PCR identification of lactic acid bacteria populations in corn silage inoculated with lyophilised or activated Lactobacillus buchneri

This study aimed to evaluate the effect of inoculation with lyophilised and/or activated Lactobacillus buchneri on lactic acid bacteria populations in corn silage. Experimental treatments consisted of corn silage without additives or silage with the inoculants of L. buchneri (1 x 105 cfu/g) applied according to the manufacturer’s recommendations (1 g/tonne fodder) in the forms of the lyophilised inoculant and pre-activated inoculant. Purified isolates from corn silage with and without the inoculant were identified, and 93% of the isolates corresponded to the lactic acid bacteria of the species Lactobacillus plantarum. Among the isolates, no bacteria of the species L. buchneri were detected. The application of lyophilised or activated L. buchneri improved the microbiological profile and reduced ethanol production in corn silage, even without being identified among the isolates captured 70 days after ensilage. Highlights: Lactic acid bacteria showed greater development at 7 days of fermentation. Lactobacillus plantarum predominated at 70 days, representing 93% of the total LAB population. Lactobacillus buchneri improved its microbiological profile with decreased ethanol production.This study aimed to evaluate the effect of inoculation with lyophilised and/or activated Lactobacillus buchneri on lactic acid bacteria populations in corn silage. Experimental treatments consisted of corn silage without additives or silage with the inoculants of L. buchneri (1 x 105 cfu/g) applied according to the manufacturer’s recommendations (1 g/tonne fodder) in the forms of the lyophilised inoculant and pre-activated inoculant. Purified isolates from corn silage with and without the inoculant were identified, and 93% of the isolates corresponded to the lactic acid bacteria of the species Lactobacillus plantarum. Among the isolates, no bacteria of the species L. buchneri were detected. The application of lyophilised or activated L. buchneri improved the microbiological profile and reduced ethanol production in corn silage, even without being identified among the isolates captured 70 days after ensilage. Highlights: Lactic acid bacteria showed greater development at 7 days of fermentation. Lactobacillus plantarum predominated at 70 days, representing 93% of the total LAB population. Lactobacillus buchneri improved its microbiological profile with decreased ethanol production

Effect of urea on gas and effluent losses, microbial populations, aerobic stability and chemical composition of corn (Zea mays L.) silage

We evaluated the effects of urea addition on gas and effluent losses, fermentation profile, microbial populations, aerobic stability and chemical composition of corn silages. A completely randomised design with five levels of urea (0, 0.5, 1.0, 1.5, and 2.0% based on dry matter) and five replicates was used. A decreasing linear effect of urea levels on effluent losses in corn silages was observed. In parallel, an increasing linear effect of urea levels on pH, increasing from 3.49 to 4.12 in silages without urea in relation to silages with the maximum urea level, was also observed. Urea addition improved the aerobic stability of the silages, with 62 h for the silages without urea and from 90 to >96 h for the silages with urea. Based on the results of the principal components, two groups (I and II) could be distinguished. The most discriminating variables in group I were dry matter (-0.9), pH (-1.2) and lactic acid bacteria (-0.9), while in group II, effluent losses (1.0), ethanol (1.0), acetic acid (0.8) and gas losses (0.8) were most important. The use of urea at inclusion levels of around 2% in corn silage reduced gas losses, improved the nutritive value and promote the aerobic stability of silages

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

NEOTROPICAL ALIEN MAMMALS: a data set of occurrence and abundance of alien mammals in the Neotropics

Biological invasion is one of the main threats to native biodiversity. For a species to become invasive, it must be voluntarily or involuntarily introduced by humans into a nonnative habitat. Mammals were among first taxa to be introduced worldwide for game, meat, and labor, yet the number of species introduced in the Neotropics remains unknown. In this data set, we make available occurrence and abundance data on mammal species that (1) transposed a geographical barrier and (2) were voluntarily or involuntarily introduced by humans into the Neotropics. Our data set is composed of 73,738 historical and current georeferenced records on alien mammal species of which around 96% correspond to occurrence data on 77 species belonging to eight orders and 26 families. Data cover 26 continental countries in the Neotropics, ranging from Mexico and its frontier regions (southern Florida and coastal-central Florida in the southeast United States) to Argentina, Paraguay, Chile, and Uruguay, and the 13 countries of Caribbean islands. Our data set also includes neotropical species (e.g., Callithrix sp., Myocastor coypus, Nasua nasua) considered alien in particular areas of Neotropics. The most numerous species in terms of records are from Bos sp. (n = 37,782), Sus scrofa (n = 6,730), and Canis familiaris (n = 10,084); 17 species were represented by only one record (e.g., Syncerus caffer, Cervus timorensis, Cervus unicolor, Canis latrans). Primates have the highest number of species in the data set (n = 20 species), partly because of uncertainties regarding taxonomic identification of the genera Callithrix, which includes the species Callithrix aurita, Callithrix flaviceps, Callithrix geoffroyi, Callithrix jacchus, Callithrix kuhlii, Callithrix penicillata, and their hybrids. This unique data set will be a valuable source of information on invasion risk assessments, biodiversity redistribution and conservation-related research. There are no copyright restrictions. Please cite this data paper when using the data in publications. We also request that researchers and teachers inform us on how they are using the data

Characterisation of microbial attack on archaeological bone

As part of an EU funded project to investigate the factors influencing bone preservation in the archaeological record, more than 250 bones from 41 archaeological sites in five countries spanning four climatic regions were studied for diagenetic alteration. Sites were selected to cover a range of environmental conditions and archaeological contexts. Microscopic and physical (mercury intrusion porosimetry) analyses of these bones revealed that the majority (68%) had suffered microbial attack. Furthermore, significant differences were found between animal and human bone in both the state of preservation and the type of microbial attack present. These differences in preservation might result from differences in early taphonomy of the bones. © 2003 Elsevier Science Ltd. All rights reserved