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.

Wildfires, exacerbated by extreme weather events and land use, threaten to change the Amazon from a net carbon sink to a net carbon source. Here, we develop and apply a coupled ecosystem-fire model to quantify how greenhouse gas-driven drying and warming would affect wildfires and associated CO 2 emissions in the southern Brazilian Amazon. Regional climate projections suggest that Amazon fire regimes will intensify under both low-and high-emission scenarios. Our results indicate that projected climatic changes will double the area burned by wildfires, affecting up to 16% of the region's forests by 2050. Although these fires could emit as much as 17.0 Pg of CO 2 equivalent to the atmosphere, avoiding new deforestation could cut total net fire emissions in half and help prevent fires from escaping into protected areas and indigenous lands. Aggressive efforts to eliminate ignition sources and suppress wildfires will be critical to conserve southern Amazon forests.

Amazonian rivers are usually suggested as dispersal barriers, limiting biogeographic units. This is evident in a widely accepted Areas of Endemism (AoEs) hypothesis proposed for Amazonian birds. We empirically test this hypothesis based on quantitative analyses of species distribution. We compiled a database of bird species and subspecies distribution records, and used this dataset to identify AoEs through three different methods. Our results show that the currently accepted Amazonian AoEs are not consistent with areas identified, which were generally congruent among datasets and methods. Some Amazonian rivers represent limits of AoEs, but these areas are not congruent with those previously proposed. However, spatial variation in species composition is correlated with largest Amazonian rivers. Overall, the previously proposed Amazonian AoEs are not consistent with the evidence from bird distribution. However, the fact that major rivers coincide with breaks in species composition suggest they can act as dispersal barriers, though not necessarily for all bird taxa. This scenario indicates a more complex picture of the Amazonian bird distribution than previously imagined.

We propose a new approach for identification of areas of endemism, the Geographical Interpolation of Endemism (GIE), based on kernel spatial interpolation. This method differs from others in being independent of grid cells. This new approach is based on estimating the overlap between the distribution of species through a kernel interpolation of centroids of species distribution and areas of influence defined from the distance between the centroid and the farthest point of occurrence of each species. We used this method to delimit areas of endemism of spiders from Brazil. To assess the effectiveness of GIE, we analyzed the same data using Parsimony Analysis of Endemism and NDM and compared the areas identified through each method. The analyses using GIE identified 101 areas of endemism of spiders in Brazil GIE demonstrated to be effective in identifying areas of endemism in multiple scales, with fuzzy edges and supported by more synendemic species than in the other methods. The areas of endemism identified with GIE were generally congruent with those identified for other taxonomic groups, suggesting that common processes can be responsible for the origin and maintenance of these biogeographic units.

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The Brazilian Caatinga is part of the seasonally dry tropical forests, a vegetation type disjunctly distributed throughout the Neotropics. It has been suggested that during Pleistocene glacial periods, these dry forests had a continuous distribution, so that these climatic shifts may have acted as important driving forces of the Caatinga biota diversification. To address how these events affected the distribution of a dry forest species, we chose Sicarius cariri, a spider endemic to the Caatinga, as a model. We studied the phylogeography of one mitochondrial and one nuclear gene and reconstructed the paleodistribution of the species using modelling algorithms. We found two allopatric and deeply divergent clades within S. cariri, suggesting that this species as currently recognized might consist of more than one independently evolving lineage. Sicarius cariri populations are highly structured, with low haplotype sharing among localities, high fixation index and isolation by distance. Models of paleodistribution, Bayesian reconstructions and coalescent simulations suggest that this species experienced a reduction in its population size during glacial periods, rather than the expansion expected by previous hypotheses on the paleodistribution of dry forest taxa. In addition to that, major splits of intraspecific lineages of S. cariri took place in the Pliocene. Taken together, these results indicate S. cariri has a complex diversification history dating back to the Tertiary, suggesting the history of dry forest taxa may be significantly older than previously thought.