Temporal patterns of three sympatric pheasant species in the Nanling Mountains: N-mixture modeling applied to detect abundance

Abstract

Background: The reliability of long-term population estimates is crucial for conservation and management purposes. Most previous studies assume that count indices are proportionally related to abundance; however, this assumption may not hold when detection varies spatially and temporally. We examined seasonal variations in abundance of three bird species (Cabot's Tragopan Tragopan caboti, Silver Pheasant Lophura nycthemera, and Whitenecklaced Partridge Arborophila gingica) along an elevational gradient, using N-mixture models that take into account imperfect detection in our bird data. Methods: Camera-trapping was used to monitor temporal activity patterns of these species at Guangdong Nanling National Nature Reserve from December 2013 to November 2017 (4 seasons per year). For abundance analysis (N-mixture modeling), we divided a year into 4 seasons, i.e. 3 months per season, and performed the analysis by season. Elevation was incorporated into the N-mixture model as a covariate that may affect abundance. We compared the N-mixture model with a null model (no covariate model) and selected the better model based on AIC values to make an inference. Results: From 24 sampling sites, we obtained 6786 photographs of 8482 individuals of 44 bird species and 26 mammal species. Silver Pheasant was photographed much more frequently and showed higher temporal activity frequency than White-necklaced Partridge or Cabot's Tragopan. Silver Pheasant was camera-captured most frequently in summer, and other two species in winters. All three species had two daytime activity peaks: between 6:00 a.m. and 10:00 a.m., and between 5:00 p.m. and 7:00 p.m., respectively. Our estimated abundance and detection probability from the N-mixture model were variable by season. In particular, all three species showed greater abundance in summer than in winter, and estimated abundance patterns of all three species were more similar with observed cameratrapping counts in summers. Moreover, in winter, elevation had a positive impact on abundance of Silver Pheasant and Cabot's Tragopan, but not on White-necklaced Partridge. Conclusions: Our results demonstrate that the N-mixture model performed well in the estimation of temporal population abundance at local fixed permanent plots in mountain habitat in southern China, based on the modeling of repeated camera-trapping counts. The seasonal differences in abundance of the three endemic bird species and the

Understanding distribution and occupancy of Himalayan monal in Uttarkashi district, Uttarakhand for conservation and management planning

“…However, this needs to be further tested with increased sample size and comparison between the sites with high and low human disturbances. Other pheasants have shown some extent of overlap in temporal activity patterns during the breeding season with livestock (Fan et al 2020) and observed a similar activity pattern as Himalayan monal (Zou et al 2019).…”

“…), r(.) to estimate the abundance and associated parameters of Himalayan monal following (Royle and Nichols 2003, Singh et al 2015, Zou et al 2019).…”

Camera Trapping Reveals Spatiotemporal Partitioning Patterns and Conservation Implications for Two Sympatric Pheasant Species in the Qilian Mountains, Northwestern China

“…The morphology of the study species makes it impossible to visually distinguish individuals reliably. Therefore, detection records were analyzed with widely accepted methods: (i) one or more individuals of the same species presenting consecutive records taken within 30 min or (ii) consecutive records of individuals of different species [12,38,56,57]. For each detection record, we recorded the site, species, date, time, elevation, and group size (the maximum number of individuals recorded during a 30 min period for a single occurrence event).…”

“…To assess monthly activity patterns of EP and BP, we calculated the percentage ratio of detection records for each month (the monthly number of detection records for each species divided by total records for both species per month), to decrease the difference between comparisons of absolute numbers of events. This was a proven method for reliable estimation of monthly activity levels, since the number of camera traps and monitoring days for both species was equivalent throughout the study period [12]. Similarly, we also assessed a monthly change in the number of different group sizes captured for each month in which camera traps were active.…”

“…To minimize the negative impacts of interspecific competition, species generally tend to be partitioned in time, space, or food resources [6,[8][9][10][11]. Animals use time as a resource that can mitigate interference or competition by shifting their activity patterns over the day and month [4,12]. For example, sympatric species of mammals in various orders (e.g., Carnivora, Cetartiodactyla or Rodentia) exhibit significant activity peak dislocations that alleviate competition [3,[13][14][15].…”