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Appendix S2.1 Description of demographic data The final dataset contained 34 species with 93 populations, of which 13 species of trees with 29 populations and 21 species of herbaceous perennials with 64 populations. In this dataset, there were 2.7 ± 2.3 (mean±1SD) populations/species on average with a median of 2 populations, and 12 species had only one population. Populations were generally studied for a short time (3.0 ± 1.3 years – mean ± 1SD, with a median of 3 years), and projection matrices were built from 5.0 ± 1.3 (mean±1SD) developmental stages with a median of 5 stages. The deterministic and stochastic population growth rates had very similar values λGeom = 1.03 ± 0.17 and λiid = 1.04 ± 0.20 (mean±1SD). Stasis was the dominant demographic process (0.120; 0.060 - 0.173) followed by progression (0.012; 0.005 - 0.024), fecundity (0.006; 0.003 - 0.015) and finally, retrogression (0.001; 0.000 - 0.007) (Median; 1st - 3rd Quartiles). The elasticity of population growth rates was highest for changes in stasis (0.666 ± 0.206; 0.668), followed by progression (0.206 ± 0.132; 0.204), retrogression (0.064 ± 0.064; 0.058) and finally fecundity (0.056 ± 0.070; 0.028) (mean ± 1SD; median).
1
Appendix S2.2 Figure S2.2a The position of stochastic population growth rates along the climate suitability axis for 93 populations across 34 species in COMPADRE Plant Matrix Database. Blue dots indicate trees, red dots indicate herbaceous perennials, and the zerointercept lines represent stable (i.e., neither increasing nor declining) populations (log(λiid) = 0).
0.2 Abies concolor
0.6 0.2 −0.2 −0.6
0.6
1.0
Abies magnifica
Acer saccharum
Calochortus albus
0.6
1.0
Actaea spicata
● ● ●
●● ●
●●
Calocedrus decurrens
0.2
0.2 Alnus incana rugosa
Cryptantha flava
1.0
Artemisia genipi
Aster amellus
● ●
● ●
●
Cirsium dissectum
0.6
Cypripedium calceolus
● ● ●● ●● ● ●
Echinacea angustifolia
Heteropogon contortus
●
log(Lambda iid)
●
●●
Khaya senegalensis
0.6 0.2 −0.2 −0.6
●● ●●
Lathyrus vernus
Manilkara zapota
● ● ●
●
●
● Mimulus cardinalis
Mimulus lewisii
●
●
Molinia caerulea
● ●
●
●
● ● ●
●
Pinus lambertiana
0.6 0.2 −0.2 −0.6
● ●
● ● Poa alpina
Primula veris
Primula vulgaris
● ● ●
● ●
0.2
0.6
● ● ● ●● ●
●
Ramonda myconi
0.6 0.2 −0.2 −0.6
1.0
Prioria copaifera
Saponaria bellidifolia Sarcocapnos enneaphylla
●●
●
0.2
Prosopis glandulosa
●
Trillium grandiflorum
●● ● ●●
● ● ●
0.6
1.0
Prunus africana
●
●
Succisa pratensis
Prosopis laevigata
0.2
0.6
Climate suitability
2
Tsuga canadensis
●
1.0
●
0.6 0.2 −0.2 −0.6
Figure S2.2b The position of projected extinction risk (time to quasi-extinction) along the climate suitability axis for 93 populations across 34 species in COMPADRE Plant Matrix Database. Blue dots indicate trees, red dots indicate herbaceous perennials. Simulations were stopped at 300 years.
0.2 300 200 100 0
Abies concolor
●●
1.0
Abies magnifica
●●
0.2 Acer saccharum
0.6
1.0
Actaea spicata
●
0.2 Alnus incana rugosa
●
0.6
1.0
Artemisia genipi
Aster amellus
●
● ●●
● ●
●
● Calocedrus decurrens
●
QExtinction time (years)
0.6
Calochortus albus
●
Cirsium dissectum
●●
●
Cryptantha flava
●● ● ●● ●
●
Cypripedium calceolus
Echinacea angustifolia
Mimulus lewisii
Molinia caerulea
Pinus lambertiana
Prosopis glandulosa
Prosopis laevigata
Prunus africana
Trillium grandiflorum
Tsuga canadensis
●
●
Heteropogon contortus
●
●
300 200 100 0
Khaya senegalensis
●● ●
●
Lathyrus vernus
●
Manilkara zapota
Mimulus cardinalis
Primula vulgaris
Prioria copaifera
●
●
Primula veris
●
●●
●●
●
●
● ●
Saponaria bellidifolia Sarcocapnos enneaphylla
●
●
Succisa pratensis
●● ● ●
●
● ● ●
● ● ●
0.6
●
●
Ramonda myconi
1.0
0.2
0.6
1.0
0.2
0.6
Climate suitability
3
●
●
●
● ● Poa alpina
0.2
● ●
●
●
●
300 200 100 0
●
300 200 100 0
1.0
●
●
300 200 100 0
Appendix S2.3 (Table S2.3) Best fit Linear Mixed Effects Models (LMMs) for the effects of climate suitability on population performance and the effects of demographic processes on population extinction risk. The first column shows the fixed effects in the full models and the abbreviated and full name of predicted variables. The next columns show the coefficient means β and standard errors SE(β) for variables selected in the best model, and marginal (fixed effects) R2 values of the best models. In all models species (“SpeciesAccepted” column in COMPADRE) were introduced as random effects (intercept-only). MD = Matrix Dimension, SL = Study Length, GT = Growth Type, CS = Climate suitability, CV = Coefficient of Variation.
Effects of climate suitability on mean and temporal variation of population growth rate, on extinction risk and transient dynamics Model structure and predicted variable log(λiid) ~ MD+SL+GT+CS+MD:CS+SL:CS+GT:CS Stochastic population growth rate log(CVλ_det) ~ MD+SL+GT+CS+MD:CS+SL:CS+GT:CS Temporal variation of deterministic population growth rates log(timeto95ext_200) ~ MD+SL+GT+CS Time to 95% probability of quasi-extinction log(RR) ~ MD+SL+GT+CS+MD:CS+SL:CS+GT:CS Reactivity range log(IR) ~ MD+SL+GT+CS+MD:CS+SL:CS+GT:CS Inertia range
β
SE(β)
R
Intercept
0.972
0.031
0.000
Intercept GT Tree
0.123 -0.075
0.016 0.026
0.127
Intercept
4.474
0.182
0.000
Intercept CS
2.751 0.555
0.541 0.235
0.029
Intercept CS
3.907 0.593
0.535 0.265
0.033
Selected variable
4
2
Effects of climate suitability on mean and temporal variation of demographic processes Model structure and predicted variable log(fec) ~ MD+SL+GT+CS+MD:CS+SL:CS+GT:CS Fecundity sqrt(progr) ~ MD+SL+GT+CS+MD:CS+SL:CS+GT:CS Progression stasis ~ MD+SL+GT+CS+MD:CS+SL:CS+GT:CS Stasis
CV_prog ~ MD+SL+CS Temporal variation of progression (Herbaceous perennials) sqrt(CV_stasis) ~ MD+SL+GT+CS+MD:CS+SL:CS+GT:CS Temporal variation of stasis
log(CV_retr) ~ MD+SL+CS+MD:CS+SL:CS Temporal variation of retrogression (Herbaceous perennials)
Selected variable
2
β
SE(β)
R
Intercept MD
-5.059 -0.415
0.247 0.211
0.071
Intercept MD
0.108 -0.015
0.010 0.009
0.059
Intercept GTTree CS MD
0.100 0.062 -0.007 -0.041
0.009 0.016 0.005 0.007
0.531
Intercept CS
-6.312 -0.540
0.614 0.219
0.037
Intercept CS
0.510 -0.116
0.048 0.044
0.086
Intercept CS MD
0.488 -0.253 -0.088
0.050 0.055 0.044
0.486
Intercept MD
0.419 -0.103
0.035 0.037
0.110
Intercept GT Tree CS
0.437 -0.102 -0.044
0.038 0.063 0.025
0.090
Intercept SL
-0.817 0.158
0.100 0.094
0.044
5
Effects of mean and temporal variation of demographic processes on population extinction risk Model structure and predicted variable timeto95ext_200~ MD+SL+Fec+Sta+Ret+Prog Time to 95% probability of quasi-extinction
timeto95ext_200~ MD+SL+CV_fec+CV_Sta+CV_Ret+CV_Prog Time to 95% probability of quasi-extinction
Selected variable
2
β
SE(β)
R
Intercept MD Retrogression SL
116.909 34.433 54.431 23.596
14.236 16.206 15.368 13.048
0.409
Intercept CV_progression CV_Stasis SL
113.42 -21.99 20.70 29.76
14.35 10.79 12.11 13.68
0.000
6
Effects of climate suitability on the elasticity of population growth rate to changes in demographic processes Model structure and predicted variable ElastFec ~ MD+SL+GT+CS+λiid+MD:CS+SL:CS+GT:CS+λiid:CS Elasticity of λ to changes in mean fecundity
ElastProg ~ MD+SL+GT+CS+λiid+MD:CS+SL:CS+GT:CS+λiid:CS Elasticity of λ to changes in mean progression
ElastStasis ~ MD+SL+GT+CS+λiid+MD:CS+SL:CS+GT:CS+λiid:CS Elasticity of λ to changes in mean stasis
ElastRetr ~ MD+SL+GT+CS+λiid+MD:CS+SL:CS+GT:CS+λiid:CS Elasticity of λ to changes in mean retrogression
Selected variable
2
β
SE(β)
R
Intercept GT Tree CS λiid SL GTTree:CS λiid:CS SL:CS
Appendix S2.4 Figure S2.4 The relationship between the elasticity of population growth rate to basic demographic processes and climate suitability in interaction with other factors detected by the Linear Mixed Effects Models detailed in Appendix S2.3. Red lines represent minimum, orange lines represent median and blue lines represent maximum values of the factor in interaction with climate suitability. Dots represent 93 populations across 34 species of trees and herbaceous perennials. Black dots represents trees, and grey dots represent herbaceous perennials. Axis x represents climate suitability values centered on 0, with unit variance.