Growth and dry matter production in sugarcane varieties grown under full irrigation

A análise de crescimento é considerada o método padrão para medir a produtividade biológica em espécies vegetais. Neste contexto objetivou-se avaliar, em onze variedades de cana-de-açúcar (SP79-1011, RB813804, RB863129, RB872552, RB943365, RB72454, RB763710, SP78-4764, SP81-3250, RB867515, RB92579) cultivadas sob irrigação plena, o crescimento e a produção de matéria seca no ciclo de cana planta. O experimento foi instalado em condições de campo no município de Carpina, PE. Utilizou-se o delineamento estatístico de blocos ao acaso, com quatro repetições. A análise de crescimento correspondeu à quantificação dos números de perfilhos e à, na mensuração da altura e diâmetro dos colmos, avaliados mensalmente em onze períodos de cultivo, os quais se estenderam dos 60 aos 360 dias após o plantio (DAP). A produção de matéria seca foi quantificada a partir dos 120 DAP, com intervalos de amostragem a cada dois meses. Observou-se que as variedades RB92579 e SP81-3250 apresentaram o maior perfilhamento e produção de matéria seca e as variedades RB813804 e RB72454 às maiores médias de altura, enquanto as variedades RB867515 e RB72454 obtiveram os maiores diâmetros do colmo.Growth analysis is considered as a standard method for measuring the biological productivity of plant species. The objective of this research was to evaluate the growth and dry matter production of eleven sugarcane varieties (SP79-1011, RB813804, RB863129, RB872552, RB943365, RB72454, RB763710, SP78-4764, SP81-3250, RB867515, RB92579), grown under full irrigation, in the planted cane cycle. The experiment was conducted in field conditions in the municipality of Carpina, PE. A randomized block design with four replications was used. The varieties' growth analysis was represented by the quantification of the tillers numbers, stalk height and diameter, measured monthly, in eleven periods of cultivation that extended from 60 to 360 days after planting (DAP). The dry matter production was measured from 120 DAP, with sampling intervals of every two months. It was observed that, at 360 DAP, the RB92579 and SP81-3250 varieties showed the highest tillering and dry matter production. The RB813804 and RB72454 varieties had the highest average for height, while the RB72454 and RB867515 varieties presented the largest stalk diameters

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0\u20135 and 5\u201315 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10\ub0C (mean = 3.0 \ub1 2.1\ub0C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 \ub1 2.3\ub0C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler ( 120.7 \ub1 2.3\ub0C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Immune and inflammatory responses to Leishmania amazonensis isolated from different clinical forms of human leishmaniasis in CBA mice

Leishmania amazonensis causes different diseases depending on the host and parasitic virulence factors. In this study, CBA mice were infected with L. amazonensis isolates from patients with localized (Ba125), diffuse cutaneous (Ba276) or visceral leishmaniasis (Ba109). Mice infected with Ba125 and Ba276 progressed rapidly and lesions displayed an infiltrate rich in parasitized macrophages and were necrotic and ulcerated. Ba109 induced smaller lesions and a mixed inflammatory infiltrate without necrosis or ulceration. Ba109 induced an insidious disease with lower parasite load in CBA mice, similar to human disease. Levels of IFN-γ, IL-4 and IL-10 did not differ among the groups. Because all groups were unable to control the infection, expression of IL-4 associated with low production of IFN-γ in the early phase of infection may account for susceptibility, but others factors may contribute to the differences observed in inflammatory responses and infection progression. Evaluation of some parasitic virulence factors revealed that Ba276 exhibits higher ecto-ADPase and 5'-nucleotidase activities compared to the Ba109 and Ba125 strains. Both Ba276 and Ba125 had higher arginase activity in comparison to Ba109. Finally, these data suggest that the differences in enzyme activities among parasites can account for differences in host inflammatory responses and infection progression

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