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.
 Changes in land-use and climate are likely to alter moisture and substrate availability in tropical forest soils, but quantitative assessment of the role of resource constraints as regulators of soil trace gas fluxes is rather limited. The primary objective of this study was to quantify the effects of moisture and substrate availability on soil trace gas fluxes in an Amazonian regrowth forest. We measured the efflux of carbon dioxide (CO 2 ), nitric oxide (NO), nitrous oxide (N 2 O), and methane (CH 4 ) from soil in response to two experimental manipulations. In the first, we increased soil moisture availability during the dry season by irrigation; in the second, we decreased substrate availability by continuous removal of aboveground litter. In the absence of irrigation, soil CO 2 efflux decreased during the dry season while irrigation maintained soil CO 2 efflux levels similar to the wet season. Large variations in soil CO 2 efflux consistent with a significant moisture constraint on respiration were observed in response to soil wet-up and dry-down events. Annual soil C efflux for irrigated plots was 27 and 13% higher than for control plots in 2001 and 2002, respectively. Litter removal significantly reduced soil CO 2 efflux; annual soil C efflux in 2002 was 28% lower for litter removal plots compared to control plots. The annual soil C efflux:litterfall C ratio for the control treatment (4.0-5.2) was consistent with previously reported values for regrowth forests that indicate a relatively large belowground C allocation. In general, fluxes of N 2 O and CH 4 were higher during the wet season and both fluxes increased during dry-season irrigation. There was no seasonal effect on NO fluxes. Litter removal had no significant impact on N oxide or CH 4 emissions. Net soil nitrification did not respond to dry-season irrigation, but was somewhat reduced by litter removal. Overall, these results demonstrate significant soil moisture and substrate constraints on soil trace gas emissions, particularly for CO 2 , and suggest that climate and land-use changes that alter moisture and substrate availability are therefore likely to have an impact on atmosphere chemistry.
O objetivo deste trabalho foi comparar critérios para seleção de genótipos de girassol com base na média geral obtida em vários locais e sua decomposição em ambientes favoráveis e desfavoráveis e por meio de outros métodos de análise de adaptabilidade e estabilidade, como os de Eberhart & Russell, Lin & Binns, Carneiro e Carvalho et al. Foram analisados dados obtidos entre os anos de 1999 e 2004 na Rede Nacional de Ensaios de Girassol, coordenada pela Embrapa Soja e que conta com a participação de empresas públicas e privadas. Os caracteres avaliados foram rendimento de grãos e de óleo (kg ha-1). A análise da decomposição da média geral em médias de ambientes favoráveis e desfavoráveis (método da indicação com base na decomposição da média geral - IDMG) foi o critério mais adequado para a indicação de genótipos. A análise de regressão contribuiu com informações adicionais, indicando a responsividade e previsibilidade dos genótipos diante das mudanças ambientais.
scite is a Brooklyn-based startup that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.