FORESTIST
Original Article

A Proposed Novel Approach in Estimation of Unbiased Community Rarity Using the Locked Matrix and Tsallis Entropy

1.

Department of Forest Engineering, Isparta University of Applied Sciences, Faculty of Forestry, Isparta, Türkiye

FORESTIST 2024; 74: 211-217
DOI: 10.5152/forestist.2024.23030
Read: 431 Downloads: 230 Published: 14 May 2024

The present study offers a new approach to measure unbiased rarity at the community level r q* . In this approach, the locked data matrix (matrix H) and the survey data matrix of the communities (matrix A) play the essential roles. q* q* The core equations of this approach are Tsallis entropy (qS) and bias-corrected Tsallis entropy q S . From the varying value of the Tsallis index (q), q* corresponds to the point in the curve where the relative difference among qS and qSmax values is maximized. AS and AS community data in the A matrix. HS * puted based on the following equation: q R q q q S q q * =1 / * r e denote Tsallis entropy and bias-corrected Tsallis entropy at the q* value using only the species * q* represents the value of Tsallis entropy obtained from the H matrix. q R S is com * * * S S S * H A A Unbiased. q* q* is defined q R S by interpolation and denotes an unbiased community rarity. In the present study, to better explain the proposed approach, a hypothetical community data set containing five com munities was used. Findings indicate that r q* seems to be promising to measure unbiased community rarity. However, its accuracy should, of course, be confirmed by further studies using real ecological data.

Cite this article as: Özkan, K. (2024). A proposed novel approach in estimation of unbiased community rarity using the locked matrix and Tsallis entropy. Forestist, 74(2), 211-217.

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