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Avian community mist net survey data from Luba/Ureca road elevational gradient, Bioko Island, Equatorial Guinea

Cite this dataset

Miller, Steven et al. (2021). Avian community mist net survey data from Luba/Ureca road elevational gradient, Bioko Island, Equatorial Guinea [Dataset]. Dryad. https://doi.org/10.5061/dryad.rjdfn2zbp

Abstract

Understanding interactive effects between anthropogenic disturbance and abiotic factors on species turnover can help identify and prioritize conservation of potentially vulnerable tropical bird communities. We investigated potential factors influencing avian understory community composition along a recently constructed road across three elevations (300, 800 and 1200 m), each with two sampling sites (road edge vs interior forest), over a four-year period on Bioko Island, Equatorial Guinea. Obligate ant following species were the most abundant guild sampled accounting for 23% of total species diversity within the data set, which increased to 40% when including occasional ant following species. Habitat associated with elevation was the most significant factor influencing the composition of avian communities at all three elevations.  Additionally, we identified species with clear statistical associations for each elevation: the yellow-lored bristlebill (Bleda notatus), olive sunbird (Cyanomitra obscura), and white-tailed warbler (Poliolias lopezi). We found evidence for significant community differences between the disturbance edge and interior forest transects at 300 m only. Likewise, understory insectivores were found at higher numbers within the interior forest transect at this elevation. Based on the data presented here, we suggest low elevation avian understory insectivores should be considered focal species for future assessment studies in this area. Furthermore, since many traditional protected areas focus on upland habitat containing high species endemism, our findings emphasize the importance of equally conserving lowland elevations as they may house commonly overlooked yet important and diverse segments of the bird community. 

Methods

Data was collected via mist net capture and processed using mixed modeling with the package "lme4" and ordination using non-metric multidimensional scaling with the package "vegan" in R.

Usage notes

Readme file uploaded