Vegetation Analysis and Carbon Sequestration in Forest Soils of Different Zones in Uttara Kannada District through Geo-informatics Approach.

Transcription

1 Vegetation Analysis and Carbon Sequestration in Forest Soils of Different Zones in Uttara Kannada District through Geo-informatics Approach. Dr.A.G. Koppad Professor and Head (NRM) Department of Natural Resource management, College of Forestry, Sirsi , Abstract: The study was taken up in Transitional, Hill and Coastal zone of UK districts during the year The study area lies between ' N to ' N Latitude and ' E to ' E Longitude. The IRS P6 LISS-III imageries were used for estimating the area under different land use land cover classes using ERDAS software with ground truth data collected from GPS. The land use land cover classes viz., Dense forest,, Horticulture plantation, Sparse forest, forest plantation, open land and Agriculture land were identified in supervised classification. According to the land use systems, soil samples at one meter depth were collected and soil organic carbon (SOC) was estimated. The result indicated that the SOC in soils of different land use classes are significantly different. The total and average SOC in Mundgod taluka was million tonne and 136 t/ha respectively, similarly in Sirsi and Kumata taluka were million tonne, 109 t/ha and 8.00 million tonnes, 144 t/ha respectively. Among the different land use land cover classes, dense forest sequesters more SOC e.i. In transitional zone 206 t/ha, hill zone 164 t/ha and in coastal zone it is 179 t/ha, which is followed by horticulture plantation and sparse forest. It is concluded that transitional zone contribute more in sequestering the SOC followed by coastal and hill zone dense forest an horticulture plantation. Least SOC was found in agricultural land, hence forest cover play an important role in sequestering atmospheric carbon and helps in mitigating climate change. Key words: GPS, GIS, remote sensing, imageries, LULC, SOC. I. Introduction Global warming is become a problem for the society due to carbon emission in the wake of modernization and urbanization. Global surface temperature has increased by 0.8 _C since the late nineteenth century and 11 out of the 12 warmest years on record have occurred since 1995 [1]. The B.S.Janagoudar Director of Research University of Agricultural Sciences, Dharwad dr@uasd.in soil plays a vital role in global carbon cycle, Carbon (C) stored in soil is times higher than that of plants [2] and two to three times more than the atmospheric CO2 [3]. Soil organic carbon (SOC) stock acts as a major part of the terrestrial carbon reservoir with a storage of about 1,500 Pg to 2,000 Pg C (1 Pg ¼ 1015 g, or 1 Pg ¼ 1 billion tonnes) in the top 100 cm depth layer in the world soils [4].Land use land cover changes directly affect the carbon sequestration rate in soil [5] and other factors including climate, vegetation type, topography and anthropogenic activities [6]. Forest and Forest soil play an important role in the global carbon balance [7]. The sequestered carbon finally acts as a sink in the forest land [8]. Through the process of photosynthesis, plants assimilate carbon and return to the soil as litter and stored as soil organic matter [9]. The remote sensing technologies are being used for preparation of land use land cover (LULC) map and area estimation under different land use practices. Geographical information system (GIS) technology is useful for spatial analysis and preparation of SOC distribution map with the help of ground truth data collected from GPS. The present study is an attempt to estimate the carbon sequestration stock in forest soils of various land use land cover system in transitional, hilly and coastal zone of Uttara kannaa district of Karnataka. II. Materials and Methods: The study area showing the different zones and taluka place in each zone of UK district is given in figure 1 and 2. The Toposheets covering the study area with scale 1:50,000 were procured from SOI Bangalore. IRS LISS-3 satellite image path 097 row 063 dated 22 January 2010 spatial resolutions with 23.5 x 23.5 meter procured from NRSC Hyderabad. The images were processed using ERDAS IMAGINE 2011 and classify the land use land cover map and spatial analysis of SOC was done using IDW technique in Arc GIS 16

2 10. The ground truth data was collected with GPS and the land use land cover was classified using supervised classification technique. sampler was used to collect the soil core at different depth for estimating the bulk density. SOC was determined using Walkley and Black rapid titration method [10]. The % of SOC value obtained from the WB method was multiplied by standard correction factor of 1.32[11] to obtain the corrected SOC. SOC % = (BTV-STV) x 0.5N FASx0.003 x 100/wt. of soil Total SOC (tones) = SOC % /100* BD (t/m 3 )*area (m 2 )*depth of soil (m) BTV= Blank titrated value, STV= Sample titrated value, FAS=Ferrous Ammonium Sulphate BD= Bulk density. Fig.1 Zonal map of UK district Fig 3. Flow chart of methodology used. The detailed methodology followed for the preparation of land use land cove map and SOC pool map is given in fig 3. III. Result and Discussions: Fig.2 Taluka places in each zone of UK district Soil samples were collected from different land use land class area viz., Dense forest, horticulture plantation, sparse forest, forest plantation, open land and agriculture land. While taking the samples the land terrain was considered. In sloppy land the number samples were taken along the slope from top to bottom and in case of flat land grid at equidistance were followed and representative soil samples were collected. The soil sample spot latitude and longitude was recorded with GPS. The soil sample to the depth of one meter was taken using soil screw auger and core The area, SOC %, SOC pool and average SOC according to land use and land cover class wise is given in table 1. The results indicated that total the average SOC in transitional zone is more (136 t/ha) followed by coastal zone (144 t/ha) and hill zone (109 t/ha). Among the land use land cover classes, dense forest sequester more SOC (206 t/ha) followed by horticulture plantation (162 t/ha) and forest plantation (145 t/ha) and very least carbon was sequestered in agricultural land (85 t/ha) in transitional zone of UK district. Similarly in Sirsi taluka representing the hill zone indicated that dense forest sequester more SOC (164 t/ha) followed by horticultural plantation and sparse forest. Similarly in coastal area also dense forest sequester more soil carbon (179 t/ha) followed by sparse forest and open land (table 1) as per the land use land cover classes. As per the GPS ground truth data land use land classes are prepared in the ERDAS and Arc GIS software land use land cover class and average SOC pool in tonnes per hectare is given in figure 4 and 5 respectively for Mundgod taluka, in figure 6 and 7 for Sirsi taluka and in figure 8 and 9 for Kumata taluka which are representing the transitional, hill and coastal zone of UK district respectively. 17

3 The results indicated that transitional zone found to influence the carbon sequestration in soil significantly higher followed by coastal zone and hill zone. This variation must be due to the higher leaf litter fall in transitional zone because all deciduous forest tree species are found in transitional zone. In hill zone consists of mostly undulating area soil erosion is the main problems, there is more chances of leaf litter transport due to high rainfall and subsequent runoff, hence there is less chances of in-situ carbon sequestration in soil. In dense forest mostly lot of barrier for runoff flow, hence only in dense forest area more SOC sequestration was noticed compared to other type of forest/vegetation. In coastal area, the SOC sequestration is in between transitional and hill zone as it has both favorable and unfavorable conditions for SOC sequestration The carbon mitigation potential of dense forest is higher mainly due to higher leaf litter fall and microbial activities which creates more soil organic content [12]. Table 1.Area,SOC pool according to land use land cover classes in different taluks of UK district Fig. 4. Land use land cover Map of Mundgod Taluka Fig. 5.SOC Pool Map of Mundgod Taluka 18

4 Fig. 6. Land use land cover Map of Sirsi Taluka Fig. 8. Land use land cover Map of KumatTaluka Fig. 7. SOC Pool Map of Sirsi Taluka Fig. 6. SOC Pool Map of Kumata Taluka IV. Conclusion: The dense forest with mixed tree species sequesters more carbon than plantations of mono species. The carbon depletion in soil is more in spare forest and 19

5 open land due to deforestation and degradation of forest. The remote sensing techniques including GPS and GIS are most suitable for acquiring current data about land use land cover. The forest cover must be maintained to sequester more atmospheric carbon in to the soil. The study indicated that transitional zone in UK district found to sequester more atmospheric carbon in soil compared to hilly and coastal zones. Acknowledgement : Authors gratefully acknowledge the Department of Science and Technology, New Delhi for providing the financial support for conducting the research study in Uttara Kannada district. [10]. A. Walkley and I.A. Black. An examination of Degtjareff method for determining organic carbon in soil: effect of variation in digestion condition of inorganic soil constitution. Soil Sci : [11]. De Vos B., Lettens S., Muys B and Deckers J. A.. Walkley-Black analysis of forest soil organic carbon: recovery, limitation and uncertainty. Soil Use Manage., , [12]. R.T., Conanat, K. Paustian,. and E.T.. Elliott, Grassland managment and conversion into grassland: effect on soil carbon. Ecol.Appl : ,. References: [1]. IPCC. Climate change Climate change impacts, adaptation and vulnerability. In Working Group II 2007 Geneva, Switzerland: IPCC [2]. W.M Post, T.H, Pengh, Emanuel, W, King, A.W, Dale, V.H, Delnglis,. The global carbon cycle.am Sci : , [3]. E.A., Davidson S.E Trumboe. and R Amudson. "Soil Warming and organic carbon content". Nature : , [4]. Yu J, Wang. Y, Li Y. Soil organic carbon storage changes in coastal wetlands of the modern Yellow River Delta from 2000 to Bio-geosciences 20129:2 : ,. [5]. R. Lal, Soil carbon sequestration to mitigate climate change. Geoderma :1 22,. [6]. D.F. Baker, Reassessing carbon sinks. Science 2007,316: ,. [7]. Kuldeep Pareta and Upasana Pareta "Forest carbon management using satellite remote sensing techniques A case study of Sagar district" E-International Scientific Research Journal, Vol-III, Issue-4, ISSN- 2011, ,. [8]. Ramchandran A, Jaykumar S, and Haroon R.M. Carbon sequestration: estimation of carbon stock in natural forest using geospatial technology in the Eastern Ghat of Tamil Nadu, India. Current Sci 2007,.92(3): , [9]. S. S. Negi. and M. K. Gupta. "Soil Organic Carbon Store Under Different Land Use Systems In Giri Catchment Of Himachal Pradesh" The Indian Forester 2010.Vol. 136 No , 20