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 = 2 *** Data files *** Species data : SPECIES.DTA Covariable data : DESIGN.DTA Environmental data : DESIGN.DTA Initialization file: Forward selection of envi. variables = 0 Scaling of ordination scores = -1 Diagnostics = 1 File : SPECIES.DTA Title : invertebrate data set chlorpyrifos experiment (Ln(10X+1) transformed van den Br Format : (1X,I5,(T10,7F10.3)) No. of couplets of species number and abundance per line : 0 No samples omitted Number of samples 132 Number of species 178 Number of occurrences 4804 File : DESIGN.DTA Title : PRC analysis: 5 treatment (ds0-ds4: 1-5) and 11 time (Wk-4-Wk24: 6-16) indicato Format : (I5,8(I5,F4.0)) No. of covariables : 16 No interaction terms defined ****************************************************************************** Names of covariables ****************************************************************************** Wk-4 Wk-1 Wk0.1 Wk1 Wk2 Wk4 Wk8 Wk12 Wk15 Wk19 Wk24 ****************************************************************************** File : DESIGN.DTA Title : PRC analysis: 5 treatment (ds0-ds4: 1-5) and 11 time (Wk-4-Wk24: 6-16) indicato Format : (I5,8(I5,F4.0)) No. of environmental variables : 16 *** Interaction terms *** Variable 17 = variable 2 * variable 6 Variable 18 = variable 2 * variable 7 Variable 19 = variable 2 * variable 8 Variable 20 = variable 2 * variable 9 Variable 21 = variable 2 * variable 10 Variable 22 = variable 2 * variable 11 Variable 23 = variable 2 * variable 12 Variable 24 = variable 2 * variable 13 Variable 25 = variable 2 * variable 14 Variable 26 = variable 2 * variable 15 Variable 27 = variable 2 * variable 16 Variable 28 = variable 3 * variable 6 Variable 29 = variable 3 * variable 7 Variable 30 = variable 3 * variable 8 Variable 31 = variable 3 * variable 9 Variable 32 = variable 3 * variable 10 Variable 33 = variable 3 * variable 11 Variable 34 = variable 3 * variable 12 Variable 35 = variable 3 * variable 13 Variable 36 = variable 3 * variable 14 Variable 37 = variable 3 * variable 15 Variable 38 = variable 3 * variable 16 Variable 39 = variable 4 * variable 6 Variable 40 = variable 4 * variable 7 Variable 41 = variable 4 * variable 8 Variable 42 = variable 4 * variable 9 Variable 43 = variable 4 * variable 10 Variable 44 = variable 4 * variable 11 Variable 45 = variable 4 * variable 12 Variable 46 = variable 4 * variable 13 Variable 47 = variable 4 * variable 14 Variable 48 = variable 4 * variable 15 Variable 49 = variable 4 * variable 16 Variable 50 = variable 5 * variable 6 Variable 51 = variable 5 * variable 7 Variable 52 = variable 5 * variable 8 Variable 53 = variable 5 * variable 9 Variable 54 = variable 5 * variable 10 Variable 55 = variable 5 * variable 11 Variable 56 = variable 5 * variable 12 Variable 57 = variable 5 * variable 13 Variable 58 = variable 5 * variable 14 Variable 59 = variable 5 * variable 15 Variable 60 = variable 5 * variable 16 No transformation of species data No species-weights specified No sample-weights specified Centring/standardization by species = 1 Centring/standardization by samples = 0 No. of active samples: 132 No. of passive samples: 0 No. of active species: 178 Total sum of squares in species data = 37858.0 Total standard deviation in species data TAU = 1.26935 Covariable Wk24 is linearly dependent, hence ignored 1 **** Correlation matrix **** SPEC AX1 1.0000 SPEC AX2 .0663 1.0000 SPEC AX3 -.0047 -.1033 1.0000 SPEC AX4 .0102 -.0944 .1280 1.0000 ENVI AX1 .9650 .0000 .0000 .0000 1.0000 ENVI AX2 .0000 .7196 .0000 .0000 .0000 1.0000 ENVI AX3 .0000 .0000 .8052 .0000 .0000 .0000 1.0000 ENVI AX4 .0000 .0000 .0000 .7752 .0000 .0000 .0000 1.0000 ds1*Wk-4 -.0016 .0071 -.2151 -.0803 -.0016 .0099 -.2671 -.1036 ds1*Wk-1 .0106 .0067 .0804 -.0834 .0109 .0093 .0999 -.1076 ds1*Wk0. -.0524 .0306 -.0257 -.1341 -.0543 .0425 -.0319 -.1730 ds1*Wk1 -.1625 .0678 -.1238 -.1791 -.1684 .0942 -.1538 -.2310 ds1*Wk2 -.1104 -.0002 .1545 -.1160 -.1144 -.0002 .1918 -.1497 ds1*Wk4 -.1427 -.0943 .1877 -.1436 -.1478 -.1310 .2332 -.1853 ds1*Wk8 -.0957 -.0936 .3398 -.1857 -.0991 -.1301 .4221 -.2395 ds1*Wk12 -.0643 -.0177 .1921 -.1275 -.0666 -.0245 .2385 -.1644 ds1*Wk15 -.0465 -.0543 .0831 -.0021 -.0481 -.0754 .1032 -.0027 ds1*Wk19 .0000 -.1592 .1028 .0503 .0000 -.2213 .1277 .0649 ds1*Wk24 -.0154 -.1478 .0767 .0830 -.0160 -.2054 .0952 .1071 ds2*Wk-4 .0016 -.0021 .0863 .1905 .0017 -.0029 .1072 .2458 ds2*Wk-1 .0309 .1439 .0212 .1851 .0320 .1999 .0263 .2387 ds2*Wk0. -.0192 .1142 .1352 .0465 -.0199 .1587 .1679 .0599 ds2*Wk1 -.0044 .0736 .2315 .0815 -.0046 .1023 .2875 .1051 ds2*Wk2 -.0062 .1634 .0862 .1535 -.0064 .2271 .1071 .1980 ds2*Wk4 -.0361 .1560 .0780 .1753 -.0374 .2167 .0968 .2261 ds2*Wk8 -.0759 .1228 .1636 .0371 -.0786 .1706 .2032 .0478 ds2*Wk12 .0086 .1308 .1072 -.0559 .0089 .1818 .1332 -.0722 ds2*Wk15 .0001 .1668 .1181 .0653 .0001 .2318 .1466 .0842 ds2*Wk19 -.0148 .1411 .0711 -.0194 -.0153 .1961 .0884 -.0251 ds2*Wk24 .0122 .1447 .0479 .2046 .0126 .2010 .0595 .2639 ds3*Wk-4 .0325 .0190 .1201 -.2166 .0337 .0263 .1491 -.2794 ds3*Wk-1 .0054 -.0009 -.0947 -.2315 .0056 -.0012 -.1176 -.2986 ds3*Wk0. .0751 .0434 -.0764 -.0653 .0778 .0604 -.0949 -.0842 ds3*Wk1 .2418 -.0367 .1356 -.1306 .2505 -.0509 .1685 -.1684 ds3*Wk2 .2061 -.0986 .0305 -.0644 .2135 -.1370 .0379 -.0830 ds3*Wk4 .2250 -.0599 -.0059 .0269 .2332 -.0833 -.0073 .0348 ds3*Wk8 .0784 .0111 .0159 .0695 .0812 .0154 .0198 .0896 ds3*Wk12 .0503 -.1131 -.0547 .0461 .0521 -.1571 -.0679 .0595 ds3*Wk15 .0244 -.1015 .0042 .2677 .0253 -.1411 .0052 .3453 ds3*Wk19 .0409 -.0517 -.0559 .0440 .0424 -.0718 -.0694 .0567 ds3*Wk24 .0222 -.1542 -.0631 -.1359 .0231 -.2142 -.0784 -.1753 ds4*Wk-4 .0229 -.0805 .0517 .0316 .0238 -.1119 .0642 .0408 ds4*Wk-1 .0317 -.0433 .0226 .1474 .0329 -.0602 .0280 .1901 ds4*Wk0. .1754 -.1065 .0372 .1265 .1818 -.1480 .0461 .1631 ds4*Wk1 .2796 -.1762 .0622 .0914 .2898 -.2449 .0772 .1179 ds4*Wk2 .2837 -.1124 -.1091 .0516 .2940 -.1563 -.1355 .0666 ds4*Wk4 .3379 .0250 -.0943 -.1038 .3502 .0347 -.1172 -.1339 ds4*Wk8 .3430 -.0014 -.2051 .0023 .3555 -.0020 -.2548 .0029 ds4*Wk12 .2453 .0766 -.0373 -.0046 .2542 .1064 -.0463 -.0059 ds4*Wk15 .1962 .1487 -.0648 -.1025 .2033 .2066 -.0804 -.1323 ds4*Wk19 .1306 .2908 -.0436 -.1149 .1354 .4040 -.0541 -.1482 ds4*Wk24 .0686 .2347 -.1410 -.1204 .0711 .3261 -.1751 -.1553 SPEC AX1 SPEC AX2 SPEC AX3 SPEC AX4 ENVI AX1 ENVI AX2 ENVI AX3 ENVI AX4 ds1*Wk-4 1.0000 ds1*Wk-1 .0000 1.0000 ds1*Wk0. .0000 .0000 1.0000 ds1*Wk1 .0000 .0000 .0000 1.0000 ds1*Wk2 .0000 .0000 .0000 .0000 1.0000 ds1*Wk4 .0000 .0000 .0000 .0000 .0000 1.0000 ds1*Wk8 .0000 .0000 .0000 .0000 .0000 .0000 1.0000 ds1*Wk12 .0000 .0000 .0000 .0000 .0000 .0000 .0000 1.0000 ds1*Wk15 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds1*Wk19 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds1*Wk24 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds2*Wk-4 -.2000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds2*Wk-1 .0000 -.2000 .0000 .0000 .0000 .0000 .0000 .0000 ds2*Wk0. .0000 .0000 -.2000 .0000 .0000 .0000 .0000 .0000 ds2*Wk1 .0000 .0000 .0000 -.2000 .0000 .0000 .0000 .0000 ds2*Wk2 .0000 .0000 .0000 .0000 -.2000 .0000 .0000 .0000 ds2*Wk4 .0000 .0000 .0000 .0000 .0000 -.2000 .0000 .0000 ds2*Wk8 .0000 .0000 .0000 .0000 .0000 .0000 -.2000 .0000 ds2*Wk12 .0000 .0000 .0000 .0000 .0000 .0000 .0000 -.2000 ds2*Wk15 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds2*Wk19 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds2*Wk24 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds3*Wk-4 -.2000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds3*Wk-1 .0000 -.2000 .0000 .0000 .0000 .0000 .0000 .0000 ds3*Wk0. .0000 .0000 -.2000 .0000 .0000 .0000 .0000 .0000 ds3*Wk1 .0000 .0000 .0000 -.2000 .0000 .0000 .0000 .0000 ds3*Wk2 .0000 .0000 .0000 .0000 -.2000 .0000 .0000 .0000 ds3*Wk4 .0000 .0000 .0000 .0000 .0000 -.2000 .0000 .0000 ds3*Wk8 .0000 .0000 .0000 .0000 .0000 .0000 -.2000 .0000 ds3*Wk12 .0000 .0000 .0000 .0000 .0000 .0000 .0000 -.2000 ds3*Wk15 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds3*Wk19 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds3*Wk24 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds4*Wk-4 -.2000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds4*Wk-1 .0000 -.2000 .0000 .0000 .0000 .0000 .0000 .0000 ds4*Wk0. .0000 .0000 -.2000 .0000 .0000 .0000 .0000 .0000 ds4*Wk1 .0000 .0000 .0000 -.2000 .0000 .0000 .0000 .0000 ds4*Wk2 .0000 .0000 .0000 .0000 -.2000 .0000 .0000 .0000 ds4*Wk4 .0000 .0000 .0000 .0000 .0000 -.2000 .0000 .0000 ds4*Wk8 .0000 .0000 .0000 .0000 .0000 .0000 -.2000 .0000 ds4*Wk12 .0000 .0000 .0000 .0000 .0000 .0000 .0000 -.2000 ds4*Wk15 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds4*Wk19 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds4*Wk24 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds1*Wk-4 ds1*Wk-1 ds1*Wk0. ds1*Wk1 ds1*Wk2 ds1*Wk4 ds1*Wk8 ds1*Wk12 ds1*Wk15 1.0000 ds1*Wk19 .0000 1.0000 ds1*Wk24 .0000 .0000 1.0000 ds2*Wk-4 .0000 .0000 .0000 1.0000 ds2*Wk-1 .0000 .0000 .0000 .0000 1.0000 ds2*Wk0. .0000 .0000 .0000 .0000 .0000 1.0000 ds2*Wk1 .0000 .0000 .0000 .0000 .0000 .0000 1.0000 ds2*Wk2 .0000 .0000 .0000 .0000 .0000 .0000 .0000 1.0000 ds2*Wk4 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds2*Wk8 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds2*Wk12 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds2*Wk15 -.2000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds2*Wk19 .0000 -.2000 .0000 .0000 .0000 .0000 .0000 .0000 ds2*Wk24 .0000 .0000 -.2000 .0000 .0000 .0000 .0000 .0000 ds3*Wk-4 .0000 .0000 .0000 -.2000 .0000 .0000 .0000 .0000 ds3*Wk-1 .0000 .0000 .0000 .0000 -.2000 .0000 .0000 .0000 ds3*Wk0. .0000 .0000 .0000 .0000 .0000 -.2000 .0000 .0000 ds3*Wk1 .0000 .0000 .0000 .0000 .0000 .0000 -.2000 .0000 ds3*Wk2 .0000 .0000 .0000 .0000 .0000 .0000 .0000 -.2000 ds3*Wk4 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds3*Wk8 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds3*Wk12 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds3*Wk15 -.2000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds3*Wk19 .0000 -.2000 .0000 .0000 .0000 .0000 .0000 .0000 ds3*Wk24 .0000 .0000 -.2000 .0000 .0000 .0000 .0000 .0000 ds4*Wk-4 .0000 .0000 .0000 -.2000 .0000 .0000 .0000 .0000 ds4*Wk-1 .0000 .0000 .0000 .0000 -.2000 .0000 .0000 .0000 ds4*Wk0. .0000 .0000 .0000 .0000 .0000 -.2000 .0000 .0000 ds4*Wk1 .0000 .0000 .0000 .0000 .0000 .0000 -.2000 .0000 ds4*Wk2 .0000 .0000 .0000 .0000 .0000 .0000 .0000 -.2000 ds4*Wk4 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds4*Wk8 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds4*Wk12 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds4*Wk15 -.2000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds4*Wk19 .0000 -.2000 .0000 .0000 .0000 .0000 .0000 .0000 ds4*Wk24 .0000 .0000 -.2000 .0000 .0000 .0000 .0000 .0000 ds1*Wk15 ds1*Wk19 ds1*Wk24 ds2*Wk-4 ds2*Wk-1 ds2*Wk0. ds2*Wk1 ds2*Wk2 ds2*Wk4 1.0000 ds2*Wk8 .0000 1.0000 ds2*Wk12 .0000 .0000 1.0000 ds2*Wk15 .0000 .0000 .0000 1.0000 ds2*Wk19 .0000 .0000 .0000 .0000 1.0000 ds2*Wk24 .0000 .0000 .0000 .0000 .0000 1.0000 ds3*Wk-4 .0000 .0000 .0000 .0000 .0000 .0000 1.0000 ds3*Wk-1 .0000 .0000 .0000 .0000 .0000 .0000 .0000 1.0000 ds3*Wk0. .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds3*Wk1 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds3*Wk2 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds3*Wk4 -.2000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds3*Wk8 .0000 -.2000 .0000 .0000 .0000 .0000 .0000 .0000 ds3*Wk12 .0000 .0000 -.2000 .0000 .0000 .0000 .0000 .0000 ds3*Wk15 .0000 .0000 .0000 -.2000 .0000 .0000 .0000 .0000 ds3*Wk19 .0000 .0000 .0000 .0000 -.2000 .0000 .0000 .0000 ds3*Wk24 .0000 .0000 .0000 .0000 .0000 -.2000 .0000 .0000 ds4*Wk-4 .0000 .0000 .0000 .0000 .0000 .0000 -.2000 .0000 ds4*Wk-1 .0000 .0000 .0000 .0000 .0000 .0000 .0000 -.2000 ds4*Wk0. .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds4*Wk1 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds4*Wk2 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds4*Wk4 -.2000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds4*Wk8 .0000 -.2000 .0000 .0000 .0000 .0000 .0000 .0000 ds4*Wk12 .0000 .0000 -.2000 .0000 .0000 .0000 .0000 .0000 ds4*Wk15 .0000 .0000 .0000 -.2000 .0000 .0000 .0000 .0000 ds4*Wk19 .0000 .0000 .0000 .0000 -.2000 .0000 .0000 .0000 ds4*Wk24 .0000 .0000 .0000 .0000 .0000 -.2000 .0000 .0000 ds2*Wk4 ds2*Wk8 ds2*Wk12 ds2*Wk15 ds2*Wk19 ds2*Wk24 ds3*Wk-4 ds3*Wk-1 ds3*Wk0. 1.0000 ds3*Wk1 .0000 1.0000 ds3*Wk2 .0000 .0000 1.0000 ds3*Wk4 .0000 .0000 .0000 1.0000 ds3*Wk8 .0000 .0000 .0000 .0000 1.0000 ds3*Wk12 .0000 .0000 .0000 .0000 .0000 1.0000 ds3*Wk15 .0000 .0000 .0000 .0000 .0000 .0000 1.0000 ds3*Wk19 .0000 .0000 .0000 .0000 .0000 .0000 .0000 1.0000 ds3*Wk24 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds4*Wk-4 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds4*Wk-1 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds4*Wk0. -.2000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds4*Wk1 .0000 -.2000 .0000 .0000 .0000 .0000 .0000 .0000 ds4*Wk2 .0000 .0000 -.2000 .0000 .0000 .0000 .0000 .0000 ds4*Wk4 .0000 .0000 .0000 -.2000 .0000 .0000 .0000 .0000 ds4*Wk8 .0000 .0000 .0000 .0000 -.2000 .0000 .0000 .0000 ds4*Wk12 .0000 .0000 .0000 .0000 .0000 -.2000 .0000 .0000 ds4*Wk15 .0000 .0000 .0000 .0000 .0000 .0000 -.2000 .0000 ds4*Wk19 .0000 .0000 .0000 .0000 .0000 .0000 .0000 -.2000 ds4*Wk24 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds3*Wk0. ds3*Wk1 ds3*Wk2 ds3*Wk4 ds3*Wk8 ds3*Wk12 ds3*Wk15 ds3*Wk19 ds3*Wk24 1.0000 ds4*Wk-4 .0000 1.0000 ds4*Wk-1 .0000 .0000 1.0000 ds4*Wk0. .0000 .0000 .0000 1.0000 ds4*Wk1 .0000 .0000 .0000 .0000 1.0000 ds4*Wk2 .0000 .0000 .0000 .0000 .0000 1.0000 ds4*Wk4 .0000 .0000 .0000 .0000 .0000 .0000 1.0000 ds4*Wk8 .0000 .0000 .0000 .0000 .0000 .0000 .0000 1.0000 ds4*Wk12 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds4*Wk15 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds4*Wk19 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds4*Wk24 -.2000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ds3*Wk24 ds4*Wk-4 ds4*Wk-1 ds4*Wk0. ds4*Wk1 ds4*Wk2 ds4*Wk4 ds4*Wk8 ds4*Wk12 1.0000 ds4*Wk15 .0000 1.0000 ds4*Wk19 .0000 .0000 1.0000 ds4*Wk24 .0000 .0000 .0000 1.0000 ds4*Wk12 ds4*Wk15 ds4*Wk19 ds4*Wk24 N name (weighted) mean stand. dev. inflation factor 1 SPEC AX1 .0000 .3065 2 SPEC AX2 .0000 .2354 3 SPEC AX3 .0000 .1796 4 SPEC AX4 .0000 .1657 5 ENVI AX1 .0000 .2958 6 ENVI AX2 .0000 .1694 7 ENVI AX3 .0000 .1446 8 ENVI AX4 .0000 .1284 17 ds1*Wk-4 .0152 .1222 1.4773 18 ds1*Wk-1 .0152 .1222 1.4773 19 ds1*Wk0. .0152 .1222 1.4773 20 ds1*Wk1 .0152 .1222 1.4773 21 ds1*Wk2 .0152 .1222 1.4773 22 ds1*Wk4 .0152 .1222 1.4773 23 ds1*Wk8 .0152 .1222 1.4773 24 ds1*Wk12 .0152 .1222 1.4773 25 ds1*Wk15 .0152 .1222 1.4773 26 ds1*Wk19 .0152 .1222 1.4773 27 ds1*Wk24 .0152 .1222 1.4773 28 ds2*Wk-4 .0152 .1222 1.4773 29 ds2*Wk-1 .0152 .1222 1.4773 30 ds2*Wk0. .0152 .1222 1.4773 31 ds2*Wk1 .0152 .1222 1.4773 32 ds2*Wk2 .0152 .1222 1.4773 33 ds2*Wk4 .0152 .1222 1.4773 34 ds2*Wk8 .0152 .1222 1.4773 35 ds2*Wk12 .0152 .1222 1.4773 36 ds2*Wk15 .0152 .1222 1.4773 37 ds2*Wk19 .0152 .1222 1.4773 38 ds2*Wk24 .0152 .1222 1.4773 39 ds3*Wk-4 .0152 .1222 1.4773 40 ds3*Wk-1 .0152 .1222 1.4773 41 ds3*Wk0. .0152 .1222 1.4773 42 ds3*Wk1 .0152 .1222 1.4773 43 ds3*Wk2 .0152 .1222 1.4773 44 ds3*Wk4 .0152 .1222 1.4773 45 ds3*Wk8 .0152 .1222 1.4773 46 ds3*Wk12 .0152 .1222 1.4773 47 ds3*Wk15 .0152 .1222 1.4773 48 ds3*Wk19 .0152 .1222 1.4773 49 ds3*Wk24 .0152 .1222 1.4773 50 ds4*Wk-4 .0152 .1222 1.4773 51 ds4*Wk-1 .0152 .1222 1.4773 52 ds4*Wk0. .0152 .1222 1.4773 53 ds4*Wk1 .0152 .1222 1.4773 54 ds4*Wk2 .0152 .1222 1.4773 55 ds4*Wk4 .0152 .1222 1.4773 56 ds4*Wk8 .0152 .1222 1.4773 57 ds4*Wk12 .0152 .1222 1.4773 58 ds4*Wk15 .0152 .1222 1.4773 59 ds4*Wk19 .0152 .1222 1.4773 60 ds4*Wk24 .0152 .1222 1.4773 **** Summary **** Axes 1 2 3 4 Total variance Eigenvalues : .087 .029 .021 .016 1.000 Species-environment correlations : .965 .720 .805 .775 Cumulative percentage variance of species data : 11.2 14.9 17.6 19.7 of species-environment relation: 26.1 34.7 41.0 45.9 Sum of all unconstrained eigenvalues .781 Sum of all canonical eigenvalues .335 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. 1 *** Sample arrangement in permutation test *** Whole plot 1 : 1 13 25 37 49 61 73 85 97 109 121 Whole plot 2 : 2 14 26 38 50 62 74 86 98 110 122 Whole plot 3 : 3 15 27 39 51 63 75 87 99 111 123 Whole plot 4 : 4 16 28 40 52 64 76 88 100 112 124 Whole plot 5 : 5 17 29 41 53 65 77 89 101 113 125 Whole plot 6 : 6 18 30 42 54 66 78 90 102 114 126 Whole plot 7 : 7 19 31 43 55 67 79 91 103 115 127 Whole plot 8 : 8 20 32 44 56 68 80 92 104 116 128 Whole plot 9 : 9 21 33 45 57 69 81 93 105 117 129 Whole plot 10 : 10 22 34 46 58 70 82 94 106 118 130 Whole plot 11 : 11 23 35 47 59 71 83 95 107 119 131 Whole plot 12 : 12 24 36 48 60 72 84 96 108 120 132 These 12 whole plots are permuted completely at random The 11 split plots are not permuted Seeds: 13189 29720 **** Summary of Monte Carlo test **** Test of significance of first canonical axis: eigenvalue = .087 F-ratio = 9.716 P-value = .005 ( 199 permutations under reduced model)