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Using GIS for carnivores distribution mapping in fragmented landscape
Yu-Ching Lai, Kurtis Jai-Chyi Pei, and Kai Yuen Suen
Introduction
For wildlife management, the ability to model spatial distribution and changes in distribution of wildlife is of considerable importance. Once spatial distribution can be adequately modeled, the distribution and abundance can be monitored efficiently over time, and future changes can be predicted. These spatial characteristics and relationship are often difficult to identify and hard to display with traditional ground survey or statistical model. Therefore, using Geographic Information System (GIS) has become an evitable trend in ecology studies and developing wildlife habitat model (Rickers et al. 1995). The characteristics of spatial analysis and spatial display of GIS not only provides efficient way of data handling, storage, and analyzing, more importantly, it also enables mapping of wildlife distribution, identification of patterns, and generation of habitat spatial characteristics, hence, a useful tool in decision making for conservation and wildlife management (Scott et al.1992, Aspinall and Veitch 1993, Buckland and Elston 1993, Long et al. 1993, Ji-Wei and Clinton 2000, Lenton et al. 2000).
Auto-trigger camera has been used successfully in mammal survey worldwide to avoid possible inconsistency induced by weather, different investigators, limiting detective abilities of researchers at night, and etc. (Gysel and Davis 1956, Dodge and Snyder 1960, Carter and Slater 1991, Jones and Raphael 1993, Kucera and Barrette 1993, Pei et al. 1997). It has also been used in wildlife study to generate their activity patterns (Pearson 1960, Carley et al. 1970, Pei 1995, 1998), spatial distribution patterns (Pei et al. 1997, Pei 1999), and to estimate population density (Karanth 1995, Karanth and Nichols 1998, McCullough et al. 2000, Pei 2001b). It has the advantages of recording secretive animals, especially those do not leave prominent signs, and collecting data day and night in a more standardized and consistent way than most traditional methods (e.g., trapping, sign-searching, transect line, etc.)
In this study, the applicability of using the existed GIS technique coupled with field survey data from auto-triggered cameras were assessed for carnivore distribution mapping in fragmented landscape of Hong Kong Special Administration Region (the Hong Kong SAR).
Material and Methods
Auto-trigger cameras were used to conduct carnivores survey from October 2001 to March 2002. A total of 100 auto-trigger cameras were distributed randomly in 16 country parks and 1 special area of Hong Kong SAR according to the size of the country parks and their habitat diversity. Each auto-trigger camera was installed 1.5 to 2.5 meters above ground and their locations were recorded using GPS receiver. Depending on the abundance of the carnivores, film and battery was collected and replaced every 2 to 4 weeks.
Relative abundance, distribution pattern, and activity pattern for each species were generated from the field survey. The relative abundance for each species was represented by the Occurrence Index (OI = the number of pictures taken per 1,000 camera working hour). Serial pictures belong to the same individual taken during a short period (usually within 30 minutes) will be considered only 1 picture in the calculation to prevent the over-representative of a lingering individual, hence, to reduce the possibility of over-estimation of the abundance for the species. Camera working hours for each roll of film was the time span between the starting time of a new roll of film and the time recorded on the last picture in the case of the film was finished before the next checking by the researchers, or the time when the researchers arrived for collecting the film, in the case of the film was not finished. Comparisons were made both among species and within species among the different country parks and special area.The spatial distribution pattern for each species in Hong Kong SAR was generated using GIS. The map of country parks and special area were generated from the 1/20,000 Hong Kong base map using ArcView 8.1 software package (ESRI 2000). Range maps of each species were generated using the 17 study areas boundaries for distribution mapping. To understand the variation of the carnivore richness among the 17 study areas, a richness distribution map was produced based on the total number of carnivores species recorded in each study areas.
The level of OI-value for each species in each study areas was adapted to provided the information of the abundance for each species in study areas and to show the general distribution pattern for each species. To avoid arbitrary classification and unequal probability of occurrence due to different activity pattern of different species, the OI-values were grouped into 5 classes based on their distances to the mean, i.e. mean ± 0.5 std., <mean – 0.5 std., mean + 0.5 std. to mean+ 1.5 std., mean + 1.5 std. to mean +2.5 std., and >mean + 2.5 std. as levels of abundance to be “medium”, “low”, “abundant”, “high”, and “very high” respectively.
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