Presence/Absence Point Records of Japanese Serow (Naemorhedus crispus) with Environmental Predictors in the Fuji-Tanzawa Region, Japan

Doko, T.^*  Chen, W. B.

Keio Research Institute at Shonan Fujisawa Campus (SFC), Keio University, Fujisawa, 2520882, Japan

Abstract: The Japanese Serow (Naemorhedus crispus) is endemic to Japan, and has been de- signated as a Japanese natural monument. We produced a total of 319 point records of Japanese Serow occurrence (160 presence records and 159 absence records), with data for 14 environmental predictors. The environmental predictors were altitude, slope, annual precipitation, annual maximum temperature, annual minimum temperature, distance to rivers, distance to all roads, distance to highways, distance to general roads, distance to paths and stone steps, distance to wide roads (>13 m), distance to narrow roads (≤13 m), the normalized difference vegetation index), and the vegetation cover types at the vegetation community level. The data formats were CSV format (.csv), Google Earth (.kmz), and Arc/Info (.shp). The projected datum was the Japanese Geodetic Datum 2000. The spatial resolution of raster data used to produce the dataset was 50 m. The data size was 43 KB for CSV (.csv), 29 KB for Google Earth (.kmz), and 249 KB for Arc/Info (.shp) format.

Keywords: Fuji-Tanzawa region; Japan, species records; Japanese Serow; point data

1 Introduction

The Japanese Serow (Naemorhedus crispus) is endemic to Japan (Figure 1). The species inhabits montane regions of Honshu, Shikoku, and Kyushu^[1]. Once overhunted for meat and fur, it became so rare that the government of Japan declared it a national treasure^[2]. It has subsequently been designated a Japanese natural monument. Since then, its population has recovered^[2].

We produced a total of 319 point records of Japanese Serow occurrence (160 presence records and 159 absence records), with data for 14 potential predictors.

Figure 1  Photographs of Japanese Serow

2 Metadata of Dataset

The metadata regarding Japanese Serow occurrence, together with the data for the environmental predictors in the Fuji-Tanzawa region in Japan (“JpSerow_env_FT”)^[5] are listed in Table 1 (Japanese Serow occurrence with data for environmental predictors in the Fuji-Tanzawa region in Japan (“JpSerow_env_FT” for short)).

3 Methods

A full description of the method can be found in the work of Doko and Chen^[1] and Doko^[7]. Here, we summarize the main methods used to produce the dataset.

3.1 Study Area

The study was conducted in the Fuji and Tanzawa region of Japan (35°10¢ to 35°40¢ N and 138°30 to 139°20¢ E in Japanese Geodetic Datum 2000, Figure 2). The study area is mountainous and includes Fuji National Park, as well as Tanzawa Quasi-National Park. These parks contain various landscapes and are characterized by a very high biodiversity, including the occurrence of a number of endemic species^[1,9].

3.2 Extraction of Species Records

First, a map containing the 160 observed point localities for Japanese Serow in the Tanzawa region^[3] was scanned. This map was created based on questionnaires and interviews with surveyors from the Research Group of the Tanzawa Mountains (57 respondents), whose research was conducted from 1993 to 1996, nature guides from prefectural parks (100 respondents), members of nature conservation groups (32 respondents), mountaineering associations (72 groups), and other respondents^[3]. These selected respondents were considered to represent people likely to have knowledge and information regarding Japanese Serow in the Tanzawa Mountains. The purpose of this activity was to collect information regarding the Japanese Serow inhabiting the Tanzawa Mountains, because the distribution and habitat of this species in Tanzawa was completely unknown^[3]. The extent of the map included the entire area of the Tanzawa region.

Table 1  Japanese Serow occurrence with data for environmental predictors in the Fuji-Tanzawa region in Japan (“JpSerow_env_FT” for short)

The scanned map was then geo-referenced. The map was suitable for georeferencing, with the locations of rivers identified in the map so that authors could find ground control points easily. A first-order polynomial affine transformation was applied to rectify the scanned

image. The associated root mean square (RMS) error was 251 m. Based on the rectified image, 160 points were digitized manually. Geographic coordinates were calculated by ArcMap^®.

Due to the lack of accurate absence data for the Japanese Serow, absence data were obtained from a national distributional map of Japanese mammals^[10] using a previously described method^[9]. A total of 160 absence points was generated. The national distribution map of Japanese mammals is composed of grid cells measuring 5×5 km² across Japan. However, instead of using grid cells directly, this method plots random points inside the polygons where no serows were observed between 1978 and 2003. Hence, the spatial resolution of the absence points was considered to be comparable to the presence data.

3.3 Geo-database for the Environmental Predictors

Based on the known ecology of the Japanese Serow^[3,11–13], the following environmental

Figure 2  The study area of the Fuji-Tanzawa region, Japan (DEM = digital elevation model)

predictors, which can potentially influence the serow’s distribution, were selected: altitude, slope, annual precipitation, annual maximum temperature, annual minimum temperature, distance to rivers, distance to all roads, distance to highways, distance to general roads, distance to paths and stone steps, distance to wide roads (>13 m), distance to narrow roads (≤13 m), the normalized difference vegetation index (NDVI), and the vegetation cover types at the vegetation community level. A threshold value of 13 m was used for the road width, because this would encompass two or more lanes, and it was assumed that it would be difficult for animals to cross such a road.

Precipitation data were derived in ESRI (Redlands, CA, USA) grid format at a resolution of 1 × 1 km² (30 arc-seconds) from the WorldClim database^[14]. The annual precipitation was calculated from the precipitation data for 12 months. The minimum and maximum temperature were derived from the WorldClim database. The annual minimum and maximum temperature were calculated. The NDVI was derived from the red:near-infrared reflectance ratio. NDVI = (NIR-RED)/(NIR+RED), where NIR and RED are the amounts of near-infrared and red light, respectively, that are reflected by the vegetation and captured by the sensor of the satellites. NDVI values range from -1 to +1, where negative values correspond to an absence of vegetation. All variables were obtained digitally from various sources (Table 2) and stored in a geographic information system (GIS) environment. Considering the relatively small size of important landscape elements in the Japanese landscape and the high precision of the species records, all predictor variables were compiled at a resolution of 50 × 50 m². Erdas Imagine^® 8.7 was used to calculate NDVI values. ArcGIS^® 9.3 was used for the other variables.

Table 2  Potential environmental predictors of Japanese Serow

The image processing procedures specified in the paper^[9] were applied.

When 320 records were plotted in ArcMap 9.3^® with other environmental variables, one absence record fell outside the study area. This record was discarded from the species data, and the total number of records became 319. Pixel values were extracted from all layers of environmental predictor variables by ArcMap 9.3^® to obtain the geographic coordinates of the records of presence and absence.

Figure 3 shows a flow chart of JpSerow_env_FT data production. Table 3 describes the

Figure 3  Flow Chart of the dataset development

Table 3  Description of the JpSerow_env_FT data

^*1 Note. 1 means presence, 0 means absence.

^*2 Note. Vegetation cover types are coded by four digits.

meaning of the columns in the JpSerow_env_FT database. Table 4 provides an additional explanation of the meaning of the vegetation code (VEG) in Table 3.

Figure 4 shows Japanese Serow records, with an ESRI satellite imagery basemap, and roads

Table 4  Look-up-table for the vegetation code [VEG] and its meaning

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^*1 Note: The four-digit vegetation code [VEG] is equivalent to “MAJOR1” in the Japanese standard classification legend of the second to fifth vegetation maps prepared by the Ministry of Environment (See http://vegetation.jp/qanda/ xls/hanrei-taiou. xls)^[15].

Figure 4  Map of Japanese Serow records, with an ESRI satellite imagery basemap, and roads and boundaries and boundaries. The point records indicated as Japanese Serow records (red and yellow triangles) in the map are available as a dataset through this study. Other items such as major mountains, wide roads, highways, boundaries as well as ESRI satellite imagery basemaps were not included in the dataset.

4 Dataset Quality Control and Validation

The dataset has been validated by researchers from Keio University in Japan. The associated RMS error was 251 m for a scanned map of Japanese Serow occurrences.

5 Conclusion

This dataset provides a record of presence/absence data for Japanese Serow, which is endemic to Japan, with records associated with environmental predictors. The environmental predictors are altitude, slope, annual precipitation, annual maximum temperature, annual minimum temperature, distance to rivers, distance to all roads, distance to highways, distance to general roads, distance to paths and stone steps, distance to wide roads (>13 m), distance to narrow roads (≤13 m), the NDVI, and vegetation cover types at the vegetation community level.

References

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[15]    Ministry of Environment. “MAJOR1” in the Japanese standard classification legend of the 2nd to 5th vegetation maps [DB/OL]. http://vegetation.jp/qanda/xls/hanrei-taiou.xls.