Table 2.

Parameters of linear regression fits between aerodynamic measures and various kinematics patterns

Dependencies (y) vs (x)y-interceptSlopeR2PFig.
Embedded Image vs Embedded Image317±148-459±2880.150.13NS-
Embedded Image vs Embedded Image-131±68.2403±1590.300.02*-
Embedded Image vs Embedded Image142±21.5-418±75.80.67<0.001*** 4A
Embedded Image vs Embedded Image54.5±18.3-22.8±13.70.160.12NS 4B
Embedded Image vs Embedded Image80.2±2.830.22±0.070.430.004**-
Embedded Image vs Embedded Image41.9±2.000.11±0.050.280.03*-
Embedded Image vs Embedded Image24.2±2.550.12±0.060.200.07NS 4C
Embedded Image vs Embedded Image-3.15±2.000.08±0.030.390.008** 4D
Embedded Image vs Embedded Image-0.25±0.630.13±0.020.68<0.0001***-
TP (Nmm) vs Embedded Image15.8±28.9-77.6±1020.040.46NS 8A
Embedded Image vs Embedded Image14.6±2.94-47.1±10.40.58<0.001*** 8C
Embedded Image vs Embedded Image-1.01±0.530.09±0.020.60<0.001*** 8D
  • Forces and force coefficients are mean values averaged throughout a stroke cycle for a single flapping wing. N=17 kinematic patterns.

    Asterisks indicate mean significance level of slope: *P<0.05, **P<0.01, ***P<0.001. NS, not significant. For further abbreviations see List of symbols and abbreviations.