METHODS AND STUDY AREA

The forest vegetation was sampled using transect-based quadrats, amethod found useful especially in surveying forested landscaped of central Western Ghats (Chandran and Mesta 2001; Ramachandra et al. 2006; Ali et al. 2007). Remote sensing imageries were used and ground surveys made to select sample plots (Figure 2 for locations). Along a transect of 180 m, 5 quadrats each of 20x20 m were laid alternatively on the right and left, for tree study (minimum girth of 30 cm at GBH or 130 cm height from the ground), keeping intervals of 20 m length between successive quadrats. Within each tree quadrat, at two diagonal corners, two sub-quadrats of 5 m × 5 m were laid for shrubs and tree saplings (< 30 cm girth). Within each of these 2 herb layer quadrats, 1 sq.m area each, were also laid down for herbs and tree seedlings (Figure 3). Climbers and other associated species were noted. A rapid assessment was made to track vegetational changes from the densely populated coast through the rugged mountainous terrain to the undulating and drier eastern lands using point-centred quarter method along line transects Ankola (coastal) and Yellapur (hilly to undulating) taluks. Sampling efforts were higher in high endemism areas (eg. Kathalekan in Siddapur). Details of formulas used for various calculations are given in the Table 2.

Figure 2: Distribution of sample study sites in Uttara Kannada forests

The data collected was analyzed to calculate the species diversity using Shanon-Weiner’s diversity index, Simpson dominance index, IVI, regeneration status, basal area, biomass and carbon sequestration potential. The Pearson Correlation Matrix with probabilities was calculated by using the ‘R’ software.  A Principal Component Analysis (PCA) was carried out using the package PAST version 2.16. This ordination technique was used to analyze the relationship between the samples and to understand the main factors influencing the forest vegetation in Uttara Kannada (Table 2). In addition, the loading score for each variable was calculated; the values were then converted into conservation scoring system and added to the respective variable (next section)

Table 1: The extent of forest areas released for other purposes from 1956

*Source: Forest working plan of Kanara circle (year 2009-10)

The above ground standing biomass of trees is referred to the weight of the trees above ground, in a given area, if harvested at a given time. The change in standing biomass over a period of time is called productivity. The standing biomass helps to estimate the productivity of an area and also gives information on the carrying capacity of land (Ramachandra and Kamakshi, 2005). It also helps in estimating the biomass that can be continuously extracted. Carbon storage in forests is estimated by taking 50% of the biomass as carbon. The mathematical equations for biomass estimations of trees have been developed and used by many researchers for different biogeography regions. For the current study, the standing above-ground biomass was calculated using the basal area equation and indirect estimation was done for calculating below ground biomass (Brown, 1997; Ravindranath et al. 1997; Murali et al. 2005; Ravindranath and Ostwald, 2008). The resultant total biomass was multiplied by 0.5 for estimating the carbon storage.