Figure 1.
Map of the study area in the Tokyo metropolitan area of Japan.
Survey grids were set in the Tama Hills (T1–T4) and on the Boso Peninsula (B1–B6), and 12 to 16 camera-trapping sites were placed in each grid.
Table 1.
Summary of camera-trapping at the study sites.
Figure 2.
Surrounding land use of the camera-trapping sites.
Principal component analysis of the camera-trapping sites was performed based on land use (forest, agricultural land, open habitat [grassland and golf course], and urban area). Land use in five buffer sizes (500-, 1000-, 2000-, 4000-, and 8000-m radius) for each site were combined into one dataset (sites × land uses), and each study site appears five times on this graph. With this analysis we were able to calculate the PC1 value, which represented the position within the urban–rural–forest landscape gradient, of a single site at various spatial scales.
Figure 3.
Land-use ratio along the urban–rural–forest landscape gradient.
PC1 is the first component of the principal component analysis for camera-trapping sites based on land use (Figure 2).
Figure 4.
Number of grids in which each mammal species was found.
An asterisk indicates a nonindigenous species.
Figure 5.
Mammal species occurrence along the urban–rural–forest landscape gradient.
Regression curves (Table 2) and 95% confidence intervals (a 2000 iteration bootstrap, shown as dashed lines) are shown. PC1 is the first component of the principal component analysis for camera-trapping sites based on land use (Figure 2); a larger PC1 value indicates forest landscape, a smaller value indicates urban landscape, and an intermediate value indicates rural landscape (Figure 3). In this analysis we assumed average values of regression coefficients for season and local topography (Table 2). The best buffer size models are shown.
Table 2.
The lowest AIC model for predicting the occurrence of each species for each buffer size (500-, 1000-, 2000-, 4000-, and 8000-m radius).
Figure 6.
Mammal assemblages in the three landscapes.
Mammal occurrence probabilities (by one camera within one day) are shown against species body weight [51], [52]. Open square indicates predicted value by the best model (Figure 5), and vertical bar indicates the range of the 95% confidence interval. In each graph, the position of the Asiatic black bear, Japanese serow, and red fox are the observed value; we could not obtain regression models of these species due to their rarity.