Profundidade de semeadura na emergência do amendoim-bravo

With the objective of studying the effects of the vertical distribution of seeds upon the emergence of seedlings of wild peanut (Euphorbia heterophylla L.), an experiment was carried out with a Dark-red sandy-phase Latosol taken from the arable layer of the soil. The soil was dried on the shade and passed through a sieve with a 2 mm mesh. The experiment was carried out at the laboratory, on lighted banks, using metallic vases of one liter of capacity. The seeds were sowed at 0 cm, 2 cm, 4 cm, 6 cm, 8 cm and 10 cm deep from the top of the vase. The humidity of the substrate was adjusted periodically to 50% - 60% of the imbibition power of the soil. The seedlings, with the young shoots visible, were daily counted and cut. The emergence period was from the 5th to the 14th day after sowing. The highest daily emergence happened to the zero cm and 2 cm depth on the 5th day; to the 6 cm and 8 cm on the 6th day, and to the 8 cm and 10 cm on the 7th day. The sowing depth, except for 0 cm, did not affect the germination of the seeds, which was about 80%; the germination of the 0 cm depth was 21,3% because of the hydric deficiency that occurred more rapidly at the soil surface. This capacity of germinating deeper in the soil profile is an important factor of aggressiveness of the species, of survival in adverse conditions, and as a factor of pre-emergence resistance to herbicide. Com o objetivo de estudar os efeitos da distribuição vertical das sementes sobre a emergência de plântulas de amendoim-bravo (Euphorbia heterophylla L.), foi instalado um experimento com solo colhido da camada arável de um Latossolo Vermelho-Escuro fase arenosa, incluído na classe textural barro argilo-arenoso. O solo foi secado à sombra e passado em peneira de malha de 2 mm. Em laboratório sobre bancada iluminada, conduziu-se o experimento utilizando vasos metálicos de 1,0 litro. As sementes foram semeadas nas profundidades de 0 cm, 2 cm, 4 cm, 6 cm, 8 cm e 10 cm, a partir da borda superior dos vasos. A umidade do substrato foi ajustada periodicamente para 50% a 60% do poder de embebição do solo. As plântulas, com a plúmula visível, foram cortadas e contadas diariamente. O período de emergência foi do quinto ao décimo quarto dia após a semeadura. A maior emergência diária ocorreu no quinto dia para as profundidades de 0 cm e 2 cm; no sexto, para 6 cm e 8 cm; e no sétimo, para 8 cm e 10 cm. A profundidade de semeadura, com exceção da superficial, não afetou a germinação das sementes, que foi, em média, de 80%; na profundidade de 0 cm, a germinação foi de 21,3%, em decorrência da eficiência hídrica que ocorreu mais rapidamente na superfície do solo. A capacidade de germinação em maiores profundidades no perfil do solo constitui fator de agressividade da espécie, de sobrevivência em condições adversas, e de resistência aos herbicidas de pré-emergência

Atividade biológica de metribuzin e linuron em duas unidades de um latossolo vermelho originalmente sob vegetação de cerrado

Aiming to study the biological activity of the metribuzin and linuron a bioassay was carried out under laboratory conditions using a 2 x 2 x 7 factorial. The factors were: two soil units (Dark-red Latosol-heavy clay and Red-Yellow Latosol-sandy loam texture), two herbicides (metribuzin and linuron) and seven rates of the herbicides (0, 72, 144, 216, 288, 360 and 432 g/ha of metribuzin and 0, 200, 400, 600, 800, 1,000 and 1,200 g/ha of linuron). The Dark-Red and Red-Yellow soils contained 65% and 17% of clay, 12% and 3% of silt, 23% and 80% of sand, 2,07% and 2,06% of organic matter and pH of 5,5 and 5,4, respectively. The experimental design was in randomized blocks with 28 treatments and five replications. Cucumis sativus L. cv. Aodai, was the test plant and the experimental plot was a plastic cup with 260 ml of soil with two seedlings in each cup. In the obtained data, no effect from the two soil materials was observed in the biological activity of herbicides. Linuron had low biological activity, possibly duo to the low solubility. There were increasing effects of doses only to metribuzin in the dry biomass, assessed by linear equation; and by cubic equation, in the green biomass and moisture of plants, in both soil materials.A atividade biológica dos herbicidas residuais depende das características de cada unidade edafológica. Instalou-se um bioensaio para estudar o comportamento do metribuzin e do linuron em um Latossolo Vemelho-Escuro (argila pesada) e um Latossolo Vermelho-Amarelo (franco arenoso). As doses utilizadas foram: 0,72,144,216,288,360 e 432 g/ha de metribuzin e 0, 200, 400,600, 800, 1.000 e 1.200 g/ha de linuron. Os solos, Escuro e Amarelo apresentavam 65% e 17% de argila, 12% e 3% de silte, 23% e 80% de areia, 2,07% e 2,06% de matéria orgânica e pH 5,5 e 5,4, respectivamente. Em laboratório ensaiaram-se 28 tratamentos no esquema fatorial 2 x 2 x 7, repetidos cinco vezes. Os produtos foram incorporados no volume de solo por tratamento; o solo tratado foi distribuído em cinco copos de plástico de 260 ml; semearam-se quatro sementes de pepino (Cucumis sativus L.) cv. Aodai por copo. Aos dez dias, realizou-se um desbaste; das duas plantas restantes coletou-se a parte aérea aos quatorze dias, para obter o peso da biomassa verde e, após secagem, a biomassa seca, e por diferença a umidade das plantas. Não houve efeito dos materiais de solo na atividade biológica dos herbicidas. O linuron foi de baixa atividade biológica, possivelmente em virtude da pequena solubilidade. Houve efeitos de doses crescentes apenas para o metribuzin no peso da biomassa seca, estimado por equação linear, e no da biomassa verde e umidade das plantas, estimado por equações cúbicas, nos dois materiais de solo

TOXICIDAD AGUDA Y RIESGO AMBIENTAL DEL FIPRONIL PARA GUPPY (POECILIA RETICULATA)

El fipronil es un insecticida que tiene amplio espectro de acción para el control de insectos. Debido a los grandes volumenes aplicados en la agricultura, hay posibilidades de que el fipronil sea lixiviado, sufra escorrentia superficial o deriva, pudiendo llegar a los cursos de agua y proporcionar riesgos en la población acuática. Para determinar la toxicidad aguda y el riesgo ambiental del fipronil para el guppy (Poecilia reticulata) 105 peces adultos fueron expuestos a siete concentraciones: 0; 0,025; 0,05; 0,075; 0,1; 0,125 y 0,15 mg·L-1, en acuarios de vidrio con capacidad para 7 L, en sistema estático. Los peces expuestos a 0,1; 0,125 y 0,15 mg·L-1 manifestaron síntomas de hiperexcitación alternados con letargia y nado errático en las primeras 12 h. La mortalidad de los peces después de 96 h de exposición fue de 100; 86,6 y 80% para 0,15; 0,25 y 0,1 mg·L-1 respectivamente, en las concentraciones de 0,025; 0,05 y 0,075 mg·L-1, la mortalidad fue de 13,3; 20 y 33,3% respectivamente. La concentración letal 50 en 96 h (CL ) 50-96h fue estimada en 0,08 mg·L-1 clasificándolo como extremamente tóxico para esta especie. Para el riesgo ambiental acuático (CAS) y el cociente de riesgo (CR) se determinó como alto riesgo de intoxicación en una columna de agua de 0,3 m con valores de 133,33 y 0,02 mg·L-1 y de moderado a bajo a los 2,0 m con valores de 1666,63 y 0,25 mg·L-1, siendo aplicado a la dosis de 400 g i.a./ha, según lo recomendado por el fabricante

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

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