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

Analysis of the effects of different nitrogen doses and spacing on millet in northern Tocantins

The experiment was conducted at the School of Veterinary Medicine and Zootechnils, Federal University of Tocantins, in order to verify the effects of four nitrogenous manuring levels (0, 30, 60 and 120kg.ha-1) and different spacings (0.25, 0.35, 0.45 and 0.65m) on plant size, biomass and dry mass in the production of millet (Pennisetum glaucum L.). The experimental design consisted of complete blocks, with 16 treatments and four replications in a 4x4 factorial arrangement to form a total of 64 experimental units, each of 9m². The plant sizes and accumulation of biomass and dry matter were estimated weekly starting from 14 days after seeding. For the highest nitrogen level (120kg.ha-1), the biomass and dry mass production were also the highest. There wereno signifi cant differences between the spacings utilized and the plant sizes at any of the phenological stages evaluated. However, the dry mass production was distinct, considering that the spacing of 0.25m presented the highest values, followed by the 0.35m, 0.45m and 0.65m spacings

Análise de diferentes doses de nitrogênio e espaçamento em milheto no norte do Tocantins

The experiment was conducted at the School of Veterinary Medicine and Zootechnils, Federal University of Tocantins, in order to verify the effects of four nitrogenous manuring levels (0, 30, 60 and 120kg.ha-1) and different spacings (0.25, 0.35, 0.45 and 0.65m) on plant size, biomass and dry mass in the production of millet (Pennisetum glaucum L.). The experimental design consisted of complete blocks, with 16 treatments and four replications in a 4x4 factorial arrangement to form a total of 64 experimental units, each of 9m². The plant sizes and accumulation of biomass and dry matter were estimated weekly starting from 14 days after seeding. For the highest nitrogen level (120kg.ha-1), the biomass and dry mass production were also the highest. There were no signifi cant differences between the spacings utilized and the plant sizes at any of the phenological stages evaluated. However, the dry mass production was distinct, considering that the spacing of 0.25m presented the highest values, followed by the 0.35m, 0.45m and 0.65m spacings. http://dx.doi.org/10.5007/2175-7925.2010v23n4p19O experimento foi conduzido na Escola de Medicina Veterinária e Zootecnia do Campus de Araguaína, da Universidade Federal do Tocantins, com o objetivo de verifi car os efeitos de quatros níveis de adubação nitrogenada (0, 30, 60 e 120 kg.ha-1), e quatro diferentes espaçamentos (0,25, 0,35, 0,45 e 0,65m) sobre a altura de plantas e produção de biomassa e matéria seca da cultura do milheto – Pennisetum glaucum L. O delineamento experimental utilizado foi o de blocos casualizados, com dezesseis tratamentos, em fatorial 4 x 4 e quatro repetições, totalizando 64 unidades experimentais, com 9m² cada. As alturas de plantas, o acúmulo de biomassa e de massa seca foi avaliado semanalmente a partir de 14 dias após a semeadura. Na maior dose de nitrogênio (120kg.ha-1) as produções de massa seca foram superiores às demais doses. Não houve diferença significativa entre os espaçamentos utilizados e a altura de plantas em todos os estágios fenológicos avaliados. No entanto, a produção de massa seca foi diferente, sendo que o espaçamento de 0,25m foi o que apresentou maiores valores, seguido pelos espaçamentos 0,35m, 0,45m e 0,65m.

Spatial variability of chemical and physical attributes of dystrophic Red-Yellow Latosol in no tillage

O conhecimento da variabilidade espacial dos atributos químicos e físicos no solo é muito importante, principalmente, para a agricultura de precisão. A geoestatística vem em busca de aprimorar técnicas que possam viabilizar o uso correto e responsável do solo. Assim, durante o ano agrícola 2011/2012, em área de plantio de direto com a cultura do milho, no município de Gurupi (TO), no Cerrado brasileiro, objetivou-se analisar a variabilidade espacial de atributos físico-químicos de um Latossolo Vermelho-Amarelo distrófico sob plantio direto. Foi instalada a malha de amostragem para a coleta de dados do solo, com 100 pontos amostrais, numa área de 1755 m2. Foram determinados os teores de P disponível, matéria orgânica, valor de pH (H2O), teores de K+, Ca2+ e Mg2+, e calculados os valores de soma de bases (SB) e saturação por bases (V%), na profundidade de 0-0,20 m, resistência do solo à penetração (RP), nas profundidades de 0-0,05 m, 0,05-0,10 m, 0,10-0,20 m e 0,20-0,40 m e densidade do solo na profundidade de 0-0,10 m (Ds). Efetuou-se a análise descritiva dos dados e em seguida foram modelados semivariogramas para todos os atributos, obtendo-se as respectivas validações cruzadas e mapas de krigagens. Os atributos químicos e físicos do solo, exceto a saturação por bases (V%), apresentaram dependência espacial. Provavelmente, a descontinuidade da dependência espacial para V%, seja devido a fertilização ao longo dos anos.Knowledge of spatial variability in chemical and physical properties of the soil is very important, especially for precision agriculture. Geostatistics is seeking to improve techniques that can enable the correct and responsible use of soil. So during the agricultural year 2011/2012 in an area of direct planting the corn crop in the municipality of Gurupi (TO), in the Brazilian Cerrado, aimed to analyze the spatial variability of chemical and physical properties in a Typic Dystrophic tillage. Was installed sampling grid for the collection of soil, with 100 sampling points in an area of 1755m2. The contents of available phosphorus, organic matter, pH (H2O), concentrations of K +, Ca2+, Mg2+, the sum of values and base saturation (BS, V) at depths of 0-0.20 m, and resistance to penetration (RP) at depths 0-0.05 m, 0.05-0.10 m, 0.10-0.20 m and 0.20-0.40 m and bulk density (Ds). We conducted a descriptive analysis classic, with the aid of statistical software ASSISTAT, and then were modeled semivariograms for all attributes, resulting in their cross-validation and kriging maps. The chemical and physical properties of soil, except the base saturation (V), spatial dependence. Probably the discontinuity of the spatial dependence of Vvalue, is due to fertility management over the years