1 Life history mediates the trade-offs among different components

2 of demographic resilience

3

4 Authors: Pol Capdevila1,2*, Iain Stott3, James Cant4, Maria Beger4,5, Gwilym

5 Rowlands1, Molly Grace1, Roberto Salguero-Gómez1,5,6

6 1Zoology Department, Oxford University, Zoology Research and Administration Building, 11a

7 Mansfield Rd, Oxford OX1 3SZ, UK

8 2School of Biological Sciences, University of Bristol, 24 Tyndall Ave, BS8 1TQ, Bristol, UK

9 3School of Life Sciences, University of Lincoln, Brayford Pool, Lincoln LN6 7TS, UK

10 4School of Biology, Faculty of Biological Sciences, University of Leeds, UK, LS2 9JT

11 5Centre for Biodiversity and Conservation Science, School of Biological Sciences, University of

12 Queensland, Brisbane, 4072, Australia

13 6Max Planck Institute for Demographic Research, Konrad Zuse Straße 1, Rostock 18057, Germany

14 *Corresponding author: [email protected]

1

15 Table S1. Taxonomic summary of the matrix population models used in our 16 analyses. N sp represents the number of species and N pop the number of 17 populations.

Kingdom Class Order N sp N pop Perciformes 3 3 Actinopterygii Siluriformes 1 1 Elasmobranchii Lamniformes 1 2 Accipitriformes 5 9 Anseriformes 1 3 Charadriiformes 3 6 Falconiformes 1 2 Galliformes 1 1 Aves Gruiformes 1 1 Passeriformes 1 1 Pelecaniformes 1 1 Procellariiformes 2 2 Animalia Psittaciformes 2 3 Strigiformes 1 1 Artiodactyla 5 43 Carnivora 12 24 Chiroptera 1 1 Mammalia Diprotodontia 1 1 Primates 9 14 Proboscidea 1 1 Rodentia 4 5 Crocodylia 1 1 Reptilia Squamata 1 3 Testudines 8 19 1 1 Asparagales 5 18 1 1 Liliopsida Liliales 14 72 Poales 7 19 Zingiberales 2 6 Apiales 7 20 Plantae Asterales 20 44 Brassicales 10 34 Caryophyllales 33 84 Magnoliopsida Cornales 1 1 Dipsacales 2 6 Ericales 11 60 Fabales 12 70

2

Fagales 4 31 Gentianales 3 4 Geraniales 2 8 11 45 1 1 Malpighiales 10 23 Malvales 4 8 Myrtales 3 12 1 2 11 31 4 7 Sapindales 4 4 1 1 Solanales 2 2 Pinopsida Pinales 4 6 18

3

19 Table S2. Model outputs for the correlations among the components of 20 demographic resilience: compensation, resistance, and recovery time. Median 21 represents the median of the posterior distribution. CI low and high are the lower and 22 higher values of the 95% confidence intervals, respectively. Rhat is the ratio of the 23 effective sample size to the overall number of iterations, with values close to one 24 indicating convergence values.

Kingdom Response Parameter Median CI_low CI_high Rhat Intercept 0.01 -0.09 0.12 1.00 Generation time 0.08 0.04 0.13 1.00 Mean reproductive 0.99 0.94 1.04 1.00 Compensation output Generation time: Mean reproductive 0.06 0.02 0.10 1.00 output Matrix dimension 0.00 -0.05 0.05 1.00 Intercept -0.42 -1.73 0.91 1.00 Generation time -0.12 -0.28 0.04 1.00 Mean reproductive 0.29 0.10 0.48 1.00 Animals Resistance output Generation time: Mean reproductive -0.06 -0.16 0.04 1.00 output Matrix dimension 0.15 0.02 0.29 1.00 Intercept 0.14 -0.14 0.62 1.00 Generation time 0.31 0.20 0.42 1.00 Mean reproductive 0.33 0.21 0.46 1.00 Recovery time output Generation time: Mean reproductive -0.07 -0.14 0.01 1.00 output Matrix dimension 0.49 0.37 0.60 1.00 Intercept -0.08 -0.63 0.49 1.00 Generation time 0.04 0.00 0.07 1.00 Mean reproductive 0.94 0.91 0.97 1.00 Compensation output Generation time: Mean reproductive 0.05 0.03 0.08 1.00 output Matrix dimension 0.15 0.10 0.19 1.00 Plants Intercept -0.64 -2.12 0.80 1.00 Generation time 0.24 0.14 0.34 1.00 Mean reproductive 0.36 0.28 0.43 1.00 Resistance output Generation time: Mean reproductive 0.03 -0.05 0.09 1.00 output Matrix dimension 0.15 0.03 0.27 1.00 Recovery time Intercept 0.60 -0.89 2.13 1.00

4

Generation time 0.24 0.17 0.32 1.00 Mean reproductive 0.03 -0.03 0.09 1.00 output Generation time: Mean reproductive -0.05 -0.11 0.00 1.00 output Matrix dimension 0.23 0.12 0.34 1.00 25

26

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27 Effects of body size on demographic resilience

28 To test the influence of the body size of a species on its demographic resilience, we

29 fitted separated multivariate multilevel Bayesian model for animals and plants. We

30 used compensation, resistance, and recovery time as response variables, and adult

31 body weight (g) for animals or maximum height (m) in plants as fixed effects. We

32 obtained adult body mass (g) data from Myhrvold et al.1 for mammals birds, reptiles

33 and amphibians, and from FishBase2 for the only elasmobranch species in the study.

34 For terrestrial plants, we utilised maximum height (m) reported per species in the

35 TRY database3, complemented with information from the Botanical Information and

36 Ecology Network4 (BIEN; http://bien.nceas.ucsb.edu/bien/). Not all our species had

37 body dimension information available from these databases or via an online search,

38 and so this limitation reduced our initial sample size. The number of populations of

39 animals decreased from 164 to 153, while for plants it decreased from 621 to 273

40 populations.

41 For the models, we used weakly regularising normally-distributed priors for

42 the global intercept and slope:

2 43 푦푖,푗~푁표푟푚푎푙(µ푖,푗, 휎 ) (15)

44 µ푖,푗 = 훽0 + 훽0푖 + 훽0푗 + 훽퐵 + 훽퐵푖 + 훽퐵푗 + 훽퐷 + 훽퐷푖 + 훽퐷푗 (16)

45 훽0~ 푁표푟푚푎푙(0,1) (17)

46 훽~ 푁표푟푚푎푙(0,10) (18)

47 휎2~푁표푟푚푎푙(0,1) (19)

6

48 where 훽0 is the global intercept, 훽0푖 and 훽0푗 are the population-level and

49 phylogenetic-level departure from 훽0, respectively; 푦푖,푗 is the estimate for

50 compensation, resistance and recovery time for the ith population for the jth

51 phylogenetic distance. 훽퐵 and 훽퐷 represent the effects of the animal adult body size

52 (g) or plant maximum height (m) and matrix dimension, respectively.

53 Body dimension influences the components of demographic resilience of

54 species. Both for animals and plants, as the body size increases, compensation

55 abilities increase (Fig. S1 a,d; Table S2). While this pattern would be expected in

56 plants, where large individuals tend to be highly reproductive and then have a greater

57 ability to compensate mortality events5,6, in most animals larger body sizes are linked

58 to lower reproductive values7. Resistance is independent from body dimension for

59 both animals and plants, with the slopes of these correlations showing no clear trend

60 (Fig. S1b,e; Table S2). Finally, animal body size is positively correlated with recovery

61 time (Fig. S1c; Table S2), while plant body height only shows a slight positive trend

62 (Fig. S1f; Table S2).

7

63

64 Fig. S1. Correlation between the components of demographic resilience and 65 body dimensions of animals (a, b, and c) and plants (d, e, and f). The 66 correlations between the scaled values of the demographic resilience components 67 of resistance, compensation, and recovery time with the scaled values of adult body 68 weight (g) of 149 populations of animals (blue) and 254 plants (orange). Lines

8

69 represent the predictions from the multivariate multilevel Bayesian models (Table 70 S2), where thin lines correspond to the predictions drawn from each of the 250 71 posterior samples of the model, and the thick line represents the mean outcome of 72 the model. 73 74 Table S2. Model outputs for the correlations between the components of 75 resilience and body dimension for animals and plants. Median represents the 76 median of the posterior distribution. CI low and high are the lower and higher values 77 of the 95% confidence interval. Rhat is the ratio of the effective sample size to the 78 overall number of iterations, with values close to one indicating convergence values.

Kingdom Response Parameter Median CI_low CI_high Rhat Intercept 0.08 -1.43 1.65 1.00 Compensation Body mass 0.34 0.02 0.65 1.00 Matrix -0.14 -0.24 -0.05 1.00 dimension Intercept -0.08 -1.42 1.18 1.00 Animals Resistance Body mass 0.00 -0.30 0.31 1.00 Matrix 0.09 -0.06 0.23 1.00 dimension Intercept 0.26 -0.86 1.19 1.00 Recovery time Body mass 0.45 0.21 0.67 1.00 Matrix 0.47 0.33 0.59 1.00 dimension Intercept 0.08 -1.13 1.40 1.00 Compensation Body height 0.24 -0.18 0.66 1.00 Matrix 0.16 -0.06 0.37 1.00 dimension Intercept -0.18 -1.50 1.27 1.00 Plants Resistance Body height 0.16 -0.28 0.64 1.00 Matrix -0.02 -0.26 0.19 1.00 dimension Intercept 0.16 -1.10 1.40 1.00 Recovery time Body height 0.28 -0.08 0.66 1.00 Matrix 0.23 0.08 0.38 1.00 dimension 79

80 Effects of plant growth form on demographic resilience

81 To test whether plant growth form shapes its demographic resilience, we fitted a

82 multivariate multilevel Bayesian model. We used compensation, resistance, and

9

83 recovery time as response variables and the life form categorisation of Raunkiær8

84 as a fixed effect. We classified each plant species according to Raunkiær’s growth

85 form scheme8, in which the height of the shoot apical meristems (SAMs) in relation

86 to ground level determines their life form. Briefly, the levels used here include: (i)

87 helophyte: SAMs under water; (ii) geophyte: SAMs underground; (iii)

88 hemicryptophyte: SAMs at ground level; (iv) chamaephyte: SAMs 0-0.25 m height;

89 (v) nanophanerophyte: SAMs 0.25-8 m; (vi) mesophanerophyte: SAMs 8-30 m; and

90 (vii) megaphanerophyte: SAMs >30m. Importantly, Raunkiær’s growth form is often

91 associated with the size or the plant, but also accounts for the shape of the plant and

92 its ability to fully regenerate8. Due to lack of information online for some species, our

93 initial sample size from 621 populations was constrained to 437 populations in this

94 specific test.

95 We used weakly regularising normally-distributed priors for the global

96 intercept and slope:

2 97 푦푖,푗~푁표푟푚푎푙(µ푖,푗, 휎 ) (15)

98 µ푖,푗 = 훽0 + 훽0푖 + 훽0푗 + 훽푅 + 훽푅푖 + 훽푅푗 + 훽퐷 + 훽퐷푖 + 훽퐷푗 (16)

99 훽0~ 푁표푟푚푎푙(0,1) (17)

100 훽~ 푁표푟푚푎푙(0,10) (18)

101 휎2~푁표푟푚푎푙(0,1) (19)

102 where 훽0 is the global intercept, 훽0푖 and 훽0푗 are the population-level and

103 phylogenetic-level departure from 훽0, respectively; 푦푖,푗 is the estimate for

104 compensation, resistance and recovery time for the ith population for the jth

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105 phylogenetic distance. 훽푅 and 훽퐷 represent the effects of the Raunkiær life form and

106 matrix dimension, respectively.

107 Our examined plant species have different values of compensation,

108 resistance and recovery time depending on their Raunkiær life form8. Still, the

109 overlap among the posterior estimates is considerable (Fig S2), so that species with

110 different growth forms can show similar levels of demographic resilience.

111 Compensation increased from Helophytes to Macrophanerophytes (Fig. S2),

112 indicating that plant species whose shot apical meristems overwinter at higher

113 distance from the ground have a higher ability to compensate from disturbances. On

114 the contrary, resistance shows no clear patterns across Raunkiær life forms (Fig.

115 S2), suggesting that resistance is independent of the location of SAMs on the plant

116 anatomy. Finally, recovery time displays a concave shape (Fig. S2) from Helophytes

117 to Macrophanerophytes, indicating that plants with SAMs very close to or far from

118 the ground level have the shortest recovery times post disturbance. These results

119 are in agreement with previous studies5,6, were trees were reported to have a greater

120 ability to bounce back from disturbances than other plant growth forms, due to their

121 higher reproductive outputs. However, we also note a high degree of overlap in the

122 various index of demographic resilience across life forms.

123

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124 125 Fig. S2. Demographic resilience components of plants classified according to 126 Raunkiær life forms. We show here the posterior distributions of multivariate 127 multilevel Bayesian models with scaled values of compensation, resistance and 128 recovery time as response variable and the Raunkiaer life form classification8. n= 129 indicates the sample size of the original dataset.

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130 Conservation status

131 To test whether there was any correlation between the demographic resilience of the

132 species and their conservation status, we fitted two separate multivariate multilevel

133 Bayesian models for animals and plants. We used compensation, resistance and

134 recovery time as response variables and the conservation status and the

135 conservation status of the studied species as reported on the IUCN Red List9 as

136 fixed effects. Not all the included species had a conservation status available in the

137 IUCN Red List, reducing our initial sample size from 164 to 155 populations of

138 animals, and from 621 to 212 populations of plants.

139 For these models we used weakly regularising normally-distributed priors for

140 the global intercept and slope:

2 141 푦푖,푗~푁표푟푚푎푙(µ푖,푗, 휎 ) (15)

142 µ푖,푗 = 훽0 + 훽0푖 + 훽0푗 + 훽퐶 + 훽퐶푖 + 훽퐶푗 + 훽퐷 + 훽퐷푖 + 훽퐷푗 (16)

143 훽0~ 푁표푟푚푎푙(0,1) (17)

144 훽~ 푁표푟푚푎푙(0,10) (18)

145 휎2~푁표푟푚푎푙(0,1) (19)

146 where 훽0 is the global intercept, 훽0푖 and 훽0푗 are the population-level and

147 phylogenetic-level departure from 훽0, respectively; 푦푖,푗 is the estimate for

148 compensation, resistance and recovery time for the ith population for the jth

149 phylogenetic distance. 훽퐶, and 훽퐷 represent the effects of the conservation status

150 and matrix dimension, respectively.

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151 There was a high variation in the compensation, resistance and recovery time

152 among the different conservation statuses of the species (Fig. S3). Interestingly,

153 these results suggest the current conservation status of species is independent of

154 their inherent ability to compensate, resist and recover from disturbances.

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155 15

156 Fig. S3. Demographic resilience components of species against their 157 conservation status in animals (a) and plants (b). We show here the posterior 158 distributions of multivariate multilevel Bayesian models for animals (a) and plants 159 (b), with scaled values of compensation, resistance and recovery time as response 160 variable and the conservation status of the studied species as reported on the IUCN 161 Red List9 as fixed effects. LC = Least Concerned, NT = Near Threatened, VU = 162 Vulnerable, EN = Endangered, CR = Critically Endangered. n = indicates the sample 163 size. 164

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