Abstract
Biodiversity conservation necessitates not only preservation of single or multiple species but also the habitat as a whole along with its environment. Biological richness (BR) is a cumulative property of an ecological habitat and its surrounding environment, which has emerging implications in terms of management and planning. Six biodiversity attributes (i.e., spatial, phytosociological, social, physical, economical and ecological) were linked together based on their relative importance to qualitatively stratify biological richness of forest vegetation in Subansiri district of Eastern Himalaya using customized software, Bio_CAP. Higher biological richness was assigned to the habitats with (i) high species diversity, (ii) high degree of ecosystem uniqueness (EU), (iii) high economical value, (iv) complex terrain and (v) low disturbance level. This simple idea of integrated ‘three-tier modeling approach’ of (i) utilization of geospatial tools, (ii) limited field survey and (iii) landscape analysis; formed the basis of rapid assessment of biological richness. Satellite image interpretation using hybrid classification approach provided spatial distribution of vegetation types (corresponding to ecological habitats), with 89% accuracy. Landscape analysis was done using various quantitative indices that measured the heterogeneity and evaluated the patch characteristics. A methodology was developed for deriving relative adjacency weights from field data for calculation of juxtaposition of vegetation types. Biotic disturbance buffers (i.e., proximity zones around roads and human settlements) along with landscape parameters were combined to calculate disturbance index (DI), which in turn became an intermediate surrogate for BR assessment. Species diversity patterns along fragmentation and biotic disturbance gradients were adjudged to derive relative weights for DI computation. Species diversity (Shannon's index), ecosystem uniqueness (endemism status) and biodiversity value (BV) (total importance value (TIV)) were enumerated quantitatively that provided relative weights for BR computation. Terrain complexity (TC) was generated by calculating variance of the elevation image. Fifty-nine of total 764 species were found endemic to Eastern Himalaya with over all species endemism of 13 per ha. Shannon's index increased with decrease in fragmentation levels and increase of distance from sources of disturbance. BR index of the district was presented in five qualitative levels. Subtropical forests claim highest degree of biological richness as well as high disturbance index. This methodology has implications for rapid biodiversity assessment. Forest managers can use the DI and BR maps for gap analysis and prioritization of conservation activities viz., introduction of locale-specific species, thus protecting the forest habitats in situ.
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