Ejemplo: Inventario de especies

El empleo de cámaras-trampa para obtener diferente información biológica de los animales se ha aplicado desde hace algunas décadas pero actualmente está en auge debido al desarrollo tecnológico y a la reducción de costos.

Con el foto-trampeo se puede obtener mucha información en poco tiempo y con poco personal, lo que hace que sea un método muy atractivo para monitoreos de fauna a largo plazo en diferentes tipos de hábitat. En particular, el foto-trampeo se ha utilizado para:

  1. realizar inventarios,
  2. estimar la abundancia de diferentes especies,
  3. calcular índices de abundancia relativa,
  4. estimar la ocupación,
  5. evaluar el uso de hábitat,
  6. conocer patrones de actividad,
  7. entre las principales aplicaciones.

En este sentido, la organización de las cientos, miles o decenas de miles de fotos obtenidas con las camáras-trampa, requiere de herramientas eficentes de gestión y análisis de la información. En este ejemplo se muestran los pasos generales para ambas tareas empleando el programa R y varias paqueterías.

El presente ejemplo está basado en el siguiente capítulo: Rovero, F. y D. Spitale. 2016. Presence/absence and species inventory. Pp. 43-67, in: F. Rovero & F. Zimmermann (eds.), Camera Trapping for Wildlife Research. Pelagic Publishing, UK.

El contenido del libro citado se puede consultar en la siguiente liga: Ver libro.

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PASO 1: Instalar las siguientes librerias:

library(chron) 
library(reshape)
library (vegan)
library(plotrix)
library(ggplot2)
library(maptools)
library(rgdal)

Además se debe llamar al paquete TEAM library 1.7.R que es un recurso necesario con múltiples funciones para realizar los anlisis siguientes

source("TEAM library 1.7.R")

PASO 2: Se deben cargar los datos previamente generados en Wild.ID y guardados como teamexample.csv

Tabla 1. Datos de las cámaras-trampa empleadas en el presente ejemplo. Aquí Solo se muestran los primeros 20 datos.

Sampling.Unit.Name Latitude Longitude Project.Name Sampling.Event Photo.Date Photo.Time Genus Species Number.of.Animals Camera.Start.Date.and.Time Camera.End.Date.and.Time
CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-07-28 00:26:25 Cricetomys gambianus 1 2009-07-27 13:16:17 2009-08-28 15:39:15
CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-01 05:17:18 Atilax paludinosus 1 2009-07-27 13:16:17 2009-08-28 15:39:15
CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-01 05:17:19 Atilax paludinosus 1 2009-07-27 13:16:17 2009-08-28 15:39:15
CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-01 05:17:20 Atilax paludinosus 1 2009-07-27 13:16:17 2009-08-28 15:39:15
CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-04 00:08:21 Bdeogale crassicauda 1 2009-07-27 13:16:17 2009-08-28 15:39:15
CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-04 00:08:23 Bdeogale crassicauda 1 2009-07-27 13:16:17 2009-08-28 15:39:15
CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-04 00:08:24 Bdeogale crassicauda 1 2009-07-27 13:16:17 2009-08-28 15:39:15
CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-06 16:12:27 Cercocebus sanjei 1 2009-07-27 13:16:17 2009-08-28 15:39:15
CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-06 16:12:28 Cercocebus sanjei 1 2009-07-27 13:16:17 2009-08-28 15:39:15
CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-06 16:12:29 Cercocebus sanjei 1 2009-07-27 13:16:17 2009-08-28 15:39:15
CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-06 16:12:53 Cercocebus sanjei 1 2009-07-27 13:16:17 2009-08-28 15:39:15
CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-06 16:12:54 Cercocebus sanjei 1 2009-07-27 13:16:17 2009-08-28 15:39:15
CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-06 16:12:55 Cercocebus sanjei 1 2009-07-27 13:16:17 2009-08-28 15:39:15
CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-06 16:15:06 Cercocebus sanjei 2 2009-07-27 13:16:17 2009-08-28 15:39:15
CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-06 16:15:08 Cercocebus sanjei 2 2009-07-27 13:16:17 2009-08-28 15:39:15
CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-06 16:15:09 Cercocebus sanjei 2 2009-07-27 13:16:17 2009-08-28 15:39:15
CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-06 16:19:29 Cercocebus sanjei 1 2009-07-27 13:16:17 2009-08-28 15:39:15
CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-06 16:19:31 Cercocebus sanjei 1 2009-07-27 13:16:17 2009-08-28 15:39:15
CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-06 16:19:33 Cercocebus sanjei 2 2009-07-27 13:16:17 2009-08-28 15:39:15
CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-06 16:19:35 Cercocebus sanjei 2 2009-07-27 13:16:17 2009-08-28 15:39:15

PASO 3: Adicionar datos sobre la Clase, Orden, Familia empleando la base IUCN

iucn.full <- read.csv("IUCN.csv", sep=",",h=T)
iucn <- iucn.full[,c("Class","Order","Family","Genus","Species")]
team <- merge(iucn, team_data, all.y=T) # esto sirve para integrar ambas data.frames

Tabla 2. Se añaden los datos taxonómicos de las especies. Aquí solo se muestran los primeros 20 datos.

Genus Species Class Order Family Sampling.Unit.Name Latitude Longitude Project.Name Sampling.Event Photo.Date Photo.Time Number.of.Animals Camera.Start.Date.and.Time Camera.End.Date.and.Time
Accipiter tachiro AVES FALCONIFORMES ACCIPITRIDAE CT-UDZ-1-10 -7.82257 36.85191 Udzungwa 2013.01 2013-07-29 16:48:41 1 2013-07-04 12:45:36 2013-08-04 11:19:29
Accipiter tachiro AVES FALCONIFORMES ACCIPITRIDAE CT-UDZ-1-10 -7.82257 36.85191 Udzungwa 2013.01 2013-07-29 16:48:57 1 2013-07-04 12:45:36 2013-08-04 11:19:29
Accipiter tachiro AVES FALCONIFORMES ACCIPITRIDAE CT-UDZ-1-10 -7.82257 36.85191 Udzungwa 2013.01 2013-07-29 16:48:59 1 2013-07-04 12:45:36 2013-08-04 11:19:29
Accipiter tachiro AVES FALCONIFORMES ACCIPITRIDAE CT-UDZ-1-10 -7.82257 36.85191 Udzungwa 2013.01 2013-07-29 16:49:00 1 2013-07-04 12:45:36 2013-08-04 11:19:29
Accipiter tachiro AVES FALCONIFORMES ACCIPITRIDAE CT-UDZ-1-10 -7.82257 36.85191 Udzungwa 2013.01 2013-07-29 16:49:04 1 2013-07-04 12:45:36 2013-08-04 11:19:29
Accipiter tachiro AVES FALCONIFORMES ACCIPITRIDAE CT-UDZ-1-10 -7.82257 36.85191 Udzungwa 2013.01 2013-07-29 16:49:06 1 2013-07-04 12:45:36 2013-08-04 11:19:29
Accipiter tachiro AVES FALCONIFORMES ACCIPITRIDAE CT-UDZ-1-10 -7.82257 36.85191 Udzungwa 2013.01 2013-07-29 16:49:07 1 2013-07-04 12:45:36 2013-08-04 11:19:29
Accipiter tachiro AVES FALCONIFORMES ACCIPITRIDAE CT-UDZ-1-10 -7.82257 36.85191 Udzungwa 2013.01 2013-07-29 16:52:58 1 2013-07-04 12:45:36 2013-08-04 11:19:29
Accipiter tachiro AVES FALCONIFORMES ACCIPITRIDAE CT-UDZ-1-10 -7.82257 36.85191 Udzungwa 2013.01 2013-07-29 16:53:00 1 2013-07-04 12:45:36 2013-08-04 11:19:29
Accipiter tachiro AVES FALCONIFORMES ACCIPITRIDAE CT-UDZ-1-10 -7.82257 36.85191 Udzungwa 2013.01 2013-07-29 16:53:01 1 2013-07-04 12:45:36 2013-08-04 11:19:29
Accipiter tachiro AVES FALCONIFORMES ACCIPITRIDAE CT-UDZ-1-10 -7.82257 36.85191 Udzungwa 2013.01 2013-07-29 16:33:38 1 2013-07-04 12:45:36 2013-08-04 11:19:29
Accipiter tachiro AVES FALCONIFORMES ACCIPITRIDAE CT-UDZ-1-10 -7.82257 36.85191 Udzungwa 2013.01 2013-07-29 16:33:39 1 2013-07-04 12:45:36 2013-08-04 11:19:29
Accipiter tachiro AVES FALCONIFORMES ACCIPITRIDAE CT-UDZ-1-10 -7.82257 36.85191 Udzungwa 2013.01 2013-07-29 16:48:38 1 2013-07-04 12:45:36 2013-08-04 11:19:29
Accipiter tachiro AVES FALCONIFORMES ACCIPITRIDAE CT-UDZ-1-10 -7.82257 36.85191 Udzungwa 2013.01 2013-07-29 16:48:40 1 2013-07-04 12:45:36 2013-08-04 11:19:29
Accipiter tachiro AVES FALCONIFORMES ACCIPITRIDAE CT-UDZ-1-10 -7.82257 36.85191 Udzungwa 2013.01 2013-07-29 16:33:36 1 2013-07-04 12:45:36 2013-08-04 11:19:29
Alethe fuelleborni AVES PASSERIFORMES TURDIDAE CT-UDZ-2-09 -7.77168 36.89202 Udzungwa 2011.01 2011-08-30 07:14:26 1 2011-08-19 10:05:32 2011-09-20 10:02:38
Alethe fuelleborni AVES PASSERIFORMES TURDIDAE CT-UDZ-2-09 -7.77168 36.89202 Udzungwa 2011.01 2011-08-30 07:14:27 1 2011-08-19 10:05:32 2011-09-20 10:02:38
Alethe fuelleborni AVES PASSERIFORMES TURDIDAE CT-UDZ-2-07 -7.77157 36.86570 Udzungwa 2011.01 2011-09-07 18:18:34 1 2011-08-25 10:38:37 2011-09-26 11:29:59
Alethe fuelleborni AVES PASSERIFORMES TURDIDAE CT-UDZ-2-09 -7.77168 36.89202 Udzungwa 2011.01 2011-08-30 07:14:24 1 2011-08-19 10:05:32 2011-09-20 10:02:38
Alethe fuelleborni AVES PASSERIFORMES TURDIDAE CT-UDZ-2-09 -7.77168 36.89202 Udzungwa 2011.01 2011-08-29 16:40:35 1 2011-08-19 10:05:32 2011-09-20 10:02:38

PASO 4: Se emplea función para darle el formato adecuado a la matriz de datos

data <- fix.dta(team) 
data <- droplevels(data[data$bin!="Homo sapiens", ])

Tabla 3. Matriz de datos con los que se realizarán los siguientes análisis. Aquí Solo se muestran los primeros 20 datos.

Genus Species Class Order Family Sampling.Unit.Name Latitude Longitude Project.Name Sampling.Event Photo.Date Photo.Time Number.of.Animals Camera.Start.Date.and.Time Camera.End.Date.and.Time Start.Date End.Date bin td.photo
46284 Cricetomys gambianus MAMMALIA RODENTIA NESOMYIDAE CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-07-28 00:26:25 1 (09-07-27 13:16:17) (09-08-28 15:39:15) 2009-07-27 2009-08-28 Cricetomys gambianus (09-07-28 00:26:25)
537 Atilax paludinosus MAMMALIA CARNIVORA HERPESTIDAE CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-01 05:17:18 1 (09-07-27 13:16:17) (09-08-28 15:39:15) 2009-07-27 2009-08-28 Atilax paludinosus (09-08-01 05:17:18)
529 Atilax paludinosus MAMMALIA CARNIVORA HERPESTIDAE CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-01 05:17:19 1 (09-07-27 13:16:17) (09-08-28 15:39:15) 2009-07-27 2009-08-28 Atilax paludinosus (09-08-01 05:17:19)
519 Atilax paludinosus MAMMALIA CARNIVORA HERPESTIDAE CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-01 05:17:20 1 (09-07-27 13:16:17) (09-08-28 15:39:15) 2009-07-27 2009-08-28 Atilax paludinosus (09-08-01 05:17:20)
1098 Bdeogale crassicauda MAMMALIA CARNIVORA HERPESTIDAE CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-04 00:08:21 1 (09-07-27 13:16:17) (09-08-28 15:39:15) 2009-07-27 2009-08-28 Bdeogale crassicauda (09-08-04 00:08:21)
893 Bdeogale crassicauda MAMMALIA CARNIVORA HERPESTIDAE CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-04 00:08:23 1 (09-07-27 13:16:17) (09-08-28 15:39:15) 2009-07-27 2009-08-28 Bdeogale crassicauda (09-08-04 00:08:23)
812 Bdeogale crassicauda MAMMALIA CARNIVORA HERPESTIDAE CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-04 00:08:24 1 (09-07-27 13:16:17) (09-08-28 15:39:15) 2009-07-27 2009-08-28 Bdeogale crassicauda (09-08-04 00:08:24)
36820 Cercocebus sanjei MAMMALIA PRIMATES CERCOPITHECIDAE CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-06 16:12:27 1 (09-07-27 13:16:17) (09-08-28 15:39:15) 2009-07-27 2009-08-28 Cercocebus sanjei (09-08-06 16:12:27)
37666 Cercocebus sanjei MAMMALIA PRIMATES CERCOPITHECIDAE CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-06 16:12:28 1 (09-07-27 13:16:17) (09-08-28 15:39:15) 2009-07-27 2009-08-28 Cercocebus sanjei (09-08-06 16:12:28)
38634 Cercocebus sanjei MAMMALIA PRIMATES CERCOPITHECIDAE CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-06 16:12:29 1 (09-07-27 13:16:17) (09-08-28 15:39:15) 2009-07-27 2009-08-28 Cercocebus sanjei (09-08-06 16:12:29)
37540 Cercocebus sanjei MAMMALIA PRIMATES CERCOPITHECIDAE CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-06 16:12:53 1 (09-07-27 13:16:17) (09-08-28 15:39:15) 2009-07-27 2009-08-28 Cercocebus sanjei (09-08-06 16:12:53)
37541 Cercocebus sanjei MAMMALIA PRIMATES CERCOPITHECIDAE CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-06 16:12:54 1 (09-07-27 13:16:17) (09-08-28 15:39:15) 2009-07-27 2009-08-28 Cercocebus sanjei (09-08-06 16:12:54)
37297 Cercocebus sanjei MAMMALIA PRIMATES CERCOPITHECIDAE CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-06 16:12:55 1 (09-07-27 13:16:17) (09-08-28 15:39:15) 2009-07-27 2009-08-28 Cercocebus sanjei (09-08-06 16:12:55)
36211 Cercocebus sanjei MAMMALIA PRIMATES CERCOPITHECIDAE CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-06 16:15:06 2 (09-07-27 13:16:17) (09-08-28 15:39:15) 2009-07-27 2009-08-28 Cercocebus sanjei (09-08-06 16:15:06)
37180 Cercocebus sanjei MAMMALIA PRIMATES CERCOPITHECIDAE CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-06 16:15:08 2 (09-07-27 13:16:17) (09-08-28 15:39:15) 2009-07-27 2009-08-28 Cercocebus sanjei (09-08-06 16:15:08)
35845 Cercocebus sanjei MAMMALIA PRIMATES CERCOPITHECIDAE CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-06 16:15:09 2 (09-07-27 13:16:17) (09-08-28 15:39:15) 2009-07-27 2009-08-28 Cercocebus sanjei (09-08-06 16:15:09)
36816 Cercocebus sanjei MAMMALIA PRIMATES CERCOPITHECIDAE CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-06 16:19:29 1 (09-07-27 13:16:17) (09-08-28 15:39:15) 2009-07-27 2009-08-28 Cercocebus sanjei (09-08-06 16:19:29)
39378 Cercocebus sanjei MAMMALIA PRIMATES CERCOPITHECIDAE CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-06 16:19:31 1 (09-07-27 13:16:17) (09-08-28 15:39:15) 2009-07-27 2009-08-28 Cercocebus sanjei (09-08-06 16:19:31)
39746 Cercocebus sanjei MAMMALIA PRIMATES CERCOPITHECIDAE CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-06 16:19:33 2 (09-07-27 13:16:17) (09-08-28 15:39:15) 2009-07-27 2009-08-28 Cercocebus sanjei (09-08-06 16:19:33)
41936 Cercocebus sanjei MAMMALIA PRIMATES CERCOPITHECIDAE CT-UDZ-1-01 -7.84697 36.82797 Udzungwa 2009.01 2009-08-06 16:19:35 2 (09-07-27 13:16:17) (09-08-28 15:39:15) 2009-07-27 2009-08-28 Cercocebus sanjei (09-08-06 16:19:35)

PASO 5: Si se quiere analizar solo alguno de los años, por ejemplo el 2009 en este ejemplo, entonces se debe seleccionar esos campos de la base original:

##  [1] "Genus"                      "Species"                   
##  [3] "Class"                      "Order"                     
##  [5] "Family"                     "Sampling.Unit.Name"        
##  [7] "Latitude"                   "Longitude"                 
##  [9] "Project.Name"               "Sampling.Event"            
## [11] "Photo.Date"                 "Photo.Time"                
## [13] "Number.of.Animals"          "Camera.Start.Date.and.Time"
## [15] "Camera.End.Date.and.Time"   "Start.Date"                
## [17] "End.Date"                   "bin"                       
## [19] "td.photo"
##  [1] "CT-UDZ-1-01" "CT-UDZ-1-02" "CT-UDZ-1-03" "CT-UDZ-1-04" "CT-UDZ-1-05"
##  [6] "CT-UDZ-1-06" "CT-UDZ-1-07" "CT-UDZ-1-08" "CT-UDZ-1-09" "CT-UDZ-1-10"
## [11] "CT-UDZ-1-11" "CT-UDZ-1-13" "CT-UDZ-1-14" "CT-UDZ-1-15" "CT-UDZ-1-16"
## [16] "CT-UDZ-1-17" "CT-UDZ-1-18" "CT-UDZ-1-19" "CT-UDZ-1-20" "CT-UDZ-2-01"
## [21] "CT-UDZ-2-02" "CT-UDZ-2-03" "CT-UDZ-2-04" "CT-UDZ-2-05" "CT-UDZ-2-06"
## [26] "CT-UDZ-2-07" "CT-UDZ-2-08" "CT-UDZ-2-09" "CT-UDZ-2-10" "CT-UDZ-2-11"
## [31] "CT-UDZ-2-12" "CT-UDZ-2-13" "CT-UDZ-2-14" "CT-UDZ-2-15" "CT-UDZ-2-16"
## [36] "CT-UDZ-2-17" "CT-UDZ-2-18" "CT-UDZ-2-19" "CT-UDZ-2-20" "CT-UDZ-3-01"
## [41] "CT-UDZ-3-02" "CT-UDZ-3-03" "CT-UDZ-3-04" "CT-UDZ-3-05" "CT-UDZ-3-06"
## [46] "CT-UDZ-3-07" "CT-UDZ-3-08" "CT-UDZ-3-09" "CT-UDZ-3-10" "CT-UDZ-3-11"
## [51] "CT-UDZ-3-12" "CT-UDZ-3-14" "CT-UDZ-3-15" "CT-UDZ-3-16" "CT-UDZ-3-17"
## [56] "CT-UDZ-3-18" "CT-UDZ-3-19" "CT-UDZ-3-20"
##  [1] Cricetomys gambianus      Atilax paludinosus       
##  [3] Bdeogale crassicauda      Cercocebus sanjei        
##  [5] Cephalophus harveyi       Cephalophus spadix       
##  [7] Panthera pardus           Hystrix africaeaustralis 
##  [9] Civettictis civetta       Potamochoerus larvatus   
## [11] Nesotragus moschatus      Papio cynocephalus       
## [13] Loxodonta africana        Colobus angolensis       
## [15] Nandinia binotata         Paraxerus vexillarius    
## [17] Genetta servalina         Cercopithecus mitis      
## [19] Mellivora capensis        Procolobus gordonorum    
## [21] Dendrohyrax arboreus      Rhynchocyon cirnei       
## [23] Mungos mungo              Petrodromus tetradactylus
## [25] Syncerus caffer           Rhynchocyon udzungwensis 
## 38 Levels: Accipiter tachiro Alethe fuelleborni ... Zoothera gurneyi
##  [1] (09-07-27 13:16:17) (09-07-25 15:52:52) (09-07-26 11:46:24)
##  [4] (09-07-24 09:36:22) (09-07-27 09:06:32) (09-07-28 16:04:54)
##  [7] (09-07-25 13:02:52) (09-07-25 10:02:38) (09-07-28 10:32:04)
## [10] (09-07-28 13:27:05) (09-07-29 10:24:05) (09-07-31 23:55:10)
## [13] (09-08-01 14:40:50) (09-08-02 14:14:42) (09-08-03 10:01:05)
## [16] (09-07-31 04:27:01) (09-08-02 11:05:03) (09-07-31 13:20:12)
## [19] (09-07-30 11:58:13) (09-09-16 15:14:05) (09-09-16 13:19:42)
## [22] (09-09-09 15:10:34) (09-09-09 17:13:43) (09-09-15 15:58:33)
## [25] (09-09-15 14:19:36) (09-09-15 11:54:22) (09-09-09 11:47:24)
## [28] (09-09-08 11:03:32) (09-09-07 16:04:19) (09-09-14 14:18:19)
## [31] (09-09-14 12:05:05) (09-09-13 22:12:17) (09-09-10 11:08:01)
## [34] (09-09-08 14:30:22) (09-09-07 13:33:22) (09-09-13 14:36:00)
## [37] (09-09-13 11:59:01) (09-09-12 22:17:49) (09-09-10 15:00:47)
## [40] (09-10-28 15:21:03) (09-10-28 12:33:12) (09-10-28 10:33:56)
## [43] (09-10-30 14:40:43) (09-11-01 15:35:32) (09-10-31 13:50:31)
## [46] (09-11-03 13:36:15) (09-11-02 15:25:13) (09-10-26 14:02:31)
## [49] (09-10-30 11:35:57) (09-11-01 10:41:29) (09-11-02 15:54:44)
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PASO 6: Para calcular el número de días cámaras:

Ejemplo:

PASO 7: Para elegir el intervalo de eventos independientes

events_hh <- event.sp(dtaframe=data, year=2009.01, thresh=60) # en minutos
write.table(events_hh, file="events_hh.txt",quote=F, sep="\t")

Ejemplo:

events_dd <- event.sp(dtaframe=data, year=2009.01, thresh=1440) # 24 horas
write.table(events_dd, file="events_dd.txt",quote=F, sep="\t")

Ejemplo:

PASO 8: Eventos acumulados por especies

events_hh_species <- colSums(events_hh)
write.table(events_hh_species, file="events_hh_species.txt", quote=F, sep="\t")

Ejemplo:

events_dd_species <- colSums(events_dd)
write.table(events_dd_species, file="events_dd_species.txt",quote=F, sep="\t")

Ejemplo:

PASO 9: Eventos acumulados por cámara-sitio

cameras <- rowSums(events_hh)
write.table(cameras, file="events_species.txt",quote=F, sep="\t")

Ejemplo:

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DIFERENTES ANÁLISIS

PASO 10: Cálculo de la ocupación naive

yr2009 <- data[data$Sampling.Event =="2009.01" & data$Class=="MAMMALIA",]
mat <- f.matrix.creator(yr2009) 
naive_occu_2009 <- naive(mat) # naive occupancy
write.table(naive_occu_2009, file="naive_occu_2009.txt",quote=F, sep="\t",row.names = F)

Ejemplo:

PASO 11: Curva de acumulación

accumulation <- acc.curve(data,2009.01)
write.table(accumulation, file="accsp_2009.txt",quote=F, sep="\t")

Ejemplo:

ggplot(accumulation, aes(x=Camera.trap.days, y=species)) +
  geom_line(aes(y=species-sd), colour="grey50", linetype="dotted") +
  geom_line(aes(y=species+sd), colour="grey50", linetype="dotted") +
  theme_bw() +
  geom_line()

PASO 12: Patrón de actividad de especies

activity_24h <- events.hours(yr2009)
write.table(activity_24h, file="events_24hour_2009.txt",quote=F, sep="\t",row.names = F)

Ejemplo:

####activity_24h <- events.hours(data)

clock <- c(0:23) 
clock24.plot(activity_24h$Cephalophus.harveyi,clock,show.grid=T,lwd=2,line.col="blue", main="Cephalophus.harveyi",cex.lab=0.5)

par(mfrow=c(1,3),cex.lab=0.5, cex.axis=0.5)
clock24.plot(activity_24h$Cephalophus.spadix,clock,show.grid=T,lwd=2,line.col="green", main="Cephalophus.spadix")
clock24.plot(activity_24h$Cephalophus.harveyi,clock,show.grid=T,lwd=2,line.col="blue", main="Cephalophus.harveyi")
clock24.plot(activity_24h$Nesotragus.moschatus,clock,show.grid=T,lwd=2,line.col="red", main="Nesotragus.moschatus")

PASO 13: Mapa de dos especies

shape <- readShapeSpatial("park.shp", repair=T)
## Warning: use rgdal::readOGR or sf::st_read

## Warning: use rgdal::readOGR or sf::st_read
ev.dd.map <- merge(unique(data[,c("Sampling.Unit.Name","Longitude","Latitude")]),events_dd)
coord <- ev.dd.map[,c("Longitude","Latitude")]
xy <- project(as.matrix(coord), "+proj=utm +zone=37 +south +ellps=clrk80 +units=m +no_defs")
ev.dd.map$Longitude<-xy[,1]
ev.dd.map$Latitude<-xy[,2]

par(mfcol=c(1,2), mar=c(0.5,0.5,0.5,0.5), oma=c(1,1,1,1))
plot(shape,axes=F)
mtext("Rhynchocyon cirnei", cex = 1.5,font =3 )
Rc <- ev.dd.map[,c("Rhynchocyon cirnei")]/max(ev.dd.map[,c("Rhynchocyon cirnei")])
points(ev.dd.map[,"Longitude"],ev.dd.map[,"Latitude"],pch = 21,bg=grey(1-Rc))

plot(shape,axes=F)
mtext("Rhynchocyon udzungwensis",cex = 1.5, font =3)
Ru <- ev.dd.map[,c("Rhynchocyon udzungwensis")]/max(ev.dd.map[,c("Rhynchocyon udzungwensis")])
points(ev.dd.map[,"Longitude"],ev.dd.map[,"Latitude"],pch = 21,bg=grey(1-Ru))

PASO 14: Tabla general de resultados.

resultados <- read.csv(file="Tabla_final.csv", sep=",",h=T,stringsAsFactors=F)

Tabla 4. Resultados generales por especie. Se presenta: eventos (por hora y 24 h), esfuerzo de muestreo, índice de abundancia relativa (RAI), número de sitios con cámaras, total de sitios, y ocupación naive.

Especie Eventos_hh Eventos_dd dias_muestreo RAI_hh RAI_dd Naive_occu
Atilax paludinosus 3 3 1818 0.17 0.17 0.05
Bdeogale crassicauda 130 126 1818 7.15 6.93 0.74
Cephalophus harveyi 367 281 1818 20.19 15.46 0.86
Cephalophus spadix 60 58 1818 3.30 3.19 0.47
Cercocebus sanjei 73 71 1818 4.02 3.91 0.52
Cercopithecus mitis 22 22 1818 1.21 1.21 0.24
Civettictis civetta 1 1 1818 0.06 0.06 0.02
Colobus angolensis 1 1 1818 0.06 0.06 0.02
Cricetomys gambianus 276 215 1818 15.18 11.83 0.53
Dendrohyrax arboreus 23 23 1818 1.27 1.27 0.24
Francolinus squamatus 4 4 1818 0.22 0.22 0.26
Genetta servalina 18 18 1818 0.99 0.99 0.09
Guttera pucherani 34 30 1818 1.87 1.65 0.12
Hystrix africaeaustralis 11 10 1818 0.61 0.55 0.10
Loxodonta africana 11 10 1818 0.61 0.55 0.03
Mellivora capensis 7 6 1818 0.39 0.33 0.03
Mungos mungo 2 2 1818 0.11 0.11 0.45
Nandinia binotata 2 2 1818 0.11 0.11 0.05
Nesotragus moschatus 114 97 1818 6.27 5.34 0.05
Panthera pardus 8 8 1818 0.44 0.44 0.33
Papio cynocephalus 3 3 1818 0.17 0.17 0.02
Paraxerus vexillarius 46 46 1818 2.53 2.53 0.19
Petrodromus tetradactylus 3 2 1818 0.17 0.11 0.07
Potamochoerus larvatus 18 18 1818 0.99 0.99 0.05
Procolobus gordonorum 5 5 1818 0.28 0.28 0.26
Rhynchocyon cirnei 4 4 1818 0.22 0.22 0.05
NA NA NA NA NA NA

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CONCLUSIONES

La gestión de datos obtenidos con el foto-trampeo, ya sea en programas como Wild.ID o en paquetes R como camtrapR, permiten organizar las miles de fotos en proyectos y carpetas que facilitan su posterior análisis.

En este ejemplo, basado totalmente en el trabajo de Rovero y Spitale (2016), hemos visto cómo a partir de una tabla con formato *.csv, se puede importar en R para la organización, extracción y diferentes análisis de la información.

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REFERENCIAS

Rovero, F. y D. Spitale. 2016. Presence/absence and species inventory. Pp. 43-67, in: F. Rovero & F. Zimmermann (eds.), Camera Trapping for Wildlife Research. Pelagic Publishing, UK.

TEAM Network. 2009. Terrestrial Vertebrate Protocol Implementation Manual, v. 3.1. Arlington: Tropical Ecology Assessment and Monitoring Network, Conservation International.