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

Forage mass production and grazing loss of sorghum hybrid in response to the density of the sowing and the spacing between planting lines

The objective of this experiment was to evaluate dry matter yield and loss of grazing due to animal trampling in response to sowing density and spacing between lines in the planting. Sorghum hybrid 1P400 was submitted to six treatments, composed of three sowing density combinations (12; 16 and 20 kg/ha of seeds) and two spacing between lines (0.40 and 0.80 m). Sorghum hybrid 1P400 was sowed in two seasons, at the end of spring (December 3rd, 2005) and the other at the end of summer (March 20th, 2006). Cultivation strategies influenced plant population in the two experimental seasons. Diameter of the stem in season 1 decreased with density increase, whereas in the second season, interaction between sowing density and spacing was significant. In the first season, 0.40-m spacing promoted greater losses due to grazing stepping, that is, 891 kg/ha of DM, whereas in the second season there was no statistical difference. There was no significant difference in forage dry matter yield in sowing densities among the two studied seasons. Dry mater production of sorghum hybrids 1P400 did not increase with the increase of the sowing density in the two sowing seasons, therefore it is recommended 12 kg/ha of seeds for the sowing. Sorghum IP400 cultivated in 0.80-m spacing resulted in lower forage loss caused by grazing bovine trampling. © 2011 Sociedade Brasileira de Zootecnia

Silicon reduces aluminum content in tissues and ameliorates its toxic effects on potato plant growth

ABSTRACT: Aluminum (Al) is highly toxic to plants, causing stress and inhibiting growth and silicon (Si) is considered beneficial for plants. This chemical element has a high affinity with Al. The aim of this study was to investigate the potential of Si to mitigate the toxic effects of Al on potato ( Solanum tuberosum L.) plants and assess whether this behavior is different among genotypes with differing degrees of sensitivity to Al. Potato plants of the genotypes SMIJ319-7 (Al-sensitive) and SMIF212-3 (Al-tolerant) were grown for fourteen days in nutrient solution (without P and pH 4.5±0.1) under exposure to combinations of Al (0 and 1.85mM) and Si (0, 0.5 and 1.0mM). After this period, shoot and roots of the two genotypes were collected to determine Al content in tissues and assess morphological parameters of root and shoot growth. Roots of both genotypes accumulated more Al than shoots and the Al-tolerant genotype accumulated more Al than the sensitive one, both in roots and in shoot. Furthermore, the presence of 0.5 and 1.0mM Si together with Al reduced the Al content in shoot in both genotypes and in roots of the Al-tolerant genotype, respectively. Si ameliorated the toxic effects of Al with regard to number of root branches and leaf number in both potato genotypes. Si has the potential to mitigate the toxic effects of Al in potato plants regardless of Al sensitivity