Table 1. The number of ignition tests performed in the study by species, moisture content and wind velocity. Total number of tests: 293, location of the study: Evo state forest, Hämeenlinna, Finland.
Wind velocity 0 m s–1
Moisture content 11% 25% 43% 67% 100%
Species
Pleurozium schreberi 6 5 5 5 5
Dicranum spp. 5 -^ 2 5 5
Hylocomium splendens 5 4 5 5 5
Cladonia rangiferina 5 5 5 5 5
  Wind velocity 1 m s–1
Pleurozium schreberi 5 4 5 5 4
Dicranum spp. 5 4 3 7 4
Hylocomium splendens 5 7 7 5 4
Cladonia rangiferina 3 5 6 6 6
  Wind velocity 2 m s–1
Pleurozium schreberi 6 5 4 6 5
Dicranum spp. 5 8 4 4 5
Hylocomium splendens 5 5 5 5 5
Cladonia rangiferina 6 5 5 4 4
^) All samples in this group were contaminated by mold and omitted from analysis
1

Fig. 1. Ignition probabilities of the studied species by wind velocity and fuel moisture content (%, dry weight basis) of used logistic regression models. Shaded areas show the standard errors of each fitted model and dots show the original measured observations. View larger in new window/tab.

Table 2. Coefficients of the logistic regression model (ignition probability analysis).
Species Variable Estimate Std. error p
Cladonia rangiferina Intercept 14.08 13.22 0.28
Moisture% –0.13 0.14 0.34
Wind 1 m s–1 0.35 1.59 0.83
Wind 2 m s–1 18.26 4715.29 1
Dicranum spp. Intercept 2.22 1.14 0.05
Moisture% –0.01 0.01 0.30
Wind 1 m s–1 0.36 1.27 0.78
Wind 2 m s–1 2.95 1.11 0.01**
Hylocomium splendens Intercept –0.14 0.75 0.86
Moisture% –0.05 0.01 <0.001***
Wind 1 m s–1 3.60 0.96 <0.001***
Wind 2 m s–1 3.78 0.99 <0.001***
Pleurozium schreberi Intercept 0.06 0.68 0.92
Moisture% –0.05 0.01 <0.001***
Wind 1 m s–1 1.95 0.81 0.016**
Wind 2 m s–1 3.45 0.92 <0.001***
2

Fig. 2. Mass losses (%, dry weight) of the studied species by wind velocity and fuel moisture content (%, dry weight basis) of used generalized additive models. Shaded areas show the standard errors of each fitted model and dots show the original measured observations. View larger in new window/tab.

Table 3. Parametric coefficients and significances of smoother terms of generalized additive model (mass loss analysis). Edf: efficient degrees of freedom.
Species Variable/Smooth term Estimate Std.error p edf
Cladonia rangiferina Parametric coefficients
Intercept 4.43 0.12 <0.001***
Wind 1 m s–1 –0.11 0.18 0.54
Wind 2 m s–1 0.11 0.21 0.60
Smooth terms
s(moisture): wind 0 m s–1 <0.001*** 1.03
s(moisture): wind 1 m s–1 <0.001*** 0.98
s(moisture): wind 2 m s–1 <0.001*** 1.80
Dicranum spp. Parametric coefficients
Intercept 0.27 0.38 0.48
Wind 1 m s–1 1.83 0.67 0.008**
Wind 2 m s–1 3.99 0.68 <0.001***
Smooth terms
s(moisture): wind 0 m s–1 ̶̶ 0
s(moisture): wind 1 m s–1 0.66 0.65
s(moisture): wind 2 m s–1 0.21 1.11
Hylocomium splendens Parametric coefficients
Intercept 2.70 0.26 <0.001***
Wind 1 m s–1 1.80 0.47 <0.001***
Wind 2 m s–1 2.06 0.47 <0.001***
Smooth terms
s(moisture): wind 0 m s–1 <0.001*** 1.00
s(moisture): wind 1 m s–1 <0.001*** 0.93
s(moisture): wind 2 m s–1 0.001** 1.11
Pleurozium schreberi Parametric coefficients
Intercept 4.81 1.44 0.001**
Wind 1 m s–1 0.04 2.44 0.99
Wind 2 m s–1 0.05 1.52 0.97
Smooth terms
s(moisture): wind 0 m s–1 <0.001*** 2.38
s(moisture): wind 1 m s–1 <0.001*** 3.20
s(moisture): wind 2 m s–1 0.05* 1.24