2025/05/20 by Carlos Salustio‐Gomes, Mauro Pichorim · 1 voice
Environmental Science · #Ecology and Vegetation Dynamics Studies #Land Use and Ecosystem Services #Wildlife Ecology and Conservation
paper · doi:10.1080/15594491.2025.2497004
openalex publication_date 2025/05/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/06/14
Environmental features are predictors that assist in identifying patterns of species richness. To obtain accurate richness estimates, occupancy modeling is a useful tool because it can encompass variables at multi-scales and considers imperfect detection. We estimated the relative bird richness in a protected area in the Atlantic Forest to understand habitat requirements of a species assemblage as a function of environmental factors. Our study spanned dry and rainy seasons and covered four habitats (seasonal semideciduous forest, restinga, a planted experimental forest, and patch edge) across 42 sampling sites. Using point counts, we recorded all bird species during three visits at each site. We estimated species richness across temporal and spatial scales using community occupancy modeling. We recorded 86 species where four were threatened: the Pectoral Antwren (Herpsilochmus pectoralis), the White-collared Kite (Leptodon forbesi), the Rusty-margined Guan (Penelope superciliaris), and the Long-tailed Woodnymph (Thalurania watertonii). Relative species richness in the rainy season (ψ = 0.31–0.66) was lower compared to the dry season (ψ = 0.37–0.76). Open habitats had a higher richness (ψ of patch edge = 0.66 and 0.76, ψ of restinga = 0.51 and 0.62) than seasonal semideciduous forest (ψ = 0.31 and 0.37) and planted experimental forest (ψ = 0.36 and 0.40). Rates of species gain varied among habitats (γ = 0.15–0.59), unlike species loss, which did not vary (ε = 0.15). Richness at each site was negatively affected by pond distance, tree cover, and diameter of tree trunks. The low richness observed in seasonal semideciduous forest is probably a reflection of negative impacts on the area, such as the effects of forest fragmentation. We also highlight that occupancy modeling results in reliable estimates for ecological inferences, aiding in understanding patterns that can be evaluated and used in habitats and community conservation strategies.