Download the brms model fitted to novelforest_data (Lai et al. 2021).
The model object is too large (16.5 MB) to be included with the package,
so this function downloads the model from the developmental GitHub website.
The generalised linear mixed-effect model was fitted via brms::brm so
this package is recommended to make full use of the model object.
download_model(save_to = NULL)Path and name of the file where the R object is saved to. Defaults to NULL, which does not save the model object locally.
A brms model output of class brmsfit,
which is a list containing the input data and other slots
that store the model components.
Notably, the data slot contains a data.frame with the following
response variables:
first-order native taxonomic diversity, i.e., species richness
second-order native taxonomic diversity, i.e., inverse Simpson index
first-order exotic taxonomic diversity
second-order exotic taxonomic diversity
first-order native functional diversity
second-order native functional diversity
first-order exotic functional diversity
second-order exotic functional diversity,
and the following explanatory variables (and measurement units if you backtransform
them using backtransform):
Distance to old-growth forests (m)
Patch area (km^2)
Total soil nitrogen (mg/kg)
Total extractable soil phosphorous (mg/kg)
Total extractable soil potassium (mg/kg)
Forest patch ID
#' Note that all explanatory variables were log-transformed and standardised to zero mean and
unit standard deviations. Use backtransform to obtain the variables in
their original scales. See Lai et al. (2021) for more details on model building and
data collection.
Lai, H.R., Tan, G.S.Y., Neo, L., Kee, C.Y., Yee, A.T.K., Tan, H.T.W. and Chong, K.Y. (2021) Decoupled responses of native and exotic tree diversities to distance from old-growth forest and soil phosphorous in novel secondary forests. Applied Vegetation Science, 24, e12548. doi:10.1111/avsc.12548
backtransform, brms::brmsfit, brms::brm
novelforest_model <- download_model()
#> To save the model locally, use argument save_to = 'path/filename.rds'
#> Downloading model (size: 16.5 Mb)
# library(brms) # recommended
summary(novelforest_model)
#> Family: MV(hurdle_gamma, hurdle_gamma, hurdle_gamma, hurdle_gamma, hurdle_gamma, hurdle_gamma, hurdle_gamma, hurdle_gamma)
#> Links: mu = log; shape = identity; hu = identity
#> mu = log; shape = identity; hu = identity
#> mu = log; shape = identity; hu = identity
#> mu = log; shape = identity; hu = identity
#> mu = log; shape = identity; hu = identity
#> mu = log; shape = identity; hu = identity
#> mu = log; shape = identity; hu = identity
#> mu = log; shape = identity; hu = identity
#> Formula: SD_N_0 ~ dist + size + nitrogen + phosphorous + potassium + (1 | 1 | patch)
#> SD_N_2 ~ dist + size + nitrogen + phosphorous + potassium + (1 | 1 | patch)
#> SD_E_0 ~ dist + size + nitrogen + phosphorous + potassium + (1 | 1 | patch)
#> SD_E_2 ~ dist + size + nitrogen + phosphorous + potassium + (1 | 1 | patch)
#> FD_N_0 ~ dist + size + nitrogen + phosphorous + potassium + (1 | 1 | patch)
#> FD_N_2 ~ dist + size + nitrogen + phosphorous + potassium + (1 | 1 | patch)
#> FD_E_0 ~ dist + size + nitrogen + phosphorous + potassium + (1 | 1 | patch)
#> FD_E_2 ~ dist + size + nitrogen + phosphorous + potassium + (1 | 1 | patch)
#> Data: novel_D_scaled_long (Number of observations: 97)
#> Draws: 4 chains, each with iter = 2000; warmup = 1000; thin = 1;
#> total post-warmup draws = 4000
#>
#> Group-Level Effects:
#> ~patch (Number of levels: 20)
#> Estimate Est.Error l-95% CI u-95% CI Rhat
#> sd(SDN0_Intercept) 0.24 0.07 0.10 0.40 1.00
#> sd(SDN2_Intercept) 0.17 0.07 0.04 0.32 1.00
#> sd(SDE0_Intercept) 0.30 0.07 0.19 0.47 1.00
#> sd(SDE2_Intercept) 0.27 0.06 0.16 0.41 1.00
#> sd(FDN0_Intercept) 0.53 0.16 0.26 0.88 1.00
#> sd(FDN2_Intercept) 0.43 0.12 0.22 0.70 1.00
#> sd(FDE0_Intercept) 0.51 0.17 0.22 0.89 1.00
#> sd(FDE2_Intercept) 0.45 0.13 0.23 0.75 1.00
#> cor(SDN0_Intercept,SDN2_Intercept) 0.42 0.26 -0.16 0.84 1.00
#> cor(SDN0_Intercept,SDE0_Intercept) -0.13 0.25 -0.60 0.38 1.00
#> cor(SDN2_Intercept,SDE0_Intercept) -0.01 0.27 -0.51 0.51 1.00
#> cor(SDN0_Intercept,SDE2_Intercept) -0.12 0.25 -0.59 0.39 1.00
#> cor(SDN2_Intercept,SDE2_Intercept) 0.00 0.26 -0.51 0.51 1.00
#> cor(SDE0_Intercept,SDE2_Intercept) 0.62 0.19 0.16 0.91 1.00
#> cor(SDN0_Intercept,FDN0_Intercept) 0.51 0.24 -0.03 0.88 1.00
#> cor(SDN2_Intercept,FDN0_Intercept) 0.40 0.27 -0.19 0.82 1.00
#> cor(SDE0_Intercept,FDN0_Intercept) -0.13 0.25 -0.61 0.38 1.00
#> cor(SDE2_Intercept,FDN0_Intercept) -0.17 0.25 -0.62 0.33 1.00
#> cor(SDN0_Intercept,FDN2_Intercept) 0.50 0.23 -0.03 0.87 1.00
#> cor(SDN2_Intercept,FDN2_Intercept) 0.46 0.25 -0.13 0.85 1.00
#> cor(SDE0_Intercept,FDN2_Intercept) -0.06 0.25 -0.52 0.42 1.00
#> cor(SDE2_Intercept,FDN2_Intercept) -0.09 0.25 -0.56 0.39 1.00
#> cor(FDN0_Intercept,FDN2_Intercept) 0.56 0.22 0.05 0.89 1.00
#> cor(SDN0_Intercept,FDE0_Intercept) -0.11 0.27 -0.61 0.41 1.00
#> cor(SDN2_Intercept,FDE0_Intercept) 0.02 0.28 -0.52 0.57 1.00
#> cor(SDE0_Intercept,FDE0_Intercept) 0.43 0.26 -0.12 0.85 1.00
#> cor(SDE2_Intercept,FDE0_Intercept) 0.40 0.26 -0.15 0.83 1.00
#> cor(FDN0_Intercept,FDE0_Intercept) -0.08 0.26 -0.57 0.43 1.00
#> cor(FDN2_Intercept,FDE0_Intercept) 0.00 0.26 -0.50 0.51 1.00
#> cor(SDN0_Intercept,FDE2_Intercept) -0.10 0.26 -0.59 0.42 1.00
#> cor(SDN2_Intercept,FDE2_Intercept) 0.06 0.28 -0.48 0.60 1.00
#> cor(SDE0_Intercept,FDE2_Intercept) 0.47 0.25 -0.09 0.86 1.00
#> cor(SDE2_Intercept,FDE2_Intercept) 0.46 0.24 -0.07 0.84 1.00
#> cor(FDN0_Intercept,FDE2_Intercept) -0.09 0.26 -0.58 0.43 1.00
#> cor(FDN2_Intercept,FDE2_Intercept) 0.02 0.26 -0.49 0.49 1.00
#> cor(FDE0_Intercept,FDE2_Intercept) 0.50 0.23 -0.02 0.87 1.00
#> Bulk_ESS Tail_ESS
#> sd(SDN0_Intercept) 2125 1672
#> sd(SDN2_Intercept) 1917 1528
#> sd(SDE0_Intercept) 2713 2767
#> sd(SDE2_Intercept) 2834 2823
#> sd(FDN0_Intercept) 2602 2718
#> sd(FDN2_Intercept) 2918 2971
#> sd(FDE0_Intercept) 2624 2121
#> sd(FDE2_Intercept) 3251 2993
#> cor(SDN0_Intercept,SDN2_Intercept) 2888 3033
#> cor(SDN0_Intercept,SDE0_Intercept) 2015 2695
#> cor(SDN2_Intercept,SDE0_Intercept) 1698 2572
#> cor(SDN0_Intercept,SDE2_Intercept) 1935 2603
#> cor(SDN2_Intercept,SDE2_Intercept) 1886 2750
#> cor(SDE0_Intercept,SDE2_Intercept) 2899 3182
#> cor(SDN0_Intercept,FDN0_Intercept) 2595 3276
#> cor(SDN2_Intercept,FDN0_Intercept) 2542 2540
#> cor(SDE0_Intercept,FDN0_Intercept) 3879 3369
#> cor(SDE2_Intercept,FDN0_Intercept) 4459 3802
#> cor(SDN0_Intercept,FDN2_Intercept) 2612 3069
#> cor(SDN2_Intercept,FDN2_Intercept) 2300 2276
#> cor(SDE0_Intercept,FDN2_Intercept) 4164 3662
#> cor(SDE2_Intercept,FDN2_Intercept) 4089 3814
#> cor(FDN0_Intercept,FDN2_Intercept) 3342 3584
#> cor(SDN0_Intercept,FDE0_Intercept) 2904 3106
#> cor(SDN2_Intercept,FDE0_Intercept) 2607 2455
#> cor(SDE0_Intercept,FDE0_Intercept) 3099 2966
#> cor(SDE2_Intercept,FDE0_Intercept) 3204 3135
#> cor(FDN0_Intercept,FDE0_Intercept) 3833 3763
#> cor(FDN2_Intercept,FDE0_Intercept) 3759 3011
#> cor(SDN0_Intercept,FDE2_Intercept) 2648 3128
#> cor(SDN2_Intercept,FDE2_Intercept) 2558 3065
#> cor(SDE0_Intercept,FDE2_Intercept) 3306 3214
#> cor(SDE2_Intercept,FDE2_Intercept) 3617 3442
#> cor(FDN0_Intercept,FDE2_Intercept) 3793 3724
#> cor(FDN2_Intercept,FDE2_Intercept) 3737 3915
#> cor(FDE0_Intercept,FDE2_Intercept) 3018 3402
#>
#> Population-Level Effects:
#> Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
#> SDN0_Intercept 1.45 0.08 1.30 1.59 1.00 2471 3140
#> SDN2_Intercept 1.09 0.06 0.97 1.21 1.00 3525 3150
#> SDE0_Intercept 0.70 0.08 0.53 0.87 1.00 2589 2858
#> SDE2_Intercept 0.43 0.07 0.30 0.58 1.00 2877 3001
#> FDN0_Intercept 4.09 0.16 3.77 4.40 1.00 2633 2617
#> FDN2_Intercept 3.55 0.14 3.29 3.82 1.00 2666 2917
#> FDE0_Intercept 2.79 0.19 2.42 3.15 1.00 2980 2769
#> FDE2_Intercept 2.51 0.16 2.18 2.83 1.00 3037 2925
#> SDN0_dist -0.32 0.08 -0.47 -0.17 1.00 3516 3261
#> SDN0_size -0.01 0.08 -0.17 0.15 1.00 3213 3140
#> SDN0_nitrogen -0.10 0.07 -0.24 0.04 1.00 4239 3171
#> SDN0_phosphorous -0.02 0.06 -0.13 0.11 1.00 4758 3294
#> SDN0_potassium -0.04 0.07 -0.18 0.10 1.00 4525 2890
#> SDN2_dist -0.29 0.07 -0.42 -0.16 1.00 4268 3472
#> SDN2_size -0.01 0.07 -0.13 0.12 1.00 3869 2990
#> SDN2_nitrogen -0.07 0.06 -0.19 0.05 1.00 4631 3654
#> SDN2_phosphorous -0.01 0.05 -0.11 0.10 1.00 6169 3247
#> SDN2_potassium -0.01 0.06 -0.13 0.11 1.00 5330 3192
#> SDE0_dist 0.11 0.09 -0.05 0.29 1.00 2933 2876
#> SDE0_size -0.04 0.09 -0.22 0.14 1.00 2566 2859
#> SDE0_nitrogen 0.02 0.07 -0.11 0.15 1.00 4984 3380
#> SDE0_phosphorous 0.20 0.06 0.07 0.32 1.00 4841 3369
#> SDE0_potassium -0.00 0.07 -0.14 0.14 1.00 5077 3393
#> SDE2_dist 0.05 0.08 -0.09 0.20 1.00 2915 3138
#> SDE2_size -0.05 0.08 -0.20 0.11 1.00 2462 2813
#> SDE2_nitrogen 0.09 0.06 -0.02 0.20 1.00 5028 3279
#> SDE2_phosphorous 0.12 0.05 0.01 0.23 1.00 4946 2635
#> SDE2_potassium -0.05 0.06 -0.17 0.07 1.00 5276 2724
#> FDN0_dist -0.53 0.17 -0.86 -0.20 1.00 3610 3361
#> FDN0_size -0.03 0.17 -0.36 0.31 1.00 3201 2842
#> FDN0_nitrogen -0.18 0.14 -0.45 0.09 1.00 4723 3405
#> FDN0_phosphorous -0.12 0.12 -0.36 0.12 1.00 5511 3337
#> FDN0_potassium -0.10 0.14 -0.38 0.18 1.00 5207 3438
#> FDN2_dist -0.48 0.14 -0.75 -0.21 1.00 4100 3329
#> FDN2_size -0.01 0.14 -0.27 0.26 1.00 3256 2860
#> FDN2_nitrogen -0.14 0.11 -0.35 0.07 1.00 4907 3221
#> FDN2_phosphorous -0.09 0.10 -0.28 0.10 1.00 5491 2921
#> FDN2_potassium -0.07 0.11 -0.29 0.14 1.00 4713 3254
#> FDE0_dist 0.06 0.18 -0.29 0.44 1.00 3838 3153
#> FDE0_size 0.17 0.18 -0.17 0.53 1.00 4030 3372
#> FDE0_nitrogen -0.03 0.15 -0.32 0.26 1.00 5116 3221
#> FDE0_phosphorous 0.04 0.15 -0.26 0.33 1.00 5057 3192
#> FDE0_potassium -0.00 0.18 -0.36 0.35 1.00 4896 3226
#> FDE2_dist 0.04 0.16 -0.27 0.36 1.00 3728 2875
#> FDE2_size 0.14 0.15 -0.17 0.42 1.00 3359 3036
#> FDE2_nitrogen -0.00 0.12 -0.25 0.24 1.00 5668 3059
#> FDE2_phosphorous 0.03 0.12 -0.22 0.27 1.00 5032 3164
#> FDE2_potassium 0.00 0.15 -0.28 0.29 1.00 6020 2963
#>
#> Family Specific Parameters:
#> Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
#> shape_SDN0 4.85 0.77 3.48 6.48 1.00 5827 2784
#> shape_SDN2 6.01 0.93 4.33 7.99 1.00 5630 3015
#> shape_SDE0 5.69 0.89 4.10 7.62 1.00 7002 3158
#> shape_SDE2 8.11 1.29 5.79 10.87 1.00 7372 2878
#> shape_FDN0 1.56 0.25 1.13 2.08 1.00 6141 2904
#> shape_FDN2 2.28 0.36 1.63 3.06 1.00 6047 3098
#> shape_FDE0 1.86 0.36 1.23 2.65 1.00 5539 2772
#> shape_FDE2 2.66 0.53 1.73 3.80 1.00 5413 2902
#> hu_SDN0 0.07 0.03 0.03 0.13 1.00 7876 2644
#> hu_SDN2 0.07 0.03 0.03 0.13 1.00 6828 2724
#> hu_SDE0 0.05 0.02 0.02 0.10 1.00 9739 2676
#> hu_SDE2 0.05 0.02 0.02 0.10 1.00 9364 3035
#> hu_FDN0 0.15 0.04 0.09 0.23 1.00 8964 2818
#> hu_FDN2 0.15 0.04 0.09 0.23 1.00 9427 2845
#> hu_FDE0 0.39 0.05 0.30 0.49 1.00 9169 2550
#> hu_FDE2 0.39 0.05 0.30 0.49 1.00 9008 2500
#>
#> Draws were sampled using sampling(NUTS). For each parameter, Bulk_ESS
#> and Tail_ESS are effective sample size measures, and Rhat is the potential
#> scale reduction factor on split chains (at convergence, Rhat = 1).
# to obtain input data
novelforest_model$data
#> SD_N_0 dist size nitrogen phosphorous potassium patch
#> 1 2 0.34018403 1.01559837 0.67459639 0.57571244 -0.05023288 AD
#> 2 8 0.30610447 1.01559837 -0.44642115 -0.08104609 -0.22461032 AD
#> 3 2 0.33135980 1.01559837 0.54188573 0.21932955 0.70159236 AD
#> 4 1 0.34625195 1.01559837 0.25346635 -0.51665575 0.53435074 AD
#> 5 0 0.35794036 1.01559837 0.47281510 -0.45852057 -0.25781745 AD
#> 6 6 0.44004163 0.04359803 0.60911425 0.89633096 0.36958155 AW
#> 7 5 0.47390839 0.04359803 1.19803868 -0.33515406 0.88010791 AW
#> 8 8 0.42323121 0.04359803 0.67459639 -0.86346927 -0.08482016 AW
#> 9 3 0.47561449 0.04359803 0.54188573 -0.73824554 -0.17167092 AW
#> 10 5 0.47076580 0.04359803 0.92073519 -1.06720860 -0.07708810 AW
#> 11 6 -0.61174710 -1.30243313 -1.00894826 -0.13310625 -1.25691603 BBE
#> 12 7 -0.58576466 -1.30243313 1.49496033 0.21932955 1.87739357 BBE
#> 13 9 -0.44648062 -1.30243313 -0.88595215 -0.04117684 0.28573608 BBE
#> 14 8 -0.62931766 -1.30243313 -1.00894826 -1.50825971 -0.59552058 BBE
#> 15 4 -0.42584629 -1.30243313 -0.65661954 -0.81929128 -1.43298517 BBE
#> 16 7 0.24805440 0.76404822 -2.09491768 -1.23225799 -1.86657088 BBH
#> 17 3 0.24915015 0.76404822 -2.29669897 -1.11738261 -1.87512457 BBH
#> 18 6 0.20251560 0.76404822 -1.41864554 -0.43772030 -0.56177181 BBH
#> 19 7 0.32649330 0.76404822 -1.41864554 -1.23225799 -0.99869523 BBH
#> 20 2 0.18825991 0.76404822 -0.54933014 -0.24170548 -0.17167092 BBH
#> 21 6 -0.78197085 0.49907107 -0.76867889 -0.27239316 -0.26200296 BBN
#> 22 4 -0.67731816 0.49907107 -1.13825457 0.22777923 -0.38689241 BBN
#> 23 4 -0.63823685 0.49907107 -1.41864554 0.14006352 -1.80758713 BBN
#> 24 5 -0.77893710 0.49907107 -0.88595215 -0.08784038 0.17806697 BBN
#> 25 5 -0.82959808 0.49907107 0.09585751 -0.46663147 -0.50973839 BBN
#> 26 4 -0.31690329 0.82880093 -0.54933014 -0.80347175 -0.24115273 BBT
#> 27 6 -0.25319324 0.82880093 -0.44642115 -1.25958366 -1.60870216 BBT
#> 28 5 -0.27947361 0.82880093 0.01319697 -1.54846763 -1.21177217 BBT
#> 29 4 -0.24438167 0.82880093 0.17589345 -0.53909422 0.00625863 BBT
#> 30 3 -0.17081588 0.82880093 0.09585751 -0.69893398 -0.35174326 BBT
#> 31 2 1.46034726 -0.42130821 0.67459639 0.36930292 0.70704973 BR
#> 32 1 1.45309440 -0.42130821 0.60911425 -0.41422016 0.70704973 BR
#> 33 1 1.45648755 -0.42130821 0.01319697 0.13087587 1.17981108 BR
#> 34 4 -0.04570421 0.98551824 2.03874446 2.70417842 1.53858587 CL
#> 35 3 0.02027511 0.98551824 -0.54933014 -0.23384507 -0.46804133 CL
#> 36 3 -0.01257541 0.98551824 -0.16072856 2.27363310 0.92756005 CL
#> 37 5 -0.02643236 0.98551824 -0.34754885 3.16066524 -1.40498614 CL
#> 38 6 -0.04935458 0.98551824 -0.25240849 1.10945654 0.75291150 CL
#> 39 4 0.44069915 -0.36109405 -0.16072856 2.59120752 1.06420147 DO
#> 40 10 0.41006932 -0.36109405 -1.27455373 0.19356551 1.09653246 DO
#> 41 5 0.40340678 -0.36109405 -0.34754885 -0.14743536 0.99811400 DO
#> 42 3 0.47188345 -0.36109405 -0.54933014 2.32873541 0.83678698 DO
#> 43 4 0.45514712 -0.36109405 -0.07226614 3.12269495 0.98369673 DO
#> 44 8 -2.43288531 1.70526856 -0.07226614 -0.06758775 -2.40392388 GA
#> 45 6 -1.41944585 1.70526856 0.01319697 0.08369401 -2.44769017 GA
#> 46 12 -3.04529065 1.70526856 -0.34754885 -0.22733931 -1.27654368 GA
#> 47 10 -2.14649141 1.70526856 0.17589345 -0.13310625 -0.90761644 GA
#> 48 11 -2.36494195 1.70526856 1.25001826 0.05433455 -0.40914228 GA
#> 49 0 1.47610486 0.17611782 -2.29669897 -1.23563513 -0.17167092 IK
#> 50 2 1.49427336 0.17611782 0.54188573 0.44040965 1.62001616 IK
#> 51 1 1.47713856 0.17611782 0.80066867 0.01386883 1.22357738 IK
#> 52 0 1.46795314 0.17611782 0.92073519 0.30091920 0.62659454 IK
#> 53 2 1.48306823 0.17611782 -1.41864554 -0.98145457 1.79482414 IK
#> 54 1 0.36229994 -0.10313850 0.86141668 -1.96143434 0.24596046 JR
#> 55 7 0.40441364 -0.10313850 -0.65661954 -1.36505151 0.02108693 JR
#> 56 3 0.36742939 -0.10313850 0.32872329 -0.63970751 0.60103026 JR
#> 57 3 0.39127523 -0.10313850 -1.27455373 -0.22087353 -0.08482016 JR
#> 58 5 0.33693748 -0.10313850 -0.65661954 -0.57277461 0.35688352 JR
#> 59 4 0.43810391 -1.02150327 0.73842056 -0.10617599 0.25597036 KJ
#> 60 3 0.44381514 -1.02150327 1.88356192 -1.03597346 0.68789084 KJ
#> 61 2 0.46953936 -1.02150327 0.67459639 -0.86584662 0.20206302 KJ
#> 62 1 0.49581880 -1.02150327 -0.54933014 -0.30679711 -0.79340200 KJ
#> 63 0 0.50425905 -1.02150327 0.47281510 -0.69488011 0.73414012 KJ
#> 64 5 -0.18982852 0.38913283 0.47281510 0.93998781 0.04680400 LD
#> 65 8 -0.23023720 0.38913283 -0.65661954 -0.43455645 -0.19188535 LD
#> 66 9 -0.23155490 0.38913283 -0.16072856 -0.69084179 -0.01241499 LD
#> 67 3 -0.22691122 0.38913283 2.25495579 0.30091920 0.39789321 LD
#> 68 5 -0.23432506 0.38913283 3.09823735 0.74818934 1.22357738 LD
#> 69 6 1.40586249 -1.18163961 -1.57147538 0.92274186 -2.10025099 PO
#> 70 7 1.40699198 -1.18163961 0.32872329 1.42205493 -0.58099490 PO
#> 71 2 1.40349556 -1.18163961 0.92073519 0.73268077 1.92552123 PO
#> 72 1 1.40052120 -1.18163961 0.09585751 -0.22993679 -0.25781745 PO
#> 73 1 1.40756167 -1.18163961 -0.65661954 1.29578069 -0.08482016 PO
#> 74 3 -1.62817709 -0.86528500 0.97868993 2.06533647 1.15760506 PT
#> 75 8 -1.36349621 -0.86528500 0.54188573 0.34699864 0.41657199 PT
#> 76 0 -1.20627492 -0.86528500 0.86141668 0.39832487 1.22357738 PT
#> 77 4 -1.56018763 -0.86528500 0.40179856 0.30874064 2.00351840 PT
#> 78 2 -1.65219175 -0.86528500 1.30094768 1.14171737 1.03375881 PT
#> 79 5 0.05410735 -1.30990447 0.73842056 0.19356551 0.48376620 SA
#> 80 7 0.07776372 -1.30990447 0.01319697 -0.24039133 -0.71522445 SA
#> 81 5 0.13514903 -1.30990447 0.60911425 0.61720432 0.05773641 SA
#> 82 8 0.10236705 -1.30990447 0.01319697 -0.99213466 0.13632702 SA
#> 83 4 0.11597520 -1.30990447 0.32872329 -0.37171017 0.19181027 SA
#> 84 5 -0.27834014 -1.71031213 -1.13825457 -0.07541750 -0.63966788 SJ
#> 85 4 -0.12255293 -1.71031213 -1.00894826 -0.45207657 -0.40914228 SJ
#> 86 2 -0.17415310 -1.71031213 -3.02192255 -1.31281487 -1.07550636 SJ
#> 87 0 -0.24035938 -1.71031213 1.14496472 -0.17175966 0.92013370 SJ
#> 88 4 -0.13828006 -1.71031213 -0.07226614 -0.24170548 -0.05787320 SJ
#> 89 2 1.41955417 0.03034498 0.17589345 -0.68481324 1.13292305 TP
#> 90 2 1.38949609 0.03034498 0.40179856 0.32421120 1.41064357 TP
#> 91 4 1.39217206 0.03034498 0.32872329 -0.59461579 -0.08869616 TP
#> 92 2 1.41423233 0.03034498 -0.34754885 -0.93469225 -1.56347202 TP
#> 93 5 -1.60701925 1.67666501 0.01319697 0.42656762 -1.19269821 UT
#> 94 7 -1.35726962 1.67666501 -0.44642115 -0.16562565 -1.66264406 UT
#> 95 9 -1.29936584 1.67666501 0.09585751 1.17301824 -0.59552058 UT
#> 96 5 -2.12168702 1.67666501 1.03534221 0.56964915 -0.50973839 UT
#> 97 6 -1.41364697 1.67666501 1.14496472 0.21932955 0.35369781 UT
#> SD_N_2 SD_E_0 SD_E_2 FD_N_0 FD_N_2 FD_E_0 FD_E_2
#> 1 1.600000 3 1.549356 6.068161 6.068161 19.061061 14.349844
#> 2 5.128205 2 1.124514 176.741963 80.528861 6.345825 6.345825
#> 3 1.600000 2 1.045431 6.276896 6.276896 6.351461 6.351461
#> 4 1.000000 1 1.000000 0.000000 0.000000 0.000000 0.000000
#> 5 0.000000 3 2.461538 0.000000 0.000000 19.061061 13.579309
#> 6 4.121951 2 1.800000 95.149105 54.255080 6.345825 6.345825
#> 7 2.648649 3 2.133333 62.773106 34.887145 19.167086 14.356864
#> 8 4.232000 2 1.800000 177.033677 56.810206 6.345825 6.345825
#> 9 1.588235 2 2.000000 19.299513 14.826368 6.396550 6.396550
#> 10 2.000000 2 1.045431 62.215777 29.702331 6.396550 6.396550
#> 11 4.571429 3 1.119171 94.236570 71.343714 19.356083 13.158064
#> 12 4.444444 1 1.000000 135.157197 62.094609 0.000000 0.000000
#> 13 7.117647 2 1.198020 231.052893 173.608806 6.391431 6.391431
#> 14 1.838906 0 0.000000 176.327692 41.129042 0.000000 0.000000
#> 15 3.266667 1 1.000000 38.250256 29.217622 0.000000 0.000000
#> 16 3.082192 1 1.000000 134.058465 60.809027 0.000000 0.000000
#> 17 3.000000 1 1.000000 18.793740 18.793740 0.000000 0.000000
#> 18 4.840000 1 1.000000 94.236018 65.252739 0.000000 0.000000
#> 19 2.232068 1 1.000000 132.295135 48.953894 0.000000 0.000000
#> 20 2.000000 2 1.882353 6.274281 6.274281 6.387492 6.387492
#> 21 4.481481 6 5.333333 96.881205 65.444844 95.614574 79.645150
#> 22 2.909091 2 1.132743 38.786866 27.265040 6.202454 6.202454
#> 23 2.682540 6 3.321839 38.858853 17.927659 95.705907 40.645428
#> 24 2.864407 4 1.228879 64.043986 37.015475 37.592069 18.014955
#> 25 4.500000 1 1.000000 63.029816 56.151139 0.000000 0.000000
#> 26 3.571429 1 1.000000 38.367889 34.545024 0.000000 0.000000
#> 27 4.500000 1 1.000000 96.190066 60.103087 0.000000 0.000000
#> 28 2.813953 1 1.000000 62.998358 35.832949 0.000000 0.000000
#> 29 2.578947 1 1.000000 38.378461 28.285722 0.000000 0.000000
#> 30 2.666667 1 1.000000 19.063042 17.670762 0.000000 0.000000
#> 31 2.000000 2 1.470588 6.120796 6.120796 6.201227 6.201227
#> 32 1.000000 4 1.640777 0.000000 0.000000 38.109678 22.855183
#> 33 1.000000 0 0.000000 0.000000 0.000000 0.000000 0.000000
#> 34 1.603960 3 1.945946 37.438460 19.611355 19.356083 12.113701
#> 35 1.851852 1 1.000000 18.711982 13.191554 0.000000 0.000000
#> 36 1.843658 3 1.457831 18.429523 8.680781 19.206442 14.038891
#> 37 3.125000 2 1.180328 64.619019 39.382151 6.202454 6.202454
#> 38 4.666667 3 1.851852 95.373958 61.895365 19.338876 13.616616
#> 39 2.909091 2 1.219512 37.445985 26.193978 6.371743 6.371743
#> 40 5.236364 0 0.000000 287.339299 128.648669 0.000000 0.000000
#> 41 3.650667 1 1.000000 64.017472 35.527770 0.000000 0.000000
#> 42 2.666667 4 1.923077 19.242167 17.790449 38.168703 24.714305
#> 43 2.909091 2 1.923077 38.094578 26.578393 6.371743 6.371743
#> 44 6.250000 1 1.000000 176.981404 132.736059 0.000000 0.000000
#> 45 2.964912 1 1.000000 94.720546 47.585811 0.000000 0.000000
#> 46 4.370629 1 1.000000 420.347047 129.604871 0.000000 0.000000
#> 47 8.166667 1 1.000000 283.387544 204.311674 0.000000 0.000000
#> 48 7.810811 1 1.000000 346.268906 198.139140 0.000000 0.000000
#> 49 0.000000 3 1.135255 0.000000 0.000000 19.085394 13.202412
#> 50 1.600000 2 1.800000 6.301612 6.301612 6.396550 6.396550
#> 51 1.000000 1 1.000000 0.000000 0.000000 0.000000 0.000000
#> 52 0.000000 3 2.000000 0.000000 0.000000 19.041104 15.553319
#> 53 2.000000 1 1.000000 6.309702 6.309702 0.000000 0.000000
#> 54 1.000000 1 1.000000 0.000000 0.000000 0.000000 0.000000
#> 55 3.983607 1 1.000000 132.228700 49.129541 0.000000 0.000000
#> 56 2.272727 3 2.086420 19.291174 16.513704 18.806499 11.072302
#> 57 1.741935 1 1.000000 19.094310 10.467885 0.000000 0.000000
#> 58 3.225806 1 1.000000 63.622635 27.656591 0.000000 0.000000
#> 59 4.000000 3 3.000000 38.376026 38.376026 19.071534 19.071534
#> 60 3.000000 4 4.000000 19.268292 19.268292 37.983308 37.983308
#> 61 2.000000 2 2.000000 6.526282 6.526282 6.327744 6.327744
#> 62 1.000000 4 4.000000 0.000000 0.000000 37.946456 37.946456
#> 63 0.000000 3 1.975610 0.000000 0.000000 19.071534 13.834141
#> 64 2.469388 6 5.260870 62.748522 27.612225 94.613170 76.003687
#> 65 6.736842 2 1.396807 176.829594 128.857883 6.371743 6.371743
#> 66 6.428571 2 1.198020 226.360116 130.991195 6.387492 6.387492
#> 67 2.666667 3 2.102804 19.062079 17.639762 19.269549 10.455300
#> 68 5.000000 3 1.515152 63.783967 63.783967 19.004983 14.242388
#> 69 4.787234 2 1.172608 94.784655 62.590512 6.202454 6.202454
#> 70 2.084599 0 0.000000 130.886011 43.247232 0.000000 0.000000
#> 71 1.882353 3 1.800000 6.276896 6.276896 18.937631 13.235973
#> 72 1.000000 1 1.000000 0.000000 0.000000 0.000000 0.000000
#> 73 1.000000 3 1.546828 0.000000 0.000000 18.937631 8.841082
#> 74 2.739726 1 1.000000 18.763870 16.670540 0.000000 0.000000
#> 75 3.881988 2 1.445902 174.232562 49.457428 6.327744 6.327744
#> 76 0.000000 2 1.724138 0.000000 0.000000 6.327744 6.327744
#> 77 3.846154 2 1.280000 38.657762 36.614554 6.327744 6.327744
#> 78 1.724138 2 1.800000 6.291827 6.291827 6.327744 6.327744
#> 79 3.446809 2 1.710059 64.393372 33.364788 6.327744 6.327744
#> 80 5.555556 2 1.882353 135.724596 91.230646 6.327744 6.327744
#> 81 3.595745 2 1.800000 63.678893 36.142133 6.327744 6.327744
#> 82 3.531073 1 1.000000 177.309397 62.124638 0.000000 0.000000
#> 83 2.941176 1 1.000000 37.763198 21.365859 0.000000 0.000000
#> 84 2.000000 2 1.689655 63.518026 30.329428 6.387492 6.387492
#> 85 3.521739 4 2.769231 38.179587 30.619519 37.592069 18.300971
#> 86 1.342282 2 1.470588 6.262615 6.262615 6.396550 6.396550
#> 87 0.000000 2 2.000000 0.000000 0.000000 6.483252 6.483252
#> 88 3.130435 1 1.000000 38.604423 25.415840 0.000000 0.000000
#> 89 1.600000 1 1.000000 6.331174 6.331174 0.000000 0.000000
#> 90 1.800000 2 1.324324 6.474740 6.474740 6.201227 6.201227
#> 91 2.076923 3 1.684211 38.193122 25.473886 18.534312 14.389511
#> 92 2.000000 2 1.753425 6.344339 6.344339 6.201227 6.201227
#> 93 2.500000 1 1.000000 62.774729 37.542058 0.000000 0.000000
#> 94 6.000000 1 1.000000 133.193222 102.797463 0.000000 0.000000
#> 95 4.389610 3 3.000000 226.585433 69.508383 18.504130 18.504130
#> 96 3.521739 2 1.600000 63.086499 41.744229 6.428676 6.428676
#> 97 5.142857 5 3.595745 95.965939 73.268482 63.746937 36.094626