Evaluating the Brazilian system of strictly protected areas using owls
as an indicator group
Abstract
AIM To set or assess conservation and management efforts based on the
knowledge of the total biodiversity is unrealistic. For such a reason,
the identification of priority areas based on biodiversity hotspots
determined through indicator groups has become a common approach. This
requires a crystal-clear knowledge of the taxonomy and distribution of
such indicator groups, which in the Tropics can be troublesome,
especially for rare or secretive taxa. Thus, we assessed the potential
distribution of 21 species and 21 subspecies of Brazilian Strigidae
through Species Distribution Modelling (SDM) based on a Maximum Entropy
approach. LOCATION Brazil. METHODS We (1) gathered and filtered
occurrences data for Brazilian Strigidae, (2) generated SDMs for each
species and subspecies, (3) evaluated the niche similarity among
subspecies, (4) built up species’ richness maps, and (5) contrasted such
information to the strict protection areas in Brazil. RESULTS With 81%
of the Brazilian species recorded, both the Atlantic Forest and the
Cerrado have the highest richness, followed by the Amazonia (67%),
Pampa (62%), Caatinga (57%) and Pantanal (48%). However, the
comparison of the recorded and predicted richness suggests overall
incomplete inventories, especially in the Caatinga and Pantanal. On the
other hand, subspecies showed marked niches divergencies, suggesting
that the recognized Strigidae species richness is underestimated in
Brazil. Cerrado and Atlantic forest are the most threatened biomes, with
preservation areas relatively small and sparse. MAIN CONCLUSIONS We
demonstrated that the situation of Brazilian Strigidae involves an
underestimated species richness, within an inadequate framework of
protected areas, in a megadiverse Country characterized by high rates of
habitat transformations. Thus, our study is a hurrying call to explore
owl lineage diversification in Brazil to improve biodiversity-related
conservation efforts.