Differences in the community structure between seasons we tested Middle and Low level separately.
Exploratory analysis
## [1] "Mes" "ID_fila" "Foto"
## [4] "Nivel.Intermareal" "Anio" "Cobertura"
## [7] "Diversidad" "Riqueza" "Equitatividad"
## [10] "Estacion" "Cob.T" "num_lapas"
## [13] "cob_lapasT" "RS_T" "RG_T"
## [16] "RM_T" "G_T" "SD_T"
## [19] "Mon_har" "Ade_utr" "Asc_mir"
## [22] "Des_men" "Des_ant" "Pha_ant"
## [25] "Delesseriaceae" "Corallinaceae" "Gig_sko"
## [28] "Iri_cor" "Pal_dec" "Plo_car"
## [31] "Pyr_end" "Cur_rac" "Ulv_NI"
## [34] "lluviamm" "vientovelmax" "diaslluvia"
## [37] "diasnieve" "diasniebla" "Temp_prom_of"
## [40] "Temp_max_of" "Temp_min_of" "Num_dias5menos_of"
## [43] "vientovelmedia_of" "vientodirecprom_of" "Insolacion_acum_MES"
## [46] "Temp_media_acum_MES"
## Loading required package: Hmisc
## Loading required package: lattice
## Loading required package: survival
## Loading required package: Formula
## Loading required package: ggplot2
##
## Attaching package: 'Hmisc'
## The following objects are masked from 'package:base':
##
## format.pval, round.POSIXt, trunc.POSIXt, units
## Mes Cob.T SD_T Diversidad Equitatividad Riqueza
## Mes 1.00 -0.10 0.10 -0.10 -0.13 0.01
## Cob.T -0.10 1.00 -1.00 -0.17 -0.31 0.16
## SD_T 0.10 -1.00 1.00 0.17 0.31 -0.16
## Diversidad -0.10 -0.17 0.17 1.00 0.91 0.64
## Equitatividad -0.13 -0.31 0.31 0.91 1.00 0.33
## Riqueza 0.01 0.16 -0.16 0.64 0.33 1.00
## num_lapas 0.06 -0.30 0.29 0.25 0.30 0.05
## cob_lapasT 0.07 -0.29 0.29 0.26 0.31 0.05
## diaslluvia -0.90 0.27 -0.27 0.01 0.01 0.01
## diasnieve -0.67 -0.31 0.32 0.03 0.15 -0.19
## diasniebla -0.10 0.08 -0.08 -0.21 -0.20 -0.14
## lluviamm -0.90 -0.09 0.09 -0.04 0.05 -0.18
## vientovelmedia_of 0.50 0.03 -0.03 -0.40 -0.36 -0.21
## vientovelmax 0.15 -0.07 0.07 -0.26 -0.17 -0.18
## Temp_prom_of -0.60 0.55 -0.55 0.07 -0.03 0.20
## Temp_max_of -0.70 0.37 -0.37 0.17 0.08 0.18
## Temp_min_of -0.30 0.59 -0.59 -0.09 -0.19 0.14
## Insolacion_acum_MES 0.90 -0.08 0.08 -0.25 -0.25 -0.10
## Temp_media_acum_MES -0.60 0.55 -0.55 0.07 -0.03 0.20
## num_lapas cob_lapasT diaslluvia diasnieve diasniebla
## Mes 0.06 0.07 -0.90 -0.67 -0.10
## Cob.T -0.30 -0.29 0.27 -0.31 0.08
## SD_T 0.29 0.29 -0.27 0.32 -0.08
## Diversidad 0.25 0.26 0.01 0.03 -0.21
## Equitatividad 0.30 0.31 0.01 0.15 -0.20
## Riqueza 0.05 0.05 0.01 -0.19 -0.14
## num_lapas 1.00 1.00 -0.13 0.04 0.09
## cob_lapasT 1.00 1.00 -0.15 0.04 0.08
## diaslluvia -0.13 -0.15 1.00 0.56 0.00
## diasnieve 0.04 0.04 0.56 1.00 -0.31
## diasniebla 0.09 0.08 0.00 -0.31 1.00
## lluviamm 0.02 0.01 0.80 0.82 0.20
## vientovelmedia_of 0.03 0.03 -0.20 -0.21 0.20
## vientovelmax -0.03 -0.03 0.15 0.37 -0.41
## Temp_prom_of -0.18 -0.19 0.70 -0.15 0.30
## Temp_max_of -0.10 -0.11 0.60 -0.05 0.40
## Temp_min_of -0.16 -0.17 0.50 -0.41 0.50
## Insolacion_acum_MES 0.10 0.10 -0.80 -0.67 0.30
## Temp_media_acum_MES -0.18 -0.19 0.70 -0.15 0.30
## lluviamm vientovelmedia_of vientovelmax Temp_prom_of
## Mes -0.90 0.50 0.15 -0.60
## Cob.T -0.09 0.03 -0.07 0.55
## SD_T 0.09 -0.03 0.07 -0.55
## Diversidad -0.04 -0.40 -0.26 0.07
## Equitatividad 0.05 -0.36 -0.17 -0.03
## Riqueza -0.18 -0.21 -0.18 0.20
## num_lapas 0.02 0.03 -0.03 -0.18
## cob_lapasT 0.01 0.03 -0.03 -0.19
## diaslluvia 0.80 -0.20 0.15 0.70
## diasnieve 0.82 -0.21 0.37 -0.15
## diasniebla 0.20 0.20 -0.41 0.30
## lluviamm 1.00 -0.20 0.10 0.30
## vientovelmedia_of -0.20 1.00 0.72 -0.30
## vientovelmax 0.10 0.72 1.00 -0.36
## Temp_prom_of 0.30 -0.30 -0.36 1.00
## Temp_max_of 0.40 -0.60 -0.67 0.90
## Temp_min_of 0.10 0.10 -0.21 0.90
## Insolacion_acum_MES -0.70 0.70 0.15 -0.50
## Temp_media_acum_MES 0.30 -0.30 -0.36 1.00
## Temp_max_of Temp_min_of Insolacion_acum_MES
## Mes -0.70 -0.30 0.90
## Cob.T 0.37 0.59 -0.08
## SD_T -0.37 -0.59 0.08
## Diversidad 0.17 -0.09 -0.25
## Equitatividad 0.08 -0.19 -0.25
## Riqueza 0.18 0.14 -0.10
## num_lapas -0.10 -0.16 0.10
## cob_lapasT -0.11 -0.17 0.10
## diaslluvia 0.60 0.50 -0.80
## diasnieve -0.05 -0.41 -0.67
## diasniebla 0.40 0.50 0.30
## lluviamm 0.40 0.10 -0.70
## vientovelmedia_of -0.60 0.10 0.70
## vientovelmax -0.67 -0.21 0.15
## Temp_prom_of 0.90 0.90 -0.50
## Temp_max_of 1.00 0.70 -0.60
## Temp_min_of 0.70 1.00 -0.10
## Insolacion_acum_MES -0.60 -0.10 1.00
## Temp_media_acum_MES 0.90 0.90 -0.50
## Temp_media_acum_MES
## Mes -0.60
## Cob.T 0.55
## SD_T -0.55
## Diversidad 0.07
## Equitatividad -0.03
## Riqueza 0.20
## num_lapas -0.18
## cob_lapasT -0.19
## diaslluvia 0.70
## diasnieve -0.15
## diasniebla 0.30
## lluviamm 0.30
## vientovelmedia_of -0.30
## vientovelmax -0.36
## Temp_prom_of 1.00
## Temp_max_of 0.90
## Temp_min_of 0.90
## Insolacion_acum_MES -0.50
## Temp_media_acum_MES 1.00
##
## n= 75
##
##
## P
## Mes Cob.T SD_T Diversidad Equitatividad Riqueza
## Mes 0.4135 0.4124 0.3861 0.2733 0.9219
## Cob.T 0.4135 0.0000 0.1429 0.0067 0.1689
## SD_T 0.4124 0.0000 0.1415 0.0065 0.1681
## Diversidad 0.3861 0.1429 0.1415 0.0000 0.0000
## Equitatividad 0.2733 0.0067 0.0065 0.0000 0.0036
## Riqueza 0.9219 0.1689 0.1681 0.0000 0.0036
## num_lapas 0.6152 0.0099 0.0124 0.0281 0.0101 0.6962
## cob_lapasT 0.5467 0.0104 0.0131 0.0224 0.0075 0.6969
## diaslluvia 0.0000 0.0175 0.0178 0.9645 0.9143 0.9188
## diasnieve 0.0000 0.0060 0.0059 0.8267 0.1943 0.1046
## diasniebla 0.3933 0.5002 0.4733 0.0735 0.0786 0.2176
## lluviamm 0.0000 0.4210 0.4286 0.7022 0.6803 0.1154
## vientovelmedia_of 0.0000 0.8311 0.8210 0.0003 0.0017 0.0670
## vientovelmax 0.1874 0.5459 0.5383 0.0256 0.1346 0.1225
## Temp_prom_of 0.0000 0.0000 0.0000 0.5498 0.7722 0.0800
## Temp_max_of 0.0000 0.0010 0.0010 0.1535 0.4870 0.1224
## Temp_min_of 0.0089 0.0000 0.0000 0.4327 0.0940 0.2340
## Insolacion_acum_MES 0.0000 0.4896 0.5002 0.0336 0.0323 0.3815
## Temp_media_acum_MES 0.0000 0.0000 0.0000 0.5498 0.7722 0.0800
## num_lapas cob_lapasT diaslluvia diasnieve diasniebla
## Mes 0.6152 0.5467 0.0000 0.0000 0.3933
## Cob.T 0.0099 0.0104 0.0175 0.0060 0.5002
## SD_T 0.0124 0.0131 0.0178 0.0059 0.4733
## Diversidad 0.0281 0.0224 0.9645 0.8267 0.0735
## Equitatividad 0.0101 0.0075 0.9143 0.1943 0.0786
## Riqueza 0.6962 0.6969 0.9188 0.1046 0.2176
## num_lapas 0.0000 0.2566 0.7154 0.4331
## cob_lapasT 0.0000 0.2138 0.7286 0.4807
## diaslluvia 0.2566 0.2138 0.0000 1.0000
## diasnieve 0.7154 0.7286 0.0000 0.0072
## diasniebla 0.4331 0.4807 1.0000 0.0072
## lluviamm 0.8640 0.9336 0.0000 0.0000 0.0854
## vientovelmedia_of 0.8242 0.8169 0.0854 0.0774 0.0854
## vientovelmax 0.8003 0.8196 0.1874 0.0011 0.0003
## Temp_prom_of 0.1313 0.1039 0.0000 0.1874 0.0089
## Temp_max_of 0.3830 0.3269 0.0000 0.6620 0.0004
## Temp_min_of 0.1837 0.1495 0.0000 0.0003 0.0000
## Insolacion_acum_MES 0.4063 0.3726 0.0000 0.0000 0.0089
## Temp_media_acum_MES 0.1313 0.1039 0.0000 0.1874 0.0089
## lluviamm vientovelmedia_of vientovelmax Temp_prom_of
## Mes 0.0000 0.0000 0.1874 0.0000
## Cob.T 0.4210 0.8311 0.5459 0.0000
## SD_T 0.4286 0.8210 0.5383 0.0000
## Diversidad 0.7022 0.0003 0.0256 0.5498
## Equitatividad 0.6803 0.0017 0.1346 0.7722
## Riqueza 0.1154 0.0670 0.1225 0.0800
## num_lapas 0.8640 0.8242 0.8003 0.1313
## cob_lapasT 0.9336 0.8169 0.8196 0.1039
## diaslluvia 0.0000 0.0854 0.1874 0.0000
## diasnieve 0.0000 0.0774 0.0011 0.1874
## diasniebla 0.0854 0.0854 0.0003 0.0089
## lluviamm 0.0854 0.3811 0.0089
## vientovelmedia_of 0.0854 0.0000 0.0089
## vientovelmax 0.3811 0.0000 0.0016
## Temp_prom_of 0.0089 0.0089 0.0016
## Temp_max_of 0.0004 0.0000 0.0000 0.0000
## Temp_min_of 0.3933 0.3933 0.0774 0.0000
## Insolacion_acum_MES 0.0000 0.0000 0.1874 0.0000
## Temp_media_acum_MES 0.0089 0.0089 0.0016 0.0000
## Temp_max_of Temp_min_of Insolacion_acum_MES
## Mes 0.0000 0.0089 0.0000
## Cob.T 0.0010 0.0000 0.4896
## SD_T 0.0010 0.0000 0.5002
## Diversidad 0.1535 0.4327 0.0336
## Equitatividad 0.4870 0.0940 0.0323
## Riqueza 0.1224 0.2340 0.3815
## num_lapas 0.3830 0.1837 0.4063
## cob_lapasT 0.3269 0.1495 0.3726
## diaslluvia 0.0000 0.0000 0.0000
## diasnieve 0.6620 0.0003 0.0000
## diasniebla 0.0004 0.0000 0.0089
## lluviamm 0.0004 0.3933 0.0000
## vientovelmedia_of 0.0000 0.3933 0.0000
## vientovelmax 0.0000 0.0774 0.1874
## Temp_prom_of 0.0000 0.0000 0.0000
## Temp_max_of 0.0000 0.0000
## Temp_min_of 0.0000 0.3933
## Insolacion_acum_MES 0.0000 0.3933
## Temp_media_acum_MES 0.0000 0.0000 0.0000
## Temp_media_acum_MES
## Mes 0.0000
## Cob.T 0.0000
## SD_T 0.0000
## Diversidad 0.5498
## Equitatividad 0.7722
## Riqueza 0.0800
## num_lapas 0.1313
## cob_lapasT 0.1039
## diaslluvia 0.0000
## diasnieve 0.1874
## diasniebla 0.0089
## lluviamm 0.0089
## vientovelmedia_of 0.0089
## vientovelmax 0.0016
## Temp_prom_of 0.0000
## Temp_max_of 0.0000
## Temp_min_of 0.0000
## Insolacion_acum_MES 0.0000
## Temp_media_acum_MES
##
## Call:
## glm.nb(formula = Cob.T ~ diasnieve + Equitatividad + Riqueza +
## Temp_prom_of + num_lapas + Insolacion_acum_MES + Temp_media_acum_MES,
## data = da, link = "log", init.theta = 98798.18398)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.1621 -0.7971 0.2045 0.5079 0.8745
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -0.648118 1.417469 -0.457 0.648
## diasnieve -0.028228 0.089771 -0.314 0.753
## Equitatividad -0.402682 0.620823 -0.649 0.517
## Riqueza 0.081964 0.127667 0.642 0.521
## Temp_prom_of 0.761558 1.270864 0.599 0.549
## num_lapas -0.015919 0.161545 -0.099 0.922
## Insolacion_acum_MES 0.001583 0.008523 0.186 0.853
## Temp_media_acum_MES -0.004548 0.010490 -0.434 0.665
##
## (Dispersion parameter for Negative Binomial(98798.18) family taken to be 1)
##
## Null deviance: 38.896 on 74 degrees of freedom
## Residual deviance: 33.584 on 67 degrees of freedom
## AIC: 145.6
##
## Number of Fisher Scoring iterations: 1
##
##
## Theta: 98798
## Std. Err.: 2450922
## Warning while fitting theta: iteration limit reached
##
## 2 x log-likelihood: -127.601
## Single term deletions
##
## Model:
## Cob.T ~ diasnieve + Equitatividad + Riqueza + Temp_prom_of +
## num_lapas + Insolacion_acum_MES + Temp_media_acum_MES
## Df Deviance AIC LRT Pr(>Chi)
## <none> 33.584 143.60
## diasnieve 1 33.683 141.70 0.09890 0.7532
## Equitatividad 1 34.013 142.03 0.42907 0.5124
## Riqueza 1 33.991 142.01 0.40718 0.5234
## Temp_prom_of 1 33.942 141.96 0.35824 0.5495
## num_lapas 1 33.594 141.61 0.00983 0.9210
## Insolacion_acum_MES 1 33.618 141.63 0.03444 0.8528
## Temp_media_acum_MES 1 33.771 141.79 0.18742 0.6651
##
## Call:
## glm.nb(formula = Cob.T ~ Mes + diasnieve + Diversidad + Riqueza +
## Temp_prom_of + num_lapas + Insolacion_acum_MES, data = da,
## link = "log", init.theta = 95481.93913)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.1293 -0.8204 0.1547 0.4869 0.8787
##
## Coefficients: (3 not defined because of singularities)
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -0.38608 0.44844 -0.861 0.389
## Mes2 0.04117 0.44454 0.093 0.926
## Mes10 -0.70980 0.51149 -1.388 0.165
## Mes11 -0.39396 0.47237 -0.834 0.404
## Mes12 0.02231 0.40898 0.055 0.956
## diasnieve NA NA NA NA
## Diversidad -0.24933 0.41825 -0.596 0.551
## Riqueza 0.11326 0.15470 0.732 0.464
## Temp_prom_of NA NA NA NA
## num_lapas -0.01350 0.16349 -0.083 0.934
## Insolacion_acum_MES NA NA NA NA
##
## (Dispersion parameter for Negative Binomial(95481.94) family taken to be 1)
##
## Null deviance: 38.896 on 74 degrees of freedom
## Residual deviance: 33.655 on 67 degrees of freedom
## AIC: 145.67
##
## Number of Fisher Scoring iterations: 1
##
##
## Theta: 95482
## Std. Err.: 2329802
## Warning while fitting theta: iteration limit reached
##
## 2 x log-likelihood: -127.672
## Likelihood ratio tests of Negative Binomial Models
##
## Response: Cob.T
## Model
## 1 diasnieve + Equitatividad + Riqueza + Temp_prom_of + num_lapas + Insolacion_acum_MES + Temp_media_acum_MES
## 2 Mes + diasnieve + Diversidad + Riqueza + Temp_prom_of + num_lapas + Insolacion_acum_MES
## theta Resid. df 2 x log-lik. Test df LR stat. Pr(Chi)
## 1 98798.18 67 -127.6006
## 2 95481.94 67 -127.6718 1 vs 2 0 -0.07116038 1
Nothing is significative, assumptions are not meet.
## Loading required package: quantreg
## Loading required package: SparseM
##
## Attaching package: 'SparseM'
## The following object is masked from 'package:base':
##
## backsolve
##
## Attaching package: 'quantreg'
## The following object is masked from 'package:Hmisc':
##
## latex
## The following object is masked from 'package:survival':
##
## untangle.specials
##
## Kruskal-Wallis rank sum test
##
## data: Cob.T by Mes
## Kruskal-Wallis chi-squared = 31.082, df = 4, p-value = 2.945e-06
##
## Call: rq(formula = Cob.T ~ Mes, tau = c(0.25, 0.5, 0.75), data = da)
##
## tau: [1] 0.25
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.63250 0.12070 5.24034 0.00000
## Mes2 0.23750 0.19391 1.22479 0.22476
## Mes10 -0.46500 0.15188 -3.06163 0.00312
## Mes11 -0.41000 0.20887 -1.96292 0.05363
## Mes12 0.21250 0.13151 1.61580 0.11064
##
## Call: rq(formula = Cob.T ~ Mes, tau = c(0.25, 0.5, 0.75), data = da)
##
## tau: [1] 0.5
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.94500 0.09396 10.05727 0.00000
## Mes2 -0.05250 0.09480 -0.55380 0.58148
## Mes10 -0.62500 0.19477 -3.20894 0.00201
## Mes11 -0.37250 0.13253 -2.81066 0.00641
## Mes12 -0.02750 0.09719 -0.28295 0.77805
##
## Call: rq(formula = Cob.T ~ Mes, tau = c(0.25, 0.5, 0.75), data = da)
##
## tau: [1] 0.75
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.99000 0.01721 57.53417 0.00000
## Mes2 -0.02500 0.02818 -0.88721 0.37800
## Mes10 -0.33250 0.10875 -3.05757 0.00316
## Mes11 -0.20000 0.12589 -1.58870 0.11664
## Mes12 -0.02000 0.02862 -0.69871 0.48705
##
## Call: rq(formula = Cob.T ~ Equitatividad, tau = c(0.25, 0.5, 0.75),
## data = da)
##
## tau: [1] 0.25
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.76122 0.20044 3.79778 0.00030
## Equitatividad -0.49746 0.35140 -1.41564 0.16113
##
## Call: rq(formula = Cob.T ~ Equitatividad, tau = c(0.25, 0.5, 0.75),
## data = da)
##
## tau: [1] 0.5
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.97500 0.07522 12.96157 0.00000
## Equitatividad -0.54213 0.21412 -2.53183 0.01350
##
## Call: rq(formula = Cob.T ~ Equitatividad, tau = c(0.25, 0.5, 0.75),
## data = da)
##
## tau: [1] 0.75
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 1.00000 0.01012 98.85468 0.00000
## Equitatividad -0.16011 0.04166 -3.84363 0.00026
## Smoothing formula not specified. Using: y ~ x
## Smoothing formula not specified. Using: y ~ x
## Smoothing formula not specified. Using: y ~ x
## Smoothing formula not specified. Using: y ~ x
##
## Call: rq(formula = Cob.T ~ Riqueza, tau = c(0.25, 0.5, 0.75), data = da)
##
## tau: [1] 0.25
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) -0.01125 0.12376 -0.09090 0.92782
## Riqueza 0.15187 0.03399 4.46759 0.00003
##
## Call: rq(formula = Cob.T ~ Riqueza, tau = c(0.25, 0.5, 0.75), data = da)
##
## tau: [1] 0.5
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.51500 0.22226 2.31709 0.02331
## Riqueza 0.07000 0.05314 1.31727 0.19187
##
## Call: rq(formula = Cob.T ~ Riqueza, tau = c(0.25, 0.5, 0.75), data = da)
##
## tau: [1] 0.75
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.96188 0.05487 17.52851 0.00000
## Riqueza -0.00813 0.01541 -0.52732 0.59957
## Smoothing formula not specified. Using: y ~ x
## Smoothing formula not specified. Using: y ~ x
## Smoothing formula not specified. Using: y ~ x
## Smoothing formula not specified. Using: y ~ x
##
## Call: rq(formula = Cob.T ~ Temp_prom_of, tau = c(0.25, 0.5, 0.75),
## data = da)
##
## tau: [1] 0.25
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.24248 0.07697 3.15042 0.00236
## Temp_prom_of 0.24161 0.04726 5.11280 0.00000
##
## Call: rq(formula = Cob.T ~ Temp_prom_of, tau = c(0.25, 0.5, 0.75),
## data = da)
##
## tau: [1] 0.5
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.49087 0.07970 6.15899 0.00000
## Temp_prom_of 0.18624 0.03467 5.37241 0.00000
##
## Call: rq(formula = Cob.T ~ Temp_prom_of, tau = c(0.25, 0.5, 0.75),
## data = da)
##
## tau: [1] 0.75
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.72942 0.06132 11.89462 0.00000
## Temp_prom_of 0.10096 0.03057 3.30272 0.00148
## Smoothing formula not specified. Using: y ~ x
## Smoothing formula not specified. Using: y ~ x
##
## Call: rq(formula = Cob.T ~ num_lapas, tau = c(0.25, 0.5, 0.75), data = da)
##
## tau: [1] 0.25
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.57250 0.12594 4.54567 0.00002
## num_lapas -0.08250 0.09341 -0.88323 0.38001
##
## Call: rq(formula = Cob.T ~ num_lapas, tau = c(0.25, 0.5, 0.75), data = da)
##
## tau: [1] 0.5
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.86500 0.05993 14.43389 0.00000
## num_lapas -0.11500 0.06637 -1.73280 0.08735
##
## Call: rq(formula = Cob.T ~ num_lapas, tau = c(0.25, 0.5, 0.75), data = da)
##
## tau: [1] 0.75
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.96750 0.01679 57.61059 0.00000
## num_lapas -0.06208 0.04414 -1.40639 0.16385
## Smoothing formula not specified. Using: y ~ x
##
## Call: rq(formula = Cob.T ~ diasnieve, tau = c(0.25, 0.5, 0.75), data = da)
##
## tau: [1] 0.25
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.98562 0.15411 6.39549 0.00000
## diasnieve -0.05844 0.01527 -3.82711 0.00027
##
## Call: rq(formula = Cob.T ~ diasnieve, tau = c(0.25, 0.5, 0.75), data = da)
##
## tau: [1] 0.5
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 1.18556 0.12221 9.70086 0.00000
## diasnieve -0.05361 0.01979 -2.70851 0.00841
##
## Call: rq(formula = Cob.T ~ diasnieve, tau = c(0.25, 0.5, 0.75), data = da)
##
## tau: [1] 0.75
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 1.15694 0.06707 17.24914 0.00000
## diasnieve -0.03139 0.01020 -3.07782 0.00294
## Smoothing formula not specified. Using: y ~ x
## Smoothing formula not specified. Using: y ~ x
##
## Call: rq(formula = Cob.T ~ Insolacion_acum_MES, tau = c(0.25, 0.5,
## 0.75), data = da)
##
## tau: [1] 0.25
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.49115 0.31214 1.57351 0.11992
## Insolacion_acum_MES -0.00004 0.00599 -0.00711 0.99435
##
## Call: rq(formula = Cob.T ~ Insolacion_acum_MES, tau = c(0.25, 0.5,
## 0.75), data = da)
##
## tau: [1] 0.5
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.68193 0.17863 3.81754 0.00028
## Insolacion_acum_MES 0.00190 0.00271 0.70064 0.48575
##
## Call: rq(formula = Cob.T ~ Insolacion_acum_MES, tau = c(0.25, 0.5,
## 0.75), data = da)
##
## tau: [1] 0.75
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.94164 0.04256 22.12326 0.00000
## Insolacion_acum_MES 0.00010 0.00063 0.15359 0.87836
## Smoothing formula not specified. Using: y ~ x
## Smoothing formula not specified. Using: y ~ x
## Loading required package: pander
 | Varname | Value | Std.Err | tvalue | Pval | tau | padj |
---|---|---|---|---|---|---|---|
8 | Mes10 | -0.625 | 0.1948 | -3.209 | 0.00201 | 0.5 | 0.04224 |
6 | Equitatividad | -0.1601 | 0.04166 | -3.844 | 0.00026 | 0.75 | 0.00667 |
22 | Riqueza | 0.1519 | 0.03399 | 4.468 | 3e-05 | 0.25 | 0.00079 |
23 | Temp_prom_of | 0.2416 | 0.04726 | 5.113 | 0 | 0.25 | 7e-05 |
43 | Temp_prom_of | 0.1862 | 0.03467 | 5.372 | 0 | 0.5 | 3e-05 |
62 | Temp_prom_of | 0.101 | 0.03057 | 3.303 | 0.00148 | 0.75 | 0.03266 |
25 | diasnieve | -0.05844 | 0.01527 | -3.827 | 0.00027 | 0.25 | 0.00705 |
## [1] "Mes" "ID_fila" "Foto"
## [4] "Nivel.Intermareal" "Anio" "Cobertura"
## [7] "Diversidad" "Riqueza" "Equitatividad"
## [10] "Estacion" "Cob.T" "num_lapas"
## [13] "cob_lapasT" "RS_T" "RG_T"
## [16] "RM_T" "G_T" "SD_T"
## [19] "Mon_har" "Ade_utr" "Asc_mir"
## [22] "Des_men" "Des_ant" "Pha_ant"
## [25] "Delesseriaceae" "Corallinaceae" "Gig_sko"
## [28] "Iri_cor" "Pal_dec" "Plo_car"
## [31] "Pyr_end" "Cur_rac" "Ulv_NI"
## [34] "lluviamm" "vientovelmax" "diaslluvia"
## [37] "diasnieve" "diasniebla" "Temp_prom_of"
## [40] "Temp_max_of" "Temp_min_of" "Num_dias5menos_of"
## [43] "vientovelmedia_of" "vientodirecprom_of" "Insolacion_acum_MES"
## [46] "Temp_media_acum_MES"
##
## Call: rq(formula = Cob.T ~ Mes, tau = c(0.25, 0.5, 0.75), data = da)
##
## tau: [1] 0.25
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.70750 0.12346 5.73056 0.00000
## Mes2 -0.08750 0.15190 -0.57602 0.56735
## Mes10 -0.35500 0.23688 -1.49863 0.14066
## Mes11 -0.25750 0.21635 -1.19022 0.23994
## Mes12 -0.18500 0.15094 -1.22569 0.22642
##
## Call: rq(formula = Cob.T ~ Mes, tau = c(0.25, 0.5, 0.75), data = da)
##
## tau: [1] 0.5
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.77000 0.09428 8.16758 0.00000
## Mes2 0.01500 0.10326 0.14526 0.88513
## Mes10 -0.02750 0.22280 -0.12343 0.90229
## Mes11 -0.01250 0.13094 -0.09546 0.92435
## Mes12 -0.08000 0.12655 -0.63216 0.53035
##
## Call: rq(formula = Cob.T ~ Mes, tau = c(0.25, 0.5, 0.75), data = da)
##
## tau: [1] 0.75
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.98500 0.05949 16.55799 0.00000
## Mes2 -0.11500 0.08521 -1.34956 0.18362
## Mes10 -0.16000 0.11769 -1.35950 0.18047
## Mes11 -0.11000 0.09201 -1.19558 0.23786
## Mes12 -0.04750 0.11237 -0.42271 0.67443
##
## Call: rq(formula = Cob.T ~ Equitatividad, tau = c(0.25, 0.5, 0.75),
## data = da)
##
## tau: [1] 0.25
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.51465 0.13243 3.88618 0.00030
## Equitatividad 0.10425 0.29194 0.35711 0.72251
##
## Call: rq(formula = Cob.T ~ Equitatividad, tau = c(0.25, 0.5, 0.75),
## data = da)
##
## tau: [1] 0.5
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.75500 0.09395 8.03618 0.00000
## Equitatividad 0.00748 0.21605 0.03462 0.97252
##
## Call: rq(formula = Cob.T ~ Equitatividad, tau = c(0.25, 0.5, 0.75),
## data = da)
##
## tau: [1] 0.75
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.84559 0.05613 15.06417 0.00000
## Equitatividad 0.13649 0.13694 0.99675 0.32369
## Smoothing formula not specified. Using: y ~ x
##
## Call: rq(formula = Cob.T ~ Riqueza, tau = c(0.25, 0.5, 0.75), data = da)
##
## tau: [1] 0.25
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.23417 0.31120 0.75246 0.45530
## Riqueza 0.08583 0.07966 1.07744 0.28645
##
## Call: rq(formula = Cob.T ~ Riqueza, tau = c(0.25, 0.5, 0.75), data = da)
##
## tau: [1] 0.5
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.75375 0.17025 4.42743 0.00005
## Riqueza 0.00125 0.05105 0.02448 0.98056
##
## Call: rq(formula = Cob.T ~ Riqueza, tau = c(0.25, 0.5, 0.75), data = da)
##
## tau: [1] 0.75
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.92000 0.10090 9.11791 0.00000
## Riqueza -0.00875 0.03006 -0.29112 0.77216
## Smoothing formula not specified. Using: y ~ x
##
## Call: rq(formula = Cob.T ~ Temp_prom_of, tau = c(0.25, 0.5, 0.75),
## data = da)
##
## tau: [1] 0.25
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.38265 0.09606 3.98368 0.00022
## Temp_prom_of 0.11224 0.04751 2.36238 0.02209
##
## Call: rq(formula = Cob.T ~ Temp_prom_of, tau = c(0.25, 0.5, 0.75),
## data = da)
##
## tau: [1] 0.5
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.73847 0.15038 4.91069 0.00001
## Temp_prom_of 0.01176 0.07691 0.15297 0.87904
##
## Call: rq(formula = Cob.T ~ Temp_prom_of, tau = c(0.25, 0.5, 0.75),
## data = da)
##
## tau: [1] 0.75
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.84219 0.03982 21.14816 0.00000
## Temp_prom_of 0.05208 0.02763 1.88532 0.06520
## Smoothing formula not specified. Using: y ~ x
## Smoothing formula not specified. Using: y ~ x
## Smoothing formula not specified. Using: y ~ x
## Smoothing formula not specified. Using: y ~ x
##
## Call: rq(formula = Cob.T ~ num_lapas, tau = c(0.25, 0.5, 0.75), data = da)
##
## tau: [1] 0.25
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.61500 0.07063 8.70719 0.00000
## num_lapas -0.11375 0.13075 -0.86996 0.38848
##
## Call: rq(formula = Cob.T ~ num_lapas, tau = c(0.25, 0.5, 0.75), data = da)
##
## tau: [1] 0.5
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.75750 0.03306 22.91249 0.00000
## num_lapas -0.05000 0.11733 -0.42616 0.67182
##
## Call: rq(formula = Cob.T ~ num_lapas, tau = c(0.25, 0.5, 0.75), data = da)
##
## tau: [1] 0.75
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.90250 0.03313 27.24173 0.00000
## num_lapas -0.01000 0.09155 -0.10922 0.91346
## Smoothing formula not specified. Using: y ~ x
##
## Call: rq(formula = Cob.T ~ diasnieve, tau = c(0.25, 0.5, 0.75), data = da)
##
## tau: [1] 0.25
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.81625 0.18474 4.41847 0.00005
## diasnieve -0.03312 0.02596 -1.27597 0.20786
##
## Call: rq(formula = Cob.T ~ diasnieve, tau = c(0.25, 0.5, 0.75), data = da)
##
## tau: [1] 0.5
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.76875 0.16933 4.54004 0.00004
## diasnieve -0.00187 0.02457 -0.07633 0.93946
##
## Call: rq(formula = Cob.T ~ diasnieve, tau = c(0.25, 0.5, 0.75), data = da)
##
## tau: [1] 0.75
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.98000 0.09942 9.85669 0.00000
## diasnieve -0.01107 0.01348 -0.82153 0.41525
## Smoothing formula not specified. Using: y ~ x
##
## Call: rq(formula = Cob.T ~ Insolacion_acum_MES, tau = c(0.25, 0.5,
## 0.75), data = da)
##
## tau: [1] 0.25
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.66963 0.14582 4.59211 0.00003
## Insolacion_acum_MES -0.00183 0.00268 -0.68302 0.49775
##
## Call: rq(formula = Cob.T ~ Insolacion_acum_MES, tau = c(0.25, 0.5,
## 0.75), data = da)
##
## tau: [1] 0.5
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.82886 0.10243 8.09227 0.00000
## Insolacion_acum_MES -0.00162 0.00197 -0.82219 0.41487
##
## Call: rq(formula = Cob.T ~ Insolacion_acum_MES, tau = c(0.25, 0.5,
## 0.75), data = da)
##
## tau: [1] 0.75
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.93549 0.10817 8.64835 0.00000
## Insolacion_acum_MES -0.00096 0.00229 -0.41763 0.67800
## Smoothing formula not specified. Using: y ~ x
##
## Call: rq(formula = Cob.T ~ Insolacion_acum_MES, tau = c(0.25, 0.5,
## 0.75), data = da)
##
## tau: [1] 0.25
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.66963 0.16339 4.09839 0.00015
## Insolacion_acum_MES -0.00183 0.00304 -0.60330 0.54904
##
## Call: rq(formula = Cob.T ~ Insolacion_acum_MES, tau = c(0.25, 0.5,
## 0.75), data = da)
##
## tau: [1] 0.5
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.82886 0.09194 9.01501 0.00000
## Insolacion_acum_MES -0.00162 0.00175 -0.92629 0.35875
##
## Call: rq(formula = Cob.T ~ Insolacion_acum_MES, tau = c(0.25, 0.5,
## 0.75), data = da)
##
## tau: [1] 0.75
##
## Coefficients:
## Value Std. Error t value Pr(>|t|)
## (Intercept) 0.93549 0.10934 8.55618 0.00000
## Insolacion_acum_MES -0.00096 0.00236 -0.40588 0.68656
Varname | Value | Std.Err | tvalue | Pval | tau | padj |
About species scores:
metaMDS’s plot method can add species points as weighted averages of the NMDS site scores if you fit the model using the raw data not the Dij (Dissimilarity matrix). https://stackoverflow.com/questions/14711470/plotting-envfit-vectors-vegan-package-in-ggplot2
## [1] "Mes" "ID_fila" "Foto"
## [4] "Nivel.Intermareal" "Anio" "Cobertura"
## [7] "Diversidad" "Riqueza" "Equitatividad"
## [10] "Estacion" "Cob.T" "num_lapas"
## [13] "cob_lapasT" "RS_T" "RG_T"
## [16] "RM_T" "G_T" "SD_T"
## [19] "Mon_har" "Ade_utr" "Asc_mir"
## [22] "Des_men" "Des_ant" "Pha_ant"
## [25] "Delesseriaceae" "Corallinaceae" "Gig_sko"
## [28] "Iri_cor" "Pal_dec" "Plo_car"
## [31] "Pyr_end" "Cur_rac" "Ulv_NI"
## [34] "lluviamm" "vientovelmax" "diaslluvia"
## [37] "diasnieve" "diasniebla" "Temp_prom_of"
## [40] "Temp_max_of" "Temp_min_of" "Num_dias5menos_of"
## [43] "vientovelmedia_of" "vientodirecprom_of" "Insolacion_acum_MES"
## [46] "Temp_media_acum_MES"
## [1] "Mon_har" "Ade_utr" "Asc_mir" "Des_men"
## [5] "Des_ant" "Pha_ant" "Delesseriaceae" "Corallinaceae"
## [9] "Gig_sko" "Iri_cor" "Pal_dec" "Plo_car"
## [13] "Pyr_end" "Cur_rac" "Ulv_NI"
## Loading required package: permute
## This is vegan 2.3-5
## Run 0 stress 0.1479653
## Run 1 stress 0.1672498
## Run 2 stress 0.157539
## Run 3 stress 0.148847
## Run 4 stress 0.1650021
## Run 5 stress 0.1706966
## Run 6 stress 0.1640186
## Run 7 stress 0.1609926
## Run 8 stress 0.1613058
## Run 9 stress 0.1639545
## Run 10 stress 0.1468707
## ... New best solution
## ... procrustes: rmse 0.05170064 max resid 0.3617867
## Run 11 stress 0.1565993
## Run 12 stress 0.1492111
## Run 13 stress 0.1624997
## Run 14 stress 0.1715144
## Run 15 stress 0.1482944
## Run 16 stress 0.1618768
## Run 17 stress 0.157548
## Run 18 stress 0.1720912
## Run 19 stress 0.1582596
## Run 20 stress 0.1460578
## ... New best solution
## ... procrustes: rmse 0.01971681 max resid 0.1540176
## Run 21 stress 0.1460579
## ... procrustes: rmse 1.86854e-05 max resid 9.322331e-05
## *** Solution reached
## NMDS1 NMDS2
## Mon_har 0.23749918 0.7907169
## Ade_utr 0.17146463 0.8688904
## Asc_mir -0.42483266 0.2893818
## Des_men -0.30717801 -0.1480430
## Des_ant 0.47986208 -1.0290866
## Pha_ant -0.91576273 -1.1548063
## Corallinaceae -0.70493705 -1.1132767
## Gig_sko -0.62087380 -1.1301885
## Iri_cor -0.94030936 -0.7124782
## Pal_dec 1.30966478 -0.2897029
## Plo_car 0.02655735 1.5831324
## Loading required package: RColorBrewer
##
## ***VECTORS
##
## NMDS1 NMDS2 r2 Pr(>r)
## Cobertura 0.67012 -0.74226 0.6197 0.001 ***
## Riqueza 0.46927 -0.88305 0.0515 0.148
## Diversidad -0.58356 0.81207 0.0097 0.707
## Equitatividad -0.40255 0.91540 0.0575 0.127
## num_lapas -0.69657 -0.71749 0.0532 0.144
## diasnieve -0.99999 -0.00523 0.2804 0.001 ***
## Temp_prom_of 0.97386 0.22716 0.4944 0.001 ***
## Insolacion_acum_MES -0.44035 -0.89783 0.0242 0.405
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Permutation: free
## Number of permutations: 999
##
## ***FACTORS:
##
## Centroids:
## NMDS1 NMDS2
## Mes1 0.7789 0.3657
## Mes2 0.3876 -0.1004
## Mes10 -1.1334 -0.0569
## Mes11 -0.3937 -0.0417
## Mes12 0.3606 -0.1667
##
## Goodness of fit:
## r2 Pr(>r)
## Mes 0.3394 0.001 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Permutation: free
## Number of permutations: 999
##
## ***VECTORS
##
## NMDS1 NMDS2 r2 Pr(>r)
## Cover 0.67012 -0.74226 0.6197 0.001 ***
## Richness 0.46927 -0.88305 0.0515 0.157
## Diversity -0.58356 0.81207 0.0097 0.702
## Equit. -0.40255 0.91540 0.0575 0.117
## No.Limpets -0.69657 -0.71749 0.0532 0.127
## SnowDays -0.99999 -0.00523 0.2804 0.001 ***
## Temp 0.97386 0.22716 0.4944 0.001 ***
## Insolation -0.44035 -0.89783 0.0242 0.448
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Permutation: free
## Number of permutations: 999
## png
## 2
## Loading required package: dplyr
##
## Attaching package: 'dplyr'
## The following object is masked from 'package:MASS':
##
## select
## The following objects are masked from 'package:Hmisc':
##
## combine, src, summarize
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
## [1] "Mes" "ID_fila" "Foto"
## [4] "Nivel.Intermareal" "Anio" "Cobertura"
## [7] "Diversidad" "Riqueza" "Equitatividad"
## [10] "Estacion" "Cob.T" "num_lapas"
## [13] "cob_lapasT" "RS_T" "RG_T"
## [16] "RM_T" "G_T" "SD_T"
## [19] "Mon_har" "Ade_utr" "Asc_mir"
## [22] "Des_men" "Des_ant" "Pha_ant"
## [25] "Delesseriaceae" "Corallinaceae" "Gig_sko"
## [28] "Iri_cor" "Pal_dec" "Plo_car"
## [31] "Pyr_end" "Cur_rac" "Ulv_NI"
## [34] "lluviamm" "vientovelmax" "diaslluvia"
## [37] "diasnieve" "diasniebla" "Temp_prom_of"
## [40] "Temp_max_of" "Temp_min_of" "Num_dias5menos_of"
## [43] "vientovelmedia_of" "vientodirecprom_of" "Insolacion_acum_MES"
## [46] "Temp_media_acum_MES"
## [1] "Mon_har" "Ade_utr" "Asc_mir" "Des_men"
## [5] "Des_ant" "Pha_ant" "Delesseriaceae" "Corallinaceae"
## [9] "Gig_sko" "Iri_cor" "Pal_dec" "Plo_car"
## [13] "Pyr_end" "Cur_rac" "Ulv_NI"
## Run 0 stress 0.1385196
## Run 1 stress 0.1390024
## ... procrustes: rmse 0.08292426 max resid 0.3523316
## Run 2 stress 0.1553067
## Run 3 stress 0.1295787
## ... New best solution
## ... procrustes: rmse 0.07842746 max resid 0.3494467
## Run 4 stress 0.1533206
## Run 5 stress 0.1314757
## Run 6 stress 0.130015
## ... procrustes: rmse 0.07791265 max resid 0.3741461
## Run 7 stress 0.1314614
## Run 8 stress 0.1314619
## Run 9 stress 0.1485037
## Run 10 stress 0.1818045
## Run 11 stress 0.1233342
## ... New best solution
## ... procrustes: rmse 0.0276722 max resid 0.1896264
## Run 12 stress 0.1584325
## Run 13 stress 0.1233355
## ... procrustes: rmse 0.000789619 max resid 0.003305323
## *** Solution reached
## NMDS1 NMDS2
## Mon_har -0.6518157 -0.14249785
## Ade_utr -2.1995518 0.06421081
## Asc_mir 0.1215374 -1.04486610
## Des_men 0.3847252 0.26999625
## Pha_ant -0.2444533 1.36788837
## Delesseriaceae 0.5073213 -0.08995343
## Corallinaceae 0.3592252 -0.78006455
## Gig_sko 0.5027030 -0.48476090
## Iri_cor 0.3608004 -0.04581693
## Pal_dec 0.1980402 0.35327182
## Cur_rac 0.7014406 0.09273031
## null device
## 1
##
## ***VECTORS
##
## NMDS1 NMDS2 r2 Pr(>r)
## Cobertura 0.28615 0.95818 0.5079 0.001 ***
## Riqueza 0.82192 -0.56961 0.0029 0.934
## Diversidad -0.92511 -0.37970 0.0059 0.861
## Equitatividad -0.99671 -0.08103 0.0082 0.827
## num_lapas -0.36089 -0.93261 0.1282 0.079 .
## diasnieve 0.06604 -0.99782 0.1110 0.064 .
## Temp_prom_of -0.26082 0.96539 0.2785 0.001 ***
## Insolacion_acum_MES 0.95116 -0.30869 0.1048 0.067 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Permutation: free
## Number of permutations: 999
##
## ***FACTORS:
##
## Centroids:
## NMDS1 NMDS2
## Mes1 0.1627 0.3676
## Mes2 -0.7371 0.1459
## Mes10 0.1510 -0.4629
## Mes11 0.2044 -0.2132
## Mes12 0.1801 0.0894
##
## Goodness of fit:
## r2 Pr(>r)
## Mes 0.2777 0.001 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Permutation: free
## Number of permutations: 999
##
## ***VECTORS
##
## NMDS1 NMDS2 r2 Pr(>r)
## Cobertura 0.28615 0.95818 0.5079 0.001 ***
## Riqueza 0.82192 -0.56961 0.0029 0.932
## Diversidad -0.92511 -0.37970 0.0059 0.873
## Equitatividad -0.99671 -0.08103 0.0082 0.834
## num_lapas -0.36089 -0.93261 0.1282 0.056 .
## diasnieve 0.06604 -0.99782 0.1110 0.066 .
## Temp_prom_of -0.26082 0.96539 0.2785 0.001 ***
## Insolacion_acum_MES 0.95116 -0.30869 0.1048 0.050 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Permutation: free
## Number of permutations: 999