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Table 4 The linear and non-linear effects of food C/N ratios on the nine different traits of the oribatid mite Archegozetes longisetosus

From: Nutritional quality modulates trait variability

  Linear effect Nonlinear effect
C/N C/N x C/N
Chemistry
 Amount (log transformation)
  Estimatea ± SE 0.125 ± 0.023 −0.007 ± 0.001
  t286 5.546 −5.242
  p <  0.0001 <  0.0001
 Composition (1/4-power transformation)
  pseudoF286b 354.390 118.350
  r2 0.469 0.157
  p <  0.0001 <  0.0001
 Regeneration (arcsine square root transformation)
  Estimatea ± SE 0.229 ± 0.057 −0.012 ± 0.003
  t100 4.031 −3.641
  p 0.0001 0.0004
Life history
 Developmental time (no transformation)
  Estimatea ± SE −0.081 ± 0.035 0.005 ± 0.002
  t172 −2.321 2.455
  p 0.0215 0.0151
 Survival (arcsine square root transformation)
  Estimatea ± SE 0.130 ± 0.039 − 0.006 ± 0.002
  t216 3.357 −2.693
  p 0.0009 0.0077
 Offspring (square root transformation)
  Estimatea ± SE 0.144 ± 0.029 −0.007 ± 0.002
  t216 4.906 −4.140
  p <  0.0001 <  0.0001
 Output (square root transformation)
  Estimatea ± SE 0.203 ± 0.033 − 0.010 ± 0.002
  t208 6.191 −5.530
  p < 0.0001 < 0.0001
Morphology
 Body mass (log transformation)  
  Estimatea ± SE 0.135 ± 0.021 −0.008 ± 0.001
  t208 6.543 −7.082
  p < 0.0001 < 0.0001
 Morphometry (1/4-power transformation)
  pseudoF201b 0.960 2.781
  r2 0.005 0.013
  p 0.3457 0.0603
  1. aThe estimate of the linear effect describes the slope of the relationship between the C/N ratio and the response variable (i.e. normalized trait value), while the estimate of the non-linear effect is the curvature of the quadratic relationship (i.e. normalized trait value ~ C/N x C/N). b For the multivariate traits we used permutational multivariate analysis of variance (PERMANOVA), instead of a normal linear model