Abstract
Similarity Indices are widely applied in the field of ecology to measure species diversity as well as to map patterns of conservation and monitor threats to biodiversity. Among the known, Jaccard's and Sorensen's indices are the most frequently employed similarity Indices. Here, we propose a new and efficient statistical approach in the field of ethnobiology and validate its efficacy by comparing the results with predefined similarity Indices used in previous studies. The core objective was to propose a new index for quantitative ethnobiological analyses and to find out solutions for sorting the plants having similar ethnobiological uses in allied, aligned, national and global regions; as the pre-existing indices like Jaccard's and Sorensen's indices provides best estimates in the field of ecology but not in ethnobiological studies. In comparative ethnobiological studies, ethnobiologists use conventional ecological tools for evaluation of similarities and dissimilarities. Our proposed similarity index is based on the quantification of similar uses of common medicinal plants via comparing present study with previously published reports from various areas where, the author(s) have used the Sorensen's index and/or Jaccard's index. To assess the significance and validity of this newly developed index, similarities and differences in ethnomedicinal studies on medicinal plants in different regions were evaluated. Data regarding medicinal plants usage here was compared with 20 previously published studies and then analyzed through preexisting indices as well as Rahman's index to examine the novelty in the study. Our preliminary results revealed noteworthy coherence with the existing similarity indices, albeit, the new index was more efficient than the previous. Our comparison revealed, that as far as common vegetation and floral levels are concerned, the existing ecological coefficients of similarity are efficient and precise; but for similarities in the field of medicinal plant studies certain constraints are overcome by the proposed similarity index. Inferences derived from Rahman's similarity index (RSI) are as reliable as the previously known and well-established similarity indices. Further, RSI specifically targets the ethnobiological similarities, a limitation in Jaccard's and Sorensen's indices. Thus, RSI would be a useful tool/index in the assessment of rigorous quantitative ethnobiological data.