darren — Jun 16, 2014, 9:42 AM
library(vegan)
Loading required package: permute
Loading required package: lattice
This is vegan 2.0-10
# todas as informações são baseadas nos "Vignettes" que faz parte do pacote
# Ordination methods, diversity analysis and other
#functions for community and vegetation ecologists.
# Diversidade de comunidades ecológicas -
# perguntas:
# 1) quantos espécies
# 2) diversidade em um ponto (diversidade alfa)
# 3) diversidade ao longo de uma gradiente ambiental (diversidade beta)
# quantos espécies comparada com a media
# Refs
#Tuomisto H (2010a). \A diversity of beta diver-
#sities: straightening up a concept gone awry. 1.
#Defining beta diversity as a function of alpha and
#gamma diversity." Ecography, 33, 2{22.
#Tuomisto H (2010b). \A diversity of beta diver-
#sities: straightening up a concept gone awry. 2.
#Quantifying beta diversity and related phenomena.
#Ecography, 33, 23{45.
# dados de uma comunidade de arbustos
data(dune)
?dune # o que é
starting httpd help server ... done
mydune<-dune
str(mydune) # estrutura de "dune", 30 espécies em 20 pontos de amostragem
'data.frame': 20 obs. of 30 variables:
$ Belper: num 3 0 2 0 0 0 0 2 0 0 ...
$ Empnig: num 0 0 0 0 0 0 0 0 0 0 ...
$ Junbuf: num 0 3 0 0 0 0 0 0 0 0 ...
$ Junart: num 0 0 0 3 0 0 4 0 0 3 ...
$ Airpra: num 0 0 0 0 0 0 0 0 2 0 ...
$ Elepal: num 0 0 0 8 0 0 4 0 0 5 ...
$ Rumace: num 0 0 0 0 6 0 0 5 0 0 ...
$ Viclat: num 0 0 0 0 0 0 0 0 0 0 ...
$ Brarut: num 0 0 2 4 6 0 2 2 0 4 ...
$ Ranfla: num 0 2 0 2 0 0 2 0 0 2 ...
$ Cirarv: num 0 0 2 0 0 0 0 0 0 0 ...
$ Hyprad: num 0 0 0 0 0 0 0 0 2 0 ...
$ Leoaut: num 5 2 2 0 3 0 3 3 2 2 ...
$ Potpal: num 0 0 0 0 0 0 0 0 0 2 ...
$ Poapra: num 4 2 4 0 3 4 4 2 1 0 ...
$ Calcus: num 0 0 0 3 0 0 0 0 0 0 ...
$ Tripra: num 0 0 0 0 5 0 0 2 0 0 ...
$ Trirep: num 5 2 1 0 5 0 2 2 0 1 ...
$ Antodo: num 0 0 0 0 3 0 0 4 4 0 ...
$ Salrep: num 0 0 0 0 0 0 0 0 0 0 ...
$ Achmil: num 3 0 0 0 2 1 0 2 2 0 ...
$ Poatri: num 7 9 5 2 4 2 4 6 0 0 ...
$ Chealb: num 0 1 0 0 0 0 0 0 0 0 ...
$ Elyrep: num 4 0 4 0 0 4 0 4 0 0 ...
$ Sagpro: num 0 2 5 0 0 0 2 0 0 0 ...
$ Plalan: num 0 0 0 0 5 0 0 5 2 0 ...
$ Agrsto: num 0 5 8 7 0 0 4 0 0 4 ...
$ Lolper: num 5 0 5 0 6 7 4 2 0 0 ...
$ Alogen: num 2 5 2 4 0 0 5 0 0 0 ...
$ Brohor: num 4 0 3 0 0 0 0 2 0 0 ...
names(mydune) # nomes das colunas
[1] "Belper" "Empnig" "Junbuf" "Junart" "Airpra" "Elepal" "Rumace"
[8] "Viclat" "Brarut" "Ranfla" "Cirarv" "Hyprad" "Leoaut" "Potpal"
[15] "Poapra" "Calcus" "Tripra" "Trirep" "Antodo" "Salrep" "Achmil"
[22] "Poatri" "Chealb" "Elyrep" "Sagpro" "Plalan" "Agrsto" "Lolper"
[29] "Alogen" "Brohor"
summary(mydune) # resumo de cada coluna
Belper Empnig Junbuf Junart Airpra
Min. :0.00 Min. :0.0 Min. :0.00 Min. :0.00 Min. :0.00
1st Qu.:0.00 1st Qu.:0.0 1st Qu.:0.00 1st Qu.:0.00 1st Qu.:0.00
Median :0.00 Median :0.0 Median :0.00 Median :0.00 Median :0.00
Mean :0.65 Mean :0.1 Mean :0.65 Mean :0.90 Mean :0.25
3rd Qu.:2.00 3rd Qu.:0.0 3rd Qu.:0.00 3rd Qu.:0.75 3rd Qu.:0.00
Max. :3.00 Max. :2.0 Max. :4.00 Max. :4.00 Max. :3.00
Elepal Rumace Viclat Brarut Ranfla
Min. :0.00 Min. :0.0 Min. :0.0 Min. :0.00 Min. :0.0
1st Qu.:0.00 1st Qu.:0.0 1st Qu.:0.0 1st Qu.:1.50 1st Qu.:0.0
Median :0.00 Median :0.0 Median :0.0 Median :2.00 Median :0.0
Mean :1.25 Mean :0.9 Mean :0.2 Mean :2.45 Mean :0.7
3rd Qu.:1.00 3rd Qu.:0.5 3rd Qu.:0.0 3rd Qu.:4.00 3rd Qu.:2.0
Max. :8.00 Max. :6.0 Max. :2.0 Max. :6.00 Max. :4.0
Cirarv Hyprad Leoaut Potpal Poapra
Min. :0.0 Min. :0.00 Min. :0.0 Min. :0.0 Min. :0.0
1st Qu.:0.0 1st Qu.:0.00 1st Qu.:2.0 1st Qu.:0.0 1st Qu.:0.0
Median :0.0 Median :0.00 Median :2.0 Median :0.0 Median :3.0
Mean :0.1 Mean :0.45 Mean :2.7 Mean :0.2 Mean :2.4
3rd Qu.:0.0 3rd Qu.:0.00 3rd Qu.:3.0 3rd Qu.:0.0 3rd Qu.:4.0
Max. :2.0 Max. :5.00 Max. :6.0 Max. :2.0 Max. :5.0
Calcus Tripra Trirep Antodo Salrep
Min. :0.0 Min. :0.00 Min. :0.00 Min. :0.00 Min. :0.00
1st Qu.:0.0 1st Qu.:0.00 1st Qu.:1.00 1st Qu.:0.00 1st Qu.:0.00
Median :0.0 Median :0.00 Median :2.00 Median :0.00 Median :0.00
Mean :0.5 Mean :0.45 Mean :2.35 Mean :1.05 Mean :0.55
3rd Qu.:0.0 3rd Qu.:0.00 3rd Qu.:3.00 3rd Qu.:2.25 3rd Qu.:0.00
Max. :4.0 Max. :5.00 Max. :6.00 Max. :4.00 Max. :5.00
Achmil Poatri Chealb Elyrep Sagpro
Min. :0.0 Min. :0.00 Min. :0.00 Min. :0.0 Min. :0
1st Qu.:0.0 1st Qu.:0.00 1st Qu.:0.00 1st Qu.:0.0 1st Qu.:0
Median :0.0 Median :4.00 Median :0.00 Median :0.0 Median :0
Mean :0.8 Mean :3.15 Mean :0.05 Mean :1.3 Mean :1
3rd Qu.:2.0 3rd Qu.:5.00 3rd Qu.:0.00 3rd Qu.:4.0 3rd Qu.:2
Max. :4.0 Max. :9.00 Max. :1.00 Max. :6.0 Max. :5
Plalan Agrsto Lolper Alogen Brohor
Min. :0.0 Min. :0.0 Min. :0.0 Min. :0.00 Min. :0.00
1st Qu.:0.0 1st Qu.:0.0 1st Qu.:0.0 1st Qu.:0.00 1st Qu.:0.00
Median :0.0 Median :1.5 Median :2.0 Median :0.00 Median :0.00
Mean :1.3 Mean :2.4 Mean :2.9 Mean :1.80 Mean :0.75
3rd Qu.:3.0 3rd Qu.:4.0 3rd Qu.:6.0 3rd Qu.:3.25 3rd Qu.:0.50
Max. :5.0 Max. :8.0 Max. :7.0 Max. :8.00 Max. :4.00
mydune
Belper Empnig Junbuf Junart Airpra Elepal Rumace Viclat Brarut Ranfla
2 3 0 0 0 0 0 0 0 0 0
13 0 0 3 0 0 0 0 0 0 2
4 2 0 0 0 0 0 0 0 2 0
16 0 0 0 3 0 8 0 0 4 2
6 0 0 0 0 0 0 6 0 6 0
1 0 0 0 0 0 0 0 0 0 0
8 0 0 0 4 0 4 0 0 2 2
5 2 0 0 0 0 0 5 0 2 0
17 0 0 0 0 2 0 0 0 0 0
15 0 0 0 3 0 5 0 0 4 2
10 2 0 0 0 0 0 0 1 2 0
11 0 0 0 0 0 0 0 2 4 0
9 0 0 4 4 0 0 2 0 2 0
18 2 0 0 0 0 0 0 1 6 0
3 2 0 0 0 0 0 0 0 2 0
20 0 0 0 4 0 4 0 0 4 4
14 0 0 0 0 0 4 0 0 0 2
19 0 2 0 0 3 0 0 0 3 0
12 0 0 4 0 0 0 2 0 4 0
7 0 0 2 0 0 0 3 0 2 0
Cirarv Hyprad Leoaut Potpal Poapra Calcus Tripra Trirep Antodo Salrep
2 0 0 5 0 4 0 0 5 0 0
13 0 0 2 0 2 0 0 2 0 0
4 2 0 2 0 4 0 0 1 0 0
16 0 0 0 0 0 3 0 0 0 0
6 0 0 3 0 3 0 5 5 3 0
1 0 0 0 0 4 0 0 0 0 0
8 0 0 3 0 4 0 0 2 0 0
5 0 0 3 0 2 0 2 2 4 0
17 0 2 2 0 1 0 0 0 4 0
15 0 0 2 2 0 0 0 1 0 0
10 0 0 3 0 4 0 0 6 4 0
11 0 2 5 0 4 0 0 3 0 0
9 0 0 2 0 4 0 0 3 0 0
18 0 0 5 0 3 0 0 2 0 3
3 0 0 2 0 5 0 0 2 0 0
20 0 0 2 0 0 3 0 0 0 5
14 0 0 2 2 0 4 0 6 0 0
19 0 5 6 0 0 0 0 2 4 3
12 0 0 2 0 0 0 0 3 0 0
7 0 0 3 0 4 0 2 2 2 0
Achmil Poatri Chealb Elyrep Sagpro Plalan Agrsto Lolper Alogen Brohor
2 3 7 0 4 0 0 0 5 2 4
13 0 9 1 0 2 0 5 0 5 0
4 0 5 0 4 5 0 8 5 2 3
16 0 2 0 0 0 0 7 0 4 0
6 2 4 0 0 0 5 0 6 0 0
1 1 2 0 4 0 0 0 7 0 0
8 0 4 0 0 2 0 4 4 5 0
5 2 6 0 4 0 5 0 2 0 2
17 2 0 0 0 0 2 0 0 0 0
15 0 0 0 0 0 0 4 0 0 0
10 4 4 0 0 0 3 0 6 0 4
11 0 0 0 0 2 3 0 7 0 0
9 0 5 0 6 2 0 3 2 3 0
18 0 0 0 0 0 3 0 2 0 0
3 0 6 0 4 0 0 4 6 7 0
20 0 0 0 0 0 0 5 0 0 0
14 0 0 0 0 0 0 4 0 0 0
19 0 0 0 0 3 0 0 0 0 0
12 0 4 0 0 4 0 4 0 8 0
7 2 5 0 0 0 5 0 6 0 2
# dados ambientais
data(dune.env)
?dune.env # o que é
mydune.env<-dune.env
str(mydune.env) # estrutura de "dune.env",
'data.frame': 20 obs. of 5 variables:
$ A1 : num 3.5 6 4.2 5.7 4.3 2.8 4.2 6.3 4 11.5 ...
$ Moisture : Ord.factor w/ 4 levels "1"<"2"<"4"<"5": 1 4 2 4 1 1 4 1 2 4 ...
$ Management: Factor w/ 4 levels "BF","HF","NM",..: 1 4 4 4 2 4 2 2 3 3 ...
$ Use : Ord.factor w/ 3 levels "Hayfield"<"Haypastu"<..: 2 2 2 3 2 2 3 1 1 2 ...
$ Manure : Ord.factor w/ 5 levels "0"<"1"<"2"<"3"<..: 3 4 5 4 3 5 4 3 1 1 ...
names(mydune.env) # nomes das colunas
[1] "A1" "Moisture" "Management" "Use" "Manure"
summary(mydune.env) # resumo de cada coluna
A1 Moisture Management Use Manure
Min. : 2.80 1:7 BF:3 Hayfield:7 0:6
1st Qu.: 3.50 2:4 HF:5 Haypastu:8 1:3
Median : 4.20 4:2 NM:6 Pasture :5 2:4
Mean : 4.85 5:7 SF:6 3:4
3rd Qu.: 5.72 4:3
Max. :11.50
mydune.env
A1 Moisture Management Use Manure
2 3.5 1 BF Haypastu 2
13 6.0 5 SF Haypastu 3
4 4.2 2 SF Haypastu 4
16 5.7 5 SF Pasture 3
6 4.3 1 HF Haypastu 2
1 2.8 1 SF Haypastu 4
8 4.2 5 HF Pasture 3
5 6.3 1 HF Hayfield 2
17 4.0 2 NM Hayfield 0
15 11.5 5 NM Haypastu 0
10 3.3 2 BF Hayfield 1
11 3.5 1 BF Pasture 1
9 3.7 4 HF Hayfield 1
18 4.6 1 NM Hayfield 0
3 4.3 2 SF Haypastu 4
20 3.5 5 NM Hayfield 0
14 9.3 5 NM Pasture 0
19 3.7 5 NM Hayfield 0
12 5.8 4 SF Haypastu 2
7 2.8 1 HF Pasture 3
# 1) quantos espécies
## numero (riqueza) de espécies em cada ponto ou seja diversidade alfa
specnumber(mydune)
2 13 4 16 6 1 8 5 17 15 10 11 9 18 3 20 14 19 12 7
10 10 13 8 11 5 12 14 7 8 12 9 13 9 10 8 7 9 9 13
plot(specnumber(mydune)) # verificar erros
## numero (riqueza) de espécies em cada tipo de manejo
specnumber(mydune,groups=mydune.env$Management)
BF HF NM SF
16 21 21 21
## diversidade de espécies em cada ponto
diversity(mydune, index="shannon")
2 13 4 16 6 1 8 5 17 15 10 11
2.253 2.100 2.427 1.960 2.346 1.440 2.435 2.544 1.876 1.979 2.399 2.106
9 18 3 20 14 19 12 7
2.494 2.079 2.194 2.048 1.864 2.134 2.114 2.472
diversity(mydune, index="simpson")
2 13 4 16 6 1 8 5 17 15
0.8900 0.8522 0.9007 0.8430 0.9002 0.7346 0.9087 0.9140 0.8356 0.8507
10 11 9 18 3 20 14 19 12 7
0.9032 0.8672 0.9116 0.8615 0.8788 0.8678 0.8333 0.8741 0.8686 0.9075
#Pielou's evenness ("equabilidade J"): J = H0= log(S) :
H<-diversity(mydune, index="shannon")
J <- H/log(specnumber(mydune))
J
2 13 4 16 6 1 8 5 17 15
0.9783 0.9119 0.9461 0.9425 0.9783 0.8950 0.9799 0.9641 0.9642 0.9518
10 11 9 18 3 20 14 19 12 7
0.9653 0.9585 0.9722 0.9464 0.9527 0.9850 0.9577 0.9712 0.9623 0.9637
## diversidade de espécies em tipo de manejo
diversity(mydune, groups=mydune.env$Management,index="shannon")
Error: unused argument (groups = mydune.env$Management)
#NÃO, erro !!!!
## mas sim, tem como fazer usando funções em outro pacote
library(BiodiversityR)
Loading required package: tcltk
diversitycomp(mydune, y=mydune.env, factor1='Management', factor2="Moisture",
index='Shannon' ,method='all', sortit=TRUE, digits=3)
, , = n
Moisture
Management 1 2 4 5
BF 2 1 0 0
HF 3 0 1 1
NM 1 1 0 4
SF 1 2 1 2
, , = Shannon
Moisture
Management 1 2 4 5
BF 2.52 2.40 NA NA
HF 2.57 NA 2.49 2.44
NM 2.08 1.88 NA 2.58
SF 1.44 2.43 2.11 2.38
### e agora para riqueza
diversitycomp(mydune, y=mydune.env, factor1='Management', factor2="Moisture",
index='richness' ,method='all', sortit=TRUE, digits=3)
, , = n
Moisture
Management 1 2 4 5
BF 2 1 0 0
HF 3 0 1 1
NM 1 1 0 4
SF 1 2 1 2
, , = richness
Moisture
Management 1 2 4 5
BF 15 12 NA NA
HF 15 NA 13 12
NM 9 7 NA 15
SF 5 13 9 14
## faltando quantos espécies?
specpool(mydune) # total em todos os amostragens
Species chao chao.se jack1 jack1.se jack2 boot boot.se n
All 30 32.2 3.4 32.9 1.65 33.8 31.5 1.15 20
pool1<-specpool(mydune) # total em todos os amostragens
pool1$Species/pool1$chao # proporçao de espécies na amostragem
[1] 0.93
pool1$chao/pool1$Species # numero de espécies faltando
[1] 1.07
specpool(mydune, mydune.env$Management) # total em tipos de manejo
Species chao chao.se jack1 jack1.se jack2 boot boot.se n
BF 16 17.8 2.19 19.3 2.21 19.8 17.7 1.65 3
HF 21 21.6 1.12 23.4 1.88 22.1 22.6 1.82 5
NM 21 23.2 2.50 26.0 3.29 25.7 23.8 2.30 6
SF 21 31.7 10.27 27.7 3.50 31.4 24.0 1.85 6
pool2<-specpool(mydune, mydune.env$Management) # total em tipos de manejo
pool2
Species chao chao.se jack1 jack1.se jack2 boot boot.se n
BF 16 17.8 2.19 19.3 2.21 19.8 17.7 1.65 3
HF 21 21.6 1.12 23.4 1.88 22.1 22.6 1.82 5
NM 21 23.2 2.50 26.0 3.29 25.7 23.8 2.30 6
SF 21 31.7 10.27 27.7 3.50 31.4 24.0 1.85 6
str(pool2)
'data.frame': 4 obs. of 9 variables:
$ Species : int 16 21 21 21
$ chao : num 17.8 21.6 23.2 31.7
$ chao.se : num 2.19 1.12 2.5 10.27
$ jack1 : num 19.3 23.4 26 27.7
$ jack1.se: num 2.21 1.88 3.29 3.5
$ jack2 : num 19.8 22.1 25.7 31.4
$ boot : num 17.7 22.6 23.8 24
$ boot.se : num 1.65 1.82 2.3 1.85
$ n : int 3 5 6 6
- attr(*, "pool")= Factor w/ 4 levels "BF","HF","NM",..: 1 4 4 4 2 4 2 2 3 3 ...
pool2$Species/pool2$chao # proporção de espécies amostrados
[1] 0.900 0.970 0.903 0.663
pool2$chao-pool2$Species # # numero de espécies "faltando"
[1] 1.786 0.643 2.250 10.667
# acresentar novos dados
pool2$Esp.Prop<-pool2$Species/pool2$chao
pool2$Esp.Falt<-pool2$chao-pool2$Species
pool2
Species chao chao.se jack1 jack1.se jack2 boot boot.se n Esp.Prop
BF 16 17.8 2.19 19.3 2.21 19.8 17.7 1.65 3 0.900
HF 21 21.6 1.12 23.4 1.88 22.1 22.6 1.82 5 0.970
NM 21 23.2 2.50 26.0 3.29 25.7 23.8 2.30 6 0.903
SF 21 31.7 10.27 27.7 3.50 31.4 24.0 1.85 6 0.663
Esp.Falt
BF 1.786
HF 0.643
NM 2.250
SF 10.667
str(pool2)
'data.frame': 4 obs. of 11 variables:
$ Species : int 16 21 21 21
$ chao : num 17.8 21.6 23.2 31.7
$ chao.se : num 2.19 1.12 2.5 10.27
$ jack1 : num 19.3 23.4 26 27.7
$ jack1.se: num 2.21 1.88 3.29 3.5
$ jack2 : num 19.8 22.1 25.7 31.4
$ boot : num 17.7 22.6 23.8 24
$ boot.se : num 1.65 1.82 2.3 1.85
$ n : int 3 5 6 6
$ Esp.Prop: num 0.9 0.97 0.903 0.663
$ Esp.Falt: num 1.786 0.643 2.25 10.667
- attr(*, "pool")= Factor w/ 4 levels "BF","HF","NM",..: 1 4 4 4 2 4 2 2 3 3 ...
# gráficos
sp1<-specaccum(mydune, method = "rarefaction") # rarefaction
#indivíduos em vezes de pontos
sp2<-specaccum(mydune, method = "exact") # exact
sp3<-specaccum(mydune, method = "random") # random = ordem aleatória
sp4<-specaccum(mydune, method = "collector") # collector = na sequencia
windows(width=8,height=8)
par(mfrow=c(2,2)) # 4 gráficos na mesma pagina, 2 colunas e 2 linhas
plot(sp1, ci.type="poly", col="blue", lwd=2, ci.lty=0, ci.col="lightblue")
plot(sp2, ci.type="poly", col="grey", lwd=2, ci.lty=0, ci.col="lightgrey")
plot(sp3, ci.type="poly", col="black", lwd=2, ci.lty=0, ci.col="yellow")
plot(sp4, ci.type="poly", col="blue", lwd=2, ci.lty=0, ci.col="lightblue")
## em cada tipo de manejo?
library(BiodiversityR)
accumcomp(mydune, y=mydune.env, factor='Management', method='exact', legend=FALSE, conditioned=TRUE)
, , = Sites
obs
Management 1 2 3 4 5 6
BF 1 2 3 NA NA NA
HF 1 2 3 4 5 NA
NM 1 2 3 4 5 6
SF 1 2 3 4 5 6
, , = Richness
obs
Management 1 2 3 4 5 6
BF 10.33 14.3 16.0 NA NA NA
HF 12.60 16.7 19.1 20.4 21.0 NA
NM 8.00 12.9 16.2 18.5 20.0 21
SF 9.17 13.6 16.3 18.1 19.7 21
, , = sd
obs
Management 1 2 3 4 5 6
BF 1.247 0.471 0.00 NA NA NA
HF 1.020 1.334 1.73 0.80 0.000 NA
NM 0.816 1.001 1.35 1.64 1.155 0
SF 2.409 1.428 1.23 1.23 0.943 0
accumcomp(mydune, y=mydune.env, factor='Management', method='rarefaction', legend=FALSE, conditioned=TRUE)
, , = Sites
obs
Management 1 2 3 4 5 6
BF 1.000 2.00 3.00 NA NA NA
HF 1.009 2.00 3.00 3.99 5.00 NA
NM 0.993 1.99 3.02 4.01 5.01 6
SF 1.000 2.00 3.00 4.00 5.00 6
, , = Richness
obs
Management 1 2 3 4 5 6
BF 13.6 15.6 16.0 NA NA NA
HF 16.9 19.7 20.6 20.9 21.0 NA
NM 13.3 17.3 19.2 20.2 20.7 21
SF 13.9 17.3 19.0 20.0 20.6 21
, , = sd
obs
Management 1 2 3 4 5 6
BF 1.18 0.586 0.000 NA NA NA
HF 1.41 0.956 0.585 0.285 0.000 NA
NM 1.51 1.377 1.095 0.805 0.493 0
SF 1.54 1.370 1.126 0.865 0.583 0
# exemplo com ambos os gráficos em uma figura
windows(width=8,height=8)
par(mfrow=c(2,1))
accumcomp(mydune, y=mydune.env, factor='Management', method='exact', legend=FALSE, conditioned=TRUE)
, , = Sites
obs
Management 1 2 3 4 5 6
BF 1 2 3 NA NA NA
HF 1 2 3 4 5 NA
NM 1 2 3 4 5 6
SF 1 2 3 4 5 6
, , = Richness
obs
Management 1 2 3 4 5 6
BF 10.33 14.3 16.0 NA NA NA
HF 12.60 16.7 19.1 20.4 21.0 NA
NM 8.00 12.9 16.2 18.5 20.0 21
SF 9.17 13.6 16.3 18.1 19.7 21
, , = sd
obs
Management 1 2 3 4 5 6
BF 1.247 0.471 0.00 NA NA NA
HF 1.020 1.334 1.73 0.80 0.000 NA
NM 0.816 1.001 1.35 1.64 1.155 0
SF 2.409 1.428 1.23 1.23 0.943 0
accumcomp(mydune, y=mydune.env, factor='Management', method='rarefaction', legend=FALSE, conditioned=TRUE)
, , = Sites
obs
Management 1 2 3 4 5 6
BF 1.000 2.00 3.00 NA NA NA
HF 1.009 2.00 3.00 3.99 5.00 NA
NM 0.993 1.99 3.02 4.01 5.01 6
SF 1.000 2.00 3.00 4.00 5.00 6
, , = Richness
obs
Management 1 2 3 4 5 6
BF 13.6 15.6 16.0 NA NA NA
HF 16.9 19.7 20.6 20.9 21.0 NA
NM 13.3 17.3 19.2 20.2 20.7 21
SF 13.9 17.3 19.0 20.0 20.6 21
, , = sd
obs
Management 1 2 3 4 5 6
BF 1.18 0.586 0.000 NA NA NA
HF 1.41 0.956 0.585 0.285 0.000 NA
NM 1.51 1.377 1.095 0.805 0.493 0
SF 1.54 1.370 1.126 0.865 0.583 0
# diversidade beta
# 24 indices
#Koleff, P., Gaston, K.J. and Lennon, J.J.
#(2003) Measuring beta diversity for presence-absence data.
#Journal of Animal Ecology 72, 367382.
z <- betadiver(mydune, "z")
mod <- with(mydune.env, betadisper(z, Management))
mod
Homogeneity of multivariate dispersions
Call: betadisper(d = z, group = Management)
No. of Positive Eigenvalues: 12
No. of Negative Eigenvalues: 7
Average distance to median:
BF HF NM SF
0.308 0.251 0.441 0.363
Eigenvalues for PCoA axes:
PCoA1 PCoA2 PCoA3 PCoA4 PCoA5 PCoA6 PCoA7 PCoA8
1.655 0.887 0.533 0.374 0.287 0.224 0.161 0.081
# gráfico
boxplot(mod)
