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Table 1 A combination of landscape fragmentation and elevation best explain the distribution of wingless queens along ecological gradients. Based on previous studies, we generated 12 models (M01 to M12) representing alternative hypotheses to explain the variation in frequency of wingless queens along the ecological gradient of each Sky Islands. The 12 models were ranked using the method of [121] implemented in R (Additional file 1: Table S2) and model probabilities (Prob) are reported, with m06 scoring as the highest ranking model

From: Past climate change on Sky Islands drives novelty in a core developmental gene network and its phenotype

Model

Formula

Prob

Underlying biological hypotheses

m01

Elev

0.03

Flightlessness in insects has been reported to increase with altitude [47, 127].

   

Elevation influences a wide range of ecological factors and may account for their joint effects.

   

Atmospheric pressure is lower at higher altitude and efficient flight may require costly adaptations [128].

m02

Temp

0.02

Insects will experience a decrease in annual thermal budget for growth and development. Critical temperature thresholds for growth, development and activity will be exceeded less frequently [128].

m03

Seas

0.02

Temperature seasonality, the variability in temperature over the year, is indicative a less stable environment. Flightless insects are known to be found in higher frequencies in more stable habitats [47].

m04

Frag

0.11

Flying insects will have a tendency to be blown away from patchy habitats, thus only wingless forms remain [46, 47]. The probability of finding a suitable habitat is decreased when habitats are patchy, thus dispersal risk is increased [129].

m05

Prod

0.17

The need for dispersal in high productivity habitats is reduced because the conditions for survival are met and the relative risk of long distance dispersal becomes too high [130]

m06

Frag + Elev

0.56

Both fragmentation and elevation influence the distribution of wingless queens.

m07

Frag + Elev + Frag x Elev

0.03

The effect of fragmentation depends on elevation: fragmentation may only be affecting the distribution of wingless queens at certain altitudes.

m08

Frag + Temp

0.03

Both fragmentation and temperature may influence the distribution of wingless queens.

m09

Frag + Temp + Frag x Temp

0.00

The effect of fragmentation depends on temperature: fragmentation may only be affecting the distribution of wingless queens at certaine temperature. Habitat fragmentation and temperature are know to be potentially interrelated [131].

m10

Frag + Prod

0.02

Both fragmentation and productivity can influence the distribution of wingless queens.

m11

Frag + Prod + Frag x Prod

0.00

Habitat fragmentation can affect productivity. Fragmentation may affect wingless queen distribution in habitats with a certain productivity level only. Habitat fragmentation and biomass growth are know to be potentially interrelated [131].

m12

Elev + Temp + Prod + Frag + Seas

0.00

Structure-rich model, including the effects of elevation, temperature, productivity, fragmentation and seasonality. Interactions were omitted.

  1. Parameters abbreviations are Elev: elevation, Temp: temperature, Seas: seasonality, Frag: fragmentation, Prod: productivity. An (x) in the formula indicate the interaction between two variables