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Amazon deforestation causes severe climatic and ecological disruptions, with negative consequences for the livelihood of forest-dependent peoples. To avoid further disruptions, Brazil will need to take bold steps to eliminate both illegal and legal Amazon deforestation over the short term. Amazon deforestation declined by 70% between 2005 and 2014 due to drops in commodity prices and interventions by federal and state governments, such as law enforcement campaigns and credit restrictions for landowners who deforest illegally. Despite these impressive achievements, Brazil still deforests 5,000 km 2 of Amazonian forests each year. How then will Brazil eliminate Amazon deforestation altogether if the country is only committed to cut illegal deforestation by 2030-as stated in its Intended Nationally Determined Contributions (iNDC) to the 2015 climate change treaty meeting in Paris? Here we provide an analysis of the major socioeconomic political threats that could constrain Brazil from achieving its current goals. We then propose six fundamental strategies to help Brazil achieve a more ambitious goal to eliminate all major legal and illegal Amazon deforestation. These strategies involve bringing social and environmental safeguards to the infrastructure plans in the region, consolidating and expanding positive incentives for the production of sustainable commodities, establishing a new policy to guarantee the social and environmental sustainability of rural settlements, fully implementing the national legislation protecting forests (the Forest Code), protecting the land rights of indigenous people and traditional communities, and expanding the existing network of protected areas, allocating the 80 million hectares of not designated public forests as protected areas or areas for sustainable use of timber and non-timber forest products. The implementation of these strategies however depends on the formulation of a new development paradigm that promotes economic growth, social justice and productive agriculture, while protecting the fundamentally important ecological services of tropical forests.

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The success of jurisdictional reducing emissions from deforestation and forest degradation (REDD+) initiatives is entirely dependent on how the REDD+ benefits are distributed among the stakeholders seeking to preserve the native vegetation and is considered one of the main challenges of REDD+. Among the existing benefit-sharing options, the adoption of the stock-and-flow approach to share REDD+ benefits has afforded fair jurisdictional systems in the states of Acre and Mato Grosso in the Brazilian Amazon. This innovative perspective is also the dividing line between inequitable and socially balanced jurisdictional REDD+ initiatives. However, these jurisdictions present challenges to fully implementing a robust benefit-sharing mechanism including the stock-and-flow approach and guaranteeing that resources will be accessible to the relevant beneficiaries. To better understand these challenges, we applied the Options Assessment Framework (OAF), a methodology proposed by the World Bank to evaluate the capacity to implement an effective benefit-sharing mechanism for REDD+, in Acre and Mato Grosso. The results indicated that these jurisdictions need to strengthen their conditions to guarantee the multi-faceted functionality of this mechanism and determine what aspects need more attention and where resources should be invested. Additionally, the results indicated that an equitable benefit-sharing mechanism is, by far, the main challenge faced by jurisdictions. Despite being a more evolved state in its REDD+ policies, Acre still needs to improve its institutional capacities, particularly in its local civil society organizations, to help communities access these benefits. The state of Mato Grosso, on the other hand, is still engaging in its REDD+ initiative and needs its institutional capacities to further mature to better organize its monitoring mechanisms and governance.

The Haseman & Elston (1972) sibling-pair regression method has been used to detect and estimate the variance contribution to observed values of a quantitative trait by allelic variation in specific candidate genes. The procedure was developed under a model with a single biallelic trait locus. This assumption does not hold for several known systems. In this paper we prove that for candidate gene analysis the Haseman-Elston procedure extends to the case of multiple trait loci, each possibly having more than two alleles. Simulation experiments comparing single-locus to two-locus models show that fitting the extended regression equations maintains nominal significance levels, but the power to detect linkage to trait variation is not improved by including additional loci. These results indicate that the original proposal is statistically robust to violations of the underlying genetic model. Practical issues associated with quantifying the relative variance contribution by individual loci are also discussed. Applications of the extended regression equations to lipoprotein(a) and high density lipoprotein cholesterol are given for illustration. Interindividual variability in observed values of most quantitative traits arises from both genetic and environmental sources. The proportion of trait variation attributable to genetic factors can be estimated from phenotypic correlations among family members, but identification of the specific genetic polymorphisms that confer heritable variation in trait levels has proved considerably more difficult. The contribution to trait variation by a specific locus can be assessed by comparing the trait levels of sibling pairs sharing different numbers of alleles at the locus. If allelic variation in a candidate gene is associated with variation in a trait, then trait levels should be more similar in siblings sharing both alleles of the candidate gene identical by descent (ibd) than in siblings sharing neither allele ibd. Conversely, if variation in a candidate gene does not influence a trait, then concordance for trait levels among siblings should be independent of the number of alleles of the candidate gene they share. Haseman & Elston (1972) showed that the slope of the regression of squared differences in trait values between two siblings on the proportion of alleles shared ibd at a locus provides a test statistic for linkage between the trait locus and a marker locus.The original Haseman and Elston (H-E) procedure and most subsequent extensions and related work have assumed a genetic model with a single trait locus with two alleles, and incomplete information on ibd sharing leading to the use of estimated ibd proportions. Kruglyak & Lander