JOURNAL OF SCIENCE, Hue University, Vol. 67, No. 4A, 2011

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1 JOURNAL OF SCIENCE, Hue University, Vol. 67, No. 4A, 2011 APPLICATION OF PGIS AND ZONATION FOR CONSERVING SAOLA SPECIES IN THUA THIEN HUE AND QUANG NAM PROVINCES, VIETNAM Luong Van Duc 1, Ho Dac Thai Hoang 2, Nicholas Michael Wilkinson 3, Ong Dinh Bao Tri 4 1 Kumamoto University, Japan 2 College of Agriculture and Forestry, Hue University, Vietnam 3 Cambridge University, England 4 WWF Vietnam, Vietnam Abstract. Thua Thien Hue and Quang Nam provinces are recognized by the scientists as an important area for Saola which is an endemic species. However Saola is being on the brink of extinction as a result of hunting and demands for timber as well as non-timber products. This paper presents some studied results on applying PGIS and Zonation conservation planning model in researching the distribution and predicting the priority zones of Saola species in Saola landscape that locates along the southern of Thua Thien Hue and the northern of Quang Nam landscape frontier. Community mapping results revealed the quantity distribution of Saola, Zonation then indicated the priority zones for Saola. From this finding, the robust patrol routes for conserving this species were identified with the area of ha. Keywords: PGIS, systematic conservation planning, Zonation, Saola species, conservation priority zones. 1 Introduction The Saola species is ranked as Critically Endangered by the IUCN [5]. A large number of studies [2],[5], have been implemented to identify the distribution of this species in Vietnam. It seems that the extent of the Saola s occurrence has declined significantly within these provinces over the past 20 years [6]. However, so far our understanding of the distribution of the Saola species as well as its bio-characteristics in the Truong Son has been modest. The latest researches of Nguyen Xuan Dang et al. (2007), WWF Vietnam s database or Green Corridor Project initially made the sketch map in point shape-files or recorded the scatter information identified for the huge areas. Most of these achieved records had been mainly derived from local people s perception without any verification on account of its complication and miscellaneousness. It was clear that these findings were only primary; their accuracy and detail level had to be improved due to the uncertainty of the information. These things hinder efforts of Saola conservationists while the detriment factors to Saola were not depreciated. In this 35

2 scenario, an assessment based on indigenous knowledge and systematic conservation planning model is urgent and essential. The systematic conservation planning model such as Zonation, Marxan and so forth had been applied and achieved the expected efficiency as an optimal choice for selecting a robust solution in order to conserve the endangered species but such application in Vietnam had never been studied in the long run. Based on this information, GIS and Zonation model were applied in order to determine Saola priority zones for patrol. In this combination, the community map on distribution of Saola species was established by using beans as an efficient and flexible tool that expressed local people perception about Saola's abundance. Zonation and GIS then played a decisive role in analyzing, assessing and appraising data quality and output results. 2 Materials and methods Community mapping was carried out two following stages that included making master maps and using it to estimate the abundance of Saola. This process was conducted individually with all villages of Huong Huu, Thuong Long, Thuong Quang and Thuong Nhat communes. As their hunting locations extended as far as the north of Quang Nam, the investigated and map-making areas embraced this method. At stage 1, respondents would be selected from hunters and village patriarchs who had the best knowledge of their forest. At this stage, names of rivers were put on the river map after getting total agreement from all respondents. Also, other pieces of information such as village history and livelihood were collected with semi-structured questionnaires. This is beneficial for the second stage which uses the map. Respondents were required to place beans on the master map with the names of rivers established at the last stage. This latter stage also collected information by getting the description of the appearance and habitat characteristics of serow, sambar, mousedeer, wide pig and muntjacs. Indirectly, this gave valuable information about Saola when some hunters made an unintentional comparison among the resembled features. These descriptions would be compared with the available understanding to eliminate the disturbing information. On the master map, depending on their perception of the abundance of Saola (X) at each location, hunters put beans with more beans where X is higher, fewer beans where X is lower (Fig.1.). Fig. 1. The master map. 36

3 After that, data were digitized and coded in point shape-files enclosed with the attribute record in ArcGIS software. The hydrology toolbox in ArcGIS was applied to generate the stream catchment layers, these catchments represented as polygons. A flow accumulation layer will be created from a 30m resolution. The community mapping data were computed to create the probability shape, converted to ASCII format and imported into Zonation as species distribution files. The uncertainty would be calculated with the data provided in community maps on the areas where villagers visited. Local people were expected to have less accurate information about areas which they visited less often. Uncertain assessment: the simplifying assumption is that all villages have the same competence so the probability that hunters in all villages were correct with question k was calculated according to the following formula: (1) where V 1 is the number of villages that answer 'yes' to question k. V 0 is the number of villages that answer 'no' to that question. Therefore, the total probability that all hunters in all villages are wrong with question is: P 0 =1 P 1 (E k ). Reserve network aggregation: there are four methods for creating connectivity in Zonation model. For conserving Saola, the boundary-quality penalty (BQP) is the most suitable method to connect the proximity compartments which had nearly the same priority value. Two components were used in this method to estimate the response of species to the disaggregation and habitat loss, namely radius size and response curve. At the confident level of 90%, the home range of Saola under limit is 0.198km 2, above limit is 125.8km 2 and the middle value is 4.99km 2. Consequently, radius size of Saola was computed as follows: Radius size = (2) Therefore, buffer size surrounding home-range of Saola species at each grid 200m x 200m will be of 5 x radius size. These values correspond to 1; 18 and 4, respectively. Probability of species distribution: 37

4 (3) where n is number of sites which do not have Saola based on hunter perception. m is number of sites which have Saola based on hunter perception. i=1 if hunter asserted that species exists in that sites; otherwise i=0 The density surface was created from computing P species with search radius (r) by Kernel method. Value of r can be calculated with the following formula: where, r: search radius A: area of surrounding polygon of sites that they usually go forest n: number of beans used for community mapping by hunters. The output was verified with the suitable habitat which had been listed in the previous study [1]. The suitability habitat map had been built from layers such as landcover, elevation, human-derived disturbance areas, slope, road and river. 1. Topography Criteria Slope Table 1. Ranking the selected criteria Altitude 2. Hydrology Distance to rivers 3. Landcover Forest types 4. Human effects Distance to residence Distance to road Classification Suitability Unsuitability >30 0 or <45 0 Suitability 200m-1000m Unsuitability <200m or >1000m Suitability <500m Unsuitability >500m Suitability Unsuitability Suitability Unsuitability Suitability Unsuitability (4) Flowchart of this research is summarized step by step as below: Evergreen forest others >1km <1km >1km <1km 38

5 3 Results and discussion Fig. 2. The flowchart of research. 3.1 Community map on Saola s distribution Fig. 3. Distribution of Saola species. 39

Through interview and mapping, most respondents totally agreed that the number of Saola had dropped dramatically and that at that time they seldom saw it.

Comparing with the latest scientific documents [5], there were 9 records that were of Saola; other footprint records had not been verified.

6 Through interview and mapping, most respondents totally agreed that the number of Saola had dropped dramatically and that at that time they seldom saw it. There were 16 records that hunters met Saola or its signs such as footprints. These places were far from the current places of villagers. Comparing with the latest scientific documents [5], there were 9 records that were of Saola; other footprint records had not been verified. From the distribution of Saola, its probability were computed and illustrated on the map (Fig. 3.). The highest probability areas of Saola are in forest compartment as follow: 352, 12, 13, 347, 429, 430, 182, 183. Based on the factors that threatened Saola identified by hunters as habitat loss, hunting by trap, exploited forest and non-forest product, the corresponding maps were also established and figured out. 3.2 Priority zones solution from running Zonation software There were three basic solutions and thirty-nine others which had been created from sensitive analysis in Zonation model with priority ranks in each solution. By comparing these solutions, the discrepancy identified between the basic solutions (only file splist) and others (including files splist.spp, BQPcurve.txt and UCweight.spp) is 0,218±0,014. This proved that the aggregation and the uncertainty can be significant in confining the disaggregation as well as the uncertainty that resulted from the interview. The summed solution was computed and depicted in the map. Generally speaking, the highest priority zones in Zonation summed solution were almost the same as those in the Saola s suitability habitat map. Iterative Sum High: 39 Low: 0 Fig. 4. The summed solutions with top 25% (left) and top 50% (right) priority areas. 3.3 The robust patrol routes Based on the summed solution, the patrol routes were built with total area of approximately ha. These areas belong to top 25% priority solution. 40

Fig. 5. The priority zones for patrol. These routes comprise of specific subunits which are the forest compartments as tabulated below (table 2). Landscapes Table 2.

7 Fig. 5. The priority zones for patrol. These routes comprise of specific subunits which are the forest compartments as tabulated below (table 2). Landscapes Table 2. The robust patrol routes Forest compartment Saola landscape in Thua Thien Hue province Saola landscape in Quang Nam province 330; 331; 335; 336; 338; 339; 340; 341; 343; 344; 345; 347; 348; 350; 351; 352; 353, 402; 404, 405; 429; ; 13; 14; 35; 36 Suggested area 393; 394; 39; 399; 400; 20; 21; 23 Area total (ha) This result corresponds to a more specific level than the published research in [1][4]. However, as hunters perception could be wrong, this research was carried out by not only basing on hunters indigenous knowledge as the early authors but also taking account of how vulnerable the conserved areas are with the uncertainty of the respondents perception. Therefore, the final solution for zoning would be optimal 41

8 which was obviously considered as robust solution. With the desired uncertainty of hunters perception, the robust solution was created which would not compromise the hot spot on Saola diversity. This was not given the attention in the previous research in [1] [2] where the results only identified the huge conserved areas on provincial or district level resulting in difficulty in patrol. At the same time, the final results have identified the researched location with a variety of priority hierarchies which supplied more solutions for conservation depending on the available staff and facilities. In this research, top 25% of area was selected aiming to identify the most important forest compartments. Moreover, its compatibility with the suitable habitat characteristics was examined. This ensures the result would be more reliable and effective for forest rangers in patrol with more concentrated routes. Creating the linked corridor of the proximity forest compartments by BQP smooth function, Zonation have proved its effectiveness in preventing the separation of the priority zones which is one of reasons that affected Saola. By this way, some of the forest compartments should be paid attention to in establishing Saola landscape in the north of Quang Nam such as the compartments of 12, 13, 14, 20, 21 and Conclusions The following results have been obtained: 4.1. The Saola distribution map has been built and the density surface map showed the highest probability areas in the following forest compartments: 352, 12, 13, 347, 429, 430, 182 and Aggregation and uncertainty can be significant in confining the disaggregation as well as the uncertainty resulting from interview Top 25% priority solution was found including forest compartments of 36 (accounts for ha) It is necessary to carry out systematically the other solutions such as gene technology, awareness raising and strategy for supporting patrol in order to conserve Saola Community mapping, GIS and Zonation systematic conservation planning model are useful for selecting the robust solution in conservation. Acknowledgment. The authors gratefully acknowledge the contributions of Dr. Pham Khac Lieu for his valuable comments on our work. This research was financed by Darwin project

9 References 1. Nguyen Xuan Đang, Dang Ngoc Can, Ha Van Tue, Do Huu Thu, Nguyen Truong Son, Dang Huy Phuong, Ha Quy Quynh, Nguyen Minh Tam, Nguyen Thi Phuong Trang, Trinh Viet Cuong, Nguyen Xuan Nghia, Do Tuoc, Current status and characteristic of Saola species (Pseudoryx nghetinhensis), Vietnam Technology and Science Institution, Hanoi, Hoang Ngoc Khanh, Saola conservation in Thua Thien Hue province, Proceeding of the Rediscovering the Saola - a status review and conservation planning workshop, Nghe An, Kremen C., Cameron A., Moilanen A., Phillips S., Thomas C.D., Beentje H., Dransfeld J., Fisher B.L., Glaw F., Good T., Harper G., Hijmans R.J., Lees D.C., Jr. E.L, Nussbaum R.A., Raxworthy C.J., Razafimpahanana A., Schatz G., Vences M., Vieites D.R., Wright P.C., Zjhra M.L, Aligning conservation priorities across taxa in Madagascar, a biodiversity hotspot, with high-resolution planning tools, Science, 320, (2008), Margules C.R. and R.L Pressey, Systematic conservation planning, Nature, 405, (2000), Timmins R.J., Robichaud W.G., Long B., Hedges S., Steinmetz R., Abramov A., Do Tuoc and Mallon D.P., Pseudoryx nghetinhensis, In: IUCN IUCN Red List of Threatened Species, Version , Wilkinson N., Long B., Minh Hoang, Status of the southernmost population of Saola Pseudoryx nghetinhensis in Thua Thien Hue and Quang Nam provinces, Vietnam-A critical review of existing evidence with recommendations for future conservation and research, Un-published report,

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