Table 1

Statistical analysis of capture data in relation to weather patterns
Taxon
 Weather variable in best model
 Number of models
 Average explained deviance in %



SR
 TDD
 WIND
 PREC
s(·)
 Weather
 Final model
Window traps







Chironomidae*
 20.00
 27.00
 30.00
 23.00
 10
 79.67
 7.52
 85.81
Muscidae*
 27.00
 30.00
 19.00
 24.00
 10
 85.74
 23.47
 89.68
Sciaridae*
 16.67
 33.33
 26.67
 23.33
 3
 58.91
 18.26
 80.69
Pitfall traps







Chironomidae
 24.67
 28.89
 25.11
 21.33
 45
 82.64
 12.91
 88.56
Muscidae
 28.80
 26.80
 21.80
 22.60
 50
 84.38
 15.58
 90.87
Sciaridae*
 25.14
 31.14
 23.43
 20.29
 35
 78.15
 16.10
 85.82
Nymphalidae*
 26.11
 31.67
 26.11
 16.11
 18
 76.26
 29.22
 90.28
Ichneumonidae
 26.19
 25.71
 26.19
 21.90
 42
 81.66
 19.45
 86.65
Linyphiidae*
 35.00
 31.67
 -
 33.33
 30
 75.98
 19.21
 83.06
Lycosidae*
 42.20
 30.85
 -
 26.95
 47
 70.70
 24.51
 85.48
Acari
 34.07
 35.56
 -
 30.37
 45
 78.53
 23.22
 89.28
Collembola*
 33.00
 32.67
 -
 34.33
 50
 71.88
 13.82
 81.09

Summary results of generalized additive models of the ten years of data for the different arthropod taxa aggregated across years and plots. Models with each of four weather variables: solar radiation in W/m2 (SR), thawing day-degrees in °C (TDD), proportion of capture period with wind speeds above 3 m/s (WIND) or precipitation in mm (PREC) were ranked from one to four, with four assigned to the model with the best fit. The table gives the summed rank relative to the possible maximum (in %) for each of the four weather variables. The weather variable that was ranked highest is given in bold for each taxon in each of the two trap types. In addition, the number of sets of models is given as well as the average percentage of null deviance explained by the generalized additive models of a spline of capture date alone s(·), of the weather variable alone and finally of the combined model of both the spline of capture date as well as the linear weather variable. Asterisks indicate that the use of Gaussian curves (parametric models) instead of GAM's identified the same weather variables as the most important.

Høye and Forchhammer BMC Ecology 2008 8:8   doi:10.1186/1472-6785-8-8