Spatiotemporal patterns of tropical deforestation and forest degradation in response to the operation of the Tucuruí hydroelectric dam in the Amazon basin

Chen, Gang; Powers, Ryan; Carvalho, Luís Marcelo Tavares de; Mora, B.

doi:10.1016/j.apgeog.2015.06.001

Cited by 74 publications

(58 citation statements)

References 34 publications

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“…It is urgent to halt deforestation, keeping in mind that almost 1 million square kilometers of the Amazon tropical forests have already been deforested and another equal portion finds itself in the process of degradation (27). The rate of deforestation has declined in the last several years; this decline is conspicuous in the Brazilian Amazon, where deforestation rates have been cut down by almost 80% since 2005 (32)(33)(34) at the same time that the agricultural output in the region has been increasing significantly (35).…”

Section: Significancementioning

confidence: 99%

“…This sharp decline of deforestation was enabled by several factors, including purpose-built satellite monitoring capabilities, effective law enforcement and compliance, industry value chain initiatives like the soy moratorium, restrictions on access to credit for farms located in deforested areas, and expansion of protected areas and indigenous territory encompassing 47% of the entire Brazilian Amazon region (37). Long-term-demand growth for agricultural commodities in the emerging markets, weak institutions, and large energy infrastructure projects may potentially contribute as underlying and proximate drivers to the return of high deforestation rates in the absence of alternative development pathways (27,30,(38)(39)(40).…”

Section: Significancementioning

confidence: 99%

“…The plan calls for 30 new large dams in the next 30 y (23), with the associated flooding of ∼12,000 km 2 (144). The flooding of these areas will cause a series of environmental impacts: significant increases of greenhouse gas emissions (145), disorders to local wildlife by blocking mass fish migration patterns and changes in ichthyological diversity (146,147), loss in connectivity between upstream and downstream (148), decreased productivity in lowland Amazon floodplains due to the retention of nutrients by reservoirs (149), hydrological alterations through the water level change (150), deforestation and degradation of forests near the reservoir (27), transmission of parasitic diseases to humans such as malaria and leishmaniasis (151,152), social impacts with the displacement of traditional populations and indigenous peoples (153,154), and reduction of fish catch potential (155).…”

Section: Impacts Of Anthropogenic Drivers Of Change In the Amazonmentioning

confidence: 99%

“…The prevailing model for rural development in the Amazon over the last half century-replacing forests with agriculture, cattle ranching, and large-scale hydropower generation-has long been outdated for a number of environmental, economic, and social reasons (25)(26)(27). For instance, for Brazil, the gross agricultural product of the Amazon represents 14.5% of Brazil's agriculture sector gross domestic product (GDP), using a deforested area of about 750,000 km 2 .…”

mentioning

confidence: 99%

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Land-use and climate change risks in the Amazon and the need of a novel sustainable development paradigm

Nobre

Sampaio

Borma

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

697

449

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For half a century, the process of economic integration of the Amazon has been based on intensive use of renewable and nonrenewable natural resources, which has brought significant basin-wide environmental alterations. The rural development in the Amazonia pushed the agricultural frontier swiftly, resulting in widespread land-cover change, but agriculture in the Amazon has been of low productivity and unsustainable. The loss of biodiversity and continued deforestation will lead to high risks of irreversible change of its tropical forests. It has been established by modeling studies that the Amazon may have two "tipping points," namely, temperature increase of 4°C or deforestation exceeding 40% of the forest area. If transgressed, large-scale "savannization" of mostly southern and eastern Amazon may take place. The region has warmed about 1°C over the last 60 y, and total deforestation is reaching 20% of the forested area. The recent significant reductions in deforestation-80% reduction in the Brazilian Amazon in the last decade-opens up opportunities for a novel sustainable development paradigm for the future of the Amazon. We argue for a new development paradigm-away from only attempting to reconcile maximizing conservation versus intensification of traditional agriculture and expansion of hydropower capacity-in which we research, develop, and scale a high-tech innovation approach that sees the Amazon as a global public good of biological assets that can enable the creation of innovative high-value products, services, and platforms through combining advanced digital, biological, and material technologies of the Fourth Industrial Revolution in progress.Amazon tropical forests | Amazon sustainability | Amazon land use | Amazon savannization | climate change impacts

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Section: Significancementioning

confidence: 99%

Section: Significancementioning

confidence: 99%

Section: Impacts Of Anthropogenic Drivers Of Change In the Amazonmentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Land-use and climate change risks in the Amazon and the need of a novel sustainable development paradigm

Nobre

Sampaio

Borma

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

697

449

View full text Add to dashboard Cite

show abstract

“…Thus, the information from field measurements is limited in the spatial and temporal dimensions. Satellite images, because of their immense spatial dimension and high temporal frequency, may reliably detect forest changes over large areas and provide insights into the agents underlying these changes [18][19][20]. Landsat data are especially well suited to detecting forest changes over decades and a variety of spatial extents [21,22].…”

Section: Introductionmentioning

confidence: 99%

Attribution of Disturbance Agents to Forest Change Using a Landsat Time Series in Tropical Seasonal Forests in the Bago Mountains, Myanmar

Shimizu

Ahmed

Poncé-Hernandez

et al. 2017

Forests

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Abstract:In 2016, in response to forest loss, the Myanmar government banned logging operations for 1 year throughout the entire country and for 10 years in specific regions. However, it is unclear whether this measure will effectively reduce forest loss, because disturbance agents other than logging may have substantial effects on forest loss. In this study, we investigated an approach to attribute disturbance agents to forest loss, and we characterized the attribution of disturbance agents, as well as the areas affected by these agents, in tropical seasonal forests in the Bago Mountains, Myanmar. A trajectory-based analysis using a Landsat time series was performed to detect change pixels. After the aggregation process that grouped adjacent change pixels in the same year as patches, a change attribution was implemented using the spectral, geometric, and topographic information of each patch via random forest modeling. The attributed agents of change include "logging", "plantation", "shifting cultivation", "urban expansion", "water invasion", "recovery", "other change", and "no change". The overall accuracy of the attribution model at the patch and area levels was 84.7% and 96.0%, respectively. The estimated disturbance area from the attribution model accounted for 10.0% of the study area. The largest disturbance agent was found to be logging (59.8%), followed by water invasion (14.6%). This approach quantifies disturbance agents at both spatial and temporal scales in tropical seasonal forests, where limited information is available for forest management, thereby providing crucial information for assessing forest conditions in such environments.

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Assessment on land use changes and livelihood transition under the hydropower dam construction in Paunglaung Township, Southern Shan Highlands, Myanmar

et al. 2023

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We examined agricultural land use changes and their impacts on the local livelihoods of upstream farmers after the Paunglaung hydropower dam construction in Myanmar. Landsat and GeoEye images, acquired in 2011 and 2018, were used to detect agricultural land use changes. A marked decrease in agricultural land (5.77% of farmland and 9.64% of swidden) was observed, whereas orchards and plantations were introduced as new farming practices. Using the household survey, the income strategies were categorized by different wealth groups, and the socioeconomic condition was compared among the groups. We also compared the annual household income before and after dam construction. A significant change in income strategies after the dam construction were observed in low‐income households, but not in medium and high‐income households. Local people engaged in diversified livelihood strategies after the dam construction, mainly in relocated villages. Besides, farmland lost due to dam construction caused the significant insufficiency of rice self‐consumption and consequently resulted in greater dependency on the market of rice and their products. This study highlighted land use changes due to dam construction and its impacts on the livelihood of local farmers, contributing to planning the land use and livelihood strategies for affected farmers to ensure their livelihood security.

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Spatiotemporal patterns of tropical deforestation and forest degradation in response to the operation of the Tucuruí hydroelectric dam in the Amazon basin

Cited by 74 publications

References 34 publications

Land-use and climate change risks in the Amazon and the need of a novel sustainable development paradigm

Land-use and climate change risks in the Amazon and the need of a novel sustainable development paradigm

Attribution of Disturbance Agents to Forest Change Using a Landsat Time Series in Tropical Seasonal Forests in the Bago Mountains, Myanmar

Assessment on land use changes and livelihood transition under the hydropower dam construction in Paunglaung Township, Southern Shan Highlands, Myanmar

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