Although Brazil is a megadiverse country and thus a conservation priority, no study has yet quantified conservation gaps in the Brazilian protected areas (PAs) using extensive empirical data. Here, we evaluate the degree of biodiversity protection and knowledge within all the Brazilian PAs through a gap analysis of vertebrate, arthropod and angiosperm occurrences and phylogenetic data. Our results show that the knowledge on biodiversity in most Brazilian PAs remain scant as 71% of PAs have less than 0.01 species records per km2. Almost 55% of Brazilian species and about 40% of evolutionary lineages are not found in PAs, while most species have less than 30% of their geographic distribution within PAs. Moreover, the current PA network fails to protect the majority of endemic species. Most importantly, these results are similar for all taxonomic groups analysed here. The methods and results of our countrywide assessment are suggested to help design further inventories in order to map and secure the key biodiversity of the Brazilian PAs. In addition, our study illustrates the most common biodiversity knowledge shortfalls in the tropics.
Aim The knowledge of biodiversity facets such as species composition, distribution and ecological niche is fundamental for the construction of biogeographic hypotheses and conservation strategies. However, the knowledge on these facets is affected by major shortfalls, which are even more pronounced in the tropics. This study aims to evaluate the effect of sampling bias and variation in collection effort on Linnean, Wallacean and Hutchinsonian shortfalls and diversity measures as species richness, endemism and beta-diversity. Location Brazil.Methods We have built a database with over 1.5 million records of arthropods, vertebrates and angiosperms of Brazil, based on specimens deposited in scientific collections and on the taxonomic literature. We used null models to test the collection bias regarding the proximity to access routes. We also tested the influence of sampling effort on diversity measures by regression models. To investigate the Wallacean shortfall, we modelled the geographic distribution of over 4000 species and compared their observed distribution with models. To quantify the Hutchinsonian shortfall, we used environmental Euclidean distance of the records to identify regions with poorly sampled environmental conditions. To estimate the Linnean shortfall, we measured the similarity of species composition between regions close to and far from access routes. Results We demonstrated that despite the differences in sampling effort, the strong collection bias affects all taxonomic groups equally, generating a pattern of spatially biased sampling effort. This collection pattern contributes greatly to the biodiversity knowledge shortfalls, which directly affects the knowledge on the distribution patterns of diversity.Main conclusions The knowledge on species richness, species composition and endemism in the Brazilian biodiversity is strongly biased spatially. Despite differences in sampling effort for each taxonomic group, roadside bias affected them equally. Species composition similarity decreased with the distance from access routes, suggesting collection surveys at sites far from roads could increase the probability of sampling new geographic records or new species.
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