Back

Understanding distribution and occupancy of Himalayan Monal in Uttarkashi district, Uttarakhand

Sharief, A.; Singh, H.; Joshi, B. D.; Mukherjee, T.; Chandra, K.; Thakur, M.; Sharma, L. K.

2021-02-17 ecology
10.1101/2021.02.16.431367 bioRxiv
Show abstract

The Himalayan Monal is a conservation priority species in its entire distribution range. Its population is declining in many areas due to various anthropogenic threats. The information on species distribution and its abundance is lacking in many areas which are vital for conservation and management planning. Hence, through the present study, we have assessed the abundance and occupancy of Himalayan monal in Uttarkashi district (Uttarakhand). We used camera traps and conventional sign surveys for documenting the species during 2018-2019. We installed a total of 69 camera traps (2819 trap nights) and surveyed 54 trails (650 km) which represents entire habitat and topographic variability of the landscape. The occupancy and detection probability was modelled using the habitat variables. The top model showed that occupancy probability of Himalayan monal was positively influenced by the slope ({beta} =27.52 {+/-}16.25) and negatively influenced by Reserve Forest (RF) ({beta}= -8.14 SE {+/-} 4.99). The observed naive occupancy of Himalayan Monal was 0.69 in the study area, which was slightly lower than the estimated occupancy. However, in the null model, the site occupancy estimated was found to be 0.82{+/-}0.08 and with detection probability 0.23{+/-}0.03. The overall abundance of monal was estimated about 171.58 {+/-}10.2 in the study area with an average density of 0.62/ km2. The activity pattern analysis indicates that monal remains very active between 6.00 hrs -12.00 hrs and relatively less active during mid-day when humans are most active 11.30 hrs-16.30 hrs. The present study is a first attempt to estimate occupancy and abundance using camera traps as well as sign survey for the species primarily from non-Protected Area (PA). We found that Himalayan monal is abundant outside the PAs, which is a good indication for its long-term viability and also identified areas for conservation and management prioritization in Uttarkashi.

Matching journals

The top 2 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.