Least-biased Estimations of True Species Richness of Butterfly Fauna in Sub-urban Sites around Jhansi (India) and the Range of Inter-annual Variation of Species Richness

As a rule, most biodiversity inventories at local scales remain more or less incomplete, when dealing with relatively speciose taxonomic groups, such as butterfly in tropical regions. Yet, it remains possible to take maximum advantage of partial inventories and to develop reliable predictions by extrapolating the species accumulation curves beyond the already achieved samplings. Besides, due to the wide diversity of available estimators of total species richness, selecting for the less-biased estimator and the associated expression of the species accumulation curve is desirable. Accordingly, the “least-biased extrapolation procedure” is recommended in this respect.

Least-biased extrapolation procedure was applied to nine inventories carried on by Ashok Kumar in (sub-) urban sites in the vicinity of Jhansi (Uttar Pradesh, India), thus providing more accurate evaluations of remnant butterfly species richness in these sites. The range of estimated sampling completeness of inventories was comprised between 65% and 99%, depending on sites and years and the estimated true species richness was comprised between 25 species (along Highway in 2010) and 44 species (Jhansi Fort in 2011).

Importantly, the levels of sampling completeness prove to be poorly correlated with sampling size. This highlights the fact that, contrary to still a current opinion, comparisons between levels of species richness may well remain irrelevant, even when made at a same sampling size (for example by using appropriate “rarefaction” procedure).

Four, out of the nine studied inventories, were conducted at two same sites for two successive years (2010-2011) and, thus, provide opportunity to evaluate the range of inter-annual variations of true species richness of butterfly fauna in this sub-urban context. Inter-annual variations within the range 24% to 48% were registered, according to sites.