ecoteach (version 0.1.0)

raccoondog_environment: Raccoon dog activity and environmental factors in China

Description

This dataset contains records of raccoon dog (Nyctereutes procyonoides) detections and other mammal species from camera traps in the Sizuolou Nature Reserve, Beijing, China, along with associated environmental variables. The data was collected from October 15, 2023, to February 29, 2024, covering both autumn and winter seasons. The study examined seasonal activity changes in raccoon dogs and their relationship to environmental and mammalian factors.

Usage

raccoondog_environment

Format

A data frame with 144 rows and 21 variables:

point_id

Camera installation point ID

asian_badger

Number of Asian badger detection events

wild_boar

Number of wild boar detection events

hog_badger

Number of hog badger detection events

leopard_cat

Number of leopard cat detection events

masked_palm_civet

Number of masked palm civet detection events

rock_squirrel

Number of Père David's rock squirrel detection events

raccoon_dog

Number of raccoon dog detection events

red_squirrel

Number of red squirrel detection events

roe_deer

Number of Siberian roe deer detection events

siberian_weasel

Number of Siberian weasel detection events

striped_squirrel

Number of Swinhoe's striped squirrel detection events

tolai_hare

Number of Tolai hare detection events

dist_impervious

Distance from camera to nearest impervious area (meters)

dist_agricultural

Distance from camera to nearest agricultural land (meters)

dist_water

Distance from camera to nearest water source (meters)

dist_roads

Distance from camera to nearest road (meters)

Altitude

Elevation of camera installation point (meters above sea level)

tpi

Topographic Position Index of the camera installation point

Day

Date of detection (days since start of study, October 15, 2023)

Season

Season at time of detection ("Autumn" or "Winter")

Vegetation

Type of vegetation at the camera installation point

Examples

# \donttest{
# Load the dataset
data(raccoondog_environment)

# Basic exploration
head(raccoondog_environment)
summary(raccoondog_environment)

# Compare raccoon dog detections by season
boxplot(raccoon_dog ~ Season, data = raccoondog_environment,
        main = "Raccoon Dog Detections by Season",
        ylab = "Number of Detections", xlab = "Season")
        
# Examine relationship between environmental factors and raccoon dog presence
# Create a binary presence variable
raccoondog_presence <- raccoondog_environment
raccoondog_presence$presence <- ifelse(raccoondog_presence$raccoon_dog > 0, 1, 0)

# Plot relationship with distance to agricultural land
plot(dist_agricultural ~ presence, data = raccoondog_presence,
     main = "Raccoon Dog Presence vs. Distance to Agricultural Land",
     xlab = "Presence (0=Absent, 1=Present)", 
     ylab = "Distance to Agricultural Land (m)")
     
# Examine vegetation types where raccoon dogs were detected
table(raccoondog_presence$Vegetation[raccoondog_presence$presence == 1])
# }