[Mon Feb 02 10:04:17 1998] Log file created [Mon Feb 02 10:04:19 1998] Running CANOCO: [Mon Feb 02 10:04:19 1998] CON file [C:\canoco\samples\STREAMS\forward.con] saved Program CANOCO Version 4.0 September 1997 - written by Cajo J.F. Ter Braak Copyright (c) 1988-1997 Centre for Biometry Wageningen, CPRO-DLO Box 100, 6700 AC Wageningen, the Netherlands. CANOCO performs (partial) (detrended) (canonical) correspondence analysis, principal components analysis and redundancy analysis. CANOCO is an extension of Cornell Ecology program DECORANA (Hill,1979) For explanation of the input/output see the manual or Ter Braak, C.J.F. (1995) Ordination. Chapter 5 in: Data Analysis in Community and Landscape Ecology (Jongman, R.H.G., Ter Braak, C.J.F. and Van Tongeren, O.F.R., Eds) Cambridge University Press, Cambridge, UK, 91-173 pp. *** Type of analysis *** Model Gradient analysis indirect direct hybrid linear 1=PCA 2= RDA 3 unimodal 4= CA 5= CCA 6 ,, 7=DCA 8=DCCA 9 10=non-standard analysis Type analysis number Answer = 5 *** Data files *** Species data : SPECIES.DTA Covariable data : ENVIRONM.DTA Environmental data : ENVIRONM.DTA Initialization file: Forward selection of envi. variables = 1 Scaling of ordination scores = 2 Diagnostics = 3 File : SPECIES.DTA Title : Macro fauna in tributaries of Hierden stream: (ter Braak & Verdonschot, 1995) Format : (I5,6(I5,F6.0)) No. of couplets of species number and abundance per line : 6 No samples omitted Number of samples 40 Number of species 197 Number of occurrences 1269 File : ENVIRONM.DTA Title : Environment data of tributaries of Hierden stream: (ter Braak & Verdonschot, 19 Format : (1X,I5,(T10,7F9.2)) No. of covariables : 29 No interaction terms defined ****************************************************************************** Names of covariables ****************************************************************************** October January April June August ****************************************************************************** File : ENVIRONM.DTA Title : Environment data of tributaries of Hierden stream: (ter Braak & Verdonschot, 19 Format : (1X,I5,(T10,7F9.2)) No. of environmental variables : 29 No interaction terms defined ln(Ay+B)-transformation of species data A = 1.000 B = 1.000 No species-weights specified No sample-weights specified No downweighting of rare species No. of active samples: 40 No. of passive samples: 0 No. of active species: 197 Total inertia in species data= Sum of all eigenvalues of CA = 3.98960 Covariable August is linearly dependent, hence ignored ****** Collinearity detected when fitting variable 19 ****** ****** Check on influence in covariable/environment data ****** The following sample(s) have extreme values Sample Environmental Covariable + Environment space variable Influence influence influence 6 13 6.7x 9 2 5.1x 11 7 5.8x 14 3 15.7x 14 8 8.6x 16 7 7.7x 20 9 5.3x 31 10 6.5x 33 9 7.2x 38 10 12.8x 40 4 8.5x 40 6 5.0x ****** End of check ****** **** Start of forward selection of variables **** *** Unrestricted permutation *** Seeds: 23239 945 N Name Extra fit 22 Silt .07 3 St_Depth .08 15 Grassy .08 21 FineDetr .09 13 CSubstrt .09 8 C-Submer .11 20 CorsDetr .11 4 Velocity .12 9 C-Emers .12 7 C-Algae .13 16 HangWeed .13 10 C-BankV .13 17 HighWeed .14 2 St_Width .14 12 Grainsiz .14 14 Shading .15 11 TCoverV .16 6 Discharg .17 5 EC .20 1 SourcDis .22 19 NoShrubs .25 18 Shrubs .25 Environmental variable 18 tested Number of permutations= 199 *** Permutation under reduced model *** P-value .0050 (variable 18; F-ratio= 2.66; number of permutations= 199) Environmental variable 18 added to model Variance explained by the variables selected: .25 " " " all variables : 2.34 N Name Extra fit 3 St_Depth .07 22 Silt .07 15 Grassy .08 21 FineDetr .08 13 CSubstrt .10 20 CorsDetr .10 14 Shading .11 17 HighWeed .11 8 C-Submer .11 9 C-Emers .11 7 C-Algae .11 2 St_Width .11 10 C-BankV .12 16 HangWeed .12 12 Grainsiz .12 11 TCoverV .12 4 Velocity .13 5 EC .16 6 Discharg .17 1 SourcDis .19 Environmental variable 1 tested Number of permutations= 199 *** Permutation under reduced model *** P-value .0050 (variable 1; F-ratio= 2.10; number of permutations= 199) Environmental variable 1 added to model Variance explained by the variables selected: .44 " " " all variables : 2.34 N Name Extra fit 13 CSubstrt .06 22 Silt .07 3 St_Depth .07 15 Grassy .08 21 FineDetr .08 4 Velocity .09 11 TCoverV .09 20 CorsDetr .10 9 C-Emers .10 7 C-Algae .10 17 HighWeed .10 2 St_Width .10 8 C-Submer .11 14 Shading .11 10 C-BankV .11 16 HangWeed .12 12 Grainsiz .12 5 EC .18 6 Discharg .19 Environmental variable 6 tested Number of permutations= 199 *** Permutation under reduced model *** P-value .0050 (variable 6; F-ratio= 2.18; number of permutations= 199) Environmental variable 6 added to model Variance explained by the variables selected: .63 " " " all variables : 2.34 N Name Extra fit 13 CSubstrt .06 3 St_Depth .06 22 Silt .07 15 Grassy .08 21 FineDetr .08 4 Velocity .09 8 C-Submer .09 11 TCoverV .09 17 HighWeed .10 7 C-Algae .10 20 CorsDetr .10 16 HangWeed .10 2 St_Width .10 14 Shading .10 9 C-Emers .10 10 C-BankV .11 12 Grainsiz .12 5 EC .13 Environmental variable 5 tested Number of permutations= 199 *** Permutation under reduced model *** P-value .0250 (variable 5; F-ratio= 1.47; number of permutations= 199) Environmental variable 5 added to model Variance explained by the variables selected: .75 " " " all variables : 2.34 N Name Extra fit 3 St_Depth .06 13 CSubstrt .07 22 Silt .07 21 FineDetr .08 15 Grassy .08 20 CorsDetr .09 4 Velocity .09 8 C-Submer .09 2 St_Width .09 17 HighWeed .10 11 TCoverV .09 7 C-Algae .10 14 Shading .10 12 Grainsiz .10 16 HangWeed .11 10 C-BankV .11 9 C-Emers .11 Environmental variable 9 tested Number of permutations= 199 *** Permutation under reduced model *** P-value .0950 (variable 9; F-ratio= 1.28; number of permutations= 199) Environmental variable 9 added to model Variance explained by the variables selected: .86 " " " all variables : 2.34 N Name Extra fit 3 St_Depth .06 13 CSubstrt .07 22 Silt .08 21 FineDetr .08 20 CorsDetr .08 11 TCoverV .08 15 Grassy .09 8 C-Submer .09 14 Shading .09 4 Velocity .09 17 HighWeed .09 2 St_Width .09 7 C-Algae .10 12 Grainsiz .10 10 C-BankV .11 16 HangWeed .11 Environmental variable 16 tested Number of permutations= 199 *** Permutation under reduced model *** P-value .0550 (variable 16; F-ratio= 1.37; number of permutations= 199) Environmental variable 16 added to model Variance explained by the variables selected: .98 " " " all variables : 2.34 N Name Extra fit 13 CSubstrt .07 3 St_Depth .07 22 Silt .08 21 FineDetr .08 4 Velocity .08 20 CorsDetr .09 17 HighWeed .09 15 Grassy .09 11 TCoverV .09 8 C-Submer .09 2 St_Width .09 12 Grainsiz .10 7 C-Algae .10 14 Shading .10 10 C-BankV .12 Environmental variable 10 tested Number of permutations= 199 *** Permutation under reduced model *** P-value .0450 (variable 10; F-ratio= 1.39; number of permutations= 199) Environmental variable 10 added to model Variance explained by the variables selected: 1.09 " " " all variables : 2.34 N Name Extra fit 3 St_Depth .06 13 CSubstrt .07 22 Silt .08 20 CorsDetr .08 4 Velocity .08 21 FineDetr .08 15 Grassy .09 11 TCoverV .09 17 HighWeed .09 7 C-Algae .09 2 St_Width .09 12 Grainsiz .10 8 C-Submer .10 14 Shading .10 Environmental variable 22 omitted Environmental variable 21 omitted Environmental variable 20 omitted Environmental variable 17 omitted Environmental variable 15 omitted Environmental variable 14 omitted Environmental variable 13 omitted Environmental variable 12 omitted Environmental variable 11 omitted Environmental variable 8 omitted Environmental variable 7 omitted Environmental variable 4 omitted Environmental variable 3 omitted Environmental variable 2 omitted ****** Collinearity detected when fitting variable 19 ****** 1 **** Weighted correlation matrix (weight = sample total) **** SPEC AX1 1.0000 SPEC AX2 .0023 1.0000 SPEC AX3 .0502 .0027 1.0000 SPEC AX4 -.0418 .0607 -.0560 1.0000 ENVI AX1 .9718 .0000 .0000 .0000 1.0000 ENVI AX2 .0000 .9559 .0000 .0000 .0000 1.0000 ENVI AX3 .0000 .0000 .9118 .0000 .0000 .0000 1.0000 ENVI AX4 .0000 .0000 .0000 .9170 .0000 .0000 .0000 1.0000 SourcDis .5120 -.6341 -.4533 .0116 .5268 -.6634 -.4971 .0127 EC -.4434 -.7726 .0740 -.1216 -.4562 -.8083 .0812 -.1326 Discharg .0671 -.8028 -.4276 .0033 .0691 -.8399 -.4690 .0036 C-Emers -.2346 .2042 .2301 .3179 -.2414 .2136 .2523 .3466 C-BankV -.2179 -.0465 .4230 .4206 -.2243 -.0487 .4639 .4587 HangWeed -.3698 -.0018 -.1417 -.0948 -.3805 -.0019 -.1554 -.1034 Shrubs .7185 .1525 .1474 -.3990 .7394 .1595 .1617 -.4351 NoShrubs -.7185 -.1525 -.1474 .3990 -.7394 -.1595 -.1617 .4351 SPEC AX1 SPEC AX2 SPEC AX3 SPEC AX4 ENVI AX1 ENVI AX2 ENVI AX3 ENVI AX4 SourcDis 1.0000 EC .3124 1.0000 Discharg .8740 .6777 1.0000 C-Emers -.3823 -.1247 -.2589 1.0000 C-BankV -.2374 .2667 -.1185 -.1717 1.0000 HangWeed .0259 .4592 .2352 .2047 .1347 1.0000 Shrubs .2671 -.3148 -.0463 -.1511 -.1957 -.0460 1.0000 NoShrubs -.2671 .3148 .0463 .1511 .1957 .0460 -1.0000 1.0000 SourcDis EC Discharg C-Emers C-BankV HangWeed Shrubs NoShrubs N name (weighted) mean stand. dev. inflation factor 1 SPEC AX1 .0000 1.0290 2 SPEC AX2 .0000 1.0462 3 SPEC AX3 .0000 1.0967 4 SPEC AX4 .0000 1.0905 5 ENVI AX1 .0000 1.0000 6 ENVI AX2 .0000 1.0000 7 ENVI AX3 .0000 1.0000 8 ENVI AX4 .0000 1.0000 1 SourcDis 976.3687 501.3077 21.8108 5 EC 343.0267 203.0193 7.2170 6 Discharg 85.8973 50.8544 31.6101 9 C-Emers 13.0417 28.7105 1.8912 10 C-BankV 3.9067 7.9610 1.6052 16 HangWeed .6159 .4864 2.2851 18 Shrubs .1647 .3709 1.9936 19 NoShrubs .8353 .3709 .0000 **** Summary **** Axes 1 2 3 4 Total inertia Eigenvalues : .356 .173 .165 .126 3.990 Species-environment correlations : .972 .956 .912 .917 Cumulative percentage variance of species data : 10.4 15.5 20.3 24.0 of species-environment relation: 32.7 48.5 63.6 75.1 Sum of all unconstrained eigenvalues 3.411 Sum of all canonical eigenvalues 1.091 The sum of all unconstrained eigenvalues is after fitting covariables Percentages are taken with respect to residual variances i.e. variances after fitting covariables *** MESSAGE *** The fit for species is additional to the fit due to covariables. With covariables, CANOCO cannot calculate residuals for samples. [Mon Feb 02 10:04:50 1998] CANOCO call succeeded