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Examining linkages among multiple sustainable development outcomes is key for understanding sustainability transitions. Yet rigorous evidence on social and environmental outcomes of sustainable development policies remains scarce. We conduct a national-level analysis of Brazil’s flagship social protection program, Zero Hunger (ZH), which aims to reduce food insecurity and poverty. Using data from rural municipalities across Brazil and quasi-experimental causal inference techniques, we assess relationships between social protection investment and outcomes related to sustainable development goals (SDGs): "no poverty" (SDG 1), "zero hunger" (SDG 2), and "health and well being" (SDG 3). We also assess potential perverse outcomes arising from agricultural development impacting "climate action" (SDG 13) and "life on land" (SDG 15) via clearance of natural vegetation. Despite increasing daily per capita protein and kilocalorie production, summed ZH investment did not alleviate child malnutrition or infant mortality and negligibly influenced multidimensional poverty. Higher investment increased natural vegetation cover in some biomes but increased losses in the Cerrado and especially the Pampa. Effects varied substantially across subprograms. Conditional cash transfer (Bolsa Familia [BF]) was mainly associated with nonbeneficial impacts but increased protein production and improved educational participation in some states. The National Program to Strengthen Family Farming (PRONAF) was typically associated with increased food production (protein and calories), multidimensional poverty alleviation, and changes in natural vegetation. Our results inform policy development by highlighting successful elements of Brazil’s ZH program, variable outcomes across divergent food security dimensions, and synergies and trade-offs between sustainable development goals, including environmental protection. [ABSTRACT FROM AUTHOR]

Deforestation and land use change are among the most pressing anthropogenic environmental impacts. In Brazil, a resurgence of malaria in recent decades paralleled rapid deforestation and settlement in the Amazon basin, yet evidence of a deforestation-driven increase in malaria remains equivocal. We hypothesize an underlying cause of this ambiguity is that deforestation and malaria influence each other in bidirectional causal relationships--deforestation increases malaria through ecological mechanisms and malaria reduces deforestation through socioeconomic mechanisms--and that the strength of these relationships depends on the stage of land use transformation. We test these hypotheses with a large geospatial dataset encompassing 795 municipalities across 13 y (2003 to 2015) and show deforestation has a strong positive effect on malaria incidence. Our results suggest a 10% increase in deforestation leads to a 3.3% increase in malaria incidence (~9,980 additional cases associated with 1,567 additional km² lost in 2008, the study midpoint, Amazon-wide). The effect is larger in the interior and absent in outer Amazonian states where little forest remains. However, this strong effect is only detectable after controlling for a feedback of malaria burden on forest loss, whereby increased malaria burden significantly reduces forest clearing, possibly mediated by human behavior or economic development. We estimate a 1% increase in malaria incidence results in a 1.4% decrease in forest area cleared (~219 fewer km² cleared associated with 3,024 additional cases in 2008). This bidirectional socioecological feedback between deforestation and malaria, which attenuates as land use intensifies, illustrates the intimate ties between environmental change and human health. [ABSTRACT FROM AUTHOR]

Protected areas (PAs) remain the dominant policy to protect biodiversity and ecosystem services but have been shown to have limited impact when development interests force them to locations with lower deforestation pressure. Far less known is that such interests also cause widespread tempering, reduction, or removal of protection [i.e., PA downgrading, downsizing, and degazettement (PADDD)]. We inform responses to PADDD by proposing and testing a bargaining explanation for PADDD risks and deforestation impacts. We examine recent degazettements for hydropower development and rural settlements in the state of Rondônia in the Brazilian Amazon. Results support two hypotheses: (i) ineffective PAs (i.e., those where internal deforestation was similar to nearby rates) were more likely to be degazetted and (ii) degazettement of ineffective PAs caused limited, if any, additional deforestation. We also report on cases in which ineffective portions were upgraded. Overall our results suggest that enhancing PAs' ecological impacts enhances their legal durability. [ABSTRACT FROM AUTHOR]

Annual deforestation rates in the Brazilian Amazon fell by 77% between 2004 and 2011, yet have stabilized since 2009 at 5,000–7,000 km2. We provide the first submunicipality assessment, to our knowledge, of actor-specific contributions to the deforestation slowdown by linking agricultural census and remote-sensing data on deforestation and forest degradation. Almost half (36,158 km2) of the deforestation between 2004 and 2011 occurred in areas dominated by larger properties (>500 ha), whereas only 12% (9,720 km2) occurred in areas dominated by smallholder properties (<100 ha). In addition, forests in areas dominated by smallholders tend to be less fragmented and less degraded. However, although annual deforestation rates fell during this period by 68–85% for all actors, the contribution of the largest landholders (>2,500 ha) to annual deforestation decreased over time (63% decrease between 2005 and 2011), whereas that of smallholders went up by a similar amount (69%) during the same period. In addition, the deforestation share attributable to remote areas increased by 88% between 2009 and 2011. These observations are consistent across the Brazilian Amazon, regardless of geographical differences in actor dominance or socioenvironmental context. Our findings suggest that deforestation policies to date, which have been particularly focused on command and control measures on larger properties in deforestation hotspots, may be increasingly limited in their effectiveness and fail to address all actors equally. Further reductions in deforestation are likely to be increasingly costly and require actor-tailored approaches, including better monitoring to detect small-scale deforestation and a shift toward more incentive-based conservation policies. [ABSTRACT FROM AUTHOR]

The Brazilian Amazon is one of the most rapidly developing agricultural areas in the world and represents a potentially large future source of greenhouse gases from land clearing and subsequent agricultural management In an integrated approach, we estimate the greenhouse gas dynamics of natural ecosystems and agricultural ecosystems after. clearing in the context of a future climate. We examine scenarios of deforestation and postclearing land use to estimate the future (2006- 2050) impacts on carbon dioxide (CO2), methane (CH4). and nitrous oxide (N2O) emissions from the agricultural frontier state of Mato Grosso, using a process-based biogeochemistry model, the Terrestrial Ecosystems Model (TEM). We estimate a net emission of greenhouse gases from Mato Grosso, ranging from 2.8 to 15.9 Pg CO2-equivalents (CO2-e) from 2006 to 2050. Deforestation is the largest source of greenhouse gas emissions over this period, but land uses following clearing account for a substantial portion (24-49%) of the net greenhouse gas budget Due to land-cover and land-use change, there is a small foregone carbon sequestration of 0.2-0.4 Pg CO2-e by natural forests and cerrado between 2006 and 2050. Both deforestation and future land- use management play important roles in the net greenhouse gas emissions of this frontier, suggesting that both should be considered in emissions policies. We find that avoided deforestation remains the best strategy for minimizing future greenhouse gas emissions from Mato Grosso. [ABSTRACT FROM AUTHOR]

The planned expansion of biofuel plantations in Brazil could potentially cause both direct and indirect land-use changes (e.g., biofuel plantations replace rangelands, which replace forests). In this study, we use a spatially explicit model to project land-use changes caused by that expansion in 2020, assuming that ethanol (biodiesel) production increases by 35 (4) x 109 liter in the 2003-2020 period. Our simulations show that direct land-use changes will have a small impact on carbon emissions because most biofuel plantations would replace rangeland areas. However, indirect land-use changes, especially those pushing the rangeland frontier into the Amazonian forests, could offset the carbon savings from biofuels. Sugarcane ethanol and soybean biodiesel each contribute to nearly half of the projected indirect deforestation of 121,970 km2 by 2020, creating a carbon debt that would take about 250 years to be repaid using these biofuels instead of fossil fuels. We also tested different crops that could serve as feedstock to fulfill Brazil's biodiesel demand and found that oil palm would cause the least land-use changes and associated carbon debt. The modeled livestock density increases by 0.09 head per hectare. But a higher increase of 0.13 head per hectare in the average livestock density throughout the country could avoid the indirect land-use changes caused by biofuels (even with soybean as the biodiesel feedstock), while still fulfilling all food and bioenergy demands. We suggest that a closer collaboration or strengthened institutional link between the biofuel and cattle-ranching sectors in the coming years is crucial for effective carbon savings from biofuels in Brazil. [ABSTRACT FROM AUTHOR]