Diferenças entre as dimensões das fibras nos anéis de crescimento determinados no D. A. P. e em níveis diferentes do fuste de árvores adultas de Eucaliptus saligna Smith

This paper deals with the variation of fiber dimentions in growth rings taken at the breast height (B.H.) and at three aditional level of trunk height (10%, 20% and 30% of total height) of two plants of Eucalyptus saligna Smith. Statistical analyses of variance for fiber length, fiber diameter and fiber thikness in diferent growth rings at B.H., 10%, 20% and 30% of trunk height is prsented. Analysis of variance allowed the following conclusion: 1° - Significant diferences were observed for fiber dimentions mean, taken at B.H. and those taken at the levels of 10%, 20% and 30% of trink height; 2° - In any growth rings along the trunk, the fiber length means increased consistently from B.H. to the levels of 10%, 20% and 30% of trink height, however the means for fiber diameter and thikness of the wall decreace from the B.H. point to the leves of 10%, 20% and 30% of trink height; 3° - The results obtained in the present study confirm those obtained by BISSET & DASDWELL (1949) in that the maximum fiber lenght is reached at aproxmately one third of the total height of the trink and also confirm the afirmation made by RUDMAN et al (1969) that the samples taken at the B.H. level are inadequate for qualitative wood studies, specially in raltion with forest genetics investigation.Neste trabalho apresentamos os resultados dos estudos das diferenças entre as dimensões (comprimento, diâmetro e espessura) das fibras lenhosas nos anéis de crescimento (da periferia ao centro do fuste), determinadas ao nível do D. A. P. (distância a altura do peito) e em diferentes níveis (10%, 20% e 30% da altura do fuste) de árvores adultas de Eucalyptus saligna Smith, tendo como objetivo verificar se em nossas condições, as amostras tomadas apenas no D. A. P. representam o fuste da árvore

Estudo sôbre as temperaturas médias em Campinas

This paper deals with the study by orthogonal polynomials of trends in the mean annual and mean monthly temperatures (in degrees Centigrade) in Campinas (State of São Paulo, Brasil), from 1890 up to 1956. Only 4 months were studied (January, April, July and October) taken as typical of their respective season. For the annual averages both linear and quadratic components were significant, the regression equation being y = 19.95 - 0.0219 x + 0.00057 x², where y is the temperature (in degrees Centigrade) and x is the number of years after 1889. Thus 1890 corresponds to x = 1, 1891, to x = 2, etc. The equation shows a minimum for the year 1908, with a calculated mean y = 19.74. The expected means by the regression equation are given below. Anual temperature means for Campinas (SP, Brasil) calculated by the regression equation Year Annual mean (Degrees Centigrade) 1890 19.93 1900 10.78 1908 19.74 (minimum) 1010 19.75 1920 19.82 1930 20.01 1940 20.32 1950 20.74 1956 21.05 The mean for 67 years was 20.08°C with standard error of the mean 0.08°G. For January the regression equation was y = 23.08 - 0.0661 x + 0.00122 x², with a minimum of 22.19°C for 1916. The average for 67 years was 22.70°C, with standard error 0.12°C. For April no component of regression was significant. The average was 20.42°C, with standard error 0.13°C. For July the regression equation was of first degree, y = 16.01 + 0.0140X. The average for 67 years was 16.49°C, with standard error of the mean 0.14°C. Finally, for October the regression equation was y = 20.55 - 0.0362x + 0.00078x², with a minimum of 20.13°C for 1912. The average was 20.52°C, with standard error of the mean equal to 0.14°C

Efeito de operadores, dia de observação e tamanho de amostra e de grânulos na determinação do arredondamento de grânulos da fração areia de solos

Using Krumbein's visual comparison chart, a study is made of the effect of day of observation, observer and sample size on the roundness of quartz grains, using medium, fine and very fine sand as obtained from the "arenito Botucatu" soils in the region of Piracicaba, SP, Brazil. As to sample si ze, 25 grains proved to be sufficient. No significant statistical effect was observed for day of observation. The effect of observer was verified for medium and fine fractions only.Estudam-se, através da carta de comparação visual de Krumbein, os efeitos do dia de observação, observadores e tamanho de amostra na determinação do arredondamento de granulos de quartzo, nas frações areia media, areia fina e areia muito fina de solos do arenito Botucatu, no Município de Piracicaba. Conclui-se que amostras de 25 granulos sao suficientes. Não foi observado efeito estatisticamente significativo do dia de observação. Efeito de observadores foi verificado apenas para as frações media e fina

Legacy of Amazonian Dark Earth soils on forest structure and species composition

This is the final version. Available from the publisher via the DOI in this record.Aim: Amazonian forests predominantly grow on highly weathered and nutrient poor soils. Anthropogenically enriched Amazonian Dark Earths (ADE), traditionally known as Terra Preta de Índio, were formed by pre-Columbian populations. ADE soils are characterized by increased fertility and have continued to be exploited following European colonization. Here, we evaluated the legacy of land-use and soil enrichment on the composition and structure in ADE and non-ADE (NDE) forests. Location: Eastern and southern Amazonia. Time period: Pre-Columbia – 2014. Methods: We sampled nine pairs of ADE and adjacent NDE forest plots in eastern and southern Amazonia. In each plot, we collected soil samples at 0–10 and 10–20 cm depth and measured stem diameter, height, and identified all individual woody plants (palms, trees and lianas) with diameter ≥ 10 cm. We compared soil physicochemical properties, vegetation diversity, floristic composition, aboveground biomass, and percentage of useful species. Results: In the nine paired plots, soil fertility was significantly higher in ADE soil. We sampled 4,191 individual woody plants representing 404 species and 65 families. The floristic composition of ADE and NDE forests differed significantly at both local and regional levels. In southern Amazonia, ADE forests had, on average, higher aboveground biomass than other forests of the region, while in eastern Amazonia, biomass was similar to that of NDE forests. Species richness of both forest types did not differ and was within the range of existing regional studies. The differences in composition between large and small diameter tree recruits may indicate long-term recovery and residual effects from historical land-use. Additionally, the proportion of edible species tended to be higher in the ADE forests of eastern and southern Amazonia. Main conclusions: The marked differences in soil fertility, floristic composition and aboveground biomass between ADE and NDE forests are consistent with a small-scale long-term land-use legacy and a regional increase in tree diversity

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