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:
- realizar inventarios,
- estimar la abundancia de diferentes especies,
- calcular índices de abundancia relativa,
- estimar la ocupación,
- evaluar el uso de hábitat,
- conocer patrones de actividad,
- 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
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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.