Estimadores de Riqueza
Giovanna Pessoa
2023-02-03
Atividade 3 - Estimadores de riqueza
Nesta atividade, vamos estimar a riqueza de uma comunidade
library(iNEXT)
library(devtools)## Carregando pacotes exigidos: usethislibrary(ecodados)
library(ggplot2)
library(vegan)## Carregando pacotes exigidos: permute##
## Attaching package: 'permute'## The following object is masked from 'package:devtools':
##
## check## Carregando pacotes exigidos: lattice## This is vegan 2.6-4library(nlme)
library(dplyr)##
## Attaching package: 'dplyr'## The following object is masked from 'package:nlme':
##
## collapse## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionlibrary(piecewiseSEM)##
## This is piecewiseSEM version 2.1.0.
##
##
## Questions or bugs can be addressed to <LefcheckJ@si.edu>.Utilizaremos dados de 17 espécies de anuros em uma comunidade hipotética, cuja amostragem foi realizada durante 14 dias, na região noroeste de São paulo.
dados_coleta <- poca_anuros
data(mite)
data(mite.xy)
coord <- mite.xy
colnames(coord) <- c("long", "lat")
data(mite.env)
agua <- mite.env[, 2]
head(dados_coleta)## Boana_albopunctata Boana_faber Boana_raniceps Dendropsophus_eliane
## Dia_1 5 0 2 0
## Dia_2 0 0 0 0
## Dia_3 0 0 0 6
## Dia_4 0 0 0 15
## Dia_5 0 0 0 2
## Dia_6 1 0 0 2
## Dendropsophus_melanargyrius Dendropsophus_minutus Dendropsophus_nanus
## Dia_1 0 0 4
## Dia_2 0 2 0
## Dia_3 0 1 3
## Dia_4 0 15 15
## Dia_5 1 8 2
## Dia_6 0 2 2
## Dermatonotus_muelleri Elachistocleis_bicolor Elachistocleis_sp
## Dia_1 0 0 0
## Dia_2 0 0 0
## Dia_3 0 0 0
## Dia_4 3 0 0
## Dia_5 12 0 0
## Dia_6 0 0 0
## Leptodactylus_chaquensis Leptodactylus_fuscus Leptodactylus_labyrinthicus
## Dia_1 0 8 0
## Dia_2 0 3 0
## Dia_3 0 2 0
## Dia_4 0 5 0
## Dia_5 11 4 0
## Dia_6 0 2 0
## Physalameus_cuvieri Physalaemus_nattereri Rhinella_schneideri
## Dia_1 5 0 2
## Dia_2 3 4 1
## Dia_3 4 1 2
## Dia_4 2 0 2
## Dia_5 2 17 1
## Dia_6 2 0 1
## Scinax_fuscovarius
## Dia_1 0
## Dia_2 0
## Dia_3 0
## Dia_4 0
## Dia_5 0
## Dia_6 0Chao 1
Realizando o cálculo do estimador de riqueza de Chao 1. Ele estima o valor absoluto de espécies em uma determinada comunidade.
est_chao1 <- estaccumR(dados_coleta, permutations = 100)## Warning in sqrt(sum(Deriv.Ch1 %*% t(Deriv.Ch1) * (diag(a) - a %*%
## t(a)/S.ACE))): NaNs produzidos
## Warning in sqrt(sum(Deriv.Ch1 %*% t(Deriv.Ch1) * (diag(a) - a %*%
## t(a)/S.ACE))): NaNs produzidos
## Warning in sqrt(sum(Deriv.Ch1 %*% t(Deriv.Ch1) * (diag(a) - a %*%
## t(a)/S.ACE))): NaNs produzidos
## Warning in sqrt(sum(Deriv.Ch1 %*% t(Deriv.Ch1) * (diag(a) - a %*%
## t(a)/S.ACE))): NaNs produzidos
## Warning in sqrt(sum(Deriv.Ch1 %*% t(Deriv.Ch1) * (diag(a) - a %*%
## t(a)/S.ACE))): NaNs produzidos
## Warning in sqrt(sum(Deriv.Ch1 %*% t(Deriv.Ch1) * (diag(a) - a %*%
## t(a)/S.ACE))): NaNs produzidos
## Warning in sqrt(sum(Deriv.Ch1 %*% t(Deriv.Ch1) * (diag(a) - a %*%
## t(a)/S.ACE))): NaNs produzidos
## Warning in sqrt(sum(Deriv.Ch1 %*% t(Deriv.Ch1) * (diag(a) - a %*%
## t(a)/S.ACE))): NaNs produzidos
## Warning in sqrt(sum(Deriv.Ch1 %*% t(Deriv.Ch1) * (diag(a) - a %*%
## t(a)/S.ACE))): NaNs produzidos
## Warning in sqrt(sum(Deriv.Ch1 %*% t(Deriv.Ch1) * (diag(a) - a %*%
## t(a)/S.ACE))): NaNs produzidossummary(est_chao1, display = "chao")## $chao
## N Chao 2.5% 97.5% Std.Dev
## Dia_1 1 6.765000 3.0000 12.33333 2.734906
## Dia_9 2 9.511619 6.0000 16.52500 3.016299
## Dia_14 3 11.441333 8.0000 16.75000 2.482803
## Dia_4 4 12.549000 9.0000 18.17500 2.385277
## Dia_7 5 13.684167 9.4750 20.00000 2.534064
## Dia_8 6 14.413333 10.0000 22.00000 2.755515
## Dia_3 7 15.048333 10.4750 22.00000 2.931819
## Dia_10 8 15.995000 11.0000 22.00000 2.781155
## Dia_5 9 17.000000 12.2375 22.00000 2.851546
## Dia_6 10 17.795000 12.4750 22.00000 2.591843
## Dia_2 11 18.510000 14.4750 22.00000 2.322464
## Dia_11 12 19.330000 15.2375 22.00000 1.967180
## Dia_12 13 19.560000 15.5000 22.00000 1.458656
## Dia_13 14 20.000000 20.0000 20.00000 0.000000
##
## attr(,"class")
## [1] "summary.poolaccum"Construindo o gráfico
resultados <- summary(est_chao1, display = c("S", "chao"))
res_chao <- cbind(resultados$chao[, 1:4], resultados$S[, 2:4])
res_chao <- as.data.frame(res_chao)
colnames(res_chao) <- c("Amostras", "Chao", "C_inferior", "C_superior",
"Riqueza", "R_inferior", "R_superior")ggplot(res_chao, aes(y = Riqueza, x = Amostras)) +
geom_point(aes(y = Chao, x = Amostras + 0.1), size = 4,
color = "purple", alpha = 0.7) +
geom_point(aes(y = Riqueza, x = Amostras), size = 4,
color = "cyan4", alpha = 0.7) +
geom_point(y = 7.5, x = 9, size = 4, color = "purple", alpha = 0.7) +
geom_point(y = 5.9, x = 9, size = 4, color = "cyan4", alpha = 0.7) +
geom_label(y = 7.5, x = 12, label = "Riqueza estimada - Chao 1") +
geom_label(y = 5.9, x = 11.3, label = "Riqueza observada") +
geom_line(aes(y = Chao, x = Amostras), color = "purple") +
geom_line(aes(y = Riqueza, x = Amostras), color = "cyan4") +
geom_linerange(aes(ymin = C_inferior, ymax = C_superior,
x = Amostras + 0.1), color = "purple") +
geom_linerange(aes(ymin = R_inferior, ymax = R_superior,
x = Amostras), color = "cyan4") +
scale_x_continuous(limits = c(1, 15), breaks = seq(1, 15, 1)) +
labs (x = "Número de amostras", y = "Riqueza estimada - Chao 1") +
tema_livro()
Este gráfico representa nossa análise de um estimador simples do número de espécies. Esse número é uma forma bruta de espécies raras na determinada amostra analisada, segundo o estimador de Chao 1, que é relacionado com a abundância das espécies. Há a possibilidade de encontrar mais três espécies, se a amostragem fosse maior.
ACE
Agora, iremos analisar a abundância pelo estimador de ACE. Esse estimador nos permite definir os limites para considerarmos se uma espécie é rara ou não em determinada comunidade. Vamos fazer o cálculo.
est_ace <- estaccumR(dados_coleta, permutations = 100)## Warning in sqrt(sum(Deriv.Ch1 %*% t(Deriv.Ch1) * (diag(a) - a %*%
## t(a)/S.ACE))): NaNs produzidos
## Warning in sqrt(sum(Deriv.Ch1 %*% t(Deriv.Ch1) * (diag(a) - a %*%
## t(a)/S.ACE))): NaNs produzidos
## Warning in sqrt(sum(Deriv.Ch1 %*% t(Deriv.Ch1) * (diag(a) - a %*%
## t(a)/S.ACE))): NaNs produzidos
## Warning in sqrt(sum(Deriv.Ch1 %*% t(Deriv.Ch1) * (diag(a) - a %*%
## t(a)/S.ACE))): NaNs produzidos
## Warning in sqrt(sum(Deriv.Ch1 %*% t(Deriv.Ch1) * (diag(a) - a %*%
## t(a)/S.ACE))): NaNs produzidos
## Warning in sqrt(sum(Deriv.Ch1 %*% t(Deriv.Ch1) * (diag(a) - a %*%
## t(a)/S.ACE))): NaNs produzidos
## Warning in sqrt(sum(Deriv.Ch1 %*% t(Deriv.Ch1) * (diag(a) - a %*%
## t(a)/S.ACE))): NaNs produzidos
## Warning in sqrt(sum(Deriv.Ch1 %*% t(Deriv.Ch1) * (diag(a) - a %*%
## t(a)/S.ACE))): NaNs produzidos
## Warning in sqrt(sum(Deriv.Ch1 %*% t(Deriv.Ch1) * (diag(a) - a %*%
## t(a)/S.ACE))): NaNs produzidos
## Warning in sqrt(sum(Deriv.Ch1 %*% t(Deriv.Ch1) * (diag(a) - a %*%
## t(a)/S.ACE))): NaNs produzidos
## Warning in sqrt(sum(Deriv.Ch1 %*% t(Deriv.Ch1) * (diag(a) - a %*%
## t(a)/S.ACE))): NaNs produzidossummary(est_ace, display = "ace")## $ace
## N ACE 2.5% 97.5% Std.Dev
## Dia_8 1 7.683961 3.545190 13.71429 2.928246
## Dia_5 2 10.218268 6.146771 16.67297 2.868331
## Dia_13 3 11.280857 7.475000 16.32215 2.382129
## Dia_2 4 12.332902 8.636160 17.47496 2.453243
## Dia_4 5 13.238731 9.146513 19.36689 2.459454
## Dia_9 6 13.710617 10.000000 18.90807 2.325098
## Dia_1 7 14.877128 10.400335 20.82837 2.630076
## Dia_14 8 15.779437 11.000000 22.34773 2.947395
## Dia_10 9 17.444051 12.436721 24.60822 3.624231
## Dia_11 10 19.196907 13.497706 25.51766 3.931383
## Dia_12 11 20.687666 13.933641 25.72368 3.856975
## Dia_7 12 22.282204 17.238095 25.72368 3.436633
## Dia_3 13 23.578782 17.676471 25.72368 2.671744
## Dia_6 14 24.703704 24.703704 24.70370 0.000000
##
## attr(,"class")
## [1] "summary.poolaccum"Visualizaçãp de resultados com intervalo de confiança de 95%, a partir de um gráfico.
resultados_ace <- summary(est_ace, display = c("S", "ace"))
res_ace <- cbind(resultados_ace$ace[, 1:4], resultados_ace$S[, 2:4])
res_ace <- as.data.frame(res_ace)
colnames(res_ace) <- c("Amostras", "ACE", "ACE_inferior", "ACE_superior",
"Riqueza", "R_inferior", "R_superior")ggplot(res_ace, aes(y = Riqueza, x = Amostras)) +
geom_point(aes(y = ACE, x = Amostras + 0.1), size = 4,
color = "purple", alpha = 0.7) +
geom_point(aes(y = Riqueza, x = Amostras), size = 4,
color = "cyan4", alpha = 0.7) +
geom_point(y = 7.5, x = 9, size = 4, color = "purple", alpha = 0.7) +
geom_point(y = 5.9, x = 9, size = 4, color = "cyan4", alpha = 0.7) +
geom_label(y = 7.5, x = 11.7, label = "Riqueza estimada - ACE") +
geom_label(y = 5.9, x = 11.3, label = "Riqueza observada") +
geom_line(aes(y = ACE, x = Amostras), color = "purple") +
geom_line(aes(y = Riqueza, x = Amostras), color = "cyan4") +
geom_linerange(aes(ymin = ACE_inferior, ymax = ACE_superior,
x = Amostras + 0.1), color = "purple") +
geom_linerange(aes(ymin = R_inferior, ymax = R_superior,
x = Amostras), color = "cyan4") +
scale_x_continuous(limits = c(1, 15), breaks = seq(1, 15, 1)) +
labs(x = "Número de amostras", y = "Riqueza estimada - ACE") +
tema_livro()
### Possibilidade de encontrar mmais 7 espécies, se a amostragem fosse
maior.
Chao 2
Vamos analisar o índice de Chao 2. Esse índice realiza uma analise com o uso de dados baseado na presença ou ausência de espécies, e leva em consideração a distribuição das mesmas.
est_chao2 <- poolaccum(dados_coleta, permutations = 100)
summary(est_chao2, display = "chao")## $chao
## N Chao 2.5% 97.5% Std.Dev
## [1,] 3 14.32467 8.269444 25.94583 4.431597
## [2,] 4 14.96409 9.395000 27.52500 4.841077
## [3,] 5 15.83693 10.260000 27.16500 4.593428
## [4,] 6 18.54458 11.120660 35.41667 6.467817
## [5,] 7 19.90786 11.176786 35.57500 6.827182
## [6,] 8 20.90573 11.530469 37.43750 6.728372
## [7,] 9 23.21889 12.888889 38.77778 7.266839
## [8,] 10 25.91000 13.900000 40.70375 7.629032
## [9,] 11 28.04182 18.540909 39.27273 7.170347
## [10,] 12 29.81208 21.333333 39.45833 5.912932
## [11,] 13 30.91077 22.384615 39.61538 5.038323
## [12,] 14 33.71429 33.714286 33.71429 0.000000
##
## attr(,"class")
## [1] "summary.poolaccum"Vamos visualizar esses resultados com um intervalo de 95% de confiança.
resultados_chao2 <- summary(est_chao2, display = c("S", "chao"))
res_chao2 <- cbind(resultados_chao2$chao[, 1:4], resultados_chao2$S[, 2:4])
res_chao2 <- as.data.frame(res_chao2)
colnames(res_chao2) <- c("Amostras", "Chao2", "C_inferior", "C_superior",
"Riqueza", "R_inferior", "R_superior")ggplot(res_chao2, aes(y = Riqueza, x = Amostras)) +
geom_point(aes(y = Chao2, x = Amostras + 0.1), size = 4,
color = "purple", alpha = 0.7) +
geom_point(aes(y = Riqueza, x = Amostras), size = 4,
color = "cyan4", alpha = 0.7) +
geom_point(y = 9.8, x = 10, size = 4, color = "purple", alpha = 0.7) +
geom_point(y = 7.7, x = 10, size = 4, color = "cyan4", alpha = 0.7) +
geom_label(y = 9.8, x = 12.95, label = "Riqueza estimada - Chao 2") +
geom_label(y = 7.7, x = 12.3, label = "Riqueza observada") +
geom_line(aes(y = Chao2, x = Amostras), color = "purple") +
geom_line(aes(y = Riqueza, x = Amostras), color = "cyan4") +
geom_linerange(aes(ymin = C_inferior, ymax = C_superior,
x = Amostras + 0.1), color = "purple") +
geom_linerange(aes(ymin = R_inferior, ymax = R_superior,
x = Amostras), color = "cyan4") +
scale_x_continuous(limits = c(1, 15), breaks = seq(1, 15, 1)) +
labs(x = "Número de amostras", y = "Riqueza estimada - Chao 2") +
tema_livro()
De acordo com os dados e com o número de espécies raras, o estimador mostrou a possibilidade de existência de mais dezesseis espécies na amostra, caso a amostragem fosse maior.
Jackknife 1
O estimador Jackknife 1 apresenta uma análise baseada no número de espécies de apenas uma única amostra.
est_jack1 <- poolaccum(dados_coleta, permutations = 100)
summary(est_jack1, display = "jack1")## $jack1
## N Jackknife 1 2.5% 97.5% Std.Dev
## [1,] 3 13.79667 8.82500 18.50833 2.665360
## [2,] 4 15.00750 9.61875 20.25000 2.770346
## [3,] 5 16.07600 9.80000 22.40000 3.028855
## [4,] 6 16.77167 11.66667 22.66667 2.907540
## [5,] 7 17.23429 11.78214 23.38214 2.918498
## [6,] 8 18.02125 13.29062 23.58437 2.671460
## [7,] 9 18.77444 13.31111 23.68889 2.476449
## [8,] 10 19.65200 15.22750 23.77250 2.257087
## [9,] 11 20.20636 15.25000 24.27273 2.264608
## [10,] 12 21.12583 16.75000 23.41667 2.021611
## [11,] 13 21.83154 18.69231 23.46154 1.417156
## [12,] 14 22.57143 22.57143 22.57143 0.000000
##
## attr(,"class")
## [1] "summary.poolaccum"#> $jack1Visualização dos dados com intervalo de 95% de confiança.
resultados_jack1 <- summary(est_jack1, display = c("S", "jack1"))
res_jack1 <- cbind(resultados_jack1$jack1[, 1:4], resultados_jack1$S[, 2:4])
res_jack1 <- as.data.frame(res_jack1)
colnames(res_jack1) <- c("Amostras", "JACK1", "JACK1_inferior", "JACK1_superior",
"Riqueza", "R_inferior", "R_superior")ggplot(res_jack1, aes(y = Riqueza, x = Amostras)) +
geom_point(aes(y = JACK1, x = Amostras + 0.1), size = 4,
color = "purple", alpha = 0.7) +
geom_point(aes(y = Riqueza, x = Amostras), size = 4,
color = "cyan4", alpha = 0.7) +
geom_point(y = 9.9, x = 9, size = 4, color = "purple", alpha = 0.7) +
geom_point(y = 8.6, x = 9, size = 4, color = "cyan4", alpha = 0.7) +
geom_label(y = 9.9, x = 12.5, label = "Riqueza estimada - Jackknife 1") +
geom_label(y = 8.6, x = 11.5, label = "Riqueza observada") +
geom_line(aes(y = JACK1, x = Amostras), color = "purple") +
geom_line(aes(y = Riqueza, x = Amostras), color = "cyan4") +
geom_linerange(aes(ymin = JACK1_inferior, ymax = JACK1_superior,
x = Amostras + 0.1), color = "purple") +
geom_linerange(aes(ymin = R_inferior, ymax = R_superior,
x = Amostras), color = "cyan4") +
scale_x_continuous(limits = c(1, 15), breaks = seq(1, 15, 1)) +
labs(x = "Número de amostras", y = "Riqueza estimada - Jackknife 1") +
tema_livro()
O estimador Jackknife 1 encontrou a possibilidade de existência de mais seis espécies em uma amostragem maior.
Jackknife 2
Estimador que se baseia no número de espécies que ocorrem em uma amostra e em exatamente duas amostras.
est_jack2 <- poolaccum(dados_coleta, permutations = 100)
summary(est_jack2, display = "jack2")## $jack2
## N Jackknife 2 2.5% 97.5% Std.Dev
## [1,] 3 14.60000 7.666667 21.50000 3.393894
## [2,] 4 15.94667 9.500000 22.41667 3.474323
## [3,] 5 17.25850 10.097500 24.63875 4.000688
## [4,] 6 18.43133 11.840000 26.43333 3.812625
## [5,] 7 19.34143 13.447619 27.21250 3.815575
## [6,] 8 20.26036 13.321429 28.39777 4.008002
## [7,] 9 21.59444 14.463194 27.98611 3.876177
## [8,] 10 22.47678 14.977778 30.60000 3.770115
## [9,] 11 23.78355 15.718182 28.35455 3.358209
## [10,] 12 24.95712 18.492424 28.49242 2.977387
## [11,] 13 25.76718 21.301282 27.76859 2.015644
## [12,] 14 26.92308 26.923077 26.92308 0.000000
##
## attr(,"class")
## [1] "summary.poolaccum"Vamos visualizar os dados com intervalo de confiança de 95%.
resultados_jack2 <- summary(est_jack2, display = c("S", "jack2"))
res_jack2 <- cbind(resultados_jack2$jack2[, 1:4], resultados_jack2$S[, 2:4])
res_jack2 <- as.data.frame(res_jack2)
colnames(res_jack2) <- c("Amostras", "JACK2", "JACK2_inferior", "JACK2_superior",
"Riqueza", "R_inferior", "R_superior")ggplot(res_jack2, aes(y = Riqueza, x = Amostras)) +
geom_point(aes(y = JACK2, x = Amostras + 0.1), size = 4,
color = "purple", alpha = 0.7) +
geom_point(aes(y = Riqueza, x = Amostras), size = 4,
color = "cyan4", alpha = 0.7) +
geom_point(y = 9.9, x = 9, size = 4, color = "purple", alpha = 0.7) +
geom_point(y = 8.2, x = 9, size = 4, color = "cyan4", alpha = 0.7) +
geom_label(y = 9.9, x = 12.5, label = "Riqueza estimada - Jackknife 2") +
geom_label(y = 8.2, x = 11.5, label = "Riqueza observada") +
geom_line(aes(y = JACK2, x = Amostras), color = "purple") +
geom_line(aes(y = Riqueza, x = Amostras), color = "cyan4") +
geom_linerange(aes(ymin = JACK2_inferior, ymax = JACK2_superior,
x = Amostras + 0.1), color = "purple") +
geom_linerange(aes(ymin = R_inferior, ymax = R_superior,
x = Amostras), color = "cyan4") +
scale_x_continuous(limits = c(1, 15), breaks = seq(1, 15, 1)) +
labs(x = "Número de amostras", y = "Riqueza estimada - Jackknife 2") +
tema_livro()
De acordo com o estimador Jackknife 2, há a possibilidade de existência de mais dez espécies em uma amostragem maior.
Bootstrap
O estimador Bootstrap se caracteriza por analisar a riqueza total, não se restringindo a espécies raras.
est_boot <- poolaccum(dados_coleta, permutations = 100)
summary(est_boot, display = "boot")## $boot
## N Bootstrap 2.5% 97.5% Std.Dev
## [1,] 3 11.92889 8.499074 16.52037 2.2259022
## [2,] 4 12.79918 8.559668 17.26660 2.2616562
## [3,] 5 13.72744 9.511680 18.48602 2.1304637
## [4,] 6 14.08845 9.942482 18.36809 2.2053123
## [5,] 7 14.78743 10.622544 18.98684 2.2082158
## [6,] 8 15.32154 11.730262 19.31007 2.1264109
## [7,] 9 16.28693 11.831942 19.32715 2.0310410
## [8,] 10 17.04330 12.959856 19.69951 1.9211687
## [9,] 11 17.58096 13.878679 19.81428 1.7499672
## [10,] 12 18.25513 16.020003 19.58719 1.2774487
## [11,] 13 18.87397 16.570376 19.59107 0.9155631
## [12,] 14 19.27832 19.278321 19.27832 0.0000000
##
## attr(,"class")
## [1] "summary.poolaccum"Vamos visualizar os dados com intervalo de confiança de 95%.
resultados_boot <- summary(est_boot, display = c("S", "boot"))
res_boot <- cbind(resultados_boot$boot[,1:4], resultados_boot$S[,2:4])
res_boot <- as.data.frame(res_boot)
colnames(res_boot) <- c("Amostras", "BOOT", "BOOT_inferior", "BOOT_superior",
"Riqueza", "R_inferior", "R_superior")ggplot(res_boot, aes(y = Riqueza, x = Amostras)) +
geom_point(aes(y = BOOT, x = Amostras + 0.1), size = 4,
color = "purple", alpha = 0.7) +
geom_point(aes(y = Riqueza, x = Amostras), size = 4,
color = "cyan4", alpha = 0.7) +
geom_point(y = 10.4, x = 9, size = 4, color = "purple", alpha = 0.7) +
geom_point(y = 9.3, x = 9, size = 4, color = "cyan4", alpha = 0.7) +
geom_label(y = 10.4, x = 12.3, label = "Riqueza estimada - Bootstrap") +
geom_label(y = 9.3, x = 11.5, label = "Riqueza observada") +
geom_line(aes(y = BOOT, x = Amostras), color = "purple") +
geom_line(aes(y = Riqueza, x = Amostras), color = "cyan4") +
geom_linerange(aes(ymin = BOOT_inferior, ymax = BOOT_superior,
x = Amostras + 0.1), color = "purple") +
geom_linerange(aes(ymin = R_inferior, ymax = R_superior,
x = Amostras), color = "cyan4") +
scale_x_continuous(limits = c(1, 15), breaks = seq(1, 15, 1)) +
labs(x = "Número de amostras", y = "Riqueza estimada - Bootstrap") +
tema_livro()
Exercícios
11.1
Cap11_exercicio1## sp1 sp2 sp3 sp4 sp5 sp6 sp7 sp8 sp9 sp10 sp11 sp12 sp13 sp14 sp15
## Amostra_1 0 0 0 18 1 0 0 0 1 0 0 0 0 0 7
## Amostra_2 2 0 0 7 0 0 0 0 0 0 0 0 0 0 0
## Amostra_3 0 0 1 17 3 0 0 2 2 0 0 0 0 0 4
## Amostra_4 0 0 0 9 2 0 0 1 0 0 0 0 0 0 0
## Amostra_5 0 1 1 9 8 0 1 4 0 0 0 0 0 0 0
## Amostra_6 2 0 1 8 11 0 0 0 0 0 0 1 0 0 0
## Amostra_7 0 2 0 3 8 1 0 1 0 0 0 0 0 0 0
## Amostra_8 2 0 1 10 1 0 0 1 0 0 1 0 0 0 1
## Amostra_9 0 0 2 12 2 0 0 1 0 0 0 0 0 0 0
## Amostra_10 2 1 0 1 3 0 0 2 2 0 0 0 0 1 0
## Amostra_11 1 0 0 38 0 0 0 0 1 0 0 0 0 0 0
## Amostra_12 1 0 4 29 3 0 0 1 0 0 0 0 0 0 0
## Amostra_13 0 3 0 2 5 0 0 2 0 0 0 0 0 0 0
## Amostra_14 0 0 0 1 5 0 0 2 0 0 0 0 0 0 0
## Amostra_15 0 0 0 2 4 0 0 0 0 0 0 0 0 0 0
## Amostra_16 1 0 0 7 6 0 0 1 1 0 0 0 0 0 0
## Amostra_17 0 0 0 25 5 0 0 3 0 0 0 0 0 0 0
## Amostra_18 0 0 0 16 11 0 0 0 0 0 0 1 0 0 0
## Amostra_19 2 0 0 17 2 0 0 0 1 0 0 0 0 0 2
## Amostra_20 0 0 2 4 6 0 0 3 0 0 0 0 0 0 0
## Amostra_21 2 0 2 13 17 0 0 0 0 0 0 2 0 0 1
## Amostra_22 0 0 0 4 3 0 0 2 1 0 0 2 0 0 2
## Amostra_23 1 0 3 27 2 0 0 1 0 0 0 0 0 0 0
## Amostra_24 1 1 2 29 5 0 0 0 1 0 0 0 0 0 0
## Amostra_25 1 0 0 13 10 0 0 0 0 0 0 1 0 0 0
## Amostra_26 1 2 1 12 3 0 0 0 0 0 0 0 1 0 1
## Amostra_27 1 0 1 11 1 0 0 2 0 0 0 1 0 0 1
## Amostra_28 0 0 0 17 2 0 0 1 0 0 0 0 0 0 0
## Amostra_29 1 1 0 42 2 0 0 0 0 0 0 0 0 0 0
## Amostra_30 0 0 0 16 5 0 0 1 0 1 0 0 0 0 0
## sp16 sp17 sp18 sp19 sp20 sp21 sp22 sp23 sp24 sp25 sp26 sp27 sp28
## Amostra_1 0 0 0 0 0 0 0 0 0 0 0 0 0
## Amostra_2 0 0 0 0 0 0 0 0 0 4 2 0 0
## Amostra_3 0 1 0 0 0 0 1 0 0 3 1 0 8
## Amostra_4 0 0 0 0 0 0 0 0 0 1 0 0 2
## Amostra_5 0 0 0 0 0 0 0 0 0 2 1 1 1
## Amostra_6 0 0 0 0 1 0 1 0 1 0 0 0 0
## Amostra_7 0 0 0 0 0 0 0 0 0 0 0 1 5
## Amostra_8 0 0 0 0 0 0 0 0 0 2 0 0 2
## Amostra_9 0 0 0 0 0 0 1 0 0 1 2 0 0
## Amostra_10 0 0 0 0 0 0 0 0 0 0 2 1 3
## Amostra_11 0 0 0 0 0 0 1 0 0 5 1 0 0
## Amostra_12 2 0 0 0 0 0 0 0 0 5 0 0 2
## Amostra_13 0 2 0 0 0 0 0 0 0 0 2 0 2
## Amostra_14 0 0 0 0 0 0 0 1 0 0 1 0 3
## Amostra_15 0 0 0 1 0 0 0 0 0 0 0 0 1
## Amostra_16 0 0 0 0 0 0 1 0 0 0 0 0 2
## Amostra_17 0 2 0 0 0 1 0 0 0 1 0 0 3
## Amostra_18 0 0 0 1 0 0 2 0 0 1 0 0 9
## Amostra_19 1 0 0 0 0 0 1 0 0 1 0 0 1
## Amostra_20 1 0 0 0 0 1 0 0 0 4 3 0 5
## Amostra_21 1 0 0 0 0 0 0 1 0 14 1 0 0
## Amostra_22 0 0 1 0 0 0 0 0 0 0 1 0 1
## Amostra_23 0 1 0 0 0 0 0 0 0 2 0 0 0
## Amostra_24 0 1 0 0 0 0 0 1 0 4 1 0 3
## Amostra_25 0 0 0 0 0 0 0 0 0 3 0 1 2
## Amostra_26 0 0 0 0 0 0 0 0 0 7 0 0 1
## Amostra_27 1 0 0 0 0 0 0 0 0 0 0 0 0
## Amostra_28 0 0 0 0 0 0 0 0 0 2 0 1 0
## Amostra_29 0 0 0 0 0 0 0 0 0 14 1 0 0
## Amostra_30 0 1 0 0 0 0 4 1 0 1 0 1 7
## sp29 sp30 sp31 sp32 sp33 sp34 sp35 sp36 sp37 sp38 sp39 sp40 sp41
## Amostra_1 0 0 0 3 0 0 38 0 0 0 0 0 0
## Amostra_2 0 0 0 0 0 0 7 0 0 0 1 1 0
## Amostra_3 0 0 3 2 0 0 30 0 0 0 0 0 0
## Amostra_4 0 0 0 0 0 0 6 0 1 0 3 0 0
## Amostra_5 0 0 0 0 0 1 9 0 0 0 2 0 0
## Amostra_6 0 0 0 0 0 0 7 1 0 0 0 0 0
## Amostra_7 1 0 1 0 0 0 5 0 0 0 8 0 0
## Amostra_8 0 0 0 1 0 0 14 0 0 0 1 0 0
## Amostra_9 0 0 0 0 0 0 2 0 0 0 2 3 0
## Amostra_10 0 0 1 0 0 0 13 0 0 0 1 0 0
## Amostra_11 0 0 1 0 0 0 14 0 0 0 0 0 0
## Amostra_12 0 0 0 2 0 0 14 0 0 0 0 0 0
## Amostra_13 0 0 2 0 0 0 1 0 0 0 1 1 0
## Amostra_14 0 1 1 0 0 0 0 0 0 0 1 0 0
## Amostra_15 0 0 2 0 0 0 3 0 0 0 0 0 0
## Amostra_16 0 1 0 0 0 0 1 0 0 0 2 0 0
## Amostra_17 0 0 0 0 0 0 23 0 0 0 7 0 1
## Amostra_18 0 0 0 1 0 0 6 0 0 0 2 0 0
## Amostra_19 0 0 0 1 0 0 10 0 0 0 1 0 0
## Amostra_20 0 0 1 0 0 0 14 0 0 0 1 1 0
## Amostra_21 0 0 0 0 0 0 12 0 0 0 0 1 0
## Amostra_22 0 0 0 0 0 0 3 0 0 0 1 1 0
## Amostra_23 0 0 1 0 0 0 4 0 0 0 5 0 0
## Amostra_24 0 0 1 3 1 0 16 0 0 0 1 1 0
## Amostra_25 0 0 0 0 0 0 5 0 0 0 3 1 0
## Amostra_26 0 0 0 0 0 0 4 0 0 0 0 0 0
## Amostra_27 0 0 0 0 0 0 6 0 0 0 0 1 0
## Amostra_28 0 0 0 1 0 0 55 0 0 0 2 0 0
## Amostra_29 0 0 0 2 0 0 58 0 0 0 0 0 0
## Amostra_30 0 0 0 0 0 0 11 0 0 1 0 0 0
## sp42 sp43 sp44 sp45 sp46 sp47 sp48 sp49 sp50
## Amostra_1 0 0 0 0 0 0 0 2 0
## Amostra_2 0 0 0 0 0 0 0 0 0
## Amostra_3 0 0 0 0 0 0 0 0 0
## Amostra_4 0 0 0 0 0 0 0 3 1
## Amostra_5 0 0 0 0 0 0 0 0 0
## Amostra_6 0 0 0 0 0 0 0 0 0
## Amostra_7 0 0 0 0 1 0 0 3 0
## Amostra_8 0 0 0 0 0 0 0 3 0
## Amostra_9 2 0 0 0 0 0 0 2 0
## Amostra_10 0 0 1 0 0 0 0 1 0
## Amostra_11 0 0 0 0 0 0 0 0 0
## Amostra_12 0 0 0 0 2 0 0 1 0
## Amostra_13 2 0 2 0 1 0 0 0 0
## Amostra_14 0 0 0 0 0 0 0 0 0
## Amostra_15 1 0 0 0 0 0 0 0 0
## Amostra_16 0 0 1 0 1 0 1 1 0
## Amostra_17 2 0 0 0 0 1 0 1 0
## Amostra_18 0 0 0 0 1 0 0 0 0
## Amostra_19 0 0 0 0 0 1 0 0 0
## Amostra_20 1 0 0 0 0 0 0 0 0
## Amostra_21 0 0 0 0 0 0 0 2 0
## Amostra_22 0 0 0 0 0 0 0 0 0
## Amostra_23 0 0 0 1 0 0 0 0 0
## Amostra_24 1 0 0 0 0 0 0 1 0
## Amostra_25 0 0 1 0 0 0 0 0 0
## Amostra_26 0 0 0 0 0 0 0 0 0
## Amostra_27 0 1 1 0 0 0 0 0 0
## Amostra_28 0 0 0 0 0 0 1 1 0
## Amostra_29 0 0 0 0 0 0 0 0 0
## Amostra_30 1 0 0 0 0 0 0 1 0Calculando os estimadores de Chao 1 e ACE
Chao 1
est_chao1 <- estaccumR(dados_coleta, permutations = 100)## Warning in sqrt(sum(Deriv.Ch1 %*% t(Deriv.Ch1) * (diag(a) - a %*%
## t(a)/S.ACE))): NaNs produzidos
## Warning in sqrt(sum(Deriv.Ch1 %*% t(Deriv.Ch1) * (diag(a) - a %*%
## t(a)/S.ACE))): NaNs produzidos
## Warning in sqrt(sum(Deriv.Ch1 %*% t(Deriv.Ch1) * (diag(a) - a %*%
## t(a)/S.ACE))): NaNs produzidossummary(est_chao1, display = "chao")## $chao
## N Chao 2.5% 97.5% Std.Dev
## Dia_4 1 6.906667 3.000 11.70000 2.535889
## Dia_6 2 9.334262 6.000 12.76250 2.076015
## Dia_2 3 10.957167 7.475 17.40625 2.250555
## Dia_1 4 12.254167 9.000 17.57500 2.370003
## Dia_14 5 13.368333 9.000 20.00000 2.800918
## Dia_10 6 14.274167 10.000 22.00000 2.767387
## Dia_7 7 15.385000 10.475 22.00000 3.043059
## Dia_9 8 15.905000 11.475 22.00000 2.903929
## Dia_11 9 16.688333 12.000 22.00000 2.907926
## Dia_8 10 17.520000 13.000 22.00000 2.818517
## Dia_5 11 18.245000 13.000 22.00000 2.600015
## Dia_12 12 18.655000 14.475 22.00000 2.094600
## Dia_13 13 19.470000 15.500 22.00000 1.577653
## Dia_3 14 20.000000 20.000 20.00000 0.000000
##
## attr(,"class")
## [1] "summary.poolaccum"Visualização de gráfico
resultados <- summary(est_chao1, display = c("S", "chao"))
res_chao <- cbind(resultados$chao[, 1:4], resultados$S[, 2:4])
res_chao <- as.data.frame(res_chao)
colnames(res_chao) <- c("Amostras", "Chao", "C_inferior", "C_superior",
"Riqueza", "R_inferior", "R_superior")ggplot(res_chao, aes(y = Riqueza, x = Amostras)) +
geom_point(aes(y = Chao, x = Amostras + 0.1), size = 4,
color = "purple", alpha = 0.7) +
geom_point(aes(y = Riqueza, x = Amostras), size = 4,
color = "cyan4", alpha = 0.7) +
geom_point(y = 7.5, x = 9, size = 4, color = "purple", alpha = 0.7) +
geom_point(y = 5.9, x = 9, size = 4, color = "cyan4", alpha = 0.7) +
geom_label(y = 7.5, x = 12, label = "Riqueza estimada - Chao 1") +
geom_label(y = 5.9, x = 11.3, label = "Riqueza observada") +
geom_line(aes(y = Chao, x = Amostras), color = "purple") +
geom_line(aes(y = Riqueza, x = Amostras), color = "cyan4") +
geom_linerange(aes(ymin = C_inferior, ymax = C_superior,
x = Amostras + 0.1), color = "purple") +
geom_linerange(aes(ymin = R_inferior, ymax = R_superior,
x = Amostras), color = "cyan4") +
scale_x_continuous(limits = c(1, 30), breaks = seq(1, 30, 1)) +
labs (x = "Número de amostras", y = "Riqueza estimada - Chao 1") +
tema_livro()
#### O estimador mostra a possibilidade de pelo menos mais 3 amostras
para uma amostragem maior.
ACE
est_ace <- estaccumR(dados_coleta, permutations = 100)## Warning in sqrt(sum(Deriv.Ch1 %*% t(Deriv.Ch1) * (diag(a) - a %*%
## t(a)/S.ACE))): NaNs produzidos
## Warning in sqrt(sum(Deriv.Ch1 %*% t(Deriv.Ch1) * (diag(a) - a %*%
## t(a)/S.ACE))): NaNs produzidos
## Warning in sqrt(sum(Deriv.Ch1 %*% t(Deriv.Ch1) * (diag(a) - a %*%
## t(a)/S.ACE))): NaNs produzidos
## Warning in sqrt(sum(Deriv.Ch1 %*% t(Deriv.Ch1) * (diag(a) - a %*%
## t(a)/S.ACE))): NaNs produzidos
## Warning in sqrt(sum(Deriv.Ch1 %*% t(Deriv.Ch1) * (diag(a) - a %*%
## t(a)/S.ACE))): NaNs produzidossummary(est_ace, display = "ace")## $ace
## N ACE 2.5% 97.5% Std.Dev
## Dia_13 1 7.817329 3.761224 13.71429 2.982787
## Dia_1 2 10.194996 6.150000 17.60296 2.987303
## Dia_3 3 11.292618 7.000000 16.63852 2.609053
## Dia_12 4 12.578094 8.000000 19.35108 2.939695
## Dia_7 5 13.358153 9.278395 20.23986 2.760742
## Dia_4 6 14.374077 10.000000 20.60335 3.096006
## Dia_11 7 15.260699 10.214489 21.64473 3.190736
## Dia_8 8 16.162148 11.815457 22.34839 3.102435
## Dia_2 9 17.474562 12.052778 25.09679 3.501827
## Dia_6 10 18.962331 13.528019 25.72368 3.943197
## Dia_10 11 20.867163 13.720826 25.72368 3.771783
## Dia_9 12 22.632853 17.344028 25.72368 3.125210
## Dia_5 13 24.231527 17.676471 25.72368 1.987253
## Dia_14 14 24.703704 24.703704 24.70370 0.000000
##
## attr(,"class")
## [1] "summary.poolaccum"Visualização de gráfico
resultados_ace <- summary(est_ace, display = c("S", "ace"))
res_ace <- cbind(resultados_ace$ace[, 1:4], resultados_ace$S[, 2:4])
res_ace <- as.data.frame(res_ace)
colnames(res_ace) <- c("Amostras", "ACE", "ACE_inferior", "ACE_superior",
"Riqueza", "R_inferior", "R_superior")ggplot(res_ace, aes(y = Riqueza, x = Amostras)) +
geom_point(aes(y = ACE, x = Amostras + 0.1), size = 4,
color = "purple", alpha = 0.7) +
geom_point(aes(y = Riqueza, x = Amostras), size = 4,
color = "cyan4", alpha = 0.7) +
geom_point(y = 7.5, x = 9, size = 4, color = "purple", alpha = 0.7) +
geom_point(y = 5.9, x = 9, size = 4, color = "cyan4", alpha = 0.7) +
geom_label(y = 7.5, x = 11.7, label = "Riqueza estimada - ACE") +
geom_label(y = 5.9, x = 11.3, label = "Riqueza observada") +
geom_line(aes(y = ACE, x = Amostras), color = "purple") +
geom_line(aes(y = Riqueza, x = Amostras), color = "cyan4") +
geom_linerange(aes(ymin = ACE_inferior, ymax = ACE_superior,
x = Amostras + 0.1), color = "purple") +
geom_linerange(aes(ymin = R_inferior, ymax = R_superior,
x = Amostras), color = "cyan4") +
scale_x_continuous(limits = c(1, 30), breaks = seq(1, 30, 1)) +
labs(x = "Número de amostras", y = "Riqueza estimada - ACE") +
tema_livro()
O estimador mostra a possibilidade de existência de pelo menos mais nove espécies se a amostragem fosse maior.
11.2
Cap11_exercicio1## sp1 sp2 sp3 sp4 sp5 sp6 sp7 sp8 sp9 sp10 sp11 sp12 sp13 sp14 sp15
## Amostra_1 0 0 0 18 1 0 0 0 1 0 0 0 0 0 7
## Amostra_2 2 0 0 7 0 0 0 0 0 0 0 0 0 0 0
## Amostra_3 0 0 1 17 3 0 0 2 2 0 0 0 0 0 4
## Amostra_4 0 0 0 9 2 0 0 1 0 0 0 0 0 0 0
## Amostra_5 0 1 1 9 8 0 1 4 0 0 0 0 0 0 0
## Amostra_6 2 0 1 8 11 0 0 0 0 0 0 1 0 0 0
## Amostra_7 0 2 0 3 8 1 0 1 0 0 0 0 0 0 0
## Amostra_8 2 0 1 10 1 0 0 1 0 0 1 0 0 0 1
## Amostra_9 0 0 2 12 2 0 0 1 0 0 0 0 0 0 0
## Amostra_10 2 1 0 1 3 0 0 2 2 0 0 0 0 1 0
## Amostra_11 1 0 0 38 0 0 0 0 1 0 0 0 0 0 0
## Amostra_12 1 0 4 29 3 0 0 1 0 0 0 0 0 0 0
## Amostra_13 0 3 0 2 5 0 0 2 0 0 0 0 0 0 0
## Amostra_14 0 0 0 1 5 0 0 2 0 0 0 0 0 0 0
## Amostra_15 0 0 0 2 4 0 0 0 0 0 0 0 0 0 0
## Amostra_16 1 0 0 7 6 0 0 1 1 0 0 0 0 0 0
## Amostra_17 0 0 0 25 5 0 0 3 0 0 0 0 0 0 0
## Amostra_18 0 0 0 16 11 0 0 0 0 0 0 1 0 0 0
## Amostra_19 2 0 0 17 2 0 0 0 1 0 0 0 0 0 2
## Amostra_20 0 0 2 4 6 0 0 3 0 0 0 0 0 0 0
## Amostra_21 2 0 2 13 17 0 0 0 0 0 0 2 0 0 1
## Amostra_22 0 0 0 4 3 0 0 2 1 0 0 2 0 0 2
## Amostra_23 1 0 3 27 2 0 0 1 0 0 0 0 0 0 0
## Amostra_24 1 1 2 29 5 0 0 0 1 0 0 0 0 0 0
## Amostra_25 1 0 0 13 10 0 0 0 0 0 0 1 0 0 0
## Amostra_26 1 2 1 12 3 0 0 0 0 0 0 0 1 0 1
## Amostra_27 1 0 1 11 1 0 0 2 0 0 0 1 0 0 1
## Amostra_28 0 0 0 17 2 0 0 1 0 0 0 0 0 0 0
## Amostra_29 1 1 0 42 2 0 0 0 0 0 0 0 0 0 0
## Amostra_30 0 0 0 16 5 0 0 1 0 1 0 0 0 0 0
## sp16 sp17 sp18 sp19 sp20 sp21 sp22 sp23 sp24 sp25 sp26 sp27 sp28
## Amostra_1 0 0 0 0 0 0 0 0 0 0 0 0 0
## Amostra_2 0 0 0 0 0 0 0 0 0 4 2 0 0
## Amostra_3 0 1 0 0 0 0 1 0 0 3 1 0 8
## Amostra_4 0 0 0 0 0 0 0 0 0 1 0 0 2
## Amostra_5 0 0 0 0 0 0 0 0 0 2 1 1 1
## Amostra_6 0 0 0 0 1 0 1 0 1 0 0 0 0
## Amostra_7 0 0 0 0 0 0 0 0 0 0 0 1 5
## Amostra_8 0 0 0 0 0 0 0 0 0 2 0 0 2
## Amostra_9 0 0 0 0 0 0 1 0 0 1 2 0 0
## Amostra_10 0 0 0 0 0 0 0 0 0 0 2 1 3
## Amostra_11 0 0 0 0 0 0 1 0 0 5 1 0 0
## Amostra_12 2 0 0 0 0 0 0 0 0 5 0 0 2
## Amostra_13 0 2 0 0 0 0 0 0 0 0 2 0 2
## Amostra_14 0 0 0 0 0 0 0 1 0 0 1 0 3
## Amostra_15 0 0 0 1 0 0 0 0 0 0 0 0 1
## Amostra_16 0 0 0 0 0 0 1 0 0 0 0 0 2
## Amostra_17 0 2 0 0 0 1 0 0 0 1 0 0 3
## Amostra_18 0 0 0 1 0 0 2 0 0 1 0 0 9
## Amostra_19 1 0 0 0 0 0 1 0 0 1 0 0 1
## Amostra_20 1 0 0 0 0 1 0 0 0 4 3 0 5
## Amostra_21 1 0 0 0 0 0 0 1 0 14 1 0 0
## Amostra_22 0 0 1 0 0 0 0 0 0 0 1 0 1
## Amostra_23 0 1 0 0 0 0 0 0 0 2 0 0 0
## Amostra_24 0 1 0 0 0 0 0 1 0 4 1 0 3
## Amostra_25 0 0 0 0 0 0 0 0 0 3 0 1 2
## Amostra_26 0 0 0 0 0 0 0 0 0 7 0 0 1
## Amostra_27 1 0 0 0 0 0 0 0 0 0 0 0 0
## Amostra_28 0 0 0 0 0 0 0 0 0 2 0 1 0
## Amostra_29 0 0 0 0 0 0 0 0 0 14 1 0 0
## Amostra_30 0 1 0 0 0 0 4 1 0 1 0 1 7
## sp29 sp30 sp31 sp32 sp33 sp34 sp35 sp36 sp37 sp38 sp39 sp40 sp41
## Amostra_1 0 0 0 3 0 0 38 0 0 0 0 0 0
## Amostra_2 0 0 0 0 0 0 7 0 0 0 1 1 0
## Amostra_3 0 0 3 2 0 0 30 0 0 0 0 0 0
## Amostra_4 0 0 0 0 0 0 6 0 1 0 3 0 0
## Amostra_5 0 0 0 0 0 1 9 0 0 0 2 0 0
## Amostra_6 0 0 0 0 0 0 7 1 0 0 0 0 0
## Amostra_7 1 0 1 0 0 0 5 0 0 0 8 0 0
## Amostra_8 0 0 0 1 0 0 14 0 0 0 1 0 0
## Amostra_9 0 0 0 0 0 0 2 0 0 0 2 3 0
## Amostra_10 0 0 1 0 0 0 13 0 0 0 1 0 0
## Amostra_11 0 0 1 0 0 0 14 0 0 0 0 0 0
## Amostra_12 0 0 0 2 0 0 14 0 0 0 0 0 0
## Amostra_13 0 0 2 0 0 0 1 0 0 0 1 1 0
## Amostra_14 0 1 1 0 0 0 0 0 0 0 1 0 0
## Amostra_15 0 0 2 0 0 0 3 0 0 0 0 0 0
## Amostra_16 0 1 0 0 0 0 1 0 0 0 2 0 0
## Amostra_17 0 0 0 0 0 0 23 0 0 0 7 0 1
## Amostra_18 0 0 0 1 0 0 6 0 0 0 2 0 0
## Amostra_19 0 0 0 1 0 0 10 0 0 0 1 0 0
## Amostra_20 0 0 1 0 0 0 14 0 0 0 1 1 0
## Amostra_21 0 0 0 0 0 0 12 0 0 0 0 1 0
## Amostra_22 0 0 0 0 0 0 3 0 0 0 1 1 0
## Amostra_23 0 0 1 0 0 0 4 0 0 0 5 0 0
## Amostra_24 0 0 1 3 1 0 16 0 0 0 1 1 0
## Amostra_25 0 0 0 0 0 0 5 0 0 0 3 1 0
## Amostra_26 0 0 0 0 0 0 4 0 0 0 0 0 0
## Amostra_27 0 0 0 0 0 0 6 0 0 0 0 1 0
## Amostra_28 0 0 0 1 0 0 55 0 0 0 2 0 0
## Amostra_29 0 0 0 2 0 0 58 0 0 0 0 0 0
## Amostra_30 0 0 0 0 0 0 11 0 0 1 0 0 0
## sp42 sp43 sp44 sp45 sp46 sp47 sp48 sp49 sp50
## Amostra_1 0 0 0 0 0 0 0 2 0
## Amostra_2 0 0 0 0 0 0 0 0 0
## Amostra_3 0 0 0 0 0 0 0 0 0
## Amostra_4 0 0 0 0 0 0 0 3 1
## Amostra_5 0 0 0 0 0 0 0 0 0
## Amostra_6 0 0 0 0 0 0 0 0 0
## Amostra_7 0 0 0 0 1 0 0 3 0
## Amostra_8 0 0 0 0 0 0 0 3 0
## Amostra_9 2 0 0 0 0 0 0 2 0
## Amostra_10 0 0 1 0 0 0 0 1 0
## Amostra_11 0 0 0 0 0 0 0 0 0
## Amostra_12 0 0 0 0 2 0 0 1 0
## Amostra_13 2 0 2 0 1 0 0 0 0
## Amostra_14 0 0 0 0 0 0 0 0 0
## Amostra_15 1 0 0 0 0 0 0 0 0
## Amostra_16 0 0 1 0 1 0 1 1 0
## Amostra_17 2 0 0 0 0 1 0 1 0
## Amostra_18 0 0 0 0 1 0 0 0 0
## Amostra_19 0 0 0 0 0 1 0 0 0
## Amostra_20 1 0 0 0 0 0 0 0 0
## Amostra_21 0 0 0 0 0 0 0 2 0
## Amostra_22 0 0 0 0 0 0 0 0 0
## Amostra_23 0 0 0 1 0 0 0 0 0
## Amostra_24 1 0 0 0 0 0 0 1 0
## Amostra_25 0 0 1 0 0 0 0 0 0
## Amostra_26 0 0 0 0 0 0 0 0 0
## Amostra_27 0 1 1 0 0 0 0 0 0
## Amostra_28 0 0 0 0 0 0 1 1 0
## Amostra_29 0 0 0 0 0 0 0 0 0
## Amostra_30 1 0 0 0 0 0 0 1 0Jackknife
est_jack1 <- poolaccum(dados_coleta, permutations = 100)
summary(est_jack1, display = "jack1")## $jack1
## N Jackknife 1 2.5% 97.5% Std.Dev
## [1,] 3 13.81000 8.491667 19.17500 2.833286
## [2,] 4 14.88000 9.618750 19.25000 2.749307
## [3,] 5 15.49800 10.800000 21.12500 2.752629
## [4,] 6 16.46333 10.833333 21.83333 2.689567
## [5,] 7 17.49857 12.264286 23.00000 2.754543
## [6,] 8 18.15125 12.290625 23.58437 2.713503
## [7,] 9 18.87778 13.311111 23.68889 2.671549
## [8,] 10 19.56600 14.275000 24.20000 2.587234
## [9,] 11 20.22000 14.818182 23.36364 2.379448
## [10,] 12 21.09583 17.185417 23.41667 2.063300
## [11,] 13 21.84000 18.692308 23.46154 1.481247
## [12,] 14 22.57143 22.571429 22.57143 0.000000
##
## attr(,"class")
## [1] "summary.poolaccum"#> $jack1Visualização dos gráficos
resultados_jack1 <- summary(est_jack1, display = c("S", "jack1"))
res_jack1 <- cbind(resultados_jack1$jack1[, 1:4], resultados_jack1$S[, 2:4])
res_jack1 <- as.data.frame(res_jack1)
colnames(res_jack1) <- c("Amostras", "JACK1", "JACK1_inferior", "JACK1_superior",
"Riqueza", "R_inferior", "R_superior")ggplot(res_jack1, aes(y = Riqueza, x = Amostras)) +
geom_point(aes(y = JACK1, x = Amostras + 0.1), size = 4,
color = "purple", alpha = 0.7) +
geom_point(aes(y = Riqueza, x = Amostras), size = 4,
color = "cyan4", alpha = 0.7) +
geom_point(y = 9.9, x = 9, size = 4, color = "purple", alpha = 0.7) +
geom_point(y = 8.6, x = 9, size = 4, color = "cyan4", alpha = 0.7) +
geom_label(y = 9.9, x = 12.5, label = "Riqueza estimada - Jackknife 1") +
geom_label(y = 8.6, x = 11.5, label = "Riqueza observada") +
geom_line(aes(y = JACK1, x = Amostras), color = "purple") +
geom_line(aes(y = Riqueza, x = Amostras), color = "cyan4") +
geom_linerange(aes(ymin = JACK1_inferior, ymax = JACK1_superior,
x = Amostras + 0.1), color = "purple") +
geom_linerange(aes(ymin = R_inferior, ymax = R_superior,
x = Amostras), color = "cyan4") +
scale_x_continuous(limits = c(1, 30), breaks = seq(1, 30, 1)) +
labs(x = "Número de amostras", y = "Riqueza estimada - Jackknife 1") +
tema_livro()
### O estimador mostra a possibilidade de existência de pelo menos mais
7 espécies se a amostragem fosse maior.
Bootstrap
est_boot <- poolaccum(dados_coleta, permutations = 100)
summary(est_boot, display = "boot")## $boot
## N Bootstrap 2.5% 97.5% Std.Dev
## [1,] 3 12.27926 7.951852 16.48148 2.382221
## [2,] 4 13.29715 9.695312 17.22559 2.153864
## [3,] 5 13.94542 9.623904 18.18239 2.183436
## [4,] 6 14.63382 10.778721 18.33590 2.007072
## [5,] 7 15.25758 11.865295 18.43875 1.855118
## [6,] 8 15.76388 12.875698 19.44605 1.935421
## [7,] 9 16.29510 12.885639 19.82035 1.995421
## [8,] 10 16.91332 12.970294 19.58766 1.805977
## [9,] 11 17.58663 14.041373 19.57988 1.545609
## [10,] 12 18.16246 15.530379 19.58724 1.410121
## [11,] 13 18.71286 16.570376 19.59107 1.014125
## [12,] 14 19.27832 19.278321 19.27832 0.000000
##
## attr(,"class")
## [1] "summary.poolaccum"Visualização do gráfico
resultados_boot <- summary(est_boot, display = c("S", "boot"))
res_boot <- cbind(resultados_boot$boot[,1:4], resultados_boot$S[,2:4])
res_boot <- as.data.frame(res_boot)
colnames(res_boot) <- c("Amostras", "BOOT", "BOOT_inferior", "BOOT_superior",
"Riqueza", "R_inferior", "R_superior")ggplot(res_boot, aes(y = Riqueza, x = Amostras)) +
geom_point(aes(y = BOOT, x = Amostras + 0.1), size = 4,
color = "purple", alpha = 0.7) +
geom_point(aes(y = Riqueza, x = Amostras), size = 4,
color = "cyan4", alpha = 0.7) +
geom_point(y = 10.4, x = 9, size = 4, color = "purple", alpha = 0.7) +
geom_point(y = 9.3, x = 9, size = 4, color = "cyan4", alpha = 0.7) +
geom_label(y = 10.4, x = 12.3, label = "Riqueza estimada - Bootstrap") +
geom_label(y = 9.3, x = 11.5, label = "Riqueza observada") +
geom_line(aes(y = BOOT, x = Amostras), color = "purple") +
geom_line(aes(y = Riqueza, x = Amostras), color = "cyan4") +
geom_linerange(aes(ymin = BOOT_inferior, ymax = BOOT_superior,
x = Amostras + 0.1), color = "purple") +
geom_linerange(aes(ymin = R_inferior, ymax = R_superior,
x = Amostras), color = "cyan4") +
scale_x_continuous(limits = c(1, 30), breaks = seq(1, 30, 1)) +
labs(x = "Número de amostras", y = "Riqueza estimada - Bootstrap") +
tema_livro()
#### O estimador mostra a possibilidade de existência de pelo menos mais
2 espécies numa amostragem maior.
11.3
anuros_composicao## AEP AGA APJ BFF CRS EEB EEC EEJ EGH FAC FBV
## Adenomera_bokermanni 0 0 0 0 25 0 0 0 0 0 0
## Adenomera_marmorata 72 0 0 0 0 1 0 0 78 0 0
## Ameerega_picta 0 0 0 0 0 0 0 0 0 0 0
## Aparasphenedon_bokermanni 0 0 0 0 0 0 0 31 0 0 0
## Aparasphenodon_brunoi 0 71 0 0 0 0 0 0 7 0 0
## Aplastodiscus_albofrenatus 0 0 0 0 0 70 0 0 0 0 0
## Aplastodiscus_albosignatus 0 0 0 0 0 14 0 79 0 0 0
## Aplastodiscus_arildae 0 0 80 0 0 0 0 0 0 0 0
## Aplastodiscus_cavicola 50 44 0 0 0 0 0 0 0 0 0
## Aplastodiscus_cochranae 0 0 0 0 0 0 0 0 0 0 0
## Aplastodiscus_ehrhardti 0 0 0 0 3 0 0 0 0 0 0
## Aplastodiscus_eugenioi 0 0 0 0 0 0 0 0 0 0 0
## Aplastodiscus_leucopygius 0 0 53 0 0 78 0 0 0 0 0
## Aplastodiscus_perviridis 0 0 0 0 0 0 0 0 0 0 0
## Aplastodiscus_weygoldti 0 0 0 0 0 0 0 0 0 0 0
## Arcovomer_passarellii 0 0 0 0 0 0 0 0 0 0 0
## Barycholos_ternetzi 0 0 0 0 0 0 0 0 0 0 0
## Bokermannohyla_alvarengai 0 0 0 0 0 0 0 0 0 0 0
## Bokermannohyla_astartea 0 0 0 0 0 61 0 0 0 0 0
## Bokermannohyla_circumdata 0 57 75 0 0 8 0 0 0 0 0
## Bokermannohyla_hylax 0 0 0 0 63 78 0 8 0 0 0
## Bokermannohyla_izecksoni 0 0 0 0 0 0 0 0 0 0 0
## Brachycephalus_ephippium 0 0 70 0 0 0 0 0 0 0 0
## Brachycephalus_pitanga 0 0 0 0 0 0 0 0 66 0 0
## Ceratophrys_aurita 0 17 0 0 0 18 0 0 0 0 0
## Ceratophrys_cranwelli 0 0 0 0 0 26 0 0 0 0 0
## Ceratophrys_joazeirensis 0 0 0 0 0 0 0 0 0 0 0
## Ceratophrys_ornata 0 77 0 0 0 0 0 0 0 0 0
## Chiasmocleis_albopunctata 0 0 0 13 0 0 0 0 0 0 0
## Chiasmocleis_cruci 0 0 0 0 0 0 0 0 0 0 0
## Chiasmocleis_leucosticta 0 0 0 0 0 0 0 7 0 0 0
## Chiasmocleis_mantiqueira 0 0 0 0 0 0 0 0 0 0 0
## Corythomantis_greeningi 0 0 0 0 0 0 0 0 32 0 0
## Crossodactylus_caramaschii 0 0 0 0 0 0 0 0 0 0 0
## Crossodactylus_schmdti 0 48 0 0 0 0 0 0 0 0 0
## Cycloramphus_acangatan 0 0 0 0 0 0 0 0 0 0 0
## Cycloramphus_boraceiensis 0 0 0 0 0 43 0 0 0 0 0
## Cycloramphus_eleutherodactylus 0 0 0 0 0 2 0 0 0 0 0
## Cycloramphus_lutzorum 0 0 0 0 0 0 0 0 0 0 0
## Dasypops_schirchi 0 0 0 0 0 0 0 58 0 0 0
## Dendrobates_auratus 0 0 0 0 0 7 0 0 0 0 0
## Dendrophryniscus_brevipollicatus 0 0 0 0 0 61 0 0 54 0 0
## Dendrophryniscus_leucomystax 0 30 0 0 0 0 0 0 0 0 0
## Dendropsophus_anceps 0 0 0 0 0 0 0 0 67 0 0
## Dendropsophus_berthalutzae 0 0 0 0 71 0 0 0 28 0 0
## Dendropsophus_ebraccatus 0 39 0 0 0 0 0 0 28 0 0
## Dendropsophus_elegans 63 62 0 0 53 0 0 0 15 0 0
## Dendropsophus_elianeae 0 0 0 19 0 0 0 0 0 0 57
## Dendropsophus_giesleri 0 0 0 0 0 0 0 0 58 0 0
## Dendropsophus_jimi 0 22 0 0 0 0 0 0 0 0 0
## Dendropsophus_microcephalus 0 0 0 0 0 0 0 0 0 0 0
## Dendropsophus_microps 0 0 12 0 30 7 0 60 0 0 0
## Dendropsophus_minutus 29 15 52 0 20 35 16 0 10 62 71
## Dendropsophus_nanus 0 0 0 62 0 0 29 0 0 47 43
## Dendropsophus_parviceps 8 0 0 0 0 0 0 0 0 0 0
## Dendropsophus_rubicundulus 79 0 0 0 0 0 0 0 0 0 0
## Dendropsophus_sanborni 0 0 5 0 0 0 0 0 0 24 3
## Dendropsophus_seniculus 0 0 0 0 0 29 0 0 28 0 0
## Dendropsophus_triangulum 0 0 0 0 0 0 0 0 0 0 0
## Dendropsophus_werneri 0 0 0 0 0 0 0 34 0 0 0
## Dermatonotus_muelleri 0 0 0 0 0 0 0 0 0 39 47
## Elachistocleis_bicolor 0 0 0 0 67 0 0 0 0 50 78
## Elachistocleis_cesarii 0 0 0 0 0 0 32 0 0 0 0
## Engystomops_petersi 0 0 52 0 0 0 0 0 0 0 0
## Euparkerella_brasiliensis 0 0 0 0 0 0 0 0 76 0 0
## Fritziana_aff._fissilis 0 0 0 0 0 23 0 0 0 0 0
## Fritziana_goeldii 0 42 0 0 0 0 0 0 79 0 0
## Fritziana_ohausi 0 0 0 0 0 72 0 0 0 0 0
## Gastrotheca_cornuta 0 0 0 0 0 0 0 0 0 0 0
## Gastrotheca_fissipes 0 0 0 0 0 0 0 0 0 0 0
## Gastrotheca_pulchra 0 0 0 0 0 0 0 0 0 0 0
## Haddadus_binotatus 1 51 10 0 0 46 11 13 30 0 0
## Holoaden_bradei 0 0 0 0 0 0 0 0 0 0 0
## Holoaden_luederwaldti 0 0 0 0 0 48 0 0 0 0 0
## Hylodes_asper 0 0 0 0 0 3 0 0 0 0 0
## Hylodes_dactylocinus 0 0 0 0 0 0 0 0 0 0 0
## Hylodes_hayeri 0 0 0 0 31 0 0 0 0 0 0
## Hylodes_phyllodes 0 79 0 0 0 0 48 0 0 0 0
## Hylodes_sazimai 0 0 63 0 0 0 0 0 0 0 0
## Hypsiboas_albomarginatus 0 30 0 0 80 0 0 61 55 0 0
## Hypsiboas_albopunctata 41 66 46 10 0 15 48 0 0 0 80
## Hypsiboas_alfarroi 0 0 0 0 0 73 0 0 0 0 0
## Hypsiboas_bischoffi 0 0 72 0 39 50 0 0 0 0 0
## Hypsiboas_caingua 0 0 0 0 0 0 44 0 0 0 0
## Hypsiboas_calcaratus 0 0 0 0 0 0 0 0 0 0 0
## Hypsiboas_crepitans 0 76 0 0 0 0 0 0 0 0 0
## Hypsiboas_faber 19 59 1 0 56 65 19 72 61 10 0
## Hypsiboas_lundii 0 0 0 35 0 0 28 0 0 0 0
## Hypsiboas_marginatus 0 0 0 0 0 0 0 0 0 42 13
## Hypsiboas_multifasciatus 0 0 0 0 0 0 0 0 0 0 0
## Hypsiboas_pardalis 0 40 0 0 0 59 0 0 0 0 0
## Hypsiboas_polytaenius 10 0 0 0 0 66 0 0 0 0 0
## Hypsiboas_pulchellus 0 0 16 0 0 53 0 0 0 0 0
## Hypsiboas_semiguttatus 0 0 0 0 0 0 0 0 0 0 0
## Hypsiboas_semilineatus 0 13 0 0 0 0 0 74 37 0 0
## Hypsiboas_sibleszi 0 0 0 0 0 0 0 0 62 0 0
## Ischnocnema_henseli 0 0 0 0 0 0 0 0 0 0 0
## Ischnocnema_holti 0 50 22 0 24 5 0 74 0 0 0
## Ischnocnema_juipoca 0 0 0 0 0 23 0 0 0 0 0
## Ischnocnema_parva 6 0 0 0 0 0 0 0 0 0 0
## Ischnocnemaguentheri_C1 0 0 69 0 0 0 0 0 0 0 0
## Ischnocnemaguentheri_C3 0 0 0 0 0 0 0 0 0 0 0
## Ischnocnemaguentheri_C4 0 0 0 0 0 0 0 0 0 0 0
## Itapotihyla_langsdorffii 0 71 0 0 0 56 76 76 0 0 0
## Leptodactylus_chaquensis 0 0 0 0 0 0 0 0 0 33 0
## Leptodactylus_flavopictus 0 0 0 0 0 0 0 0 0 0 0
## Leptodactylus_furnarius 0 0 0 0 0 0 0 0 0 0 0
## Leptodactylus_fuscus 0 0 0 0 0 24 0 0 0 0 0
## Leptodactylus_labyrinthicus 0 0 0 0 0 0 0 0 0 0 0
## Leptodactylus_latrans 0 46 0 45 0 80 57 0 31 40 58
## Leptodactylus_mystaceus 0 0 0 0 0 0 0 0 0 0 0
## Leptodactylus_mystacinus 15 0 0 5 0 0 67 0 0 0 19
## Leptodactylus_notoaktites 0 0 0 0 0 0 19 0 0 0 0
## Leptodactylus_plaumanni 0 0 0 15 0 0 2 0 0 29 14
## Leptodactylus_podicipinus 0 0 0 0 0 0 0 0 0 0 0
## Leptodactylus_rhodomystax 0 0 0 0 70 0 0 0 0 0 0
## Limnomedusa_macroglossa 68 78 41 0 19 5 0 5 65 0 50
## Lysapsus_limellum 0 0 0 42 0 0 0 0 0 38 47
## Lysapus_laevis 0 0 0 0 0 0 0 0 71 0 0
## Macrogenioglottus_alipioi 0 0 0 0 0 0 0 0 0 0 0
## Megaelosia_aff._boticariana 0 0 0 0 0 0 0 0 0 0 0
## Megaelosia_boticariana 0 0 0 0 0 26 0 0 0 0 0
## Melanophryniscus_devincenzii 0 0 0 0 0 0 0 0 0 0 0
## Myersiella_microps 0 0 0 0 0 52 0 0 59 0 0
## Odontophrynus_americanus 0 0 12 0 0 0 36 0 0 0 0
## Odontophrynus_cultripes 25 0 0 0 0 0 0 0 0 0 0
## Paratelmatobius_cardosoi 0 0 0 0 0 0 0 0 0 0 0
## Paratelmatobius_gaigeae 0 0 0 0 0 53 0 0 0 0 0
## Phasmahyla_cochranae 0 0 23 0 0 54 0 0 0 0 0
## Phasmahyla_exilis 0 0 0 0 0 0 0 0 0 0 0
## Phasmahyla_guttata 0 0 0 0 0 0 0 0 0 0 0
## Phrynomedusa_dryade 0 0 0 0 0 25 0 0 0 0 0
## Phyllobates_bicolor 0 13 0 0 0 0 0 0 0 0 0
## Phyllodytes_luteolus 0 0 0 0 0 0 0 0 0 0 4
## Phyllomedusa_azurea 72 62 36 0 0 0 0 0 0 0 0
## Phyllomedusa_burmeisteri 0 0 0 0 47 0 0 5 0 0 0
## Phyllomedusa_camba 0 0 0 0 0 0 0 0 6 0 0
## Phyllomedusa_distincta 0 0 0 0 0 0 0 0 0 0 0
## Phyllomedusa_hypochondrialis 0 0 0 0 0 0 28 0 0 0 0
## Phyllomedusa_megacephala 0 0 0 0 0 0 0 0 0 0 0
## Phyllomedusa_nordestina 0 0 0 0 0 0 0 0 0 25 23
## Phyllomedusa_rohdei 0 43 0 0 0 0 0 0 0 0 0
## Phyllomedusa_sauvagii 17 75 10 39 37 49 67 0 0 45 6
## Phyllomedusa_tetraploidea 0 0 0 0 0 0 0 0 0 0 0
## Phyllomedusa_tomopterna 0 0 0 0 0 0 0 0 0 0 0
## Physalaemus_atlanticus 0 0 0 0 0 67 0 0 0 0 0
## Physalaemus_bokermanni 0 0 0 0 0 0 0 0 0 46 0
## Physalaemus_centralis 0 0 0 0 0 28 0 0 0 0 0
## Physalaemus_cuvieri 0 0 0 0 0 0 0 0 0 0 0
## Physalaemus_lateristriga 0 0 0 0 3 44 57 0 0 0 0
## Physalaemus_maculiventris 0 0 0 0 0 0 0 0 53 0 0
## Physalaemus_marmoratus 0 0 0 0 0 0 0 74 0 0 0
## Physalaemus_nattereri 0 0 0 54 0 0 71 0 0 8 46
## Physalaemus_olfersii 0 0 0 0 0 0 0 0 0 0 0
## Physalaemus_spiniger 55 0 53 0 9 72 0 0 0 0 0
## Pipa_carvalhoi 0 28 0 0 0 0 0 0 0 0 0
## Pleurodema_brachyops 0 0 0 0 0 1 0 0 0 0 0
## Pleurodema_diplolister 0 0 0 0 0 0 0 0 0 0 0
## Proceratophrys_appendiculata 0 0 0 40 0 0 0 0 0 1 1
## Proceratophrys_avelinoi 0 0 0 0 0 0 0 0 0 1 1
## Proceratophrys_boiei 0 0 0 0 0 0 0 0 0 0 0
## Proceratophrys_cristiceps 0 0 0 0 0 0 0 0 0 0 0
## Proceratophrys_laticeps 0 63 0 0 25 0 0 1 7 0 0
## Proceratophrys_melanopogon 0 0 0 0 0 0 0 0 0 0 0
## Proceratophrys_schirchi 0 15 0 0 2 0 0 0 20 0 0
## Pseudis_minuta 0 0 0 0 0 0 0 0 0 0 0
## Pseudis_paradoxa 0 0 0 0 0 33 0 0 0 0 0
## Pseudis_platensis 0 0 0 0 0 0 0 0 0 0 0
## Pseudopaludicola_falcipes 0 59 0 0 0 0 0 0 0 0 0
## Pseudopaludicola_mineira 0 0 0 0 0 75 0 0 0 0 0
## Pseudopaludicola_mystacalis 1 0 0 0 0 0 0 0 0 0 0
## Pseudopaludicola_saltica 0 22 0 0 0 0 0 0 47 0 0
## Rhinella_crucifer 0 11 29 0 0 61 0 61 0 0 0
## Rhinella_granulosa 0 1 0 0 0 0 0 0 0 0 0
## Rhinella_henseli 1 0 36 0 0 0 0 0 46 0 0
## Rhinella_hoogmoedi 0 0 0 0 0 0 0 0 67 0 0
## Rhinella_icterica 1 0 0 2 0 0 0 0 0 62 76
## Rhinella_ocellata 1 0 56 3 2 0 2 0 0 0 2
## Rhinella_ornata 0 0 0 0 0 0 45 0 48 0 0
## Rhinella_schneideri 0 50 0 18 0 0 64 0 0 60 2
## Scinax_argyreonatus 0 0 65 0 0 0 0 0 0 0 0
## Scinax_crospedospilus 0 0 0 0 0 0 0 0 72 0 0
## Scinax_fuscomarginatus 0 0 0 0 0 0 0 6 0 0 0
## Scinax_fuscovarius 0 0 0 0 0 0 0 0 0 0 0
## Scinax_hayii 0 0 0 0 1 0 0 39 0 0 0
## Scinax_imbegue 2 0 0 0 0 0 0 0 0 0 0
## Scinax_littoralis 0 0 0 0 0 0 0 0 0 0 0
## Scinax_obtriangulatus 0 0 0 0 0 0 0 0 0 0 0
## Scinax_perpusillus 0 0 0 0 0 1 0 0 0 0 0
## Scinax_rizibilis 0 0 0 0 9 0 0 67 0 0 0
## Scinax_ruber 0 3 0 0 67 60 0 39 0 0 0
## Scinax_similis 0 0 0 0 56 0 1 0 0 0 0
## Scinax_squalirostris 0 0 0 0 0 0 0 0 0 0 0
## Scinax_tymbamirim 0 0 0 70 0 0 0 0 1 0 1
## Scythrophrys_sawayae 0 0 0 0 0 0 0 0 0 0 0
## Sphaenorhynchus_caramaschii 0 0 0 0 0 1 45 0 0 0 0
## Sphaenorhynchus_dorisae 0 0 0 0 0 0 0 0 0 0 0
## Sphaenorhynchus_lacteus 0 0 0 0 0 0 0 0 0 0 0
## Stereocyclops_incrassatus 0 0 0 0 0 14 0 0 0 0 0
## Thoropa_miliaris 0 0 0 0 0 0 0 0 51 0 0
## Thoropa_taophora 0 0 0 0 0 0 0 0 0 0 0
## Trachycephalus_imitatrix 0 0 0 0 0 0 0 0 0 0 0
## Trachycephalus_lepidus 0 0 0 0 0 0 0 0 0 0 0
## Trachycephalus_mesophaeus 0 0 0 0 0 0 0 0 0 0 0
## Trachycephalus_nigromaculatus 1 7 0 0 0 31 0 43 5 0 0
## Trachycephalus_typhonius 0 35 0 0 1 0 0 0 71 0 0
## Vitreorana_eurygnatha 0 7 0 0 0 0 0 0 0 0 0
## Vitreorana_uranoscopa 0 0 0 0 0 0 0 0 0 66 1
## Xenohyla_truncata 0 0 0 0 0 55 0 5 0 0 0
## Zachaenus_carvalhoi 0 0 0 0 7 4 0 0 0 0 0
## Zachaenus_parvulus 0 0 0 0 0 0 0 0 0 0 0
## FCB FEN FMG FSF GSJ ICE IFP MFC NHS NIT PBV
## Adenomera_bokermanni 0 0 0 0 0 0 0 0 0 0 0
## Adenomera_marmorata 0 0 0 0 0 0 0 0 0 0 0
## Ameerega_picta 0 0 0 0 0 0 0 0 0 0 0
## Aparasphenedon_bokermanni 0 0 0 0 0 0 0 0 0 0 0
## Aparasphenodon_brunoi 0 0 0 0 0 0 0 0 0 0 0
## Aplastodiscus_albofrenatus 0 0 0 0 0 0 0 0 0 0 0
## Aplastodiscus_albosignatus 0 0 0 0 0 0 0 0 0 0 0
## Aplastodiscus_arildae 0 0 0 0 0 0 0 0 0 0 0
## Aplastodiscus_cavicola 0 0 0 0 0 0 0 0 0 0 0
## Aplastodiscus_cochranae 0 0 0 0 0 0 0 0 0 0 0
## Aplastodiscus_ehrhardti 0 0 0 0 0 0 0 0 0 0 0
## Aplastodiscus_eugenioi 0 0 0 0 0 0 0 0 0 0 0
## Aplastodiscus_leucopygius 0 0 0 0 0 0 0 0 0 0 0
## Aplastodiscus_perviridis 0 0 0 0 0 0 0 0 0 0 0
## Aplastodiscus_weygoldti 0 0 0 0 0 0 0 0 0 0 0
## Arcovomer_passarellii 0 0 0 0 0 0 0 0 0 0 0
## Barycholos_ternetzi 0 0 0 0 0 0 0 0 0 0 0
## Bokermannohyla_alvarengai 0 0 0 0 0 0 0 0 0 0 0
## Bokermannohyla_astartea 0 0 0 0 0 0 0 0 0 0 0
## Bokermannohyla_circumdata 0 0 0 0 0 0 0 0 0 0 0
## Bokermannohyla_hylax 0 0 0 0 0 0 0 0 0 0 0
## Bokermannohyla_izecksoni 0 0 0 0 0 0 0 0 0 0 0
## Brachycephalus_ephippium 0 0 57 0 0 0 0 0 0 0 0
## Brachycephalus_pitanga 0 0 0 0 0 0 0 0 0 0 0
## Ceratophrys_aurita 0 0 0 0 0 0 0 0 0 0 0
## Ceratophrys_cranwelli 0 0 0 0 0 0 0 0 0 0 0
## Ceratophrys_joazeirensis 0 0 55 0 0 0 0 0 0 0 0
## Ceratophrys_ornata 0 0 0 0 0 0 0 0 0 0 0
## Chiasmocleis_albopunctata 52 72 0 0 31 0 18 14 39 0 0
## Chiasmocleis_cruci 0 0 0 0 0 0 0 0 0 0 0
## Chiasmocleis_leucosticta 0 0 14 0 0 0 0 0 0 0 0
## Chiasmocleis_mantiqueira 0 0 0 0 0 0 0 0 0 0 0
## Corythomantis_greeningi 0 0 0 0 0 0 0 0 0 0 0
## Crossodactylus_caramaschii 0 0 18 0 0 0 0 0 0 0 0
## Crossodactylus_schmdti 0 0 0 0 0 0 0 0 0 0 0
## Cycloramphus_acangatan 0 0 2 0 0 0 0 0 0 0 0
## Cycloramphus_boraceiensis 0 0 0 0 0 0 0 0 0 0 0
## Cycloramphus_eleutherodactylus 0 0 0 0 0 0 0 0 0 0 0
## Cycloramphus_lutzorum 0 0 0 0 0 0 0 0 0 0 0
## Dasypops_schirchi 0 0 0 0 0 0 0 0 0 0 0
## Dendrobates_auratus 0 0 0 0 0 0 0 0 0 0 0
## Dendrophryniscus_brevipollicatus 0 0 36 0 0 0 0 0 0 0 0
## Dendrophryniscus_leucomystax 0 0 0 0 0 0 0 0 0 0 0
## Dendropsophus_anceps 0 0 0 0 0 0 0 0 0 0 0
## Dendropsophus_berthalutzae 0 0 0 0 0 0 0 0 0 0 0
## Dendropsophus_ebraccatus 0 0 0 0 0 0 0 0 0 0 0
## Dendropsophus_elegans 0 0 0 0 0 0 0 0 0 0 0
## Dendropsophus_elianeae 0 0 0 40 1 45 56 0 0 46 72
## Dendropsophus_giesleri 0 0 0 0 0 0 0 0 0 0 0
## Dendropsophus_jimi 0 0 0 0 0 0 0 0 0 0 0
## Dendropsophus_microcephalus 0 0 0 0 0 0 0 0 0 0 0
## Dendropsophus_microps 0 0 12 0 0 0 0 0 0 0 0
## Dendropsophus_minutus 51 55 0 19 56 1 80 56 20 53 33
## Dendropsophus_nanus 7 15 0 63 33 53 53 24 37 21 10
## Dendropsophus_parviceps 0 0 0 0 0 0 0 0 0 0 0
## Dendropsophus_rubicundulus 0 0 0 0 0 0 0 0 0 0 0
## Dendropsophus_sanborni 0 62 0 0 0 0 0 0 42 29 0
## Dendropsophus_seniculus 0 0 0 0 0 0 0 0 0 0 0
## Dendropsophus_triangulum 0 0 0 48 0 0 0 0 0 0 0
## Dendropsophus_werneri 0 0 0 0 0 0 0 0 0 0 0
## Dermatonotus_muelleri 0 0 0 73 0 57 49 0 0 0 0
## Elachistocleis_bicolor 0 0 0 61 26 11 46 20 0 41 11
## Elachistocleis_cesarii 0 37 0 0 0 58 0 0 0 0 0
## Engystomops_petersi 0 0 0 0 0 0 0 0 0 0 0
## Euparkerella_brasiliensis 0 0 0 0 0 0 0 0 0 0 0
## Fritziana_aff._fissilis 0 0 36 0 0 0 0 0 0 0 0
## Fritziana_goeldii 0 0 0 0 0 0 0 0 0 0 0
## Fritziana_ohausi 0 0 0 0 0 0 0 0 0 0 0
## Gastrotheca_cornuta 0 0 0 0 0 0 0 0 0 0 0
## Gastrotheca_fissipes 0 0 0 0 0 0 0 0 0 0 0
## Gastrotheca_pulchra 0 0 0 0 0 0 0 0 0 0 0
## Haddadus_binotatus 0 0 5 0 0 0 0 0 0 0 0
## Holoaden_bradei 0 0 0 0 0 0 0 0 0 0 0
## Holoaden_luederwaldti 0 0 0 0 0 0 0 0 0 0 0
## Hylodes_asper 0 0 0 0 0 0 0 0 0 0 0
## Hylodes_dactylocinus 0 0 0 0 0 0 0 0 0 0 0
## Hylodes_hayeri 0 0 0 0 0 0 0 0 0 0 0
## Hylodes_phyllodes 0 0 0 0 0 0 0 0 0 0 0
## Hylodes_sazimai 0 0 0 0 0 0 0 0 0 0 0
## Hypsiboas_albomarginatus 0 0 0 0 0 0 0 0 0 0 0
## Hypsiboas_albopunctata 51 79 0 67 5 46 56 29 31 31 72
## Hypsiboas_alfarroi 0 0 0 0 0 0 0 0 0 0 0
## Hypsiboas_bischoffi 0 0 18 0 0 0 0 0 0 0 0
## Hypsiboas_caingua 0 0 0 0 0 0 0 0 0 0 0
## Hypsiboas_calcaratus 0 0 0 0 0 0 0 0 0 0 0
## Hypsiboas_crepitans 0 0 0 0 0 0 0 0 0 0 0
## Hypsiboas_faber 0 54 0 0 0 0 0 2 0 0 0
## Hypsiboas_lundii 40 33 0 0 0 0 78 54 0 0 0
## Hypsiboas_marginatus 0 0 0 49 9 44 1 0 55 1 12
## Hypsiboas_multifasciatus 0 0 0 0 0 0 0 0 0 0 0
## Hypsiboas_pardalis 0 0 0 0 0 0 0 0 0 0 0
## Hypsiboas_polytaenius 0 0 0 0 0 0 0 0 0 0 0
## Hypsiboas_pulchellus 0 0 0 0 0 0 0 0 0 0 0
## Hypsiboas_semiguttatus 0 0 0 0 0 0 0 0 0 0 0
## Hypsiboas_semilineatus 0 0 0 0 0 0 0 0 0 0 0
## Hypsiboas_sibleszi 0 0 0 0 0 0 0 0 0 0 0
## Ischnocnema_henseli 0 0 0 0 0 0 0 0 0 0 0
## Ischnocnema_holti 0 0 45 0 0 0 0 0 0 0 0
## Ischnocnema_juipoca 0 0 0 0 0 0 0 0 0 0 0
## Ischnocnema_parva 0 0 0 0 0 0 0 0 0 0 0
## Ischnocnemaguentheri_C1 0 0 50 0 0 0 0 0 0 0 0
## Ischnocnemaguentheri_C3 0 0 56 0 0 0 0 0 0 0 0
## Ischnocnemaguentheri_C4 0 0 0 0 0 0 0 0 0 0 0
## Itapotihyla_langsdorffii 0 7 0 0 0 0 0 0 0 0 0
## Leptodactylus_chaquensis 31 0 0 1 74 0 30 0 0 68 48
## Leptodactylus_flavopictus 0 0 0 0 0 0 0 0 0 0 0
## Leptodactylus_furnarius 0 0 0 0 0 0 0 0 0 0 0
## Leptodactylus_fuscus 0 0 0 0 0 0 0 0 0 0 0
## Leptodactylus_labyrinthicus 0 0 0 40 0 40 0 0 0 47 0
## Leptodactylus_latrans 52 12 0 42 31 28 24 7 17 74 6
## Leptodactylus_mystaceus 0 0 0 0 0 0 0 0 0 0 0
## Leptodactylus_mystacinus 0 35 0 0 75 8 40 36 61 44 35
## Leptodactylus_notoaktites 0 0 0 59 58 0 60 39 75 0 0
## Leptodactylus_plaumanni 43 32 0 34 23 49 64 28 65 45 0
## Leptodactylus_podicipinus 0 0 0 0 0 0 0 0 0 0 0
## Leptodactylus_rhodomystax 0 0 0 0 0 0 0 0 0 0 0
## Limnomedusa_macroglossa 0 0 59 29 0 18 36 0 0 63 5
## Lysapsus_limellum 0 0 0 29 26 13 67 1 26 48 73
## Lysapus_laevis 0 0 0 0 0 0 0 0 0 0 0
## Macrogenioglottus_alipioi 0 0 55 0 0 0 0 0 0 0 0
## Megaelosia_aff._boticariana 0 0 0 0 0 0 0 0 0 0 0
## Megaelosia_boticariana 0 0 0 0 0 0 0 0 0 0 0
## Melanophryniscus_devincenzii 0 0 0 0 0 0 0 0 0 0 0
## Myersiella_microps 0 0 52 0 0 0 0 0 0 0 0
## Odontophrynus_americanus 0 0 0 0 0 0 0 0 0 0 0
## Odontophrynus_cultripes 0 0 0 0 0 0 0 0 0 0 0
## Paratelmatobius_cardosoi 0 0 0 0 0 0 0 0 0 0 0
## Paratelmatobius_gaigeae 0 0 0 0 0 0 0 0 0 0 0
## Phasmahyla_cochranae 0 0 0 0 0 0 0 0 0 0 0
## Phasmahyla_exilis 0 0 0 0 0 0 0 0 0 0 0
## Phasmahyla_guttata 0 0 0 0 0 0 0 0 0 0 0
## Phrynomedusa_dryade 0 0 0 0 0 0 0 0 0 0 0
## Phyllobates_bicolor 0 0 0 0 0 0 0 0 0 0 0
## Phyllodytes_luteolus 0 0 0 0 0 0 0 0 0 0 0
## Phyllomedusa_azurea 0 0 0 0 0 0 0 0 0 0 0
## Phyllomedusa_burmeisteri 0 0 0 0 0 0 0 0 0 0 0
## Phyllomedusa_camba 0 0 0 0 0 0 0 0 0 0 0
## Phyllomedusa_distincta 0 0 0 0 0 0 0 0 0 0 0
## Phyllomedusa_hypochondrialis 0 0 0 0 0 0 0 0 0 0 0
## Phyllomedusa_megacephala 0 0 0 0 0 0 0 0 0 0 0
## Phyllomedusa_nordestina 0 36 0 33 0 31 62 53 16 10 29
## Phyllomedusa_rohdei 0 0 0 0 0 0 0 0 0 0 0
## Phyllomedusa_sauvagii 17 61 30 77 42 1 22 70 53 70 32
## Phyllomedusa_tetraploidea 0 0 0 0 0 0 0 0 0 0 0
## Phyllomedusa_tomopterna 0 0 0 0 0 0 0 0 0 0 0
## Physalaemus_atlanticus 0 0 0 0 0 0 0 0 0 0 0
## Physalaemus_bokermanni 0 50 0 0 0 0 0 0 0 36 0
## Physalaemus_centralis 0 0 0 0 0 0 0 0 0 0 0
## Physalaemus_cuvieri 0 0 0 0 0 0 0 0 0 0 0
## Physalaemus_lateristriga 0 0 47 0 0 0 0 0 0 0 0
## Physalaemus_maculiventris 0 0 0 0 0 0 0 0 0 0 0
## Physalaemus_marmoratus 0 0 0 0 0 0 0 0 0 0 0
## Physalaemus_nattereri 32 62 0 50 35 50 69 73 14 40 30
## Physalaemus_olfersii 0 0 0 0 0 0 0 0 0 0 0
## Physalaemus_spiniger 0 0 35 0 0 0 0 0 0 0 0
## Pipa_carvalhoi 0 0 0 0 0 0 0 0 0 0 0
## Pleurodema_brachyops 0 0 0 0 0 0 0 0 0 0 0
## Pleurodema_diplolister 0 0 0 0 0 0 0 0 0 0 0
## Proceratophrys_appendiculata 0 0 0 2 0 5 11 0 76 55 45
## Proceratophrys_avelinoi 0 0 0 0 0 3 3 0 0 0 3
## Proceratophrys_boiei 0 0 0 7 7 5 0 0 0 0 0
## Proceratophrys_cristiceps 0 0 0 0 0 0 0 0 0 7 0
## Proceratophrys_laticeps 0 0 41 0 0 0 0 0 0 0 0
## Proceratophrys_melanopogon 0 0 0 0 0 0 0 0 0 0 0
## Proceratophrys_schirchi 0 0 0 0 0 0 0 0 0 0 0
## Pseudis_minuta 0 0 0 0 0 0 0 0 0 25 0
## Pseudis_paradoxa 0 0 0 0 0 0 0 0 0 0 0
## Pseudis_platensis 0 0 0 0 0 0 0 0 0 0 0
## Pseudopaludicola_falcipes 0 0 0 0 0 0 0 0 0 0 0
## Pseudopaludicola_mineira 0 0 0 0 0 0 0 0 0 0 0
## Pseudopaludicola_mystacalis 0 0 0 0 0 0 0 0 0 0 0
## Pseudopaludicola_saltica 0 0 0 0 0 0 0 0 0 0 0
## Rhinella_crucifer 0 26 0 0 0 0 0 0 0 0 0
## Rhinella_granulosa 0 0 0 0 0 0 0 0 0 0 0
## Rhinella_henseli 0 0 0 0 0 0 0 0 0 0 0
## Rhinella_hoogmoedi 0 0 0 0 0 0 0 0 0 0 0
## Rhinella_icterica 0 0 0 2 1 15 31 40 76 42 4
## Rhinella_ocellata 5 5 18 2 2 1 38 1 16 29 57
## Rhinella_ornata 0 0 76 0 0 0 0 22 0 0 0
## Rhinella_schneideri 2 2 0 24 19 30 45 2 71 18 55
## Scinax_argyreonatus 0 0 0 0 0 0 0 0 0 0 0
## Scinax_crospedospilus 0 0 0 0 0 0 0 0 0 0 0
## Scinax_fuscomarginatus 0 0 0 0 0 0 0 0 0 0 0
## Scinax_fuscovarius 0 0 0 0 0 0 0 0 0 0 0
## Scinax_hayii 0 0 0 0 0 0 0 0 0 0 0
## Scinax_imbegue 0 0 0 0 0 0 0 0 0 0 0
## Scinax_littoralis 0 0 0 0 0 0 0 0 0 0 0
## Scinax_obtriangulatus 0 0 0 0 0 0 0 0 0 0 0
## Scinax_perpusillus 0 0 0 0 0 0 0 0 0 0 0
## Scinax_rizibilis 0 0 0 0 0 0 0 0 0 0 0
## Scinax_ruber 0 0 36 0 0 0 0 0 0 0 0
## Scinax_similis 0 0 0 0 0 0 0 0 0 0 0
## Scinax_squalirostris 0 0 0 0 0 0 0 0 0 0 0
## Scinax_tymbamirim 24 50 0 0 2 1 0 1 0 1 19
## Scythrophrys_sawayae 0 0 0 0 0 0 0 0 0 0 0
## Sphaenorhynchus_caramaschii 0 0 0 0 0 0 0 0 0 0 0
## Sphaenorhynchus_dorisae 0 0 0 0 0 0 0 0 0 0 0
## Sphaenorhynchus_lacteus 0 0 0 0 0 0 0 0 0 0 0
## Stereocyclops_incrassatus 0 0 0 0 0 0 0 0 0 0 0
## Thoropa_miliaris 0 0 0 0 0 0 0 0 0 0 0
## Thoropa_taophora 0 0 0 0 0 0 0 0 0 0 0
## Trachycephalus_imitatrix 0 0 0 0 0 0 0 0 0 0 0
## Trachycephalus_lepidus 0 0 0 0 0 0 0 0 0 0 0
## Trachycephalus_mesophaeus 0 0 0 0 0 0 0 0 0 0 0
## Trachycephalus_nigromaculatus 0 0 0 0 0 0 0 0 0 0 0
## Trachycephalus_typhonius 0 0 0 0 0 0 0 0 0 0 0
## Vitreorana_eurygnatha 0 0 0 0 0 0 0 0 0 0 0
## Vitreorana_uranoscopa 0 0 0 8 0 77 0 24 0 14 0
## Xenohyla_truncata 0 0 0 0 0 0 0 0 0 0 0
## Zachaenus_carvalhoi 0 0 0 0 0 0 0 0 0 0 0
## Zachaenus_parvulus 0 0 0 0 0 0 0 0 0 0 0
## PCB PEE PEI PEJ PES PET PFT PMD PMG PNC PRD
## Adenomera_bokermanni 0 0 0 0 0 0 0 0 0 18 0
## Adenomera_marmorata 48 0 0 9 3 0 0 0 0 0 37
## Ameerega_picta 0 0 0 0 0 0 0 0 0 0 0
## Aparasphenedon_bokermanni 0 0 0 0 0 0 0 0 0 0 0
## Aparasphenodon_brunoi 44 0 0 0 0 0 0 0 0 0 12
## Aplastodiscus_albofrenatus 0 0 0 0 0 0 0 0 0 0 0
## Aplastodiscus_albosignatus 65 0 64 0 0 7 0 0 0 0 0
## Aplastodiscus_arildae 0 0 0 0 0 68 0 0 0 36 0
## Aplastodiscus_cavicola 0 0 0 0 0 0 0 0 0 0 0
## Aplastodiscus_cochranae 0 0 0 0 0 0 0 0 0 46 0
## Aplastodiscus_ehrhardti 0 0 0 0 59 0 0 0 0 0 0
## Aplastodiscus_eugenioi 0 0 0 0 0 0 0 0 0 0 0
## Aplastodiscus_leucopygius 0 0 0 25 0 56 0 0 0 0 0
## Aplastodiscus_perviridis 0 0 0 55 0 0 0 0 20 0 0
## Aplastodiscus_weygoldti 0 0 0 0 0 0 0 0 0 0 0
## Arcovomer_passarellii 0 0 0 0 35 0 0 0 0 0 0
## Barycholos_ternetzi 0 0 0 0 0 0 0 0 0 0 0
## Bokermannohyla_alvarengai 0 0 0 0 0 0 0 0 0 10 0
## Bokermannohyla_astartea 52 0 0 0 0 0 0 0 0 0 0
## Bokermannohyla_circumdata 52 0 0 21 59 22 0 0 0 38 0
## Bokermannohyla_hylax 59 0 0 59 0 46 0 0 0 0 0
## Bokermannohyla_izecksoni 0 0 0 0 0 0 0 0 0 52 0
## Brachycephalus_ephippium 0 0 0 0 0 0 0 0 0 0 0
## Brachycephalus_pitanga 0 0 0 0 0 0 0 0 0 0 0
## Ceratophrys_aurita 53 0 0 0 0 8 0 0 0 0 0
## Ceratophrys_cranwelli 0 0 0 0 0 0 0 0 0 0 0
## Ceratophrys_joazeirensis 0 0 0 66 31 0 0 0 0 0 0
## Ceratophrys_ornata 27 0 0 0 0 63 0 0 0 0 76
## Chiasmocleis_albopunctata 0 21 0 0 0 0 0 69 0 0 0
## Chiasmocleis_cruci 0 0 0 0 2 0 0 0 0 0 0
## Chiasmocleis_leucosticta 0 0 0 15 0 0 0 0 0 0 0
## Chiasmocleis_mantiqueira 0 0 0 0 0 0 0 0 0 0 0
## Corythomantis_greeningi 0 0 0 0 8 0 0 0 0 0 0
## Crossodactylus_caramaschii 48 0 0 47 0 63 0 0 0 0 0
## Crossodactylus_schmdti 0 0 0 0 0 0 0 0 0 0 0
## Cycloramphus_acangatan 11 0 0 24 0 0 0 0 0 0 0
## Cycloramphus_boraceiensis 0 0 0 0 8 0 0 0 0 0 0
## Cycloramphus_eleutherodactylus 0 0 0 0 0 67 0 0 0 0 0
## Cycloramphus_lutzorum 57 0 0 0 0 66 0 0 0 0 0
## Dasypops_schirchi 0 0 0 0 0 0 0 0 0 0 0
## Dendrobates_auratus 0 0 0 0 0 0 0 0 0 0 0
## Dendrophryniscus_brevipollicatus 15 0 0 46 44 0 0 0 0 0 0
## Dendrophryniscus_leucomystax 0 0 0 0 0 0 0 0 0 0 0
## Dendropsophus_anceps 0 0 0 0 0 0 0 0 0 0 5
## Dendropsophus_berthalutzae 0 0 0 0 65 0 0 0 0 0 0
## Dendropsophus_ebraccatus 28 0 0 0 0 75 0 0 0 0 0
## Dendropsophus_elegans 60 0 0 0 77 40 0 0 0 69 2
## Dendropsophus_elianeae 0 35 0 0 0 0 29 0 0 0 0
## Dendropsophus_giesleri 69 0 0 0 34 0 0 0 0 0 0
## Dendropsophus_jimi 0 0 0 0 0 0 0 0 0 0 41
## Dendropsophus_microcephalus 0 0 0 0 0 0 0 0 0 0 0
## Dendropsophus_microps 72 0 55 40 0 34 0 0 0 0 0
## Dendropsophus_minutus 37 16 74 0 70 44 15 47 64 25 21
## Dendropsophus_nanus 0 68 0 0 0 0 79 20 52 0 0
## Dendropsophus_parviceps 0 0 0 0 0 0 0 0 0 0 16
## Dendropsophus_rubicundulus 0 0 0 0 0 0 0 0 0 0 0
## Dendropsophus_sanborni 8 8 68 15 0 0 30 0 0 0 0
## Dendropsophus_seniculus 43 0 76 0 0 2 0 0 0 33 68
## Dendropsophus_triangulum 0 0 0 0 0 0 0 0 0 0 0
## Dendropsophus_werneri 31 0 38 0 0 9 0 0 0 0 0
## Dermatonotus_muelleri 0 0 0 0 0 0 49 0 0 0 0
## Elachistocleis_bicolor 0 64 0 0 0 0 38 72 72 0 0
## Elachistocleis_cesarii 0 0 0 0 0 0 0 0 0 0 0
## Engystomops_petersi 0 0 0 0 0 0 0 0 0 63 8
## Euparkerella_brasiliensis 0 0 0 0 0 0 0 0 0 0 0
## Fritziana_aff._fissilis 46 0 0 9 0 46 0 0 0 0 0
## Fritziana_goeldii 0 0 0 0 0 0 0 0 0 0 0
## Fritziana_ohausi 64 0 0 0 0 73 0 0 0 0 0
## Gastrotheca_cornuta 0 0 0 0 0 0 0 0 0 0 0
## Gastrotheca_fissipes 37 0 0 0 0 0 0 0 0 0 0
## Gastrotheca_pulchra 0 0 0 0 0 0 0 0 0 0 0
## Haddadus_binotatus 32 0 0 0 14 20 0 0 36 0 0
## Holoaden_bradei 0 0 0 0 0 0 0 0 0 47 0
## Holoaden_luederwaldti 0 0 0 0 0 0 0 0 0 0 0
## Hylodes_asper 0 0 0 0 68 30 0 0 0 0 0
## Hylodes_dactylocinus 12 0 0 0 0 37 0 0 0 0 0
## Hylodes_hayeri 0 0 0 0 0 9 0 0 0 0 0
## Hylodes_phyllodes 0 0 0 0 0 0 0 0 0 0 0
## Hylodes_sazimai 0 0 0 0 0 0 0 0 0 0 0
## Hypsiboas_albomarginatus 51 0 0 55 44 24 0 0 0 0 63
## Hypsiboas_albopunctata 71 72 0 59 0 0 41 79 26 15 48
## Hypsiboas_alfarroi 21 0 0 20 15 0 0 0 0 0 0
## Hypsiboas_bischoffi 73 0 27 42 0 0 0 0 0 0 0
## Hypsiboas_caingua 0 0 0 31 0 0 0 0 0 0 0
## Hypsiboas_calcaratus 38 0 0 0 0 0 0 0 0 0 0
## Hypsiboas_crepitans 0 0 0 0 0 0 0 0 0 0 0
## Hypsiboas_faber 32 0 65 12 76 29 0 75 62 62 31
## Hypsiboas_lundii 0 77 0 0 0 0 0 48 0 0 0
## Hypsiboas_marginatus 0 0 0 0 0 0 42 17 2 0 0
## Hypsiboas_multifasciatus 0 0 0 0 0 0 0 80 0 0 0
## Hypsiboas_pardalis 40 0 70 75 0 35 0 0 0 0 0
## Hypsiboas_polytaenius 0 0 0 0 0 0 0 0 0 18 0
## Hypsiboas_pulchellus 37 0 35 78 0 47 0 0 28 0 0
## Hypsiboas_semiguttatus 0 0 0 0 0 0 0 0 0 0 0
## Hypsiboas_semilineatus 11 0 0 40 78 38 0 0 0 0 28
## Hypsiboas_sibleszi 0 0 0 0 0 0 0 0 0 0 0
## Ischnocnema_henseli 0 0 0 0 60 0 0 0 0 0 0
## Ischnocnema_holti 31 0 0 73 78 47 0 0 45 0 0
## Ischnocnema_juipoca 0 0 0 69 0 0 0 0 0 0 0
## Ischnocnema_parva 0 0 0 0 0 49 0 0 0 70 0
## Ischnocnemaguentheri_C1 0 0 0 0 0 0 0 0 0 9 0
## Ischnocnemaguentheri_C3 0 0 0 28 0 0 0 0 0 0 0
## Ischnocnemaguentheri_C4 0 0 0 0 0 0 0 0 0 0 0
## Itapotihyla_langsdorffii 0 0 0 0 54 0 0 61 0 0 80
## Leptodactylus_chaquensis 0 1 0 0 0 0 0 53 0 0 0
## Leptodactylus_flavopictus 0 0 0 0 0 72 0 0 0 0 0
## Leptodactylus_furnarius 0 0 0 0 0 0 0 0 0 0 0
## Leptodactylus_fuscus 17 0 0 0 0 30 0 0 0 0 0
## Leptodactylus_labyrinthicus 0 43 0 0 0 0 0 0 0 0 0
## Leptodactylus_latrans 78 65 51 52 0 0 69 45 76 57 66
## Leptodactylus_mystaceus 0 0 0 0 0 0 0 0 0 5 0
## Leptodactylus_mystacinus 0 1 0 0 0 0 0 20 54 0 8
## Leptodactylus_notoaktites 0 8 0 0 0 0 0 43 0 0 0
## Leptodactylus_plaumanni 0 40 0 55 0 23 41 45 80 0 0
## Leptodactylus_podicipinus 0 0 0 0 0 0 0 0 0 0 0
## Leptodactylus_rhodomystax 70 0 7 0 0 76 0 0 0 0 0
## Limnomedusa_macroglossa 70 0 26 4 0 67 0 20 54 8 72
## Lysapsus_limellum 0 42 0 0 0 0 34 57 0 0 0
## Lysapus_laevis 0 0 0 0 0 0 0 0 0 0 38
## Macrogenioglottus_alipioi 36 0 0 8 65 7 0 0 0 0 0
## Megaelosia_aff._boticariana 0 0 0 0 0 0 0 0 0 0 0
## Megaelosia_boticariana 0 0 0 0 0 0 0 0 0 0 0
## Melanophryniscus_devincenzii 0 0 0 0 0 0 0 0 0 0 0
## Myersiella_microps 20 0 0 17 23 5 0 0 0 0 0
## Odontophrynus_americanus 0 0 57 62 0 0 0 17 50 0 0
## Odontophrynus_cultripes 0 0 0 0 0 0 0 0 0 13 0
## Paratelmatobius_cardosoi 0 0 0 75 0 0 0 0 0 0 0
## Paratelmatobius_gaigeae 0 0 0 0 0 0 0 0 0 0 0
## Phasmahyla_cochranae 17 0 0 0 0 0 0 0 0 0 0
## Phasmahyla_exilis 0 0 0 0 0 0 0 0 0 0 0
## Phasmahyla_guttata 0 0 0 0 31 0 0 0 0 0 0
## Phrynomedusa_dryade 0 0 0 0 0 0 0 0 0 0 0
## Phyllobates_bicolor 0 0 0 0 0 0 0 0 0 0 0
## Phyllodytes_luteolus 0 0 0 0 0 0 0 0 0 0 0
## Phyllomedusa_azurea 0 0 0 0 0 0 0 0 0 76 8
## Phyllomedusa_burmeisteri 72 0 30 0 0 50 0 0 0 0 0
## Phyllomedusa_camba 0 0 0 0 0 0 0 0 0 0 3
## Phyllomedusa_distincta 0 0 0 0 0 0 0 0 0 0 0
## Phyllomedusa_hypochondrialis 0 0 0 0 0 0 0 0 61 0 0
## Phyllomedusa_megacephala 0 0 0 0 0 0 0 0 0 0 0
## Phyllomedusa_nordestina 0 60 0 0 0 0 4 0 0 0 0
## Phyllomedusa_rohdei 0 0 0 0 0 0 0 0 0 0 0
## Phyllomedusa_sauvagii 49 70 30 37 0 75 7 2 1 1 30
## Phyllomedusa_tetraploidea 0 0 0 0 0 0 0 0 0 65 0
## Phyllomedusa_tomopterna 0 0 0 0 0 0 0 0 0 0 0
## Physalaemus_atlanticus 0 0 0 0 0 17 0 0 0 0 0
## Physalaemus_bokermanni 0 0 0 0 0 0 0 0 0 0 0
## Physalaemus_centralis 59 0 0 0 0 0 0 0 0 0 0
## Physalaemus_cuvieri 0 0 0 0 0 0 0 0 0 0 1
## Physalaemus_lateristriga 45 0 3 4 0 12 0 0 0 0 0
## Physalaemus_maculiventris 0 0 0 0 68 0 0 0 0 0 0
## Physalaemus_marmoratus 30 0 0 0 0 47 0 0 0 0 0
## Physalaemus_nattereri 0 60 0 0 0 0 73 72 0 0 0
## Physalaemus_olfersii 0 0 0 0 0 0 0 0 41 0 0
## Physalaemus_spiniger 61 0 1 1 0 1 0 0 0 1 0
## Pipa_carvalhoi 0 0 0 0 0 0 0 0 0 0 0
## Pleurodema_brachyops 0 0 0 0 0 0 0 0 0 0 0
## Pleurodema_diplolister 0 0 0 0 0 0 0 0 0 0 4
## Proceratophrys_appendiculata 0 0 0 0 0 0 30 9 0 0 0
## Proceratophrys_avelinoi 0 0 0 0 0 0 6 0 0 0 3
## Proceratophrys_boiei 0 0 0 0 0 0 0 0 0 0 0
## Proceratophrys_cristiceps 0 0 0 0 0 0 0 0 0 0 0
## Proceratophrys_laticeps 2 0 0 0 38 0 0 0 0 0 0
## Proceratophrys_melanopogon 0 0 0 0 17 0 0 0 0 0 0
## Proceratophrys_schirchi 0 0 0 0 41 0 0 0 0 0 22
## Pseudis_minuta 0 0 0 0 0 43 0 49 0 0 0
## Pseudis_paradoxa 65 0 0 0 0 0 0 0 0 0 0
## Pseudis_platensis 0 0 0 0 0 0 0 0 0 0 48
## Pseudopaludicola_falcipes 16 0 0 0 0 0 0 0 0 0 0
## Pseudopaludicola_mineira 0 0 15 52 0 0 0 0 0 0 0
## Pseudopaludicola_mystacalis 0 0 0 0 0 0 0 0 0 0 0
## Pseudopaludicola_saltica 0 0 0 0 0 75 0 0 0 0 12
## Rhinella_crucifer 0 0 3 0 7 0 0 0 6 0 77
## Rhinella_granulosa 0 0 0 0 0 0 0 0 0 0 0
## Rhinella_henseli 0 0 0 0 25 0 0 0 0 35 32
## Rhinella_hoogmoedi 26 0 0 0 0 0 0 0 0 0 0
## Rhinella_icterica 46 21 0 68 0 0 29 52 0 0 74
## Rhinella_ocellata 0 57 37 0 0 70 51 33 25 24 45
## Rhinella_ornata 17 0 0 80 0 14 0 56 0 0 0
## Rhinella_schneideri 0 66 0 0 0 0 25 57 68 0 19
## Scinax_argyreonatus 0 0 0 0 0 0 0 0 0 0 0
## Scinax_crospedospilus 0 0 0 0 0 0 0 0 0 0 0
## Scinax_fuscomarginatus 0 0 0 0 0 0 0 0 0 0 0
## Scinax_fuscovarius 0 0 0 0 0 0 0 0 0 0 0
## Scinax_hayii 78 0 0 0 0 0 0 0 0 0 0
## Scinax_imbegue 0 0 0 0 0 0 0 0 0 6 0
## Scinax_littoralis 0 0 0 0 0 0 0 0 0 64 0
## Scinax_obtriangulatus 0 0 0 0 0 0 0 0 0 0 0
## Scinax_perpusillus 0 0 0 0 0 0 0 0 0 0 0
## Scinax_rizibilis 1 0 0 7 0 56 0 0 75 0 0
## Scinax_ruber 1 0 0 0 0 33 0 0 0 0 0
## Scinax_similis 48 0 22 46 0 34 0 0 0 0 0
## Scinax_squalirostris 31 0 0 72 0 0 0 0 0 0 0
## Scinax_tymbamirim 0 6 0 0 0 0 22 7 0 0 0
## Scythrophrys_sawayae 0 0 0 0 63 0 0 0 0 0 0
## Sphaenorhynchus_caramaschii 0 0 0 0 0 0 0 0 0 0 29
## Sphaenorhynchus_dorisae 0 0 0 0 0 0 0 0 0 0 0
## Sphaenorhynchus_lacteus 0 0 0 0 0 14 0 0 0 0 0
## Stereocyclops_incrassatus 0 0 0 0 0 0 0 0 0 0 0
## Thoropa_miliaris 0 0 0 0 0 36 0 0 0 0 0
## Thoropa_taophora 0 0 0 0 0 0 0 0 0 0 53
## Trachycephalus_imitatrix 0 0 79 49 0 0 0 0 0 0 0
## Trachycephalus_lepidus 0 0 0 0 0 0 0 0 0 0 35
## Trachycephalus_mesophaeus 0 0 0 0 0 0 0 0 0 1 0
## Trachycephalus_nigromaculatus 11 0 0 0 13 0 0 0 0 77 0
## Trachycephalus_typhonius 0 0 0 0 11 0 0 0 0 0 0
## Vitreorana_eurygnatha 0 0 0 0 0 0 0 0 0 0 0
## Vitreorana_uranoscopa 0 0 0 0 0 0 0 66 0 0 0
## Xenohyla_truncata 0 0 0 0 0 0 0 0 0 0 0
## Zachaenus_carvalhoi 8 0 0 27 12 70 0 0 16 73 0
## Zachaenus_parvulus 0 0 0 0 0 0 0 0 0 0 0
## PSB RDB RRP SAA SFS SJB SJP SMV TSJ TSS VFP
## Adenomera_bokermanni 0 0 0 0 0 0 0 0 0 0 0
## Adenomera_marmorata 0 0 1 0 0 0 23 0 0 0 0
## Ameerega_picta 69 0 0 0 0 0 0 0 0 0 0
## Aparasphenedon_bokermanni 0 0 0 0 0 0 0 0 0 0 0
## Aparasphenodon_brunoi 0 0 0 0 0 0 0 0 0 0 0
## Aplastodiscus_albofrenatus 0 0 0 0 0 0 0 0 0 0 0
## Aplastodiscus_albosignatus 0 0 0 0 0 0 19 0 0 0 0
## Aplastodiscus_arildae 0 0 41 0 0 0 0 0 0 0 0
## Aplastodiscus_cavicola 0 44 0 0 0 0 0 0 0 0 0
## Aplastodiscus_cochranae 0 0 0 0 0 0 0 0 0 0 0
## Aplastodiscus_ehrhardti 0 0 0 0 0 0 35 0 0 0 0
## Aplastodiscus_eugenioi 0 0 33 0 0 0 0 0 0 0 0
## Aplastodiscus_leucopygius 0 0 0 0 0 43 0 0 0 0 0
## Aplastodiscus_perviridis 0 0 0 0 0 40 59 0 0 0 0
## Aplastodiscus_weygoldti 0 73 0 0 0 0 0 0 0 0 0
## Arcovomer_passarellii 0 0 0 0 0 0 0 0 0 0 0
## Barycholos_ternetzi 0 30 0 0 0 0 0 0 0 0 0
## Bokermannohyla_alvarengai 0 0 0 0 0 0 0 0 0 0 0
## Bokermannohyla_astartea 0 0 0 0 0 0 0 0 0 0 0
## Bokermannohyla_circumdata 0 0 59 0 0 68 79 0 0 0 0
## Bokermannohyla_hylax 0 0 0 0 0 0 0 0 0 0 0
## Bokermannohyla_izecksoni 0 0 0 0 0 0 0 0 0 0 0
## Brachycephalus_ephippium 0 0 1 0 0 0 0 0 0 0 0
## Brachycephalus_pitanga 0 0 16 0 0 0 0 0 0 0 0
## Ceratophrys_aurita 0 0 0 0 0 0 0 0 0 0 0
## Ceratophrys_cranwelli 0 0 0 0 0 0 0 0 0 0 0
## Ceratophrys_joazeirensis 0 0 0 0 0 0 0 0 0 0 0
## Ceratophrys_ornata 0 42 0 0 0 0 0 0 0 0 0
## Chiasmocleis_albopunctata 6 0 0 0 0 0 0 0 0 22 0
## Chiasmocleis_cruci 0 0 0 0 0 0 0 0 0 0 0
## Chiasmocleis_leucosticta 0 0 0 0 0 0 27 0 0 0 0
## Chiasmocleis_mantiqueira 0 29 0 0 0 0 0 0 0 0 0
## Corythomantis_greeningi 0 22 38 0 0 0 0 0 0 0 0
## Crossodactylus_caramaschii 0 0 0 0 0 0 0 0 0 0 0
## Crossodactylus_schmdti 0 0 0 0 0 0 0 0 0 0 0
## Cycloramphus_acangatan 0 0 0 0 0 0 0 0 0 0 0
## Cycloramphus_boraceiensis 0 0 0 0 0 0 0 0 0 0 0
## Cycloramphus_eleutherodactylus 0 0 0 0 0 0 0 0 0 0 0
## Cycloramphus_lutzorum 0 0 0 0 0 0 0 0 0 0 0
## Dasypops_schirchi 0 0 0 0 0 0 0 0 0 0 0
## Dendrobates_auratus 0 0 0 0 0 0 0 0 0 0 0
## Dendrophryniscus_brevipollicatus 0 0 35 0 0 0 0 0 0 0 0
## Dendrophryniscus_leucomystax 0 0 0 0 0 0 0 0 0 0 0
## Dendropsophus_anceps 0 0 76 0 0 0 0 0 0 0 0
## Dendropsophus_berthalutzae 0 0 0 0 0 0 0 0 0 0 0
## Dendropsophus_ebraccatus 0 1 25 0 0 0 0 0 0 0 0
## Dendropsophus_elegans 0 59 45 0 0 44 0 27 0 0 0
## Dendropsophus_elianeae 68 0 0 0 32 0 0 0 25 0 4
## Dendropsophus_giesleri 0 0 6 0 0 0 0 0 0 0 0
## Dendropsophus_jimi 0 36 0 0 0 0 0 0 0 0 0
## Dendropsophus_microcephalus 19 0 0 0 0 0 0 0 0 0 0
## Dendropsophus_microps 0 77 0 0 0 9 12 0 0 0 0
## Dendropsophus_minutus 14 17 78 75 12 60 43 45 37 0 71
## Dendropsophus_nanus 12 0 0 10 4 0 0 0 47 41 71
## Dendropsophus_parviceps 0 53 39 0 0 0 0 20 0 0 0
## Dendropsophus_rubicundulus 40 0 0 0 0 0 0 0 0 0 0
## Dendropsophus_sanborni 0 0 0 12 0 0 0 0 0 0 0
## Dendropsophus_seniculus 0 38 63 0 0 0 0 0 0 0 0
## Dendropsophus_triangulum 0 0 0 0 0 0 0 0 0 0 0
## Dendropsophus_werneri 0 0 0 0 0 0 0 0 0 0 0
## Dermatonotus_muelleri 0 0 0 47 70 0 0 0 42 0 3
## Elachistocleis_bicolor 50 0 0 0 0 0 0 0 0 43 0
## Elachistocleis_cesarii 0 0 0 0 0 0 0 0 0 0 0
## Engystomops_petersi 0 0 0 0 0 0 0 0 0 0 0
## Euparkerella_brasiliensis 0 0 0 0 0 0 0 0 0 0 0
## Fritziana_aff._fissilis 0 0 0 0 0 0 0 0 0 0 0
## Fritziana_goeldii 0 0 17 0 0 0 0 0 0 0 0
## Fritziana_ohausi 0 0 49 0 0 0 0 0 0 0 0
## Gastrotheca_cornuta 0 0 9 0 0 0 0 0 0 0 0
## Gastrotheca_fissipes 0 0 0 0 0 0 0 0 0 0 0
## Gastrotheca_pulchra 0 78 0 0 0 0 0 0 0 0 0
## Haddadus_binotatus 0 8 63 0 0 75 0 35 0 0 0
## Holoaden_bradei 0 0 0 0 0 0 0 0 0 0 0
## Holoaden_luederwaldti 0 0 0 0 0 0 0 0 0 0 0
## Hylodes_asper 0 0 80 0 0 0 0 0 0 0 0
## Hylodes_dactylocinus 0 0 0 0 0 0 0 0 0 0 0
## Hylodes_hayeri 0 0 0 0 0 0 7 0 0 0 0
## Hylodes_phyllodes 0 53 0 0 0 0 0 0 0 0 0
## Hylodes_sazimai 0 0 0 0 0 0 0 0 0 0 0
## Hypsiboas_albomarginatus 0 71 10 0 0 0 0 49 0 0 0
## Hypsiboas_albopunctata 0 57 0 5 15 32 34 0 43 13 44
## Hypsiboas_alfarroi 0 0 23 0 0 0 0 0 0 0 0
## Hypsiboas_bischoffi 0 0 0 0 0 0 57 0 0 0 0
## Hypsiboas_caingua 0 0 0 0 0 0 0 0 0 0 0
## Hypsiboas_calcaratus 0 0 0 0 0 0 0 0 0 0 0
## Hypsiboas_crepitans 0 0 0 0 0 0 0 0 0 0 0
## Hypsiboas_faber 0 42 79 0 0 18 43 14 0 0 0
## Hypsiboas_lundii 0 0 0 0 0 0 0 0 0 0 0
## Hypsiboas_marginatus 73 0 0 3 48 0 0 0 77 0 33
## Hypsiboas_multifasciatus 16 0 0 0 0 0 0 0 0 0 0
## Hypsiboas_pardalis 0 23 0 0 0 37 0 51 0 0 0
## Hypsiboas_polytaenius 0 0 0 0 0 32 0 0 0 0 0
## Hypsiboas_pulchellus 0 0 0 0 0 0 1 0 0 0 0
## Hypsiboas_semiguttatus 0 0 0 0 0 0 53 0 0 0 0
## Hypsiboas_semilineatus 0 20 79 0 0 12 0 59 0 0 0
## Hypsiboas_sibleszi 0 0 0 0 0 0 0 0 0 0 0
## Ischnocnema_henseli 0 0 0 0 0 0 0 0 0 0 0
## Ischnocnema_holti 0 58 50 0 0 38 68 0 0 0 0
## Ischnocnema_juipoca 0 0 0 0 0 0 0 0 0 0 0
## Ischnocnema_parva 0 0 0 0 0 0 0 0 0 0 0
## Ischnocnemaguentheri_C1 0 0 0 0 0 0 0 0 0 0 0
## Ischnocnemaguentheri_C3 0 0 0 0 0 30 0 0 0 0 0
## Ischnocnemaguentheri_C4 0 0 57 0 0 0 0 0 0 0 0
## Itapotihyla_langsdorffii 0 0 0 0 0 0 0 0 0 0 0
## Leptodactylus_chaquensis 76 0 0 0 71 0 0 0 48 0 29
## Leptodactylus_flavopictus 0 44 0 0 0 0 0 0 0 0 0
## Leptodactylus_furnarius 17 0 0 0 0 0 0 0 0 0 0
## Leptodactylus_fuscus 0 0 0 0 0 0 0 0 0 0 0
## Leptodactylus_labyrinthicus 0 0 0 0 0 0 0 0 0 0 0
## Leptodactylus_latrans 28 0 0 30 5 72 0 0 15 49 2
## Leptodactylus_mystaceus 63 0 0 0 0 0 0 0 0 0 0
## Leptodactylus_mystacinus 63 0 0 0 6 76 0 0 57 0 0
## Leptodactylus_notoaktites 0 0 0 0 0 0 0 0 40 0 1
## Leptodactylus_plaumanni 19 0 0 70 0 0 0 0 6 61 55
## Leptodactylus_podicipinus 0 23 0 0 0 0 0 0 0 0 0
## Leptodactylus_rhodomystax 0 0 0 0 0 0 41 0 0 0 0
## Limnomedusa_macroglossa 0 57 60 0 0 50 80 7 0 0 0
## Lysapsus_limellum 7 0 0 21 39 0 0 0 6 71 44
## Lysapus_laevis 0 0 15 0 0 0 0 14 0 0 0
## Macrogenioglottus_alipioi 0 0 0 0 0 0 0 0 0 0 0
## Megaelosia_aff._boticariana 67 0 0 0 0 0 0 0 0 0 0
## Megaelosia_boticariana 0 0 0 0 0 0 0 0 0 0 0
## Melanophryniscus_devincenzii 6 0 0 0 0 0 0 0 0 0 0
## Myersiella_microps 0 0 0 0 0 0 0 0 0 0 0
## Odontophrynus_americanus 60 0 0 0 0 0 0 0 0 0 0
## Odontophrynus_cultripes 0 0 0 0 0 0 0 0 0 0 0
## Paratelmatobius_cardosoi 0 0 0 0 0 0 0 0 0 0 0
## Paratelmatobius_gaigeae 0 0 0 0 0 0 0 0 0 0 0
## Phasmahyla_cochranae 0 0 0 0 0 0 0 0 0 0 0
## Phasmahyla_exilis 0 4 0 0 0 0 0 0 0 0 0
## Phasmahyla_guttata 0 0 34 0 0 0 0 0 0 0 0
## Phrynomedusa_dryade 0 0 0 0 0 0 0 0 0 0 0
## Phyllobates_bicolor 0 0 0 0 0 0 0 0 0 0 0
## Phyllodytes_luteolus 12 0 0 0 0 0 0 0 0 0 0
## Phyllomedusa_azurea 0 79 60 0 0 3 0 74 0 0 0
## Phyllomedusa_burmeisteri 0 0 0 0 0 0 0 0 0 0 0
## Phyllomedusa_camba 0 0 0 0 0 0 0 0 0 0 0
## Phyllomedusa_distincta 14 0 0 0 0 0 0 0 0 0 0
## Phyllomedusa_hypochondrialis 0 0 0 0 0 0 0 0 0 0 0
## Phyllomedusa_megacephala 2 0 0 0 0 0 0 0 0 0 0
## Phyllomedusa_nordestina 0 0 0 58 33 0 0 0 51 0 30
## Phyllomedusa_rohdei 0 13 0 0 0 0 0 0 0 0 0
## Phyllomedusa_sauvagii 1 2 0 2 2 3 4 0 56 5 23
## Phyllomedusa_tetraploidea 0 0 0 0 0 0 0 0 0 0 0
## Phyllomedusa_tomopterna 0 0 0 0 0 0 19 0 0 0 0
## Physalaemus_atlanticus 0 0 0 0 0 0 0 0 0 0 0
## Physalaemus_bokermanni 0 0 0 0 65 0 0 0 0 0 0
## Physalaemus_centralis 0 0 0 0 0 0 0 0 0 0 0
## Physalaemus_cuvieri 0 0 0 0 0 0 0 0 0 0 0
## Physalaemus_lateristriga 0 0 0 0 0 15 40 0 0 0 0
## Physalaemus_maculiventris 0 0 0 0 0 0 0 0 0 0 0
## Physalaemus_marmoratus 0 0 0 0 0 0 0 0 0 0 0
## Physalaemus_nattereri 49 0 0 30 79 0 0 0 17 0 3
## Physalaemus_olfersii 0 0 0 0 0 0 0 0 0 0 0
## Physalaemus_spiniger 0 0 0 0 0 1 1 0 0 0 0
## Pipa_carvalhoi 0 1 0 0 0 0 0 0 0 0 0
## Pleurodema_brachyops 0 6 0 0 0 0 0 0 0 0 0
## Pleurodema_diplolister 0 0 0 0 0 0 0 0 0 0 0
## Proceratophrys_appendiculata 2 0 0 0 0 0 0 0 80 0 13
## Proceratophrys_avelinoi 0 0 0 1 0 0 0 0 22 43 54
## Proceratophrys_boiei 2 0 0 0 0 0 0 0 0 0 11
## Proceratophrys_cristiceps 0 0 0 0 3 0 0 0 0 0 0
## Proceratophrys_laticeps 0 4 0 0 0 0 0 0 0 0 0
## Proceratophrys_melanopogon 0 0 6 0 0 0 0 0 0 0 0
## Proceratophrys_schirchi 0 5 6 0 0 0 0 0 0 0 0
## Pseudis_minuta 0 0 0 0 0 0 0 0 0 0 0
## Pseudis_paradoxa 0 0 0 0 0 0 0 0 0 0 0
## Pseudis_platensis 0 0 0 0 0 0 0 0 0 0 0
## Pseudopaludicola_falcipes 0 57 0 0 0 0 5 0 0 0 0
## Pseudopaludicola_mineira 0 0 0 0 0 0 0 0 0 0 0
## Pseudopaludicola_mystacalis 0 0 0 0 0 0 0 0 0 0 0
## Pseudopaludicola_saltica 0 78 0 0 0 0 0 0 0 0 0
## Rhinella_crucifer 0 25 0 0 0 0 0 46 0 0 0
## Rhinella_granulosa 76 33 0 0 0 0 0 0 0 0 0
## Rhinella_henseli 0 0 0 0 0 0 0 0 0 0 0
## Rhinella_hoogmoedi 0 0 0 0 0 0 0 0 0 0 0
## Rhinella_icterica 39 0 0 47 0 18 0 0 6 0 53
## Rhinella_ocellata 78 5 55 0 53 5 58 29 73 0 34
## Rhinella_ornata 0 0 14 0 0 12 0 0 0 0 0
## Rhinella_schneideri 12 0 0 62 39 0 0 0 12 0 10
## Scinax_argyreonatus 0 0 0 0 0 0 0 0 0 0 0
## Scinax_crospedospilus 0 17 0 0 0 52 0 0 0 0 0
## Scinax_fuscomarginatus 0 0 0 0 0 0 0 0 0 0 0
## Scinax_fuscovarius 0 54 0 0 0 0 0 0 0 0 0
## Scinax_hayii 0 0 0 0 0 0 0 0 0 0 0
## Scinax_imbegue 0 0 0 0 0 0 0 0 0 0 0
## Scinax_littoralis 0 0 0 0 0 0 0 0 0 0 0
## Scinax_obtriangulatus 72 0 0 0 0 0 0 0 0 0 0
## Scinax_perpusillus 0 0 0 0 0 0 0 0 0 0 0
## Scinax_rizibilis 0 0 0 0 0 0 28 0 0 0 0
## Scinax_ruber 0 0 3 0 0 79 0 0 0 0 0
## Scinax_similis 0 0 0 0 0 0 53 0 0 0 0
## Scinax_squalirostris 50 0 0 0 0 0 14 0 0 0 0
## Scinax_tymbamirim 0 0 0 0 43 64 0 0 21 0 47
## Scythrophrys_sawayae 0 0 0 0 0 0 0 58 0 0 0
## Sphaenorhynchus_caramaschii 0 0 0 0 0 0 20 79 0 0 0
## Sphaenorhynchus_dorisae 0 0 0 0 0 0 23 0 0 0 0
## Sphaenorhynchus_lacteus 0 0 0 0 0 0 0 0 0 0 0
## Stereocyclops_incrassatus 0 0 0 0 0 0 0 0 0 0 0
## Thoropa_miliaris 0 0 0 0 0 0 0 0 0 0 0
## Thoropa_taophora 0 0 0 0 0 0 0 0 0 0 0
## Trachycephalus_imitatrix 0 0 0 0 0 0 12 0 0 0 0
## Trachycephalus_lepidus 0 0 0 0 0 0 0 0 0 0 0
## Trachycephalus_mesophaeus 0 0 0 0 0 0 0 0 0 0 0
## Trachycephalus_nigromaculatus 0 3 65 0 0 0 0 3 0 0 0
## Trachycephalus_typhonius 0 63 23 0 0 0 0 0 0 0 0
## Vitreorana_eurygnatha 0 0 0 0 0 0 0 0 0 0 0
## Vitreorana_uranoscopa 78 0 0 0 65 0 0 0 0 0 0
## Xenohyla_truncata 0 0 0 0 0 77 0 0 0 0 0
## Zachaenus_carvalhoi 0 69 64 0 0 0 0 0 0 0 0
## Zachaenus_parvulus 0 71 0 0 0 0 0 0 0 0 0anuros_ambientais## Temp_anual Range_altitude Prec_anual sazonalidade Latitude Longitude
## AEP 20.62500 390 1394 88.56409 19.86733 43.35887
## AGA 22.59167 102 1225 54.43643 19.93278 40.45849
## APJ 17.24167 480 1359 66.98990 23.24134 46.95850
## BFF 22.83750 130 1305 80.46240 20.63722 48.75167
## CRS 21.31667 1350 1958 45.52962 25.49861 48.84139
## EEB 16.76667 210 2315 40.30820 23.65005 45.95666
## EEC 20.27500 182 1296 61.86909 22.40209 49.69718
## EEJ 20.43750 800 2045 44.28981 24.51667 47.26667
## EGH 22.64167 700 1560 55.51461 22.58041 43.03419
## FAC 22.40000 65 1200 70.65537 21.40472 49.50028
## FBV 22.55417 88 1194 72.38655 20.92111 49.92611
## FCB 22.44167 96 1340 80.81953 20.88500 48.54056
## FEN 20.22917 215 1306 74.39306 22.40739 47.52815
## FMG 16.73750 240 1769 52.98825 23.72642 46.96822
## FSF 23.03750 73 1181 72.33449 20.47361 50.29333
## GSJ 23.16667 95 1281 81.56695 20.54361 49.24639
## ICE 23.79167 117 1266 81.82911 20.33333 49.18333
## IFP 22.53750 110 1220 73.09477 20.74278 49.92917
## MFC 21.42917 100 1318 77.70323 21.62056 48.53722
## NHS 22.13333 90 1236 71.72170 21.52083 49.29472
## NIT 22.52500 70 1173 74.74605 21.06667 49.53333
## PBV 23.18333 92 1217 81.84919 20.32111 49.50472
## PCB 21.44583 187 1586 51.58942 24.11203 47.62764
## PEE 22.11667 101 1278 77.02185 21.22000 48.91778
## PEI 20.40417 785 1628 49.54435 24.17445 47.95255
## PEJ 18.35417 283 1747 49.75492 23.97605 47.37681
## PES 18.57917 980 1948 53.87132 23.53640 45.30610
## PET 18.01250 375 1389 44.14913 24.37500 48.56667
## PFT 22.62083 84 1185 71.48864 21.00139 49.97389
## PMD 22.06667 200 1188 44.69418 22.54029 52.31120
## PMG 20.71250 192 1496 39.31201 23.45300 51.23909
## PNC 20.23750 1213 1369 87.84981 20.09701 43.40438
## PRD 23.60417 230 1144 82.23320 19.58671 42.53896
## PSB 22.02500 155 1354 45.53205 20.98100 56.71567
## RDB 21.67917 180 1242 50.37565 20.27675 40.50187
## RRP 21.71667 700 1463 57.01697 22.99011 44.08947
## SAA 22.61250 100 1190 70.24669 20.92611 50.34861
## SFS 22.65833 99 1250 69.40527 20.18333 50.88333
## SJB 19.98333 870 1512 73.67402 22.61902 44.65343
## SJP 15.94583 370 1602 30.44136 25.68333 49.05000
## SMV 20.89167 921 1277 67.22585 21.48333 41.86667
## TSJ 23.01667 80 1200 74.70548 20.00361 50.43389
## TSS 22.22917 102 1289 78.73780 21.40222 48.68722
## VFP 23.01667 105 1207 72.58030 20.51444 50.08667
## Riqueza
## AEP 24
## AGA 41
## APJ 30
## BFF 16
## CRS 31
## EEB 64
## EEC 24
## EEJ 25
## EGH 39
## FAC 20
## FBV 24
## FCB 13
## FEN 20
## FMG 25
## FSF 24
## GSJ 20
## ICE 25
## IFP 24
## MFC 21
## NHS 18
## NIT 26
## PBV 20
## PCB 64
## PEE 22
## PEI 25
## PEJ 45
## PES 39
## PET 55
## PFT 20
## PMD 28
## PMG 23
## PNC 37
## PRD 36
## PSB 36
## RDB 49
## RRP 41
## SAA 15
## SFS 19
## SJB 32
## SJP 34
## SMV 19
## TSJ 21
## TSS 9
## VFP 21