bio<-read.table("cwmbent.txt",header=T)
nrow(bio);ncol(bio);names(bio)
## [1] 45
## [1] 29
## [1] "Mobile"
## [2] "s_Mobile"
## [3] "S_Sessile_Tube"
## [4] "Sessile"
## [5] "Deposi_Detriti"
## [6] "Susp_Filtr"
## [7] "Scavenger_Opport"
## [8] "Herbivore"
## [9] "Predator_Carni"
## [10] "Builder_Tube"
## [11] "Burrowing"
## [12] "Outhers.free_living_in_matriz_sediment.superficials."
## [13] "Epifauna"
## [14] "Superficial"
## [15] "Conveyors"
## [16] "Biodiffusors_Gallery"
## [17] "Size_1"
## [18] "Size_1_3"
## [19] "Size_3_5"
## [20] "Size_5"
## [21] "LS_Short"
## [22] "LS_Medium"
## [23] "LS_Long"
## [24] "LS_Very_long"
## [25] "Plank"
## [26] "Lec"
## [27] "Dir"
## [28] "Praia"
## [29] "Praias"
biot<-bio[1:45,1:27]
result<-rda(biot,abiot)
summary(result)
##
## Call:
## rda(X = biot, Y = abiot)
##
## Partitioning of variance:
## Inertia Proportion
## Total 0.4524 1.0000
## Constrained 0.2339 0.5171
## Unconstrained 0.2185 0.4829
##
## Eigenvalues, and their contribution to the variance
##
## Importance of components:
## RDA1 RDA2 RDA3 RDA4 RDA5 RDA6
## Eigenvalue 0.1448 0.05685 0.01620 0.006178 0.004681 0.002677
## Proportion Explained 0.3202 0.12567 0.03581 0.013656 0.010347 0.005916
## Cumulative Proportion 0.3202 0.44585 0.48166 0.495315 0.505662 0.511579
## RDA7 RDA8 PC1 PC2 PC3 PC4
## Eigenvalue 0.002110 0.0003767 0.07881 0.03506 0.02571 0.01904
## Proportion Explained 0.004665 0.0008328 0.17422 0.07750 0.05684 0.04208
## Cumulative Proportion 0.516243 0.5170761 0.69129 0.76880 0.82564 0.86772
## PC5 PC6 PC7 PC8 PC9 PC10
## Eigenvalue 0.01481 0.01124 0.008018 0.006778 0.005334 0.003036
## Proportion Explained 0.03274 0.02486 0.017725 0.014982 0.011790 0.006712
## Cumulative Proportion 0.90046 0.92531 0.943039 0.958021 0.969811 0.976523
## PC11 PC12 PC13 PC14 PC15 PC16
## Eigenvalue 0.002669 0.002253 0.00166 0.001201 0.0009696 0.0007747
## Proportion Explained 0.005901 0.004980 0.00367 0.002655 0.0021433 0.0017125
## Cumulative Proportion 0.982424 0.987404 0.99107 0.993729 0.9958719 0.9975844
## PC17 PC18 PC19 PC20 PC21
## Eigenvalue 0.0004572 0.0003847 0.0001332 8.018e-05 3.144e-05
## Proportion Explained 0.0010106 0.0008504 0.0002944 1.772e-04 6.950e-05
## Cumulative Proportion 0.9985951 0.9994454 0.9997398 9.999e-01 1.000e+00
## PC22 PC23 PC24
## Eigenvalue 3.321e-06 2.693e-06 7.659e-08
## Proportion Explained 7.342e-06 5.953e-06 1.693e-07
## Cumulative Proportion 1.000e+00 1.000e+00 1.000e+00
##
## Accumulated constrained eigenvalues
## Importance of components:
## RDA1 RDA2 RDA3 RDA4 RDA5 RDA6
## Eigenvalue 0.1448 0.05685 0.01620 0.006178 0.004681 0.002677
## Proportion Explained 0.6192 0.24304 0.06925 0.026409 0.020011 0.011442
## Cumulative Proportion 0.6192 0.86225 0.93151 0.957915 0.977926 0.989368
## RDA7 RDA8
## Eigenvalue 0.002110 0.0003767
## Proportion Explained 0.009021 0.0016106
## Cumulative Proportion 0.998389 1.0000000
##
## Scaling 2 for species and site scores
## * Species are scaled proportional to eigenvalues
## * Sites are unscaled: weighted dispersion equal on all dimensions
## * General scaling constant of scores: 2.11222
##
##
## Species scores
##
## RDA1 RDA2
## Mobile -0.47791 0.1611791
## s_Mobile 0.30157 -0.0563788
## S_Sessile_Tube 0.12231 -0.0093129
## Sessile 0.04793 -0.0809970
## Deposi_Detriti 0.31732 0.0109460
## Susp_Filtr 0.12937 -0.1227082
## Scavenger_Opport 0.02392 -0.0266062
## Herbivore -0.60865 0.0613298
## Predator_Carni 0.14133 0.0739577
## Builder_Tube 0.07201 0.0958005
## Burrowing 0.05817 -0.3586663
## Outhers.free_living_in_matriz_sediment.superficials. -0.13017 0.2628658
## Epifauna 0.06215 -0.1021692
## Superficial -0.11304 0.2949072
## Conveyors 0.07315 -0.0002617
## Biodiffusors_Gallery -0.02255 -0.1927788
## Size_1 -0.08876 0.0738848
## Size_1_3 -0.18937 -0.0229287
## Size_3_5 0.01748 -0.1498142
## Size_5 0.26065 0.0988581
## LS_Short 0.19056 0.1300088
## LS_Medium -0.11100 0.0451269
## LS_Long -0.08530 -0.1349843
## LS_Very_long 0.02287 -0.0260826
## Plank -0.49440 -0.2284135
## Lec 0.22756 0.0685167
## Dir 0.26610 0.1592319
## RDA3 RDA4
## Mobile 0.027527 0.063918
## s_Mobile 0.117330 -0.063587
## S_Sessile_Tube -0.119374 -0.001185
## Sessile -0.022553 0.004888
## Deposi_Detriti 0.016004 0.024612
## Susp_Filtr -0.124077 -0.018421
## Scavenger_Opport 0.016787 -0.007058
## Herbivore 0.012652 0.021208
## Predator_Carni 0.086267 -0.019103
## Builder_Tube -0.127904 0.025824
## Burrowing 0.133756 -0.024708
## Outhers.free_living_in_matriz_sediment.superficials. -0.005852 -0.001115
## Epifauna -0.051531 -0.053673
## Superficial 0.088953 -0.100097
## Conveyors -0.075824 0.019289
## Biodiffusors_Gallery 0.037820 0.134794
## Size_1 -0.023483 -0.028988
## Size_1_3 0.044025 0.012852
## Size_3_5 -0.022475 0.050114
## Size_5 0.001932 -0.033978
## LS_Short -0.126344 0.011426
## LS_Medium 0.127196 0.045683
## LS_Long 0.045924 -0.034652
## LS_Very_long -0.045022 0.012497
## Plank -0.094851 -0.081525
## Lec 0.080016 0.036354
## Dir 0.015184 0.045015
## RDA5 RDA6
## Mobile 0.0324393 -0.025047
## s_Mobile 0.0217685 -0.036198
## S_Sessile_Tube -0.0510055 0.030372
## Sessile -0.0034409 0.024944
## Deposi_Detriti -0.0357567 -0.022095
## Susp_Filtr 0.0520745 0.038002
## Scavenger_Opport 0.0009717 -0.012640
## Herbivore -0.0383294 -0.024678
## Predator_Carni 0.0289027 0.019099
## Builder_Tube -0.0205426 0.026835
## Burrowing -0.0306828 -0.025135
## Outhers.free_living_in_matriz_sediment.superficials. 0.0512254 -0.001700
## Epifauna -0.0451257 0.004685
## Superficial -0.0019357 0.012708
## Conveyors -0.0090340 0.008597
## Biodiffusors_Gallery 0.0562381 -0.026282
## Size_1 0.0336056 -0.006095
## Size_1_3 -0.1138851 0.008049
## Size_3_5 0.0244895 0.021234
## Size_5 0.0557900 -0.023187
## LS_Short -0.0599100 -0.079954
## LS_Medium -0.0264334 0.070056
## LS_Long 0.0114099 0.040896
## LS_Very_long 0.0572790 -0.009500
## Plank 0.0247554 -0.013255
## Lec -0.0148852 -0.032991
## Dir -0.0105993 0.046123
##
##
## Site scores (weighted sums of species scores)
##
## RDA1 RDA2 RDA3 RDA4 RDA5 RDA6
## SA1 -0.58181 0.288116 -0.20900 -1.24642 0.46019 1.03273
## SA2 -0.78457 0.357006 -0.13093 -0.51518 0.35924 0.93345
## SA3 -0.25533 -0.108131 0.44221 0.42182 -0.34189 0.24181
## SA4 -0.07958 -0.266880 0.44517 1.74182 -0.19821 -0.69147
## SA5 -0.30903 0.189964 0.33249 0.69122 0.21450 0.28429
## SB1 -0.59619 0.001105 0.22156 0.37528 0.23073 -0.19583
## SB2 -0.53052 0.296197 0.03606 0.05255 0.09902 0.04839
## SB3 -0.42896 -0.018916 0.22858 0.61467 -0.08742 -0.63615
## SB4 0.13026 -0.042374 0.55190 0.28235 0.18200 0.22990
## SB5 -0.38896 -0.133569 0.23733 0.99305 -0.14949 -0.54492
## SC1 -0.32671 0.388205 -0.47446 -0.46125 -0.33056 -0.22840
## SC2 -0.03560 -0.160411 -0.24504 0.31487 -0.01455 -0.84571
## SC3 -0.66366 0.408046 -0.35695 -0.70102 -0.43306 1.68065
## SC4 -0.62253 0.113502 -0.12313 -0.49712 0.45123 -0.79722
## SC5 0.42906 0.314294 -1.38948 0.83859 -2.62747 0.99209
## CA1 0.40440 0.187983 0.76910 -0.97690 -0.19306 -0.75583
## CA2 0.35229 0.154074 0.54248 -0.27893 0.12831 -0.31300
## CA3 0.19230 0.394234 0.45924 -0.25473 -0.57122 0.55950
## CA4 0.18637 0.464125 1.04346 -0.05562 0.27588 1.60370
## CA5 0.32476 0.324497 0.12132 -0.01648 -0.35947 0.37452
## CB1 0.35215 0.311088 -0.09075 0.23747 0.34549 -0.61291
## CB2 0.42542 0.434464 -0.29341 0.42840 0.16218 -1.88997
## CB3 0.41108 0.401987 0.19306 -0.05802 -0.61872 -0.13464
## CB4 0.39278 0.334953 -0.33394 0.04780 -0.39862 -0.59044
## CB5 0.28801 0.092065 0.32146 -0.31247 -0.22147 0.40381
## CC1 0.23895 -0.022959 -0.72892 0.31985 0.18777 0.76058
## CC2 0.24279 0.372356 -0.12727 0.06701 1.06274 0.30192
## CC3 0.29626 0.311308 -0.48061 0.18134 0.81881 0.78517
## CC4 0.33027 0.420876 -0.38196 0.18819 0.42763 -0.39123
## CC5 0.30359 0.172304 -0.28807 0.13386 0.47040 -0.47795
## TA1 0.27820 -0.565556 0.58091 0.89731 -0.08494 -1.50707
## TA2 0.20102 -0.464302 -0.88520 -0.73577 -0.14279 1.25086
## TA3 0.28616 -0.459254 0.33097 1.18644 0.15723 0.49661
## TA4 0.24973 -0.508291 -0.01564 -0.90330 -0.22328 0.11757
## TA5 0.22311 -0.839186 0.33399 1.06735 -0.76034 -0.86862
## TB1 0.21382 -0.470692 0.22952 -0.36846 -0.18975 0.79333
## TB2 0.29094 -0.446662 0.33497 -0.14811 -0.19020 -0.83809
## TB3 0.09559 -0.504449 -0.77570 0.32812 0.64237 0.99337
## TB4 0.18940 -0.336548 -0.23951 -0.36313 0.05047 0.35721
## TB5 0.13822 -0.705251 -0.17976 -0.61418 -0.08610 0.07039
## TC1 -0.10566 -0.323569 0.29305 -0.97370 0.23384 -0.71343
## TC2 -0.58210 0.049565 0.25329 -0.22123 0.21329 -0.40966
## TC3 -0.23983 -0.492534 -0.37937 0.26773 0.62301 -1.57793
## TC4 -0.31489 -0.146660 0.05926 -0.85178 0.05965 0.01698
## TC5 -0.62098 0.233880 -0.23229 -1.12329 0.36664 0.69164
##
##
## Site constraints (linear combinations of constraining variables)
##
## RDA1 RDA2 RDA3 RDA4 RDA5 RDA6
## SA1 -0.4021 0.09201 0.17599 0.21865 0.09877 0.3602
## SA2 -0.4021 0.09201 0.17599 0.21865 0.09877 0.3602
## SA3 -0.4021 0.09201 0.17599 0.21865 0.09877 0.3602
## SA4 -0.4021 0.09201 0.17599 0.21865 0.09877 0.3602
## SA5 -0.4021 0.09201 0.17599 0.21865 0.09877 0.3602
## SB1 -0.3629 0.02049 0.25509 0.46358 0.05497 -0.2197
## SB2 -0.3629 0.02049 0.25509 0.46358 0.05497 -0.2197
## SB3 -0.3629 0.02049 0.25509 0.46358 0.05497 -0.2197
## SB4 -0.3629 0.02049 0.25509 0.46358 0.05497 -0.2197
## SB5 -0.3629 0.02049 0.25509 0.46358 0.05497 -0.2197
## SC1 -0.2439 0.21273 -0.51781 -0.10119 -0.59088 0.1603
## SC2 -0.2439 0.21273 -0.51781 -0.10119 -0.59088 0.1603
## SC3 -0.2439 0.21273 -0.51781 -0.10119 -0.59088 0.1603
## SC4 -0.2439 0.21273 -0.51781 -0.10119 -0.59088 0.1603
## SC5 -0.2439 0.21273 -0.51781 -0.10119 -0.59088 0.1603
## CA1 0.2920 0.30498 0.58712 -0.31653 -0.14391 0.2938
## CA2 0.2920 0.30498 0.58712 -0.31653 -0.14391 0.2938
## CA3 0.2920 0.30498 0.58712 -0.31653 -0.14391 0.2938
## CA4 0.2920 0.30498 0.58712 -0.31653 -0.14391 0.2938
## CA5 0.2920 0.30498 0.58712 -0.31653 -0.14391 0.2938
## CB1 0.3739 0.31491 -0.04072 0.06864 -0.14623 -0.5648
## CB2 0.3739 0.31491 -0.04072 0.06864 -0.14623 -0.5648
## CB3 0.3739 0.31491 -0.04072 0.06864 -0.14623 -0.5648
## CB4 0.3739 0.31491 -0.04072 0.06864 -0.14623 -0.5648
## CB5 0.3739 0.31491 -0.04072 0.06864 -0.14623 -0.5648
## CC1 0.2824 0.25078 -0.40136 0.17805 0.59347 0.1957
## CC2 0.2824 0.25078 -0.40136 0.17805 0.59347 0.1957
## CC3 0.2824 0.25078 -0.40136 0.17805 0.59347 0.1957
## CC4 0.2824 0.25078 -0.40136 0.17805 0.59347 0.1957
## CC5 0.2824 0.25078 -0.40136 0.17805 0.59347 0.1957
## TA1 0.2476 -0.56732 0.06901 0.30241 -0.21082 -0.1021
## TA2 0.2476 -0.56732 0.06901 0.30241 -0.21082 -0.1021
## TA3 0.2476 -0.56732 0.06901 0.30241 -0.21082 -0.1021
## TA4 0.2476 -0.56732 0.06901 0.30241 -0.21082 -0.1021
## TA5 0.2476 -0.56732 0.06901 0.30241 -0.21082 -0.1021
## TB1 0.1856 -0.49272 -0.12610 -0.23315 0.04536 0.2752
## TB2 0.1856 -0.49272 -0.12610 -0.23315 0.04536 0.2752
## TB3 0.1856 -0.49272 -0.12610 -0.23315 0.04536 0.2752
## TB4 0.1856 -0.49272 -0.12610 -0.23315 0.04536 0.2752
## TB5 0.1856 -0.49272 -0.12610 -0.23315 0.04536 0.2752
## TC1 -0.3727 -0.13586 -0.00121 -0.58045 0.29929 -0.3985
## TC2 -0.3727 -0.13586 -0.00121 -0.58045 0.29929 -0.3985
## TC3 -0.3727 -0.13586 -0.00121 -0.58045 0.29929 -0.3985
## TC4 -0.3727 -0.13586 -0.00121 -0.58045 0.29929 -0.3985
## TC5 -0.3727 -0.13586 -0.00121 -0.58045 0.29929 -0.3985
##
##
## Biplot scores for constraining variables
##
## RDA1 RDA2 RDA3 RDA4 RDA5 RDA6
## Meanmm 0.4006 0.3802 0.4055 0.32868 -0.1760 -0.02846
## Gravel 0.6672 0.6127 0.2584 -0.17405 -0.1029 -0.24076
## Sand -0.6947 -0.5127 -0.1909 0.41154 -0.1373 0.05256
## mo 0.7024 0.1586 0.3554 -0.56501 0.1627 -0.04835
## CaCO3 0.7577 -0.2228 0.2098 -0.49473 0.1935 -0.20735
## MNS -0.4445 -0.5345 0.1183 -0.15249 -0.5333 -0.31802
## MNL 0.3332 -0.4253 0.6256 -0.13139 -0.3497 0.05040
## MLL 0.4308 0.7139 0.5196 -0.08313 -0.1508 -0.04500
plot(result, type = c("text"))
anova(result)
## Permutation test for rda under reduced model
## Permutation: free
## Number of permutations: 999
##
## Model: rda(X = biot, Y = abiot)
## Df Variance F Pr(>F)
## Model 8 0.23392 4.8182 0.001 ***
## Residual 36 0.21846
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
result<-rda(biot~Gravel+mo+MNL,abiot)# usando variável constrained
plot(result, type = c("text"))
anova(result)
## Permutation test for rda under reduced model
## Permutation: free
## Number of permutations: 999
##
## Model: rda(formula = biot ~ Gravel + mo + MNL, data = abiot)
## Df Variance F Pr(>F)
## Model 3 0.13292 5.6863 0.001 ***
## Residual 41 0.31946
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
library(vegan)
abio<-read.table("laisabiot2.txt",header=TRUE)
nrow(abio);ncol(abio);head(abio,2)
## [1] 45
## [1] 9
## Meanmm Gravel Sand mo CaCO3 MNS MNL MLL
## SA1 0.1977082 0.006820706 90.74722 0.7793154 2.026049 15.8 1.276844 10.39545
## SA2 0.1977082 0.006820706 90.74722 0.7793154 2.026049 15.8 1.276844 10.39545
## Praia
## SA1 S
## SA2 S
abiot<-abio[1:45,1:8]
library(BBmisc)
## Warning: package 'BBmisc' was built under R version 4.1.3
##
## Attaching package: 'BBmisc'
## The following object is masked from 'package:base':
##
## isFALSE
abiotn<-normalize(abiot, method = "standardize", range = c(0, 1), margin = 1L, on.constant = "quiet")
library(vegan)
data(mite)
nrow(mite);ncol(mite)
## [1] 70
## [1] 35
group.1 <- c(1,2,4:8,10:15,17,19:22,24,26:30)
group.2 <- c(3,9,16,18,23,25,31:35)
mite.hel.1 <- decostand(mite[,group.1], "hel")
mite.hel.2 <- decostand(mite[,group.2], "hel")
rownames(mite.hel.1) = paste("S",1:nrow(mite),sep="")
rownames(mite.hel.2) = paste("S",1:nrow(mite),sep="")