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Abstract: Assessing biodiversity is crucial in ecology, requiring robust
measures of species distribution and similarity between communities.
Traditional similarity indices, do not account for asymmetry and are
limited in detecting deviations from expected biodiversity patterns. In
this study we present a modified version of the Kullback-Leibler divergence
that can be effectively used as a similarity index in biodiversity
assessment. Results form a simulation study and a real data application
show that our proposal outperforms consistently the reference standard,
the Bray-Curtis similarity.