Ecological traits modulate bird species responses to forest fragmentation in an Amazonian anthropogenic archipelago

• Published in: Diversity & distributions Vol. 24; no. 3; pp. 387 - 402
• Main Authors: Bueno, Anderson Saldanha, Dantas, Sidnei M., Henriques, Luiza Magalli Pinto, Peres, Carlos A., Strubbe, Diederik
• Format: Journal Article
• Language: English
• Published: Oxford John Wiley & Sons, Inc 01.03.2018
• Subjects: Abundance; Anthropogenic factors; Birds; Decay; detectability; Estimates; Forests; Fragmentation; Habitats; insularization; island biogeography; Mathematical models; occupancy; Phylogeny; Predictions; rarity; Small mammals; Species richness; Species-area relationship; species‐area relationships
• ISSN: 1366-9516; 1472-4642
• DOI: 10.1111/ddi.12689

Aim We assessed patterns of avian species loss and the role of morpho‐ecological traits in explaining species vulnerability to forest fragmentation in an anthropogenic island system. We also contrasted observed and detectability‐corrected estimates of island occupancy, which are often used to infer species vulnerability. Location Tucuruí Hydroelectric Reservoir, eastern Brazilian Amazonia. Methods We surveyed forest birds within 36 islands (3.4–2,551.5 ha) after 22 years of post‐isolation history. We applied species–area relationships to assess differential patterns of species loss among three data sets: all species, forest specialists and habitat generalists. After controlling for phylogenetic non‐independence, we used observed and detectability‐corrected estimates of island occupancy separately to build competing models as a function of species traits. The magnitude of the difference between these estimates of island occupancy was contrasted against species detectability. Results The rate of species loss as a function of island area reduction was higher for forest specialists than for habitat generalists. Accounting for the area effect, forest fragmentation did not affect the overall number of species regardless of the data set. Only the interactive model including natural abundance, habitat breadth and geographic range size was strongly supported for both estimates of island occupancy. For 30 species with detection probabilities below 30%, detectability‐corrected estimates were at least tenfold higher than those observed. Conversely, differences between estimates were negligible or non‐existent for all 31 species with detection probabilities exceeding 45.5%. Main conclusions Predicted decay of avian species richness induced by forest loss is affected by the degree of habitat specialisation of the species under consideration, and may be unrelated to forest fragmentation per se. Natural abundance was the main predictor of species island occupancy, although habitat breadth and geographic range size also played a role. We caution against using occupancy models for low‐detectability species, because overestimates of island occupancy reduce the power of species‐level predictions of vulnerability.