Table 2.
Summary of the modelling results on the factors explaining annual variation in the three dispersal measures. The models were built by entering statistically significant adjusting variables first before testing the significance of the weather variables. (a) The emigration rate was modelled using a generalized linear model (GLM) with a binomial error distribution and a logit link function. (b) Annual average residence times and distances moved were modelled based on multiple linear regression models.
| variable | coefficient | d.f. | residual deviance | p-value |
|---|---|---|---|---|
| (a) | ||||
| emigration rate | ||||
| null model | 11 | 55.07 | ||
| metapopulation size | 0.00104 | 10 | 17.58 | <0.001 |
| mean daily solar radiation | 0.00011 | 9 | 7.99 | 0.002 |
| 85% of the total deviance explained by the model | ||||
| variable | coefficient | t | p-value | |
|---|---|---|---|---|
| (b) | ||||
| residence time | ||||
| recapture rate | 0.056 | 4.03 | 0.003 | |
| proportion of especially warm days | −14.64 | −8.23 | <0.001 | |
| n, F, P, R2 | 12, 56.0, <0.001, 0.91 | |||
| distance moved | ||||
| number of occupied patches | 5.17 | 4.34 | 0.002 | |
| mean temperature | 7.70 | 2.63 | 0.027 | |
| n, F, P, R2 | 12, 21.36, <0.001, 0.79 | |||