Green arrows represent increasing effects, whereas red arrows represent reducing effects.
Area of squares is proportional to the experiment sample size (1/s.e.).
Area of squares is proportional to the experiment sample size (1/s.e.).
Area of dots is proportional to the experiment sample size (i.e. square root of the number of individuals in which GCs were measured).
Panels show the association without ln-transforming metabolic rate effect sizes (left panel) and when ln-transforming them (right panel). Size of dots is proportional to the experiment sample size …
Size of dots is proportional to the experiment sample size (i.e. square root of the number of individuals in which glucocorticoids were measured). Shaded areas represent 95% CI. Note that the number …
Estimate | s.e. | Z | p | 95% CI | |
---|---|---|---|---|---|
Intercept | 0.72 | 0.11 | 6.40 | <0.0001 | 0.50–0.95 |
MR effect size (ln) | 0.31 | 0.10 | 2.94 | 0.003 | 0.10–0.51 |
Variance components: Study.ID (Sigma^2)– Estimate = 0.00, sqrt = 0.00, n = 21.
Residual heterogeneity: QE(df = 33) = 28.40, p=0.70.
Test of moderators: QM(df = 1) = 8.64, p=0.003.
Full models are shown in Supplementary file 4.
Variable | p |
---|---|
MR effect size (ln) | 0.003 |
Taxa | 0.63 |
Before/after | 0.49 |
Experiment/control | 0.68 |
Metabolic variable | 0.94 |
Treatment type | |
Treat. 2 | 0.93 |
Treat. 3 | 0.60 |
Estimate | s.e. | z | P | 95% C.I.. | |
---|---|---|---|---|---|
Intercept | 0.76 | 0.11 | 7.20 | < 0.0001 | 0.55-0.96 |
MR effect size (In) | 0.32 | 0.10 | 2.97 | 0.003 | 0.11-0.52 |
Variance components: outer factor: Lab(N=16), inner factor: Study.ID (N=21). tau^2- Estimate = 0.02, sqrt = 0.1 | |||||
Residual heterogeneity: QE(df=33)=28.26,p=0.70 | |||||
Test of moderators: QM(df=1)=8.83,p=0.003 |
(a) | Estimate | s.e. | z | P | 95% C.I. |
---|---|---|---|---|---|
Intercept | 0.72 | 0.11 | 6.30 | < 0.0001 | 0.50-0.95 |
MR effect size (In) | 0.30 | 0.11 | 2.75 | 0.006 | 0.09-0.52 |
Taxa (mammal) | 0.07 | 0.23 | 0.33 | 0.74 | -0.38-0.54 |
MR : Taxa | 0.16 | 0.22 | 0.71 | 0.48 | -0.28-0.59 |
Variance components: outer factor: Lab (N=16), inner factor: Study. ID (N=21). tau^2- Estimate = 0.00, sqrt = 0.09 | |||||
Residual heterogeneity: QE(df=31)=27.47,p=0.65 | |||||
Test of moderators: QM(df=3)=9.53,p=0.023 | |||||
(b) | Estimate | s.e. | z | P | 95% C.I. |
Intercept | 0.77 | 0.10 | 7.69 | < 0.0001 | 0.57-0.96 |
MR effect size (ln) | 0.32 | 0.11 | 3.00 | 0.002 | 0.11-0.54 |
Before / after effect (yes) | -0.30 | 0.38 | -0.79 | 0.43 | -1.06-0.45 |
MR : Time effect | -0.00 | 0.31 | 0.05 | 0.96 | -0.59-0.62 |
Variance components: Lab (N=16), inner factor: Study.ID (N=21). tau^2 - Estimate = 0.03, sqrt = 0.16 | |||||
Residual heterogeneity: QE(df=31)=27.72,p=0.64 | |||||
Test of moderators: QM(df=3)=9.39,p=0.024 | |||||
(c) | Estimate | s.e. | z | P | 95% C.I. |
Intercept | 0.76 | 0.10 | 7.51 | < 0.0001 | 0.56-0.96 |
MR effect size (ln) | 0.32 | 0.11 | 2.97 | 0.003 | 0.11-0.52 |
Exp./ control effect (yes) | 0.08 | 0.31 | 0.25 | 0.80 | -0.53-0.69 |
MR : Exp. / control effect | -0.05 | 0.32 | -0.00 | 0.99 | -0.62-0.62 |
Variance components: Lab (N=16), inner factor: Study.ID (N=21). tau^2- Estimate = 0.02, sqrt = 0.15 | |||||
Residual heterogeneity: QE(df=31)=28.18,p=0.61 | |||||
Test of moderators: QM(df=3)=8.88,p=0.030 | |||||
(d) | Estimate | s.e. | P | 95% C.I. | |
Intercept | 0.76 | 0.11 | 7.12 | < 0.0001 | 0.55-0.97 |
MR effect size (ln) | 0.34 | 0.11 | 3.00 | 0.003 | 0.12-0.56 |
Met. variable (HR) | 0.15 | 0.22 | 0.68 | 0.49 | -0.28-0.59 |
MR : Met. variable | 0.01 | 0.23 | 0.06 | 0.96 | -0.43-0.46 |
Variance components: outer factor: Lab (N=16), inner factor: Study.ID (N=21). tau^2- Estimate = 0.03, sqrt = 0.16 | |||||
Residual heterogeneity: QE(df=31)=28.03,p=0.62 | |||||
Test of moderators: QM(df=3)=9.21,p=0.027 | |||||
e) | Estimate | s.e. | z | P | 95% C.I. |
Intercept | 0.82 | 0.20 | 4.09 | < 0.0001 | 0.43-1.21 |
MR effect size (In) | 0.26 | 0.20 | 1.30 | 0.19 | -0.13-0.64 |
Treat. Type 2 | 0.01 | 0.29 | 0.02 | 0.98 | -0.57-0.58 |
Treat. Type 3 | -0.20 | 0.32 | -0.62 | 0.53 | -0.81-0.42 |
MR: Treat. Type 2 | 0.09 | 0.27 | 0.34 | 0.74 | -0.44-0.62 |
MR: Treat. Type 3 | 0.08 | 0.29 | 0.28 | 0.78 | -0.49-0.66 |
Variance components: Lab (N=16), inner factor: Study.ID (N=21). tau^2- Estimate = 0.04, sqrt = 0.20 | |||||
Residual heterogeneity: QE(df=29)=27.77,p=0.53 | |||||
Test of moderators: QM(df=5)=9.32,p=0.097 |
Study selection steps and number of studies found.
Table showing the information extracted from each study included in the meta-analysis.
Studies included in the meta analysis: Cohen et al., 2008; Booth-McLean et al., 2007; Celi et al., 2010; Cyr et al., 2008; Frank et al., 1997; Jimeno et al., 2018; Kaciuba-Uscilko et al., 1992; Keselman et al., 2017; Kleist et al., 2017; Nephew and Romero, 2003; Peake et al., 2014; Srámek et al., 2000; Wikelski et al., 1999; Xu et al., 2018; Beerling et al., 2011; de Bruijn and Romero, 2011; de Bruijn and Romero, 2013; Hipólide et al., 2006; Nephew et al., 2003; Buwalda et al., 2012; Harlow et al., 1987.
Effect size calculations.
The document Includes one sheet per study with the data extracted, the part of the article it was extracted from, and the effect size calculations and results further included in the meta analysis and Supplementary file 2.
Meta-regression model (quantitative approach) testing the effect of (a) taxa, (b) before/after effect, (c) experiment/control effect, (d) use of metabolic rate (MR) or heart rate as metabolic variable, and (e) treatment type, on the association between MR and glucocorticoid effect sizes across studies.