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Geospatial technology based diversity and above ground biomass assessment of woody species of West Kameng district of Arunachal Pradesh

Geospatial technology based diversity and above ground biomass assessment of woody species of... FOREST SCIENCE AND TECHNOLOGY, 2018 E–ISSN 2158-0715, VOL. 14, NO. 2, 84–90 https://doi.org/10.1080/21580103.2018.1452797 Geospatial technology based diversity and above ground biomass assessment of woody species of West Kameng district of Arunachal Pradesh Yakhari Kashung, Biswajit Das, Sangeeta Deka, Reetashree Bordoloi, Ashish Paul and Om Prakash Tripathi Department of Forestry, North Eastern Regional Institute of Science and Technology (Deemed to be University), Nirjuli, Arunachal Pradesh, India ABSTRACT ARTICLE HISTORY Received 17 July 2017 Comprehending the prominence of forest carbon in climate change, this study was piloted in different Accepted 8 March 2018 land use of West Kameng district, Arunachal Pradesh, India to record the floristic composition, community characteristics, and above ground biomass (AGB) carbon using random sampling and KEYWORDS geospatial approach. Preliminary field survey was done in 2016. Altogether 45 quadrats (0.1 ha each) Species diversity; community were laid. Total tree richness recorded was 164 species from 49 families. Dominance and frequency composition; geospatial distribution pattern of species revealed heterogeneity in composition with majority species showing technique; satellite data; tree clumped distribution. Plantations showed highest tree density while mixed dense forest showed biomass 2 ¡1 maximum basal area (58.89 m ha ). Estimated AGB were 218.21 ton/ha for mixed dense forest, 84.94 ton/ha for abandoned forest, and 105.09 ton/ha for plantations. Total estimated carbon stocks were 120.01, 46.17, and 57.80 ton/ha for mixed dense, abandoned forest, and plantations, respectively. Predicted average AGB using Geographic Information System (GIS) techniques was 163.25 ton/ha. Field-based AGB was slightly greater than the values observed from satellite data. Findings of the study may be useful for calculating total biomass and carbon stored in the major land cover of the district in particular and region in general. It will also support in future studies for calculating the long-term data on biomass carbon sequestration. Introduction observation, and historical data archives. Recently, there have been tremendous efforts at national to global level on appli- Forest ecosystem of earth surface accounts for 75% of the cation of satellite and field-based data in assessing AGB and gross primary productivity of the earth’s biosphere, and carbon pool (Chhabra et al. 2002; Zheng et al. 2004; Manhas encompasses 80% of the plant biomass. They are the largest, et al. 2006; Gunlu et al. 2014; Wani et al. 2014; Salunkhee complex, and self-regenerating natural resources. They are et al. 2016). considered important for their unique role as major carbon Himalayan ecosystem shows great variability in physiog- sinks because of their capability to capture and store carbon raphy and composition and housings over 51 million people. dioxide from the atmosphere. Thus, maintaining forest bio- These ecosystems are dynamic to the ecological retreat of the mass and sequestration potential is dependent on maintain- Indian landmass, through forest cover, feeding perennial riv- ing forests. However, structure and function of forest ers, hydropower, safeguarding biodiversity, enriching soil ecosystems are changing drastically due to various anthropo- and agriculture, and spectacular landscapes for sustainable genic activities. Forest degradation and deforestation have tourism. The state of Arunachal Pradesh, India (Eastern direct impact on biomass and carbon pool. These activities Himalaya), where the study was carried out, has a geographi- have altered the concentration of greenhouse gases in the cal area of 83,743 km . State biodiversity is very rich support- atmosphere thereby impacting climate and weather condi- ing 20% faunal species of the nation, 4500 flowering plants, tions, biodiversity, food production, and human health. Sev- 400 pteridophytes, 23 coniferous species, 35 variety of bam- eral studies have reported that carbon storage in forests are boos, 20 cane species, 106 Rhododendron taxa, and 500 directly regulated by composition, age, site characteristics, orchid species. Degradation and poor forest management succession, and climatic variation (Chen et al. 2005; Waring have the potential to reduce the carbon stock while sustain- and Running 2007; Gough et al. 2008; Goward et al. 2008). able management can increase the carbon stock. Like other The amount of carbon sequestered by a forest can be esti- parts, eastern Himalayan regions are also exposed to various mated from the biomass accumulated and such database is levels of threat. Hence, there is a need to carry out the studies important for many national developments planning pertain- on spatial and temporal scale on diversity, degradations, ing to productivity and carbon budget. An increase of 0.65– management, etc. for their sustainability. However, the chal- 1.06 C temperature was reported in the fifth assessment lenges remain to find a commonly agreed and scientifically report of International Panel on Climate Change (IPCC). sound methodological framework for accounting for carbon Hence, emphasis was given on control of emission and stock. The study emphasizes on plant diversity, community removal of carbon dioxide from the atmosphere to mitigate characterization, and stand biomass. Findings of the study climate change. Remote sensing and GIS have been used for could be helpful for developing suitable region-specific strate- rapid and consistent assessments of above ground biomass gies by the land use planners. However, topography of the (AGB) and carbon pool because of its coverage, systematic study area is mostly mountainous with steep terrain, hence CONTACT Om Prakash Tripathi tripathiom7@gmail.com, opt@nerist.ac.in © 2018 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, dis- tribution, and reproduction in any medium, provided the original work is properly cited. E-ISSN 2158-0715 FOREST SCIENCE AND TECHNOLOGY 85 limited plots could be established which otherwise would mountainous zone, consisting of a mass of tangled peaks and have given more accurate results. valleys and its altitudinal variability ranges from 115 to 5780 m asl. The district shares an International border with Tibet in the north, Bhutan in west, Tawang district in north- west, and southern border with districts of Assam. The study Materials and methods area has three principle mountain chains, i.e. Sela, Bomdila, Study site and Chaku ranges. The district is rich in biodiversity and is Present study was undertaken in West Kameng district (26 home to the Eaglenest Wild life Sanctuary covering an area 54’ to 28 01’ N latitudes and 91 30’ to 92 40’ E longitudes) of 217 km and Sessa Orchid Wildlife sanctuary with an area of Arunachal Pradesh (Figure 1). The district covers an area of 100 km . There are five major tribes inhabiting in the study of 7422 km accounting 8.86% of total geographical area of area, namely Monpa, Miji, Sherdukpen, Aka, and Bugun. the state. A greater part of it falls within the higher Monpas and majority of inhabitants follow Buddhist religion. Figure 1. Map showing location of the study area. 86 Y. KASHUNG ET AL. E-ISSN 2158-0715 Data acquisition and analysis Vegetation analysis Landsat operational land imager (OLI) satellite (Landsat 8) Total 45 quadrats of 30 m £ 30 m were laid in selected forest data was used (NASA’s public domain). Landsat 8 collects patch (100 m £ 100 m). All individuals (gbh > 30 cm) encoun- data in nine spectral bands with 30 m spatial resolution tered in the quadrats were recorded with their height and girth except band-8 (15 m). Band-wise radiometric calibration at breast height (1.37 m). Coordinates and elevation of the sam- was performed to remove spurious digital number present pling sites were recorded using GPS during the study. Collected in the scene following the process laid down in Landsat 8 specimens were identified with the help of regional floras and user handbook (2016). Images were re-projected to Univer- published literatures. Community characteristics such as fre- sal Transverse Projection followed by layer stacking, sub- quency, density, basal area, spatial distribution pattern, and setting, and extraction of the study area. Land use and land diversity indices were calculated according to Misra (1968), cover map was prepared using supervised classification in Mueller-Dombois and Ellengberg (1974), and Magurran (1988). ERDAS Imagine 9.1 (Figure 2). Based on the classified map, Density-distribution, basal area, and biomass were studied by three major land use types, namely mixed dense forest, determining the number of individuals in different girth classes. abandoned forest, and plantations were selected for detail Non-destructive approach of AGB estimation was adopted for studies. estimating biomass and carbon. Figure 2. Flow chart of geospatial mapping. E-ISSN 2158-0715 FOREST SCIENCE AND TECHNOLOGY 87 Biomass and carbon estimation distribution pattern of species. Such forest composition does not allow dominance of a species. However, in abandoned Standing volume was estimated using diameter at breast and plantations, it showed that a few species dominated the height (dbh) and height of trees as an input in volumetric community which could be due to disproportionate sharing equations for existing tree species. In case of unidentified spe- of resources among the plant species. Maximum tree density cies and species with no species-specific equations, common was observed in plantations followed by mixed dense and equation for Arunachal Pradesh (Tirap) was used. Further, abandoned forests. Greater basal area was observed in mixed estimated volumes were converted into dry biomass by using forest mainly due to presence of larger number of individuals specific gravity or wood density (FSI 1996). AGB carbon having more girth (Table 1). Density-girth class distribution stock was estimated by assuming that the carbon content in pattern showed a gradual decrease in number of individuals wood is 55% of the total AGB (MacDicken 1997). Biomass with increase in girth in all the selected areas (Figure 3(a)). was also estimated using remote sensed data through four widely used vegetation indices, namely normalized difference vegetation index (NDVI; Rouse et al. 1974), difference vege- Above ground biomass and carbon tation index (DVI; Tucker 1979), soil adjusted vegetation AGB and carbon distribution in different girth class showed index (SAVI; Huete 1988), and red reflection band. Based on reverse trend to that of density distribution. Study showed the results of linear regression analysis of different indices, that the lower girth class (<75 cm gbh) contributed to 64%– best-fit model was used for spectral modeling of biomass of 74% of the stand density while only 17% to biomass and car- the study area. Various steps to study community character- bon. However, 47% biomass was contributed by higher girth istics, biomass, and carbon stock are presented in Figure 2. class (>151 cm gbh) although they represented 1%–8% of the total density (Figure 3(b)). Total AGB of selected land use showed maximum in mixed dense forest (218.21 ton/ha) Results followed by plantations (108 ton/ha) and abandoned forest Tree diversity and community characteristics (84.94 ton/ha). Distribution of AGB carbon also showed sim- ilar trend to that of AGB distribution (Table 1). Linear Altogether, 164 tree species were recorded from the study regression model exhibited significant correlation between area. Maximum species richness (126 species) was recorded biomass and basal area. in mixed dense forest followed by abandoned (41 species) Plot-based biomass estimation using different vegetation and plantations (33 species) (Table 1). Based on density, Cas- indices of selected land use ranged between 0.53 and 0.76 for tonopsis hystrix, Illicium griffithii, Duabanga grandiflora, NDVI, 0.23 and 0.55 for SAVI, 0.10 and 0.30 for DVI, and Michelia champaka, Toona ciliata, Rhododendron sp., Macar- 0.03 and 0.07 for red band. Linear regression analysis was anga denticulata, Altingia excela, Tectona grandis, Diptero- carried out between field-based estimated AGB and satellite- carpus macrocarpus, Citrus sinensis, Albiza sinus, Terminalia derived vegetation indices to understand their relationships myriocarpa, and Schima wallichii were among the most dom- (Table 2). R values for NDVI, DVI, SAVI, and red band inant species. Shannon and Wiener diversity index was high- were 0.51, 0.51, 0.68, and 0.41, respectively, signifying that est (1.38) in mixed dense forest and lowest (1.35) in SAVI have resulted better relationship with biomass as com- plantation forest while reverse trend was observed in Simp- pared to other indices which could be due to soil brightness son dominance index. Majority of the species (>90%) factor. Hence, SAVI was considered the best-fit model and showed clumped distribution, whereas only few species regression equation (Y = 192.77x ¡ 50.568, R = 0.68) was showed random/regular distribution pattern. Sorenson’s used for AGB prediction in the present study. Average pre- index of similarity was observed highest (24.32%) between dicted AGB was 163.25 ton/ha. However, it was 192.74 ton/ abandoned forest and plantations followed by mixed dense ha (13.5–552.6 ton/ha) in mixed dense, 148.49 ton/ha (1.3– forest and abandoned forest resulting marked difference in 213.3 ton/ha) in abandoned forest, and 119.04 ton/ha (97.2– species composition between the sites. 555.9 ton/ha) in plantation forest (Figure 4). Raunkaier’s frequency analysis revealed that most of the species (70%–90%) in different forest stands showed low fre- quency (<20%) distribution and species were completely Discussion absent in higher frequency classes signifying community is Forests of Eastern Himalayan regions are exposed to various heterogeneous in composition. Forests’ heterogeneity was levels of anthropogenic threats such as shifting cultivation, further supported by occurrence of log-normal dominance habitat loss, fragmentation, and colonization of invasive spe- cies leading to serious ecological and environmental implica- Table 1. Community characteristics of selected forest stand of West Kameng tions (Mishra et al. 2003; Sarma et al. 2008; Tripathi et al. district. 2010). Hengeveld (1996) argued that species composition is Mixed dense Abandoned an important attribute of a natural community that influen- Community parameter forest forest Plantations ces functioning of an ecosystem. Higher species richness in a Number of species 126 41 33 Number of families 42 26 22 habitat is mainly due to the presence of synuisae in the forest ¡1 Density (stem ha ) 518 347 622 (Richards 1996). Tree species richness of the study can be 2 ¡1 Basal area (m ha ) 58.89 12.66 13.52 supported by the reported tree richness (76–103 species) Simpson dominance index 0.02 0.08 0.06 Shannon and Wiener 1.38 1.37 1.35 from subtropical broad-leaved forests of Meghalaya (Jamir diversity index 2000; Tripathi and Tripathi 2011). Variation in species rich- Above ground biomass (t 218.21 84.94 105.09 ¡1 ness among the studied land cover could be due to either dis- ha ) Above ground biomass 120.01 46.17 57.80 turbance or management. Comparison of species richness ¡1 carbon (t ha ) among the habitats is quite perplexing and often leads to 88 Y. KASHUNG ET AL. E-ISSN 2158-0715 ¡1 Figure 3. (a) Density (individuals ha ) distribution and (b) biomass distribution in different girth classes of woody species of selected study area. fallible conclusions mainly on account of wide variation in Dominance is an imperative component of the commu- the sampling area studied by the researchers. Hence, it is nity and such species may exert a controlling effect on associ- extremely difficult to give plausible reasons for such a varia- ated species due to their competitive ability (Krebs 1994). tion in the species richness. They act as a key-species and have greater influence on struc- tural and functional attributes (Janzen 1986; Krebs 1994). Dominance-distribution curves signify equitability and sta- Table 2. Coefficient for R for biomass and different vegetation indices. bility of the community. Log-normal distribution pattern sig- Vegetation indices Equation Coefficient (R ) nifies abundance of species that have transitional dominance Normalized difference y = 219.6x ¡ 121.7 0.514 values in the community and maturity and complexity of vegetation index (NDVI) natural community (Magurran 1988). However, logarithmic Difference vegetation y = 251.4x ¡ 29.52 0.509 or broken-stick distribution reflects that the community is index (DVI) Soil adjusted vegetation y = 192.77x ¡ 50.568 0.68 primarily ordered with respect to one dominating factor index (SAVI) (May 1975). Mixed forest was represented by older plants as Red band y = 1129x ¡ 32.69 0.414 is evident by the presence of larger number of trees having E-ISSN 2158-0715 FOREST SCIENCE AND TECHNOLOGY 89 (2016) reported 20–229.50 ton/ha from natural and planta- tion forest of Northern China. AGB of 92–268.49 ton/ha from tropical rain forest of Western Ghats (Bhat et al. 2003) and 230 ton/ha from evergreen forest of Karnataka (Devagiri et al. 2013) were also recorded. SAVI values varied across the vegetation types. In order to realize the relationship, regres- sion analysis was performed between indices and area weighted biomass which revealed a significant positive correlation. Conclusions Findings of the study may be useful for calculating total bio- mass and carbon stored in the major land cover of West Kameng district. Based on the results, it was observed that tree diversity, density, basal area and biomass decrease from mixed forest to plantations. Therefore, to conserve tree diver- sity and maximize AGB, forest resource manager may mini- mize the influence of driving factors responsible for land use change. Further, protective buffer of edge species around the land cover may be created with reduced anthropogenic activ- ities to ensure further degradation. SAVI derived average spa- tial AGB carbon was 89.79 ton/ha. Regression analysis Figure 4. Map showing total biomass stock in study area. between biomass and basal area showed positive relationship and suggested that AGB increases with increase in girth. It more girth. Tree density ranged between 347 and 622 stem will also support in future studies for calculating the long- ¡1 2 ¡1 ha and basal area from 12.66 to 58.89 m ha which cor- term data on biomass carbon sequestration. roborates with the findings of Swamy et al. (2010) from the tropical evergreen forests of Western Ghats and subtropical forest of Arunachal Pradesh (Yam and Tripathi 2015, 2016). Acknowledgments Majority of the species showed contagious distribution which Authors are thankful to forest officials of West Kameng district for nec- could be attributed to inefficient mode of seed dispersal mak- essary permission and assistance during the field study, and also to the ing community highly heterogeneous and patchy (Richards Head, Forestry Department, NERIST for support. Financial Assistance 1996; Tripathi et al. 2010; Yam and Tripathi 2016). received in the form of research grant by the DST, New Delhi (DST/IS- Biomass is the function of tree density, age, girth, and STAC/CO -SR-225/14(G)-AICP-AFOLU-II) is duly acknowledged. height. It is also largely regulated by the habitats and species composition (Joshi and Ghose 2014). Large numbers of methodological literatures are available for modeling the spa- Disclosure statement tial distribution of AGB using single value of biomass esti- No potential conflict of interest was reported by the authors. mated from ground truth measurements to sophisticated methods that integrate different data sources. AGB observed in the study can be supported by the reported values of sev- Funding eral researchers (Murphy and Lugo 1986; Devagiri et al. DST, New Delhi [grant number DST/IS-STAC/CO2-SR-225/14(G)- 2013; Yam and Tripathi 2016). NDVI-derived AGB showed AICP-AFOLU-II]. higher R value as compared to values (0.14 and 0.05) reported by Rahman et al. (2008) and Ren and Zhou (2014). However, Foody et al. (2003) reported lower R value (0.01– References 0.08) from Thailand, Brazil and Malaysia using Landsat TM Bhat DM, Murali K , Ravindranath NH. 2003. Carbon stock dynamics in satellite data. Devagiri et al. 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Geospatial technology based diversity and above ground biomass assessment of woody species of West Kameng district of Arunachal Pradesh

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FOREST SCIENCE AND TECHNOLOGY, 2018 E–ISSN 2158-0715, VOL. 14, NO. 2, 84–90 https://doi.org/10.1080/21580103.2018.1452797 Geospatial technology based diversity and above ground biomass assessment of woody species of West Kameng district of Arunachal Pradesh Yakhari Kashung, Biswajit Das, Sangeeta Deka, Reetashree Bordoloi, Ashish Paul and Om Prakash Tripathi Department of Forestry, North Eastern Regional Institute of Science and Technology (Deemed to be University), Nirjuli, Arunachal Pradesh, India ABSTRACT ARTICLE HISTORY Received 17 July 2017 Comprehending the prominence of forest carbon in climate change, this study was piloted in different Accepted 8 March 2018 land use of West Kameng district, Arunachal Pradesh, India to record the floristic composition, community characteristics, and above ground biomass (AGB) carbon using random sampling and KEYWORDS geospatial approach. Preliminary field survey was done in 2016. Altogether 45 quadrats (0.1 ha each) Species diversity; community were laid. Total tree richness recorded was 164 species from 49 families. Dominance and frequency composition; geospatial distribution pattern of species revealed heterogeneity in composition with majority species showing technique; satellite data; tree clumped distribution. Plantations showed highest tree density while mixed dense forest showed biomass 2 ¡1 maximum basal area (58.89 m ha ). Estimated AGB were 218.21 ton/ha for mixed dense forest, 84.94 ton/ha for abandoned forest, and 105.09 ton/ha for plantations. Total estimated carbon stocks were 120.01, 46.17, and 57.80 ton/ha for mixed dense, abandoned forest, and plantations, respectively. Predicted average AGB using Geographic Information System (GIS) techniques was 163.25 ton/ha. Field-based AGB was slightly greater than the values observed from satellite data. Findings of the study may be useful for calculating total biomass and carbon stored in the major land cover of the district in particular and region in general. It will also support in future studies for calculating the long-term data on biomass carbon sequestration. Introduction observation, and historical data archives. Recently, there have been tremendous efforts at national to global level on appli- Forest ecosystem of earth surface accounts for 75% of the cation of satellite and field-based data in assessing AGB and gross primary productivity of the earth’s biosphere, and carbon pool (Chhabra et al. 2002; Zheng et al. 2004; Manhas encompasses 80% of the plant biomass. They are the largest, et al. 2006; Gunlu et al. 2014; Wani et al. 2014; Salunkhee complex, and self-regenerating natural resources. They are et al. 2016). considered important for their unique role as major carbon Himalayan ecosystem shows great variability in physiog- sinks because of their capability to capture and store carbon raphy and composition and housings over 51 million people. dioxide from the atmosphere. Thus, maintaining forest bio- These ecosystems are dynamic to the ecological retreat of the mass and sequestration potential is dependent on maintain- Indian landmass, through forest cover, feeding perennial riv- ing forests. However, structure and function of forest ers, hydropower, safeguarding biodiversity, enriching soil ecosystems are changing drastically due to various anthropo- and agriculture, and spectacular landscapes for sustainable genic activities. Forest degradation and deforestation have tourism. The state of Arunachal Pradesh, India (Eastern direct impact on biomass and carbon pool. These activities Himalaya), where the study was carried out, has a geographi- have altered the concentration of greenhouse gases in the cal area of 83,743 km . State biodiversity is very rich support- atmosphere thereby impacting climate and weather condi- ing 20% faunal species of the nation, 4500 flowering plants, tions, biodiversity, food production, and human health. Sev- 400 pteridophytes, 23 coniferous species, 35 variety of bam- eral studies have reported that carbon storage in forests are boos, 20 cane species, 106 Rhododendron taxa, and 500 directly regulated by composition, age, site characteristics, orchid species. Degradation and poor forest management succession, and climatic variation (Chen et al. 2005; Waring have the potential to reduce the carbon stock while sustain- and Running 2007; Gough et al. 2008; Goward et al. 2008). able management can increase the carbon stock. Like other The amount of carbon sequestered by a forest can be esti- parts, eastern Himalayan regions are also exposed to various mated from the biomass accumulated and such database is levels of threat. Hence, there is a need to carry out the studies important for many national developments planning pertain- on spatial and temporal scale on diversity, degradations, ing to productivity and carbon budget. An increase of 0.65– management, etc. for their sustainability. However, the chal- 1.06 C temperature was reported in the fifth assessment lenges remain to find a commonly agreed and scientifically report of International Panel on Climate Change (IPCC). sound methodological framework for accounting for carbon Hence, emphasis was given on control of emission and stock. The study emphasizes on plant diversity, community removal of carbon dioxide from the atmosphere to mitigate characterization, and stand biomass. Findings of the study climate change. Remote sensing and GIS have been used for could be helpful for developing suitable region-specific strate- rapid and consistent assessments of above ground biomass gies by the land use planners. However, topography of the (AGB) and carbon pool because of its coverage, systematic study area is mostly mountainous with steep terrain, hence CONTACT Om Prakash Tripathi tripathiom7@gmail.com, opt@nerist.ac.in © 2018 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, dis- tribution, and reproduction in any medium, provided the original work is properly cited. E-ISSN 2158-0715 FOREST SCIENCE AND TECHNOLOGY 85 limited plots could be established which otherwise would mountainous zone, consisting of a mass of tangled peaks and have given more accurate results. valleys and its altitudinal variability ranges from 115 to 5780 m asl. The district shares an International border with Tibet in the north, Bhutan in west, Tawang district in north- west, and southern border with districts of Assam. The study Materials and methods area has three principle mountain chains, i.e. Sela, Bomdila, Study site and Chaku ranges. The district is rich in biodiversity and is Present study was undertaken in West Kameng district (26 home to the Eaglenest Wild life Sanctuary covering an area 54’ to 28 01’ N latitudes and 91 30’ to 92 40’ E longitudes) of 217 km and Sessa Orchid Wildlife sanctuary with an area of Arunachal Pradesh (Figure 1). The district covers an area of 100 km . There are five major tribes inhabiting in the study of 7422 km accounting 8.86% of total geographical area of area, namely Monpa, Miji, Sherdukpen, Aka, and Bugun. the state. A greater part of it falls within the higher Monpas and majority of inhabitants follow Buddhist religion. Figure 1. Map showing location of the study area. 86 Y. KASHUNG ET AL. E-ISSN 2158-0715 Data acquisition and analysis Vegetation analysis Landsat operational land imager (OLI) satellite (Landsat 8) Total 45 quadrats of 30 m £ 30 m were laid in selected forest data was used (NASA’s public domain). Landsat 8 collects patch (100 m £ 100 m). All individuals (gbh > 30 cm) encoun- data in nine spectral bands with 30 m spatial resolution tered in the quadrats were recorded with their height and girth except band-8 (15 m). Band-wise radiometric calibration at breast height (1.37 m). Coordinates and elevation of the sam- was performed to remove spurious digital number present pling sites were recorded using GPS during the study. Collected in the scene following the process laid down in Landsat 8 specimens were identified with the help of regional floras and user handbook (2016). Images were re-projected to Univer- published literatures. Community characteristics such as fre- sal Transverse Projection followed by layer stacking, sub- quency, density, basal area, spatial distribution pattern, and setting, and extraction of the study area. Land use and land diversity indices were calculated according to Misra (1968), cover map was prepared using supervised classification in Mueller-Dombois and Ellengberg (1974), and Magurran (1988). ERDAS Imagine 9.1 (Figure 2). Based on the classified map, Density-distribution, basal area, and biomass were studied by three major land use types, namely mixed dense forest, determining the number of individuals in different girth classes. abandoned forest, and plantations were selected for detail Non-destructive approach of AGB estimation was adopted for studies. estimating biomass and carbon. Figure 2. Flow chart of geospatial mapping. E-ISSN 2158-0715 FOREST SCIENCE AND TECHNOLOGY 87 Biomass and carbon estimation distribution pattern of species. Such forest composition does not allow dominance of a species. However, in abandoned Standing volume was estimated using diameter at breast and plantations, it showed that a few species dominated the height (dbh) and height of trees as an input in volumetric community which could be due to disproportionate sharing equations for existing tree species. In case of unidentified spe- of resources among the plant species. Maximum tree density cies and species with no species-specific equations, common was observed in plantations followed by mixed dense and equation for Arunachal Pradesh (Tirap) was used. Further, abandoned forests. Greater basal area was observed in mixed estimated volumes were converted into dry biomass by using forest mainly due to presence of larger number of individuals specific gravity or wood density (FSI 1996). AGB carbon having more girth (Table 1). Density-girth class distribution stock was estimated by assuming that the carbon content in pattern showed a gradual decrease in number of individuals wood is 55% of the total AGB (MacDicken 1997). Biomass with increase in girth in all the selected areas (Figure 3(a)). was also estimated using remote sensed data through four widely used vegetation indices, namely normalized difference vegetation index (NDVI; Rouse et al. 1974), difference vege- Above ground biomass and carbon tation index (DVI; Tucker 1979), soil adjusted vegetation AGB and carbon distribution in different girth class showed index (SAVI; Huete 1988), and red reflection band. Based on reverse trend to that of density distribution. Study showed the results of linear regression analysis of different indices, that the lower girth class (<75 cm gbh) contributed to 64%– best-fit model was used for spectral modeling of biomass of 74% of the stand density while only 17% to biomass and car- the study area. Various steps to study community character- bon. However, 47% biomass was contributed by higher girth istics, biomass, and carbon stock are presented in Figure 2. class (>151 cm gbh) although they represented 1%–8% of the total density (Figure 3(b)). Total AGB of selected land use showed maximum in mixed dense forest (218.21 ton/ha) Results followed by plantations (108 ton/ha) and abandoned forest Tree diversity and community characteristics (84.94 ton/ha). Distribution of AGB carbon also showed sim- ilar trend to that of AGB distribution (Table 1). Linear Altogether, 164 tree species were recorded from the study regression model exhibited significant correlation between area. Maximum species richness (126 species) was recorded biomass and basal area. in mixed dense forest followed by abandoned (41 species) Plot-based biomass estimation using different vegetation and plantations (33 species) (Table 1). Based on density, Cas- indices of selected land use ranged between 0.53 and 0.76 for tonopsis hystrix, Illicium griffithii, Duabanga grandiflora, NDVI, 0.23 and 0.55 for SAVI, 0.10 and 0.30 for DVI, and Michelia champaka, Toona ciliata, Rhododendron sp., Macar- 0.03 and 0.07 for red band. Linear regression analysis was anga denticulata, Altingia excela, Tectona grandis, Diptero- carried out between field-based estimated AGB and satellite- carpus macrocarpus, Citrus sinensis, Albiza sinus, Terminalia derived vegetation indices to understand their relationships myriocarpa, and Schima wallichii were among the most dom- (Table 2). R values for NDVI, DVI, SAVI, and red band inant species. Shannon and Wiener diversity index was high- were 0.51, 0.51, 0.68, and 0.41, respectively, signifying that est (1.38) in mixed dense forest and lowest (1.35) in SAVI have resulted better relationship with biomass as com- plantation forest while reverse trend was observed in Simp- pared to other indices which could be due to soil brightness son dominance index. Majority of the species (>90%) factor. Hence, SAVI was considered the best-fit model and showed clumped distribution, whereas only few species regression equation (Y = 192.77x ¡ 50.568, R = 0.68) was showed random/regular distribution pattern. Sorenson’s used for AGB prediction in the present study. Average pre- index of similarity was observed highest (24.32%) between dicted AGB was 163.25 ton/ha. However, it was 192.74 ton/ abandoned forest and plantations followed by mixed dense ha (13.5–552.6 ton/ha) in mixed dense, 148.49 ton/ha (1.3– forest and abandoned forest resulting marked difference in 213.3 ton/ha) in abandoned forest, and 119.04 ton/ha (97.2– species composition between the sites. 555.9 ton/ha) in plantation forest (Figure 4). Raunkaier’s frequency analysis revealed that most of the species (70%–90%) in different forest stands showed low fre- quency (<20%) distribution and species were completely Discussion absent in higher frequency classes signifying community is Forests of Eastern Himalayan regions are exposed to various heterogeneous in composition. Forests’ heterogeneity was levels of anthropogenic threats such as shifting cultivation, further supported by occurrence of log-normal dominance habitat loss, fragmentation, and colonization of invasive spe- cies leading to serious ecological and environmental implica- Table 1. Community characteristics of selected forest stand of West Kameng tions (Mishra et al. 2003; Sarma et al. 2008; Tripathi et al. district. 2010). Hengeveld (1996) argued that species composition is Mixed dense Abandoned an important attribute of a natural community that influen- Community parameter forest forest Plantations ces functioning of an ecosystem. Higher species richness in a Number of species 126 41 33 Number of families 42 26 22 habitat is mainly due to the presence of synuisae in the forest ¡1 Density (stem ha ) 518 347 622 (Richards 1996). Tree species richness of the study can be 2 ¡1 Basal area (m ha ) 58.89 12.66 13.52 supported by the reported tree richness (76–103 species) Simpson dominance index 0.02 0.08 0.06 Shannon and Wiener 1.38 1.37 1.35 from subtropical broad-leaved forests of Meghalaya (Jamir diversity index 2000; Tripathi and Tripathi 2011). Variation in species rich- Above ground biomass (t 218.21 84.94 105.09 ¡1 ness among the studied land cover could be due to either dis- ha ) Above ground biomass 120.01 46.17 57.80 turbance or management. Comparison of species richness ¡1 carbon (t ha ) among the habitats is quite perplexing and often leads to 88 Y. KASHUNG ET AL. E-ISSN 2158-0715 ¡1 Figure 3. (a) Density (individuals ha ) distribution and (b) biomass distribution in different girth classes of woody species of selected study area. fallible conclusions mainly on account of wide variation in Dominance is an imperative component of the commu- the sampling area studied by the researchers. Hence, it is nity and such species may exert a controlling effect on associ- extremely difficult to give plausible reasons for such a varia- ated species due to their competitive ability (Krebs 1994). tion in the species richness. They act as a key-species and have greater influence on struc- tural and functional attributes (Janzen 1986; Krebs 1994). Dominance-distribution curves signify equitability and sta- Table 2. Coefficient for R for biomass and different vegetation indices. bility of the community. Log-normal distribution pattern sig- Vegetation indices Equation Coefficient (R ) nifies abundance of species that have transitional dominance Normalized difference y = 219.6x ¡ 121.7 0.514 values in the community and maturity and complexity of vegetation index (NDVI) natural community (Magurran 1988). However, logarithmic Difference vegetation y = 251.4x ¡ 29.52 0.509 or broken-stick distribution reflects that the community is index (DVI) Soil adjusted vegetation y = 192.77x ¡ 50.568 0.68 primarily ordered with respect to one dominating factor index (SAVI) (May 1975). Mixed forest was represented by older plants as Red band y = 1129x ¡ 32.69 0.414 is evident by the presence of larger number of trees having E-ISSN 2158-0715 FOREST SCIENCE AND TECHNOLOGY 89 (2016) reported 20–229.50 ton/ha from natural and planta- tion forest of Northern China. AGB of 92–268.49 ton/ha from tropical rain forest of Western Ghats (Bhat et al. 2003) and 230 ton/ha from evergreen forest of Karnataka (Devagiri et al. 2013) were also recorded. SAVI values varied across the vegetation types. In order to realize the relationship, regres- sion analysis was performed between indices and area weighted biomass which revealed a significant positive correlation. Conclusions Findings of the study may be useful for calculating total bio- mass and carbon stored in the major land cover of West Kameng district. Based on the results, it was observed that tree diversity, density, basal area and biomass decrease from mixed forest to plantations. Therefore, to conserve tree diver- sity and maximize AGB, forest resource manager may mini- mize the influence of driving factors responsible for land use change. Further, protective buffer of edge species around the land cover may be created with reduced anthropogenic activ- ities to ensure further degradation. SAVI derived average spa- tial AGB carbon was 89.79 ton/ha. Regression analysis Figure 4. Map showing total biomass stock in study area. between biomass and basal area showed positive relationship and suggested that AGB increases with increase in girth. It more girth. Tree density ranged between 347 and 622 stem will also support in future studies for calculating the long- ¡1 2 ¡1 ha and basal area from 12.66 to 58.89 m ha which cor- term data on biomass carbon sequestration. roborates with the findings of Swamy et al. (2010) from the tropical evergreen forests of Western Ghats and subtropical forest of Arunachal Pradesh (Yam and Tripathi 2015, 2016). Acknowledgments Majority of the species showed contagious distribution which Authors are thankful to forest officials of West Kameng district for nec- could be attributed to inefficient mode of seed dispersal mak- essary permission and assistance during the field study, and also to the ing community highly heterogeneous and patchy (Richards Head, Forestry Department, NERIST for support. Financial Assistance 1996; Tripathi et al. 2010; Yam and Tripathi 2016). received in the form of research grant by the DST, New Delhi (DST/IS- Biomass is the function of tree density, age, girth, and STAC/CO -SR-225/14(G)-AICP-AFOLU-II) is duly acknowledged. height. It is also largely regulated by the habitats and species composition (Joshi and Ghose 2014). Large numbers of methodological literatures are available for modeling the spa- Disclosure statement tial distribution of AGB using single value of biomass esti- No potential conflict of interest was reported by the authors. mated from ground truth measurements to sophisticated methods that integrate different data sources. AGB observed in the study can be supported by the reported values of sev- Funding eral researchers (Murphy and Lugo 1986; Devagiri et al. DST, New Delhi [grant number DST/IS-STAC/CO2-SR-225/14(G)- 2013; Yam and Tripathi 2016). NDVI-derived AGB showed AICP-AFOLU-II]. higher R value as compared to values (0.14 and 0.05) reported by Rahman et al. (2008) and Ren and Zhou (2014). However, Foody et al. (2003) reported lower R value (0.01– References 0.08) from Thailand, Brazil and Malaysia using Landsat TM Bhat DM, Murali K , Ravindranath NH. 2003. Carbon stock dynamics in satellite data. Devagiri et al. 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Journal

Forest Science and TechnologyTaylor & Francis

Published: Apr 3, 2018

Keywords: Species diversity; community composition; geospatial technique; satellite data; tree biomass

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