
Campopleginae
Campopleginae
Campopleginae
Campopleginae
Ichneumonidae
Ichneumonidae
Ichneumonidae
Ichneumonidae
Ichneumonidae
Ichneumonidae
Ichneumonidae
Ichneumonidae
Ichneumonidae
Ichneumonidae
Ichneumonidae
Ichneumonidae
Ichneumonidae
Ichneumonidae
Ichneumonidae
Ichneumonidae
genus
Trigonospila
Sympiesis
Aleiodes
Aleiodes
Choeras
Cotesia
Dolichogenidae
Dolichogenidae
Glyptapanteles
Glyptapanteles
Glyptapanteles
Glyptapanteles
Glyptapanteles
Glyptapanteles
Glyptapanteles
Meteorus
Meteorus
Diadegma
Diadegma
Diadegma
Diadegma
Campoletis
Campoletis
Campoletis
Campoletis
Campoplex
Campoplex
Campoplex
Campoplex
Campoplex
Campoplex
Carria
Carria
Carria
Carria
Casinaria
Ophion
species
sp.
sp.
declanae
sp.
sp.
sp.
darklegs sp. 4
lightly punct
dark
sp. 2
sp. 3
sp. 4
sp. 5
sp. 6
sp. 9
cinctellus
pulchricornis
brown
gold setae
sp. 1
sp. 3
sp. 1
sp. 4
sp. 5
sp. 9
sp. 1
sp. 13
sp. 2
sp. 3
sp. 4
sp. 9
fortipes
petiolate areolet
sp. 2
sp. 3
sp. 3
sp.
GenBank
accessions (28S)
AB466052
FJ812246
JF979752
JF979752
AY044218
DQ538976
AF102743
AF102743
AF102738
AF102738
AF102738
AF102738
AF102738
AF102738
AF102738
HQ263734
HQ263734
EU378397
EU378397
EU378397
EU378397
EU378388
EU378388
EU378388
EU378388
EF374043
EF374043
EF374043
EF374043
EF374043
EF374043
EU378665
EU378665
EU378665
EU378665
EF406252
EU378715
GenBank
accessions (COI)
GU142770
HM574130
KM106895
KM106896
KM107122
KM107110
KM107132
KM107070
KM107101
KM107118
KM107119
KM107094
KM107078
KM107108
KM107089
KM107164
HQ264010
KM107176
KM107045
KM106863
KM106859
KM106882
KM107173
KM107174
KM107181
KM106909
KM106910
KM107149
KM107187
KM107186
KM107190
KM106987
KM106851
KM106852
KM106853
KM106927
KM107171
13
Table S2. Coefficient tables from generalized linear mixed effects models to determine
changes in the species richness and abundance of plants, herbivores and parasitoids across a
habitat edge gradient. These are the results from the best-fitting models, which were
simplified from a maximal model including forest type (native vs. plantation), location (edge
vs. interior) and their interaction as fixed effects. All models included plot nested within site
as random factors. For each species richness model, the respective abundance (biomass for
plants) was incorporated as a covariate to control for potential variation in abundance.
Parasitoid abundance was tested as parasitism rates, to control for differences in the
abundance of herbivores, and for the herbivore abundance model we included plant biomass
as a covariate. We used a Poisson distribution for all the species richness models (Z-values),
Gaussian for log transformed plant biomass (t-value), negative binomial for herbivore
abundance (Z-values) and binomial for parasitism rates (Z-value). Forest P = plantation
forest; Location E = edge location. Bold values indicate significant results (α = 0.05).
Response variable
Plant species richness
Plant biomass
Herbivore species
richness
Herbivore abundance
Parasitoid species
richness
Parasitism rates
Native parasitoid species
richness
Parasitism rates (by native
parasitoids)
Predictors
Intercept
Forest P
Location E
Intercept
Forest P
Intercept
Herbivore abundance
Forest P
Intercept
Plant biomass
Forest P
Location E
Forest P*Location E
Intercept
Parasitoid abundance
Forest P
Intercept
Location E
Intercept
Native parasitoid
abundance
Forest P
Intercept
Forest P
Estimate± SE
3.012 ± 0.110
-0.527 ± 0.118
0.169 ± 0.083
3.936 ± 0.117
0.309 ± 0.165
2.557 ± 0.132
10e-4 ± 80e-4
-0.108 ± 0.107
4.788 ± 0.145
30e-4 ± 0.002
0.598 ± 0.133
0.210 ± 0.117
-0.628 ± 0.167
1.618 ± 0.142
0.020 ± 0.006
0.126 ± 0.132
-2.291 ± 0.108
0.140 ± 0.093
0.661 ± 0.177
Z/t-value
27.325
-4.485
2.028
33.612
1.868
19.431
0.239
-1.012
32.990
0.220
4.500
1.790
-3.760
11.400
3.081
0.954
-21.160
1.500
3.730
P-value
< 0.001
< 0.001
0.042
< 0.001
0.083
< 0.001
0.811
0.311
< 0.001
0.826
< 0.001
0.073
< 0.001
< 0.001
0.002
0.340
< 0.001
0.134
< 0.001
0.038 ± 0.013
2.878
0.004
0.100 ± 0.238
-3.586 ± 0.225
0.550 ± 0.221
0.419
-15.933
2.487
0.675
< 0.001
0.013
14
Table S3: Results from GLMMs (with Gaussian distribution) showing differences in
phylogenetic diversity of native plants and parasitoids across forest types (native vs.
plantation) and location (edge vs. interior). Results are from the best-fitting model (with
lowest AIC), after model selection. Herbivore abundance was entered as a covariate in the
parasitoids PSE model. PSV = phylogenetic species variability, PSE = phylogenetic species
evenness. Bold values indicate significant results (α = 0.05). Forest P = plantation forest.
Phylogenetic diversity
metric
PSV of native plants
PSE of native plants
PSV of native parasitoids
PSE of native parasitoids
Fixed effects
Estimate ± SE
t-value
P-value
Intercept
Forest P
Location E
Forest P*Location E
Intercept
Forest P
Intercept
Location E
Intercept
Herbivore abundance
Location E
0.682 ± 0.022
0.045 ± 0.030
0.035 ± 0.017
-0.088 ± 0.025
0.585 ± 0.038
-0.085 ± 0.054
0.412 ± 0.038
0.196 ± 0.056
0.345 ± 0.009
30e-4 ± 40e-4
0.199 ± 0.006
31.518
1.500
2.092
-3.584
15.426
-1.569
10.853
3.503
3.995
0.851
3.515
<0.001
0.166
0.056
0.003
<0.001
0.140
<0.001
0.002
<0.001
0.404
0.002
15
Table S4: Coefficient tables from generalized linear mixed effects models to determine
changes in community phylogenetic diversity of different trophic levels across habitats (with
a Gaussian error distribution). These are the results from the best-fitting models, which were
simplified from a maximal model including forest type (native vs. plantation), location (edge
vs. interior) and their interaction as fixed effects. All models included plot nested within site
as random factors. The herbivore and parasitoid PSE models included plant biomass and
herbivore abundance respectively as a covariate, to control for potential variation in resource
abundance. Forest P = plantation forest; Location E = edge location. Bold values indicate
significant results (α = 0.05).
Trophic
level
Phylogenetic
diversity
metric
PSV
Plant
PSE
PSV
Herbivore
PSE
PVS
Parasitoid
PSE
Fixed effects
Estimate ± SE
t-value
P-value
Intercept
Forest P
Location E
Forest P*Location E
Intercept
Forest P
Location E
Intercept
Location E
Intercept
Plant biomass
Forest P
Location E
Forest P*Location E
Intercept
Location E
Intercept
Host abundance
Location E
0.653 ± 0.025
0.059 ± 0.031
0.051 ± 0.016
-0.100 ± 0.022
0.533 ± 0.035
-0.230 ± 0.034
0.085 ± 0.034
0.473 ± 0.009
-0.009 ± 0.012
0.375 ± 0.026
-10e-4 ± 30e-4
-0.066 ± 0.025
-0.025 ± 0.020
0.085 ± 0.029
0.583 ± 0.022
0.036 ± 0.031
0.542 ± 0.005
-60e-5 ± 20e-4
0.003 ± 0.003
26.556
1.911
3.308
-4.544
15.091
-6.768
2.490
55.056
-0.767
14.197
-0.460
-2.648
-1.197
2.872
26.949
1.194
11.161
-0.270
1.012
<0.001
0.088
0.005
<0.001
<0.001
<0.001
0.021
<0.001
0.449
<0.001
0.650
0.018
0.252
0.012
<0.001
0.242
<0.001
0.789
0.322
16
Table S5: Results of GLMMs with binomial error distribution testing whether a) the
proportion of total native interactions (i.e. parasitism events) with coevolutionary signal and
b) the proportion of unique native herbivore-parasitoid links with coevolutionary signal
changed across forest types. Both models included host abundance as a covariate and plot
nested within site as a random factor. Bold values indicate significant results (α = 0.05).
A)
B)
Response variable
Proportion of native
parasitism events with
coevolutionary signal
Proportion of unique
native herbivoreparasitoid links with
coevolutionary signal
Fixed effects
Intercept
Host abundance
Forest P
Intercept
Host abundance
Forest P
Estimate ± SE
0.886 ± 0.677
-0.003 ± 0.003
1.226 ± 0.379
1.114 ± 0.597
-0.004 ± 0.003
Z-value
1.310
-0.802
3.233
1.865
-1.177
P
0.190
0.422
0.001
0.062
0.239
0.647 ± 0.426
1.519
0.129
17
Native forest
Edge
Native forest
Plantation forest
Edge
NI
10 m
10 m
10 m
10 m
NE
A
B
500 m
500 m
Pine forest
PE
C
D
PI
500 m
500 m
Fig. S1: Schematic diagram of each sampling site. Each site (of eight sites in total) comprised
a native forest adjacent to a pine forest. The dotted line indicates the centre of the edge zone,
defined as the last row of pine trees in the plantation forest. In each forest type there were two
locations (edge vs. interior), represented by black and white circles respectively. Each forest
type within a site was treated as a plot, and each subplot was a specific location (edge vs.
interior) within the plot. Therefore, at each site four subplots were sampled: NI = native
interior forest, NE = native edge, PE = plantation edge, and PI = plantation interior forest. In
total, 32 subplots were sampled across the eight sites, and a quantitative parasitoid-host food
web was constructed for each subplot.
18
Pseudopanax anomalus
Pseudopanax arboreus
Pseudopanax sp.
Schefflera digitata
Pittosporum eugenioides
Pittosporum rigidum
Pittosporum sp.
Griselinia littoralis
Griselinia lucida
Pennantia corymbosa
Leycesteria formosa *
Quintinia serrata
Brachyglottis repanda
Helichrysum lanceolatum
Olearia avicenniifolia
Olearia rani
Senecio sp. *
Carpodetus serratus
Nestegis montana
Digitalis purpurea *
Hebe sp.
Coprosma areolata
Coprosma colensoi
Coprosma foetidissima
Coprosma grandifolia
Coprosma linariifolia
Coprosma lucida
Coprosma microcarpa
Coprosma propinqua
Coprosma rhamnoides
Coprosma robusta
Coprosma rotundifolia
Erica lusitanica *
Gaultheria antipoda
Leptecophylla juniperina
Leucopogon fasciculatus
Myrsine australis
Coriaria arborea
Nothofagus fusca
Nothofagus menziesii
Nothofagus solandri
Rubus cissoides
Rubus fruticosus *
Chamaecytisus palmensis *
Ulex europaeus *
Weinmannia racemosa
Aristotelia serrata
Elaeocarpus dentatus
Elaeocarpus hookerianus
Passiflora tetrandra
Melicytus ramiflorus
Kunzea ericoides
Leptospermum scoparium
Metrosideros sp.
Neomyrtus pedunculata
Lophomyrtus obcordata
Lophomyrtus bullata
Fuchsia excorticata
Alectryon excelsus
Berberis sp *
Cortaderia richardii
Dianella nigra
Phormium tenax
Rhipogonum scandens
Beilschmiedia tawa
Hedycarya arborea
Pseudowintera axillaris
Pseudowintera colorata
Pinus radiata *
Pinus sylvestris *
Pseudotsuga menziesii *
Dacrydium cupressinum
Podocarpus hallii
Prumnopitys ferruginea
Prumnopitys taxifolia
Asplenium oblongifolium
Asplenium polyodon
Blechnum discolor
Blechnum minus
Histiopteris incisa
Pteridium aquilinum
Polystichum vestitum
Cyathea colensoi
Cyathea dealbata
Cyathea medullaris
Cyathea smithii
Dicksonia sp
Leptopteris hymenophylloides
Marattia salicina
a)
Araliaceae
Pittosporaceae
Griseliniaceae
Pennantiaceae
Caprifoliaceae
Paracryphiaceae
Asteraceae
Rousseaceae
Oleaceae
Plantaginaceae
Rubiaceae
Ericaceae
Primulaceae
Coriariaceae
Nothofagaceae
Rosaceae
Fabaceae
Cunoniaceae
Elaeocarpaceae
Passifloraceae
Violaceae
Myrtaceae
Onagraceae
Sapindaceae
Berberidaceae
Poaceae
Xanthorrhoeaceae
Rhipogonaceae
Lauraceae
Monimiaceae
Winteraceae
Pinaceae
Podocarpaceae
Aspleniaceae
Blechnaceae
Dennstaedtiaceae
Dryopteridaceae
Cyatheaceae
Dicksoniaceae
Osmundaceae
Marattiaceae
50.0
19
b)
Caloptilia sp.
Gracillariidae
Orthenches sp.
Plutellidae
Ctenopseustis sp.
Leucotenes coprosmae
Planotortrix excessana
Planotortrix octo
Planotortrix notophaea
Epiphyas postvittana *
Tortricidae
Dipterina sp.
Epichorista sp.
Holocola sp.
Strepsicrates sp.
Cnephasia sp.
Tatosoma sp.
Austrocidaria sp.
Chloroclystis sp.
Pasiphila sandycias
Poecilasthena sp.
Hydriomena sp.
Geometridae
Helastia sp.
Pseudocoremia sp.
Cleora sp.
Ischalis sp.
Declana sp.
Deana hybreasalis
Crambidae
Musotima nitidalis
Heterocrossa sp.
Carposinidae
Paramorpha sp.
Chrysodeixis eriosoma
Noctuidae
Rhapsa sp.
Erebidae
Gelechiidae
Thiotricha sp.
Gymnobathra sp.
Phaeosaces sp.
Stathmopoda sp.
Eutorna phaulocosma *
Oecophoridae
Nymphostola galactina
Proteodes sp.
Erechthias sp.
Yponomeutidae
Tineidae
Pogonomyrmex subdentatus
Formicidae (outgroup)
Kessleria sp.
0.08
20
c)
Choeras sp.
Glytapanteles dark *
Glyptapanteles sp. 5 *
Glyptapanteles sp. 3 *
Glyptapanteles sp. 9 *
Glyptapanteles sp. 2 *
Glyptapanteles sp. 4 *
Glyptapanteles sp. 6 *
Braconidae
Cotesia sp. 1 *
Dolichogenidea lightly punct *
Dolichogenidea darklegs sp. 4 *
Meteorus cinctellus *
Meteorus pulchricornis *
Aleiodes declanae
Aleiodes sp.
Sympiesis sp. *
Eulophidae
Diadegma sp. 1 *
Diadegma sp. 3 *
Diadegma gold setae *
Campoletis sp. 9
Campoletis sp. 1
Campoletis sp. 5
Campoplex sp. 4
Campoplex sp. 1
Campoplex sp. 9
Campoplex sp. 13
Ichneumonidae
Campoplex sp. 3
Campoplex sp. 2
Campoletis sp. 4
Casinaria sp. 3
Carria petiolate areolet
Carria sp. 2
Carria sp. 3
Carria fortipes
Ophion sp.
Trigonospila_sp. *
Tachinidae
0.05
Fig. S2: a) Ultrametric plant phylogeny extracted from the Phylomatic tree for plants
(R20120829), using the Phylomatic software. b) Ultrametric herbivore phylogeny of the
species found in the study area, with phylogenetic relationships inferred using DNA
sequences obtained from GenBank, including one nuclear marker (Wgl) and one
mitochondrial marker (COI). Because all herbivore species were from the same order
(Lepidoptera) Pogonomyrmex subdentatus (Hymenoptera: Formicidae) was included as
outgroup. c) Ultrametric parasitoid phylogeny, with phylogenetic relationships based on one
ribosomal marker (28s RNA) and one mitochondrial marker (COI). White bars represent
families, and non-native species are indicated with *. Voucher specimens of plants have been
deposited at the University of Canterbury Herbarium (CANU), Ichneumonidae and
Tachinidae parasitoids at the New Zealand Arthropod Collection (NZAC) in Auckland, and
21
Braconidae and Eulophinae parasitoids at the Te Papa Museum Entomology Collection in
Wellington, NZ.
22
15
20
10
30
10
20
0
0
5
10
0
NE
PE
PI
NI
NE
PE
PI
NI
NE
PE
PI
NI
NE
PE
PI
NE
PE
PI
NI
NE
PE
PI
20
200
0
0
10
100
80
40
0
NI
30
300
NI
120
Species richness
Abundance
Parasitoids
Herbivores
Plants
Fig. S3: Mean and SE of species richness and abundance of plants, herbivores and parasitoids
(including native and non-native species) across a habitat edge gradient from native interior
(NI) forest, across native forest side of the edge (NE), plantation forest side of the edge (PE)
and plantation interior forest (PI). Plant abundance represents biomass sampled (kg), while
abundance of herbivores is the number of individuals collected, and of parasitoids, the
number that emerged from herbivores.
23
0.5
0.0
0.5
0.0
PE
PI
NI
NE
PE
PI
PSE
NE
PE
PI
NI
NE PE
PI
0.0
0.5
0.0
PSE
NI
1.0
NE
1.0
NI
0.5
PSV
1.0
Parasitoids
1.0
Plants
Fig. S4: Phylogenetic species variability (PSV) and phylogenetic species evenness (PSE) of
native plant and parasitoid species across a habitat edge gradient from native interior (NI)
forest, across native forest side of the edge (NE), plantation forest side of the edge (PE) and
plantation interior forest (PI).
24
Fig. S5: Plant-herbivore food web. The top and bottom rectangles represent herbivore and plant species respectively, with different colours
indicating different families. Links between both trophic levels indicate an herbivory event, coloured according to herbivore family. Plant
phylogeny was constructed using the Phylomatic software, and herbivore phylogeny was built using one nuclear marker (Wgl) and one
mitochondrial marker (COI).
25
26