Classificação numérica da qualidade de um Latossolo Amarelo sob sistema de integração lavoura-pecuária

Ações antrópicas afetam a atmosfera da terra, despertando para uma consciência global sobre a necessidade de sistemas agrícolas sustentáveis. O objetivo deste estudo foi determinar índices de sustentabilidade do solo para um sistema de integração lavoura-pecuária em um Latossolo Amarelo do cerrado brasileiro no Piauí, utilizando uma classificação numérica. Foram estudados três sistemas de manejo do solo: preparo convencional (PC) com disco de arado e grade pesada em cultivo de soja; plantio direto com rotação de milho soja e milheto como cobertura viva (NT + M); e dois sistemas de integração lavoura-pecuária, um com cinco meses, em pastagens e cultivo de soja (ICL + S) e outro com pastejo contínuo (ICL + P). Uma área sob mata nativa (NF) foi avaliado, como um solo sob condições naturais. Propriedades físicas, químicas e biológicas foram avaliadas no 0,00-0,05 m camada. Na análise de componentes principais, os ambientes ICL + S e ICL + P foram classificados como um único grupo, e pode ser caracterizados pelas propriedades de carbono orgânico no solo, reservatórios de carbono e nitrogênio no solo, o nitrogênio da biomassa microbiana, e total de nitrogênio. A propriedade do solo que melhor caracterizou o ambiente CT foi a atividade da enzima FDA (hidrolisa acetato). As propriedades que melhor caracterizam o ambiente NF são a capacidade de troca catiônica, carbono da biomassa microbiana, microporosidade, índice de estabilidade de agregados, diâmetro médio geométrico e percentagem de agregados estáveis> 2,00 milímetros.Anthropic action is affecting the Earth's atmosphere, awakening a global awareness about the need for sustainable farming systems. The objective of this study was to determine indices of soil sustainability for an integrated crop-livestock system in a Yellow Latosol of the Brazilian Cerrado in Piauí by using a numerical rating. Three systems of soil management were studied: an area under conventional tillage (CT) with plow disk and heavy harrow and soybean cultivation; an area under no-tillage with soybean-maize rotation and millet as a cover crop (NT+M); and two areas under an Integrated Crop-Livestock System, one with five-month pasture grazing and soybean cultivation and the other with continuous pasture grazing (ICL + S and ICL + P, respectively). An area under Native Forest (NF) was evaluated as well as a soil under natural conditions. The physical, chemical, and biological properties were evaluated in the 0.00-0.05 m layer. The environments ICL + S and ICL + P were classified as a single group, and can be characterized by the properties soil organic carbon, soil carbon and nitrogen pools, microbial biomass nitrogen, and total soil N. The property that best characterizes the CT environment is enzyme activity FDA (Fluorescein diacetate hydrolysis). The properties that best characterize the NF environment are cation exchange capacity, microbial biomass carbon, microporosity, aggregate stability index, geometric mean diameter, and percentage of stable >2.00 mm aggregates.Facultad de Ciencias Agrarias y Forestale

Pervasive gaps in Amazonian ecological research

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

Pervasive gaps in Amazonian ecological research

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

Estado nutricional e produção da pimenteira com uso de biofertilizantes líquidos

Os biofertilizantes podem melhorar a sanidade das plantas e incrementar a produtividade das culturas, com baixo custo. Objetivou-se, com este trabalho, avaliar o estado nutricional e características relacionadas à produtividade do fruto de pimenteira em resposta à aplicação de biofertilizantes líquidos na variedade de pimenta Dedo de Moça (Capsicum baccatum var. pendulum L.). O trabalho foi realizado em campo, no município de Teresina, Piauí, Brasil, no período de dezembro de 2010 a setembro de 2011. O delineamento experimental foi em blocos inteiramente casualizados, com quatro repetições. Os tratamentos foram os biofertilizantes "supermagro", "fermentado biológico" e "P + K", com aplicações via foliar e no solo, adubação NPK, conforme recomendação para a cultura do pimentão, e a testemunha absoluta, sem adubação. A variedade de pimenta Dedo de Moça respondeu positivamente ao uso de biofertilizantes líquidos, com aplicação foliar e no solo. O biofertilizante fermentado biológico promoveu maior massa de fruto