An investigation into the spatiotemporal patterns of the Nymphalid butterfly Vagrans egista sinha (Kollar, )

Abstract

Vagrans egista sinha (Kollar, [1844]), the Himalayan Vagrant is a subspecies of Nymphalid (Brush-footed) butterflies spread across Asia, whose western limit is in the north-west India. Observations of this subspecies have considerably increased over the past half-a-decade, with a spike in new sightings to the west of their previously known range. This has been considered as a range extension. The current study reports new records of this species from Bilaspur District, Himachal Pradesh, India (which are the first records for the district), through systematic and opportunistic sampling. This raises the question of whether the purported range extension towards the west could instead be a range shift or vagrancy, and whether there is any shift in elevational ranges in the populations across their known range. Questions pertaining to spatial differences in elevational ranges and seasonal variation, across their range, also piqued our curiosity. Using data from academic sources (such as published literature and museum collections), supplemented by data from public participation in scientific research and personal observations, these research questions are addressed. The accuracy of results when using citizen science data is also explored using the same dataset, focused on the impact of method of extraction of coordinates, and elevation derived from it under different scenarios. It was discovered that there has not been a range shift (either longitudinal or latitudinal) and observations dont suggest vagrancy but a case of range extension. Other results indicated that there was no climb of population to higher elevations, no spatial differences in elevational ranges in the populations, or seasonal variation in activities across their range. It was also discovered that the method of data collection by, and extraction from, citizen science databases, can influence the accuracy of the results. Some problems involved in collecting data are discussed, and remedial solutions are suggested.