Dynamic occupancy modeling of a cryptic ground-dwelling pheasant species in the Upper Blue Nile Basin in Ethiopia

Abstract

Modeling the occupancy of species in the context of habitat components is a crucial step to deliver an appropriate conservation strategy. Accounting for imperfect detection in occupancy models helps to conclude on true species distribution and occupancy. We used dynamic occupancy modeling to investigate the influence of habitat covariates on occupancy dynamics of the Near Threatened Harwood’s Francolin (Pternistis harwoodi) in the Upper Blue Nile Basin in Ethiopia. We used direct observation and playback technique to collect presence/absence data both during a wet and a dry season in 2019 and 2020. By accounting for species’ imperfect detection, the model averaged estimates of occupancy probabilities (mean ± SE) across respective seasons were 0.81 ± 0.08 and 0.79 ± 0.07 and detection probabilities were 0.47 ± 0.08 and 0.62 ± 0.06. The colonization and local extinction probability estimates between seasons were 0.59 ± 0.20 and 0.12 ± 0.07, respectively. We demonstrate that occupancy probability significantly decreased with increasing both Normalized Difference Vegetation Index (NDVI: ꞵmean ± SE = −1.83 ± 0.66; 95% CI: −3.12, −0.54) and quadratic term of slope (SL2 = −1.51 ± 0.62; 95% CI: −2.73, −0.29) in the study area. Furthermore, human disturbance index (HDI: = −1.06 ± 0.54; 95% CI: −2.12, −0.004) significantly negatively influenced the occupancy of the species. As we hypothesized, the detection probability increased significantly as a function of average temperature (0.37 ± 0.13; 95% CI: 0.12, 0.63). There were no statistically significant associations among covariates and the dynamic parameters, yet important covariates such as NDVI slightly negatively influenced colonization, whereas HDI positively influenced local extinction. The aversion of the species towards human disturbance and its persistence at lower NDVI and lower slopes has important implications for conservation strategy in the area. The current study demonstrates empirical evidence of dynamic occupancy modeling for a cryptic ground-dwelling pheasant species in the Upper Blue Nile Basin. Further study is recommended to understand spatiotemporal species-habitat association at fine and landscape scales.