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Cerrado is the second largest biome in South America and accounted for the second largest contribution to carbon emissions in Brazil for the last 10 years, mainly due to land-use changes. It comprises approximately 2 million km2 and is divided into 22 ecoregions, based on environmental conditions and vegetation. The most dominant vegetation type is cerrado sensu stricto (cerrado ss), a savanna woodland. Quantifying variation of biomass density of this vegetation is crucial for climate change mitigation policies. Integrating remote sensing data with adequate allometric equations and field-based data sets can provide large-scale estimates of biomass. We developed individual-tree aboveground biomass (AGB) allometric models to compare different regression techniques and explanatory variables. We applied the model with the strongest fit to a comprehensive ground-based data set (77 sites, 893 plots, and 95,484 trees) to describe AGB density variation of cerrado ss. We also investigated the influence of physiographic and climatological variables on AGB density; this analysis was restricted to 68 sites because eight sites could not be classified into a specific ecoregion, and one site had no soil texture data. In addition, we developed two models to estimate plot AGB density based on plot basal area. Our data show that for individual-tree AGB models a) log-log linear models provided better estimates than nonlinear power models; b) including species as a random effect improved model fit; c) diameter at 30 cm above ground was a reliable predictor for individual-tree AGB, and although height significantly improved model fit, species wood density did not. Mean tree AGB density in cerrado ss was 22.9 tons ha-1 (95% confidence interval = ± 2.2) and varied widely between ecoregions (8.8 to 42.2 tons ha-1), within ecoregions (e.g. 4.8 to 39.5 tons ha-1), and even within sites (24.3 to 69.9 tons ha-1). Biomass density tended to be higher in sites close to the Amazon. Ecoregion explained 42% of biomass variation between the 68 sites (P < 0.01) and shows strong potential as a parameter for classifying regional biomass variation in the Cerrado. [ABSTRACT FROM AUTHOR]

Cabruca agroforestry systems play a crucial role as ecological corridors in biodiversity conservation on the south coast of Bahia. The decline in these agroecosystems due to land-use changes poses as a major threat to Atlantic Forest biodiversity conservation. Therefore, efficient agricultural extension actions towards the maintenance of these agroforestry systems are paramount. This research evaluated the process of construction and sharing of knowledge in agricultural extension practices toward agroecological management of the Cabruca in three agrarian reform settlements, and the challenges for the persistence of Cabruca in this region. We interviewed seven farmers and three extension agents from the Cabruca Institute. The study showed that most of the proposed practices adopted by farmers were already part of the traditional Cabruca management. The main limitations for the adoption of new practices were that they required increased labor, which is scarce and expensive. In fact, exodus and aging of the rural population remain major threats for long-term sustainability and persistence of Cabruca agroecosystems. Other limitations for organic management include the absence of differentiated price and marketing channels for organic cocoa and other products for the Cabruca social biodiversity. Although the process of construction and sharing of knowledge was participatory, overall community participation in the process was low. Extensionists should devise and implement innovative community engagement strategies to empower these small-scale farmer communities to ensure the persistence of Cabruca in the region and consolidate organic management of Cabruca agroecosystems. [ABSTRACT FROM AUTHOR]

Climate change is a global phenomenon that affects biophysical systems and human well-being. The Paris Agreement of the United Nations Framework Convention on Climate Change entered into force in 2016 with the objective of strengthening the global response to climate change by keeping global temperature rise this century well below 2 °C above pre-industrial levels and to pursue efforts to limit the temperature increase even further to 1.5 °C. The agreement requires all Parties to submit their "nationally determined contributions" (NDCs) and to strengthen these efforts in the years ahead. Reducing carbon emissions from deforestation and forest degradation is an important strategy for mitigating climate change, particularly in developing countries with large forests. Extensive tropical forest loss and degradation have increased awareness at the international level of the need to undertake large-scale ecological restoration, highlighting the need to identify cases in which restoration strategies can contribute to mitigation and adaptation. Here we consider Brazil as a case study to evaluate the benefits and challenges of implementing large-scale restoration programs in developing countries. The Brazilian NDC included the target of restoring and reforesting 12 million hectares of forests for multiple uses by 2030. Restoration of native vegetation is one of the foundations of sustainable rural development in Brazil and should consider multiple purposes, from biodiversity and ecosystem services conservation to social and economic development. However, ecological restoration still presents substantial challenges for tropical and mega-diverse countries, including the need to develop plans that are technically and financially feasible, as well as public policies and monitoring instruments that can assess effectiveness. The planning, execution, and monitoring of restoration efforts strongly depend on the context and the diagnosis of the area with respect to reference ecosystems (e.g., forests, savannas, grasslands, wetlands). In addition, poor integration of climate change policies at the national and subnational levels and with other sectorial policies constrains the large-scale implementation of restoration programs. The case of Brazil shows that slowing deforestation is possible; however, this analysis highlights the need for increased national commitment and international support for actions that require large-scale transformations of the forest sector regarding ecosystem restoration efforts. Scaling up the ambitions and actions of the Paris Agreement implies the need for a global framework that recognizes landscape restoration as a cost-effective nature-based solution and that supports countries in addressing their remaining needs, challenges, and barriers. [ABSTRACT FROM AUTHOR]

Large-scale land governance and environmental monitoring are huge challenges for tropical countries with significant forest cover. In this discussion paper, we analyzed the conditions and achievements of the implementation of the Brazilian Rural Environmental Registry (CAR). CAR was an important breakthrough of the Native Vegetation Protection Law for environmental monitoring in Brazil. CAR is the mandatory and self-declaratory registry for rural properties. Owners must provide georeferenced delimitation of their property’s boundaries and legally protected areas, such as Areas of Permanent Preservation and Legal Reserves. We used the example of the State of Mato Grosso (transition between the two largest biomes in Brazil – Amazon and Cerrado) to discuss how CAR and its national information system (called SICAR) provide important inputs for land-use, environmental, economic, territorial, and food security policies. Future policies should include increasing investments and coordination between different sectors to integrate CAR and conservation efforts with agricultural production and sustainable management. [ABSTRACT FROM AUTHOR]

The field of strategic human resource management (SHRM) is mainly concerned with the development of HRM systems that create value to the organization and its internal customers. In this paper, we evaluate the effects of high performance work systems (HPWS) and leader-member exchange (LMX) quality on employee engagement, and also the relationship between employee engagement and turnover intention. The research involved 189 employees of a nonprofit Brazilian organization. Results from hierarchical multiple regression analyses showed that HPWS and LMX quality have a positive and significant effect on employee engagement. It was also shown that engagement has a negative and significant effect on employees’ turnover intention. Implications of these findings are discussed. [ABSTRACT FROM AUTHOR]

We used stationary matrix models to assess size–class dynamics of a protected neotropical gallery forest in Central Brazil, and tested their predictive capacity for different calibration periods. Data series comprised of all trees (with diameter ≥ 10 cm) registered in 151 (10 m × 20 m) permanent plots in the years of 1985, 1988, 1991, 1994, 1999, 2004, and 2009. Demographic and diameter growth rates fluctuated, and recruitment slightly decreased after 1991. All models produced reliable ( P > 0.05) short-term projections (≤10 years). However, models calibrated before 1991 produced unreliable >10-year projections. The model calibrated over the 1991–1994 period reliably predicted size–class structure after 5 consecutive 3-year simulations (15 years). Results show that short-term (10-year) size–class structure of protected neotropical rainforests can be reliably predicted using stationary matrix models; and that predictions are slightly sensitive to the calibration period. Although stand dynamics were variable and affected by environmental stochasticity, size–class structural dynamics remained close to constant after 1991, since all projections from stationary models calibrated after that year were similar to the observed data ( P > 0.05). This indicates that, under the recent levels of natural disturbances, the forest has maintained stability in the size–class dynamics. [ABSTRACT FROM AUTHOR]

There are 553 development banks in the world: 18% of these institutions have emerged since the 2008 financial crisis. There is a large theoretical literature on such institutions, but the evidence on their effectiveness is scattered. This paper provides a systematic review of causal effect studies of one of the largest and most representative development banks in the world, the Brazilian Development Bank (BNDES). We review 48 academic papers that estimate BNDES loans and credit programs impact in several policy dimensions. In general, the evidence indicates that development banks can be an effective instrument to increase investment, exports, employment and GDP, particularly when borrowers are micro, small and medium-sized companies. The Brazilian experience also suggests that development banks can be an important tool to fight against climate change, reducing deforestation. On the other hand, evidence indicates that the greatest difficulty for these institutions is to generate positive impacts on productivity, an essential variable for economic growth. Finally, the evidence is inconclusive on political influence on development bank's loans. [ABSTRACT FROM AUTHOR]

Structural and floristic changes of a fire-protected cerrado sensu stricto are described over a 13-year period. The study site is located in a biological reserve (2,800 ha) surrounded by large Pinus spp. and Eucalyptus spp. plantations (36,000 ha), in southwestern Bahia, Brazil. The region occurs in the outer-core of the Cerrado domain, near the Cerrado-Caatinga ecotone, and is mainly occupied by pasture and cropland. Surveys were carried out in 1991 and 2004 in 13 permanent plots (20 × 50 m). Stems with diameter ≥5 cm at 0.30 m above ground level were identified and measured. Floristic changes were significant (Sørensen´s index = 0.45). Species number rose from 62 to 84 (35.48%). Alpha diversity increased significantly ( P > 0.001). New species migrated to the area, and there was an expansion of many fire-sensitive species. Woody layer expanded, increasing 19.09% in density and 14.93% in basal area. Diameter distributions followed a “reversed-j” pattern on both occasions, but differed ( P > 0.05) due to a significant increase in the first two size-classes, indicating a high recruitment. Community dynamics was high and had a positive balance between recruitment (3.72% yr−1) and mortality (1.93% yr−1). Conversely, mean annual increment was very small, 0.096 cm yr−1 (SD = 0.14; N = 808). Most species, including many dominant ones, had a positive balance in favor of recruitment and low turnover, indicating that although species immigration rate is high (1.42 spp ha−1), structural changes in species composition happens at a much slower pace. The surrounding forest plantations are permeable and do not limit species immigration; and may be connecting the reserve with the larger neighboring natural fragments, providing an abundant source for diaspores, and possibly neutralizing any fragmentation effects. Succession is also influenced by the ecotonal condition. The structure and floristics of the cerrado sensu stricto at this site (under present climatic conditions) is fire-dependent. [ABSTRACT FROM AUTHOR]

The original version of the article unfortunately contained an error. [ABSTRACT FROM AUTHOR]

• We presented a new benchmark map of AGWB in the Cerrado for the year 2019. • We explored multi-sensor indices to predict AGWB over different vegetation types. • We compiled a unique field dataset of the vegetation from a network of researchers. • Machine learning (CART and RF algorithms) was used to map AGWB. • We improved woody biomass stocks estimates especially in savanna woodlands. The Brazilian Cerrado biome consists of a highly heterogeneous tropical savanna, and is one of the world's biodiversity hotspots. High rates of deforestation, however, place it as the second-largest source of carbon emissions in Brazil. Due to its heterogeneity, biomass and carbon stocks in the Cerrado vegetation are highly variable, and mapping and monitoring these stocks are not a trivial effort. To address this challenge, we built an aboveground woody biomass (AGWB) model for the Cerrado biome using 30-m resolution optical satellite imagery (Landsat-5 and Landsat-8), 25-m resolution SAR imagery (ALOS and ALOS-2), and a set of plot-based and LiDAR-derived AGWB estimates (n = 1858) from a wide network of researchers in Brazil. We implemented both a Classification and Regression Tree (CART) and a Random Forest (RF) algorithm to model AGWB over the native vegetation in the year 2019 (as classified by MapBiomas) in the Cerrado. The RF algorithms resulted in a slightly better result (R2 = 53%; rel. RMSE = 57%) than the CART model (R2 = 45%; rel. RMSE = 63%), but our map shows an underestimation of very high AGWB (negative bias over 200 t ha−1) and a slight overestimation of low AGWB (positive bias), especially in the RF model (bias of 1.19 t ha−1 against 0.86 t ha−1 for the CART model). We believe we have contributed to knowledge on the woody biomass stocks in the biome, especially in the predominant savanna woodlands, which is where the highest current rates of conversion take place in the Cerrado. [ABSTRACT FROM AUTHOR]

The tropical savanna in Brazil known as the Cerrado covers circa 23% of the Brazilian territory, but only 3% of this area is protected. High rates of deforestation and degradation in the woodland and forest areas have made the Cerrado the second-largest source of carbon emissions in Brazil. However, data on these emissions are highly uncertain because of the spatial and temporal variability of the aboveground biomass (AGB) in this biome. Remote-sensing data combined with local vegetation inventories provide the means to quantify the AGB at large scales. Here, we quantify the spatial distribution of woody AGB in the Rio Vermelho watershed, located in the centre of the Cerrado, at a high spatial resolution of 30 metres, with a random forest (RF) machine-learning approach. We produced the first high-resolution map of the AGB for a region in the Brazilian Cerrado using a combination of vegetation inventory plots, airborne light detection and ranging (LiDAR) data, and multispectral and radar satellite images (Landsat 8 and ALOS-2/PALSAR-2). A combination of random forest (RF) models and jackknife analyses enabled us to select the best remote-sensing variables to quantify the AGB on a large scale. Overall, the relationship between the ground data from vegetation inventories and remote-sensing variables was strong (R2 = 0.89), with a root-mean-square error (RMSE) of 7.58 Mg ha−1 and a bias of 0.43 Mg ha−1. [ABSTRACT FROM AUTHOR]

The paper 'Are Brazil deforesters avoiding detection?' recently published in Conservation Letters by Richards et al. 2016 has critical shortcomings and conclusions based on biased and not very robust analyses. Here, we provide clarifications to some of the most critical points regarding the monitoring of land use changes in the Brazilian Amazon and related greenhouse emissions. Such clarifications are relevant to the readers of Conservation Letters and to a broader audience that rely on sound and robust science for a better management of environmental issues. [ABSTRACT FROM AUTHOR]