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A crucial aspect analysed during the last years, aiming to improve sugarcane production, is the impact of climate change on sugarcane productivity. One of the strategies to mitigate climate change's impact on sugarcane yield is the development of new varieties known to positively affect crop production. This paper analysed how climate change impacts sugarcane production regarding the different planted varieties. Data regarding sugarcane harvest were collected from a cooperative in the south of Goiás state—Brazil, the second biggest national sugarcane producer. Results indicate that climate impact on sugarcane yield is irrelevant when controlling for different varieties. Considering the results presented in this work, the Brazilian government should keep the incentives for the development of new sugarcane varieties and, at the same time, spur sugarcane producers to use the new sugarcane varieties. The results imply that if the variety is correctly chosen, sugarcane can be produced without harming the environment, contributing to reaching SDG 15. Moreover, it is less probable that an adverse climatic event will destroy the planted area, preventing sugarcane producers from severe loss and contributing to achieving SDGs number 1 and 2. [ABSTRACT FROM AUTHOR]

This paper aims to analyze the economy-wide and regional effects of climate change-induced productivity decrease in Brazil. Our methodological framework was based on the General Equilibrium Analysis of the Brazilian Economy Project—PAEGDyn, a dynamic CGE model. The results show that the projected falls in agricultural productivity impose reductions in the performance of Brazilian GDP over time. Even with the use by other sectors of the economy of the factors unemployed in agriculture, there is no intersectoral compensation in economic production over time able to bring it back to the reference trajectory. In addition, the impact will be greater in warmer and poor regions, which depend on agriculture and present greater income inequality, accentuated by the free mobility of production factors within the national border. Therefore, the main implication of this study is the need to allocate scarce resources for adaptation and mitigation policies primarily for these regions, including broadly stimulating economic development with more income distribution. This will allow these regions to protect themselves by making investments in new technologies and modern infrastructure for the agricultural sector. [ABSTRACT FROM AUTHOR]

This paper analysed the effect of freshwater withdrawals and management on agricultural and industrial sectors productivity in the emerging market economies. The auto-regressive distributed lag model and the panel analyses were employed in our estimations. Our result revealed that Brazil had better water use efficiency in agricultural production with annual withdrawals which contribute significantly and positively to the increase in crop and livestock index. In contrast, annual withdrawals for agriculture were considered to be least efficient in Russia, followed by China and India, although, in South Africa, the result suggested an insignificant positive effect in the incremental index. Furthermore, our analysis revealed that freshwater withdrawals have a significant positive impact on industrial outputs in South Africa. Similarly, water withdrawals were positively related to industrial sector productivity in China and Russia. Brazil and India appear to be the least efficient countries where withdrawals impacted negatively (and significantly for Brazil) on industrial sector outputs. Our panel analyses showed that freshwater withdrawals were positively associated with crop and livestock production index and industrial outputs in the BRICS economies. However, the magnitude of the impacts was only significant for the industrial sector. Moreover, investments and private participation in water and sanitation projects impacted significantly and positively in productivity in both sectors. [ABSTRACT FROM AUTHOR]

Coffee farms receive ecosystem services that rely on pollinators and pest predators. Landscape-scale processes regulate the flow of these biodiversity-based services. Consequently, the coffee farms' surrounding landscape impacts coffee production. This paper investigates how landscape structure can influence coffee production at different scales. We also evaluated the predictive utility of landscape metrics in a spatial (farm level) and aspatial approach (municipality level). We tested the effect of landscape structure on coffee production for 25 farms and 30 municipalities in southern Brazil. We used seven landscape metrics at landscape and class levels to measure the effect of landscape structure. At the farm level, we calculated metrics in five buffers from 1 to 5 km from the farm centroid to measure their scale of effect. We conducted a model selection using the generalized linear model (GLM) with a Gamma error distribution and inverse link function to evaluate the impact of landscape metrics on coffee production in both spatial and aspatial approaches. The landscape intensity index had a negative effect on coffee production (AICc = 375.59, p < 0.001). The native forest patch density (AICc = 390.14, p = 0.011) and landscape diversity (AICc = 391.18, p = 0.023) had a positive effect on production. All significant factors had effects at the farm level in the 2 km buffer but no effects at the municipality level. Our findings suggest that the landscape composition in the immediate surroundings of coffee farms helps predict production in a spatially explicit approach. However, these metrics cannot detect the impact of the landscape when analyzed in an aspatial approach. These findings highlight the importance of the landscape spatial structure, mainly the natural one, in the stability of coffee production. This study enhanced the knowledge of coffee production dependence on landscape-level processes. This advance can help to improve the sustainability of land use and better planning of agriculture, ensuring food and economic safety. Furthermore, our framework provides a method that can be useful to scrutinize any cropping system with census data that is either spatialized or not. [ABSTRACT FROM AUTHOR]

This paper analyzes the productivity of farms across 370 municipalities in the Center-West region of Brazil. A stochastic frontier model with a latent spatial structure is proposed to account for possible unknown geographical variation of the outputs. The paper compares versions of the model that include the latent spatial effect in the mean of output or as a variable that conditions the distribution of inefficiency, include or not observed municipal variables, and specify independent normal or conditional autoregressive priors for the spatial effects. The Bayesian paradigm is used to estimate the proposed models. As the resultant posterior distributions do not have a closed form, stochastic simulation techniques are used to obtain samples from them. Two model comparison criteria provide support for including the latent spatial effects, even after considering covariates at the municipal level. Models that ignore the latent spatial effects produce significantly different rankings of inefficiencies across agents. [ABSTRACT FROM AUTHOR]

This paper presents a dataset of yearly land use and land cover classification maps for Mato Grosso State, Brazil, from 2001 to 2017. Mato Grosso is one of the world's fast moving agricultural frontiers. To ensure multi-year compatibility, the work uses MODIS sensor analysis-ready products and an innovative method that applies machine learning techniques to classify satellite image time series. The maps provide information about crop and pasture expansion over natural vegetation, as well as spatially explicit estimates of increases in agricultural productivity and trade-offs between crop and pasture expansion. Therefore, the dataset provides new and relevant information to understand the impact of environmental policies on the expansion of tropical agriculture in Brazil. Using such results, researchers can make informed assessments of the interplay between production and protection within Amazon, Cerrado, and Pantanal biomes. Measurement(s) land • land use Technology Type(s) computational modeling technique Factor Type(s) year • geographic location • land use and cover class Sample Characteristic - Environment land Sample Characteristic - Location Mato Grosso State Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.11440461 [ABSTRACT FROM AUTHOR]

In tropical areas, pioneer occupation fronts steer the rapid expansion of deforestation, contributing to carbon emissions. Up-to-date carbon emission estimates covering the long-term development of such frontiers depend on the availability of high spatial-temporal resolution data. In this paper, we provide a detailed assessment of carbon losses from deforestation and potential forest degradation from fragmentation for one expanding frontier in the Brazilian Amazon. We focused on one of the Amazonia's hot-spots of forest loss, the BR-163 highway that connects the high productivity agricultural landscapes in Mato Grosso with the exporting harbors of the Amazon. We used multi-decadal (1984-2012) Landsat-based time series on forested and non-forested area in combination with a carbon book-keeping model. We show a 36% reduction in 1984s biomass carbon stocks, which led to the emission of 611.5 TgCO between 1985 and 1998 (43.6 TgCO year) and 959.8 TgCO over 1999-2012 (68.5 TgCO year). Overall, fragmentation-related carbon losses represented 1.88% of total emissions by 2012, with an increasing relevance since 2004. We compared the Brazilian Space Agency deforestation assessment (PRODES) with our data and found that small deforestation polygons not captured by PRODES had increasing importance on estimated deforestation carbon losses since 2000. The comparative analysis improved the understanding of data-source-related uncertainties on carbon estimates and indicated disagreement areas between datasets that could be subject of future research. Furthermore, spatially explicit, annual deforestation and emission estimates like the ones derived from this study are important for setting regional baselines for REDD+ or similar payment for ecosystem services frameworks. [ABSTRACT FROM AUTHOR]

This paper measures the influence of climate normals (average long-term surface wetness and temperature) and interannual climate variance on farms in the United States and Brazil using satellite data. The paper finds that just climate normals or just climate variance variables can explain both net revenues and how much land is used for cropland. However, because they are correlated with each other, it is important to include both normals and variance in the same statistical model to get accurate measures of their individual contribution to farm outcomes. In general, higher climate variance increases the probability that land is used for cropland in both countries and higher temperatures reduce both cropland and land values. Other annual effects were not consistent across the two countries. [ABSTRACT FROM AUTHOR]

Background, aim, and scope Brazil is the world's largest orange producing country, with a total planted area of more than 820,000 hectares. The bulk of the oranges produced in Brazil (70%) is processed into frozen concentrated orange juice (FCOJ) by large processing companies. Exports represent around 97% of the total FCOJ produced, making Brazil the largest world producer and exporter of FCOJ. The Brazilian citrus sector accounts for half of the world's supply of orange juice and for 80% of the juice traded on the international market. The goal of this study is to characterize the Brazilian orange producers in terms of farm size, cultivated varieties, watering system and tillage practices. In addition, the study presents some aspects of the LCI of oranges grown specifically for the production of FCOJ in the two major orange-growing areas in Brazil (the Northern and Southern regions of the State of São Paulo) during reference crop year 2002/03 in order to generate detailed production inventory data and identify the potential environmental impacts of tillage, both of which are key to enable the formulation of sustainability parameters for the production of FCOJ in Brazil. Methods This study was performed in compliance with the guidelines and requirements of the ISO 14040 standard series. All information and data considered and evaluated in this study (the use of water, energy, fertilizers, pesticides and soil correctors) were gathered through in-depth questionnaires either filled in directly by the farm manager or completed by the farm manager and sent in by mail. The data cover a total of 367,200 metric tons of oranges produced by 4 million plants in commercial production from a total evaluated area that accounts for 19.5% of the overall production of oranges in the State of São Paulo. The two major orange-producing areas in Brazil located respectively in the Northern and Southern regions of the State of São Paulo were evaluated. Only the inputs and outputs associated with tillage practices and technology were considered in this paper. The environmental aspects of the production of fertilizers and pesticides were not included within the boundaries. The functional unit selected for this study was 1,000 kg of oranges for FCOJ. Farm specific data have been combined with agricultural production data to construct an orange cultivation model. Results The orange varieties for the production of FCOJ evaluated in this study were Pêra, Valência and Natal. The farms investigated had a cultivated area varying from 22 to 7,000 ha, with a plant density ranging from 170 to 500 plants/ha and an average yield of 30,500 kg/ha for mature trees.… [ABSTRACT FROM AUTHOR]

Goal, Scope and Background. Brazil is the world's biggest producer of coffee beans with approx, a 30% market share. Depending on climate conditions, approx. 30 million bags of coffee beans are exported annually from Brazil, while domestic consumption is around 10 million bags, which makes Brazil the world's third largest coffee-consuming country. Therefore, the goal of this paper is to present the LCA of green coffee produced in Brazil for the reference crops 2001/02 and 2002/03 in order to generate detailed production inventory data as well as to identify the potential environmental impacts of its tillage in order to realize how to reduce those impacts and increase the environmental sustainability of this product. Only the inputs and outputs relative to the coffee tillage were considered. The production of fertilizers, correctives and pesticides were not included in the boundary, but only their amounts. The functional unit selected for this study was 1,000 kg of green coffee destined for exportation. Methods. The LCI was performed according to the ISO 14040 standard series. All information considered in this study (use of water, fossil based energy, fertilizers and chemicals) were taken up in in-depth data collection and evaluation by questionnaires applied on a farm level and/or received by mail. Four Brazilian coffee producer regions were evaluated: Cerrado Mineiro, South of Minas Gerais State, the Marilia and Alta Mogiana regions in Silo Paulo State. These regions have the following geographic coordinates: 44 to 50° W longitude and 18 to 24° S latitude. The data refer to a production of 420,000 coffee bean bags and a productive area of approx. 14,300 ha. The varieties of coffee beans considered in this study were Mundo Novo, Catuaí (yellow and red), Icatu (yellow and red), Catucaí (yellow and red) and Obatã. Farm specific data along with agricultural production data have been combined to elaborate a coffee cultivation inventory, which will be applied in an emissions estimation. Results and Conclusion. The production of 1,000 kg of green coffee in Brazil requires approx. 11,400 kg of water, 94 kg of diesel, 270 kg of fertilizers as NPK, 900 kg of total fertilizers, 620 kg of correctives, 10 kg of pesticides and 0.05 hectare of annual land use. Outputs related to these functional units are approx. 3,000 kg of waste water from coffee washing, 8,500 kg of waste water from the wet method and 750 kg of organic residue that is reincorporated to the tillage as fertilizer. The publication of an LCI of agricultural products is a fundamental step for understanding the potential environmental impacts of each tillage and then establishes the basis for product sustainability. In this way, this work is the first Brazilian initiative for applying LCA to coffee cultivation. Recommendation and Perspective. Different agricultural practices demonstrate different environmental profiles. The amount of agricultural pesticide is directly related to agricultural practices as tillage rotation, density of plants, etc. This study supplied important results for a better correlation of the agricultural practices and potential environmental impacts of coffee. Future updates of this study will show the evolution of the natural resource management such as land use, new agricultural practices, lower fertilizers and chemicals use. [ABSTRACT FROM AUTHOR]

Over the last decade, the Amazon region has been hit by some of the worst floods in history. The floods killed hundreds of people and damaged thousands of homes. However, in southeast Brazil, specifically in the states of Sao Paulo, Rio de Janeiro, and Minas Gerais, a highly significant decreasing rainfall trend has been discovered. The Sao Paulo State drought has had a significant impact on national electrical energy and agricultural productivity. In the last 100 years and 90 years, respectively, 2021 was a record flood in the Amazon region and a record drought in southeast Brazil. According to this study, recent floods in the Amazon and droughts in southeast Brazil, particularly extreme events in 2021, are strongly linked to the changing Hadley cell. [ABSTRACT FROM AUTHOR]

The importance of markets in promoting rural development points to the need to identify the most relevant capital for the commercialization of family farm production. We seeks to verify the extent to which livelihood assets help family farmers commercialize their production through research among 125 family farmers settled in agricultural lands redistributed by the government during land reform, in the Federal District, Brazil. Data were collected in the field using a structured form in the Likert scale format and assessed using Partial Least Squares Structural Equation Modeling (PLS-SEM). We show that livelihoods have a positive and significant influence on commercialization, and that human and social capital are the major contributors to the commercialization of family farm production. Our findings show the need to reinforce public policies focused on training of farmers in market opportunities and the promotion of a collective organization aimed at fostering commercialization as a rural development strategy. [ABSTRACT FROM AUTHOR]

Bush fires raged across the Brazilian Amazon in 2019. The CO2 that was sequestered in those forests is now in the atmosphere, adding to the rate of global warming. The burned-over land will likely be converted to agriculture. Possible contributors to these events include climate change itself, creating hotter, drier conditions, and what is reportedly a reduction in the vigor of forest preservation efforts under a new government. But here we explore a third possible contributor: technical change may have been increasing the incentives to convert forests to agriculture. We examine the nature of technical change from 2003 to 2015, across 287 municipalities within Brazil's "arc of deforestation." We consider grains, livestock and timber as agricultural outputs and CO2 emission from deforestation as an undesirable output. On average across the region, we estimate the annual rate of technical change in agriculture over this period to have been 4.9%, with a significant bias toward agricultural outputs and away from CO2 emissions, meaning that it has been increasingly attractive to convert these forests to agriculture. This technological incentive for deforestation has thus been building up during the early part of this century, but actual deforestation was held in check somewhat by forest preservation policies until recently, when a more relaxed policy environment has allowed the increased technological incentive for deforestation to be more fully expressed. These changes have added to climate change as contributors to the recent burst in Amazon forest destruction. [ABSTRACT FROM AUTHOR]

It has been suggested that rainfall in the Amazon decreases if forest loss exceeds some threshold, but the specific value of this threshold remains uncertain. Here, we investigate the relationship between historical deforestation and rainfall at different geographical scales across the Southern Brazilian Amazon (SBA). We also assess impacts of deforestation policy scenarios on the region's agriculture. Forest loss of up to 55–60% within 28 km grid cells enhances rainfall, but further deforestation reduces rainfall precipitously. This threshold is lower at larger scales (45–50% at 56 km and 25–30% at 112 km grid cells), while rainfall decreases linearly within 224 km grid cells. Widespread deforestation results in a hydrological and economic negative-sum game, because lower rainfall and agricultural productivity at larger scales outdo local gains. Under a weak governance scenario, SBA may lose 56% of its forests by 2050. Reducing deforestation prevents agricultural losses in SBA up to US$ 1 billion annually. Deforestation in the Amazon region has suggested to influence precipitation in a non-linear way. Here, the authors show that forest loss is associated with decreasing precipitation after a scale-dependent threshold is crossed, which can cause stress on agriculture if deforestation is expanded. [ABSTRACT FROM AUTHOR]

Agricultural activity is largely influenced by climatic conditions. Rainfall is essential for crop production, and precipitation events also interfere with soil preparation, planting, application of pesticides and harvesting. Weather forecast models are tools to facilitate decision making for agricultural activities, hence high accuracy is desired. Farmers often criticize the accuracy of weather forecasts, which sometimes fail to predict precipitation events, leading to yield loss and environmental harm. In this study, precipitation forecasts of the Eta Model were evaluated for 28 of Brazil's most productive sugarcane areas, considering a grid of 15 × 15 km. Using a combination of different indicators of forecast success, observed and forecasted daily precipitation data were compared for consecutive days of all 10-day periods in a course of 6 years (2005–2010). Skill scores and performance diagrams based on the indicators were used to evaluate the goodness and robustness of the model forecasts. The Eta Model forecasts showed overall accuracies ranging between 55 and 71% for the Atlantic forest biomes (located North-West and South-East of São Paulo) and the Cerrado biomes (located in the Goiás State and in the Center-North São Paulo State), respectively. The forecasts were most reliable for up to 4 days, showing an accuracy of 60%. Forecasts for periods of more than 4 days had an average accuracy of 40–50%. The probability of detecting rainfall correctly was the strongest characteristic of Eta Model, with more than 70% hits. [ABSTRACT FROM AUTHOR]

The global food system is increasingly interconnected and under pressure to support growing demand. At the same time, crop production is facing new and uncertain impacts from climate change. To date, understanding how downstream supply chain actors, such as commodity traders, are exposed to climate change risks has been difficult due to a lack of high-resolution climate and trade data. However, the recent availability of supply chain data linking subnational production to downstream actors, and gridded projections of crop yield under climate change, allows us to assess individual commodity trader exposure to long-term climate change risk. We apply such an analysis to soy production in Brazil, the world's largest soy exporter. Whilst uncertainty across crop models' yield projections means it remains difficult to accurately predict how production across the region will be affected by climate change, we demonstrate that the risk exposure of trading actors differs substantially due to the heterogeneity in their sourcing. Our study offers a first attempt to analyze subnational climate risk to individual trading actors operating across an entire production landscape, leading to more precise risk exposure analysis. With sufficient subnational data, this method can be applied to any crop and country combination, and in the context of wider food security issues, it will be pertinent to apply these methods across other production systems and downstream actors in the food system. [ABSTRACT FROM AUTHOR]

Potassium (K), along with nitrogen and phosphorus, is an essential resource to ensure agricultural productivity and, therefore, food security around the world. However, diminishing physical reserves of potash salts and high-price volatility of potassium chloride, the main source of K to agricultural soils, has raised concerns about a K scarcity scenario, mainly in countries that depend on fertilizer imports to sustain its production. In this context, Brazil is one of the main agricultural producers in the world, having a major role in the global K flows, since the country sustains its production by a high consumption of imported K fertilizers. In order to seek opportunities to contribute to a more sustainable management of K resources, tools such as the material flow analysis (MFA) can be used to highlight the main K stocks and flows in a country scale, and identify options for reuse and recycle. This study proposed a MFA of K for Brazil, considering the base-year 2013. A total of forty-four flows and seven stocks were identified and quantified considering nine main processes related to human activity. According to the results, for the year of study, the main inputs of K in Brazil were in the form of fertilizers (4.1 × 103 Gg of K per year), and the main outputs were in the form of grain exports (9.1 × 102 Gg of K per year). Agricultural soils were the main stock for K in the country, and from the total flow of 7.3 × 103 Gg of K per year applied to soils, 67% came out as agricultural products, 13% was lost through erosion and leaching, and 20% remained in the soils. The flow of K actually consumed by the Brazilian population was 3.5 × 102 Gg of K per year, just 8.4% of the total food produced in the country. About 1.9 × 103 Gg of K per year has been lost to the environment in sewage streams and solid landfill waste. Prospects for more sustainable K management in the country are identified and discussed. [ABSTRACT FROM AUTHOR]

Although Brazil is predominantly a tropical country, frosts are observed with relative high frequency in the Center-Southern states of the country, affecting mainly agriculture, forestry, and human activities. Therefore, information about the frost climatology is of high importance for planning of these activities. Based on that, the aims of the present study were to develop monthly meteorological (FMET) and agronomic (FAGR) frost day models, based on minimum shelter air temperature (TMN), in order to characterize the temporal and spatial frost days variability in Center-Southern Brazil. Daily minimum air temperature data from 244 weather stations distributed across the study area were used, being 195 for developing the models and 49 for validating them. Multivariate regression models were obtained to estimate the monthly TMN, once the frost day models were based on this variable. All TMN regression models were statistically significant (p < 0.001), presenting adjusted R2 between 0.69 and 0.90. Center-Southern Brazil is mainly hit by frosts from mid-fall (April) to mid-spring (October). The period from November to March is considered as frost-free, being very rare a frost day within that period. Monthly FMET and FAGR presented significant sigmoidal relationships with TMN (p < 0.0001), with adjusted R2 above of 0.82. The residuals of the frost day models were random, which means that the sigmoidal models performed quite well for interpreting the frost day variability throughout the study area. The highlands of Santa Catarina, Rio Grande do Sul, São Paulo, and Minas Gerais had in average more than 25 and 13 frosts per year, respectively, for FMET and FAGR. The FMET and FAGR maps developed in this study for Center-Southern Brazil is a useful tool for farmers, foresters, and researchers, since they contribute to reduce frost spatial and temporal uncertainty, helping in planning project for strategic purposes. Furthermore, the monthly FMET and FAGR maps for this Brazilian region are the first zoning of these variables for the country. [ABSTRACT FROM AUTHOR]

The global Climate change may affect biodiversity and the functioning of ecosystems by changing the appropriate locations for the development and establishment of the species. The Hancornia speciosa, popularly called Mangaba, is a plant species that has potential commercial value and contributes to rural economic activities in Brazil. The aim of this study was to evaluate the impact of global climate change on the potential geographic distribution, productivity, and value of production of H. speciosa in Brazil. We used MaxEnt to estimate the potential geographic distribution of the species in current and future (2050) climate scenarios. We obtained the productivity and value of production for 74 municipalities in Brazil. Moreover, to explain the variation the productivity and value of production, we constructed 15 models based on four variables: two ecological (ecological niche model and the presence of Unity of conservation) and two socio-economic (gross domestic product and human developed index). The models were selected using Akaike Information Criteria. Our results suggest that municipalities currently harvesting H. speciosa will have lower harvest rates in the future (mainly in northeastern Brazil). The best model to explain the productivity was ecological niche model; thus, municipalities with higher productivity are inserted in regions with higher environmental suitability (indicated by niche model). Thus, in the future, the municipalities harvesting H. speciosa will produce less because there will be less suitable habitat for H. speciosa, which in turn will affect the H. speciosa harvest and the local economy. [ABSTRACT FROM AUTHOR]

This study compares aboveground and belowground carbon stocks and tree diversity in different cocoa cultivation systems in Bolivia: monoculture, simple agroforestry, and successional agroforestry, as well as fallow as a control. Since diversified, agroforestry-based cultivation systems are often considered important for sustainable development, we also evaluated the links between carbon stocks and tree diversity, as well as the role of organic certification in transitioning from monoculture to agroforestry. Biomass, tree diversity, and soil physiochemical parameters were sampled in 15 plots measuring 48 × 48 m. Semi-structured interviews with 52 cocoa farmers were used to evaluate the role of organic certification and farmers' organizations (e.g., cocoa cooperatives) in promoting tree diversity. Total carbon stocks in simple agroforestry systems (128.4 ± 20 Mg ha) were similar to those on fallow plots (125.2 ± 10 Mg ha). Successional agroforestry systems had the highest carbon stocks (143.7 ± 5.3 Mg ha). Monocultures stored significantly less carbon than all other systems (86.3 ± 4.0 Mg ha, posterior probability P(Diff > 0) of 0.000-0.006). Among shade tree species, Schizolobium amazonicum, Centrolobium ochroxylum, and Anadenanthera sp. accumulated the most biomass. High-value timber species ( S. amazonicum, C. ochroxylum, Amburana cearensis, and Swietenia macrophylla) accounted for 22.0 % of shade tree biomass. The Shannon index and tree species richness were highest in successional agroforestry systems. Cocoa plots on certified organic farms displayed significantly higher tree species richness than plots on non-certified farms. Thus, expanding the coverage of organic farmers' organizations may be an effective strategy for fostering transitions from monoculture to agroforestry systems. [ABSTRACT FROM AUTHOR]

We use under-explored municipality level datasets to assess the recent economic and policy determinants of deforestation in the Brazilian Amazon. We estimate yearly panel data models (from 2002 to 2009) for 663 municipalities in the region. The results show that recent deforestation is increasing with economic activity and is also affected by economic incentives, measured by fluctuations in agricultural product and wood prices. Moreover, we document that the increasing enforcement efforts of the Brazilian environmental police (IBAMA) were effective in reducing deforestation rates. [ABSTRACT FROM AUTHOR]

We explore the welfare implications of agricultural expansion in the Brazilian Amazon by comparing spatially explicit estimates of soybean rents and the value of ecosystem services. Although these estimates are generated from different datasets, models, and estimation techniques, the values are comparable, such that the value of ecosystem services is greater than soybean rents for about 61% of the total area and 24% of the area where soybean rents are positive if protected areas are well enforced. Based on the balance between the benefits and costs of conversion, failure to value ecosystem services reduces total social welfare by 7.13 billion dollars annually relative to an optimum. Policy instruments that internalize the value of ecosystem services via protected lands, land conversion taxes, conservation subsidies, or excise taxes can avoid much of this loss. Regardless of intervention regime, policy makers should be cognizant of the diminishing net benefits of converting natural ecosystems to agriculture. Realizing the final 3.8% requires the conversion of an additional 15% natural ecosystems to soybean production. [ABSTRACT FROM AUTHOR]

One of Daniel Hogan's lasting impacts on international demography community comes through his advocacy for studying bidirectional relationships between environment and demography, particularly migration. We build on his holistic approach to mobility and examine dynamic changes in land use and migration among small farm families in Altamira, Pará, Brazil. We find that prior area in either pasture or perennials promotes out-migration of adult children, but that out-migration is not directly associated with land-use change. In contrast to early formulations of household life cycle models that argued that aging parents would decrease productive land use as children left the farm, we find no effect of out-migration of adult children on land-use change. Instead, remittances facilitate increases in area in perennials, a slower to pay off investment that requires scarce capital, but in pasture. While remittances are rare, they appear to permit sound investments in the rural milieu and thus to slow rural exodus and the potential consolidation of land into large holdings. We would do well to promote the conditions that allow them to be sent and to be used productively to keep families on the land to avoid the specter of extensive deforestation for pasture followed by land consolidation. [ABSTRACT FROM AUTHOR]

Balancing ever-increasing agricultural and biofuel needs with biodiversity conservation is one of the greatest challenges facing conservation biologists in the 21st century. The conversion of >75 million hectares of forests in Brazilian Amazonia over four decades for agropastoral uses has resulted in the 'creation' of a similar-sized amount of non-forest 'agricultural matrix' habitats. Despite extensive research on the effects of forest loss and fragmentation on the Amazonian biota, the value of increasingly larger areas of non-forest habitat for forest wildlife remains poorly understood. We conducted 325 fixed-radius point counts of the avifaunal assemblage of non-forest vegetation within a 1200-km region along the Amazonian 'Arc of Deforestation' in Northern Mato Grosso, Brazil. Our sampling included 2,814 records of 164 species, 15 and 54% of which were recorded in more than 10% and fewer than 2% of all sampling sites, respectively. In particular, nearly 70% of the regional scale avifauna of 560 species failed to use the agricultural matrix, regardless of the persistence of ameliorating structural features, such as isolated trees. At the local scale, higher species richness in the agricultural matrix was best predicted by the presence of relictual trees, and to a lesser extent by standing water and scrubby habitats. The presence of relictual trees, rather than scrub, predicted the occurrence of those forest-dependent species that did use the agricultural matrix. Our results indicate that intensive agricultural production coupled with land sparing would better suit conservation of vulnerable forest species than more extensive 'wildlife friendly' agricultural practices that require more land under production to produce the same yield. [ABSTRACT FROM AUTHOR]

Precision agriculture (PA) technologies are being applied to crops in Brazil, which are important to ensure Brazil's position in agricultural production. However, there are no studies available at present to indicate the extent to which PA technologies are being used in the country. Therefore, the main objective of this research was to investigate how the sugar-ethanol industry in São Paulo state, which produces 60% of the domestic sugarcane, is adopting and using these techniques. For this purpose, primary data were used, which were obtained from a questionnaire sent to all companies operating in the sugar-ethanol industry in the region. The aim was to determine to what extent these companies are adopting and using PA technologies, and also to promote a more in-depth discussion of the topic within the sugar-ethanol industry. Information was obtained on the features of the companies, on sources of information that they use for adopting these technologies, on their impacts on these companies and on obstacles hindering their adoption. The main conclusions of this research suggest that companies that adopt and use PA practices reap benefits, such as managerial improvements, higher yields, lower costs, minimization of environmental impacts and improvements in sugarcane quality. [ABSTRACT FROM AUTHOR]