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 : weeds83.DTA Covariable data : bloctime.dta Environmental data : bloctime.dta Initialization file: Forward selection of envi. variables = 0 Scaling of ordination scores = -1 Diagnostics = 1 File : weeds83.DTA Title : ploughing time experiment B. Post; weeds in 1983 Format : (1X,I5,(T10,11F6.1)) No. of couplets of species number and abundance per line : 0 ***WARNING*** End of file detected in species data when reading names of species and samples No samples omitted Number of samples 12 Number of species 13 Number of occurrences 148 File : bloctime.dta Title : design: 4 blocks and 3 treatments (ploughing times) Format : (1X,I5,(T10,4F2.0, 2X, 3F2.0)) No. of covariables : 7 No interaction terms defined ***** WARNING ***** Missing sample names in file with covariables ************************* ****************************************************************************** Names of covariables ****************************************************************************** block 1 block 2 block 3 block 4 ****************************************************************************** File : bloctime.dta Title : design: 4 blocks and 3 treatments (ploughing times) Format : (1X,I5,(T10,4F2.0, 2X, 3F2.0)) No. of environmental variables : 7 No interaction terms defined ***** WARNING ***** Missing sample names in file with environmental variables ************************* ln(Ay+B)-transformation of species data A = 1.000 B = 1.000 No species-weights specified No sample-weights specified Centring/standardization by species = 1 Centring/standardization by samples = 0 No. of active samples: 12 No. of passive samples: 0 No. of active species: 13 Total sum of squares in species data = 124.466 Total standard deviation in species data TAU = .893230 Covariable block 4 is linearly dependent, hence ignored ****** Collinearity detected when fitting variable 7 ****** 1 **** Correlation matrix **** SPEC AX1 1.0000 SPEC AX2 -.1065 1.0000 SPEC AX3 -.2481 .5203 1.0000 SPEC AX4 .0521 -.3930 .0000 1.0000 ENVI AX1 .9229 .0000 .0000 .0000 1.0000 ENVI AX2 .0000 .7273 .0000 .0000 .0000 1.0000 ENVI AX3 .0000 .0000 .0000 .0000 .0000 .0000 .0000 ENVI AX4 .0000 .0000 .0000 .0000 .0000 .0000 .0000 .0000 pltime 1 .9211 -.0442 .0000 .0000 .9981 -.0608 .0000 .0000 pltime 2 -.5092 -.6066 .0000 .0000 -.5518 -.8340 .0000 .0000 pltime 3 -.4120 .6508 .0000 .0000 -.4464 .8948 .0000 .0000 SPEC AX1 SPEC AX2 SPEC AX3 SPEC AX4 ENVI AX1 ENVI AX2 ENVI AX3 ENVI AX4 pltime 1 1.0000 pltime 2 -.5000 1.0000 pltime 3 -.5000 -.5000 1.0000 pltime 1 pltime 2 pltime 3 N name (weighted) mean stand. dev. inflation factor 1 SPEC AX1 .0000 .4365 2 SPEC AX2 .0000 .3402 3 SPEC AX3 .0000 .3814 4 SPEC AX4 .0000 .2604 5 ENVI AX1 .0000 .4028 6 ENVI AX2 .0000 .2474 7 ENVI AX3 .0000 .0000 8 ENVI AX4 .0000 .0000 5 pltime 1 .3333 .4714 1.3333 6 pltime 2 .3333 .4714 1.3333 7 pltime 3 .3333 .4714 .0000 **** Summary **** Axes 1 2 3 4 Total variance Eigenvalues : .162 .061 .145 .068 1.000 Species-environment correlations : .923 .727 .000 .000 Cumulative percentage variance of species data : 30.1 41.4 68.4 81.0 of species-environment relation: 72.6 100.0 .0 .0 Sum of all unconstrained eigenvalues .539 Sum of all canonical eigenvalues .223 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 *** Specification of blocks *** *** The permutations are conditioned on 3 covariable(s), namely: *** covariable block 1 covariable block 2 covariable block 3 *** Sample arrangement in permutation test *** Samples in block 1 : 1 2 3 The 3 plots are permuted completely at random Samples in block 2 : 4 5 6 The 3 plots are permuted completely at random Samples in block 3 : 7 8 9 The 3 plots are permuted completely at random Samples in block 4 : 10 11 12 The 3 plots are permuted completely at random Seeds: 23239 945 Number of permutations= 999 *** Permutation under reduced model *** No F-ratio F-ratio of axis 1 Data 2.123 2.582 1 .549 .611 2 .483 .549 3 .652 1.089 4 1.577 1.765 5 1.022 1.066 6 .823 .824 7 .841 .921 8 1.525 1.910 9 .749 .896 10 1.185 1.855 11 1.408 1.411 12 .998 1.082 13 1.372 1.512 14 1.273 1.669 15 1.359 1.806 16 .699 .972 17 1.539 1.474 18 1.183 1.445 19 .811 .878 20 1.263 1.636 21 .913 1.008 22 .895 1.087 23 .984 1.641 24 .936 .841 25 1.253 1.531 26 .772 .884 27 .895 1.087 28 .981 1.274 29 .798 1.191 30 .972 1.003 31 .747 1.101 32 1.025 1.636 33 .852 1.339 34 .993 1.134 35 1.216 1.615 36 .633 .851 37 .699 .972 38 1.546 2.003 39 2.227 2.708 40 1.126 1.304 41 1.085 1.020 42 1.546 2.003 43 .810 .849 44 1.329 1.501 45 .749 .896 46 .864 1.423 47 1.472 1.485 48 .731 .819 49 .760 1.135 50 .801 1.103 51 .660 .705 52 1.408 1.411 53 .618 .899 54 1.508 1.686 55 1.372 1.512 56 1.275 1.642 57 .800 .793 58 .889 .998 59 1.130 1.788 60 .933 .960 61 .618 .899 62 1.087 1.232 63 .917 1.038 64 .998 1.082 65 1.253 1.531 66 1.067 1.729 67 .751 1.068 68 1.437 1.725 69 .765 .771 70 2.420 2.682 71 .760 1.135 72 .851 .988 73 .543 .603 74 1.058 1.666 75 .888 1.055 76 1.145 1.774 77 .917 1.038 78 1.036 1.566 79 .998 1.004 80 .973 1.686 81 .802 .879 82 .592 .721 83 1.036 1.566 84 1.185 1.855 85 .739 1.030 86 1.006 1.162 87 .746 1.019 88 1.130 1.788 89 1.072 1.582 90 1.487 1.525 91 .816 1.105 92 .800 .793 93 1.143 1.062 94 .618 .899 95 .818 .888 96 1.893 2.577 97 1.022 1.066 98 1.346 1.617 99 .893 .950 100 .673 .833 101 1.006 1.162 102 1.437 1.725 103 1.037 1.332 104 .889 .998 105 .816 1.105 106 1.332 1.715 107 1.220 1.257 108 1.605 1.549 109 1.253 1.929 110 .673 .833 111 1.192 1.353 112 1.038 1.578 113 1.022 1.066 114 .592 .721 115 2.420 2.682 116 1.067 1.729 117 .755 .821 118 .601 .757 119 1.008 1.026 120 .670 .823 121 .977 1.320 122 1.652 1.679 123 1.054 1.189 124 .984 1.641 125 .939 .920 126 .902 1.373 127 .543 .603 128 1.180 1.234 129 1.067 1.729 130 .749 .896 131 1.346 1.617 132 .731 .819 133 .893 .950 134 1.110 1.842 135 .998 1.082 136 .880 1.077 137 .818 .888 138 .749 .896 139 .858 1.204 140 .739 1.030 141 .699 .972 142 1.006 1.162 143 .889 .806 144 .960 1.184 145 .909 1.208 146 1.332 1.715 147 .810 .849 148 .857 .875 149 .699 .972 150 .683 .750 151 .721 .970 152 2.123 2.582 153 1.145 1.774 154 1.524 1.977 155 .858 1.204 156 .933 .960 157 1.255 1.101 158 1.329 1.501 159 .880 1.077 160 1.487 1.525 161 .893 .950 162 .777 .804 163 1.346 1.617 164 .755 .821 165 1.546 2.003 166 .951 1.258 167 1.484 1.594 168 1.546 2.003 169 .670 .823 170 1.216 1.615 171 .739 1.030 172 .972 1.003 173 1.229 1.578 174 1.216 1.615 175 .936 .841 176 .483 .549 177 .800 .793 178 .678 .694 179 2.227 2.708 180 1.185 1.855 181 .618 .899 182 .819 1.189 183 .661 .679 184 .960 1.184 185 1.253 1.531 186 1.219 1.593 187 .933 .903 188 1.220 1.257 189 .801 1.103 190 1.126 1.304 191 1.244 1.782 192 .868 1.034 193 1.216 1.615 194 .868 1.034 195 .771 .796 196 .892 1.273 197 .811 1.084 198 1.025 1.234 199 1.130 1.788 200 .618 .899 201 .696 1.009 202 .963 1.051 203 .818 .888 204 1.085 1.020 205 1.695 1.646 206 .941 1.384 207 1.570 1.865 208 .592 .721 209 .921 1.448 210 .857 .875 211 1.272 1.289 212 1.527 1.580 213 .933 .903 214 .907 1.148 215 1.110 1.818 216 .549 .611 217 .913 1.008 218 1.025 1.234 219 1.109 1.286 220 .831 .861 221 2.420 2.682 222 .831 .861 223 .776 .805 224 .984 1.641 225 .856 .794 226 1.072 1.582 227 1.272 1.289 228 2.443 2.745 229 .902 1.373 230 1.171 1.494 231 .932 .883 232 .823 .824 233 1.088 1.240 234 .800 .793 235 .977 1.320 236 .661 .679 237 .728 .722 238 .788 1.298 239 .998 1.004 240 1.460 1.430 241 1.220 1.257 242 1.219 1.593 243 .739 1.030 244 .746 1.019 245 1.253 1.531 246 .800 .793 247 1.570 1.865 248 .699 .972 249 1.437 1.725 250 1.244 1.782 251 .696 1.009 252 1.329 1.501 253 .831 .861 254 .932 .883 255 1.253 1.531 256 .951 1.258 257 .749 .896 258 1.695 1.646 259 .811 .878 260 .800 .793 261 .851 .923 262 .913 1.008 263 1.359 1.806 264 .800 .793 265 .921 1.448 266 .851 .988 267 .748 .773 268 1.072 1.582 269 .851 .923 270 .907 1.148 271 .670 .823 272 1.484 1.594 273 .824 1.134 274 1.054 1.189 275 1.275 1.642 276 1.275 1.642 277 .569 .692 278 .800 .793 279 1.437 1.725 280 1.702 1.960 281 1.153 1.089 282 1.219 1.593 283 .777 .804 284 .739 1.030 285 .967 1.249 286 .483 .549 287 1.058 1.231 288 .939 .920 289 .553 .712 290 .748 .773 291 1.526 1.693 292 .915 1.003 293 1.253 1.531 294 .892 1.391 295 1.508 1.686 296 .981 1.274 297 .798 1.191 298 .915 1.003 299 .998 1.004 300 .993 1.134 301 .841 .921 302 .998 1.004 303 .967 1.249 304 .939 .920 305 1.216 1.615 306 1.153 1.089 307 .902 1.373 308 .543 .603 309 .967 1.249 310 1.605 1.549 311 .895 1.087 312 1.109 1.286 313 .936 .841 314 .858 1.204 315 1.058 1.666 316 1.472 1.485 317 1.126 1.304 318 .738 1.039 319 1.373 1.477 320 .973 1.686 321 .941 1.384 322 .993 1.134 323 .962 .865 324 .831 .861 325 1.075 1.209 326 1.085 1.020 327 .930 1.021 328 .921 1.448 329 1.372 1.512 330 .831 .861 331 1.026 1.212 332 .755 .821 333 1.117 1.033 334 1.695 1.646 335 .678 .694 336 1.695 1.646 337 .461 .609 338 1.289 1.532 339 .857 .875 340 .683 .750 341 .998 1.309 342 .856 .794 343 1.088 1.240 344 .637 .632 345 .670 .823 346 .813 .920 347 .777 .804 348 .902 1.373 349 1.220 1.257 350 .973 1.686 351 .771 .796 352 .823 .824 353 1.329 1.501 354 .721 .937 355 .852 1.339 356 1.101 1.614 357 .747 1.101 358 2.252 2.575 359 1.255 1.101 360 .652 1.089 361 .731 .819 362 .852 1.339 363 .933 .903 364 .748 .773 365 .693 .877 366 .721 .970 367 1.460 1.430 368 1.038 1.578 369 1.359 1.806 370 .576 .657 371 .981 1.274 372 1.088 1.240 373 1.893 2.577 374 1.185 1.855 375 .601 .757 376 1.487 1.525 377 1.229 1.578 378 1.263 1.636 379 1.408 1.411 380 .933 .960 381 .858 1.204 382 .601 .757 383 .772 .884 384 .993 1.134 385 .810 .849 386 .889 1.335 387 1.068 1.507 388 .977 1.320 389 1.702 1.960 390 .921 1.032 391 .816 1.105 392 .798 1.191 393 1.253 1.531 394 1.460 1.430 395 .811 .878 396 .998 1.082 397 .693 .877 398 .728 .722 399 1.272 1.289 400 1.067 1.729 401 .868 1.034 402 1.605 1.549 403 1.332 1.715 404 .816 1.105 405 .739 1.030 406 .553 .712 407 1.110 1.842 408 1.329 1.501 409 .811 .878 410 .891 1.306 411 1.068 1.507 412 .939 .920 413 .984 1.641 414 1.006 1.162 415 .893 .950 416 1.568 1.875 417 .731 .819 418 1.183 1.445 419 .793 .817 420 1.408 1.411 421 .939 .920 422 .626 .770 423 2.252 2.575 424 .841 .921 425 1.088 1.240 426 .751 1.068 427 .951 1.211 428 .930 1.021 429 1.332 1.715 430 .744 .756 431 1.068 1.507 432 .921 1.448 433 .977 1.320 434 1.026 1.212 435 .893 .950 436 .813 .880 437 1.487 1.525 438 1.143 1.062 439 2.056 2.586 440 .981 1.274 441 1.088 1.240 442 1.527 1.580 443 1.329 1.501 444 1.006 1.162 445 .802 .879 446 1.110 1.842 447 .592 .721 448 .942 .992 449 1.220 1.257 450 1.605 1.549 451 .818 .888 452 .726 1.195 453 .728 .722 454 .818 .888 455 .721 .970 456 .777 .804 457 1.472 1.485 458 .893 .950 459 1.255 1.101 460 2.056 2.586 461 .895 1.087 462 1.036 1.566 463 .576 .657 464 .618 .899 465 .793 .817 466 1.233 1.280 467 .818 .888 468 .811 .878 469 .772 .884 470 1.192 1.353 471 .788 1.298 472 1.220 1.257 473 1.075 1.209 474 2.227 2.708 475 1.487 1.525 476 1.108 1.277 477 .810 .849 478 .810 .849 479 1.437 1.725 480 2.123 2.582 481 1.016 1.077 482 1.016 1.077 483 1.272 1.289 484 1.109 1.286 485 .880 1.077 486 .721 .970 487 .807 .926 488 .482 .584 489 2.056 2.586 490 .849 1.017 491 .939 .920 492 .895 1.087 493 1.185 1.855 494 .652 1.089 495 .895 1.087 496 .981 1.274 497 .749 .896 498 1.472 1.485 499 1.026 1.212 500 1.408 1.411 501 .673 .833 502 .750 .752 503 .915 1.003 504 .889 .998 505 1.526 1.693 506 1.524 1.977 507 .777 .804 508 1.058 1.666 509 .913 1.008 510 .930 1.021 511 .751 1.068 512 1.359 1.806 513 1.359 1.806 514 1.110 1.842 515 .889 1.335 516 2.227 2.708 517 .559 .692 518 1.171 1.494 519 .917 1.038 520 1.143 1.062 521 1.087 1.232 522 .731 .819 523 1.526 1.693 524 1.145 1.774 525 .800 .793 526 .824 1.134 527 1.539 1.474 528 .933 .903 529 .818 .888 530 1.088 1.240 531 .868 1.034 532 .660 .705 533 .652 .681 534 .831 .861 535 1.077 1.280 536 .746 1.019 537 1.568 1.875 538 .543 .603 539 1.332 1.715 540 .553 .712 541 .807 .926 542 .721 .937 543 .880 1.077 544 .673 .833 545 .813 .920 546 .939 .920 547 .864 1.423 548 .483 .549 549 .592 .721 550 .726 1.195 551 .801 1.103 552 .892 1.391 553 .909 1.208 554 .892 1.391 555 .880 1.077 556 1.373 1.477 557 .750 .752 558 1.025 1.234 559 .981 1.274 560 .993 1.134 561 .902 1.373 562 .652 1.089 563 1.702 1.960 564 .461 .609 565 .936 .841 566 1.016 1.077 567 .902 1.373 568 .851 .988 569 .811 .878 570 .771 .796 571 1.229 1.578 572 1.126 1.304 573 .893 .950 574 2.311 2.691 575 .852 1.339 576 .973 1.686 577 1.472 1.485 578 .738 1.039 579 .744 .756 580 .802 .879 581 .849 1.017 582 .823 .824 583 .849 1.017 584 .841 .921 585 .772 .884 586 1.110 1.818 587 .783 .775 588 1.225 1.215 589 .907 1.148 590 1.153 1.089 591 .824 1.134 592 1.424 1.553 593 .921 1.448 594 .998 1.004 595 1.022 1.066 596 1.484 1.594 597 .984 1.641 598 .856 .794 599 1.695 1.646 600 1.026 1.212 601 1.272 1.289 602 2.443 2.745 603 1.526 1.693 604 2.123 2.582 605 .461 .609 606 .670 .823 607 .800 .793 608 1.067 1.729 609 1.652 1.679 610 .892 1.391 611 1.192 1.353 612 .721 .970 613 .760 1.135 614 1.207 1.321 615 .813 .880 616 .892 1.273 617 1.702 1.960 618 1.359 1.806 619 .933 .960 620 2.420 2.682 621 .813 .880 622 1.244 1.782 623 1.893 2.577 624 .626 .770 625 .998 1.309 626 .482 .584 627 .891 1.306 628 .800 .793 629 1.289 1.532 630 .895 1.087 631 .816 1.105 632 1.346 1.617 633 .868 1.034 634 .748 .773 635 .637 .632 636 .907 1.148 637 1.072 1.582 638 .751 1.068 639 .889 .998 640 .813 .880 641 1.108 1.277 642 .569 .692 643 .963 1.051 644 .921 1.032 645 .800 .793 646 .559 .692 647 1.526 1.693 648 .652 .681 649 1.088 1.240 650 .569 .692 651 .880 1.077 652 1.289 1.532 653 1.241 1.321 654 .893 .950 655 .893 .950 656 .576 .657 657 .661 .679 658 1.126 1.304 659 1.220 1.257 660 1.038 1.578 661 1.087 1.232 662 .461 .609 663 .810 .849 664 .693 .877 665 .683 .750 666 1.022 1.066 667 1.472 1.485 668 1.008 1.026 669 .721 .937 670 1.025 1.636 671 .981 1.274 672 1.272 1.289 673 1.527 1.580 674 .998 1.082 675 .783 .775 676 .549 .611 677 1.072 1.582 678 .984 1.641 679 1.652 1.679 680 .921 1.448 681 .738 1.039 682 1.702 1.960 683 .889 .998 684 .699 .972 685 .960 1.184 686 1.130 1.788 687 .652 .681 688 .744 .756 689 1.893 2.577 690 1.359 1.806 691 .998 1.082 692 .998 1.004 693 2.227 2.708 694 .800 .793 695 1.075 1.209 696 .936 .841 697 .801 1.103 698 .813 .920 699 1.025 1.234 700 .543 .603 701 .851 .923 702 1.225 1.215 703 1.219 1.593 704 .670 .823 705 1.101 1.614 706 .637 .632 707 .889 .806 708 1.346 1.617 709 .592 .721 710 .913 1.008 711 .810 .849 712 .951 1.258 713 .683 .750 714 .811 1.084 715 1.022 1.066 716 .811 1.084 717 .981 1.274 718 1.180 1.234 719 .977 1.320 720 1.372 1.512 721 .993 1.134 722 .673 .833 723 1.408 1.411 724 2.311 2.691 725 .902 1.373 726 .739 1.030 727 .670 .823 728 .731 .819 729 .670 .823 730 1.508 1.686 731 1.702 1.960 732 .893 .950 733 1.088 1.240 734 .892 1.273 735 1.025 1.234 736 .652 .681 737 .771 .796 738 .731 1.075 739 .765 .771 740 1.289 1.532 741 1.219 1.593 742 .748 .773 743 .857 .875 744 1.068 1.507 745 1.652 1.679 746 .721 .970 747 1.185 1.855 748 1.225 1.215 749 1.577 1.765 750 .800 .793 751 .917 1.038 752 1.346 1.617 753 1.255 1.101 754 .941 1.384 755 1.143 1.062 756 .892 1.391 757 .960 1.184 758 1.546 2.003 759 1.026 1.212 760 1.546 2.003 761 .868 1.034 762 1.108 1.277 763 .816 1.105 764 .851 .923 765 1.527 1.580 766 1.153 1.089 767 1.546 2.003 768 1.372 1.512 769 .849 1.017 770 1.702 1.960 771 1.893 2.577 772 .973 1.686 773 .807 .926 774 1.289 1.532 775 .998 1.004 776 .783 .775 777 .823 .824 778 1.241 1.321 779 1.253 1.531 780 .893 .950 781 1.332 1.715 782 .888 1.055 783 1.207 1.321 784 1.110 1.842 785 .483 .549 786 2.123 2.582 787 .696 1.009 788 1.424 1.553 789 .678 .694 790 1.207 1.321 791 1.332 1.715 792 .816 1.105 793 1.220 1.257 794 .626 .770 795 .721 .937 796 1.526 1.693 797 .951 1.211 798 1.130 1.788 799 1.372 1.512 800 .549 .611 801 1.054 1.189 802 .746 1.019 803 1.183 1.445 804 .933 .960 805 .678 .694 806 .543 .603 807 .973 1.686 808 1.539 1.474 809 .731 1.075 810 .553 .712 811 .739 1.030 812 1.054 1.189 813 1.527 1.580 814 1.484 1.594 815 .889 .806 816 .748 .773 817 .888 1.055 818 1.695 1.646 819 .913 1.008 820 .802 .879 821 1.539 1.474 822 2.420 2.682 823 .998 1.309 824 1.272 1.289 825 1.220 1.257 826 1.332 1.715 827 1.373 1.477 828 .721 .970 829 .553 .712 830 .549 .611 831 1.346 1.617 832 .936 .841 833 1.570 1.865 834 .807 .838 835 .915 1.003 836 1.225 1.215 837 .941 1.384 838 2.252 2.575 839 .915 1.003 840 .802 .879 841 .601 .757 842 .760 1.135 843 1.025 1.234 844 .749 .896 845 .652 .681 846 1.346 1.617 847 1.373 1.477 848 1.255 1.101 849 .933 .903 850 .813 .920 851 1.068 1.507 852 .748 .773 853 .951 1.211 854 .856 .794 855 .823 .824 856 1.242 1.063 857 .851 .988 858 .936 .841 859 .807 .838 860 1.695 1.646 861 .739 1.030 862 .972 1.003 863 .921 1.448 864 .889 .998 865 .852 1.339 866 .811 .878 867 .967 1.249 868 .840 .812 869 .952 1.181 870 .921 1.032 871 1.108 1.277 872 2.252 2.575 873 .601 .865 874 1.605 1.549 875 1.346 1.617 876 .856 .794 877 .977 1.320 878 1.192 1.353 879 .652 1.089 880 1.058 1.231 881 .851 .923 882 .800 .793 883 1.108 1.277 884 1.037 1.332 885 .746 1.019 886 .739 1.030 887 .776 .805 888 .984 1.641 889 .543 .603 890 1.527 1.580 891 1.036 1.566 892 .998 1.309 893 .824 1.134 894 .936 .841 895 1.109 1.286 896 .913 1.008 897 .800 .793 898 1.527 1.580 899 .960 1.184 900 .559 .692 901 .981 1.274 902 .731 1.075 903 .652 .681 904 1.255 1.101 905 .731 1.075 906 1.577 1.765 907 1.275 1.642 908 .868 1.034 909 1.108 1.277 910 .932 .883 911 .907 1.148 912 .807 .926 913 1.037 1.332 914 .932 .883 915 .823 .824 916 .856 .794 917 .921 1.032 918 .771 .796 919 1.006 1.162 920 1.546 2.003 921 .852 1.339 922 .601 .865 923 .972 1.003 924 .858 1.204 925 1.372 1.512 926 1.605 1.549 927 .951 1.258 928 1.437 1.725 929 .553 .712 930 .760 1.135 931 1.088 1.240 932 2.227 2.708 933 1.539 1.474 934 1.219 1.593 935 .788 1.298 936 .772 .884 937 1.484 1.594 938 1.460 1.430 939 .744 .756 940 1.437 1.725 941 .909 1.208 942 1.054 1.189 943 .569 .692 944 .933 .960 945 .818 .888 946 1.143 1.062 947 .917 1.038 948 1.054 1.189 949 .807 .926 950 1.372 1.512 951 .893 .950 952 .633 .851 953 .800 .793 954 1.145 1.774 955 1.016 1.077 956 1.006 1.162 957 .771 .796 958 .543 .603 959 .678 .694 960 .749 .896 961 .652 1.089 962 .660 .705 963 .728 .722 964 .543 .603 965 .482 .584 966 1.568 1.875 967 .960 1.184 968 .811 .878 969 .721 .937 970 1.332 1.715 971 1.527 1.580 972 .693 .877 973 1.025 1.234 974 .592 .721 975 .889 .998 976 1.668 2.128 977 .921 1.448 978 .482 .584 979 1.373 1.477 980 1.207 1.321 981 .559 .692 982 1.484 1.594 983 1.702 1.960 984 .747 1.101 985 .772 .884 986 .771 .796 987 1.183 1.445 988 1.037 1.332 989 .852 1.339 990 1.241 1.321 991 1.145 1.774 992 .744 .756 993 .602 .762 994 .841 .921 995 1.058 1.666 996 .892 1.391 997 .981 1.274 998 .601 .865 999 1.273 1.669 P-value .024 .023 (number of permutations= 999) **** Summary of Monte Carlo test **** Test of significance of first canonical axis: eigenvalue = .16 F-ratio = 2.58 P-value = .02 Overall test : Trace = .22 F-ratio = 2.12 P-value = .02 ( 999 permutations under reduced model)