Accurate assessments of distribution and conservation status of species are vital parameters to plan effective management strategies. Assessments should also include reliable quantification of target species as it helps in understanding its global and regional conservation significance. Evaluation of species status over a period of time allows revision of status criteria for species of interest. Based on the assessments provided by the evaluators, the species is upgraded, downgraded or maintained in the current status in the Red Data List of the IUCN.
Surveys are carried out to confirm presence/absence of a species and also to ascertain the status of a species in terms of its distribution and abundance. Surveys are typically carried out by searching for a species at a number of sites using appropriate field methods for detection of the species. When a species is detected, it is considered to be present but when a species is not detected, care should be taken before declaring it as being absent from the site. The surveys for species presence must take into account the problems of imperfect detections. Detection probability is always < 1.
Differences in detections can occur mainly due to vastness of the area to be surveyed and also due to the intrinsic detectability quotient of a species. Some species are very conspicuous and are easily seen while others are difficult to detect even if present on the site. Also, if areas to be sampled are enormous in scale, it will not be possible to cover all different types of habitats within the given resources and time leading to incomplete sampling of the area (MacKenzie et al. 2002, 2003).
Traditionally, studies have used abundance measure of a species to obtain near-reliable estimates or count statistics in a small area or over a long study period but this method is time consuming and effort intensive if it is to be implemented over a wide-geographical area. Investigators have used mainly two types of survey methods for detecting presence of R .indica. A survey for estimating encounters of squirrel presence such as direct sightings and indirect evidences such as nests and calls in different forest and vegetation types (Borges et al 1998, Umapathy and Kumar 2000, Kumara and Singh 2006, Molur and Singh 2009). The abundance index was calculated based on the count statistics.
Jathana et al. (2008) used line-transect based distance sampling method to estimate densities of giant squirrel. Srinivas et al. (2008) used grid-based occupancy survey to assess the status of giant squirrel. Both the investigators used the function of detection probabilities to model densities and occupancy of giant squirrels from a small and compact Protected Area in southern India.