Estimation of population density or abundance of arboreal primates such as Hylobates agilis is generally difficult due to their highly mobile nature and accessibility to sampling area can be very difficult. Conventional methods such as distance sampling or mark- recapture method requires big amount of effort, funding and man power. Alternatively, presence-absence method can be used which is relatively easy, less costly and requires lesser personnel The presence-absence method used in this study is one of the approach developed for estimating occupancy of single species within single season(MacKenzie, Nichols, Gideon, Droege, Royle and Langtimm, 2002).
Occupancy is the proportion of a randomly selected sampling unit in an area under study is occupied with interested species. Occupancy modeling allows us to estimate the probability that a sampling unit is occupied, given that species are imperfectly detected or in other words probability that a site is within a group of sites is occupied with species of interest. Occupancy model has wide range of applications such as species occurrence, range, distribution, habitat selection and wild life monitoring (MacKenzie et al, 2005).
In this, study we used single season single species occupancy model and carried out based on presence – absence data or detection –non detection data. In the single season model, populations are assumed to be closed no migration, birth of new individual, death take place during the period of study. If x and s represents the number of occupied sites and total number of surveyed site, then occupancy of particular species is:
However, x count may be lower than expected due to absence of species in the occupied site which leads to false absence. Therefore multiple surveys are carried out to estimate the detection probability, giving us estimate of x Hence, an estimator of the proportion of sties occupied is:
In other word, presence of species from the sites where the species was observed once, is used to estimate the probability of the sites where species is not detected. (MacKenzie et al, 2005).
The general model of single species, single season consists of two random processes which may affect the detection of of a species at a survey site. First, If a site is occupied then the probability is Ψ or may be unoccupied by the species with probability of 1- Ψ . Second, given that the location is occupied at each survey (j) there is probability of detecting the species (pj) and (1-pj) for probability of not detecting the species (MacKenzie et al, 2005).
L(ψ,p)= [ψ^(n.) ∏_(t=1)^T▒p_t^(n_t ) 〖(1-p_t)〗^(n.-n_t ) ]×[ψ∏_(t=1)^T▒〖(1-p_t )+(1-ψ〗]^(N-n.)
In the general model of single species single season, five assumption were made. Firstly, the occupancy state of the survey sites does not change during the period of study as we have already assumed earlier that it is closed population. Second, the probability of occupancy(Ψ) is equal across the sites....