The dataset contains information about points distributed across a small oceanic island (Soares, 2017). In each of these points, a 10-minute count was carried out to record the species presence (assuming 1 if the species was present, or 0 if it was absent). The species' presence/absence is the binary response variable (i.e., dependent variable). Additionally, all sampled points were characterized by multiple environmental variables.
tropicbirdA data frame with 2398 rows and 8 variables:
Point identification
remoteness is an index that represents the difficulty of movement through the landscape, with the highest values corresponding to the most remote areas
land use is an index that represents the land-use intensification, with the highest values corresponding to the more humanized areas (e.g., cities, agricultural areas, horticultures, oil-palm monocultures)
altitude is a continuous variable, with the highest values corresponding to the higher altitude areas
slope is a continuous variable, with the highest values corresponding to the steepest areas
rainfall is a continuous variable, with the highest values corresponding to the rainy wet areas
distance to the coast is the minimum linear distance between each point and the coast line, with the highest values corresponding to the points further away from the coastline
Species presence