1. Tiger Habitat Types: Classification of Vegetation Pornkamol Jornburom and Katie Purdham Kwanchai Waitanyakan WCS Thailand Program

2. Outline  Background  Objectives  Data Used  Method Classification Tiger Occupancy Survey  Results  Conclusion

3. FOREST RESOURCES Forest cover 28% of land area Protected area system 15% of land area - National parks (102); wildlife sanctuaries (44) National Forest & Forest plantations ~10% Land Area 513,000 km 2 (198,000 mi 2 ) (larger than California but less than Texas) GENERAL INFOMATION Current population = 64 million Area Background

4. Huai Kha Khaeng WS. Area 2,780 sq.km The major vegetation types - Tropical evergreen forest - Mixed deciduous forest Elevations ranged from 200-1,560 msl. 20 Park ranger stations > 30 villages located around Area Background

5. Classify vegetation type in the HKK area Analyze correlations between tiger occupancy and vegetation types Look into other possible explanations for tiger occupancy (elevation, presence of streams, etc.) Project Goals

6. Landsat 5 (NDVI) – April/May 2011 Landsat 5 (Classification) – 2004 Dry Season Tiger Occupancy Data – November, 2010- May, 2011 Other Spatial Data (DEM, streams, villages) – Department of National Park, Wildlife, and Plant Conservation Data

7. Image classification Methods NDVI – Mosaic Unsupervised Classification – Preprocessed – K means, 9 classes, 15 iterations, convergence threshold of.95

8. NDVI Results Unsupervised Classification

9. Tiger occupancy survey Map Survey Index of WEFCOM Methods

10. Tiger occupancy survey Methods The proportion of sites occupied by species the or “the probability that a site within a groups of sites is occupied” inc orporated with detection probability. - Occupancy - Detection probability Sign-based survey Large landscape

11. Replicate scale  Probability of habitat use 1 2 3 4 5 6 To investigate the tiger’s habitat-use within certain land cover types, each1-km transect was treated as the ‘site’ while the 100-meter segments represented ‘replicates. Methods When a sign of tigers is found at one replicate, successive replicates will have a much higher probability of the tigers being present than those farther away. A single season custom spatial correlation model

12. Methods Forest type NDVI Elevation Streams Village Ranger Station Substrate Ecological variables

13. VariableBSEExp(B) Probability of Occupancy-0.3236.5700.724 -1.4346.5670.238 -0.0826.5870.921 Large prey0.0550.0601.057 Medium prey0.0870.0661.091 Small prey-0.0980.0710.906 NDVI0.2560.0951.292 DEM0.1520.1101.164 Village0.0810.0841.084 Stream-0.1500.0770.860 Distance form Ranger Station-0.0480.0750.953 Forest type: Evergreen Forest-0.2926.5670.075 Forest type: Hill evergreen Forest-0.7886.5700.455 Forest type: Mixed deciduous Forest-0.2116.5660.810 Forest type: Dry dipterocarp Forest-0.0486.5670.954 Forest type: Bamboo Forest-0.4986.5720.608 Detection probability-0.21638.4570.805 Substrate: Soft soil0.15338.4601.166 Substrate: Leaf Litter-0.71738.4550.488 Substrate: Hard soil0.34738.4591.415 Results Estimates of B coefficient estimates for the logit link function

14. Accuracy Assessment Unsupervised classification Field Data Dry evergreen forest Hill evergreen forest Mixed deciduous forest Dry dipterocarp forest Bamboo forest Total Dry evergreen forest550 20112 Hill evergreen forest540192075 Mixed deciduous forest300226200276 Dry dipterocarp forest309270102 Bamboo forest00232025 Total1420415330590 Dry evergreen forest Hill evergreen forest Mixed deciduous forest Dry dipterocarp forest Bamboo forest

15. Discussion and Future Projects Tiger Occupancy Data Landsat 5 More and Better Data Habitat Suitability Map

16. Discussion and Future Projects Khao Nang Ram Wildlife Research Station, Thailand