Controlling deforestation in the Brazilian Amazon: Regional economic impacts and land-use change

Brazil confirmed targets for reducing greenhouse gas emissions in 2008, including an 80% reduction in deforestation in the Amazon by 2020. With this in mind, we investigated the trade-off between environmental conservation and economic growth in the Amazon. The aim of this study is to project the economic losses and land-use changes resulting from a policy to control deforestation and the rise in land productivity that is necessary to offset those losses. We developed a Dynamic Interregional Computable General Equilibrium Model for 30 Amazon regions with a land module allowing conversion between types of land. The results have shown that the most affected regions would be soybeans and cattle producers as well as regions dominated by family farms. To offset these impacts, it was estimated that an annual gain of land productivity of approximately 1.4% would be required.     

The new economic geography of land use change: Supply chain configurations and land use in the Brazilian Amazon

In this paper we present a framework for understanding regional land use processes by incorporating the concept of agglomeration economies into agricultural frontier theory. We show that agricultural firms can obtain positive externalities from locating in close proximity to other agricultural firms, leading to agglomeration economies. Agglomeration economies lead to high levels of competition and diversity within a local agricultural supply chain and influence local prices, information flows, and private enforcement of environmental institutions. We use the theory of agglomeration economies to understand the development of soybean production in two counties along the Santarém-Cuiaba (BR-163) highway in the Brazilian Amazon: Santarém, Pará and Sorriso, Mato Grosso. We conclude that differences in environmental and land tenure institutions influenced the occurrence of agglomeration economies in these two counties, which in turn affected the total factor productivity of soy in each region. In particular, the supply chain became extremely competitive and diverse in Sorriso where few environmental regulations existed, while environmental restrictions reduced the diversification of the supply chain in Santarém. The presence of a soy agglomeration economy in Sorriso spurred innovation, increased productivity, and led to extremely rapid soy expansion in that county, while the monopolistic supply chain in Santarém reduced producers’ access to land and capital and impeded soy expansion.     

Quantifying and understanding land cover changes by large and small oil palm expansion regimes in the Peruvian Amazon

With rapid increases in global food demand and production, oil palm expansion constitutes a major emerging challenge for forest conservation in Amazonia and other tropical forest regions. This threat is evident in the Peruvian Amazon, where local and national incentives for oil palm cultivation along with growing large-scale investments translate into accelerated oil palm expansion. Environmental sustainability of oil palm cultivation in the Peruvian Amazon is contingent on policy incentives for expansion onto already-cleared lands instead of biodiverse, high carbon primary rainforests. Previous research indicates that while industrial plantations use less land area than local smallholders, companies have a higher tendency to expand into primary rainforests. However, the motivations behind these differing expansion scenarios remain unclear. In this study we combine data from optical and radar satellite sensors with training information, field discussions, and review of public documents to examine the policy incentives and spatial patterns associated with oil palm expansion by smallholders and industries in one of Peru’s most rapidly changing Amazonian landscapes: the Ucayali region of the city of Pucallpa. Based on our satellite-based land cover change analysis, we found that between 2010 and 2016, smallholders utilized 21,070 ha more land area for oil palm than industries but industrial expansion occurred predominantly in old growth forests (70%) in contrast to degraded lands for smallholders (56%). Our analysis of national policies related to oil palm expansion reveal policy loopholes associated with Peru’s “best land use” classification system that allow for standing forests to undergo large-scale agricultural development with little government oversight. We conclude that both sectors will need careful, real-time monitoring and government engagement to reduce old-growth forest loss and develop successful strategies for mitigating future environmental impacts of oil palm expansion.     

Exploring land use changes and the role of palm oil production in Indonesia and Malaysia

This study compiles and analyses national-level data on land use change (LUC) and its causes in Indonesia and Malaysia over the past 30 years. The study also explores the role that palm oil has played in past LUC and that projected growth in palm oil production may play in LUC until 2020 and suggests strategies to minimize negative effects. Data collection for the study revealed that the quality and quantity of data on LUC on a national scale over time are low. Despite these uncertainties, the overview of past LUC indicates that large changes in land use have occurred in Indonesia and Malaysia. In Indonesia, LUC can primarily be characterized by forest cover loss on 40 million ha (Mha) of land, a 30% reduction in forest land. Deforestation in Malaysia has been smaller in both absolute and relative terms, with a forest cover loss of nearly 5 Mha (20% reduction in forest land). Other large changes in Malaysia occurred in permanent cropland (excluding oil palm), which has decreased rapidly since the early 1990s, and in land under oil palm cultivation, which experienced a sharp increase. Projections of additional land demand for palm oil production in 2020 range from 1 to 28 Mha in Indonesia. The demand can be met to a large extent by degraded land if no further deforestation is assumed. In Malaysia, expansion projections range from 0.06 to 5 Mha, but only the lowest projection of oil palm expansion is feasible when only degraded land may be used. The role of palm oil production in future LUC depends on the size of the projected expansion as well as agricultural management factors such as implementation of best management practices, earlier replanting with higher yielding plants, and establishment of new plantations on degraded land. The current use of degraded land needs to be investigated in order to reduce possible indirect LUC, land tenure conflicts, or other social impacts. In addition to minimizing direct and indirect LUC by the palm oil sector, measures that reduce deforestation triggered by other causes must also be implemented. A key element for doing so is better planning and governance of land use, which entails more appropriate demarcation of forest land and protection of land that still has forest cover, improved monitoring of land use, and more research to uncover the complexities and dynamics of the causes and drivers of LUC.     

Implications of land use transitions and climate change on local flooding in urban areas: An assessment of 42 Indian cities

Urban development induced land transitions affect urban hydrology, resulting in increased flooding risks. Climate change-related precipitation changes are an added complexity to the flood risks of cities. This study examines the role of land use changes in determining the occurrence of urban flooding events across 42 Indian cities under current and future climate change scenarios. Landsat images for 1990, 2000, 2010, and 2017 have been processed using a hybrid classification technique to determine the land use shares for all cities. A typical event-count study using newspaper archives has been conducted to create a flooding event database. A multilevel model employing logistic mixed-effects approach was used. Future projections of the occurrence of flooding events for nine models under three climate change-related Representative Concentration Pathways (RCPs)—2.6, 4.5, and 8.5—and three urban development scenarios have been carried out. The results suggest that cities should preserve the land uses that act as a sponge—the green, open and blue spaces. As these spaces decrease, the projected flooding events increase. Under the RCP 2.6 scenario, the number of flooding events is significantly lower (95 % confidence) than under RCPs 4.5 and 8.5. The expected flooding occurrences between RCP4.5 and RCP8.5 are not significantly different (95 % confidence) for many scenarios, suggesting that Indian cities should aim for a world temperature increase of below 2 °C, or devastating consequences are imminent. This study highlights the need for Indian cities to undertake integrated spatial planning measures for a resilient, sustainable urban future.     

Addressing climate change cause and effect on land cover and land use in South Asia

This paper evaluates the role of trade liberalization and agricultural intensification in mitigating climate change cause and effects on land use and emissions using a computable general equilibrium model. Our results indicate that cropland expansion triggered by climate-induced crop productivity changes results in deforestation and increases emissions in South Asia and globally. Global full trade liberalization on all goods is the optimum policy for South Asia despite significant global deforestation, but for the world, unilateral partial trade liberalization on all goods is a more appropriate policy while ensuring a considerable emissions reduction for South Asia. These results indicate that mitigation responses to climate change are location specific and no one trade policy is suitable at the regional and global levels. Lastly, agricultural intensification by improving productivity growth is the best strategy in land-based emissions mitigation, thereby avoiding the transformation of forest and pasture lands for agricultural cultivation both at regional and global levels.     

The impact of commodity price and conservation policy scenarios on deforestation and agricultural land use in a frontier area within the Amazon

Deforestation in the Amazon is caused by the complex interplay of different drivers. Price of commodities such as beef and soya, and incoming migration are paramount factors. Construction of new highways is a key aspect, as they enable a growing flow of people and economic activities, provoking an intensification of the conversion of forests into pasture and agricultural areas. The pavement of road BR-163 accelerates the expansion of the agricultural frontier from the state of Mato Grosso to Pará, inside the Amazon. Today, the Brazilian government applies two main kinds of policies to protect the environment. First by establishing conservation units (CUs) that include an array of reserve types from natural areas to indigenous lands, and second by enforcing the Forest Code (FC), a law that limits the occupation and use of forests. Legal reserve requirements for rural properties are 80% in the Amazon rainforest, 35% in the Cerrado shrublands and 20% in other regions. However, the effectiveness of these policies relies on a fragile institutional capacity, which causes a flawed monitoring, law enforcement and control. To assess the impact of effective conservation policies on land use and deforestation by 2020, we used the LUSMAPA model in combination with two scenarios, one that included different commodity price developments and migration rates and one on the assumption of the institutional strength to uphold the conservation policies. A revision of the FC from an average 80% policy target to 60% effective implementation and disregard borders of CUs by allowing 5% deforestation in CUs, that both corresponds to a ‘weak’ governmental enforcement, leads to additional deforestation of 41–57%, depending on the commodity price scenario. The results of the simulations are discussed in the light of recent policy changes in Brazil.     

Methodology to calculate the carbon footprint of household land use in the urban planning stage

The growing concerns of climate change require implementing measures to quantify, to monitor and to minimize greenhouse gas (GHG) emissions. Nonetheless, most of the measures available are not easy to define or execute because they rely on current emissions and have a corrective character. To address this issue, a methodology to characterize GHG emissions that allows implementing preventive measures is proposed in this paper. The methodology is related to household urban planning procedures and considers urban infrastructures to characterize GHG emissions and to execute preventive measures based on sustainability design criteria. The methodology has been tested by applying it to a set of medium-sized municipalities with average GHG emissions from 6,822.32 kgCO_2eq/year to 5,913.79 kgCO_2eq/year for every residential unit. The results indicate that the greatest pollutant source is transport, especially in the issuance of street network design, followed by gas and electricity consumption. The average undevelopable land area required for the complete GHG emissions capture amounts to 3.42 m² of undevelopable land for every m² of urbanizable land and 9.02 m² of undevelopable land for every m² of built land.     

Biophysical and socioeconomic determinants of tea expansion: Apportioning their relative importance for sustainable land use policy

Tea expansion, a typical process of regional land use and cover change (LUCC), has raised great concerns on regional sustainability. In this regard, exploring the determinants of tea expansion should provide critical implications for land use policy. It has been widely recognized that LUCC interacts nonlinearly with a set of determinants and their feedbacks should be rather complex. Policy makers are now facing the challenge to identify, apportion, and compare the determinants of regional tea expansion for designing more targeted political intervenes. Our paper utilizes a robust tool, the random forest (RF) regression in particular, to explore the determinants of tea expansion across two periods (1985–2007 and 2007–2016) in Anji County, a typical region of tea production in subtropical China. More specifically, tea is extracted from Landsat imageries and total tea cultivated area acts as the dependent variable. Exploratory variables include 38 potential determinants and these determinants are divided into two categories (biophysical and socioeconomic) at two levels (pixel and village). We obtain some similar findings, though the relative importance of determinants varies with the two periods. In general, biophysical determinants (e.g., topography, soil type, land use in the neighborhood) present greater relative importance than the socioeconomic determinants in both periods. In period 1985–2007, biophysical determinants at pixel level are more essential in governing tea expansion. In period 2007–2016, the relative importance of pixel level biophysical determinants is comparable with that of the village level determinants. Comparisons of the two periods indicate that relative importance of soil type and socioeconomic proximity becomes greater in period 2007–2016, while that of the total employees and non-agricultural population proportion becomes lower. Partial dependency plots are further drawn to visualize the marginal effect of each determinant. We finally propose three options for land use policy towards sustainability. Our study demonstrates that the RF regression is efficient for policy makers to understand the determinants of tea expansion with a nonlinear and complex nature.     

Simulating the impacts of future land use change on soil erosion in the Kasilian watershed,Iran

Predicting soil erosion potential is important in watershed management. A rapidly growing Iranian population and climate change are expected to influence land use and soil sustainability. In recent years, northern Iran has experienced significant land use changes due to internal migration along the Caspian coast and conversion of forests and rangelands. Considering the effect of these changes in the future, the purpose of this study is to forecast land use patterns and investigate soil erosion scenarios using the Revised Universal Loss Equation and Markov Cellular Automata. Data from 1981 to 2011 were used as a baseline to estimate changes that might occur in 2030. The results reveal that the mean erosion potential will increase 45% from the estimated 104.52 t ha⁻¹ year⁻¹ in the baseline period. Moreover, the results indicate that land use change from forest area to settlements will be the most significant factor in erosion induced by land use change, showing the highest correlation among erosional factors. Projecting land use change and its effect on soil erosion indicate that conversion may be unsustainable if change occurs on land that is not suited to the use. The method predicts soil erosion under different scenarios and provides policymakers a basis for altering programs related to land use optimization and urban growth. Those results indicated the necessity of appropriate policies and regulations particularly for limiting land use changes and urban sprawl in areas of unfavorable soil erosion risk factors.     

The economic costs of avoided deforestation in the developing world: A meta-analysis

This meta-analysis aims to identify the key factors governing the economic costs of avoided deforestation in developing countries. To this end, data were collected from 32 primary studies published between 1995 and 2012, yielding 277 observations. Results show that unit costs depend significantly on cost features like estimation methodology, inclusion or exclusion of cost components, carbon accounting method, area size, alternative land uses and beneficiaries, time horizon, and the continent in which the forest protection scheme is implemented, but also factors like the share of agriculture in a nation's economy play a significant role in explaining unit costs. In future studies, greater attention needs to be paid to additional cost components like transaction costs and the presence of the co-benefits of avoided deforestation.     

Rice to shrimp: Land use/land cover changes and soil degradation in Southwestern Bangladesh

This paper examines the impact of shrimp farming on rice ecosystem in a village in Southwestern Bangladesh. The village Damarpota has experienced transformation of 274 ha (79%) of its prime quality rice fields into shrimp farms during the period between 1985 and 2003. Prolonged shrimp farming for 5-, 10-, and 15-year period has increased soil salinity, acidity, and depleted soil Ca, K, Mg, and organic C content of all three types of soils in the villages to a variable degree and caused soil degradation that significantly affected the rice yield. Declined yield and acreage of rice jointly reduced the total production of rice and animal fodder. Soil degradation and loss of acreage under rice have threatened the sustainability of the village rice ecosystem.     

Technology,market policies and institutional reform for sustainable land use in southern Mali

To identify appropriate interventions that support sustainable land use; a farm household modelling approach is applied to analyze micro-economic supply reactions to various policy measures. The modelling framework links agro-technical and economic data, and takes both production and consumption decisions into account, allowing land use and production technology adjustments in accordance with farm household objectives. Different types of farm households are distinguished on the basis of their resource endowments, savings coefficients and time discount rate. Actual and alternative (sustainable) cropping and livestock activities for different weather regimes are defined for southern Mali. The effects on sustainable land use and expected farm household welfare of adopting alternative technologies and modifying prices, transaction costs, access to credit and land taxes are demonstrated. Even with full information on sustainable technologies, strong policy interventions are required to halt soil degradation. Structural policies proved to be more effective than price policies to reduce soil degradation while maintaining positive income effects. When prices are determined endogenously, structural policy loses some effectiveness as an incentive for sustainable land use due to the effect of additional supply on local cereal and meat Prices.     

Crossing spatial analyses and livestock economics to understand deforestation processes in the Brazilian Amazon: the case of São Félix do Xingú in South Pará

The Amazon is the largest tropical forest area on Earth, and has been undergoing rapid deforestation for the last four decades. In the Brazilian Amazon, large‐scale pasture for cattle ranching and soybean production are the main land uses, leading to a yearly deforestation rate of 0.5%. These conversions are mostly located in frontier areas distributed along the so‐called “arc of deforestation”. Within this large zone, various land use change processes are interacting through several modes of land valuation and organisation. From several case studies in the State of Pará (Brazil), the current project aims at analysing how landscape dynamics are related to infrastructure development, ecological conditions, zoning policies and to the evolution and the organisation of the production, consumption and marketing chains of livestock products. This paper presents the results for one test site, the region of São Félix do Xingú, South of Pará This region is the focus of land speculation, cattle expansion, and deforestation. Road construction, investments in electrical energy, financial credit for cattle, and the land reform policies have all fuelled this process. All these factors make this region one of the most dynamic agricultural frontiers in the Brazilian Amazon. The main objective of the paper is to improve our understanding of deforestation processes by crossing spatial analyses and 1ivestock economics.studies, and to characterise the role and impact of various natural and anthropic factors in the location and development of the main types of farmers, and their policy implications.     

The impact of climate and price risks on agricultural land use and crop management decisions

This article aims to investigate the impacts of climate change and of lower and more volatile crop price levels as currently observed in the European Union (EU) on optimal management decisions, average income and income risks in crop production in Western Switzerland. To this end, a bioeconomic whole-farm model has been developed that non-parametrically combines the crop growth model CropSyst with an economic decision model using a genetic algorithm. The analysis focuses on the farm level, which enables us to integrate a wide set of potential adaptation responses, comprising changes in agricultural land use as well as crop-specific fertilization and irrigation strategies. Furthermore, the farmer's certainty equivalent is employed as objective function, which enables the consideration of not only impacts on average income but also impacts on income variability.The study shows that that the effects of EU crop prices on the optimal management decisions as well as on the farmer's certainty equivalent are much stronger than the effects of climate change. Furthermore, our results indicate that the impacts of income risks on the crop farm's optimal management schemes are of rather low importance. This is due to two major reasons: first, direct payments make up a large percentage of the agricultural income in Switzerland which makes Swiss farmers less vulnerable to market and climate volatility. Second, arable crop farms in Switzerland have by law to cultivate at least four different crops. Due to these diverse cropping systems and high government direct payments risk does neither under climate change, market liberalization nor combinations thereof, play a very decisive role in arable farming in Switzerland.     

Farmer-specific relationships between land use change and landscape factors: Introducing agents in empirical land use modelling

Traditional empirical land use change models generally assume one average land use decision-maker. Multi-Agent System (MAS) models, on the other hand, acknowledge existence of different types of agents, but their poor empirical embedding remains a serious handicap. This paper demonstrates how agent information can also be incorporated into empirical, biophysical land use models.     

The role of land use conversion in shaping the land cover of the Central American Dry Corridor

The Central American Dry Corridor (CADC) is a trans-border region characterized by climatic and ecological continuities. It is expected to experience rising aridity and severe hydro-climatic events due to climate change. Subsistence agriculture and other rural livelihoods to which land cover is central are widely practiced in this impoverished territory of approximately eleven million people.The CADC’s land cover was profiled to determine: a) how it differs from Non-CADC areas, and b) the role of land use in shaping these differences. Spatial autocorrelation analysis using satellite data showed that forest cover is a third less prevalent in the CADC than in the Non-CADC while the share of mosaic vegetation and mosaic cropland is nearly double. A naturally prevalent cover type in the CADC, tropical dry forest (TDF), has been largely eliminated.The significantly lesser proportion of forest and greater percentage of coverage consistent with agriculture and ranching implicate land use conversion, specifically deforestation for agricultural expansion and cattle ranching, in shaping CADC land coverage. The process began in the mid-1800s when small-scale agriculturalists migrated to the region followed by large-scale export crop and beef production, primarily for international markets. Deforestation peaked after WWII, concluding by the 1990s with the conversion of most woodlands. Similar patterns now threaten forests along the Caribbean coast.Traditional land use practices cannot sustain local communities or preserve the resource base, thereby contributing to rural outmigration. Adopting sustainable practices and promoting livelihoods strategies leading to forest regeneration will be fundamental for CC adaptation in the CADC.     

Farm-level adaptation to climate change in Western Bangladesh: An analysis of adaptation dynamics,profitability and risks

Using long-term district-level climate data and a case study from a drought-prone village in western Bangladesh, this research explored trends in climate change, and analysed farmers’ adaptation dynamics, profitability and risks. This is the first study of its kind for drought-prone areas in Bangladesh.Farmers perceived climate changes included increases in temperature and decreases in rainfall which were as consistent with the trends of Chuadanga climate records. Farmers’ adaptation measures included changes in cropping systems, cropping calendars, crop varieties, agronomic practices, crop diversification and improved animal husbandry. Reducing environmental stress, ensuring self-sufficiency in staple crops (mainly rice) and other crop production practices, and enhancing economic viability of farm enterprises have underpinned these adaptations. Off-farm and non-farm wage employment, temporary migration, self-employment and educating children, constituted the core non-farm adaptation strategies.Emerging cropping systems like maize/cucumber and maize/stem amaranth/rice were economically more viable than the traditional rice/rice and rice/maize systems. Despite some uncertainties, farming was preferred to off-farm work, generating higher returns to labour for all cropping systems. Limited access to stress-tolerant varieties, extension services and affordable agricultural credit, combined with high production costs, variability in crop yields and output prices, are the main barriers to adaptation. Stronger agricultural research and support services, affordable credit, community-focussed farming education and training are critically important for effective adaptation to climate change.     

Forest land consolidation and its effect on climate

Land use changes and forests both play an important role in combating climate change. The climate effects of forest land consolidation have, however, not been studied in detail. As such, this study identifies a number of possible climate effects of forest land consolidation. To specify these, the increased carbon storage in the Pahkakoski land consolidation project (Finland) due to increased forest growth is valued through substitution costs. The results show that the value of the increased carbon storage in the project area is approximately 750 000 euros, or €153/ha. This emanates from the increased growth due to remedial drainage and from the increased forested area. The result is, however, sensitive to changes in the shadow price of carbon. Likewise, the study recognises a need for studies concerning the total climate effect of measures, such as remedial drainage that may also release carbon from the ground. While the overall effects of forest land consolidation are difficult to estimate with current knowledge, this article highlights the potential of land consolidation to combat climate change.     

Regional interdependence and forest “transitions”: Substitute deforestation limits the relevance of local reversals

Using case studies and concepts we suggest that constraints upon aggregate or global forest transition are significantly more severe than those upon local forest reversals. The basic reason is that one region's reversal can be facilitated by other regions that supply resources and goods, reducing the demands upon the region where forests rise. Many past forest reversals involve such interdependence. For ‘facilitating regions’ also to rise in forest requires other changes, since they will not be receiving such help. We start by discussing forest-transitions analysis within the context of Environmental Kuznets Curves (EKCs), for a useful typology of possible shifts underlying transitions. We then consider the historical Northeast US where a regional reversal was dramatic and impressive. Yet this depended upon agricultural price shocks, due to the Midwest US supplying food, and also upon the availability of timber from other US regions. Next we consider deforestation in Amazônia, whose history (like the Northeast US) suggests a potential local role for urbanization, i.e. spatial concentration of population. Yet inter-regional issues again are crucial. For cattle and soy, expansion of global demands may give to Amazonia a role more like the Midwest than the Northeast US. In addition, across-region interdependencies will help determine where reversal and facilitation occur. Finally we discuss the constraints upon very broad forest transition.