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1
Sandker, Marieke, Oswaldo Carrillo, Chivin Leng, Donna Lee, Rémi d’Annunzio, and Julian Fox. "The Importance of High–Quality Data for REDD+ Monitoring and Reporting." Forests 12, no. 1 (2021): 99. http://dx.doi.org/10.3390/f12010099.
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This article discusses the importance of quality deforestation area estimates for reliable and credible REDD+ monitoring and reporting. It discusses how countries can make use of global spatial tree cover change assessments, but how considerable additional efforts are required to translate these into national deforestation estimates. The article illustrates the relevance of countries’ continued efforts on improving data quality for REDD+ monitoring by looking at Mexico, Cambodia, and Ghana. The experience in these countries show differences between deforestation areas assessed directly from maps and improved sample-based deforestation area estimates, highlighting significant changes in both magnitude and trend of assessed deforestation from both methods. Forests play an important role in achieving the goals of the Paris Agreement, and therefore the ability of countries to accurately measure greenhouse gases from forests is critical. Continued efforts by countries are needed to produce credible and reliable data. Supporting countries to continually increase the quality of deforestation area estimates will also support more efficient allocation of finance that rewards REDD+ results-based payments.
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Hultera, Hultera, Lilik Budi Prasetyo, and Yudi Setiawan. "Spatial Model Of The Deforestation Potential 2020 & 2024 And The Prevention Approach, Kutai Barat District." Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) 10, no. 2 (2020): 294–306. http://dx.doi.org/10.29244/jpsl.10.2.294-306.
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Kutai Barat have high forest cover and high deforestation rates. The study purpose to make spatial model, potential distribution of deforestation 2020 and 2024, analysis of the drivers of deforestation, compile and map the approach to reducing deforestation. Deforestation modeling done using MaxEnt and Zonation software. Deforestation sample data used from land cover maps 2009, 2013 and 2016. Deforestation rates used to estimate potential deforestation 2020 and 2024. The drivers of deforestation analyze from land cover change matrix. Prevention strategy approach by overlaying potential deforestation modeling results with RTRW maps. The model has good performance with AUC value 0.873. The validation show very good accuracy for the prediction of area to be deforested by 94%, the accuracy of the spatial distribution of the model 31%. Environmental variables have the highest contribution to the model is the distance from previous deforestation 37.4%. The potential of deforestation 2020 is 85,908 ha and 171,778 ha 2024. Oil palm, agriculture, rubber, HTI and mining are the driver of deforestation. Social forestry is expected to prevent potential deforestation 120,861 ha. Others expected programs to contribute to the deforestation reduction are community land intensification 30,316 ha and implementation of the HCV in plantation 20,120 ha.
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Longobardi, P., A. Montenegro, H. Beltrami, and M. Eby. "Spatial scale dependency of the modelled climatic response to deforestation." Biogeosciences Discussions 9, no. 10 (2012): 14639–87. http://dx.doi.org/10.5194/bgd-9-14639-2012.
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Abstract. Deforestation is associated with increased atmospheric CO2 and alterations to the surface energy and mass balances that can lead to local and global climate changes. Previous modelling studies show that the global surface air temperature (SAT) response to deforestation depends on latitude, with most simulations showing that high latitude deforestation results in cooling, low latitude deforestation causes warming and that the mid latitude response is mixed. These earlier conclusions are based on simulated large scale land cover change, with complete removal of trees from whole latitude bands. Using a global climate model we determine effects of removing fractions of 5% to 100% of forested areas in the high, mid and low latitudes. All high latitude deforestation scenarios reduce mean global SAT, the opposite occurring for low latitude deforestation, although a decrease in SAT is registered over low latitude deforested areas. Mid latitude SAT response is mixed. For all simulations deforested areas tend to become drier and have lower surface air temperature, although soil temperatures increase over deforested mid and low latitude grid cells. For high latitude deforestation fractions of 45% and above, larger net primary productivity, in conjunction with colder and drier conditions after deforestation, cause an increase in soil carbon large enough to generate a previously not reported net drawdown of CO2 from the atmosphere. Our results support previous indications of the importance of changes in cloud cover in the modelled temperature response to deforestation at low latitudes. They also show the complex interaction between soil carbon dynamics and climate and the role this plays on the climatic response to land cover change.
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Pir Bavaghar, M., H. Ghazanfari, and S. Rahimi. "COMPARISON OF ANALYTICAL HIERARCHY PROCESS AND FUZZY METHOD IN DEFORESTATION RISK ZONING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W18 (October 18, 2019): 851–56. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w18-851-2019.
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Abstract. Detection and prediction of land-cover changes are powerful tools in natural resources management and ecosystem assessment. This study was carried out to compare multi-criteria decision techniques (AHP and fuzzy) in deforestation risk zoning. The TM images of Landsat 5 were used to produce deforestation map during 1989 to 2011. In the next step, the most important criteria affecting deforestation were determined. The final weights of criteria were computed using expert's judgments, pairwise comparisons by AHP and also linguistic terms by fuzzy technique. Weighted linear combination method was used to combining the criteria, and each of the generated maps with its special weight was integrated into the GIS environment. The final deforestation risk zoning map, in both methods of AHP and fuzzy, were classified into five classes including of very high, high, moderate, low and very low risk.Evaluation of the results showed that 81.07 and 80.65 percentages of deforestation are located in the very high and high risk zones in the maps derived from AHP and fuzzy approaches, respectively. Based on the results, AHP and fuzzy methods have suitable performance in deforestation risk zoning. Thus, despite the different nature of the AHP and fuzzy methods, it was observed that these two methods do not have much difference in deforestation risk zoning of the study area, in practice.
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Del Valle Coello, Juan José. "Forest Economies: A Remedy to Amazonian Deforestation?" IU Journal of Undergraduate Research 2, no. 1 (2016): 63–71. http://dx.doi.org/10.14434/iujur.v2i1.20929.
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Commonly described as the “lungs of the planet,” the Amazon rainforest represents over half of the remaining rainforest in the world, constituting an important global carbon sink and one of the most culturally- and biologically-diverse regions of the world. The past half-century has seen a worrisome amount of deforestation in this rainforest, but different regions within the Amazon, however, compare differently in terms of deforestation trajectories. What has been the role of products obtained from managing forests, such as the now globally-consumed açaí palm fruit, in reverting deforestation trends? My hypothesis is that there is a statistically significant negative correlation between such forest products and extent of deforestation. This study examines, within the historical and social context of the Amazon Delta and Estuary, the relationship between açaí agroforestry and deforestation. The focus units are the municípios (roughly equivalent to counties) that constitute the Amazon Delta and Estuary, all located in the northern Brazilian states of Amapá and Pará. Statistical data for deforestation obtained from PRODES, a Brazilian governmental project, which monitors deforestation via satellite, is used to ascertain deforestation in the region. This dataset is then correlated with census-based production data for each município for the period from 2002 to 2012. Mapping these variables onto municípios does visually demonstrate a contrast between areas of high deforestation and high açaí production; however, the relationship is not statistically significant.
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Morton, Douglas C., Ruth S. DeFries, Yosio E. Shimabukuro, et al. "Rapid Assessment of Annual Deforestation in the Brazilian Amazon Using MODIS Data." Earth Interactions 9, no. 8 (2005): 1–22. http://dx.doi.org/10.1175/ei139.1.
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Abstract The Brazilian government annually assesses the extent of deforestation in the Legal Amazon for a variety of scientific and policy applications. Currently, the assessment requires the processing and storing of large volumes of Landsat satellite data. The potential for efficient, accurate, and less data-intensive assessment of annual deforestation using data from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) at 250-m resolution is evaluated. Landsat-derived deforestation estimates are compared to MODIS-derived estimates for six Landsat scenes with five change-detection algorithms and a variety of input data—Surface Reflectance (MOD09), Vegetation Indices (MOD13), fraction images derived from a linear mixing model, Vegetation Cover Conversion (MOD44A), and percent tree cover from the Vegetation Continuous Fields (MOD44B) product. Several algorithms generated consistently low commission errors (positive predictive value near 90%) and identified more than 80% of deforestation polygons larger than 3 ha. All methods accurately identified polygons larger than 20 ha. However, no method consistently detected a high percent of Landsat-derived deforestation area across all six scenes. Field validation in central Mato Grosso confirmed that all MODIS-derived deforestation clusters larger than three 250-m pixels were true deforestation. Application of this field-validated method to the state of Mato Grosso for 2001–04 highlighted a change in deforestation dynamics; the number of large clusters (>10 MODIS pixels) that were detected doubled, from 750 between August 2001 and August 2002 to over 1500 between August 2003 and August 2004. These analyses demonstrate that MODIS data are appropriate for rapid identification of the location of deforestation areas and trends in deforestation dynamics with greatly reduced storage and processing requirements compared to Landsat-derived assessments. However, the MODIS-based analyses evaluated in this study are not a replacement for high-resolution analyses that estimate the total area of deforestation and identify small clearings.
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Yani, Akhmad. "Analisis Perkiraan Biaya Ekonomi Deforestasi Di Kalimantan Barat." Jurnal Ekonomi Bisnis dan Kewirausahaan 8, no. 1 (2019): 59. http://dx.doi.org/10.26418/jebik.v8i1.29108.
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Almost all forest areas in the districts / cities in West Kalimantan experience reduced area. Reducing the area of forest area or deforestation can, of course, have a detrimental impact on the environment which in turn can disrupt the sustainability of development itself. Deforestation has ecological, economic and social impacts. The higher the rate of deforestation, it will cause the potential impact will also increase. West Kalimantan experienced a fairly high level of deforestation. This gives an indication that the impact caused by deforestation in West Kalimantan has a relatively high potential. In other words, deforestation causes losses including economic losses. Related to this, the research question is how much economic value is the loss caused by deforestation in West Kalimantan? This research has 2 (two) objectives: first, calculating the economic costs of deforestation in West Kalimantan during the period 2009-2015, and second, analyzing the effect of the economic costs of deforestation on West Kalimantan's GDP during the period 2009-2015. Based on the data base for the period 2009 to 2015 and using the benefit transfer technique, this research has found that the highest economic losses occur in the secondary production forest and the lowest in the conservation forest area. Furthermore, during the period 2009 to 2015, this study has found that the highest economic loss value occurred in 2013 and the lowest occurred in 2011. Overall, the value of economic losses in the form of a combination of depletion and degradation provides a less significant reduction on the value of the forestry sub-sector GRDP in West Kalimantan.
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Firmanda, Ridho, Yudi Antomi, and Febriandi . "Analysis of Deforestation of Padang City's Protection Forest in 2007-2016 and It's Impact on Forest Carbon Emissions." JURNAL BUANA 3, no. 2 (2019): 390. http://dx.doi.org/10.24036/student.v3i2.429.
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ABSTRACT
 Forest Deforestation Analysis is based on land cover, where land cover is divided into two classes of forest land cover and non-forest land cover class. Deforestation is a forested area that turns into a non-forest area. Land cover uses high resolution imagery with manual image interpretation (digit on screen) method. This study aims to determine the extent of deforestation and the rate of deforestation every year so that it is known how much carbon is lost from the impact of deforestation. The method used in this research is quantitative descriptive with carbon calculation which has been determined by the unit of weight for several classes of land cover. The results of research on forest deforestation were 319.92 ha with a deforestation rate of 38.57 ha per year, causing loss of 81.724.7 tons of forest carbon C. Accuracy test of images carried out using confusion matrix (comparison of image interpretation with field conditions) with an accuracy of 92,31%.
 
 Keywords: Manual Image Interpretation, Deforestation Rate, and Accuracy Test.
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Dass, P., C. Müller, V. Brovkin, and W. Cramer. "Can bioenergy cropping compensate high carbon emissions from large-scale deforestation of high latitudes?" Earth System Dynamics 4, no. 2 (2013): 409–24. http://dx.doi.org/10.5194/esd-4-409-2013.
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Abstract. Numerous studies have concluded that deforestation of the high latitudes result in a global cooling. This is mainly because of the increased albedo of deforested land which dominates over other biogeophysical and biogeochemical mechanisms in the energy balance. This dominance, however, may be due to an underestimation of the biogeochemical response, as carbon emissions are typically at or below the lower end of estimates. Here, we use the dynamic global vegetation model LPJmL for a better estimate of the carbon cycle under such large-scale deforestation. These studies are purely theoretical in order to understand the role of vegetation in the energy balance and the earth system. They must not be mistaken as possible mitigation options, because of the devastating effects on pristine ecosystems. For realistic assumptions of land suitability, the total emissions computed in this study are higher than that of previous studies assessing the effects of boreal deforestation. The warming due to biogeochemical effects ranges from 0.12 to 0.32 °C, depending on the climate sensitivity. Using LPJmL to assess the mitigation potential of bioenergy plantations in the suitable areas of the deforested region, we find that the global biophysical bioenergy potential is 68.1 ± 5.6 EJ yr−1 of primary energy at the end of the 21st century in the most plausible scenario. The avoided combustion of fossil fuels over the time frame of this experiment would lead to further cooling. However, since the carbon debt caused by the cumulative emissions is not repaid by the end of the 21st century, the global temperatures would increase by 0.04 to 0.11 °C. The carbon dynamics in the high latitudes especially with respect to permafrost dynamics and long-term carbon losses, require additional attention in the role for the Earth's carbon and energy budget.
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CATTANEO, ANDREA. "Inter-regional innovation in Brazilian agriculture and deforestation in the Amazon: income and environment in the balance." Environment and Development Economics 10, no. 4 (2005): 485–511. http://dx.doi.org/10.1017/s1355770x05002305.
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The paper examines how recent trends in agricultural productivity in Brazil, occurring both inside and outside the Amazon, affected deforestation and agricultural incomes. The analysis uses a computable general equilibrium model adapted to capture regional economic structures, and accounts for uncertainty concerning productivity improvements. Due to countervailing effects on deforestation of innovation inside and outside the Amazon – respectively, increasing and decreasing it – innovation in Brazilian agriculture in the period from 1985 to 1995 has not altered substantially deforestation rates. However, innovation inside the Amazon has to be reckoned as a driving force behind the continuing high levels of deforestation rates.Innovation rates for livestock activities, inside and outside the Amazon, prove crucial in determining deforestation and agricultural income. Technological improvements outside the Amazon for small farm production systems and for farms in general in the North-East increase agricultural income, improve income distribution, and limit deforestation rates.
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Khanal, S., and A. Khadka. "Mapping deforestation and forest degradation using CLASlite approach in Eastern Churia of Nepal." Banko Janakari 26, no. 1 (2016): 17–23. http://dx.doi.org/10.3126/banko.v26i1.15497.
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Monitoring deforestation and forest degradation is essential for forest conservation and sustainable management. Those activities have become more relevant in order to get reference emission level required for Reducing emissions from deforestation and forest degradation (REDD) initiative. The study aimed to assess forest degradation and deforestation in the Churia region of Eastern Nepal using CLASlite approach. This approach is based on Spectral Mixture Analysis and provides highly automated technique for forest cover, deforestation and forest degradation mapping. The Landsat imageries of 2002 and 2013 were processed for estimation of deforestation and forest degradation. The validation of results based on the high-resolution multi-temporal Google Earth imageries and the field sample plots indicated that CLASlite approach could be feasible approach to monitor forests for deforestation and degradation. The results can be further improved by including more frequent time-series observation from Landsat.Banko JanakariA Journal of Forestry Information for NepalVol. 26, No. 1, Page: 17-23, 2016
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Mataveli, Guilherme A. V., Gabriel de Oliveira, Hugo T. Seixas, et al. "Relationship between Biomass Burning Emissions and Deforestation in Amazonia over the Last Two Decades." Forests 12, no. 9 (2021): 1217. http://dx.doi.org/10.3390/f12091217.
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With deforestation and associated fires ongoing at high rates, and amidst urgent need to preserve Amazonia, improving the understanding of biomass burning emissions drivers is essential. The use of orbital remote sensing data enables the estimate of both biomass burning emissions and deforestation. In this study, we have estimated emissions of particulate matter with diameter less than 2.5 µm (PM2.5) associated with biomass burning, a primary human health risk, using the Brazilian Biomass Burning emission model with Fire Radiative Power (3BEM_FRP), and estimated deforestation based on the MapBiomas dataset. Using these estimates, we have assessed for the first time how deforestation drove biomass burning emissions in Amazonia over the last two decades at three scales of analysis: Amazonia-wide, country/state and pixel. Amazonia accounted for 48% of PM2.5 emitted from biomass burning in South America and current deforestation rates have reached values on par with those of the early 21st Century. Emissions and deforestation were concentrated in the Eastern and Central-Southern portions of Amazonia. Amazonia-wide deforestation and emissions were linked through time (R = 0.65). Countries/states with the widest spread agriculture were less likely to be correlated at this scale, likely because of the importance of biomass burning in agricultural practices. Concentrated in regions of ongoing deforestation, in 18% of Amazonia grid cells PM2.5 emissions associated with biomass burning and deforestation were significantly positively correlated. Deforestation is an important driver of emissions in Amazonia but does not explain biomass burning alone. Therefore, future work must link climate and other non-deforestation drivers to completely understand biomass burning emissions in Amazonia. The advance of anthropogenic activities over forested areas, which ultimately leads to more fires and deforestation, is expected to continue, worsening a crisis of dangerous emissions.
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Zhu, Y., R. H. Zong, and T. Y. Zhang. "Deforestation effects on land surface energy coupling: a data-driven perspective." E3S Web of Conferences 96 (2019): 02001. http://dx.doi.org/10.1051/e3sconf/20199602001.
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Deforestation dramatically alters land surface properties and functions through multiple biogeophysical and biogeochemical pathways. However, a quantitative identification of how deforestation affects local energy-water-vegetation coupling is still challenging. In this study we employed information theory and transfer entropy framework to identify the overall feedback pattern of land surface water-energy-vegetation coupling, using high frequency eddy covariance measurements at forested versus deforested sites. We found that deforestation strengthened the directional influence of atmospheric demand on land surface water flux, and more importantly, deforestation broke the coupling between vegetation activities and local precipitation, which led to a less efficient ecosystem to recycle and maintain water within this system.
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Evans, Megan C. "Deforestation in Australia: drivers, trends and policy responses." Pacific Conservation Biology 22, no. 2 (2016): 130. http://dx.doi.org/10.1071/pc15052.
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Australia’s terrestrial environment has been dramatically modified since European colonisation. Deforestation – the clearing and modification of native forest for agricultural, urban and industrial development – remains a significant threat to Australia’s biodiversity. Substantial policy reform over the last 40 years has delivered a range of policy instruments aimed to control deforestation across all Australian States and Territories. Despite these policy efforts – as well as strong governance and high institutional capacity – deforestation rates in Australia were nonetheless globally significant at the turn of this century. Legislation introduced in Queensland and New South Wales during the mid-2000s was at the time seen to have effectively ended broad-scale clearing; however, recent policy changes have raised concerns that Australia may again become a global hotspot for deforestation. Here, I describe the deforestation trends, drivers and policy responses in Australia over the last four decades. Using satellite imagery of forest cover and deforestation events across Australia between 1972 and 2014, I present a comprehensive analysis of deforestation rates at a fine resolution. I discuss trends in deforestation with reference to the institutional, macroeconomic and environmental conditions that are associated with human-induced forest loss in Australia. I provide a detailed history and critique of the native vegetation policies introduced across Australia over the last 40 years, including recent legislative amendments and reviews. Finally, I comment on future prospects for curbing deforestation in Australia, including the role of incentive-based policies such as carbon farming, private land conservation and biodiversity offsets. Despite being a highly active policy space, very little is known of the effectiveness of policy responses to deforestation in Australia, and whether the recent shift away from ‘command and control’ policies will necessarily lead to better outcomes. My analysis demonstrates the need for an effective policy mix to curb deforestation in Australia, including a greater focus on monitoring, evaluation and policy learning.
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Agaja, Toluwalope Mubo, Elisha Ademola Adeleke, Enekole Esther Adeniyi, and Precious Temilade Afolayan. "The Assessment of Deforestation Impact Towards Microclimate and Environment in Ilorin, Nigeria." Geosfera Indonesia 5, no. 3 (2020): 301. http://dx.doi.org/10.19184/geosi.v5i3.16874.
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Nigeria obtains high rate of deforestation with a loss of about 60 percent of its primary forests between 2000 and 2005 as a result of logging, subsistence agriculture, wood exploitation, and urban expansion.This research assessed the level of deforestation and how it has affected Ilorin’s microclimate and the environments. The specific objectives of this study were assessing the relationship that occurs between deforestation and microclimate, examining deforestation and the impact it has within the study area of microclimate, and forecasting the microclimate within the study area by the year 2030. The statistical tools engaged were both descriptive (mean, frequency distribution table and, bar charts) and inferential statistics (multiple regression analysis). The research indicated that there is a significant relationship between deforestation with r2 variables of 0.888 for maximum temperature, 0.201 for minimum temperature, 0.997 for precipitation, 0.43 for solar output, -0.797 and -0.873 for evapotranspiration and relative humidity respectively and Ilorin’s microclimate. The study concludes that deforestation greatly influences the microclimate of Ilorin and occurs due to human’s anthropogenic activities. Deforestation has also led to climate change.
 Keywords: Deforestation; Climate; Micro-climate; Vegetation Cover
 Copyright (c) 2020 Geosfera Indonesia Journal and Department of Geography Education, University of Jember
 This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License
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Fanin, T., and G. R. van der Werf. "Relationships between burned area, forest cover loss and land use change in the Brazilian Amazon based on satellite data." Biogeosciences Discussions 12, no. 11 (2015): 8235–63. http://dx.doi.org/10.5194/bgd-12-8235-2015.
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Abstract. Fires are used as a tool in the deforestation process. Yet, the relationship between fire and deforestation may vary temporally and spatially depending on the type of deforestation and climatic conditions. This study evaluates spatiotemporal dynamics of deforestation and fire represented by burned area over the 2002–2012 period in the Brazilian Legal Amazon. As a first step, we compared newly available Landsat-based maps of gross forest cover loss from the Global Forest Change (GFC) project with maps of deforestation extent from the Amazon Deforestation Monitoring Project (PRODES) produced by the Brazilian National Institute for Space Research (INPE). As a second step, we rescaled the Landsat-based data to the 500 m resolution of the Moderate Resolution Imaging Spectroradiometer (MODIS) burned area data (MCD64A1) and stratified this using MODIS land cover data to study the role of burned area in forest cover loss and deforestation. We found that while GFC forest cover loss and PRODES deforestation generally agreed on spatial and temporal dynamics, there were several key differences between the datasets. Both showed a decrease in the extent of forest cover loss or deforestation after 2004, but the drop was larger and more continuous in PRODES than in GFC. The observed decrease in forest cover loss or deforestation rates over our study period was mainly due to lower clearing rates in the evergreen broadleaf forests in the states of Mato Grosso, Pará and Rondônia. GFC indicated anomalous high forest cover loss in the years 2007 and 2010 not reported by PRODES. The burned area data showed that this was predominantly related to increased fire activity occurring outside of the tropical forest area during these dry years, mainly in Pará. This indicates that fire and forest loss dynamics in woodlands or secondary forests may be equally important as deforestation in regulating atmospheric CO2 concentrations. In addition to the decrease in forest cover loss rates, we also found that post-deforestation fire use declined; burned area within 5 years after forest cover loss decreased from 54 to 39% during our study period.
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Nezalizov, Ana. "Proposal of public policies regarding the reduction of deforestation in Romania." Technium Social Sciences Journal 3, no. 2 (2020): 29–33. http://dx.doi.org/10.47577/tssj.v3i2.85.
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Romania, the problem of deforestation is not a novelty, but, on the contrary, the Romanian state has been facing this for a long time, I would like to mention that the problem of deforestation is not only at national level, but is also felt globally. Massive deforestation is due to a high demand on the market, wood, but also wood products, the more they are illegal, because poaching is at high levels in our country. The issue of deforestation is not unique, but it still entails a lot of shortcomings, such as: desertification of the soil and decrease of its quality, which can be followed by water drying, landslides, etc., decreased air quality due to CO2 emissions, which is constantly increasing, floods, which endanger the citizens who have their homes nearby, thus biodiversity suffers, following the loss of shelter or climate change. The general objective of the public policy proposal is stopping illegalities regarding the forestry fund, improving air quality and biodiversity, stopping illegal trade.
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Lohani, Sapana, Thomas Dilts, Peter Weisberg, Sarah Null, and Zeb Hogan. "Rapidly Accelerating Deforestation in Cambodia’s Mekong River Basin: A Comparative Analysis of Spatial Patterns and Drivers." Water 12, no. 8 (2020): 2191. http://dx.doi.org/10.3390/w12082191.
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The Mekong River is a globally important river system, known for its unique flood pulse hydrology, ecological productivity, and biodiversity. Flooded forests provide critical terrestrial nutrient inputs and habitat to support aquatic species. However, the Mekong River is under threat from anthropogenic stressors, including deforestation from land cultivation and urbanization, and dam construction that inundates forests and encourages road development. This study investigated spatio-temporal patterns of deforestation in Cambodia and portions of neighboring Laos and Vietnam that form the Srepok–Sesan–Sekong watershed. A random forest model predicted tree cover change over a 25-year period (1993–2017) using the Landsat satellite archive. Then, a statistical predictive deforestation model was developed using annual-resolution predictors such as land-cover change, hydropower development, forest fragmentation, and socio-economic, topo-edaphic and climatic predictors. The results show that almost 19% of primary forest (nearly 24,000 km2) was lost, with more deforestation in floodplain (31%) than upland (18%) areas. Our results corroborate studies showing extremely high rates of deforestation in Cambodia. Given the rapidly accelerating deforestation rates, even in protected areas and community forests, influenced by a growing population and economy and extreme poverty, our study highlights landscape features indicating an increased risk of future deforestation, supporting a spatial framework for future conservation and mitigation efforts.
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Steininger, Marc K., Compton J. Tucker, John R. G. Townshend, et al. "Tropical deforestation in the Bolivian Amazon." Environmental Conservation 28, no. 2 (2001): 127–34. http://dx.doi.org/10.1017/s0376892901000133.
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The distributions of forest and deforestation throughout the tropics are poorly known despite their importance to regional biodiversity and global climate and biodiversity. Deforestation estimates based on surveys or sampling have large errors, and high-resolution, wall-to-wall mapping of tropical forests is necessary to assess the impacts of fragmentation. Landsat satellite images from the mid-1980s and early 1990s were thus used to map closed-canopy tropical forest extent and anthropogenic deforestation in an approximately 700 000 km2 area of Amazonian Bolivia with precipitation >1000 mm yr−1. Total potential forest cover extent, including tropical deciduous forest, was 448 700 km2, while the area of natural non-forest formations was 245 100 km2. The area deforested was 15 500 km2 in the mid-1980s and 24 700 km2 by the early 1990s. The rate of tropical deforestation in the forest zone of Bolivia with >1000 mm yr−1 precipitation below 1500 m elevation and north of 19° S, was 1529 km2 yr−1 from 1985–1986 to 1992–1994. Our estimates of deforestation are significantly lower than those reported by the Food and Agriculture Organization of the United Nations (FAO). We document a spatially-concentrated ‘deforestation zone’ in Santa Cruz where >60% of the Bolivian deforestation has occurred. These results indicate that the rate of deforestation in Bolivia has been rapid despite a relatively small human population, and, as in Brazil, clearance has concentrated in the more deciduous forests.
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Pedraza, Carlos, Nicola Clerici, Cristian Forero, et al. "Zero Deforestation Agreement Assessment at Farm Level in Colombia Using ALOS PALSAR." Remote Sensing 10, no. 9 (2018): 1464. http://dx.doi.org/10.3390/rs10091464.
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Due to the fast deforestation rates in the tropics, multiple international efforts have been launched to reduce deforestation and develop consistent methodologies to assess forest extension and change. Since 2010 Colombia implemented the Mainstream Sustainable Cattle Ranching project with the participation of small farmers in a payment for environmental services (PES) scheme where zero deforestation agreements are signed. To assess the fulfillment of such agreements at farm level, ALOS-1 and ALOS-2 PALSAR fine beam dual imagery for years 2010 and 2016 was processed with ad-hoc routines to estimate stable forest, deforestation, and stable nonforest extension for 2615 participant farms in five heterogeneous regions of Colombia. Landsat VNIR imagery was integrated in the processing chain to reduce classification uncertainties due to radar limitations. Farms associated with Meta Foothills regions showed zero deforestation during the period analyzed (2010–2016), while other regions showed low deforestation rates with the exception of the Cesar River Valley (75 ha). Results, suggests that topography and dry weather conditions have an effect on radar-based mapping accuracy, i.e., deforestation and forest classes showed lower user accuracy values on mountainous and dry regions revealing overestimations in these environments. Nevertheless, overall ALOS Phased Array L-band SAR (PALSAR) data provided overall accurate, relevant, and consistent information for forest change analysis for local zero deforestation agreements assessment. Improvements to preprocessing routines and integration of high dense radar time series should be further investigated to reduce classification errors from complex topography conditions.
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Heidarlou, H. Beygi, A. Banj Shafiei, M. Erfanian, A. Tayyebi, and A. Alijanpour. "Underlying driving forces of forest cover changes due to the implementation of preservation policies in Iranian northern Zagros forests." International Forestry Review 22, no. 2 (2020): 241–56. http://dx.doi.org/10.1505/146554820829403531.
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Many countries have implemented policies to reduce the negative effects of deforestation. In Iran, the Zagros Forest Preservation Plan (ZFPP) began in 2003. This study evaluates the effectiveness of ZFPP on land cover changes in two periods, before (1993–2002) and after (2002–2017) implementation of the plan. Logistic regression (LR) analysis was used to examine the effectiveness of key socio-economic, environmental and demographic drivers associated with deforestation activities. The results showed that despite the implementation of ZFPP forest conversion to other land-use types increased during the second period compared to the first. Calculating the annual rate of deforestation showed that this rate increased from -0.4% to -0.5%. The results of LR showed that the occurrence of deforestation in different years was significantly related to distance from rivers, croplands, cities, roads, and slope such that areas with low slope and close to these features have a high probability of deforestation activities.
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Dass, P., C. Müller, V. Brovkin, and W. Cramer. "Can bioenergy cropping compensate high carbon emissions from large-scale deforestation of mid to high latitudes?" Earth System Dynamics Discussions 4, no. 1 (2013): 317–54. http://dx.doi.org/10.5194/esdd-4-317-2013.
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Abstract. Numerous studies have concluded that deforestation of mid to high latitudes result in a global cooling. This is mainly because of the increased albedo of deforested land which dominates over other biogeophysical and biogeochemical mechanisms in the energy balance. This dominance however may be due to an underestimation of the biogeochemical response, as carbon emissions are typically at or below the lower end of estimates. Here, we use the dynamic global vegetation model LPJmL for a better estimate of the carbon cycle under such large-scale deforestation. These studies are purely academic to understand the role of vegetation in the energy balance and the earth system. They must not be mistaken as possible mitigation options, because of the devastating effects on pristine ecosystems. We show that even optimistic assumptions on the manageability of these areas and its utilization for bioenergy crops could not make up for the strong carbon losses in connection with the losses of vegetation carbon and the long-term decline of soil carbon stocks. We find that the global biophysical bioenergy potential is 78.9 ± 7.9 EJ yr−1 of primary energy at the end of the 21st century for the most plausible scenario. Due to avoided usage of fossil fuels over the time frame of this experiment, the cooling due to the biogeophysical feedback could be supplemented by an avoided warming of approximately 0.1 to 0.3 °C. However, the extensive deforestation simulated in this study causes an immediate emission of 182.3 ± 0.7 GtC followed by long term emissions. In the most plausible scenario, this carbon debt is not neutralized even if bioenergy production is assumed to be carbon-neutral other than for the land use emissions so that global temperatures would increase by ~0.2 to 0.6 °C by the end of the 21st century. The carbon dynamics in the high latitudes, especially with respect to permafrost dynamics and long-term carbon losses, require additional attention in the role for the Earth's carbon and energy budget.
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Urgilez-Clavijo, Andrea, David Andrés Rivas-Tabares, Juan José Martín-Sotoca, and Ana María Tarquis Alfonso. "Local Fractal Connections to Characterize the Spatial Processes of Deforestation in the Ecuadorian Amazon." Entropy 23, no. 6 (2021): 748. http://dx.doi.org/10.3390/e23060748.
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Deforestation by human activities is a common issue in Amazonian countries. This occurs at different spatial and temporal scales causing primary forest loss and land fragmentation issues. During the deforestation process as the forest loses connectivity, the deforested patches create new intricate connections, which in turn create complex networks. In this study, we analyzed the local connected fractal dimension (LCFD) of the deforestation process in the Sumaco Biosphere Reserve (SBR) with two segmentation methods, —CA-wavelet and K-means—to categorize the complexity of deforested patches’ connections and then relate these with the spatial processes. The results showed an agreement with both methods, in which LCFD values below 1 corresponded to isolated patches with simple shapes and those above 1 signified more complex and connected patches. From CA-wavelet a threshold of 1.57 was detected allowing us to identify and discern low and high land transformation, while the threshold for K-means was 1.61. Both values represent the region from which deforestation performs local aggressive expansion networks. The thresholds were used to map the LCFD in which all spatial processes were visually detected. However, the threshold of 1.6 ± 0.03 was more effective in discerning high land transformation. such as shrinkage and attrition, in the deforestation process in the SBR.
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van der Werf, G. R., D. C. Morton, R. S. DeFries, et al. "Estimates of fire emissions from an active deforestation region in the southern Amazon based on satellite data and biogeochemical modelling." Biogeosciences 6, no. 2 (2009): 235–49. http://dx.doi.org/10.5194/bg-6-235-2009.
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Abstract. Tropical deforestation contributes to the build-up of atmospheric carbon dioxide in the atmosphere. Within the deforestation process, fire is frequently used to eliminate biomass in preparation for agricultural use. Quantifying these deforestation-induced fire emissions represents a challenge, and current estimates are only available at coarse spatial resolution with large uncertainty. Here we developed a biogeochemical model using remote sensing observations of plant productivity, fire activity, and deforestation rates to estimate emissions for the Brazilian state of Mato Grosso during 2001–2005. Our model of DEforestation CArbon Fluxes (DECAF) runs at 250-m spatial resolution with a monthly time step to capture spatial and temporal heterogeneity in fire dynamics in our study area within the ''arc of deforestation'', the southern and eastern fringe of the Amazon tropical forest where agricultural expansion is most concentrated. Fire emissions estimates from our modelling framework were on average 90 Tg C year−1, mostly stemming from fires associated with deforestation (74%) with smaller contributions from fires from conversions of Cerrado or pastures to cropland (19%) and pasture fires (7%). In terms of carbon dynamics, about 80% of the aboveground living biomass and litter was combusted when forests were converted to pasture, and 89% when converted to cropland because of the highly mechanized nature of the deforestation process in Mato Grosso. The trajectory of land use change from forest to other land uses often takes more than one year, and part of the biomass that was not burned in the dry season following deforestation burned in consecutive years. This led to a partial decoupling of annual deforestation rates and fire emissions, and lowered interannual variability in fire emissions. Interannual variability in the region was somewhat dampened as well because annual emissions from fires following deforestation and from maintenance fires did not covary, although the effect was small due to the minor contribution of maintenance fires. Our results demonstrate how the DECAF model can be used to model deforestation fire emissions at relatively high spatial and temporal resolutions. Detailed model output is suitable for policy applications concerned with annual emissions estimates distributed among post-clearing land uses and science applications in combination with atmospheric emissions modelling to provide constrained global deforestation fire emissions estimates. DECAF currently estimates emissions from fire; future efforts can incorporate other aspects of net carbon emissions from deforestation including soil respiration and regrowth.
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van der Werf, G. R., D. C. Morton, R. S. DeFries, et al. "Estimates of fire emissions from an active deforestation region in the southern Amazon based on satellite data and biogeochemical modelling." Biogeosciences Discussions 5, no. 4 (2008): 3533–73. http://dx.doi.org/10.5194/bgd-5-3533-2008.
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Abstract. Tropical deforestation contributes to the build-up of atmospheric carbon dioxide in the atmosphere. Within the deforestation process, fire is frequently used to eliminate biomass in preparation for agricultural use. Quantifying these deforestation-induced fire emissions represents a challenge, and current estimates are only available at coarse spatial resolution with large uncertainty. Here we developed a biogeochemical model using remote sensing observations of plant productivity, fire activity, and deforestation rates to estimate emissions for the Brazilian state of Mato Grosso during 2001–2005. Our model of DEforestation CArbon Fluxes (DECAF) runs at 250-m spatial resolution with a monthly time step to capture spatial and temporal heterogeneity in fire dynamics in our study area within the "arc of deforestation", the southern and eastern fringe of the Amazon tropical forest where agricultural expansion is most concentrated. Fire emissions estimates from our modelling framework were on average 90 Tg C year−1, mostly stemming from fires associated with deforestation (74%) with smaller contributions from fires from conversions of Cerrado or pastures to cropland (19%) and pasture fires (7%). In terms of carbon dynamics, about 80% of the aboveground living biomass and litter was combusted when forests were converted to pasture, and 89% when converted to cropland because of the highly mechanized nature of the deforestation process in Mato Grosso. The trajectory of land use change from forest to other land uses often takes more than one year, and part of the biomass that was not burned in the dry season following deforestation burned in consecutive years. This led to a partial decoupling of annual deforestation rates and fire emissions, and lowered interannual variability in fire emissions. Interannual variability in the region was somewhat dampened as well because annual emissions from fires following deforestation and from maintenance fires did not covary, although the effect was small due to the minor contribution of maintenance fires. Our results demonstrate how the DECAF model can be used to model deforestation fire emissions at relatively high spatial and temporal resolutions. Detailed model output is suitable for policy applications concerned with annual emissions estimates distributed among post-clearing land uses and science applications in combination with atmospheric emissions modelling to provide constrained global deforestation fire emissions estimates. DECAF currently estimates emissions from fire; future efforts can incorporate other aspects of net carbon emissions from deforestation including soil respiration and regrowth.
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Malahayati, Marissa. "The role of the forest-related sector to the Indonesian Economy: SAM Multiplier Analysis 1985-2008." Open Agriculture 3, no. 1 (2018): 171–79. http://dx.doi.org/10.1515/opag-2018-0018.
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Abstract Indonesia is now the country with the highest deforestation rate in the world, and due to the high rate of associated land use change, Indonesia has also become one of the biggest greenhouse gas emitters in the world. It is commonly thought that the cause of this is Indonesia’s high dependence on the forest-related sector. To investigate the role of forest-related sectors to the Indonesian economy, this study tried to analyze the Social Accounting Matrix (SAM) multiplier from 1985-2008. It was found that there is a tendency for the forest-related sector to contribute a higher multiplier effect to the economy, meaning that Indonesia’s economy is very dependent on the forest-related sector. However, the contribution to the economy is paid for by a high rate of deforestation. Our analysis predicts that the high deforestation rate is mainly due to the establishment of new commercial plantation areas, especially palm oil, and the high rate of illegal logging.
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Cook, Allison G., Anthony C. Janetos, and W. Ted Hinds. "Global Effects of Tropical Deforestation: Towards an Integrated Perspective." Environmental Conservation 17, no. 3 (1990): 201–12. http://dx.doi.org/10.1017/s0376892900032343.
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Deforestation of the tropical moist forests is taking place at an alarming pace; some experts believe that the entire ecobiome will be virtually destroyed within the next ten years. Although the ultimate ecological effects of tropical deforestation remain controversial, our present scientific understanding is adequate to justify efforts to slow the deforestation trend. The impacts that this trend will probably have on global climate remain unclear, while the effects that it will have on biodiversity will clearly be disastrous. This suggests that the research community should place a high priority on applying data on refugia (documented sites of high endemism and species-richness) to conservation planning, and on investigating the probable combined effects of climatic change and habitat fragmentation on world biodiversity.
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Fanin, T., and G. R. van der Werf. "Relationships between burned area, forest cover loss, and land cover change in the Brazilian Amazon based on satellite data." Biogeosciences 12, no. 20 (2015): 6033–43. http://dx.doi.org/10.5194/bg-12-6033-2015.
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Abstract. Fires are used as a tool in the deforestation process. Yet, the relationship between fire and deforestation may vary temporally and spatially depending on the type of deforestation and climatic conditions. This study evaluates spatiotemporal dynamics of deforestation and fire represented by burned area over the 2002–2012 period in the Brazilian Legal Amazon. As a first step, we compared newly available Landsat-based maps of gross forest cover loss from the Global Forest Change (GFC) project with maps of deforestation extent from the Amazon Deforestation Monitoring Project (PRODES) produced by the Brazilian National Institute for Space Research (INPE). As a second step, we rescaled the Landsat-based data to the 500 m resolution of the Moderate Resolution Imaging Spectroradiometer (MODIS) burned area data (MCD64A1) and stratified this using MODIS land cover data to study the role of burned area in forest cover loss and deforestation. We found that while GFC forest cover loss and PRODES deforestation generally agreed on spatial and temporal dynamics, there were several key differences between the data sets. Both showed a decrease in the extent of forest cover loss or deforestation after 2004, but the drop was larger and more continuous in PRODES than in GFC. The observed decrease in forest cover loss or deforestation rates over our study period was mainly due to lower clearing rates in the evergreen broadleaf forests in the states of Mato Grosso, Pará, and Rondônia. GFC indicated anomalously high forest cover loss in the years 2007 and 2010, which was not reported by PRODES. The burned area data indicated that this was predominantly related to increased burned area occurring outside of the tropical forest area during these dry years, mainly in Pará. This indicated that fire and forest loss dynamics in woodlands or secondary forests may be equally important as deforestation in regulating atmospheric CO2 concentrations. In addition to the decrease in forest cover loss rates, we also found that post-deforestation fire use declined; burned area within 5 years after forest cover loss decreased from 54 to 39 % during our study period.
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AIDI, MUHAMMAD NUR, and SANDHI IMAM MAULANA. "A SPATIAL MODEL FOR PREDICTING THE OCCURENCES OF DEFORESTATION IN THE ISLAND OF SUMATRA, INDONESIA." Journal of Sustainability Science and Management 15, no. 6 (2020): 75–84. http://dx.doi.org/10.46754/jbsd.2020.08.007.
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This study primarily aims to develop a spatial model for predicting the occurrences of deforestation in Sumatra Island, Indonesia. This study was conducted based on spatial logistic regression approach that has been widely acknowledged for its flexibility and ability to accept a mixture of both categorical and numerical variables. Result of this study shows that a combination between logistic regression-based modelling and Geographical Information System (GIS) is indeed suitable for determining the probability of deforestation occurrences in Sumatra Island. Analysis conducted in this study has also revealed that physiographic variables, soil type variables, as well as human activity variables have high significant correlation with deforestation. These findings are useful to assist policy makers in Indonesia to understand the process of deforestation and to take it into consideration while formulating land use-related decisions.
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GRAU, H. RICARDO, N. IGNACIO GASPARRI, and T. MITCHELL AIDE. "Agriculture expansion and deforestation in seasonally dry forests of north-west Argentina." Environmental Conservation 32, no. 2 (2005): 140–48. http://dx.doi.org/10.1017/s0376892905002092.
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In Argentina, deforestation due to agriculture expansion is threatening the Semi-arid Chaco, one of the largest forested biomes of South America. This study focuses on the north-west boundary of the Argentine Semi-arid Chaco, where soybean is the most important crop. Deforestation was estimated for areas with different levels of soil and rainfall limitation for agriculture between 1972 and 2001, with a finer analysis in three periods starting in 1984, which are characterized by differences in rainfall, soybean price, production cost, technology-driven yield and national gross domestic product. Between 1972 and 2001, 588 900 ha (c. 20% of the forests) were deforested. Deforestation has been accelerating, reaching >28 000 ha yr−1 after 1997. The initial deforestation was associated with black bean cultivation following an increase in rainfall during the 1970s. In the 1980s, high soybean prices stimulated further deforestation. Finally, the introduction of soybean transgenic cultivars in 1997 reduced plantation costs and stimulated a further increase in deforestation. The domestic economy had little association with deforestation. Although deforestation was more intense in the moister (rainfall >600 mm yr−1) areas, more than 300 000 ha have already been deforested in the drier areas, suggesting that climatic limitations are being overcome by technological and genetic improvement. Furthermore, more than 300 000 ha of forest occur in sectors without major soil and rainfall limitations. If global trends of technology, soybean markets and climate continue, and no active conservation policies are applied, vast areas of the Chaco will be deforested in the coming decades.
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Hinkes, Cordula, and Günter Peter. "Traceability matters." Sustainability Accounting, Management and Policy Journal 11, no. 7 (2020): 1159–87. http://dx.doi.org/10.1108/sampj-04-2019-0145.
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Purpose Sustainability certification of agricultural commodities might be one measure to ensure deforestation-free supply chains. The purpose of this paper is to add to previous assessments of soy certification systems with respect to “zero deforestation” criteria by focusing on the aspect of traceability. Design/methodology/approach A conceptual framework for assessing certification systems is proposed based on a literature review. This concept is applied to 16 soy certification systems, considering previous studies and available chain-of-custody certification options. Findings Among the sample, five certification systems may contribute to ensuring deforestation-free soy supply chains, as they have relatively high “zero deforestation” and assurance requirements and support at least segregation. Other chain-of-custody systems are insufficient in terms of traceability, but still dominate the market. Research limitations/implications The assessment considers only certification systems that have been benchmarked according to criteria developed by the European feed industry. Regular updates and further assessments of certification systems for other commodities are recommended. Practical implications Supply chain actors and policymakers are informed about certification systems that may ensure deforestation-free sourcing. However, different factors influence the implementation of zero deforestation commitments, such as adverse effects, economic trade-offs and new certification and traceability concepts. Social implications The implementation of deforestation-free supply chains should contribute to achieving sustainable development goals. Potential adverse social effects need to be considered. Originality/value This study focuses on the so far rather neglected but essential aspect of traceability, which is required for ensuring deforestation-free sourcing along the whole supply chain.
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PEDLOWSKI, M. A., E. A. T. MATRICARDI, D. SKOLE, et al. "Conservation units: a new deforestation frontier in the Amazonian state of Rondônia, Brazil." Environmental Conservation 32, no. 2 (2005): 149–55. http://dx.doi.org/10.1017/s0376892905002134.
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Over the past several decades, the Brazilian State of Rondônia has been the destination of many rural migrants drawn from Brazil's middle southern regions by massive government colonization projects. Factors such as explosive population growth, logging, mining, small-scale farming and ranching have synergistically fuelled deforestation in the state. The total area deforested in Rondônia in 1978 was 4200 km2. In 1988, the area increased to 30 000 km2, in 1998 to 53 300 km2 and by the year 2003, a total of 67 764 km2 of Rondônia was deforested. In response to the high rate of deforestation observed in Rondônia and other Amazonian states, state and federal agencies worked to create a network of conservation units (CUs) in Brazil during the 1990s that was signed into law(Law 9985/00) in 2000. The ability of these CUs to reduce the rate of deforestation was analysed. Remotely-sensed data from Landsat and thematic coverages were used to measure deforestation inside all CUs in Rondônia. A more detailed analysis of CUs with the highest levels of deforestation, including an analysis between soil types and deforestation and a forecast of potential future deforestation, was conducted. The creation of conservation units in Rondônia has been useful in curbing deforestation within their boundaries; however, many CUs face pressure from the combined activities of illegal loggers, cattle ranchers and small-scale farmers seeking new sources of timber and agricultural land. For example, an exponential increase in the amount of deforestation was observed in Rondônia's Bom Futuro National Forest between 1992 and 2000. A regression model indicated a total of 20 500 ha deforested by 2002, while measurements from 2002 imagery showed an actual total deforestation of 20 720 ha. Should this trend persist, Bom Futuro National Forest could be completely deforested by 2017. CUs in Rondônia must be developed and implemented jointly by all stakeholders through the creation of partnerships between local communities, non-governmental organizations and government agencies.
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Blankespoor, Brian, Susmita Dasgupta, and David Wheeler. "Protected areas and deforestation: new results from high-resolution panel data." Natural Resources Forum 41, no. 1 (2017): 55–68. http://dx.doi.org/10.1111/1477-8947.12118.
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Damnyag, Lawrence, Olli Saastamoinen, Mark Appiah, and Ari Pappinen. "Role of tenure insecurity in deforestation in Ghana's high forest zone." Forest Policy and Economics 14, no. 1 (2012): 90–98. http://dx.doi.org/10.1016/j.forpol.2011.08.006.
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Pepey, Anaïs, Marc Souris, Amélie Vantaux, et al. "Studying Land Cover Changes in a Malaria-Endemic Cambodian District: Considerations and Constraints." Remote Sensing 12, no. 18 (2020): 2972. http://dx.doi.org/10.3390/rs12182972.
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Malaria control is an evolving public health concern, especially in times of resistance to insecticides and to antimalarial drugs, as well as changing environmental conditions that are influencing its epidemiology. Most literature demonstrates an increased risk of malaria transmission in areas of active deforestation, but knowledge about the link between land cover evolution and malaria risk is still limited in some parts of the world. In this study, we discuss different methods used for analysing the interaction between deforestation and malaria, then highlight the constraints that can arise in areas where data is lacking. For instance, there is a gap in knowledge in Cambodia about components of transmission, notably missing detailed vector ecology or epidemiology data, in addition to incomplete prevalence data over time. Still, we illustrate the situation by investigating the evolution of land cover and the progression of deforestation within a malaria-endemic area of Cambodia. To do so, we investigated the area by processing high-resolution satellite imagery from 2018 (1.5 m in panchromatic mode and 6 m in multispectral mode) and produced a land use/land cover map, to complete and homogenise existing data from 1988 and from 1998 to 2008 (land use/land cover from high-resolution satellite imagery). From these classifications, we calculated different landscapes metrics to quantify evolution of deforestation, forest fragmentation and landscape diversity. Over the 30-year period, we observed that deforestation keeps expanding, as diversity and fragmentation indices globally increase. Based on these results and the available literature, we question the mechanisms that could be influencing the relationship between land cover and malaria incidence and suggest further analyses to help elucidate how deforestation can affect malaria dynamics.
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Duque Montoya, Álvaro Javier, Edersson Cabrera Montenegro, and Álvaro Idarraga Piedrahíta. "Historical and potential extinction of shrub and tree species through deforestation in the department of Antioquia, Colombia." Revista Facultad Nacional de Agronomía Medellín 68, no. 2 (2015): 7659–65. http://dx.doi.org/10.15446/rfnam.v68n2.50981.
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We assessed the expected historical and current species richness of shrubs and trees in the Department of Antioquia, northwest region of Colombia. We used the Fisher's alpha value associated with the pooled dataset of identified species in 16 1-ha plots that were used to extrapolate the scaled species richness of the Antioquia Province under three different scenarios: 1) the entire region before deforestation began, assuming an original forest cover of around 92% of the entire province (excluding paramos, rivers, and lakes). 2) The forest cover in 2010. 3) The expected forest cover in 2100 assuming the observed deforestation rate between 2000 and 2010 as a constant. We found that, despite relatively low local and global losses of species, global extinctions in terms of number of species could be dramatically high due to the high endemism and deforestation rates.
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Laurance, William F., Ana K. M. Albernaz, and Carlos Da Costa. "Is deforestation accelerating in the Brazilian Amazon?" Environmental Conservation 28, no. 4 (2001): 305–11. http://dx.doi.org/10.1017/s0376892901000339.
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Recent studies suggest that deforestation rates in the Brazilian Amazon could increase sharply in the future as a result of over US$ 40 billion in planned investments in highway paving and major new infrastructure projects in the region. These studies have been challenged by several Brazilian ministries, which assert that recent improvements in environmental laws, enforcement and public attitudes have fundamentally reduced the threat posed to forests by such projects. The notion that hazards to Amazonian forests have declined over the last decade was assessed using available data on deforestation rates from 1978 to 2000. Although the alarmingly high rate of forest loss during 1978–1989 (1.98 million ha yr−1) declined somewhat in 1990–1994 (1.38 million ha yr−1), it rebounded to a high level in the period 1995–2000 (1.90 million ha yr−1). Moreover, correlation and regression analyses reveal that both absolute and per caput rates of forest loss accelerated significantly over the last decade. These trends fail to support the assertion that deforestation pressure in Amazonian forests has been brought under control. Poor enforcement of existing environmental laws, rapidly expanding logging and mining industries, increasing population pressure and other challenges are greatly hindering efforts to limit the environmental impacts of development activities in Brazilian Amazonia.
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Tabor, Karyn, Jennifer Hewson, Hsin Tien, Mariano González-Roglich, David Hole, and John Williams. "Tropical Protected Areas Under Increasing Threats from Climate Change and Deforestation." Land 7, no. 3 (2018): 90. http://dx.doi.org/10.3390/land7030090.
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Identifying protected areas most susceptible to climate change and deforestation represents critical information for determining conservation investments. Development of effective landscape interventions is required to ensure the preservation and protection of these areas essential to ecosystem service provision, provide high biodiversity value, and serve a critical habitat connectivity role. We identified vulnerable protected areas in the humid tropical forest biome using climate metrics for 2050 and future deforestation risk for 2024 modeled from historical deforestation and global drivers of deforestation. Results show distinct continental and regional patterns of combined threats to protected areas. Eleven Mha (2%) of global humid tropical protected area was exposed to the highest combined threats and should be prioritized for investments in landscape interventions focused on adaptation to climate stressors. Global tropical protected area exposed to the lowest deforestation risk but highest climate risks totaled 135 Mha (26%). Thirty-five percent of South America’s protected area fell into this risk category and should be prioritized for increasing protected area size and connectivity to facilitate species movement. Global humid tropical protected area exposed to a combination of the lowest deforestation and lowest climate risks totaled 89 Mha (17%), and were disproportionately located in Africa (34%) and Asia (17%), indicating opportunities for low-risk conservation investments for improved connectivity to these potential climate refugia. This type of biome-scale, protected area analysis, combining both climate change and deforestation threats, is critical to informing policies and landscape interventions to maximize investments for environmental conservation and increase ecosystem resilience to climate change.
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Avissar, Roni, and David Werth. "Global Hydroclimatological Teleconnections Resulting from Tropical Deforestation." Journal of Hydrometeorology 6, no. 2 (2005): 134–45. http://dx.doi.org/10.1175/jhm406.1.
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Abstract Past studies have indicated that deforestation of the Amazon basin would result in an important rainfall decrease in that region but that this process had no significant impact on the global temperature or precipitation and had only local implications. Here it is shown that deforestation of tropical regions significantly affects precipitation at mid- and high latitudes through hydrometeorological teleconnections. In particular, it is found that the deforestation of Amazonia and Central Africa severely reduces rainfall in the lower U.S. Midwest during the spring and summer seasons and in the upper U.S. Midwest during the winter and spring, respectively, when water is crucial for agricultural productivity in these regions. Deforestation of Southeast Asia affects China and the Balkan Peninsula most significantly. On the other hand, the elimination of any of these tropical forests considerably enhances summer rainfall in the southern tip of the Arabian Peninsula. The combined effect of deforestation of these three tropical regions causes a significant decrease in winter precipitation in California and seems to generate a cumulative enhancement of precipitation during the summer in the southern tip of the Arabian Peninsula.
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Bholanath, P., and K. Cort. "National Scale Monitoring Reporting and Verification of Deforestation and Forest Degradation in Guyana." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-7/W3 (April 29, 2015): 315–22. http://dx.doi.org/10.5194/isprsarchives-xl-7-w3-315-2015.
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Monitoring deforestation and forest degradation at national scale has been identified as a national priority under Guyana‟s REDD+ Programme. Based on Guyana‟s MRV (Monitoring Reporting and Verification) System Roadmap developed in 2009, Guyana sought to establish a comprehensive, national system to monitor, report and verify forest carbon emissions resulting from deforestation and forest degradation in Guyana. To date, four national annual assessments have been conducted: 2010, 2011, 2012 and 2013. <br><br> Monitoring of forest change in 2010 was completed with medium resolution imagery, mainly Landsat 5. In 2011, assessment was conducted using a combination of Landsat (5 and 7) and for the first time, 5m high resolution imagery, with RapidEye coverage for approximately half of Guyana where majority of land use changes were taking place. Forest change in 2013 was determined using high resolution imagery for the whole of Guyana. The current method is an automated-assisted process of careful systematic manual interpretation of satellite imagery to identify deforestation based on different drivers of change. The minimum mapping unit (MMU) for deforestation is 1 ha (Guyana‟s forest definition) and a country-specific definition of 0.25 ha for degradation. <br><br> The total forested area of Guyana is estimated as 18.39 million hectares (ha). In 2012 as planned, Guyana‟s forest area was reevaluated using RapidEye 5 m imagery. Deforestation in 2013 is estimated at 12 733 ha which equates to a total deforestation rate of 0.068%. Significant progress was made in 2012 and 2013, in mapping forest degradation. The area of forest degradation as measured by interpretation of 5 m RapidEye satellite imagery in 2013 was 4 352 ha. All results are subject to accuracy assessment and independent third party verification.
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Molotoks, Amy, and Chris West. "Which forest-risk commodities imported to the UK have the highest overseas impacts? A rapid evidence synthesis." Emerald Open Research 3 (September 24, 2021): 22. http://dx.doi.org/10.35241/emeraldopenres.14306.1.
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Background: Commodity-driven deforestation is a major driver of forest loss worldwide, and globalisation has increased the disconnect between producer and consumer countries. Recent due-diligence legislation aiming to improve supply chain sustainability covers major forest-risk commodities. However, the evidence base for specific commodities included within policy needs assessing to ensure effective reduction of embedded deforestation. Methods: We conducted a rapid evidence synthesis in October 2020 using three databases; Google Scholar, Web of Science, and Scopus, to assess the literature and identify commodities with the highest deforestation risk linked to UK imports. Inclusion criteria include publication in the past 10 years and studies that didn’t link commodity consumption to impacts or to the UK were excluded. The development of a review protocol was used to minimise bias and critical appraisal of underlying data and methods in studies was conducted in order to assess the uncertainties around results. Results: From a total of 318 results, 17 studies were included in the final synthesis. These studies used various methodologies and input data, yet there is broad alignment on commodities, confirming that those included in due diligence legislation have a high deforestation risk. Soy, palm oil, and beef were identified as critical, with their production being concentrated in just a few global locations. However, there are also emerging commodities that have a high deforestation risk but are not included in legislation, such as sugar and coffee. These commodities are much less extensively studied in the literature and may warrant further research and consideration. Conclusion: Policy recommendations in the selected studies suggests further strengthening of the UK due diligence legislation is needed. In particular, the provision of incentives for uptake of policies and wider stakeholder engagement, as well as continual review of commodities included to ensure a reduction in the UK’s overseas deforestation footprint.
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Di Corato, Luca, Michele Moretto, and Sergio Vergalli. "The effects of uncertain forest conservation benefits on long-run deforestation in the Brazilian Amazon." Environment and Development Economics 23, no. 4 (2018): 413–33. http://dx.doi.org/10.1017/s1355770x18000189.
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AbstractDeforestation results from the trade-off between benefits from forest conservation and economic profits associated with land development. However, as net gains are often uncertain, irreversible land development may later be regretted. To better inform conservation policies, we use a real options framework to model irreversible forest conversion under uncertain conservation benefits and determine the associated optimal long-run average rate of deforestation. We then analyze the impact of the demand for agricultural products on the rate of deforestation in the Brazilian Amazon. In a scenario analysis for the nine states of the Brazilian Amazon, we calculate: (i) the expected time for exhaustion of the current forest stock; and (ii) the potential forest coverage for the next 20, 100 and 200 years. Our results suggest that if forest benefits grow over time at a sufficiently high speed, they may significantly slow down deforestation. In contrast, the higher their volatility, the faster deforestation proceeds.
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Coe, Michael T., Toby R. Marthews, Marcos Heil Costa, et al. "Deforestation and climate feedbacks threaten the ecological integrity of south–southeastern Amazonia." Philosophical Transactions of the Royal Society B: Biological Sciences 368, no. 1619 (2013): 20120155. http://dx.doi.org/10.1098/rstb.2012.0155.
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A mosaic of protected areas, including indigenous lands, sustainable-use production forests and reserves and strictly protected forests is the cornerstone of conservation in the Amazon, with almost 50 per cent of the region now protected. However, recent research indicates that isolation from direct deforestation or degradation may not be sufficient to maintain the ecological integrity of Amazon forests over the next several decades. Large-scale changes in fire and drought regimes occurring as a result of deforestation and greenhouse gas increases may result in forest degradation, regardless of protected status. How severe or widespread these feedbacks will be is uncertain, but the arc of deforestation in south–southeastern Amazonia appears to be particularly vulnerable owing to high current deforestation rates and ecological sensitivity to climate change. Maintaining forest ecosystem integrity may require significant strengthening of forest conservation on private property, which can in part be accomplished by leveraging existing policy mechanisms.
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Medvigy, David, Robert L. Walko, Martin J. Otte, and Roni Avissar. "Simulated Changes in Northwest U.S. Climate in Response to Amazon Deforestation*." Journal of Climate 26, no. 22 (2013): 9115–36. http://dx.doi.org/10.1175/jcli-d-12-00775.1.
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Abstract Numerical models have long predicted that the deforestation of the Amazon would lead to large regional changes in precipitation and temperature, but the extratropical effects of deforestation have been a matter of controversy. This paper investigates the simulated impacts of deforestation on the northwest United States December–February climate. Integrations are carried out using the Ocean–Land–Atmosphere Model (OLAM), here run as a variable-resolution atmospheric GCM, configured with three alternative horizontal grid meshes: 1) 25-km characteristic length scale (CLS) over the United States, 50-km CLS over the Andes and Amazon, and 200-km CLS in the far-field; 2) 50-km CLS over the United States, 50-km CLS over the Andes and Amazon, and 200-km CLS in the far-field; and 3) 200-km CLS globally. In the high-resolution simulations, deforestation causes a redistribution of precipitation within the Amazon, accompanied by vorticity and thermal anomalies. These anomalies set up Rossby waves that propagate into the extratropics and impact western North America. Ultimately, Amazon deforestation results in 10%–20% precipitation reductions for the coastal northwest United States and the Sierra Nevada. Snowpack in the Sierra Nevada experiences declines of up to 50%. However, in the coarse-resolution simulations, this mechanism is not resolved and precipitation is not reduced in the northwest United States. These results highlight the need for adequate model resolution in modeling the impacts of Amazon deforestation. It is concluded that the deforestation of the Amazon can act as a driver of regional climate change in the extratropics, including areas of the western United States that are agriculturally important.
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Nazarova, Tatiana, Pascal Martin, and Gregory Giuliani. "Monitoring Vegetation Change in the Presence of High Cloud Cover with Sentinel-2 in a Lowland Tropical Forest Region in Brazil." Remote Sensing 12, no. 11 (2020): 1829. http://dx.doi.org/10.3390/rs12111829.
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Forests play major roles in climate regulation, ecosystem services, carbon storage, biodiversity, terrain stabilization, and water retention, as well as in the economy of numerous countries. Nevertheless, deforestation and forest degradation are rampant in many parts of the world. In particular, the Amazonian rainforest faces the constant threats posed by logging, mining, and burning for agricultural expansion. In Brazil, the “Sete de Setembro Indigenous Land”, a protected area located in a lowland tropical forest region at the border between the Mato Grosso and Rondônia states, is subject to illegal deforestation and therefore necessitates effective vegetation monitoring tools. Optical satellite imagery, while extensively used for landcover assessment and monitoring, is vulnerable to high cloud cover percentages, as these can preclude analysis and strongly limit the temporal resolution. We propose a cloud computing-based coupled detection strategy using (i) cloud and cloud shadow/vegetation detection systems with Sentinel-2 data analyzed on the Google Earth Engine with deep neural network classification models, with (ii) a classification error correction and vegetation loss and gain analysis tool that dynamically compares and updates the classification in a time series. The initial results demonstrate that such a detection system can constitute a powerful monitoring tool to assist in the prevention, early warning, and assessment of deforestation and forest degradation in cloudy tropical regions. Owing to the integrated cloud detection system, the temporal resolution is significantly improved. The limitations of the model in its present state include classification issues during the forest fire period, and a lack of distinction between natural vegetation loss and anthropogenic deforestation. Two possible solutions to the latter problem are proposed, namely, the mapping of known agricultural and bare areas and its subsequent removal from the analyzed data, or the inclusion of radar data, which would allow a large amount of finetuning of the detection processes.
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Pirker, Johannes, Aline Mosnier, Tatiana Nana, et al. "Determining a Carbon Reference Level for a High-Forest-Low-Deforestation Country." Forests 10, no. 12 (2019): 1095. http://dx.doi.org/10.3390/f10121095.
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Research Highlights: A transparent approach to developing a forest reference emissions level (FREL) adjusted to future local developments in Southern Cameroon is demonstrated. Background and Objectives: Countries with low historical deforestation can adjust their forest reference (emission) level (FREL/FRL) upwards for REDD+ to account for likely future developments. Many countries, however, find it difficult to establish a credible adjusted reference level. This article demonstrates the establishment of a FREL for southern Cameroon adjusted to societal megatrends of strong population—and economic growth combined with rapid urbanization. It demonstrates what can be done with available information and data, but most importantly outlines pathways to further improve the quality of future FREL/FRL’s in light of possibly accessing performance-based payments. Materials and Methods: The virtual FREL encompasses three main elements: Remotely sensed activity data; emission factors derived from the national forest inventory; and the adjustment of the reference level using a land use model of the agriculture sector. Sensitivity analysis is performed on all three elements using Monte Carlo methods. Results: Deforestation during the virtual reference period 2000–2015 is dominated by non-industrial agriculture (comprising both smallholders and local elites) and increases over time. The land use model projections are consistent with this trend, resulting in emissions that are on average 47% higher during the virtual performance period 2020–2030 than during the reference period 2000–2015. Monte Carlo analysis points to the adjustment term as the main driver of uncertainty in the FREL calculation. Conclusions: The available data is suitable for constructing a FREL for periodic reporting to the UNFCCC. Enhanced coherence of input data notably for activity data and adjustment is needed to apply for a performance-based payment scheme. Expanding the accounting framework to include forest degradation and forest gain are further priorities requiring future research.
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Lee, Seong-Hyeok, Kuk-Jin Han, Kwon Lee, Kwang-Jae Lee, Kwan-Young Oh, and Moung-Jin Lee. "Classification of Landscape Affected by Deforestation Using High-Resolution Remote Sensing Data and Deep-Learning Techniques." Remote Sensing 12, no. 20 (2020): 3372. http://dx.doi.org/10.3390/rs12203372.
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Human-induced deforestation has a major impact on forest ecosystems and therefore its detection and analysis methods should be improved. This study classified landscape affected by human-induced deforestation efficiently using high-resolution remote sensing and deep-learning. The SegNet and U-Net algorithms were selected for application with high-resolution remote sensing data obtained by the Kompsat-3 satellite. Land and forest cover maps were used as base data to construct accurate deep-learning datasets of deforested areas at high spatial resolution, and digital maps and a softwood database were used as reference data. Sites were classified into forest and non-forest areas, and a total of 13 areas (2 forest and 11 non-forest) were selected for analysis. Overall, U-Net was more accurate than SegNet (74.8% vs. 63.3%). The U-Net algorithm was about 11.5% more accurate than the SegNet algorithm, although SegNet performed better for the hardwood and bare land classes. The SegNet algorithm misclassified many forest areas, but no non-forest area. There was reduced accuracy of the U-Net algorithm due to misclassification among sub-items, but U-Net performed very well at the forest/non-forest area classification level, with 98.4% accuracy for forest areas and 88.5% for non-forest areas. Thus, deep-learning modeling has great potential for estimating human-induced deforestation in mountain areas. The findings of this study will contribute to more efficient monitoring of damaged mountain forests and the determination of policy priorities for mountain area restoration.
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Raiol, Roberta Dannyele Oliveira, Wolmar Benjamim Wosiacki, and Luciano Fogaça de Assis Montag. "Fish of the Taiassuí and Benfica river basins, Benevides, Pará (Brazil)." Check List 8, no. 3 (2012): 491. http://dx.doi.org/10.15560/8.3.491.
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Species inventories are relatively efficient and inexpensive tools for the monitoring of biodiversity, especially in areas that have suffered high rates of deforestation, such as the municipalities located within the “Belém Endemism Center”. This region extends from northeastern Pará to northern Maranhão and has a unique flora and fauna, but is threatened by high rates of deforestation and habitat fragmentation since it is included in the so-called “Arc of Deforestation”. Benevides is the third most impacted municipality within the metropolitan region of Belém (Pará), after Belém itself and Santa Bárbara, but the biological diversity of its freshwater fish fauna is still unknown. In the present study, 81 fish species belonging to seven orders and 23 families were identified. Characidae and Cichlidae were the families with the largest numbers of species in the Taiassuí and Benfica river basins. Two of the species – Apistogramma tucurui and Hyphessobrycon inconstans – were recorded in the state for the first time. Based on the composition analysis of the fishes, it is possible to said that the Benevides fish community is relatively well preserved, because it has high diversity of groups.
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Nobre, Carlos A., Gilvan Sampaio, Laura S. Borma, Juan Carlos Castilla-Rubio, José S. Silva, and Manoel Cardoso. "Land-use and climate change risks in the Amazon and the need of a novel sustainable development paradigm." Proceedings of the National Academy of Sciences 113, no. 39 (2016): 10759–68. http://dx.doi.org/10.1073/pnas.1605516113.
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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.
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Umunay, Peter, Breanna Lujan, Christopher Meyer, and Josefina Cobián. "Trifecta of Success for Reducing Commodity-Driven Deforestation: Assessing the Intersection of REDD+ Programs, Jurisdictional Approaches, and Private Sector Commitments." Forests 9, no. 10 (2018): 609. http://dx.doi.org/10.3390/f9100609.
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To date, numerous public- and private-sector efforts, commitments, and initiatives to reduce commodity-driven deforestation have emerged. In and of themselves, these elements—namely REDD+ programs, jurisdictional approaches (JAs), and private sector commitments—are necessary, but they are not sufficient to reduce deforestation. When operating together, however, these efforts have the potential to significantly reduce commodity-driven deforestation. This research aimed to determine whether and where REDD+ programs, JAs, and private sector commitments overlap in what are termed “trifecta jurisdictions”. Considering that each element possesses features that can enhance and complement those of the others, the authors hypothesized that—but did not ascertain whether—trifecta jurisdictions present the greatest potential to reduce commodity-driven deforestation. A total of 13 trifecta jurisdictions and six bifecta jurisdictions—where two of the three elements are present—were identified by: compiling a dataset of REDD+ programs, JAs, and private sector commitments; evaluating all potential options against established criteria; and categorizing them according to trifecta or bifecta jurisdiction status. The fact that a majority of trifecta and bifecta jurisdictions are located in countries with the most tropical tree cover loss is also significant in that it highlights the presence of these elements where most needed, and how high deforestation rates might be attracting REDD+ program, JA, and private sector commitment activities. Although many of the REDD+ programs, JAs, and private sector commitments are relatively nascent and their ability to collectively reduce deforestation is not yet clearly evident, this article posited that synergistic potential is greatest in trifecta and bifecta jurisdictions and that efforts should be made to greater align these elements.