1. Forest Degradation Assessment in Sri Lanka Raushan Kumar, Forestry Officer, FAO Sri Lanka Nishantha Edirisinghe, Deputy Conservator of Forest Sharat Kulatunga, Additional Conservator General of Forest Date: 16 June 2015

2. Presentation Outline History of forest degradation in Sri Lanka Country approach of forest degradation assessments Results

3. Why Measure and Monitor Forest Degradation In Sri Lanka 82% of the land area is under some form of state control Over the years, state land, under forest cover, has been alienated under various schemes, such as village expansion, regularization of encroachments, special leases, and others. From 1830, vast tracts of forest at middle altitudes were cleared for coffee plantation and were replaced by tea from year 1850, after the coffee plantations were devastated by a leaf-blight. Forest clearance in the dry zone began around 1869, due to introduction of large colonization schemes.

4. Why Measure and Monitor Forest Degradation Since year 1869, the closed canopy (> 70% canopy cover) of natural forest cover has declined rapidly from about 80%, until, in 1999 it was estimated at less than 22%. At the same time, the closed canopy natural forest cover is expected to decline from 22.7% in 1999 to about 17% by 2020, if no planned action is taken. The continuous economic growth and increasing population has influenced the demand for industrial round wood and poles rising from 1.7 million cubic meters in 1995 to 2.0 million cubic meters in 2020. However, the present forest cover of the island is considered to be about 30% of the total land area. Forest degradation results in decline in biomass, carbon sequestration capacity, goods and services received from forest ecosystem Decline in Canopy Cover, Species Richness / Composition Indicator of Forest Degradation

5. Causes of Forest Degradation Sri Lanka Illicit Felling of trees Shifting Cultivation Cattle Damage / Livestock Grazing Illegal Cultivation Encroachment Extraction of gravel, mineral and metal Type of damageUnderlying driversCatalystsInhibitors Degradation of forests Local demand for timber and wood products for household, Industrial and Infrastructure Limitations of monitoring capacity, Political interference, Population growth Forest policies and protected area management, Home gardens, Migration, Community dependence and customary rights

6. Forest Cover %

7. Dense forest (Canopy Cover over 40%)-22% Sparse Forests (Canopy Cover 10-40%)- 7.7 % Forest TypePercentage Lowland Rain Forests1.9 Moist Monsoon Forests1.8 Dry Monsoon Forests17.1 Montane Forests0.7 Sub Montane Forests0.4 Riverine Dry Forests0.0 Mangrove Forest0.2 Savannah Forest1.0 Open and Sparse Forest6.5 Total29.7

8. ParameterFAO 2000FAO 2001, 2006FAO 2003UNEP/ CBD 2001 Forest type Secondary forest Change within the forest Structure Crown cover 10% Species composition Stocking Reduction of capacity to provide Productivity Goods Services Carbon stocks Other functions Time scale long Cause - human- induced Cause - natural Reference state Natural forest Site Carbon stock at initial date Forest Degradation Definition (FAO, FRA, 177)

9. Study Area:Polonnaruwa District, Kandagama Forest

10. Steps in Forest Degradation Assessment in Sri Lanka LANDSAT and Google Image Based Monitoring (NDVI) Tree Density Regeneration Level Species Composition / Richness Instruction to Field Staffs / Field Checks / Primary Selection of Forest Degradation Sites Site Specific ANR Plan Circular Plot, Ground Inventory (Tree, Plants, Shrubs and Seedlings) Causes of Degradation Identification Analysis Forest Degradation Threshold Forest Type Map

11. Results: Forest Degradation Assessment Forest NameDensity Class Per hectare Kandegama Minimum1.6 Average10.8 Maximum68.4 Kumaragalakantha Minimum 10.1 Average 24.2 Maximum 50.5 Meegaswewa Minimum 0.8 Average 9.1 Maximum 132.9 Pimburanththewa Minimum 1.6 Average 18.2 Maximum 130.5 Welweri Minimum 5.1 Average 20.2 Maximum 106.1 Per Hectare Tree Density in Polannaruwa district degraded forest lands Minimum = 1 Maximum = 133 Density Thresholds preparation: 1 to 25 26 to 50 50 to 75 75 to 100 > 100

12. Results: Forest Degradation Assessment Plot IDPlot-1Plot-2Plot-3Plot-4Plot-5Plot-6Plot-7Plot-8Plot-9Plot-10Plot-11Plot-12 NDVI-0.024-0.0370.0390.0120.1060.1260.0840.0360.0070.0530.1330.015 Species Richness 0.002.812.092.553.002.263.002.821.743.203.822.70

13. Results: Forest Degradation Assessment Polonnaruwa District: Area of Polonnaruwa District: 329,300 ha Natural Forest area 134,801 ha Scrub Forest: 16,850 ha Area under forest degradation / restoration: 900 ha Country Level: Country Geographical Area: 6,570,134 ha Total Forest Area: 1,951,330 ha (29.7%) Total Forest Degraded area : Aprox. 160,000 ha (8.2%) They are located both in central highlands (wet zone) and lowland areas (dry zone). Restoration: Species selection is site specific and based on importance and adaptability Site specific disturbances are taken into consideration for species selection Species NameImportance Value Index (IVI) Tharana24.94 Wali Kohu17.82 Welan17.74 Maila15.23 Borathamana14.97 Searae14.24 Milla11.75 Badulla10.59

14. This study indicates, potential use of ground based inventory in combination with remote sensing technology for forest degradation monitoring. Out of total 12 plots 9 shows similar NDVI trends as compared to species richness NDVI and LAI (or other VI depending on country and site) is overall indicator of health of plants whereas species richness indicates diversity and ecosystem health on ground. If Selected Vis and Ecological Indicator if combined together these two have potential to meet goals set in forest degradation definitions for country circumstances. While countries forest departments have their ground force; addition of Remote Sensing increased cost effectiveness of monitoring mechanism Effective institutional arrangement and functional NFI is very essential Conclusion

15. Raushan Kumar Raushan.Kumar@fao.org Thank You Website: http://www.un-redd.orghttp://www.un-redd.org Picture Source: http://www.crisp.nus.edu.sg/~research/tutorial/optical.htm