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Canonical Correspondence Analysis in R using the vegan library
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| library(vegan) | |
| library(labdsv) | |
| data(varespec) | |
| data(varechem) | |
| vare.cca <- cca(varespec ~ Baresoil+Humdepth+pH+N+P+K+Ca+Mg+S+Al+Fe, data=varechem) | |
| vare.cca | |
| plot(vare.cca) | |
| summary(vare.cca) | |
| // See also http://ecology.msu.montana.edu/labdsv/R/labs/lab12/lab12.html |
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| > vare.cca | |
| Call: cca(formula = varespec ~ Baresoil + Humdepth + pH + N + P + K + Ca + Mg + S + Al + Fe, data = varechem) | |
| Inertia Proportion Rank | |
| Total 2.0832 1.0000 | |
| Constrained 1.2154 0.5834 11 | |
| Unconstrained 0.8678 0.4166 12 | |
| Inertia is mean squared contingency coefficient | |
| Eigenvalues for constrained axes: | |
| CCA1 CCA2 CCA3 CCA4 CCA5 CCA6 CCA7 CCA8 CCA9 CCA10 CCA11 | |
| 0.410865 0.255619 0.146158 0.131515 0.091575 0.078525 0.060261 0.019134 0.008944 0.006849 0.005946 | |
| Eigenvalues for unconstrained axes: | |
| CA1 CA2 CA3 CA4 CA5 CA6 CA7 CA8 CA9 CA10 CA11 CA12 | |
| 0.253513 0.151934 0.126683 0.093370 0.075393 0.049632 0.037929 0.026435 0.021758 0.014304 0.009052 0.007806 | |
| > plot(vare.cca) | |
| > summary(vare.cca) | |
| Call: | |
| cca(formula = varespec ~ Baresoil + Humdepth + pH + N + P + K + Ca + Mg + S + Al + Fe, data = varechem) | |
| Partitioning of mean squared contingency coefficient: | |
| Inertia Proportion | |
| Total 2.0832 1.0000 | |
| Constrained 1.2154 0.5834 | |
| Unconstrained 0.8678 0.4166 | |
| Eigenvalues, and their contribution to the mean squared contingency coefficient | |
| Importance of components: | |
| CCA1 CCA2 CCA3 CCA4 CCA5 CCA6 CCA7 CCA8 | |
| Eigenvalue 0.4109 0.2556 0.14616 0.13152 0.09158 0.07852 0.06026 0.01913 | |
| Proportion Explained 0.1972 0.1227 0.07016 0.06313 0.04396 0.03769 0.02893 0.00918 | |
| Cumulative Proportion 0.1972 0.3199 0.39009 0.45322 0.49718 0.53488 0.56381 0.57299 | |
| CCA9 CCA10 CCA11 CA1 CA2 CA3 CA4 CA5 | |
| Eigenvalue 0.008944 0.006849 0.005946 0.2535 0.15193 0.12668 0.09337 0.07539 | |
| Proportion Explained 0.004290 0.003290 0.002850 0.1217 0.07293 0.06081 0.04482 0.03619 | |
| Cumulative Proportion 0.577280 0.580570 0.583430 0.7051 0.77805 0.83886 0.88368 0.91988 | |
| CA6 CA7 CA8 CA9 CA10 CA11 CA12 | |
| Eigenvalue 0.04963 0.03793 0.02643 0.02176 0.01430 0.009052 0.007806 | |
| Proportion Explained 0.02382 0.01821 0.01269 0.01044 0.00687 0.004350 0.003750 | |
| Cumulative Proportion 0.94370 0.96191 0.97460 0.98504 0.99191 0.996250 1.000000 | |
| Accumulated constrained eigenvalues | |
| Importance of components: | |
| CCA1 CCA2 CCA3 CCA4 CCA5 CCA6 CCA7 CCA8 | |
| Eigenvalue 0.4109 0.2556 0.1462 0.1315 0.09158 0.07852 0.06026 0.01913 | |
| Proportion Explained 0.3381 0.2103 0.1203 0.1082 0.07535 0.06461 0.04958 0.01574 | |
| Cumulative Proportion 0.3381 0.5484 0.6686 0.7768 0.85218 0.91679 0.96637 0.98211 | |
| CCA9 CCA10 CCA11 | |
| Eigenvalue 0.008944 0.006849 0.005946 | |
| Proportion Explained 0.007360 0.005630 0.004890 | |
| Cumulative Proportion 0.989470 0.995110 1.000000 | |
| Scaling 2 for species and site scores | |
| * Species are scaled proportional to eigenvalues | |
| * Sites are unscaled: weighted dispersion equal on all dimensions | |
| Species scores | |
| CCA1 CCA2 CCA3 CCA4 CCA5 CCA6 | |
| Cal.vul 0.2579826 -0.80872 1.94560 -0.35626 0.697113 -0.74258 | |
| Emp.nig -0.2704679 -0.05299 -0.14437 -0.32584 -0.170125 -0.04192 | |
| Led.pal -0.9762750 -0.37214 -0.06644 -0.75402 -0.697058 0.06306 | |
| Vac.myr -1.3055169 -0.11479 0.17137 0.27104 -0.599337 0.07048 | |
| Vac.vit -0.1929037 0.08757 -0.21288 -0.35303 -0.066669 -0.10932 | |
| Pin.syl 0.2380445 0.22966 0.05686 -0.39593 -0.019382 0.07840 | |
| Des.fle -1.4062903 0.38398 0.39272 0.39030 -0.101391 0.30965 | |
| Bet.pub -0.5960443 -0.95617 -0.72698 -1.67618 -1.588060 -0.32047 | |
| Vac.uli 0.3926825 -0.94198 -0.39399 0.58151 -0.228095 -0.14642 | |
| Dip.mon 0.0229110 -0.49673 -0.89897 -0.40174 -0.174258 -0.26730 | |
| Dic.sp -0.4868957 0.65851 -1.26929 0.02094 1.419951 -0.57922 | |
| Dic.fus -0.4861256 -0.47490 0.52892 -0.51872 0.229919 0.59969 | |
| Dic.pol -0.3223530 -0.20367 -1.05718 -0.83490 -0.119395 -0.73626 | |
| Hyl.spl -1.8827323 0.65465 0.49959 1.53295 -0.308169 0.16247 | |
| Ple.sch -0.9252145 0.28944 0.09530 0.27152 0.053829 -0.02879 | |
| Pol.pil 0.2594323 -0.52462 -0.49858 0.08717 0.163650 0.43618 | |
| Pol.jun -0.7366157 0.12464 -0.27517 -0.14649 -0.314192 0.31794 | |
| Pol.com -0.9458638 -0.14755 -0.27373 -0.71188 -0.855045 -0.28475 | |
| Poh.nut -0.0348872 0.21735 -0.33522 -0.36923 0.179971 -0.30020 | |
| Pti.cil -0.5533110 -0.80045 -0.73937 -1.41351 -1.316239 -0.52927 | |
| Bar.lyc -0.5655746 -1.05360 -0.79808 -1.74760 -1.740288 -0.58626 | |
| Cla.arb 0.3082534 -0.56549 -0.03583 0.08219 -0.096060 -0.13535 | |
| Cla.ran 0.4695611 -0.53152 -0.16623 0.29331 0.037571 0.13895 | |
| Cla.ste 0.7627157 0.70289 0.12199 -0.02713 -0.053315 0.10624 | |
| Cla.unc -0.0840257 -0.04106 -0.16775 -0.54249 0.443329 -0.24384 | |
| Cla.coc 0.1998745 -0.11892 0.05746 -0.11248 0.073434 0.09607 | |
| Cla.cor -0.3377207 0.00630 -0.30418 -0.13082 0.007785 -0.09738 | |
| Cla.gra -0.0591848 -0.14946 -0.27214 -0.18229 0.113776 -0.19158 | |
| Cla.fim -0.0005966 -0.11638 0.03219 -0.27266 -0.185276 0.01141 | |
| Cla.cri -0.2353142 -0.13014 0.04825 -0.44966 -0.082457 -0.30900 | |
| Cla.chl 0.2960198 0.43031 -0.44880 -0.45712 -0.026098 -0.32614 | |
| Cla.bot -0.6121890 -0.67705 -0.17531 -1.05814 -0.701290 -0.74162 | |
| Cla.ama 0.0339234 -0.89659 -1.10581 -0.06753 0.078437 0.24184 | |
| Cla.sp 0.6893702 0.73032 0.49452 -0.39382 0.126202 -0.21620 | |
| Cet.eri 0.2703176 0.10341 -0.30842 -0.06482 0.593267 -0.44989 | |
| Cet.isl 0.1448207 0.10344 -0.31552 -0.70305 -0.482515 -0.22317 | |
| Cet.niv 1.3069886 -0.01489 0.54845 1.61791 -1.099398 -2.15267 | |
| Nep.arc -0.8040582 0.39185 -0.06934 -0.02375 -0.746439 1.04971 | |
| Ste.sp 0.2935602 -1.44392 -0.78477 0.79952 0.694834 0.72962 | |
| Pel.aph -0.6296777 0.05166 -0.34405 -0.15437 -0.058790 -0.21384 | |
| Ich.eri 0.3228067 -1.83898 -0.44899 0.64843 0.595119 0.78301 | |
| Cla.cer 0.9088477 0.22411 0.50813 1.00260 -0.582433 -0.84668 | |
| Cla.def -0.3460925 -0.21145 -0.11090 -0.54258 0.007175 -0.33724 | |
| Cla.phy 0.7223026 1.12784 -0.05001 -0.23188 0.099363 0.06092 | |
| Site scores (weighted averages of species scores) | |
| CCA1 CCA2 CCA3 CCA4 CCA5 CCA6 | |
| 18 0.2368 -1.0455 -0.79083 -0.149031 -0.49251 -0.35212 | |
| 15 -0.9799 -0.2750 0.34407 0.111139 0.63356 0.30849 | |
| 24 -1.0983 0.8478 -2.51016 -0.080535 4.40120 -2.69293 | |
| 27 -1.6399 0.4846 0.31083 1.033926 -0.68668 0.16045 | |
| 23 -0.6573 -0.3813 -0.70171 -0.837942 -0.50965 -0.35934 | |
| 19 -0.2220 0.6886 -0.03737 -0.002568 -0.65742 0.07187 | |
| 22 -1.1371 -0.7562 1.68441 -1.251373 0.68408 1.82825 | |
| 16 -0.7322 -0.9683 1.38438 -0.848066 1.09474 1.52365 | |
| 28 -2.4224 0.8605 0.77192 2.459293 -1.07010 0.02053 | |
| 13 0.5930 -1.4057 2.91790 -0.312366 1.59649 -2.08999 | |
| 14 -0.3296 -0.8773 0.53603 -1.974878 1.81909 -0.90880 | |
| 20 -0.5440 -0.3236 -0.58922 -0.198890 0.30072 -0.50529 | |
| 25 -1.2792 0.4454 -1.17274 -0.360068 1.82086 0.33613 | |
| 7 0.7264 -1.9319 -0.98918 1.155440 -0.49232 -0.08616 | |
| 5 0.9323 -2.3201 -1.39730 2.072908 0.83123 1.69279 | |
| 6 0.7454 -1.2134 -0.56548 0.372969 -0.26442 -0.15445 | |
| 3 1.3118 0.5893 -0.06894 0.401225 -0.39972 0.94502 | |
| 4 1.3726 -0.1616 0.83676 1.878597 -1.28329 -3.05924 | |
| 2 1.3068 1.3075 0.11566 -0.055773 -0.47463 1.05104 | |
| 9 1.1513 1.9030 0.25604 -0.576516 -0.64079 0.50208 | |
| 12 0.9003 1.2149 0.03147 -0.437409 -0.44022 0.54418 | |
| 10 1.2566 1.7341 0.25151 -0.507033 -0.60207 0.74947 | |
| 11 0.4809 0.1232 -0.01664 0.339108 0.09187 0.24062 | |
| 21 -0.8258 -0.3306 -1.27405 -2.712570 -3.96294 -1.33584 | |
| Site constraints (linear combinations of constraining variables) | |
| CCA1 CCA2 CCA3 CCA4 CCA5 CCA6 | |
| 18 -0.51001 -0.86277 -1.265868 -0.84832 0.00585 -0.55362 | |
| 15 -0.11359 0.47962 0.292164 -0.71983 -1.13275 -0.12336 | |
| 24 -0.22365 0.90898 -2.201280 0.15538 2.96165 -1.67268 | |
| 27 -1.64472 0.76232 0.420020 0.74263 -0.06008 0.22434 | |
| 23 -1.32539 -0.30282 -0.919558 -0.37197 0.23629 -0.78394 | |
| 19 -1.07981 0.11303 -0.113499 -0.60422 -0.19793 -1.29585 | |
| 22 -0.80792 -0.42650 1.084574 -0.98064 1.21790 1.50140 | |
| 16 -0.09523 -1.62392 0.407793 -0.06884 -0.07282 0.33619 | |
| 28 -2.23615 0.64537 0.663728 2.48585 -0.46791 0.25333 | |
| 13 0.42015 -1.10098 3.235920 -0.54956 1.29688 -1.38806 | |
| 14 -0.14558 -0.43109 0.310536 -0.84389 0.19863 -0.03026 | |
| 20 -0.46785 0.19132 -0.309976 -1.55804 -0.35312 -0.83013 | |
| 25 -0.94343 0.48338 -0.020181 -0.08962 -0.75201 1.14075 | |
| 7 1.13410 -1.71592 -0.683778 1.28206 -0.45511 -0.70628 | |
| 5 0.46572 -2.30802 -1.130203 1.25890 1.45704 1.70523 | |
| 6 0.86525 0.07408 -0.448437 -0.03867 -0.80286 1.09713 | |
| 3 1.05262 0.42467 -0.654573 0.68815 -1.10660 0.89967 | |
| 4 1.39514 -0.07478 0.728546 1.89627 -1.33345 -2.59477 | |
| 2 1.33321 0.54940 0.492977 0.24130 0.78232 0.74187 | |
| 9 1.29092 1.95150 0.005342 -0.81565 0.26355 0.18074 | |
| 12 0.41778 0.20237 0.558481 -0.57975 -0.17713 0.78064 | |
| 10 0.48239 1.37874 -0.125838 0.29170 0.38215 -0.13758 | |
| 11 0.56717 0.36508 -0.101642 -0.04929 -0.36747 0.15785 | |
| 21 -0.55130 -1.11370 -0.928444 -1.85875 -1.87942 -0.58312 | |
| Biplot scores for constraining variables | |
| CCA1 CCA2 CCA3 CCA4 CCA5 CCA6 | |
| Baresoil -0.52916 -0.39394 -0.08617 -0.48990 -0.17135 -0.47822 | |
| Humdepth -0.74502 0.09330 0.17115 -0.23030 -0.12889 -0.16495 | |
| pH 0.50738 0.14614 -0.26885 0.17600 -0.10593 0.17747 | |
| N -0.18023 -0.58693 0.04837 0.36820 0.15022 0.16997 | |
| P -0.36138 0.63661 0.04617 0.32849 0.17792 -0.38565 | |
| K -0.39232 0.31726 0.55953 0.12491 0.25046 -0.48506 | |
| Ca -0.48559 0.41273 0.01284 -0.06856 0.28471 -0.24271 | |
| Mg -0.45563 0.35145 -0.07675 -0.07944 0.47484 -0.50687 | |
| S -0.03901 0.50851 0.36649 0.02615 0.41656 -0.63216 | |
| Al 0.80742 0.10327 0.25002 0.22841 -0.03898 -0.35763 | |
| Fe 0.67570 0.02563 0.09560 0.24078 -0.08059 -0.04175 |
Hi, do you know why Im getting this error when I run the cca "Error in eval(predvars, data, env) : object 'Turb' not found"
Hi, do you know why Im getting this error when I run the cca "Error in eval(predvars, data, env) : object 'Turb' not found"
it's too late for replying, but if you have an error like that it means that the Turb is not in your R environment yet. Therefore, to solve the problem, make sure that you have already loaded the object Turb and the name in your environment and your script are the same (i.e. Turb or turb) since R is case sensitive.
Thank you for this code.
I am applying this to my data, but I don't get the OTUs and sites names. Any idea on how to resolve this ?
Thank you,
Najoua
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Dear Matthew,
I am thankful for subjects that you present.
I have a question about "Canonical Correspondence Analysis in R using the vegan library".
If it is possible for you please interpret about plot of cca!
I look forward to reply from you
Sincerely