Supplementary Methods
Mixed effects models testing species’ associations with native species richness and P
Using mixed effects logistic regressions, we modelled the probability of occurrence
for each species in relation to native species richness and sqrt-transformed P.
These two explanatory variables were mildly correlated for some species (as indicated
by appropriate multi-level analyses), so we modelled them separately for all species.
The response variables were binary, but instead of using raw presence/absence
responses, we identified the quadrats where a species made up ≥5% of the relative
abundance and considered these “occurrences” for the species. This removed
instances where the species was present in very low numbers (mainly singletons), and
therefore captured each species preferred conditions more clearly. Some species were
too rare to model, so we placed a threshold of at least 25 “occurrences” across the
dataset, leaving 59 testable species including 46 native species and 13 alien species.
For each species, only data from remnants where the species was recorded were
included in each model, i.e. we assumed that species could be absent from remnants
for reasons unrelated to measured contemporary abiotic factors. All models included
remnant and site as nested random effects and binomial errors were employed with a
logit link function. For each model, the coefficient for richness or sqrt(P) was
recorded, as was the significance of the coefficient based on Wald tests.
Null modelling details
For count data, the ‘quasiswapcount’ algorithm (Oksanen et al. 2014) was applied,
which constrains the number of individuals per quadrat (row totals in the community
data matrix) to observed values and also constrains the absolute abundance of each
species in each remnant (column totals in the community data matrix). This
constrained null model also maintains the observed number of zeros (absences) in
each randomised community data matrix. By retaining species’ overall abundances,
rare species remain rare and common species remain common. Maintaining the
number of absences ensures that individuals from each species are not unrealistically
“spread” over many communities to achieve the other constraints. For presenceabsence data we used the swap algorithm (Miklós & Podani 2004) that also constrains
row and column totals in each community matrix. Because the data are binary, the
constrained row totals mean that observed quadrat richness values are maintained and
the constrained column totals maintain each species’ frequency of occurrence.
Many neighbour species were rare in the dataset and C-scores calculated from
randomised communities included many zeros when these species were included. We
therefore limited our calculation of C-score effect sizes to neighbour species that were
present in at least 10% of the 90 quadrats in a given remnant. In addition, because the
null models randomized species occurrences across entire remnants, they often
“placed” target and neighbor species in sites where they were not recorded in the
observed dataset. In these cases their observed C-scores were zero by default,
resulting in many negative effect sizes of similar magnitude. Therefore, we only
considered effect sizes generated from species pairs where both the target and
neighbor species were present at the site in the observed dataset.
Assessing the importance of absolute versus hierarchy trait variables
We modelled all combinations of absolute and hierarchy variables for each species.
All models also included the site-scale P variable, and its interaction with hierarchy
variables. In models with interactions we ensured that interactions were only ever
included when main terms were also included. Given these various candidate models,
we then assessed the relative importance (RI) of each trait variable by calculating how
many high-ranking models (based on AICc) the variable was included in. Trait
variables that were very important were consistently selected in high-ranking models.
From these RI values we selected the combination of absolute trait distance and trait
hierarchy variables to investigate further for a given target species.
Table S1. Data sources for seed mass measurements. “Measured” indicates seed
masses that were measured in this study, “genus” indicates where the seed mass of a
congener was used and “NA” indicates species for which no reliable seed mass value
could be obtained (these are mostly very rare species in the dataset). The remaining
were sourced from publications as indicated.
Species
Data source
Species
Data source
Actinobole uliginosum
measured
Lolium perenne
measured
Aira cupaniana
measured
Lomandra effusa
NA
Angianthus tomentosus
NA
Lysimachia arvensis
measured
Arctotheca calendula
measured
Medicago minima
measured
Aristida contorta
measured
Medicago polymorpha
measured
Arthropodium curvipes
measured
Menkea sphaerocarpa
NA
Arthropodium dyeri
measured
Mesembryanthemum
crystallinum
measured
Austrostipa elegantissima
measured
Mesembryanthemum nodiflorum
NA
Austrostipa macalpinei
NA
Millotia myosotidifolia
measured
Avena barbata
measured
Monachather paradoxus
measured
Bellida graminea
measured
Monoculus monstrosus
measured
Blennospora drummondii
measured
Moraea flaccida
NA
Borya sphaerocephala
NA
Moraea setifolia
measured
Brachyscome ciliaris
genus
Myriocephalus guerinae
measured
Brachyscome iberidifolia
measured
Neurachne alopecuroidea
NA
Brachyscome perpusilla
measured
Nicotiana rotundifolia
measured
Brassica tournefortii
measured
Omphalolappula concava
measured
Briza maxima
measured
Ophioglossum lusitanicum
NA
Bromus diandrus
measured
Parentucellia latifolia
measured
Bromus madritensis
measured
Parietaria cardiostegia
NA
Brunonia australis
(Moles & Westoby 2004)
Pentameris airoides
measured
Bulbine semibarbata
measured
Petrorhagia dubia
measured
Caesia micrantha
(Moles & Westoby 2004)
Pheladenia deformis
(Arditti & Ghani 2000)
Caladenia denticulata
(Arditti & Ghani 2000)
Phyllangium sulcatum
measured
Caladenia roei
(Arditti & Ghani 2000)
Plantago coronopus
(Moles & Westoby 2004)
Calandrinia corrigioloides
(Moles & Westoby 2004)
Plantago debilis
measured
Calandrinia eremaea
measured
Podolepis canescens
measured
Calandrinia granulifera
measured
Podolepis capillaris
(Moles & Westoby 2004)
Calocephalus multiflorus
NA
Podolepis lessonii
measured
Calotis hispidula
measured
Podotheca angustifolia
(Moles & Westoby 2004)
Species
Data source
Species
Data source
Calotis multicaulis
measured
Podotheca gnaphalioides
measured
Carrichtera annua
(Moles & Westoby 2004)
Pogonolepis muelleriana
measured
Centrolepis aristata
measured
Polycarpon tetraphyllum
NA
Centrolepis drummondiana
NA
Poranthera microphylla
measured
Cephalipterum drummondii
measured
Prasophyllum sp.
(Arditti & Ghani 2000)
Ceratogyne obionoides
measured
Ptilotus declinatus
NA
Chamaescilla versicolor
measured
Ptilotus drummondii
NA
Cheilanthes austrotenuifolia
NA
Ptilotus exaltatus
(Moles & Westoby 2004)
Chthonocephalus pseudevax
measured
Ptilotus gaudichaudii
measured
Cotula bipinnata
NA
Ptilotus polystachyus
(Moles & Westoby 2004)
Crassula closiana
genus
Ptilotus spathulatus
NA
Crassula colorata
measured
Quinetia urvillei
measured
Cyanicula amplexans
(Arditti & Ghani 2000)
Rapistrum rugosum
measured
Cyanicula gemmata
(Arditti & Ghani 2000)
Rhodanthe chlorocephala
measured
Dampiera lavandulacea
(Moles & Westoby 2004)
Rhodanthe citrina
measured
Daucus glochidiatus
measured
Rhodanthe humboldtiana
measured
Dianella revoluta
(Moles & Westoby 2004)
Rhodanthe laevis
measured
Dichopogon capillipes
measured
Rhodanthe manglesii
measured
Drosera erythrorhiza
NA
Rhodanthe polycephala
measured
Drosera glanduligera
NA
Rhodanthe pygmaea
measured
Echium plantagineum
measured
Rhodanthe spicata
measured
Ehrharta longiflora
measured
Romulea rosea
measured
Emex australis
measured
Rostraria pumila
(Moles & Westoby 2004)
Enchylaena tomentosa
(Moles & Westoby 2004)
Rytidosperma caespitosum
(Moles & Westoby 2004)
Erodium aureum
measured
Schoenia cassiniana
measured
Erodium botrys
measured
Schoenus nanus
measured
Erodium cicutarium
measured
Senecio glossanthus
measured
Erodium cygnorum
measured
Silene nocturna
measured
Erymophyllum ramosum
measured
Sonchus oleraceus
measured
Euphorbia drummondii
measured
Stackhousia monogyna
NA
Gilberta tenuifolia
measured
Stenopetalum lineare
measured
Gilruthia osbornei
measured
Thysanotus manglesianus
NA
Gnephosis tenuissima
measured
Thysanotus rectantherus
measured
Gonocarpus nodulosus
measured
Trachymene cyanopetala
measured
Goodenia berardiana
measured
Trachymene ornata
measured
Goodenia krauseana
(genus; Moles & Westoby 2004)
Trachymene pilosa
measured
Goodenia occidentalis
measured
Trifolium glomeratum
measured
Goodenia pusilliflora
measured
Trifolium hirtum
NA
Species
Data source
Species
Data source
Haloragis odontocarpa
measured
Trifolium subterraneum
(Moles & Westoby 2004)
Hedypnois rhagadioloides
measured
Triglochin isingiana
measured
Hordeum leporinum
measured
Urospermum picroides
measured
Hyalosperma demissum
measured
Ursinia anthemoides
measured
Hyalosperma glutinosum
subsp. glutinosum
measured
Velleia cycnopotamica
measured
Hyalosperma glutinosum
subsp. venustum
measured
Velleia rosea
measured
Hydrocotyle pilifera
measured
Vulpia bromoides
measured
Hypochaeris glabra
measured
Vulpia myuros
measured
Isoetopsis graminifolia
measured
Wahlenbergia capensis
measured
Isotropis juncea
NA
Wahlenbergia gracilenta
measured
Lamarckia aurea
measured
Waitzia acuminata
measured
Lawrencella davenportii
measured
Waitzia nitida
measured
Lawrencella rosea
measured
Wurmbea densiflorus
measured
Levenhookia dubia
measured
Wurmbea drummondii
NA
Levenhookia leptantha
NA
Wurmbea sp. Paynes Find
NA
Lobelia gibbosa
(genus; Moles & Westoby 2004)
Zaluzianskya divaricata
measured
Zygophyllum iodocarpum
measured
Table S2. Results from the incidence-based SWAP null-modelling approach
(provided for comparison with Table 1 in the main text). Bolding indicates the trait
variable that had the highest relative importance for a given trait and a given target
species. “Not tested” indicates situations where the trait rank for the target species
was very low or very high, resulting in absolute and hierarchy variables that were
almost identical. In these cases only the hierarchy variables were examined.
Target Species
# Sites /
#
Trait
Remnants
Trait
Rank
Relative Importance
Abs. Distance
Hierarchy
EXPLOITERS
Arctotheca
calendula
(Asteraceae)
Avena barbata
(Poaceae)
Ehrharta
longiflora
(Poaceae)
15/56
41/56
39/56
0.17
39/10
SLA
Max. Height
Seed Mass
0.82
0.20
0.62
0.17
0.29
28/7
SLA
Max. Height
Seed Mass
29/54
54/54
54/54
0.01
Not Tested
Not Tested
0.97
0.99
0.73
19/5
SLA
Max. Height
Seed Mass
52/53
47/53
44/53
Not Tested
0.01
0.11
0.99
0.99
0.84
33/7
SLA
Max. Height
Seed Mass
41/54
17/54
7/54
0.24
0.00
0.37
0.36
0.99
0.63
52/9
SLA
Max. Height
Seed Mass
20/55
25/55
13/55
0.17
0.03
0.66
0.52
0.97
0.33
24/5
SLA
Max. Height
Seed Mass
5/54
28/54
14/54
0.19
0.16
0.31
0.32
0.50
0.69
SLA
Max. Height
Seed Mass
56/56
9/56
18/56
Not Tested
0.00
0.26
0.36
1.00
0.64
SLA
Max. Height
Seed Mass
27/56
32/56
52/56
0.43
1.00
Not Tested
0.38
0.00
COEXISTERS
Aira cupaniana
(Poaceae)
Pentameris
airoides (Poaceae)
Zaluzianskya
divaricata
(Scrophulariaceae)
NATIVES
Calandrinia
eremaea
(Portulacaceae)
Trachymene
cyanopetala
(Araliaceae)
57/10
51/10
0.88
Waitzia acuminata
(Asteraceae)
51/9
SLA
Max. Height
Seed Mass
4/56
45/56
19/56
Not Tested
0.12
0.63
0.92
0.88
0.36
Table S3. The number of quadrat occurrences recorded in 2010 (dry) and 2011 (wet)
for target and neighbour species across the three northern remnants included in the
temporal analysis. A total of 270 quadrats were sampled each year (in the same site
locations within remnants). Target species are indicated in bold with their “type” in
brackets: N = native, C = coexister and E = exploiter. Note: On average, each remnant
received 100 mm less rainfall in 2010 than in 2011.
Native species
2010 2011
Difference
Actinobole uliginosum
27
40
13
Austrostipa elegantissima
93
78
-15
Blennospora drummondii
13
15
2
Brachyscome perpusilla
38
37
-1
Bulbine semibarbata
3
16
13
Calandrinia eremaea (N)
23
141
118
Calandrinia granulifera
1
13
12
Calotis hispidula
19
56
37
Calotis multicaulis
24
41
17
Cephalipterum drummondii
31
35
4
Chthonocephalus pseudevax
0
22
22
Crassula closiana
0
16
16
Crassula colorata
65
208
143
Daucus glochidiatus
15
27
12
Erodium cygnorum
95
145
50
Euphorbia drummondii
19
0
-19
Gilberta tenuifolia
14
9
-5
Gnephosis tenuissima
16
15
-1
Gonocarpus nodulosus
0
13
13
Goodenia berardiana
57
79
22
Goodenia pusilliflora
5
12
7
Hyalosperma glutinosum
65
69
4
Hydrocotyle pilifera
6
34
28
Lawrencella rosea
30
30
0
Phyllangium sulcatum
4
21
17
Plantago debilis
45
49
4
Podolepis canescens
46
38
-8
Podolepis lessonii
20
19
-1
Pogonolepis muelleriana
57
62
5
Ptilotus gaudichaudii
31
45
14
Rhodanthe laevis
8
30
22
Rhodanthe polycephala
31
29
-2
Rhodanthe spicata
48
30
-18
Schoenia cassiniana
4
11
7
Schoenus nanus
0
24
24
Stenopetalum lineare
7
15
8
Trachymene cyanopetala (N)
65
111
46
Trachymene ornata
16
44
28
Velleia cycnopotamica
2
14
12
Velleia rosea
35
33
-2
Wahlenbergia gracilenta
2
18
16
Waitzia acuminate (N)
103
100
-3
Waitzia nitida
126
110
-16
Aira cupaniana (C)
15
37
22
Arctotheca calendula (E)
45
78
33
Avena barbata (E)
34
43
9
Bromus rubens
23
37
14
Echium plantagineum
45
48
3
Ehrharta longiflora (E)
10
26
16
Erodium aureum
5
11
6
Hedypnois rhagadioloides
12
29
17
Hypochaeris glabra
66
74
8
Lolium perenne
9
14
5
Medicago minima
7
10
3
Medicago polymorpha
8
13
5
Mesembryanthemum crystallinum
0
15
15
Monoculus monstrosus
25
39
14
Moraea setifolia
32
43
11
Parentucellia latifolia
11
18
7
Pentameris airoides (C)
98
131
33
Petrorhagia dubia
34
60
26
Silene nocturna
1
13
12
Sonchus oleraceus
10
18
8
Trifolium subterraneum
18
18
0
Urospermum picroides
3
10
7
Vulpia myuros
37
74
37
Zaluzianskya divaricate (C)
2
34
32
Alien species
Figure S1. Plots of significant relationships between seed mass hierarchies and segregation (C-score
effect sizes) for Coexisters: (a) A. cupaniana, (b) P. airoides and (c) Z. divaricata, and Natives: (d) C.
eremaea, (e) T. cyanopetala and (f) W. acuminata. Grey points are mean effect sizes for each neighbour
species and grey bars are +/- 1 SE. Fitted lines were derived from intercept and slope coefficients from
averaged trait hierarchy models. Dashed lines are 95% confidence intervals that capture uncertainty in
both the slope and the intercept estimates. Zero on the X-axis shows the position of the target species in
the seed mass hierarchy.
Figure S2. Ordination plots (non-metric multi-dimensional scaling) illustrating changes in composition
from 2010 (drier growing season) to 2011 (wetter growing season). Each point is a site in a given year and
colors indicate the remnant that each site was in. Arrows point from sites in 2010 to the same site in 2011.
Large points and thick arrows indicate high P sites (those with steep P gradients) and small points and thin
arrows indicate sites typical of low P (natural) conditions. Three dissimilarity metrics were investigated:
(a) Bray-Curtis which incorporates abundance information, (b) Sørensen which is similar to Bray-Curtis
but considers only presence/absence information and (c) Raup-Crick which is also based on
presence/absence, but accounts for richness differences using a null modelling approach (Chase & Myers
2011).
Figure S3. Same plots as shown in Figure 6, but using the incidence based null model to estimate
segregation (instead of the abundance-based null model). Upper panels are coefficient plots from models
assessing changes in segregation between the drier 2010 and wetter 2011 growing seasons, assessed using
data from three northern remnants that were surveyed in both years. Points are averaged coefficient
estimates and bars are corresponding 95% CIs. High P sites were those with average mean phosphorus
levels >5.5 mg g-1, with other sites considered low P sites. Lower panels are associated plots of mean (+/1 SE) segregation values per site in each year. Lines join sites where the target species was present in both
years.
Figure S4. Plots exploring relationships among seed mass, probability of occurrence and species’
abundances: (a) ln(seed mass) versus probability of occurrence, (b) ln(seed mass) versus mean species’
ln(abundance) and (c) mean species’ ln(abundance) versus probability of occurrence. In all plots point
symbols follow the legend in (a). The fitted lines in (b) are from basic linear regressions fitted separately
to native and alien species. These plots show data from all species that had at least 10 occurrences across
the dataset, and for which seed mass data were available.
Figure S5. Pairwise scatterplots of species’ mean ln(SLA) mean ln(seed mass) and ln(maximum height).
Solid red points are alien species and hollow grey points are natives. Red splines are loess smoothers fitted
to all species. Spearman’s rho correlation values for each pairwise combination are also shown.
References cited in supplementary information
1.
Arditti J. & Ghani A.K.A. (2000). Tansley Review No. 110. Numerical and Physical
Properties of Orchid Seeds and Their Biological Implications. New Phytol.,
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Chase J.M. & Myers J.A. (2011). Disentangling the importance of ecological niches
from stochastic processes across scales. Philos. Trans. R. Soc. B Biol. Sci.,
366, 2351-2363.
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Miklós I. & Podani J. (2004). Randomization of presence-absence matrices:
comments and new algorithms. Ecology, 85, 86-92.
4.
Moles A.T. & Westoby M. (2004). Seedling survival and seed size: a synthesis of
the literature. J. Ecol., 92, 372-383.
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Oksanen J., Blanchet F.G., Kindt R., Legendre P., Minchin P.R., O'Hara R.B.,
Simpson G.L., Solymos P., Stevens M.H. & Wagner H. (2014). Vegan:
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