10 research outputs found

    Combinações entre cultivares, ambientes, preparo e cobertura do solo em características agronômicas de alface.

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    Objetivou-se identificar combinações entre cultivares, ambientes de cultivo e preparo e cobertura de solo capazes de melhorar o desempenho agronômico e aumentar a produtividade da cultura da alface em cultivo orgânico. A pesquisa foi conduzida na Universidade Federal do Acre, utilizando o delineamento experimental de blocos casualizados, com parcelas subdivididas para cada experimento (campo e casa de vegetação), com quatro repetições. Em cada experimento, três cultivares de alface (Simpson, Marisa e Vera), constituindo as sub-parcelas, foram sorteadas nas parcelas, representadas por quatro preparos e cobertura do solo (encanteiramento com cobertura de palha de arroz, polietileno prateado, solo descoberto e plantio direto). A produtividade comercial de alface foi de 12,3 t ha-1 em cultivo protegido e de 7,9 t ha-1 em campo. O cultivo protegido promoveu melhor desenvolvimento das plantas, caracterizado por maior massa da matéria fresca e seca da parte aérea, massa da matéria fresca comercial e melhor classificação comercial, além de promover bom desempenho agronômico e maior produtividade em qualquer um dos preparos de solo. As cultivares Simpson e Marisa apresentaram massa da matéria seca da parte aérea semelhante e superior à ‘Vera’, porém, o crescimento do caule da ‘Simpson’ foi elevado, caracterizando pendoamento precoce, fato que reduz sua qualidade comercial. As cultivares Marisa e Vera não alongaram o caule indicando serem tolerantes às condições ambientais de Rio Branco. A cobertura do solo com casca de arroz ou plástico prateado contribuiu para minimizar os efeitos climáticos prejudiciais ao cultivo da alface em campo. O plantio direto orgânico não diferiu do plantio em canteiro descoberto

    The drivers and impacts of Amazon forest degradation

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    BACKGROUND: Most analyses of land-use and land-cover change in the Amazon forest have focused on the causes and effects of deforestation. However, anthropogenic disturbances cause degradation of the remaining Amazon forest and threaten their future. Among such disturbances, the most important are edge effects (due to deforestation and the resulting habitat fragmentation), timber extraction, fire, and extreme droughts that have been intensified by human-induced climate change. We synthesize knowledge on these disturbances that lead to Amazon forest degradation, including their causes and impacts, possible future extents, and some of the interventions required to curb them. ADVANCES: Analysis of existing data on the extent of fire, edge effects, and timber extraction between 2001 and 2018 reveals that 0.36 ×106 km2 (5.5%) of the Amazon forest is under some form of degradation, which corresponds to 112% of the total area deforested in that period. Adding data on extreme droughts increases the estimate of total degraded area to 2.5 ×106 km2, or 38% of the remaining Amazonian forests. Estimated carbon loss from these forest disturbances ranges from 0.05 to 0.20 Pg C year−1 and is comparable to carbon loss from deforestation (0.06 to 0.21 Pg C year−1). Disturbances can bring about as much biodiversity loss as deforestation itself, and forests degraded by fire and timber extraction can have a 2 to 34% reduction in dry-season evapotranspiration. The underlying drivers of disturbances (e.g., agricultural expansion or demand for timber) generate material benefits for a restricted group of regional and global actors, whereas the burdens permeate across a broad range of scales and social groups ranging from nearby forest dwellers to urban residents of Andean countries. First-order 2050 projections indicate that the four main disturbances will remain a major threat and source of carbon fluxes to the atmosphere, independent of deforestation trajectories. OUTLOOK: Whereas some disturbances such as edge effects can be tackled by curbing deforestation, others, like constraining the increase in extreme droughts, require additional measures, including global efforts to reduce greenhouse gas emissions. Curbing degradation will also require engaging with the diverse set of actors that promote it, operationalizing effective monitoring of different disturbances, and refining policy frameworks such as REDD+. These will all be supported by rapid and multidisciplinary advances in our socioenvironmental understanding of tropical forest degradation, providing a robust platform on which to co-construct appropriate policies and programs to curb it

    Pervasive gaps in Amazonian ecological research

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    Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

    The drivers and impacts of Amazon forest degradation

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    Approximately 2.5 × 10 6 square kilometers of the Amazon forest are currently degraded by fire, edge effects, timber extraction, and/or extreme drought, representing 38% of all remaining forests in the region. Carbon emissions from this degradation total up to 0.2 petagrams of carbon per year (Pg C year −1 ), which is equivalent to, if not greater than, the emissions from Amazon deforestation (0.06 to 0.21 Pg C year −1 ). Amazon forest degradation can reduce dry-season evapotranspiration by up to 34% and cause as much biodiversity loss as deforestation in human-modified landscapes, generating uneven socioeconomic burdens, mainly to forest dwellers. Projections indicate that degradation will remain a dominant source of carbon emissions independent of deforestation rates. Policies to tackle degradation should be integrated with efforts to curb deforestation and complemented with innovative measures addressing the disturbances that degrade the Amazon forest

    Pervasive gaps in Amazonian ecological research

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    Pervasive gaps in Amazonian ecological research

    Get PDF
    Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

    Estradas na Amazônia: Perspectivas nas Fronteiras Brasil e Peru

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    A apresentação usa mapas da geografia da área de fronteira entre Ucayali e Acre para introduzir dois cenários de estradas propostas: 1) A estrada proposta Trilha UC-105, Nuevo Italia-Puerto Breu, Ucayali, Perú; 2) A estrada proposta Pucallpa, Ucayali, Peru - Cruzeiro do Sul, Acre, Brasil BR-364 e PE-18C

    Roads in Amazonia: Perspectives from the Brazilian and Peruvian Borderlands

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    The main objective of the panel of eight experts is to share local perspectives on road proposals on the shared borders between Ucayali and Acre. Until now information can be found by various means explaining the projects from afar, but it is much more difficult to find the perspectives of people who know the local geography of the area. Are these proposals viable? What would be the impacts of roads on people and local landscapes if they were to be built? Using maps of the geography of the border area between Ucayali and Acre, the panel will interrogate two proposed road scenarios: 1) The proposed road Trocha UC-105, Nuevo Italia-Puerto Breu, Ucayali, Peru, with the participation of Indigenous leaders from ORAU, OPIRJ, and Yorenka Tasorentsi, and an Alto Amazonas Conservation professional with a lot of experience in the field; 2) The proposed highway Pucallpa, Ucayali, Peru - Cruzeiro do Sul, Acre, Brazil BR-364 and PE-18C, with the participation of Indigenous leaders from FECONAU and GRMMU, and experts in the area from UFAC-Floresta and SOS Amazonia

    Carreteras en la Amazonía: Perspectivas de la Frontera Perú-Brasil

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    Esta presentación usa mapas de la geografía de la zona fronteriza entre Ucayali y Acre para introducir dos escenarios de carreteras propuestas: 1) La carretera propuesta trocha UC-105, Nuevo Italia-Puerto Breu, Ucayali, Perú; 2) Lacarretera propuesta Pucallpa, Ucayali, Perú - Cruzeiro do Sul, Acre, Brasil BR-364 y PE-18C

    Data_Sheet_1_Assessment of fire hazard in Southwestern Amazon.docx

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    Fires are among the main drivers of forest degradation in Amazonia, causing multiple socioeconomic and environmental damages. Although human-ignited sources account for most of the fire events in Amazonia, extended droughts may magnify their occurrence and propagation. The southwestern Amazonia, a transnational region shared by Brazil, Peru, and Bolivia and known as the MAP region, has been articulating coordinated actions to prevent disasters, including fire, to reduce their negative impacts. Therefore, to understand the fire patterns in the MAP region, we investigated their main drivers and the changes in the suitability of fire occurrence for the years 2005, 2010, 2016, and 2020. We used a maximum entropy (MaxEnt) model approach based on active fire data from satellites, climatic data, and land use and land cover mapping to spatially quantify the suitability of fire occurrence and its drivers. We used the year 2015 to calibrate the models. For climatic data and active fire count, we only considered grid cells with active fire count over the third quartile. All our models had a satisfactory performance, with values of the area under the curve (AUC) above 0.75 and p < 0.05. Additionally, all models showed sensitivity rates higher than 0.8 and false positive rates below 0.25. We estimated that, on average, 38.5% of the study region had suitable conditions for fire occurrence during the study period. Most of the fire-prone areas belong to Acre, representing approximately 74% of the entire MAP region. The percentage of deforested areas, productive lands, forest edges, and high temperatures were the main drivers of fire occurrence in southwestern Amazonia, indicating the high vulnerability of fragmented landscapes extreme climatic conditions to fire occurrence. We observed that the modeling approach based on Maxint is useful for useful for evaluating the implications of climatic and anthropogenic variables on fire distribution. Furthermore, because the model can be easily employed to predict suitable and non-suitable locations for fire occurrence, it can to prevent potential impacts associated with large-scale wildfire in the future at regional levels.</p
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