CalcMadeira – cálculo de peças de madeira roliça e serrada / CalcMadeira – calculation of round and square pieces of wood

O mercado valora a madeira em volume (metros cúbicos ou estéreo), pela dificuldade em estimar produtos madeireiros, e o produtor, ao vender a madeira em pé, não sabe quantas peças podem ser beneficiadas de suas árvores. Para obter esta informação foram desenvolvidas rotinas para estimar a quantidade de peças de madeira roliça e de madeira serrada que um conjunto de árvores pode fornecer. O desenvolvimento foi em Visual Basic for Applications (VBA) e Python, para peças de madeira roliça mais vendidas no mercado, e peças de madeira serrada informadas na NBR. Para madeira serrada foram simulados três métodos de desdobro. A lógica adotada é a prioridade da maior dimensão em largura e espessura, usando funções dendrométricas e relações trigonométricas. As rotinas visamfacilitar ao usuário o cálculo da receita de sua madeira de acordo com os produtos que serão gerados de um povoamento florestal a ser explorado. Os potenciais usuários são produtores rurais e empresas que plantam florestas, e empresas de desdobro da madeira de eucalipto (serrarias) que vendem, compram madeira em pé

DAMAGE OF THE SPITTLEBUG Deois flavopicta (STAL) (HEMIPTERA: CERCOPIDAE) TO MAIZE IN INTERCROPPING SYSTEM WITH BRACHIARIA GRASS

One of the possibilities of recovering degraded areas intended for cattle raising is the maize-Brachiaria spp. integration. In this system, it recovers soil fertility through the correct use of lime and adequate fertilizer replacement. The plantation of the two agricultural explorations is made simultaneously. However, the presence of some insect-pest common to both crops can reduce the efficiency of the integrated process. One of these insects is the spittlebug, Deois flavopicta (Hemiptera: Cercopidae), a sucking insect causing damage to the pastures both, through nymph and adult feeding. In maize only the adult causes damage, attacking the plant soon after its emergence. The experiment was done with the maize in the V2 phase, confining for a period of eight days a density of two adult spittlebugs/maize plant, kept alone or in association with Brachiaria species, being two susceptible (Brachiaria decumbens cv. Basilisk and B. ruziziensis cv. ruziziensis), and one resistant (B. brizantha cv. marandu). In general the maize in monoculture was significantly damaged by the pest, reducing its development and showing more than 70% of yellowish leaves. The presence of Brachiaria grasses intercropped to maize plants reduced the spittlebug damage to these plants. In the presence of susceptible cultivar, such as B. decumbens, the damage to maize plant was lower than when together with the resistant cultivar B. brizantha

Adubação nitrogenada no milho safrinha em diferentes ambientes no Cerrado brasileiro

The objective of this work was to assess the grain yield and the economic response of off-season corn (Zea mays) crop subjected to different combinations of starter and topdressing nitrogen fertilization, in the Brazilian Cerrado region. The experiment was carried out in a randomized complete block design in a 3×4 factorial arrangement (0, 45, and 90 kg ha-1 N at sowing and 0, 22.5, 45, and 90 kg ha-1 N in topdressing as urea), in six environments, combining three sites and two sowing times. Grain yield was determined, and the response to total N applied as starter and topdressing was used to obtain a general model of the average trend of the technical and economic return of fertilization. The corn crop response varied according to the environment, and the observed yields were high. The application of N as a starter fertilizer increased corn yield and improved the effect of topdressing fertilization or even made it unnecessary. Fertilization with 90 kg ha-1 N as urea promotes greater yield and economic return and improves N balance in the soybean/off-season corn crop system.O objetivo deste trabalho foi avaliar a produtividade de grãos e a resposta econômica de milho (Zea mays) segunda safra submetido a diferentes combinações de adubações de N em semeadura e cobertura, na região do Cerrado brasileiro. O experimento foi conduzido em delineamento de blocos ao acaso, em arranjo fatorial 3×4 (0, 45 e 90 kg ha-1 de N na semeadura e 0, 22,5, 45 e 90 kg ha-1 de N em cobertura na forma de ureia), em seis ambientes, tendo-se combinado três locais e duas épocas de semeadura. A produtividade de grãos foi determinada, e a resposta às doses totais de N na semeadura e em cobertura foi usada para obter um modelo geral da tendência média de retorno técnico e econômico da adubação. A resposta da cultura de milho variou de acordo com o ambiente, e as produtividades observadas foram altas. A adubação nitrogenada na semeadura aumentou a produtividade do milho e melhorou o efeito da adubação em cobertura ou até a dispensou. A fertilização com 90 kg ha-1 de N na forma de ureia proporciona maior produtividade e retorno econômico e melhora o balanço deste nutriente no sistema soja/milho segunda safra

Eficiência produtiva e atributos agronômicos de milho em sistema integração lavoura-pecuária-floresta

The objective of this work was to evaluate the agronomic attributes and production efficiency of corn silage and grains in an integrated crop-livestock-forestry (ICLF) system, with intercropping of eucalyptus, corn, and Urochloa cultivars during three crop years. The experimental design was completely randomized, in 2x5x3 split-split plots with four replicates. The plots consisted of corn cropped between eucalyptus rows (ICLF) and in full sun; the subplots, of the forage grasses U. brizantha 'Marandu', U. brizantha 'Xaraés', U. brizantha 'Piatã', U. ruziziensis, and U. decumbens 'Basilisk'; and the split-split plots, of the 2011/2012, 2012/2013, and 2013/2014 crop years. There was no effect of eucalyptus on the silage and grain yields of corn when intercropped with forages in 2011/2012. The production efficiency of silage and grains decreased by 25 and 48%, respectively, in 2012/2013 (12-month-old eucalyptus). There was also a 56% reduction in grain yield in 2013/2014 (24-month-old eucalyptus), compared with full sun. In the year the ICLF system is established, the production efficiency of corn silage and grains is not affected by eucalyptus, but decreases with the development of the trees in the subsequent crop years.O objetivo deste trabalho foi avaliar os atributos agronômicos e a eficiência produtiva de forragem e grãos de milho em um sistema de integração lavoura-pecuária-floresta (ILPF), com consorciação de eucalipto, milho e cultivares de Urochloa, durante três safras. O delineamento experimental utilizado foi o inteiramente casualizado, em parcelas 2x5x3 sub-subdivididas, com quatro repetições. As parcelas consistiram de cultivo de milho entre renques de eucalipto (ILPF) e a pleno sol; as subparcelas, das forrageiras U. brizantha 'Marandu', U. brizantha 'Xaraés', U. brizantha 'Piatã', U. ruziziensis e U. decumbens 'Basilisk'; e as sub-subparcelas, das safras 2011/2012, 2012/2013 e 2013/2014. Não houve efeito do eucalipto nas produtividades de forragem e grãos de milho consorciado com as forrageiras em 2011/2012. A eficiência produtiva de forragem e grãos teve redução de25 e 48%, respectivamente, em 2012/2013 (eucalipto com 12 meses). Também houve redução de 56% na produtividade de grãos em 2013/2014 (eucalipto com 24 meses), em relação ao cultivo a pleno sol. No ano de implantação do sistema ILPF, a eficiência produtiva de forragem e grãos de milho não é afetada pelo eucalipto, mas é reduzida com o desenvolvimento das árvores nas safras subsequentes

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, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications 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, 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