Trait_based_Fungi_Ecology
## 'data.frame': 31 obs. of 45 variables:
## $ X : int 1 2 3 4 5 6 7 8 9 10 ...
## $ strainID : chr "A" "C11" "C13" "C21" ...
## $ newID : chr "RLCS21" "RLCS23" "RLCS06" "RLCS26" ...
## $ Phylum : chr "Ascomycota" "Ascomycota" "Ascomycota" "Ascomycota" ...
## $ Species : chr "Pyrenochaetopsis_leptospora" "Paramyrothecium_sp." "Chaetomium_angustispirale1" "Tetracladium_apiense" ...
## $ extension : num -0.862 -0.811 1.511 -0.934 0.577 ...
## $ density : num 1.014 0.372 -0.798 0.989 -0.467 ...
## $ biomassst : num -0.0289 -0.2348 0.5766 -0.4953 0.9904 ...
## $ biomassopt : num 0.478 -0.26 1.065 -0.691 1.129 ...
## $ biomasscomplC: num 0.305 -0.211 1.028 -0.356 0.227 ...
## $ hyphal_diam : num 3.96 4.84 4.39 4.3 4.57 ...
## $ melanin : num 0.449 0.209 0.173 0.31 0.246 ...
## $ water_cont : num 0.904 0.864 0.759 0.823 0.773 ...
## $ hydrop : num 0 53.3 39.6 0 51.7 ...
## $ DNAc : num 108.9 36.7 189.4 19.5 79.2 ...
## $ PLFAc : num 32526 16246 21798 15757 23154 ...
## $ stoich_C_XPC1: num -1.23 0.579 1.299 -1.941 2.714 ...
## $ stoich_N_XPC1: num 0.3188 1.6917 -1.1405 -1.1095 -0.0798 ...
## $ stoich_N_XPC2: num -0.534 -0.577 0.104 -0.169 -0.371 ...
## $ C_cont : num 46.9 50.9 46.6 44.4 52.7 ...
## $ enz_la : num 0.00535 3.91857 0.00944 10.49831 0.01295 ...
## $ enz_leu : num 1.4357 0.6278 0.5993 0.5332 0.0865 ...
## $ enz_cel : num 2.312 1.04 0.304 1.476 1.078 ...
## $ enz_pho : num 1.482 0.418 0.237 0.1 0.455 ...
## $ complC_use : num 1.73 1.64 2.52 1.53 1.73 ...
## $ enz_C_div : int 5 5 3 6 5 7 5 3 5 2 ...
## $ spore_abund : num -1.639 0.961 0.886 -1.639 -0.854 ...
## $ spore_shape : num 3.83 1.7 1.33 1.97 2.77 ...
## $ spore_size : num 8.6 16.5 41 41.9 88 ...
## $ spore_RRx : num 0 0.335 1.337 0 12.175 ...
## $ stoich_flex : num 0.625 0.514 0.082 0.328 0.602 0.645 0.344 0.183 0.433 0.415 ...
## $ recycling : num 4.11 5.07 2.39 2.46 3.75 ...
## $ asegurl : num 0.0717 0.2313 -0.0939 0.1454 0.1191 ...
## $ WA_explor : num -0.12518 -0.11072 -0.27802 -0.03186 0.00505 ...
## $ comp_glu : num -1.478 -0.377 2.167 -1.76 2.794 ...
## $ fungic_str : num -4.5515 -7.0901 0.3719 -3.6662 0.0854 ...
## $ cu_str : num -0.984 -0.122 -0.548 -0.474 -0.242 ...
## $ drought_str : num -3.704 -4.335 -1.372 -1.814 -0.777 ...
## $ stress_tolav : num -0.8939 -0.387 0.4809 0.0508 0.8679 ...
## $ stress_tolPC1: num -1.2518 -1.3136 1.0154 0.0135 1.4083 ...
## $ soil_aggreg : num 6.07 7.7 5.05 8.87 4.94 ...
## $ leaf_decomp : num 33.7 40.5 33.3 37.5 25.9 ...
## $ wood_decomp : num 8.54 8.34 60.35 1.4 1.76 ...
## $ decompPC1 : num 0.767 1.075 1.792 0.172 -0.297 ...
## $ CUE : num 0.785 0.526 0.809 0.65 0.731 ...#removing NA rows
traits_data<-na.omit(traits_data)
#extract trait variables and trait matrix
fungal_traits <- colnames(traits_data)[6:45]
#exclude Species column
trait_matrix <- traits_data[,fungal_traits]For PCA (and clustering based on Euclidean distance), it’s crucial to scale the traits so that they are comparable. Typically we scale each trait to mean 0 and standard deviation 1 (also known as z-scores).
# Scale the trait variables (exclude Species column)
trait_data_scaled <- scale(trait_matrix)
# Check that scaling worked:
colMeans(trait_data_scaled,na.rm = TRUE) # should be ~0 for each trait## extension density biomassst biomassopt biomasscomplC
## 1.982541e-17 -1.586033e-17 6.195441e-18 6.542386e-17 -3.766828e-17
## hyphal_diam melanin water_cont hydrop DNAc
## -9.278292e-16 7.137148e-17 -4.310044e-15 1.744636e-16 2.299748e-16
## PLFAc stoich_C_XPC1 stoich_N_XPC1 stoich_N_XPC2 C_cont
## 3.965082e-16 3.965082e-18 1.090398e-17 2.379049e-17 -2.652640e-15
## enz_la enz_leu enz_cel enz_pho complC_use
## 3.271193e-17 -9.317943e-17 -5.551115e-17 -7.930164e-18 -1.744636e-16
## enz_C_div spore_abund spore_shape spore_size spore_RRx
## 2.379049e-16 -7.137148e-17 -1.546382e-16 -1.903239e-16 1.313433e-17
## stoich_flex recycling asegurl WA_explor comp_glu
## 3.172066e-17 3.608225e-16 3.568574e-17 9.516197e-17 7.930164e-18
## fungic_str cu_str drought_str stress_tolav stress_tolPC1
## -1.110223e-16 7.930164e-18 9.119689e-17 7.930164e-18 3.766828e-17
## soil_aggreg leaf_decomp wood_decomp decompPC1 CUE
## -2.374093e-16 -8.946217e-17 4.559845e-17 2.354268e-17 -5.253734e-16## extension density biomassst biomassopt biomasscomplC
## 1 1 1 1 1
## hyphal_diam melanin water_cont hydrop DNAc
## 1 1 1 1 1
## PLFAc stoich_C_XPC1 stoich_N_XPC1 stoich_N_XPC2 C_cont
## 1 1 1 1 1
## enz_la enz_leu enz_cel enz_pho complC_use
## 1 1 1 1 1
## enz_C_div spore_abund spore_shape spore_size spore_RRx
## 1 1 1 1 1
## stoich_flex recycling asegurl WA_explor comp_glu
## 1 1 1 1 1
## fungic_str cu_str drought_str stress_tolav stress_tolPC1
## 1 1 1 1 1
## soil_aggreg leaf_decomp wood_decomp decompPC1 CUE
## 1 1 1 1 1We will use the base R function prcomp() for PCA. (There are other functions like princomp() or PCA in packages, but prcomp is straightforward and uses singular value decomposition for numerical stability.) Since we already scaled the data, we can tell prcomp not to scale again. However, for demonstration we could also let prcomp do the scaling by setting scale. = TRUE. Here we’ll use the scaled data we prepared:
##
## Attaching package: 'plotly'## The following object is masked from 'package:ggplot2':
##
## last_plot## The following object is masked from 'package:stats':
##
## filter## The following object is masked from 'package:graphics':
##
## layoutlibrary(ggfortify)
# Perform PCA on the scaled trait data
pca_result <- prcomp(trait_data_scaled, center = FALSE, scale. = FALSE)
# Print PCA summary
summary(pca_result)## Importance of components:
## PC1 PC2 PC3 PC4 PC5 PC6 PC7
## Standard deviation 2.706 2.2613 2.0964 1.81593 1.63245 1.56868 1.42489
## Proportion of Variance 0.183 0.1278 0.1099 0.08244 0.06662 0.06152 0.05076
## Cumulative Proportion 0.183 0.3109 0.4207 0.50318 0.56980 0.63132 0.68208
## PC8 PC9 PC10 PC11 PC12 PC13 PC14
## Standard deviation 1.38862 1.28079 1.1593 1.13254 1.06571 0.99139 0.8989
## Proportion of Variance 0.04821 0.04101 0.0336 0.03207 0.02839 0.02457 0.0202
## Cumulative Proportion 0.73029 0.77130 0.8049 0.83696 0.86536 0.88993 0.9101
## PC15 PC16 PC17 PC18 PC19 PC20 PC21
## Standard deviation 0.85213 0.81201 0.69095 0.64784 0.54129 0.51352 0.49076
## Proportion of Variance 0.01815 0.01648 0.01194 0.01049 0.00732 0.00659 0.00602
## Cumulative Proportion 0.92828 0.94477 0.95670 0.96719 0.97452 0.98111 0.98713
## PC22 PC23 PC24 PC25 PC26 PC27
## Standard deviation 0.39044 0.35417 0.31475 0.28769 0.18069 0.14954
## Proportion of Variance 0.00381 0.00314 0.00248 0.00207 0.00082 0.00056
## Cumulative Proportion 0.99094 0.99408 0.99656 0.99862 0.99944 1.00000
## PC28
## Standard deviation 2.579e-15
## Proportion of Variance 0.000e+00
## Cumulative Proportion 1.000e+00#The summary(pca_result) will show the proportion of variance explained by each principal component (PC). Because we collected fungal traits based on 28 species (traits data has 28 dimensions), we will get 28 PCs. We expect the first one or two to explain most of the variance. For instance, you might see something like “PC1 – X% Proportion of variance, PC2 – Y% variance,...” etc.#We can also examine the PCA loadings and scores:
#- Loadings (also called rotation in prcomp output) tell us how each trait contributes to each principal component. These are found in pca_result$rotation.
#- Scores (coordinates of each species on the PCs) are in pca_result$x. Each row corresponds to a species, and columns are PC1, PC2, etc. These tell us where each species lies in the new reduced-dimensional space.
# PCA loadings (how traits map to PCs):
pca_result$rotation## PC1 PC2 PC3 PC4
## extension 0.3093250343 -0.034397086 0.1061346626 -0.0981583479
## density -0.2501731673 0.010758071 -0.1779388670 0.0918878820
## biomassst 0.1827288791 0.229679051 -0.2477558121 -0.0605262464
## biomassopt 0.2060661430 0.267784721 -0.1829408699 -0.0290037756
## biomasscomplC 0.0617979554 0.205776789 0.2299072648 -0.1179843753
## hyphal_diam 0.0573643384 0.131536497 -0.1480271941 -0.1611048828
## melanin -0.1911917782 -0.003211710 -0.0432702647 0.0443906915
## water_cont -0.0287075677 -0.220180907 0.0015857089 0.2505528976
## hydrop 0.0770143637 0.051171761 -0.0358596090 -0.0594312935
## DNAc 0.1789877637 -0.131544870 -0.0295199373 0.1788457248
## PLFAc 0.0659997049 -0.130560085 0.0080413941 -0.1365646247
## stoich_C_XPC1 -0.0002417941 0.080830661 -0.1781676723 -0.3149102542
## stoich_N_XPC1 0.0216885555 0.124674976 -0.2281778068 -0.0136677757
## stoich_N_XPC2 0.1127625269 -0.235119951 -0.0217025816 -0.2382364176
## C_cont 0.0530780480 -0.158435655 -0.2538512042 -0.2033194502
## enz_la -0.1424251924 -0.017244831 0.1762843542 -0.0284190764
## enz_leu 0.1514284754 -0.152907550 0.1133937609 0.0143674665
## enz_cel -0.2307336998 0.038537567 0.1230207971 0.2208670106
## enz_pho -0.0154273213 -0.032221656 -0.0509674220 0.0737595509
## complC_use -0.0597999274 0.193912092 0.3331865151 0.0510548647
## enz_C_div -0.1126922293 0.141597049 0.0090438639 0.3498320662
## spore_abund 0.2153895338 -0.018401694 0.0008401137 0.0853396738
## spore_shape 0.0309120058 0.235367986 -0.1734426945 0.0192321409
## spore_size 0.1405162726 0.231326571 -0.0739838075 -0.1799213133
## spore_RRx 0.1610770087 -0.099435772 -0.0145227111 -0.1033100477
## stoich_flex 0.1056109838 0.111452979 -0.2646056887 0.2757799255
## recycling 0.0534603102 -0.051704435 -0.2690437073 0.1171834722
## asegurl -0.1005255109 0.096426358 -0.3158563892 0.1127178629
## WA_explor -0.1445954382 -0.056417858 -0.1382235699 0.1289803402
## comp_glu 0.3041589622 0.126915735 0.0687282656 -0.0443680021
## fungic_str 0.2477732959 -0.115322871 0.0096310534 0.1157930055
## cu_str 0.1206897470 -0.100974802 0.0842669493 0.1619486422
## drought_str 0.2046104151 0.197282945 0.0957155963 0.2003954356
## stress_tolav 0.2953120634 -0.009798532 0.0977103064 0.2463901384
## stress_tolPC1 0.3004600998 0.016231116 0.0808413874 0.2255162672
## soil_aggreg -0.1160290002 0.231417026 -0.0468728741 0.0968162909
## leaf_decomp -0.0450319303 0.374180075 0.0616913981 -0.0005674858
## wood_decomp -0.0356340132 0.139035923 0.2967338095 -0.1303120291
## decompPC1 -0.0548251074 0.315600156 0.1748350752 -0.0707384456
## CUE 0.0666714187 0.068757155 -0.0552578540 0.2154954645
## PC5 PC6 PC7 PC8 PC9
## extension -0.07170982 -0.153482370 -0.068103826 -0.014676302 0.113361154
## density -0.02941407 0.320622092 -0.071829552 -0.014789669 0.077565096
## biomassst 0.02697841 0.075444207 0.036825361 -0.110843448 0.198308144
## biomassopt 0.01074806 -0.072478597 0.028303389 -0.039496929 0.111278387
## biomasscomplC 0.06332883 -0.034224417 -0.064003543 -0.189723128 0.136655882
## hyphal_diam -0.01707490 -0.270016978 -0.210642583 0.186232579 -0.117908974
## melanin 0.01566304 0.273754000 -0.293449007 -0.095263301 0.047257053
## water_cont -0.24935188 -0.144492130 -0.092364773 -0.021573452 -0.059717362
## hydrop -0.15076311 -0.037191875 0.533046900 -0.008316421 -0.072250144
## DNAc -0.11098168 0.012918415 -0.238440748 -0.002414607 -0.334377983
## PLFAc -0.36921879 0.103786469 -0.158932148 0.214111837 -0.093253816
## stoich_C_XPC1 0.09840526 -0.233274260 -0.047520046 -0.056251996 -0.006426632
## stoich_N_XPC1 -0.07374229 -0.268933354 -0.167785117 0.121439054 -0.256453201
## stoich_N_XPC2 0.01244551 -0.029272890 -0.021861749 0.056609720 0.139979425
## C_cont 0.02717980 -0.026402156 0.014330746 -0.248984165 -0.180675502
## enz_la 0.34597472 -0.280413727 0.008628059 0.218294111 -0.070749968
## enz_leu -0.18972254 0.061966753 0.131801669 0.361797478 0.242451350
## enz_cel -0.02960094 -0.252811831 -0.112172854 0.007272740 -0.082730968
## enz_pho -0.39129545 -0.317331069 -0.105554139 -0.198356476 -0.013938988
## complC_use 0.16233922 -0.085135476 -0.051812826 0.071144714 -0.152314702
## enz_C_div 0.09724754 -0.056413873 0.127448297 0.208911137 0.059811545
## spore_abund -0.10426899 0.107725734 0.259367940 0.123276069 -0.093456226
## spore_shape -0.02953314 -0.084792834 -0.009445653 0.272491374 -0.065100610
## spore_size 0.24348748 0.124794583 -0.159330650 0.080878939 -0.057242272
## spore_RRx 0.26086732 0.202278089 0.138642338 -0.089775717 -0.242978081
## stoich_flex -0.01558236 0.076797329 0.176440300 0.115066782 -0.004770606
## recycling 0.04910634 0.119850190 0.009736300 -0.028348843 -0.319488368
## asegurl -0.11352702 -0.036358039 0.068986201 -0.058458060 0.137669349
## WA_explor 0.03363256 -0.210423548 0.084275133 -0.317483990 0.315023188
## comp_glu -0.13431568 -0.108243167 -0.049264195 -0.053114930 -0.003802497
## fungic_str 0.06198627 0.085073372 -0.254140651 -0.183152397 0.139189526
## cu_str 0.13355391 -0.127490629 0.274993192 -0.188386471 -0.346681434
## drought_str -0.01153760 0.060726612 -0.124325165 0.164529306 0.142005569
## stress_tolav 0.09481888 0.009435044 -0.053320763 -0.106674668 -0.033745946
## stress_tolPC1 0.06421120 0.057166245 -0.163635489 -0.065811684 0.084696381
## soil_aggreg -0.02414137 0.228578087 -0.168530232 -0.074856543 -0.223662908
## leaf_decomp -0.17265170 0.027122186 0.082273484 -0.029762672 -0.043728945
## wood_decomp -0.23855155 0.102432624 0.047547069 -0.283050736 -0.133631280
## decompPC1 -0.25546209 0.091229449 0.085205048 -0.164131406 -0.095185696
## CUE 0.17963056 -0.198667956 0.005531144 -0.243578886 0.084772700
## PC10 PC11 PC12 PC13 PC14
## extension -0.075489026 0.107773869 -0.0864313205 0.083569536 -0.030210402
## density 0.019179334 -0.109208954 0.0892607461 0.032796547 -0.134786344
## biomassst -0.010722862 0.140834296 0.1565707115 0.029567700 0.125268861
## biomassopt -0.132399972 0.108342767 0.0636847870 -0.001310938 -0.055655938
## biomasscomplC -0.066139420 -0.299536064 0.0691939798 -0.248953839 -0.193137395
## hyphal_diam 0.099368331 0.005483981 -0.2027405434 0.101390108 0.386235050
## melanin -0.058229285 0.141150635 0.0498639320 0.012375028 -0.307891131
## water_cont -0.127721899 -0.324841412 -0.0785998906 -0.104957919 -0.014407856
## hydrop 0.194673300 0.232772949 0.2207541905 0.054780605 -0.149839083
## DNAc 0.207759987 0.157204509 0.1737546536 0.062742428 -0.041737635
## PLFAc -0.027905530 0.297000007 0.2067725976 -0.130266764 0.011199815
## stoich_C_XPC1 0.042079306 -0.205802293 0.1806496798 0.196146277 -0.203184479
## stoich_N_XPC1 0.230254800 -0.129588282 0.1371671614 0.036617474 -0.320745135
## stoich_N_XPC2 0.249047881 0.049244910 -0.1985522925 0.015865162 -0.403347012
## C_cont 0.188784388 -0.214109317 0.2318695798 -0.166056786 0.068571664
## enz_la -0.047222408 0.064407561 -0.0003614703 -0.073438979 0.045174458
## enz_leu -0.014084078 -0.039337079 -0.1493220327 -0.117157599 -0.204208356
## enz_cel 0.175737727 0.151464611 0.0988999795 -0.102381914 -0.083352575
## enz_pho -0.105102113 0.127200484 0.0135563123 -0.253854814 0.021275677
## complC_use -0.065029817 -0.020198357 0.2323718564 0.154684026 -0.165888823
## enz_C_div 0.229661805 -0.037466950 0.2445813824 -0.035031462 0.074153509
## spore_abund 0.050972155 -0.266635215 0.0942046729 0.451494056 0.042728543
## spore_shape -0.364550459 -0.179596809 -0.0679956684 -0.138146506 -0.295017183
## spore_size 0.126986285 0.187530582 -0.0727858279 -0.154104145 0.112049607
## spore_RRx 0.085153376 0.039061633 -0.0428645619 -0.433894999 -0.161673384
## stoich_flex -0.050717219 -0.069574859 0.1583587019 -0.330217256 0.032448418
## recycling -0.398699124 0.035977128 -0.1009743229 0.257312483 -0.108484129
## asegurl 0.135434252 0.154585123 -0.2786986717 0.002104860 0.016621356
## WA_explor 0.231673482 -0.068971569 -0.1154045026 0.113124026 -0.130901028
## comp_glu -0.033447129 -0.078006143 -0.1507640700 0.024810299 -0.076074349
## fungic_str -0.032313192 -0.194288862 0.2256210741 -0.006022119 0.165442851
## cu_str 0.006853603 0.024461218 -0.3117756739 -0.077900684 -0.027041864
## drought_str 0.227415611 0.099467666 -0.0622714972 0.059123912 -0.161533768
## stress_tolav 0.104070514 -0.036257394 -0.0764858612 -0.012779185 -0.011920616
## stress_tolPC1 0.111164494 -0.058766464 0.0305634109 0.011253179 0.004728043
## soil_aggreg 0.213107688 -0.041194349 -0.3712764857 0.100629299 -0.074740843
## leaf_decomp 0.045595059 -0.163453262 -0.1101774301 -0.138554406 0.082278658
## wood_decomp -0.035738646 0.116582617 0.0742844654 0.149711455 -0.069664722
## decompPC1 0.030921504 -0.052986367 -0.0192603309 -0.075245883 0.053097533
## CUE -0.295717332 0.360278219 0.0690717281 0.077381016 -0.150503348
## PC15 PC16 PC17 PC18 PC19
## extension -0.148394577 -0.016255420 0.12298377 -0.131493890 -0.09672951
## density 0.047567665 -0.135364124 0.03881290 0.194039652 0.16862561
## biomassst 0.053971448 0.018016678 0.10167770 -0.101961018 -0.09280847
## biomassopt 0.189074191 -0.047047187 0.20165881 -0.023907578 -0.16431398
## biomasscomplC -0.188412769 0.187640127 0.23651488 0.266441341 0.16296527
## hyphal_diam -0.280659542 0.069257084 -0.01480565 0.234604257 0.24404653
## melanin -0.505747279 -0.132804468 0.02851474 -0.116609876 -0.01367264
## water_cont 0.174893441 -0.155192205 0.33441859 -0.168305871 0.08780658
## hydrop -0.200796969 -0.130784698 0.14766039 0.176309145 0.01105276
## DNAc 0.238077210 0.199100642 0.18636732 0.076271874 0.17491563
## PLFAc 0.106338662 -0.259747449 -0.14727325 -0.115024790 -0.12630809
## stoich_C_XPC1 0.129686498 -0.439371430 -0.13648984 0.024231776 0.15013110
## stoich_N_XPC1 -0.196841232 0.154447709 0.04887410 -0.186152768 0.06078566
## stoich_N_XPC2 0.212854456 0.192534205 0.24453755 0.025156251 -0.27802713
## C_cont 0.007303824 0.122291121 -0.02011625 -0.254385170 0.05791167
## enz_la 0.125806254 -0.036680730 0.10038004 0.026267480 -0.15234093
## enz_leu -0.178660960 0.097504828 0.14176920 -0.045700646 0.24269855
## enz_cel 0.049550959 -0.124321840 -0.02601026 0.216557480 -0.07286576
## enz_pho -0.147605534 0.133596819 -0.13422445 0.326788320 -0.27516795
## complC_use -0.028765999 -0.066553783 0.08914479 0.006271704 0.03706787
## enz_C_div -0.161896995 0.065309781 0.14925558 -0.226992189 -0.23004557
## spore_abund 0.013156755 0.183711489 -0.08279533 0.288299912 -0.08930645
## spore_shape 0.203549597 -0.067573082 -0.10625913 0.203345654 -0.15110284
## spore_size -0.085005307 -0.076743002 0.27335224 0.110126687 -0.13390084
## spore_RRx 0.051167233 0.039021559 -0.23102973 0.129772224 0.03931172
## stoich_flex -0.059647090 0.051234854 -0.10814798 0.087103663 0.10055097
## recycling -0.202668721 0.013966933 0.11899508 -0.029656209 -0.25007846
## asegurl 0.105163370 -0.242401290 0.30224007 0.130802848 0.28931681
## WA_explor -0.058210979 0.005300561 -0.20804748 0.022497605 -0.24189551
## comp_glu -0.168759084 -0.064334351 -0.25710000 -0.189878515 0.06862852
## fungic_str -0.009970353 -0.098934845 0.16891141 0.169860716 -0.15118785
## cu_str -0.126077383 -0.302287369 0.08340300 -0.074176054 0.01539349
## drought_str 0.100976266 -0.059768310 -0.30651153 -0.041353550 0.09960366
## stress_tolav -0.018072776 -0.237554298 -0.02792847 0.027997515 -0.01864954
## stress_tolPC1 0.021088597 -0.168478043 -0.04927177 0.064713664 -0.03394141
## soil_aggreg 0.114769543 0.190658994 -0.05774585 0.047223827 -0.12775217
## leaf_decomp 0.116751034 -0.001293392 0.03263755 -0.321390247 -0.07460280
## wood_decomp 0.091471248 -0.036276109 0.08035387 0.118988793 0.09314379
## decompPC1 0.045833970 0.033068364 0.07089752 -0.101042019 -0.07132191
## CUE 0.157840055 0.333713787 -0.06049362 -0.144532323 0.34866650
## PC20 PC21 PC22 PC23
## extension 0.3129165684 0.061176907 -0.2047325612 0.058030305
## density 0.0108925477 0.190264529 0.1298314123 0.141760791
## biomassst -0.1057894637 -0.027720663 -0.0602914203 -0.303186982
## biomassopt 0.0464874488 0.136359234 0.0567485426 0.048231732
## biomasscomplC -0.0142114292 -0.307632845 -0.0007120972 0.008247317
## hyphal_diam -0.3191513917 0.300369302 0.0193472382 0.197084643
## melanin -0.1996344416 0.087927605 -0.1328298216 -0.083402351
## water_cont -0.1104035783 0.080421901 -0.0258179588 -0.156498740
## hydrop 0.1073510833 0.031152194 0.0527091274 0.143603637
## DNAc -0.1697677470 0.078758424 -0.0566959495 0.076706544
## PLFAc -0.2137272204 -0.104798331 0.0735768746 -0.132304375
## stoich_C_XPC1 -0.0518396846 0.072401297 -0.1677756271 -0.109069958
## stoich_N_XPC1 0.1717249285 -0.191546424 0.3331666132 -0.025524673
## stoich_N_XPC2 -0.2092584952 0.049025939 0.1278778532 0.178651786
## C_cont 0.0453111769 0.011477397 -0.2975312114 -0.100615622
## enz_la -0.2753848014 -0.293538718 -0.1934971020 -0.200721455
## enz_leu -0.0785679645 0.221192830 -0.2056343149 -0.283180950
## enz_cel 0.3052861867 0.148095561 -0.2535391337 -0.102106785
## enz_pho -0.0339194156 -0.089898299 -0.0728873023 -0.006708475
## complC_use -0.2334810442 0.005894692 -0.0015496817 0.014947645
## enz_C_div -0.0005735552 0.227890801 -0.2391026672 0.138931110
## spore_abund -0.1096853214 -0.041242883 -0.1712991444 -0.240633177
## spore_shape 0.0723977613 0.277093290 -0.0226735171 0.049017104
## spore_size 0.0297377994 0.109761275 0.1052382420 -0.302435737
## spore_RRx -0.1214462911 0.132399126 -0.3109235790 0.180954648
## stoich_flex -0.1592561564 -0.128453728 0.2146233623 -0.214557525
## recycling -0.1161854869 -0.231139008 -0.2061001106 0.195231927
## asegurl -0.0221707101 -0.342971042 -0.3168328643 0.098969717
## WA_explor -0.3581064949 0.130996489 0.0802979982 -0.116919162
## comp_glu 0.0268443001 0.022911901 -0.1545774511 -0.046839486
## fungic_str 0.0342122101 0.112508536 -0.0093906427 0.086125405
## cu_str -0.0332907548 0.114722606 0.2643619311 -0.148907217
## drought_str -0.0536800852 -0.264460382 -0.0629304591 0.126514773
## stress_tolav -0.0271871947 -0.019184702 0.0989610885 0.032842407
## stress_tolPC1 -0.0172377395 -0.053002143 0.0217210303 0.090202570
## soil_aggreg 0.2131945115 0.037021477 -0.0934938220 -0.330012299
## leaf_decomp -0.1440321768 0.037187508 -0.0406511369 0.295571488
## wood_decomp -0.0568273824 0.116245866 -0.0004808500 -0.118024607
## decompPC1 -0.2432919592 0.041600120 -0.0474175123 0.011225302
## CUE -0.0596522791 0.178063717 0.0068595551 -0.058205603
## PC24 PC25 PC26 PC27 PC28
## extension 0.149330999 0.03917975 0.171729400 0.178522458 0.069303020
## density 0.054409366 0.22849834 -0.112795175 0.078346803 0.116525258
## biomassst 0.043895140 0.06208521 0.026801734 -0.083494615 -0.006499856
## biomassopt 0.508680086 -0.12242990 0.167934535 0.050669196 0.039450739
## biomasscomplC -0.124832174 -0.02462702 -0.007996599 -0.093591775 -0.059059937
## hyphal_diam 0.023662237 -0.05768855 0.046264879 -0.023117910 0.195661278
## melanin 0.240951289 0.04277244 -0.214318601 0.007216021 0.071387466
## water_cont 0.059224224 -0.31699710 -0.101841345 -0.045699696 0.393812492
## hydrop -0.257064219 -0.08310595 -0.184791695 0.199802562 0.285409691
## DNAc -0.056046011 -0.05660314 -0.015419599 0.070051189 -0.424007670
## PLFAc -0.144991279 0.16327438 0.102403642 0.110564935 0.106205941
## stoich_C_XPC1 -0.025165458 0.06392533 -0.109297421 -0.196065668 -0.239326960
## stoich_N_XPC1 0.103096515 0.26288643 0.250310106 -0.024964551 0.074521655
## stoich_N_XPC2 0.017786330 -0.05824846 -0.275626790 -0.025359932 -0.032321175
## C_cont -0.120990682 -0.08312289 -0.027400014 -0.027857503 0.258292681
## enz_la -0.024270009 0.27799261 -0.057183050 0.130410842 0.142021397
## enz_leu -0.056260300 0.16012437 0.209209772 -0.088648489 -0.131843477
## enz_cel 0.186615437 -0.15793892 -0.146247855 -0.066720610 -0.136724093
## enz_pho 0.066776772 0.15262880 -0.125495106 -0.117292708 0.045567306
## complC_use 0.077772389 -0.20091453 0.137007205 0.408275239 0.093683786
## enz_C_div -0.186622856 0.06974803 0.081774069 -0.204402475 -0.087314006
## spore_abund 0.285756875 0.17816462 -0.200705115 -0.043366323 0.105454368
## spore_shape -0.293830926 0.04814884 0.064234382 0.000330318 0.063571457
## spore_size -0.185811875 -0.17331386 -0.178839850 -0.147427423 0.032980106
## spore_RRx 0.226964974 0.04157483 0.235705758 0.041705582 0.116576421
## stoich_flex 0.095544406 -0.24844582 -0.032270045 0.170314084 -0.195861035
## recycling -0.175020395 -0.17241687 0.095379983 -0.177882885 -0.099788647
## asegurl -0.016733593 0.11999388 0.122864231 0.167661759 -0.051150497
## WA_explor -0.141765106 -0.13670469 0.320291093 0.143202591 -0.043270232
## comp_glu -0.140401123 -0.15308327 -0.295392990 0.361066189 -0.224214097
## fungic_str -0.160455286 0.25451167 0.050093108 0.233879423 -0.021444084
## cu_str 0.084643263 0.20930055 -0.035700771 -0.118956735 -0.126589761
## drought_str -0.002464051 -0.21376316 -0.016925375 -0.322877257 0.251067774
## stress_tolav -0.040336660 0.12885347 -0.001305306 -0.107161642 0.092426997
## stress_tolPC1 -0.081315760 0.08733106 0.013066972 -0.066611878 0.114922652
## soil_aggreg -0.144323267 0.06406402 0.053107727 0.257901752 0.146397693
## leaf_decomp 0.040114061 0.20502932 -0.200034228 0.072255002 -0.043819502
## wood_decomp -0.120933563 -0.08667035 0.353374338 -0.227489823 0.039505226
## decompPC1 0.066305170 0.11595341 -0.052790251 -0.114885898 -0.086429659
## CUE -0.139543968 0.21235194 -0.206796512 -0.035241475 0.183459160# PCA scores (species coordinates on PCs):
pca_scores <- pca_result$x
head(pca_scores, 10) # print scores for all 28 species (or use head if more cases)## PC1 PC2 PC3 PC4 PC5 PC6
## 1 -3.0229119 0.7832240 -1.0704963 1.0993658 -1.83401439 0.1407392
## 2 -1.8898007 0.6973651 -1.3005611 -0.4237364 -1.09980147 0.1864548
## 3 3.0344693 2.1311768 3.2795914 -1.9217677 0.06668774 0.1404638
## 4 -2.8431077 0.5078057 0.4699731 1.2754967 0.93076944 1.7193397
## 5 3.0605572 1.7857013 -1.7076977 -0.4918964 1.88562487 -0.4419365
## 6 0.3050325 2.8881513 -1.9531963 0.4557535 1.15938317 0.7937637
## 7 -2.3207886 1.9586536 0.9701876 1.2760880 0.14293571 1.3602899
## 8 -3.4117893 0.6581091 2.5671509 -0.8165280 -1.21532235 1.2803043
## 9 -0.8825861 0.1522947 0.6992069 -2.8186312 -2.48557639 2.6453037
## 10 1.8649040 -2.3691809 -1.3296108 -0.9072384 0.56449197 0.1462576
## PC7 PC8 PC9 PC10 PC11 PC12
## 1 -1.14903260 0.2163463 0.8399626 -2.6052885 0.6060996 0.7751050
## 2 2.62983822 0.1691776 -1.6757698 0.9238685 -1.4874226 -0.8160976
## 3 0.25927281 -2.0206993 0.4216301 -0.8701783 1.0139641 1.2025125
## 4 -0.49719226 0.2300597 1.0042976 0.5210144 0.2112051 -2.0045261
## 5 0.75729699 -1.4398451 0.5055648 0.4544844 0.7536120 0.9046143
## 6 2.05251983 0.8451850 1.0817046 -0.8384801 -0.1843635 0.4869635
## 7 -1.08841243 -2.6559832 -0.4378768 0.4983780 0.4981169 -1.0659714
## 8 0.86927708 -0.9917911 -0.4661090 0.8470619 0.3376407 -1.6983069
## 9 0.08490064 3.1018738 -0.1325203 0.8658623 -0.3485545 1.7301808
## 10 0.15097672 -1.0441830 -0.3707654 -2.2061480 1.8101128 -1.0388972
## PC13 PC14 PC15 PC16 PC17 PC18
## 1 -2.44094755 -1.4316919 0.1630345 0.7718117 -0.2725293 -0.22451611
## 2 0.29793723 0.1278812 -0.9555837 -0.7662876 0.1917387 -0.33783511
## 3 2.03213922 -0.5185504 0.5883320 -0.1167542 0.2060058 -0.09891873
## 4 -0.69977093 0.3322925 0.1438754 -0.4540071 -0.4293299 -0.65472030
## 5 -1.49506595 -0.7764491 -0.5192922 -2.2392163 -1.1530103 -0.24898536
## 6 0.18521256 -0.1236898 -0.2215801 0.9016237 0.6775013 0.15313146
## 7 -0.72027160 -0.8434581 -0.2497464 -0.2352693 1.9432471 -0.13063592
## 8 0.03913913 -0.4559673 1.5024020 0.2955213 -1.4851752 1.35316029
## 9 -1.15679343 1.4115578 0.3670263 -0.6202966 0.4503323 0.54143248
## 10 -0.44804094 1.9519039 -1.0981328 0.8836161 0.1433979 1.29840729
## PC19 PC20 PC21 PC22 PC23 PC24
## 1 -0.137830447 -0.488116139 0.141225089 0.13542191 0.08250209 0.66004763
## 2 0.007633300 -0.006430238 -1.095910473 0.24020001 -0.01561278 0.73529917
## 3 0.418266016 -0.275923641 -0.030430163 -0.22078052 0.59526437 0.41926011
## 4 -0.375134823 0.326510762 -0.127963835 0.79368652 0.92543556 -0.35473455
## 5 -0.314710102 -0.182630114 -0.006846175 -0.50851309 0.18622501 -0.28386849
## 6 -0.766939085 0.706698409 -0.211119096 -0.10034011 -0.13287804 0.04703948
## 7 1.035041739 -0.415662784 -0.130623999 -0.02274266 -0.39036715 -0.37464226
## 8 0.281199204 0.553637069 -0.001648870 -0.42453674 -0.08923158 0.15624344
## 9 0.318954804 -0.762395106 -0.029347893 -0.20780739 0.18731792 -0.25619231
## 10 -0.008587554 0.098068555 -0.118864190 -0.05890683 0.22619827 -0.16375244
## PC25 PC26 PC27 PC28
## 1 -0.01293496 -0.10293118 -0.02801499 -2.648323e-15
## 2 0.15252354 -0.13460762 0.22166960 -3.017169e-15
## 3 0.56840747 0.13227009 -0.02287826 -2.936076e-15
## 4 0.39900101 0.09290918 -0.10765631 -3.421403e-15
## 5 -0.26851976 -0.02681633 0.15534723 -2.994198e-15
## 6 -0.28043537 0.60298588 0.01481264 -3.222360e-15
## 7 -0.13327892 0.09010276 0.08663081 -2.746349e-15
## 8 -0.38042453 0.02587866 -0.04373034 -2.503336e-15
## 9 0.04957301 0.11282164 -0.02604501 -2.242911e-15
## 10 0.11249253 -0.12516898 0.24308826 -2.428262e-15# Next, let’s visualize the PCA results.
# Basic PCA biplot (PC1 vs PC2):
biplot(pca_result, scale = 0)
# Using autoplot to visualise:
p <- autoplot(pca_result, data = traits_data, colour = "Species",
loadings = TRUE, loadings.colour = 'blue',
loadings.label = TRUE, loadings.label.size = 3)
p
# Compute Euclidean distance on scaled data
dist_matrix <- dist(trait_data_scaled, method = "euclidean")
# Perform hierarchical clustering using Ward's method
hc <- hclust(dist_matrix, method = "ward.D2") # ward.D2 is Ward's in hclust
# Plot the dendrogram
plot(hc, labels = traits_data$strainID, main="Hierarchical Clustering of Fungi (Ward's method)")
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 22 23 24 25 26 27
## 1 1 2 1 2 1 1 1 1 3 3 3 2 1 2 2 2 1 3 1 2 1 1 1 1 2
## 28 30
## 1 1# See which species are in which cluster
data.frame(Species = traits_data$newID, Cluster = cluster_membership)## Species Cluster
## 1 RLCS21 1
## 2 RLCS23 1
## 3 RLCS06 2
## 4 RLCS26 1
## 5 RLCS07 2
## 6 RLCS17 1
## 7 RLCS22 1
## 8 RLCS28 1
## 9 RLCS27 1
## 10 RLCS15 3
## 11 RLCS19 3
## 12 RLCS04 3
## 13 RLCS05 2
## 14 RLCS14 1
## 15 RLCS10 2
## 16 RLCS12 2
## 17 RLCS18 2
## 18 RLCS29 1
## 19 RLCS11 3
## 20 RLCS09 1
## 22 RLCS13 2
## 23 RLCS31 1
## 24 RLCS30 1
## 25 RLCS25 1
## 26 RLCS16 1
## 27 RLCS01 2
## 28 RLCS20 1
## 30 RLCS24 1