Comprobación de R II - Riqueza de Especies
Andrés Rojas González & Jesús Herrera Mora
12/9/2021
Análisis de riqueza de especies a partir de una base de datos hipotética
Base de Datos
■■■
datos <- read.delim("D:/Downloads/UNA/II Ciclo 2021/Tecnicas de Muestreo/R/Ejrecicio_RiquezaEspecies/Diversidad_aves.txt")
View(datos)
head(datos) # Muestra las primeras 6 filas## Zona Plot Ada Albert Alice Anna Annie Arthur Bert Bertha Charlie Clara
## 1 Forest_A P1 4 0 0 0 0 0 0 0 0 0
## 2 Forest_A P1 0 0 0 4 0 0 0 0 0 0
## 3 Forest_A P1 0 0 0 1 0 0 0 0 0 0
## 4 Forest_A P1 0 0 0 0 0 0 0 4 0 0
## 5 Forest_A P1 5 0 0 5 0 0 0 3 0 2
## 6 Forest_A P1 0 0 0 0 0 0 0 5 0 2
## Clarence Cora Daisy Daniel David Edith Elizabeth Elmer Emma Ernest Ethel Eva
## 1 0 0 0 0 0 0 0 0 0 0 0 0
## 2 0 0 2 0 0 0 0 0 0 0 0 0
## 3 0 0 0 0 0 0 0 0 0 0 0 0
## 4 0 0 0 0 0 0 0 0 0 0 0 0
## 5 0 0 0 0 0 0 0 0 0 0 0 0
## 6 5 0 0 0 0 0 0 0 0 0 0 0
## Fannie Florence Frances Francis Frank Frederick Gertrude Hattie Henry Herbert
## 1 0 0 0 0 0 0 0 0 0 0
## 2 0 0 0 0 0 0 0 0 0 0
## 3 0 0 0 0 0 0 0 0 0 0
## 4 0 0 0 0 0 0 0 0 0 0
## 5 0 0 0 0 0 0 0 0 0 0
## 6 0 11 0 0 0 0 0 0 3 12
## Howard Ida Jacob James Jennie Jesse Jim Joe Josephine Julia Lee Lena Lewis
## 1 0 0 0 0 0 0 0 0 0 0 0 0 0
## 2 0 0 0 0 0 0 0 0 0 0 0 0 0
## 3 0 0 0 0 0 0 0 0 0 0 0 0 0
## 4 0 0 0 0 0 0 0 0 0 0 0 0 0
## 5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 6 5 0 0 0 0 0 0 0 0 0 0 0 0
## Lillian Lillie Louise Lucy Lula Mabel Maggie Margaret Martha Martin Mary
## 1 0 0 0 0 0 0 0 0 0 0 0
## 2 0 0 0 0 0 0 0 0 0 0 0
## 3 0 0 0 0 0 0 0 0 0 0 0
## 4 0 0 0 0 0 0 0 0 0 0 0
## 5 0 0 0 0 0 0 0 0 0 0 0
## 6 0 0 0 0 0 0 0 0 0 0 0
## Mattie Maude Myrtle Oscar Pearl Rose Roy Samuel Sarah Tom Will William
## 1 0 0 0 0 0 0 0 0 0 0 0 0
## 2 0 0 0 0 0 0 0 0 0 0 0 0
## 3 0 0 0 0 0 0 0 0 0 0 0 0
## 4 0 0 0 0 0 0 0 0 0 0 0 0
## 5 0 0 0 0 0 0 0 0 0 0 0 0
## 6 0 0 0 0 0 0 0 0 0 0 0 0tail(datos) # Muestra las últimas 6 filas## Zona Plot Ada Albert Alice Anna Annie Arthur Bert Bertha Charlie Clara
## 190 Rustic_B P14 0 0 0 0 0 0 0 0 0 0
## 191 Rustic_B P14 0 0 0 0 0 0 0 0 0 0
## 192 Rustic_B P14 0 0 0 0 0 0 0 0 0 0
## 193 Rustic_B P14 0 0 0 0 0 0 0 0 0 0
## 194 Rustic_B P14 0 0 0 0 0 0 0 0 0 0
## 195 Rustic_B P14 0 0 0 0 0 0 0 0 0 0
## Clarence Cora Daisy Daniel David Edith Elizabeth Elmer Emma Ernest Ethel
## 190 0 0 0 0 0 0 0 0 0 0 0
## 191 0 0 0 0 0 0 0 0 0 0 0
## 192 0 0 0 0 0 0 0 0 0 0 0
## 193 0 0 0 0 0 0 0 0 0 0 0
## 194 0 0 0 0 0 0 0 0 0 0 0
## 195 0 0 0 0 0 0 0 0 0 0 0
## Eva Fannie Florence Frances Francis Frank Frederick Gertrude Hattie Henry
## 190 0 0 0 0 0 0 0 0 0 0
## 191 0 0 0 0 0 0 0 0 0 0
## 192 0 0 0 0 0 0 0 0 0 0
## 193 0 0 0 0 0 0 0 0 0 0
## 194 0 0 0 0 0 0 0 0 0 0
## 195 0 0 0 0 0 0 0 0 0 0
## Herbert Howard Ida Jacob James Jennie Jesse Jim Joe Josephine Julia Lee
## 190 0 0 0 0 0 0 0 0 0 0 0 0
## 191 0 0 0 0 0 0 0 0 0 0 0 0
## 192 0 0 0 0 0 3 0 0 0 0 0 0
## 193 0 0 0 0 0 0 0 0 0 3 0 0
## 194 0 0 0 0 0 0 0 0 0 0 0 2
## 195 0 0 0 0 0 0 0 0 0 0 0 0
## Lena Lewis Lillian Lillie Louise Lucy Lula Mabel Maggie Margaret Martha
## 190 0 0 0 0 0 0 0 0 0 0 0
## 191 0 0 0 0 0 0 0 0 0 0 0
## 192 0 0 0 0 0 0 0 0 0 0 0
## 193 0 0 0 0 0 0 0 0 0 0 0
## 194 0 0 0 0 0 0 0 0 0 0 0
## 195 0 0 0 0 0 0 0 0 0 0 0
## Martin Mary Mattie Maude Myrtle Oscar Pearl Rose Roy Samuel Sarah Tom Will
## 190 0 0 0 0 0 0 0 0 0 0 0 6 0
## 191 0 0 0 0 0 0 0 0 0 0 2 0 0
## 192 0 0 0 0 0 0 0 0 0 0 0 0 0
## 193 0 0 0 0 0 0 0 0 0 0 0 0 0
## 194 0 0 0 0 0 0 0 0 0 0 0 0 0
## 195 0 0 0 0 0 0 0 0 0 0 2 0 0
## William
## 190 0
## 191 0
## 192 0
## 193 0
## 194 0
## 195 0nrow(datos) # Número de filas (sitios)## [1] 195ncol(datos) # Número de columnas (especies)## [1] 70dim(datos) # Dimensiones de la base de datos (filas y columnas)## [1] 195 70colnames(datos) # Nombres de las columnas (especies)## [1] "Zona" "Plot" "Ada" "Albert" "Alice" "Anna"
## [7] "Annie" "Arthur" "Bert" "Bertha" "Charlie" "Clara"
## [13] "Clarence" "Cora" "Daisy" "Daniel" "David" "Edith"
## [19] "Elizabeth" "Elmer" "Emma" "Ernest" "Ethel" "Eva"
## [25] "Fannie" "Florence" "Frances" "Francis" "Frank" "Frederick"
## [31] "Gertrude" "Hattie" "Henry" "Herbert" "Howard" "Ida"
## [37] "Jacob" "James" "Jennie" "Jesse" "Jim" "Joe"
## [43] "Josephine" "Julia" "Lee" "Lena" "Lewis" "Lillian"
## [49] "Lillie" "Louise" "Lucy" "Lula" "Mabel" "Maggie"
## [55] "Margaret" "Martha" "Martin" "Mary" "Mattie" "Maude"
## [61] "Myrtle" "Oscar" "Pearl" "Rose" "Roy" "Samuel"
## [67] "Sarah" "Tom" "Will" "William"rownames(datos) # Nombres de las filas (SITIOS)## [1] "1" "2" "3" "4" "5" "6" "7" "8" "9" "10" "11" "12"
## [13] "13" "14" "15" "16" "17" "18" "19" "20" "21" "22" "23" "24"
## [25] "25" "26" "27" "28" "29" "30" "31" "32" "33" "34" "35" "36"
## [37] "37" "38" "39" "40" "41" "42" "43" "44" "45" "46" "47" "48"
## [49] "49" "50" "51" "52" "53" "54" "55" "56" "57" "58" "59" "60"
## [61] "61" "62" "63" "64" "65" "66" "67" "68" "69" "70" "71" "72"
## [73] "73" "74" "75" "76" "77" "78" "79" "80" "81" "82" "83" "84"
## [85] "85" "86" "87" "88" "89" "90" "91" "92" "93" "94" "95" "96"
## [97] "97" "98" "99" "100" "101" "102" "103" "104" "105" "106" "107" "108"
## [109] "109" "110" "111" "112" "113" "114" "115" "116" "117" "118" "119" "120"
## [121] "121" "122" "123" "124" "125" "126" "127" "128" "129" "130" "131" "132"
## [133] "133" "134" "135" "136" "137" "138" "139" "140" "141" "142" "143" "144"
## [145] "145" "146" "147" "148" "149" "150" "151" "152" "153" "154" "155" "156"
## [157] "157" "158" "159" "160" "161" "162" "163" "164" "165" "166" "167" "168"
## [169] "169" "170" "171" "172" "173" "174" "175" "176" "177" "178" "179" "180"
## [181] "181" "182" "183" "184" "185" "186" "187" "188" "189" "190" "191" "192"
## [193] "193" "194" "195"Separación de datos de aves y sitios
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aves <- datos [,- c(1,2)]
head(aves)## Ada Albert Alice Anna Annie Arthur Bert Bertha Charlie Clara Clarence Cora
## 1 4 0 0 0 0 0 0 0 0 0 0 0
## 2 0 0 0 4 0 0 0 0 0 0 0 0
## 3 0 0 0 1 0 0 0 0 0 0 0 0
## 4 0 0 0 0 0 0 0 4 0 0 0 0
## 5 5 0 0 5 0 0 0 3 0 2 0 0
## 6 0 0 0 0 0 0 0 5 0 2 5 0
## Daisy Daniel David Edith Elizabeth Elmer Emma Ernest Ethel Eva Fannie
## 1 0 0 0 0 0 0 0 0 0 0 0
## 2 2 0 0 0 0 0 0 0 0 0 0
## 3 0 0 0 0 0 0 0 0 0 0 0
## 4 0 0 0 0 0 0 0 0 0 0 0
## 5 0 0 0 0 0 0 0 0 0 0 0
## 6 0 0 0 0 0 0 0 0 0 0 0
## Florence Frances Francis Frank Frederick Gertrude Hattie Henry Herbert Howard
## 1 0 0 0 0 0 0 0 0 0 0
## 2 0 0 0 0 0 0 0 0 0 0
## 3 0 0 0 0 0 0 0 0 0 0
## 4 0 0 0 0 0 0 0 0 0 0
## 5 0 0 0 0 0 0 0 0 0 0
## 6 11 0 0 0 0 0 0 3 12 5
## Ida Jacob James Jennie Jesse Jim Joe Josephine Julia Lee Lena Lewis Lillian
## 1 0 0 0 0 0 0 0 0 0 0 0 0 0
## 2 0 0 0 0 0 0 0 0 0 0 0 0 0
## 3 0 0 0 0 0 0 0 0 0 0 0 0 0
## 4 0 0 0 0 0 0 0 0 0 0 0 0 0
## 5 0 0 0 0 0 0 0 0 0 0 0 0 0
## 6 0 0 0 0 0 0 0 0 0 0 0 0 0
## Lillie Louise Lucy Lula Mabel Maggie Margaret Martha Martin Mary Mattie Maude
## 1 0 0 0 0 0 0 0 0 0 0 0 0
## 2 0 0 0 0 0 0 0 0 0 0 0 0
## 3 0 0 0 0 0 0 0 0 0 0 0 0
## 4 0 0 0 0 0 0 0 0 0 0 0 0
## 5 0 0 0 0 0 0 0 0 0 0 0 0
## 6 0 0 0 0 0 0 0 0 0 0 0 0
## Myrtle Oscar Pearl Rose Roy Samuel Sarah Tom Will William
## 1 0 0 0 0 0 0 0 0 0 0
## 2 0 0 0 0 0 0 0 0 0 0
## 3 0 0 0 0 0 0 0 0 0 0
## 4 0 0 0 0 0 0 0 0 0 0
## 5 0 0 0 0 0 0 0 0 0 0
## 6 0 0 0 0 0 0 0 0 0 0sitios <- datos [, c(1,2)]
head(sitios)## Zona Plot
## 1 Forest_A P1
## 2 Forest_A P1
## 3 Forest_A P1
## 4 Forest_A P1
## 5 Forest_A P1
## 6 Forest_A P1Exploración de especies de aves
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range(aves) # valores mínimos y máximos de abundacia## [1] 0 30apply(aves,2, range) # valores mínimos y máximos para cada especie## Ada Albert Alice Anna Annie Arthur Bert Bertha Charlie Clara Clarence Cora
## [1,] 0 0 0 0 0 0 0 0 0 0 0 0
## [2,] 6 8 10 8 12 7 5 5 6 2 12 4
## Daisy Daniel David Edith Elizabeth Elmer Emma Ernest Ethel Eva Fannie
## [1,] 0 0 0 0 0 0 0 0 0 0 0
## [2,] 3 17 15 16 15 30 2 20 9 2 24
## Florence Frances Francis Frank Frederick Gertrude Hattie Henry Herbert
## [1,] 0 0 0 0 0 0 0 0 0
## [2,] 21 7 23 12 7 23 18 5 18
## Howard Ida Jacob James Jennie Jesse Jim Joe Josephine Julia Lee Lena Lewis
## [1,] 0 0 0 0 0 0 0 0 0 0 0 0 0
## [2,] 5 10 10 5 25 21 5 8 25 5 11 7 19
## Lillian Lillie Louise Lucy Lula Mabel Maggie Margaret Martha Martin Mary
## [1,] 0 0 0 0 0 0 0 0 0 0 0
## [2,] 12 4 2 22 17 4 23 7 24 8 3
## Mattie Maude Myrtle Oscar Pearl Rose Roy Samuel Sarah Tom Will William
## [1,] 0 0 0 0 0 0 0 0 0 0 0 0
## [2,] 2 5 11 24 15 21 13 5 16 21 5 17sum(aves == 0) # Número de ausencias## [1] 12921sum(aves == 0) / (nrow(aves) * ncol(aves)) # Proporción de ceros en la base de datos## [1] 0.9744344Distribución de abundancia durante el estudio
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abundancia <- table(unlist(aves)) # cuenta los casos para cada clase de abundancia
barplot(abundancia, las=1, xlab = "Clase de abundancia",
ylab = "Frecuencia",col = gray(5 : 0 / 5))
Coordenadas geográficas de los sitios
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coor <- read.delim("D:/Downloads/UNA/II Ciclo 2021/Tecnicas de Muestreo/R/Ejrecicio_RiquezaEspecies/coordenadas.txt")
coor## X Y
## 1 679073 1125709
## 2 679063 1125699
## 3 679053 1125689
## 4 679043 1125679
## 5 679033 1125669
## 6 679023 1125659
## 7 679013 1125649
## 8 679003 1125639
## 9 678993 1125629
## 10 678983 1125619
## 11 678973 1125609
## 12 678963 1125599
## 13 678953 1125589
## 14 678943 1125579
## 15 678933 1125569
## 16 678923 1125559
## 17 678913 1125549
## 18 678903 1125539
## 19 678893 1125529
## 20 678883 1125519
## 21 678873 1125509
## 22 678863 1125499
## 23 678853 1125489
## 24 678843 1125479
## 25 678833 1125469
## 26 678823 1125459
## 27 678813 1125449
## 28 678803 1125439
## 29 678793 1125429
## 30 678783 1125419
## 31 678773 1125409
## 32 678763 1125399
## 33 678753 1125389
## 34 678743 1125379
## 35 678733 1125369
## 36 678723 1125359
## 37 678713 1125349
## 38 678703 1125339
## 39 678693 1125329
## 40 678683 1125319
## 41 678673 1125309
## 42 678663 1125299
## 43 678653 1125289
## 44 678643 1125279
## 45 678633 1125269
## 46 678623 1125259
## 47 678613 1125249
## 48 678603 1125239
## 49 678593 1125229
## 50 678583 1125219
## 51 678573 1125209
## 52 678563 1125199
## 53 678553 1125189
## 54 678543 1125179
## 55 678533 1125169
## 56 678523 1125159
## 57 678513 1125149
## 58 678503 1125139
## 59 678493 1125129
## 60 678483 1125119
## 61 678473 1125109
## 62 678463 1125099
## 63 678453 1125089
## 64 678443 1125079
## 65 678433 1125069
## 66 678423 1125059
## 67 678413 1125049
## 68 678403 1125039
## 69 678393 1125029
## 70 678383 1125019
## 71 678373 1125009
## 72 678363 1124999
## 73 678353 1124989
## 74 678343 1124979
## 75 678333 1124969
## 76 678323 1124959
## 77 678313 1124949
## 78 678303 1124939
## 79 678293 1124929
## 80 678283 1124919
## 81 678273 1124909
## 82 678263 1124899
## 83 678253 1124889
## 84 678243 1124879
## 85 678233 1124869
## 86 678223 1124859
## 87 678213 1124849
## 88 678203 1124839
## 89 678193 1124829
## 90 678183 1124819
## 91 678173 1124809
## 92 678163 1124799
## 93 678153 1124789
## 94 678143 1124779
## 95 678133 1124769
## 96 678123 1124759
## 97 678113 1124749
## 98 678103 1124739
## 99 678093 1124729
## 100 678083 1124719
## 101 678073 1124709
## 102 678063 1124699
## 103 678053 1124689
## 104 678043 1124679
## 105 678033 1124669
## 106 678023 1124659
## 107 678013 1124649
## 108 678003 1124639
## 109 677993 1124629
## 110 677983 1124619
## 111 677973 1124609
## 112 677963 1124599
## 113 677953 1124589
## 114 677943 1124579
## 115 677933 1124569
## 116 677923 1124559
## 117 677913 1124549
## 118 677903 1124539
## 119 677893 1124529
## 120 677883 1124519
## 121 677873 1124509
## 122 677863 1124499
## 123 677853 1124489
## 124 677843 1124479
## 125 677833 1124469
## 126 677823 1124459
## 127 677813 1124449
## 128 677803 1124439
## 129 677793 1124429
## 130 677783 1124419
## 131 677773 1124409
## 132 677763 1124399
## 133 677753 1124389
## 134 677743 1124379
## 135 677733 1124369
## 136 677723 1124359
## 137 677713 1124349
## 138 677703 1124339
## 139 677693 1124329
## 140 677683 1124319
## 141 677673 1124309
## 142 677663 1124299
## 143 677653 1124289
## 144 677643 1124279
## 145 677633 1124269
## 146 677623 1124259
## 147 677613 1124249
## 148 677603 1124239
## 149 677593 1124229
## 150 677583 1124219
## 151 677573 1124209
## 152 677563 1124199
## 153 677553 1124189
## 154 677543 1124179
## 155 677533 1124169
## 156 677523 1124159
## 157 677513 1124149
## 158 677503 1124139
## 159 677493 1124129
## 160 677483 1124119
## 161 677473 1124109
## 162 677463 1124099
## 163 677453 1124089
## 164 677443 1124079
## 165 677433 1124069
## 166 677423 1124059
## 167 677413 1124049
## 168 677403 1124039
## 169 677393 1124029
## 170 677383 1124019
## 171 677373 1124009
## 172 677363 1123999
## 173 677353 1123989
## 174 677343 1123979
## 175 677333 1123969
## 176 677323 1123959
## 177 677313 1123949
## 178 677303 1123939
## 179 677293 1123929
## 180 677283 1123919
## 181 677273 1123909
## 182 677263 1123899
## 183 677253 1123889
## 184 677243 1123879
## 185 677233 1123869
## 186 677223 1123859
## 187 677213 1123849
## 188 677203 1123839
## 189 677193 1123829
## 190 677183 1123819
## 191 677173 1123809
## 192 677163 1123799
## 193 677153 1123789
## 194 677143 1123779
## 195 677133 1123769dev.new() # abre una nueva ventana para visualización
par(mfrow = c(2,2)) # mapa de coordenadas para cuatro especies
plot(coor,
asp = 1,
cex.axis= 0.8,
col= "red",
cex= aves$Ada,
main = "Ada",
xlab = "x coordinate (km)", ylab = "y coordinate (km)")
plot(coor,
asp = 1,
cex.axis= 0.8,
col= "red",
cex= aves$Anna,
main = "Anna",
xlab = "x coordinate (km)", ylab = "y coordinate (km)")
plot(coor,
asp = 1,
cex.axis= 0.8,
col= "red",
cex= aves$Cora,
main = "Cora",
xlab = "x coordinate (km)", ylab = "y coordinate (km)")
plot(coor,
asp = 1,
cex.axis= 0.8,
col= "red",
cex= aves$Joe,
main = "Joe",
xlab = "x coordinate (km)", ylab = "y coordinate (km)")
Se sugiere que Cora y Ada corresponden a especies especialistas, ya que presentan una distribución espacial más restringida que las especies Joe y Ana. La distribución espacial de estas dos últimas presentan un rango más amplio con respecto a las coordenadas.
Cálculo del número de sitios de incidencia de cada especie
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aves.presencia <- apply(aves > 0, 2, sum)
sort(aves.presencia) # Ordena los resultados en orden creciente## Daniel Emma Eva Frances Frederick Gertrude Howard James
## 1 1 1 1 1 1 1 1
## Jesse Jim Lillian David Elmer Fannie Herbert Lena
## 1 1 1 2 2 2 2 2
## Louise Martin Mary Samuel William Elizabeth Ethel Frank
## 2 2 2 2 2 3 3 3
## Maggie Mattie Myrtle Will Albert Arthur Clara Cora
## 3 3 3 3 4 4 4 4
## Daisy Ernest Jennie Julia Oscar Florence Lewis Tom
## 4 4 4 4 4 5 5 5
## Francis Hattie Henry Ida Jacob Mabel Margaret Martha
## 6 6 6 6 6 6 6 6
## Rose Roy Ada Lee Lillie Lula Maude Sarah
## 6 6 7 7 7 7 7 7
## Charlie Joe Pearl Annie Bert Edith Lucy Anna
## 8 8 8 9 9 9 10 11
## Josephine Alice Bertha Clarence
## 11 12 13 26aves.frecuencia <- 100 * aves.presencia/nrow(aves) # Calcula el porcentaje de frecuencias
round(sort(aves.frecuencia), 1) # Redondea el resultado ordenado a 1 dígito## Daniel Emma Eva Frances Frederick Gertrude Howard James
## 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5
## Jesse Jim Lillian David Elmer Fannie Herbert Lena
## 0.5 0.5 0.5 1.0 1.0 1.0 1.0 1.0
## Louise Martin Mary Samuel William Elizabeth Ethel Frank
## 1.0 1.0 1.0 1.0 1.0 1.5 1.5 1.5
## Maggie Mattie Myrtle Will Albert Arthur Clara Cora
## 1.5 1.5 1.5 1.5 2.1 2.1 2.1 2.1
## Daisy Ernest Jennie Julia Oscar Florence Lewis Tom
## 2.1 2.1 2.1 2.1 2.1 2.6 2.6 2.6
## Francis Hattie Henry Ida Jacob Mabel Margaret Martha
## 3.1 3.1 3.1 3.1 3.1 3.1 3.1 3.1
## Rose Roy Ada Lee Lillie Lula Maude Sarah
## 3.1 3.1 3.6 3.6 3.6 3.6 3.6 3.6
## Charlie Joe Pearl Annie Bert Edith Lucy Anna
## 4.1 4.1 4.1 4.6 4.6 4.6 5.1 5.6
## Josephine Alice Bertha Clarence
## 5.6 6.2 6.7 13.3Histogramas
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dev.new()
par(mfrow = c(1,2))
hist(aves.presencia,
main= "Presencias de especies",
right = FALSE, las = 1,
xlab= "Número de presencias",
ylab= "Número de especies",
col= "skyblue"
)
hist(aves.frecuencia,
main = "Frecuencia relativa de especies",
right = FALSE,
las = 1,
xlab = "Frecuencia de presencias (%)",
ylab = "Número de especies",
breaks = seq(0, 100, by = 5),
col = "bisque"
)
En el histograma de la izquierda se observa que en la primera columna se obtuvieron alrededor de 40 especies, sin embargo hay una presencia de baja (0-5) comparada a las demas columnas. Existe una tendencia de los datos donde a mayor número de especies, menor número de presencias. Lo mismo se ve reflejado en las frecuencias relativas.
Cálculos y estimados de riqueza de especies
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library(vegan)## Loading required package: permute## Loading required package: lattice## This is vegan 2.5-7library(tidyverse)## -- Attaching packages --------------------------------------- tidyverse 1.3.1 --## v ggplot2 3.3.5 v purrr 0.3.4
## v tibble 3.1.4 v dplyr 1.0.7
## v tidyr 1.1.3 v stringr 1.4.0
## v readr 2.0.1 v forcats 0.5.1## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()library(BiodiversityR)## Loading required package: tcltk## BiodiversityR 2.13-1: Use command BiodiversityRGUI() to launch the Graphical User Interface;
## to see changes use BiodiversityRGUI(changeLog=TRUE, backward.compatibility.messages=TRUE)## Cálculo de la riqueza de especies durante todo el estudio
specnumber(colSums(aves))## [1] 68## Comparar sitios: riqueza de especies de aves
sit.presencia <- apply(aves >0, 1, sum)
sit.presencia## [1] 1 2 1 1 4 7 2 4 3 1 1 1 1 1 1 1 1 4 11 1 1 1 1 1 1
## [26] 1 1 1 2 1 1 1 1 1 2 1 1 2 2 3 1 5 1 1 1 1 1 1 1 2
## [51] 3 2 3 1 1 1 1 1 1 2 2 2 2 3 2 3 3 4 1 1 1 1 2 2 3
## [76] 4 2 1 1 1 1 1 1 1 1 1 1 3 3 6 2 3 4 2 3 1 1 2 2 2
## [101] 6 2 1 1 1 1 0 0 0 0 1 1 1 1 0 2 2 5 4 2 1 1 1 3 2
## [126] 1 1 1 1 1 2 1 2 2 2 1 2 5 3 1 1 1 1 3 4 4 3 0 0 0
## [151] 0 0 0 0 0 0 1 1 1 3 3 2 5 0 0 2 1 2 2 1 2 3 7 6 7
## [176] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1#-------
dev.new()
par(mfrow = c(1, 2))Riqueza de especies vs la posición de los sitios
■■■
plot(sit.presencia,
type = "s",
las = 1,
col = "gray",
main = "Riqueza de especies",
xlab = "Número de sitios",
ylab = "Riqueza de especies"
)
text(sit.presencia, row.names(aves), cex = .8, col = "red") 
Coordenadas geográficas en mapa de burbujas
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plot(coor,
asp = 1,
main = "Mapa de riqueza de especies",
pch = 21,
col = "white",
bg = "brown",
cex = 5 * sit.presencia / max(sit.presencia),
xlab = "coordenada X (km)",
ylab = "coordenada Y (km)"
)
La mayor riqueza de especies se encuentra en las coordenadas 679000 en x y 1125500 en y, aproximadamente.
Riqueza de especie por zona o parcela (Boxplot)
■■■
par(mfrow = c(1, 1))
boxplot(specnumber(aves)~ sitios$Zona)
En el sitio Rustico A se observa un mayor número de especies, seguido de policultura A. Se espera encontrar valores bajos en el bosque ya que a mayor riqueza menor abundancia.
Curva de acumulación general de especies
■■■
curva1 <-specaccum(aves, method = "exact", ylim(0, 70))
curva1## Species Accumulation Curve
## Accumulation method: exact
## Call: specaccum(comm = aves, method = "exact", permutations = ylim(0, 70))
##
##
## Sites 1.00000 2.00000 3.00000 4.00000 5.00000 6.00000 7.00000 8.00000
## Richness 1.73846 3.41311 5.02761 6.58532 8.08932 9.54244 10.94728 12.30625
## sd 1.51854 2.09110 2.49569 2.81016 3.06567 3.27867 3.45916 3.61379
##
## Sites 9.00000 10.00000 11.00000 12.00000 13.00000 14.00000 15.00000
## Richness 13.62157 14.89531 16.12936 17.32551 18.48542 19.61063 20.70258
## sd 3.74726 3.86305 3.96381 4.05164 4.12822 4.19492 4.25290
##
## Sites 16.00000 17.00000 18.00000 19.00000 20.00000 21.00000 22.00000
## Richness 21.76264 22.79208 23.79209 24.76380 25.70829 26.62656 27.51957
## sd 4.30310 4.34636 4.38338 4.41478 4.44109 4.46279 4.48030
##
## Sites 23.00000 24.00000 25.00000 26.00000 27.00000 28.00000 29.00000
## Richness 28.38823 29.23339 30.05588 30.85647 31.63593 32.39495 33.13422
## sd 4.49399 4.50419 4.51122 4.51533 4.51677 4.51577 4.51252
##
## Sites 30.00000 31.00000 32.00000 33.00000 34.00000 35.00000 36.00000
## Richness 33.85439 34.55608 35.23990 35.90641 36.55618 37.18973 37.80756
## sd 4.50722 4.50002 4.49109 4.48057 4.46858 4.45524 4.44068
##
## Sites 37.00000 38.00000 39.00000 40.00000 41.00000 42.00000 43.00000
## Richness 38.41018 38.99805 39.57163 40.13136 40.67765 41.21093 41.73157
## sd 4.42498 4.40824 4.39054 4.37198 4.35261 4.33251 4.31175
##
## Sites 44.00000 45.00000 46.00000 47.00000 48.00000 49.00000 50.00000
## Richness 42.23996 42.73647 43.22145 43.69525 44.15818 44.61057 45.05274
## sd 4.29038 4.26845 4.24603 4.22314 4.19984 4.17617 4.15216
##
## Sites 51.00000 52.00000 53.00000 54.00000 55.00000 56.00000 57.00000
## Richness 45.48497 45.90756 46.32078 46.72490 47.12019 47.50689 47.88526
## sd 4.12786 4.10328 4.07846 4.05344 4.02823 4.00285 3.97734
##
## Sites 58.00000 59.00000 60.00000 61.00000 62.00000 63.00000 64.00000
## Richness 48.25552 48.61791 48.97265 49.31994 49.66001 49.99304 50.31924
## sd 3.95171 3.92598 3.90016 3.87428 3.84834 3.82237 3.79637
##
## Sites 65.00000 66.00000 67.00000 68.00000 69.00000 70.00000 71.00000
## Richness 50.63879 50.95187 51.25867 51.55934 51.85407 52.14300 52.42630
## sd 3.77035 3.74434 3.71832 3.69233 3.66635 3.64041 3.61451
##
## Sites 72.00000 73.00000 74.00000 75.00000 76.00000 77.00000 78.00000
## Richness 52.70411 52.97659 53.24387 53.50609 53.76338 54.01587 54.26369
## sd 3.58864 3.56283 3.53707 3.51137 3.48573 3.46016 3.43466
##
## Sites 79.00000 80.00000 81.00000 82.00000 83.00000 84.00000 85.00000
## Richness 54.50697 54.74580 54.98032 55.21064 55.43685 55.65906 55.87737
## sd 3.40923 3.38387 3.35859 3.33338 3.30826 3.28322 3.25825
##
## Sites 86.00000 87.00000 88.00000 89.00000 90.00000 91.00000 92.00000
## Richness 56.09189 56.30271 56.50991 56.71360 56.91385 57.11075 57.30438
## sd 3.23337 3.20857 3.18386 3.15922 3.13467 3.11020 3.08581
##
## Sites 93.00000 94.00000 95.00000 96.00000 97.00000 98.00000 99.00000
## Richness 57.49482 57.68215 57.86644 58.04777 58.22621 58.40182 58.57467
## sd 3.06150 3.03727 3.01312 2.98905 2.96505 2.94112 2.91727
##
## Sites 100.00000 101.00000 102.00000 103.00000 104.00000 105.00000 106.00000
## Richness 58.74482 58.91235 59.07730 59.23974 59.39973 59.55732 59.71256
## sd 2.89350 2.86979 2.84615 2.82258 2.79907 2.77563 2.75225
##
## Sites 107.00000 108.00000 109.00000 110.00000 111.00000 112.00000 113.00000
## Richness 59.86552 60.01623 60.16475 60.31114 60.45542 60.59766 60.73789
## sd 2.72892 2.70566 2.68244 2.65929 2.63618 2.61312 2.59010
##
## Sites 114.00000 115.00000 116.00000 117.00000 118.00000 119.00000 120.00000
## Richness 60.87616 61.01251 61.14698 61.27961 61.41044 61.53951 61.66685
## sd 2.56713 2.54420 2.52131 2.49846 2.47563 2.45284 2.43008
##
## Sites 121.00000 122.00000 123.00000 124.00000 125.00000 126.00000 127.00000
## Richness 61.79250 61.91650 62.03886 62.15964 62.27886 62.39656 62.51275
## sd 2.40734 2.38463 2.36193 2.33926 2.31659 2.29394 2.27130
##
## Sites 128.00000 129.00000 130.00000 131.00000 132.00000 133.00000 134.00000
## Richness 62.62748 62.74077 62.85264 62.96313 63.07227 63.18006 63.28656
## sd 2.24866 2.22602 2.20338 2.18074 2.15808 2.13542 2.11274
##
## Sites 135.00000 136.00000 137.00000 138.00000 139.00000 140.00000 141.00000
## Richness 63.39176 63.49571 63.59842 63.69992 63.80022 63.89935 63.99734
## sd 2.09004 2.06732 2.04457 2.02179 1.99897 1.97612 1.95322
##
## Sites 142.00000 143.00000 144.00000 145.00000 146.00000 147.00000 148.00000
## Richness 64.09419 64.18993 64.28458 64.37816 64.47069 64.56218 64.65265
## sd 1.93027 1.90727 1.88422 1.86109 1.83790 1.81464 1.79129
##
## Sites 149.00000 150.00000 151.00000 152.00000 153.00000 154.00000 155.00000
## Richness 64.74212 64.83060 64.91812 65.00468 65.09031 65.17501 65.25881
## sd 1.76786 1.74434 1.72071 1.69698 1.67314 1.64917 1.62508
##
## Sites 156.00000 157.00000 158.00000 159.00000 160.00000 161.00000 162.00000
## Richness 65.34171 65.42374 65.50490 65.58520 65.66467 65.74331 65.82114
## sd 1.60084 1.57646 1.55192 1.52721 1.50232 1.47724 1.45195
##
## Sites 163.00000 164.00000 165.00000 166.00000 167.00000 168.00000 169.00000
## Richness 65.89816 65.97440 66.04986 66.12455 66.19848 66.27167 66.34413
## sd 1.42645 1.40072 1.37473 1.34848 1.32195 1.29511 1.26795
##
## Sites 170.00000 171.00000 172.00000 173.00000 174.00000 175.00000 176.00000
## Richness 66.41586 66.48688 66.55720 66.62682 66.69575 66.76401 66.83161
## sd 1.24043 1.21254 1.18424 1.15550 1.12629 1.09656 1.06627
##
## Sites 177.00000 178.00000 179.00000 180.00000 181.0000 182.00000 183.00000
## Richness 66.89855 66.96484 67.03049 67.09550 67.1599 67.22367 67.28684
## sd 1.03537 1.00379 0.97148 0.93834 0.9043 0.86924 0.83304
##
## Sites 184.00000 185.00000 186.00000 187.00000 188.00000 189.00000 190.00000
## Richness 67.34941 67.41138 67.47277 67.53358 67.59382 67.65349 67.71260
## sd 0.79553 0.75652 0.71578 0.67298 0.62771 0.57940 0.52723
##
## Sites 191.00000 192.00000 193.00000 194.00000 195
## Richness 67.77116 67.82918 67.88665 67.94359 68
## sd 0.46993 0.40538 0.32931 0.23071 0plot(curva1)
plot(curva1,
xlab = "unidades muestreo",
ylab = "Número de especies",
col = "blue")
points(curva1$richness,
pch= 19,
col= "red")
La acumulación de especies en este caso está llegando a la asíntota, porque la curva cada vez es más plana. Por lo tanto, ya no se esperan ver más especies en los sitios de muestreo.
Curvas de acumulación de especies por sitio
■■■
curva2 <- accumcomp(aves,
y= sitios,
factor = "Zona",
method = "exact",
legend = F,
conditioned = T,
xlim = c(0, 23),
rainbow = T,
xlab = "Plots",
ylab = "riqueza de aves",
main= "Curva de acumulacion de especies por zona"
)
library(ggplot2)
curva2 <- accumcomp(aves,
y =sitios,
factor = "Zona",
method = "exact",
conditioned = F,
plotit = F)
curva2## , , = Sites
##
## obs
## Zona 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
## Forest_A 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
## Forest_B 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 NA
## Intensive_B 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
## Polyculture_A 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
## Polyculture_B 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 NA NA NA NA NA NA
## Rustic_A 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
## Rustic_B 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
## obs
## Zona 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39
## Forest_A 25 26 27 28 29 30 31 32 33 34 NA NA NA NA NA
## Forest_B NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
## Intensive_B 25 26 NA NA NA NA NA NA NA NA NA NA NA NA NA
## Polyculture_A 25 26 27 NA NA NA NA NA NA NA NA NA NA NA NA
## Polyculture_B NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
## Rustic_A 25 26 27 28 NA NA NA NA NA NA NA NA NA NA NA
## Rustic_B 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39
##
## , , = Richness
##
## obs
## Zona 1 2 3 4 5 6 7
## Forest_A 1.882353 3.659537 5.338570 6.926147 8.428648 9.852143 11.202400
## Forest_B 1.652174 3.205534 4.669113 6.051270 7.359714 8.601533 9.783233
## Intensive_B 1.846154 3.578462 5.204231 6.730502 8.164047 9.511371 10.778712
## Polyculture_A 1.851852 3.584046 5.205470 6.724558 8.149300 9.487254 10.745559
## Polyculture_B 1.666667 3.189542 4.587010 5.875490 7.069561 8.182073 9.224265
## Rustic_A 1.428571 2.806878 4.137668 5.423590 6.667196 7.870940 9.037179
## Rustic_B 1.769231 3.468286 5.100449 6.668892 8.176680 9.626775 11.022030
## obs
## Zona 8 9 10 11 12 13 14
## Forest_A 12.48489 13.70480 14.86704 15.97624 17.03676 18.05272 19.02797
## Forest_B 10.91076 11.98952 13.02443 14.01994 14.98006 15.90838 16.80811
## Intensive_B 11.97204 13.09706 14.15920 15.16363 16.11525 17.01870 17.87833
## Polyculture_A 11.93095 13.04977 14.10796 15.11114 16.06451 16.97298 17.84110
## Polyculture_B 10.20588 11.13529 12.01961 12.86479 13.67577 14.45658 15.21046
## Rustic_A 10.16817 11.26608 12.33297 13.37080 14.38144 15.36667 16.32815
## Rustic_B 12.36520 13.65893 14.90579 16.10822 17.26858 18.38915 19.47209
## obs
## Zona 15 16 17 18 19 20 21
## Forest_A 19.96611 20.87054 21.74438 22.59056 23.41180 24.21058 24.98920
## Forest_B 17.68213 18.53297 19.36289 20.17388 20.96770 21.74591 22.50988
## Intensive_B 18.69824 19.48227 20.23398 20.95666 21.65333 22.32676 22.97943
## Polyculture_A 18.67310 19.47291 20.24417 20.99023 21.71418 22.41883 23.10676
## Polyculture_B 15.93995 16.64706 17.33333 18.00000 NA NA NA
## Rustic_A 17.26746 18.18608 19.08539 19.96667 20.83110 21.67977 22.51368
## Rustic_B 20.51950 21.53336 22.51558 23.46799 24.39234 25.29027 26.16337
## obs
## Zona 22 23 24 25 26 27 28
## Forest_A 25.74976 26.49419 27.22421 27.94139 28.64713 29.34267 30.02909
## Forest_B 23.26087 24.00000 NA NA NA NA NA
## Intensive_B 23.61358 24.23115 24.83385 25.42308 26.00000 NA NA
## Polyculture_A 23.78033 24.44165 25.09265 25.73504 26.37037 27.00000 NA
## Polyculture_B NA NA NA NA NA NA NA
## Rustic_A 23.33370 24.14064 24.93519 25.71795 26.48942 27.25000 28.00000
## Rustic_B 27.01313 27.84099 28.64828 29.43630 30.20624 30.95923 31.69636
## obs
## Zona 29 30 31 32 33 34 35
## Forest_A 30.70734 31.37823 32.04245 32.70053 33.35294 34.00000 NA
## Forest_B NA NA NA NA NA NA NA
## Intensive_B NA NA NA NA NA NA NA
## Polyculture_A NA NA NA NA NA NA NA
## Polyculture_B NA NA NA NA NA NA NA
## Rustic_A NA NA NA NA NA NA NA
## Rustic_B 32.41861 33.12693 33.82219 34.50521 35.17674 35.83748 36.48808
## obs
## Zona 36 37 38 39
## Forest_A NA NA NA NA
## Forest_B NA NA NA NA
## Intensive_B NA NA NA NA
## Polyculture_A NA NA NA NA
## Polyculture_B NA NA NA NA
## Rustic_A NA NA NA NA
## Rustic_B 37.12912 37.76113 38.38462 39
##
## , , = sd
##
## obs
## Zona 1 2 3 4 5 6
## Forest_A 0.2722319 0.5146927 0.7299377 0.9203862 1.0883268 1.2359219
## Forest_B 0.2776575 0.5142921 0.7156377 0.8868721 1.0326457 1.1571128
## Intensive_B 0.2724841 0.5122828 0.7223129 0.9053741 1.0641489 1.2012019
## Polyculture_A 0.2858998 0.5352865 0.7519037 0.9392401 1.1005441 1.2388367
## Polyculture_B 0.3256191 0.5852221 0.7912828 0.9546455 1.0846258 1.1891145
## Rustic_A 0.2074738 0.3950761 0.5645831 0.7177007 0.8560621 0.9812259
## Rustic_B 0.2224829 0.4263271 0.6128211 0.7831967 0.9386310 1.0802479
## obs
## Zona 7 8 9 10 11 12 13
## Forest_A 1.365213 1.478123 1.576463 1.661934 1.736132 1.800548 1.856576
## Forest_B 1.263962 1.356449 1.437426 1.509377 1.574451 1.634492 1.691069
## Intensive_B 1.318979 1.419807 1.505889 1.579306 1.642013 1.695834 1.742462
## Polyculture_A 1.356925 1.457416 1.542726 1.615092 1.676584 1.729111 1.774428
## Polyculture_B 1.274690 1.346739 1.409590 1.466653 1.520566 1.573339 1.626489
## Rustic_A 1.094673 1.197805 1.291940 1.378312 1.458067 1.532263 1.601870
## Rustic_B 1.209119 1.326267 1.432664 1.529236 1.616862 1.696379 1.768576
## obs
## Zona 14 15 16 17 18 19 20
## Forest_A 1.905509 1.948545 1.986788 2.021249 2.052850 2.082420 2.110703
## Forest_B 1.745512 1.798936 1.852269 1.906281 1.961601 2.018742 2.078121
## Intensive_B 1.783456 1.820238 1.854092 1.886163 1.917461 1.948862 1.981113
## Polyculture_A 1.814141 1.849715 1.882474 1.913600 1.944143 1.975017 2.007002
## Polyculture_B 1.681164 1.738250 1.798456 1.862381 1.930566 NA NA
## Rustic_A 1.667769 1.730752 1.791529 1.850727 1.908896 1.966517 2.024005
## Rustic_B 1.834204 1.893971 1.948544 1.998553 2.044588 2.087203 2.126916
## obs
## Zona 21 22 23 24 25 26 27
## Forest_A 2.138358 2.165962 2.194011 2.222928 2.253066 2.284712 2.318095
## Forest_B 2.140074 2.204872 2.272740 NA NA NA NA
## Intensive_B 2.014843 2.050570 2.088713 2.129604 2.173505 2.220619 NA
## Polyculture_A 2.040753 2.076799 2.115554 2.157326 2.202328 2.250686 2.302459
## Polyculture_B NA NA NA NA NA NA NA
## Rustic_A 2.081717 2.139961 2.199000 2.259063 2.320348 2.383033 2.447277
## Rustic_B 2.164209 2.199530 2.233293 2.265882 2.297648 2.328912 2.359967
## obs
## Zona 28 29 30 31 32 33 34
## Forest_A 2.353392 2.390733 2.430209 2.471879 2.515774 2.561906 2.610271
## Forest_B NA NA NA NA NA NA NA
## Intensive_B NA NA NA NA NA NA NA
## Polyculture_A NA NA NA NA NA NA NA
## Polyculture_B NA NA NA NA NA NA NA
## Rustic_A 2.513227 NA NA NA NA NA NA
## Rustic_B 2.391078 2.422485 2.454401 2.487019 2.520508 2.555020 2.590686
## obs
## Zona 35 36 37 38 39
## Forest_A NA NA NA NA NA
## Forest_B NA NA NA NA NA
## Intensive_B NA NA NA NA NA
## Polyculture_A NA NA NA NA NA
## Polyculture_B NA NA NA NA NA
## Rustic_A NA NA NA NA NA
## Rustic_B 2.627622 2.665932 2.705702 2.747012 2.78993curva3 <- accumcomp.long(curva2,
ci= NA,
label.freq = 19)
curva3## Grouping Obs Sites Richness SD LWR UPR labelit
## 1 Rustic_B 1 1 1.769231 0.2224829 1.317091 2.221371 TRUE
## 2 Rustic_B 2 2 3.468286 0.4263271 2.601885 4.334687 FALSE
## 3 Rustic_B 3 3 5.100449 0.6128211 3.855046 6.345851 FALSE
## 4 Rustic_B 4 4 6.668892 0.7831967 5.077244 8.260539 FALSE
## 5 Rustic_B 5 5 8.176680 0.9386310 6.269153 10.084208 FALSE
## 6 Rustic_B 6 6 9.626775 1.0802479 7.431447 11.822103 FALSE
## 7 Rustic_B 7 7 11.022030 1.2091192 8.564804 13.479256 FALSE
## 8 Rustic_B 8 8 12.365199 1.3262668 9.669901 15.060498 FALSE
## 9 Rustic_B 9 9 13.658934 1.4326637 10.747411 16.570457 FALSE
## 10 Rustic_B 10 10 14.905788 1.5292356 11.798008 18.013569 FALSE
## 11 Rustic_B 11 11 16.108218 1.6168623 12.822358 19.394077 FALSE
## 12 Rustic_B 12 12 17.268582 1.6963786 13.821126 20.716038 FALSE
## 13 Rustic_B 13 13 18.389149 1.7685762 14.794969 21.983328 FALSE
## 14 Rustic_B 14 14 19.472092 1.8342043 15.744540 23.199643 FALSE
## 15 Rustic_B 15 15 20.519495 1.8939709 16.670483 24.368507 FALSE
## 16 Rustic_B 16 16 21.533355 1.9485442 17.573437 25.493273 FALSE
## 17 Rustic_B 17 17 22.515580 1.9985529 18.454032 26.577129 FALSE
## 18 Rustic_B 18 18 23.467994 2.0445880 19.312892 27.623097 FALSE
## 19 Rustic_B 19 19 24.392337 2.0872032 20.150630 28.634045 FALSE
## 20 Rustic_B 20 20 25.290268 2.1269160 20.967855 29.612682 TRUE
## 21 Rustic_B 21 21 26.163366 2.1642087 21.765164 30.561567 FALSE
## 22 Rustic_B 22 22 27.013131 2.1995296 22.543149 31.483112 FALSE
## 23 Rustic_B 23 23 27.840987 2.2332932 23.302389 32.379585 FALSE
## 24 Rustic_B 24 24 28.648284 2.2658823 24.043457 33.253111 FALSE
## 25 Rustic_B 25 25 29.436299 2.2976481 24.766916 34.105681 FALSE
## 26 Rustic_B 26 26 30.206236 2.3289122 25.473317 34.939155 FALSE
## 27 Rustic_B 27 27 30.959233 2.3599672 26.163202 35.755263 FALSE
## 28 Rustic_B 28 28 31.696356 2.3910783 26.837100 36.555612 FALSE
## 29 Rustic_B 29 29 32.418609 2.4224847 27.495528 37.341690 FALSE
## 30 Rustic_B 30 30 33.126929 2.4544010 28.138986 38.114871 FALSE
## 31 Rustic_B 31 31 33.822191 2.4870187 28.767961 38.876421 FALSE
## 32 Rustic_B 32 32 34.505210 2.5205081 29.382921 39.627498 FALSE
## 33 Rustic_B 33 33 35.176741 2.5550195 29.984317 40.369166 FALSE
## 34 Rustic_B 34 34 35.837484 2.5906856 30.572577 41.102390 FALSE
## 35 Rustic_B 35 35 36.488079 2.6276224 31.148108 41.828050 FALSE
## 36 Rustic_B 36 36 37.129117 2.6659316 31.711292 42.546942 FALSE
## 37 Rustic_B 37 37 37.761134 2.7057021 32.262485 43.259782 FALSE
## 38 Rustic_B 38 38 38.384615 2.7470120 32.802015 43.967215 FALSE
## 39 Rustic_B 39 39 39.000000 2.7899297 33.330181 44.669819 TRUE
## 40 Rustic_A 1 1 1.428571 0.2074738 1.006934 1.850209 TRUE
## 41 Rustic_A 2 2 2.806878 0.3950761 2.003987 3.609770 FALSE
## 42 Rustic_A 3 3 4.137668 0.5645831 2.990297 5.285039 FALSE
## 43 Rustic_A 4 4 5.423590 0.7177007 3.965047 6.882133 FALSE
## 44 Rustic_A 5 5 6.667196 0.8560621 4.927468 8.406923 FALSE
## 45 Rustic_A 6 6 7.870940 0.9812259 5.876849 9.865031 FALSE
## 46 Rustic_A 7 7 9.037179 1.0946733 6.812536 11.261823 FALSE
## 47 Rustic_A 8 8 10.168173 1.1978053 7.733939 12.602406 FALSE
## 48 Rustic_A 9 9 11.266081 1.2919404 8.640542 13.891619 FALSE
## 49 Rustic_A 10 10 12.332967 1.3783121 9.531900 15.134034 FALSE
## 50 Rustic_A 11 11 13.370798 1.4580669 10.407649 16.333946 FALSE
## 51 Rustic_A 12 12 14.381441 1.5322632 11.267507 17.495374 FALSE
## 52 Rustic_A 13 13 15.366667 1.6018702 12.111275 18.622059 FALSE
## 53 Rustic_A 14 14 16.328148 1.6677688 12.938834 19.717462 FALSE
## 54 Rustic_A 15 15 17.267460 1.7307522 13.750149 20.784772 FALSE
## 55 Rustic_A 16 16 18.186081 1.7915291 14.545255 21.826906 FALSE
## 56 Rustic_A 17 17 19.085389 1.8507269 15.324259 22.846518 FALSE
## 57 Rustic_A 18 18 19.966667 1.9088963 16.087323 23.846011 FALSE
## 58 Rustic_A 19 19 20.831099 1.9665173 16.834655 24.827543 FALSE
## 59 Rustic_A 20 20 21.679772 2.0240049 17.566499 25.793045 TRUE
## 60 Rustic_A 21 21 22.513675 2.0817170 18.283117 26.744233 FALSE
## 61 Rustic_A 22 22 23.333700 2.1399605 18.984777 27.682623 FALSE
## 62 Rustic_A 23 23 24.140639 2.1989997 19.671734 28.609544 FALSE
## 63 Rustic_A 24 24 24.935189 2.2590626 20.344222 29.526157 FALSE
## 64 Rustic_A 25 25 25.717949 2.3203484 21.002434 30.433464 FALSE
## 65 Rustic_A 26 26 26.489418 2.3830333 21.646512 31.332324 FALSE
## 66 Rustic_A 27 27 27.250000 2.4472769 22.276535 32.223465 FALSE
## 67 Rustic_A 28 28 28.000000 2.5132269 22.892508 33.107492 FALSE
## 68 Polyculture_B 1 1 1.666667 0.3256191 1.004929 2.328404 TRUE
## 69 Polyculture_B 2 2 3.189542 0.5852221 2.000228 4.378857 FALSE
## 70 Polyculture_B 3 3 4.587010 0.7912828 2.978930 6.195090 FALSE
## 71 Polyculture_B 4 4 5.875490 0.9546455 3.935417 7.815563 FALSE
## 72 Polyculture_B 5 5 7.069561 1.0846258 4.865336 9.273786 FALSE
## 73 Polyculture_B 6 6 8.182073 1.1891145 5.765501 10.598644 FALSE
## 74 Polyculture_B 7 7 9.224265 1.2746898 6.633783 11.814746 FALSE
## 75 Polyculture_B 8 8 10.205882 1.3467387 7.468980 12.942785 FALSE
## 76 Polyculture_B 9 9 11.135294 1.4095896 8.270663 13.999925 FALSE
## 77 Polyculture_B 10 10 12.019608 1.4666527 9.039011 15.000205 FALSE
## 78 Polyculture_B 11 11 12.864788 1.5205659 9.774626 15.954949 FALSE
## 79 Polyculture_B 12 12 13.675770 1.5733388 10.478361 16.873179 FALSE
## 80 Polyculture_B 13 13 14.456583 1.6264887 11.151160 17.762005 FALSE
## 81 Polyculture_B 14 14 15.210458 1.6811642 11.793921 18.626994 FALSE
## 82 Polyculture_B 15 15 15.939951 1.7382504 12.407401 19.472501 FALSE
## 83 Polyculture_B 16 16 16.647059 1.7984560 12.992157 20.301961 FALSE
## 84 Polyculture_B 17 17 17.333333 1.8623806 13.548521 21.118146 FALSE
## 85 Polyculture_B 18 18 18.000000 1.9305656 14.076619 21.923381 FALSE
## 86 Polyculture_A 1 1 1.851852 0.2858998 1.270834 2.432870 TRUE
## 87 Polyculture_A 2 2 3.584046 0.5352865 2.496213 4.671879 FALSE
## 88 Polyculture_A 3 3 5.205470 0.7519037 3.677418 6.733522 FALSE
## 89 Polyculture_A 4 4 6.724558 0.9392401 4.815793 8.633324 FALSE
## 90 Polyculture_A 5 5 8.149300 1.1005441 5.912725 10.385875 FALSE
## 91 Polyculture_A 6 6 9.487254 1.2388367 6.969635 12.004873 FALSE
## 92 Polyculture_A 7 7 10.745559 1.3569254 7.987955 13.503164 FALSE
## 93 Polyculture_A 8 8 11.930950 1.4574162 8.969124 14.892776 FALSE
## 94 Polyculture_A 9 9 13.049766 1.5427257 9.914570 16.184962 FALSE
## 95 Polyculture_A 10 10 14.107965 1.6150920 10.825703 17.390227 FALSE
## 96 Polyculture_A 11 11 15.111136 1.6765842 11.703907 18.518365 FALSE
## 97 Polyculture_A 12 12 16.064511 1.7291110 12.550535 19.578488 FALSE
## 98 Polyculture_A 13 13 16.972979 1.7744276 13.366908 20.579050 FALSE
## 99 Polyculture_A 14 14 17.841095 1.8141412 14.154317 21.527873 FALSE
## 100 Polyculture_A 15 15 18.673096 1.8497155 14.914021 22.432170 FALSE
## 101 Polyculture_A 16 16 19.472910 1.8824736 15.647263 23.298556 FALSE
## 102 Polyculture_A 17 17 20.244172 1.9136001 16.355269 24.133075 FALSE
## 103 Polyculture_A 18 18 20.990234 1.9441434 17.039259 24.941209 FALSE
## 104 Polyculture_A 19 19 21.714178 1.9750170 17.700461 25.727896 FALSE
## 105 Polyculture_A 20 20 22.418828 2.0070024 18.340109 26.497548 TRUE
## 106 Polyculture_A 21 21 23.106763 2.0407529 18.959454 27.254072 FALSE
## 107 Polyculture_A 22 22 23.780329 2.0767986 19.559767 28.000892 FALSE
## 108 Polyculture_A 23 23 24.441652 2.1155539 20.142330 28.740975 FALSE
## 109 Polyculture_A 24 24 25.092650 2.1573265 20.708435 29.476864 FALSE
## 110 Polyculture_A 25 25 25.735043 2.2023278 21.259374 30.210711 FALSE
## 111 Polyculture_A 26 26 26.370370 2.2506859 21.796426 30.944314 FALSE
## 112 Polyculture_A 27 27 27.000000 2.3024588 22.320841 31.679159 FALSE
## 113 Intensive_B 1 1 1.846154 0.2724841 1.292400 2.399908 TRUE
## 114 Intensive_B 2 2 3.578462 0.5122828 2.537378 4.619546 FALSE
## 115 Intensive_B 3 3 5.204231 0.7223129 3.736314 6.672147 FALSE
## 116 Intensive_B 4 4 6.730502 0.9053741 4.890560 8.570443 FALSE
## 117 Intensive_B 5 5 8.164047 1.0641489 6.001436 10.326658 FALSE
## 118 Intensive_B 6 6 9.511371 1.2012019 7.070235 11.952507 FALSE
## 119 Intensive_B 7 7 10.778712 1.3189793 8.098224 13.459201 FALSE
## 120 Intensive_B 8 8 11.972040 1.4198070 9.086645 14.857435 FALSE
## 121 Intensive_B 9 9 13.097057 1.5058892 10.036722 16.157392 FALSE
## 122 Intensive_B 10 10 14.159197 1.5793065 10.949660 17.368734 FALSE
## 123 Intensive_B 11 11 15.163629 1.6420129 11.826657 18.500600 FALSE
## 124 Intensive_B 12 12 16.115251 1.6958335 12.668903 19.561599 FALSE
## 125 Intensive_B 13 13 17.018696 1.7424616 13.477588 20.559804 FALSE
## 126 Intensive_B 14 14 17.878328 1.7834557 14.253910 21.502746 FALSE
## 127 Intensive_B 15 15 18.698244 1.8202378 14.999076 22.397412 FALSE
## 128 Intensive_B 16 16 19.482274 1.8540917 15.714307 23.250242 FALSE
## 129 Intensive_B 17 17 20.233980 1.8861632 16.400835 24.067125 FALSE
## 130 Intensive_B 18 18 20.956656 1.9174612 17.059906 24.853405 FALSE
## 131 Intensive_B 19 19 21.653328 1.9488617 17.692764 25.613891 FALSE
## 132 Intensive_B 20 20 22.326756 1.9811128 18.300650 26.352861 TRUE
## 133 Intensive_B 21 21 22.979431 2.0148429 18.884778 27.074085 FALSE
## 134 Intensive_B 22 22 23.613579 2.0505698 19.446319 27.780838 FALSE
## 135 Intensive_B 23 23 24.231154 2.0887126 19.986379 28.475929 FALSE
## 136 Intensive_B 24 24 24.833846 2.1296042 20.505970 29.161723 FALSE
## 137 Intensive_B 25 25 25.423077 2.1735053 21.005983 29.840171 FALSE
## 138 Intensive_B 26 26 26.000000 2.2206187 21.487160 30.512840 FALSE
## 139 Forest_B 1 1 1.652174 0.2776575 1.087906 2.216442 TRUE
## 140 Forest_B 2 2 3.205534 0.5142921 2.160366 4.250701 FALSE
## 141 Forest_B 3 3 4.669113 0.7156377 3.214763 6.123464 FALSE
## 142 Forest_B 4 4 6.051270 0.8868721 4.248930 7.853611 FALSE
## 143 Forest_B 5 5 7.359714 1.0326457 5.261125 9.458302 FALSE
## 144 Forest_B 6 6 8.601533 1.1571128 6.249997 10.953070 FALSE
## 145 Forest_B 7 7 9.783233 1.2639622 7.214553 12.351913 FALSE
## 146 Forest_B 8 8 10.910755 1.3564486 8.154120 13.667390 FALSE
## 147 Forest_B 9 9 11.989515 1.4374256 9.068315 14.910715 FALSE
## 148 Forest_B 10 10 13.024429 1.5093772 9.957005 16.091852 FALSE
## 149 Forest_B 11 11 14.019941 1.5744514 10.820271 17.219611 FALSE
## 150 Forest_B 12 12 14.980059 1.6344916 11.658372 18.301745 FALSE
## 151 Forest_B 13 13 15.908378 1.6910689 12.471712 19.345043 FALSE
## 152 Forest_B 14 14 16.808113 1.7455118 13.260806 20.355420 FALSE
## 153 Forest_B 15 15 17.682130 1.7989356 14.026253 21.338007 FALSE
## 154 Forest_B 16 16 18.532973 1.8522693 14.768709 22.297237 FALSE
## 155 Forest_B 17 17 19.362893 1.9062810 15.488864 23.236922 FALSE
## 156 Forest_B 18 18 20.173883 1.9616007 16.187431 24.160336 FALSE
## 157 Forest_B 19 19 20.967702 2.0187419 16.865125 25.070279 FALSE
## 158 Forest_B 20 20 21.745906 2.0781208 17.522657 25.969156 TRUE
## 159 Forest_B 21 21 22.509881 2.1400736 18.160729 26.859034 FALSE
## 160 Forest_B 22 22 23.260870 2.2048723 18.780030 27.741709 FALSE
## 161 Forest_B 23 23 24.000000 2.2727395 19.381238 28.618762 FALSE
## 162 Forest_A 1 1 1.882353 0.2722319 1.329111 2.435595 TRUE
## 163 Forest_A 2 2 3.659537 0.5146927 2.613555 4.705518 FALSE
## 164 Forest_A 3 3 5.338570 0.7299377 3.855158 6.821981 FALSE
## 165 Forest_A 4 4 6.926147 0.9203862 5.055697 8.796597 FALSE
## 166 Forest_A 5 5 8.428648 1.0883268 6.216902 10.640395 FALSE
## 167 Forest_A 6 6 9.852143 1.2359219 7.340448 12.363839 FALSE
## 168 Forest_A 7 7 11.202400 1.3652126 8.427954 13.976846 FALSE
## 169 Forest_A 8 8 12.484892 1.4781226 9.480985 15.488798 FALSE
## 170 Forest_A 9 9 13.704804 1.5764626 10.501047 16.908562 FALSE
## 171 Forest_A 10 10 14.867043 1.6619338 11.489587 18.244499 FALSE
## 172 Forest_A 11 11 15.976241 1.7361316 12.447997 19.504485 FALSE
## 173 Forest_A 12 12 17.036765 1.8005484 13.377610 20.695919 FALSE
## 174 Forest_A 13 13 18.052721 1.8565761 14.279705 21.825738 FALSE
## 175 Forest_A 14 14 19.027967 1.9055089 15.155507 22.900427 FALSE
## 176 Forest_A 15 15 19.966114 1.9485449 16.006194 23.926034 FALSE
## 177 Forest_A 16 16 20.870536 1.9867879 16.832898 24.908175 FALSE
## 178 Forest_A 17 17 21.744379 2.0212494 17.636706 25.852052 FALSE
## 179 Forest_A 18 18 22.590564 2.0528496 18.418672 26.762456 FALSE
## 180 Forest_A 19 19 23.411797 2.0824196 19.179811 27.643783 FALSE
## 181 Forest_A 20 20 24.210576 2.1107030 19.921111 28.500040 TRUE
## 182 Forest_A 21 21 24.989197 2.1383583 20.643530 29.334864 FALSE
## 183 Forest_A 22 22 25.749763 2.1659618 21.347999 30.151527 FALSE
## 184 Forest_A 23 23 26.494189 2.1940108 22.035422 30.952955 FALSE
## 185 Forest_A 24 24 27.224211 2.2229280 22.706678 31.741744 FALSE
## 186 Forest_A 25 25 27.941392 2.2530656 23.362612 32.520172 FALSE
## 187 Forest_A 26 26 28.647131 2.2847115 24.004038 33.290223 FALSE
## 188 Forest_A 27 27 29.342666 2.3180947 24.631731 34.053602 FALSE
## 189 Forest_A 28 28 30.029088 2.3533916 25.246421 34.811755 FALSE
## 190 Forest_A 29 29 30.707341 2.3907325 25.848788 35.565894 FALSE
## 191 Forest_A 30 30 31.378234 2.4302087 26.439456 36.317013 FALSE
## 192 Forest_A 31 31 32.042447 2.4718786 27.018985 37.065908 FALSE
## 193 Forest_A 32 32 32.700535 2.5157739 27.587867 37.813202 FALSE
## 194 Forest_A 33 33 33.352941 2.5619059 28.146522 38.559360 FALSE
## 195 Forest_A 34 34 34.000000 2.6102711 28.695291 39.304709 FALSE#----------------------------
ggplot(curva3, aes(x = Sites, y = Richness, ymax = UPR, ymin= LWR)) +
scale_x_continuous(expand=c(0, 1), sec.axis = dup_axis(labels=NULL, name=NULL)) +
scale_y_continuous(sec.axis = dup_axis(labels=NULL, name=NULL)) +
geom_line(aes(colour=Grouping), size=2) +
geom_point(data=subset(curva3, labelit==TRUE),
aes(colour=Grouping, shape=Grouping), size=5) +
#geom_ribbon(aes(colour=Grouping), alpha=0.2, show.legend=FALSE) +
theme_classic()## Warning: The shape palette can deal with a maximum of 6 discrete values because
## more than 6 becomes difficult to discriminate; you have 7. Consider
## specifying shapes manually if you must have them.## Warning: Removed 3 rows containing missing values (geom_point).
El sitio rústico B y el bosque A presentan una mayor riqueza. La abundancia de árboles en Rústico B es de 10.5, con 6 especies de árboles y una cobertura del dosel de 54.3. Esto puede explicar la riqueza de especies de este sitio. El bosque A tiene una cobertura de dosel de 100, una abundancia de árboles de 16 y 12 especies de árboles, a pesar de tener valores más altos que rústico B en estas variables, se sugiere que un factor determinante pueda ser la disponibilidad de alimento por el cultivo del café.
Métodos no paramétricos
■■■
specpool(aves) #estimado del número de especies observadas en la muestra.## Species chao chao.se jack1 jack1.se jack2 boot boot.se n
## All 68 74.01897 4.77657 78.94359 3.299616 79.98435 73.92185 2.25353 195# Utilizando cantidad de especies observadas, podemos calcular la riqueza para cada sitio de muestreo
estimacion <- poolaccum(aves)
estimacion## N S Chao Jackknife 1 Jackknife 2 Bootstrap
## 3 4.80 11.94833 7.84000 9.32000 6.160000
## 4 6.53 21.49625 11.15000 14.10667 8.502187
## 5 8.00 31.66200 13.98400 18.24700 10.490131
## 6 9.52 41.37208 16.83667 22.32733 12.521040
## 7 11.21 51.23357 19.95286 26.67905 14.767543
## 8 12.36 59.22573 22.00250 29.48964 16.270540
## 9 13.77 60.18274 24.42778 32.66444 18.094727
## 10 14.82 65.01495 26.22300 35.01500 19.446927
## 11 16.09 69.45500 28.42636 37.95327 21.091860
## 12 17.35 73.27740 30.59583 40.79659 22.722266
## 13 18.62 77.11682 32.73385 43.53077 24.352932
## 14 19.72 77.52414 34.54000 45.76725 25.752824
## 15 20.70 80.95514 36.11867 47.72395 26.987487
## 16 21.86 80.48391 37.93812 49.89821 28.437489
## 17 22.99 79.66148 39.64882 51.82529 29.835910
## 18 23.96 81.64508 41.19611 53.76239 31.050313
## 19 24.93 77.77442 42.57947 55.20918 32.225739
## 20 25.92 80.71137 44.10300 56.95500 33.457251
## 21 26.88 79.06559 45.53714 58.60281 34.634131
## 22 27.94 77.02980 47.10727 60.30554 35.938285
## 23 28.89 78.57183 48.57522 62.05796 37.116429
## 24 29.60 73.83277 49.42792 62.74708 37.928572
## 25 30.47 77.23499 50.70680 64.26377 38.981660
## 26 31.27 73.70255 51.79885 65.38322 39.932679
## 27 32.12 73.04068 52.94889 66.58422 40.935681
## 28 32.69 73.06689 53.61500 67.15701 41.573812
## 29 33.42 72.94895 54.50690 67.93674 42.410386
## 30 34.15 72.97082 55.49400 68.96490 43.270926
## 31 34.87 72.74912 56.43129 69.87669 44.111850
## 32 35.52 72.95774 57.19094 70.47834 44.845783
## 33 36.19 72.14613 57.94030 71.03898 45.592396
## 34 36.85 72.45817 58.69794 71.65167 46.331000
## 35 37.51 72.17046 59.51286 72.33045 47.092328
## 36 38.08 70.05798 60.17861 72.88409 47.733570
## 37 38.68 68.79720 60.78595 73.20989 48.381403
## 38 39.21 68.38198 61.28342 73.43201 48.939527
## 39 39.70 67.91059 61.74974 73.66764 49.458423
## 40 40.25 67.67530 62.30450 74.01873 50.047525
## 41 40.71 68.33416 62.77829 74.39910 50.535981
## 42 41.28 68.32238 63.37119 74.83298 51.149116
## 43 41.67 67.68971 63.65651 74.76919 51.538406
## 44 42.07 66.67521 63.93159 74.62805 51.935253
## 45 42.48 66.12941 64.23556 74.63613 52.342608
## 46 42.92 65.52400 64.50043 74.41553 52.769280
## 47 43.40 65.84520 64.96128 74.67374 53.275098
## 48 43.84 64.72727 65.16625 74.34260 53.678997
## 49 44.28 65.26707 65.64490 74.85286 54.145425
## 50 44.76 65.75592 66.20240 75.47091 54.667665
## 51 45.21 65.89246 66.59235 75.65505 55.126219
## 52 45.57 65.51404 66.78404 75.44034 55.461948
## 53 46.12 66.46966 67.51849 76.34042 56.093815
## 54 46.43 66.25391 67.68889 76.26435 56.376264
## 55 46.75 66.15479 67.82964 76.13850 56.651851
## 56 47.16 66.60750 68.24661 76.53789 57.077314
## 57 47.56 66.56944 68.63368 76.81218 57.490943
## 58 47.88 66.10236 68.73414 76.49249 57.764085
## 59 48.14 65.60115 68.71525 75.96635 57.959069
## 60 48.49 65.63684 68.98267 76.09012 58.293985
## 61 48.87 65.68044 69.27000 76.22394 58.658996
## 62 49.21 65.98187 69.54661 76.50912 58.978836
## 63 49.60 66.20269 69.94190 76.82838 59.387747
## 64 49.94 66.19521 70.07047 76.63906 59.673985
## 65 50.23 66.35837 70.30631 76.81666 59.952148
## 66 50.45 66.32559 70.33409 76.62176 60.115510
## 67 50.74 66.43251 70.50060 76.57594 60.378237
## 68 51.04 66.92016 70.69662 76.76048 60.641471
## 69 51.21 67.05501 70.74275 76.77575 60.762802
## 70 51.54 67.10464 70.95857 76.85557 61.064024
## 71 51.86 67.49276 71.26282 77.17835 61.377662
## 72 52.18 67.39586 71.38944 76.90893 61.655851
## 73 52.48 67.63121 71.65370 77.10500 61.952655
## 74 52.74 67.28723 71.69041 76.77346 62.157197
## 75 53.01 67.39550 71.85533 76.75383 62.404526
## 76 53.36 67.96895 72.29750 77.35975 62.783040
## 77 53.63 68.06959 72.51156 77.52433 63.035642
## 78 53.82 67.90648 72.56654 77.45187 63.176893
## 79 54.09 68.09131 72.76063 77.52883 63.428264
## 80 54.29 68.23825 72.77600 77.34863 63.570565
## 81 54.51 68.43464 72.92975 77.50078 63.762270
## 82 54.80 68.36502 73.08427 77.44091 64.020604
## 83 54.90 68.24261 72.97952 77.17864 64.044028
## 84 55.10 68.10590 72.98452 76.92974 64.184641
## 85 55.38 68.39585 73.24729 77.16248 64.458128
## 86 55.63 68.52165 73.36140 77.11002 64.668112
## 87 55.86 68.41150 73.39609 76.90016 64.838230
## 88 56.03 68.36046 73.40034 76.74699 64.947636
## 89 56.24 68.53235 73.51371 76.84863 65.117391
## 90 56.42 68.60419 73.52778 76.71489 65.236078
## 91 56.64 68.63218 73.67077 76.81739 65.426951
## 92 56.86 68.44418 73.85326 76.94048 65.633275
## 93 57.05 68.52150 73.93645 76.94415 65.784555
## 94 57.20 68.35534 73.90043 76.74062 65.869311
## 95 57.30 68.42650 73.84400 76.63317 65.904135
## 96 57.57 68.62740 74.05646 76.82472 66.151892
## 97 57.83 68.92715 74.38753 77.32037 66.432359
## 98 57.97 68.83799 74.34122 77.10650 66.504578
## 99 58.15 68.90151 74.41404 77.10948 66.645491
## 100 58.30 68.96756 74.40730 76.93540 66.741457
## 101 58.52 68.94236 74.47050 76.80209 66.911442
## 102 58.73 69.38435 74.71176 77.21749 67.113814
## 103 58.89 69.56819 74.82379 77.39618 67.242654
## 104 59.15 69.72265 75.01596 77.58691 67.471521
## 105 59.31 70.20727 75.15762 77.97050 67.597752
## 106 59.46 70.15680 75.22981 77.95381 67.718198
## 107 59.61 70.30150 75.34159 78.07425 67.847579
## 108 59.69 70.29438 75.35361 78.14331 67.886960
## 109 59.82 70.54725 75.46514 78.36101 67.992995
## 110 60.01 70.65491 75.57718 78.35501 68.158127
## 111 60.10 70.47299 75.50000 78.14921 68.180382
## 112 60.26 70.76559 75.60179 78.24986 68.313289
## 113 60.34 70.89040 75.57398 78.23023 68.344284
## 114 60.54 71.15234 75.70579 78.23427 68.527292
## 115 60.61 71.29216 75.70757 78.27381 68.557429
## 116 60.79 71.46457 75.88871 78.41542 68.736993
## 117 60.94 71.60476 75.94068 78.41727 68.849013
## 118 61.00 71.39028 75.86297 78.26959 68.850429
## 119 61.18 71.51430 75.99445 78.41961 69.004552
## 120 61.29 71.64462 76.05592 78.50937 69.085230
## 121 61.40 71.89487 76.13719 78.66791 69.170540
## 122 61.55 72.21699 76.25844 78.85671 69.299684
## 123 61.66 72.03920 76.21073 78.58283 69.352583
## 124 61.76 72.27766 76.32161 78.77137 69.444465
## 125 61.94 72.29192 76.47280 78.91209 69.608380
## 126 62.03 72.07063 76.42484 78.75518 69.642508
## 127 62.16 72.19739 76.52598 78.88491 69.750790
## 128 62.30 72.41322 76.69664 79.21160 69.884957
## 129 62.46 72.46356 76.81783 79.41021 70.017811
## 130 62.59 72.42818 76.85938 79.44091 70.108028
## 131 62.66 72.25732 76.80122 79.27389 70.125924
## 132 62.80 72.49136 76.93212 79.47273 70.250157
## 133 62.95 72.64872 77.06308 79.65204 70.386031
## 134 63.07 72.65401 77.12433 79.66360 70.481838
## 135 63.23 72.70438 77.22556 79.73469 70.617954
## 136 63.37 72.83040 77.32662 79.85466 70.734585
## 137 63.47 72.80587 77.33803 79.73792 70.798891
## 138 63.56 72.70228 77.27986 79.47286 70.839032
## 139 63.66 72.79061 77.31108 79.48364 70.905862
## 140 63.77 72.89718 77.39200 79.59333 70.994141
## 141 63.82 72.64385 77.27390 79.25835 70.986064
## 142 63.90 72.68895 77.25528 79.17991 71.025431
## 143 64.06 72.94093 77.42587 79.48727 71.170263
## 144 64.24 73.29081 77.64625 79.74674 71.360328
## 145 64.35 73.26513 77.66752 79.71807 71.434067
## 146 64.40 73.07419 77.61884 79.59980 71.443923
## 147 64.52 73.18465 77.73946 79.74947 71.556304
## 148 64.66 73.39837 77.87014 79.95813 71.678800
## 149 64.75 73.47127 77.90114 79.95902 71.740169
## 150 64.83 73.48638 77.90227 79.94950 71.779286
## 151 64.92 73.67345 78.01272 80.18719 71.861010
## 152 64.96 73.37430 77.92414 79.89162 71.858819
## 153 65.06 73.34543 77.97503 79.89285 71.938981
## 154 65.16 73.34255 78.00604 79.90349 72.008286
## 155 65.28 73.60234 78.14645 80.17122 72.122504
## 156 65.41 73.73020 78.22731 80.19262 72.230947
## 157 65.50 73.84467 78.30790 80.24344 72.312424
## 158 65.55 73.72535 78.26899 80.09576 72.328415
## 159 65.64 73.69433 78.29987 80.10636 72.388902
## 160 65.73 73.70762 78.34069 80.09751 72.456704
## 161 65.80 73.74731 78.37143 80.13753 72.504755
## 162 65.88 73.91250 78.46185 80.36514 72.572372
## 163 65.95 73.94591 78.48264 80.37554 72.617069
## 164 66.05 73.84052 78.52348 80.36667 72.690466
## 165 66.13 73.93215 78.59400 80.47615 72.757420
## 166 66.18 73.95175 78.59476 80.47636 72.779341
## 167 66.22 73.92924 78.56563 80.42692 72.786040
## 168 66.32 74.04961 78.63625 80.60516 72.858216
## 169 66.40 74.03322 78.66698 80.62555 72.913714
## 170 66.47 74.07345 78.67776 80.59646 72.958412
## 171 66.55 74.22012 78.73830 80.67631 73.023505
## 172 66.65 74.18615 78.76913 80.58860 73.101772
## 173 66.69 74.01276 78.69023 80.32208 73.102230
## 174 66.73 74.02724 78.67098 80.27276 73.115282
## 175 66.85 74.19194 78.81126 80.48172 73.237292
## 176 66.92 74.24866 78.86176 80.54171 73.295106
## 177 66.98 74.14793 78.83266 80.42340 73.319336
## 178 67.02 74.04284 78.76365 80.25523 73.320091
## 179 67.09 73.94817 78.71469 80.07755 73.345974
## 180 67.15 73.97981 78.70544 80.05785 73.372824
## 181 67.25 74.15170 78.79586 80.22665 73.460123
## 182 67.36 74.28414 78.89626 80.37596 73.560418
## 183 67.40 74.21275 78.85705 80.31642 73.563966
## 184 67.44 74.16179 78.79793 80.16802 73.563806
## 185 67.52 74.19241 78.85838 80.20846 73.634085
## 186 67.54 74.08799 78.80909 80.07987 73.625359
## 187 67.59 74.04692 78.81963 80.02110 73.660407
## 188 67.63 74.01535 78.83011 79.98200 73.687750
## 189 67.67 74.01864 78.83063 79.94273 73.708231
## 190 67.74 74.06172 78.88105 80.04204 73.761208
## 191 67.78 74.14692 78.91141 80.17056 73.782695
## 192 67.83 74.10943 78.93187 80.12176 73.820582
## 193 67.87 74.14689 78.96223 80.17154 73.848215
## 194 67.93 74.08554 78.95289 80.08288 73.881273
## 195 68.00 74.01897 78.94359 79.98435 73.921846plot(estimacion)
estimacion2 <- with (sitios, specpool(aves,Zona))
estimacion2## Species chao chao.se jack1 jack1.se jack2 boot
## Forest_A 34 112.29412 56.88723 55.35294 8.776049 73.32086 42.52113
## Forest_B 24 70.07246 35.39890 40.26087 5.724619 53.16798 30.58192
## Intensive_B 26 53.04327 20.12216 40.42308 5.040516 50.72462 32.08528
## Polyculture_A 27 96.57407 60.23955 43.37037 6.387574 57.33048 33.59651
## Polyculture_B 18 40.66667 19.10982 29.33333 4.488669 37.49020 22.70034
## Rustic_A 28 81.15625 36.02444 48.25000 7.494641 64.17328 36.15621
## Rustic_B 39 85.76923 27.85479 62.38462 8.222258 79.61134 48.72456
## boot.se n
## Forest_A 4.424519 34
## Forest_B 2.670009 23
## Intensive_B 2.560986 26
## Polyculture_A 3.022041 27
## Polyculture_B 2.122509 18
## Rustic_A 3.513429 28
## Rustic_B 4.199400 39