Species variables or environmental variables as indicators of forest biodiversity: a case study using saproxylic beetles in Maritime pine plantations

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Table III

Results of PLS regressions with species abundance as predictors of the species richness of saproxylic beetles (RMSEP: root mean squared error of prediction). The number of independent variables (predictors) entered in the model is indicated in brackets.

Species	VIP	Model 1 (p = 26)	Model 2 (p = 23)	Model 3 (p = 14)	Model 4 (p = 11)	Model 5 (p = 6)
Hylastes attenuatus	2.36	×	×	×	×	x
Hylis olexai	2.15	×	×	×	×	x
Prionus coriarius	2.13	×	×	×	×	x
Dacne sp.	2.11	×	×	×	×	x
Crypturgus cinereus	2.09	×	×	×	×	x
Hylobius abietis	2.08	×	×	×	×	x
Anisotoma humeralis	1.96	×	×	×	×
Wanachia triguttata	1.96	×	×	×	×
Arhopalus rusticus	1.92	×	×	×	×
Rhagium inquisitor	1.89	×	×	×	×
Stenagostus rhombeus	1.88	×	×	×	×
Brachytemnus porcatus	1.77	×	×	×
Aulonothroscus brevicollis	1.66	×	×	×
Thanasimus formicarius	1.66	×	×	×
Mesocoelopus niger	1.51	×	×
Enicmus rugosus	1.50	×	×
Hylurgus ligniperda	1.44	×	×
Cetonia aurata	1.37	×	×
Hylastes angustatus	1.36	×	×
Magdalis memnonia	1.28	×	×
Diaperis boleti	1.27	×	×
Ptinus dubius	1.27	×	×
Anaspis maculata	1.25	×	×
Xyleborus saxesenii	1.06	×
Spondylis buprestoides	1.05	×
Berginus tamarisci	1.04	×
	RMSEP	4.6	4.7	5.9	5.6	5.3
	R²	0.82	0.79	0.71	0.73	0.71
	P	0.061	0.026	0.001	< 0.001	< 0.001